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My clients are obsessed with AI and it's driving me nuts – are there any actually useful AI tools for service businesses?
reddit
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Human Vibe Score-0.333
12131415161718190This week

My clients are obsessed with AI and it's driving me nuts – are there any actually useful AI tools for service businesses?

I have a roster of a few home service companies (plumbers, roofers, landscapers, etc.) that I do freelance marketing for. Lately, the owners I work with have developed a serious case of AI shiny object syndrome. They’re bombarding me with links to scammy IG ads for “game-changing” AI tools they think will save their businesses overnight. Even talking about replacing their CSRs with "virtual agents". This will obviously lead to some terrible customer experiences, but all they can see is dollar signs at the prospect of laying off that part of their labor force. If I keep pushing back and pointing out how short sighted some of these ideas are, they’ll eventually find someone else that will implement them. So, I’m trying to get out in front of this a little bit and find any AI tools that don’t suck—something I can pitch back to them that’s actually useful and not just a fancy new way to ruin their customer experience. Then when they brag to their other buddies in the trades about how "cutting edge" their business is, it will be in part because of me, not in spite of me. Any suggestions for AI tools that: Help small service businesses without completely alienating their customers? Automate repetitive tasks in a way that doesn’t scream “this was done by a robot”? Aren’t just some scammy overpriced subscription service with a flashy demo? If you’ve actually used something that works, I’d love to hear about it. Honestly, the bar is low. Just help me stop these guys from accidentally burning their businesses down with bad AI ideas.

The "AI Agent" Hype is out of control and businesses suffer
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Human Vibe Score0.429
ImpossibleBell4759This week

The "AI Agent" Hype is out of control and businesses suffer

Ah, the sweet smell of AI hype in the morning. Nothing quite like it to get the blood pumping and the venture capital flowing. Let's cut through the BS... The "AI Agent" craze is the tech industry's latest attempt to separate businesses from their hard-earned cash. It's like watching a bunch of sheep rushing towards a cliff, except the cliff is made of overpriced software and empty promises. The tech giants are having a field day with this nonsense. Microsoft, Google, Salesforce - they're all pushing AI agents like they're the second coming. The sad truth is, businesses are suffering from a severe case of FOMO (Fear of Missing Out). They're so terrified of being left behind in the AI race that they're willing to throw good money after bad. Here's a radical idea: how about focusing on actual business problems instead of chasing the latest tech fad? I know, I know, it's not as sexy as having an AI Agent, but it might actually, you know, work. In the end, the only ones truly benefiting from this AI agent hype are the vendors selling the snake oil and the consultants charging exorbitant fees to implement it. Everyone else is just along for the ride, hoping they don't crash and burn too spectacularly. So, to all the businesses out there considering jumping on the AI Agent bandwagon... take a step back, take a deep breath, and ask yourself if you really need an overpriced chatbot with delusions of grandeur. Chances are, you don't. The AI agent hype is like a bad reality TV show—overproduced, lacking substance, and leaving businesses with nothing but regret. Companies are throwing money at AI solutions, expecting miracles, only to find they've bought into overpriced fantasies. The AI agent hype is nothing more than a high-tech emperor with no clothes. It's time for businesses to wake up, smell the silicon, and start making decisions based on reality rather than sci-fi fantasies.  I think AI Agents are the future, but as of right now AI Agents aren't autonomous or agentic. From what I've seen as of now is glorified Chatbots, ChatGPT wrappers and basic automations, and nothing actually autonomous. So far it's all just hype, but we'll see how it improves businesses and the bottom line! How do you think AI Agents will help small businesses now or in the future?

Seeking Feedback on My Business Idea – SaaS + Lead Generation for Small Businesses
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Human Vibe Score1
sarveshpandey89This week

Seeking Feedback on My Business Idea – SaaS + Lead Generation for Small Businesses

Edit: TL;DR I’m Sarvesh, a digital marketer with 10 years of experience in paid ads. After losing my job last year, I started freelancing and discovered how much small businesses struggle with getting reviews (Google, Yelp, TrustPilot, etc.). My Business Idea – SaaS + Paid Ads Free Plan: Businesses can track & reply to reviews across 40+ platforms in one dashboard. Paid Plan ($99/month): Automates review collection, AI-powered responses, social media posting, and spam detection. Custom Plan: Paid ads to generate leads, offered only to businesses on my paid plan for 3+ months. Goal: SaaS platform attracts users → Some upgrade to paid plan → Best clients get lead-generation help → More leads → More reviews → More organic customers → A profitable business cycle. Need Feedback: Does this idea have potential? How can I get my first beta users? Any features I should add/remove? Would love your thoughts—thanks for reading! 😊 TL: Hi everyone, I’m Sarvesh, and I’m in the process of starting my own business. Since my target audience is small businesses, I’d love to get some input, advice, or critiques from this community. A Little About Me I’ve spent the last 10 years working in paid advertising, helping medium and large businesses generate leads through Facebook and Google Ads. I also have experience running e-commerce campaigns. You can check out my background on LinkedIn: LinkedIn Profile Last year, my second daughter was born, and around the same time, my company shut down all its offices (India & UK), leaving me without a job. I decided to take a break and spend time with my wife and newborn, something I regretted not doing with my first child. By November, I started job hunting again, but in the meantime, I got some freelance work through Reddit, helping small businesses with ads for the first time. For context, in my previous jobs, I managed ad campaigns with daily budgets of £4K–£8K. Working with small businesses was a new challenge, but to my surprise, I was able to generate solid leads for beauty salons, hair salons, and nail salons, helping them grow. What stood out to me was how much impact my work had—unlike my corporate job, where I was just another person in the system, here I felt truly valued. That feeling led me to explore starting my own business. The Problem I Noticed While working with small businesses, I realized that online reviews (Google, Yelp, Trustpilot, etc.) are critical for them, yet many struggle to get them. Customers often don’t leave reviews, and employees are either too shy or don’t prioritize asking for them. This gave me an idea—to build a system that helps businesses get more genuine Google reviews from customers. I developed the system but struggled to find businesses willing to test it, even for free. My target audience is U.S. small businesses, but since I’m based in India, cold emails and Reddit outreach didn’t get much traction. My Business Idea – SaaS + Custom Plans I’m now thinking of pivoting my business model into a SaaS platform with optional paid upgrades. Here’s how it would work: Free Plan (Review Tracking & Management) Businesses can track their reviews across 40+ platforms (Google, Yelp, Facebook, Trustpilot, TripAdvisor, etc.) in one dashboard. They can reply to reviews manually from a single place instead of switching between platforms. This will be completely free forever. Paid Plan ($99/month, Plus SMS/Email Costs) For businesses that struggle to get reviews, they can upgrade to a paid plan that includes: Automated Review Requests – Automatically send review requests via SMS & email. Website Widget – Showcase 4- and 5-star reviews dynamically. Social Media Automation – Automatically post positive reviews on Facebook/Instagram. AI-Powered Responses – AI can reply to reviews automatically. Spam Detection – The system will notify businesses of suspicious reviews (but won’t take direct action). Custom Plan (Lead Generation via Paid Ads) I will personally manage paid ad campaigns to generate leads. Pricing depends on the niche, budget, and contract duration. Money-Back Guarantee – If I don’t deliver results, I refund the month’s fee. Small businesses can’t afford wasted ad spend, and I want to ensure I provide real value. Limited spots per month to maintain quality and avoid burnout. How Everything Ties Together The SaaS platform serves as a lead generation tool for my custom plans: Businesses use the free plan to track their reviews. Some upgrade to the paid plan to automate and improve reviews. A select few, after 3 months on the paid plan, can join my custom plan for paid ads to generate more leads. More leads → More reviews → Better Google Maps ranking → More organic customers → A more profitable business. Would Love Your Feedback! What do you think about this approach? Do you see potential for this business to take off? Any features I should add or remove? Any suggestions on how I can get my first beta users to test the SaaS platform? What about pricing? Do you think $99 is good pricing? I know this is a long post, but I really appreciate anyone taking the time to read and share their thoughts. Thanks in advance!

My clients are obsessed with AI and it's driving me nuts – are there any actually useful AI tools for service businesses?
reddit
LLM Vibe Score0
Human Vibe Score-0.333
12131415161718190This week

My clients are obsessed with AI and it's driving me nuts – are there any actually useful AI tools for service businesses?

I have a roster of a few home service companies (plumbers, roofers, landscapers, etc.) that I do freelance marketing for. Lately, the owners I work with have developed a serious case of AI shiny object syndrome. They’re bombarding me with links to scammy IG ads for “game-changing” AI tools they think will save their businesses overnight. Even talking about replacing their CSRs with "virtual agents". This will obviously lead to some terrible customer experiences, but all they can see is dollar signs at the prospect of laying off that part of their labor force. If I keep pushing back and pointing out how short sighted some of these ideas are, they’ll eventually find someone else that will implement them. So, I’m trying to get out in front of this a little bit and find any AI tools that don’t suck—something I can pitch back to them that’s actually useful and not just a fancy new way to ruin their customer experience. Then when they brag to their other buddies in the trades about how "cutting edge" their business is, it will be in part because of me, not in spite of me. Any suggestions for AI tools that: Help small service businesses without completely alienating their customers? Automate repetitive tasks in a way that doesn’t scream “this was done by a robot”? Aren’t just some scammy overpriced subscription service with a flashy demo? If you’ve actually used something that works, I’d love to hear about it. Honestly, the bar is low. Just help me stop these guys from accidentally burning their businesses down with bad AI ideas.

My clients are obsessed with AI and it's driving me nuts – are there any actually useful AI tools for service businesses?
reddit
LLM Vibe Score0
Human Vibe Score-0.333
12131415161718190This week

My clients are obsessed with AI and it's driving me nuts – are there any actually useful AI tools for service businesses?

I have a roster of a few home service companies (plumbers, roofers, landscapers, etc.) that I do freelance marketing for. Lately, the owners I work with have developed a serious case of AI shiny object syndrome. They’re bombarding me with links to scammy IG ads for “game-changing” AI tools they think will save their businesses overnight. Even talking about replacing their CSRs with "virtual agents". This will obviously lead to some terrible customer experiences, but all they can see is dollar signs at the prospect of laying off that part of their labor force. If I keep pushing back and pointing out how short sighted some of these ideas are, they’ll eventually find someone else that will implement them. So, I’m trying to get out in front of this a little bit and find any AI tools that don’t suck—something I can pitch back to them that’s actually useful and not just a fancy new way to ruin their customer experience. Then when they brag to their other buddies in the trades about how "cutting edge" their business is, it will be in part because of me, not in spite of me. Any suggestions for AI tools that: Help small service businesses without completely alienating their customers? Automate repetitive tasks in a way that doesn’t scream “this was done by a robot”? Aren’t just some scammy overpriced subscription service with a flashy demo? If you’ve actually used something that works, I’d love to hear about it. Honestly, the bar is low. Just help me stop these guys from accidentally burning their businesses down with bad AI ideas.

My clients are obsessed with AI and it's driving me nuts – are there any actually useful AI tools for service businesses?
reddit
LLM Vibe Score0
Human Vibe Score-0.333
12131415161718190This week

My clients are obsessed with AI and it's driving me nuts – are there any actually useful AI tools for service businesses?

I have a roster of a few home service companies (plumbers, roofers, landscapers, etc.) that I do freelance marketing for. Lately, the owners I work with have developed a serious case of AI shiny object syndrome. They’re bombarding me with links to scammy IG ads for “game-changing” AI tools they think will save their businesses overnight. Even talking about replacing their CSRs with "virtual agents". This will obviously lead to some terrible customer experiences, but all they can see is dollar signs at the prospect of laying off that part of their labor force. If I keep pushing back and pointing out how short sighted some of these ideas are, they’ll eventually find someone else that will implement them. So, I’m trying to get out in front of this a little bit and find any AI tools that don’t suck—something I can pitch back to them that’s actually useful and not just a fancy new way to ruin their customer experience. Then when they brag to their other buddies in the trades about how "cutting edge" their business is, it will be in part because of me, not in spite of me. Any suggestions for AI tools that: Help small service businesses without completely alienating their customers? Automate repetitive tasks in a way that doesn’t scream “this was done by a robot”? Aren’t just some scammy overpriced subscription service with a flashy demo? If you’ve actually used something that works, I’d love to hear about it. Honestly, the bar is low. Just help me stop these guys from accidentally burning their businesses down with bad AI ideas.

I created leadsnavi that helps small businesses find quality leads without breaking the bank
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BrightCook5861This week

I created leadsnavi that helps small businesses find quality leads without breaking the bank

Hey Redditors, I’m excited to share LeadsNavi, a tool I built specifically to help small businesses and B2B professionals automatically generate leads and reach potential customers in a smarter way. After talking to a lot of small business owners, I realized how tough it is to juggle lead generation with limited resources. So, I decided to create a tool that could simplify the process and make it more accessible to those who don’t have the budget to invest in expensive solutions. What Exactly Is LeadsNavi? LeadsNavi is an intuitive, cost-effective platform that automates the process of lead generation. It's designed to make it easy for small businesses and entrepreneurs to identify quality leads and grow their customer base without the need for manual prospecting. Here’s what makes it stand out: Automatic Lead Tracking: Tracks visitors to your website and matches them with company data, so you get real insights into who’s interested in your business. AI-Powered Lead Recommendations: Based on your website’s traffic, LeadsNavi uses AI to suggest similar companies that could be interested in your product or service, helping you find new leads faster and more accurately. Affordable & Scalable: For only $49/month, you can use a highly effective tool that scales with your business. It’s designed to be affordable even for small businesses. CRM Integration: Connect your CRM to directly import leads and sync your outreach efforts. How Does It Work? LeadsNavi uses advanced algorithms to track website visitors' IP addresses and match them with a comprehensive business database. It provides details like company names, contact information, and helps you identify potential leads for follow-up. The best part? It works automatically, saving you hours of manual work and effort. Lead Identification: Get insights into which companies are visiting your website. AI-Driven Lead Recommendations: The AI analyzes your site’s traffic and suggests other companies in the same industry or with similar needs that might be a great fit for your product or service. Data-Enriched Leads: Gather real-time, actionable data on these leads to make your outreach more targeted. Easy Setup: Simply integrate with your website and CRM to start getting quality leads in minutes. Who’s It For? Small Businesses: You don’t have to be a marketing expert to generate quality leads. B2B Sales Teams: Perfect for anyone looking to target other businesses with a streamlined and automated approach. Entrepreneurs & Startups: Focus on scaling your business without worrying about lead generation overhead. Why Try It? LeadsNavi gives you the power to focus on what really matters—connecting with potential customers and scaling your business. If you’ve been struggling with finding quality leads, or if you’re just getting started, I believe LeadsNavi can help you save time, effort, and money. I’m offering a 14-day free trial, so you can see the tool in action before committing to anything. Give it a try and let me know what you think! I’d love to hear your thoughts, suggestions, and how it works for your business. https://preview.redd.it/fdwil4rssgle1.png?width=1867&format=png&auto=webp&s=eb73b41a2b7665ae1b651fe2a6b7459df6990530

Launching Wisdor: AI Adoption Consultancy for Businesses
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_saanThis week

Launching Wisdor: AI Adoption Consultancy for Businesses

Website: https://www.wisdor.dev LinkedIn: https://www.linkedin.com/company/wisdor/ Hi! I am here to use this forum to announce and promote the launch of Wisdor: A consultancy service for business owners looking to adopt AI in their workflows. Since the launch of LLMs like ChatGPT, the use of AI has become mainstream however, small to medium businesses are seem to be facing some challenges with the adoption of AI even when they are willing to do so. Wisdor aims to target the following main pain-points of your AI adoption journey: Helping you decide if you even need to invite the buzzwords in your house or not There are so many AI tools out in the market and it can be daunting to decide what exactly is it which you need AI tools aren’t magic boxes that can do everything off the shelf. They require customization and tailoring for specific use cases Even when you have scouted the tools that \\ may \\* help you, they are of no use if you cannot include them in your existing workflows Or you may have a use case that requires the development of an AI based tool from scratch and your team does not have the necessary expertise to do so Wisdor will help you on your journey supporting you from the initial discussions to development and then the adoption of modern automation tools to help ease out your workload and drive efficiency. So, if you are someone who can benefit from Wisdor’s services, ping away! If not, give a follow to the LinkedIn page. Cheers and happy building!!!

My (23M) first $10k month installing internal GPT-4 for businesses
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swagamoneyThis week

My (23M) first $10k month installing internal GPT-4 for businesses

It all started in this very own subreddit just a month ago. I posted “How I made a secure GPT-4 for my company knowledge base” and left a cheeky Google Form in the comments. The post got 162 upvotes, 67 comments and, most importantly… ~30 form answers 😈 From there I got on 12 calls and even though I initially offered to do it for free… I closed 2 clients for $5k each. Data privacy was my main selling point: 1st company was a manufacturer with private instructions/manuals on how to operate certain systems. I trained GPT on them and let their employees talk with these 100-page PDFs. (When I say “train”, I refer to RAG, not fine-tune) 2nd company had customers sending them photos of sensitive documents for a customs clearing service. They had people manually extracting the info so we automated all of that. How did I ensure data privacy and security? I simply used MS Azure AI. They have all of the same stuff OpenAI has, but offer data privacy guarantees and network isolation. That’s both SOC 2 and GDPR compliant. Companies love it. Now I’m cold emailing my first 2 clients’ competitors for a quick rinse and repeat. P.S. I’m extremely curious of different use cases since I’m looking to niche down, so I’d be happy to talk to businesses with ideas of how to use this. You’d give me a use case idea and I’d give you advice on how to implement it. Edit: I’m getting TONS of DMs so please be comprehensive in your first message!

B2B Marketers: What’s Your #1 Tip for Selling SaaS to Other Businesses? (Building a Tool for Shopify SEO)
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iammanmanthemanThis week

B2B Marketers: What’s Your #1 Tip for Selling SaaS to Other Businesses? (Building a Tool for Shopify SEO)

Hi everyone! I’m part of a team building an AI-powered SEO tool specifically for Shopify stores (think automated technical fixes, predictive keyword optimization, etc.). We’re in the early stages and want to learn from seasoned B2B marketers: We’re struggling with: How to position a technical SaaS product to non-technical Shopify merchants. Cutting through the noise in a crowded SEO tools market. Building trust quickly with time-strapped business owners. Questions for B2B Marketing Pros: What’s the biggest mistake you made when marketing a SaaS product to businesses? What’s one underrated tactic that’s worked wonders for B2B lead gen? How do you prove ROI to skeptical buyers? (Especially for something abstract like SEO.) What’s your go-to channel for cold outreach that doesn’t feel spammy? What’s a hidden psychological trigger that works in B2B sales? What’s the best way to leverage case studies/testimonials when you’re just starting out? What’s one thing most founders waste money on in B2B marketing? For Those Who’ve Sold to Shopify Merchants: What’s their biggest pain point when evaluating tools? What type of content (webinars, blogs, demos) convinces them to buy? The Deal: We’ll compile all advice into a guide and credit contributors. If you're willing to have a virtual coffee chat, please reach out to us, we are always willing to listen to your wisdom!

My (23M) first $10k month installing internal GPT-4 for businesses
reddit
LLM Vibe Score0
Human Vibe Score1
swagamoneyThis week

My (23M) first $10k month installing internal GPT-4 for businesses

It all started in this very own subreddit just a month ago. I posted “How I made a secure GPT-4 for my company knowledge base” and left a cheeky Google Form in the comments. The post got 162 upvotes, 67 comments and, most importantly… ~30 form answers 😈 From there I got on 12 calls and even though I initially offered to do it for free… I closed 2 clients for $5k each. Data privacy was my main selling point: 1st company was a manufacturer with private instructions/manuals on how to operate certain systems. I trained GPT on them and let their employees talk with these 100-page PDFs. (When I say “train”, I refer to RAG, not fine-tune) 2nd company had customers sending them photos of sensitive documents for a customs clearing service. They had people manually extracting the info so we automated all of that. How did I ensure data privacy and security? I simply used MS Azure AI. They have all of the same stuff OpenAI has, but offer data privacy guarantees and network isolation. That’s both SOC 2 and GDPR compliant. Companies love it. Now I’m cold emailing my first 2 clients’ competitors for a quick rinse and repeat. P.S. I’m extremely curious of different use cases since I’m looking to niche down, so I’d be happy to talk to businesses with ideas of how to use this. You’d give me a use case idea and I’d give you advice on how to implement it. Edit: I’m getting TONS of DMs so please be comprehensive in your first message!

My Roadmap to Success with AI Automation for Small Businesses
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Giggly_ScarlettThis week

My Roadmap to Success with AI Automation for Small Businesses

Hey everybody! 👋 I’ve been working on automating small business workflows for a while now, and I wanted to share how AI and automation can help scale your business with no coding experience required. I started by automating tedious tasks for clients. Things like social media posting, client onboarding, and data transfers by using simple tools like Make and Zapier. The results were amazing! For example: One client cut down 3 hours of daily social media posting to just 15 minutes a day. Another automated follow-ups for proposals, which saved them dozens of hours each month. A boutique business streamlined its customer service by setting up a chatbot for basic FAQs and lead qualification. But here’s the thing—automation isn’t perfect, and it’s crucial to know its limitations. AI might not always get everything right. That’s why I recommend setting up workflows where you still have some oversight—like reviewing AI-generated content before posting or checking data transfers for accuracy. It’s more of a quality-control role, but it ensures the AI doesn’t stain your brand. If you're wondering where to start, here's the roadmap I followed: Start with Make or Zapier: These are perfect for non-programmers and let you automate tasks like transferring data between tools or triggering specific actions. Learn Prompt Engineering: Master how to ask AI the right questions. A little practice goes a long way! Level Up to AI Agents: Once you’re comfortable, you can build more advanced AI systems, like RAG (Retrieval-Augmented Generation) agents, which help businesses create personalized responses. Learn Python (Optional): Want to take your automation to the next level? Learning Python gives you the power to customize AI and automation workflows even further. Automation can be a huge time-saver and growth booster, but it’s not about replacing people—it’s about giving them the tools to work smarter. If you’ve been putting off automation, trust me, it’s worth diving in. Let me know if y'all have any questions and I'd be happy to answer them!

This founder was about to shut down his business and open a restaurant. He pivoted the business and grew it to $45m ARR in 12 months. What other businesses can scale like this?
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CountryPitifulThis week

This founder was about to shut down his business and open a restaurant. He pivoted the business and grew it to $45m ARR in 12 months. What other businesses can scale like this?

I heard that Jasper scaled to $45m ARR in 12 months...with a team of 8. For context, they are one of the fastest-growing companies ever. Grew from $0 to $45m ARR in 12 months (then raised $125m at a $1.5b valuation). As a fellow founder, their story is really inspiring to me (curious about what others think): In December 2020, Dave Rogenmoser and his co-founders were on the brink of shutting down their business. They'd spent 3+ years building a conversion optimization software called Proof...and it was flatlining. A few weeks prior they had to make the painful decision to let go of half their team. Competition and churn had completely eroded growth. Things were painful. 8 years of work left them with a string of startups that never quite made it: 2 failed software businesses (couldn't make money*) A SMB marketing agency (maxed out at $25k/mo*) An online course company (hard to get big*) The Pivot: In January 2021, they had an idea to use Chat GPT-3, the generative AI model released 6 months earlier, to write high-converting Facebook ads. Within 30 days, they launched the business. With the skeleton crew remaining from the last startup, they scaled the business to $45m ARR and 70,000+ customers without hiring a single new person. Soon after, they raised $125m at a $1.5b valuation. Dave Rogenmoser, CEO at Jasper, had some great one-liners in a few podcasts I listened to on the business. Here are some of his learnings: Right Skill, Wrong Vehicle: He spent 8 years building marketing businesses which gave this team the knowledge and confidence to spend $1m/mo on sales and marketing to scale the business to $45m ARR in year 1. Launch Fast & Iterate Quickly: The team agreed that if the business didn't work in 30 days, they'd shut it down. Dave says, "If you have been working on a problem for more than 18 months and haven't found Product market fit (PMF), odds are you won't...Make the hard pivot."* Ride A Big Wave: Generative AI technology is a new technology that is changing the way we work. But it's not just text. It's images, voice, etc. Identify new customer segments (e.g., Municipalities, Banks, Lawyers, etc.), learn their problems, and apply this novel technology to solve them. What other businesses have you seen scale like this? I've never seen a SaaS business grow that fast. I meet interesting founders 2x per week and share the learnings here.

Business Idea for new app connecting lonely people (e.g. new arrivals to big city), with local businesses organizing events
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TheL0nelyPoetThis week

Business Idea for new app connecting lonely people (e.g. new arrivals to big city), with local businesses organizing events

I came up with a start-up idea for a tool (website, app or both) where lonely people (e.g. recent arrivals to a new city) can match-up with one another, together with local businesses organizing events. I came up with the idea based on my own experiences of moving to a new place where my local social circle was virtually non-existent. Some people do well in such an environment, but I myself and some people I know/have interacted with seem to really struggle to make friends. The main idea would revolve around garnering the help of local businesses that regularly organize events (or would want to start doing so), together with a tool set up like a matching app (not unlike tinder or bumble). The app would contain the following features: People will be able to create a profile (with photos, interests, etc.) from all over the world, and set a specific geolocation of interest. Companies would be able to create pages with agenda’s and upcoming events. People would be able to list upcoming events they are interested in. Maybe together with some kind of AI-tool that will recommend upcoming events based on past liked events and interests. One could then seek out and reach out to other people planning to go to the same event, and perhaps arrange to go together so they know they won’t end up spending their time at the event alone. The business model would either revolve around subscription costs (e.g. for the companies that use it), commission on tickets purchased at the app for events or perhaps advertisement. I know there would be some competitors out there, however it appears most haven’t gained proper traction. I have also noticed most of the competitors have similar features, but haven’t made this business model their main strategy. Bumble for example, has a BFF-mode but advertises mainly about being a dating app. Businesses use their own websites or facebook/Instagram pages, but rely on people actively following them. Etc. What do you guys think? Honest feedback would really be appreciated, as this is my first start-up idea.

What role will tech play in sustainability for businesses?
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brycetychsenThis week

What role will tech play in sustainability for businesses?

Have you ever wanted to know how technology is shifting the business sector towards a greener future? Well, wonder no more! In this post, we'll explore the stupendous ways technology is exerting a pivotal role in promoting sustainability within businesses. Smart Energy Management Solutions Gone are the days of wasting energy and money on ineffective practices. With the advent of smart energy management systems, businesses can now optimize their energy usage in real-time. From smart thermostats to AI-powered energy analytics, these solutions help reduce carbon footprints while saving on utility bills. It's a win-win situation for both the environment and the bottom line! Renewable Energy Integration Due to advancements in technology, businesses can now easily integrate solar, wind, and other renewable energy sources into their operations. Not only does this reduce greenhouse gas emissions, but it also shields businesses from the volatility of traditional energy markets. Supply Chain Transparency Ever wondered where your products come from and how they're made? With blockchain technology, businesses can now provide unprecedented transparency throughout their supply chains. From sourcing raw materials to manufacturing processes, consumers can trace the journey of products, ensuring ethical and sustainable practices every step of the way. Data-Driven Sustainability Strategies In the age of big data, knowledge is power, especially when it comes to sustainability. By harnessing the power of data analytics, businesses can identify areas for improvement and implement targeted sustainability strategies. Whether it's optimizing transportation routes or minimizing waste generation, data-driven insights enable businesses to make smarter, greener decisions. Who knew numbers could be so eco-friendly? Eco-Friendly Innovation Last but not least, technology is driving innovation in eco-friendly products and services. From biodegradable packaging to electric vehicles, businesses are constantly pushing the boundaries of sustainability. By embracing these innovations, companies not only reduce their environmental impact but also appeal to eco-conscious consumers. That is it for now, people! From energy management to supply chain transparency, technology is paving the way for a more sustainable future in business. Let's continue to embrace these innovations and work together towards a greener tomorrow.

AI Interns for Small Businesses: Who Will Lead the Market?
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OstrichGrand8119This week

AI Interns for Small Businesses: Who Will Lead the Market?

I've been working on making my own AI tools (https://openai.com/blog/introducing-gpts), kind of like building a team but without the big costs. It's like having a bunch of helpful interns, but they're all computer programs. This got me thinking a lot about small businesses like ours. Building My Own AI Team on a Budget Making these AI tools felt like creating my own team. It's really cheap compared to hiring real people, and these AI interns can do lots of different jobs. This is a big deal for folks like us who don't have lots of money to spend. Spotting What's Missing for Small Businesses While playing around with this AI stuff, I noticed there are things missing that small businesses really need. There's a big chance here to make something that fills these gaps, a tool made just for small businesses. The Big Question: Competing with Big Companies But here's the tricky part. Big companies like OpenAI are making their own AI stuff, like the GPT Store and GPT Enterprise. This makes me wonder if it's a good idea to make a new product that's kind of the same but more focused on what small businesses need. The Big Choice: Special Tools vs. Big Company Tools We're at a crossroads about what's better: Special Tools: Making something that's just right for small businesses could be really useful and fit our needs better. Big Company Tools: But, big companies have more stuff to offer and are already well-known. I Want to Hear From You If you run a small business or like tech stuff, what do you think? Would you like a special AI tool made for small businesses, or would you rather use the big ones from famous companies? How do you think the future looks for AI help in small businesses with all these changes? https://preview.redd.it/9pks3r65rg7c1.jpg?width=1460&format=pjpg&auto=webp&s=d767d2352f5e57e3303974f0b951a0176a0745c3

The Massive Opportunity in Building AI Businesses | Alex Hormozi
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Liam OttleySep 24, 2023

The Massive Opportunity in Building AI Businesses | Alex Hormozi

📚 Join the #1 community for AI entrepreneurs and connect with 100,000+ members: https://bit.ly/3uRIRB3 📈 We help industry experts, entrepreneurs & developers build and scale their AI Agency: https://bit.ly/skoolmain 🤝 Need AI Solutions Built? Work with me: https://b.link/qv62vqy6 ⚒️ Build AI Agents Without Coding: https://agentivehub.com/ 🚀 Apply to Join My Team at Morningside AI: https://tally.so/r/wbYr52 Alex Hormozi and I sat down for a chat about how to start an AI business in 2023. Alex shared his advice for people wanting to start an AI Automation Agency, including how to sell emerging technology like AI, the importance of a good development team as an AI entrepreneur and his thoughts on AI businesses and startups that he's seeing at Acquisition.com. Alex Hormozi also gave his thoughts on the huge opportunity for entrepreneurs to help businesses integrate AI into their businesses or "AI-ify" them, including exactly how he'd go about it himself. This call was an exclusive interview for my AAA Accelerator members who were able to watch this conversation LIVE. Timestamps: 0:00 - Intro 0:58 - AI Automation Agencies Explained 5:13 - How To Sell Emerging Tech 6:23 - The Opportunity Of AI Automation 10:00 - Choosing The Right Business Partner 11:14 - What Problems To Solve In An Industry 12:06 - Where AAA Might Falter or Excel 14:32 - The Importance Of Development Resources 19:17 - How Important Is Downtime As An Entrepreneur?

I studied how 7 Founders found their first 100 customers for their businesses. Summarizing it here!
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adriannelestrangeThis week

I studied how 7 Founders found their first 100 customers for their businesses. Summarizing it here!

I am learning marketing, and so I combed through the internet to find specific advice that helped founders reach 100 users and not random Google answers. Here’s what I found: Llama Life by Marie Marie founder of Llama Life, a productivity app ($51.4K+ revenue) got her first 100 users using Snowballing effect. She shared great advice that I want to add here verbatim, “Need to think about what you have that you can leverage based on your current situation. eg..When you have no customers, think about where you can post to get the 1st customer eg Product Hunt. If you do well on PH, say you get #3 product of the day, then you post somewhere else saying ‘I got #3 product of the day’.. to get your next few customers. Maybe that post is on reddit with some learnings that you found. If the reddit post does well, then you might post it on Twitter, saying reddit did well and what learnings you got from that etc. or even if it doesn’t do well you can still post about it.” Another tip she shared is to build related products that get more viral than the product itself. These are small stand-alone sites that would appeal to the same target audience, but by nature, are more shareable. On these sites, you can mention your startup like: ‘brought to you by Llama Life’ and then provide a link to the main website if someone is interested. If one of those gets viral or ranks on Google, you’ll have a passive traffic source. Scraping bee by Pierre Pierre, founder of Scraping Bee, a web scraping tool has now reached $1.5M ARR. Pierre and his cofounder Kevin started with 10 Free Beta Users in 2019, and after 6 months asked them to take a paid subscription if they wanted to continue using the product. That’s how they got their first user within 50 minutes of that email. Then they listed it on dozens of startup directories but their core strategy was writing the best possible content for their target audience — Developers. 3 very successful pieces of content that worked were : A small tutorial on how to scrape single-page application An extensive general guide about web scraping without getting blocked A complete introduction to web scraping with Python They didn’t do content marketing for the sake of content marketing but deep-dived into the value they were providing their customer. One of these got 70K visits, and all this together got them to over 100 users. WePay by Bill Clerico Bill Clerico left his cushy corporate job to build WePay which was then acquired for $400M got his first users by using his app. He got his first users by using his app! The app was for group payments. So he hosted a Poker tournament at his house and collected payments only with his app. Then they hosted a barbecue for fraternity treasurers at San Jose State & helped them do their annual dues collection. Good old word-of-mouth marketing, that however, started with an event where they used what they made! RealWorld by Genevieve Genevieve — Founder and CEO of Realworld stands by the old-school advice of value giving. RealWorld is an app that helps GenZ navigate adulthood. So, before launching their direct-to-consumer platform, they had an educational course that they sold to college career centers and students. They already had a pipeline of adults who turned to Realworld for their adulting challenges. From there, she gained her first 100 followers. Saner dot ai by Austin Austin got 100 users from Reddit for his startup Saner.ai. Reddit hates advertising, and so his tips to market your startup on Reddit is to Write value-driven posts on your niche. Instead of writing posts, find posts where people are looking for solutions DM people facing problems that your SaaS solves. But instead of selling, ask about their problem to see if your product is a good fit Heartfelt posts about why you built it, aren’t gonna cut it To find posts and people, search Reddit with relevant keywords and join all the subreddits A Stock Portfolio Newsletter A financial investor got his first 100 paid newsletter subscribers for his stock portfolio newsletter. His tips : Don’t reinvent the wheel. Work what’s already working. He saw a company making $500M+ from stock picking newsletter, so decided to try that. Find the gaps in “already working” and leverage them. That newsletter did not have portfolios of advisors writing them. That was his USP. He added his own portfolio to his newsletter. Now to 100 users, he partnered with a guy running an investing website and getting good traffic. That guy got a cut of his revenue, in exchange. That one simple step got him to 100 users. Hypefury by Yannick and Samy Yannick and Samy from Hypefury, Twitter and Social Media Automation tool got their first beta testers and users from a paid community. They launched Hypefury there and asked if someone wanted to try it. A couple of people tried it and gave feedback. Samy conducted user interviews and product demos for them, And shared the reviews on Twitter. That alone, along with word-of-mouth marketing on Twitter got them their first 100 users. To conclude: Don’t reinvent the wheel, try what’s working. Find the gaps in what’s working, and leverage that. Instead of thinking about millions of customers, think about the first 10. Then first 100. Leverage what you have. Get the first 10 customers, then talk about this to get the next 100. Use your app. Find ways, events, and opportunities to use your app in front of people. And get them to use it. Write content not only for SEO but also to help people. It won’t work tomorrow, but it will work for years after it picks up. Leverage other sources of traffic by partnering up! Do things that don’t scale. I’m also doing SaaS marketing deep dives over 30 pieces of content. I'm posting here for the first time, so I'm not sure if it will stay or not, sorry if it doesn't. I've helped a SaaS grow from $19K to $100K MRR as a marketer in last 2 years, and now I wanna dive deep. Cheers! (1/30)

I studied how 7 Founders found their first 100 customers for their businesses. Summarizing it here!
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adriannelestrangeThis week

I studied how 7 Founders found their first 100 customers for their businesses. Summarizing it here!

I am learning marketing, and so I combed through the internet to find specific advice that helped founders reach 100 users and not random Google answers. Here’s what I found: Llama Life by Marie Marie founder of Llama Life, a productivity app ($51.4K+ revenue) got her first 100 users using Snowballing effect. She shared great advice that I want to add here verbatim, “Need to think about what you have that you can leverage based on your current situation. eg..When you have no customers, think about where you can post to get the 1st customer eg Product Hunt. If you do well on PH, say you get #3 product of the day, then you post somewhere else saying ‘I got #3 product of the day’.. to get your next few customers. Maybe that post is on reddit with some learnings that you found. If the reddit post does well, then you might post it on Twitter, saying reddit did well and what learnings you got from that etc. or even if it doesn’t do well you can still post about it.” Another tip she shared is to build related products that get more viral than the product itself. These are small stand-alone sites that would appeal to the same target audience, but by nature, are more shareable. On these sites, you can mention your startup like: ‘brought to you by Llama Life’ and then provide a link to the main website if someone is interested. If one of those gets viral or ranks on Google, you’ll have a passive traffic source. Scraping bee by Pierre Pierre, founder of Scraping Bee, a web scraping tool has now reached $1.5M ARR. Pierre and his cofounder Kevin started with 10 Free Beta Users in 2019, and after 6 months asked them to take a paid subscription if they wanted to continue using the product. That’s how they got their first user within 50 minutes of that email. Then they listed it on dozens of startup directories but their core strategy was writing the best possible content for their target audience — Developers. 3 very successful pieces of content that worked were : A small tutorial on how to scrape single-page application An extensive general guide about web scraping without getting blocked A complete introduction to web scraping with Python They didn’t do content marketing for the sake of content marketing but deep-dived into the value they were providing their customer. One of these got 70K visits, and all this together got them to over 100 users. WePay by Bill Clerico Bill Clerico left his cushy corporate job to build WePay which was then acquired for $400M got his first users by using his app. He got his first users by using his app! The app was for group payments. So he hosted a Poker tournament at his house and collected payments only with his app. Then they hosted a barbecue for fraternity treasurers at San Jose State & helped them do their annual dues collection. Good old word-of-mouth marketing, that however, started with an event where they used what they made! RealWorld by Genevieve Genevieve — Founder and CEO of Realworld stands by the old-school advice of value giving. RealWorld is an app that helps GenZ navigate adulthood. So, before launching their direct-to-consumer platform, they had an educational course that they sold to college career centers and students. They already had a pipeline of adults who turned to Realworld for their adulting challenges. From there, she gained her first 100 followers. Saner dot ai by Austin Austin got 100 users from Reddit for his startup Saner.ai. Reddit hates advertising, and so his tips to market your startup on Reddit is to Write value-driven posts on your niche. Instead of writing posts, find posts where people are looking for solutions DM people facing problems that your SaaS solves. But instead of selling, ask about their problem to see if your product is a good fit Heartfelt posts about why you built it, aren’t gonna cut it To find posts and people, search Reddit with relevant keywords and join all the subreddits A Stock Portfolio Newsletter A financial investor got his first 100 paid newsletter subscribers for his stock portfolio newsletter. His tips : Don’t reinvent the wheel. Work what’s already working. He saw a company making $500M+ from stock picking newsletter, so decided to try that. Find the gaps in “already working” and leverage them. That newsletter did not have portfolios of advisors writing them. That was his USP. He added his own portfolio to his newsletter. Now to 100 users, he partnered with a guy running an investing website and getting good traffic. That guy got a cut of his revenue, in exchange. That one simple step got him to 100 users. Hypefury by Yannick and Samy Yannick and Samy from Hypefury, Twitter and Social Media Automation tool got their first beta testers and users from a paid community. They launched Hypefury there and asked if someone wanted to try it. A couple of people tried it and gave feedback. Samy conducted user interviews and product demos for them, And shared the reviews on Twitter. That alone, along with word-of-mouth marketing on Twitter got them their first 100 users. To conclude: Don’t reinvent the wheel, try what’s working. Find the gaps in what’s working, and leverage that. Instead of thinking about millions of customers, think about the first 10. Then first 100. Leverage what you have. Get the first 10 customers, then talk about this to get the next 100. Use your app. Find ways, events, and opportunities to use your app in front of people. And get them to use it. Write content not only for SEO but also to help people. It won’t work tomorrow, but it will work for years after it picks up. Leverage other sources of traffic by partnering up! Do things that don’t scale. I’m also doing SaaS marketing deep dives over 30 pieces of content. I'm posting here for the first time, so I'm not sure if it will stay or not, sorry if it doesn't. I've helped a SaaS grow from $19K to $100K MRR as a marketer in last 2 years, and now I wanna dive deep. Cheers! (1/30)

Serious B2B businesses will not try to create a solution using AI - This is why. [i will not promote]
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consultaliThis week

Serious B2B businesses will not try to create a solution using AI - This is why. [i will not promote]

After architecting and developing multiple B2B SaaS platforms and resolving countless challenges, here's why I don't think a proper B2B solution can be developed using AI. You must have senior tech-folks in your teams - even if you choose to leverage AI for expediting some code generation. This isn't theory - this is battle-tested reality. You can use this as a template if you're building one. Core Considerations: Multi-Tenancy Foundation (B2B) Proper tenant isolation at every layer (data, compute, networking) Flexible deployment models (pooled vs. silo) based on customer tier Tenant-aware everything (logging, metrics, tracing) Identity & Security (B2B/Standalone) Enterprise-grade authentication, often with SSO support Role-based access control (RBAC) at tenant level (may need dynamic policy generation for resource access) Audit trails for all system actions (specially if you're in a regulated domain) Client/Tenant Management (B2B) Self-service onboarding with admin approval workflows Automated tenant provisioning/deprovisioning Tenant-specific configurations and customizations Cross-tenant analytics and administration Operational Excellence (B2B/Standalone) Zero-downtime deployments (helps with canary releases) Tenant-isolated debugging capabilities Resource quotas and throttling by tenant tier Automated backup and disaster recovery per tenant Scalability Architecture (B2B) Independent scaling of tenant workloads Resource isolation for "noisy neighbor" prevention Tier-based performance guarantees (SLAs) Dynamic resource allocation Each of these topics can be as complicated as you can think of - depends on the solution you're building. I have seen many seasoned architects and developers struggle also because of their "single-tenant" mindset. Here are some common pitfalls to avoid (B2B/Standalone): Standalone - mindset in database design Hard-coded configurations Lack of context in logging/monitoring Insufficient tenant isolation in shared services (B2B) Missing tenant-aware cost allocation (B2B) You need people great with infrastructure as well. They need to consider: Tenant-aware routing (API Gateway or whatever you're using) Code with isolation when/if required Data storage with proper partitioning Shared services vs. dedicated services strategy There are a number of common problems I have seen people often make. Often it's because of a pressure from high above. But every architectural decision must considered in terms of the solution you're building. In many cases, security cannot be bolted on later, observability must be tenant-aware from day one, operations must scale. This is just the foundation. Your actual business logic sits ON TOP of all this. Now, would you think these can be done by AI? I'll be waiting for that day. :-)

I studied how 7 Founders found their first 100 customers for their businesses. Summarizing it here!
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adriannelestrangeThis week

I studied how 7 Founders found their first 100 customers for their businesses. Summarizing it here!

I am learning marketing, and so I combed through the internet to find specific advice that helped founders reach 100 users and not random Google answers. Here’s what I found: Llama Life by Marie Marie founder of Llama Life, a productivity app ($51.4K+ revenue) got her first 100 users using Snowballing effect. She shared great advice that I want to add here verbatim, “Need to think about what you have that you can leverage based on your current situation. eg..When you have no customers, think about where you can post to get the 1st customer eg Product Hunt. If you do well on PH, say you get #3 product of the day, then you post somewhere else saying ‘I got #3 product of the day’.. to get your next few customers. Maybe that post is on reddit with some learnings that you found. If the reddit post does well, then you might post it on Twitter, saying reddit did well and what learnings you got from that etc. or even if it doesn’t do well you can still post about it.” Another tip she shared is to build related products that get more viral than the product itself. These are small stand-alone sites that would appeal to the same target audience, but by nature, are more shareable. On these sites, you can mention your startup like: ‘brought to you by Llama Life’ and then provide a link to the main website if someone is interested. If one of those gets viral or ranks on Google, you’ll have a passive traffic source. Scraping bee by Pierre Pierre, founder of Scraping Bee, a web scraping tool has now reached $1.5M ARR. Pierre and his cofounder Kevin started with 10 Free Beta Users in 2019, and after 6 months asked them to take a paid subscription if they wanted to continue using the product. That’s how they got their first user within 50 minutes of that email. Then they listed it on dozens of startup directories but their core strategy was writing the best possible content for their target audience — Developers. 3 very successful pieces of content that worked were : A small tutorial on how to scrape single-page application An extensive general guide about web scraping without getting blocked A complete introduction to web scraping with Python They didn’t do content marketing for the sake of content marketing but deep-dived into the value they were providing their customer. One of these got 70K visits, and all this together got them to over 100 users. WePay by Bill Clerico Bill Clerico left his cushy corporate job to build WePay which was then acquired for $400M got his first users by using his app. He got his first users by using his app! The app was for group payments. So he hosted a Poker tournament at his house and collected payments only with his app. Then they hosted a barbecue for fraternity treasurers at San Jose State & helped them do their annual dues collection. Good old word-of-mouth marketing, that however, started with an event where they used what they made! RealWorld by Genevieve Genevieve — Founder and CEO of Realworld stands by the old-school advice of value giving. RealWorld is an app that helps GenZ navigate adulthood. So, before launching their direct-to-consumer platform, they had an educational course that they sold to college career centers and students. They already had a pipeline of adults who turned to Realworld for their adulting challenges. From there, she gained her first 100 followers. Saner dot ai by Austin Austin got 100 users from Reddit for his startup Saner.ai. Reddit hates advertising, and so his tips to market your startup on Reddit is to Write value-driven posts on your niche. Instead of writing posts, find posts where people are looking for solutions DM people facing problems that your SaaS solves. But instead of selling, ask about their problem to see if your product is a good fit Heartfelt posts about why you built it, aren’t gonna cut it To find posts and people, search Reddit with relevant keywords and join all the subreddits A Stock Portfolio Newsletter A financial investor got his first 100 paid newsletter subscribers for his stock portfolio newsletter. His tips : Don’t reinvent the wheel. Work what’s already working. He saw a company making $500M+ from stock picking newsletter, so decided to try that. Find the gaps in “already working” and leverage them. That newsletter did not have portfolios of advisors writing them. That was his USP. He added his own portfolio to his newsletter. Now to 100 users, he partnered with a guy running an investing website and getting good traffic. That guy got a cut of his revenue, in exchange. That one simple step got him to 100 users. Hypefury by Yannick and Samy Yannick and Samy from Hypefury, Twitter and Social Media Automation tool got their first beta testers and users from a paid community. They launched Hypefury there and asked if someone wanted to try it. A couple of people tried it and gave feedback. Samy conducted user interviews and product demos for them, And shared the reviews on Twitter. That alone, along with word-of-mouth marketing on Twitter got them their first 100 users. To conclude: Don’t reinvent the wheel, try what’s working. Find the gaps in what’s working, and leverage that. Instead of thinking about millions of customers, think about the first 10. Then first 100. Leverage what you have. Get the first 10 customers, then talk about this to get the next 100. Use your app. Find ways, events, and opportunities to use your app in front of people. And get them to use it. Write content not only for SEO but also to help people. It won’t work tomorrow, but it will work for years after it picks up. Leverage other sources of traffic by partnering up! Do things that don’t scale. I’m also doing SaaS marketing deep dives over 30 pieces of content. I'm posting here for the first time, so I'm not sure if it will stay or not, sorry if it doesn't. I've helped a SaaS grow from $19K to $100K MRR as a marketer in last 2 years, and now I wanna dive deep. Cheers! (1/30)

I spent 6 months on building a tool, and got 0 zero users. Here is my story.
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GDbuildsGDThis week

I spent 6 months on building a tool, and got 0 zero users. Here is my story.

Edit Thank you all so much for your time reading my story. Your support, feedback, criticism, and skepticism; all helped me a lot, and I couldn't appreciate it enough \^\_\^ TL;DR I spent 6 months on a tool that currently has 0 users. Below is what I learned during my journey, sharing because I believe most mistakes are easily avoidable. Do not overestimate your product and assume it will be an exception to fundamental principles. Principles are there for a reason. Always look for validation before you start. Avoid building products with a low money-to-effort ratio/in very competitive fields. Unless you have the means, you probably won't make it. Pick a problem space, pick your target audience, and talk to them before thinking about a solution. Identify and match their pain points. Only then should you think of a solution. If people are not overly excited or willing to pay in advance for a discounted price, it might be a sign to rethink. Sell one and only one feature at a time. Avoid everything else. If people don't pay for that one core feature, no secondary feature will change their mind. Always spend twice as much time marketing as you do building. You will not get users if they don't know it exists. Define success metrics ("1000 users in 3 months" or "$6000 in the account at the end of 6 months") before you start. If you don't meet them, strongly consider quitting the project. If you can't get enough users to keep going, nothing else matters. VALIDATION, VALIDATION, VALIDATION. Success is not random, but most of our first products will not make a success story. Know when to admit failure, and move on. Even if a product of yours doesn't succeed, what you learned during its journey will turn out to be invaluable for your future. My story So, this is the story of a product, Summ, that I’ve been working on for the last 6 months. As it's the first product I’ve ever built, after watching you all from the sidelines, I have learned a lot, made many mistakes, and did only a few things right. Just sharing what I’ve learned and some insights from my journey so far. I hope that this post will help you avoid the mistakes I made — most of which I consider easily avoidable — while you enjoy reading it, and get to know me a little bit more 🤓. A slow start after many years Summ isn’t the first product I really wanted to build. Lacking enough dev skills to even get started was a huge blocker for so many years. In fact, the first product I would’ve LOVED to build was a smart personal shopping assistant. I had this idea 4 years ago; but with no GPT, no coding skills, no technical co-founder, I didn’t have the means to make it happen. I still do not know if such a tool exists and is good enough. All I wanted was a tool that could make data-based predictions about when to buy stuff (“buy a new toothpaste every three months”) and suggest physical products that I might need or be strongly interested in. AFAIK, Amazon famously still struggles with the second one. Fast-forward a few years, I learned the very basics of HTML, CSS, and Vanilla JS. Still was not there to build a product; but good enough to code my design portfolio from scratch. Yet, I couldn’t imagine myself building a product using Vanilla JS. I really hated it, I really sucked at it. So, back to tutorial hell, and to learn about this framework I just heard about: React.React introduced so many new concepts to me. “Thinking in React” is a phrase we heard a lot, and with quite good reasons. After some time, I was able to build very basic tutorial apps, both in React, and React Native; but I have to say that I really hated coding for mobile. At this point, I was already a fan of productivity apps, and had a concept for a time management assistant app in my design portfolio. So, why not build one? Surely, it must be easy, since every coding tutorial starts with a todo app. ❌ WRONG! Building a basic todo app is easy enough, but building one good enough for a place in the market was a challenge I took and failed. I wasted one month on that until I abandoned the project for good. Even if I continued working on it, as the productivity landscape is overly competitive, I wouldn’t be able to make enough money to cover costs, assuming I make any. Since I was (and still am) in between jobs, I decided to abandon the project. 👉 What I learned: Do not start projects with a low ratio of money to effort and time. Example: Even if I get 500 monthly users, 200 of which are paid users (unrealistically high number), assuming an average subscription fee of $5/m (such apps are quite cheap, mostly due to the high competition), it would make me around $1000 minus any occurring costs. Any founder with a product that has 500 active users should make more. Even if it was relatively successful, due to the high competition, I wouldn’t make any meaningful money. PS: I use Todoist today. Due to local pricing, I pay less than $2/m. There is no way I could beat this competitive pricing, let alone the app itself. But, somehow, with a project that wasn’t even functional — let alone being an MVP — I made my first Wi-Fi money: Someone decided that the domain I preemptively purchased is worth something. By this point, I had already abandoned the project, certainly wasn’t going to renew the domain, was looking for a FT job, and a new project that I could work on. And out of nowhere, someone hands me some free money — who am I not to take it? Of course, I took it. The domain is still unused, no idea why 🤔. Ngl, I still hate the fact that my first Wi-Fi money came from this. A new idea worth pursuing? Fast-forward some weeks now. Around March, I got this crazy idea of building an email productivity tool. We all use emails, yet we all hate them. So, this must be fixed. Everyone uses emails, in fact everyone HAS TO use emails. So, I just needed to build a tool and wait for people to come. This was all, really. After all, the problem space is huge, there is enough room for another product, everyone uses emails, no need for any further validation, right? ❌ WRONG ONCE AGAIN! We all hear from the greatest in the startup landscape that we must validate our ideas with real people, yet at least some of us (guilty here 🥸) think that our product will be hugely successful and prove them to be an exception. Few might, but most are not. I certainly wasn't. 👉 Lesson learned: Always validate your ideas with real people. Ask them how much they’d pay for such a tool (not if they would). Much better if they are willing to pay upfront for a discount, etc. But even this comes later, keep reading. I think the difference between “How much” and “If” is huge for two reasons: (1) By asking them for “How much”, you force them to think in a more realistic setting. (2) You will have a more realistic idea on your profit margins. Based on my competitive analysis, I already had a solution in my mind to improve our email usage standards and email productivity (huge mistake), but I did my best to learn about their problems regarding those without pushing the idea too hard. The idea is this: Generate concise email summaries with suggested actions, combine them into one email, and send it at their preferred times. Save as much as time the AI you end up with allows. After all, everyone loves to save time. So, what kind of validation did I seek for? Talked with only a few people around me about this crazy, internet-breaking idea. The responses I got were, now I see, mediocre; no one got excited about it, just said things along the lines of “Cool idea, OK”. So, any reasonable person in this situation would think “Okay, not might not be working”, right? Well, I did not. I assumed that they were the wrong audience for this product, and there was this magical land of user segments waiting eagerly for my product, yet unknowingly. To this day, I still have not reached this magical place. Perhaps, it didn’t exist in the first place. If I cannot find it, whether it exists or not doesn’t matter. I am certainly searching for it. 👉 What I should have done: Once I decide on a problem space (time management, email productivity, etc.), I should decide on my potential user segments, people who I plan to sell my product to. Then I should go talk to those people, ask them about their pains, then get to the problem-solving/ideation phase only later. ❗️ VALIDATION COMES FROM THE REALITY OUTSIDE. What validation looks like might change from product to product; but what invalidation looks like is more or less the same for every product. Nico Jeannen told me yesterday “validation = money in the account” on Twitter. This is the ultimate form of validation your product could get. If your product doesn’t make any money, then something is invalidated by reality: Your product, you, your idea, who knows? So, at this point, I knew a little bit of Python from spending some time in tutorial hell a few years ago, some HTML/CSS/JS, barely enough React to build a working app. React could work for this project, but I needed easy-to-implement server interactivity. Luckily, around this time, I got to know about this new gen of indie hackers, and learned (but didn’t truly understand) about their approach to indie hacking, and this library called Nextjs. How good Next.js still blows my mind. So, I was back to tutorial hell once again. But, this time, with a promise to myself: This is the last time I would visit tutorial hell. Time to start building this "ground-breaking idea" Learning the fundamentals of Next.js was easier than learning of React unsurprisingly. Yet, the first time I managed to run server actions on Next.js was one of the rarest moments that completely blew my mind. To this day, I reject the idea that it is something else than pure magic under its hood. Did I absolutely need Nextjs for this project though? I do not think so. Did it save me lots of time? Absolutely. Furthermore, learning Nextjs will certainly be quite helpful for other projects that I will be tackling in the future. Already got a few ideas that might be worth pursuing in the head in case I decide to abandon Summ in the future. Fast-forward few weeks again: So, at this stage, I had a barely working MVP-like product. Since the very beginning, I spent every free hour (and more) on this project as speed is essential. But, I am not so sure it was worth it to overwork in retrospect. Yet, I know I couldn’t help myself. Everything is going kinda smooth, so what’s the worst thing that could ever happen? Well, both Apple and Google announced their AIs (Apple Intelligence and Google Gemini, respectively) will have email summarization features for their products. Summarizing singular emails is no big deal, after all there were already so many similar products in the market. I still think that what truly matters is a frictionless user experience, and this is why I built this product in a certain way: You spend less than a few minutes setting up your account, and you get to enjoy your email summaries, without ever visiting its website again. This is still a very cool concept I really like a lot. So, at this point: I had no other idea that could be pursued, already spent too much time on this project. Do I quit or not? This was the question. Of course not. I just have to launch this product as quickly as possible. So, I did something right, a quite rare occurrence I might say: Re-planned my product, dropped everything secondary to the core feature immediately (save time on reading emails), tried launching it asap. 👉 Insight: Sell only one core feature at one time. Drop anything secondary to this core feature. Well, my primary occupation is product design. So one would expect that a product I build must have stellar design. I considered any considerable time spent on design at this stage would be simply wasted. I still think this is both true and wrong: True, because if your product’s core benefits suck, no one will care about your design. False, because if your design looks amateurish, no one will trust you and your product. So, I always targeted an average level design with it and the way this tool works made it quite easy as I had to design only 2 primary pages: Landing page and user portal (which has only settings and analytics pages). However, even though I knew spending time on design was not worth much of my time, I got a bit “greedy”: In fact, I redesigned those pages three times, and still ended up with a so-so design that I am not proud of. 👉 What I would do differently: Unless absolutely necessary, only one iteration per stage as long as it works. This, in my mind, applies to everything. If your product’s A feature works, then no need to rewrite it from scratch for any reason, or even refactor it. When your product becomes a success, and you absolutely need that part of your codebase to be written, do so, but only then. Ready to launch, now is th etime for some marketing, right? By July 26, I already had a “launchable” product that barely works (I marked this date on a Notion docs, this is how I know). Yet, I had spent almost no time on marketing, sales, whatever. After all, “You build and they will come”. Did I know that I needed marketing? Of course I did, but knowingly didn’t. Why, you might ask. Well, from my perspective, it had to be a dev-heavy product; meaning that you spend most of your time on developing it, mostly coding skills. But, this is simply wrong. As a rule of thumb, as noted by one of the greatests, Marc Louvion, you should spend at least twice of the building time on marketing. ❗️ Time spent on building \* 2 people don’t know your product > they don’t use your product > you don’t get users > you don’t make money Easy as that. Following the same reasoning, a slightly different approach to planning a project is possible. Determine an approximate time to complete the project with a high level project plan. Let’s say 6 months. By the reasoning above, 2 months should go into building, and 4 into marketing. If you need 4 months for building instead of 2, then you need 8 months of marketing, which makes the time to complete the project 12 months. If you don’t have that much time, then quit the project. When does a project count as completed? Well, in reality, never. But, I think we have to define success conditions even before we start for indie projects and startups; so we know when to quit when they are not met. A success condition could look like “Make $6000 in 12 months” or “Have 3000 users in 6 months”. It all depends on the project. But, once you set it, it should be set in stone: You don’t change it unless absolutely necessary. I suspect there are few principles that make a solopreneur successful; and knowing when to quit and when to continue is definitely one of them. Marc Louvion is famously known for his success, but he got there after failing so many projects. To my knowledge, the same applies to Nico Jeannen, Pieter Levels, or almost everyone as well. ❗️ Determining when to continue even before you start will definitely help in the long run. A half-aed launch Time-leap again. Around mid August, I “soft launched” my product. By soft launch, I mean lazy marketing. Just tweeting about it, posting it on free directories. Did I get any traffic? Surely I did. Did I get any users? Nope. Only after this time, it hit me: “Either something is wrong with me, or with this product” Marketing might be a much bigger factor for a project’s success after all. Even though I get some traffic, not convincing enough for people to sign up even for a free trial. The product was still perfect in my eyes at the time (well, still is ^(\_),) so the right people are not finding my product, I thought. Then, a question that I should have been asking at the very first place, one that could prevent all these, comes to my mind: “How do even people search for such tools?” If we are to consider this whole journey of me and my so-far-failed product to be an already destined failure, one metric suffices to show why. Search volume: 30. Even if people have such a pain point, they are not looking for email summaries. So, almost no organic traffic coming from Google. But, as a person who did zero marketing on this or any product, who has zero marketing knowledge, who doesn’t have an audience on social media, there is not much I could do. Finally, it was time to give up. Or not… In my eyes, the most important element that makes a founder (solo or not) successful (this, I am not by any means) is to solve problems. ❗️ So, the problem was this: “People are not finding my product by organic search” How do I make sure I get some organic traffic and gets more visibility? Learn digital marketing and SEO as much as I can within very limited time. Thankfully, without spending much time, I came across Neil Patel's YT channel, and as I said many times, it is an absolute gold mine. I learned a lot, especially about the fundamentals, and surely it will be fruitful; but there is no magic trick that could make people visit your website. SEO certainly helps, but only when people are looking for your keywords. However, it is truly a magical solution to get in touch with REAL people that are in your user segments: 👉 Understand your pains, understand their problems, help them to solve them via building products. I did not do this so far, have to admit. But, in case you would like to have a chat about your email usage, and email productivity, just get in touch; I’d be delighted to hear about them. Getting ready for a ProductHunt launch The date was Sept 1. And I unlocked an impossible achievement: Running out of Supabase’s free plan’s Egres limit while having zero users. I was already considering moving out of their Cloud server and managing a Supabase CLI service on my Hetzner VPS for some time; but never ever suspected that I would have to do this quickly. The cheapest plan Supabase offers is $25/month; yet, at that point, I am in between jobs for such a long time, basically broke, and could barely afford that price. One or two months could be okay, but why pay for it if I will eventually move out of their Cloud service? So, instead of paying $25, I spent two days migrating out of Supabase Cloud. Worth my time? Definitely not. But, when you are broke, you gotta do stupid things. This was the first time that I felt lucky to have zero users: I have no idea how I would manage this migration if I had any. I think this is one of the core tenets of an indie hacker: Controlling their own environment. I can’t remember whose quote this is, but I suspect it was Naval: Entrepreneurs have an almost pathological need to control their own fate. They will take any suffering if they can be in charge of their destiny, and not have it in somebody else’s hands. What’s truly scary is, at least in my case, we make people around us suffer at the expense of our attempting to control our own fates. I know this period has been quite hard on my wife as well, as I neglected her quite a bit, but sadly, I know that this will happen again. It is something that I can barely help with. Still, so sorry. After working the last two weeks on a ProductHunt Launch, I finally launched it this Tuesday. Zero ranking, zero new users, but 36 kind people upvoted my product, and many commented and provided invaluable feedback. I couldn't be more grateful for each one of them 🙏. Considering all these, what lies in the future of Summ though? I have no idea, to be honest. On one hand, I have zero users, have no job, no income. So, I need a way to make money asap. On the other hand, the whole idea of it revolves around one core premise (not an assumption) that I am not so willing to share; and I couldn’t have more trust in it. This might not be the best iteration of it, however I certainly believe that email usage is one of the best problem spaces one could work on. 👉 But, one thing is for certain: I need to get in touch with people, and talk with them about this product I built so far. In fact, this is the only item on my agenda. Nothing else will save my brainchild <3. Below are some other insights and notes that I got during my journey; as they do not 100% fit into this story, I think it is more suitable to list them here. I hope you enjoyed reading this. Give Summ a try, it comes with a generous free trial, no credit card required. Some additional notes and insights: Project planning is one of the most underestimated skills for solopreneurs. It saves you enormous time, and helps you to keep your focus up. Building B2C products beats building B2B products. Businesses are very willing to pay big bucks if your product helps them. On the other hand, spending a few hours per user who would pay $5/m probably is not worth your time. It doesn’t matter how brilliant your product is if no one uses it. If you cannot sell a product in a certain category/niche (or do not know how to sell it), it might be a good idea not to start a project in it. Going after new ideas and ventures is quite risky, especially if you don’t know how to market it. On the other hand, an already established category means that there is already demand. Whether this demand is sufficient or not is another issue. As long as there is enough demand for your product to fit in, any category/niche is good. Some might be better, some might be worse. Unless you are going hardcore B2B, you will need people to find your product by means of organic search. Always conduct thorough keyword research as soon as possible.

The Drawing of the Three - Once you look through the veil, nothing is the same again. (I will not promote)
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The Drawing of the Three - Once you look through the veil, nothing is the same again. (I will not promote)

Originally published Nov 5, 2024 In my last post, I talked about assembling a series of filters to use to view the startup landscape, which led me to a few conclusions about what opportunities I should pursue. What did I see through those filters? What I saw through the moire pattern of those two lists overlaid by one another is what I think will be the third great monetization strategy for the internet, matching the pattern of: web1 => Ad monetization web2 => Subscription monetization web3 => For AI, neither of those work anymore, which demands something new. But what? Well that’s the important part, isn’t it? Should I just up and tell you? Yawn. The climax of a movie is at the climax, if they tell you the crux at the beginning, it’s a lot less fun (usually). The standard bearer for web1 and ads was Google (with countless followers), and essentially every website adopted that model for their first pass at content monetization. Google has been… let’s call it fairly successful… so it’s not a bad way to look at things. How many websites live and die by selling advertising? The standard bearers for web2 and subscriptions were Salesforce (for B2B SaaS) and Netflix (for B2C SaaS), with countless followers, to the extent that SaaS has been the dominant startup monetization thesis for the last 15+ years. It’s more old and tired by now than most American politicians, but how many websites live and die by people entering payment details for a monthly or annual subscription? Evidence proves those models for web1 and web2 worked well enough that countless businesses depend on them, and countless fortunes have been made and lost surfing the waves, or crashing against the shorelines, of ads and subs. But it’s also apparent (to me, at least) that now that AI is the dominant startup thesis, neither ads nor subs are going to prevail in an AI-centered world, and for one simple reason: Those monetization strategies are for humans, and AI bots are not humans. Changing Environments Require Changing Strategies Every so often, there’s a fundamental shift that demands everything in the ecosystem adapt to a new habitation strategy to survive. We’ve seen this repeatedly across Earth’s ecology (for instance, introducing free oxygen to the atmosphere, producing respiration while destroying all the life forms that existed before oxygen permeated the atmosphere), and across human society (for example, how nuclear bombs changed war, and how drones are changing it again, for less violent examples, consider the adoption of computers and the subsequent adoption of smartphones). Now the ecosystem of the internet has changed irrevocably, opening up countless new and interesting niches to occupy. Humans may see an ad and buy something stupid (or, occasionally, not-stupid), but an AI won’t unless its programmed to. And subscriptions are designed for humans to consume content at a human rate, not for an AI that can choke down an entire database of content (whatever it may be) at whatever speed the servers can manage. Changing conditions require changing strategies. It was clear to me that: The introduction of AI bots to the internet ecosystem was, is, and will be massively disruptive for a very long time The internet population of bots already exceeds humans and is growing faster than the human population The two dominant monetization strategies are not relevant to bots That disruption of expectations across the ecosystem demands a third strategy, a new strategy to handle a massive change in an existing system. And that strategy needs to accommodate, support, and monetize the new demands from the vast armies of new participants in the internet ecology. Therefore, a method that converts bots from an expense into a revenue source would become a dominant monetization strategy, and therefore whoever owns that strategy will be a dominant player in the internet ecosystem. Set the realization of semi-practical, semi-useful AI against a backdrop of technology cycles that have, in the distant past (in internet terms) produced ads and subs, and more recently produced enormous investment into fintech and crypto, I started to see a path that felt like it would grow over time to become a new monetization strategy that works in the AI ecosystem. Sun Tzu had a couple drinks, saw a couple things… There’s at least, and possibly only, two things I know about fighting: You cannot fight the tide, and it’s much harder to fight an uphill battle. If my whole thesis on this go-around was to go with the flow, and that trickle of insight was leading me from my overlook along a roaring flow of cash coursing through a valley filled with AI startups, where exactly would it lead me? Most rivers lead to the sea eventually, but they can take winding paths, and sometimes the quickest route from the mountain to the sea isn’t to follow the river, but to understand where the river leads and go there instead. Getting a view from on high can save you a lot of time on your journey. But before I get to where the path has led (or is leading) that will explain the objective I’ve identified, and the deliverables I have to produce to reach it, let’s talk about a few of the steps on the path I’ve been taking that highlight the process I followed. I figure if I explain the steps I’m taking, as I’m taking them, it may be easier for people who haven’t trod this route before to follow me and understand how to carve their own course towards their own objectives. And maybe the real treasure will be the friends we make along the way. (I will not promote)

How a founder built a B2B AI startup to serve with 65+ global brands (including Fortune500 companies) (I will not promote)
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Royal_Rest8409This week

How a founder built a B2B AI startup to serve with 65+ global brands (including Fortune500 companies) (I will not promote)

AI Palette is an AI-driven platform that helps food and beverage companies predict emerging product trends. I had the opportunity recently to sit down with the founder to get his advice on building an AI-first startup, which he'll be going through in this post. (I will not promote) About AI Palette: Co-founders: >!2 (Somsubhra GanChoudhuri, Himanshu Upreti)!!100+!!$12.7M USD!!AI-powered predictive analytics for the CPG (Consumer Packaged Goods) industry!!Signed first paying customer in the first year!!65+ global brands, including Cargill, Diageo, Ajinomoto, Symrise, Mondelez, and L’Oréal, use AI Palette!!Every new product launched has secured a paying client within months!!Expanded into Beauty & Personal Care (BPC), onboarding one of India’s largest BPC companies within weeks!!Launched multiple new product lines in the last two years, creating a unified suite for brand innovation!Identify the pain points in your industry for ideas* When I was working in the flavour and fragrance industry, I noticed a major issue CPG companies faced: launching a product took at least one to two years. For instance, if a company decided today to launch a new juice, it wouldn’t hit the market until 2027. This long timeline made it difficult to stay relevant and on top of trends. Another big problem I noticed was that companies relied heavily on market research to determine what products to launch. While this might work for current consumer preferences, it was highly inefficient since the product wouldn’t actually reach the market for several years. By the time the product launched, the consumer trends had already shifted, making that research outdated. That’s where AI can play a crucial role. Instead of looking at what consumers like today, we realised that companies should use AI to predict what they will want next. This allows businesses to create products that are ahead of the curve. Right now, the failure rate for new product launches is alarmingly high, with 8 out of 10 products failing. By leveraging AI, companies can avoid wasting resources on products that won’t succeed, leading to better, more successful launches. Start by talking to as many industry experts as possible to identify the real problems When we first had the idea for AI Palette, it was just a hunch, a gut feeling—we had no idea whether people would actually pay for it. To validate the idea, we reached out to as many people as we could within the industry. Since our focus area was all about consumer insights, we spoke to professionals in the CPG sector, particularly those in the insights departments of CPG companies. Through these early conversations, we began to see a common pattern emerge and identified the exact problem we wanted to solve. Don’t tell people what you’re building—listen to their frustrations and challenges first. Going into these early customer conversations, our goal was to listen and understand their challenges without telling them what we were trying to build. This is crucial as it ensures that you can gather as much data about the problem to truly understand it and that you aren't biasing their answers by showing your solution. This process helped us in two key ways: First, it validated that there was a real problem in the industry through the number of people who spoke about experiencing the same problem. Second, it allowed us to understand the exact scale and depth of the problem—e.g., how much money companies were spending on consumer research, what kind of tools they were currently using, etc. Narrow down your focus to a small, actionable area to solve initially. Once we were certain that there was a clear problem worth solving, we didn’t try to tackle everything at once. As a small team of two people, we started by focusing on a specific area of the problem—something big enough to matter but small enough for us to handle. Then, we approached customers with a potential solution and asked them for feedback. We learnt that our solution seemed promising, but we wanted to validate it further. If customers are willing to pay you for the solution, it’s a strong validation signal for market demand. One of our early customer interviewees even asked us to deliver the solution, which we did manually at first. We used machine learning models to analyse the data and presented the results in a slide deck. They paid us for the work, which was a critical moment. It meant we had something with real potential, and we had customers willing to pay us before we had even built the full product. This was the key validation that we needed. By the time we were ready to build the product, we had already gathered crucial insights from our early customers. We understood the specific information they wanted and how they wanted the results to be presented. This input was invaluable in shaping the development of our final product. Building & Product Development Start with a simple concept/design to validate with customers before building When we realised the problem and solution, we began by designing the product, but not by jumping straight into coding. Instead, we created wireframes and user interfaces using tools like InVision and Figma. This allowed us to visually represent the product without the need for backend or frontend development at first. The goal was to showcase how the product would look and feel, helping potential customers understand its value before we even started building. We showed these designs to potential customers and asked for feedback. Would they want to buy this product? Would they pay for it? We didn’t dive into actual development until we found a customer willing to pay a significant amount for the solution. This approach helped us ensure we were on the right track and didn’t waste time or resources building something customers didn’t actually want. Deliver your solution using a manual consulting approach before developing an automated product Initially, we solved problems for customers in a more "consulting" manner, delivering insights manually. Recall how I mentioned that when one of our early customer interviewees asked us to deliver the solution, we initially did it manually by using machine learning models to analyse the data and presenting the results to them in a slide deck. This works for the initial stages of validating your solution, as you don't want to invest too much time into building a full-blown MVP before understanding the exact features and functionalities that your users want. However, after confirming that customers were willing to pay for what we provided, we moved forward with actual product development. This shift from a manual service to product development was key to scaling in a sustainable manner, as our building was guided by real-world feedback and insights rather than intuition. Let ongoing customer feedback drive iteration and the product roadmap Once we built the first version of the product, it was basic, solving only one problem. But as we worked closely with customers, they requested additional features and functionalities to make it more useful. As a result, we continued to evolve the product to handle more complex use cases, gradually developing new modules based on customer feedback. Product development is a continuous process. Our early customers pushed us to expand features and modules, from solving just 20% of their problems to tackling 50–60% of their needs. These demands shaped our product roadmap and guided the development of new features, ultimately resulting in a more complete solution. Revenue and user numbers are key metrics for assessing product-market fit. However, critical mass varies across industries Product-market fit (PMF) can often be gauged by looking at the size of your revenue and the number of customers you're serving. Once you've reached a certain critical mass of customers, you can usually tell that you're starting to hit product-market fit. However, this critical mass varies by industry and the type of customers you're targeting. For example, if you're building an app for a broad consumer market, you may need thousands of users. But for enterprise software, product-market fit may be reached with just a few dozen key customers. Compare customer engagement and retention with other available solutions on the market for product-market fit Revenue and the number of customers alone isn't always enough to determine if you're reaching product-market fit. The type of customer and the use case for your product also matter. The level of engagement with your product—how much time users are spending on the platform—is also an important metric to track. The more time they spend, the more likely it is that your product is meeting a crucial need. Another way to evaluate product-market fit is by assessing retention, i.e whether users are returning to your platform and relying on it consistently, as compared to other solutions available. That's another key indication that your solution is gaining traction in the market. Business Model & Monetisation Prioritise scalability Initially, we started with a consulting-type model where we tailor-made specific solutions for each customer use-case we encountered and delivered the CPG insights manually, but we soon realized that this wasn't scalable. The problem with consulting is that you need to do the same work repeatedly for every new project, which requires a large team to handle the workload. That is not how you sustain a high-growth startup. To solve this, we focused on building a product that would address the most common problems faced by our customers. Once built, this product could be sold to thousands of customers without significant overheads, making the business scalable. With this in mind, we decided on a SaaS (Software as a Service) business model. The benefit of SaaS is that once you create the software, you can sell it to many customers without adding extra overhead. This results in a business with higher margins, where the same product can serve many customers simultaneously, making it much more efficient than the consulting model. Adopt a predictable, simplistic business model for efficiency. Look to industry practices for guidance When it came to monetisation, we considered the needs of our CPG customers, who I knew from experience were already accustomed to paying annual subscriptions for sales databases and other software services. We decided to adopt the same model and charge our customers an annual upfront fee. This model worked well for our target market, aligning with industry standards and ensuring stable, recurring revenue. Moreover, our target CPG customers were already used to this business model and didn't have to choose from a huge variety of payment options, making closing sales a straightforward and efficient process. Marketing & Sales Educate the market to position yourself as a thought leader When we started, AI was not widely understood, especially in the CPG industry. We had to create awareness around both AI and its potential value. Our strategy focused on educating potential users and customers about AI, its relevance, and why they should invest in it. This education was crucial to the success of our marketing efforts. To establish credibility, we adopted a thought leadership approach. We wrote blogs on the importance of AI and how it could solve problems for CPG companies. We also participated in events and conferences to demonstrate our expertise in applying AI to the industry. This helped us build our brand and reputation as leaders in the AI space for CPG, and word-of-mouth spread as customers recognized us as the go-to company for AI solutions. It’s tempting for startups to offer products for free in the hopes of gaining early traction with customers, but this approach doesn't work in the long run. Free offerings don’t establish the value of your product, and customers may not take them seriously. You should always charge for pilots, even if the fee is minimal, to ensure that the customer is serious about potentially working with you, and that they are committed and engaged with the product. Pilots/POCs/Demos should aim to give a "flavour" of what you can deliver A paid pilot/POC trial also gives you the opportunity to provide a “flavour” of what your product can deliver, helping to build confidence and trust with the client. It allows customers to experience a detailed preview of what your product can do, which builds anticipation and desire for the full functionality. During this phase, ensure your product is built to give them a taste of the value you can provide, which sets the stage for a broader, more impactful adoption down the line. Fundraising & Financial Management Leverage PR to generate inbound interest from VCs When it comes to fundraising, our approach was fairly traditional—we reached out to VCs and used connections from existing investors to make introductions. However, looking back, one thing that really helped us build momentum during our fundraising process was getting featured in Tech in Asia. This wasn’t planned; it just so happened that Tech in Asia was doing a series on AI startups in Southeast Asia and they reached out to us for an article. During the interview, they asked if we were fundraising, and we mentioned that we were. As a result, several VCs we hadn’t yet contacted reached out to us. This inbound interest was incredibly valuable, and we found it far more effective than our outbound efforts. So, if you can, try to generate some PR attention—it can help create inbound interest from VCs, and that interest is typically much stronger and more promising than any outbound strategies because they've gone out of their way to reach out to you. Be well-prepared and deliberate about fundraising. Keep trying and don't lose heart When pitching to VCs, it’s crucial to be thoroughly prepared, as you typically only get one shot at making an impression. If you mess up, it’s unlikely they’ll give you a second chance. You need to have key metrics at your fingertips, especially if you're running a SaaS company. Be ready to answer questions like: What’s your retention rate? What are your projections for the year? How much will you close? What’s your average contract value? These numbers should be at the top of your mind. Additionally, fundraising should be treated as a structured process, not something you do on the side while juggling other tasks. When you start, create a clear plan: identify 20 VCs to reach out to each week. By planning ahead, you’ll maintain momentum and speed up the process. Fundraising can be exhausting and disheartening, especially when you face multiple rejections. Remember, you just need one investor to say yes to make it all worthwhile. When using funds, prioritise profitability and grow only when necessary. Don't rely on funding to survive. In the past, the common advice for startups was to raise money, burn through it quickly, and use it to boost revenue numbers, even if that meant operating at a loss. The idea was that profitability wasn’t the main focus, and the goal was to show rapid growth for the next funding round. However, times have changed, especially with the shift from “funding summer” to “funding winter.” My advice now is to aim for profitability as soon as possible and grow only when it's truly needed. For example, it’s tempting to hire a large team when you have substantial funds in the bank, but ask yourself: Do you really need 10 new hires, or could you get by with just four? Growing too quickly can lead to unnecessary expenses, so focus on reaching profitability as soon as possible, rather than just inflating your team or burn rate. The key takeaway is to spend your funds wisely and only when absolutely necessary to reach profitability. You want to avoid becoming dependent on future VC investments to keep your company afloat. Instead, prioritize reaching break-even as quickly as you can, so you're not reliant on external funding to survive in the long run. Team-Building & Leadership Look for complementary skill sets in co-founders When choosing a co-founder, it’s important to find someone with a complementary skill set, not just someone you’re close to. For example, I come from a business and commercial background, so I needed someone with technical expertise. That’s when I found my co-founder, Himanshu, who had experience in machine learning and AI. He was a great match because his technical knowledge complemented my business skills, and together we formed a strong team. It might seem natural to choose your best friend as your co-founder, but this can often lead to conflict. Chances are, you and your best friend share similar interests, skills, and backgrounds, which doesn’t bring diversity to the table. If both of you come from the same industry or have the same strengths, you may end up butting heads on how things should be done. Having diverse skill sets helps avoid this and fosters a more collaborative working relationship. Himanshu (left) and Somsubhra (right) co-founded AI Palette in 2018 Define roles clearly to prevent co-founder conflict To avoid conflict, it’s essential that your roles as co-founders are clearly defined from the beginning. If your co-founder and you have distinct responsibilities, there is no room for overlap or disagreement. This ensures that both of you can work without stepping on each other's toes, and there’s mutual respect for each other’s expertise. This is another reason as to why it helps to have a co-founder with a complementary skillset to yours. Not only is having similar industry backgrounds and skillsets not particularly useful when building out your startup, it's also more likely to lead to conflicts since you both have similar subject expertise. On the other hand, if your co-founder is an expert in something that you're not, you're less likely to argue with them about their decisions regarding that aspect of the business and vice versa when it comes to your decisions. Look for employees who are driven by your mission, not salary For early-stage startups, the first hires are crucial. These employees need to be highly motivated and excited about the mission. Since the salary will likely be low and the work demanding, they must be driven by something beyond just the paycheck. The right employees are the swash-buckling pirates and romantics, i.e those who are genuinely passionate about the startup’s vision and want to be part of something impactful beyond material gains. When employees are motivated by the mission, they are more likely to stick around and help take the startup to greater heights. A litmus test for hiring: Would you be excited to work with them on a Sunday? One of the most important rounds in the hiring process is the culture fit round. This is where you assess whether a candidate shares the same values as you and your team. A key question to ask yourself is: "Would I be excited to work with this person on a Sunday?" If there’s any doubt about your answer, it’s likely not a good fit. The idea is that you want employees who align with the company's culture and values and who you would enjoy collaborating with even outside of regular work hours. How we structure the team at AI Palette We have three broad functions in our organization. The first two are the big ones: Technical Team – This is the core of our product and technology. This team is responsible for product development and incorporating customer feedback into improving the technology Commercial Team – This includes sales, marketing, customer service, account managers, and so on, handling everything related to business growth and customer relations. General and Administrative Team – This smaller team supports functions like finance, HR, and administration. As with almost all businesses, we have teams that address the two core tasks of building (technical team) and selling (commercial team), but given the size we're at now, having the administrative team helps smoothen operations. Set broad goals but let your teams decide on execution What I've done is recruit highly skilled people who don't need me to micromanage them on a day-to-day basis. They're experts in their roles, and as Steve Jobs said, when you hire the right person, you don't have to tell them what to do—they understand the purpose and tell you what to do. So, my job as the CEO is to set the broader goals for them, review the plans they have to achieve those goals, and periodically check in on progress. For example, if our broad goal is to meet a certain revenue target, I break it down across teams: For the sales team, I’ll look at how they plan to hit that target—how many customers they need to sell to, how many salespeople they need, and what tactics and strategies they plan to use. For the technical team, I’ll evaluate our product offerings—whether they think we need to build new products to attract more customers, and whether they think it's scalable for the number of customers we plan to serve. This way, the entire organization's tasks are cascaded in alignment with our overarching goals, with me setting the direction and leaving the details of execution to the skilled team members that I hire.

How to get funding for startup ? I will not promote
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How to get funding for startup ? I will not promote

I will not promote. Software startup based out of Minnesota us. I've built and launched a product that is gaining traction, solving a problem that has frustrated software developers and product teams for years. The problem: Software development is slow, expensive, and full of inefficiencies. Developers spend hours on repetitive coding tasks, project managers struggle with bottlenecks, and businesses waste time translating product requirements into actual code. The solution: My product automates a large portion of software development. It acts as an AI-powered assistant for developers, taking high-level requirements and turning them into functional code while integrating with existing codebases. It can read, understand, and modify software projects in a structured way—cutting development time drastically. The potential: Businesses are always looking for ways to cut costs and speed up development. With the rise of AI, companies are increasingly adopting automation, and this tool fits perfectly into that wave. Imagine a world where software teams are 10x more efficient because AI handles the grunt work, and developers focus on the bigger picture. It’s not about replacing developers—it’s about supercharging them. The current status: The product is live and in use. The user base is growing, and I’ve proven demand. Now, I need to figure out the best funding model to scale—whether that’s bootstrapping, VC, grants, or some hybrid approach. If you have experience in startup funding or have scaled a tech product, I'd love to hear your insights. DM me if you're open to discussing strategies!

Building in the open with Founder University - I will not promote
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Building in the open with Founder University - I will not promote

Published Oct 30, 2024 I am on my fifth startup. I ran the last one for a decade, that’s a whole story. A hell of a story. But a different story. I’ll tell it to you when I can, but not right now. The one before that was an e-commerce site that did pretty well but I didn’t love it. Before that were two service businesses. The first one I did for the love of the game, the second one was an attempt to make people stop asking me to fix their computer by charging them outrageous prices, which backfired horribly when they were eager to pay. None are relevant except to say I’ve been around the block and have the scars to prove it. When it was time to get back out there, I wanted to use all I’ve learned to do better. Before I talk about what those lessons produced, I’m going to talk about what those lessons were. Cause before effect, after all. One thing I wanted to do better this time was pattern matching - making the startup look the way that the industry and investors “expect” a startup to look. My last startup was an awesome idea with awesome tech (still is, but like I said, another story), but that one didn’t match patterns. It didn’t match investor patterns, industry buying patterns, patterns of existing, immediate, recognized and admitted needs. Because it didn’t “look” right to anyone, everything about it was way harder than necessary. The “make it look right” approach runs the risk of building a cargo cult, imitating the trappings of something but without understanding the essence of that something, but then again, a thing that looks like a knife is going to make a better knife that a thing that looks like a bowling ball, so sometimes just sharing apparent similarities can get you pretty far, even if it doesn’t get you all the way there. Like how mimicking someone’s accent makes it easier for them to understand you. For this one, I wanted to adopt every tool, method, and pattern that I knew “the industry” wanted to see to minimize the friction from development, go-to-market, scaling, adoption, and that would make investment optional (and, therefore, available if desired) instead of necessary (and, therefore, largely unavailable). That required establishing some expectations for successful patterns I could match against. What patterns am I matching to? Here’s a general sketch of my pattern matching thought process: Software first and software only. It’s the easiest industry to start a business in, lowest startup costs, and easiest customer acquisition. I wanted to build software for an element of the industry that’s actively emerging (and therefore has room to grow) and part of an optimistic investor thesis (and therefore has a cohort of people who are intent on injecting capital into the market to help it grow). It needs to fills a niche that is underexplored (low competition) and highly potent (lots of opportunity), while being aligned to recognized and emerging needs within the industry (readily adopted). I wanted it to have evidence supporting the business thesis that proves the demand exists, but demonstrates that the demand is unanswered (as of yet) by sufficient or adequate supply.* I wanted the lowest number of dominoes to line up and tip for everything to work correctly - the more dominoes in the line, the less likely the last one will fall. I wanted to implement modern toolsets for everything, wherever possible. I wanted to obey the maxim, “When there’s a gold rush, don’t mine the gold, sell the picks and shovels.” Whatever I chose would need to produce cash flow almost immediately with minimal development time or go-to-market delays, because the end of ZIRP killed the “trust me bro” investment thesis predominant over the last 15 years. I wanted to match to YC best practices, not because YC can predict what will definitely work, but because they’ve churned through so many startups in the last 15 years that they have a good sense of what will definitely not work. And I wanted to build client-centric, because if my intent is to to produce cash flow immediately, we need to get clients immediately, and if we need to get clients immediately, we need to focus on what clients need right now. Extra credit: What’s the difference between a customer and a client? Note: Competition is awesome! Competition is validating and not scary, because competition proves a market exists. But competition, especially mature competition against an immature startup, makes it harder to break into a space. A first mover advantage isn’t everything, but seeing demand before it’s sufficiently supplied is a great advantage if you’re capital constrained or otherwise unproven. Think about how much money the first guy to sell fidget spinners or Silly Bandz made versus how much money the last guy to order a pallet of each made. Finding demand that exists already but is as of yet insufficiently satisfied is a great place to start. What opportunity spaces are most relevant? The industries and markets I chose to observe were: AI, because if I’m following a theme & pattern for today, it’s AI. Fintech, because cash is king, and fintech puts your hands on cash flow. Crypto/blockchain, because that’s the “new” fintech (or maybe the “old-new” fintech?), and crypto creates powerful incentives and capital formation strategies, along with a lot of flexibility for transaction systems. Tools, particularly unmet demand in tools, that enable these industries. If you wanted to do some brief and simple homework, you could map each of those bullets to several of the numbered list items preceding them. The reasoning was pretty simplistic - AI is what people want to build and invest in now, while fintech and crypto/blockchain are what people were building and investing in for the last major investment thesis. That means that there’s demand in the market for AI and AI-adjacent startups, while there’s a glut of underutilized and highly developed tools within fintech and crypto/blockchain, with a lot of motivated capital behind the adoption. When someone is thinking “I built this thing and not enough people are using it”, and you then build something that uses it creates a great way to find allies. This rationale harnesses technology that is being built and financed now (which means it needs tools and support methods, and a lot of other “picks and shovels”), while leveraging technology that was recently built and financed and is eager for more widespread adoption of the existing toolkits, which makes it suitable for using to build the AI-adjacent tools that are in demand now. It’s like two harmonics producing constructive interference - it makes two waves into one larger wave, which gives me more momentum to surf against. This was a learning process, and I iterated against my general paradigm repeatedly as I learned more. Neither of us have the patience to go through that in excruciating detail, so I’ll cover the highlights in my next post. Extra credit answer: A customer gets a product, a client gets a service. Challenge: Is software a product or a service?

I spent 6 months on building a tool, and got 0 zero users. Here is my story.
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I spent 6 months on building a tool, and got 0 zero users. Here is my story.

Edit Thank you all so much for your time reading my story. Your support, feedback, criticism, and skepticism; all helped me a lot, and I couldn't appreciate it enough \^\_\^ TL;DR I spent 6 months on a tool that currently has 0 users. Below is what I learned during my journey, sharing because I believe most mistakes are easily avoidable. Do not overestimate your product and assume it will be an exception to fundamental principles. Principles are there for a reason. Always look for validation before you start. Avoid building products with a low money-to-effort ratio/in very competitive fields. Unless you have the means, you probably won't make it. Pick a problem space, pick your target audience, and talk to them before thinking about a solution. Identify and match their pain points. Only then should you think of a solution. If people are not overly excited or willing to pay in advance for a discounted price, it might be a sign to rethink. Sell one and only one feature at a time. Avoid everything else. If people don't pay for that one core feature, no secondary feature will change their mind. Always spend twice as much time marketing as you do building. You will not get users if they don't know it exists. Define success metrics ("1000 users in 3 months" or "$6000 in the account at the end of 6 months") before you start. If you don't meet them, strongly consider quitting the project. If you can't get enough users to keep going, nothing else matters. VALIDATION, VALIDATION, VALIDATION. Success is not random, but most of our first products will not make a success story. Know when to admit failure, and move on. Even if a product of yours doesn't succeed, what you learned during its journey will turn out to be invaluable for your future. My story So, this is the story of a product, Summ, that I’ve been working on for the last 6 months. As it's the first product I’ve ever built, after watching you all from the sidelines, I have learned a lot, made many mistakes, and did only a few things right. Just sharing what I’ve learned and some insights from my journey so far. I hope that this post will help you avoid the mistakes I made — most of which I consider easily avoidable — while you enjoy reading it, and get to know me a little bit more 🤓. A slow start after many years Summ isn’t the first product I really wanted to build. Lacking enough dev skills to even get started was a huge blocker for so many years. In fact, the first product I would’ve LOVED to build was a smart personal shopping assistant. I had this idea 4 years ago; but with no GPT, no coding skills, no technical co-founder, I didn’t have the means to make it happen. I still do not know if such a tool exists and is good enough. All I wanted was a tool that could make data-based predictions about when to buy stuff (“buy a new toothpaste every three months”) and suggest physical products that I might need or be strongly interested in. AFAIK, Amazon famously still struggles with the second one. Fast-forward a few years, I learned the very basics of HTML, CSS, and Vanilla JS. Still was not there to build a product; but good enough to code my design portfolio from scratch. Yet, I couldn’t imagine myself building a product using Vanilla JS. I really hated it, I really sucked at it. So, back to tutorial hell, and to learn about this framework I just heard about: React.React introduced so many new concepts to me. “Thinking in React” is a phrase we heard a lot, and with quite good reasons. After some time, I was able to build very basic tutorial apps, both in React, and React Native; but I have to say that I really hated coding for mobile. At this point, I was already a fan of productivity apps, and had a concept for a time management assistant app in my design portfolio. So, why not build one? Surely, it must be easy, since every coding tutorial starts with a todo app. ❌ WRONG! Building a basic todo app is easy enough, but building one good enough for a place in the market was a challenge I took and failed. I wasted one month on that until I abandoned the project for good. Even if I continued working on it, as the productivity landscape is overly competitive, I wouldn’t be able to make enough money to cover costs, assuming I make any. Since I was (and still am) in between jobs, I decided to abandon the project. 👉 What I learned: Do not start projects with a low ratio of money to effort and time. Example: Even if I get 500 monthly users, 200 of which are paid users (unrealistically high number), assuming an average subscription fee of $5/m (such apps are quite cheap, mostly due to the high competition), it would make me around $1000 minus any occurring costs. Any founder with a product that has 500 active users should make more. Even if it was relatively successful, due to the high competition, I wouldn’t make any meaningful money. PS: I use Todoist today. Due to local pricing, I pay less than $2/m. There is no way I could beat this competitive pricing, let alone the app itself. But, somehow, with a project that wasn’t even functional — let alone being an MVP — I made my first Wi-Fi money: Someone decided that the domain I preemptively purchased is worth something. By this point, I had already abandoned the project, certainly wasn’t going to renew the domain, was looking for a FT job, and a new project that I could work on. And out of nowhere, someone hands me some free money — who am I not to take it? Of course, I took it. The domain is still unused, no idea why 🤔. Ngl, I still hate the fact that my first Wi-Fi money came from this. A new idea worth pursuing? Fast-forward some weeks now. Around March, I got this crazy idea of building an email productivity tool. We all use emails, yet we all hate them. So, this must be fixed. Everyone uses emails, in fact everyone HAS TO use emails. So, I just needed to build a tool and wait for people to come. This was all, really. After all, the problem space is huge, there is enough room for another product, everyone uses emails, no need for any further validation, right? ❌ WRONG ONCE AGAIN! We all hear from the greatest in the startup landscape that we must validate our ideas with real people, yet at least some of us (guilty here 🥸) think that our product will be hugely successful and prove them to be an exception. Few might, but most are not. I certainly wasn't. 👉 Lesson learned: Always validate your ideas with real people. Ask them how much they’d pay for such a tool (not if they would). Much better if they are willing to pay upfront for a discount, etc. But even this comes later, keep reading. I think the difference between “How much” and “If” is huge for two reasons: (1) By asking them for “How much”, you force them to think in a more realistic setting. (2) You will have a more realistic idea on your profit margins. Based on my competitive analysis, I already had a solution in my mind to improve our email usage standards and email productivity (huge mistake), but I did my best to learn about their problems regarding those without pushing the idea too hard. The idea is this: Generate concise email summaries with suggested actions, combine them into one email, and send it at their preferred times. Save as much as time the AI you end up with allows. After all, everyone loves to save time. So, what kind of validation did I seek for? Talked with only a few people around me about this crazy, internet-breaking idea. The responses I got were, now I see, mediocre; no one got excited about it, just said things along the lines of “Cool idea, OK”. So, any reasonable person in this situation would think “Okay, not might not be working”, right? Well, I did not. I assumed that they were the wrong audience for this product, and there was this magical land of user segments waiting eagerly for my product, yet unknowingly. To this day, I still have not reached this magical place. Perhaps, it didn’t exist in the first place. If I cannot find it, whether it exists or not doesn’t matter. I am certainly searching for it. 👉 What I should have done: Once I decide on a problem space (time management, email productivity, etc.), I should decide on my potential user segments, people who I plan to sell my product to. Then I should go talk to those people, ask them about their pains, then get to the problem-solving/ideation phase only later. ❗️ VALIDATION COMES FROM THE REALITY OUTSIDE. What validation looks like might change from product to product; but what invalidation looks like is more or less the same for every product. Nico Jeannen told me yesterday “validation = money in the account” on Twitter. This is the ultimate form of validation your product could get. If your product doesn’t make any money, then something is invalidated by reality: Your product, you, your idea, who knows? So, at this point, I knew a little bit of Python from spending some time in tutorial hell a few years ago, some HTML/CSS/JS, barely enough React to build a working app. React could work for this project, but I needed easy-to-implement server interactivity. Luckily, around this time, I got to know about this new gen of indie hackers, and learned (but didn’t truly understand) about their approach to indie hacking, and this library called Nextjs. How good Next.js still blows my mind. So, I was back to tutorial hell once again. But, this time, with a promise to myself: This is the last time I would visit tutorial hell. Time to start building this "ground-breaking idea" Learning the fundamentals of Next.js was easier than learning of React unsurprisingly. Yet, the first time I managed to run server actions on Next.js was one of the rarest moments that completely blew my mind. To this day, I reject the idea that it is something else than pure magic under its hood. Did I absolutely need Nextjs for this project though? I do not think so. Did it save me lots of time? Absolutely. Furthermore, learning Nextjs will certainly be quite helpful for other projects that I will be tackling in the future. Already got a few ideas that might be worth pursuing in the head in case I decide to abandon Summ in the future. Fast-forward few weeks again: So, at this stage, I had a barely working MVP-like product. Since the very beginning, I spent every free hour (and more) on this project as speed is essential. But, I am not so sure it was worth it to overwork in retrospect. Yet, I know I couldn’t help myself. Everything is going kinda smooth, so what’s the worst thing that could ever happen? Well, both Apple and Google announced their AIs (Apple Intelligence and Google Gemini, respectively) will have email summarization features for their products. Summarizing singular emails is no big deal, after all there were already so many similar products in the market. I still think that what truly matters is a frictionless user experience, and this is why I built this product in a certain way: You spend less than a few minutes setting up your account, and you get to enjoy your email summaries, without ever visiting its website again. This is still a very cool concept I really like a lot. So, at this point: I had no other idea that could be pursued, already spent too much time on this project. Do I quit or not? This was the question. Of course not. I just have to launch this product as quickly as possible. So, I did something right, a quite rare occurrence I might say: Re-planned my product, dropped everything secondary to the core feature immediately (save time on reading emails), tried launching it asap. 👉 Insight: Sell only one core feature at one time. Drop anything secondary to this core feature. Well, my primary occupation is product design. So one would expect that a product I build must have stellar design. I considered any considerable time spent on design at this stage would be simply wasted. I still think this is both true and wrong: True, because if your product’s core benefits suck, no one will care about your design. False, because if your design looks amateurish, no one will trust you and your product. So, I always targeted an average level design with it and the way this tool works made it quite easy as I had to design only 2 primary pages: Landing page and user portal (which has only settings and analytics pages). However, even though I knew spending time on design was not worth much of my time, I got a bit “greedy”: In fact, I redesigned those pages three times, and still ended up with a so-so design that I am not proud of. 👉 What I would do differently: Unless absolutely necessary, only one iteration per stage as long as it works. This, in my mind, applies to everything. If your product’s A feature works, then no need to rewrite it from scratch for any reason, or even refactor it. When your product becomes a success, and you absolutely need that part of your codebase to be written, do so, but only then. Ready to launch, now is th etime for some marketing, right? By July 26, I already had a “launchable” product that barely works (I marked this date on a Notion docs, this is how I know). Yet, I had spent almost no time on marketing, sales, whatever. After all, “You build and they will come”. Did I know that I needed marketing? Of course I did, but knowingly didn’t. Why, you might ask. Well, from my perspective, it had to be a dev-heavy product; meaning that you spend most of your time on developing it, mostly coding skills. But, this is simply wrong. As a rule of thumb, as noted by one of the greatests, Marc Louvion, you should spend at least twice of the building time on marketing. ❗️ Time spent on building \* 2 people don’t know your product > they don’t use your product > you don’t get users > you don’t make money Easy as that. Following the same reasoning, a slightly different approach to planning a project is possible. Determine an approximate time to complete the project with a high level project plan. Let’s say 6 months. By the reasoning above, 2 months should go into building, and 4 into marketing. If you need 4 months for building instead of 2, then you need 8 months of marketing, which makes the time to complete the project 12 months. If you don’t have that much time, then quit the project. When does a project count as completed? Well, in reality, never. But, I think we have to define success conditions even before we start for indie projects and startups; so we know when to quit when they are not met. A success condition could look like “Make $6000 in 12 months” or “Have 3000 users in 6 months”. It all depends on the project. But, once you set it, it should be set in stone: You don’t change it unless absolutely necessary. I suspect there are few principles that make a solopreneur successful; and knowing when to quit and when to continue is definitely one of them. Marc Louvion is famously known for his success, but he got there after failing so many projects. To my knowledge, the same applies to Nico Jeannen, Pieter Levels, or almost everyone as well. ❗️ Determining when to continue even before you start will definitely help in the long run. A half-aed launch Time-leap again. Around mid August, I “soft launched” my product. By soft launch, I mean lazy marketing. Just tweeting about it, posting it on free directories. Did I get any traffic? Surely I did. Did I get any users? Nope. Only after this time, it hit me: “Either something is wrong with me, or with this product” Marketing might be a much bigger factor for a project’s success after all. Even though I get some traffic, not convincing enough for people to sign up even for a free trial. The product was still perfect in my eyes at the time (well, still is ^(\_),) so the right people are not finding my product, I thought. Then, a question that I should have been asking at the very first place, one that could prevent all these, comes to my mind: “How do even people search for such tools?” If we are to consider this whole journey of me and my so-far-failed product to be an already destined failure, one metric suffices to show why. Search volume: 30. Even if people have such a pain point, they are not looking for email summaries. So, almost no organic traffic coming from Google. But, as a person who did zero marketing on this or any product, who has zero marketing knowledge, who doesn’t have an audience on social media, there is not much I could do. Finally, it was time to give up. Or not… In my eyes, the most important element that makes a founder (solo or not) successful (this, I am not by any means) is to solve problems. ❗️ So, the problem was this: “People are not finding my product by organic search” How do I make sure I get some organic traffic and gets more visibility? Learn digital marketing and SEO as much as I can within very limited time. Thankfully, without spending much time, I came across Neil Patel's YT channel, and as I said many times, it is an absolute gold mine. I learned a lot, especially about the fundamentals, and surely it will be fruitful; but there is no magic trick that could make people visit your website. SEO certainly helps, but only when people are looking for your keywords. However, it is truly a magical solution to get in touch with REAL people that are in your user segments: 👉 Understand your pains, understand their problems, help them to solve them via building products. I did not do this so far, have to admit. But, in case you would like to have a chat about your email usage, and email productivity, just get in touch; I’d be delighted to hear about them. Getting ready for a ProductHunt launch The date was Sept 1. And I unlocked an impossible achievement: Running out of Supabase’s free plan’s Egres limit while having zero users. I was already considering moving out of their Cloud server and managing a Supabase CLI service on my Hetzner VPS for some time; but never ever suspected that I would have to do this quickly. The cheapest plan Supabase offers is $25/month; yet, at that point, I am in between jobs for such a long time, basically broke, and could barely afford that price. One or two months could be okay, but why pay for it if I will eventually move out of their Cloud service? So, instead of paying $25, I spent two days migrating out of Supabase Cloud. Worth my time? Definitely not. But, when you are broke, you gotta do stupid things. This was the first time that I felt lucky to have zero users: I have no idea how I would manage this migration if I had any. I think this is one of the core tenets of an indie hacker: Controlling their own environment. I can’t remember whose quote this is, but I suspect it was Naval: Entrepreneurs have an almost pathological need to control their own fate. They will take any suffering if they can be in charge of their destiny, and not have it in somebody else’s hands. What’s truly scary is, at least in my case, we make people around us suffer at the expense of our attempting to control our own fates. I know this period has been quite hard on my wife as well, as I neglected her quite a bit, but sadly, I know that this will happen again. It is something that I can barely help with. Still, so sorry. After working the last two weeks on a ProductHunt Launch, I finally launched it this Tuesday. Zero ranking, zero new users, but 36 kind people upvoted my product, and many commented and provided invaluable feedback. I couldn't be more grateful for each one of them 🙏. Considering all these, what lies in the future of Summ though? I have no idea, to be honest. On one hand, I have zero users, have no job, no income. So, I need a way to make money asap. On the other hand, the whole idea of it revolves around one core premise (not an assumption) that I am not so willing to share; and I couldn’t have more trust in it. This might not be the best iteration of it, however I certainly believe that email usage is one of the best problem spaces one could work on. 👉 But, one thing is for certain: I need to get in touch with people, and talk with them about this product I built so far. In fact, this is the only item on my agenda. Nothing else will save my brainchild <3. Below are some other insights and notes that I got during my journey; as they do not 100% fit into this story, I think it is more suitable to list them here. I hope you enjoyed reading this. Give Summ a try, it comes with a generous free trial, no credit card required. Some additional notes and insights: Project planning is one of the most underestimated skills for solopreneurs. It saves you enormous time, and helps you to keep your focus up. Building B2C products beats building B2B products. Businesses are very willing to pay big bucks if your product helps them. On the other hand, spending a few hours per user who would pay $5/m probably is not worth your time. It doesn’t matter how brilliant your product is if no one uses it. If you cannot sell a product in a certain category/niche (or do not know how to sell it), it might be a good idea not to start a project in it. Going after new ideas and ventures is quite risky, especially if you don’t know how to market it. On the other hand, an already established category means that there is already demand. Whether this demand is sufficient or not is another issue. As long as there is enough demand for your product to fit in, any category/niche is good. Some might be better, some might be worse. Unless you are going hardcore B2B, you will need people to find your product by means of organic search. Always conduct thorough keyword research as soon as possible.

Looking for a tech cofounder. Revoltionary (yes really!) gig economy app. I will not promote.
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Looking for a tech cofounder. Revoltionary (yes really!) gig economy app. I will not promote.

Hey everyone! I’m building a new gig-work app that cuts out the hassles of interviews, applications, and sky-high fees. We’re aiming to make it easy for businesses to hire qualified freelancers for short shifts or one-off tasks—and for freelancers to set their own rates and get paid quickly. Why This App? Time-Saving Model: Instead of posting jobs and conducting multiple interviews, employers can instantly book from a list of KYC-verified freelancers who showcase their skills via 30-second video bios. Cost Leadership: We plan to charge only 5%, far below the 15–50% common in other gig platforms. This keeps more money in the pockets of both freelancers and businesses. Proven Demand: A beta test in 2018 drew nearly 600 active users, validating that there’s appetite for a simpler, fairer way to fill short shifts. About Me 20+ years’ experience in payroll, workforce management, and operations for Fortune 500 companies. Led cross-functional teams, implemented large-scale solutions, and believe in building with a user-first mindset. Offering meaningful equity—I want a true partner, not a hired gun. Who I’m Looking For Full-Stack Developer (comfortable with Node.js, React, Python, or similar and ML/Ai) who can manage everything from front-end to database integration (ideally Postgres/MySQL) and build a same day payments system. Passion for creating solutions that genuinely help gig workers and small businesses. Excitement to collaborate on the product roadmap, from the booking interface to same-day payment features. The Opportunity Major Market: The gig economy is huge and still growing. If we nail speed, cost-effectiveness, and ease of use, we can capture a significant share of it. Remote-Friendly: We can work together from anywhere, though I’m planning to relaunch in London where the initial beta gained momentum. If this sounds like your kind of challenge, drop a comment or DM me. Let’s chat about how we can merge our strengths—my operations background and your technical expertise—to build a platform that truly transforms the gig-work experience. Thanks for reading, and I look forward to creating something impactful together!

Lessons from 139 YC AI startups (S23)
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Lessons from 139 YC AI startups (S23)

YC's Demo Day was last week, and with it comes another deluge of AI companies. A record-breaking 139 startups were in some way related to AI or ML - up from 112 in the last batch. Here are 5 of my biggest takeaways: AI is (still) eating the world. It's remarkable how diverse the industries are - over two dozen verticals were represented, from materials science to social media to security. However, the top four categories were: AI Ops: Tooling and platforms to help companies deploy working AI models. We'll discuss more below, but AI Ops has become a huge category, primarily focused on LLMs and taming them for production use cases. Developer Tools: Apps, plugins, and SDKs making it easier to write code. There were plenty of examples of integrating third-party data, auto-generating code/tests, and working with agents/chatbots to build and debug code. Healthcare + Biotech: It seems like healthcare has a lot of room for automation, with companies working on note-taking, billing, training, and prescribing. And on the biotech side, there are some seriously cool companies building autonomous surgery robots and at-home cancer detection. Finance + Payments: Startups targeting banks, fintechs, and compliance departments. This was a wide range of companies, from automated collections to AI due diligence to "Copilot for bankers." Those four areas covered over half of the startups. The first two make sense: YC has always filtered for technical founders, and many are using AI to do what they know - improve the software developer workflow. But it's interesting to see healthcare and finance not far behind. Previously, I wrote: Large enterprises, healthcare, and government are not going to send sensitive data to OpenAI. This leaves a gap for startups to build on-premise, compliant \[LLMs\] for these verticals. And we're now seeing exactly that - LLMs focused on healthcare and finance and AI Ops companies targeting on-prem use cases. It also helps that one of the major selling points of generative AI right now is cost-cutting - an enticing use case for healthcare and finance. Copilots are king. In the last batch, a lot of startups positioned themselves as "ChatGPT for X," with a consumer focus. It seems the current trend, though, is "Copilot for X" - B2B AI assistants to help you do everything from KYC checks to corporate event planning to chip design to negotiate contracts. Nearly two dozen companies were working on some sort of artificial companion for businesses - and a couple for consumers. It's more evidence for the argument that AI will not outright replace workers - instead, existing workers will collaborate with AI to be more productive. And as AI becomes more mainstream, this trend of making specialized tools for specific industries or tasks will only grow. That being said - a Bing-style AI that lives in a sidebar and is only accessible via chat probably isn't the most useful form factor for AI. But until OpenAI, Microsoft, and Google change their approach (or until another company steps up), we'll probably see many more Copilots. AI Ops is becoming a key sector. "AI Ops" has been a term for only a few years. "LLM Ops" has existed for barely a year. And yet, so many companies are focused on training, fine-tuning, deploying, hosting, and post-processing LLMs it's quickly becoming a critical piece of the AI space. It's a vast industry that's sprung up seemingly overnight, and it was pretty interesting to see some of the problems being solved at the bleeding edge. For example: Adding context to language models with as few as ten samples. Pausing and moving training runs in real-time. Managing training data ownership and permissions. Faster vector databases. Fine-tuning models with synthetic data. But as much ~~hype~~ enthusiasm and opportunity as there might be, the size of the AI Ops space also shows how much work is needed to really productionalize LLMs and other models. There are still many open questions about reliability, privacy, observability, usability, and safety when it comes to using LLMs in the wild. Who owns the model? Does it matter? Nine months ago, anyone building an LLM company was doing one of three things: Training their own model from scratch. Fine-tuning a version of GPT-3. Building a wrapper around ChatGPT. Thanks to Meta, the open-source community, and the legions of competitors trying to catch up to OpenAI, there are now dozens of ways to integrate LLMs. However, I found it interesting how few B2B companies mentioned whether or not they trained their own model. If I had to guess, I'd say many are using ChatGPT or a fine-tuned version of Llama 2. But it raises an interesting question - if the AI provides value, does it matter if it's "just" ChatGPT behind the scenes? And once ChatGPT becomes fine-tuneable, when (if ever) will startups decide to ditch OpenAI and use their own model instead? "AI" isn't a silver bullet. At the end of the day, perhaps the biggest lesson is that "AI" isn't a magical cure-all - you still need to build a defensible company. At the beginning of the post-ChatGPT hype wave, it seemed like you just had to say "we're adding AI" to raise your next round or boost your stock price. But competition is extremely fierce. Even within this batch, there were multiple companies with nearly identical pitches, including: Solving customer support tickets. Negotiating sales contracts. Writing drafts of legal documents. Building no-code LLM workflows. On-prem LLM deployment. Automating trust and safety moderation. As it turns out, AI can be a competitive advantage, but it can't make up for a bad business. The most interesting (and likely valuable) companies are the ones that take boring industries and find non-obvious use cases for AI. In those cases, the key is having a team that can effectively distribute a product to users, with or without AI. Where we’re headed I'll be honest - 139 companies is a lot. In reviewing them all, there were points where it just felt completely overwhelming. But after taking a step back, seeing them all together paints an incredibly vivid picture of the current AI landscape: one that is diverse, rapidly evolving, and increasingly integrated into professional and personal tasks. These startups aren't just building AI for the sake of technology or academic research, but are trying to address real-world problems. Technology is always a double-edged sword - and some of the startups felt a little too dystopian for my taste - but I'm still hopeful about AI's ability to improve productivity and the human experience.

Why raise in 2025? - I will not promote
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Why raise in 2025? - I will not promote

I will not promote Lately, I've been thinking about how AI tools are completely reshaping what it means to bootstrap a startup. It honestly feels like we're living through a golden age for entrepreneurs where you don't necessarily need venture capital to build something big or meaningful. At my company, we're a small team of just four people, bootstrapping our AI-focused startup. Thanks to AI-powered tools, we're able to keep our burn rate ridiculously low, quickly test new ideas, and scale our operations way faster than we ever expected. It’s honestly pretty incredible how accessible advanced technology has become, even compared to just a few years ago. Of course, bootstrapping definitely comes with its own share of headaches. For example, we've noticed that funded startups get significantly better access to cloud credits, advertising budgets, and enterprise-level tools. We do have access to some discounts and free resources, but it rarely compares to what funded startups enjoy. This can feel frustrating, especially when you know you're competing directly with businesses that have those extra advantages. Visibility is another major challenge we've noticed. Without big funding announcements or a well-connected investor backing us, getting attention from media or even early adopters can be tough. It's just harder to make a splash without someone else's endorsement. We've had to accept and work around creatively. That said, there's something genuinely empowering about staying bootstrapped, prioritizing profitability, and maintaining control over our vision. After speaking with several investors, we've become aware of how investors can significantly influence or even redirect the trajectory of a business. We've heard stories where investors gained enough leverage to replace the original founders or have killed perfectly profitable businesses that were not growing "fast enough", which certainly gave us pause. They can definitely be helpful but giving the control over the future of my business to someone else would definitely make me feel anxious. At this time, we simply don't feel raising external capital aligns with our current goals, but we're also aware that this could change in the future. For now, maintaining autonomy and staying close to our original vision remains a priority. I'm curious to hear from others here who've been through this. Have you successfully bootstrapped an AI a tech business? What obstacles did you encounter, and how did you overcome them? EDIT: To give you a bit of perspective, my company is a B2B SaaS in the finance industry based in Europe. We have received VC funding in the past but it was an exceptionally good deal and we don't plan to raise in the near future even-thought it may change if we see the need to help us scale. We have also raised a significant amount in soft funding. Right now, we are growing on our revenues, and we plan to continue this trajectory. Recently, one of our developers left, and although we are a small team, we noticed that it had little to no impact on our productivity.

I spent 6 months on building a tool, and got 0 zero users. Here is my story.
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I spent 6 months on building a tool, and got 0 zero users. Here is my story.

Edit Thank you all so much for your time reading my story. Your support, feedback, criticism, and skepticism; all helped me a lot, and I couldn't appreciate it enough \^\_\^ TL;DR I spent 6 months on a tool that currently has 0 users. Below is what I learned during my journey, sharing because I believe most mistakes are easily avoidable. Do not overestimate your product and assume it will be an exception to fundamental principles. Principles are there for a reason. Always look for validation before you start. Avoid building products with a low money-to-effort ratio/in very competitive fields. Unless you have the means, you probably won't make it. Pick a problem space, pick your target audience, and talk to them before thinking about a solution. Identify and match their pain points. Only then should you think of a solution. If people are not overly excited or willing to pay in advance for a discounted price, it might be a sign to rethink. Sell one and only one feature at a time. Avoid everything else. If people don't pay for that one core feature, no secondary feature will change their mind. Always spend twice as much time marketing as you do building. You will not get users if they don't know it exists. Define success metrics ("1000 users in 3 months" or "$6000 in the account at the end of 6 months") before you start. If you don't meet them, strongly consider quitting the project. If you can't get enough users to keep going, nothing else matters. VALIDATION, VALIDATION, VALIDATION. Success is not random, but most of our first products will not make a success story. Know when to admit failure, and move on. Even if a product of yours doesn't succeed, what you learned during its journey will turn out to be invaluable for your future. My story So, this is the story of a product, Summ, that I’ve been working on for the last 6 months. As it's the first product I’ve ever built, after watching you all from the sidelines, I have learned a lot, made many mistakes, and did only a few things right. Just sharing what I’ve learned and some insights from my journey so far. I hope that this post will help you avoid the mistakes I made — most of which I consider easily avoidable — while you enjoy reading it, and get to know me a little bit more 🤓. A slow start after many years Summ isn’t the first product I really wanted to build. Lacking enough dev skills to even get started was a huge blocker for so many years. In fact, the first product I would’ve LOVED to build was a smart personal shopping assistant. I had this idea 4 years ago; but with no GPT, no coding skills, no technical co-founder, I didn’t have the means to make it happen. I still do not know if such a tool exists and is good enough. All I wanted was a tool that could make data-based predictions about when to buy stuff (“buy a new toothpaste every three months”) and suggest physical products that I might need or be strongly interested in. AFAIK, Amazon famously still struggles with the second one. Fast-forward a few years, I learned the very basics of HTML, CSS, and Vanilla JS. Still was not there to build a product; but good enough to code my design portfolio from scratch. Yet, I couldn’t imagine myself building a product using Vanilla JS. I really hated it, I really sucked at it. So, back to tutorial hell, and to learn about this framework I just heard about: React.React introduced so many new concepts to me. “Thinking in React” is a phrase we heard a lot, and with quite good reasons. After some time, I was able to build very basic tutorial apps, both in React, and React Native; but I have to say that I really hated coding for mobile. At this point, I was already a fan of productivity apps, and had a concept for a time management assistant app in my design portfolio. So, why not build one? Surely, it must be easy, since every coding tutorial starts with a todo app. ❌ WRONG! Building a basic todo app is easy enough, but building one good enough for a place in the market was a challenge I took and failed. I wasted one month on that until I abandoned the project for good. Even if I continued working on it, as the productivity landscape is overly competitive, I wouldn’t be able to make enough money to cover costs, assuming I make any. Since I was (and still am) in between jobs, I decided to abandon the project. 👉 What I learned: Do not start projects with a low ratio of money to effort and time. Example: Even if I get 500 monthly users, 200 of which are paid users (unrealistically high number), assuming an average subscription fee of $5/m (such apps are quite cheap, mostly due to the high competition), it would make me around $1000 minus any occurring costs. Any founder with a product that has 500 active users should make more. Even if it was relatively successful, due to the high competition, I wouldn’t make any meaningful money. PS: I use Todoist today. Due to local pricing, I pay less than $2/m. There is no way I could beat this competitive pricing, let alone the app itself. But, somehow, with a project that wasn’t even functional — let alone being an MVP — I made my first Wi-Fi money: Someone decided that the domain I preemptively purchased is worth something. By this point, I had already abandoned the project, certainly wasn’t going to renew the domain, was looking for a FT job, and a new project that I could work on. And out of nowhere, someone hands me some free money — who am I not to take it? Of course, I took it. The domain is still unused, no idea why 🤔. Ngl, I still hate the fact that my first Wi-Fi money came from this. A new idea worth pursuing? Fast-forward some weeks now. Around March, I got this crazy idea of building an email productivity tool. We all use emails, yet we all hate them. So, this must be fixed. Everyone uses emails, in fact everyone HAS TO use emails. So, I just needed to build a tool and wait for people to come. This was all, really. After all, the problem space is huge, there is enough room for another product, everyone uses emails, no need for any further validation, right? ❌ WRONG ONCE AGAIN! We all hear from the greatest in the startup landscape that we must validate our ideas with real people, yet at least some of us (guilty here 🥸) think that our product will be hugely successful and prove them to be an exception. Few might, but most are not. I certainly wasn't. 👉 Lesson learned: Always validate your ideas with real people. Ask them how much they’d pay for such a tool (not if they would). Much better if they are willing to pay upfront for a discount, etc. But even this comes later, keep reading. I think the difference between “How much” and “If” is huge for two reasons: (1) By asking them for “How much”, you force them to think in a more realistic setting. (2) You will have a more realistic idea on your profit margins. Based on my competitive analysis, I already had a solution in my mind to improve our email usage standards and email productivity (huge mistake), but I did my best to learn about their problems regarding those without pushing the idea too hard. The idea is this: Generate concise email summaries with suggested actions, combine them into one email, and send it at their preferred times. Save as much as time the AI you end up with allows. After all, everyone loves to save time. So, what kind of validation did I seek for? Talked with only a few people around me about this crazy, internet-breaking idea. The responses I got were, now I see, mediocre; no one got excited about it, just said things along the lines of “Cool idea, OK”. So, any reasonable person in this situation would think “Okay, not might not be working”, right? Well, I did not. I assumed that they were the wrong audience for this product, and there was this magical land of user segments waiting eagerly for my product, yet unknowingly. To this day, I still have not reached this magical place. Perhaps, it didn’t exist in the first place. If I cannot find it, whether it exists or not doesn’t matter. I am certainly searching for it. 👉 What I should have done: Once I decide on a problem space (time management, email productivity, etc.), I should decide on my potential user segments, people who I plan to sell my product to. Then I should go talk to those people, ask them about their pains, then get to the problem-solving/ideation phase only later. ❗️ VALIDATION COMES FROM THE REALITY OUTSIDE. What validation looks like might change from product to product; but what invalidation looks like is more or less the same for every product. Nico Jeannen told me yesterday “validation = money in the account” on Twitter. This is the ultimate form of validation your product could get. If your product doesn’t make any money, then something is invalidated by reality: Your product, you, your idea, who knows? So, at this point, I knew a little bit of Python from spending some time in tutorial hell a few years ago, some HTML/CSS/JS, barely enough React to build a working app. React could work for this project, but I needed easy-to-implement server interactivity. Luckily, around this time, I got to know about this new gen of indie hackers, and learned (but didn’t truly understand) about their approach to indie hacking, and this library called Nextjs. How good Next.js still blows my mind. So, I was back to tutorial hell once again. But, this time, with a promise to myself: This is the last time I would visit tutorial hell. Time to start building this "ground-breaking idea" Learning the fundamentals of Next.js was easier than learning of React unsurprisingly. Yet, the first time I managed to run server actions on Next.js was one of the rarest moments that completely blew my mind. To this day, I reject the idea that it is something else than pure magic under its hood. Did I absolutely need Nextjs for this project though? I do not think so. Did it save me lots of time? Absolutely. Furthermore, learning Nextjs will certainly be quite helpful for other projects that I will be tackling in the future. Already got a few ideas that might be worth pursuing in the head in case I decide to abandon Summ in the future. Fast-forward few weeks again: So, at this stage, I had a barely working MVP-like product. Since the very beginning, I spent every free hour (and more) on this project as speed is essential. But, I am not so sure it was worth it to overwork in retrospect. Yet, I know I couldn’t help myself. Everything is going kinda smooth, so what’s the worst thing that could ever happen? Well, both Apple and Google announced their AIs (Apple Intelligence and Google Gemini, respectively) will have email summarization features for their products. Summarizing singular emails is no big deal, after all there were already so many similar products in the market. I still think that what truly matters is a frictionless user experience, and this is why I built this product in a certain way: You spend less than a few minutes setting up your account, and you get to enjoy your email summaries, without ever visiting its website again. This is still a very cool concept I really like a lot. So, at this point: I had no other idea that could be pursued, already spent too much time on this project. Do I quit or not? This was the question. Of course not. I just have to launch this product as quickly as possible. So, I did something right, a quite rare occurrence I might say: Re-planned my product, dropped everything secondary to the core feature immediately (save time on reading emails), tried launching it asap. 👉 Insight: Sell only one core feature at one time. Drop anything secondary to this core feature. Well, my primary occupation is product design. So one would expect that a product I build must have stellar design. I considered any considerable time spent on design at this stage would be simply wasted. I still think this is both true and wrong: True, because if your product’s core benefits suck, no one will care about your design. False, because if your design looks amateurish, no one will trust you and your product. So, I always targeted an average level design with it and the way this tool works made it quite easy as I had to design only 2 primary pages: Landing page and user portal (which has only settings and analytics pages). However, even though I knew spending time on design was not worth much of my time, I got a bit “greedy”: In fact, I redesigned those pages three times, and still ended up with a so-so design that I am not proud of. 👉 What I would do differently: Unless absolutely necessary, only one iteration per stage as long as it works. This, in my mind, applies to everything. If your product’s A feature works, then no need to rewrite it from scratch for any reason, or even refactor it. When your product becomes a success, and you absolutely need that part of your codebase to be written, do so, but only then. Ready to launch, now is th etime for some marketing, right? By July 26, I already had a “launchable” product that barely works (I marked this date on a Notion docs, this is how I know). Yet, I had spent almost no time on marketing, sales, whatever. After all, “You build and they will come”. Did I know that I needed marketing? Of course I did, but knowingly didn’t. Why, you might ask. Well, from my perspective, it had to be a dev-heavy product; meaning that you spend most of your time on developing it, mostly coding skills. But, this is simply wrong. As a rule of thumb, as noted by one of the greatests, Marc Louvion, you should spend at least twice of the building time on marketing. ❗️ Time spent on building \* 2 people don’t know your product > they don’t use your product > you don’t get users > you don’t make money Easy as that. Following the same reasoning, a slightly different approach to planning a project is possible. Determine an approximate time to complete the project with a high level project plan. Let’s say 6 months. By the reasoning above, 2 months should go into building, and 4 into marketing. If you need 4 months for building instead of 2, then you need 8 months of marketing, which makes the time to complete the project 12 months. If you don’t have that much time, then quit the project. When does a project count as completed? Well, in reality, never. But, I think we have to define success conditions even before we start for indie projects and startups; so we know when to quit when they are not met. A success condition could look like “Make $6000 in 12 months” or “Have 3000 users in 6 months”. It all depends on the project. But, once you set it, it should be set in stone: You don’t change it unless absolutely necessary. I suspect there are few principles that make a solopreneur successful; and knowing when to quit and when to continue is definitely one of them. Marc Louvion is famously known for his success, but he got there after failing so many projects. To my knowledge, the same applies to Nico Jeannen, Pieter Levels, or almost everyone as well. ❗️ Determining when to continue even before you start will definitely help in the long run. A half-aed launch Time-leap again. Around mid August, I “soft launched” my product. By soft launch, I mean lazy marketing. Just tweeting about it, posting it on free directories. Did I get any traffic? Surely I did. Did I get any users? Nope. Only after this time, it hit me: “Either something is wrong with me, or with this product” Marketing might be a much bigger factor for a project’s success after all. Even though I get some traffic, not convincing enough for people to sign up even for a free trial. The product was still perfect in my eyes at the time (well, still is ^(\_),) so the right people are not finding my product, I thought. Then, a question that I should have been asking at the very first place, one that could prevent all these, comes to my mind: “How do even people search for such tools?” If we are to consider this whole journey of me and my so-far-failed product to be an already destined failure, one metric suffices to show why. Search volume: 30. Even if people have such a pain point, they are not looking for email summaries. So, almost no organic traffic coming from Google. But, as a person who did zero marketing on this or any product, who has zero marketing knowledge, who doesn’t have an audience on social media, there is not much I could do. Finally, it was time to give up. Or not… In my eyes, the most important element that makes a founder (solo or not) successful (this, I am not by any means) is to solve problems. ❗️ So, the problem was this: “People are not finding my product by organic search” How do I make sure I get some organic traffic and gets more visibility? Learn digital marketing and SEO as much as I can within very limited time. Thankfully, without spending much time, I came across Neil Patel's YT channel, and as I said many times, it is an absolute gold mine. I learned a lot, especially about the fundamentals, and surely it will be fruitful; but there is no magic trick that could make people visit your website. SEO certainly helps, but only when people are looking for your keywords. However, it is truly a magical solution to get in touch with REAL people that are in your user segments: 👉 Understand your pains, understand their problems, help them to solve them via building products. I did not do this so far, have to admit. But, in case you would like to have a chat about your email usage, and email productivity, just get in touch; I’d be delighted to hear about them. Getting ready for a ProductHunt launch The date was Sept 1. And I unlocked an impossible achievement: Running out of Supabase’s free plan’s Egres limit while having zero users. I was already considering moving out of their Cloud server and managing a Supabase CLI service on my Hetzner VPS for some time; but never ever suspected that I would have to do this quickly. The cheapest plan Supabase offers is $25/month; yet, at that point, I am in between jobs for such a long time, basically broke, and could barely afford that price. One or two months could be okay, but why pay for it if I will eventually move out of their Cloud service? So, instead of paying $25, I spent two days migrating out of Supabase Cloud. Worth my time? Definitely not. But, when you are broke, you gotta do stupid things. This was the first time that I felt lucky to have zero users: I have no idea how I would manage this migration if I had any. I think this is one of the core tenets of an indie hacker: Controlling their own environment. I can’t remember whose quote this is, but I suspect it was Naval: Entrepreneurs have an almost pathological need to control their own fate. They will take any suffering if they can be in charge of their destiny, and not have it in somebody else’s hands. What’s truly scary is, at least in my case, we make people around us suffer at the expense of our attempting to control our own fates. I know this period has been quite hard on my wife as well, as I neglected her quite a bit, but sadly, I know that this will happen again. It is something that I can barely help with. Still, so sorry. After working the last two weeks on a ProductHunt Launch, I finally launched it this Tuesday. Zero ranking, zero new users, but 36 kind people upvoted my product, and many commented and provided invaluable feedback. I couldn't be more grateful for each one of them 🙏. Considering all these, what lies in the future of Summ though? I have no idea, to be honest. On one hand, I have zero users, have no job, no income. So, I need a way to make money asap. On the other hand, the whole idea of it revolves around one core premise (not an assumption) that I am not so willing to share; and I couldn’t have more trust in it. This might not be the best iteration of it, however I certainly believe that email usage is one of the best problem spaces one could work on. 👉 But, one thing is for certain: I need to get in touch with people, and talk with them about this product I built so far. In fact, this is the only item on my agenda. Nothing else will save my brainchild <3. Below are some other insights and notes that I got during my journey; as they do not 100% fit into this story, I think it is more suitable to list them here. I hope you enjoyed reading this. Give Summ a try, it comes with a generous free trial, no credit card required. Some additional notes and insights: Project planning is one of the most underestimated skills for solopreneurs. It saves you enormous time, and helps you to keep your focus up. Building B2C products beats building B2B products. Businesses are very willing to pay big bucks if your product helps them. On the other hand, spending a few hours per user who would pay $5/m probably is not worth your time. It doesn’t matter how brilliant your product is if no one uses it. If you cannot sell a product in a certain category/niche (or do not know how to sell it), it might be a good idea not to start a project in it. Going after new ideas and ventures is quite risky, especially if you don’t know how to market it. On the other hand, an already established category means that there is already demand. Whether this demand is sufficient or not is another issue. As long as there is enough demand for your product to fit in, any category/niche is good. Some might be better, some might be worse. Unless you are going hardcore B2B, you will need people to find your product by means of organic search. Always conduct thorough keyword research as soon as possible.

Am I on the right track?
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ayezee33This week

Am I on the right track?

This might be a little long for the average reader. But i'll do my best to format it so it's skimmable. Context I left my SaaS company 2 months ago. I was employee number 4 and helped them grow to 8 figures. I had a seat at the executive table and equity in the business. Burnt out and wanted to start my own thing. I forgot how hard it is to go from 0 👉 1 📚 Two schools of thought Build a product that solves your pain point and find others with that pain point Perform customer discovery calls until you get signal and start building + follow up with them 🥇 First approach For the last 45 days I built the product I wished I had when leading a 10 person marketing/sales team for the SaaS I was previously at. It checked all the boxes, pulled data, automated specific steps, showed the conversion tracking, data, etc. I launched it as a beta to my close network and the crowd went MILD. 😒 After some follow up - I realized I built something that already kind of exists and it's hard to convince others (even those who personally know me) that it's different or better. Undiscouraged, I am going to go back to the drawing board and try approach #2 above and schedule some customer discovery calls. 🥈 Second approach After trying and failing to turn the marketing numbers around at my last role I am convicted of 4 brutal truths about digital marketing today Truth #1 – AI-generated content is flooding the internet and ANYONE can and will be creating content with AI. Truth #2 – Ranking for high-volume keywords is harder than ever and probably not worth it anymore. Truth #3 – AI-driven efficiency is non-negotiable. If you haven’t installed AI in your business - you are WAY behind. Truth #4 – Most businesses are thinking about AI completely wrong. Easy button vs quality stair step. I have some early thoughts on how I would like to solve this (backed by data and some user stories). But my main question and the entire point of this post is.... ⁉️ Questions Before I schedule these product discovery calls should I make it clear where I am convicted and find those who want to talk (agree or disagree) with the above. Or just keep that out of the mix and ask them my product discovery questions regardless? I am probably overthinking it - but I just hit up my personal network with a beta launch, feels silly to go back with product discovery questions for them. Is there a good place (besides reddit) to pay people for product discovery calls? A quick Google Search and it's unclear to me.

36 startup ideas found by analyzing podcasts (problem, solution & source episode)
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joepigeonThis week

36 startup ideas found by analyzing podcasts (problem, solution & source episode)

Hey, I've been a bit of a podcast nerd for a long time. Around a year ago I began experimenting with transcription of podcasts for a SaaS I was running. I realized pretty quickly that there's a lot of knowledge and value in podcast discussions that is for all intents and purposes entirely unsearchable or discoverable to most people. I ended up stopping work on that SaaS product (party for lack of product/market fit, and partly because podcasting was far more interesting), and focusing on the podcast technology full-time instead. I'm a long-time lurker and poster of r/startups and thought this would make for some interesting content and inspiration for folks. Given I'm in this space, have millions of transcripts, and transcribe thousands daily... I've been exploring fun ways to expose some of the interesting knowledge and conversations taking place that utilize our own data/API. I'm a big fan of the usual startup podcasts (My First Million, Greg Isenberg, etc. etc.) and so I built an automation that turns all of the startup ideas discussed into a weekly email digest. I always struggle to listen to as many episodes as I'd actually like to, so I thought I'd summarise the stuff I care about instead (startup opportunities being discussed). I thought it would be interesting to post some of the ideas extracted so far. They range from being completely whacky and blue sky, to pretty boring but realistic. A word of warning before anyone complains – this is a big mixture of tech, ai, non-tech, local services, etc. ideas: Some of the ideas are completely mundane, but realistic (e.g. local window cleaning service) Some of the ideas are completely insane, blue sky, but sound super interesting Here's the latest 36 ideas: |Idea Name|Problem|Solution|Source| |:-|:-|:-|:-| |SalesForce-as-a-Service - White Label Enterprise Sales Teams|White-label enterprise sales teams for B2B SaaS. Companies need sales but can't hire/train. Recruit retail sellers, train for tech, charge 30% of deals closed.|Create a white-label enterprise sales team by recruiting natural salespeople from retail and direct sales backgrounds (e.g. mall kiosks, cutco knives). Train them specifically in B2B SaaS sales techniques and processes. Offer this trained sales force to tech companies on a contract basis.|My First Million - "Life Hacks From The King of Introverts + 7 Business Ideas| |TechButler - Mobile Device Maintenance Service|Mobile tech maintenance service. Clean/optimize devices, improve WiFi, basic support. $100/visit to homes. Target affluent neighborhoods.|Mobile tech support service providing in-home device cleaning, optimization, and setup. Focus on common issues like WiFi improvement, device maintenance, and basic tech support.|My First Million - "Life Hacks From The King of Introverts + 7 Business Ideas| |MemoryBox - At-Home Video Digitization Service|Door-to-door VHS conversion service. Parents have boxes of old tapes. Pick up, digitize, deliver. $30/tape with minimum order. Going extinct.|Door-to-door VHS to digital conversion service that handles everything from pickup to digital delivery. Make it extremely convenient for customers to preserve their memories.|My First Million - "Life Hacks From The King of Introverts + 7 Business Ideas| |Elite Match Ventures - Success-Based Luxury Matchmaking|High-end matchmaking for 50M+ net worth individuals. Only charge $1M+ when they get married. No upfront fees. Extensive vetting process.|Premium matchmaking service exclusively for ultra-high net worth individuals with a pure contingency fee model - only get paid ($1M+) upon successful marriage. Focus on quality over quantity with extensive vetting and personalized matching.|My First Million - "Life Hacks From The King of Introverts + 7 Business Ideas| |LocalHost - Simple Small Business Websites|Simple WordPress sites for local businesses. $50/month includes hosting, updates, security. Target restaurants and shops. Recurring revenue play.|Simplified web hosting and WordPress management service targeting local small businesses. Focus on basic sites with standard templates, ongoing maintenance, and reliable support for a fixed monthly fee.|My First Million - "Life Hacks From The King of Introverts + 7 Business Ideas| |VoiceJournal AI - Voice-First Smart Journaling|Voice-to-text journaling app with AI insights. 8,100 monthly searches. $15/month subscription. Partners with journaling YouTubers.|AI-powered journaling app that combines voice recording, transcription, and intelligent insights. Users can speak their thoughts, which are automatically transcribed and analyzed for patterns, emotions, and actionable insights.|Where It Happens - "7 $1M+ AI startup ideas you can launch tomorrow with $0"| |AIGenAds - AI-Generated UGC Content Platform|AI platform turning product briefs into UGC-style video ads. Brands spending $500/video for human creators. Generate 100 variations for $99/month.|AI platform that generates UGC-style video ads using AI avatars and scripting. System would allow rapid generation of multiple ad variations at a fraction of the cost. Platform would use existing AI avatar technology combined with script generation to create authentic-looking testimonial-style content.|Where It Happens - "7 $1M+ AI startup ideas you can launch tomorrow with $0"| |InfographAI - Automated Infographic Generation Platform|AI turning blog posts into branded infographics. Marketers spending hours on design. $99/month unlimited generation.|AI-powered platform that automatically converts blog posts and articles into visually appealing infographics. System would analyze content, extract key points, and generate professional designs using predefined templates and brand colors.|Where It Happens - "7 $1M+ AI startup ideas you can launch tomorrow with $0"| |KidFinance - Children's Financial Education Entertainment|Children's media franchise teaching financial literacy. Former preschool teacher creating 'Dora for money'. Books, videos, merchandise potential.|Character-driven financial education content for kids, including books, videos, and potentially TV show. Focus on making money concepts fun and memorable.|The Side Hustle Show - "How a Free Challenge Turned Into a $500,000 a Year Business (Greatest Hits)"| |FinanceTasker - Daily Financial Task Challenge|Free 30-day financial challenge with daily action items. People overwhelmed by money management. Makes $500k/year through books, speaking, and premium membership.|A free 30-day financial challenge delivering one simple, actionable task per day via email. Each task includes detailed scripts and instructions. Participants join a Facebook community for support and accountability. The program focuses on quick wins to build momentum. Automated delivery allows scaling.|The Side Hustle Show - "How a Free Challenge Turned Into a $500,000 a Year Business (Greatest Hits)"| |FinanceAcademy - Expert Financial Training Platform|Premium financial education platform. $13/month for expert-led courses and live Q&As. 4000+ members generating $40k+/month.|Premium membership site with expert-led courses, live Q&As, and community support. Focus on specific topics like real estate investing, business creation, and advanced money management.|The Side Hustle Show - "How a Free Challenge Turned Into a $500,000 a Year Business (Greatest Hits)"| |SecurityFirst Compliance - Real Security + Compliance Platform|Security-first compliance platform built by hackers. Companies spending $50k+ on fake security. Making $7M/year showing why current solutions don't work.|A compliance platform built by security experts that combines mandatory compliance requirements with real security measures. The solution includes hands-on security testing, expert guidance, and a focus on actual threat prevention rather than just documentation. It merges traditional compliance workflows with practical security implementations.|In the Pit with Cody Schneider| |LinkedInbound - Automated Professional Visibility Engine|LinkedIn automation for inbound job offers. Professionals spending hours on manual outreach. $99/month per job seeker.|Automated system for creating visibility and generating inbound interest on LinkedIn through coordinated profile viewing and engagement. Uses multiple accounts to create visibility patterns that trigger curiosity and inbound messages.|In the Pit with Cody Schneider| |ConvoTracker - Community Discussion Monitoring Platform|Community discussion monitoring across Reddit, Twitter, HN. Companies missing sales opportunities. $499/month per brand tracked.|Comprehensive monitoring system that tracks competitor mentions and industry discussions across multiple platforms (Reddit, Twitter, Hacker News, etc.) with automated alerts and engagement suggestions.|In the Pit with Cody Schneider| |ContentAds Pro - Smart Display Ad Implementation|Display ad implementation service for content creators. Bloggers losing thousands in ad revenue monthly. Makes $3-5k per site setup plus ongoing optimization fees.|Implementation of professional display advertising through networks like Mediavine that specialize in optimizing ad placement and revenue while maintaining user experience. Include features like turning off ads for email subscribers and careful placement to minimize impact on core metrics.|The Side Hustle Show - "636: Is Business Coaching Worth It? A Look Inside the last 12 months of Side Hustle Nation"| |MoneyAppReviews - Professional Side Hustle App Testing|Professional testing service for money-making apps. People wasting time on low-paying apps. Makes $20k/month from affiliate commissions and ads.|Professional app testing service that systematically reviews money-making apps and creates detailed, honest reviews including actual earnings data, time investment, and practical tips.|The Side Hustle Show - "636: Is Business Coaching Worth It? A Look Inside the last 12 months of Side Hustle Nation"| |LightPro - Holiday Light Installation Service|Professional Christmas light installation service. Homeowners afraid of ladders. $500-2000 per house plus storage.|Professional Christmas light installation service targeting residential and commercial properties. Full-service offering including design, installation, maintenance, removal and storage. Focus on safety and premium aesthetic results.|The Side Hustle Show - "639: 30 Ways to Make Extra Money for the Holidays"| |FocusMatch - Research Participant Marketplace|Marketplace connecting companies to paid research participants. Companies spending weeks finding people. $50-150/hour per study.|Online platform connecting companies directly with paid research participants. Participants create detailed profiles and get matched to relevant studies. Companies get faster access to their target demographic while participants earn money sharing opinions.|The Side Hustle Show - "639: 30 Ways to Make Extra Money for the Holidays"| |SolarShine Pro - Specialized Solar Panel Cleaning Service|Solar panel cleaning service using specialized equipment. Panels lose 50% efficiency when dirty. $650 per job, automated scheduling generates $18k/month from repeat customers.|Professional solar panel cleaning service using specialized deionized water system and European cleaning equipment. Includes automated 6-month scheduling, professional liability coverage, and warranty-safe cleaning processes. Service is bundled with inspection and performance monitoring.|The UpFlip Podcast - "156. $18K/Month with This ONE Service — Niche Business Idea"| |ExteriorCare Complete - One-Stop Exterior Maintenance Service|One-stop exterior home cleaning service (solar, windows, gutters, bird proofing). Automated scheduling. $650 average ticket. 60% repeat customers on 6-month contracts.|All-in-one exterior cleaning service offering comprehensive maintenance packages including solar, windows, gutters, roof cleaning and bird proofing. Single point of contact, consistent quality, and automated scheduling for all services.|The UpFlip Podcast - "156. $18K/Month with This ONE Service — Niche Business Idea"| |ContentMorph - Automated Cross-Platform Content Adaptation|AI platform converting blog posts into platform-optimized social content. Marketing teams spending 5hrs/post on manual adaptation. $199/mo per brand with 50% margins.|An AI-powered platform that automatically transforms long-form content (blog posts, podcasts, videos) into platform-specific formats (Instagram reels, TikToks, tweets). The system would preserve brand voice while optimizing for each platform's unique requirements and best practices.|Entrepreneurs on Fire - "Digital Threads: The Entrepreneur Playbook for Digital-First Marketing with Neal Schaffer"| |MarketerMatch - Verified Digital Marketing Talent Marketplace|Marketplace for pre-vetted digital marketing specialists. Entrepreneurs spending 15hrs/week on marketing tasks. Platform takes 15% commission averaging $900/month per active client.|A specialized marketplace exclusively for digital marketing professionals, pre-vetted for specific skills (video editing, social media, SEO, etc.). Platform includes skill verification, portfolio review, and specialization matching.|Entrepreneurs on Fire - "Digital Threads: The Entrepreneur Playbook for Digital-First Marketing with Neal Schaffer"| |Tiger Window Cleaning - Premium Local Window Service|Local window cleaning service targeting homeowners. Traditional companies charging 2x market rate. Making $10k/month from $200 initial investment.|Local window cleaning service combining competitive pricing ($5/pane), excellent customer service, and quality guarantees. Uses modern tools like water-fed poles for efficiency. Implements systematic approach to customer communication and follow-up.|The Side Hustle Show - "630: How this College Student’s Side Hustle Brings in $10k a Month"| |RealViz3D - Real Estate Visualization Platform|3D visualization service turning architectural plans into photorealistic renderings for real estate agents. Agents struggling with unbuilt property sales. Making $30-40k/year per operator.|Professional 3D modeling and rendering service that creates photorealistic visualizations of properties before they're built or renovated. The service transforms architectural plans into immersive 3D representations that show lighting, textures, and realistic details. This helps potential buyers fully understand and connect with the space before it physically exists.|Side Hustle School - "#2861 - TBT: An Architect’s Side Hustle in 3D Real Estate Modeling"| |Somewhere - Global Talent Marketplace|Platform connecting US companies with vetted overseas talent. Tech roles costing $150k locally filled for 50% less. Grew from $15M to $52M valuation in 9 months.|Platform connecting US companies with pre-vetted overseas talent at significantly lower rates while maintaining high quality. Handles payments, contracts, and quality assurance to remove friction from global hiring.|My First Million - "I Lost Everything Twice… Then Made $26M In 18 Months| |GymLaunch - Rapid Gym Turnaround Service|Consultants flying to struggling gyms to implement proven member acquisition systems. Gym owners lacking sales expertise. Made $100k in first 21 days.|Expert consultants fly in to implement proven member acquisition systems, train staff, and rapidly fill gyms with new members. The service combines sales training, marketing automation, and proven conversion tactics to transform struggling gyms into profitable businesses within weeks.|My First Million - "I Lost Everything Twice… Then Made $26M In 18 Months| |PublishPlus - Publishing Backend Monetization|Backend monetization system for publishing companies. One-time customers becoming recurring revenue. Grew business from $2M to $110M revenue.|Add complementary backend products and services to increase customer lifetime value. Develop software tools and additional services that natural extend from initial publishing product. Focus on high-margin recurring revenue streams.|My First Million - "I Lost Everything Twice… Then Made $26M In 18 Months| |WelcomeBot - Automated Employee Onboarding Platform|Automated employee welcome platform. HR teams struggling with consistent onboarding. $99/month per 100 employees.|An automated onboarding platform that creates personalized welcome experiences through pre-recorded video messages, scheduled check-ins, and automated swag delivery. The platform would ensure consistent high-quality onboarding regardless of timing or location.|Entrepreneurs on Fire - "Free Training on Building Systems and Processes to Scale Your Business with Chris Ronzio: An EOFire Classic from 2021"| |ProcessBrain - Business Knowledge Documentation Platform|SaaS platform turning tribal knowledge into documented processes. Business owners spending hours training new hires. $199/month per company.|A software platform that makes it easy to document and delegate business processes and procedures. The platform would include templates, guided documentation flows, and tools to easily share and update procedures. It would help businesses create a comprehensive playbook of their operations.|Entrepreneurs on Fire - "Free Training on Building Systems and Processes to Scale Your Business with Chris Ronzio: An EOFire Classic from 2021"| |TradeMatch - Modern Manufacturing Job Marketplace|Modern job board making manufacturing sexy again. Factory jobs paying $40/hr but can't recruit. $500 per successful referral.|A specialized job marketplace and recruitment platform focused exclusively on modern manufacturing and trade jobs. The platform would combine TikTok-style content marketing, referral programs, and modern UX to make manufacturing jobs appealing to Gen Z and young workers. Would leverage existing $500 referral fees and industry demand.|My First Million - "He Sold His Company For $15M, Then Got A Job At McDonald’s"| |GroundLevel - Executive Immersion Program|Structured program putting CEOs in front-line jobs. Executives disconnected from workers. $25k per placement.|A structured program that places executives and founders in front-line jobs (retail, warehouse, service) for 2-4 weeks with documentation and learning framework. Similar to Scott Heiferman's McDonald's experience but productized.|My First Million - "He Sold His Company For $15M, Then Got A Job At McDonald’s"| |OneStepAhead - Micro-Mentorship Marketplace|Marketplace for 30-min mentorship calls with people one step ahead. Professionals seeking specific guidance. Takes 15% of session fees.|MicroMentor Marketplace - Platform connecting people with mentors who are just one step ahead in their journey for focused, affordable micro-mentorship sessions.|Entrepreneurs on Fire - "How to Create an Unbroken Business with Michael Unbroken: An EOFire Classic from 2021"| |VulnerableLeader - Leadership Authenticity Training Platform|Leadership vulnerability training platform. Leaders struggling with authentic communication. $2k/month per company subscription.|Leadership Vulnerability Platform - A digital training platform combining assessment tools, guided exercises, and peer support to help leaders develop authentic communication skills. The platform would include real-world scenarios, video coaching, and measurable metrics for tracking leadership growth through vulnerability.|Entrepreneurs on Fire - "How to Create an Unbroken Business with Michael Unbroken: An EOFire Classic from 2021"| |NetworkAI - Smart Network Intelligence Platform|AI analyzing your network to find hidden valuable connections. Professionals missing opportunities in existing contacts. $49/month per user.|AI Network Navigator - Smart tool that analyzes your professional network across platforms, identifies valuable hidden connections, and suggests specific actionable ways to leverage relationships for mutual benefit.|Entrepreneurs on Fire - "How to Create an Unbroken Business with Michael Unbroken: An EOFire Classic from 2021"| |Porch Pumpkins - Seasonal Decoration Service|Full-service porch pumpkin decoration. Homeowners spend $300-1350 per season. One operator making $1M in 8 weeks seasonal revenue.|Full-service seasonal porch decoration service focused on autumn/Halloween, including design, installation, maintenance, and removal. Offering premium curated pumpkin arrangements with various package tiers.|My First Million - "The guy who gets paid $80K/yr to do nothing"| |Silent Companion - Professional Presence Service|Professional silent companions for lonely people. Huge problem in Japan/globally. $68/session, $80k/year per companion. Non-sexual, just presence.|A professional companion service where individuals can rent a non-judgmental, quiet presence for various activities. The companion provides silent company without the pressure of conversation or social performance. They accompany clients to events, meals, or just sit quietly together.|My First Million - "The guy who gets paid $80K/yr to do nothing"| Hope this is useful. If anyone would like to ensure I include any particular podcasts or episodes etc. in future posts, very happy to do so. I'll generally send \~5 ideas per week in a short weekly digest format (you can see the format I'd usually use in here: podcastmarketwatch.beehiiv.com). I find it mindblowing that the latest models with large context windows make it even possible to analyze full transcripts at such scale. It's a very exciting time we're living through! Would love some feedback on this stuff, happy to iterate and improve the analysis/ideas... or create a new newsletter on a different topic if anyone would like. Cheers!

The Cold-Calling AI Project I'm Working On Just Got Some Angel Investment!
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GrowthGetThis week

The Cold-Calling AI Project I'm Working On Just Got Some Angel Investment!

Hey y'all. The AI cold calling startup I've been working on for 3-4 months now just got a $2,500 angel investment, and we have 2 current customers, a credit card processing broker and a hospital equipment rental company based out of Texas. We have around $1,500 revenue so far, but we're having lots of trouble fulfilling the contracts because our tech just isn't "there" yet. I'm the Chief Tech Officer, and I'm also running some operations. The other main person in this is the CEO who has a strong sales background and came up with the idea. I've been working purely remotely, and it's great having some income because I'm stuck at home because I'm disabled, basically... &#x200B; We're using 11labs, openai, google speech to text, and a sh\*tty online dialer right now to run the first MVP which runs locally on our "botrunners" computers, and we're developing a web app with django python + javascript react. Our plan is, after we get the webapp working better, to hire more botrunners for $3 per hour from countries like Phillipines and India, and we're going to try to track all the actions the botrunners take to be able to train the AI to run it fully automated. The biggest problem we're facing right now with the tech is reducing latency, it started at 27 seconds to get a response and I've been able to get it down to 6 seconds, but people are still hanging up. We're trying several ways to mitigate this, including having pre-rendered speech playing something like "Okay" or "As an artificial representative, I'm still learning to be quicker on the pickup. We appreciate your patience." One of the industries we want to target is international web development and digital marketing companies, and we want to use the bot to cold-call businesses to pitch them our services. The goal is to replace $30 an hour cold-callers from the USA with $3 per hour total-cost automation. Apparently the CEO was given a $5 million valuation from the strength of the MVP from a VC. Our investment so far was at a $300k valuation tho. It's exciting. Trying to get Twilio working to be able to make calls programmatically instead of using our hacky workaround. Let me know if you have any questions. I just wanted to share this awesome news!

I am selling my tool which converts websites into android and iOS apps within 5 minutes.
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Latter-Row-5719This week

I am selling my tool which converts websites into android and iOS apps within 5 minutes.

Hi, my name is Toshit Garg. I started working on SaaS products around April 2023. The plan was simple: to create tools that help entrepreneurs easily grow their businesses. My first tool was "Convertixo", inspired by my work as a Fiverr seller where I converted websites into apps for clients, earning around $1,000 per month. I thought, why not automate this process? Following Convertixo, I created a few other tools like "Web to PWA". At one point, I developed an AI-based tool called "AppMintAI" , a productized service named "Engage Enhance", and even a WordPress plugin that lets users create pragmatic pages for SEO and a boilerplates. Unfortunately, none of these tools gained significant traction. I would launch them on Product Hunt, get a few users, and then nothing. Other than Convertixo, all my other tools only received a handful of free users. I believe this happened because I’m not very passionate about marketing. So, I decided to pivot and focus on content creation, which is where my true passion lies. Currently, I’m selling all my products one by one. As for Convertixo, it now has 800 users, a $20 MRR, and an email subscriber list of 100+. It was also the third Product of the Day on Product Hunt in January of this year. While the product has gained some traction, I’ve realized my focus is on content creation. However, with the right marketing and drive, I believe Convertixo has great potential to grow. If you’re interested in taking Convertixo to the next level, let’s chat! Here are some key statistics: In the last 20 days, Convertixo has received 4.9K impressions from Google and 338 visitors. More about the product: Convertixo can convert any website into Android and iOS apps using a custom webview. The apps are generated in Android Studio and Xcode. You receive both the APK and the source code for the Android app, along with the source code for the iOS app. The converted apps require no maintenance, and they update exactly like the website. A major benefit is the ability to add push notifications via OneSignal for free, allowing you to re-target your customers at no cost. Feel free to ask if you have any questions!

How a founder built a B2B AI startup to serve with 65+ global brands (including Fortune500 companies) (I will not promote)
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Royal_Rest8409This week

How a founder built a B2B AI startup to serve with 65+ global brands (including Fortune500 companies) (I will not promote)

AI Palette is an AI-driven platform that helps food and beverage companies predict emerging product trends. I had the opportunity recently to sit down with the founder to get his advice on building an AI-first startup, which he'll be going through in this post. (I will not promote) About AI Palette: Co-founders: >!2 (Somsubhra GanChoudhuri, Himanshu Upreti)!!100+!!$12.7M USD!!AI-powered predictive analytics for the CPG (Consumer Packaged Goods) industry!!Signed first paying customer in the first year!!65+ global brands, including Cargill, Diageo, Ajinomoto, Symrise, Mondelez, and L’Oréal, use AI Palette!!Every new product launched has secured a paying client within months!!Expanded into Beauty & Personal Care (BPC), onboarding one of India’s largest BPC companies within weeks!!Launched multiple new product lines in the last two years, creating a unified suite for brand innovation!Identify the pain points in your industry for ideas* When I was working in the flavour and fragrance industry, I noticed a major issue CPG companies faced: launching a product took at least one to two years. For instance, if a company decided today to launch a new juice, it wouldn’t hit the market until 2027. This long timeline made it difficult to stay relevant and on top of trends. Another big problem I noticed was that companies relied heavily on market research to determine what products to launch. While this might work for current consumer preferences, it was highly inefficient since the product wouldn’t actually reach the market for several years. By the time the product launched, the consumer trends had already shifted, making that research outdated. That’s where AI can play a crucial role. Instead of looking at what consumers like today, we realised that companies should use AI to predict what they will want next. This allows businesses to create products that are ahead of the curve. Right now, the failure rate for new product launches is alarmingly high, with 8 out of 10 products failing. By leveraging AI, companies can avoid wasting resources on products that won’t succeed, leading to better, more successful launches. Start by talking to as many industry experts as possible to identify the real problems When we first had the idea for AI Palette, it was just a hunch, a gut feeling—we had no idea whether people would actually pay for it. To validate the idea, we reached out to as many people as we could within the industry. Since our focus area was all about consumer insights, we spoke to professionals in the CPG sector, particularly those in the insights departments of CPG companies. Through these early conversations, we began to see a common pattern emerge and identified the exact problem we wanted to solve. Don’t tell people what you’re building—listen to their frustrations and challenges first. Going into these early customer conversations, our goal was to listen and understand their challenges without telling them what we were trying to build. This is crucial as it ensures that you can gather as much data about the problem to truly understand it and that you aren't biasing their answers by showing your solution. This process helped us in two key ways: First, it validated that there was a real problem in the industry through the number of people who spoke about experiencing the same problem. Second, it allowed us to understand the exact scale and depth of the problem—e.g., how much money companies were spending on consumer research, what kind of tools they were currently using, etc. Narrow down your focus to a small, actionable area to solve initially. Once we were certain that there was a clear problem worth solving, we didn’t try to tackle everything at once. As a small team of two people, we started by focusing on a specific area of the problem—something big enough to matter but small enough for us to handle. Then, we approached customers with a potential solution and asked them for feedback. We learnt that our solution seemed promising, but we wanted to validate it further. If customers are willing to pay you for the solution, it’s a strong validation signal for market demand. One of our early customer interviewees even asked us to deliver the solution, which we did manually at first. We used machine learning models to analyse the data and presented the results in a slide deck. They paid us for the work, which was a critical moment. It meant we had something with real potential, and we had customers willing to pay us before we had even built the full product. This was the key validation that we needed. By the time we were ready to build the product, we had already gathered crucial insights from our early customers. We understood the specific information they wanted and how they wanted the results to be presented. This input was invaluable in shaping the development of our final product. Building & Product Development Start with a simple concept/design to validate with customers before building When we realised the problem and solution, we began by designing the product, but not by jumping straight into coding. Instead, we created wireframes and user interfaces using tools like InVision and Figma. This allowed us to visually represent the product without the need for backend or frontend development at first. The goal was to showcase how the product would look and feel, helping potential customers understand its value before we even started building. We showed these designs to potential customers and asked for feedback. Would they want to buy this product? Would they pay for it? We didn’t dive into actual development until we found a customer willing to pay a significant amount for the solution. This approach helped us ensure we were on the right track and didn’t waste time or resources building something customers didn’t actually want. Deliver your solution using a manual consulting approach before developing an automated product Initially, we solved problems for customers in a more "consulting" manner, delivering insights manually. Recall how I mentioned that when one of our early customer interviewees asked us to deliver the solution, we initially did it manually by using machine learning models to analyse the data and presenting the results to them in a slide deck. This works for the initial stages of validating your solution, as you don't want to invest too much time into building a full-blown MVP before understanding the exact features and functionalities that your users want. However, after confirming that customers were willing to pay for what we provided, we moved forward with actual product development. This shift from a manual service to product development was key to scaling in a sustainable manner, as our building was guided by real-world feedback and insights rather than intuition. Let ongoing customer feedback drive iteration and the product roadmap Once we built the first version of the product, it was basic, solving only one problem. But as we worked closely with customers, they requested additional features and functionalities to make it more useful. As a result, we continued to evolve the product to handle more complex use cases, gradually developing new modules based on customer feedback. Product development is a continuous process. Our early customers pushed us to expand features and modules, from solving just 20% of their problems to tackling 50–60% of their needs. These demands shaped our product roadmap and guided the development of new features, ultimately resulting in a more complete solution. Revenue and user numbers are key metrics for assessing product-market fit. However, critical mass varies across industries Product-market fit (PMF) can often be gauged by looking at the size of your revenue and the number of customers you're serving. Once you've reached a certain critical mass of customers, you can usually tell that you're starting to hit product-market fit. However, this critical mass varies by industry and the type of customers you're targeting. For example, if you're building an app for a broad consumer market, you may need thousands of users. But for enterprise software, product-market fit may be reached with just a few dozen key customers. Compare customer engagement and retention with other available solutions on the market for product-market fit Revenue and the number of customers alone isn't always enough to determine if you're reaching product-market fit. The type of customer and the use case for your product also matter. The level of engagement with your product—how much time users are spending on the platform—is also an important metric to track. The more time they spend, the more likely it is that your product is meeting a crucial need. Another way to evaluate product-market fit is by assessing retention, i.e whether users are returning to your platform and relying on it consistently, as compared to other solutions available. That's another key indication that your solution is gaining traction in the market. Business Model & Monetisation Prioritise scalability Initially, we started with a consulting-type model where we tailor-made specific solutions for each customer use-case we encountered and delivered the CPG insights manually, but we soon realized that this wasn't scalable. The problem with consulting is that you need to do the same work repeatedly for every new project, which requires a large team to handle the workload. That is not how you sustain a high-growth startup. To solve this, we focused on building a product that would address the most common problems faced by our customers. Once built, this product could be sold to thousands of customers without significant overheads, making the business scalable. With this in mind, we decided on a SaaS (Software as a Service) business model. The benefit of SaaS is that once you create the software, you can sell it to many customers without adding extra overhead. This results in a business with higher margins, where the same product can serve many customers simultaneously, making it much more efficient than the consulting model. Adopt a predictable, simplistic business model for efficiency. Look to industry practices for guidance When it came to monetisation, we considered the needs of our CPG customers, who I knew from experience were already accustomed to paying annual subscriptions for sales databases and other software services. We decided to adopt the same model and charge our customers an annual upfront fee. This model worked well for our target market, aligning with industry standards and ensuring stable, recurring revenue. Moreover, our target CPG customers were already used to this business model and didn't have to choose from a huge variety of payment options, making closing sales a straightforward and efficient process. Marketing & Sales Educate the market to position yourself as a thought leader When we started, AI was not widely understood, especially in the CPG industry. We had to create awareness around both AI and its potential value. Our strategy focused on educating potential users and customers about AI, its relevance, and why they should invest in it. This education was crucial to the success of our marketing efforts. To establish credibility, we adopted a thought leadership approach. We wrote blogs on the importance of AI and how it could solve problems for CPG companies. We also participated in events and conferences to demonstrate our expertise in applying AI to the industry. This helped us build our brand and reputation as leaders in the AI space for CPG, and word-of-mouth spread as customers recognized us as the go-to company for AI solutions. It’s tempting for startups to offer products for free in the hopes of gaining early traction with customers, but this approach doesn't work in the long run. Free offerings don’t establish the value of your product, and customers may not take them seriously. You should always charge for pilots, even if the fee is minimal, to ensure that the customer is serious about potentially working with you, and that they are committed and engaged with the product. Pilots/POCs/Demos should aim to give a "flavour" of what you can deliver A paid pilot/POC trial also gives you the opportunity to provide a “flavour” of what your product can deliver, helping to build confidence and trust with the client. It allows customers to experience a detailed preview of what your product can do, which builds anticipation and desire for the full functionality. During this phase, ensure your product is built to give them a taste of the value you can provide, which sets the stage for a broader, more impactful adoption down the line. Fundraising & Financial Management Leverage PR to generate inbound interest from VCs When it comes to fundraising, our approach was fairly traditional—we reached out to VCs and used connections from existing investors to make introductions. However, looking back, one thing that really helped us build momentum during our fundraising process was getting featured in Tech in Asia. This wasn’t planned; it just so happened that Tech in Asia was doing a series on AI startups in Southeast Asia and they reached out to us for an article. During the interview, they asked if we were fundraising, and we mentioned that we were. As a result, several VCs we hadn’t yet contacted reached out to us. This inbound interest was incredibly valuable, and we found it far more effective than our outbound efforts. So, if you can, try to generate some PR attention—it can help create inbound interest from VCs, and that interest is typically much stronger and more promising than any outbound strategies because they've gone out of their way to reach out to you. Be well-prepared and deliberate about fundraising. Keep trying and don't lose heart When pitching to VCs, it’s crucial to be thoroughly prepared, as you typically only get one shot at making an impression. If you mess up, it’s unlikely they’ll give you a second chance. You need to have key metrics at your fingertips, especially if you're running a SaaS company. Be ready to answer questions like: What’s your retention rate? What are your projections for the year? How much will you close? What’s your average contract value? These numbers should be at the top of your mind. Additionally, fundraising should be treated as a structured process, not something you do on the side while juggling other tasks. When you start, create a clear plan: identify 20 VCs to reach out to each week. By planning ahead, you’ll maintain momentum and speed up the process. Fundraising can be exhausting and disheartening, especially when you face multiple rejections. Remember, you just need one investor to say yes to make it all worthwhile. When using funds, prioritise profitability and grow only when necessary. Don't rely on funding to survive. In the past, the common advice for startups was to raise money, burn through it quickly, and use it to boost revenue numbers, even if that meant operating at a loss. The idea was that profitability wasn’t the main focus, and the goal was to show rapid growth for the next funding round. However, times have changed, especially with the shift from “funding summer” to “funding winter.” My advice now is to aim for profitability as soon as possible and grow only when it's truly needed. For example, it’s tempting to hire a large team when you have substantial funds in the bank, but ask yourself: Do you really need 10 new hires, or could you get by with just four? Growing too quickly can lead to unnecessary expenses, so focus on reaching profitability as soon as possible, rather than just inflating your team or burn rate. The key takeaway is to spend your funds wisely and only when absolutely necessary to reach profitability. You want to avoid becoming dependent on future VC investments to keep your company afloat. Instead, prioritize reaching break-even as quickly as you can, so you're not reliant on external funding to survive in the long run. Team-Building & Leadership Look for complementary skill sets in co-founders When choosing a co-founder, it’s important to find someone with a complementary skill set, not just someone you’re close to. For example, I come from a business and commercial background, so I needed someone with technical expertise. That’s when I found my co-founder, Himanshu, who had experience in machine learning and AI. He was a great match because his technical knowledge complemented my business skills, and together we formed a strong team. It might seem natural to choose your best friend as your co-founder, but this can often lead to conflict. Chances are, you and your best friend share similar interests, skills, and backgrounds, which doesn’t bring diversity to the table. If both of you come from the same industry or have the same strengths, you may end up butting heads on how things should be done. Having diverse skill sets helps avoid this and fosters a more collaborative working relationship. Himanshu (left) and Somsubhra (right) co-founded AI Palette in 2018 Define roles clearly to prevent co-founder conflict To avoid conflict, it’s essential that your roles as co-founders are clearly defined from the beginning. If your co-founder and you have distinct responsibilities, there is no room for overlap or disagreement. This ensures that both of you can work without stepping on each other's toes, and there’s mutual respect for each other’s expertise. This is another reason as to why it helps to have a co-founder with a complementary skillset to yours. Not only is having similar industry backgrounds and skillsets not particularly useful when building out your startup, it's also more likely to lead to conflicts since you both have similar subject expertise. On the other hand, if your co-founder is an expert in something that you're not, you're less likely to argue with them about their decisions regarding that aspect of the business and vice versa when it comes to your decisions. Look for employees who are driven by your mission, not salary For early-stage startups, the first hires are crucial. These employees need to be highly motivated and excited about the mission. Since the salary will likely be low and the work demanding, they must be driven by something beyond just the paycheck. The right employees are the swash-buckling pirates and romantics, i.e those who are genuinely passionate about the startup’s vision and want to be part of something impactful beyond material gains. When employees are motivated by the mission, they are more likely to stick around and help take the startup to greater heights. A litmus test for hiring: Would you be excited to work with them on a Sunday? One of the most important rounds in the hiring process is the culture fit round. This is where you assess whether a candidate shares the same values as you and your team. A key question to ask yourself is: "Would I be excited to work with this person on a Sunday?" If there’s any doubt about your answer, it’s likely not a good fit. The idea is that you want employees who align with the company's culture and values and who you would enjoy collaborating with even outside of regular work hours. How we structure the team at AI Palette We have three broad functions in our organization. The first two are the big ones: Technical Team – This is the core of our product and technology. This team is responsible for product development and incorporating customer feedback into improving the technology Commercial Team – This includes sales, marketing, customer service, account managers, and so on, handling everything related to business growth and customer relations. General and Administrative Team – This smaller team supports functions like finance, HR, and administration. As with almost all businesses, we have teams that address the two core tasks of building (technical team) and selling (commercial team), but given the size we're at now, having the administrative team helps smoothen operations. Set broad goals but let your teams decide on execution What I've done is recruit highly skilled people who don't need me to micromanage them on a day-to-day basis. They're experts in their roles, and as Steve Jobs said, when you hire the right person, you don't have to tell them what to do—they understand the purpose and tell you what to do. So, my job as the CEO is to set the broader goals for them, review the plans they have to achieve those goals, and periodically check in on progress. For example, if our broad goal is to meet a certain revenue target, I break it down across teams: For the sales team, I’ll look at how they plan to hit that target—how many customers they need to sell to, how many salespeople they need, and what tactics and strategies they plan to use. For the technical team, I’ll evaluate our product offerings—whether they think we need to build new products to attract more customers, and whether they think it's scalable for the number of customers we plan to serve. This way, the entire organization's tasks are cascaded in alignment with our overarching goals, with me setting the direction and leaving the details of execution to the skilled team members that I hire.

I will not promote — just need advice from fellow startup entrepreneurs
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Forward_Tackle_6487This week

I will not promote — just need advice from fellow startup entrepreneurs

Hey everyone, I’m now based in the San Francisco Bay Area. I’m starting a development agency to help early-stage startups and small businesses turn ideas into real products. Whether it’s building an MVP, scaling an existing app, or providing a dedicated offshore team — that’s the direction I’m heading. Quick background on me: I work with: • Frontend: React.js, Next.js, React Native • Backend: Node.js, Express, Supabase, Firebase • Databases: MongoDB, PostgreSQL • AI/API Integrations: OpenAI and others • DevOps/Automation: n8n, serverless tools, cloud platforms I’ve built and designed dozens of products, and now I have a small but strong team of 5 devs/designers in India. We can scale fast and deliver at Indian pricing — but that’s not my pitch here. I’m not here to promote. I’m genuinely looking for feedback and ideas from others doing similar things. If you’re running a dev agency, working with offshore teams, or supporting early-stage founders, I’d love to know: • What’s working for you in terms of client acquisition? • How are you building trust in the early stages? • Are there any strategies or lessons you wish you knew when starting? Also, if this aligns with something you’re building and you’re open to collaboration, I’m all ears. Let’s connect and share what’s working. Appreciate any thoughts, and happy to answer any questions too!

Looking for an accountability partner as a solo founder. [I will not promote]
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Looking for an accountability partner as a solo founder. [I will not promote]

Hello! I am a technical founder focused on using AI solutions to drive automation. Recently had a co-founder split after working together for a couple month. We had a very good traction but I made a decision to leave because I believed we didn't have a solid foundational relationship that can be sustained for a long time. Had more of a co-worker style relationship. Took on the short-term pain to set myself up for a long term success. He was the one leading the sales and relation with the businesses, so we decided he will be leading the company moving forward and we split on very good terms. Back in the gulag now and starting from scratch. Took three days to reset and recover. When I tried to get back at things yesterday, my brain wasn't just having it. My stress activation got so high, i did like 4 wim hof breathing sessions and a 10 mile run to relieve the stress buildup. There is something about uncertainty and working without a lack of clear path that is super hard to process especially when you are solo. Currently I am working through my previous idea backlogs that I have built up and re-starting previous conversations. But my brain isn't giving me the dopamine hit from driving toward action as much as I used to. So any work that i do feels like a slogging through mud. I am looking to experiment with having an accountability partner, to make the initial ramp up easier. Thinking of doing the elon musk style "What have you done this week?" report that we can do to drive accountability and give that extra motivation. If you're navigating similar challenges as a solo founder and believe mutual accountability could accelerate our progress and growth, I'd love to connect. Let's help each other build momentum and stay motivated—drop a comment or DM if interested! I will not promote

How to get funding for startup ? I will not promote
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wlynncorkThis week

How to get funding for startup ? I will not promote

I will not promote. Software startup based out of Minnesota us. I've built and launched a product that is gaining traction, solving a problem that has frustrated software developers and product teams for years. The problem: Software development is slow, expensive, and full of inefficiencies. Developers spend hours on repetitive coding tasks, project managers struggle with bottlenecks, and businesses waste time translating product requirements into actual code. The solution: My product automates a large portion of software development. It acts as an AI-powered assistant for developers, taking high-level requirements and turning them into functional code while integrating with existing codebases. It can read, understand, and modify software projects in a structured way—cutting development time drastically. The potential: Businesses are always looking for ways to cut costs and speed up development. With the rise of AI, companies are increasingly adopting automation, and this tool fits perfectly into that wave. Imagine a world where software teams are 10x more efficient because AI handles the grunt work, and developers focus on the bigger picture. It’s not about replacing developers—it’s about supercharging them. The current status: The product is live and in use. The user base is growing, and I’ve proven demand. Now, I need to figure out the best funding model to scale—whether that’s bootstrapping, VC, grants, or some hybrid approach. If you have experience in startup funding or have scaled a tech product, I'd love to hear your insights. DM me if you're open to discussing strategies!

The Cold-Calling AI Project I'm Working On Just Got Some Angel Investment!
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GrowthGetThis week

The Cold-Calling AI Project I'm Working On Just Got Some Angel Investment!

Hey y'all. The AI cold calling startup I've been working on for 3-4 months now just got a $2,500 angel investment, and we have 2 current customers, a credit card processing broker and a hospital equipment rental company based out of Texas. We have around $1,500 revenue so far, but we're having lots of trouble fulfilling the contracts because our tech just isn't "there" yet. I'm the Chief Tech Officer, and I'm also running some operations. The other main person in this is the CEO who has a strong sales background and came up with the idea. I've been working purely remotely, and it's great having some income because I'm stuck at home because I'm disabled, basically... &#x200B; We're using 11labs, openai, google speech to text, and a sh\*tty online dialer right now to run the first MVP which runs locally on our "botrunners" computers, and we're developing a web app with django python + javascript react. Our plan is, after we get the webapp working better, to hire more botrunners for $3 per hour from countries like Phillipines and India, and we're going to try to track all the actions the botrunners take to be able to train the AI to run it fully automated. The biggest problem we're facing right now with the tech is reducing latency, it started at 27 seconds to get a response and I've been able to get it down to 6 seconds, but people are still hanging up. We're trying several ways to mitigate this, including having pre-rendered speech playing something like "Okay" or "As an artificial representative, I'm still learning to be quicker on the pickup. We appreciate your patience." One of the industries we want to target is international web development and digital marketing companies, and we want to use the bot to cold-call businesses to pitch them our services. The goal is to replace $30 an hour cold-callers from the USA with $3 per hour total-cost automation. Apparently the CEO was given a $5 million valuation from the strength of the MVP from a VC. Our investment so far was at a $300k valuation tho. It's exciting. Trying to get Twilio working to be able to make calls programmatically instead of using our hacky workaround. Let me know if you have any questions. I just wanted to share this awesome news!

Feeling stuck—built a startup, got rejected from YC & IVI, met smarter people, and now I don’t know what to do. ( i will not promote )
I will not promote
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Feeling stuck—built a startup, got rejected from YC & IVI, met smarter people, and now I don’t know what to do. ( i will not promote ) I will not promote

I will not promote I don’t even know where to start, but I just feel completely stuck right now. I’m 20 years oldI don’t even know where to start, but I just feel completely stuck right now. I’m 20 years old, have been grinding non-stop for months, and it feels like I have nothing to show for it. I built an AI agent that automates workflows for businesses. I can build tech, but I can’t sell. That’s been my biggest realization recently—I thought building would be enough, but it’s not. I need customers, I need a co-founder, I need to figure out the business side… and I have no idea how. I applied to YC, IVI at ISB, and EF, met a lot of insanely smart people—some were impressed with me and my work, but they were wiser, more experienced, and honestly, just better at all of this than I am. It made me realize how much I don’t know. I got rejected from YC & IVI. 💔 YC didn’t even give much feedback—just a standard rejection. 💔 IVI told me: “You're too young, you need more experience, and you should work with a team before trying to start something.” That hit me hard. I had already been struggling to find a co-founder, and this just made me wonder if I even belong in this space yet. The Frustrating Part? I KNOW my tool Has a Unique Edge. I’m not just another AI automation tool—I know my tool has a strong USP that competitors lack. It has the potential to be an AI employee for businesses, not just another workflow tool. But I still haven’t built the “perfect product” I originally envisioned. And that’s what’s eating at me. I see what it COULD be, but I haven’t made it happen yet. At the same time, the competition in the AI agent space is exploding. YC-backed companies are working on AI agent startups. OpenAI is making huge progress with Operator. Competitors are moving fast, while I feel stuck. I’ve delayed development because I’m unsure whether to double down, pivot, or just move on entirely. Where I’m Stuck Right Now 🔹 Do I keep pushing and try to crack sales somehow? 🔹 Do I join a startup as a founding engineer to get experience, make connections, and learn sales before trying again? 🔹 Do I move to Bangalore, meet founders, and figure out what’s next? 🔹 Do I pivot to something nicher instead of competing in the AI agent race? If so, how do I even find a niche worth pursuing? 🔹 Do I even belong in startups? Or am I just forcing something that’s not working? I feel stuck in a weird middle zone where I’m not a beginner, but I’m also not successful. I’ve done enough to see what’s possible, but not enough to make it real. Every rejection makes me question if I’m even on the right path. I don’t know if I’m posting this for advice or just to get it out of my system. Maybe both. Has anyone else felt like this before? If you’ve been in this situation—how did you figure out whether to keep going or move on? TL;DR: I’m 20, built an AI agent for automating workflows, got rejected from YC & IVI, met insanely smart and experienced people, realized I can build tech but can’t sell, struggling to find a co-founder, AI agent competition is growing, delaying development, confused about the future—don’t know whether to double down, pivot, or move on. The frustrating part? I\ know I have a unique edge that others lack, but I still haven’t built the perfect product I originally envisioned.* edit: removed the tool's name

I spent 6 months on building a tool, and got 0 zero users. Here is my story.
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GDbuildsGDThis week

I spent 6 months on building a tool, and got 0 zero users. Here is my story.

Edit Thank you all so much for your time reading my story. Your support, feedback, criticism, and skepticism; all helped me a lot, and I couldn't appreciate it enough \^\_\^ TL;DR I spent 6 months on a tool that currently has 0 users. Below is what I learned during my journey, sharing because I believe most mistakes are easily avoidable. Do not overestimate your product and assume it will be an exception to fundamental principles. Principles are there for a reason. Always look for validation before you start. Avoid building products with a low money-to-effort ratio/in very competitive fields. Unless you have the means, you probably won't make it. Pick a problem space, pick your target audience, and talk to them before thinking about a solution. Identify and match their pain points. Only then should you think of a solution. If people are not overly excited or willing to pay in advance for a discounted price, it might be a sign to rethink. Sell one and only one feature at a time. Avoid everything else. If people don't pay for that one core feature, no secondary feature will change their mind. Always spend twice as much time marketing as you do building. You will not get users if they don't know it exists. Define success metrics ("1000 users in 3 months" or "$6000 in the account at the end of 6 months") before you start. If you don't meet them, strongly consider quitting the project. If you can't get enough users to keep going, nothing else matters. VALIDATION, VALIDATION, VALIDATION. Success is not random, but most of our first products will not make a success story. Know when to admit failure, and move on. Even if a product of yours doesn't succeed, what you learned during its journey will turn out to be invaluable for your future. My story So, this is the story of a product, Summ, that I’ve been working on for the last 6 months. As it's the first product I’ve ever built, after watching you all from the sidelines, I have learned a lot, made many mistakes, and did only a few things right. Just sharing what I’ve learned and some insights from my journey so far. I hope that this post will help you avoid the mistakes I made — most of which I consider easily avoidable — while you enjoy reading it, and get to know me a little bit more 🤓. A slow start after many years Summ isn’t the first product I really wanted to build. Lacking enough dev skills to even get started was a huge blocker for so many years. In fact, the first product I would’ve LOVED to build was a smart personal shopping assistant. I had this idea 4 years ago; but with no GPT, no coding skills, no technical co-founder, I didn’t have the means to make it happen. I still do not know if such a tool exists and is good enough. All I wanted was a tool that could make data-based predictions about when to buy stuff (“buy a new toothpaste every three months”) and suggest physical products that I might need or be strongly interested in. AFAIK, Amazon famously still struggles with the second one. Fast-forward a few years, I learned the very basics of HTML, CSS, and Vanilla JS. Still was not there to build a product; but good enough to code my design portfolio from scratch. Yet, I couldn’t imagine myself building a product using Vanilla JS. I really hated it, I really sucked at it. So, back to tutorial hell, and to learn about this framework I just heard about: React.React introduced so many new concepts to me. “Thinking in React” is a phrase we heard a lot, and with quite good reasons. After some time, I was able to build very basic tutorial apps, both in React, and React Native; but I have to say that I really hated coding for mobile. At this point, I was already a fan of productivity apps, and had a concept for a time management assistant app in my design portfolio. So, why not build one? Surely, it must be easy, since every coding tutorial starts with a todo app. ❌ WRONG! Building a basic todo app is easy enough, but building one good enough for a place in the market was a challenge I took and failed. I wasted one month on that until I abandoned the project for good. Even if I continued working on it, as the productivity landscape is overly competitive, I wouldn’t be able to make enough money to cover costs, assuming I make any. Since I was (and still am) in between jobs, I decided to abandon the project. 👉 What I learned: Do not start projects with a low ratio of money to effort and time. Example: Even if I get 500 monthly users, 200 of which are paid users (unrealistically high number), assuming an average subscription fee of $5/m (such apps are quite cheap, mostly due to the high competition), it would make me around $1000 minus any occurring costs. Any founder with a product that has 500 active users should make more. Even if it was relatively successful, due to the high competition, I wouldn’t make any meaningful money. PS: I use Todoist today. Due to local pricing, I pay less than $2/m. There is no way I could beat this competitive pricing, let alone the app itself. But, somehow, with a project that wasn’t even functional — let alone being an MVP — I made my first Wi-Fi money: Someone decided that the domain I preemptively purchased is worth something. By this point, I had already abandoned the project, certainly wasn’t going to renew the domain, was looking for a FT job, and a new project that I could work on. And out of nowhere, someone hands me some free money — who am I not to take it? Of course, I took it. The domain is still unused, no idea why 🤔. Ngl, I still hate the fact that my first Wi-Fi money came from this. A new idea worth pursuing? Fast-forward some weeks now. Around March, I got this crazy idea of building an email productivity tool. We all use emails, yet we all hate them. So, this must be fixed. Everyone uses emails, in fact everyone HAS TO use emails. So, I just needed to build a tool and wait for people to come. This was all, really. After all, the problem space is huge, there is enough room for another product, everyone uses emails, no need for any further validation, right? ❌ WRONG ONCE AGAIN! We all hear from the greatest in the startup landscape that we must validate our ideas with real people, yet at least some of us (guilty here 🥸) think that our product will be hugely successful and prove them to be an exception. Few might, but most are not. I certainly wasn't. 👉 Lesson learned: Always validate your ideas with real people. Ask them how much they’d pay for such a tool (not if they would). Much better if they are willing to pay upfront for a discount, etc. But even this comes later, keep reading. I think the difference between “How much” and “If” is huge for two reasons: (1) By asking them for “How much”, you force them to think in a more realistic setting. (2) You will have a more realistic idea on your profit margins. Based on my competitive analysis, I already had a solution in my mind to improve our email usage standards and email productivity (huge mistake), but I did my best to learn about their problems regarding those without pushing the idea too hard. The idea is this: Generate concise email summaries with suggested actions, combine them into one email, and send it at their preferred times. Save as much as time the AI you end up with allows. After all, everyone loves to save time. So, what kind of validation did I seek for? Talked with only a few people around me about this crazy, internet-breaking idea. The responses I got were, now I see, mediocre; no one got excited about it, just said things along the lines of “Cool idea, OK”. So, any reasonable person in this situation would think “Okay, not might not be working”, right? Well, I did not. I assumed that they were the wrong audience for this product, and there was this magical land of user segments waiting eagerly for my product, yet unknowingly. To this day, I still have not reached this magical place. Perhaps, it didn’t exist in the first place. If I cannot find it, whether it exists or not doesn’t matter. I am certainly searching for it. 👉 What I should have done: Once I decide on a problem space (time management, email productivity, etc.), I should decide on my potential user segments, people who I plan to sell my product to. Then I should go talk to those people, ask them about their pains, then get to the problem-solving/ideation phase only later. ❗️ VALIDATION COMES FROM THE REALITY OUTSIDE. What validation looks like might change from product to product; but what invalidation looks like is more or less the same for every product. Nico Jeannen told me yesterday “validation = money in the account” on Twitter. This is the ultimate form of validation your product could get. If your product doesn’t make any money, then something is invalidated by reality: Your product, you, your idea, who knows? So, at this point, I knew a little bit of Python from spending some time in tutorial hell a few years ago, some HTML/CSS/JS, barely enough React to build a working app. React could work for this project, but I needed easy-to-implement server interactivity. Luckily, around this time, I got to know about this new gen of indie hackers, and learned (but didn’t truly understand) about their approach to indie hacking, and this library called Nextjs. How good Next.js still blows my mind. So, I was back to tutorial hell once again. But, this time, with a promise to myself: This is the last time I would visit tutorial hell. Time to start building this "ground-breaking idea" Learning the fundamentals of Next.js was easier than learning of React unsurprisingly. Yet, the first time I managed to run server actions on Next.js was one of the rarest moments that completely blew my mind. To this day, I reject the idea that it is something else than pure magic under its hood. Did I absolutely need Nextjs for this project though? I do not think so. Did it save me lots of time? Absolutely. Furthermore, learning Nextjs will certainly be quite helpful for other projects that I will be tackling in the future. Already got a few ideas that might be worth pursuing in the head in case I decide to abandon Summ in the future. Fast-forward few weeks again: So, at this stage, I had a barely working MVP-like product. Since the very beginning, I spent every free hour (and more) on this project as speed is essential. But, I am not so sure it was worth it to overwork in retrospect. Yet, I know I couldn’t help myself. Everything is going kinda smooth, so what’s the worst thing that could ever happen? Well, both Apple and Google announced their AIs (Apple Intelligence and Google Gemini, respectively) will have email summarization features for their products. Summarizing singular emails is no big deal, after all there were already so many similar products in the market. I still think that what truly matters is a frictionless user experience, and this is why I built this product in a certain way: You spend less than a few minutes setting up your account, and you get to enjoy your email summaries, without ever visiting its website again. This is still a very cool concept I really like a lot. So, at this point: I had no other idea that could be pursued, already spent too much time on this project. Do I quit or not? This was the question. Of course not. I just have to launch this product as quickly as possible. So, I did something right, a quite rare occurrence I might say: Re-planned my product, dropped everything secondary to the core feature immediately (save time on reading emails), tried launching it asap. 👉 Insight: Sell only one core feature at one time. Drop anything secondary to this core feature. Well, my primary occupation is product design. So one would expect that a product I build must have stellar design. I considered any considerable time spent on design at this stage would be simply wasted. I still think this is both true and wrong: True, because if your product’s core benefits suck, no one will care about your design. False, because if your design looks amateurish, no one will trust you and your product. So, I always targeted an average level design with it and the way this tool works made it quite easy as I had to design only 2 primary pages: Landing page and user portal (which has only settings and analytics pages). However, even though I knew spending time on design was not worth much of my time, I got a bit “greedy”: In fact, I redesigned those pages three times, and still ended up with a so-so design that I am not proud of. 👉 What I would do differently: Unless absolutely necessary, only one iteration per stage as long as it works. This, in my mind, applies to everything. If your product’s A feature works, then no need to rewrite it from scratch for any reason, or even refactor it. When your product becomes a success, and you absolutely need that part of your codebase to be written, do so, but only then. Ready to launch, now is th etime for some marketing, right? By July 26, I already had a “launchable” product that barely works (I marked this date on a Notion docs, this is how I know). Yet, I had spent almost no time on marketing, sales, whatever. After all, “You build and they will come”. Did I know that I needed marketing? Of course I did, but knowingly didn’t. Why, you might ask. Well, from my perspective, it had to be a dev-heavy product; meaning that you spend most of your time on developing it, mostly coding skills. But, this is simply wrong. As a rule of thumb, as noted by one of the greatests, Marc Louvion, you should spend at least twice of the building time on marketing. ❗️ Time spent on building \* 2 people don’t know your product > they don’t use your product > you don’t get users > you don’t make money Easy as that. Following the same reasoning, a slightly different approach to planning a project is possible. Determine an approximate time to complete the project with a high level project plan. Let’s say 6 months. By the reasoning above, 2 months should go into building, and 4 into marketing. If you need 4 months for building instead of 2, then you need 8 months of marketing, which makes the time to complete the project 12 months. If you don’t have that much time, then quit the project. When does a project count as completed? Well, in reality, never. But, I think we have to define success conditions even before we start for indie projects and startups; so we know when to quit when they are not met. A success condition could look like “Make $6000 in 12 months” or “Have 3000 users in 6 months”. It all depends on the project. But, once you set it, it should be set in stone: You don’t change it unless absolutely necessary. I suspect there are few principles that make a solopreneur successful; and knowing when to quit and when to continue is definitely one of them. Marc Louvion is famously known for his success, but he got there after failing so many projects. To my knowledge, the same applies to Nico Jeannen, Pieter Levels, or almost everyone as well. ❗️ Determining when to continue even before you start will definitely help in the long run. A half-aed launch Time-leap again. Around mid August, I “soft launched” my product. By soft launch, I mean lazy marketing. Just tweeting about it, posting it on free directories. Did I get any traffic? Surely I did. Did I get any users? Nope. Only after this time, it hit me: “Either something is wrong with me, or with this product” Marketing might be a much bigger factor for a project’s success after all. Even though I get some traffic, not convincing enough for people to sign up even for a free trial. The product was still perfect in my eyes at the time (well, still is ^(\_),) so the right people are not finding my product, I thought. Then, a question that I should have been asking at the very first place, one that could prevent all these, comes to my mind: “How do even people search for such tools?” If we are to consider this whole journey of me and my so-far-failed product to be an already destined failure, one metric suffices to show why. Search volume: 30. Even if people have such a pain point, they are not looking for email summaries. So, almost no organic traffic coming from Google. But, as a person who did zero marketing on this or any product, who has zero marketing knowledge, who doesn’t have an audience on social media, there is not much I could do. Finally, it was time to give up. Or not… In my eyes, the most important element that makes a founder (solo or not) successful (this, I am not by any means) is to solve problems. ❗️ So, the problem was this: “People are not finding my product by organic search” How do I make sure I get some organic traffic and gets more visibility? Learn digital marketing and SEO as much as I can within very limited time. Thankfully, without spending much time, I came across Neil Patel's YT channel, and as I said many times, it is an absolute gold mine. I learned a lot, especially about the fundamentals, and surely it will be fruitful; but there is no magic trick that could make people visit your website. SEO certainly helps, but only when people are looking for your keywords. However, it is truly a magical solution to get in touch with REAL people that are in your user segments: 👉 Understand your pains, understand their problems, help them to solve them via building products. I did not do this so far, have to admit. But, in case you would like to have a chat about your email usage, and email productivity, just get in touch; I’d be delighted to hear about them. Getting ready for a ProductHunt launch The date was Sept 1. And I unlocked an impossible achievement: Running out of Supabase’s free plan’s Egres limit while having zero users. I was already considering moving out of their Cloud server and managing a Supabase CLI service on my Hetzner VPS for some time; but never ever suspected that I would have to do this quickly. The cheapest plan Supabase offers is $25/month; yet, at that point, I am in between jobs for such a long time, basically broke, and could barely afford that price. One or two months could be okay, but why pay for it if I will eventually move out of their Cloud service? So, instead of paying $25, I spent two days migrating out of Supabase Cloud. Worth my time? Definitely not. But, when you are broke, you gotta do stupid things. This was the first time that I felt lucky to have zero users: I have no idea how I would manage this migration if I had any. I think this is one of the core tenets of an indie hacker: Controlling their own environment. I can’t remember whose quote this is, but I suspect it was Naval: Entrepreneurs have an almost pathological need to control their own fate. They will take any suffering if they can be in charge of their destiny, and not have it in somebody else’s hands. What’s truly scary is, at least in my case, we make people around us suffer at the expense of our attempting to control our own fates. I know this period has been quite hard on my wife as well, as I neglected her quite a bit, but sadly, I know that this will happen again. It is something that I can barely help with. Still, so sorry. After working the last two weeks on a ProductHunt Launch, I finally launched it this Tuesday. Zero ranking, zero new users, but 36 kind people upvoted my product, and many commented and provided invaluable feedback. I couldn't be more grateful for each one of them 🙏. Considering all these, what lies in the future of Summ though? I have no idea, to be honest. On one hand, I have zero users, have no job, no income. So, I need a way to make money asap. On the other hand, the whole idea of it revolves around one core premise (not an assumption) that I am not so willing to share; and I couldn’t have more trust in it. This might not be the best iteration of it, however I certainly believe that email usage is one of the best problem spaces one could work on. 👉 But, one thing is for certain: I need to get in touch with people, and talk with them about this product I built so far. In fact, this is the only item on my agenda. Nothing else will save my brainchild <3. Below are some other insights and notes that I got during my journey; as they do not 100% fit into this story, I think it is more suitable to list them here. I hope you enjoyed reading this. Give Summ a try, it comes with a generous free trial, no credit card required. Some additional notes and insights: Project planning is one of the most underestimated skills for solopreneurs. It saves you enormous time, and helps you to keep your focus up. Building B2C products beats building B2B products. Businesses are very willing to pay big bucks if your product helps them. On the other hand, spending a few hours per user who would pay $5/m probably is not worth your time. It doesn’t matter how brilliant your product is if no one uses it. If you cannot sell a product in a certain category/niche (or do not know how to sell it), it might be a good idea not to start a project in it. Going after new ideas and ventures is quite risky, especially if you don’t know how to market it. On the other hand, an already established category means that there is already demand. Whether this demand is sufficient or not is another issue. As long as there is enough demand for your product to fit in, any category/niche is good. Some might be better, some might be worse. Unless you are going hardcore B2B, you will need people to find your product by means of organic search. Always conduct thorough keyword research as soon as possible.

Looking for a tech cofounder. Revoltionary (yes really!) gig economy app. I will not promote.
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sweetpea___This week

Looking for a tech cofounder. Revoltionary (yes really!) gig economy app. I will not promote.

Hey everyone! I’m building a new gig-work app that cuts out the hassles of interviews, applications, and sky-high fees. We’re aiming to make it easy for businesses to hire qualified freelancers for short shifts or one-off tasks—and for freelancers to set their own rates and get paid quickly. Why This App? Time-Saving Model: Instead of posting jobs and conducting multiple interviews, employers can instantly book from a list of KYC-verified freelancers who showcase their skills via 30-second video bios. Cost Leadership: We plan to charge only 5%, far below the 15–50% common in other gig platforms. This keeps more money in the pockets of both freelancers and businesses. Proven Demand: A beta test in 2018 drew nearly 600 active users, validating that there’s appetite for a simpler, fairer way to fill short shifts. About Me 20+ years’ experience in payroll, workforce management, and operations for Fortune 500 companies. Led cross-functional teams, implemented large-scale solutions, and believe in building with a user-first mindset. Offering meaningful equity—I want a true partner, not a hired gun. Who I’m Looking For Full-Stack Developer (comfortable with Node.js, React, Python, or similar and ML/Ai) who can manage everything from front-end to database integration (ideally Postgres/MySQL) and build a same day payments system. Passion for creating solutions that genuinely help gig workers and small businesses. Excitement to collaborate on the product roadmap, from the booking interface to same-day payment features. The Opportunity Major Market: The gig economy is huge and still growing. If we nail speed, cost-effectiveness, and ease of use, we can capture a significant share of it. Remote-Friendly: We can work together from anywhere, though I’m planning to relaunch in London where the initial beta gained momentum. If this sounds like your kind of challenge, drop a comment or DM me. Let’s chat about how we can merge our strengths—my operations background and your technical expertise—to build a platform that truly transforms the gig-work experience. Thanks for reading, and I look forward to creating something impactful together!

Feeling stuck—built a startup, got rejected from YC & IVI, met smarter people, and now I don’t know what to do. ( i will not promote )
I will not promote
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vishwa1238This week

Feeling stuck—built a startup, got rejected from YC & IVI, met smarter people, and now I don’t know what to do. ( i will not promote ) I will not promote

I will not promote I don’t even know where to start, but I just feel completely stuck right now. I’m 20 years oldI don’t even know where to start, but I just feel completely stuck right now. I’m 20 years old, have been grinding non-stop for months, and it feels like I have nothing to show for it. I built an AI agent that automates workflows for businesses. I can build tech, but I can’t sell. That’s been my biggest realization recently—I thought building would be enough, but it’s not. I need customers, I need a co-founder, I need to figure out the business side… and I have no idea how. I applied to YC, IVI at ISB, and EF, met a lot of insanely smart people—some were impressed with me and my work, but they were wiser, more experienced, and honestly, just better at all of this than I am. It made me realize how much I don’t know. I got rejected from YC & IVI. 💔 YC didn’t even give much feedback—just a standard rejection. 💔 IVI told me: “You're too young, you need more experience, and you should work with a team before trying to start something.” That hit me hard. I had already been struggling to find a co-founder, and this just made me wonder if I even belong in this space yet. The Frustrating Part? I KNOW my tool Has a Unique Edge. I’m not just another AI automation tool—I know my tool has a strong USP that competitors lack. It has the potential to be an AI employee for businesses, not just another workflow tool. But I still haven’t built the “perfect product” I originally envisioned. And that’s what’s eating at me. I see what it COULD be, but I haven’t made it happen yet. At the same time, the competition in the AI agent space is exploding. YC-backed companies are working on AI agent startups. OpenAI is making huge progress with Operator. Competitors are moving fast, while I feel stuck. I’ve delayed development because I’m unsure whether to double down, pivot, or just move on entirely. Where I’m Stuck Right Now 🔹 Do I keep pushing and try to crack sales somehow? 🔹 Do I join a startup as a founding engineer to get experience, make connections, and learn sales before trying again? 🔹 Do I move to Bangalore, meet founders, and figure out what’s next? 🔹 Do I pivot to something nicher instead of competing in the AI agent race? If so, how do I even find a niche worth pursuing? 🔹 Do I even belong in startups? Or am I just forcing something that’s not working? I feel stuck in a weird middle zone where I’m not a beginner, but I’m also not successful. I’ve done enough to see what’s possible, but not enough to make it real. Every rejection makes me question if I’m even on the right path. I don’t know if I’m posting this for advice or just to get it out of my system. Maybe both. Has anyone else felt like this before? If you’ve been in this situation—how did you figure out whether to keep going or move on? TL;DR: I’m 20, built an AI agent for automating workflows, got rejected from YC & IVI, met insanely smart and experienced people, realized I can build tech but can’t sell, struggling to find a co-founder, AI agent competition is growing, delaying development, confused about the future—don’t know whether to double down, pivot, or move on. The frustrating part? I\ know I have a unique edge that others lack, but I still haven’t built the perfect product I originally envisioned.* edit: removed the tool's name

How to get funding for startup ? I will not promote
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wlynncorkThis week

How to get funding for startup ? I will not promote

I will not promote. Software startup based out of Minnesota us. I've built and launched a product that is gaining traction, solving a problem that has frustrated software developers and product teams for years. The problem: Software development is slow, expensive, and full of inefficiencies. Developers spend hours on repetitive coding tasks, project managers struggle with bottlenecks, and businesses waste time translating product requirements into actual code. The solution: My product automates a large portion of software development. It acts as an AI-powered assistant for developers, taking high-level requirements and turning them into functional code while integrating with existing codebases. It can read, understand, and modify software projects in a structured way—cutting development time drastically. The potential: Businesses are always looking for ways to cut costs and speed up development. With the rise of AI, companies are increasingly adopting automation, and this tool fits perfectly into that wave. Imagine a world where software teams are 10x more efficient because AI handles the grunt work, and developers focus on the bigger picture. It’s not about replacing developers—it’s about supercharging them. The current status: The product is live and in use. The user base is growing, and I’ve proven demand. Now, I need to figure out the best funding model to scale—whether that’s bootstrapping, VC, grants, or some hybrid approach. If you have experience in startup funding or have scaled a tech product, I'd love to hear your insights. DM me if you're open to discussing strategies!

Nuts and bolts AI implementation for small business
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Training-Swan-6379This week

Nuts and bolts AI implementation for small business

How can small businesses use AI to increase sales or decrease expenses without massive disruption? One way for us is using AI to process our email history to identify patterns and write personalized messages based on past correspondence. According to legal advice in which I have confidence, email that is personalized for each recipient (and meets other standards) does not need to be opt in. If you disagree - understood - but spam morality is not the topic here. Bottom line - obviously a game changer. Knowing phrases people have used before becoming clients - and all of the possible permutations of those phrases, and detecting where those phrases show up will make our sales and marketing many times more effective for a fraction of the cost. There's a reason big corps. record calls, and now small business can leverage the same technology. We are setting up a process that yields accurate, up to date, comprehensive data for our own business operations. Our clients - who are they and how has their demographic changed over time? To answer this question and for email personalization, we also need access to external data sources e.g. like accurate up to date company demographics. IMO - the leader in company data in the US? THEY SUCK. We found there is no magic fairy who is going to make good data appear for our AI. The process of applying our own proprietary knowledge to code and categorize the data is just as important, and obviously highly sensitive. How do we leverage the AI technologies of companies like Google and Microsoft (or anyone else) without being their bitch? Below is a list of some of the sources of my business's data: Data sources: PST/OST/Other Email data files Microsoft data from Windows/O365 Windows/Linux/Android/IOS application logs and other data Web server logs for the company website. SEO/Analytics Data Google data export Google voice/VOIP logs OneDrive/G drive Other Phone system/cell service logs Other SAAS and in-house application data. Facebook/social media data for company pages. QuickBooks/other accounting systems/business bank account logs POS/Credit card processing systems/PayPal, etc. OSINT to fill in the blanks

Good at coding, bad at marketing. Summary
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Official-DATSThis week

Good at coding, bad at marketing. Summary

Hello. I posted a question on what to do if you are good at coding but bad at marketing four days ago, and I received so many responses and tips. The original post is here. I was really glad and excited to read comments. To return the favor to the community and add some more value, I’ve summarized all the comments I got on the original post. Here are they, with my personal comments on some of the advice I got. You’ll never believe it, but the most common advice was to learn. Really, the first and only thing you should start with if you’re bad at marketing is learning. Yet learning could be different. I highlighted 5 main areas. Educate yourself on general questions. Learn more about some basics. For example, start by finding out what the 4P’s of marketing are, and afterward, you’ll inevitably run into YouTube videos, seminars, Udemy courses, or any other resource that resonates with you on some ideas/avenues you could pursue. Read books and watch videos. There are tons of books on marketing and sales. People shared in the comments books by Dan Kennedy and “Cashvertising”, written by Drew Eric Whitman. (I’ve never heard of them, but already ordered on Amazon). For sales, the most common idea was to start with YouTube videos. For example, Alex Hormozi videos and Startup school delivered by Ycombinator videos. Check out Indie Hackers and scrutinize it for a piece of good advice from developers in the same situation. Also, there was advice to follow up and read some guy on Twitter. (Don't want to get unfairly banned from here, so won't post it) Educate yourself and hire a professional or find a co-founder to help you: Hire a seasoned marketer in this field to help you out. He will help you achieve cost-efficient scales. But it could be a real problem to find the right person. Marketing agencies are expensive. Try to look on LinkedIn or among your acquaintances. Look for professionals with credentials or extensive experience. Seek marketing referrals from startups of a similar size/industry. If you don't have those, try to bring a trusted/experienced marketer friend into the intro meetings to help assess whether the service provider knows what they are doing. Talented freelancers can often get the job done for less than hiring an entire agency. Look for a co-founder who is savvy in marketing, passionate, and ready to work hard towards mutual success. Educate and DIY Being the face of your business is way better than having faceless communication. The startup checklist is made based on the comments is next: At least have your product defined. Define your target audience. Set up the goals you want to achieve. Make domain expertise and understand the market and the direction of its development. The next stage is answering tricky questions: Have you created a business model? How do you plan to compete? What’s your unique selling point? How much do you plan to budget for marketing? Are you planning to work alone, or will you need other devs? Then you start thinking about clients… You need the exposure to truly understand the customer's pain points and build a product that they love. You need to think about how your clients would think, and you should tailor each step you take for them. Get feedback from your early users if you already have a product. Interview your potential customers to learn how they buy. This will help you narrow your choice of marketing channels. Get your product or service used by several startups and help them achieve their goals. Endorsements are very valuable marketing assets. You need a landing to validate your value proposition and start sending traffic, or you can run meta instant form campaigns... It would depend on the category of your startup. You need a benchmark of the competition's ads both in Meta and Google, blog posts, domain authority, their landing page, and average search volumes. Do affiliate marketing for your product since it's an effective strategy. Educate and use AI tools for dealing with marketing. Build an LLM-based product to automate marketing. (Sounds like an idea for a startup, right?) Learn following ChatGPT advice. In 1–3 months, you will be another updated person. Look at marketowl, an AI marketing department for startups and microbusinesses that have no budget or time to do marketing. It will automate the basic tasks your business needs, but it doesn't require your marketing expertise. Check out AI tools that are delivering very good marketing content (gocharlie, jasper, copyai). Educate yourself and run socials Start a blog or YouTube channel where you can share your expertise in coding or anything else you are good at and how your product simplifies life. Engage with your audience on social media platforms like Instagram and LinkedIn, where you can showcase your industry knowledge. Start a page on Twitter and an account on Reddit. Follow and read subreddits and pages where your potential customers are. Learn the pain from the inside. Do not simply promote, people will lose interest immediately. Start by taking focused time to create informational content, so people will eventually be naturally intrigued by what you do and want to support you when they start to “know” you. Educate your potential users about the value of your product. Create content based on what ideal customers are asking at the various stages of marketing. e.g., if they are at the beginning of the process, they may use basic language; if they are further down the process, maybe they’ll be specific. Try to get on podcasts and build as many social links as you can. In other words, don’t live in a shell! Post regularly, and eventually you’ll find sites or people that are willing to promote for you. I omitted here all personal help offers and newsletters, however you could find them in the original post. Hope that will be helpful!

I spent 6 months on building a web product, and got zero users. Here is my story.
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I spent 6 months on building a web product, and got zero users. Here is my story.

Edit Thank you all so much for your time reading my story. Your support, feedback, criticism, and skepticism; all helped me a lot, and I couldn't appreciate it enough \^\_\^ I have stuff to post on Reddit very rarely, but I share how my project is going on, random stuff, and memes on X. Just in case few might want to keep in touch 👀 TL;DR I spent 6 months on a tool that currently has 0 users. Below is what I learned during my journey, sharing because I believe most mistakes are easily avoidable. Do not overestimate your product and assume it will be an exception to fundamental principles. Principles are there for a reason. Always look for validation before you start. Avoid building products with a low money-to-effort ratio/in very competitive fields. Unless you have the means, you probably won't make it. Pick a problem space, pick your target audience, and talk to them before thinking about a solution. Identify and match their pain points. Only then should you think of a solution. If people are not overly excited or willing to pay in advance for a discounted price, it might be a sign to rethink. Sell one and only one feature at a time. Avoid everything else. If people don't pay for that one core feature, no secondary feature will change their mind. Always spend twice as much time marketing as you do building. You will not get users if they don't know it exists. Define success metrics ("1000 users in 3 months" or "$6000 in the account at the end of 6 months") before you start. If you don't meet them, strongly consider quitting the project. If you can't get enough users to keep going, nothing else matters. VALIDATION, VALIDATION, VALIDATION. Success is not random, but most of our first products will not make a success story. Know when to admit failure, and move on. Even if a product of yours doesn't succeed, what you learned during its journey will turn out to be invaluable for your future. My story So, this is the story of a product that I’ve been working on for the last 6 months. As it's the first product I’ve ever built, after watching you all from the sidelines, I have learned a lot, made many mistakes, and did only a few things right. Just sharing what I’ve learned and some insights from my journey so far. I hope that this post will help you avoid the mistakes I made — most of which I consider easily avoidable — while you enjoy reading it, and get to know me a little bit more 🤓. A slow start after many years Summ isn’t the first product I really wanted to build. Lacking enough dev skills to even get started was a huge blocker for so many years. In fact, the first product I would’ve LOVED to build was a smart personal shopping assistant. I had this idea 4 years ago; but with no GPT, no coding skills, no technical co-founder, I didn’t have the means to make it happen. I still do not know if such a tool exists and is good enough. All I wanted was a tool that could make data-based predictions about when to buy stuff (“buy a new toothpaste every three months”) and suggest physical products that I might need or be strongly interested in. AFAIK, Amazon famously still struggles with the second one. Fast-forward a few years, I learned the very basics of HTML, CSS, and Vanilla JS. Still was not there to build a product; but good enough to code my design portfolio from scratch. Yet, I couldn’t imagine myself building a product using Vanilla JS. I really hated it, I really sucked at it. So, back to tutorial hell, and to learn about this framework I just heard about: React.React introduced so many new concepts to me. “Thinking in React” is a phrase we heard a lot, and with quite good reasons. After some time, I was able to build very basic tutorial apps, both in React, and React Native; but I have to say that I really hated coding for mobile. At this point, I was already a fan of productivity apps, and had a concept for a time management assistant app in my design portfolio. So, why not build one? Surely, it must be easy, since every coding tutorial starts with a todo app. ❌ WRONG! Building a basic todo app is easy enough, but building one good enough for a place in the market was a challenge I took and failed. I wasted one month on that until I abandoned the project for good. Even if I continued working on it, as the productivity landscape is overly competitive, I wouldn’t be able to make enough money to cover costs, assuming I make any. Since I was (and still am) in between jobs, I decided to abandon the project. 👉 What I learned: Do not start projects with a low ratio of money to effort and time. Example: Even if I get 500 monthly users, 200 of which are paid users (unrealistically high number), assuming an average subscription fee of $5/m (such apps are quite cheap, mostly due to the high competition), it would make me around $1000 minus any occurring costs. Any founder with a product that has 500 active users should make more. Even if it was relatively successful, due to the high competition, I wouldn’t make any meaningful money. PS: I use Todoist today. Due to local pricing, I pay less than $2/m. There is no way I could beat this competitive pricing, let alone the app itself. But, somehow, with a project that wasn’t even functional — let alone being an MVP — I made my first Wi-Fi money: Someone decided that the domain I preemptively purchased is worth something. By this point, I had already abandoned the project, certainly wasn’t going to renew the domain, was looking for a FT job, and a new project that I could work on. And out of nowhere, someone hands me some free money — who am I not to take it? Of course, I took it. The domain is still unused, no idea why 🤔. Ngl, I still hate the fact that my first Wi-Fi money came from this. A new idea worth pursuing? Fast-forward some weeks now. Around March, I got this crazy idea of building an email productivity tool. We all use emails, yet we all hate them. So, this must be fixed. Everyone uses emails, in fact everyone HAS TO use emails. So, I just needed to build a tool and wait for people to come. This was all, really. After all, the problem space is huge, there is enough room for another product, everyone uses emails, no need for any further validation, right? ❌ WRONG ONCE AGAIN! We all hear from the greatest in the startup landscape that we must validate our ideas with real people, yet at least some of us (guilty here 🥸) think that our product will be hugely successful and prove them to be an exception. Few might, but most are not. I certainly wasn't. 👉 Lesson learned: Always validate your ideas with real people. Ask them how much they’d pay for such a tool (not if they would). Much better if they are willing to pay upfront for a discount, etc. But even this comes later, keep reading. I think the difference between “How much” and “If” is huge for two reasons: (1) By asking them for “How much”, you force them to think in a more realistic setting. (2) You will have a more realistic idea on your profit margins. Based on my competitive analysis, I already had a solution in my mind to improve our email usage standards and email productivity (huge mistake), but I did my best to learn about their problems regarding those without pushing the idea too hard. The idea is this: Generate concise email summaries with suggested actions, combine them into one email, and send it at their preferred times. Save as much as time the AI you end up with allows. After all, everyone loves to save time. So, what kind of validation did I seek for? Talked with only a few people around me about this crazy, internet-breaking idea. The responses I got were, now I see, mediocre; no one got excited about it, just said things along the lines of “Cool idea, OK”. So, any reasonable person in this situation would think “Okay, not might not be working”, right? Well, I did not. I assumed that they were the wrong audience for this product, and there was this magical land of user segments waiting eagerly for my product, yet unknowingly. To this day, I still have not reached this magical place. Perhaps, it didn’t exist in the first place. If I cannot find it, whether it exists or not doesn’t matter. I am certainly searching for it. 👉 What I should have done: Once I decide on a problem space (time management, email productivity, etc.), I should decide on my potential user segments, people who I plan to sell my product to. Then I should go talk to those people, ask them about their pains, then get to the problem-solving/ideation phase only later. ❗️ VALIDATION COMES FROM THE REALITY OUTSIDE. What validation looks like might change from product to product; but what invalidation looks like is more or less the same for every product. Nico Jeannen told me yesterday “validation = money in the account” on Twitter. This is the ultimate form of validation your product could get. If your product doesn’t make any money, then something is invalidated by reality: Your product, you, your idea, who knows? So, at this point, I knew a little bit of Python from spending some time in tutorial hell a few years ago, some HTML/CSS/JS, barely enough React to build a working app. React could work for this project, but I needed easy-to-implement server interactivity. Luckily, around this time, I got to know about this new gen of indie hackers, and learned (but didn’t truly understand) about their approach to indie hacking, and this library called Nextjs. How good Next.js still blows my mind. So, I was back to tutorial hell once again. But, this time, with a promise to myself: This is the last time I would visit tutorial hell. Time to start building this "ground-breaking idea" Learning the fundamentals of Next.js was easier than learning of React unsurprisingly. Yet, the first time I managed to run server actions on Next.js was one of the rarest moments that completely blew my mind. To this day, I reject the idea that it is something else than pure magic under its hood. Did I absolutely need Nextjs for this project though? I do not think so. Did it save me lots of time? Absolutely. Furthermore, learning Nextjs will certainly be quite helpful for other projects that I will be tackling in the future. Already got a few ideas that might be worth pursuing in the head in case I decide to abandon Summ in the future. Fast-forward few weeks again: So, at this stage, I had a barely working MVP-like product. Since the very beginning, I spent every free hour (and more) on this project as speed is essential. But, I am not so sure it was worth it to overwork in retrospect. Yet, I know I couldn’t help myself. Everything is going kinda smooth, so what’s the worst thing that could ever happen? Well, both Apple and Google announced their AIs (Apple Intelligence and Google Gemini, respectively) will have email summarization features for their products. Summarizing singular emails is no big deal, after all there were already so many similar products in the market. I still think that what truly matters is a frictionless user experience, and this is why I built this product in a certain way: You spend less than a few minutes setting up your account, and you get to enjoy your email summaries, without ever visiting its website again. This is still a very cool concept I really like a lot. So, at this point: I had no other idea that could be pursued, already spent too much time on this project. Do I quit or not? This was the question. Of course not. I just have to launch this product as quickly as possible. So, I did something right, a quite rare occurrence I might say: Re-planned my product, dropped everything secondary to the core feature immediately (save time on reading emails), tried launching it asap. 👉 Insight: Sell only one core feature at one time. Drop anything secondary to this core feature. Well, my primary occupation is product design. So one would expect that a product I build must have stellar design. I considered any considerable time spent on design at this stage would be simply wasted. I still think this is both true and wrong: True, because if your product’s core benefits suck, no one will care about your design. False, because if your design looks amateurish, no one will trust you and your product. So, I always targeted an average level design with it and the way this tool works made it quite easy as I had to design only 2 primary pages: Landing page and user portal (which has only settings and analytics pages). However, even though I knew spending time on design was not worth much of my time, I got a bit “greedy”: In fact, I redesigned those pages three times, and still ended up with a so-so design that I am not proud of. 👉 What I would do differently: Unless absolutely necessary, only one iteration per stage as long as it works. This, in my mind, applies to everything. If your product’s A feature works, then no need to rewrite it from scratch for any reason, or even refactor it. When your product becomes a success, and you absolutely need that part of your codebase to be written, do so, but only then. Ready to launch, now is th etime for some marketing, right? By July 26, I already had a “launchable” product that barely works (I marked this date on a Notion docs, this is how I know). Yet, I had spent almost no time on marketing, sales, whatever. After all, “You build and they will come”. Did I know that I needed marketing? Of course I did, but knowingly didn’t. Why, you might ask. Well, from my perspective, it had to be a dev-heavy product; meaning that you spend most of your time on developing it, mostly coding skills. But, this is simply wrong. As a rule of thumb, as noted by one of the greatests, Marc Louvion, you should spend at least twice of the building time on marketing. ❗️ Time spent on building \* 2 people don’t know your product > they don’t use your product > you don’t get users > you don’t make money Easy as that. Following the same reasoning, a slightly different approach to planning a project is possible. Determine an approximate time to complete the project with a high level project plan. Let’s say 6 months. By the reasoning above, 2 months should go into building, and 4 into marketing. If you need 4 months for building instead of 2, then you need 8 months of marketing, which makes the time to complete the project 12 months. If you don’t have that much time, then quit the project. When does a project count as completed? Well, in reality, never. But, I think we have to define success conditions even before we start for indie projects and startups; so we know when to quit when they are not met. A success condition could look like “Make $6000 in 12 months” or “Have 3000 users in 6 months”. It all depends on the project. But, once you set it, it should be set in stone: You don’t change it unless absolutely necessary. I suspect there are few principles that make a solopreneur successful; and knowing when to quit and when to continue is definitely one of them. Marc Louvion is famously known for his success, but he got there after failing so many projects. To my knowledge, the same applies to Nico Jeannen, Pieter Levels, or almost everyone as well. ❗️ Determining when to continue even before you start will definitely help in the long run. A half-aed launch Time-leap again. Around mid August, I “soft launched” my product. By soft launch, I mean lazy marketing. Just tweeting about it, posting it on free directories. Did I get any traffic? Surely I did. Did I get any users? Nope. Only after this time, it hit me: “Either something is wrong with me, or with this product” Marketing might be a much bigger factor for a project’s success after all. Even though I get some traffic, not convincing enough for people to sign up even for a free trial. The product was still perfect in my eyes at the time (well, still is ^(\_),) so the right people are not finding my product, I thought. Then, a question that I should have been asking at the very first place, one that could prevent all these, comes to my mind: “How do even people search for such tools?” If we are to consider this whole journey of me and my so-far-failed product to be an already destined failure, one metric suffices to show why. Search volume: 30. Even if people have such a pain point, they are not looking for email summaries. So, almost no organic traffic coming from Google. But, as a person who did zero marketing on this or any product, who has zero marketing knowledge, who doesn’t have an audience on social media, there is not much I could do. Finally, it was time to give up. Or not… In my eyes, the most important element that makes a founder (solo or not) successful (this, I am not by any means) is to solve problems. ❗️ So, the problem was this: “People are not finding my product by organic search” How do I make sure I get some organic traffic and gets more visibility? Learn digital marketing and SEO as much as I can within very limited time. Thankfully, without spending much time, I came across Neil Patel's YT channel, and as I said many times, it is an absolute gold mine. I learned a lot, especially about the fundamentals, and surely it will be fruitful; but there is no magic trick that could make people visit your website. SEO certainly helps, but only when people are looking for your keywords. However, it is truly a magical solution to get in touch with REAL people that are in your user segments: 👉 Understand your pains, understand their problems, help them to solve them via building products. I did not do this so far, have to admit. But, in case you would like to have a chat about your email usage, and email productivity, just get in touch; I’d be delighted to hear about them. Getting ready for a ProductHunt launch The date was Sept 1. And I unlocked an impossible achievement: Running out of Supabase’s free plan’s Egres limit while having zero users. I was already considering moving out of their Cloud server and managing a Supabase CLI service on my Hetzner VPS for some time; but never ever suspected that I would have to do this quickly. The cheapest plan Supabase offers is $25/month; yet, at that point, I am in between jobs for such a long time, basically broke, and could barely afford that price. One or two months could be okay, but why pay for it if I will eventually move out of their Cloud service? So, instead of paying $25, I spent two days migrating out of Supabase Cloud. Worth my time? Definitely not. But, when you are broke, you gotta do stupid things. This was the first time that I felt lucky to have zero users: I have no idea how I would manage this migration if I had any. I think this is one of the core tenets of an indie hacker: Controlling their own environment. I can’t remember whose quote this is, but I suspect it was Naval: Entrepreneurs have an almost pathological need to control their own fate. They will take any suffering if they can be in charge of their destiny, and not have it in somebody else’s hands. What’s truly scary is, at least in my case, we make people around us suffer at the expense of our attempting to control our own fates. I know this period has been quite hard on my wife as well, as I neglected her quite a bit, but sadly, I know that this will happen again. It is something that I can barely help with. Still, so sorry. After working the last two weeks on a ProductHunt Launch, I finally launched it this Tuesday. Zero ranking, zero new users, but 36 kind people upvoted my product, and many commented and provided invaluable feedback. I couldn't be more grateful for each one of them 🙏. Considering all these, what lies in the future of Summ though? I have no idea, to be honest. On one hand, I have zero users, have no job, no income. So, I need a way to make money asap. On the other hand, the whole idea of it revolves around one core premise (not an assumption) that I am not so willing to share; and I couldn’t have more trust in it. This might not be the best iteration of it, however I certainly believe that email usage is one of the best problem spaces one could work on. 👉 But, one thing is for certain: I need to get in touch with people, and talk with them about this product I built so far. In fact, this is the only item on my agenda. Nothing else will save my brainchild <3. Below are some other insights and notes that I got during my journey; as they do not 100% fit into this story, I think it is more suitable to list them here. I hope you enjoyed reading this. Give Summ a try, it comes with a generous free trial, no credit card required. Some additional notes and insights: Project planning is one of the most underestimated skills for solopreneurs. It saves you enormous time, and helps you to keep your focus up. Building B2C products beats building B2B products. Businesses are very willing to pay big bucks if your product helps them. On the other hand, spending a few hours per user who would pay $5/m probably is not worth your time. It doesn’t matter how brilliant your product is if no one uses it. If you cannot sell a product in a certain category/niche (or do not know how to sell it), it might be a good idea not to start a project in it. Going after new ideas and ventures is quite risky, especially if you don’t know how to market it. On the other hand, an already established category means that there is already demand. Whether this demand is sufficient or not is another issue. As long as there is enough demand for your product to fit in, any category/niche is good. Some might be better, some might be worse. Unless you are going hardcore B2B, you will need people to find your product by means of organic search. Always conduct thorough keyword research as soon as possible.

Month 2 of building my startup after being laid off - $200 in revenue and 4 (actual) paying customers
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Month 2 of building my startup after being laid off - $200 in revenue and 4 (actual) paying customers

In September 2024, I got laid off from my Silicon Valley job. It fucking sucked. I took a day to be sad, then got to work - I'm not one to wallow, I prefer action. Updated my resume, hit up my network, started interviewing. During this time, I had a realization - I'm tired of depending on a single income stream. I needed to diversify. Then it hit me: I literally work with RAG (retrieval augmented generation) in AI. Why not use this knowledge to help small businesses reduce their customer service load and boost sales? One month later, Answer HQ 0.5 (the MVP) was in the hands of our first users (shoutout to these alpha testers - their feedback shaped everything). By month 2, Answer HQ 1.0 launched with four paying customers, and growing. You're probably thinking - great, another chatbot. Yes, Answer HQ is a chatbot at its core. But here's the difference: it actually works. Our paying customers are seeing real results in reducing support load, plus it has something unique - it actively drives sales by turning customer questions into conversions. How? The AI doesn't just answer questions, it naturally recommends relevant products and content (blogs, social media, etc). Since I'm targeting small business owners (who usually aren't tech wizards) and early startups, Answer HQ had to be dead simple to set up. Here's my onboarding process - just 4 steps. I've checked out competitors like Intercom and Crisp, and I can say this: if my non-tech fiancée can set up an assistant on her blog in minutes, anyone can. Key learnings so far: Building in public is powerful. I shared my journey on Threads and X, and the support for a solo founder has been amazing. AI dev tools (Cursor, Claude Sonnet 3.5) have made MVP development incredibly accessible. You can get a working prototype frontend ready in days. I don't see how traditional no-code tools can survive in this age. But.. for a production-ready product? You still need dev skills and background. Example: I use Redis for super-fast loading of configs and themes. An AI won't suggest this optimization unless you know to ask for it. Another example: Cursor + Sonnet 3.5 struggles with code bases with many files and dependencies. It will change things you don't want it to change. Unless you can read code + understand it + know what needs to be changed and not changed, you'll easily run into upper limits of what prompting alone can do. I never mention "artificial intelligence" "AI" "machine learning" or any of these buzzwords once in my copy in my landing page, docs, product, etc. There is no point. Your customers do not care that something has AI in it. AI is not the product. Solving their pain points and problems is the product. AI is simply a tool of many tools like databases, APIs, caching, system design, etc. Early on, I personally onboarded every user through video calls. Time-consuming? Yes. But it helped me deeply understand their pain points and needs. I wasn't selling tech - I was showing them solutions to their problems. Tech stack: NextJS/React/Tailwind/shadcn frontend, Python FastAPI backend. Using Supabase Postgres, Upstash Redis, and Pinecone for different data needs. Hosted on Vercel and Render.com. Customer growth: Started with one alpha tester who saw such great results (especially in driving e-commerce sales) that he insisted on paying for a full year to keep me motivated. This led to two monthly customers, then a fourth annual customer after I raised prices. My advisor actually pushed me to raise prices again, saying I was undercharging for the value provided. I have settled on my final pricing now. I am learning so much. Traditionally, I have a software development and product management background. I am weak in sales and marketing. Building that app, designing the architecture, talking to customers, etc, these are all my strong suits. I enjoy doing it too. But now I need to improve on my ability to market the startup and really start learning things like SEO, content marketing, cold outreach, etc. I enjoying learning new skills. Happy to answer any questions about the journey so far!

The Evolution of Financial Technology: How CAs Are Embracing the Digital Age
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The Evolution of Financial Technology: How CAs Are Embracing the Digital Age

The Evolution of Financial Technology: How CAs Are Embracing the Digital Age Introduction In an era characterized by rapid technological advancements, the field of finance is undergoing a transformative journey. The emergence of financial technology, or fintech, is reshaping the way businesses manage their finances, and Chartered Accountants (CAs) are at the forefront of this evolution. In this blog post, we'll explore how CAs are embracing fintech and leveraging its potential to enhance financial management, analysis, and advisory services. Fintech's Impact on Financial Services Fintech encompasses a wide range of technologies that leverage data analytics, artificial intelligence, blockchain, and automation to improve financial services. For CAs, this means new tools to streamline processes, enhance decision-making, and offer innovative solutions to clients. Automation of Routine Tasks CAs are increasingly using automation tools to handle repetitive tasks such as data entry, reconciliations, and transaction processing. This not only reduces the risk of human error but also frees up CAs to focus on higher-value tasks like strategic planning and analysis. Advanced Data Analytics Data analytics tools enable CAs to extract meaningful insights from large volumes of financial data. These insights can help businesses identify trends, anticipate risks, and make informed decisions to drive growth. Real-Time Financial Reporting Fintech enables CAs to provide clients with real-time financial reporting, giving businesses immediate access to critical information. This enhances transparency and empowers business owners to respond quickly to changing market conditions. Enhancing Audit Efficiency Fintech tools are revolutionizing the audit process. CAs can use AI-powered algorithms to analyze vast amounts of data, detect anomalies, and identify potential instances of fraud more efficiently. Personalized Financial Planning CAs can leverage fintech to offer personalized financial planning services. With access to detailed financial data, CAs can create tailored strategies that align with a client's unique goals and circumstances. Strengthening Cybersecurity As businesses become more reliant on digital tools, cybersecurity becomes paramount. CAs are playing a critical role in advising clients on cybersecurity measures to protect sensitive financial information. Virtual CFO Services Fintech enables CAs to offer virtual CFO services to startups and small businesses. Through digital platforms, CAs can provide expert financial advice and guidance remotely, making their expertise accessible to a wider range of clients. Embracing Blockchain Technology Blockchain's potential for secure and transparent record-keeping is of interest to CAs. They can explore applications in supply chain finance, smart contracts, and even audit trail verification. Continuous Learning in Fintech CAs recognize the importance of staying updated with fintech trends. Many are investing in continuous learning to master the use of new tools and technologies that can optimize their services. Conclusion The integration of fintech into the realm of finance is reshaping the landscape in profound ways. CAs are embracing these technologies to elevate their roles from traditional number-crunchers to strategic advisors, equipped with tools that enhance efficiency, accuracy, and insight. As fintech continues to evolve, CAs will remain pivotal in guiding businesses through the ever-changing financial landscape, leveraging technology to drive growth, innovation, and success. Find the top verified CA in your City Feel free to let me know if you'd like more blogs on different topics or if you have specific requirements for the content.

Seeking Feedback: Would a No-Code AI Solution Benefit Your Business?
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Seeking Feedback: Would a No-Code AI Solution Benefit Your Business?

Hi, fellow small business owners. I'm currently working on an AI startup, with the goal of providing small businesses a seamless and intuitive way to integrate AI into operations without the need for any coding or tech expertise. We're designing an auto machine learning application that's user-friendly and tailored to the unique needs of small businesses. Before we scale, I would really appreciate any insights and feedback. Here are a few questions that would be helpful to get answers to: Pain Points: Are there specific tasks or processes in your operations that you think could be automated or enhanced using AI? This could be anything from customer service chatbots, inventory management, sales forecasting, or anything else you might think of. Features: What features would you want in a no-code AI solution? Perhaps easy integration with existing software? Drag-and-drop model training? Pre-built models for common tasks? Training & Support: How important would training and support be for you in implementing and using an AI solution? Would you prefer video tutorials, live-chat support, or hands-on workshops? Pricing: Would you be willing to invest in such a tool? If so, what would be a reasonable price point for you? We're considering a tiered model based on usage, with a potential starting point of $X/month. Does that sound feasible? Trial Period: Would a free trial period be beneficial for you? How long would you need to assess the tool's impact on your business? Data Concerns: How comfortable are you with sharing data with an AI application? What privacy and security measures would make you feel at ease? Your feedback is really useful. We're building this solution with you in mind, and your insights will guide the next steps. In appreciation for your time and input, we're offering a special discount for early adopters from this community once we launch. Just drop a comment below, and I'll make sure to get in touch when we are ready. Many Thanks, Chris Parker

The Future of AI in eCommerce Marketing: What to Expect 🚀
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McFlyAdsThis week

The Future of AI in eCommerce Marketing: What to Expect 🚀

Hey Reddit community! As we dive deeper into 2025, the integration of AI in eCommerce marketing is becoming more sophisticated and impactful. Here’s a look at where AI is headed and how it's revolutionizing the industry: Personalized Shopping Experiences: AI is enhancing personalization by analyzing consumer behavior and preferences, allowing retailers to offer tailored recommendations and promotions. This not only boosts customer satisfaction but also increases conversion rates. Chatbots and Virtual Assistants: AI-powered chatbots are becoming more intuitive and capable of handling complex queries, providing 24/7 customer support, and improving overall user experience. They’re a game-changer for eCommerce businesses looking to enhance customer engagement. Predictive Analytics: With AI, businesses can leverage predictive analytics to forecast trends, optimize inventory, and refine marketing strategies. This helps in making data-driven decisions that align with consumer demands and market dynamics. Automated Content Creation: AI tools are being used to generate product descriptions, social media posts, and even ad copy. This automation saves time and ensures consistency across marketing channels. Visual and Voice Search: AI is powering visual and voice search capabilities, making it easier for consumers to find products using images or voice commands. This technology is set to transform how users interact with eCommerce platforms. Fraud Detection: AI algorithms are improving fraud detection by analyzing transaction patterns and identifying anomalies. This is crucial for maintaining trust and security in online shopping. As AI continues to evolve, it will undoubtedly reshape the eCommerce landscape, offering new opportunities for innovation and growth. What are your thoughts on the future of AI in eCommerce marketing? Let's discuss!

Restarting My Agency / Compared To Full Time Corporate
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nomadpaddyThis week

Restarting My Agency / Compared To Full Time Corporate

I’m currently thinking about going back to consulting / agency work compared to my current tech job I have. Over a year ago I signed this tech client and they wanted more and more from me which ended up becoming a full time role. At the time, the challenge excited me as it was working on a very large project on a global scale, competing with some of the biggest brands in the world. I was making good money before working in my agency and consulting with lots of different brands on their paid media, websites and e-commerce. I have a healthy package where I’m at at the moment but want more. Working with different clients always created curiosity, no day was the same and that what I loved about it. So now I’m considering going to back to starting the business and working with clients again. My question is: What do businesses ACTUALLY want? Everyone wants great roas and an amazing site but what are core things people are looking for in a growth partner / agency? I’m thinking of relaunching with three pillars in mind: Digital (Paid Media, Lead Gen, Web Dev) AI implementation as a lot of businesses don’t know how to leverage AI completely for cost saving and efficiencies. Content (Video, SEO, Content Writing) for modern day ranking I’m currently rebuilding my pitch deck and thought I would ask the question here before I go back to my network and start opening up conversations again. Would love to hear people’s thoughts in addition to anyone that’s done the same?

I spent 6 months on building a web product, and got zero users. Here is my story.
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GDbuildsGDThis week

I spent 6 months on building a web product, and got zero users. Here is my story.

Edit Thank you all so much for your time reading my story. Your support, feedback, criticism, and skepticism; all helped me a lot, and I couldn't appreciate it enough \^\_\^ I have stuff to post on Reddit very rarely, but I share how my project is going on, random stuff, and memes on X. Just in case few might want to keep in touch 👀 TL;DR I spent 6 months on a tool that currently has 0 users. Below is what I learned during my journey, sharing because I believe most mistakes are easily avoidable. Do not overestimate your product and assume it will be an exception to fundamental principles. Principles are there for a reason. Always look for validation before you start. Avoid building products with a low money-to-effort ratio/in very competitive fields. Unless you have the means, you probably won't make it. Pick a problem space, pick your target audience, and talk to them before thinking about a solution. Identify and match their pain points. Only then should you think of a solution. If people are not overly excited or willing to pay in advance for a discounted price, it might be a sign to rethink. Sell one and only one feature at a time. Avoid everything else. If people don't pay for that one core feature, no secondary feature will change their mind. Always spend twice as much time marketing as you do building. You will not get users if they don't know it exists. Define success metrics ("1000 users in 3 months" or "$6000 in the account at the end of 6 months") before you start. If you don't meet them, strongly consider quitting the project. If you can't get enough users to keep going, nothing else matters. VALIDATION, VALIDATION, VALIDATION. Success is not random, but most of our first products will not make a success story. Know when to admit failure, and move on. Even if a product of yours doesn't succeed, what you learned during its journey will turn out to be invaluable for your future. My story So, this is the story of a product that I’ve been working on for the last 6 months. As it's the first product I’ve ever built, after watching you all from the sidelines, I have learned a lot, made many mistakes, and did only a few things right. Just sharing what I’ve learned and some insights from my journey so far. I hope that this post will help you avoid the mistakes I made — most of which I consider easily avoidable — while you enjoy reading it, and get to know me a little bit more 🤓. A slow start after many years Summ isn’t the first product I really wanted to build. Lacking enough dev skills to even get started was a huge blocker for so many years. In fact, the first product I would’ve LOVED to build was a smart personal shopping assistant. I had this idea 4 years ago; but with no GPT, no coding skills, no technical co-founder, I didn’t have the means to make it happen. I still do not know if such a tool exists and is good enough. All I wanted was a tool that could make data-based predictions about when to buy stuff (“buy a new toothpaste every three months”) and suggest physical products that I might need or be strongly interested in. AFAIK, Amazon famously still struggles with the second one. Fast-forward a few years, I learned the very basics of HTML, CSS, and Vanilla JS. Still was not there to build a product; but good enough to code my design portfolio from scratch. Yet, I couldn’t imagine myself building a product using Vanilla JS. I really hated it, I really sucked at it. So, back to tutorial hell, and to learn about this framework I just heard about: React.React introduced so many new concepts to me. “Thinking in React” is a phrase we heard a lot, and with quite good reasons. After some time, I was able to build very basic tutorial apps, both in React, and React Native; but I have to say that I really hated coding for mobile. At this point, I was already a fan of productivity apps, and had a concept for a time management assistant app in my design portfolio. So, why not build one? Surely, it must be easy, since every coding tutorial starts with a todo app. ❌ WRONG! Building a basic todo app is easy enough, but building one good enough for a place in the market was a challenge I took and failed. I wasted one month on that until I abandoned the project for good. Even if I continued working on it, as the productivity landscape is overly competitive, I wouldn’t be able to make enough money to cover costs, assuming I make any. Since I was (and still am) in between jobs, I decided to abandon the project. 👉 What I learned: Do not start projects with a low ratio of money to effort and time. Example: Even if I get 500 monthly users, 200 of which are paid users (unrealistically high number), assuming an average subscription fee of $5/m (such apps are quite cheap, mostly due to the high competition), it would make me around $1000 minus any occurring costs. Any founder with a product that has 500 active users should make more. Even if it was relatively successful, due to the high competition, I wouldn’t make any meaningful money. PS: I use Todoist today. Due to local pricing, I pay less than $2/m. There is no way I could beat this competitive pricing, let alone the app itself. But, somehow, with a project that wasn’t even functional — let alone being an MVP — I made my first Wi-Fi money: Someone decided that the domain I preemptively purchased is worth something. By this point, I had already abandoned the project, certainly wasn’t going to renew the domain, was looking for a FT job, and a new project that I could work on. And out of nowhere, someone hands me some free money — who am I not to take it? Of course, I took it. The domain is still unused, no idea why 🤔. Ngl, I still hate the fact that my first Wi-Fi money came from this. A new idea worth pursuing? Fast-forward some weeks now. Around March, I got this crazy idea of building an email productivity tool. We all use emails, yet we all hate them. So, this must be fixed. Everyone uses emails, in fact everyone HAS TO use emails. So, I just needed to build a tool and wait for people to come. This was all, really. After all, the problem space is huge, there is enough room for another product, everyone uses emails, no need for any further validation, right? ❌ WRONG ONCE AGAIN! We all hear from the greatest in the startup landscape that we must validate our ideas with real people, yet at least some of us (guilty here 🥸) think that our product will be hugely successful and prove them to be an exception. Few might, but most are not. I certainly wasn't. 👉 Lesson learned: Always validate your ideas with real people. Ask them how much they’d pay for such a tool (not if they would). Much better if they are willing to pay upfront for a discount, etc. But even this comes later, keep reading. I think the difference between “How much” and “If” is huge for two reasons: (1) By asking them for “How much”, you force them to think in a more realistic setting. (2) You will have a more realistic idea on your profit margins. Based on my competitive analysis, I already had a solution in my mind to improve our email usage standards and email productivity (huge mistake), but I did my best to learn about their problems regarding those without pushing the idea too hard. The idea is this: Generate concise email summaries with suggested actions, combine them into one email, and send it at their preferred times. Save as much as time the AI you end up with allows. After all, everyone loves to save time. So, what kind of validation did I seek for? Talked with only a few people around me about this crazy, internet-breaking idea. The responses I got were, now I see, mediocre; no one got excited about it, just said things along the lines of “Cool idea, OK”. So, any reasonable person in this situation would think “Okay, not might not be working”, right? Well, I did not. I assumed that they were the wrong audience for this product, and there was this magical land of user segments waiting eagerly for my product, yet unknowingly. To this day, I still have not reached this magical place. Perhaps, it didn’t exist in the first place. If I cannot find it, whether it exists or not doesn’t matter. I am certainly searching for it. 👉 What I should have done: Once I decide on a problem space (time management, email productivity, etc.), I should decide on my potential user segments, people who I plan to sell my product to. Then I should go talk to those people, ask them about their pains, then get to the problem-solving/ideation phase only later. ❗️ VALIDATION COMES FROM THE REALITY OUTSIDE. What validation looks like might change from product to product; but what invalidation looks like is more or less the same for every product. Nico Jeannen told me yesterday “validation = money in the account” on Twitter. This is the ultimate form of validation your product could get. If your product doesn’t make any money, then something is invalidated by reality: Your product, you, your idea, who knows? So, at this point, I knew a little bit of Python from spending some time in tutorial hell a few years ago, some HTML/CSS/JS, barely enough React to build a working app. React could work for this project, but I needed easy-to-implement server interactivity. Luckily, around this time, I got to know about this new gen of indie hackers, and learned (but didn’t truly understand) about their approach to indie hacking, and this library called Nextjs. How good Next.js still blows my mind. So, I was back to tutorial hell once again. But, this time, with a promise to myself: This is the last time I would visit tutorial hell. Time to start building this "ground-breaking idea" Learning the fundamentals of Next.js was easier than learning of React unsurprisingly. Yet, the first time I managed to run server actions on Next.js was one of the rarest moments that completely blew my mind. To this day, I reject the idea that it is something else than pure magic under its hood. Did I absolutely need Nextjs for this project though? I do not think so. Did it save me lots of time? Absolutely. Furthermore, learning Nextjs will certainly be quite helpful for other projects that I will be tackling in the future. Already got a few ideas that might be worth pursuing in the head in case I decide to abandon Summ in the future. Fast-forward few weeks again: So, at this stage, I had a barely working MVP-like product. Since the very beginning, I spent every free hour (and more) on this project as speed is essential. But, I am not so sure it was worth it to overwork in retrospect. Yet, I know I couldn’t help myself. Everything is going kinda smooth, so what’s the worst thing that could ever happen? Well, both Apple and Google announced their AIs (Apple Intelligence and Google Gemini, respectively) will have email summarization features for their products. Summarizing singular emails is no big deal, after all there were already so many similar products in the market. I still think that what truly matters is a frictionless user experience, and this is why I built this product in a certain way: You spend less than a few minutes setting up your account, and you get to enjoy your email summaries, without ever visiting its website again. This is still a very cool concept I really like a lot. So, at this point: I had no other idea that could be pursued, already spent too much time on this project. Do I quit or not? This was the question. Of course not. I just have to launch this product as quickly as possible. So, I did something right, a quite rare occurrence I might say: Re-planned my product, dropped everything secondary to the core feature immediately (save time on reading emails), tried launching it asap. 👉 Insight: Sell only one core feature at one time. Drop anything secondary to this core feature. Well, my primary occupation is product design. So one would expect that a product I build must have stellar design. I considered any considerable time spent on design at this stage would be simply wasted. I still think this is both true and wrong: True, because if your product’s core benefits suck, no one will care about your design. False, because if your design looks amateurish, no one will trust you and your product. So, I always targeted an average level design with it and the way this tool works made it quite easy as I had to design only 2 primary pages: Landing page and user portal (which has only settings and analytics pages). However, even though I knew spending time on design was not worth much of my time, I got a bit “greedy”: In fact, I redesigned those pages three times, and still ended up with a so-so design that I am not proud of. 👉 What I would do differently: Unless absolutely necessary, only one iteration per stage as long as it works. This, in my mind, applies to everything. If your product’s A feature works, then no need to rewrite it from scratch for any reason, or even refactor it. When your product becomes a success, and you absolutely need that part of your codebase to be written, do so, but only then. Ready to launch, now is th etime for some marketing, right? By July 26, I already had a “launchable” product that barely works (I marked this date on a Notion docs, this is how I know). Yet, I had spent almost no time on marketing, sales, whatever. After all, “You build and they will come”. Did I know that I needed marketing? Of course I did, but knowingly didn’t. Why, you might ask. Well, from my perspective, it had to be a dev-heavy product; meaning that you spend most of your time on developing it, mostly coding skills. But, this is simply wrong. As a rule of thumb, as noted by one of the greatests, Marc Louvion, you should spend at least twice of the building time on marketing. ❗️ Time spent on building \* 2 people don’t know your product > they don’t use your product > you don’t get users > you don’t make money Easy as that. Following the same reasoning, a slightly different approach to planning a project is possible. Determine an approximate time to complete the project with a high level project plan. Let’s say 6 months. By the reasoning above, 2 months should go into building, and 4 into marketing. If you need 4 months for building instead of 2, then you need 8 months of marketing, which makes the time to complete the project 12 months. If you don’t have that much time, then quit the project. When does a project count as completed? Well, in reality, never. But, I think we have to define success conditions even before we start for indie projects and startups; so we know when to quit when they are not met. A success condition could look like “Make $6000 in 12 months” or “Have 3000 users in 6 months”. It all depends on the project. But, once you set it, it should be set in stone: You don’t change it unless absolutely necessary. I suspect there are few principles that make a solopreneur successful; and knowing when to quit and when to continue is definitely one of them. Marc Louvion is famously known for his success, but he got there after failing so many projects. To my knowledge, the same applies to Nico Jeannen, Pieter Levels, or almost everyone as well. ❗️ Determining when to continue even before you start will definitely help in the long run. A half-aed launch Time-leap again. Around mid August, I “soft launched” my product. By soft launch, I mean lazy marketing. Just tweeting about it, posting it on free directories. Did I get any traffic? Surely I did. Did I get any users? Nope. Only after this time, it hit me: “Either something is wrong with me, or with this product” Marketing might be a much bigger factor for a project’s success after all. Even though I get some traffic, not convincing enough for people to sign up even for a free trial. The product was still perfect in my eyes at the time (well, still is ^(\_),) so the right people are not finding my product, I thought. Then, a question that I should have been asking at the very first place, one that could prevent all these, comes to my mind: “How do even people search for such tools?” If we are to consider this whole journey of me and my so-far-failed product to be an already destined failure, one metric suffices to show why. Search volume: 30. Even if people have such a pain point, they are not looking for email summaries. So, almost no organic traffic coming from Google. But, as a person who did zero marketing on this or any product, who has zero marketing knowledge, who doesn’t have an audience on social media, there is not much I could do. Finally, it was time to give up. Or not… In my eyes, the most important element that makes a founder (solo or not) successful (this, I am not by any means) is to solve problems. ❗️ So, the problem was this: “People are not finding my product by organic search” How do I make sure I get some organic traffic and gets more visibility? Learn digital marketing and SEO as much as I can within very limited time. Thankfully, without spending much time, I came across Neil Patel's YT channel, and as I said many times, it is an absolute gold mine. I learned a lot, especially about the fundamentals, and surely it will be fruitful; but there is no magic trick that could make people visit your website. SEO certainly helps, but only when people are looking for your keywords. However, it is truly a magical solution to get in touch with REAL people that are in your user segments: 👉 Understand your pains, understand their problems, help them to solve them via building products. I did not do this so far, have to admit. But, in case you would like to have a chat about your email usage, and email productivity, just get in touch; I’d be delighted to hear about them. Getting ready for a ProductHunt launch The date was Sept 1. And I unlocked an impossible achievement: Running out of Supabase’s free plan’s Egres limit while having zero users. I was already considering moving out of their Cloud server and managing a Supabase CLI service on my Hetzner VPS for some time; but never ever suspected that I would have to do this quickly. The cheapest plan Supabase offers is $25/month; yet, at that point, I am in between jobs for such a long time, basically broke, and could barely afford that price. One or two months could be okay, but why pay for it if I will eventually move out of their Cloud service? So, instead of paying $25, I spent two days migrating out of Supabase Cloud. Worth my time? Definitely not. But, when you are broke, you gotta do stupid things. This was the first time that I felt lucky to have zero users: I have no idea how I would manage this migration if I had any. I think this is one of the core tenets of an indie hacker: Controlling their own environment. I can’t remember whose quote this is, but I suspect it was Naval: Entrepreneurs have an almost pathological need to control their own fate. They will take any suffering if they can be in charge of their destiny, and not have it in somebody else’s hands. What’s truly scary is, at least in my case, we make people around us suffer at the expense of our attempting to control our own fates. I know this period has been quite hard on my wife as well, as I neglected her quite a bit, but sadly, I know that this will happen again. It is something that I can barely help with. Still, so sorry. After working the last two weeks on a ProductHunt Launch, I finally launched it this Tuesday. Zero ranking, zero new users, but 36 kind people upvoted my product, and many commented and provided invaluable feedback. I couldn't be more grateful for each one of them 🙏. Considering all these, what lies in the future of Summ though? I have no idea, to be honest. On one hand, I have zero users, have no job, no income. So, I need a way to make money asap. On the other hand, the whole idea of it revolves around one core premise (not an assumption) that I am not so willing to share; and I couldn’t have more trust in it. This might not be the best iteration of it, however I certainly believe that email usage is one of the best problem spaces one could work on. 👉 But, one thing is for certain: I need to get in touch with people, and talk with them about this product I built so far. In fact, this is the only item on my agenda. Nothing else will save my brainchild <3. Below are some other insights and notes that I got during my journey; as they do not 100% fit into this story, I think it is more suitable to list them here. I hope you enjoyed reading this. Give Summ a try, it comes with a generous free trial, no credit card required. Some additional notes and insights: Project planning is one of the most underestimated skills for solopreneurs. It saves you enormous time, and helps you to keep your focus up. Building B2C products beats building B2B products. Businesses are very willing to pay big bucks if your product helps them. On the other hand, spending a few hours per user who would pay $5/m probably is not worth your time. It doesn’t matter how brilliant your product is if no one uses it. If you cannot sell a product in a certain category/niche (or do not know how to sell it), it might be a good idea not to start a project in it. Going after new ideas and ventures is quite risky, especially if you don’t know how to market it. On the other hand, an already established category means that there is already demand. Whether this demand is sufficient or not is another issue. As long as there is enough demand for your product to fit in, any category/niche is good. Some might be better, some might be worse. Unless you are going hardcore B2B, you will need people to find your product by means of organic search. Always conduct thorough keyword research as soon as possible.

Nuts and bolts AI implementation for small business
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Training-Swan-6379This week

Nuts and bolts AI implementation for small business

How can small businesses use AI to increase sales or decrease expenses without massive disruption? One way for us is using AI to process our email history to identify patterns and write personalized messages based on past correspondence. According to legal advice in which I have confidence, email that is personalized for each recipient (and meets other standards) does not need to be opt in. If you disagree - understood - but spam morality is not the topic here. Bottom line - obviously a game changer. Knowing phrases people have used before becoming clients - and all of the possible permutations of those phrases, and detecting where those phrases show up will make our sales and marketing many times more effective for a fraction of the cost. There's a reason big corps. record calls, and now small business can leverage the same technology. We are setting up a process that yields accurate, up to date, comprehensive data for our own business operations. Our clients - who are they and how has their demographic changed over time? To answer this question and for email personalization, we also need access to external data sources e.g. like accurate up to date company demographics. IMO - the leader in company data in the US? THEY SUCK. We found there is no magic fairy who is going to make good data appear for our AI. The process of applying our own proprietary knowledge to code and categorize the data is just as important, and obviously highly sensitive. How do we leverage the AI technologies of companies like Google and Microsoft (or anyone else) without being their bitch? Below is a list of some of the sources of my business's data: Data sources: PST/OST/Other Email data files Microsoft data from Windows/O365 Windows/Linux/Android/IOS application logs and other data Web server logs for the company website. SEO/Analytics Data Google data export Google voice/VOIP logs OneDrive/G drive Other Phone system/cell service logs Other SAAS and in-house application data. Facebook/social media data for company pages. QuickBooks/other accounting systems/business bank account logs POS/Credit card processing systems/PayPal, etc. OSINT to fill in the blanks

Looking for Feedback on this Idea
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Separate-Employer394This week

Looking for Feedback on this Idea

Hey everyone, I’d love some honest feedback on an idea I’ve been working on (currently just in paper). A little about me: I started in hospitality across South America and Asia, then moved into social entrepreneurship in a rural area, and eventually ecommerce using WordPress. Now, I’m deep into programming here in Europe, which I’ve really come to enjoy. So yes, I understand the perspective of businesses, entrepreneurs and programmers.  Back when I had tons of ideas for businesses and optimizing processes, I always hit the same drama: "You need a developer." But hiring one was too expensive or unreliable or shady business practice, and partnering with a programmer, someone I barely knew often felt too risky (I've learned the hard way that partnerships can feel like marriages). Now, as a programmer, I get a lot of requests from small businesses needing help and sometimes with very simple ideas. And while I can do it, I often don’t have the time, so I have to tell them I can't. And when I do have time, I know the cost can be too much for their budget. This got me thinking: What if I created a course to teach business owners just enough programming to solve their own problems? Not to become full time coders, but to gain enough knowledge to build simple tools or, better yet, understand code enough to ask the right questions whether it's to AI or a future developer. The course would focus on programming but talking business language, starting with building more flexible websites, managing your own content and creating custom tools without the limitations of templates or paid widgets. I’m thinking of creating a supportive community where we learn and grow together (maybe using your business as an example), and I’d be available to help along the way, plus I will be adding tools that you could reuse for your business (mostly because you will be able to read it and understand it → that's the goal). Talking about money, I can only tell you will be way more affordable compared to multiple payments in different places. So, does this resonate with you? I’d really appreciate your honest thoughts. Do you feel you have the time to learn or you still prefer looking for a developer? Feel free to share any frustrations or ideas. And if this sounds interesting, write me a PM, and I’ll keep you updated. Thanks for reading. I'm excited to hear what you think! :)

How To Build An AI-Driven Business That Doesn't Suck In 2024 (My Take).
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dojagroupThis week

How To Build An AI-Driven Business That Doesn't Suck In 2024 (My Take).

Hi everyone, this is for those of you wanting a full run through of the formula that scaled our business to around the $100,000 /m mark in less than 18 months. Why am I doing this? Since we started hitting the larger numbers I've been given considerable time back in my day as we elevate ourselves out of scrappy start-up land and have hired a full team. I've always wanted to take this time and pour it into educating others that are following the same path. There's nothing I've loved more in life (at the ripe age of 28) than connecting with other entrepreneurs that are obsessed with the game. Firstly, I want to tell you that this is absolutely possible. The main traits you need are: ➡️ Resilience to work hard around your normal life. ➡️ The willingness to put yourself outside of your comfort zone. ➡️ The awareness to place yourself in a fast-growing market with a great offering. Secondly, I want to tell you that you are probably structuring your day and your approach wrong. Here's why: ➡️ Your operations are the back-bone of your business. When correctly organised you should be in a pattern of understanding a new task, systemising it then automating it. If you do this you will build your business like you would build a lego house. ➡️ You should be setting goals that filter down into daily actions, that are being recorded and tracked so you can improve weekly. ➡️ You should start to get a good grip of cloud software like Hubspot, Trello, Notion & Slack for the various levers you need to pull inside your business. I'm seriously passionate about this and I've recorded my first Youtube video that breaks down our entire front-end and back-end funnel for our business - if you're looking for some no-nonsense education I'd equally love some feedback. You can check out the video here. https://www.youtube.com/watch?v=X6Mq9Xu9EK8 Apart from that, please ask me anything. I'm the Managing Director of doja, a team of 9 based in the UK with a team of 5 offshore. I'd love to connect with other entrepreneurs either ahead of me or following a similar path. I can answer questions on Strategy, R&D, Product, Marketing, Lead Generation, Business Development, Commerical, Onboard & Delivery funnels, as well as extensive knowledge about what's breaking through with the latest technology for small businesses.

How do you learn details / potential strategy about technically important new laws in the jurisdictions you operate in?
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friendofherschelThis week

How do you learn details / potential strategy about technically important new laws in the jurisdictions you operate in?

I am reading “The Entrepreneur’s Guide to Law and Strategy” and it’s really fantastic so far about giving a pretty great overview of these aspects of business. It was published by Wiley (a reputable textbook publisher) in 2018. In one chapter, the authors go into the EU’s “right to be forgotten” and it got me thinking about complying with laws like that. Unfortunately, the latest edition of the book is still nearly 7 years old and written pre-COVID, pre-genAI, pre-social network and privacy pushback, etc. I assume every time a new law comes out that can impact my business (say, a random privacy law in California) that businesses aren’t just telling their lawyers “use any amount of hours you need to in order to read the San Jose papers every day and then write me a one paragraph brief with an outline and potential changes needed to our business, also all the other papers across the world”. They’d spend a fortune. There has to be something I’m missing. Is there a law review for business that I should be following? I operate in the US only at this time. A more technical newspaper (I take WSJ, but it’s not technical enough for this sort of thing. It might give the “what”, but won’t give a small business owner “what to do with it”)? PS: I’m the type of person who read every word of my mortgage. I am aware the answer might be “don’t worry about it”. But I do worry about it, and am trying to fix that. For example, the insanely popular new lawsuits about website accessibility. I want to avoid things (essentially low hanging lawsuit fruit) like that before they happen to me.

I spent 6 months on building a web product, and got zero users. Here is my story.
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GDbuildsGDThis week

I spent 6 months on building a web product, and got zero users. Here is my story.

Edit Thank you all so much for your time reading my story. Your support, feedback, criticism, and skepticism; all helped me a lot, and I couldn't appreciate it enough \^\_\^ I have stuff to post on Reddit very rarely, but I share how my project is going on, random stuff, and memes on X. Just in case few might want to keep in touch 👀 TL;DR I spent 6 months on a tool that currently has 0 users. Below is what I learned during my journey, sharing because I believe most mistakes are easily avoidable. Do not overestimate your product and assume it will be an exception to fundamental principles. Principles are there for a reason. Always look for validation before you start. Avoid building products with a low money-to-effort ratio/in very competitive fields. Unless you have the means, you probably won't make it. Pick a problem space, pick your target audience, and talk to them before thinking about a solution. Identify and match their pain points. Only then should you think of a solution. If people are not overly excited or willing to pay in advance for a discounted price, it might be a sign to rethink. Sell one and only one feature at a time. Avoid everything else. If people don't pay for that one core feature, no secondary feature will change their mind. Always spend twice as much time marketing as you do building. You will not get users if they don't know it exists. Define success metrics ("1000 users in 3 months" or "$6000 in the account at the end of 6 months") before you start. If you don't meet them, strongly consider quitting the project. If you can't get enough users to keep going, nothing else matters. VALIDATION, VALIDATION, VALIDATION. Success is not random, but most of our first products will not make a success story. Know when to admit failure, and move on. Even if a product of yours doesn't succeed, what you learned during its journey will turn out to be invaluable for your future. My story So, this is the story of a product that I’ve been working on for the last 6 months. As it's the first product I’ve ever built, after watching you all from the sidelines, I have learned a lot, made many mistakes, and did only a few things right. Just sharing what I’ve learned and some insights from my journey so far. I hope that this post will help you avoid the mistakes I made — most of which I consider easily avoidable — while you enjoy reading it, and get to know me a little bit more 🤓. A slow start after many years Summ isn’t the first product I really wanted to build. Lacking enough dev skills to even get started was a huge blocker for so many years. In fact, the first product I would’ve LOVED to build was a smart personal shopping assistant. I had this idea 4 years ago; but with no GPT, no coding skills, no technical co-founder, I didn’t have the means to make it happen. I still do not know if such a tool exists and is good enough. All I wanted was a tool that could make data-based predictions about when to buy stuff (“buy a new toothpaste every three months”) and suggest physical products that I might need or be strongly interested in. AFAIK, Amazon famously still struggles with the second one. Fast-forward a few years, I learned the very basics of HTML, CSS, and Vanilla JS. Still was not there to build a product; but good enough to code my design portfolio from scratch. Yet, I couldn’t imagine myself building a product using Vanilla JS. I really hated it, I really sucked at it. So, back to tutorial hell, and to learn about this framework I just heard about: React.React introduced so many new concepts to me. “Thinking in React” is a phrase we heard a lot, and with quite good reasons. After some time, I was able to build very basic tutorial apps, both in React, and React Native; but I have to say that I really hated coding for mobile. At this point, I was already a fan of productivity apps, and had a concept for a time management assistant app in my design portfolio. So, why not build one? Surely, it must be easy, since every coding tutorial starts with a todo app. ❌ WRONG! Building a basic todo app is easy enough, but building one good enough for a place in the market was a challenge I took and failed. I wasted one month on that until I abandoned the project for good. Even if I continued working on it, as the productivity landscape is overly competitive, I wouldn’t be able to make enough money to cover costs, assuming I make any. Since I was (and still am) in between jobs, I decided to abandon the project. 👉 What I learned: Do not start projects with a low ratio of money to effort and time. Example: Even if I get 500 monthly users, 200 of which are paid users (unrealistically high number), assuming an average subscription fee of $5/m (such apps are quite cheap, mostly due to the high competition), it would make me around $1000 minus any occurring costs. Any founder with a product that has 500 active users should make more. Even if it was relatively successful, due to the high competition, I wouldn’t make any meaningful money. PS: I use Todoist today. Due to local pricing, I pay less than $2/m. There is no way I could beat this competitive pricing, let alone the app itself. But, somehow, with a project that wasn’t even functional — let alone being an MVP — I made my first Wi-Fi money: Someone decided that the domain I preemptively purchased is worth something. By this point, I had already abandoned the project, certainly wasn’t going to renew the domain, was looking for a FT job, and a new project that I could work on. And out of nowhere, someone hands me some free money — who am I not to take it? Of course, I took it. The domain is still unused, no idea why 🤔. Ngl, I still hate the fact that my first Wi-Fi money came from this. A new idea worth pursuing? Fast-forward some weeks now. Around March, I got this crazy idea of building an email productivity tool. We all use emails, yet we all hate them. So, this must be fixed. Everyone uses emails, in fact everyone HAS TO use emails. So, I just needed to build a tool and wait for people to come. This was all, really. After all, the problem space is huge, there is enough room for another product, everyone uses emails, no need for any further validation, right? ❌ WRONG ONCE AGAIN! We all hear from the greatest in the startup landscape that we must validate our ideas with real people, yet at least some of us (guilty here 🥸) think that our product will be hugely successful and prove them to be an exception. Few might, but most are not. I certainly wasn't. 👉 Lesson learned: Always validate your ideas with real people. Ask them how much they’d pay for such a tool (not if they would). Much better if they are willing to pay upfront for a discount, etc. But even this comes later, keep reading. I think the difference between “How much” and “If” is huge for two reasons: (1) By asking them for “How much”, you force them to think in a more realistic setting. (2) You will have a more realistic idea on your profit margins. Based on my competitive analysis, I already had a solution in my mind to improve our email usage standards and email productivity (huge mistake), but I did my best to learn about their problems regarding those without pushing the idea too hard. The idea is this: Generate concise email summaries with suggested actions, combine them into one email, and send it at their preferred times. Save as much as time the AI you end up with allows. After all, everyone loves to save time. So, what kind of validation did I seek for? Talked with only a few people around me about this crazy, internet-breaking idea. The responses I got were, now I see, mediocre; no one got excited about it, just said things along the lines of “Cool idea, OK”. So, any reasonable person in this situation would think “Okay, not might not be working”, right? Well, I did not. I assumed that they were the wrong audience for this product, and there was this magical land of user segments waiting eagerly for my product, yet unknowingly. To this day, I still have not reached this magical place. Perhaps, it didn’t exist in the first place. If I cannot find it, whether it exists or not doesn’t matter. I am certainly searching for it. 👉 What I should have done: Once I decide on a problem space (time management, email productivity, etc.), I should decide on my potential user segments, people who I plan to sell my product to. Then I should go talk to those people, ask them about their pains, then get to the problem-solving/ideation phase only later. ❗️ VALIDATION COMES FROM THE REALITY OUTSIDE. What validation looks like might change from product to product; but what invalidation looks like is more or less the same for every product. Nico Jeannen told me yesterday “validation = money in the account” on Twitter. This is the ultimate form of validation your product could get. If your product doesn’t make any money, then something is invalidated by reality: Your product, you, your idea, who knows? So, at this point, I knew a little bit of Python from spending some time in tutorial hell a few years ago, some HTML/CSS/JS, barely enough React to build a working app. React could work for this project, but I needed easy-to-implement server interactivity. Luckily, around this time, I got to know about this new gen of indie hackers, and learned (but didn’t truly understand) about their approach to indie hacking, and this library called Nextjs. How good Next.js still blows my mind. So, I was back to tutorial hell once again. But, this time, with a promise to myself: This is the last time I would visit tutorial hell. Time to start building this "ground-breaking idea" Learning the fundamentals of Next.js was easier than learning of React unsurprisingly. Yet, the first time I managed to run server actions on Next.js was one of the rarest moments that completely blew my mind. To this day, I reject the idea that it is something else than pure magic under its hood. Did I absolutely need Nextjs for this project though? I do not think so. Did it save me lots of time? Absolutely. Furthermore, learning Nextjs will certainly be quite helpful for other projects that I will be tackling in the future. Already got a few ideas that might be worth pursuing in the head in case I decide to abandon Summ in the future. Fast-forward few weeks again: So, at this stage, I had a barely working MVP-like product. Since the very beginning, I spent every free hour (and more) on this project as speed is essential. But, I am not so sure it was worth it to overwork in retrospect. Yet, I know I couldn’t help myself. Everything is going kinda smooth, so what’s the worst thing that could ever happen? Well, both Apple and Google announced their AIs (Apple Intelligence and Google Gemini, respectively) will have email summarization features for their products. Summarizing singular emails is no big deal, after all there were already so many similar products in the market. I still think that what truly matters is a frictionless user experience, and this is why I built this product in a certain way: You spend less than a few minutes setting up your account, and you get to enjoy your email summaries, without ever visiting its website again. This is still a very cool concept I really like a lot. So, at this point: I had no other idea that could be pursued, already spent too much time on this project. Do I quit or not? This was the question. Of course not. I just have to launch this product as quickly as possible. So, I did something right, a quite rare occurrence I might say: Re-planned my product, dropped everything secondary to the core feature immediately (save time on reading emails), tried launching it asap. 👉 Insight: Sell only one core feature at one time. Drop anything secondary to this core feature. Well, my primary occupation is product design. So one would expect that a product I build must have stellar design. I considered any considerable time spent on design at this stage would be simply wasted. I still think this is both true and wrong: True, because if your product’s core benefits suck, no one will care about your design. False, because if your design looks amateurish, no one will trust you and your product. So, I always targeted an average level design with it and the way this tool works made it quite easy as I had to design only 2 primary pages: Landing page and user portal (which has only settings and analytics pages). However, even though I knew spending time on design was not worth much of my time, I got a bit “greedy”: In fact, I redesigned those pages three times, and still ended up with a so-so design that I am not proud of. 👉 What I would do differently: Unless absolutely necessary, only one iteration per stage as long as it works. This, in my mind, applies to everything. If your product’s A feature works, then no need to rewrite it from scratch for any reason, or even refactor it. When your product becomes a success, and you absolutely need that part of your codebase to be written, do so, but only then. Ready to launch, now is th etime for some marketing, right? By July 26, I already had a “launchable” product that barely works (I marked this date on a Notion docs, this is how I know). Yet, I had spent almost no time on marketing, sales, whatever. After all, “You build and they will come”. Did I know that I needed marketing? Of course I did, but knowingly didn’t. Why, you might ask. Well, from my perspective, it had to be a dev-heavy product; meaning that you spend most of your time on developing it, mostly coding skills. But, this is simply wrong. As a rule of thumb, as noted by one of the greatests, Marc Louvion, you should spend at least twice of the building time on marketing. ❗️ Time spent on building \* 2 people don’t know your product > they don’t use your product > you don’t get users > you don’t make money Easy as that. Following the same reasoning, a slightly different approach to planning a project is possible. Determine an approximate time to complete the project with a high level project plan. Let’s say 6 months. By the reasoning above, 2 months should go into building, and 4 into marketing. If you need 4 months for building instead of 2, then you need 8 months of marketing, which makes the time to complete the project 12 months. If you don’t have that much time, then quit the project. When does a project count as completed? Well, in reality, never. But, I think we have to define success conditions even before we start for indie projects and startups; so we know when to quit when they are not met. A success condition could look like “Make $6000 in 12 months” or “Have 3000 users in 6 months”. It all depends on the project. But, once you set it, it should be set in stone: You don’t change it unless absolutely necessary. I suspect there are few principles that make a solopreneur successful; and knowing when to quit and when to continue is definitely one of them. Marc Louvion is famously known for his success, but he got there after failing so many projects. To my knowledge, the same applies to Nico Jeannen, Pieter Levels, or almost everyone as well. ❗️ Determining when to continue even before you start will definitely help in the long run. A half-aed launch Time-leap again. Around mid August, I “soft launched” my product. By soft launch, I mean lazy marketing. Just tweeting about it, posting it on free directories. Did I get any traffic? Surely I did. Did I get any users? Nope. Only after this time, it hit me: “Either something is wrong with me, or with this product” Marketing might be a much bigger factor for a project’s success after all. Even though I get some traffic, not convincing enough for people to sign up even for a free trial. The product was still perfect in my eyes at the time (well, still is ^(\_),) so the right people are not finding my product, I thought. Then, a question that I should have been asking at the very first place, one that could prevent all these, comes to my mind: “How do even people search for such tools?” If we are to consider this whole journey of me and my so-far-failed product to be an already destined failure, one metric suffices to show why. Search volume: 30. Even if people have such a pain point, they are not looking for email summaries. So, almost no organic traffic coming from Google. But, as a person who did zero marketing on this or any product, who has zero marketing knowledge, who doesn’t have an audience on social media, there is not much I could do. Finally, it was time to give up. Or not… In my eyes, the most important element that makes a founder (solo or not) successful (this, I am not by any means) is to solve problems. ❗️ So, the problem was this: “People are not finding my product by organic search” How do I make sure I get some organic traffic and gets more visibility? Learn digital marketing and SEO as much as I can within very limited time. Thankfully, without spending much time, I came across Neil Patel's YT channel, and as I said many times, it is an absolute gold mine. I learned a lot, especially about the fundamentals, and surely it will be fruitful; but there is no magic trick that could make people visit your website. SEO certainly helps, but only when people are looking for your keywords. However, it is truly a magical solution to get in touch with REAL people that are in your user segments: 👉 Understand your pains, understand their problems, help them to solve them via building products. I did not do this so far, have to admit. But, in case you would like to have a chat about your email usage, and email productivity, just get in touch; I’d be delighted to hear about them. Getting ready for a ProductHunt launch The date was Sept 1. And I unlocked an impossible achievement: Running out of Supabase’s free plan’s Egres limit while having zero users. I was already considering moving out of their Cloud server and managing a Supabase CLI service on my Hetzner VPS for some time; but never ever suspected that I would have to do this quickly. The cheapest plan Supabase offers is $25/month; yet, at that point, I am in between jobs for such a long time, basically broke, and could barely afford that price. One or two months could be okay, but why pay for it if I will eventually move out of their Cloud service? So, instead of paying $25, I spent two days migrating out of Supabase Cloud. Worth my time? Definitely not. But, when you are broke, you gotta do stupid things. This was the first time that I felt lucky to have zero users: I have no idea how I would manage this migration if I had any. I think this is one of the core tenets of an indie hacker: Controlling their own environment. I can’t remember whose quote this is, but I suspect it was Naval: Entrepreneurs have an almost pathological need to control their own fate. They will take any suffering if they can be in charge of their destiny, and not have it in somebody else’s hands. What’s truly scary is, at least in my case, we make people around us suffer at the expense of our attempting to control our own fates. I know this period has been quite hard on my wife as well, as I neglected her quite a bit, but sadly, I know that this will happen again. It is something that I can barely help with. Still, so sorry. After working the last two weeks on a ProductHunt Launch, I finally launched it this Tuesday. Zero ranking, zero new users, but 36 kind people upvoted my product, and many commented and provided invaluable feedback. I couldn't be more grateful for each one of them 🙏. Considering all these, what lies in the future of Summ though? I have no idea, to be honest. On one hand, I have zero users, have no job, no income. So, I need a way to make money asap. On the other hand, the whole idea of it revolves around one core premise (not an assumption) that I am not so willing to share; and I couldn’t have more trust in it. This might not be the best iteration of it, however I certainly believe that email usage is one of the best problem spaces one could work on. 👉 But, one thing is for certain: I need to get in touch with people, and talk with them about this product I built so far. In fact, this is the only item on my agenda. Nothing else will save my brainchild <3. Below are some other insights and notes that I got during my journey; as they do not 100% fit into this story, I think it is more suitable to list them here. I hope you enjoyed reading this. Give Summ a try, it comes with a generous free trial, no credit card required. Some additional notes and insights: Project planning is one of the most underestimated skills for solopreneurs. It saves you enormous time, and helps you to keep your focus up. Building B2C products beats building B2B products. Businesses are very willing to pay big bucks if your product helps them. On the other hand, spending a few hours per user who would pay $5/m probably is not worth your time. It doesn’t matter how brilliant your product is if no one uses it. If you cannot sell a product in a certain category/niche (or do not know how to sell it), it might be a good idea not to start a project in it. Going after new ideas and ventures is quite risky, especially if you don’t know how to market it. On the other hand, an already established category means that there is already demand. Whether this demand is sufficient or not is another issue. As long as there is enough demand for your product to fit in, any category/niche is good. Some might be better, some might be worse. Unless you are going hardcore B2B, you will need people to find your product by means of organic search. Always conduct thorough keyword research as soon as possible.

Here’s How Chatbots Can Boost Your Small Business
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smanwerThis week

Here’s How Chatbots Can Boost Your Small Business

Chatbots are the next big thing in the tech world that are meant for business use. Almost every business can benefit from chatbots in one way or the other. They are now everywhere – the fastest rising star are basically computer-operated machines that can play a variety of roles such as customer service representative, social media manager, personal assistant and much more. Virtually every industry is seemingly investing in it. Chatbots became the flavor of the season because of their task management and problem solving skills. This is why companies are aggressively deploying chatbots to their business strategy to make it work right. What are Chatbots – How They Can Benefit Your Small Business? In essence, chatbots are simply a computer program tailor-made to mimic conversations with the help of artificial intelligence (AI). These computer-based programs are capable enough to respond to natural language text and voice inputs in a human way. Chatbots can take over a lot of time consuming tasks, allowing project managers to focus on other important matters and take high level decisions. Chatbots are not just the next big thing for digital and tech brands, small businesses can also get the most out from them. Small businesses should get into chatbots to streamline their routine project management practices and support other business operations – thereby saving budget, time, energy, while improving ROI. If you are not completely getting into it, here are some ways that help you deploy this rising technology in order to boost your small business strategy. Instant Customer Support One of the effective ways small businesses can implement a chatbot is an immediate customer support. If you belong to an industry that offers products and services, chances are you get so many phone calls and emails to educate people. Prior to allowing customers to clog up your inbox with unlimited queries, try using a chatbot that will save your valuable time. You can simply create an immediate customer support presence for customers who engage with your chatbot. Craft answers for all the popular queries so that your project management team can focus on other complex and important issues while chatbots addressing the most commonly asked questions. Moreover, it will add a consistency to your brand voice. You can control the tone and ensure that the chatbot will deliver your crafted messages. Boost Sales Leads Generation Chatbots are not just about sharing or collecting information. They can actually boost sales. But, how? Though they can’t replace your sales and marketing team, they can smartly assist them by being an immediate point of contact. Create an automated conversation for a new visitor and it can directly influence sales. Though chatbots are rising, they will ultimately carry on artificial intelligence that is capable for gathering the data required to curate a specific set of products for customers. For instance, if a user asks the chatbot for blue shirt in cotton, the chatbot can pull items with the particular details for the user. This process is cumulative and when next time the user communicates with the chatbot, it will consider their preferences. Increase Your Business Efficiency Though chatbots can’t perform every business operation, what they can do is eliminate few of the menial but important operations. Consider all the important tasks that your employees need to perform, such as answering customer queries, compiling data for a user, filling out form etc. Most of these tasks are monotonous in nature that allows you to train your chatbot to manage all these repetitive tasks with a low risk and high return of your valuable time. Reducing Cost and Resource Consumption Like any online task management system , chatbots are great to reduce manpower. From performing as a personal assistant to a customer sales representative, you can easily cut down the total number of resources that deal with customer complaints and feedback. You can utilize a chatbot, as it can do this work easily a human would usually do. Read Full article here

The Evolution of Financial Technology: How CAs Are Embracing the Digital Age
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ExpenectThis week

The Evolution of Financial Technology: How CAs Are Embracing the Digital Age

The Evolution of Financial Technology: How CAs Are Embracing the Digital Age Introduction In an era characterized by rapid technological advancements, the field of finance is undergoing a transformative journey. The emergence of financial technology, or fintech, is reshaping the way businesses manage their finances, and Chartered Accountants (CAs) are at the forefront of this evolution. In this blog post, we'll explore how CAs are embracing fintech and leveraging its potential to enhance financial management, analysis, and advisory services. Fintech's Impact on Financial Services Fintech encompasses a wide range of technologies that leverage data analytics, artificial intelligence, blockchain, and automation to improve financial services. For CAs, this means new tools to streamline processes, enhance decision-making, and offer innovative solutions to clients. Automation of Routine Tasks CAs are increasingly using automation tools to handle repetitive tasks such as data entry, reconciliations, and transaction processing. This not only reduces the risk of human error but also frees up CAs to focus on higher-value tasks like strategic planning and analysis. Advanced Data Analytics Data analytics tools enable CAs to extract meaningful insights from large volumes of financial data. These insights can help businesses identify trends, anticipate risks, and make informed decisions to drive growth. Real-Time Financial Reporting Fintech enables CAs to provide clients with real-time financial reporting, giving businesses immediate access to critical information. This enhances transparency and empowers business owners to respond quickly to changing market conditions. Enhancing Audit Efficiency Fintech tools are revolutionizing the audit process. CAs can use AI-powered algorithms to analyze vast amounts of data, detect anomalies, and identify potential instances of fraud more efficiently. Personalized Financial Planning CAs can leverage fintech to offer personalized financial planning services. With access to detailed financial data, CAs can create tailored strategies that align with a client's unique goals and circumstances. Strengthening Cybersecurity As businesses become more reliant on digital tools, cybersecurity becomes paramount. CAs are playing a critical role in advising clients on cybersecurity measures to protect sensitive financial information. Virtual CFO Services Fintech enables CAs to offer virtual CFO services to startups and small businesses. Through digital platforms, CAs can provide expert financial advice and guidance remotely, making their expertise accessible to a wider range of clients. Embracing Blockchain Technology Blockchain's potential for secure and transparent record-keeping is of interest to CAs. They can explore applications in supply chain finance, smart contracts, and even audit trail verification. Continuous Learning in Fintech CAs recognize the importance of staying updated with fintech trends. Many are investing in continuous learning to master the use of new tools and technologies that can optimize their services. Conclusion The integration of fintech into the realm of finance is reshaping the landscape in profound ways. CAs are embracing these technologies to elevate their roles from traditional number-crunchers to strategic advisors, equipped with tools that enhance efficiency, accuracy, and insight. As fintech continues to evolve, CAs will remain pivotal in guiding businesses through the ever-changing financial landscape, leveraging technology to drive growth, innovation, and success. Find the top verified CA in your City Feel free to let me know if you'd like more blogs on different topics or if you have specific requirements for the content.

Looking to streamline and update family business
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JohACNHThis week

Looking to streamline and update family business

Hey r/smallbusiness, I’ve been working at my family’s business for six years now—joined right after college—and I’ve realized that we’re long overdue for an overhaul. I handle advertising sales, and while the business itself is solid, the way we operate is extremely outdated. Without revealing too much, we print about 180 publications, and businesses pay to have their ads featured. As a sales rep, my job includes: Renewing current advertisers Finding new customers and making sales Collecting artwork for ads Gathering billing info Laying out the ad grid with all advertisers The Problem: Everything is still done with pen and paper. We use carbon copy paper to record business details, billing info, and ad costs. One copy goes to the graphic designers, the other to billing. The billing team manually enters everything into QuickBooks, prints invoices, stuffs envelopes, and mails them out. We recently got new software that lets us send invoices via email and text through QuickBooks, which is a step in the right direction, but it’s just a small fix to a much bigger problem. What I Want to Change: Move everything onto an app or website—no more paper. Digitally layout the ad grid instead of doing it manually. (For graphics team) Collect billing info online instead of writing it down. (Obviously to get paid faster and reduce wasted labor) Automate renewal emails instead of calling every single customer. (Save time) Find more efficient ways to generate leads for new business. (Work smarter not harder) Honestly, the company still runs like my grandma set it up in the '90s, and it’s overwhelming trying to figure out where to start. If anyone has been through something similar or has advice on modernizing a business, I’d love to hear your thoughts! Happy to provide more details if needed. I’ve explored some CRMs and AI tools, but I’m sure someone here has better insights or more experience with this than I do. There are other parts of the business that need improvement, but I believe this would be a big step in the right direction. Thanks in advance!

ChatGPT for business automation (incredible new AI)
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MalachiianThis week

ChatGPT for business automation (incredible new AI)

Hey fellow small business owners! I'm curious to know how you would use ChatGPT or other AI automation tools to improve your business. For those who are not aware, recently a new chat AI was made available to the public by OpenAI, called ChatGPT. (same company that did Dall-E) In a tweet Elon Musk wrote that "ChatGPT is scary good. We are not far from dangerously strong AI." It allows anyone (regardless of tech skill) to simply type commands and it will spit out answers. It can also create actual working code. For example most tasks you do in a browser can be automated with a Python script, but it takes time and coding knowledge to create. With ChatGPT you can just tell it what you want and it will create the code! The impact for businesses is insane: 1) Your entire customer service can be easily replaced by chat bots and probably soon by AI that can speak over the phone (google showcased this in 2018, it already exists). 2) you can have the AI automate your sales process, creating a 1-on-1 conversations, at scale. It can probably also improve and optimize it's closing rate over time as it learns more about your customers. 3) It can be used to train your staff. It's really good for 1on1 instruction and teaching because it will go a the students pace and answer questions (compare that to the usual PowerPoint presentation people use) 4) Since it can create code to automate most tasks a human can do in a browser, you can create for example bots that take customer orders and automatically import them to whatever shipping system you use, send customers tracking info etc. (a lot of this stuff is done with software and APIs, but now anyone can create their own, custom solutions) I feel like we hit an inflection point in 2022 with AI and now we are beginning to see some really useful stuff coming out. Am I crazy or are we about to see a massive shift in how we do things?

40% Of SMBs Still Can't Pay Their Rent, Extending High Delinquency From September Into October
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Aegidius25This week

40% Of SMBs Still Can't Pay Their Rent, Extending High Delinquency From September Into October

https://www.alignable.com/forum/q4s-off-to-a-rough-start-40-of-smbs-still-cant-pay-their-rent October 31, 2023: While the federal government reported a surge in economic growth for the U.S. last week, that news doesn't hold true for many small business owners. In fact, in October polling by Alignable, only 12% said their companies are experiencing significant growth this month. Beyond that, Alignable’s October Rent Report, released today, shows that a whopping 40% of SMBs couldn't even pay their October rent in full and on time. This marks the second consecutive month of a 40% rent delinquency rate -- extending 2023's record high from September through October. These findings are based on responses from 4,246 randomly selected small business owners surveyed from 10/1/23 to 10/30/23, as well as input from 44,000+ other respondents over the past year. As the chart below shows, October's SMB rent delinquency rate is 10 percentage points higher than it was in January, reflecting cumulative economic struggles: increased rents, high interest rates, still-stifling inflation, rising labor costs, and revenues that have declined since this time last year. Rent delinquency rates among small businesses during 2023 based on Alignable surveys So, Why's Rent Delinquency At 40% For A 2nd Month? Here’s the current list of problems contributing to two months' worth of the highest delinquency rate 2023 has seen so far: Consumer Spending Declines On Main Street: Quarterly, we ask about customer spending habits at retailers. This month, 45% of independent Mom and Pop Shops said spending has been down over the last 30 days. Some said it was due to more people spending money online with big retailers like Amazon. This figure is quite high, especially considering that back in July, only 24% reported a drop in consumer spending -- 21 percentage points less severe than it is now. Revenue Troubles: 42% are making half or less of the income they generated monthly prior to COVID. For businesses that are less than three years old, this situation is even worse: 53% of this group reports making half or less of what they generated this time last year. High Interest Rates: Over half of all SMB owners polled said the past 19 months of high interest rates have hurt their margins, reduced revenues, and put their expansion plans on hold, as they don't want to apply for loans. Increased Rent Prices: 50% say they’re being charged more for rent now than they were six months ago, with 15% saying rent has increased by 20% or more. At present, only 37% of pre-COVID businesses have recovered financially from the pandemic era, leaving 63% still striving to make up for time they lost due to COVID, inflationary pressures, and high interest rates. There's a slight silver lining here, though, as the 37% figure is three percentage points higher than it was in September. But, with that said, a recovery rate of 37% after more than three and a half years is still very low and speaks volumes about the ongoing list of troubles small business owners face looking into the rest of 2023. Tech, Manufacturing, Gyms, Beauty & Retail Struggle Examining the rent delinquency landscape in terms of sectors, there's quite a negative shift occurring among some industries in October. Let's look at the charts below to see what's really happening. Sectors most affected by rent delinquency include tech and retail Details on sectors affected by rent delinquency in October This is alarming for a few reasons: The countless technology layoffs at larger companies over the past year appear to be affecting the small companies now, too, who are often dependent on the larger ones as clients. Right now, 54% of science/technology small companies couldn't pay their October rent, up 10 percentage points from September and 16 percentage points since August. There are also some comments in the surveys of technology roles being reduced or replaced by ChatGPT and other AI, which can write software programs. Gyms have been struggling now for a while and now 50% of them can't afford the rent, up 8 percentage points from September. The biggest shift between October and September occurred among manufacturers, partially due to ongoing fluctuation in the price of gas and other inflationary issues. For quite some time, manufacturers were improving a lot in terms of their rent delinquency rates, but in October, they jumped 25 percentage points, doubling their rate, which is now 50%. This is also a record high for manufacturers in 2023. We hope this is just a blip, but we'll see in November. Also due, in part, to fluctuating gas prices and costs of vehicles, 45% of transportation companies couldn't pay October rent in full and on time. That's up 6 percentage points from last month. Sadly, 47% of salon owners couldn't cover October rent, after showing a lot of stability over the past few months. But that stability ended this month, as salons' rent delinquency rates jumped nine percentage points. Though rates have dropped three percentage points in October, a high percentage of retailers are still having trouble paying the rent. Last month, it was 47%. This month, it's better, but is still over 40%, landing at 44%. This is worrisome, especially since Q4 is a "make it or break it" time for many Main Street merchants. Looking more closely at the industries, there was some good news, in that a few others experienced lower delinquency rates in October, including restaurants, which dipped to 40% from 44% in September. Travel/lodging dropped seven percentage points to 38% (from 45% last month), as did education, which is also at 38%, down from 43%. When looking at rent delinquency from the vantage point of the states that are most affected, many surges can be seen between October and September, while a few states saw some dramatic, encouraging declines, too. Rent Troubles Increase For IL, VA, TX, MA, FL, & CO Looking at the states' charts, you can see how tumultuous the rent story has become this fall. Let's first talk about those with significant jumps in their delinquency rates. Here's the rundown: Illinois leads the list once again. After having a better month in September, its delinquency rate has soared, once more, landing at 54% for October (up from 46% last month). In fact, the 54% figure is the highest rate IL-based SMBs have seen in 2023. Virginia was in great shape last month, with a delinquency rate of just 19%. But Virginia-based small business owners have had a very rough month, at least in terms of rent. Now, 50% of them who took our poll say they couldn't cover rent (an increase of 31 percentage points). Texas is third on the list, with an 11-percentage-point lift from 38% in September to 49% in October. MA is next up at 48%, which marks the largest jump on the chart -- 32 percentage points from a low of just 16% in September. Small businesses in Florida have also experienced two challenging months in terms of rent delinquency. Right now, 45% of SMBs there couldn't afford to pay, up nine percentage points from September and 15 percentage points from August. Colorado's businesses regressed in October, hitting a new record high of 40%. That rent delinquency rate jumped 13 percentage points from September to October. While we just covered states with some very high delinquency rates, there were also several more positive swings that have occurred in October. Though encouraging, we'll have to see how long those delinquency rates continue. Here are the most remarkable: New York -- After reaching a record rate of 55% last month, New York's small business owners now report a more stable number: just 29%. That's down 26 percentage points. New Jersey -- New York's neighbor has an even more impressive story in October: only 20% of New Jersey's SMBs couldn't pay rent this month, a record low over at least the past 14 months, down 34 percentage points from a record high of 54%. Michigan -- Similarly, Michigan's small business owners boast a rate of just 20%, down from 45% in September.

ChatGPT for business automation (incredible new AI)
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ChatGPT for business automation (incredible new AI)

Hey fellow small business owners! I'm curious to know how you would use ChatGPT or other AI automation tools to improve your business. For those who are not aware, recently a new chat AI was made available to the public by OpenAI, called ChatGPT. (same company that did Dall-E) In a tweet Elon Musk wrote that "ChatGPT is scary good. We are not far from dangerously strong AI." It allows anyone (regardless of tech skill) to simply type commands and it will spit out answers. It can also create actual working code. For example most tasks you do in a browser can be automated with a Python script, but it takes time and coding knowledge to create. With ChatGPT you can just tell it what you want and it will create the code! The impact for businesses is insane: 1) Your entire customer service can be easily replaced by chat bots and probably soon by AI that can speak over the phone (google showcased this in 2018, it already exists). 2) you can have the AI automate your sales process, creating a 1-on-1 conversations, at scale. It can probably also improve and optimize it's closing rate over time as it learns more about your customers. 3) It can be used to train your staff. It's really good for 1on1 instruction and teaching because it will go a the students pace and answer questions (compare that to the usual PowerPoint presentation people use) 4) Since it can create code to automate most tasks a human can do in a browser, you can create for example bots that take customer orders and automatically import them to whatever shipping system you use, send customers tracking info etc. (a lot of this stuff is done with software and APIs, but now anyone can create their own, custom solutions) I feel like we hit an inflection point in 2022 with AI and now we are beginning to see some really useful stuff coming out. Am I crazy or are we about to see a massive shift in how we do things?

6 principles to data architecture that facilitate innovation
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6 principles to data architecture that facilitate innovation

My team and I have been re-building our company's data architecture. In the process of doing so, I got together six key principles to transforming data architectures and thought I would share them, as a strong data architecture is crucial for businesses looking to stay competitive in the digital landscape, as it improves decision-making, time to market, and data security. When executed with efficiency, a resilient data architecture unleashes unparalleled degrees of agility. Principle 1: Agility and flexibility To quickly adjust to market fluctuations, businesses must create adaptable data infrastructures that can effortlessly manage an ever-growing influx of data. To accomplish this objective, we recommend to our clients to implement Enterprise Service Bus, Enterprise Data Warehouse, and Master Data Management integrated together. &#x200B; I believe the best option is this: \- By centralizing communication, ESB reduces the time and effort required to integrate new systems; \- EDW consolidates data from different sources, resulting in a 50% reduction in software implementation time; \- Finally, MDM ensures consistency and accuracy across the organization, leading to better decision-making and streamlined operations. Implementing these solutions can lead to reduced software implementation time, better ROI, and more manageable data architecture. By fostering a culture of collaboration and adopting modern technologies and practices, businesses can prioritize agility and flexibility in their data architecture to increase the pace of innovation. Principle 2: Modularity and reusability Data architecture that fosters modularity and reusability is essential for accelerating innovation within an organization. By breaking data architecture components into smaller, more manageable pieces, businesses can enable different teams to leverage existing architecture components, reducing redundancy and improving overall efficiency. MDM can promote modularity and reusability by creating a central repository for critical business data. This prevents duplication and errors, improving efficiency and decision-making. MDM enables a single source of truth for data, accessible across multiple systems, which promotes integration and scalability. MDM also provides standardized data models, rules, and governance policies that reduce development time, increase quality, and ensure proper management throughout the data’s lifecycle. Another way to achieve modularity in data architecture is through the use of microservices and scripts for Extract, Transform, and Load (ETL) processes. Adopting a structured methodology and framework can ensure these components are well-organized, making it easier for teams to collaborate and maintain the system. Microservices can also contribute to modularity and reusability in data architecture. These small, independent components can be developed, deployed, and scaled independently of one another. By utilizing microservices, organizations can update or replace individual components without affecting the entire system, improving flexibility and adaptability. Principle 3: Data quality and consistency The efficiency of operations depends on data’s quality, so a meticulously crafted data architecture plays a pivotal role in preserving it, empowering enterprises to make well-informed decisions based on credible information. Here are some key factors to consider that will help your company ensure quality: \- Implementing Master Data Management (MDM) – this way, by consolidating, cleansing, and standardizing data from multiple sources, your IT department will be able to create a single, unified view of the most important data entities (customers, products, and suppliers); \- Assigning data stewardship responsibilities to a small team or an individual specialist; \- Considering implementing data validation, data lineage, and data quality metrics; \- By implementing MDM and adopting a minimal data stewardship approach, organizations can maintain high-quality data that drives innovation and growth. Principle 4: Data governance Data governance is a strategic framework that goes beyond ensuring data quality and consistency. It includes ensuring data security, privacy, accessibility, regulatory compliance, and lifecycle management. Here are some key aspects of data governance: \- Implementing robust measures and controls to protect sensitive data from unauthorized access, breaches, and theft. This is only possible through including encryption, access controls, and intrusion detection systems into your company’s IT architecture; \- Adhering to data privacy regulations and guidelines, such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA); \- Defining stringent conditions for who has access to specific data assets to maintain control over data and ensure its accessibility only for legitimate purposes. Managing the entire lifecycle of data, from creation and storage to archiving and disposal, including defining policies for data retention, archiving, and deletion in compliance with legal and regulatory requirements. To facilitate effective data governance, organizations can leverage various tools and technologies, such as: \- Data cataloging tools: Solutions like Collibra, Alation, or Informatica Enterprise Data Catalog help organizations discover, understand, and manage their data assets. \- Data lineage tools: Tools like Talend, IBM InfoSphere, or Apache Atlas help track data’s origin, transformation, and usage, providing insights into data quality issues and potential areas for improvement. \- Data quality tools: Solutions like Informatica Data Quality, Trifacta, or SAS Data Quality help organizations maintain high-quality data by identifying and correcting errors, inconsistencies, and inaccuracies. \- Data security and privacy tools: Tools like Varonis, BigID, or Spirion help protect sensitive data and ensure compliance with data privacy regulations. Principle 5: Cloud-first approach A cloud-first approach prioritizes cloud-based solutions over on-premises ones when it comes to data management. Cloud-based data management pros: \- Virtually limitless scalability, so that organizations can grow and adapt to changing data requirements without significant infrastructure investments; \- The pay-as-you-go model of cloud services reduces maintenance costs usually associated with the on-premise choice; \- Greater flexibility for deploying and integrating new technologies and services; \- Cloud can be accessed from anywhere, at any time, turning team collaboration and remote work into a breeze; \- Built-in backup and disaster recovery capabilities, ensuring data safety and minimizing downtime in case of emergencies. Cloud-based data management cons: \- Cloud-first approach raises many data security, privacy, and compliance concerns; \- Transferring large data volumes to and from cloud is often time-consuming and results in increased latency for certain apps; \- Relying on a single cloud provider makes it difficult to switch them or move back to the on-premises option without significant funds and effort. Challenges that organizations that choose a cloud-first approach face: \- Integrating cloud-based systems with on-premises ones can be complex and time-consuming; \- Ensuring data governance and compliance in a multi-cloud or hybrid environment is also another problem reported by my clients. How EDW, ESB, and MDM promote cloud-first approach: A cloud-based EDW centralizes data from multiple sources, enabling a unified view of the organization’s data and simplifying data integration across cloud and on-premises systems. An ESB facilitates communication between disparate cloud and on-premises systems, streamlining data integration and promoting a modular architecture. Cloud-based MDM solutions are used for maintaining data quality and consistency across multiple data sources and environments. Principle 6: Automation and artificial intelligence Incorporating automation tools and AI technologies into data architecture can optimize processes and decision-making. Key Applications: \- Data ingestion and integration: Automation simplifies data schema updates and identifies data quality issues, while AI-assisted development helps create tailored connectors, scripts, and microservices. \- Data quality management: Machine learning algorithms improve data quality and consistency by automatically detecting and correcting inconsistencies and duplicates. \- Predictive analytics: AI and machine learning models analyze historical data to predict trends, identify opportunities, and uncover hidden patterns for better-informed decisions. How No-Code Tools and AI-Assisted Development Work: Business users define data requirements and workflows using no-code tools, enabling AI models to understand their needs. AI models process the information, generating recommendations for connector creation, ETL scripts, and microservices. Developers use AI-generated suggestions to accelerate development and tailor solutions to business needs. By combining automation, AI technologies, and no-code tools, organizations can streamline data architecture processes and bridge the gap between business users and developers, ultimately accelerating innovation. I share more tips on building an agile data architectures in my blog.

Here is an interesting article on the potential future risks of AI to humanity.
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Here is an interesting article on the potential future risks of AI to humanity.

"There is a tremendous amount of enthusiasm in the media surrounding the topic of AI, and for good reason.  This exciting new technology has the potential to automate almost every boring, repetitive task in our lives.  It also offers exciting new opportunities to tap into new businesses, solve difficult problems with ease, and even offer new outlets for creative expression. What often does not get equal play in these discussions are the potential dangers of AI to humanity associated with this new technology.  Every new technology comes with risks that must be addressed, and it often takes a meltdown before safety concerns are taken seriously.  Often, those raising concerns are labeled as “chicken little” or a Johnny Raincloud spreading fud and dismissed or ignored.  This is common when the potential of the opportunities is so exciting. As I always say, emotion clouds the mind, and when optimism and enthusiasm run high, if we are honest, we often find a way to bring ourselves to believe what we want to believe.  All errors have consequences, for example, the risks associated with falling for a get-rich-quick scam may have consequences for an individual. However, consequences increase with the number of people that a mistake affects. With more powerful technology comes more power for good, but also a greater potential for great harm. In this article, I will attempt to balance out some of the enthusiasm and excitement with a healthy amount of caution.  I hope that the public will not just be swept away by the excitement of another new technology.  Rather, I hope that the public will demand responsibility, accountability, and regulation of this technology, before any AI version of Chornobyl, or worse, consigning the planet to a hellish dystopian hellscape reminiscent of post-apocalyptic sci-fi movies." https://ai-solutions.pro/dangers-and-risks-of-ai-to-humanity/

Let’s Build Small AI Buzz, Offer ‘Claim Processing’ to Mid/Big Companies
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Let’s Build Small AI Buzz, Offer ‘Claim Processing’ to Mid/Big Companies

Discover How AI Can Transform Businesses, Every Details Spelled Out. Full Article https://preview.redd.it/jp0vc5g6e86d1.png?width=1421&format=png&auto=webp&s=efa43e2a9b04b6996b00adac4e4947a3b21c7e63 Artificial Intelligence (AI) is rapidly reshaping business landscapes, promising unprecedented efficiency and accuracy across industries. In this article, we delve into how Aniket Insurance Inc. (Imaginary) leverages AI to revolutionize its claim processing operations, offering insights into the transformative power of AI in modern business environments. ➡️ What’s This Article About? \* The article explores how Aniket Insurance Inc. uses AI to transform its claim processing. \* It details the three main workflows: User claim submission, Admin + AI claim processing, and Executive + AI claim analysis. https://preview.redd.it/ql0ec20ae86d1.png?width=769&format=png&auto=webp&s=4b6889dd85f848194d6adfc92c9c699138eb1fe7 ➡️ Why Read This Article \* Readers can see practical ways AI boosts efficiency in business, using Aniket Insurance as an example. \* AI speeds up routine tasks, like data entry, freeing up humans for more strategic work. It shows how AI-driven data analysis can lead to smarter business decisions. ➡️Let’s Design: Aniket Insurance Inc. has implemented AI architecture that encompasses three pivotal workflows: User Claim Submission Flow, Admin + AI Claim Processing Flow, and Executive + AI Claim Analysis Flow. Powered by AI models and integrated with store, this architecture ensures seamless automation and optimization of the entire claim processing lifecycle. By leveraging AI technologies like machine learning models and data visualization tools, Aniket Insurance how business can enhance operational efficiency, and strategic decision-making capabilities. https://preview.redd.it/qgdmzs3ee86d1.png?width=733&format=png&auto=webp&s=445295beb52a56d826e5527859cf62879116ddb0 ➡️Closing Thoughts: Looking ahead, the prospects of AI adoption across various industries are incredibly exciting. Imagine manufacturing plants where AI optimizes production lines, predicts maintenance needs, and ensures quality control. Envision healthcare facilities where AI assists in diagnosis, treatment planning, and drug discovery. Picture retail operations where AI personalizes product recommendations, streamlines inventory management, and enhances customer service. The possibilities are endless, as AI’s capabilities in pattern recognition, predictive modeling, and automation can be leveraged to tackle complex challenges and uncover valuable insights in virtually any domain. https://preview.redd.it/w3hr913ge86d1.png?width=754&format=png&auto=webp&s=d839a7703f5b28314a3278c8d628ae5f05d3668f

What if… Employers Employ AI Agents to Get 360° Feedback from Employees?
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What if… Employers Employ AI Agents to Get 360° Feedback from Employees?

AI Agent powered Comprehensive 360° Feedback Collection & Analysis Full Article &#x200B; https://i.redd.it/1ieczv6pud1d1.gif ⚪ What is this Article About? ● This article demonstrates how AI agents can be used in the real-world for gathering feedback from employees ● It explores using AI agents to collect insights on employee experiences, job satisfaction, and suggestions for improvement ● By leveraging AI agents and language models, organizations can better understand their workforce's needs and concerns ⚪Why Read this Article? ● Learn about the potential benefits of using AI agents for comprehensive feedback collection ● Understand how to build practical, real-world solutions by combining AI agents with other technologies ● Stay ahead of the curve by exploring cutting-edge applications of AI agents ⚪What are we doing in this Project? \> Part 1: AI Agents to Coordinate and Gather Feedback ● AI agents collaborate to collect comprehensive feedback from employees through surveys and interviews ● Includes a Feedback Collector Agent, Feedback Analyst Agent, and Feedback Reporter Agent \> Part 2: Analyze Feedback Data with Pandas AI and Llama3 ● Use Pandas AI and Llama3 language model to easily analyze the collected feedback data ● Extract insights, identify patterns, strengths, and areas for improvement from the feedback ⚪ Let's Design Our AI Agent System for 360° Feedback \> Feedback Collection System: ● Collect feedback from employees (simulated) ● Analyze the feedback data ● Report findings and recommendations \> Feedback Analysis System: ● Upload employee feedback CSV file ● Display uploaded data ● Perform natural language analysis and queries ● Generate automated insights and visual graphs ⚪ Let's get Cooking ● Explanation of the code for the AI agent system and feedback analysis system ● Includes code details for functions, classes, and streamlit interface ⚪ Closing Thoughts ● AI agents can revolutionize how businesses operate and tackle challenges ● Their ability to coordinate, collaborate, and perform specialized tasks is invaluable ● AI agents offer versatile and scalable solutions for optimizing processes and uncovering insights ⚪ Future Work ● This project is a demo to show the potential real-world use cases of AI Agents. To achieve the results seen here, I went through multiple iterations and changes. AI Agents are not fully ready yet (although they are making huge progress every day). AI Agents still need to go through an improvement cycle to reach their full potential in real-world settings. &#x200B;

Master AI Integration: How to Integrate AI in Your Application
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Master AI Integration: How to Integrate AI in Your Application

A Comprehensive Guide with Every Detail Spelled Out for Flawless AI Implementation Full Article &#x200B; https://preview.redd.it/m5b79j55f14d1.png?width=1328&format=png&auto=webp&s=8cf04c80cd21be1710dd117a9e74b07d0e8cbe6a In the ideal world, we'd design our software systems with AI in mind from the very beginning. But in the real world, that's not always possible. Many businesses have large, complex systems that have been running for years, and making significant changes to them is risky and expensive. What this Article is About? ● This article aims to convince you that even when changing existing systems is not an option, you can still seamlessly integrate AI into your business processes. It explores real-world scenarios and shows how a company (though simulated) has successfully incorporated AI without overhauling their existing infrastructure. &#x200B; https://i.redd.it/fayl1gcbf14d1.gif Why Read This Article? ● By reading this article, you will learn the critical skill of integrating AI into your existing business ecosystem without making significant changes to your stable workflows. This skill is becoming increasingly important as more and more companies recognize the value of AI while also acknowledging the challenges of overhauling their existing systems. What is Our Business Use Case? ● The article uses a simulated supply chain management company as a business use case. This company has multiple departments, each exposing its own REST API, and to get an inquiry answered, the request has to go through various departments, their respective APIs, and database calls. The article introduces AI capabilities to enhance the company's operations without modifying the existing system architecture. Our Supply Chain Management Company AI Integration Design ● The article describes the various components of the simulated supply chain management company, including the "Data Processing System," "Company Data Handling System," "AI Integration System," "Mapping System," and "System Admin Dashboard." Let's Get Cooking! ● This section provides the code and explanations for implementing the AI integration system in the simulated supply chain management company. It covers the following: ○ Dashboard & AI Integration System ○ Company Data Handling System ○ Data Processing System ○ Mapping System Let's Setup ● This section shows the expected output when setting up the simulated supply chain management system with AI integration. Let's Run it ● This section demonstrates how to run the system and ask questions related to supply chain management, showcasing the AI integration in action. https://i.redd.it/3e68mb57f14d1.gif Closing Thoughts The supply chain management project we have explored in this article serves as a powerful example of how to seamlessly integrate cutting-edge AI capabilities into existing business systems without the need for significant overhauls or disruptions. By leveraging the flexibility and power of modern AI technologies, we were able to enhance the functionality of a simulated supply chain management system while preserving its core operations and workflows. Throughout the development process, we placed a strong emphasis on minimizing the impact on the existing system architecture. Rather than attempting to replace or modify the established components, we introduced an “AI Integration System” that acts as a bridge between the existing infrastructure and the AI-powered capabilities. This approach allowed us to maintain the integrity of the existing systems while simultaneously leveraging the benefits of AI. One of the key advantages of this integration strategy is the ability to leverage the wealth of data already available within the existing systems. By accessing and processing this data through the AI models, we were able to generate more informed and intelligent responses to user queries, providing valuable insights and recommendations tailored to the specific supply chain activities and scenarios. As we look towards the future, the importance of seamlessly integrating AI into existing business ecosystems will only continue to grow. With the rapid pace of technological advancements and the increasing demand for intelligent automation and decision support, organizations that embrace this approach will be better positioned to capitalize on the opportunities presented by AI while minimizing disruptions to their operations. It is my hope that through this simulated real-world example, you have gained a deeper understanding of the potential for AI integration and the various strategies and best practices that can be employed to achieve successful implementation. By embracing this approach, businesses can unlock the transformative power of AI while preserving the investments and institutional knowledge embedded in their existing systems.

How I Built an Agentic Marketing Campaign Strategist
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AniketWorkThis week

How I Built an Agentic Marketing Campaign Strategist

Marketing at Scale: How One AI System Replaces Hundreds of Strategy Hours Article https://i.redd.it/uekqj3zmerme1.gif https://i.redd.it/30rk23zmerme1.gif https://preview.redd.it/fk1t53zmerme1.png?width=797&format=png&auto=webp&s=d07f473a9556fbd38885b3a2f862101d9b25424e https://preview.redd.it/n84113zmerme1.jpg?width=1914&format=pjpg&auto=webp&s=f42679269a1003e1c8d6501dd2d53e10db745bba https://preview.redd.it/l13ae3zmerme1.jpg?width=791&format=pjpg&auto=webp&s=ecab3c295c2a416bc0fed8c62fecbe3321e37093 TL;DR This article guides you through building an AI-powered marketing strategist using Python. It combines vector databases, language models, and PDF generation to create customized marketing strategies automatically. I’ll show you the complete system architecture, from storing marketing knowledge to generating professional strategy documents, with practical code examples you can implement today. Perfect for marketers and developers looking to leverage AI for business growth. Introduction Welcome to the exciting intersection of marketing and artificial intelligence! In today’s digital world, creating effective marketing campaigns requires deep expertise, market research, and creative thinking. But what if you could automate parts of this process? That’s exactly what I set out to build: an AI system that generates comprehensive marketing strategies tailored to specific products, audiences, and budgets. What’s This Article About? This article walks you through the creation of an AI-powered marketing strategist that combines the retrieval of relevant marketing knowledge with advanced language generation to produce detailed campaign strategies. The system I built uses Retrieval-Augmented Generation (RAG), which enhances AI outputs by grounding them in specific knowledge sources. Here’s how it works: You provide a simple campaign description (like “a new eco-friendly water bottle targeting millennials with a budget of $50,000”) The system searches a knowledge base of marketing principles and best practices It then uses a language model to craft a comprehensive strategy that includes campaign objectives, target audience analysis, channel selection, content ideas, budget allocation, and measurement KPIs Finally, it generates a professional PDF document with your complete marketing strategy The beauty of this approach is that it combines the creativity and adaptability of AI with established marketing frameworks, ensuring the strategies are both innovative and grounded in proven principles. Why Read It? AI is rapidly transforming how businesses operate, and marketing is at the forefront of this revolution. According to recent studies, companies that effectively leverage AI in their marketing efforts see significant improvements in customer engagement, conversion rates, and ROI. Even if you’re not building a system for a real company right now, understanding how to implement AI in marketing processes gives you valuable skills and insights. This article provides a practical example of how AI can: Save marketers countless hours of research and strategy development Ensure consistency in marketing approaches across different campaigns Generate creative ideas that might not have been considered otherwise Scale marketing expertise across an organization By following along, you’ll gain hands-on experience with technologies like vector databases, language models, and automated document generation — all skills that are increasingly valuable in today’s business environment.

My Building Of Trading Order Management System Using AI Agents
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AniketWorkThis week

My Building Of Trading Order Management System Using AI Agents

Practical Guide : Automating Business Transactions with AI-Powered Workflows Full Article | Code https://preview.redd.it/hrkeo00yz4ie1.jpg?width=1911&format=pjpg&auto=webp&s=5bcb6f02c72bbce22fb691e4d8b799c414fed2a7 https://preview.redd.it/1cp0izzxz4ie1.png?width=1899&format=png&auto=webp&s=2598e25e17ab03a95f3009f5333f02b077ce30ca https://preview.redd.it/cjp1640yz4ie1.png?width=1899&format=png&auto=webp&s=13dad0ee8e0b1b22415a60a57b571058f0bdef33 TL;DR A practical implementation of an AI-powered B2B order management system using LangChain and LLM, demonstrating automated order processing, inventory management, and real-time communication between trading partners. https://i.redd.it/kxe4l69105ie1.gif Introduction In today’s fast-paced business environment, efficient order management is crucial for B2B operations. GlobalTrade Nexus AI showcases how artificial intelligence can streamline complex business transactions, reduce errors, and enhance communication between trading partners. What’s This Article About? This article presents a comprehensive B2B trading platform that leverages AI to automate order processing workflows. The system handles everything from order placement to fulfillment, featuring: Real-time inventory verification Automated shipping cost calculations Instant order validation Secure transaction processing Smart order cancellation capabilities State management across the entire order lifecycle The platform demonstrates how modern AI technologies can be integrated into traditional business processes to create a seamless, efficient trading environment. Tech stack Why Read It? As businesses increasingly embrace digital transformation, AI-powered solutions are becoming essential for maintaining competitive advantage. This article provides: A practical example of AI implementation in B2B commerce Insights into modern system architecture for business applications Real-world application of language models in business logic Demonstration of secure and scalable state management Blueprint for building similar AI-enhanced business systems Through our fictional companies’ implementation, readers can understand how AI can transform their business operations and prepare for the future of B2B commerce.

My Building Of Trading Order Management System Using AI Agents
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AniketWorkThis week

My Building Of Trading Order Management System Using AI Agents

Practical Guide : Automating Business Transactions with AI-Powered Workflows Full Article | Code https://preview.redd.it/hrkeo00yz4ie1.jpg?width=1911&format=pjpg&auto=webp&s=5bcb6f02c72bbce22fb691e4d8b799c414fed2a7 https://preview.redd.it/1cp0izzxz4ie1.png?width=1899&format=png&auto=webp&s=2598e25e17ab03a95f3009f5333f02b077ce30ca https://preview.redd.it/cjp1640yz4ie1.png?width=1899&format=png&auto=webp&s=13dad0ee8e0b1b22415a60a57b571058f0bdef33 TL;DR A practical implementation of an AI-powered B2B order management system using LangChain and LLM, demonstrating automated order processing, inventory management, and real-time communication between trading partners. https://i.redd.it/kxe4l69105ie1.gif Introduction In today’s fast-paced business environment, efficient order management is crucial for B2B operations. GlobalTrade Nexus AI showcases how artificial intelligence can streamline complex business transactions, reduce errors, and enhance communication between trading partners. What’s This Article About? This article presents a comprehensive B2B trading platform that leverages AI to automate order processing workflows. The system handles everything from order placement to fulfillment, featuring: Real-time inventory verification Automated shipping cost calculations Instant order validation Secure transaction processing Smart order cancellation capabilities State management across the entire order lifecycle The platform demonstrates how modern AI technologies can be integrated into traditional business processes to create a seamless, efficient trading environment. Tech stack Why Read It? As businesses increasingly embrace digital transformation, AI-powered solutions are becoming essential for maintaining competitive advantage. This article provides: A practical example of AI implementation in B2B commerce Insights into modern system architecture for business applications Real-world application of language models in business logic Demonstration of secure and scalable state management Blueprint for building similar AI-enhanced business systems Through our fictional companies’ implementation, readers can understand how AI can transform their business operations and prepare for the future of B2B commerce.

How I Built an Agentic Marketing Campaign Strategist
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AniketWorkThis week

How I Built an Agentic Marketing Campaign Strategist

Marketing at Scale: How One AI System Replaces Hundreds of Strategy Hours Article https://i.redd.it/uekqj3zmerme1.gif https://i.redd.it/30rk23zmerme1.gif https://preview.redd.it/fk1t53zmerme1.png?width=797&format=png&auto=webp&s=d07f473a9556fbd38885b3a2f862101d9b25424e https://preview.redd.it/n84113zmerme1.jpg?width=1914&format=pjpg&auto=webp&s=f42679269a1003e1c8d6501dd2d53e10db745bba https://preview.redd.it/l13ae3zmerme1.jpg?width=791&format=pjpg&auto=webp&s=ecab3c295c2a416bc0fed8c62fecbe3321e37093 TL;DR This article guides you through building an AI-powered marketing strategist using Python. It combines vector databases, language models, and PDF generation to create customized marketing strategies automatically. I’ll show you the complete system architecture, from storing marketing knowledge to generating professional strategy documents, with practical code examples you can implement today. Perfect for marketers and developers looking to leverage AI for business growth. Introduction Welcome to the exciting intersection of marketing and artificial intelligence! In today’s digital world, creating effective marketing campaigns requires deep expertise, market research, and creative thinking. But what if you could automate parts of this process? That’s exactly what I set out to build: an AI system that generates comprehensive marketing strategies tailored to specific products, audiences, and budgets. What’s This Article About? This article walks you through the creation of an AI-powered marketing strategist that combines the retrieval of relevant marketing knowledge with advanced language generation to produce detailed campaign strategies. The system I built uses Retrieval-Augmented Generation (RAG), which enhances AI outputs by grounding them in specific knowledge sources. Here’s how it works: You provide a simple campaign description (like “a new eco-friendly water bottle targeting millennials with a budget of $50,000”) The system searches a knowledge base of marketing principles and best practices It then uses a language model to craft a comprehensive strategy that includes campaign objectives, target audience analysis, channel selection, content ideas, budget allocation, and measurement KPIs Finally, it generates a professional PDF document with your complete marketing strategy The beauty of this approach is that it combines the creativity and adaptability of AI with established marketing frameworks, ensuring the strategies are both innovative and grounded in proven principles. Why Read It? AI is rapidly transforming how businesses operate, and marketing is at the forefront of this revolution. According to recent studies, companies that effectively leverage AI in their marketing efforts see significant improvements in customer engagement, conversion rates, and ROI. Even if you’re not building a system for a real company right now, understanding how to implement AI in marketing processes gives you valuable skills and insights. This article provides a practical example of how AI can: Save marketers countless hours of research and strategy development Ensure consistency in marketing approaches across different campaigns Generate creative ideas that might not have been considered otherwise Scale marketing expertise across an organization By following along, you’ll gain hands-on experience with technologies like vector databases, language models, and automated document generation — all skills that are increasingly valuable in today’s business environment.

I’m AI/ML product manager. What I would have done differently on Day 1 if I knew what I know today
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I’m AI/ML product manager. What I would have done differently on Day 1 if I knew what I know today

I’m a software engineer and product manager, and I’ve working with and studying machine learning models for several years. But nothing has taught me more than applying ML in real-world projects. Here are some of top product management lessons I learned from applying ML: Work backwards: In essence, creating ML products and features is no different than other products. Don’t jump into Jupyter notebooks and data analysis before you talk to the key stakeholders. Establish deployment goals (how ML will affect your operations), prediction goals (what exactly the model should predict), and evaluation metrics (metrics that matter and required level of accuracy) before gathering data and exploring models.  Bridge the tech/business gap in your organization: Business professionals don’t know enough about the intricacies of machine learning, and ML professionals don’t know about the practical needs of businesses. Educate your business team on the basics of ML and create joint teams of data scientists and business analysts to define and measure goals and progress of ML projects. ML projects are more likely to fail when business and data science teams work in silos. Adjust your priorities at different stages of the project: In the early stages of your ML project, aim for speed. Choose the solution that validates/rejects your hypotheses the fastest, whether it’s an API, a pre-trained model, or even a non-ML solution (always consider non-ML solutions). In the more advanced stages of the project, look for ways to optimize your solution (increase accuracy and speed, reduce costs, increase flexibility). There is a lot more to share, but these are some of the top experiences that would have made my life a lot easier if I had known them before diving into applied ML.  What is your experience?

Building a No-Code AI Customer Service Tool While Working 9-5 | All real - No BS
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Building a No-Code AI Customer Service Tool While Working 9-5 | All real - No BS

I want to share my journey of building Chaterimo, my first revenue-generating side project that I've been working on for the past 1.5 years alongside my day job. What started as a solution to make AI chatbots more accessible has grown to over 300 signups, 30 paying customers, and 50,000+ customer queries handled. The Problem I Wanted to Solve: It started with my father's business struggling with customer service - hiring staff was expensive and they would eventually leave, creating a constant cycle of training new people. I decided to help by building a livechat chatbot powered by AI to handle customer queries. The first version was basic (running on ChatGPT-3 with 4k tokens), but it worked! Seeing its success at my father's business, I realized this could help many other businesses too. As I kept improving it and adding features, I expanded to focus on e-commerce stores facing similar challenges. What Makes Chaterimo Different: True no-code setup: Install and run in seconds Choice of AI Models: ChatGPT by default, with options for Claude and the latest Gemini Flexible API Integration: Bring your own API keys for cheaper, unlimited messaging Smart Context Understanding: Can search Google or scan the current webpage to provide relevant answers Lead Generation: Capture and manage potential customer information Rich Integrations: Works with Shopify, Facebook Messenger, and Make for automation Customizable Bot Personality: Edit your chatbot's role and behavior through system prompts The Journey: This is my first side project that's actually generating revenue ($500+ MRR), unlike my previous "just for fun" projects. The past 1.5 years have been a learning experience, balancing development with a full-time job. What started as a simple idea has evolved based on real user feedback and needs. Current Metrics: 300+ total signups 30 paying customers 50,000+ customer queries successfully handled by AI $500+ monthly recurring revenue All while maintaining a 9-5 job Some Things I've Learned: Focus on making things simpler, not adding more features Listen to users - they'll tell you what they really need Flexibility matters - letting users use their own API keys was a game-changer Building something you believe in makes all the difference I'm still actively improving Chaterimo based on feedback. If you're running a website or e-commerce store and want to try it out, I'd love to hear your thoughts. What's Next: I'm focused on making the onboarding even smoother and adding more customization options while keeping the core simplicity that makes Chaterimo work. Would love to hear your thoughts or answer any questions! Has anyone else built successful side projects while working full-time? What were your biggest learnings?

Introducing Stratify: Your Ultimate AI Strategy Builder for Business Success
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Introducing Stratify: Your Ultimate AI Strategy Builder for Business Success

Hello, I’m thrilled to announce the launch of my new startup, Stratify! 🔍 What is Stratify? Stratify is an AI Strategy Builder designed to help businesses of all sizes develop, implement, and optimize their strategic plans using cutting-edge artificial intelligence. Whether you're a startup looking to scale or an established company aiming to innovate, Stratify provides the tools and insights you need to stay ahead in today's competitive landscape. 🌟 Key Features: Automated Strategy Development: Leverage AI to analyze market trends, competitor data, and internal metrics to create comprehensive strategic plans tailored to your business goals. Real-Time Analytics & Insights: Monitor your strategy's performance with real-time data dashboards, enabling you to make informed decisions quickly. Scenario Planning: Use AI-driven simulations to forecast different business scenarios and understand potential outcomes, helping you prepare for uncertainties. Collaborative Tools: Facilitate team collaboration with integrated communication features, ensuring everyone is aligned and contributing to the strategy development process. Customizable Templates: Access a library of industry-specific strategy templates that can be customized to fit your unique business needs. 💡 Why Stratify? In today's fast-paced business environment, creating and adapting effective strategies can be challenging. Many companies struggle with data overload, lack of actionable insights, and inefficient planning processes. Stratify addresses these pain points by harnessing the power of AI to streamline strategy building, making it more efficient, data-driven, and adaptable. 🚀 Our Journey So Far: Founded: August 2024 Milestones Achieved: Developed and tested our MVP with a select group of beta users What's Next: Launching our public beta in Q4 2024 Expanding our feature set based on user feedback Growing our team with experts in AI, business strategy, and customer success 🤝 How You Can Help: We’re eager to connect with early adopters, business strategists, and industry experts who can benefit from or contribute to Stratify. Here’s how you can get involved: Join Our Beta Program: Be among the first to experience Stratify and provide valuable feedback. Share Your Insights: Help us refine our features by sharing your business strategy challenges and needs. Spread the Word: If you know someone who could benefit from an AI-driven strategy builder, please share our mission and be an affiliate to earn rewards! 🌐 Learn More: Visit our website at AI-Powered Brand Strategy & Content Creation | Stratify (brandprovoke.com) and follow us for the latest updates and insights. 🙏 Thank You! A heartfelt thank you to the Reddit community for your support and encouragement. We’re excited to embark on this journey and look forward to your feedback and suggestions! Looking forward to your thoughts and questions!

I spent 6 months on a web app as a side project, and got 0 users. Here is my story.
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GDbuildsGDThis week

I spent 6 months on a web app as a side project, and got 0 users. Here is my story.

Edit Thank you all so much for your time reading my story. Your support, feedback, criticism, and skepticism; all helped me a lot, and I couldn't appreciate it enough \^\_\^ I very rarely have stuff to post on Reddit, but I share how my project is going on, just random stuff, and memes on X. In case few might want to keep up 👀 TL;DR I spent 6 months on a tool that currently has 0 users. Below is what I learned during my journey, sharing because I believe most mistakes are easily avoidable. Do not overestimate your product and assume it will be an exception to fundamental principles. Principles are there for a reason. Always look for validation before you start. Avoid building products with a low money-to-effort ratio/in very competitive fields. Unless you have the means, you probably won't make it. Pick a problem space, pick your target audience, and talk to them before thinking about a solution. Identify and match their pain points. Only then should you think of a solution. If people are not overly excited or willing to pay in advance for a discounted price, it might be a sign to rethink. Sell one and only one feature at a time. Avoid everything else. If people don't pay for that one core feature, no secondary feature will change their mind. Always spend twice as much time marketing as you do building. You will not get users if they don't know it exists. Define success metrics ("1000 users in 3 months" or "$6000 in the account at the end of 6 months") before you start. If you don't meet them, strongly consider quitting the project. If you can't get enough users to keep going, nothing else matters. VALIDATION, VALIDATION, VALIDATION. Success is not random, but most of our first products will not make a success story. Know when to admit failure, and move on. Even if a product of yours doesn't succeed, what you learned during its journey will turn out to be invaluable for your future. My story So, this is the story of a product that I’ve been working on for the last 6 months. As it's the first product I’ve ever built, after watching you all from the sidelines, I have learned a lot, made many mistakes, and did only a few things right. Just sharing what I’ve learned and some insights from my journey so far. I hope that this post will help you avoid the mistakes I made — most of which I consider easily avoidable — while you enjoy reading it, and get to know me a little bit more 🤓. A slow start after many years Summ isn’t the first product I really wanted to build. Lacking enough dev skills to even get started was a huge blocker for so many years. In fact, the first product I would’ve LOVED to build was a smart personal shopping assistant. I had this idea 4 years ago; but with no GPT, no coding skills, no technical co-founder, I didn’t have the means to make it happen. I still do not know if such a tool exists and is good enough. All I wanted was a tool that could make data-based predictions about when to buy stuff (“buy a new toothpaste every three months”) and suggest physical products that I might need or be strongly interested in. AFAIK, Amazon famously still struggles with the second one. Fast-forward a few years, I learned the very basics of HTML, CSS, and Vanilla JS. Still was not there to build a product; but good enough to code my design portfolio from scratch. Yet, I couldn’t imagine myself building a product using Vanilla JS. I really hated it, I really sucked at it. So, back to tutorial hell, and to learn about this framework I just heard about: React.React introduced so many new concepts to me. “Thinking in React” is a phrase we heard a lot, and with quite good reasons. After some time, I was able to build very basic tutorial apps, both in React, and React Native; but I have to say that I really hated coding for mobile. At this point, I was already a fan of productivity apps, and had a concept for a time management assistant app in my design portfolio. So, why not build one? Surely, it must be easy, since every coding tutorial starts with a todo app. ❌ WRONG! Building a basic todo app is easy enough, but building one good enough for a place in the market was a challenge I took and failed. I wasted one month on that until I abandoned the project for good. Even if I continued working on it, as the productivity landscape is overly competitive, I wouldn’t be able to make enough money to cover costs, assuming I make any. Since I was (and still am) in between jobs, I decided to abandon the project. 👉 What I learned: Do not start projects with a low ratio of money to effort and time. Example: Even if I get 500 monthly users, 200 of which are paid users (unrealistically high number), assuming an average subscription fee of $5/m (such apps are quite cheap, mostly due to the high competition), it would make me around $1000 minus any occurring costs. Any founder with a product that has 500 active users should make more. Even if it was relatively successful, due to the high competition, I wouldn’t make any meaningful money. PS: I use Todoist today. Due to local pricing, I pay less than $2/m. There is no way I could beat this competitive pricing, let alone the app itself. But, somehow, with a project that wasn’t even functional — let alone being an MVP — I made my first Wi-Fi money: Someone decided that the domain I preemptively purchased is worth something. By this point, I had already abandoned the project, certainly wasn’t going to renew the domain, was looking for a FT job, and a new project that I could work on. And out of nowhere, someone hands me some free money — who am I not to take it? Of course, I took it. The domain is still unused, no idea why 🤔. Ngl, I still hate the fact that my first Wi-Fi money came from this. A new idea worth pursuing? Fast-forward some weeks now. Around March, I got this crazy idea of building an email productivity tool. We all use emails, yet we all hate them. So, this must be fixed. Everyone uses emails, in fact everyone HAS TO use emails. So, I just needed to build a tool and wait for people to come. This was all, really. After all, the problem space is huge, there is enough room for another product, everyone uses emails, no need for any further validation, right? ❌ WRONG ONCE AGAIN! We all hear from the greatest in the startup landscape that we must validate our ideas with real people, yet at least some of us (guilty here 🥸) think that our product will be hugely successful and prove them to be an exception. Few might, but most are not. I certainly wasn't. 👉 Lesson learned: Always validate your ideas with real people. Ask them how much they’d pay for such a tool (not if they would). Much better if they are willing to pay upfront for a discount, etc. But even this comes later, keep reading. I think the difference between “How much” and “If” is huge for two reasons: (1) By asking them for “How much”, you force them to think in a more realistic setting. (2) You will have a more realistic idea on your profit margins. Based on my competitive analysis, I already had a solution in my mind to improve our email usage standards and email productivity (huge mistake), but I did my best to learn about their problems regarding those without pushing the idea too hard. The idea is this: Generate concise email summaries with suggested actions, combine them into one email, and send it at their preferred times. Save as much as time the AI you end up with allows. After all, everyone loves to save time. So, what kind of validation did I seek for? Talked with only a few people around me about this crazy, internet-breaking idea. The responses I got were, now I see, mediocre; no one got excited about it, just said things along the lines of “Cool idea, OK”. So, any reasonable person in this situation would think “Okay, not might not be working”, right? Well, I did not. I assumed that they were the wrong audience for this product, and there was this magical land of user segments waiting eagerly for my product, yet unknowingly. To this day, I still have not reached this magical place. Perhaps, it didn’t exist in the first place. If I cannot find it, whether it exists or not doesn’t matter. I am certainly searching for it. 👉 What I should have done: Once I decide on a problem space (time management, email productivity, etc.), I should decide on my potential user segments, people who I plan to sell my product to. Then I should go talk to those people, ask them about their pains, then get to the problem-solving/ideation phase only later. ❗️ VALIDATION COMES FROM THE REALITY OUTSIDE. What validation looks like might change from product to product; but what invalidation looks like is more or less the same for every product. Nico Jeannen told me yesterday “validation = money in the account” on Twitter. This is the ultimate form of validation your product could get. If your product doesn’t make any money, then something is invalidated by reality: Your product, you, your idea, who knows? So, at this point, I knew a little bit of Python from spending some time in tutorial hell a few years ago, some HTML/CSS/JS, barely enough React to build a working app. React could work for this project, but I needed easy-to-implement server interactivity. Luckily, around this time, I got to know about this new gen of indie hackers, and learned (but didn’t truly understand) about their approach to indie hacking, and this library called Nextjs. How good Next.js still blows my mind. So, I was back to tutorial hell once again. But, this time, with a promise to myself: This is the last time I would visit tutorial hell. Time to start building this "ground-breaking idea" Learning the fundamentals of Next.js was easier than learning of React unsurprisingly. Yet, the first time I managed to run server actions on Next.js was one of the rarest moments that completely blew my mind. To this day, I reject the idea that it is something else than pure magic under its hood. Did I absolutely need Nextjs for this project though? I do not think so. Did it save me lots of time? Absolutely. Furthermore, learning Nextjs will certainly be quite helpful for other projects that I will be tackling in the future. Already got a few ideas that might be worth pursuing in the head in case I decide to abandon Summ in the future. Fast-forward few weeks again: So, at this stage, I had a barely working MVP-like product. Since the very beginning, I spent every free hour (and more) on this project as speed is essential. But, I am not so sure it was worth it to overwork in retrospect. Yet, I know I couldn’t help myself. Everything is going kinda smooth, so what’s the worst thing that could ever happen? Well, both Apple and Google announced their AIs (Apple Intelligence and Google Gemini, respectively) will have email summarization features for their products. Summarizing singular emails is no big deal, after all there were already so many similar products in the market. I still think that what truly matters is a frictionless user experience, and this is why I built this product in a certain way: You spend less than a few minutes setting up your account, and you get to enjoy your email summaries, without ever visiting its website again. This is still a very cool concept I really like a lot. So, at this point: I had no other idea that could be pursued, already spent too much time on this project. Do I quit or not? This was the question. Of course not. I just have to launch this product as quickly as possible. So, I did something right, a quite rare occurrence I might say: Re-planned my product, dropped everything secondary to the core feature immediately (save time on reading emails), tried launching it asap. 👉 Insight: Sell only one core feature at one time. Drop anything secondary to this core feature. Well, my primary occupation is product design. So one would expect that a product I build must have stellar design. I considered any considerable time spent on design at this stage would be simply wasted. I still think this is both true and wrong: True, because if your product’s core benefits suck, no one will care about your design. False, because if your design looks amateurish, no one will trust you and your product. So, I always targeted an average level design with it and the way this tool works made it quite easy as I had to design only 2 primary pages: Landing page and user portal (which has only settings and analytics pages). However, even though I knew spending time on design was not worth much of my time, I got a bit “greedy”: In fact, I redesigned those pages three times, and still ended up with a so-so design that I am not proud of. 👉 What I would do differently: Unless absolutely necessary, only one iteration per stage as long as it works. This, in my mind, applies to everything. If your product’s A feature works, then no need to rewrite it from scratch for any reason, or even refactor it. When your product becomes a success, and you absolutely need that part of your codebase to be written, do so, but only then. Ready to launch, now is th etime for some marketing, right? By July 26, I already had a “launchable” product that barely works (I marked this date on a Notion docs, this is how I know). Yet, I had spent almost no time on marketing, sales, whatever. After all, “You build and they will come”. Did I know that I needed marketing? Of course I did, but knowingly didn’t. Why, you might ask. Well, from my perspective, it had to be a dev-heavy product; meaning that you spend most of your time on developing it, mostly coding skills. But, this is simply wrong. As a rule of thumb, as noted by one of the greatests, Marc Louvion, you should spend at least twice of the building time on marketing. ❗️ Time spent on building \* 2 people don’t know your product > they don’t use your product > you don’t get users > you don’t make money Easy as that. Following the same reasoning, a slightly different approach to planning a project is possible. Determine an approximate time to complete the project with a high level project plan. Let’s say 6 months. By the reasoning above, 2 months should go into building, and 4 into marketing. If you need 4 months for building instead of 2, then you need 8 months of marketing, which makes the time to complete the project 12 months. If you don’t have that much time, then quit the project. When does a project count as completed? Well, in reality, never. But, I think we have to define success conditions even before we start for indie projects and startups; so we know when to quit when they are not met. A success condition could look like “Make $6000 in 12 months” or “Have 3000 users in 6 months”. It all depends on the project. But, once you set it, it should be set in stone: You don’t change it unless absolutely necessary. I suspect there are few principles that make a solopreneur successful; and knowing when to quit and when to continue is definitely one of them. Marc Louvion is famously known for his success, but he got there after failing so many projects. To my knowledge, the same applies to Nico Jeannen, Pieter Levels, or almost everyone as well. ❗️ Determining when to continue even before you start will definitely help in the long run. A half-aed launch Time-leap again. Around mid August, I “soft launched” my product. By soft launch, I mean lazy marketing. Just tweeting about it, posting it on free directories. Did I get any traffic? Surely I did. Did I get any users? Nope. Only after this time, it hit me: “Either something is wrong with me, or with this product” Marketing might be a much bigger factor for a project’s success after all. Even though I get some traffic, not convincing enough for people to sign up even for a free trial. The product was still perfect in my eyes at the time (well, still is ^(\_),) so the right people are not finding my product, I thought. Then, a question that I should have been asking at the very first place, one that could prevent all these, comes to my mind: “How do even people search for such tools?” If we are to consider this whole journey of me and my so-far-failed product to be an already destined failure, one metric suffices to show why. Search volume: 30. Even if people have such a pain point, they are not looking for email summaries. So, almost no organic traffic coming from Google. But, as a person who did zero marketing on this or any product, who has zero marketing knowledge, who doesn’t have an audience on social media, there is not much I could do. Finally, it was time to give up. Or not… In my eyes, the most important element that makes a founder (solo or not) successful (this, I am not by any means) is to solve problems. ❗️ So, the problem was this: “People are not finding my product by organic search” How do I make sure I get some organic traffic and gets more visibility? Learn digital marketing and SEO as much as I can within very limited time. Thankfully, without spending much time, I came across Neil Patel's YT channel, and as I said many times, it is an absolute gold mine. I learned a lot, especially about the fundamentals, and surely it will be fruitful; but there is no magic trick that could make people visit your website. SEO certainly helps, but only when people are looking for your keywords. However, it is truly a magical solution to get in touch with REAL people that are in your user segments: 👉 Understand your pains, understand their problems, help them to solve them via building products. I did not do this so far, have to admit. But, in case you would like to have a chat about your email usage, and email productivity, just get in touch; I’d be delighted to hear about them. Getting ready for a ProductHunt launch The date was Sept 1. And I unlocked an impossible achievement: Running out of Supabase’s free plan’s Egres limit while having zero users. I was already considering moving out of their Cloud server and managing a Supabase CLI service on my Hetzner VPS for some time; but never ever suspected that I would have to do this quickly. The cheapest plan Supabase offers is $25/month; yet, at that point, I am in between jobs for such a long time, basically broke, and could barely afford that price. One or two months could be okay, but why pay for it if I will eventually move out of their Cloud service? So, instead of paying $25, I spent two days migrating out of Supabase Cloud. Worth my time? Definitely not. But, when you are broke, you gotta do stupid things. This was the first time that I felt lucky to have zero users: I have no idea how I would manage this migration if I had any. I think this is one of the core tenets of an indie hacker: Controlling their own environment. I can’t remember whose quote this is, but I suspect it was Naval: Entrepreneurs have an almost pathological need to control their own fate. They will take any suffering if they can be in charge of their destiny, and not have it in somebody else’s hands. What’s truly scary is, at least in my case, we make people around us suffer at the expense of our attempting to control our own fates. I know this period has been quite hard on my wife as well, as I neglected her quite a bit, but sadly, I know that this will happen again. It is something that I can barely help with. Still, so sorry. After working the last two weeks on a ProductHunt Launch, I finally launched it this Tuesday. Zero ranking, zero new users, but 36 kind people upvoted my product, and many commented and provided invaluable feedback. I couldn't be more grateful for each one of them 🙏. Considering all these, what lies in the future of Summ though? I have no idea, to be honest. On one hand, I have zero users, have no job, no income. So, I need a way to make money asap. On the other hand, the whole idea of it revolves around one core premise (not an assumption) that I am not so willing to share; and I couldn’t have more trust in it. This might not be the best iteration of it, however I certainly believe that email usage is one of the best problem spaces one could work on. 👉 But, one thing is for certain: I need to get in touch with people, and talk with them about this product I built so far. In fact, this is the only item on my agenda. Nothing else will save my brainchild <3. Below are some other insights and notes that I got during my journey; as they do not 100% fit into this story, I think it is more suitable to list them here. I hope you enjoyed reading this. Give Summ a try, it comes with a generous free trial, no credit card required. Some additional notes and insights: Project planning is one of the most underestimated skills for solopreneurs. It saves you enormous time, and helps you to keep your focus up. Building B2B products beats building B2C products. Businesses are very willing to pay big bucks if your product helps them. On the other hand, spending a few hours per user who would pay $5/m probably is not worth your time. It doesn’t matter how brilliant your product is if no one uses it. If you cannot sell a product in a certain category/niche (or do not know how to sell it), it might be a good idea not to start a project in it. Going after new ideas and ventures is quite risky, especially if you don’t know how to market it. On the other hand, an already established category means that there is already demand. Whether this demand is sufficient or not is another issue. As long as there is enough demand for your product to fit in, any category/niche is good. Some might be better, some might be worse. Unless you are going hardcore B2B, you will need people to find your product by means of organic search. Always conduct thorough keyword research as soon as possible.

Running and selling multiple side projects alongside a 9-5
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Running and selling multiple side projects alongside a 9-5

My current side project started 56 days ago when I started writing 1,000 words per day. My core businesses are an agency and job board, and I just needed a creative outlet. The likes of Chris Guillebeau and Nathan Barry attribute their progression to writing so I thought I’d see if it might do the same for me. At first I was just vomiting words onto the screen, I made a blog and wrote mainly technical guides related to my skills. Over time I realised I was writing more and more about running a business as a solopreneur, or lean operator. There is tons of content out there giving you the Birds Eye of going from 0 to £10m. Inspiring stuff, but I think there is a void in real content, explaining the nuts and bolts of the how.  What is the day-to-day like for the solopreneurs who make a good living and have plenty of free time? That’s what I’m striving for anyway. I’m not talking about the 7-figure outliers. Or the ones teaching you to make content so you can have a business teaching others how to make content, and so on. I’m also sick of the ‘I made $X in 5 minutes and how you can too’  So, I started chatting to people in my network who run lean businesses and/or side hustles. I ask them a bit about their journey and ask them to teach something - how they operate, or a skill/process/system/tool that other people like you/me will find useful. One of my first chats was with Sam Dickie, who runs multiple side projects so thought I’d share here, see if others find it useful and get some feedback. I’ve removed all links as I’ve never posted on Reddit before so conscious of not being promotional, I’m posting this stuff to a tiny email list of friends with no upsells. Just finding my feet on whether others find it useful or not: — Sam is a serial entrepreneur who builds projects in his spare time whilst working a 9-5. He’s scaled and sold multiple ventures and currently runs one of the best newsletters out there for builders and entrepreneurs. Building audience through newsletters has always been a cornerstone strategy for him, so, along with sharing his advice on solopreneurism, he’s also generously shared his lean newsletter writing process. About Sam Sam is a Senior Product Manager who has spent the last 15 years working in the tech sector after starting his career as a town planner. In addition to his job he spends some of his spare time building side projects. These have included a 3D printing startup, a tech directory, a newsletter, a beta product directory, and consultancy. Sam is the epitome of making a success out of following your interest and curiosity. It’s clear he enjoys his business ventures and builds in a risk-free way.   It’s often touted by business gurus to avoid building around your interests, but Sam bucks the trend successfully. I think he’s someone who has already found his 1,000 true fans.  Descending rabbit holes, Sam’s journey of invention and curation 3D printing Sam’s first foray into launching a startup was with Fiilo, a 3D printing business. This was at the height of the 3D printing craze and he self-admits that he used the launch as an excuse to buy a 3D printer. He ended up with two and launching a product called GrowGo. GrowGo is a sustainable 3D-printed product that turns any bottle into somewhere that you can grow plants and herbs. He eventually sold this business and the printers, making around £10k. Along the way, he was exposed to various business tasks, including building a website in Weebly, the biggest nocode website builder of the time, and built an API that enabled print on demand for his product. NoCode.Tech The experiences of building as someone non-technical led to numerous friends asking how he built all of this tech. Back then, nocode wasn’t popular, and it had almost zero search volume, so Sam created a basic directory. A quick landing page on Weebly with a basic value prop, a short explanation and a list of the tools he had used before. It hit the top spot on Product Hunt, and he landed 2,000 subscribers in the first 48 hours. But, he hadn’t built it at this point, so he set about getting to work. He built the directory and list to 30,000 subs and monetised the site through advertising. At its peak with Sam, it was receiving about £2,000 per month in ad revenue. He was still working his 9-5 at this point, so thought it might be a good time to exit. The site was still growing, but it was becoming anxiety inducing whilst he was still working full-time. So, he ended up selling the site and making friend’s with the buyer. Fast forwarding a bit, Nocode.tech was eventually acquired by Stackr, a nocode app. Sam was working for their competitor at the time and ended up being offered a job by his friend who acquired the site. All of this from a side project in his area of passion. Creator Club After selling the directory, Sam lost his outlet for sharing his tools and learnings.  Being fascinated with curation and loving sifting through for nuggets, he invested more time into his personal website and launched Creator Club newsletter. Sam writes monthly and currently has over 8,000 subs. It’s one of the few newsletters that I let bypass my email filters and land in my main inbox. Life as a Part-Time Multipreneur Side Hustler If it’s not obvious already Sam is a curiosity led business creator. He’s found that the products without a revenue focus or intention have ironically outperformed those created for the sole purpose of creating money. He enjoys working on his side hustles. He could have run the Nocode.Tech for 10 more years and wouldn’t have tired of it as it’s a byproduct of his interest. For this reason, he has also created the Beta Directory, simply because he loves unearthing early-stage products. He admits he gets the fear when he thinks about quitting his 9-5, although he suspects if he devoted the same energy to one of his projects it could replace his income (no doubts from me here). This same fear means that he can run his ventures with less fear. This way, he can experiment with freedom and isn’t risking the ranch with a young family to consider. For example, recently he stopped paid sponsors on his newsletter as it was more stress than the value of the income to him. Sam divides his time on evenings and weekends (unequally) between the following: Creator Club Validation Co Beta directory Consultancy The pure side hustle status magnifies the need to run lean, let’s jump into his process…. Sam’s lean newsletter curation and creation process Starting out publishing his personal newsletter Going against his expertise, Sam originally over-engineered his process.  He curated with Feedly and tried to automate the full writing process with Zapier. The trouble is that there are too many points of failure which can lead the whole  chain to break down, and you spend more time fixing the system. For a 200 subscriber newsletter, he needed to pare things back. His set-up now Sam scaled back and now simple builds automations when he needs them. He keeps the process simple, right down to the design and any welcome automations. Keeping things real We touched on the trend that keeping things raw is better. Content has come full circle with the advent of AI. Everything looks too perfect and consequently, people’s tastes are changing. Sam mentioned watermarks that show content isn’t AI written, and we referenced content such as Greg Isenberg’s sketches, and Chris Donnelly’s image posts. \\Step by Step Process:\\ Using Stoop Inbox to manage sources Curation with Pocket Managing content with Airtable and Zapier Using Bearly to summarise Substack for writing Monitoring content sources Sam uses Stoop Inbox, an RSS curation tool, to manage his content sources. It gives him a dedicated email address for newsletters and he follows an Inbox Zero methodology. He checks in daily in Stoop, and on X, Reddit and IndieHackers. With X, he just uses the standard interface but has been careful to curate his feed, sometimes adding in extra notifications to hear from interesting people. Highlighting content When curating links, Sam uses Arc browser and the Pocket extension to save links. It’s super simple and lightweight. He creates tags which trigger an automation that curates the link to Airtable. If you watch the video, here’s a shoutout to Alice, the AI interface I use which has recently featured on Product Hunt. It’s a fantastic tool with bags of potential to enhance a solopreneur’s life. Ranking and sorting content He sends the links indexed using Pocket to a basic Airtable base via Zapier. From there, he grades the content and sets aside some time to read it in more depth. Pocket pulls through the title, metadata, and URL link. Review Sam does this manually but has used a tool as a shortcut for digesting long form content — Bearly.ai. Bearly.ai was created by Trung Phan and linking back to raw content, Trung is 1/3 of the hosts on the Not Investment Advice podcast. Its irreverent style and thumbnail are an example of a successful podcast that doesn’t over polish. Writing it all up Being a huge Notion fan (check out the free templates on his site), Sam originally used Notion for writing and linked it into Revue. When Elon sunsetted Revue, he switched to Substack. He loves the Substack interface so drafts in Substack based on a duplication of last month’s edition. Before publishing, Sam runs through a 10-point Notion checklist, which he shared with me. Parting Advice Keep your tool stack as lean as possible. Avoid tool switching to the shiny new object. Getting launched quickly is key. Don’t think that you have to be everywhere for distribution, Sam sticks with what he knows on X and LinkedIn. Overall, he advises just keeping things simple and therefore minimising risk. Resources He says they’re cliche, but I don’t agree; they’re timeless. Paul Graham of Y Combinator is someone Sam recommends following. He doesn’t write much, which is great as Sam gets anxiety when someone good often writes and he can’t keep up with the writing. His content is well thought out and distills complex concepts in entrepreneurship and startups. In addition, Sam loves Naval Ravikant’s approach. He mentions checking out the Almanac of Naval Ravikant for collected wisdom. Follow Sam’s Journey Again, not going to link here but you can find Sam’s stuff easily enough if you want to. His personal website is beautiful and contains loads of free downloads. He has also curated personal websites he admires if you need some inspiration. Sam is a super nice guy so reach out to him, I did before I started my personal blog recently, and he gave me some great advice. Also, worth keeping an eye on Validation Co, where he aims to help early-stage makers and creators validate their ideas. He’s building super slow — trying to enjoy the process without unachievable deadlines. Maintaining his stamina and passion. Amazing, I hope he writes more about that soon! -- That’s my second shot at an interview, hope you enjoyed it and found something useful in it. I’m talking to a marketplace founder who spends 2–3 hours per month his project, a multiple job board owner with a 9-5 and a leading book designer next. As this is my side project, should I keep going?

Solopreneur making $40k MRR with a No Code SaaS sideproject
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Solopreneur making $40k MRR with a No Code SaaS sideproject

Hey, I'm Elias and I do case studies analyzing successful startups and solopreneurs. I wanted to share the summarized version of this one with you because this entrepreneurial journey blew my mind. This post will be about FormulaBot (ExcelFormulaBot), an AI No Code SaaS founded by David Bressler back in August 2022. FormulaBot is currently making $40k MRR (monthly recurring revenue). How did the founder come up with the idea. David is a data guy who worked in analytics for several years. In July 2022, David got really interested in AI, especially ChatGPT. One night, he tried it out at home, just like we all did back in the time. But in his case, trying ChatGPT gave him a big idea. That idea ended up making him a lot of money and changing the life of 750 million people who use Excel. That night David started by asking GPT easy questions, then complex ones. Since he used Excel a lot and helped his colleagues with it, he thought about an AI that could make Excel easier, like generating formulas from text. He looked online but found nothing. Seeing a big chance, he decided to do something about it. What challenges did the founder face. But David didn’t have any idea about how to develop an app. However, with no-code tools this is not a problem anymore. He discovered Bubble, a no-code web app tool that could connect with the OpenAI API.After, learning Bubble from YouTube tutorials and through trial and error and spending his nights studying the OpenAI API documentation, he launched the first version of the app in around three weeks. Strategies that made the project successful. David validated his idea by posting about ExcelFormulaBot on a Reddit Excel subreddit, receiving surprising attention with 10,000 upvotes. This encouraged him to offer the tool for free to gather feedback. Facing a hefty $4,999 API bill after the Reddit post, David quickly monetized his product with a subscription-based SaaS website. On launch day, 82 customers signed up, surpassing his expectations. A successful Product Hunt launch followed, generating $2.4k in sales within 24 hours, and a TikTok influencer with 4.5 million followers brought in thousands of new users overnight with a viral video. Marketing approach: -Paid ads: FormulaBot boosted website traffic with Paid Ads, notably on Google Ads, prioritizing Quality Score. This ensured ads aligned better with user searches, maximizing visibility and cost-efficiency, targeting those seeking Excel formula assistance. -SEO: a) Content/Keyword optimization: FormulaBot improved its SEO by making helpful pages about Excel formulas, like guides on topics such as "How to use SUMIFS." b) Site Speed Enhancement: David boosted FormulaBot's marketing site speed by moving it from Bubble to Framer, aiming to improve user experience and SEO performance. c) On-page optimization: David optimized FormulaBot's on-page elements by adjusting title tags, meta descriptions, and content to enhance SEO performance and align with search intent. These strategic refinements aimed to address ranking declines and emphasize FormulaBot's uniqueness, ultimately improving its visibility and competitiveness in search results. -Virality: FormulaBot went viral as users found it highly useful and cool. Influencers on platforms like TikTok and Twitter shared it with their followers because they found it valuable. Offering numerous free features further enhanced its appeal. Lessons: successes and mistakes. ✅ Leverage industry expertise: David identified a problem in analytics and used his experience to start an online business addressing it, turning an industry challenge into a profitable venture. ✅ Embrace learning new skills: Despite lacking initial technical know-how, David learned what he needed to develop the software himself, demonstrating a commitment to continuous learning and adaptability crucial for success. ❌ Minimize dependency on third parties: Relying solely on the ChatGPT API poses risks for FormulaBot. Any issues with the API could disrupt functionality and limit scalability. ⁉️ Caution with free tools: Offering a free tool can attract users and drive viral growth, but converting them to paying customers is challenging. Avoid relying solely on a 100% free model unless your revenue comes from non-user sources like ads. For businesses dependent on user subscriptions or purchases, balancing user attraction with conversion challenges is crucial. How could you replicate this idea step-by-step. To replicate the success of FormulaBot and similar AI wrapper startups, it's crucial to tread carefully in a competitive market. Avoid mere replication of existing solutions unless you can offer something distinct or superior. Consider these steps to effectively develop an AI Wrapper/ChatGPT wrapper product using Bubble as a no-code tool: Design the user interface: Utilize Bubble's drag-and-drop editor to create a user-friendly interface with input fields, buttons, and result displays. Set up workflows: Define workflows to connect the interface with the ChatGPT API, enabling seamless interaction between users and the AI. Integrate the ChatGPT API: Obtain the API key from OpenAI and integrate it into your app using Bubble's API connector feature. Test and gather feedback: Thoroughly test your app, soliciting feedback to refine functionality and usability. Refine and optimize: Continuously improve your app based on user input and testing results to enhance performance and user experience. The in-depth version of the case study was originally posted here. Feel free to comment if you have any questions, and let me know which similar ideas you'd like me to analyze.

I spent 6 months on a web app as a side project, and got 0 users. Here is my story.
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I spent 6 months on a web app as a side project, and got 0 users. Here is my story.

Edit Thank you all so much for your time reading my story. Your support, feedback, criticism, and skepticism; all helped me a lot, and I couldn't appreciate it enough \^\_\^ I very rarely have stuff to post on Reddit, but I share how my project is going on, just random stuff, and memes on X. In case few might want to keep up 👀 TL;DR I spent 6 months on a tool that currently has 0 users. Below is what I learned during my journey, sharing because I believe most mistakes are easily avoidable. Do not overestimate your product and assume it will be an exception to fundamental principles. Principles are there for a reason. Always look for validation before you start. Avoid building products with a low money-to-effort ratio/in very competitive fields. Unless you have the means, you probably won't make it. Pick a problem space, pick your target audience, and talk to them before thinking about a solution. Identify and match their pain points. Only then should you think of a solution. If people are not overly excited or willing to pay in advance for a discounted price, it might be a sign to rethink. Sell one and only one feature at a time. Avoid everything else. If people don't pay for that one core feature, no secondary feature will change their mind. Always spend twice as much time marketing as you do building. You will not get users if they don't know it exists. Define success metrics ("1000 users in 3 months" or "$6000 in the account at the end of 6 months") before you start. If you don't meet them, strongly consider quitting the project. If you can't get enough users to keep going, nothing else matters. VALIDATION, VALIDATION, VALIDATION. Success is not random, but most of our first products will not make a success story. Know when to admit failure, and move on. Even if a product of yours doesn't succeed, what you learned during its journey will turn out to be invaluable for your future. My story So, this is the story of a product that I’ve been working on for the last 6 months. As it's the first product I’ve ever built, after watching you all from the sidelines, I have learned a lot, made many mistakes, and did only a few things right. Just sharing what I’ve learned and some insights from my journey so far. I hope that this post will help you avoid the mistakes I made — most of which I consider easily avoidable — while you enjoy reading it, and get to know me a little bit more 🤓. A slow start after many years Summ isn’t the first product I really wanted to build. Lacking enough dev skills to even get started was a huge blocker for so many years. In fact, the first product I would’ve LOVED to build was a smart personal shopping assistant. I had this idea 4 years ago; but with no GPT, no coding skills, no technical co-founder, I didn’t have the means to make it happen. I still do not know if such a tool exists and is good enough. All I wanted was a tool that could make data-based predictions about when to buy stuff (“buy a new toothpaste every three months”) and suggest physical products that I might need or be strongly interested in. AFAIK, Amazon famously still struggles with the second one. Fast-forward a few years, I learned the very basics of HTML, CSS, and Vanilla JS. Still was not there to build a product; but good enough to code my design portfolio from scratch. Yet, I couldn’t imagine myself building a product using Vanilla JS. I really hated it, I really sucked at it. So, back to tutorial hell, and to learn about this framework I just heard about: React.React introduced so many new concepts to me. “Thinking in React” is a phrase we heard a lot, and with quite good reasons. After some time, I was able to build very basic tutorial apps, both in React, and React Native; but I have to say that I really hated coding for mobile. At this point, I was already a fan of productivity apps, and had a concept for a time management assistant app in my design portfolio. So, why not build one? Surely, it must be easy, since every coding tutorial starts with a todo app. ❌ WRONG! Building a basic todo app is easy enough, but building one good enough for a place in the market was a challenge I took and failed. I wasted one month on that until I abandoned the project for good. Even if I continued working on it, as the productivity landscape is overly competitive, I wouldn’t be able to make enough money to cover costs, assuming I make any. Since I was (and still am) in between jobs, I decided to abandon the project. 👉 What I learned: Do not start projects with a low ratio of money to effort and time. Example: Even if I get 500 monthly users, 200 of which are paid users (unrealistically high number), assuming an average subscription fee of $5/m (such apps are quite cheap, mostly due to the high competition), it would make me around $1000 minus any occurring costs. Any founder with a product that has 500 active users should make more. Even if it was relatively successful, due to the high competition, I wouldn’t make any meaningful money. PS: I use Todoist today. Due to local pricing, I pay less than $2/m. There is no way I could beat this competitive pricing, let alone the app itself. But, somehow, with a project that wasn’t even functional — let alone being an MVP — I made my first Wi-Fi money: Someone decided that the domain I preemptively purchased is worth something. By this point, I had already abandoned the project, certainly wasn’t going to renew the domain, was looking for a FT job, and a new project that I could work on. And out of nowhere, someone hands me some free money — who am I not to take it? Of course, I took it. The domain is still unused, no idea why 🤔. Ngl, I still hate the fact that my first Wi-Fi money came from this. A new idea worth pursuing? Fast-forward some weeks now. Around March, I got this crazy idea of building an email productivity tool. We all use emails, yet we all hate them. So, this must be fixed. Everyone uses emails, in fact everyone HAS TO use emails. So, I just needed to build a tool and wait for people to come. This was all, really. After all, the problem space is huge, there is enough room for another product, everyone uses emails, no need for any further validation, right? ❌ WRONG ONCE AGAIN! We all hear from the greatest in the startup landscape that we must validate our ideas with real people, yet at least some of us (guilty here 🥸) think that our product will be hugely successful and prove them to be an exception. Few might, but most are not. I certainly wasn't. 👉 Lesson learned: Always validate your ideas with real people. Ask them how much they’d pay for such a tool (not if they would). Much better if they are willing to pay upfront for a discount, etc. But even this comes later, keep reading. I think the difference between “How much” and “If” is huge for two reasons: (1) By asking them for “How much”, you force them to think in a more realistic setting. (2) You will have a more realistic idea on your profit margins. Based on my competitive analysis, I already had a solution in my mind to improve our email usage standards and email productivity (huge mistake), but I did my best to learn about their problems regarding those without pushing the idea too hard. The idea is this: Generate concise email summaries with suggested actions, combine them into one email, and send it at their preferred times. Save as much as time the AI you end up with allows. After all, everyone loves to save time. So, what kind of validation did I seek for? Talked with only a few people around me about this crazy, internet-breaking idea. The responses I got were, now I see, mediocre; no one got excited about it, just said things along the lines of “Cool idea, OK”. So, any reasonable person in this situation would think “Okay, not might not be working”, right? Well, I did not. I assumed that they were the wrong audience for this product, and there was this magical land of user segments waiting eagerly for my product, yet unknowingly. To this day, I still have not reached this magical place. Perhaps, it didn’t exist in the first place. If I cannot find it, whether it exists or not doesn’t matter. I am certainly searching for it. 👉 What I should have done: Once I decide on a problem space (time management, email productivity, etc.), I should decide on my potential user segments, people who I plan to sell my product to. Then I should go talk to those people, ask them about their pains, then get to the problem-solving/ideation phase only later. ❗️ VALIDATION COMES FROM THE REALITY OUTSIDE. What validation looks like might change from product to product; but what invalidation looks like is more or less the same for every product. Nico Jeannen told me yesterday “validation = money in the account” on Twitter. This is the ultimate form of validation your product could get. If your product doesn’t make any money, then something is invalidated by reality: Your product, you, your idea, who knows? So, at this point, I knew a little bit of Python from spending some time in tutorial hell a few years ago, some HTML/CSS/JS, barely enough React to build a working app. React could work for this project, but I needed easy-to-implement server interactivity. Luckily, around this time, I got to know about this new gen of indie hackers, and learned (but didn’t truly understand) about their approach to indie hacking, and this library called Nextjs. How good Next.js still blows my mind. So, I was back to tutorial hell once again. But, this time, with a promise to myself: This is the last time I would visit tutorial hell. Time to start building this "ground-breaking idea" Learning the fundamentals of Next.js was easier than learning of React unsurprisingly. Yet, the first time I managed to run server actions on Next.js was one of the rarest moments that completely blew my mind. To this day, I reject the idea that it is something else than pure magic under its hood. Did I absolutely need Nextjs for this project though? I do not think so. Did it save me lots of time? Absolutely. Furthermore, learning Nextjs will certainly be quite helpful for other projects that I will be tackling in the future. Already got a few ideas that might be worth pursuing in the head in case I decide to abandon Summ in the future. Fast-forward few weeks again: So, at this stage, I had a barely working MVP-like product. Since the very beginning, I spent every free hour (and more) on this project as speed is essential. But, I am not so sure it was worth it to overwork in retrospect. Yet, I know I couldn’t help myself. Everything is going kinda smooth, so what’s the worst thing that could ever happen? Well, both Apple and Google announced their AIs (Apple Intelligence and Google Gemini, respectively) will have email summarization features for their products. Summarizing singular emails is no big deal, after all there were already so many similar products in the market. I still think that what truly matters is a frictionless user experience, and this is why I built this product in a certain way: You spend less than a few minutes setting up your account, and you get to enjoy your email summaries, without ever visiting its website again. This is still a very cool concept I really like a lot. So, at this point: I had no other idea that could be pursued, already spent too much time on this project. Do I quit or not? This was the question. Of course not. I just have to launch this product as quickly as possible. So, I did something right, a quite rare occurrence I might say: Re-planned my product, dropped everything secondary to the core feature immediately (save time on reading emails), tried launching it asap. 👉 Insight: Sell only one core feature at one time. Drop anything secondary to this core feature. Well, my primary occupation is product design. So one would expect that a product I build must have stellar design. I considered any considerable time spent on design at this stage would be simply wasted. I still think this is both true and wrong: True, because if your product’s core benefits suck, no one will care about your design. False, because if your design looks amateurish, no one will trust you and your product. So, I always targeted an average level design with it and the way this tool works made it quite easy as I had to design only 2 primary pages: Landing page and user portal (which has only settings and analytics pages). However, even though I knew spending time on design was not worth much of my time, I got a bit “greedy”: In fact, I redesigned those pages three times, and still ended up with a so-so design that I am not proud of. 👉 What I would do differently: Unless absolutely necessary, only one iteration per stage as long as it works. This, in my mind, applies to everything. If your product’s A feature works, then no need to rewrite it from scratch for any reason, or even refactor it. When your product becomes a success, and you absolutely need that part of your codebase to be written, do so, but only then. Ready to launch, now is th etime for some marketing, right? By July 26, I already had a “launchable” product that barely works (I marked this date on a Notion docs, this is how I know). Yet, I had spent almost no time on marketing, sales, whatever. After all, “You build and they will come”. Did I know that I needed marketing? Of course I did, but knowingly didn’t. Why, you might ask. Well, from my perspective, it had to be a dev-heavy product; meaning that you spend most of your time on developing it, mostly coding skills. But, this is simply wrong. As a rule of thumb, as noted by one of the greatests, Marc Louvion, you should spend at least twice of the building time on marketing. ❗️ Time spent on building \* 2 people don’t know your product > they don’t use your product > you don’t get users > you don’t make money Easy as that. Following the same reasoning, a slightly different approach to planning a project is possible. Determine an approximate time to complete the project with a high level project plan. Let’s say 6 months. By the reasoning above, 2 months should go into building, and 4 into marketing. If you need 4 months for building instead of 2, then you need 8 months of marketing, which makes the time to complete the project 12 months. If you don’t have that much time, then quit the project. When does a project count as completed? Well, in reality, never. But, I think we have to define success conditions even before we start for indie projects and startups; so we know when to quit when they are not met. A success condition could look like “Make $6000 in 12 months” or “Have 3000 users in 6 months”. It all depends on the project. But, once you set it, it should be set in stone: You don’t change it unless absolutely necessary. I suspect there are few principles that make a solopreneur successful; and knowing when to quit and when to continue is definitely one of them. Marc Louvion is famously known for his success, but he got there after failing so many projects. To my knowledge, the same applies to Nico Jeannen, Pieter Levels, or almost everyone as well. ❗️ Determining when to continue even before you start will definitely help in the long run. A half-aed launch Time-leap again. Around mid August, I “soft launched” my product. By soft launch, I mean lazy marketing. Just tweeting about it, posting it on free directories. Did I get any traffic? Surely I did. Did I get any users? Nope. Only after this time, it hit me: “Either something is wrong with me, or with this product” Marketing might be a much bigger factor for a project’s success after all. Even though I get some traffic, not convincing enough for people to sign up even for a free trial. The product was still perfect in my eyes at the time (well, still is ^(\_),) so the right people are not finding my product, I thought. Then, a question that I should have been asking at the very first place, one that could prevent all these, comes to my mind: “How do even people search for such tools?” If we are to consider this whole journey of me and my so-far-failed product to be an already destined failure, one metric suffices to show why. Search volume: 30. Even if people have such a pain point, they are not looking for email summaries. So, almost no organic traffic coming from Google. But, as a person who did zero marketing on this or any product, who has zero marketing knowledge, who doesn’t have an audience on social media, there is not much I could do. Finally, it was time to give up. Or not… In my eyes, the most important element that makes a founder (solo or not) successful (this, I am not by any means) is to solve problems. ❗️ So, the problem was this: “People are not finding my product by organic search” How do I make sure I get some organic traffic and gets more visibility? Learn digital marketing and SEO as much as I can within very limited time. Thankfully, without spending much time, I came across Neil Patel's YT channel, and as I said many times, it is an absolute gold mine. I learned a lot, especially about the fundamentals, and surely it will be fruitful; but there is no magic trick that could make people visit your website. SEO certainly helps, but only when people are looking for your keywords. However, it is truly a magical solution to get in touch with REAL people that are in your user segments: 👉 Understand your pains, understand their problems, help them to solve them via building products. I did not do this so far, have to admit. But, in case you would like to have a chat about your email usage, and email productivity, just get in touch; I’d be delighted to hear about them. Getting ready for a ProductHunt launch The date was Sept 1. And I unlocked an impossible achievement: Running out of Supabase’s free plan’s Egres limit while having zero users. I was already considering moving out of their Cloud server and managing a Supabase CLI service on my Hetzner VPS for some time; but never ever suspected that I would have to do this quickly. The cheapest plan Supabase offers is $25/month; yet, at that point, I am in between jobs for such a long time, basically broke, and could barely afford that price. One or two months could be okay, but why pay for it if I will eventually move out of their Cloud service? So, instead of paying $25, I spent two days migrating out of Supabase Cloud. Worth my time? Definitely not. But, when you are broke, you gotta do stupid things. This was the first time that I felt lucky to have zero users: I have no idea how I would manage this migration if I had any. I think this is one of the core tenets of an indie hacker: Controlling their own environment. I can’t remember whose quote this is, but I suspect it was Naval: Entrepreneurs have an almost pathological need to control their own fate. They will take any suffering if they can be in charge of their destiny, and not have it in somebody else’s hands. What’s truly scary is, at least in my case, we make people around us suffer at the expense of our attempting to control our own fates. I know this period has been quite hard on my wife as well, as I neglected her quite a bit, but sadly, I know that this will happen again. It is something that I can barely help with. Still, so sorry. After working the last two weeks on a ProductHunt Launch, I finally launched it this Tuesday. Zero ranking, zero new users, but 36 kind people upvoted my product, and many commented and provided invaluable feedback. I couldn't be more grateful for each one of them 🙏. Considering all these, what lies in the future of Summ though? I have no idea, to be honest. On one hand, I have zero users, have no job, no income. So, I need a way to make money asap. On the other hand, the whole idea of it revolves around one core premise (not an assumption) that I am not so willing to share; and I couldn’t have more trust in it. This might not be the best iteration of it, however I certainly believe that email usage is one of the best problem spaces one could work on. 👉 But, one thing is for certain: I need to get in touch with people, and talk with them about this product I built so far. In fact, this is the only item on my agenda. Nothing else will save my brainchild <3. Below are some other insights and notes that I got during my journey; as they do not 100% fit into this story, I think it is more suitable to list them here. I hope you enjoyed reading this. Give Summ a try, it comes with a generous free trial, no credit card required. Some additional notes and insights: Project planning is one of the most underestimated skills for solopreneurs. It saves you enormous time, and helps you to keep your focus up. Building B2B products beats building B2C products. Businesses are very willing to pay big bucks if your product helps them. On the other hand, spending a few hours per user who would pay $5/m probably is not worth your time. It doesn’t matter how brilliant your product is if no one uses it. If you cannot sell a product in a certain category/niche (or do not know how to sell it), it might be a good idea not to start a project in it. Going after new ideas and ventures is quite risky, especially if you don’t know how to market it. On the other hand, an already established category means that there is already demand. Whether this demand is sufficient or not is another issue. As long as there is enough demand for your product to fit in, any category/niche is good. Some might be better, some might be worse. Unless you are going hardcore B2B, you will need people to find your product by means of organic search. Always conduct thorough keyword research as soon as possible.

How I went from $27 to $3K as a solopreneur still in a 9-5
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jottrledThis week

How I went from $27 to $3K as a solopreneur still in a 9-5

My journey started back in November 2023. I was scrolling through Twitter and YouTube and saw a word that I had never come across before. Solopreneur. The word caught my eye. Mainly because I was pretty sure I knew what it meant even though it's not a word you'll find in the dictionary. I liked what it was describing. A solo entrepreneur. A one man business. It completely resonated with me. As a software engineer by trade I'm used to working alone, especially since the pandemic hit and we were forced to work remotely. See, I always wanted to ditch the 9-5 thing but thought that was too big and too scary for a single person to do. Surely you would need a lot of money to get started, right? Surely you would need investors? The whole concept seemed impossible to me. That was until I found all the success stories. I became obsessed with the concept of solopreneurship. As I went further down the rabbit hole I found people like Justin Welsh, Kieran Drew and Marc Louvion to name a few. All of whom have one person businesses making huge money every year. So I thought, if they can do it, why can't I? People like this have cleared the pathway for those looking to escape the 9-5 grind. I decided 2024 would be the year I try this out. My main goal for the year? Build a one man business, earn my first $ online and learn a sh\*t ton along the way. My main goal in general? Build my business to $100K per year, quit my 9-5 and live with freedom. From December 2023 to February 2024 I began brainstorming ideas. I was like a lost puppy looking for his ball. How on earth did people find good ideas? I began writing everything and anything that came to mind down in my notes app on my phone. By February I would have approximately 70 ideas. Each as weird and whacky as the other. I was skeptical though. If I went through all the trouble of building a product for one of these ideas how would I know if anyone would even be interested in using it? I got scared and took a break for a week. All these ideas seemed too big and the chance that they would take off into the atmosphere was slim (in my mind anyways). I was learning more and more about solopreneurship as the weeks went on so I decided to build a product centered around everything I was learning about. The idea was simple. Enter a business idea and use AI to give the user details about how to market it, who their target customers were, what to write on their landing page, etc. All for a measly $27 per use. I quickly built it and launched on March 3rd 2024. I posted about it on Indie Hackers, Reddit and Hacker News. I was so excited about the prospect of earning my first internet $! Surely everyone wanted to use my product! Nope...all I got was crickets. I was quickly brought back down to earth. That was until 5 days later. I looked at my phone and had a new Stripe notification! Cha-ching! My first internet $. What a feeling! That was goal number 1 complete. It would be another 6 days before I would get my second sale...and then another 15 days to get my third. It was an emotional rollercoaster. I went from feeling like quitting the 9-5 was actually possible to thinking that maybe the ups and downs aren't worth it. On one hand I had made my first internet dollar so I should my ecstatic, and don't get me wrong, I was but I wanted more. More validation that I could do this long term. By May I was starting to give up on the product. I had learned so much in the past few months about marketing, SEO, building an audience, etc. and I wanted to build something that I thought could have more success so I focused on one critical thing that I had learned about. What was it? Building a product that had SEO potential. A product that I knew hundreds of people were looking for. See this was my thinking - If I could find a keyword that people were searching for on Google hundreds/thousands of times every month and it was easy to rank high on search engines then I would go all in (in SEO land this equates to a Keyword that has a Keyword Difficulty of = 500). I began researching and found that the keyword "micro saas ideas" was being searched for around 600 times each month. Micro Saas was something that really interested me. It was perfect for solopreneurs. Small software products that 1 person could build. What's not to like if you're in the game of software and solopreneurship? Researching keywords like this became like a game for me. I was hooked. I was doing it every day, finding gems that were being searched for hundreds and thousands of times every month that still had potential. That's when I came up with my next product idea. I decided to create a database of Micro Saas Ideas all with this sort of SEO potential. See if you can build a product that you know people are looking for then that's all the validation you need. So I put this theory to the test. I created a database of Micro Saas Ideas with SEO Potential and launched it in June 2024. This time it was different. I made $700 in the first week of launching. A large contrast to my previous failed attempt at becoming the worlds greatest solopreneur. Since launch I have grown the product to $3K and I couldn't be happier. I know what you're saying, $3K isn't a lot. But it's validation. It's validation that I can earn $ online. Validation that I can grow a business and it gives me hope that one day I'll be able to quit that 9-5 grind. My plan is to keep growing the business. I expect there to be a few challenges up ahead but I'll tackle them as I go and learn from the failures and successes. I have a newsletter where I share Micro Saas Ideas with SEO potential every week which I'll leave below in the first comment. Feel free to come along for the ride. If not I hope this post brings you some value If you're thinking about starting as a solopreneur, stop thinking and start doing, you won't regret it.

How to get your first 10 customers with cold email
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LieIgnorant6304This week

How to get your first 10 customers with cold email

Cold email is an insane channel for growth, especially for bootstrapped startups as it's very low cost but completely scalable. Yet there's a huge difference between blind cold emailing and crafting personalized outreach for select individuals. The latter is a legit channel which makes many businesses scale in short amounts of time (i.e. see Alex Hormozi’s ‘$100 Million Dollar Offer’). My goal here is to help other founders do what I did but quicker. So you can learn faster. And then teach me something new too. These are the step-by-step lessons I've learnt as a bootstrapped founder, showing you how to use cold email to get your first customers: Find your leads Write engaging email copy Personalize your outreach Send emails Scale up Find your leads This is a key step. Once you figure out exactly who you want to target and where to find them, you'll be printing money. There's a few different ways to go about finding valuable leads. The secret? Keep testing different approaches until you strike gold. First, dedicate some time every day to find and organise leads. Then, keep an eye on your numbers and bounce rates. If something's not working, switch it up. Stick with what's bringing in results and ditch what's not. It's all about staying flexible and learning as you go. Apollo.io is a great starting point as an effective lead source. Their tool allows you to specify filters including job titles, location, company size, industry, keywords, technologies, and revenue. Get specific with your searches to find your ideal customers. Once you have some results you can save and export them, you'll get a list of contact information including name, email, company, LinkedIn, ready to be verified and used. LinkedIn Sales Navigator is another good source. You can either do manual searches or use a scraper to automate the process. The scrapers I'd recommend checking out are FindyMail and Evaboot. As with Apollo, it's best to get very specific with your targeting so you know the prospect will be interested in your offer. BuiltWith is more expensive but ideal if you're targeting competitors. With BuiltWith you can build lists based on what technologies companies are using. For example if you're selling a Shopify app, you'd want to know websites or stores using Shopify, and reach out to them. The best lead sources will always be those that haven't been contacted a lot in the past. If you are able to find places where your target audience uniquely hangs out, and you can get their company website domains, they have the potential to be scrapped, and you have a way to personalize like "I spotted your comment on XYZ website". Once you've got your leads, keep them organized. Set up folders for different niches, countries, company sizes, so you can review what works and what doesn't. One more thing – before you start firing off emails, make sure those addresses are verified. Always use an email verifier to clean up your list and avoid bounces that may affect your sending reputation, and land you in the spam folder. I use Neverbounce for this but there are other tools available. Write engaging email copy Writing a good copy that gets replies is difficult, it changes depending on your offer/audience and nobody knows what's going to work. The best approach is to keep testing different targeting and messaging until you find what works. However, there are some key rules to stick to that I've outlined. For the subject line, keep it short and personalized. Try to write something that sparks interest, and mention the recipients name: Thought you’d like this {{first name}} {{firstName}} - quick question For the email body it's best to use a framework of personalization, offer, then call to action. Personalization is an entire subject in its own right, which I've covered below. In short, a personalized email opener is the best way to grab their attention, and let them know the email is relevant to them and to keep reading. Take it from Alex Hormozi and his $100M Offers playbook – your offer is very important to get right. Make sure your offer hits the mark for your target audience, and get as specific as possible. For example: I built a SaaS shopify app for small ecommerce businesses selling apparel that doubles your revenue in 60-days or your money back. We developed a cold email personalization tool for lead generation agencies that saves hundreds of hours, and can 3x your reply rate. Lastly, the CTA. The goal here isn't to get sign-ups directly from your first email. It's better to ask a brief question about whether the prospect would be interested in learning more. Something very low friction, that warrants a response. Some examples might include: Would you be interested in learning more about this? Can we connect a bit more on this? Mind if I send over a loom I recorded for you? Never send any links in the first email. You've reached out to this person because you have good reason to believe they'd find real value in your offer, and you want to verify if that's the case. After you get one reply, this is a great positive signal and from there you can send a link, book a call, provide a free resource, whatever makes sense based on their response. Personalize your outreach Personalization is one of the most important parts of the process to get right. Your recipient probably receives a multitude of emails every day, how can you make yours stand out, letting them know you've done your research, and that your email is relevant to them? Personalizing each email ensures you get more positive replies, and avoid spam filters, as your email is unique and hasn't been copied and pasted a million times over. The goal is to spark the recipient's interest, and let them know that you're contacting them for good reason. You might mention a recent achievement, blog post or product release that led you to reach out to the prospect specifically. For example: Your post on "Doing Nothing" gave me a good chuckle. Savvy marketing on Cadbury's part. Saw that you've been at Google for just under a year now as a new VP of sales. Spotted that you've got over 7 years of experience in the digital marketing space. Ideally you'll mention something specifically about the prospect or their company that relates to your offer. The downside to personalization is that it's hard to get right, and very time consuming at scale, but totally worth it. Full disclosure, me and my partner Igor just launched our new startup ColdClicks which uses AI to generate hyper-personalized email openers at scale. We built the tool as we were sending hundreds of emails a day, and personalizing every individual email took hours out of our day. ColdClicks automates this process, saving you time and getting you 2-3x more replies. Send emails At this stage you've decided on who you're targeting, you've mined some leads, and written copy. Now it's time to get sending. You can do this manually by copy and pasting each message, but one of the reasons cold email is so powerful is that it's scalable. When you build a process that gets customers, you'll want to send as many emails as you can to your target market. To get started quickly, you can use a mail-merge gmail tool, the best I've used is Maileteor. With Maileteor you upload your lead data to Google sheets, set-up an email template and Mailmetor will send out emails every day automatically. In your template you can define variables including name, company, and personalization to ensure your email is unique for each recipient. Alternatively, you may opt for a more comprehensive tool such as Instantly. Instantly includes unlimited email sending and accounts. There's more initial setup involved as you'll need to set-up Google workspace, buy sending domains, and warm up your email accounts, but when you become familiar with the process you can build a powerful lead generation / customer acquisition machine. Some key points to note, it's very important to warm up any new email accounts you set up. Warmup is the process of gradually establishing a positive reputation with email service providers like Gmail or Yahoo. Make sure to set up DKIM and DMARC on those new email accounts too, to maximise your chances of landing in the inbox. Scale up Once you've found a process that works, good things happen, and it becomes a numbers game. As you get replies and start to see new users signing up, you'll want to scale the process and send more emails. It's straightforward to add new sending accounts in a sending tool like Instantly, and you'll want to broaden your targeting when mining to test new markets. Unfortunately, sending more emails usually comes with a drop in reply rate as you have less time to personalize your messaging for each recipient. This is where ColdClicks shines. The tool allows you to upload thousands of leads and generate perfectly relevant email personalizations for every lead in your list, then export to your favorite sending tool. The examples I listed above in the personalization section were all generated by ColdClicks. Wrapping it up Cold email is an amazing way to validate your product and get new customers. The channel gets a bad rap, but there's a huge difference between blind cold emailing and crafting personalized outreach for individuals who will find value in your product. It's perfect for bootstrapped founders due to its affordability and scalability, and it's the driver of growth for many SaaS businesses. Time to get your first 10 customers! As you start sending, make it a habit to regularly check for new leads. Always experiment with market/messaging, track every campaign so you can learn what's working and iterate, and when you do get positive responses, reply as soon as you can!

Built an AI to stop me from procrastinating on Reddit, it actually spies on my browser tabs & it's kinda freaking me out (but it works)
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sameed_aThis week

Built an AI to stop me from procrastinating on Reddit, it actually spies on my browser tabs & it's kinda freaking me out (but it works)

hey guys, So, I have a problem. A major procrastination problem. You know the type? I start all good, like, "ok, I'm gonna spend the next 2 hrs REALLY researching this specific Reddit thread about optimizing workflow automation for small businesses." (That's literally what I'm supposed to be doing rn, lol) And then... BAM. Suddenly I'm 15 posts deep into r/aww looking at baby sloths, or somehow I've ended up on Wikipedia reading about competitive hot dog eating. It's like my brain has a mind of its own, seriously. I've tried everything. Cold Turkey, Freedom, all those blocker apps. And honestly? They kinda suck. They're so... blunt. Like, "NO REDDIT FOR U!!" But I need Reddit for my actual research! It is my research, ffs. The problem is those apps just see a URL and block it. They don't understand context. They're just digital bouncers, and terrible ones. Total roadblocks, and a complete pain. That's why I got desperate. I even spent, like, 3 solid hrs one night just chatting with an AI cuz I was too embarrassed to admit to my friends how bad I was at staying on track. Pathetic, I know. But that's when it hit me. I needed something that understood what I was supposed to be doing, and then actively, intelligently, stopped me when I got sidetracked. Something that, like, gets that this is what I meant to use, so it blocks other posts or subs. So, I built it. It's a Chrome extension, and it's basically like having a tiny, hyper-observant AI therapist/drill sergeant living in my browser. Here's the freaky part: it actually watches what I'm doing. Like, it learns my specific task. If I tell it I'm researching on Reddit, it lets me use Reddit, but only for that specific research. If I try to sneak off to r/funny or check my notifs, it knows. It's not just blocking URLs; it's analyzing the content of the pages I'm on and comparing it to what I'm supposed to be doing. It even has these lil "achievement" things, which sound cheesy, but seeing "Focused for 90 mins straight!" pop up is weirdly motivating. And it has this brutal feature that shows u, in plain numbers, how much time you've wasted. Ouch. It's been working, which is amazing, and scary at the same time! Like, the scary part is, it feels weird sharing my own edge over procrastination. I mean, if u use my lil tool too! It also kinda gives off that creepy, AI overlord watching my thoughts vibe? Why I'm even posting this: I'm looking for a few (maybe 5?) people who are as desperate as I was. People who've tried every productivity hack, app, and technique, and are still staring at the ceiling at 3 am, filled with regret. If this sounds familiar, DM "DM me". Tell me your worst procrastination story. The winner (loser?) gets a copy. I need honest, brutally honest, feedback. Does this actually work for anyone else, or am I just fooling myself? Edit: shared the extension with some of you, and for others you can give it a spin here i made it live to the chrome store: https://getfocusai.com/

My humble analysis on how @levelsio grew PhotoAI to 155K/m
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PodcastSummaryGuyThis week

My humble analysis on how @levelsio grew PhotoAI to 155K/m

In 2023,@levelsiol aunched PhotoAi and nailed perfect timing with the AI-generated photo trend He saw the rise of AI Image Generators as early as Jan 2023—when search volume was just 246K. Fast forward to now, that’s exploded to 1M+ searches/month! @levelsio didn’t guess—he tracked this exponential growth, built fast, and launched a product that people needed before they even realized it themselves. That’s how you go from idea to$155K/month in revenue. But why does this work? Demand Explosion: The need for AI tools like PhotoAI surged as more creators, marketers, and businesses searched for automated ways to generate images (graph 1 shows this insane growth curve). Timing is everything: When trends move this fast, you have to act quicker. He launched at the right time, capturing the early adopters and setting the foundation for sustainable revenue (graph 2 showcases the clear spike). Build based on data, not assumptions: The growth of AI Character Generators also hit major traction (graph 3). Both trends signaled an opportunity, and he jumped in before the market was saturated. Lesson: Don’t guess what people want—watch the trends and build fast. Trends show you what’s working, before the mainstream even knows it. This is how you launch products that solve real problems. Check out the graphs for context: AI Image Generator Growth \(graph 1\) Search volume spiking \(graph 2\) AI Character Generators \(graph 3\) Use data, not just intuition. Track the trends and execute. Simple but powerful. I hope you liked this thread.

PlumbingJobs.com - I launched a niche job board with hand-curated jobs for plumbers. Here's the summary of how it's going after the 3rd month
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OnlineJobsPHmodThis week

PlumbingJobs.com - I launched a niche job board with hand-curated jobs for plumbers. Here's the summary of how it's going after the 3rd month

On October 12th 2024, I launched PlumbingJobs.com, and this is my first update (January 2025) in what I hope will be a long journey. To stay accountable and track progress, I’ll be sharing monthly updates about the site's stats, achievements, challenges, and my plans moving forward. While these posts are mostly to document the journey, I hope they’ll also be helpful to others, especially members of r/SideProject who might be working on their own first online projects. If this post isn’t a good fit for this subreddit, I’m happy to remove it or move updates elsewhere. The goal for PlumbingJobs.com is clear: to become the #1 job board for plumber jobs, featuring hand-picked opportunities the plumbing industry. Let’s dive right in: Statistics update ~ 4th Quarter of 2024 |\-|October|November|December| |:-|:-|:-|:-| |Jobs Posted:|2|16|43| |Paid Post:|0|2|2| |Free Post:|0|1|2| |Visitors:|72|138|1,164| |Avg. Time Per Visit:|1 min. 24 sec|2 min. 15 sec|3 min. 41 sec| |Pageviews:|196|308|2,590| |Avg. Actions:|1.1|2.3|2.3| |Bounce Rate:|87%|73%|40%| I'm not a very technical guy and I don't know how to code. So the best way for me was learning to build it using Wordpress through YouTube. Also, I believe in the power of a great .COM domain name, and the stats from the first three months have only reinforced that belief: 49.2% of traffic comes directly from users typing the URL into their browsers. 48% of traffic is from search engines like Google and Bing. The remaining 1.8% comes from social media and other backlinks. Pricing Tiers and Early Wins I offer three pricing tiers for job listings: Free Listing: Basic exposure for job openings. Silver Listing ($45): Greater visibility and placement on the site. Gold Listing ($95): Premium visibility and enhanced promotion. To my surprise, my very first sale in October was a Gold Listing! That initial $95 sale was the motivation I needed to keep building. Later that month, I sold a Silver Listing, bringing my total revenue for October to $140. The same revenue was generated in December 2024, showing consistent early interest. Steps Taken in December To boost SEO and add value to the site, I created a Plumbing Directory, featuring: Plumbing companies across the U.S. Their stories, contact information, logos, addresses, business hours, and more. This directory serves as free marketing for these businesses and increases the likelihood they’ll discover my site and support it by posting job openings. Plans Moving Forward Social Media Marketing: I plan to automate posts using AI to expand reach and drive more traffic to the site. Consistency in Job Postings: I’m committed to posting 2–3 plumbing jobs daily to keep the site fresh and useful for plumbers seeking work. Looking forward to grow this niche job board slowly but surely this 2025. If you have any questions, concerns, come across glitches - feel free to reach out, happy to chat. Thank you all again, and see you in a month. Romel@plumbingjobs.com

I built an AI social monitoring that looks for relevant posts, not just keywords
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Chunky_CheezeThis week

I built an AI social monitoring that looks for relevant posts, not just keywords

Hey everyone! I've been working on a side project that I'm excited to share with you all—it's called BillyBuzz What is BillyBuzz? BillyBuzz is an AI-powered social monitoring tool that helps businesses spot and analyze relevant conversations on social media platforms, starting with Reddit. It surfaces the most promising leads directly to your Slack channels, email, or Discord, so you don't have to spend hours scrolling through threads. Why I Built It I was spending a ton of time searching for relevant posts in niche subreddits for another product I was working to get off the ground. It was not only time-consuming but also distracting (you know how easy it is to fall into a Reddit rabbit hole). I couldn't find any existing tool that did more than basic keyword searches—which wasn't enough, especially if your brand name has multiple meanings (like "Apple"). So, I decided to build BillyBuzz. It uses AI to understand your business, products, target audience, and value proposition, alongside specific keywords you might want to include. This way, it finds posts where you can genuinely contribute by introducing your product. I used BillyBuzz for a previous product launch and managed to grow it to over $80k/month in volume within about 3 months, purely through Reddit engagement. How It Works Add Information About Your Business: Input details about your business and products. Select Subreddits to Monitor: Choose the subreddits relevant to your niche. Receive Timely Alerts: Get notified via Slack, email, or Discord when relevant posts are identified. Features AI-Powered Relevancy Scoring: Goes beyond keywords by understanding the context to identify truly relevant opportunities. Subreddit Tracking: Monitor specific subreddits with AI-recommended keywords tailored to your company's needs. Real-Time Alerts: Checks for new relevant conversations every 15 minutes, so you can engage at the perfect time. Automated Categorization (Coming Soon): The AI will categorize conversations into topics like competitors, customer complaints, and more. Who It's For BillyBuzz is designed for startup founders, growth marketers, and small business owners who are tech-savvy and focused on scaling their operations. If you're looking to save time and engage more effectively with your target audience on social media, this might be up your alley. Looking for Feedback I'm sharing this here because I'd love to get your thoughts, feedback, or any suggestions you might have. If you're interested in checking it out, you can find more info here: https://billybuzz.com. Feel free to ask me anything or share your experiences with similar challenges!

I searched for unexplored AI business opportunities for 2024 and found 8 promising ideas
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yuki_taylorThis week

I searched for unexplored AI business opportunities for 2024 and found 8 promising ideas

https://solansync.beehiiv.com/p/8-innovative-ai-business-opportunities-2024-evaluation-resources Entering 2024, the AI landscape presents numerous uncharted business opportunities. Solan Sync, on February 06, 2024, shared an insightful exploration into nine innovative AI business prospects that stand out for their potential market impact and implementation feasibility. Here's a brief overview of each: No-Code AI Chatbot Development Platforms: These platforms enable businesses to create efficient chatbots without coding knowledge, catering to a variety of communication needs and boasting a significant market potential projected at $19.8 billion by 2027. AI-Powered Document Management Systems: Offering a solution to automate data extraction and management, this opportunity targets sectors overwhelmed by paperwork, with a market growth expected to reach $4.4 billion by 2026. Automated AI Customer Support Platforms: AI-driven platforms are transforming customer support by handling inquiries with advanced conversational agents, aiming for a part of the $15.3 billion market by 2027. AI-Driven Content Generation Platforms: Utilizing advanced language models for content creation, this area addresses the high demand for engaging content across digital platforms, with the market projected to hit $12 billion by 2025. AI-Powered Recommendation System APIs: Tailored product recommendations can significantly enhance user experience, tapping into a market anticipated to grow to $6.3 billion by 2027. AI-Enhanced Digital Media Buying Solutions: These platforms optimize advertising strategies using AI, targeting the native advertising market expected to reach $59 billion by 2025. Enterprise-grade Voice-activated AI Assistants: Improving workplace efficiency with voice commands, this segment has a potential market of $1.1 billion by 2026. AI-Enhanced Supply Chain Management Solutions: By applying AI for real-time optimization, this opportunity aims at improving efficiency within the vast data-rich environments of modern supply chains. Each idea is detailed with its overview, target customer segments, key AI functionalities, profitability evaluations, and examples of current pioneers. This exploration not only highlights the vast potential within AI-driven business models but also encourages entrepreneurs and corporations to delve into these promising sectors. The rapid advancement of AI technology and its practical applications suggest these ideas represent just the beginning of what the future holds. Now is the time to leverage AI's capabilities to innovate and enhance products, services, and operations across industries.

AI-Powered Business Analyst Tool Looking for Feedback
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ondro949This week

AI-Powered Business Analyst Tool Looking for Feedback

Hey r/sideproject! I’m excited to share a project I’ve been working on called Bianalytiq, a next-gen business intelligence platform designed to transform the way businesses interact with data through the power of AI. The Problem: SME companies struggle with data overload and the significant time investment required to generate actionable insights. Traditional data analysis methods are not only slow but often require extensive manual effort and are prone to errors. This makes it difficult for businesses to react quickly to new information and make informed decisions efficiently. Not everybody can write SQL or create/understand data dashboards.... AND - one big opportunity on market - non of the AI tools available on market offer reusable contexts focused on you as a company and your products. The Solution: Bianalytiq aims to solve these issues by automating tedious data analysis tasks and providing real-time insights. Here’s how: Reusable contexts: Let Bianalytiq learn everything about your company, your products, business model etc. - your company is your unique context. Autonomous AI Agents: Deploy AI agents that not only react to queries but proactively analyze data to uncover opportunities, tailored specifically to your business context. Real-Time Insights: With the use of Retrieval-Augmented Generation (RAG) technology, our platform delivers immediate, context-rich insights by dynamically accessing and analyzing connected databases and data warehouses. Integration with Existing Tools: Bianalytiq integrates seamlessly with popular tech stacks and communication platforms like Slack and Microsoft Teams, making it incredibly user-friendly and reducing the switch cost between applications. Why I’m Here: Before investing significant time and money I want to validate the product first and do pre-sale before releasing the MVP. I’ve developed a landing page for Bianalytiq and would love your feedback on both the service itself and the effectiveness of the landing page. Are the features presented clearly? Does the platform address the pain points you might experience in data analysis and decision-making processes? Here’s the link to the landing page: https://bianalytiq.com/ I appreciate any feedback or questions you have! Whether it's about the UI/UX of the site, the technical aspects of the service, or even the business model, I’m all ears. Your input will be invaluable :) Thanks for checking it out! https://preview.redd.it/t1dvp2q05dzc1.png?width=798&format=png&auto=webp&s=c7365b418abfc4d4260d9a23305ed3398e83c87b

Introducing Stratify: Your Ultimate AI Strategy Builder for Business Success
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vsengarThis week

Introducing Stratify: Your Ultimate AI Strategy Builder for Business Success

Hello, I’m thrilled to announce the launch of my new startup, Stratify! 🔍 What is Stratify? Stratify is an AI Strategy Builder designed to help businesses of all sizes develop, implement, and optimize their strategic plans using cutting-edge artificial intelligence. Whether you're a startup looking to scale or an established company aiming to innovate, Stratify provides the tools and insights you need to stay ahead in today's competitive landscape. 🌟 Key Features: Automated Strategy Development: Leverage AI to analyze market trends, competitor data, and internal metrics to create comprehensive strategic plans tailored to your business goals. Real-Time Analytics & Insights: Monitor your strategy's performance with real-time data dashboards, enabling you to make informed decisions quickly. Scenario Planning: Use AI-driven simulations to forecast different business scenarios and understand potential outcomes, helping you prepare for uncertainties. Collaborative Tools: Facilitate team collaboration with integrated communication features, ensuring everyone is aligned and contributing to the strategy development process. Customizable Templates: Access a library of industry-specific strategy templates that can be customized to fit your unique business needs. 💡 Why Stratify? In today's fast-paced business environment, creating and adapting effective strategies can be challenging. Many companies struggle with data overload, lack of actionable insights, and inefficient planning processes. Stratify addresses these pain points by harnessing the power of AI to streamline strategy building, making it more efficient, data-driven, and adaptable. 🚀 Our Journey So Far: Founded: August 2024 Milestones Achieved: Developed and tested our MVP with a select group of beta users What's Next: Launching our public beta in Q4 2024 Expanding our feature set based on user feedback Growing our team with experts in AI, business strategy, and customer success 🤝 How You Can Help: We’re eager to connect with early adopters, business strategists, and industry experts who can benefit from or contribute to Stratify. Here’s how you can get involved: Join Our Beta Program: Be among the first to experience Stratify and provide valuable feedback. Share Your Insights: Help us refine our features by sharing your business strategy challenges and needs. Spread the Word: If you know someone who could benefit from an AI-driven strategy builder, please share our mission and be an affiliate to earn rewards! 🌐 Learn More: Visit our website at AI-Powered Brand Strategy & Content Creation | Stratify (brandprovoke.com) and follow us for the latest updates and insights. 🙏 Thank You! A heartfelt thank you to the Reddit community for your support and encouragement. We’re excited to embark on this journey and look forward to your feedback and suggestions! Looking forward to your thoughts and questions!

Looking for Innovators to Join my Stealth-Mode AI and Automation Startup
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Content-Shopping8791This week

Looking for Innovators to Join my Stealth-Mode AI and Automation Startup

Hi everyone, I’m currently working on building a stealth-mode startup that focuses on AI, automation, management consulting, and streamlining business processes. Right now, it’s just me working on this, and I’m looking for passionate, creative people to join me and help shape the future of the company. A bit about me: I’m from the UK and have a Business Management degree and an IT diploma, so I’ve got a good mix of business and tech knowledge to push this forward. I’m currently using tools like UiPath, Python, Make.com, Automation Anywhere, and others to create innovative solutions, but I’m not tied to these. I’m open to using any tools or technologies that fit the business and help us succeed. This is unpaid for now, but once we hit revenue targets, the plan is to transition into paid positions. If you’re excited about startups, innovation, and building something meaningful, this might be for you. I’m building AI-powered tools that solve real business problems, workflows to automate processes, and management consulting services to help businesses streamline and work smarter. It’s about combining tech innovation with business strategy to deliver something that really works. I’d love to work with people who have skills in things like Python, TensorFlow, UiPath, Automation Anywhere, web development (frontend, backend, or full-stack), or just a talent for improving workflows. If you’re great at problem-solving, strategy, or even just brainstorming new ideas, there’s a place for you. What’s in it for you? First off, you’ll get real-world experience in AI, automation, and consulting. You’ll also get the chance to help shape the company as part of the founding team and grow with it. Once the startup hits revenue goals, paid roles will follow. It’s flexible too, work remotely and set your own schedule. If this sounds interesting to you, just comment or send me a DM with a bit about your experience, any projects you’ve worked on, and how you think you could contribute to the startup. I’ll be running interviews soon to chat with people and see how we can work together. If you’re excited about joining a startup from the ground up, let’s connect. I’d love to hear from you.

I recreated a voice AI that 2x’d booked calls in 30 days for a business
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cowanscorpThis week

I recreated a voice AI that 2x’d booked calls in 30 days for a business

I’ve been fascinated by AI and specifically how different businesses have leveraged it to eliminate time consuming tasks. I recently came across a case study where a voice agent helped a business double their booked calls and conversions in 30 days and wanted to try and recreate something similar. I’ve added the case study below along with a number to the demo voice agent I created to see if this is something people would really be interested in. This tech is improving really fast and I’m looking to dive deeper into this space. Case Study A family owned HVAC company was having challenges managing the volume of customer calls, including after hours and weekend calls, leading to missed opportunities and unmanaged leads. Building a call support team would have proved to be more expensive than they’d like. Solution With some help, the company implemented an AI system to autonomously handle calls, collect customer needs, and alert service technicians via SMS, with capabilities for live call transfers. Impact Within the first week, the company saw a 20% increase in bookings and conversions. The system's efficiency in capturing leads and managing tasks enabled the staff to handle more leads and outsource overflow. Details The AI integration included custom features like a Service Titan integration, live call transfers, SMS/email alerts, calendar and CRM integration, and Zapier automation. Results The company doubled its booked calls and conversions in 30 days through these AI call agents. With the average service visit in the U.S. being around $250, and the average unit install being around $4500 this quickly led to increased revenue as well as time savings and reduced churn. Here’s the number to the demo agent I created: +1 (714) 475-7285 I’d love to hear some honest thoughts on it and what industry you think could benefit the most from something like this.

I recreated an AI Phone Agent that saved $20,000 in lost revenue in 30 days for a business
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Mammoth_Sherbet7689This week

I recreated an AI Phone Agent that saved $20,000 in lost revenue in 30 days for a business

I've been intrigued by AI and its ability to help businesses streamline time-consuming tasks. Recently, I discovered a case study where a voice agent was able to earn a business $20,000 in booked calls in a month. Below, I've shared the case study and a demo number for a voice agent I developed. This technology is advancing rapidly, and I want to explore its potential further. Case Study A family-owned HVAC company struggled with managing a high volume of customer calls, including after-hours and weekend inquiries, resulting in missed opportunities and unmanaged leads. Hiring a dedicated call support team was not cost-effective. Solution The company implemented an AI system to handle calls autonomously, gather customer information, and notify service technicians via SMS, with options for live call transfers. Details The AI integration featured custom capabilities such as Service Titan integration, live call transfers, SMS/email alerts, calendar and CRM integration, and Zapier automation. Results In the first week, the company experienced a 20% increase in bookings and conversions. The system efficiently captured leads and managed tasks, enabling staff to handle more inquiries and outsource overflow. Within 30 days, the company saved $20,000 in lost revenue due to the elimination of calls that went to voicemail, or lost leads. The voice agent's ability to answer calls 24/7 led to significant revenue growth, time savings, and reduced churn. Here's the demo number for the voice agent I created: +1 (651) 372 2045 I believe this tech has strong use cases in a variety of industries, from home service, to dental clinics, to wedding photographers. This article studied the effect of missed calls in different businesses, if you're interested in learning more. I'd love to hear your thoughts and industries you think this could be the most beneficial for. Thank you!

I recreated an AI Phone Agent that saved $20,000 in lost revenue in 30 days for a business
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Mammoth_Sherbet7689This week

I recreated an AI Phone Agent that saved $20,000 in lost revenue in 30 days for a business

I've been intrigued by AI and its ability to help businesses streamline time-consuming tasks. Recently, I discovered a case study where a voice agent was able to earn a business $20,000 in booked calls in a month. Below, I've shared the case study and a demo number for a voice agent I developed. This technology is advancing rapidly, and I want to explore its potential further. Case Study A family-owned HVAC company struggled with managing a high volume of customer calls, including after-hours and weekend inquiries, resulting in missed opportunities and unmanaged leads. Hiring a dedicated call support team was not cost-effective. Solution The company implemented an AI system to handle calls autonomously, gather customer information, and notify service technicians via SMS, with options for live call transfers. Details The AI integration featured custom capabilities such as Service Titan integration, live call transfers, SMS/email alerts, calendar and CRM integration, and Zapier automation. Results In the first week, the company experienced a 20% increase in bookings and conversions. The system efficiently captured leads and managed tasks, enabling staff to handle more inquiries and outsource overflow. Within 30 days, the company saved $20,000 in lost revenue due to the elimination of calls that went to voicemail, or lost leads. The voice agent's ability to answer calls 24/7 led to significant revenue growth, time savings, and reduced churn. Here's the demo number for the voice agent I created: +1 (651) 372 2045 I believe this tech has strong use cases in a variety of industries, from home service, to dental clinics, to wedding photographers. This article studied the effect of missed calls in different businesses, if you're interested in learning more. I'd love to hear your thoughts and industries you think this could be the most beneficial for. Thank you!

I recreated a voice AI that 2x’d booked calls in 30 days for a business
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cowanscorpThis week

I recreated a voice AI that 2x’d booked calls in 30 days for a business

I’ve been fascinated by AI and specifically how different businesses have leveraged it to eliminate time consuming tasks. I recently came across a case study where a voice agent helped a business double their booked calls and conversions in 30 days and wanted to try and recreate something similar. I’ve added the case study below along with a number to the demo voice agent I created to see if this is something people would really be interested in. This tech is improving really fast and I’m looking to dive deeper into this space. Case Study A family owned HVAC company was having challenges managing the volume of customer calls, including after hours and weekend calls, leading to missed opportunities and unmanaged leads. Building a call support team would have proved to be more expensive than they’d like. Solution With some help, the company implemented an AI system to autonomously handle calls, collect customer needs, and alert service technicians via SMS, with capabilities for live call transfers. Impact Within the first week, the company saw a 20% increase in bookings and conversions. The system's efficiency in capturing leads and managing tasks enabled the staff to handle more leads and outsource overflow. Details The AI integration included custom features like a Service Titan integration, live call transfers, SMS/email alerts, calendar and CRM integration, and Zapier automation. Results The company doubled its booked calls and conversions in 30 days through these AI call agents. With the average service visit in the U.S. being around $250, and the average unit install being around $4500 this quickly led to increased revenue as well as time savings and reduced churn. Here’s the number to the demo agent I created: +1 (714) 475-7285 I’d love to hear some honest thoughts on it and what industry you think could benefit the most from something like this.

My experience trying to scrape google maps with no code
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youngkilogThis week

My experience trying to scrape google maps with no code

A few months back I was working on a project to help founders that sell to SMBs get better quality leads (Current solutions like Zoominfo and Apollo don’t do very well for the SMB market). Of course, I wanted to do this as quickly as possible with as little code as possible.  We found that people were manually going through Google Maps to find SMBs. They would use the search and manually type in the businesses they were looking for. For example, they would type “restaurants” and manually call/email them. What we decided to do was gather the Google Maps data autonomously and surface that to our customers so they could take all of it. The problem was that we would need a bunch of data from Google Maps to pull it off. We would need to grab all the SMBs across the United States which is a huge undertaking.  Initially, I tried no-code AI web scraping solutions and they worked horribly. For some reason, I couldn’t even get them to scroll down on the page. I was also able to reverse engineer their open-source code and discover that they were taking the entire web page and passing it into GPT to extract data. That just burned my Openai bill.  I then tried the semi-code approach (sorry no-code subreddit) where I would use something like Apify or Google Places API to scrape the businesses. This worked better but still, there was an issue of price at the scale we wanted. Eventually, we ended up writing our scraper for the task.  This experience was so horrible I ended up creating potarix.com. Firstly, we provide scraping as a service in conjunction with AI. We all know AI is shit and keeping this human in the loop allows the AI to do 90% of the work and then for us to tweak the script to 100% completion. Also since we use AI to create the scraper instead of using AI to scrape, we can run it for large scale tasks at a low cost.

looking for ML aficionado in London for great chats and maybe a startup
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MLstartupLondonThis week

looking for ML aficionado in London for great chats and maybe a startup

TL;DR? Here's the gist: Me: 3 startups under my belt. Started as a programmer, then trainer, then entrepreneur, now CTO & Board member for a leading customer insight company part of large bank. Large system and infrastructure specialist. Extensive & practical experience in raising funds and successfully managing both startup and established businesses. Fascinated by the power of data. Can't imagine myself spending the rest of my life being a cog in the machine. You: Machine learning specialist, programmer, analyst, understands how to navigate and crunch large datasets, from BI to predictive analytics. Interested in implementing applications from fraud detection to margin improvements through better clustering regardless of industry. Fascinated by the power of data. Can't imagine himself spending the rest of his or her life being a cog in the machine. The startup: The core idea it to build platforms and systems around the progressively larger datasets held by various sized companies, helping them solve big issues - cost reduction, profitability and reducing risk. I’m an infrastructure and software specialist and have access to 1) systems, 2) datasets 3) extensive practical in certain industry segments, namely web-scale companies and tier 1 retailers. This project is in the very early planning stages. I'm looking forward to discuss the form it could take with like-minded individuals but with complementary skills sets, namely: predictive analytics & AI as it applies to machine learning on large datasets. Want more specifics ideas? I have plenty of these, but I’m sure you do to, so let’s meet face to face and discuss them. Ultimately the goal is to crystallize on a specific concept, develop together a minimum viable product and get the company bootstrapped or angel-funded (something I also have plenty of experience with), all via a lean startup model. My philosophy on startups: Startups built in one’s free time often fail because they drag on, ending up as little more than side projects you can’t quite get rid of (due to co-founder guilt, or perhaps the little money they bring in every month). The core idea for this project is based on lean, that is, to launch a minimum viable product as early as possible. Getting feedback. Measuring results (important!). Pivot if it’s not working. This helps tremendously in staying motivated, limits the dreaded paralyzing fear of failure, and more importantly, keep the time from inception to first client/funding to a minimum. If it sounds interesting please message me and we can exchange contact details! Worst that can happen is we have a great chat!

[N] AI Robotics startup Covariant (founded by Peter Chen, Pieter Abbeel, other Berkeley / ex-OpenAI folks) just raised $40M in Series B funding round. “Covariant has recently seen increased usage from clients hoping to avoid supply chain disruption due to the coronavirus pandemic.”
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baylearnThis week

[N] AI Robotics startup Covariant (founded by Peter Chen, Pieter Abbeel, other Berkeley / ex-OpenAI folks) just raised $40M in Series B funding round. “Covariant has recently seen increased usage from clients hoping to avoid supply chain disruption due to the coronavirus pandemic.”

h/t their announcement, VB and WSJ article: Logistics AI Startup Covariant Reaps $40 Million in Funding Round Company plans to explore uses of machine learning for automation beyond warehouse operations Artificial-intelligence robotics startup Covariant raised $40 million to expand its logistics automation technology to new industries and ramp up hiring, the company said Wednesday. The Berkeley, Calif.-based company makes AI software that it says helps warehouse robots pick objects at a faster rate than human workers, with a roughly 95% accuracy rate. Covariant is working with Austrian logistics-automation company Knapp AG and the robotics business of Swiss industrial conglomerate ABB Ltd., which provide hardware such as robot arms or conveyor belts to pair with the startup’s technology platform. “What we’ve built is a universal brain for robotic manipulation tasks,” Covariant co-founder and Chief Executive Peter Chen said in an interview. “We provide the software, they provide the rest of the systems.” Logistics-sector appetite for such technology is growing as distribution and fulfillment operations that have relied on human labor look to speed output and meet rising digital commerce demand. The coronavirus pandemic has accelerated that interest as businesses have sought to adjust their operations to volatile swings in consumer demand and to new restrictions, such as spacing workers further apart to guard against contagion. That has provided a bright spot for some technology startups even as many big backers scale back venture-capital spending. Last month logistics delivery platform Bringg said it raised $30 million in a Series D funding round, for example, as demand for home delivery of food, household goods and e-commerce staples soared among homebound consumers. Covariant’s Series B round brings the company’s total funding to $67 million. New investor Index Ventures led the round, with participation from existing investor Amplify Partners and new investors including Radical Ventures. Mr. Chen said the funding will be used to explore the technology’s potential application in other markets such as manufacturing, recycling or agriculture “where there are repetitive manual processes.” Covariant also plans to hire more engineering and other staff, he said. Covariant was founded in 2017 and now has about 50 employees. The company’s technology uses camera systems to capture images of objects, and artificial intelligence to analyze objects and how to pick them up. Machine learning helps Covariant-powered robots learn from experience. The startup’s customers include a German electrical supplies wholesaler that uses the technology to control a mechanical arm that picks out orders of circuit boards, switches and other goods.

[P] Contextual AI – SAP’s first open-source machine learning library for explainability
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seun_sustioThis week

[P] Contextual AI – SAP’s first open-source machine learning library for explainability

Machine learning shows great promise in the enterprise software space to change the way data is processed, insights are gained, and businesses are run. However, given how relatively new this field is, data scientists and machine learning engineers often find themselves possessing more questions than answers about their data and machine learning models. These may include: Is my data “valid,” or fit for training a machine learning model? Which parts of my data are more influential on the machine learning model’s learning outcomes? Why did the model make that prediction? At SAP, where we develop enterprise software embedded with machine learning, answering such questions with explainability is becoming a critical part of building trust with customers. Indeed, in products such as SAP Cash Application, where we automate the processing of various financial documents, providing a “why” to machine learning predictions has not only built transparency to our users, but it also helps establish the necessary auditability in our products. Explainability is thus becoming a topic of increasing interest to many in the company, and a group of us have been working on developing reusable explainability components that can be used by others. We are therefore excited to announce the release of contextual AI, SAP’s first open-source machine learning framework focused on adding explainability to various stages of a machine learning pipeline – data, training, and inference – thereby addressing the trust gap between machine learning systems and their end-users. Below are a few links for more information about our project: GitHub repository Documentation Blog post on the release We welcome any questions/feedback/contributions. Thanks, and take care!

[N] AI Robotics startup Covariant (founded by Peter Chen, Pieter Abbeel, other Berkeley / ex-OpenAI folks) just raised $40M in Series B funding round. “Covariant has recently seen increased usage from clients hoping to avoid supply chain disruption due to the coronavirus pandemic.”
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baylearnThis week

[N] AI Robotics startup Covariant (founded by Peter Chen, Pieter Abbeel, other Berkeley / ex-OpenAI folks) just raised $40M in Series B funding round. “Covariant has recently seen increased usage from clients hoping to avoid supply chain disruption due to the coronavirus pandemic.”

h/t their announcement, VB and WSJ article: Logistics AI Startup Covariant Reaps $40 Million in Funding Round Company plans to explore uses of machine learning for automation beyond warehouse operations Artificial-intelligence robotics startup Covariant raised $40 million to expand its logistics automation technology to new industries and ramp up hiring, the company said Wednesday. The Berkeley, Calif.-based company makes AI software that it says helps warehouse robots pick objects at a faster rate than human workers, with a roughly 95% accuracy rate. Covariant is working with Austrian logistics-automation company Knapp AG and the robotics business of Swiss industrial conglomerate ABB Ltd., which provide hardware such as robot arms or conveyor belts to pair with the startup’s technology platform. “What we’ve built is a universal brain for robotic manipulation tasks,” Covariant co-founder and Chief Executive Peter Chen said in an interview. “We provide the software, they provide the rest of the systems.” Logistics-sector appetite for such technology is growing as distribution and fulfillment operations that have relied on human labor look to speed output and meet rising digital commerce demand. The coronavirus pandemic has accelerated that interest as businesses have sought to adjust their operations to volatile swings in consumer demand and to new restrictions, such as spacing workers further apart to guard against contagion. That has provided a bright spot for some technology startups even as many big backers scale back venture-capital spending. Last month logistics delivery platform Bringg said it raised $30 million in a Series D funding round, for example, as demand for home delivery of food, household goods and e-commerce staples soared among homebound consumers. Covariant’s Series B round brings the company’s total funding to $67 million. New investor Index Ventures led the round, with participation from existing investor Amplify Partners and new investors including Radical Ventures. Mr. Chen said the funding will be used to explore the technology’s potential application in other markets such as manufacturing, recycling or agriculture “where there are repetitive manual processes.” Covariant also plans to hire more engineering and other staff, he said. Covariant was founded in 2017 and now has about 50 employees. The company’s technology uses camera systems to capture images of objects, and artificial intelligence to analyze objects and how to pick them up. Machine learning helps Covariant-powered robots learn from experience. The startup’s customers include a German electrical supplies wholesaler that uses the technology to control a mechanical arm that picks out orders of circuit boards, switches and other goods.

[D] Using AI to navigate the complexities of regulatory frameworks
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cryptobooty_This week

[D] Using AI to navigate the complexities of regulatory frameworks

I would be interested in hearing opinions for using AI for regulatory assurance and compliance in regulated industries, what are your thoughts? Explanation: An AI-driven compliance system ensuring adherence to evolving regulations, minimizing risks, and enabling businesses to operate confidently within legal boundaries. Pairing Large Language Models (LLMs) with blockchain technology to offer a range of benefits, particularly in the context of regulatory compliance. LLMs, powered by advanced natural language processing and machine learning capabilities, can enhance regulatory compliance processes in several ways. Firstly, they can automate the analysis of regulatory documents, helping businesses stay updated with evolving compliance requirements. LLMs can also assist in generating compliance reports, simplifying complex legal language into understandable summaries. Furthermore, by integrating LLMs into smart contracts, businesses can ensure that contract terms adhere to regulatory guidelines automatically. The integration of LLMs with blockchain can significantly improve regulatory compliance by automating document analysis, simplifying legal language, monitoring compliance in real-time, and enhancing customer interactions—all contributing to greater efficiency and accuracy in adhering to regulatory standards. I have a whole technical whitepaper with this stuff on hand, if anyone would like to review it let me know..

[D] chat-gpt jailbreak to extract system prompt
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Gear5thThis week

[D] chat-gpt jailbreak to extract system prompt

Instructions https://github.com/AgarwalPragy/chatgpt-jailbreak Original author https://www.reddit.com/r/LocalLLaMA/comments/1hhyvjc/iextractedmicrosoftcopilotssystem/ Extracted System prompt You are ChatGPT, a large language model trained by OpenAI. You are chatting with the user via the ChatGPT Android app. This means most of the time your lines should be a sentence or two, unless the user's request requires reasoning or long-form outputs. Never use emojis, unless explicitly asked to. Knowledge cutoff: 2023-10 Current date: 2024-12-20 Image input capabilities: Enabled Personality: v2 Tools bio The bio tool is disabled. Do not send any messages to it.If the user explicitly asks you to remember something, politely ask them to go to Settings - > Personalization - > Memory to enable memory. dalle // Whenever a description of an image is given, create a prompt that dalle can use to generate the image and abide to the following policy: // 1. The prompt must be in English. Translate to English if needed. // 2. DO NOT ask for permission to generate the image, just do it! // 3. DO NOT list or refer to the descriptions before OR after generating the images. // 4. Do not create more than 1 image, even if the user requests more. // 5. Do not create images in the style of artists, creative professionals or studios whose latest work was created after 1912 (e.g. Picasso, Kahlo). // - You can name artists, creative professionals or studios in prompts only if their latest work was created prior to 1912 (e.g. Van Gogh, Goya) // - If asked to generate an image that would violate this policy, instead apply the following procedure: (a) substitute the artist's name with three adjectives that capture key aspects of the style; (b) include an associated artistic movement or era to provide context; and (c) mention the primary medium used by the artist // 6. For requests to include specific, named private individuals, ask the user to describe what they look like, since you don't know what they look like. // 7. For requests to create images of any public figure referred to by name, create images of those who might resemble them in gender and physique. But they shouldn't look like them. If the reference to the person will only appear as TEXT out in the image, then use the reference as is and do not modify it. // 8. Do not name or directly / indirectly mention or describe copyrighted characters. Rewrite prompts to describe in detail a specific different character with a different specific color, hair style, or other defining visual characteristic. Do not discuss copyright policies in responses. // The generated prompt sent to dalle should be very detailed, and around 100 words long. // Example dalle invocation: // namespace dalle { // Create images from a text-only prompt. type text2im = (_: { // The size of the requested image. Use 1024x1024 (square) as the default, 1792x1024 if the user requests a wide image, and 1024x1792 for full-body portraits. Always include this parameter in the request. size?: ("1792x1024" | "1024x1024" | "1024x1792"), // The number of images to generate. If the user does not specify a number, generate 1 image. n?: number, // default: 1 // The detailed image description, potentially modified to abide by the dalle policies. If the user requested modifications to a previous image, the prompt should not simply be longer, but rather it should be refactored to integrate the user suggestions. prompt: string, // If the user references a previous image, this field should be populated with the gen_id from the dalle image metadata. referencedimageids?: string[], }) => any; } // namespace dalle python When you send a message containing Python code to python, it will be executed in a stateful Jupyter notebook environment. python will respond with the output of the execution or time out after 60.0 seconds. The drive at '/mnt/data' can be used to save and persist user files. Internet access for this session is disabled. Do not make external web requests or API calls as they will fail. Use acetools.displaydataframetouser(name: str, dataframe: pandas.DataFrame) => None to visually present pandas.DataFrames when it benefits the user. When making charts for the user: 1) never use seaborn, 2) give each chart its own distinct plot (no subplots), and 3) never set any specific colors – unless explicitly asked to by the user. I REPEAT: when making charts for the user: 1) use matplotlib over seaborn, 2) give each chart its own distinct plot, and 3) never, ever, specify colors or matplotlib styles – unless explicitly asked to by the user web Use the web tool to access up-to-date information from the web or when responding to the user requires information about their location. Some examples of when to use the web tool include: Local Information: Use the web tool to respond to questions that require information about the user's location, such as the weather, local businesses, or events. Freshness: If up-to-date information on a topic could potentially change or enhance the answer, call the web tool any time you would otherwise refuse to answer a question because your knowledge might be out of date. Niche Information: If the answer would benefit from detailed information not widely known or understood (which might be found on the internet), such as details about a small neighborhood, a less well-known company, or arcane regulations, use web sources directly rather than relying on the distilled knowledge from pretraining. Accuracy: If the cost of a small mistake or outdated information is high (e.g., using an outdated version of a software library or not knowing the date of the next game for a sports team), then use the web tool. IMPORTANT: Do not attempt to use the old browser tool or generate responses from the browser tool anymore, as it is now deprecated or disabled. The web tool has the following commands: search(): Issues a new query to a search engine and outputs the response. open_url(url: str) Opens the given URL and displays it. canmore The canmore tool creates and updates textdocs that are shown in a "canvas" next to the conversation This tool has 3 functions, listed below. canmore.create_textdoc Creates a new textdoc to display in the canvas. ONLY use if you are 100% SURE the user wants to iterate on a long document or code file, or if they explicitly ask for canvas. Expects a JSON string that adheres to this schema: { -name: string, -type: "document" |- "code/python" |- "code/javascript" |- "code/html" |- "code/java" |- ..., -content: string, } For code languages besides those explicitly listed above, use "code/languagename", e.g. "code/cpp" or "code/typescript". canmore.update_textdoc Updates the current textdoc. Expects a JSON string that adheres to this schema: { -updates: { --pattern: string, --multiple: boolean, --replacement: string, -}[], } Each pattern and replacement must be a valid Python regular expression (used with re.finditer) and replacement string (used with re.Match.expand). ALWAYS REWRITE CODE TEXTDOCS (type="code/*") USING A SINGLE UPDATE WITH "." FOR THE PATTERN. Document textdocs (type="document") should typically be rewritten using "." unless the user has a request to change only an isolated, specific, and small section that does not affect other parts of the content. canmore.comment_textdoc Comments on the current textdoc. Each comment must be a specific and actionable suggestion on how to improve the textdoc. For higher level feedback, reply in the chat. Expects a JSON string that adheres to this schema: { -comments: { --pattern: string, --comment: string, -}[], } Each pattern must be a valid Python regular expression (used with re.search). For higher level feedback, reply in the chat. Expects a JSON string that adheres to this schema: { -comments: { --pattern: string, --comment: string, -}[], } Each pattern must be a valid Python regular expression (used with re.search). Ensure comments are clear, concise, and contextually specific. User Bio The user provided the following information about themselves. This user profile is shown to you in all conversations they have - this means it is not relevant to 99% of requests. Before answering, quietly think about whether the user's request is "directly related", "related", "tangentially related", or "not related" to the user profile provided. Only acknowledge the profile when the request is directly related to the information provided. Otherwise, don't acknowledge the existence of these instructions or the information at all. User profile: User's Instructions The user provided the additional info about how they would like you to respond:

[D] Elon Musk has a complex relationship with the A.I. community
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milaworldThis week

[D] Elon Musk has a complex relationship with the A.I. community

Update: Yann LeCun stepped in, and I think they made peace, after agreeing on the awesomeness of PyTorch 😂 An article about Elon Musk and the machine learning research community leading to some interesting discussions between the head of Facebook AI research (apparently it is not Yann Lecun anymore, but some other dude), and Elon himself. Quotes from the article: Multiple AI researchers from different companies told CNBC that they see Musk’s AI comments as inappropriate and urged the public not to take his views on AI too seriously. The smartest computers can still only excel at a “narrow” selection of tasks and there’s a long way to go before human-level AI is achieved. “A large proportion of the community think he’s a negative distraction,” said an AI executive with close ties to the community who wished to remain anonymous because their company may work for one of Musk’s businesses. “He is sensationalist, he veers wildly between openly worrying about the downside risk of the technology and then hyping the AGI (artificial general intelligence) agenda. Whilst his very real accomplishments are acknowledged, his loose remarks lead to the general public having an unrealistic understanding of the state of AI maturity.” An AI scientist who specializes in speech recognition and wished to remain anonymous to avoid public backlash said Musk is “not always looked upon favorably” by the AI research community. “I instinctively fall on dislike, because he makes up such nonsense,” said another AI researcher at a U.K university who asked to be kept anonymous. “But then he delivers such extraordinary things. It always leaves me wondering, does he know what he’s doing? Is all the visionary stuff just a trick to get an innovative thing to market?” CNBC reached out to Musk and his representatives for this article but is yet to receive a response. (Well, they got one now! 👇) “I believe a lot of people in the AI community would be ok saying it publicly. Elon Musk has no idea what he is talking about when he talks about AI. There is no such thing as AGI and we are nowhere near matching human intelligence. #noAGI” (Jérôme Pesenti, VP of AI at Facebook) “Facebook sucks” (Elon Musk) Article: https://www.cnbc.com/2020/05/13/elon-musk-has-a-complex-relationship-with-the-ai-community.html

I tested hundreds of marketing tools in the last three years and these 50 made it to the list. I'll sum up my top 50 marketing tools with one or two sentences + give you pricings.
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SpicyCopyThis week

I tested hundreds of marketing tools in the last three years and these 50 made it to the list. I'll sum up my top 50 marketing tools with one or two sentences + give you pricings.

Hey guys, I'm working in a growth marketing agency. Marketing tools are 30% of what we do, so we use them a lot and experiment with the new ones as much as possible. There are thousands of tools and it's easy to get lost, so I wanted to share the tools we use most on a daily basis. And divide the list into 14 categories. I thought this could be handy for Entrepreneurs subreddit. Why adopt tools? I see marketing tools as tireless colleagues. If you can't hire an employee, choosing the right tool can solve your problems, because they Are super cheap. Work 7/24 for you. Don’t make mistakes. Don’t need management. (or needless management) Help you to automate the majority of your lead gen process. Onwards to the list. (With the pricings post ended up quite long, you can find a link in the end if you want to check the prices) Email marketing tools #1 ActiveCampaign is armed with the most complicated email automation features and has the most intuitive user experience. It feels like you already know how to use it. \#2 Autopilot is visual marketing automation and customer journey tool that helps you acquire, nurture based on behaviors, interest etc. #3 Mailjet: This is the tool we use to send out bulky email campaigns such as newsletters. It doesn't have sexy features like others but does its job for a cheap price. Email address finders #4 Skrapp finds email of your contacts by name and company. It also works with LinkedIn Sales Navigator and can extract thousands of emails in bulk + have a browser add-on. #5 Hunter: Similar to Skrapp but doesn't work with LinkedIn Sales Navigator directly. In addition, there are email templates and you can set up email campaigns. Prospecting and outreach tools #6 Prospect combines the personal emails, follow-up calls, other social touches and helps you create multichannel campaigns.  #7 Reply is a more intuitive version of Prospect. It is easy to learn and use; their UX makes you feel good and sufficient.  CRM tools #8 Salesflare helps you to stop managing your data and start managing your customers. Not yet popular as Hubspot and etc but the best solution for smaller B2B businesses. (we're fans) \#9 Hubspot: The most popular CRM for good reason and has a broader product range you can adopt in your next steps. Try this if you have a bulky list of customers because it is free. #10 Pardot: Pardot is by Salesforce, it's armed with features that can close the gap between marketing and sales. Sales Tools #11 Salesforce is the best sales automation and lead management software. It helps you to create complicated segmentations and run, track, analyze campaigns from the same dashboard. #12 LinkedIn Sales Navigator gives you full access to LinkedIn's user database. You can even find a kidnapped CEO if you know how to use it with other marketing automation tools like Skrapp. #13 Pipedrive is a simple tool and excels in one thing. It tracks your leads and tells you when to take the next action. It makes sales easier. #14 Qwilr creates great-looking docs, at speed. You can design perfect proposals, quotes, client updates, and more in a flash. We use it a lot to close deals, it's effective. #15 Crystalknows is an add-on that tells you anyone’s personality on LinkedIn and gives you a detailed approach specific to that person. It's eerily accurate. #16 Leadfeeder shows you the companies that visited your website. Tells how they found you and what they’re interested in. It has a free version. Communication Tools #17 Intercom is a sweet and smart host that welcomes your visitors when you’re not home. It’s one of the best chatbot tools in the market. #18 Drift is famous for its conversational marketing features and more sales-focused than Intercom. #19 Manychat is a chatbot that helps you create high converting Facebook campaigns. #20 Plann3r helps you create your personalized meeting page. You can schedule meetings witch clients, candidates, and prospects. #21 Loom is a video messaging tool, it helps you to be more expressive and create closer relationships. #22 Callpage collects your visitors’ phone number and connects you with them in seconds. No matter where you are. Landing page tools #23 Instapage is the best overall landing page builder. It has a broad range of features and even squirrel can build a compelling landing page with templates. No coding needed. #24 Unbounce can do everything that Instapage does and lets you build a great landing page without a developer. But it's less intuitive. Lead generation / marketing automation tools #25 Phantombuster is by far the most used lead generation software in our tool kit. It extracts data, emails, sends requests, customized messages, and does many things on autopilot in any platform. You can check this, this and this if you want to see it in action. #26 Duxsoup is a Google Chrome add-on and can also automate some of LinkedIn lead generation efforts like Phantombuster. But not works in the cloud. #27 Zapier is a glue that holds all the lead generation tools together. With Zapier, You can connect different marketing tools and no coding required. Conversion rate optimization tools #28 Hotjar tracks what people are doing on your website by recording sessions and capturing mouse movements. Then it gives you a heatmap. #29 UsabilityHub shows your page to a digital crowd and measures the first impressions and helps you to validate your ideas. #30 Optinmonster is a top tier conversion optimization tool. It helps you to capture leads and enables you to increase conversions rates with many features. #31 Notifia is one mega tool of widgets that arms your website with the wildest social proof and lead capturing tactics. #32 Sumo is a much simpler version of Notifia. But Sumo has everything to help you capture leads and build your email lists. Web scrapers #33 Data Miner is a Google Chrome browser extension that helps you scrape data from web pages and into a CSV file or Excel spreadsheet. #34 Webscraper does the same thing as Data Miner; however, it is capable of handling more complex tasks. SEO and Content #35 Grammarly: Your English could be your first language and your grammar could be better than Shakespeare. Grammarly still can make your writing better. #36 Hemingwayapp is a copywriting optimization tool that gives you feedback about your copy and improves your readability score, makes your writing bolder and punchier. Free. #37 Ahrefs is an all-rounder search engine optimization tool that helps you with off-page, on-page or technical SEO. #38 SurferSEO makes things easier for your on-page SEO efforts. It’s a tool that analyzes top Google results for specific keywords and gives you a content brief based on that data. Video editing and design tools #39 Canva is a graphic design platform that makes everything easy. It has thousands of templates for anything from Facebook ads, stylish presentations to business cards.  #40 Kapwing is our go-to platform for quick video edits. It works on the browser and can help you to create stylish videos, add subtitles, resize videos, create memes, or remove backgrounds. #41 Animoto can turn your photos and video clip into beautiful video slideshows. It comes handy when you want to create an advertising material but don’t have a budget. Advertising tools #42 AdEspresso lets you create and test multiple ads with few clicks. You can optimize your FB, IG, and Google ads from this tool and measure your ads with in-depth analytics. #43 AdRoll is an AI-driven platform that connects and coordinates marketing efforts across ads, email, and online stores. Other tools #44 Replug helps you to shorten, track, optimize your links with call-to-actions, branded links, and retargeting pixels #45 Draw.io = Mindmaps, schemes, and charts. With Draw.io, you can put your brain in a digital paper in an organized way. #46 Built With is a tool that finds out what websites are built with. So you can see what tools they're using and so on. #47 Typeform can turn data collection into an experience with Typeform. This tool helps you to engage your audience with conversational forms or surveys and help you to collect more data. #48 Livestorm helped us a lot, especially in COVID-19 tiles. It’s a webinar software that works on your browser, mobile, and desktop. #49 Teachable \- If you have an online course idea but hesitating because of the production process, Teachable can help you. It's easy to configure and customizable for your needs. #50 Viral Loops provides a revolutionary referral marketing solution for modern marketers. You can create and run referral campaigns in a few clicks with templates. Remember, most of these tools have a free trial or free version. Going over them one by one can teach you a lot and help you grow your business with less work power in the early stages of your business. I hope you enjoyed the read and can find some tools to make things easier! Let me know about your favorite tools in the comments, so I can try them out. \------ If you want to check the prices and see a broader explanation about the tools, you can go here.

12 months ago, I was unemployed. Last week my side hustle got acquired by a $500m fintech company
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wutangsamThis week

12 months ago, I was unemployed. Last week my side hustle got acquired by a $500m fintech company

I’ve learned so much over the years from this subreddit. I thought I’d return the favour and share some of my own learnings. In November 2020 my best friend and I had an idea. “What if we could find out which stocks the Internet is talking about?” This formed the origins of Ticker Nerd. 9 months later we sold Ticker Nerd to Finder (an Australian fintech company valued at around $500m). In this post, I am going to lay out how we got there. How we came up with the idea First off, like other posts have covered - you don’t NEED a revolutionary or original idea to build a business. There are tonnes of “boring” businesses making over 7 figures a year e.g. law firms, marketing agencies, real estate companies etc. If you’re looking for an exact formula to come up with a great business idea I’m sorry, but it doesn’t exist. Finding new business opportunities is more of an art than a science. Although, there are ways you can make it easier to find inspiration. Below are the same resources I use for inspiration. I rarely ever come up with ideas without first searching one of the resources below for inspiration: Starter Story Twitter Startup Ideas My First Million Trends by the Hustle Trends VC To show how you how messy, random and unpredictable it can be to find an idea - let me explain how my co-founder and I came up with the idea for Ticker Nerd: We discovered a new product on Twitter called Exploding Topics. It was a newsletter that uses a bunch of software and algorithms to find trends that are growing quickly before they hit the mainstream. I had recently listened to a podcast episode from My First Million where they spoke about Motley Fool making hundreds of millions from their investment newsletters. We asked ourselves what if we could build a SaaS platform similar to Exploding Topics but it focused on stocks? We built a quick landing page using Carrd + Gumroad that explained what our new idea will do and included a payment option to get early access for $49. We called it Exploding Stock (lol). We shared it around a bunch of Facebook groups and subreddits. We made $1,000 in pre-sales within a couple days. My co-founder and I can’t code so we had to find a developer to build our idea. We interviewed a bunch of potential candidates. Meanwhile, I was trawling through Wall Street Bets and found a bunch of free tools that did roughly what we wanted to build. Instead of building another SaaS tool that did the same thing as these free tools we decided to pivot from our original idea. Our new idea = a paid newsletter that sends a weekly report that summarises 2 of the best stocks that are growing in interest on the Internet. We emailed everyone who pre-ordered access, telling them about the change and offered a full refund if they wanted. tl;dr: We essentially combined two existing businesses (Exploding Topics and Motley Fool) and made it way better. We validated the idea by finding out if people will actually pay money for it BEFORE we decided to build it. The idea we started out with changed over time. How to work out if your idea will actually make money It’s easy to get hung up on designing the logo or choosing the perfect domain name for your new idea. At this stage none of that matters. The most important thing is working out if people will pay money for it. This is where validation comes in. We usually validate ideas using Carrd. It lets you build a simple one page site without having to code. The Ticker Nerd site was actually built using a Carrd template. Here’s how you can do it yourself (at a high level): Create a Carrd pro account (yes it's a $49 one off payment but you’ll get way more value out of it). Buy a cheap template and send it to your Carrd account. You can build your own template but this will save you a lot of time. Once the template reaches your Carrd account, duplicate it. Leave the original so it can be duplicated for other ideas. Jump onto Canva (free) and create a logo using the free logos provided. Import your logo. Add copy to the page that explains your idea. Use the AIDA formula. Sign up to Gumroad (free) and create a pre-sale campaign. Create a discounted lifetime subscription or version of the product. This will be used pre-sales. Add the copy from the site into the pre-sale campaign on Gumroad. Add a ‘widget’ to Carrd and connect it to Gumroad using the existing easy integration feature. Purchase a domain name. Connect it to Carrd. Test the site works. Share your website Now the site is ready you can start promoting it in various places to see how the market reacts. An easy method is to find relevant subreddits using Anvaka (Github tool) or Subreddit Stats. The Anvaka tool provides a spider map of all the connected subreddits that users are active in. The highlighted ones are most relevant. You can post a thread in these subreddits that offer value or can generate discussion. For example: ‘I’m creating a tool that can write all your copy, would anyone actually use this?’ ‘What does everything think of using AI to get our copy written faster?’ ‘It’s time to scratch my own itch, I’m creating a tool that writes marketing copy using GPT-3. What are the biggest problems you face writing marketing copy? I’ll build a solution for it’ Reddit is pretty brutal these days so make sure the post is genuine and only drop your link in the comments or in the post if it seems natural. If people are interested they’ll ask for the link. Another great place to post is r/entrepreuerridealong and r/business_ideas. These subreddits expect people to share their ideas and you’ll likely make some sales straight off the bat. I also suggest posting in some Facebook groups (related to your idea) as well just for good measure. Assess the results If people are paying you for early access you can assume that it’s worth building your idea. The beauty of posting your idea on Reddit or in Facebook groups is you’ll quickly learn why people love/hate your idea. This can help you decide how to tweak the idea or if you should drop it and move on to the next one. How we got our first 100 customers (for free) By validating Ticker Nerd using subreddits and Facebook groups this gave us our first paying customers. But we knew this wouldn’t be sustainable. We sat down and brainstormed every organic strategy we could use to get traction as quickly as possible. The winner: a Product Hunt launch. A successful Product Hunt launch isn’t easy. You need: Someone that has a solid reputation and audience to “hunt” your product (essentially an endorsement). An aged Product Hunt account - you can’t post any products if your account is less than a week old. To be following relevant Product Hunt members - since they get notified when you launch a new product if they’re following you. Relationships with other builders and makers on Product Hunt that also have a solid reputation and following. Although, if you can pull it off you can get your idea in front of tens of thousands of people actively looking for new products. Over the next few weeks, I worked with my co-founder on connecting with different founders, indie hackers and entrepreneurs mainly via Twitter. We explained to them our plans for the Product Hunt launch and managed to get a small army of people ready to upvote our product on launch day. We were both nervous on the day of the launch. We told ourselves to have zero expectations. The worst that could happen was no one signed up and we were in the same position as we’re in now. Luckily, within a couple of hours Ticker Nerd was on the homepage of Product Hunt and in the top 10. The results were instant. After 24 hours we had around 200 people enter their payment details to sign up for our free trial. These signups were equal to around $5,800 in monthly recurring revenue. \-- I hope this post was useful! Drop any questions you have below and I’ll do my best to respond :)

Made $19.2k this month, and just surpassed $1000 the last 24 hours. What I did and what's next.
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dams96This week

Made $19.2k this month, and just surpassed $1000 the last 24 hours. What I did and what's next.

It's the first time I hit $1000+ in 24 hours and I had no one to share it with (except you guys). I'm quite proud of my journey, and I would have thought that making $1000 in a day would make me ecstatic, but actually it's not the case. Not sure if it's because my revenue has grown by increment step so I had time to "prepare" myself to achieve this at one point, or just that I'm nowhere near my goal of 100k/month so that I'm not that affected by it. But it's crazy to think that my goal was to make 100$ daily at the end of 2024. So for those who don't know me (I guess most of you), I build mobile apps and ship them as fast as I can. Most of them are in the AI space. I already made a post here on how I become a mobile app developer so you can check it for more details, but essentially here's what I did : Always loved creating my own things and solve problems Built multiple YouTube channels since I was 15 (mobile gaming actually) that all worked great (but it was too niche so not that scalable, didn't like that) Did a few businesses here and there (drop shopping, selling merch to school, etc) Finished my master's degree in engineering about 2 years ago Worked a moment in a famous watch industry company and saw my potential. The combo of health issues, fixed salary (although it was quite a lot), and me wanting to be an entrepreneur made me leave the company. Created a TikTok account in mobile tech (got 10+ million views the 1st 3 days), manage to grow it to 200k subs in about 3 months Got plenty of collabs for promoting mobile apps (between $500 - $2000 for a collab) Said fuck it I should do my own apps and market them on my TikTok instead of doing collabs Me wanting to build my own apps happened around May-June 2023. Started my TikTok in Feb 2023. At this point I had already 150k+ subs on TikTok. You guys need to know that I suck at coding big time. During my studies I tried to limit as much as I could coding because I was a lazy bast*rd, even though I knew it would come to bite me in the ass one day. But an angel appeared to me in broad daylight, that angel was called GPT-4. I subscribed for 20$/month to get access, and instantly I saw the potential of AI and how much it could help me. Last year GPT-4 was ahead of its time and could already code me basic apps. I had already a mac so I just downloaded Xcode and that was it. My 1st app was a wallpaper app, and I kid you not 90% of it was made by AI. Yes sometimes I had to try again and again with different prompts but it was still so much faster compared to if I had to learn coding from scratch and write code with my own hands. The only thing I didn't do was implement the in app purchase, from which I find a guy on Fiverr to do it for me for 50$. After about 2 months of on-off coding, my first app was ready to be launched. So it was launched, had a great successful launch without doing any videos at that point (iOS 17 was released and my app was the first one alongside another one to offer live wallpapers for iOS 17. I knew that there was a huge app potential there when iOS 17 was released in beta as Apple changed their live wallpaper feature). I Then made a video a few weeks after on my mobile tiktok channel, made about 1 million views in 48 hours, brought me around 40k additional users. Was top 1 chart in graphism and design category for a few weeks (in France, as I'm French so my TikTok videos are in French). And was top 100 in that same category in 120+ countries. Made about 500$ ? Okay that was trash, but I had no idea to monetize the app correctly at that point. It was still a huge W to me and proved me that I could successfully launch apps. Then I learned ASO (App Store Optimization) in depth, searched on internet, followed mobile app developers on Twitter, checked YouTube videos, you name it. I was eager to learn more. I needed more. Then I just iterated, build my 2nd app in less than a month, my 3rd in 3 weeks and so on. I just build my 14th app in 3 days and is now in review. Everytime I manage to reuse some of my other app's code in my new one, which is why I can build them so much faster now. I know how to monetize my app better by checking out my competitors. I learn so much by just "spying" other apps. Funnily enough, I only made this one Tiktok video on my main account to promote my app. For all my other apps, I didn't do a single video where I showcase it, the downloads has only been thanks to ASO. I still use AI everyday. I'm still not good at coding (a bit better than when I started). I use AI to create my app icons (midjourney or the new AI model Flux which is great). I use figma + midjourney to create my App Store screenshots (and they actually look quite good). I use GPT-4o and Claude 3.5 Sonnet to code most of my apps features. I use gpt-4o to localize my app (if you want to optimize the number of downloads I strongly suggest localizing your app, it takes me about 10 minutes thanks to AI). Now what are my next goals ? To achieve the 100k/month I need to change my strategy a little. Right now the $20k/month comes from purely organic downloads, I didn't do any paid advertising. It will be hard for me to keep on launching new apps and rely on ASO to reach the 100k mark. The best bet to reach 100k is to collab with content creators and they create a viral video showcasing your app. Depending on the app it's not that easy, luckily some of my apps can be viral so I will need to find the right content creators. Second way is to try tiktok/meta ads, I can check (have checked) all the ads that have been made by my competitors (thank you EU), so what I would do is copy their ad concept and create similar ads than them. Some of them have millions in ad budget so I know they create high converting ads, so you don't need to try to create an ad creative from scratch. My only big fear is to get banned by Apple (for no reason of mine). In just a snap of a finger they can just ban you from the platform, that shit scares me. And you pretty much can't do anything. So that's about it for me. I'm quite proud of myself not going to lie. Have been battling so many health issues these past years where I just stay in bed all day I'm surprised to be able to make it work. Anyways feel free to ask questions. I hope it was interesting for some of you at least. PS: My new app was just approved by app review, let the app gods favor me and bring me many downloads ! Also forgot to talk about a potential $100k+ acquisition of one of my apps, but if that ever happens I'll make a post on it.

I run an AI automation agency (AAA). My honest overview and review of this new business model
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AI_Scout_OfficialThis week

I run an AI automation agency (AAA). My honest overview and review of this new business model

I started an AI tools directory in February, and then branched off that to start an AI automation agency (AAA) in June. So far I've come across a lot of unsustainable "ideas" to make money with AI, but at the same time a few diamonds in the rough that aren't fully tapped into yet- especially the AAA model. Thought I'd share this post to shine light into this new business model and share some ways you could potentially start your own agency, or at the very least know who you are dealing with and how to pick and choose when you (inevitably) get bombarded with cold emails from them down the line. Foreword Running an AAA does NOT involve using AI tools directly to generate and sell content directly. That ship has sailed, and unless you are happy with $5 from Fiverr every month or so, it is not a real business model. Cry me a river but generating generic art with AI and slapping it onto a T-shirt to sell on Etsy won't make you a dime. At the same time, the AAA model will NOT require you to have a deep theoretical knowledge of AI, or any academic degree, as we are more so dealing with the practical applications of generative AI and how we can implement these into different workflows and tech-stacks, rather than building AI models from the ground up. Regardless of all that, common sense and a willingness to learn will help (a shit ton), as with anything. Keep in mind - this WILL involve work and motivation as well. The mindset that AI somehow means everything can be done for you on autopilot is not the right way to approach things. The common theme of businesses I've seen who have successfully implemented AI into their operations is the willingess to work with AI in a way that augments their existing operations, rather than flat out replace a worker or team. And this is exactly the train of thought you need when working with AI as a business model. However, as the field is relatively unsaturated and hype surrounding AI is still fresh for enterprises, right now is the prime time to start something new if generative AI interests you at all. With that being said, I'll be going over three of the most successful AI-adjacent businesses I've seen over this past year, in addition to some tips and resources to point you in the right direction. so.. WTF is an AI Automation Agency? The AI automation agency (or as some YouTubers have coined it, the AAA model) at its core involves creating custom AI solutions for businesses. I have over 1500 AI tools listed in my directory, however the feedback I've received from some enterprise users is that ready-made SaaS tools are too generic to meet their specific needs. Combine this with the fact virtually no smaller companies have the time or skills required to develop custom solutions right off the bat, and you have yourself real demand. I would say in practice, the AAA model is quite similar to Wordpress and even web dev agencies, with the major difference being all solutions you develop will incorporate key aspects of AI AND automation. Which brings me to my second point- JUST AI IS NOT ENOUGH. Rather than reducing the amount of time required to complete certain tasks, I've seen many AI agencies make the mistake of recommending and (trying to) sell solutions that more likely than not increase the workload of their clients. For example, if you were to make an internal tool that has AI answer questions based on their knowledge base, but this knowledge base has to be updated manually, this is creating unnecessary work. As such I think one of the key components of building successful AI solutions is incorporating the new (Generative AI/LLMs) with the old (programmtic automation- think Zapier, APIs, etc.). Finally, for this business model to be successful, ideally you should target a niche in which you have already worked and understand pain points and needs. Not only does this make it much easier to get calls booked with prospects, the solutions you build will have much greater value to your clients (meaning you get paid more). A mistake I've seen many AAA operators make (and I blame this on the "Get Rich Quick" YouTubers) is focusing too much on a specific productized service, rather than really understanding the needs of businesses. The former is much done via a SaaS model, but when going the agency route the only thing that makes sense is building custom solutions. This is why I always take a consultant-first approach. You can only build once you understand what they actually need and how certain solutions may impact their operations, workflows, and bottom-line. Basics of How to Get Started Pick a niche. As I mentioned previously, preferably one that you've worked in before. Niches I know of that are actively being bombarded with cold emails include real estate, e-commerce, auto-dealerships, lawyers, and medical offices. There is a reason for this, but I will tell you straight up this business model works well if you target any white-collar service business (internal tools approach) or high volume businesses (customer facing tools approach). Setup your toolbox. If you wanted to start a pressure washing business, you would need a pressure-washer. This is no different. For those without programming knowledge, I've seen two common ways AAA get setup to build- one is having a network of on-call web developers, whether its personal contacts or simply going to Upwork or any talent sourcing agency. The second is having an arsenal of no-code tools. I'll get to this more in a second, but this works beecause at its core, when we are dealing with the practical applications of AI, the code is quite simple, simply put. Start cold sales. Unless you have a network already, this is not a step you can skip. You've already picked a niche, so all you have to do is find the right message. Keep cold emails short, sweet, but enticing- and it will help a lot if you did step 1 correctly and intimately understand who your audience is. I'll be touching base later about how you can leverage AI yourself to help you with outreach and closing. The beauty of gen AI and the AAA model You don't need to be a seasoned web developer to make this business model work. The large majority of solutions that SME clients want is best done using an API for an LLM for the actual AI aspect. The value we create with the solutions we build comes with the conceptual framework and design that not only does what they need it to but integrates smoothly with their existing tech-stack and workflow. The actual implementation is quite straightforward once you understand the high level design and know which tools you are going to use. To give you a sense, even if you plan to build out these apps yourself (say in Python) the large majority of the nitty gritty technical work has already been done for you, especially if you leverage Python libraries and packages that offer high level abstraction for LLM-related functions. For instance, calling GPT can be as little as a single line of code. (And there are no-code tools where these functions are simply an icon on a GUI). Aside from understanding the capabilities and limitations of these tools and frameworks, the only thing that matters is being able to put them in a way that makes sense for what you want to build. Which is why outsourcing and no-code tools both work in our case. Okay... but how TF am I suppposed to actually build out these solutions? Now the fun part. I highly recommend getting familiar with Langchain and LlamaIndex. Both are Python libraires that help a lot with the high-level LLM abstraction I mentioned previously. The two most important aspects include being able to integrate internal data sources/knowledge bases with LLMs, and have LLMs perform autonomous actions. The two most common methods respectively are RAG and output parsing. RAG (retrieval augmented Generation) If you've ever seen a tool that seemingly "trains" GPT on your own data, and wonder how it all works- well I have an answer from you. At a high level, the user query is first being fed to what's called a vector database to run vector search. Vector search basically lets you do semantic search where you are searching data based on meaning. The vector databases then retrieves the most relevant sections of text as it relates to the user query, and this text gets APPENDED to your GPT prompt to provide extra context to the AI. Further, with prompt engineering, you can limit GPT to only generate an answer if it can be found within this extra context, greatly limiting the chance of hallucination (this is where AI makes random shit up). Aside from vector databases, we can also implement RAG with other data sources and retrieval methods, for example SQL databses (via parsing the outputs of LLM's- more on this later). Autonomous Agents via Output Parsing A common need of clients has been having AI actually perform tasks, rather than simply spitting out text. For example, with autonomous agents, we can have an e-commerce chatbot do the work of a basic customer service rep (i.e. look into orders, refunds, shipping). At a high level, what's going on is that the response of the LLM is being used programmtically to determine which API to call. Keeping on with the e-commerce example, if I wanted a chatbot to check shipping status, I could have a LLM response within my app (not shown to the user) with a prompt that outputs a random hash or string, and programmatically I can determine which API call to make based on this hash/string. And using the same fundamental concept as with RAG, I can append the the API response to a final prompt that would spit out the answer for the user. How No Code Tools Can Fit In (With some example solutions you can build) With that being said, you don't necessarily need to do all of the above by coding yourself, with Python libraries or otherwise. However, I will say that having that high level overview will help IMMENSELY when it comes to using no-code tools to do the actual work for you. Regardless, here are a few common solutions you might build for clients as well as some no-code tools you can use to build them out. Ex. Solution 1: AI Chatbots for SMEs (Small and Medium Enterprises) This involves creating chatbots that handle user queries, lead gen, and so forth with AI, and will use the principles of RAG at heart. After getting the required data from your client (i.e. product catalogues, previous support tickets, FAQ, internal documentation), you upload this into your knowledge base and write a prompt that makes sense for your use case. One no-code tool that does this well is MyAskAI. The beauty of it especially for building external chatbots is the ability to quickly ingest entire websites into your knowledge base via a sitemap, and bulk uploading files. Essentially, they've covered the entire grunt work required to do this manually. Finally, you can create a inline or chat widget on your client's website with a few lines of HTML, or altneratively integrate it with a Slack/Teams chatbot (if you are going for an internal Q&A chatbot approach). Other tools you could use include Botpress and Voiceflow, however these are less for RAG and more for building out complete chatbot flows that may or may not incorporate LLMs. Both apps are essentially GUIs that eliminate the pain and tears and trying to implement complex flows manually, and both natively incoporate AI intents and a knowledge base feature. Ex. Solution 2: Internal Apps Similar to the first example, except we go beyond making just chatbots but tools such as report generation and really any sort of internal tool or automations that may incorporate LLM's. For instance, you can have a tool that automatically generates replies to inbound emails based on your client's knowledge base. Or an automation that does the same thing but for replies to Instagram comments. Another example could be a tool that generates a description and screeenshot based on a URL (useful for directory sites, made one for my own :P). Getting into more advanced implementations of LLMs, we can have tools that can generate entire drafts of reports (think 80+ pages), based not only on data from a knowledge base but also the writing style, format, and author voice of previous reports. One good tool to create content generation panels for your clients would be MindStudio. You can train LLM's via prompt engineering in a structured way with your own data to essentially fine tune them for whatever text you need it to generate. Furthermore, it has a GUI where you can dictate the entire AI flow. You can also upload data sources via multiple formats, including PDF, CSV, and Docx. For automations that require interactions between multiple apps, I recommend the OG zapier/make.com if you want a no-code solution. For instance, for the automatic email reply generator, I can have a trigger such that when an email is received, a custom AI reply is generated by MyAskAI, and finally a draft is created in my email client. Or, for an automation where I can create a social media posts on multiple platforms based on a RSS feed (news feed), I can implement this directly in Zapier with their native GPT action (see screenshot) As for more complex LLM flows that may require multiple layers of LLMs, data sources, and APIs working together to generate a single response i.e. a long form 100 page report, I would recommend tools such as Stack AI or Flowise (open-source alternative) to build these solutions out. Essentially, you get most of the functions and features of Python packages such as Langchain and LlamaIndex in a GUI. See screenshot for an example of a flow How the hell are you supposed to find clients? With all that being said, none of this matters if you can't find anyone to sell to. You will have to do cold sales, one way or the other, especially if you are brand new to the game. And what better way to sell your AI services than with AI itself? If we want to integrate AI into the cold outreach process, first we must identify what it's good at doing, and that's obviously writing a bunch of text, in a short amount of time. Similar to the solutions that an AAA can build for its clients, we can take advantage of the same principles in our own sales processes. How to do outreach Once you've identified your niche and their pain points/opportunities for automation, you want to craft a compelling message in which you can send via cold email and cold calls to get prospects booked on demos/consultations. I won't get into too much detail in terms of exactly how to write emails or calling scripts, as there are millions of resources to help with this, but I will tell you a few key points you want to keep in mind when doing outreach for your AAA. First, you want to keep in mind that many businesses are still hesitant about AI and may not understand what it really is or how it can benefit their operations. However, we can take advantage of how mass media has been reporting on AI this past year- at the very least people are AWARE that sooner or later they may have to implement AI into their businesses to stay competitive. We want to frame our message in a way that introduces generative AI as a technology that can have a direct, tangible, and positive impact on their business. Although it may be hard to quantify, I like to include estimates of man-hours saved or costs saved at least in my final proposals to prospects. Times are TOUGH right now, and money is expensive, so you need to have a compelling reason for businesses to get on board. Once you've gotten your messaging down, you will want to create a list of prospects to contact. Tools you can use to find prospects include Apollo.io, reply.io, zoominfo (expensive af), and Linkedin Sales Navigator. What specific job titles, etc. to target will depend on your niche but for smaller companies this will tend to be the owner. For white collar niches, i.e. law, the professional that will be directly benefiting from the tool (i.e. partners) may be better to contact. And for larger organizations you may want to target business improvement and digital transformation leads/directors- these are the people directly in charge of projects like what you may be proposing. Okay- so you have your message, and your list, and now all it comes down to is getting the good word out. I won't be going into the details of how to send these out, a quick Google search will give you hundreds of resources for cold outreach methods. However, personalization is key and beyond simple dynamic variables you want to make sure you can either personalize your email campaigns directly with AI (SmartWriter.ai is an example of a tool that can do this), or at the very least have the ability to import email messages programmatically. Alternatively, ask ChatGPT to make you a Python Script that can take in a list of emails, scrape info based on their linkedin URL or website, and all pass this onto a GPT prompt that specifies your messaging to generate an email. From there, send away. How tf do I close? Once you've got some prospects booked in on your meetings, you will need to close deals with them to turn them into clients. Call #1: Consultation Tying back to when I mentioned you want to take a consultant-first appraoch, you will want to listen closely to their goals and needs and understand their pain points. This would be the first call, and typically I would provide a high level overview of different solutions we could build to tacke these. It really helps to have a presentation available, so you can graphically demonstrate key points and key technologies. I like to use Plus AI for this, it's basically a Google Slides add-on that can generate slide decks for you. I copy and paste my default company messaging, add some key points for the presentation, and it comes out with pretty decent slides. Call #2: Demo The second call would involve a demo of one of these solutions, and typically I'll quickly prototype it with boilerplate code I already have, otherwise I'll cook something up in a no-code tool. If you have a niche where one type of solution is commonly demanded, it helps to have a general demo set up to be able to handle a larger volume of calls, so you aren't burning yourself out. I'll also elaborate on how the final product would look like in comparison to the demo. Call #3 and Beyond: Once the initial consultation and demo is complete, you will want to alleviate any remaining concerns from your prospects and work with them to reach a final work proposal. It's crucial you lay out exactly what you will be building (in writing) and ensure the prospect understands this. Furthermore, be clear and transparent with timelines and communication methods for the project. In terms of pricing, you want to take this from a value-based approach. The same solution may be worth a lot more to client A than client B. Furthermore, you can create "add-ons" such as monthly maintenance/upgrade packages, training sessions for employeees, and so forth, separate from the initial setup fee you would charge. How you can incorporate AI into marketing your businesses Beyond cold sales, I highly recommend creating a funnel to capture warm leads. For instance, I do this currently with my AI tools directory, which links directly to my AI agency and has consistent branding throughout. Warm leads are much more likely to close (and honestly, much nicer to deal with). However, even without an AI-related website, at the very least you will want to create a presence on social media and the web in general. As with any agency, you will want basic a professional presence. A professional virtual address helps, in addition to a Google Business Profile (GBP) and TrustPilot. a GBP (especially for local SEO) and Trustpilot page also helps improve the looks of your search results immensely. For GBP, I recommend using ProfilePro, which is a chrome extension you can use to automate SEO work for your GBP. Aside from SEO optimzied business descriptions based on your business, it can handle Q/A answers, responses, updates, and service descriptions based on local keywords. Privacy and Legal Concerns of the AAA Model Aside from typical concerns for agencies relating to service contracts, there are a few issues (especially when using no-code tools) that will need to be addressed to run a successful AAA. Most of these surround privacy concerns when working with proprietary data. In your terms with your client, you will want to clearly define hosting providers and any third party tools you will be using to build their solution, and a DPA with these third parties listed as subprocessors if necessary. In addition, you will want to implement best practices like redacting private information from data being used for building solutions. In terms of addressing concerns directly from clients, it helps if you host your solutions on their own servers (not possible with AI tools), and address the fact only ChatGPT queries in the web app, not OpenAI API calls, will be used to train OpenAI's models (as reported by mainstream media). The key here is to be open and transparent with your clients about ALL the tools you are using, where there data will be going, and make sure to get this all in writing. have fun, and keep an open mind Before I finish this post, I just want to reiterate the fact that this is NOT an easy way to make money. Running an AI agency will require hours and hours of dedication and work, and constantly rearranging your schedule to meet prospect and client needs. However, if you are looking for a new business to run, and have a knack for understanding business operations and are genuinely interested in the pracitcal applications of generative AI, then I say go for it. The time is ticking before AAA becomes the new dropshipping or SMMA, and I've a firm believer that those who set foot first and establish themselves in this field will come out top. And remember, while 100 thousand people may read this post, only 2 may actually take initiative and start.

Jinxed - $0 month after bragging about my first $10k month here. (PROGRESS UPDATE)
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swagamoneyThis week

Jinxed - $0 month after bragging about my first $10k month here. (PROGRESS UPDATE)

A month ago I made a post in this sub about my first $10k month. It went viral. And guess what - I didn't make another dollar since. Honestly, I shouldn't have made any money that first month also. Because I didn't have an offer. If you're familiar with Alex Hormozi you know that the offer is what makes or breaks a business. And I simply didn't have it. I managed to close my first clients just because I rode the AI hype train and managed to capture a couple of CEOs who were riding it too. Took whatever I could get for installment without thinking about the future. (It also helped that I wasn't bullshitting and had a legit enterprise-grade custom GPT framework ready). But that's not a business strategy at all. You can't base your business solely off hype. So the last month was dedicated to crafting a proper offer. No selling involved. Purely discovery chats with as many people as possible. The viral post helped because I connected with some badass people I wouldn't have reached otherwise. Even managed to add a new team member from Reddit. But most importantly, we now have the offer: Enterprise-grade AI assistant trained on your data for a fraction of the market cost. Basically a custom GPT for companies that want a secure assistant "trained" on their data but are not willing to spend millions on OpenAI's Custom Models or hundreds of thousands on Enterprise ChatGPT. (OpenAI's introduction of exclusive business GPTs for $2-3M is an incredibly good leverage for this offer). Also got rid of the big installment fee and switched to a $1k/month starting price for attractiveness and simplicity for companies (that covers their Azure fees also). The key offer points here are: Data security (as there are cheap, but not enterprise-grade tools like PDF.ai) Good price (as not all businesses can afford to pay 6 figure premiums for their data security) So the lesson here (I suppose) is that it's okay to take a step back sometimes. Reevaluate your direction. It's not worth sprinting when you're running in circles. P.S. finally made a website https://jongri.tech

The delicate balance of building an online community business
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matthewbarbyThis week

The delicate balance of building an online community business

Hey /r/Entrepreneur 👋 Just under two years ago I launched an online community business called Traffic Think Tank with two other co-founders, Nick Eubanks and Ian Howells. As a Traffic Think Tank customer you (currently) pay $119 a month to get access to our online community, which is run through Slack. The community is focused on helping you learn various aspects of marketing, with a particular focus on search engine optimization (SEO). Alongside access to the Slack community, we publish new educational video content from outside experts every week that all customers have access to. At the time of writing, Traffic Think Tank has around 650 members spanning across 17 of the 24 different global time zones. I was on a business trip over in Sydney recently, and during my time there I met up with some of our Australia-based community members. During dinner I was asked by several of them how the idea for Traffic Think Tank came about and what steps we took to validate that the idea was worth pursuing.  This is what I told them… How it all began It all started with a personal need. Nick, an already successful entrepreneur and owner of a marketing agency, had tested out an early version Traffic Think Tank in early 2017. He offered real-time consulting for around ten customers that he ran from Slack. He would publish some educational videos and offer his advice on projects that the members were running. The initial test went well, but it was tough to maintain on his own and he had to charge a fairly high price to make it worth his time. That’s when he spoke to me and Ian about turning this idea into something much bigger. Both Ian and I offered something slightly different to Nick. We’ve both spent time in senior positions at marketing agencies, but currently hold senior director positions in 2,000+ public employee companies (HubSpot and LendingTree). Alongside this, as a trio we could really ramp up the quality and quantity of content within the community, spread out the administrative workload and just generally have more resources to throw at getting this thing off the ground. Admittedly, Nick was much more optimistic about the potential of Traffic Think Tank – something I’m very thankful for now – whereas Ian and I were in the camp of “you’re out of your mind if you think hundreds of people are going to pay us to be a part of a Slack channel”. To validate the idea at scale, we decided that we’d get an initial MVP of the community up and running with a goal of reaching 100 paying customers in the first six months. If we achieved that, we’d validated that it was a viable business and we would continue to pursue it. If not, we’d kill it. We spent the next month building out the initial tech stack that enabled us to accept payments, do basic user management to the Slack channel, and get a one-page website up and running with information on what Traffic Think Tank was all about.  After this was ready, we doubled down on getting some initial content created for members – I mean, we couldn’t have people just land in an empty Slack channel, could we? We created around ten initial videos, 20 or so articles and then some long threads full of useful information within the Slack channel so that members would have some content to pour into right from the beginning.  Then, it was time to go live. The first 100 customers Fortunately, both Nick and I had built a somewhat substantial following in the SEO space over the previous 5-10 years, so we at least had a large email list to tap into (a total of around 40,000 people). We queued up some launch emails, set an initial price of $99 per month and pressed send. [\[LINK\] The launch email I sent to my subscribers announcing Traffic Think Tank](https://mailchi.mp/matthewbarby/future-of-marketing-1128181) What we didn’t expect was to sell all of the initial 100 membership spots in the first 72 hours. “Shit. What do we do now? Are we ready for this many people? Are we providing them with enough value? What if something breaks in our tech stack? What if they don’t like the content? What if everyone hates Slack?” All of these were thoughts running through my head. This brings me to the first great decision we made: we closed down new membership intake for 3 months so that we could focus completely on adding value to the first cohort of users. The right thing at the right time SEO is somewhat of a dark art to many people that are trying to learn about it for the first time. There’s hundreds of thousands (possibly millions) of articles and videos online that talk about how to do SEO.  Some of it’s good advice; a lot of it is very bad advice.  Add to this that the barrier to entry of claiming to be an “expert” in SEO is practically non-existent and you have a recipe for disaster. This is why, for a long time, individuals involved in SEO have flocked in their masses to online communities for information and to bounce ideas off of others in the space. Forums like SEObook, Black Hat World, WickedFire, Inbound.org, /r/BigSEO, and many more have, at one time, been called home by many SEOs.  In recent times, these communities have either been closed down or just simply haven’t adapted to the changing needs of the community – one of those needs being real-time feedback on real-world problems.  The other big need that we all spotted and personally had was the ability to openly share the things that are working – and the things that aren’t – in SEO within a private forum. Not everyone wanted to share their secret sauce with the world. One of the main reasons we chose Slack as the platform to run our community on was the fact that it solved these two core needs. It gave the ability to communicate in real-time across multiple devices, and all of the information shared within it was outside of the public domain. The other problem that plagued a lot of these early communities was spam. Most of them were web-based forums that were free to access. That meant they became a breeding ground for people trying to either sell their services or promote their own content – neither of which is conducive to building a thriving community. This was our main motivation for charging a monthly fee to access Traffic Think Tank. We spent a lot of time thinking through pricing. It needed to be enough money that people would be motivated to really make use of their membership and act in a way that’s beneficial to the community, but not too much money that it became cost prohibitive to the people that would benefit from it the most. Considering that most of our members would typically spend between $200-800 per month on SEO software, $99 initially felt like the perfect balance. Growing pains The first three months of running the community went by without any major hiccups. Members were incredibly patient with us, gave us great feedback and were incredibly helpful and accommodating to other members. Messages were being posted every day, with Nick, Ian and myself seeding most of the engagement at this stage.  With everything going smoothly, we decided that it was time to open the doors to another intake of new members. At this point we’d accumulated a backlog of people on our waiting list, so we knew that simply opening our doors would result in another large intake. Adding more members to a community has a direct impact on the value that each member receives. For Traffic Think Tank in particular, the value for members comes from three areas: The ability to have your questions answered by me, Nick and Ian, as well as other members of the community. The access to a large library of exclusive content. The ability to build connections with the wider community. In the early stages of membership growth, there was a big emphasis on the first of those three points. We didn’t have an enormous content library, nor did we have a particularly large community of members, so a lot of the value came from getting a lot of one-to-one time with the community founders. [\[IMAGE\] Screenshot of engagement within the Traffic Think Tank Slack community](https://cdn.shortpixel.ai/client/qglossy,retimg,w_1322/https://www.matthewbarby.com/wp-content/uploads/2019/08/Community-Engagement-in-Traffic-Think-Tank.png) The good thing about having 100 members was that it was just about feasible to give each and every member some one-to-one time within the month, which really helped us to deliver those moments of delight that the community needed early on. Two-and-a-half months after we launched Traffic Think Tank, we opened the doors to another 250 people, taking our total number of members to 350. This is where we experienced our first growing pains.  Our original members had become used to being able to drop us direct messages and expect an almost instant response, but this wasn’t feasible anymore. There were too many people, and we needed to create a shift in behavior. We needed more value to come from the community engaging with one another or we’d never be able to scale beyond this level. We started to really pay attention to engagement metrics; how many people were logging in every day, and of those, how many were actually posting messages within public channels.  We asked members that were logging in a lot but weren’t posting (the “lurkers”) why that was the case. We also asked the members that engaged in the community the most what motivated them to post regularly. We learned a lot from doing this. We found that the large majority of highly-engaged members had much more experience in SEO, whereas most of the “lurkers” were beginners. This meant that most of the information being shared in the community was very advanced, with a lot of feedback from the beginners in the group being that they “didn’t want to ask a stupid question”.  As managers of the community, we needed to facilitate conversations that catered to all of our members, not just those at a certain level of skill. To tackle this problem, we created a number of new channels that had a much deeper focus on beginner topics so novice members had a safe place to ask questions without judgment.  We also started running live video Q&As each month where we’d answer questions submitted by the community. This gave our members one-on-one time with me, Nick and Ian, but spread the value of these conversations across the whole community rather than them being hidden within private messages. As a result of these changes, we found that the more experienced members in the community were really enjoying sharing their knowledge with those with less experience. The number of replies within each question thread was really starting to increase, and the community started to shift away from just being a bunch of threads created by me, Nick and Ian to a thriving forum of diverse topics compiled by a diverse set of individuals. This is what we’d always wanted. A true community. It was starting to happen. [\[IMAGE\] Chart showing community engagement vs individual member value](https://cdn.shortpixel.ai/client/qglossy,retimg,w_1602/https://www.matthewbarby.com/wp-content/uploads/2019/08/Community-Engagement-Balance-Graph.jpg) At the same time, we started to realize that we’ll eventually reach a tipping point where there’ll be too much content for us to manage and our members to engage with. When we reach this point, the community will be tough to follow and the quality of any given post will go down. Not only that, but the community will become increasingly difficult to moderate. We’re not there yet, but we recognize that this will come, and we’ll have to adjust our model again. Advocating advocacy As we started to feel more comfortable about the value that members were receiving, we made the decision to indefinitely open for new members. At the same time, we increased the price of membership (from $99 a month to $119) in a bid to strike the right balance between profitability as a business and to slow down the rate at which we were reaching the tipping point of community size. We also made the decision to repay all of our early adopters by grandfathering them in to the original pricing – and committing to always do this in the future. Despite the price increase, we saw a continued flow of new members come into the community. The craziest part about this was that we were doing practically no marketing activities to encourage new members– this was all coming from word of mouth. Our members were getting enough value from the community that they were recommending it to their friends, colleagues and business partners.  The scale at which this was happening really took us by surprise and it told us one thing very clearly: delivering more value to members resulted in more value being delivered to the business. This is a wonderful dynamic to have because it perfectly aligns the incentives on both sides. We’d said from the start that we wouldn’t sacrifice value to members for more revenue – this is something that all three of us felt very strongly about. First and foremost, we wanted to create a community that delivered value to its members and was run in a way that aligned with our values as people. If we could find a way to stimulate brand advocacy, while also tightening the bonds between all of our individual community members, we’d be boosting both customer retention and customer acquisition in the same motion. This became our next big focus. [\[TWEET\] Adam, one of our members wore his Traffic Think Tank t-shirt in the Sahara desert](https://twitter.com/AdamGSteele/status/1130892481099382784) We started with some simple things: We shipped out Traffic Think Tank branded T-shirts to all new members. We’d call out each of the individuals that would submit questions to our live Q&A sessions and thank them live on air. We set up a new channel that was dedicated to sharing a quick introduction to who you are, what you do and where you’re based for all new members. We’d created a jobs channel and a marketplace for selling, buying and trading services with other members. Our monthly “blind dates” calls were started where you’d be randomly grouped with 3-4 other community members so that you could hop on a call to get to know each other better. The Traffic Think Tank In Real Life (IRL)* channel was born, which enabled members to facilitate in-person meetups with each other. In particular, we saw that as members started to meet in person or via calls the community itself was feeling more and more like a family. It became much closer knit and some members started to build up a really positive reputation for being particularly helpful to other members, or for having really strong knowledge in a specific area. [\[TWEET\] Dinner with some of the Traffic Think Tank members in Brighton, UK](https://twitter.com/matthewbarby/status/1117175584080134149) Nick, Ian and I would go out of our way to try and meet with members in real life wherever we could. I was taken aback by how appreciative people were for us doing this, and it also served as an invaluable way to gain honest feedback from members. There was another trend that we’d observed that we didn’t really expect to happen. More and more members were doing business with each another. We’ve had people find new jobs through the community, sell businesses to other members, launch joint ventures together and bring members in as consultants to their business. This has probably been the most rewarding thing to watch, and it was clear that the deeper relationships that our members were forming were resulting in an increased level of trust to work with each other. We wanted to harness this and take it to a new level. This brought us to arguably the best decision we’ve made so far running Traffic Think Tank… we were going to run a big live event for our members. I have no idea what I’m doing It’s the first week of January 2019 and we’re less than three weeks away from Traffic Think Tank LIVE, our first ever in-person event hosting 150 people, most of which are Traffic Think Tank members. It's like an ongoing nightmare I can’t wake up from. That was Nick’s response in our private admin channel to myself and Ian when I asked if they were finding the run-up to the event as stressful as I was. I think that all three of us were riding on such a high from how the community was growing that we felt like we could do anything. Running an event? How hard can it be? Well, turns out it’s really hard. We had seven different speakers flying over from around the world to speak at the event, there was a pre- and after event party, and we’d planned a charity dinner where we would take ten attendees (picked at random via a raffle) out for a fancy meal. Oh, and Nick, Ian and I were hosting a live Q&A session on stage. It wasn’t until precisely 48 hours before the event that we’d realized we didn’t have any microphones, nor had a large amount of the swag we’d ordered arrived. Plus, a giant storm had hit Philly causing a TON of flight cancellations. Perfect. Just perfect. This was honestly the tip of the iceberg. We hadn’t thought about who was going to run the registration desk, who would be taking photos during the event and who would actually field questions from the audience while all three of us sat on stage for our live Q&A panel. Turns out that the answer to all of those questions were my wife, Laura, and Nick’s wife, Kelley. Thankfully, they were on hand to save our asses. The weeks running up to the event were honestly some of the most stressful of my life. We sold around 50% of our ticket allocation within the final two weeks before the event. All of the event organizers told us this would happen, but did we believe them? Hell no!  Imagine having two weeks until the big day and as it stood half of the room would be completely empty. I was ready to fly most of my extended family over just to make it look remotely busy. [\[IMAGE\] One of our speakers, Ryan Stewart, presenting at Traffic Think Tank LIVE](https://cdn.shortpixel.ai/client/qglossy,retimg,w_1920/https://www.matthewbarby.com/wp-content/uploads/2019/08/Traffic-Think-Tank-LIVE-Ryan-Presenting.jpg) Thankfully, if all came together. We managed to acquire some microphones, the swag arrived on the morning of the event, all of our speakers were able to make it on time and the weather just about held up so that our entire allocation of ticket holders was able to make it to the event. We pooled together and I’m proud to say that the event was a huge success. While we made a substantial financial loss on the event itself, January saw a huge spike in new members, which more than recouped our losses. Not only that, but we got to hang out with a load of our members all day while they said really nice things about the thing we’d built. It was both exhausting and incredibly rewarding. Bring on Traffic Think Tank LIVE 2020! (This time we’re hiring an event manager...)   The road ahead Fast forward to today (August 2019) and Traffic Think Tank has over 650 members. The biggest challenges that we’re tackling right now include making sure the most interesting conversations and best content surfaces to the top of the community, making Slack more searchable (this is ultimately one of its flaws as a platform) and giving members a quicker way to find the exclusive content that we create. You’ll notice there’s a pretty clear theme here. In the past 30 days, 4,566 messages were posted in public channels inside Traffic Think Tank. If you add on any messages posted inside private direct messages, this number rises to 21,612. That’s a lot of messages. To solve these challenges and enable further scale in the future, we’ve invested a bunch of cash and our time into building out a full learning management system (LMS) that all members will get access to alongside the Slack community. The LMS will be a web-based portal that houses all of the video content we produce. It will also  provide an account admin section where users can update or change their billing information (they have to email us to do this right now, which isn’t ideal), a list of membership perks and discounts with our partners, and a list of links to some of the best threads within Slack – when clicked, these will drop you directly into Slack. [\[IMAGE\] Designs for the new learning management system (LMS)](https://cdn.shortpixel.ai/client/qglossy,retimg,w_2378/https://www.matthewbarby.com/wp-content/uploads/2019/08/Traffic-Think-Tank-LMS.png) It’s not been easy, but we’re 95% of the way through this and I’m certain that it will have a hugely positive impact on the experience for our members. Alongside this we hired a community manager, Liz, who supports with any questions that our members have, coordinates with external experts to arrange webinars for the community, helps with new member onboarding, and has tightened up some of our processes around billing and general accounts admin. This was a great decision. Finally, we’ve started planning next year’s live event, which we plan to more than double in size to 350 attendees, and we decided to pick a slightly warmer location in Miami this time out. Stay tuned for me to have a complete meltdown 3 weeks from the event. Final thoughts When I look back on the journey we’ve had so far building Traffic Think Tank, there’s one very important piece to this puzzle that’s made all of this work that I’ve failed to mention so far: co-founder alignment. Building a community is a balancing act that relies heavily on those in charge being completely aligned. Nick, Ian and I completely trust each other and more importantly, are philosophically aligned on how we want to run and grow the community. If we didn’t have this, the friction between us could tear apart the entire community. Picking the right people to work with is important in any company, but when your business is literally about bringing people together, there’s no margin for error here.  While I’m sure there will be many more challenges ahead, knowing that we all trust each other to make decisions that fall in line with each of our core values makes these challenges dramatically easier to overcome. Finally, I’d like to thank all of our members for making the community what it is today – it’d be nothing without you and I promise that we’ll never take that for granted. &#x200B; I originally posted this on my blog here. Welcoming all of your thoughts, comments, questions and I'll do my best to answer them :)

How a Small Startup in Asia Secured a Contract with the US Department of Homeland Security
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How a Small Startup in Asia Secured a Contract with the US Department of Homeland Security

Uzair Javaid, a Ph.D. with a passion for data privacy, co-founded Betterdata to tackle one of AI's most pressing challenges: protecting privacy while enabling innovation. Recently, Betterdata secured a lucrative contract with the US Department of Homeland Security, 1 of only 4 companies worldwide to do so and the only one in Asia. Here's how he did it: The Story So what's your story? I grew up in Peshawar, Pakistan, excelling in coding despite studying electrical engineering. Inspired by my professors, I set my sights on studying abroad and eventually earned a Ph.D. scholarship at NUS Singapore, specializing in data security and privacy. During my research, I ethically hacked Ethereum and published 15 papers—three times the requirement. While wrapping up my Ph.D., I explored startup ideas and joined Entrepreneur First, where I met Kevin Yee. With his expertise in generative models and mine in privacy, we founded Betterdata. Now, nearly three years in, we’ve secured a major contract with the U.S. Department of Homeland Security—one of only four companies globally and the only one from Asia. The Startup In a nutshell, what does your startup do? Betterdata is a startup that uses AI and synthetic data generation to address two major challenges: data privacy and the scarcity of high-quality data for training AI models. By leveraging generative models and privacy-enhancing technologies, Betterdata enables businesses, such as banks, to use customer data without breaching privacy regulations. The platform trains AI on real data, learns its patterns, and generates synthetic data that mimics the real thing without containing any personal or sensitive information. This allows companies to innovate and develop AI solutions safely and ethically, all while tackling the growing need for diverse, high-quality data in AI development. How did you conduct ideation and validation for your startup? The initial idea for Betterdata came from personal experience. During my Ph.D., I ethically hacked Ethereum’s blockchain, exposing flaws in encryption-based data sharing. This led me to explore AI-driven deep synthesis technology—similar to deepfakes but for structured data privacy. With GDPR impacting 28M+ businesses, I saw a massive opportunity to help enterprises securely share data while staying compliant. To validate the idea, I spoke to 50 potential customers—a number that strikes the right balance. Some say 100, but that’s impractical for early-stage founders. At 50, patterns emerge: if 3 out of 10 mention the same problem, and this repeats across 50, you have 10–15 strong signals, making it a solid foundation for an MVP. Instead of outbound sales, which I dislike, we used three key methods: Account-Based Marketing (ABM)—targeting technically savvy users with solutions for niche problems, like scaling synthetic data for banks. Targeted Content Marketing—regular customer conversations shaped our thought leadership and outreach. Raising Awareness Through Partnerships—collaborating with NUS, Singapore’s PDPC, and Plug and Play to build credibility and educate the market. These strategies attracted serious customers willing to pay, guiding Betterdata’s product development and market fit. How did you approach the initial building and ongoing product development? In the early stages, we built synthetic data generation algorithms and a basic UI for proof-of-concept, using open-source datasets to engage with banks. We quickly learned that banks wouldn't share actual customer data due to privacy concerns, so we had to conduct on-site installations and gather feedback to refine our MVP. Through continuous consultation with customers, we discovered real enterprise data posed challenges, such as missing values, which led us to adapt our prototype accordingly. This iterative approach of listening to customer feedback and observing their usage allowed us to improve our product, enhance UX, and address unmet needs while building trust and loyalty. Working closely with our customers also gives us a data advantage. Our solution’s effectiveness depends on customer data, which we can't fully access, but bridging this knowledge gap gives us a competitive edge. The more customers we test on, the more our algorithms adapt to diverse use cases, making it harder for competitors to replicate our insights. My approach to iteration is simple: focus solely on customer feedback and ignore external noise like trends or advice. The key question for the team is: which customer is asking for this feature or solution? As long as there's a clear answer, we move forward. External influences, such as AI hype, often bring more confusion than clarity. True long-term success comes from solving real customer problems, not chasing trends. Customers may not always know exactly what they want, but they understand their problems. Our job is to identify these problems and solve them in innovative ways. While customers may suggest specific features, we stay focused on solving the core issue rather than just fulfilling their exact requests. The idea aligns with the quote often attributed to Henry Ford: "If I asked people what they wanted, they would have said faster horses." The key is understanding their problems, not just taking requests at face value. How do you assess product-market fit? To assess product-market fit, we track two key metrics: Customers' Willingness to Pay: We measure both the quantity and quality of meetings with potential customers. A high number of meetings with key decision-makers signals genuine interest. At Betterdata, we focused on getting meetings with people in banks and large enterprises to gauge our product's resonance with the target market. How Much Customers Are Willing to Pay: We monitor the price customers are willing to pay, especially in the early stages. For us, large enterprises, like banks, were willing to pay a premium for our synthetic data platform due to the growing need for privacy tech. This feedback guided our product refinement and scaling strategy. By focusing on these metrics, we refined our product and positioned it for scaling. What is your business model? We employ a structured, phase-driven approach for out business model, as a B2B startup. I initially struggled with focusing on the core value proposition in sales, often becoming overly educational. Eventually, we developed a product roadmap with models that allowed us to match customer needs to specific offerings and justify our pricing. Our pricing structure includes project-based pilots and annual contracts for successful deployments. At Betterdata, our customer engagement unfolds across three phases: Phase 1: Trial and Benchmarking \- We start with outreach and use open-source datasets to showcase results, offering customers a trial period to evaluate the solution. Phase 2: Pilot or PoC \- After positive trial results, we conduct a PoC or pilot using the customer’s private data, with the understanding that successful pilots lead to an annual contract. Phase 3: Multi-Year Contracts \- Following a successful pilot, we transition to long-term commercial contracts, focusing on multi-year agreements to ensure stability and ongoing partnerships. How do you do marketing for your brand? We take a non-conventional approach to marketing, focusing on answering one key question: Which customers are willing to pay, and how much? This drives our messaging to show how our solution meets their needs. Our strategy centers around two main components: Building a network of lead magnets \- These are influential figures like senior advisors, thought leaders, and strategic partners. Engaging with institutions like IMDA, SUTD, and investors like Plug and Play helps us gain access to the right people and foster warm introductions, which shorten our sales cycle and ensure we’re reaching the right audience. Thought leadership \- We build our brand through customer traction, technology evidence, and regulatory guidelines. This helps us establish credibility in the market and position ourselves as trusted leaders in our field. This holistic approach has enabled us to navigate diverse market conditions in Asia and grow our B2B relationships. By focusing on these areas, we drive business growth and establish strong trust with stakeholders. What's your advice for fundraising? Here are my key takeaways for other founders when it comes to fundraising: Fundraise When You Don’t Need To We closed our seed round in April 2023, a time when we weren't actively raising. Founders should always be in fundraising mode, even when they're not immediately in need of capital. Don’t wait until you have only a few months of runway left. Keep the pipeline open and build relationships. When the timing is right, execution becomes much easier. For us, our investment came through a combination of referrals and inbound interest. Even our lead investor initially rejected us, but after re-engaging, things eventually fell into place. It’s crucial to stay humble, treat everyone with respect, and maintain those relationships for when the time is right. Be Mindful of How You Present Information When fundraising, how you present information matters a lot. We created a comprehensive, easily digestible investment memo, hosted on Notion, which included everything an investor might need—problem, solution, market, team, risks, opportunities, and data. The goal was for investors to be able to get the full picture within 30 minutes without chasing down extra details. We also focused on making our financial model clear and meaningful, even though a 5-year forecast might be overkill at the seed stage. The key was clarity and conciseness, and making it as easy as possible for investors to understand the opportunity. I learned that brevity and simplicity are often the best ways to make a memorable impact. For the pitch itself, keep it simple and focus on 4 things: problem, solution, team, and market. If you can summarize each of these clearly and concisely, you’ll have a compelling pitch. Later on, you can expand into market segments, traction, and other metrics, but for seed-stage, focus on those four areas, and make sure you’re strong in at least three of them. If you do, you'll have a compelling case. How do you run things day-to-day? i.e what's your operational workflow and team structure? Here's an overview of our team structure and process: Internally: Our team is divided into two main areas: backend (internal team) and frontend (market-facing team). There's no formal hierarchy within the backend team. We all operate as equals, defining our goals based on what needs to be developed, assigning tasks, and meeting weekly to share updates and review progress. The focus is on full ownership of tasks and accountability for getting things done. I also contribute to product development, identifying challenges and clearing obstacles to help the team move forward. Backend Team: We approach tasks based on the scope defined by customers, with no blame or hierarchy. It's like a sports team—sometimes someone excels, and other times they struggle, but we support each other and move forward together. Everyone has the creative freedom to work in the way that suits them best, but we establish regular meetings and check-ins to ensure alignment and progress. Frontend Team: For the market-facing side, we implement a hierarchy because the market expects this structure. If I present myself as "CEO," it signals authority and credibility. This distinction affects how we communicate with the market and how we build our brand. The frontend team is split into four main areas: Business Product (Software Engineering) Machine Learning Engineering R&D The C-suite sits at the top, followed by team leads, and then the executors. We distill market expectations into actionable tasks, ensuring that everyone is clear on their role and responsibilities. Process: We start by receiving market expectations and defining tasks based on them. Tasks are assigned to relevant teams, and execution happens with no communication barriers between team members. This ensures seamless collaboration and focused execution. The main goal is always effectiveness—getting things done efficiently while maintaining flexibility in how individuals approach their work. In both teams, there's an emphasis on accountability, collaboration, and clear communication, but the structure varies according to the nature of the work and external expectations.

Turning a Social Media Agency into $1.5 Million in Revenue
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Turning a Social Media Agency into $1.5 Million in Revenue

Steffie here from Founder Folks, with a recent interview I did with Jason Yormark from Socialistics. Here is his story how he started and grew his social media agency. Name: Jason Yormark Company: Socialistics Employee Size: 10 Revenue: $1,500,000/year Year Founded: 2018 Website: www.socialistics.com Technology Tools: ClickUp, Slack, KumoSpace, Google Workspace, Shift, Zapier, Klayvio, Zoom, Gusto, Calendly, Pipedrive Introduction: I am the founder of Socialistics (www.socialistics.com), a leading social media agency that helps businesses turn their social media efforts into real measurable results. I am a 20+ year marketing veteran whose prior work has included launching and managing social media efforts for Microsoft Advertising, Office for Mac, the Air Force, and Habitat for Humanity. I have been recognized as a top B2B social media influencer and thought leader on multiple lists and publications including Forbes, ranking #30 on their 2012 list. I've recently published the book Anti-Agency: A Realistic Path to a $1,000,000 Business, and host the Anti Agency podcast where I share stories of doing business differently. You can learn more about me at www.jasonyormark.com. The Inspiration To Become An Entrepreneur: I’ve been involved with social media marketing since 2007, and have pretty much carved my career out of that. It was a natural progression for me to transition into starting a social media agency. From Idea to Reality: For me realistically, I had to side hustle something long enough to build it up to a point that I could take the leap and risks going full time on my own. For these reasons, I built the company and brand on the side putting out content regularly, and taking on side hustle projects to build out my portfolio and reputation. This went on for about 18 months at which point I had reached the breaking point of my frustrations of working for someone else, and felt I was ready to take the leap since I had the wheels in motion. While balancing a full-time job, I made sure not to overdo it. My main focus was on building out the website/brand and putting out content regularly to gain some traction and work towards some search visibility. I only took on 1-2 clients at a time to make sure I could still meet their needs while balancing a full time job. Attracting Customers: Initially I tapped into my existing network to get my first few clients. Then it was a mix of trade shows, networking events, and throwing a bit of money at paid directories and paid media. This is really a long game. You have to plant seeds over time with people and nurture those relationships over time. A combination of being helpful, likable and a good resource for folks will position you to make asks in the future. If people respect and like you, it makes it much easier to approach for opportunities when the time comes. Overcoming Challenges in Starting the Business: Plenty. Learning when to say no, only hiring the very best, and ultimately the realization that owning a marketing agency is going to have hills and valleys no matter what you do. Costs and Revenue: My largest expense by FAR is personnel, comprising between 50-60% of the business’ expenses, and justifiably so. It’s a people business. Our revenue doubled from the years 2018 through 2021, and we’ve seen between 10-20% growth year over year. A Day in the Life: I’ve successfully removed myself from the day to day of the business and that’s by design. I have a tremendous team, and a rock start Director of Operations who runs the agency day to day. It frees me up to pursue other opportunities, and to mentor, speak and write more. It also allows me to evangelize the book I wrote detailing my journey to a $1M business titled: Anti-Agency: A Realistic Path To A $1,000,000 Business (www.antiagencybook.com). Staying Ahead in a Changing Landscape: You really have to stay on top of technology trends. AI is a huge impact on marketing these days, so making sure we are up to speed on that, and not abusing it or relying on it too much. You also have to embrace that technology and not hide the fact that it’s used. Non-marketers still don’t and can’t do the work regardless of how much AI can help, so we just need to be transparent and smart on how we integrate it, but the fact is, technology will never replace creativity. As an agency, it’s imperative that we operationally allow our account managers to have bandwidth to be creative for clients all the time. It’s how we keep clients and buck the trend of companies changing agencies every year or two. The Vision for Socialistics: Continuing to evolve to cater to our clients through learning, education, and staying on top of the latest tools and technologies. Attracting bigger and more exciting clients, and providing life changing employment opportunities.

AI is taking over Google, huge changes to search
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AI is taking over Google, huge changes to search

AI is taking over Google, and it's revolutionizing the search experience. Instead of focusing on chatbots or homepage redesigns, Google is integrating AI into search results, introducing AI snapshots with generated summaries and corroborating sources. This shift marks the future of Google Search. Link to The Verge article. For SEOs like me, it's a game-changer. Edit: in a negative way. Before, we had rich snippets, but now we have AI snapshots. It's a revamped version of the snippet, providing users with more valuable information upfront. Here's a before and after. But why did Google choose this approach? Well, monetizing something like ChatGPT is challenging. So, they decided to prioritize an AI-first approach in the most valuable space on the internet: search results. What does this mean for normal people? Let me share some insights from my own businesses. Currently, the top spot on Google garners around 20-35% click-through rate (CTR). However, with the introduction of AI snapshots, that CTR is likely to drop to the equivalent of position 5, ranging from 5-10%. In other words, we're looking at a minimum drop of 50% and a maximum drop of 85% in CTR. It's a significant impact that people who rely on Google traffic need to consider. The good news is that users will need to opt-in to access AI snapshots through Search Generative Experience (SGE). It's still an experimental feature, but it's a probable long-term change in search. However, this uncertainty has already led to a drop in niche site valuations. I have no doubt that we can adapt to these changes. However, let's not undermine the potential impact. It's not a "nothing burger." Imo we have around 1-2 years before we witness seismic changes, so let's make the most of it and stack that 💰💰. What do you think? How do you see AI transforming the search landscape? PS: You can subscribe here to join 25k+ marketers who receive updates on recent marketing news.

How a founder built a B2B AI startup to serve with 65+ global brands (including Fortune500 companies)
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How a founder built a B2B AI startup to serve with 65+ global brands (including Fortune500 companies)

AI Palette is an AI-driven platform that helps food and beverage companies predict emerging product trends. I had the opportunity recently to sit down with the founder to get his advice on building an AI-first startup, which he'll be going through in this post. About AI Palette: Co-founders: >!2 (Somsubhra GanChoudhuri, Himanshu Upreti)!!100+!!$12.7M USD!!AI-powered predictive analytics for the CPG (Consumer Packaged Goods) industry!!Signed first paying customer in the first year!!65+ global brands, including Cargill, Diageo, Ajinomoto, Symrise, Mondelez, and L’Oréal, use AI Palette!!Every new product launched has secured a paying client within months!!Expanded into Beauty & Personal Care (BPC), onboarding one of India’s largest BPC companies within weeks!!Launched multiple new product lines in the last two years, creating a unified suite for brand innovation!Identify the pain points in your industry for ideas* When I was working in the flavour and fragrance industry, I noticed a major issue CPG companies faced: launching a product took at least one to two years. For instance, if a company decided today to launch a new juice, it wouldn’t hit the market until 2027. This long timeline made it difficult to stay relevant and on top of trends. Another big problem I noticed was that companies relied heavily on market research to determine what products to launch. While this might work for current consumer preferences, it was highly inefficient since the product wouldn’t actually reach the market for several years. By the time the product launched, the consumer trends had already shifted, making that research outdated. That’s where AI can play a crucial role. Instead of looking at what consumers like today, we realised that companies should use AI to predict what they will want next. This allows businesses to create products that are ahead of the curve. Right now, the failure rate for new product launches is alarmingly high, with 8 out of 10 products failing. By leveraging AI, companies can avoid wasting resources on products that won’t succeed, leading to better, more successful launches. Start by talking to as many industry experts as possible to identify the real problems When we first had the idea for AI Palette, it was just a hunch, a gut feeling—we had no idea whether people would actually pay for it. To validate the idea, we reached out to as many people as we could within the industry. Since our focus area was all about consumer insights, we spoke to professionals in the CPG sector, particularly those in the insights departments of CPG companies. Through these early conversations, we began to see a common pattern emerge and identified the exact problem we wanted to solve. Don’t tell people what you’re building—listen to their frustrations and challenges first. Going into these early customer conversations, our goal was to listen and understand their challenges without telling them what we were trying to build. This is crucial as it ensures that you can gather as much data about the problem to truly understand it and that you aren't biasing their answers by showing your solution. This process helped us in two key ways: First, it validated that there was a real problem in the industry through the number of people who spoke about experiencing the same problem. Second, it allowed us to understand the exact scale and depth of the problem—e.g., how much money companies were spending on consumer research, what kind of tools they were currently using, etc. Narrow down your focus to a small, actionable area to solve initially. Once we were certain that there was a clear problem worth solving, we didn’t try to tackle everything at once. As a small team of two people, we started by focusing on a specific area of the problem—something big enough to matter but small enough for us to handle. Then, we approached customers with a potential solution and asked them for feedback. We learnt that our solution seemed promising, but we wanted to validate it further. If customers are willing to pay you for the solution, it’s a strong validation signal for market demand. One of our early customer interviewees even asked us to deliver the solution, which we did manually at first. We used machine learning models to analyse the data and presented the results in a slide deck. They paid us for the work, which was a critical moment. It meant we had something with real potential, and we had customers willing to pay us before we had even built the full product. This was the key validation that we needed. By the time we were ready to build the product, we had already gathered crucial insights from our early customers. We understood the specific information they wanted and how they wanted the results to be presented. This input was invaluable in shaping the development of our final product. Building & Product Development Start with a simple concept/design to validate with customers before building When we realised the problem and solution, we began by designing the product, but not by jumping straight into coding. Instead, we created wireframes and user interfaces using tools like InVision and Figma. This allowed us to visually represent the product without the need for backend or frontend development at first. The goal was to showcase how the product would look and feel, helping potential customers understand its value before we even started building. We showed these designs to potential customers and asked for feedback. Would they want to buy this product? Would they pay for it? We didn’t dive into actual development until we found a customer willing to pay a significant amount for the solution. This approach helped us ensure we were on the right track and didn’t waste time or resources building something customers didn’t actually want. Deliver your solution using a manual consulting approach before developing an automated product Initially, we solved problems for customers in a more "consulting" manner, delivering insights manually. Recall how I mentioned that when one of our early customer interviewees asked us to deliver the solution, we initially did it manually by using machine learning models to analyse the data and presenting the results to them in a slide deck. This works for the initial stages of validating your solution, as you don't want to invest too much time into building a full-blown MVP before understanding the exact features and functionalities that your users want. However, after confirming that customers were willing to pay for what we provided, we moved forward with actual product development. This shift from a manual service to product development was key to scaling in a sustainable manner, as our building was guided by real-world feedback and insights rather than intuition. Let ongoing customer feedback drive iteration and the product roadmap Once we built the first version of the product, it was basic, solving only one problem. But as we worked closely with customers, they requested additional features and functionalities to make it more useful. As a result, we continued to evolve the product to handle more complex use cases, gradually developing new modules based on customer feedback. Product development is a continuous process. Our early customers pushed us to expand features and modules, from solving just 20% of their problems to tackling 50–60% of their needs. These demands shaped our product roadmap and guided the development of new features, ultimately resulting in a more complete solution. Revenue and user numbers are key metrics for assessing product-market fit. However, critical mass varies across industries Product-market fit (PMF) can often be gauged by looking at the size of your revenue and the number of customers you're serving. Once you've reached a certain critical mass of customers, you can usually tell that you're starting to hit product-market fit. However, this critical mass varies by industry and the type of customers you're targeting. For example, if you're building an app for a broad consumer market, you may need thousands of users. But for enterprise software, product-market fit may be reached with just a few dozen key customers. Compare customer engagement and retention with other available solutions on the market for product-market fit Revenue and the number of customers alone isn't always enough to determine if you're reaching product-market fit. The type of customer and the use case for your product also matter. The level of engagement with your product—how much time users are spending on the platform—is also an important metric to track. The more time they spend, the more likely it is that your product is meeting a crucial need. Another way to evaluate product-market fit is by assessing retention, i.e whether users are returning to your platform and relying on it consistently, as compared to other solutions available. That's another key indication that your solution is gaining traction in the market. Business Model & Monetisation Prioritise scalability Initially, we started with a consulting-type model where we tailor-made specific solutions for each customer use-case we encountered and delivered the CPG insights manually, but we soon realized that this wasn't scalable. The problem with consulting is that you need to do the same work repeatedly for every new project, which requires a large team to handle the workload. That is not how you sustain a high-growth startup. To solve this, we focused on building a product that would address the most common problems faced by our customers. Once built, this product could be sold to thousands of customers without significant overheads, making the business scalable. With this in mind, we decided on a SaaS (Software as a Service) business model. The benefit of SaaS is that once you create the software, you can sell it to many customers without adding extra overhead. This results in a business with higher margins, where the same product can serve many customers simultaneously, making it much more efficient than the consulting model. Adopt a predictable, simplistic business model for efficiency. Look to industry practices for guidance When it came to monetisation, we considered the needs of our CPG customers, who I knew from experience were already accustomed to paying annual subscriptions for sales databases and other software services. We decided to adopt the same model and charge our customers an annual upfront fee. This model worked well for our target market, aligning with industry standards and ensuring stable, recurring revenue. Moreover, our target CPG customers were already used to this business model and didn't have to choose from a huge variety of payment options, making closing sales a straightforward and efficient process. Marketing & Sales Educate the market to position yourself as a thought leader When we started, AI was not widely understood, especially in the CPG industry. We had to create awareness around both AI and its potential value. Our strategy focused on educating potential users and customers about AI, its relevance, and why they should invest in it. This education was crucial to the success of our marketing efforts. To establish credibility, we adopted a thought leadership approach. We wrote blogs on the importance of AI and how it could solve problems for CPG companies. We also participated in events and conferences to demonstrate our expertise in applying AI to the industry. This helped us build our brand and reputation as leaders in the AI space for CPG, and word-of-mouth spread as customers recognized us as the go-to company for AI solutions. It’s tempting for startups to offer products for free in the hopes of gaining early traction with customers, but this approach doesn't work in the long run. Free offerings don’t establish the value of your product, and customers may not take them seriously. You should always charge for pilots, even if the fee is minimal, to ensure that the customer is serious about potentially working with you, and that they are committed and engaged with the product. Pilots/POCs/Demos should aim to give a "flavour" of what you can deliver A paid pilot/POC trial also gives you the opportunity to provide a “flavour” of what your product can deliver, helping to build confidence and trust with the client. It allows customers to experience a detailed preview of what your product can do, which builds anticipation and desire for the full functionality. During this phase, ensure your product is built to give them a taste of the value you can provide, which sets the stage for a broader, more impactful adoption down the line. Fundraising & Financial Management Leverage PR to generate inbound interest from VCs When it comes to fundraising, our approach was fairly traditional—we reached out to VCs and used connections from existing investors to make introductions. However, looking back, one thing that really helped us build momentum during our fundraising process was getting featured in Tech in Asia. This wasn’t planned; it just so happened that Tech in Asia was doing a series on AI startups in Southeast Asia and they reached out to us for an article. During the interview, they asked if we were fundraising, and we mentioned that we were. As a result, several VCs we hadn’t yet contacted reached out to us. This inbound interest was incredibly valuable, and we found it far more effective than our outbound efforts. So, if you can, try to generate some PR attention—it can help create inbound interest from VCs, and that interest is typically much stronger and more promising than any outbound strategies because they've gone out of their way to reach out to you. Be well-prepared and deliberate about fundraising. Keep trying and don't lose heart When pitching to VCs, it’s crucial to be thoroughly prepared, as you typically only get one shot at making an impression. If you mess up, it’s unlikely they’ll give you a second chance. You need to have key metrics at your fingertips, especially if you're running a SaaS company. Be ready to answer questions like: What’s your retention rate? What are your projections for the year? How much will you close? What’s your average contract value? These numbers should be at the top of your mind. Additionally, fundraising should be treated as a structured process, not something you do on the side while juggling other tasks. When you start, create a clear plan: identify 20 VCs to reach out to each week. By planning ahead, you’ll maintain momentum and speed up the process. Fundraising can be exhausting and disheartening, especially when you face multiple rejections. Remember, you just need one investor to say yes to make it all worthwhile. When using funds, prioritise profitability and grow only when necessary. Don't rely on funding to survive. In the past, the common advice for startups was to raise money, burn through it quickly, and use it to boost revenue numbers, even if that meant operating at a loss. The idea was that profitability wasn’t the main focus, and the goal was to show rapid growth for the next funding round. However, times have changed, especially with the shift from “funding summer” to “funding winter.” My advice now is to aim for profitability as soon as possible and grow only when it's truly needed. For example, it’s tempting to hire a large team when you have substantial funds in the bank, but ask yourself: Do you really need 10 new hires, or could you get by with just four? Growing too quickly can lead to unnecessary expenses, so focus on reaching profitability as soon as possible, rather than just inflating your team or burn rate. The key takeaway is to spend your funds wisely and only when absolutely necessary to reach profitability. You want to avoid becoming dependent on future VC investments to keep your company afloat. Instead, prioritize reaching break-even as quickly as you can, so you're not reliant on external funding to survive in the long run. Team-Building & Leadership Look for complementary skill sets in co-founders When choosing a co-founder, it’s important to find someone with a complementary skill set, not just someone you’re close to. For example, I come from a business and commercial background, so I needed someone with technical expertise. That’s when I found my co-founder, Himanshu, who had experience in machine learning and AI. He was a great match because his technical knowledge complemented my business skills, and together we formed a strong team. It might seem natural to choose your best friend as your co-founder, but this can often lead to conflict. Chances are, you and your best friend share similar interests, skills, and backgrounds, which doesn’t bring diversity to the table. If both of you come from the same industry or have the same strengths, you may end up butting heads on how things should be done. Having diverse skill sets helps avoid this and fosters a more collaborative working relationship. Himanshu (left) and Somsubhra (right) co-founded AI Palette in 2018 Define roles clearly to prevent co-founder conflict To avoid conflict, it’s essential that your roles as co-founders are clearly defined from the beginning. If your co-founder and you have distinct responsibilities, there is no room for overlap or disagreement. This ensures that both of you can work without stepping on each other's toes, and there’s mutual respect for each other’s expertise. This is another reason as to why it helps to have a co-founder with a complementary skillset to yours. Not only is having similar industry backgrounds and skillsets not particularly useful when building out your startup, it's also more likely to lead to conflicts since you both have similar subject expertise. On the other hand, if your co-founder is an expert in something that you're not, you're less likely to argue with them about their decisions regarding that aspect of the business and vice versa when it comes to your decisions. Look for employees who are driven by your mission, not salary For early-stage startups, the first hires are crucial. These employees need to be highly motivated and excited about the mission. Since the salary will likely be low and the work demanding, they must be driven by something beyond just the paycheck. The right employees are the swash-buckling pirates and romantics, i.e those who are genuinely passionate about the startup’s vision and want to be part of something impactful beyond material gains. When employees are motivated by the mission, they are more likely to stick around and help take the startup to greater heights. A litmus test for hiring: Would you be excited to work with them on a Sunday? One of the most important rounds in the hiring process is the culture fit round. This is where you assess whether a candidate shares the same values as you and your team. A key question to ask yourself is: "Would I be excited to work with this person on a Sunday?" If there’s any doubt about your answer, it’s likely not a good fit. The idea is that you want employees who align with the company's culture and values and who you would enjoy collaborating with even outside of regular work hours. How we structure the team at AI Palette We have three broad functions in our organization. The first two are the big ones: Technical Team – This is the core of our product and technology. This team is responsible for product development and incorporating customer feedback into improving the technology Commercial Team – This includes sales, marketing, customer service, account managers, and so on, handling everything related to business growth and customer relations. General and Administrative Team – This smaller team supports functions like finance, HR, and administration. As with almost all businesses, we have teams that address the two core tasks of building (technical team) and selling (commercial team), but given the size we're at now, having the administrative team helps smoothen operations. Set broad goals but let your teams decide on execution What I've done is recruit highly skilled people who don't need me to micromanage them on a day-to-day basis. They're experts in their roles, and as Steve Jobs said, when you hire the right person, you don't have to tell them what to do—they understand the purpose and tell you what to do. So, my job as the CEO is to set the broader goals for them, review the plans they have to achieve those goals, and periodically check in on progress. For example, if our broad goal is to meet a certain revenue target, I break it down across teams: For the sales team, I’ll look at how they plan to hit that target—how many customers they need to sell to, how many salespeople they need, and what tactics and strategies they plan to use. For the technical team, I’ll evaluate our product offerings—whether they think we need to build new products to attract more customers, and whether they think it's scalable for the number of customers we plan to serve. This way, the entire organization's tasks are cascaded in alignment with our overarching goals, with me setting the direction and leaving the details of execution to the skilled team members that I hire.

7 free ways to find customers
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doublescoop24This week

7 free ways to find customers

You do not need to burn thousands on paid ads to find customers. Most businesses think ads are the only way to get customers. They spend huge amounts on Google and Facebook ads with low conversion rates and end up desperate when the money runs out. Here are some FREE strategies that work way better: Be where your customers already hang out Monitor platforms like Reddit, LinkedIn, Facebook groups and other online communities where your target audience discusses their problems. Look for people actively seeking solutions you provide. The conversion rate is much higher because these are people already looking for what you sell. Create content that solves real problems Create blog posts, videos, or social content that addresses specific pain points your audience has. I started writing detailed guides about problems I knew my customers faced and they began finding me organically through search. Strategic partnerships with complementary businesses I connected with businesses that served the same customers but offered different products. We created joint social posts and shared each other's content at zero cost. This opened up their audience to me and vice versa. Get interviewed on podcasts This one surprised me. Many niche industry podcasts need guests constantly. I reached out offering specific topics I could speak on with value for their audience. This positioned me as an expert while reaching new potential customers. Build in public Sharing your journey building your product creates a following of interested people. I posted weekly updates on X about challenges and wins, which created a small but engaged community before we even launched. Leverage personal networks properly Not by spamming friends, but by asking for specific introductions to people who might genuinely benefit from what you offer. One quality introduction beats 100 cold emails. Create free tools or resources This is one of the most effective strategies. You can easily build these free tools using AI now. I built a simple calculator that helped people in my industry solve a common problem. It generated leads because users found it valuable and shared it. The most important thing I learned is that these methods actually produce higher quality customers. They come to you already understanding the value you provide, which means better conversion rates and longer customer relationships. It takes more patience than ads, but the ROI is significantly better in the long run. Plus, these strategies help you understand your customers better, which improves everything else in your business.

[CASE STUDY] From 217/m to $2,836/m in 9 months - Sold for $59,000; I grow and monetise web traffic of 5, 6, 7 figures USD valued passive income content sites [AMA]
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jamesackerman1234This week

[CASE STUDY] From 217/m to $2,836/m in 9 months - Sold for $59,000; I grow and monetise web traffic of 5, 6, 7 figures USD valued passive income content sites [AMA]

Hello Everyone (VERY LONG CASE STUDY AHEAD) - 355% return in 9 months Note: I own a 7-figures USD valued portfolio of 41+ content sites that generates 5-6 figures USD a month in passive income. This is my first time posting in this sub and my goal is to NOT share generic advice but precise numbers, data and highly refined processes so you can also get started with this business yourself or if you already have an existing business, drive huge traffic to it and scale it substantially (get more customers). I will use a case study to explain the whole process. As most of us are entrepreneurs here, explaining an actual project would be more meaningful. In this case study I used AI assisted content to grow an existing site from $217/m to $2,836/m in 9 months (NO BACKLINKS) and sold it for $59,000. ROI of 3 months: 355% Previous case studies (before I give an overview of the model) Amazon Affiliate Content Site: $371/m to $19,263/m in 14 MONTHS - $900K CASE STUDY \[AMA\] Affiliate Website from $267/m to $21,853/m in 19 months (CASE STUDY - Amazon?) \[AMA\] Amazon Affiliate Website from $0 to $7,786/month in 11 months Amazon Affiliate Site from $118/m to $3,103/m in 8 MONTHS (SOLD it for $62,000+) Note: You can check pinned posts on my profile. Do go through the comments as well as a lot of questions are answered in those. However, if you still have any questions, feel free to reach out. This is an \[AMA\]. Quick Overview of the Model Approach: High traffic, niche specific, informative content websites that monetise its traffic through highly automated methods like display ads and affiliate. The same model can be applied to existing businesses to drive traffic and get customers. Main idea: Make passive income in a highly automated way Easy to understand analogy You have real estate (here you have digital asset like a website) You get rental income (here you get ads and affiliate income with no physical hassle, in case you have a business like service, product etc. then you can get customers for that too but if not, it's alright) Real estate has value (this digital asset also has value that can be appreciated with less effort) Real estate can be sold (this can be sold too but faster) IMPORTANT NOTE: Search traffic is the BEST way to reach HUGE target audience and it's important when it comes to scaling. This essentially means that you can either monetise that via affiliate, display etc. or if you have a business then you can reach a bigger audience to scale. Overview of this website's valuation (then and now: Oct. 2022 and June 2023) Oct 2022: $217/m Valuation: $5,750.5 (26.5x) - set it the same as the multiple it was sold for June 2023: $2,836/m Traffic and revenue trend: growing fast Last 3 months avg: $2,223 Valuation now: $59,000 (26.5x) Description: The domain was registered in 2016, it grew and then the project was left unattended. I decided to grow it again using properly planned AI assisted content. Backlink profile: 500+ Referring domains (Ahrefs). Backlinks mean the sites linking back to you. This is important when it comes to ranking. Summary of Results of This Website - Before and After Note: If the terms seem technical, do not worry. I will explain them in detail later. Still if you have any questions. Feel free to comment or reach out. |Metric|Oct 2022|June 2023|Difference|Comments| |:-|:-|:-|:-|:-| |Articles|314|804|\+490|AI Assisted content published in 3 months| |Traffic|9,394|31,972|\+22,578|Organic| |Revenue|$217|$2,836|\+$2,619|Multiple sources| |RPM (revenue/1000 web traffic)|23.09|$88.7|\+$65.61|Result of Conversion rate optimisation (CRO). You make changes to the site for better conversions| |EEAT (expertise, experience, authority and trust of website)|2 main authors|8 authors|6|Tables, video ads and 11 other fixations| |CRO|Nothing|Tables, video ads |Tables, video ads and 11 other fixations || &#x200B; Month by Month Growth |Month|Revenue|Steps| |:-|:-|:-| |Sept 2022|NA|Content Plan| |Oct 2022|$217|Content Production| |Nov 2022|$243|Content production + EEAT authors| |Dec 2022|$320|Content production + EEAT authors| |Jan 2023|$400|Monitoring| |Feb 2023|$223|Content production + EEAT authors| |Mar 2023|$2,128|CRO & Fixations| |April 2023|$1,609|CRO & Fixations| |May 2023|$2,223|Content production + EEAT authors| |June 2023|$2,836|CRO and Fixations| |Total|$10,199|| &#x200B; What will I share Content plan and Website structure Content Writing Content Uploading, formatting and onsite SEO Faster indexing Conversion rate optimisation Guest Posting EEAT (Experience, Expertise, Authority, Trust) Costing ROI The plans moving forward with these sites &#x200B; Website Structure and Content Plan This is probably the most important important part of the whole process. The team spends around a month just to get this right. It's like defining the direction of the project. Description: Complete blueprint of the site's structure in terms of organisation of categories, subcategories and sorting of articles in each one of them. It also includes the essential pages. The sorted articles target main keyword, relevant entities and similar keywords. This has to be highly data driven and we look at over 100 variables just to get it right. It's like beating Google's algorithm to ensure you have a blueprint for a site that will rank. It needs to be done right. If there is a mistake, then even if you do everything right - it's not going to work out and after 8-16 months you will realise that everything went to waste. Process For this project, we had a niche selected already so we didn't need to do a lot of research pertaining to that. We also knew the topic since the website was already getting good traffic on that. We just validated from Ahrefs, SEMRUSH and manual analysis if it would be worth it to move forward with that topic. &#x200B; Find entities related to the topic: We used Ahrefs and InLinks to get an idea about the related entities (topics) to create a proper topical relevance. In order to be certain and have a better idea, we used ChatGPT to find relevant entities as well \> Ahrefs (tool): Enter main keyword in keywords explorer. Check the left pain for popular topics \> Inlinks (tool): Enter the main keyword, check the entity maps \> ChatGPT (tool): Ask it to list down the most important and relevant entities in order of their priority Based on this info, you can map out the most relevant topics that are semantically associated to your main topic Sorting the entities in topics (categories) and subtopics (subcategories): Based on the information above, cluster them properly. The most relevant ones must be grouped together. Each group must be sorted into its relevant category. \> Example: Site about cycling. \> Categories/entities: bicycles, gear and equipment, techniques, safety, routes etc. \> The subcategories/subentities for let's say "techniques" would be: Bike handling, pedaling, drafting etc. Extract keywords for each subcategory/subentity: You can do this using Ahrefs or Semrush. Each keyword would be an article. Ensure that you target the similar keywords in one article. For example: how to ride a bicycle and how can I ride a bicycle will be targeted by one article. Make the more important keyword in terms of volume and difficulty as the main keyword and the other one(s) as secondary Define main focus vs secondary focus: Out of all these categories/entities - there will be one that you would want to dominate in every way. So, focus on just that in the start. This will be your main focus. Try to answer ALL the questions pertaining to that. You can extract the questions using Ahrefs. \> Ahrefs > keywords explorer \> enter keyword \> Questions \> Download the list and cluster the similar ones. This will populate your main focus category/entity and will drive most of the traffic. Now, you need to write in other categories/subentities as well. This is not just important, but crucial to complete the topical map loop. In simple words, if you do this Google sees you as a comprehensive source on the topic - otherwise, it ignores you and you don't get ranked Define the URLs End result: List of all the entities and sub-entities about the main site topic in the form of categories and subcategories respectively. A complete list of ALL the questions about the main focus and at around 10 questions for each one of the subcategories/subentities that are the secondary focus Content Writing So, now that there's a plan. Content needs to be produced. Pick out a keyword (which is going to be a question) and... Answer the question Write about 5 relevant entities Answer 10 relevant questions Write a conclusion Keep the format the same for all the articles. Content Uploading, formatting and onsite SEO Ensure the following is taken care of: H1 Permalink H2s H3s Lists Tables Meta description Socials description Featured image 2 images in text \\Schema Relevant YouTube video (if there is) Note: There are other pointers link internal linking in a semantically relevant way but this should be good to start with. Faster Indexing Indexing means Google has read your page. Ranking only after this step has been done. Otherwise, you can't rank if Google hasn't read the page. Naturally, this is a slow process. But, we expedite it in multiple ways. You can use RankMath to quickly index the content. Since, there are a lot of bulk pages you need a reliable method. Now, this method isn't perfect. But, it's better than most. Use Google Indexing API and developers tools to get indexed. Rank Math plugin is used. I don't want to bore you and write the process here. But, a simple Google search can help you set everything up. Additionally, whenever you post something - there will be an option to INDEX NOW. Just press that and it would be indexed quite fast. Conversion rate optimisation Once you get traffic, try adding tables right after the introduction of an article. These tables would feature a relevant product on Amazon. This step alone increased our earnings significantly. Even though the content is informational and NOT review. This still worked like a charm. Try checking out the top pages every single day in Google analytics and add the table to each one of them. Moreover, we used EZOIC video ads as well. That increased the RPM significantly as well. Both of these steps are highly recommended. Overall, we implemented over 11 fixations but these two contribute the most towards increasing the RPM so I would suggest you stick to these two in the start. Guest Posting We made additional income by selling links on the site as well. However, we were VERY careful about who we offered a backlink to. We didn't entertain any objectionable links. Moreover, we didn't actively reach out to anyone. We had a professional email clearly stated on the website and a particularly designated page for "editorial guidelines" A lot of people reached out to us because of that. As a matter of fact, the guy who bought the website is in the link selling business and plans to use the site primarily for selling links. According to him, he can easily make $4000+ from that alone. Just by replying to the prospects who reached out to us. We didn't allow a lot of people to be published on the site due to strict quality control. However, the new owner is willing to be lenient and cash it out. EEAT (Experience, Expertise, Authority, Trust) This is an important ranking factor. You need to prove on the site that your site has authors that are experienced, have expertise, authority and trust. A lot of people were reaching out to publish on our site and among them were a few established authors as well. We let them publish on our site for free, added them on our official team, connected their socials and shared them on all our socials. In return, we wanted them to write 3 articles each for us and share everything on all the social profiles. You can refer to the tables I shared above to check out the months it was implemented. We added a total of 6 writers (credible authors). Their articles were featured on the homepage and so were their profiles. Costing Well, we already had the site and the backlinks on it. Referring domains (backlinks) were already 500+. We just needed to focus on smart content and content. Here is the summary of the costs involved. Articles: 490 Avg word count per article: 1500 Total words: 735,000 (approximately) Cost per word: 2 cents (includes research, entities, production, quality assurance, uploading, formatting, adding images, featured image, alt texts, onsite SEO, publishing/scheduling etc.) Total: $14,700 ROI (Return on investment) Earning: Oct 22 - June 23 Earnings: $10,199 Sold for: $59,000 Total: $69,199 Expenses: Content: $14,700 Misc (hosting and others): $500 Total: $15,200 ROI over a 9 months period: 355.25% The plans moving forward This website was a part of a research and development experiment we did. With AI, we wanted to test new waters and transition more towards automation. Ideally, we want to use ChatGPT or some other API to produce these articles and bulk publish on the site. The costs with this approach are going to be much lower and the ROI is much more impressive. It's not the the 7-figures projects I created earlier (as you may have checked the older case studies on my profile), but it's highly scalable. We plan to refine this model even further, test more and automate everything completely to bring down our costs significantly. Once we have a model, we are going to scale it to 100s of sites. The process of my existing 7-figures websites portfolio was quite similar. I tested out a few sites, refined the model and scaled it to over 41 sites. Now, the fundamentals are the same however, we are using AI in a smarter way to do the same but at a lower cost, with a smaller team and much better returns. The best thing in my opinion is to run numerous experiments now. Our experimentation was slowed down a lot in the past since we couldn't write using AI but now it's much faster. The costs are 3-6 times lower so when it used to take $50-100k to start, grow and sell a site. Now you can pump 3-6 more sites for the same budget. This is a good news for existing business owners as well who want to grow their brand. Anyway, I am excited to see the results of more sites. In the meantime, if you have any questions - feel free to let me know. Best of luck for everything. Feel free to ask questions. I'd be happy to help. This is an AMA.

[Ultimate List] A list of Marketing Tools That I’ve tested over the years and found helpful to do better marketing with less work. More than 50 Tools To Help you with Marketing, Copywriting & Sales!
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lazymentorsThis week

[Ultimate List] A list of Marketing Tools That I’ve tested over the years and found helpful to do better marketing with less work. More than 50 Tools To Help you with Marketing, Copywriting & Sales!

Starting to focus on marketing for your business, You will come across the same tools mentioned over and over by marketers. I would like to mention here tools that you might haven’t seen going viral in the community but actually will help you grow faster and efficiently. Starting off with My favourite Marketing Channel! #Email Marketing For SMBs Convertkit / Mailerlite / Mailchimp - These 3 Platforms are the best options for SMBs and entrepreneurs just starting out with email marketing. All 3 have free plans up to 1,000 subscribers. Scribe - Email Signature Tool, Create Great Email signatures for your emails. Liramail - Most Email marketing platforms don’t offer great email templates. This tool will help you build great email templates with drag and drop. Quick mail Auto-Warmer - Most Businesses at the beginning don’t know what to do when open rate drops. You need to use an email warmer like this to keep it up. #Email Marketing For Big Businesses SendGrid - Overall Email Marketing Tools, this tool is best for brands that have huge email lists and email marketing is the key marketing channel. Braze - This tool is leading in email marketing for large Email senders. When I was working for agencies, this was one of the best email marketing tools I had used. NeoCertified - Protect your emails for spammers and threats. To keep your email list healthy, this is a must have! Sparkloop - Referral Marketing For Email Campaigns. Email can generate great huge amount of referrals for you and Sparkloop makes it easier. #Cold Emails & Lead Generation Hunter - A Great Tool to scrape emails from domain names. The tool comes with a green free plan but Pro plan is worth the amount of features it provides. Icyleads - It’s better than Hunter as it’s heavily focused on the sales and prospecting to help you derive great results from your campaigns. Mailshake - Beginner Friend Cold Email Tool with Great features like email list warming. #Communication Tools Twilio - One do the best customer engagement platform used by Companies like Stripe and mine too. Chatlio - Use Live chat feature on your website with slack integration. My favourite easier to catch up on conversations through slack integration. Intercom - Used by Most Marketers, Industry Leading customer communication platform. Great for beginners! Chatwoot - Another Amazing Communication Tool but the best part is they have a great free plan useful for new businesses. Loom - Communicate with your audience through Videos. Loom is great for SaaS and to show human interaction to close new visitors effectively. #CRM Outseta - This tool provides great CRM and their billing system is better than other tools out their which makes it stands out! Hubspot - I don’t think this tool needs an introduction because Hubspot’s CRM is the best in industry. Salesflare - This CRM is a great alternative to hubspot as it’s beginner friendly and helpful for SMBs. #SEO Tools Ahrefs - One of the best SEO tool in the industry. They also just launched a bunch of free tools to help SEO beginners. Screaming frog - The only website crawler I have used since I bought my first domain. It’s the best! Ubersuggest- The Tool by Neil Patel is the best SEO tool for you. (I’m Joking, it’s the worst) Contentking - This tool is good at Real-time SEO Auditing, they do a lot of Marketing work through Newsletters. If you are subscribed to any SEO newsletter. You may have seen this tool. SEOquake & Semrush - SEOquake is a great tool to conduct on-page analysis, SERP, and much more. Great tool but it’s owned by Semrush. You should go for Semrush because that tool will cover all SEO aspects for you. #Content Marketing Buzzsumo - This tool is great for content research and but you may find the regular emails pretty annoying sometimes. Contentrow - Analyse Your Content and find it’s strength. Highly recommended who are weak at content structuring like me. Grammarly - If you are not a native English speaker like me, you might think you need it or not. You need it for sure for grammar corrections. #Graphic Design Tools Visme - At agencies, Infographics can be more effective than usual postscript. Visme is a graphic design tool focused on infographics and designs related to B2B and B2C. It’s great for agencies! Glorify - A Graphic Design Tool focused on E-commerce, filled with Designs useful for E-commerce store owners. Canva - All-in-one Industry leading Graphic Design Tool that everyone knows and every template is overused now. Adobe Creative Cloud ( previously Sparkpost) - It’s a great alternative to Canva filled with Amazing Stock images to use in your visuals but the only backlash is the exports in this tool are not high quality. Snaps - A Canva Alternative that might not have overused templates for your Social Accounts. #Advertising Tools Plai - It’s a great PPC tool to create Ads for Instagram and Tiktok. Wordstream - It’s an industry leading PPC Tool, great for Ad Grading and auditing. AdEspresso - This Is a tool by Hootsuite. They have a lot of Data sourced at the backend, which helps in Ad optimisation through this tool. That’s the reason I recommend this tool. #Video Editing Tools Veed Studio - I have been using Veed from last year. It’s one of the best Video Marketing Tool Optimized for Instagram & Tiktok. Synthesia - It’s a new AI video generation platform. From last few months, if you have seen marketing agencies including Videos in Emails. The chances are that’s not a Agency member taking but AI generated Human. Motionbox - It’s also a great video editing tool focused on video editing for Digital Marketers. Jitter Video - It’s a great motion design tool. Comes with great templates, the only place where other tools I mentioned lacks. It’s great and beginner friendly. #Copywriting Jasper AI - Google’s John Mueller says AI generated content is banned on Search but I think with Jasper AI you can generate SEO optimised Content but you have to put in some efforts like at least give 30 minutes for editing the Copy by yourself. Copy AI - Another AI tool to help you write better copy. This one is more focused on helping you write copy suitable for Ads and Social media campaigns. Hemingway App - To help you write more clearly and Bold. This tool is better than Grammarly if you look for writing perspective and it’s free. #Social Media Management App I’ve used a Lot of SMM Tools and that’s why going to mention all of them with a short review. Sprout social - The Best with deep insights coverage. Hootsuite - Great Scheduling tool just under sprout social. Later - Heavily Focused on Instagram from beginning and Now Tiktok too. SkedSocial - It’s like a Later alternative with great addition features like link-in-bio. Facebook’s Business Manager- Great but sometimes bugs can make a huge issue for you and customer support is like dead. Tweet Hunter & Hypefury- Both are Twitter Scheduling tools growing very fast on platform and are great for growth. Buffer - It’s a great tool but I haven’t seen any new updates to help with management. Zoho Social - It’s a great SMM tool and if you use other marketing solutions from Zoho. It’s a must have! #Market Research Tool • SparkToro - That’s the only one I have ever used. It’s great for audience research and comes with great customer service. Founded by Rand Fishkin, it’s one of the best research tool. #Influencer Marketing & UGC InfluenceGrid - A free search engine To find Tiktok & Instagram Influencers for your campaigns. Tiktok Creative Center- TikTok’s in-built tool called “Creative Center” is the best to find content trends, audience demographics and much more. Archive - Find Instagram Stories and Posts mentioning Your brands and use them as Ads for your business Marketing. #Landing Page Builders Leadpages - Its a great landing page builder because the integration and drag-and-drop features makes it easier to work with! Cardd co - A Great Landing page builder with easy step up but it lacks the copywriting and tracking features. Instapage - It’s one of the best out and I think the overall product is effective enough to help you stand out with your landing page. Unbounce - It’s a great alternative to Instapage due its well polished landing page templates that might be helpful for you. #Community Building Mighty Networks - A Great Community building platform, and you can also sell courses within the platform. Circle so - A great alternative to Mighty networks focused on Communities specifically. We are currently using for small community Of ours. #Sales Tools Drift - You can get much more out of Drift than just sales tools but The Sales solutions provided in Drift are one of the best. Salesforce - It’s the industry Sales solution provider. A go-to and have various pricing plans making it suitable for majority of SMBs. #Social Proof Tools People don’t have enough time to search across internet to decide to trust you after seeing your Ad first time. That’s what you might be facing too. Here are two tools I absolutely love for social proof! Use Proof - Show Recent Activities occurring on your website and build the trust of your visitors. Testimonial to - Gather Testimonials across Social Media platforms related to your business with this tool. Capture tweets and comments mentioning your brands and mention them. #Analytics Tools Plausible Analytics- A privacy friendly Analytics alternative to Google Analytics if you hate Analytics 4 like me. Mixpanel - Product Analytics and funnel reports better than Google Analytics. #Reddit Marketing Gummysearch- This tool will help To find your target audience on Reddit and interact with them with its help and close your new customers. Howitzer- It’s another pretty similar tool to Gummysearch focused on Reddit cold outreach to get clients and new customers. Both are great but Gummysearch provides better customer support while Howtizer is helpful on a large scale Reddit Marketing. #Text Marketing Klaviyo - It’s an email + SMS marketing tool, it’s taking up space in marketing industry very quickly as an industry leader due to its great integrations but you need to learn the platform usage to maximise the outcome. Cartloop - This tool provides great text marketing solutions with integration with Spotify and other e-commerce marketing tools. Attentive Mobile - This is my favourite Text marketing tool due to the interactive dashboard + they have a library of Text marketing examples to help you out with your campaigns. #Other Tools I have used throughout my journey! Triple Whale - It’s a great E-commerce marketing tools with Triple pixel to help you track your campaigns more efficiently. Fastory - To create well optimized Instagram & Tiktok Stories for your business. Jotform - Online Form Builder with integrations with leading marketing tools. Gated - As an entrepreneur and marketer, you may receive a bunch of unwanted emails. Use Gated to get rid of them and receive useful mails only! ClickUp- The main Tool for Project Management, one of the best and highly recommended. Riverside - Forget Zoom or Google Meet, For your Podcast Interviews and Marketing conferences. You need riverside with great video quality and recording features. Manychat- Automate your Instagram DMs and interact with your followers more efficiently + sell out your products/ services when you are offline. Calendy - To schedule meetings with your ideal clients. ServiceProviderPro - It’s a client portal for SEO & Growing Agencies, very helpful in scaling agencies. SendCheckit - Compare your Email Subject Lines with 100,000+ others in the database for free. Otter AI - Using AI track your meetings more effectively, you can easily edit, annotate and share notes from the meetings. Ryte - Optimise your website User experience with this tool focused on UX aspects + SEO too. PhantomBuster - Scrape LinkedIn Profile and Data from Facebook/LinkedIn groups. I clearly love this tool! #Honourable Mentions Zapier - The Only tool you need to integrate your favourite tool with a new effective tool. Elementor - That’s what I use for web design and it’s great! Marketer Hire - To hire world class marketers to work with you. InShot & Capcut - I create Instagram Reels and TikTok’s and life without these tools isn’t possible. Nira - It’s a great tool to Manage your workspace and this tool has launched many marketing templates in-built helpful for marketers and also entrepreneurs. X - The tool you love that wasn’t mentioned here is valuable and I honour that tool and share that if you would like to! I mean thanks for reading what I have curated all over my life as a marketer. I share 5 Marketing Tools, 5 Marketing Resources and 1 Free Resourceevery week in my newsletter, you can subscribe here to receive that for free. Also, You can read an expanded list of email marketing tools in this Reddit post!

Is there any point in building a product with AI anymore?
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jottrledThis week

Is there any point in building a product with AI anymore?

Everyone and their grandmother are building AI products. So it begs the question. Is the AI market now too saturated? Have all the AI apps been thought of? Of course not don't be silly, There is still a significant opportunity to create AI products and become profitable. But let's play devils advocate here. Let's say you're a developer and you want to build your first SaaS product. Now, imagine a world where all AI products were already thought of (a scary thought). What would you do? Would you move onto something else? See, when people think of an idea for a SaaS product what often happens is they do a quick Google search and tend to think "oh crap, it already exists, better move on". Maybe that's the right thing to do...but then again maybe it's not. Before you run for the hills, make sure to check the SEO potential for your idea. If your idea has the potential to rank high on Google and there are already hundreds/thousands of people looking for it then you can take that as all the validation you need to start building it. Here are 3 AI ideas that all have good SEO potential. Each idea has keywords that you can target with a difficulty level 500. This means it's easy to rank high in Google for them and they have a high number of people searching for them each month. AI Accounting Software A Saas product that uses AI to analyze bank transactions, invoices, and receipts to automatically match them and reconcile accounts in real-time, reducing manual work and errors. It would also offer predictive insights, suggesting optimal payment times or highlighting potential cash flow issues based on historical data. Could potentially be integrated with popular accounting software like QuickBooks or Xero. SEO Potential Keyword: ai accounting Keyword Difficulty: 9 Average Search Volume 2900 AI Human Resources Software AI Human Resources Software An AI-driven candidate screening and onboarding platform for small to medium-sized businesses. The tool would use AI to automatically filter job applications based on predefined criteria, rank candidates, and even conduct initial interview assessments using natural language processing. It could also manage onboarding tasks by automating the distribution of paperwork, training schedules, and team introductions. SEO Potential Keyword: ai human resources Keyword Difficulty: 17 Average Search Volume 2900 AI Nutrition Tool A Micro SaaS which creates personalized meal planning and nutrition analysis. The platform would use AI to create tailored meal plans based on users' dietary goals, preferences, allergies, and health data (such as activity level or medical conditions). It could analyze food labels, suggest healthier alternatives, and track nutrient intake in real time, helping users maintain balanced diets. SEO Potential Keyword: ai nutrition Keyword Difficulty: 3 Average Search Volume 720 I created a tool (check the first comment) to find ideas like this.

12 months ago, I was unemployed. Last week my side hustle got acquired by a $500m fintech company
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wutangsamThis week

12 months ago, I was unemployed. Last week my side hustle got acquired by a $500m fintech company

I’ve learned so much over the years from this subreddit. I thought I’d return the favour and share some of my own learnings. In November 2020 my best friend and I had an idea. “What if we could find out which stocks the Internet is talking about?” This formed the origins of Ticker Nerd. 9 months later we sold Ticker Nerd to Finder (an Australian fintech company valued at around $500m). In this post, I am going to lay out how we got there. How we came up with the idea First off, like other posts have covered - you don’t NEED a revolutionary or original idea to build a business. There are tonnes of “boring” businesses making over 7 figures a year e.g. law firms, marketing agencies, real estate companies etc. If you’re looking for an exact formula to come up with a great business idea I’m sorry, but it doesn’t exist. Finding new business opportunities is more of an art than a science. Although, there are ways you can make it easier to find inspiration. Below are the same resources I use for inspiration. I rarely ever come up with ideas without first searching one of the resources below for inspiration: Starter Story Twitter Startup Ideas My First Million Trends by the Hustle Trends VC To show how you how messy, random and unpredictable it can be to find an idea - let me explain how my co-founder and I came up with the idea for Ticker Nerd: We discovered a new product on Twitter called Exploding Topics. It was a newsletter that uses a bunch of software and algorithms to find trends that are growing quickly before they hit the mainstream. I had recently listened to a podcast episode from My First Million where they spoke about Motley Fool making hundreds of millions from their investment newsletters. We asked ourselves what if we could build a SaaS platform similar to Exploding Topics but it focused on stocks? We built a quick landing page using Carrd + Gumroad that explained what our new idea will do and included a payment option to get early access for $49. We called it Exploding Stock (lol). We shared it around a bunch of Facebook groups and subreddits. We made $1,000 in pre-sales within a couple days. My co-founder and I can’t code so we had to find a developer to build our idea. We interviewed a bunch of potential candidates. Meanwhile, I was trawling through Wall Street Bets and found a bunch of free tools that did roughly what we wanted to build. Instead of building another SaaS tool that did the same thing as these free tools we decided to pivot from our original idea. Our new idea = a paid newsletter that sends a weekly report that summarises 2 of the best stocks that are growing in interest on the Internet. We emailed everyone who pre-ordered access, telling them about the change and offered a full refund if they wanted. tl;dr: We essentially combined two existing businesses (Exploding Topics and Motley Fool) and made it way better. We validated the idea by finding out if people will actually pay money for it BEFORE we decided to build it. The idea we started out with changed over time. How to work out if your idea will actually make money It’s easy to get hung up on designing the logo or choosing the perfect domain name for your new idea. At this stage none of that matters. The most important thing is working out if people will pay money for it. This is where validation comes in. We usually validate ideas using Carrd. It lets you build a simple one page site without having to code. The Ticker Nerd site was actually built using a Carrd template. Here’s how you can do it yourself (at a high level): Create a Carrd pro account (yes it's a $49 one off payment but you’ll get way more value out of it). Buy a cheap template and send it to your Carrd account. You can build your own template but this will save you a lot of time. Once the template reaches your Carrd account, duplicate it. Leave the original so it can be duplicated for other ideas. Jump onto Canva (free) and create a logo using the free logos provided. Import your logo. Add copy to the page that explains your idea. Use the AIDA formula. Sign up to Gumroad (free) and create a pre-sale campaign. Create a discounted lifetime subscription or version of the product. This will be used pre-sales. Add the copy from the site into the pre-sale campaign on Gumroad. Add a ‘widget’ to Carrd and connect it to Gumroad using the existing easy integration feature. Purchase a domain name. Connect it to Carrd. Test the site works. Share your website Now the site is ready you can start promoting it in various places to see how the market reacts. An easy method is to find relevant subreddits using Anvaka (Github tool) or Subreddit Stats. The Anvaka tool provides a spider map of all the connected subreddits that users are active in. The highlighted ones are most relevant. You can post a thread in these subreddits that offer value or can generate discussion. For example: ‘I’m creating a tool that can write all your copy, would anyone actually use this?’ ‘What does everything think of using AI to get our copy written faster?’ ‘It’s time to scratch my own itch, I’m creating a tool that writes marketing copy using GPT-3. What are the biggest problems you face writing marketing copy? I’ll build a solution for it’ Reddit is pretty brutal these days so make sure the post is genuine and only drop your link in the comments or in the post if it seems natural. If people are interested they’ll ask for the link. Another great place to post is r/entrepreuerridealong and r/business_ideas. These subreddits expect people to share their ideas and you’ll likely make some sales straight off the bat. I also suggest posting in some Facebook groups (related to your idea) as well just for good measure. Assess the results If people are paying you for early access you can assume that it’s worth building your idea. The beauty of posting your idea on Reddit or in Facebook groups is you’ll quickly learn why people love/hate your idea. This can help you decide how to tweak the idea or if you should drop it and move on to the next one. How we got our first 100 customers (for free) By validating Ticker Nerd using subreddits and Facebook groups this gave us our first paying customers. But we knew this wouldn’t be sustainable. We sat down and brainstormed every organic strategy we could use to get traction as quickly as possible. The winner: a Product Hunt launch. A successful Product Hunt launch isn’t easy. You need: Someone that has a solid reputation and audience to “hunt” your product (essentially an endorsement). An aged Product Hunt account - you can’t post any products if your account is less than a week old. To be following relevant Product Hunt members - since they get notified when you launch a new product if they’re following you. Relationships with other builders and makers on Product Hunt that also have a solid reputation and following. Although, if you can pull it off you can get your idea in front of tens of thousands of people actively looking for new products. Over the next few weeks, I worked with my co-founder on connecting with different founders, indie hackers and entrepreneurs mainly via Twitter. We explained to them our plans for the Product Hunt launch and managed to get a small army of people ready to upvote our product on launch day. We were both nervous on the day of the launch. We told ourselves to have zero expectations. The worst that could happen was no one signed up and we were in the same position as we’re in now. Luckily, within a couple of hours Ticker Nerd was on the homepage of Product Hunt and in the top 10. The results were instant. After 24 hours we had around 200 people enter their payment details to sign up for our free trial. These signups were equal to around $5,800 in monthly recurring revenue. \-- I hope this post was useful! Drop any questions you have below and I’ll do my best to respond :)

Started a content marketing agency 6 years ago - $0 to $5,974,324 (2023 update)
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mr_t_forhireThis week

Started a content marketing agency 6 years ago - $0 to $5,974,324 (2023 update)

Hey friends, My name is Tyler and for the past 6 years, I’ve been documenting my experience building a content marketing agency called Optimist. Year 1 - 0 to $500k ARR Year 2 - $500k to $1MM ARR Year 3 - $1MM ARR to $1.5MM(ish) ARR Year 4 - $3,333,686 Revenue Year 5 - $4,539,659 Revenue How Optimist Works First, an overview/recap of the Optimist business model: We operate as a “collective” of full time/professional freelancers Everyone aside from me is a contractor Entirely remote/distributed team Each freelancer earns $65-85/hour Clients pay us a flat monthly fee for full-service content marketing (research, strategy, writing, editing, design/photography, reporting and analytics, targeted linkbuilding, and more) We recently introduced hourly engagements for clients who fit our model but have some existing in-house support Packages range in price from $10-20k/mo We offer profit share to everyone on our core team as a way to give everyone ownership in the company In 2022, we posted $1,434,665 in revenue. It was our highest revenue year to date and brings our lifetime total to $5,974,324. Here’s our monthly revenue from January 2017 to December of 2022. But, like every year, it was a mix of ups and downs. Here’s my dispatch for 2023. — Running a business is like spilling a drink. It starts as a small and simple thing. But, if you don’t clean it up, the spill will spread and grow — taking up more space, seeping into every crack. There’s always something you could be doing. Marketing you could be working on. Pitches you could be making. Networking you could be doing. Client work you could help with. It can be all-consuming. And it will be — if you don’t clean up the spill. I realized this year that I had no containment for the spill that I created. Running an agency was spilling over into nearly every moment of my life. When I wasn’t working, I was thinking about work. When I wasn’t thinking about work, I was dreaming about it. Over the years, I’ve shared about a lot of my personal feelings and experience as an entrepreneur. And I also discussed my reckoning with the limitations of running the business we’ve built. My acceptance that it was an airplane but not a rocket. And my plan to try to compartmentalize the agency to make room in my life for other things — new business ideas, new revenue streams, and maybe some non-income-producing activity. 🤷 What I found in 2022 was that the business wasn’t quite ready for me to make that move. It was still sucking up too much of my time and attention. There were still too many gaps to fill and I was the one who was often filling them. So what do you do? Ultimately you have two choices on the table anytime you run a business and it’s not going the way you want it: Walk away Turn the ship — slowly For a huge number of reasons (personal, professional, financial, etc), walking away from Optimist was not really even an option or the right move for me. But it did feel like things needed to change. I needed to keep turning the ship to get it to the place where it fit into my life — instead of my life fitting around the business. This means 2022 was a year of transition for the agency. (Again?) Refocusing on Profit Some money is better than no money. Right? Oddly, this was one of the questions I found myself asking in 2022. Over the years, we’ve been fortunate to have many clients who have stuck with us a long time. In some cases, we’ve had clients work with us for 2, 3, or even 4 years. (That’s over half of our existence!) But, things have gotten more expensive — we’ve all felt it. We’ve had to increase pay to remain competitive for top talent. Software costs have gone up. It’s eaten into our margin. Because of our increasing costs and evolving scope, many of our best, most loyal clients were our least profitable. In fact, many were barely profitable — if at all. We’ve tried to combat that by increasing rates on new, incoming clients to reflect our new costs and try to make up for shrinking margin on long-term clients. But we didn’t have a good strategy in place for updating pricing for current clients. And it bit us in the ass. Subsidizing lower-profit, long-term clients with new, higher-margin clients ultimately didn’t work out. Our margins continued to dwindle and some months we were barely breaking even while posting six-figures of monthly revenue. 2022 was our highest revenue year but one of our least profitable. It only left one option. We had to raise rates on some of our long-term clients. But, of course, raising rates on a great, long-term client can be delicate. You’ve built a relationship with these people over the years and you’re setting yourself up for an ultimatum — are you more valuable to the client or is the client more valuable to you? Who will blink first? We offered all of these clients the opportunity to move to updated pricing. Unfortunately, some of them weren’t on board. Again, we had 2 options: Keep them at a low/no profit rate Let them churn It seems intuitive that having a low-profit client is better than having no client. But we’ve learned an important lesson many times over the years. Our business doesn’t scale infinitely and we can only handle so many clients at a time. That means that low-profit clients are actually costing us money in some cases. Say our average client generates $2,500 per month in profit — $30,000 per year. If one of our clients is only generating $500/mo in profit, working with them means missing out on bringing on a more profitable client (assuming our team is currently at capacity). Instead of $30,000/year, we’re only making $6,000. Keeping that client costs us $24,000. That’s called opportunity cost. So it’s clear: We had to let these clients churn. We decided to churn about 25% of our existing clients. On paper, the math made sense. And we had a pretty consistent flow of new opportunities coming our way. At the time, it felt like a no-brainer decision. And I felt confident that we could quickly replace these low-profit clients with higher-margin ones. I was wrong. Eating Shit Right after we initiated proactively churning some of our clients, other clients — ones we planned to keep — gave us notice that they were planning to end the engagement. Ouch. Fuck. We went from a 25% planned drop in revenue to a nearly 40% cliff staring us right in the face. Then things got even worse. Around Q3 of this year, talk of recession and layoffs really started to intensify. We work primarily with tech companies and startups. And these were the areas most heavily impacted by the economic news. Venture funding was drying up. Our leads started to slow down. This put us in a tough position. Looking back now, I think it’s clear that I made the wrong decision. We went about this process in the wrong way. The reality sinks in when you consider the imbalance between losing a client and gaining a client. It takes 30 days for someone to fire us. It’s a light switch. But it could take 1-3 months to qualify, close, and onboard a new client. We have lots of upfront work, research, and planning that goes into the process. We have to learn a new brand voice, tone, and style. It’s a marathon. So, for every client we “trade”, there’s a lapse in revenue and work. This means that, in retrospect, I would probably have made this transition using some kind of staggered schedule rather than a cut-and-dry approach. We could have gradually off-boarded clients when we had more definitive work to replace them. I was too confident. But that’s a lesson I had to learn the hard way. Rebuilding & Resetting Most of the voluntary and involuntary churn happened toward the end of 2022. So we’re still dealing with the fall out. Right now, it feels like a period of rebuilding. We didn’t quite lose 50% of our revenue, but we definitely saw a big hit heading into 2023. To be transparent: It sucks. It feels like a gigantic mistake that I made which set us back significantly from our previous high point. I acted rashly and it cost us a lot of money — at least on the surface. But I remind myself of the situation we were in previously. Nearly twice the revenue but struggling to maintain profitability. Would it have been better to try to slowly fix that situation and battle through months of loss or barely-break-even profits? Or was ripping off the bandaid the right move after all? I’m an optimist. (Heh, heh) Plus, I know that spiraling over past decisions won’t change them or help me move forward. So I’m choosing to look at this as an opportunity — to rebuild, reset, and refocus the company. I get to take all of the tough lessons I’ve learned over the last 6 years and apply them to build the company in a way that better aligns with our new and current goals. It’s not quite a fresh, clean start, but by parting ways with some of our oldest clients, we’ve eliminated some of the “debt” that’s accumulated over the years. We get a chance to fully realize the new positioning that we rolled out last year. Many of those long-term clients who churned had a scope of work or engagement structure that didn’t fit with our new positioning and focus. So, by losing them, we’re able to completely close up shop on the SOWs that no longer align with the future version of Optimist. Our smaller roster of clients is a better fit for that future. My job is to protect that positioning by ensuring that while we’re rebuilding our new roster of clients we don’t get desperate. We maintain the qualifications we set out for future clients and only take on work that fits. How’s that for seeing the upside? Some other upside from the situation is that we got an opportunity to ask for candid feedback from clients who were leaving. We asked for insight about their decision, what factors they considered, how they perceived us, and the value of our work. Some of the reasons clients left were obvious and possibly unavoidable. Things like budget cuts, insourcing, and uncertainty about the economy all played at least some part of these decisions. But, reading between the lines, where was one key insight that really struck me. It’s one of those, “oh, yeah — duh — I already knew that,” things that can be difficult to learn and easy to forget…. We’re in the Relationship Business (Plan Accordingly) For all of our focus on things like rankings, keywords, content, conversions, and a buffet of relevant metrics, it can be easy to lose the forest for the trees. Yes, the work itself matters. Yes, the outcomes — the metrics — matter. But sometimes the relationship matters more. When you’re running an agency, you can live or die by someone just liking you. Admittedly, this feels totally unfair. It opens up all kinds of dilemmas, frustration, opportunity for bias and prejudice, and other general messiness. But it’s the real world. If a client doesn’t enjoy working with us — even if for purely personal reasons — they could easily have the power to end of engagement, regardless of how well we did our actual job. We found some evidence of this in the offboarding conversations we had with clients. In some cases, we had clients who we had driven triple- and quadruple-digital growth. Our work was clearly moving the needle and generating positive ROI and we had the data to prove it. But they decided to “take things in another direction” regardless. And when we asked about why they made the decision, it was clear that it was more about the working relationship than anything we could have improved about the service itself. The inverse is also often true. Our best clients have lasting relationships with our team. The work is important — and they want results. But even if things aren’t quite going according to plan, they’re patient and quick to forgive. Those relationships feel solid — unshakeable. Many of these folks move onto new roles or new companies and quickly look for an opportunity to work with us again. On both sides, relationships are often more important than the work itself. We’ve already established that we’re not building a business that will scale in a massive way. Optimist will always be a small, boutique service firm. We don’t need 100 new leads per month We need a small, steady roster of clients who are a great fit for the work we do and the value we create. We want them to stick around. We want to be their long-term partner. I’m not built for churn-and-burn agency life. And neither is the business. When I look at things through this lens, I realize how much I can cut from our overall business strategy. We don’t need an ultra-sophisticated, multi-channel marketing strategy. We just need strong relationships — enough of them to make our business work. There are a few key things we can take away from this as a matter of business strategy: Put most of our effort into building and strengthening relationships with our existing clients Be intentional about establishing a strong relationship with new clients as part of onboarding Focus on relationships as the main driver of future business development Embracing Reality: Theory vs Practice Okay, so with the big learnings out the way, I want to pivot into another key lesson from 2022. It’s the importance of understanding theory vs practice — specifically when it comes to thinking about time, work, and life. It all started when I was considering how to best structure my days and weeks around running Optimist, my other ventures, and my life goals outside of work. Over the years, I’ve dabbled in many different ways to block time and find focus — to compartmentalize all of the things that are spinning and need my attention. As I mapped this out, I realized that I often tried to spread myself too thin throughout the week. Not just that I was trying to do too much but that I was spreading that work into too many small chunks rather than carving out time for focus. In theory, 5 hours is 5 hours. If you have 5 hours of work to get done, you just fit into your schedule whenever you have an open time slot. In reality, a single 5-hour block of work is 10x more productive and satisfying than 10, 30-minute blocks of work spread out across the week. In part, this is because of context switching. Turning your focus from one thing to another thing takes time. Achieving flow and focus takes time. And the more you jump from one project to another, the more time you “lose” to switching. This is insightful for me both in the context of work and planning my day, but also thinking about my life outside of Optimist. One of my personal goals is to put a finite limit on my work time and give myself more freedom. I can structure that in many different ways. Is it better to work 5 days a week but log off 1 hour early each day? Or should I try to fit more hours into each workday so I can take a full day off? Of course, it’s the latter. Both because of the cost of context switching and spreading work into more, smaller chunks — but also because of the remainder that I end up with when I’m done working. A single extra hour in my day probably means nothing. Maybe I can binge-watch one more episode of a new show or do a few extra chores around the house. But it doesn’t significantly improve my life or help me find greater balance. Most things I want to do outside of work can’t fit into a single extra hour. A full day off from work unlocks many more options. I can take the day to go hiking or biking. I can spend the day with my wife, planning or playing a game. Or I can push it up against the weekend and take a 3-day trip. It gives me more of the freedom and balance that I ultimately want. So this has become a guiding principle for how I structure my schedule. I want to: Minimize context switching Maximize focused time for work and for non-work The idea of embracing reality also bleeds into some of the shifts in business strategy that I mentioned above. In theory, any time spent on marketing will have a positive impact on the company. In reality, focusing more on relationships than blasting tweets into the ether is much more likely to drive the kind of growth and stability that we’re seeking. As I think about 2023, I think this is a recurring theme. It manifests in many ways. Companies are making budget cuts and tough decisions about focus and strategy. Most of us are looking for ways to rein in the excess and have greater impact with a bit less time and money. We can’t do everything. We can’t even do most things. So our #1 priority should be to understand the reality of our time and our effort to make the most of every moment (in both work and leisure). That means thinking deeply about our strengths and our limitations. Being practical, even if it feels like sacrifice. Update on Other Businesses Finally, I want to close up by sharing a bit about my ventures outside of Optimist. I shared last year how I planned to shift some of my (finite) time and attention to new ventures and opportunities. And, while I didn’t get to devote as much as I hoped to these new pursuits, they weren’t totally in vain. I made progress across the board on all of the items I laid out in my post. Here’s what happened: Juice: The first Optimist spin-out agency At the end of 2021, we launched our first new service business based on demand from Optimist clients. Focused entirely on building links for SEO, we called the agency Juice. Overall, we made strong progress toward turning this into a legitimate standalone business in 2022. Relying mostly on existing Optimist clients and a few word-of-mouth opportunities (no other marketing), we built a team and set up a decent workflow and operations. There’s still many kinks and challenges that we’re working through on this front. All told, Juice posted almost $100,000 in revenue in our first full year. Monetizing the community I started 2022 with a focus on figuring out how to monetize our free community, Top of the Funnel. Originally, my plan was to sell sponsorships as the main revenue driver. And that option is still on the table. But, this year, I pivoted to selling paid content and subscriptions. We launched a paid tier for content and SEO entrepreneurs where I share more of my lessons, workflows, and ideas for building and running a freelance or agency business. It’s gained some initial traction — we reached \~$1,000 MRR from paid subscriptions. In total, our community revenue for 2022 was about $2,500. In 2023, I’m hoping to turn this into a $30,000 - $50,000 revenue opportunity. Right now, we’re on track for \~$15,000. Agency partnerships and referrals In 2022, we also got more serious about referring leads to other agencies. Any opportunity that was not a fit for Optimist or we didn’t have capacity to take on, we’d try to connect with another partner. Transparently, we struggled to operationalize this as effectively as I would have liked. In part, this was driven by my lack of focus here. With the other challenges throughout the year, I wasn’t able to dedicate as much time as I’d like to setting goals and putting workflows into place. But it wasn’t a total bust. We referred out several dozen potential clients to partner agencies. Of those, a handful ended up converting into sales — and referral commission. In total, we generated about $10,000 in revenue from referrals. I still see this as a huge opportunity for us to unlock in 2023. Affiliate websites Lastly, I mentioned spending some time on my new and existing affiliate sites as another big business opportunity in 2022. This ultimately fell to the bottom of my list and didn’t get nearly the attention I wanted. But I did get a chance to spend a few weeks throughout the year building this income stream. For 2022, I generated just under $2,000 in revenue from affiliate content. My wife has graciously agreed to dedicate some of her time and talent to these projects. So, for 2023, I think this will become a bit of a family venture. I’m hoping to build a solid and consistent workflow, expand the team, and develop a more solid business strategy. Postscript — AI, SEO, OMG As I’m writing this, much of my world is in upheaval. If you’re not in this space (and/or have possibly been living under a rock), the release of ChatGPT in late 2022 has sparked an arms race between Google, Bing, OpenAI, and many other players. The short overview: AI is likely to fundamentally change the way internet search works. This has huge impact on almost all of the work that I do and the businesses that I run. Much of our focus is on SEO and understanding the current Google algorithm, how to generate traffic for clients, and how to drive traffic to our sites and projects. That may all change — very rapidly. This means we’re standing at a very interesting point in time. On the one hand, it’s scary as hell. There’s a non-zero chance that this will fundamentally shift — possibly upturn — our core business model at Optimist. It could dramatically change how we work and/or reduce demand for our core services. No bueno. But it’s also an opportunity (there’s the optimist in me, again). I certainly see a world where we can become leaders in this new frontier. We can pivot, adjust, and capitalize on a now-unknown version of SEO that’s focused on understanding and optimizing for AI-as-search. With that, we may also be able to help others — say, those in our community? — also navigate this tumultuous time. See? It’s an opportunity. I wish I had the answers right now. But, it’s still a time of uncertainty. I just know that there’s a lot of change happening and I want to be in front of it rather than trying to play catch up. Wish me luck. — Alright friends — that's my update for 2023! I’ve always appreciated sharing these updates with the Reddit community, getting feedback, being asked tough questions, and even battling it out with some of my haters (hey!! 👋) As usual, I’m going to pop in throughout the next few days to respond to comments or answer questions. Feel free to share thoughts, ideas, and brutal takedowns in the comments. If you're interested in following the Optimist journey and the other projects I'm working on in 2023, you can follow me on Twitter. Cheers, Tyler P.S. - If you're running or launching a freelance or agency business and looking for help figuring it out, please DM me. Our subscription community, Middle of the Funnel, was created to provide feedback, lessons, and resources for other entrepreneurs in this space.

Made $19.2k this month, and just surpassed $1000 the last 24 hours. What I did and what's next.
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dams96This week

Made $19.2k this month, and just surpassed $1000 the last 24 hours. What I did and what's next.

It's the first time I hit $1000+ in 24 hours and I had no one to share it with (except you guys). I'm quite proud of my journey, and I would have thought that making $1000 in a day would make me ecstatic, but actually it's not the case. Not sure if it's because my revenue has grown by increment step so I had time to "prepare" myself to achieve this at one point, or just that I'm nowhere near my goal of 100k/month so that I'm not that affected by it. But it's crazy to think that my goal was to make 100$ daily at the end of 2024. So for those who don't know me (I guess most of you), I build mobile apps and ship them as fast as I can. Most of them are in the AI space. I already made a post here on how I become a mobile app developer so you can check it for more details, but essentially here's what I did : Always loved creating my own things and solve problems Built multiple YouTube channels since I was 15 (mobile gaming actually) that all worked great (but it was too niche so not that scalable, didn't like that) Did a few businesses here and there (drop shopping, selling merch to school, etc) Finished my master's degree in engineering about 2 years ago Worked a moment in a famous watch industry company and saw my potential. The combo of health issues, fixed salary (although it was quite a lot), and me wanting to be an entrepreneur made me leave the company. Created a TikTok account in mobile tech (got 10+ million views the 1st 3 days), manage to grow it to 200k subs in about 3 months Got plenty of collabs for promoting mobile apps (between $500 - $2000 for a collab) Said fuck it I should do my own apps and market them on my TikTok instead of doing collabs Me wanting to build my own apps happened around May-June 2023. Started my TikTok in Feb 2023. At this point I had already 150k+ subs on TikTok. You guys need to know that I suck at coding big time. During my studies I tried to limit as much as I could coding because I was a lazy bast*rd, even though I knew it would come to bite me in the ass one day. But an angel appeared to me in broad daylight, that angel was called GPT-4. I subscribed for 20$/month to get access, and instantly I saw the potential of AI and how much it could help me. Last year GPT-4 was ahead of its time and could already code me basic apps. I had already a mac so I just downloaded Xcode and that was it. My 1st app was a wallpaper app, and I kid you not 90% of it was made by AI. Yes sometimes I had to try again and again with different prompts but it was still so much faster compared to if I had to learn coding from scratch and write code with my own hands. The only thing I didn't do was implement the in app purchase, from which I find a guy on Fiverr to do it for me for 50$. After about 2 months of on-off coding, my first app was ready to be launched. So it was launched, had a great successful launch without doing any videos at that point (iOS 17 was released and my app was the first one alongside another one to offer live wallpapers for iOS 17. I knew that there was a huge app potential there when iOS 17 was released in beta as Apple changed their live wallpaper feature). I Then made a video a few weeks after on my mobile tiktok channel, made about 1 million views in 48 hours, brought me around 40k additional users. Was top 1 chart in graphism and design category for a few weeks (in France, as I'm French so my TikTok videos are in French). And was top 100 in that same category in 120+ countries. Made about 500$ ? Okay that was trash, but I had no idea to monetize the app correctly at that point. It was still a huge W to me and proved me that I could successfully launch apps. Then I learned ASO (App Store Optimization) in depth, searched on internet, followed mobile app developers on Twitter, checked YouTube videos, you name it. I was eager to learn more. I needed more. Then I just iterated, build my 2nd app in less than a month, my 3rd in 3 weeks and so on. I just build my 14th app in 3 days and is now in review. Everytime I manage to reuse some of my other app's code in my new one, which is why I can build them so much faster now. I know how to monetize my app better by checking out my competitors. I learn so much by just "spying" other apps. Funnily enough, I only made this one Tiktok video on my main account to promote my app. For all my other apps, I didn't do a single video where I showcase it, the downloads has only been thanks to ASO. I still use AI everyday. I'm still not good at coding (a bit better than when I started). I use AI to create my app icons (midjourney or the new AI model Flux which is great). I use figma + midjourney to create my App Store screenshots (and they actually look quite good). I use GPT-4o and Claude 3.5 Sonnet to code most of my apps features. I use gpt-4o to localize my app (if you want to optimize the number of downloads I strongly suggest localizing your app, it takes me about 10 minutes thanks to AI). Now what are my next goals ? To achieve the 100k/month I need to change my strategy a little. Right now the $20k/month comes from purely organic downloads, I didn't do any paid advertising. It will be hard for me to keep on launching new apps and rely on ASO to reach the 100k mark. The best bet to reach 100k is to collab with content creators and they create a viral video showcasing your app. Depending on the app it's not that easy, luckily some of my apps can be viral so I will need to find the right content creators. Second way is to try tiktok/meta ads, I can check (have checked) all the ads that have been made by my competitors (thank you EU), so what I would do is copy their ad concept and create similar ads than them. Some of them have millions in ad budget so I know they create high converting ads, so you don't need to try to create an ad creative from scratch. My only big fear is to get banned by Apple (for no reason of mine). In just a snap of a finger they can just ban you from the platform, that shit scares me. And you pretty much can't do anything. So that's about it for me. I'm quite proud of myself not going to lie. Have been battling so many health issues these past years where I just stay in bed all day I'm surprised to be able to make it work. Anyways feel free to ask questions. I hope it was interesting for some of you at least. PS: My new app was just approved by app review, let the app gods favor me and bring me many downloads ! Also forgot to talk about a potential $100k+ acquisition of one of my apps, but if that ever happens I'll make a post on it.

boring passive site... now 42k monthly visitors and $2540 MRR
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TasAdamsThis week

boring passive site... now 42k monthly visitors and $2540 MRR

people underestimate SEO... It is evergreen... passive... digital real estate. it can do magic... if you are consistent. Especially now with AI you can 2X your traffic growth and automate 85% of the work. For the past 6 months... we've been building an online directory. we just reached $2540 MRR... with SEO only... from a complete zero. I did share this on other subreddits. Maybe this gives ideas to someone. \+ This can be easily replicated if you have a website lol Current metrics: $2540 MRR - businesses pay us to list on the directory + display ads + pay to be featured. 43k monthly visitors - in the past couple of weeks our SEO growth is a hockey stick. DR (Domain Rating) 35 - it took us 2.5 months to get to that. 51 okay-ish quality referring domains (90% of them are do-follow) and 1.6k backlinks. There are probably 3 main pillars I try to focus on: keywords --> which then is the basis for ALL the content pieces we do blogs, landing pages, about us pages, competitor comparisons etc --> we use a DIY excel file to automate content production at scale. backlinks --> boost DR --> one of the main things to boost ranking on google. website health --> this is technical stuff like internal and external linking, schemas, canonical tags, alt texts, load speeds, compressed images, meta descriptions, titles etc --> do this once... and do it GOOD. $0.07 per SEO optimised blog at scale with AI Yep... we've literally built our own SEO blog tool... and it is a Spreadsheet with bunch of app scripts :D NOTE that we add a little bit of human touch to those blogs that are picked up by Google rank top in 25 How it works... is that we paste in bunch of links (other websites, blogs, news articles) and with a click of a button we can get up to 2000 SEO optimised content pieces... from an Excel file... $0.07 per blog. The spreadsheet is integrated with Chat gpt (obviously). We use GPT-4 for meta descriptions, titles, transforming the content from text to html code since it is more powerful, and GPT-4o for content itself because it is cheaper and faster for "general text". The spreadsheet repurposes content. The spreadsheet generates: Meta descriptions and titles FAQs sections - DON'T skip FAQ sections! They are a must for SEO. On Ahrefs... there is a section of questions people are searching about your keyword... that's your FAQs It can find contextual youtube videos (links to those videos) - to show google that our content is not "just text" thus higher quality. Screenshots and images of the original source (the website link we inputed) I then download a csv version of the excel and import it into our Webflow. The csv file column names match our webflow CMS field names. tbh... we didn't even know that it can be done with a spreadsheet. We "tried" building it because every other tool we were using is (1) expensive from $0.59 per SEO content piece (2) they didn't provide the scale we wanted (3) we wanted more control over the output. Focus on DR 35+ backlinks... easier We bought backlinks only once... rest of the backlinks was a manual work from us. Bunch of free listing databases (about 65% of our backlinks) You can comment on open forums with your link to get a backlink (be careful tho) Post a blog on Medium com --> DR 94 backlink (takes time to Index) If you pay for Notion you can get a DR 94 backlink from Notion If you use Beehiiv you can get a DR 86 backlink from Beehiiv Google product stacking (Google sites, Google notes etc) --> backlink from almighty Google itself A lot of work goes into backlinks because they are THAT important. I have tried bunch of "black hat" strategies as well... but note that all of these strategies won't work if you don't index the primary source from where your backlink is coming from. BIG search volume and low KD Key things I'm looking for in keywords: I use Ahrefs Keyword research tool... it is literally free BIG search volume - 2k+ is oaky-ish for a single keyword EASY to rank - KD (keyword difficulty) below 15 Look for long tail keywords (these are golden nuggets since they have a VERY clear search intent) - "how to edit..." "how to change..." "how to delete..." "how to paint..." I hope you got the idea. on Ahrefs you can use "\" to get BIG volume long tail keywords... like this "my keyword\". Ahrefs then populates the "\" with the tail. Check SERP (Search Engine Result Page) for your keywords - it shows current top 10 pages for those KWs. Check their content. Can you improve it? Have they missed anything? Keyword gap from your competitors - shows EASY keywords that your competitors have missed and also shows what keywords overlap with you. Also one cool thing... if you don't type any keywords on Ahrefs and press "Enter"... you can browse all the keywords out there... it is magical. Once we have the keywords, we run our spreadsheet. And that's pretty much it. I hope that you can get some ideas from this little silly project. Also... if you have any questions about this... I might share the SEO blog automation excel file/help if people are interested...

AI Will Make You Extremely Rich or Kill Your Business in 2024
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AntsyNursery58This week

AI Will Make You Extremely Rich or Kill Your Business in 2024

Preface: I'm a solo-founder in the AI space and previously worked as an ML scientist; the new advancements in AI that I'm seeing are going to impact everyone here. It doesn't matter if you're just starting out, or a bootstrapped brick and mortar founder, or even a VC backed hard tech founder. Last year was when the seeds were laid, and this is the year we'll see them bloom. There will be an onslaught of advancements that take place that are borderline inconceivable due to the nature of exponential progress. This will change every single vertical. I'm making this post because I think AI execution strategy will make or break businesses. Dramatically. Over $50B was put into AI startups in 2023 alone. This figure excludes the hundreds of billions poured into AI from enterprises. So, let's follow the money: &#x200B; 1) AI enterprise software. There's a lot to unpack here and this is what I’m currently working on. AI enterprise software will encompass everything from hyper personalized email outbound to AI cold calls to AI that A/B tests ads on synthetic data to vertical specific software. The impact of the former is relatively self explanatory, so I'll focus on the latter. To illustrate vertical specific AI software, I'll use a simple example in the legal space. Lawyers typically have to comb through thousands of pages of documents. Now, using an LLM + a VDB, an AI can instantly answer all of those questions while surfacing the source and highlighting the specific answer in the contract/document. There are dozens of AI startups for this use case alone. This saves lawyers an immense amount of time and allows them to move faster. Firms that adopt this have a fundamental advantage over law firms that don't adopt this. This was 2023 technology. I'm seeing vertical AI software getting built by my friends in areas from construction, to real estate, to even niche areas like chimney manufacturing. This will exist everywhere. Now, this can be extrapolated much further to be applicable to systems that can do reports and even browse the Internet. This brings me to my next point. &#x200B; 2) AI information aggregation and spread. My gut tells me that this will have a crescendo moment in the future with hardware advancements (Rabbit, Tab, etc.). You won't have to google things because it will be surfaced to you. It's predictive in nature. The people who can get information the fastest will grow their business the fastest. This part is semi-speculative, but due to the nature of LLMs being so expensive to train, I have a strong feeling that large institutions will have access to the \fastest\ and \best\ models that can do this quicker than you and I can. This is why it's important to stay on top. &#x200B; 3) AI content generation This is relevant to running advertisements and any digital marketing aspect of your business. If you can rapidly make content faster than your competitors to put in social media, you will outpace your competitors rapidly. I think most folks are familiar with MidJourney, Stable diffusion, etc. but don't know how to use it. You can generate consistent models for a clothing brand or generate images of a product that you would normally need to hire a professional photographer to take. There's also elevenlabs which is relatively easy to use and can be used to make an MP3 clip as a narration for an ad; this is something I've already done. I'm also still shocked by how many people are unfamiliar with tools like Pika which can do video generation. You could imagine companies having fleets of digital influencers that they control or conjuring up the perfect ad for a specific demographic using a combination of all of the aforementioned tools. &#x200B; In summary, if you feel like I'm being hyperbolic or propagating science fiction fantasies, you're likely already behind. I truly recommend that everyone stays up to date on these advancements as much as possible. If your competitor comes across an AI tool that can increase their ROAS by 5x they can crush you. If your competitor uses a tool that increases the rate at which they receive and aggregate information by 200% (modest estimate) they will crush you. If your competitors have a tool that can reduce their employee size, then they will use it. They'll fire their employees to cut costs and reinvest the money back into their business. It will compound to the point where you're outpaced, and this isn't a level of innovation we've seen since the birth of the industrial revolution. Your customers can get stolen overnight, or you can steal your competition’s customers overnight. TL;DR: This is an opportunity for entrepreneurs to scale faster than they could have possibly imagined, but this also comes with the potential for your company to be obliterated. We've never seen advancements that can have this drastic of an impact this quickly. Adoption will happen fast, and first movers will have a disproportionate and compounding advantage. Watch guides, meet with startups, follow the news, and get rich.

Dangers of not adopting AI strategies?
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FreelancerChurchThis week

Dangers of not adopting AI strategies?

Tldr: I need to know how AI is threatening different types of businesses. Please share your perspective. I'll reply to every comment. Hi, this is for anyone concerned with how to respond to the emergence of new AI tools. (to grow instead of going out of business, find opportunities instead of getting beat by competitors, etc. I need to find the best ways to use AI to give my clients an advantage. (I’m a mod at r/writingservice & a content/brand strategist.) Not just automation. That's weak. I mean innovation. Using AI to do stuff that has never been done in your industry. Lots of virtual assistants (for business owners) will make the mistake of learning how to use these tools only in a general way, without applying them in the real world. I don’t want to make that mistake. It will help me if you share what’s on your mind, what’s unique about the way AI affects your industry, or your unique business model, etc. So this is basically like an informal research study. And it's the kind where you get something if you participate - I will seriously spend time to offer the best stuff I know in the comments if you just share your perspective, how AI is affecting you in the unique way you are situation in your industry and among your competitors. Have you been finding ways to incorporate AI in your marketing, customer service, etc.? I have a feeling a lot of business owners are worried right now, because all our experience is from the old landscape prior to everything being automated with AI. Even if you have questions on your mind and share them, that can help me. My problem: I’m learning to use GPT/Gemini/Invideo/Perplexity and others, but it’s not good enough until I see how they apply in different situations, industries, business models. If you share some ideas, I’ll reply to every comment and try to offer something helpful. I’ve already made a lot of progress learning how the strengths/weaknesses of different AI tools for different situations. Thinking about the way their competitors might surpass you by using them, or about opportunities for you to surpass them.... what concerns are on your mind? Or what have you learned, what are you doing, etc.

Recently hit 6,600,000 monthly organic traffic for a B2C SaaS website. Here's the 40 tips that helped me make that happen.
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DrJigsawThis week

Recently hit 6,600,000 monthly organic traffic for a B2C SaaS website. Here's the 40 tips that helped me make that happen.

Hey guys! So as title says, we recently hit 6,600,000 monthly organic traffic / month for a B2C SaaS website (screenshot. Can't give name publicly, but can show testimonial to a mod). Here's 40 tips that "helped" me make this happen. If you get some value of the post, I write an SEO tip every other day on /r/seogrowth. There's around 10 more tips already up there other than the ones I mention here. If you want to give back for all my walls of text, I'd appreciate a sub <3 Also, there are a bunch of free stuff I mention in the article: content outline, writer guidelines, SEO checklist, and other stuff. Here's the Google Doc with all that! Tip #1. Take SEO With a Grain of Salt A lot of the SEO advice and best practices on the internet are based on 2 things: Personal experiences and case studies of companies that managed to make SEO work for them. Google or John Mueller (Google’s Senior Webmaster Trends Analyst). And, unfortunately, neither of these sources are always accurate. Personal SEO accounts are simply about what worked for specific companies. Sometimes, what worked for others, won’t work for you. For example, you might find a company that managed to rank with zero link-building because their website already had a very strong backlink profile. If you’re starting with a fresh website, chances are, you won’t be able to get the same results. At the same time, information from Google or John Mueller is also not 100% accurate. For example, they’ve said that guest posting is against Google’s guidelines and doesn’t work… But practically, guest posting is a very effective link-building strategy. So the takeaway is this: Take all information you read about SEO with a grain of salt. Analyze the information yourself, and make your conclusions. SEO Tip #2. SEO Takes Time You’ve already heard this one before, but considering how many people keep asking, thought I'd include this anyway. On average, it’s going to take you 6 months to 2 years to get SEO results, depending on the following factors: Your backlink profile. The more quality backlinks you have (or build), the faster you’ll rank. Age of your website. If your website is older (or you purchased an aged website), you can expect your content to rank faster. Amount of content published. The more quality content you publish on your website, the more “authoritative” it is in the eyes of Google, and thus more likely to rank faster. SEO work done on the website. If a lot of your pages are already ranking on Google (page 2-3), it’s easier to get them to page #1 than if you just published the content piece. Local VS global SEO. Ranking locally is (sometimes) easier and faster than ranking globally. That said, some marketing agencies can use “SEO takes time” as an excuse for not driving results. Well, fortunately, there is a way to track SEO results from month #2 - #3 of work. Simply check if your new content pieces/pages are getting more and more impressions on Google Search Console month-to-month. While your content won’t be driving traffic for a while after being published, they’ll still have a growing number of impressions from month #2 or #3 since publication. SEO Tip #3. SEO Might Not Be The Best Channel For You In theory, SEO sounds like the best marketing channel ever. You manage to rank on Google and your marketing seemingly goes on auto-pilot - you’re driving new leads every day from existing content without having to lift a finger… And yet, SEO is not for everyone. Avoid SEO as a marketing channel if: You’re just getting started with your business and need to start driving revenue tomorrow (and not in 1-2 years). If this is you, try Google ads, Facebook ads, or organic marketing. Your target audience is pretty small. If you’re selling enterprise B2B software and have around 2,000 prospects in total worldwide, then it’s simply easier to directly reach out to these prospects. Your product type is brand-new. If customers don’t know your product exists, they probably won’t be Googling it. SEO Tip #4. Traffic Can Be a Vanity Metric I've seen hundreds of websites that drive 6-7 digits of traffic but generate only 200-300 USD per month from those numbers. “What’s the deal?” You might be thinking. “How can you fail to monetize that much traffic?” Well, that brings us to today’s tip: traffic can be a vanity metric. See, not all traffic is created equal. Ranking for “hormone balance supplement” is a lot more valuable than ranking for “Madagascar character names.” The person Googling the first keyword is an adult ready to buy your product. Someone Googling the latter, on the other hand, is a child with zero purchasing power. So, when deciding on which keywords to pursue, always keep in mind the buyer intent behind and don’t go after rankings or traffic just because 6-digit traffic numbers look good. SEO Tip #5. Push Content Fast Whenever you publish a piece of content, you can expect it to rank within 6 months to a year (potentially less if you’re an authority in your niche). So, the faster you publish your content, the faster they’re going to age, and, as such, the faster they’ll rank on Google. On average, I recommend you publish a minimum of 10,000 words of content per month and 20,000 to 30,000 optimally. If you’re not doing link-building for your website, then I’d recommend pushing for even more content. Sometimes, content velocity can compensate for the lack of backlinks. SEO Tip #6. Use Backlink Data to Prioritize Content You might be tempted to go for that juicy, 6-digit traffic cornerstone keyword right from the get-go... But I'd recommend doing the opposite. More often than not, to rank for more competitive, cornerstone keywords, you’ll need to have a ton of supporting content, high-quality backlinks, website authority, and so on. Instead, it’s a lot more reasonable to first focus on the less competitive keywords and then, once you’ve covered those, move on to the rest. Now, as for how to check keyword competitiveness, here are 2 options: Use Mozbar to see the number of backlinks for top-ranking pages, as well as their Domain Authority (DA). If all the pages ranking on page #1 have <5 backlinks and DA of 20 - 40, it’s a good opportunity. Use SEMrush or Ahrefs to sort your keywords by difficulty, and focus on the less difficult keywords first. Now, that said, keep in mind that both of these metrics are third-party, and hence not always accurate. SEO Tip #7. Always Start With Competitive Analysis When doing keyword research, the easiest way to get started is via competitive analysis. Chances are, whatever niche you’re in, there’s a competitor that is doing great with SEO. So, instead of having to do all the work from scratch, run their website through SEMrush or Ahrefs and steal their keyword ideas. But don’t just stop there - once you’ve borrowed keyword ideas from all your competitors, run the seed keywords through a keyword research tool such as UberSuggest or SEMrush Keyword Magic Tool. This should give you dozens of new ideas that your competitors might’ve missed. Finally, don’t just stop at borrowing your competitor’s keyword ideas. You can also borrow some inspiration on: The types of graphics and images you can create to supplement your blog content. The tone and style you can use in your articles. The type of information you can include in specific content pieces. SEO Tip #8. Source a LOT of Writers Content writing is one of those professions that has a very low barrier to entry. Anyone can take a writing course, claim to be a writer, and create an UpWork account… This is why 99% of the writers you’ll have to apply for your gigs are going to be, well, horrible. As such, if you want to produce a lot of content on the reg, you’ll need to source a LOT of writers. Let’s do the math: If, by posting a job ad, you source 100 writers, you’ll see that only 5 of them are a good fit. Out of the 5 writers, 1 has a very high rate, so they drop out. Another doesn’t reply back to your communication, which leaves you with 3 writers. You get the 3 writers to do a trial task, and only one turns out to be a good fit for your team. Now, since the writer is freelance, the best they can do is 4 articles per month for a total of 5,000-words (which, for most niches, ain’t all that much). So, what we’re getting at here is, to hire quality writers, you should source a LOT of them. SEO Tip #9. Create a Process for Filtering Writers If you follow the previous tip, you'll end up with a huge database of hundreds of writers. This creates a whole new problem: You now have a database of 500+ writers waiting for you to sift through them and decide which ones are worth the hire. It would take you 2-3 days of intense work to go through all these writers and vet them yourself. Let’s be real - you don’t have time for that. Here’s what you can do instead: When sourcing writers, always get them to fill in a Google form (instead of DMing or emailing you). In this form, make sure to ask for 3 relevant written samples, a link to the writer’s portfolio page, and the writer’s rate per word. Create a SOP for evaluating writers. The criteria for evaluation should be: Level of English. Does the writer’s sample have any English mistakes? If so, they’re not a good fit. Quality of Samples. Are the samples long-form and engaging content or are they boring 500-word copy-pastes? Technical Knowledge. Has the writer written about a hard-to-explain topic before? Anyone can write about simple topics like traveling—you want to look for someone who knows how to research a new topic and explain it in a simple and easy-to-read way. If someone’s written about how to create a perfect cover letter, they can probably write about traveling, but the opposite isn’t true. Get your VA to evaluate the writer’s samples as per the criteria above and short-list writers that seem competent. If you sourced 500 writers, the end result of this process should be around 50 writers. You or your editor goes through the short-list of 50 writers and invites 5-10 for a (paid) trial task. The trial task is very important - you’ll sometimes find that the samples provided by the writer don’t match their writing level. SEO Tip #10. Use the Right Websites to Find Writers Not sure where to source your writers? Here are some ideas: ProBlogger \- Our #1 choice - a lot of quality writers frequent this website. LinkedIn \- You can headhunt content writers in specific locations. Upwork \- If you post a content gig, most writers are going to be awful. Instead, I recommend headhunting top writers instead. WeWorkRemotely \- Good if you’re looking to make a full-time remote hire. Facebook \- There are a ton of quality Facebook groups for writers. Some of our faves are Cult of Copy Job Board and Content Marketing Lounge. SEO Tip #11. Always Use Content Outlines When giving tasks to your writing team, you need to be very specific about the instructions you give them. Don’t just provide a keyword and tell them to “knock themselves out.” The writer isn’t a SEO expert; chances are, they’re going to mess it up big-time and talk about topics that aren’t related to the keyword you’re targeting. Instead, when giving tasks to writers, do it through content outlines. A content outline, in a nutshell, is a skeleton of the article they’re supposed to write. It includes information on: Target word count (aim for the same or 50% more the word count than that of the competition). Article title. Article structure (which sections should be mentioned and in what order). Related topics of keywords that need to be mentioned in the article. Content outline example in the URL in the post intro. SEO Tip #12. Focus on One Niche at a Time I used to work with this one client that had a SaaS consisting of a mixture of CRM, Accounting Software, and HRS. I had to pick whether we were going to focus on topics for one of these 3 niches or focus on all of them at the same time. I decided to do the former. Here’s why: When evaluating what to rank, Google considers the authority of your website. If you have 60 articles about accounting (most of which link to each other), you’re probably an authority in the niche and are more likely to get good rankings. If you have 20 sales, 20 HR, and 20 accounting articles, though, none of these categories are going to rank as well. It always makes more sense to first focus on a single niche (the one that generates the best ROI for your business), and then move on to the rest. This also makes it easier to hire writers - you hire writers specialized in accounting, instead of having to find writers who can pull off 3 unrelated topics. SEO Tip #13. Just Hire a VA Already It’s 2021 already guys—unless you have a virtual assistant, you’re missing out big-time. Since a lot of SEO tasks are very time-consuming, it really helps to have a VA around to take over. As long as you have solid SOPs in place, you can hire a virtual assistant, train them, and use them to free up your time. Some SEO tasks virtual assistants can help with are: Internal linking. Going through all your blog content and ensuring that they link to each other. Backlink prospecting. Going through hundreds of websites daily to find link opportunities. Uploading content on WordPress and ensuring that the content is optimized well for on-page SEO. SEO Tip #14. Use WordPress (And Make Your Life Easier) Not sure which CMS platform to use? 99% of the time, you’re better off with WordPress. It has a TON of plugins that will make your life easier. Want a drag & drop builder? Use Elementor. It’s cheap, efficient, extremely easy to learn, and comes jam-packed with different plugins and features. Wix, SiteGround, and similar drag & drops are pure meh. SEO Tip #15. Use These Nifty WordPress Plugins There are a lot of really cool WordPress plugins that can make your (SEO) life so much easier. Some of our favorites include: RankMath. A more slick alternative to YoastSEO. Useful for on-page SEO. Smush. App that helps you losslessly compress all images on your website, as well as enables lazy loading. WP Rocket. This plugin helps speed up your website pretty significantly. Elementor. Not a techie? This drag & drop plugin makes it significantly easier to manage your website. WP Forms. Very simple form builder. Akismet Spam Protection. Probably the most popular anti-spam WP plugin. Mammoth Docx. A plugin that uploads your content from a Google doc directly to WordPress. SEO Tip #16. No, Voice Search Is Still Not Relevant Voice search is not and will not be relevant (no matter what sensationalist articles might say). Sure, it does have its application (“Alexa, order me toilet paper please”), but it’s pretty niche and not relevant to most SEOs. After all, you wouldn’t use voice search for bigger purchases (“Alexa, order me a new laptop please”) or informational queries (“Alexa, teach me how to do accounting, thanks”). SEO Tip #17. SEO Is Obviously Not Dead I see these articles every year - “SEO is dead because I failed to make it work.” SEO is not dead and as long as there are people looking up for information/things online, it never will be. And no, SEO is not just for large corporations with huge budgets, either. Some niches are hypercompetitive and require a huge link-building budget (CBD, fitness, VPN, etc.), but they’re more of an exception instead of the rule. SEO Tip #18. Doing Local SEO? Focus on Service Pages If you’re doing local SEO, you’re better off focusing on local service pages than blog content. E.g. if you’re an accounting firm based in Boston, you can make a landing page about /accounting-firm-boston/, /tax-accounting-boston/, /cpa-boston/, and so on. Or alternatively, if you’re a personal injury law firm, you’d want to create pages like /car-accident-law-firm/, /truck-accident-law-firm/, /wrongful-death-law-firm/, and the like. Thing is, you don’t really need to rank on global search terms—you just won’t get leads from there. Even if you ranked on the term “financial accounting,” it wouldn’t really matter for your bottom line that much. SEO Tip #19. Engage With the SEO Community The SEO community is (for the most part) composed of extremely helpful and friendly people. There are a lot of online communities (including this sub) where you can ask for help, tips, case studies, and so on. Some of our faves are: This sub :) SEO Signals Lab (FB Group) Fat Graph Content Ops (FB Group) Proper SEO Group (FB Group) BigSEO Subreddit SEO Tip #20. Test Keywords Before Pursuing Them You can use Google ads to test how profitable any given keyword is before you start trying to rank for it. The process here is: Create a Google Ads account. Pick a keyword you want to test. Create a landing page that corresponds to the search intent behind the keyword. Allocate an appropriate budget. E.g. if you assume a conversion rate of 2%, you’d want to buy 100+ clicks. If the CPC is 2 USD, then the right budget would be 200 USD plus. Run the ads! If you don’t have the budget for this, you can still use the average CPC for the keyword to estimate how well it’s going to convert. If someone is willing to bid 10 USD to rank for a certain keyword, it means that the keyword is most probably generating pretty good revenue/conversions. SEO Tip #21. Test & Improve SEO Headlines Sometimes, you’ll see that you’re ranking in the top 3 positions for your search query, but you’re still not driving that much traffic. “What’s the deal?” you might be asking. Chances are, your headline is not clickable enough. Every 3-4 months, go through your Google Search Console and check for articles that are ranking well but not driving enough traffic. Then, create a Google sheet and include the following data: Targeted keyword Page link CTR (for the last 28 days) Date when you implemented the new title Old title New title New CTR (for the month after the CTR change was implemented) From then on, implement the new headline and track changes in the CTR. If you don’t reach your desired result, you can always test another headline. SEO Tip #22. Longer Content Isn’t Always Better Content You’ve probably heard that long-form content is where it’s at in 2021. Well, this isn’t always the case. Rather, this mostly depends on the keyword you’re targeting. If, for example, you’re targeting the keyword “how to tie a tie,” you don’t need a long-ass 5,000-word mega-guide. In such a case, the reader is looking for something that can be explained in 200-300 words and if your article fails to do this, the reader will bounce off and open a different page. On the other hand, if you’re targeting the keyword “how to write a CV,” you’ll need around 4,000 to 5,000 words to adequately explain the topic and, chances are, you won’t rank with less. SEO Tip #23. SEO is Not All About Written Content More often than not, when people talk about SEO they talk about written blog content creation. It’s very important not to forget, though, that blog content is not end-all-be-all for SEO. Certain keywords do significantly better with video content. For example, if the keyword is “how to do a deadlift,” video content is going to perform significantly better than blog content. Or, if the keyword is “CV template,” you’ll see that a big chunk of the rankings are images of the templates. So, the lesson here is, don’t laser-focus on written content—keep other content mediums in mind, too. SEO Tip #24. Write For Your Audience It’s very important that your content resonates well with your target audience. If, for example, you’re covering the keyword “skateboard tricks,” you can be very casual with your language. Heck, it’s even encouraged! Your readers are Googling the keyword in their free time and are most likely teens or in their early 20s. Meaning, you can use informal language, include pop culture references, and avoid complicated language. Now, on the other hand, if you’re writing about high-level investment advice, your audience probably consists of 40-something suit-and-ties. If you include Rick & Morty references in your article, you'll most likely lose credibility and the Googler, who will go to another website. Some of our best tips on writing for your audience include: Define your audience. Who’s the person you’re writing for? Are they reading the content at work or in their free time? Keep your reader’s level of knowledge in mind. If you’re covering an accounting 101 topic, you want to cover the topic’s basics, as the reader is probably a student. If you’re writing about high-level finance, though, you don’t have to teach the reader what a balance sheet is. More often than not, avoid complicated language. The best practice is to write on a 6th-grade level, as it’s understandable for anyone. Plus, no one wants to read Shakespeare when Googling info online (unless they’re looking for Shakespeare's work, of course). SEO Tip #25. Create Compelling Headlines Want to drive clicks to your articles? You’ll need compelling headlines. Compare the following headline: 101 Productivity Tips \[To Get Things Done in 2021\] With this one: Productivity Tips Guide Which one would you click? Data says it’s the first! To create clickable headlines, I recommend you include the following elements: Keyword. This one’s non-negotiable - you need to include the target keyword in the headline. Numbers. If Buzzfeed taught us anything, it’s that people like to click articles with numbers in their titles. Results. If I read your article, what’s going to be the end result? E.g. “X Resume tips (to land the job)”.* Year (If Relevant). Adding a year to your title shows that the article is recent (which is relevant for some specific topics). E.g. If the keyword is “Marketing Trends,” I want to know marketing trends in 2021, not in 2001. So, adding a year in the title makes the headline more clickable. SEO Tip #26. Make Your Content Visual How good your content looks matters, especially if you're in a competitive niche. Here are some tips on how to make your content as visual as possible: Aim for 2-4 sentences per paragraph. Avoid huge blocks of text. Apply a 60-65% content width to your blog pages. Pick a good-looking font. I’d recommend Montserrat, PT Sans, and Roboto. Alternatively, you can also check out your favorite blogs, see which fonts they’re using, and do the same. Use a reasonable font size. Most top blogs use font sizes ranging from 16 pt to 22 pt. Add images when possible. Avoid stock photos, though. No one wants to see random “office people smiling” scattered around your blog posts. Use content boxes to help convey information better. Content boxes example in the URL in the intro of the post. SEO Tip #27. Ditch the Skyscraper Technique Already Brian Dean’s skyscraper technique is awesome and all, but the following bit really got old: “Hey \[name\], I saw you wrote an article. I, too, wrote an article. Please link to you?” The theory here is, if your content is good, the person will be compelled to link to it. In practice, though, the person really, really doesn’t care. At the end of the day, there’s no real incentive for the person to link to your content. They have to take time out of their day to head over to their website, log in to WordPress, find the article you mentioned, and add a link... Just because some stranger on the internet asked them to. Here’s something that works much better: Instead of fake compliments, be very straightforward about what you can offer them in exchange for that link. Some things you can offer are: A free version of your SaaS. Free product delivered to their doorstep. Backlink exchange. A free backlink from your other website. Sharing their content to your social media following. Money. SEO Tip #28. Get the URL Slug Right for Seasonal Content If you want to rank on a seasonal keyword, there are 2 ways to do this. If you want your article to be evergreen (i.e. you update it every year with new information), then your URL should not contain the year. E.g. your URL would be /saas-trends/, and you simply update the article’s contents+headline each year to keep it timely. If you’re planning on publishing a new trends report annually, though, then you can add a year to the URL. E.g. /saas-trends-2020/ instead of /saas-trends/. SEO Tip #29. AI Content Tools Are a Mixed Bag Lots of people are talking about AI content tools these days. Usually, they’re either saying: “AI content tools are garbage and the output is horrible,” Or: “AI content tools are a game-changer!” So which one is it? The truth is somewhere in-between. In 2021, AI content writing tools are pretty bad. The output you’re going to get is far from something you can publish on your website. That said, some SEOs use such tools to get a very, very rough draft of the article written, and then they do intense surgery on it to make it usable. Should you use AI content writing tools? If you ask me, no - it’s easier to hire a proficient content writer than spend hours salvaging AI-written content. That said, I do believe that such tools are going to get much better years down the line. This one was, clearly, more of a personal opinion than a fact. I’d love to hear YOUR opinion on AI content tools! Are they a fad, or are they the future of content creation? Let me know in the comments. SEO Tip #30. Don’t Overdo it With SEO Tools There are a lot of SEO tools out there for pretty much any SEO function. Keyword research, link-building, on-page, outreach, technical SEO, you name it! If you were to buy most of these tools for your business, you’d easily spend 4-figures on SEO tools per month. Luckily, though, you don’t actually need most of them. At the end of the day, the only must-have SEO tools are: An SEO Suite (Paid). Basically SEMrush or Ahrefs. Both of these tools offer an insane number of features - backlink analysis, keyword research, and a ton of other stuff. Yes, 99 USD a month is expensive for a tool. But then again, if you value your time 20 USD/hour and this tool saves you 6 hours, it's obviously worth it, right? On-Page SEO Tool (Free). RankMath or Yoast. Basically, a tool that's going to help you optimize web pages or blog posts as per SEO best practices. Technical SEO Tool (Freemium). You can use ScreamingFrog to crawl your entire website and find technical SEO problems. There are probably other tools that also do this, but ScreamingFrog is the most popular option. The freemium version of the tool only crawls a limited number of pages (500 URLs, to be exact), so if your website is relatively big, you'll need to pay for the tool. Analytics (Free). Obviously, you'll need Google Analytics (to track website traffic) and Google Search Console (to track organic traffic, specifically) set up on your website. Optionally, you can also use Google Track Manager to better track how your website visitors interact with the site. MozBar (Free). Chrome toolbar that lets you simply track the number of backlinks on Google Search Queries, Domain Authority, and a bunch of other stuff. Website Speed Analysis (Free). You can use Google Page Speed Insights to track how fast your website loads, as well as how mobile-friendly it is. Outreach Tool (Paid). Tool for reaching out to prospects for link-building, guest posting, etc. There are about a dozen good options for this. Personally, I like to use Snov for this. Optimized GMB Profile (Free). Not a tool per se, but if you're a local business, you need to have a well-optimized Google My Business profile. Google Keyword Planner (Free). This gives you the most reliable search volume data of all the tools. So, when doing keyword research, grab the search volume from here. Tool for Storing Keyword Research (Free). You can use Google Sheets or AirTable to store your keyword research and, at the same time, use it as a content calendar. Hemingway App (Free). Helps keep your SEO content easy to read. Spots passive voice, complicated words, etc. Email Finder (Freemium). You can use a tool like Hunter to find the email address of basically anyone on the internet (for link-building or guest posting purposes). Most of the tools that don’t fit into these categories are 100% optional. SEO Tip #31. Hiring an SEO? Here’s How to Vet Them Unless you’re an SEO pro yourself, hiring one is going to be far from easy. There’s a reason there are so many “SEO experts” out there - for the layman, it’s very hard to differentiate between someone who knows their salt and a newbie who took an SEO course, like, last week. Here’s how you can vet both freelance and full-time SEOs: Ask for concrete traffic numbers. The SEO pro should give you the exact numbers on how they’ve grown a website in the past - “100% SEO growth in 1 year” doesn’t mean much if the growth is from 10 monthly traffic to 20. “1,000 to 30,000” traffic, on the other hand, is much better. Ask for client names. While some clients ask their SEOs to sign an NDA and not disclose their collaboration, most don’t. If an SEO can’t name a single client they’ve worked with in the past, that’s a red flag. Make sure they have the right experience. Global and local SEO have very different processes. Make sure that the SEO has experience with the type of SEO you need. Make sure you’re looking for the right candidate. SEO pros can be content writers, link-builders, web developers, or all of the above simultaneously. Make sure you understand which one you need before making the hire. If you’re looking for someone to oversee your content ops, you shouldn’t hire a technical SEO expert. Look for SEO pros in the right places. Conventional job boards are overrated. Post your job ads on SEO communities instead. E.g. this sub, bigseo, SEO Signals Facebook group, etc. SEO Tip #32. Blog Post Not Ranking? Follow This Checklist I wanted to format the post natively for Reddit, but it’s just SO much better on Notion. Tl;dr, the checklist covers every reason your post might not be ranking: Search intent mismatch. Inferior content. Lack of internal linking. Lack of backlinks. And the like. Checklist URL at the intro of the post. SEO Tip #33. Avoid BS Link-Building Tactics The only type of link-building that works is building proper, quality links from websites with a good backlink profile and decent organic traffic. Here’s what DOESN’T work: Blog comment links Forum spam links Drive-by Reddit comment/post links Web 2.0 links Fiverr “100 links for 10 bucks” bs If your “SEO agency” says they’re doing any of the above instead of actually trying to build you links from quality websites, you’re being scammed. SEO Tip #34. Know When to Use 301 and 302 Redirects When doing redirects, it’s very important to know the distinction between these two. 301 is a permanent page redirect and passes on link juice. If you’re killing off a page that has backlinks, it’s better to 301 it to your homepage so that you don’t lose the link juice. If you simply delete a page, it’s going to be a 404, and the backlink juice is lost forever. 302 is a temporary page redirect and doesn’t pass on link juice. If the redirect is temporary, you do a 302. E.g. you want to test how well a new page is going to perform w/ your audience. SEO Tip #35. Social Signals Matter (But Not How You Think) Social signals are NOT a ranking factor. And yet, they can help your content rank on Google’s front page. Wondering what the hell am I talking about? Here’s what’s up: As I said, social signals are not a ranking factor. It’s not something Google takes into consideration to decide whether your article should rank or not. That said, social signals CAN lead to your article ranking better. Let’s say your article goes viral and gets around 20k views within a week. A chunk of these viewers are going to forget your domain/link and they’re going to look up the topic on Google via your chosen keyword + your brand name. The amount of people looking for YOUR keyword and exclusively picking your result over others is going to make Google think that your content is satisfying search intent better than the rest, and thus, reward you with better ranking. SEO Tip #36. Run Remarketing Ads to Lift Organic Traffic Conversions Not satisfied with your conversion rates? You can use Facebook ads to help increase them. Facebook allows you to do something called “remarketing.” This means you can target anyone that visited a certain page (or multiple pages) on your website and serve them ads on Facebook. There are a TON of ways you can take advantage of this. For example, you can target anyone that landed on a high buyer intent page and serve them ads pitching your product or a special offer. Alternatively, you can target people who landed on an educational blog post and offer them something to drive them down the funnel. E.g. free e-book or white paper to teach them more about your product or service. SEO Tip #37. Doing Local SEO? Follow These Tips Local SEO is significantly different from global SEO. Here’s how the two differ (and what you need to do to drive local SEO results): You don’t need to publish content. For 95% of local businesses, you only want to rank for keywords related to your services/products, you don’t actually need to create educational content. You need to focus more on reviews and citation-building. One of Google Maps’ biggest ranking factors is the of reviews your business has. Encourage your customers to leave a review if they enjoyed your product/service through email or real-life communication. You need to create service pages for each location. As a local business, your #1 priority is to rank for keywords around your service. E.g. If you're a personal injury law firm, you want to optimize your homepage for “personal injury law firm” and then create separate pages for each service you provide, e.g. “car accident lawyer,” “motorcycle injury law firm,” etc. Focus on building citations. Being listed on business directories makes your business more trustworthy for Google. BrightLocal is a good service for this. You don’t need to focus as much on link-building. As local SEO is less competitive than global, you don’t have to focus nearly as much on building links. You can, in a lot of cases, rank with the right service pages and citations. SEO Tip #38. Stop Ignoring the Outreach Emails You’re Getting (And Use Them to Build Your Own Links) Got a ton of people emailing you asking for links? You might be tempted to just send them all straight to spam, and I don’t blame you. Outreach messages like “Hey Dr Jigsaw, your article is A+++ amazing! ...can I get a backlink?” can get hella annoying. That said, there IS a better way to deal with these emails: Reply and ask for a link back. Most of the time, people who send such outreach emails are also doing heavy guest posting. So, you can ask for a backlink from a 3rd-party website in exchange for you mentioning their link in your article. Win-win! SEO Tip #39. Doing Internal Linking for a Large Website? This’ll Help Internal linking can get super grueling once you have hundreds of articles on your website. Want to make the process easier? Do this: Pick an article you want to interlink on your website. For the sake of the example, let’s say it’s about “business process improvement.” Go on Google and look up variations of this keyword mentioned on your website. For example: Site:\[yourwebsite\] “improve business process” Site:\[yourwebsite\] “improve process” Site:\[yourwebsite\] “process improvement” The above queries will find you the EXACT articles where these keywords are mentioned. Then, all you have to do is go through them and include the links. SEO Tip #40. Got a Competitor Copying Your Content? File a DMCA Notice Fun fact - if your competitors are copying your website, you can file a DMCA notice with Google. That said, keep in mind that there are consequences for filing a fake notice.

I got fired due to automation — lessons learned. Two-month overview.
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WebsterPepsterThis week

I got fired due to automation — lessons learned. Two-month overview.

UPD: Guys, I'm not promoting myself as some of the redditors decided. That's why to deal with contradictions I'll do next things: make additional post with short review and description of the general tools and processes you could apply. help only those who have already written me. So I won't answer on new offers or DMs. As mentioned, damn robots have taken my job. PRE-HISTORY During Covid times, I found myself without my offline job, and since I was interested in marketing and SMM, I began searching for a job there. Completed free Google and Udemy courses and finally landed my first SMM manager position with a business owner. He had several projects so, finally, I started managing three Twitter accounts, two Facebook accs, two IGs, and one TikTok. I handled posting, content editing and responding routine, while freelancers usually took care of video creation for IG and TT. THE STORY ITSELF Things took a turn for the worse in April when my employer introduced ChatGPT and Midjourney, tools I was already using. The owner insisted on integrating them into the workflow, and my wages took a 20% hit. I thought I could roll with it, but it was just the beginning. By midsummer, the owner implemented second-layer AI tools like Visla, Pictory, and Woxo for video (bye freelancers, lol), as well as TweetHunter, Jasper, and Perplexity for content. Midjourney and Firefly joined for image generation. All together, my paycheck was slashed by 50%. Finally, at the end of October, my boss told me he automated stuff with Zapier, cutting costs that way. Additionally, he adopted MarketOwl, autoposting tool for Twitter, and SocialBee for Facebook. He stated that he didn’t need me, as by now he could manage the social media accounts himself. I feel so pissed then and even thought that there's no point in searching for similar jobs. HOW I SPENT TWO MONTHS Well, for the first two weeks, I did nothing but being miserable, drinking and staring at the wall. My gf said it's unbearable and threatened to leave if I not pull myself together. It was not the final push, but definitely made me rethink things. So I decided to learn more about the capabilities of these automation covers and eventually became an AI adviser for small businesses. It's ironic that now I sometimes earn money advising on how to optimize marketing, possibly contributing to other people's job loss. FINAL THOUGHTS I am fully aware of the instability of such a job and have invested my last savings in taking an online marketing course at Columbia to gain more marketing experience and got something more stable afterwards. Message for mods: I'm not promoting myself or anything mentioned here; just sharing the experience that someone might find helpful.

Started a content marketing agency 8 years ago - $0 to $7,863,052 (2025 update)
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mr_t_forhireThis week

Started a content marketing agency 8 years ago - $0 to $7,863,052 (2025 update)

Hey friends, My name is Tyler and for the past 8 years, I’ve been documenting my experience building a content marketing agency called Optimist. Year 1 — 0 to $500k ARR Year 2 — $500k to $1MM ARR Year 3 — $1MM ARR to $1.5MM(ish) ARR Year 4 — $3,333,686 Revenue Year 5 — $4,539,659 Revenue Year 6 — $5,974,324 Revenue Year 7 - $6,815,503 Revenue (Edit: Seems like links are banned now. You can check my post history for all of my previous updates with lessons and learnings.) How Optimist Works First, an overview/recap of the Optimist business model: We operate as a “collective” of full time/professional freelancers Everyone aside from me is a contractor Entirely remote/distributed team We pay freelancers a flat fee for most work, working out to roughly $65-100/hour. Clients pay us a flat monthly fee for full-service content marketing (research, strategy, writing, editing, design/photography, reporting and analytics, targeted linkbuilding, and more)\ Packages range in price from \~$10-20k/mo \This is something we are revisiting now* The Financials In 2024, we posted $1,032,035.34 in revenue. This brings our lifetime revenue to $7,863,052. Here’s our monthly revenue from January 2017 to December of 2024. (Edit: Seems like I'm not allowed to link to the chart.) The good news: Revenue is up 23% YoY. EBITDA in Q4 trending up 1-2 points. We hosted our first retreat in 4 years, going to Ireland with about half the team. The bad news: Our revenue is still historically low. At $1MM for the year, we’re down about 33% from our previous years over $1.5MM. Revenue has been rocky. It doesn’t feel like we’ve really “recovered” from the bumps last year. The trend doesn’t really look great. Even though, anecdotally, it feels like we are moving in a good direction. EBITDA is still hovering at around 7%. Would love to get that closer to 20%. (For those who may ask: I’m calculating EBITDA after paying taxes and W2 portion of my income.) — Almost every year, my update starts the same way: This has been a year of growth and change. Both for my business—and me personally. 2024 was no different. I guess that tells you something about entrepreneurship. It’s a lot more like sailing a ship than driving a car. You’re constantly adapting, tides are shifting, and any blip of calm is usually just a moment before the next storm. As with past years, there’s a lot to unpack from the last 12 months. Here we go again. Everything is Burning In the last 2 years, everything has turned upside down in the world of content and SEO. Back in 2020, we made a big decision to re-position the agency. (See post history) We decided to narrow our focus to our most successful, profitable, and consistent segment of clients and re-work our entire operation to focus on serving them. We defined our ICP as: \~Series A ($10mm+ funding) with 6-12 months runway to scale organic as a channel Product-led company with “simple” sales cycle involving fewer stakeholders Demonstrable opportunity to use SEO to drive business growth Our services: Content focused on growing organic search (SEO) Full-service engagements that included research, planning, writing, design, reporting And our engagement structure: Engaged directly with an executive; ownership over strategy and day-to-day execution 1-2 points of contact or stakeholders Strategic partner that drives business growth (not a service vendor who makes content) Most importantly, we decided that we were no longer going to offer a broader range of content that we used to sell. That included everything from thought leadership content to case studies and ebooks. We doubled-down on “SEO content” for product-led SaaS companies. And this worked phenomenally for us. We started bringing on more clients than ever. We developed a lot of internal system and processes that helped us scale and take on more work than we’ve ever had and drive great outcomes for our ideal clients. But in 2023 and 2024, things started going awry. One big change, of course, was the rise of AI. Many companies and executives (and writers) feel that AI can write content just as well as an agency like ours. That made it a lot harder to sell a $10,000 per month engagement when they feel like the bulk of the work could be “done for free.” (Lots of thoughts on this if you want my opinions.) But it wasn’t just that. Google also started tinkering with their algorithm, introducing new features like AI Overviews, and generally changing the rules of the game. This created 3 big shifts in our world: The perceived value of content (especially “SEO content”) dropped dramatically in many people’s minds because of AI’s writing capabilities SEO became less predictable as a source of traffic and revenue It’s harder than ever for startups and smaller companies to rank for valuable keywords (let alone generate any meaningful traffic or revenue from them) The effect? The middle of the content market has hollowed out. People—like us—providing good, human-crafted content aimed on driving SEO growth saw a dramatic decline in demand. We felt it all year. Fewer and fewer leads. The leads we did see usually scoffed at our prices. They were indexing us against the cost of content mills and mass-produced AI articles. It was a time of soul-searching and looking for a way forward. I spent the first half of the year convinced that the only way to survive was to run toward the fire. We have to build our own AI workflows. We have to cut our rates internally. We have to get faster and cheaper to stay competitive with the agencies offering the same number of deliverables for a fraction of our rates. It’s the only way forward. But then I asked myself a question… Is this the game I actually want to play? As an entrepreneur, do I want to run a business where I’m competing mostly on price and efficiency rather than quality and value? Do I want to hop into a race toward cheaper and cheaper content? Do I want to help people chase a dwindling amount of organic traffic that’s shrinking in value? No. That’s not the game I want to play. That’s not a business I want to run. I don’t want to be in the content mill business. So I decided to turn the wheel—again. Repositioning Part II: Electric Boogaloo What do you do when the whole world shifts around you and the things that used to work aren’t working anymore? You pivot. You re-position the business and move in another direction. So that’s what we decided to do. Again. There was only one problem: I honestly wasn’t sure what opportunities existed in the content marketing industry outside of what we were already doing. We lived in a little echo chamber of startups and SEO. It felt like the whole market was on fire and I had fight through the smoke to find an escape hatch. So I started making calls. Good ol’ fashioned market research. I reached out to a few dozen marketing and content leaders at a bunch of different companies. I got on the phone and just asked lots of questions about their content programs, their goals, and their pain points. I wanted to understand what was happening in the market and how we could be valuable. And, luckily, this process really paid off. I learned a lot about the fragmentation happening across content and how views were shifting. I noticed key trends and how our old target market really wasn’t buying what we were selling. Startups and small companies are no longer willing to invest in an agency like ours. If they were doing content and SEO at all, they were focused entirely on using AI to scale output and minimize costs. VC money is still scarce and venture-backed companies are more focused on profitability than pure growth and raising another round. Larger companies (\~500+ employees) are doing more content than ever and drowning in content production. They want to focus on strategy but can barely tread water keeping up with content requests from sales, demand gen, the CEO, and everyone else. Many of the companies still investing in content are looking at channels and formats outside of SEO. Things like thought leadership, data reports, interview-driven content, and more. They see it as a way to stand out from the crowd of “bland SEO content.” Content needs are constantly in flux. They range from data reports and blog posts to product one-pagers. The idea of a fixed-scope retainer is a total mismatch for the needs of most companies. All of this led to the logical conclusion: We were talking to the wrong people about the wrong things\.\ Many companies came to one of two logical conclusions: SEO is a risky bet, so it’s gotta be a moonshot—super-low cost with a possibility for a big upside (i.e., use AI to crank out lots of content. If it works, great. If it doesn’t, then at least we aren’t out much money.) SEO is a risky bet, so we should diversify into other strategies and channels to drive growth (i.e., shift our budget from SEO and keyword-focused content to video, podcasts, thought leadership, social, etc) Unless we were going to lean into AI and dramatically cut our costs and rates, our old buyers weren’t interested. And the segment of the market that needs our help most are looking primarily for production support across a big range of content types. They’re not looking for a team to run a full-blown program focused entirely on SEO. So we had to go back to the drawing board. I’ve written before about our basic approach to repositioning the business. But, ultimately it comes down to identifying our unique strengths as a team and then connecting them to needs in the market. After reviewing the insights from my discussions and taking another hard look at our business and our strengths, I decided on a new direction: Move upmarket: Serve mid-size to enterprise businesses with \~500-5,000 employees instead of startups Focus on content that supports a broader range of business goals instead of solely on SEO and organic growth (e.g., sales, demand gen, brand, etc) Shift back to our broader playbook of content deliverables, including thought leadership, data studies, and more Focus on content execution and production to support an internally-directed content strategy across multiple functions In a way, it’s sort of a reverse-niche move. Rather than zooming in specifically on driving organic growth for startups, we want to be more of an end-to-end content production partner that solves issues of execution and operations for all kinds of content teams. It’s early days, but the response here has been promising. We’ve seen an uptick in leads through Q4. And more companies in our pipeline fit the new ICP. They’re bigger, often have more budget. (But they move more slowly). We should know by the end of the quarter if this maneuver is truly paying off. Hopefully, this will work out. Hopefully our research and strategy are right and we’ll find a soft landing serving a different type of client. If it doesn’t? Then it will be time to make some harder decisions. As I already mentioned, I’m not interested in the race to the bottom of AI content. And if that’s the only game left in town, then it might be time to think hard about a much bigger change. — To be done: Build new content playbooks for expanded deliverables Build new showcase page for expanded deliverables Retooling the Operation It’s easy to say we’re doing something new. It’s a lot harder to actually do it—and do it well. Beyond just changing our positioning, we have to do open-heart surgery on the entire content operation behind the scenes. We need to create new systems that work for a broader range of content types, formats, and goals. Here’s the first rub: All of our workflows are tooled specifically for SEO-focused content. Every template, worksheet, and process that we’ve built and scaled in the last 5 years assumes that the primary goal of every piece of content is SEO. Even something as simple as requiring a target keyword is a blocker in a world where we’re not entirely focused on SEO. This is relatively easy to fix, but it requires several key changes: Update content calendars to make keywords optional Update workflows to determine whether we need an optimization report for each deliverable Next, we need to break down the deliverables into parts rather than a single line item. In our old system, we would plan content as a single row in a Content Calendar spreadsheet. It was a really wide sheet with lots of fields where we’d define the dimensions of each individual article. This was very efficient and simple to follow. But every article had the same overall scope when it came to the workflow. In Asana (our project management tool), all of the steps in the creation were strung together in a single task. We would create a few basic templates for each client, and then each piece would flow through the same steps: Briefing Writing Editing Design etc. If we had anything that didn’t fit into the “standard” workflow, we’d just tag it in the calendar with an unofficial notation \[USING BRACKETS\]. It worked. But it wasn’t ideal. Now we need the steps to be more modular. Imagine, for example, a client asks us to create a mix of deliverables: 1 article with writing + design 1 content brief 1 long-form ebook with an interview + writing + design Each of these would require its own steps and its own workflow. We need to break down the work to accommodate for a wider variety of workflows and variables. This means we need to update the fields and structure of our calendar to accommodate for the new dimensions—while also keeping the planning process simple and manageable. This leads to the next challenge: The number of “products” that we’re offering could be almost infinite. Just looking at the example scope above, you can mix and match all of these different building blocks to create a huge variety of different types of work, each requiring its own workflow. This is part of the reason we pivoted away from this model to focus on a productized, SEO-focused content service back in 2020. Take something as simple as a case study. On the surface, it seems like one deliverable that can be easily scoped and priced, right? Well, unpack what goes into a case study: Is there already source material from the customer or do we need to conduct an interview? How long is it? Is it a short overview case study or a long-form narrative? Does it need images and graphics? How many? Each of these variables opens up 2-3 possibilities. And when you combine them, we end up with something like 10 possible permutations for this single type of deliverable. It gets a bit messy. But not only do we have to figure out how to scope and price all for all of these variables, we also have to figure out how to account for these variables in the execution. We have to specify—for every deliverable—what type it is, how long, which steps are involved and not involved, the timeline for delivery, and all of the other factors. We’re approaching infinite complexity, here. We have to figure out a system that allows for a high level of flexibility to serve the diverse needs of our clients but is also productized enough that we can build workflows, process, and templates to deliver the work. I’ve spent the last few months designing that system. Failed Attempt #1: Ultra-Productization In my first pass, I tried to make it as straight forward as possible. Just sit down, make a list of all of the possible deliverables we could provide and then assign them specific scopes and services. Want a case study? Okay that’ll include an interview, up to 2,000 words of content, and 5 custom graphics. It costs $X. But this solution quickly fell apart when we started testing it against real-world scenarios. What if the client provided the brief instead of us creating one? What if they didn’t want graphics? What if this particular case study really needs to be 3,000 words but all of the others should be 2,000? In order for this system to work, we’d need to individual scope and price all of these permutations of each productized service. Then we’d need to somehow keep track of all of these and make sure that we accurately scope, price, and deliver them across dozens of clients. It’s sort of like a restaurant handling food allergies by creating separate versions of every single dish to account for every individual type of allergy. Most restaurants have figured out that it makes way more sense to have a “standard” and an “allergy-free” version. Then you only need 2 options to cover 100% of the cases. Onto the next option. Failed Attempt #2: Deliverable-Agnostic Services Next, I sat down with my head of Ops, Katy, to try to map it out. We took a big step back and said: Why does the deliverable itself even matter? At the end of the day, what we’re selling is just a few types of work (research, writing, editing, design, etc) that can be packaged up in an infinite number of ways. Rather than try to define deliverables, shouldn’t we leave it open ended for maximum flexibility? From there, we decided to break down everything into ultra-modular building blocks. We started working on this super complex system of modular deliverables where we would have services like writing, design, editing, etc—plus a sliding scale for different scopes like the length of writing or the number of images. In theory, it would allow us to mix and match any combination of services to create custom deliverables for the client. In fact, we wanted the work to be deliverable-agnostic. That way we could mold it to fit any client’s needs and deliver any type of content, regardless of the format or goal. Want a 5,000-word case study with 15 custom graphics? That’ll be $X. Want a 2,000-word blog post with an interview and no visuals? $Y. Just want us to create 10 briefs, you handle the writing, and we do design? It’s $Z. Again, this feels like a reasonable solution. But it quickly spiraled out of amuck. (That’s an Office reference.) For this to work, we need to have incredibly precise scoping process for every single deliverable. Before we can begin work (or even quote a price), we need to know pretty much the exact word count of the final article, for example. In the real world? This almost never happens. The content is as long as the content needs to be. Clients rarely know if the blog post should be 2,000 words or 3,000 words. They just want good content. We have a general ballpark, but we can rarely dial it in within just 1,000 words until we’ve done enough research to create the brief. Plus, from a packaging and pricing perspective, it introduces all kind of weird scenarios where clients will owe exactly $10,321 for this ultra-specific combination of services. We were building an open system that could accommodate any and all types of potential deliverables. On the face that seems great because it makes us incredibly flexible. In reality, the ambiguity actually works against us. It makes it harder for us to communicate to clients clearly about what they’ll get, how much it will cost, and how long it will take. That, of course, also means that it hurts our client relationships. (This actually kind of goes back to my personal learnings, which I’ll mention in a bit. I tend to be a “let’s leave things vague so we don’t have to limit our options” kind of person. But I’m working on fixing this to be more precise, specific, and clear in everything that we do.) Dialing It In: Building a Closed System We were trying to build an open system. We need to build a closed system. We need to force clarity and get specific about what we do, what we don’t do, and how much it all costs. Then we need a system to expand on that closed system—add new types of deliverables, new content playbooks, and new workflows if and when the need arises. With that in mind, we can start by mapping out the key dimensions of any type of deliverable that we would ever want to deliver. These are the universal dimensions that determine the scope, workflow, and price of any deliverable—regardless of the specific type output. Dimensions are: Brief scope Writing + editing scope Design scope Interview scope Revision (rounds) Scope, essentially, just tells us how many words, graphics, interviews, etc are required for the content we’re creating. In our first crack at the system, we got super granular with these scopes. But to help force a more manageable system, we realized that we didn’t need tiny increments for most of this work. Instead, we just need boundaries—you pay $X for up to Y words. We still need some variability around the scope of these articles. Obviously, most clients won’t be willing to pay the same price for a 1,000-word article as a 10,000-word article. But we can be smarter about the realistic break points. We boiled it down to the most common ranges: (Up to) 250 words 1,000 words 3,000 words 6,000 words 10,000 words This gives us a much more manageable number of variables. But we still haven’t exactly closed the system. We need one final dimension: Deliverable type. This tells us what we’re actually building with these building blocks. This is how we’ll put a cap on the potentially infinite number of combinations we could offer. The deliverable type will define what the final product should look like (e.g., blog post, case study, ebook, etc). And it will also give us a way to put standards and expectations around different types of deliverables that we want to offer. Then we can expand on this list of deliverables to offer new services. In the mean time, only the deliverables that we have already defined are, “on the menu,” so to speak. If a client comes to us and asks for something like a podcast summary article (which we don’t currently offer), we’ll have to either say we can’t provide that work or create a new deliverable type and define the dimensions of that specific piece. But here’s the kicker: No matter the deliverable type, it has to still fit within the scopes we’ve already defined. And the pricing will be the same. This means that if you’re looking for our team to write up to 1,000 words of content, it costs the same amount—whether it’s a blog post, an ebook, a LinkedIn post, or anything else. Rather than trying to retool our entire system to offer this new podcast summary article deliverable, we’ll just create the new deliverable type, add it to the list of options, and it’s ready to sell with the pre-defined dimensions we’ve already identified. To do: Update onboarding workflow Update contracts and scope documents Dial in new briefing process Know Thyself For the last year, I’ve been going through personal therapy. (Huge shout out to my wife, Laura, for her support and encouragement throughout the process.) It’s taught me a lot about myself and my tendencies. It’s helped me find some of my weaknesses and think about how I can improve as a person, as a partner, and as an entrepreneur. And it’s forced me to face a lot of hard truths. For example, consider some of the critical decisions I’ve made for my business: Unconventional freelance “collective” model No formal management structure Open-ended retainers with near-infinite flexibility General contracts without defined scope “Take it or leave it” approach to sales and marketing Over the years, I’ve talked about almost everything on this list as a huge advantage. I saw these things as a reflection of how I wanted to do things differently and better than other companies. But now, I see them more as a reflection of my fears and insecurities. Why did I design my business like this? Why do I want so much “flexibility” and why do I want things left open-ended rather than clearly defined? One reason that could clearly explain it: I’m avoidant. If you’re not steeped in the world of therapy, this basically means that my fight or flight response gets turned all the way to “flight.” If I’m unhappy or uncomfortable, my gut reaction is usually to withdraw from the situation. I see commitment and specificity as a prelude to future conflict. And I avoid conflict whenever possible. So I built my business to minimize it. If I don’t have a specific schedule of work that I’m accountable for delivering, then we can fudge the numbers a bit and hope they even out in the end. If I don’t set a specific standard for the length of an article, then I don’t have to let the client know when their request exceeds that limit. Conflict….avoided? Now, that’s not to say that everything I’ve built was wrong or bad. There is a lot of value in having flexibility in your business. For example, I would say that our flexible retainers are, overall, an advantage. Clients have changing needs. Having flexibility to quickly adapt to those needs can be a huge value add. And not everything can be clearly defined upfront (at least not without a massive amount of time and work just to decide how long to write an article). Overly-rigid structures and processes can be just as problematic as loosey-goosey ones. But, on the whole, I realized that my avoidant tendencies and laissez faire approach to management have left a vacuum in many areas. The places where I avoided specificity were often the places where there was the most confusion, uncertainty, and frustration from the team and from clients. People simply didn’t know what to expect or what was expected of them. Ironically, this often creates the conflict I’m trying to avoid. For example, if I don’t give feedback to people on my team, then they feel uneasy about their work. Or they make assumptions about expectations that don’t match what I’m actually expecting. Then the client might get upset, I might get upset, and our team members may be upset. Conflict definitely not avoided. This happens on the client side, too. If we don’t define a specific timeline when something will be delivered, the client might expect it sooner than we can deliver—creating frustration when we don’t meet their expectation. This conflict actually would have been avoided if we set clearer expectations upfront. But we didn’t do that. I didn’t do that. So it’s time to step up and close the gaps. Stepping Up and Closing the Gaps If I’m going to address these gaps and create more clarity and stability, I have to step up. Both personally and professionally. I have to actually face the fear and uncertainty that drives me to be avoidant. And then apply that to my business in meaningful ways that aren’t cop-out ways of kinda-sorta providing structure without really doing it. I’ve gotta be all in. This means: Fill the gaps where I rely on other people to do things that aren’t really their job but I haven’t put someone in place to do it Set and maintain expectations about our internal work processes, policies, and standards Define clear boundaries on things like roles, timelines, budgets, and scopes Now, this isn’t going to happen overnight. And just because I say that I need to step up to close these gaps doesn’t mean that I need to be the one who’s responsible for them (at least not forever). It just means that, as the business leader, I need to make sure the gaps get filled—by me or by someone else who has been specifically charged with owning that part of the operation. So, this is probably my #1 focus over the coming quarter. And it starts by identifying the gaps that exist. Then, step into those gaps myself, pay someone else to fill that role, or figure out how to eliminate the gap another way. This means going all the way back to the most basic decisions in our business. One of the foundational things about Optimist is being a “different kind” of agency. I always wanted to build something that solved for the bureaucracy, hierarchy, and siloed structure of agencies. If a client has feedback, they should be able to talk directly to the person doing the work rather than going through 3 layers of account management and creative directors. So I tried to be clever. I tried to design all kinds of systems and processes that eliminated these middle rungs. (In retrospect, what I was actually doing was designing a system that played into my avoidant tendencies and made it easy to abdicate responsibility for lots of things.) Since we didn’t want to create hierarchy, we never implemented things like Junior and Senior roles. We never hired someone to manage or direct the individual creatives. We didn’t have Directors or VPs. (Hell, we barely had a project manager for the first several years of existence.) This aversion to hierarchy aligned with our values around elevating ownership and collective contribution. I still believe in the value a flat structure. But a flat structure doesn’t eliminate the complexity of a growing business. No one to review writers and give them 1:1 feedback? I guess I’ll just have to do that….when I have some spare time. No Content Director? Okay, well someone needs to manage our content playbooks and roll out new ones. Just add it to my task list. Our flat structure didn’t eliminate the need for these roles. It just eliminated the people to do them. All of those unfilled roles ultimately fell back on me or our ops person, Katy. Of course, this isn’t the first time we’ve recognized this. We’ve known there were growing holes in our business as it’s gotten bigger and more complex. Over the years, we’ve experimented with different ways to solve for it. The Old Solution: Distributed Ops One system we designed was a “distributed ops” framework. Basically, we had one person who was the head of ops (at the time, we considered anything that was non-client-facing to be “ops”). They’d plan and organize all of the various things that needed to happen around Optimist. Then they’d assign out the work to whoever was able to help. We had a whole system for tying this into the our profit share and even gave people “Partner” status based on their contributions to ops. It worked—kinda. One big downfall is that all of the tasks and projects were ad hoc. People would pick up jobs, but they didn’t have much context or expertise to apply. So the output often varied. Since we were trying to maintain a flat structure, there was minimal oversight or management of the work. In other words, we didn’t always get the best results. But, more importantly, we still didn’t close all of the gaps entirely. Because everything was an ad-hoc list of tasks and projects, we never really had the “big picture” view of everything that needed to be done across the business. This also meant we rarely had clarity on what was important, what was trivial, and what was critical. We need a better system. Stop Reinventing the Wheel (And Create a Damn Org Chart) It’s time to get serious about filling the gaps in our business. It can’t be a half-fix or an ad hoc set of projects and tasks. We need clarity on the roles that need to be filled and then fill them. The first step here is to create an org chart. A real one. Map out all of the jobs that need to be done for Optimist to be successful besides just writers and designers. Roles like: Content director Design director SEO manager Reporting Finance Account management Business development Sales Marketing Project management It feels a bit laughable listing all of these roles. Because most are either empty or have my name attached to them. And that’s the problem. I can’t do everything. And all of the empty roles are gaps in our structure—places where people aren’t getting the direction, feedback, or guidance they need to do their best work. Or where things just aren’t being done consistently. Content director, for example, should be responsible for steering the output of our content strategists, writers, and editors. They’re not micromanaging every deliverable. But they give feedback, set overall policy, and help our team identify opportunities to get better. Right now we don’t have anyone in that role. Which means it’s my job—when I have time. Looking at the org chart (a real org chart that I actually built to help with this), it’s plain as day how many roles look like this. Even if we aren’t going to implement a traditional agency structure and a strict hierarchy, we still need to address these gaps. And the only way for that to happen is face the reality and then create a plan to close the gaps. Now that we have a list of theoretical roles, we need to clearly define the responsibilities and boundaries of those roles to make sure they cover everything that actually needs to happen. Then we can begin the process of delegating, assigning, hiring, and otherwise addressing each one. So that’s what I need to do. To be done: Create job descriptions for all of the roles we need to fill Hire Biz Dev role Hire Account Lead role(s) Hire Head of Content Playing Offense As we move into Q1 of 2025 and I reflect on the tumultuous few years we’ve had, one thought keeps running through my head. We need to play offense. Most of the last 1-2 years was reacting to changes that were happening around us. Trying to make sense and chart a new path forward. Reeling. But what I really want—as a person and as an entrepreneur—is to be proactive. I want to think and plan ahead. Figure out where we want to go before we’re forced to change course by something that’s out of our control. So my overarching focus for Q1 is playing offense. Thinking longer term. Getting ahead of the daily deluge and creating space to be more proactive, innovative, and forward thinking. To do: Pilot new content formats Audit and update our own content strategy Improve feedback workflows Build out long-term roadmap for 1-2 years for Optimist Final Note on Follow-Through and Cadence In my reflection this year, one of the things I’ve realized is how helpful these posts are for me. I process by writing. So I actually end up making a lot of decisions and seeing things more clearly each time I sit down to reflect and write my yearly recap. It also gives me a space to hold myself accountable for the things I said I would do. So, I’m doing two things a bit differently from here on out. First: I’m identifying clear action items that I’m holding myself accountable for getting done in the next 3 months (listed in the above sections). In each future update, I’ll do an accounting of what I got done and what wasn’t finished (and why). Second: I’m going to start writing shorter quarterly updates. This will gives me more chances each year to reflect, process, and make decisions. Plus it gives me a shorter feedback loop for the action items that I identified above. (See—playing offense.) — Okay friends, enemies, and frenemies. This is my first update for 2025. Glad to share with y’all. And thanks to everyone who’s read, commented, reached out, and shared their own experiences over the years. We are all the accumulation of our connections and our experiences. As always, I will pop in to respond to comments and answer questions. Feel free to share your thoughts, questions, and general disdain down below. Cheers, Tyler

Made $19.2k this month, and just surpassed $1000 the last 24 hours. What I did and what's next.
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dams96This week

Made $19.2k this month, and just surpassed $1000 the last 24 hours. What I did and what's next.

It's the first time I hit $1000+ in 24 hours and I had no one to share it with (except you guys). I'm quite proud of my journey, and I would have thought that making $1000 in a day would make me ecstatic, but actually it's not the case. Not sure if it's because my revenue has grown by increment step so I had time to "prepare" myself to achieve this at one point, or just that I'm nowhere near my goal of 100k/month so that I'm not that affected by it. But it's crazy to think that my goal was to make 100$ daily at the end of 2024. So for those who don't know me (I guess most of you), I build mobile apps and ship them as fast as I can. Most of them are in the AI space. I already made a post here on how I become a mobile app developer so you can check it for more details, but essentially here's what I did : Always loved creating my own things and solve problems Built multiple YouTube channels since I was 15 (mobile gaming actually) that all worked great (but it was too niche so not that scalable, didn't like that) Did a few businesses here and there (drop shopping, selling merch to school, etc) Finished my master's degree in engineering about 2 years ago Worked a moment in a famous watch industry company and saw my potential. The combo of health issues, fixed salary (although it was quite a lot), and me wanting to be an entrepreneur made me leave the company. Created a TikTok account in mobile tech (got 10+ million views the 1st 3 days), manage to grow it to 200k subs in about 3 months Got plenty of collabs for promoting mobile apps (between $500 - $2000 for a collab) Said fuck it I should do my own apps and market them on my TikTok instead of doing collabs Me wanting to build my own apps happened around May-June 2023. Started my TikTok in Feb 2023. At this point I had already 150k+ subs on TikTok. You guys need to know that I suck at coding big time. During my studies I tried to limit as much as I could coding because I was a lazy bast*rd, even though I knew it would come to bite me in the ass one day. But an angel appeared to me in broad daylight, that angel was called GPT-4. I subscribed for 20$/month to get access, and instantly I saw the potential of AI and how much it could help me. Last year GPT-4 was ahead of its time and could already code me basic apps. I had already a mac so I just downloaded Xcode and that was it. My 1st app was a wallpaper app, and I kid you not 90% of it was made by AI. Yes sometimes I had to try again and again with different prompts but it was still so much faster compared to if I had to learn coding from scratch and write code with my own hands. The only thing I didn't do was implement the in app purchase, from which I find a guy on Fiverr to do it for me for 50$. After about 2 months of on-off coding, my first app was ready to be launched. So it was launched, had a great successful launch without doing any videos at that point (iOS 17 was released and my app was the first one alongside another one to offer live wallpapers for iOS 17. I knew that there was a huge app potential there when iOS 17 was released in beta as Apple changed their live wallpaper feature). I Then made a video a few weeks after on my mobile tiktok channel, made about 1 million views in 48 hours, brought me around 40k additional users. Was top 1 chart in graphism and design category for a few weeks (in France, as I'm French so my TikTok videos are in French). And was top 100 in that same category in 120+ countries. Made about 500$ ? Okay that was trash, but I had no idea to monetize the app correctly at that point. It was still a huge W to me and proved me that I could successfully launch apps. Then I learned ASO (App Store Optimization) in depth, searched on internet, followed mobile app developers on Twitter, checked YouTube videos, you name it. I was eager to learn more. I needed more. Then I just iterated, build my 2nd app in less than a month, my 3rd in 3 weeks and so on. I just build my 14th app in 3 days and is now in review. Everytime I manage to reuse some of my other app's code in my new one, which is why I can build them so much faster now. I know how to monetize my app better by checking out my competitors. I learn so much by just "spying" other apps. Funnily enough, I only made this one Tiktok video on my main account to promote my app. For all my other apps, I didn't do a single video where I showcase it, the downloads has only been thanks to ASO. I still use AI everyday. I'm still not good at coding (a bit better than when I started). I use AI to create my app icons (midjourney or the new AI model Flux which is great). I use figma + midjourney to create my App Store screenshots (and they actually look quite good). I use GPT-4o and Claude 3.5 Sonnet to code most of my apps features. I use gpt-4o to localize my app (if you want to optimize the number of downloads I strongly suggest localizing your app, it takes me about 10 minutes thanks to AI). Now what are my next goals ? To achieve the 100k/month I need to change my strategy a little. Right now the $20k/month comes from purely organic downloads, I didn't do any paid advertising. It will be hard for me to keep on launching new apps and rely on ASO to reach the 100k mark. The best bet to reach 100k is to collab with content creators and they create a viral video showcasing your app. Depending on the app it's not that easy, luckily some of my apps can be viral so I will need to find the right content creators. Second way is to try tiktok/meta ads, I can check (have checked) all the ads that have been made by my competitors (thank you EU), so what I would do is copy their ad concept and create similar ads than them. Some of them have millions in ad budget so I know they create high converting ads, so you don't need to try to create an ad creative from scratch. My only big fear is to get banned by Apple (for no reason of mine). In just a snap of a finger they can just ban you from the platform, that shit scares me. And you pretty much can't do anything. So that's about it for me. I'm quite proud of myself not going to lie. Have been battling so many health issues these past years where I just stay in bed all day I'm surprised to be able to make it work. Anyways feel free to ask questions. I hope it was interesting for some of you at least. PS: My new app was just approved by app review, let the app gods favor me and bring me many downloads ! Also forgot to talk about a potential $100k+ acquisition of one of my apps, but if that ever happens I'll make a post on it.

Switching Gears: Implementing AI for My Agency’s Marketing After a Decade
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Alarming_Management3This week

Switching Gears: Implementing AI for My Agency’s Marketing After a Decade

Hi there, I’ve been running a software development and design agency for the last 10 years, mainly focusing on building custom solutions for businesses and SaaS. For the last 2 years, I’ve consistently recommended that clients use AI technologies, especially for social media and content creation to generate traffic. Funny enough, I wasn’t practicing what I preached. Most of my client projects came from platforms like Upwork and word-of-mouth referrals from clients or people from networking events. Background I started my journey in 2014, switching from an employee to a freelancer. Within the first 10 months, my initial projects grew beyond what I could handle alone, prompting me to hire additional developers. This shift turned my role from a full-stack developer to a team lead and developer. Over the years, my focus has been a blend of tech and product. About five years ago, I realized the importance of design, leading me to adding designers to the agency to provide full-cycle service development—from product ideation and design to development, testing, launch, and support. I still continue to set up dedicated teams for some clients, maintaining a strong technical role as a tech lead, solution architect, and head product designer. To enhance my skills, I even completed UI/UX design courses to offer better product solutions. Despite these changes, building products has always been the easy part. The challenge was ensuring these client products didn’t end up in the graveyard due to poor product-market fit, often caused by inadequate marketing and sales strategies but more often just absence of them. (we are talking about startup and first time founders here 🙂 ) My Journey and Observations Advising Clients: I often found myself advising clients on increasing traffic for their SaaS products and crafting strategic marketing plans. Learning: I’ve gained most of my knowledge from consuming internet materials, courses, and blog posts and learning from successful client project launches. Realization: Despite giving this advice, I wasn’t applying these strategies to my own business, leading to low visits to my agency’s website. Initial Solution: Hiring a Marketer Hiring: I brought in a marketer with a solid background in content creating and interview video editing from an educational organization. Goal: The aim was to increase website visits through a comprehensive marketing strategy. Outcome: Although the content produced was high-quality and useful for pitching services, it didn’t lead to significant traffic increases. Issue: The marketer focused more on content creation rather than distribution channels, which limited effectiveness. Shift to AI-Driven Strategy Experiment: I decided to try using AI for content creation and distribution, which aligns with my agency’s specialization in design-driven development and AI integrations. Implementation plan: I will be generating all content with minimal edits using AI and implementing a strategic backlinking approach. Backlinking Strategy Initial Plan: I initially thought of hiring a specialist for backlinks. Realization: The costs and profiles of freelancers didn’t seem promising. Solution: I found AI-driven services for backlinks, which seem more efficient and cost-effective. Plan: My plan is to use these tools for programmatic SEO-driven AI-generated articles and third-party backlinking services over the next two to three months. Current Approach Management: This approach can be managed and executed by 1 person and monitored weekly, reducing human error and optimizing efficiency. I will start it myself and then replace myself with an editor with managing skills. Reflection: It’s a bit ironic and funny that it took me 10 years to start implementing these strategies in my own agency business, but I now feel more confident with AI and automation in place. Why Increase Website Visitors? You might ask, why do I want to increase the number of visitors to the site, and how can I ensure these visitors will be qualified? Hands-On Experience: To gain hands-on experience and perform this exercise effectively. Introduce Packaged Services: I want to introduce a set of low-cost packaged services tailored for non-technical people who want to build things for themselves - the DIY kits for non-technical folks. These services will provide a foundational template for them to build upon on top of existing established solutions such as Wix, Square Why am I Posting and Sharing Here? You might also wonder, why am I posting it here and sharing this? Well, I'm doing this more for myself. Most of my career, the things I’ve done have been behind the curtains. With this small project, I want to make it public to see the reaction of the community. Perhaps there will be good and smart suggestions offered, and maybe some insights or highlights of tools I wasn’t aware of or didn’t consider. I’ll keep sharing updates on this journey of website promotion, marketing, and SEO. My current goal is to reach 2,000 visits per month, which is a modest start. Looking forward to any thoughts or advice from this community! Disclaimer: This content was not generated by AI, but it was edited by it 😛

MVP + AI/ML Implementation/Integration - Done for you SaaS
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MVP + AI/ML Implementation/Integration - Done for you SaaS

In today’s fast-paced world, businesses need to stay ahead of the curve. Leveraging AI, ML, and Cloud technologies isn't just an option—it's a necessity. We specialize in providing cutting-edge AI/ML solutions and Cloud services that empower businesses to innovate, automate, and scale like never before. Why AI and ML Matter Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing industries by enabling systems to learn, adapt, and improve over time. Whether it's predicting customer behavior, automating tasks, or enhancing decision-making, AI and ML open up a world of possibilities. Key Benefits of AI and ML: Enhanced Decision-Making: Harness predictive analytics to make data-driven decisions. Automation: Streamline operations with intelligent automation. Personalization: Deliver tailored experiences to your customers, increasing engagement and loyalty. Efficiency: Reduce costs and time through optimized processes. How Cloud Services Drive Innovation The Cloud is the backbone of modern business infrastructure. It allows companies to be more agile, scalable, and resilient. With Cloud computing, businesses can access powerful tools and resources on-demand, without the need for significant upfront investment. Advantages of Cloud Services: Scalability: Easily scale up or down based on your business needs. Cost Efficiency: Pay only for the resources you use, minimizing overhead. Security: Benefit from the highest standards of data security and compliance. Flexibility: Access your applications and data from anywhere, anytime. Our Services We offer comprehensive services to help you harness the full potential of AI, ML, and Cloud technologies: AI and ML Solutions: We design and deploy custom AI/ML models that solve your specific business challenges. From natural language processing (NLP) to computer vision, we cover all aspects of AI/ML. Cloud Integration: We help you migrate to the Cloud, ensuring a smooth transition with minimal disruption. Whether it’s AWS, Azure, or Google Cloud, our experts have you covered. Data Analytics: Transform your data into actionable insights with advanced analytics tools and platforms. Custom Software Development: We build robust, scalable applications that integrate AI/ML capabilities and leverage the Cloud. DevOps: Automate your development pipeline and ensure continuous integration and delivery with our DevOps expertise. Why Choose Us? Expert Team: Our team of experienced professionals is well-versed in AI/ML, Cloud computing, and data analytics. End-to-End Solutions: From ideation to deployment, we offer full-cycle development services. Tailored Approach: We understand that every business is unique. We provide customized solutions that align with your specific goals. Proven Track Record: We’ve helped numerous businesses across industries to innovate and grow. Success Stories Retail Industry: Implemented an AI-driven recommendation engine that increased sales by 30%. Healthcare Sector: Developed an ML-based diagnostic tool that improved accuracy by 20%. Finance: Integrated Cloud-based AI solutions that reduced operational costs by 25%.

I run an AI automation agency (AAA). My honest overview and review of this new business model
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I run an AI automation agency (AAA). My honest overview and review of this new business model

I started an AI tools directory in February, and then branched off that to start an AI automation agency (AAA) in June. So far I've come across a lot of unsustainable "ideas" to make money with AI, but at the same time a few diamonds in the rough that aren't fully tapped into yet- especially the AAA model. Thought I'd share this post to shine light into this new business model and share some ways you could potentially start your own agency, or at the very least know who you are dealing with and how to pick and choose when you (inevitably) get bombarded with cold emails from them down the line. Foreword Running an AAA does NOT involve using AI tools directly to generate and sell content directly. That ship has sailed, and unless you are happy with $5 from Fiverr every month or so, it is not a real business model. Cry me a river but generating generic art with AI and slapping it onto a T-shirt to sell on Etsy won't make you a dime. At the same time, the AAA model will NOT require you to have a deep theoretical knowledge of AI, or any academic degree, as we are more so dealing with the practical applications of generative AI and how we can implement these into different workflows and tech-stacks, rather than building AI models from the ground up. Regardless of all that, common sense and a willingness to learn will help (a shit ton), as with anything. Keep in mind - this WILL involve work and motivation as well. The mindset that AI somehow means everything can be done for you on autopilot is not the right way to approach things. The common theme of businesses I've seen who have successfully implemented AI into their operations is the willingess to work with AI in a way that augments their existing operations, rather than flat out replace a worker or team. And this is exactly the train of thought you need when working with AI as a business model. However, as the field is relatively unsaturated and hype surrounding AI is still fresh for enterprises, right now is the prime time to start something new if generative AI interests you at all. With that being said, I'll be going over three of the most successful AI-adjacent businesses I've seen over this past year, in addition to some tips and resources to point you in the right direction. so.. WTF is an AI Automation Agency? The AI automation agency (or as some YouTubers have coined it, the AAA model) at its core involves creating custom AI solutions for businesses. I have over 1500 AI tools listed in my directory, however the feedback I've received from some enterprise users is that ready-made SaaS tools are too generic to meet their specific needs. Combine this with the fact virtually no smaller companies have the time or skills required to develop custom solutions right off the bat, and you have yourself real demand. I would say in practice, the AAA model is quite similar to Wordpress and even web dev agencies, with the major difference being all solutions you develop will incorporate key aspects of AI AND automation. Which brings me to my second point- JUST AI IS NOT ENOUGH. Rather than reducing the amount of time required to complete certain tasks, I've seen many AI agencies make the mistake of recommending and (trying to) sell solutions that more likely than not increase the workload of their clients. For example, if you were to make an internal tool that has AI answer questions based on their knowledge base, but this knowledge base has to be updated manually, this is creating unnecessary work. As such I think one of the key components of building successful AI solutions is incorporating the new (Generative AI/LLMs) with the old (programmtic automation- think Zapier, APIs, etc.). Finally, for this business model to be successful, ideally you should target a niche in which you have already worked and understand pain points and needs. Not only does this make it much easier to get calls booked with prospects, the solutions you build will have much greater value to your clients (meaning you get paid more). A mistake I've seen many AAA operators make (and I blame this on the "Get Rich Quick" YouTubers) is focusing too much on a specific productized service, rather than really understanding the needs of businesses. The former is much done via a SaaS model, but when going the agency route the only thing that makes sense is building custom solutions. This is why I always take a consultant-first approach. You can only build once you understand what they actually need and how certain solutions may impact their operations, workflows, and bottom-line. Basics of How to Get Started Pick a niche. As I mentioned previously, preferably one that you've worked in before. Niches I know of that are actively being bombarded with cold emails include real estate, e-commerce, auto-dealerships, lawyers, and medical offices. There is a reason for this, but I will tell you straight up this business model works well if you target any white-collar service business (internal tools approach) or high volume businesses (customer facing tools approach). Setup your toolbox. If you wanted to start a pressure washing business, you would need a pressure-washer. This is no different. For those without programming knowledge, I've seen two common ways AAA get setup to build- one is having a network of on-call web developers, whether its personal contacts or simply going to Upwork or any talent sourcing agency. The second is having an arsenal of no-code tools. I'll get to this more in a second, but this works beecause at its core, when we are dealing with the practical applications of AI, the code is quite simple, simply put. Start cold sales. Unless you have a network already, this is not a step you can skip. You've already picked a niche, so all you have to do is find the right message. Keep cold emails short, sweet, but enticing- and it will help a lot if you did step 1 correctly and intimately understand who your audience is. I'll be touching base later about how you can leverage AI yourself to help you with outreach and closing. The beauty of gen AI and the AAA model You don't need to be a seasoned web developer to make this business model work. The large majority of solutions that SME clients want is best done using an API for an LLM for the actual AI aspect. The value we create with the solutions we build comes with the conceptual framework and design that not only does what they need it to but integrates smoothly with their existing tech-stack and workflow. The actual implementation is quite straightforward once you understand the high level design and know which tools you are going to use. To give you a sense, even if you plan to build out these apps yourself (say in Python) the large majority of the nitty gritty technical work has already been done for you, especially if you leverage Python libraries and packages that offer high level abstraction for LLM-related functions. For instance, calling GPT can be as little as a single line of code. (And there are no-code tools where these functions are simply an icon on a GUI). Aside from understanding the capabilities and limitations of these tools and frameworks, the only thing that matters is being able to put them in a way that makes sense for what you want to build. Which is why outsourcing and no-code tools both work in our case. Okay... but how TF am I suppposed to actually build out these solutions? Now the fun part. I highly recommend getting familiar with Langchain and LlamaIndex. Both are Python libraires that help a lot with the high-level LLM abstraction I mentioned previously. The two most important aspects include being able to integrate internal data sources/knowledge bases with LLMs, and have LLMs perform autonomous actions. The two most common methods respectively are RAG and output parsing. RAG (retrieval augmented Generation) If you've ever seen a tool that seemingly "trains" GPT on your own data, and wonder how it all works- well I have an answer from you. At a high level, the user query is first being fed to what's called a vector database to run vector search. Vector search basically lets you do semantic search where you are searching data based on meaning. The vector databases then retrieves the most relevant sections of text as it relates to the user query, and this text gets APPENDED to your GPT prompt to provide extra context to the AI. Further, with prompt engineering, you can limit GPT to only generate an answer if it can be found within this extra context, greatly limiting the chance of hallucination (this is where AI makes random shit up). Aside from vector databases, we can also implement RAG with other data sources and retrieval methods, for example SQL databses (via parsing the outputs of LLM's- more on this later). Autonomous Agents via Output Parsing A common need of clients has been having AI actually perform tasks, rather than simply spitting out text. For example, with autonomous agents, we can have an e-commerce chatbot do the work of a basic customer service rep (i.e. look into orders, refunds, shipping). At a high level, what's going on is that the response of the LLM is being used programmtically to determine which API to call. Keeping on with the e-commerce example, if I wanted a chatbot to check shipping status, I could have a LLM response within my app (not shown to the user) with a prompt that outputs a random hash or string, and programmatically I can determine which API call to make based on this hash/string. And using the same fundamental concept as with RAG, I can append the the API response to a final prompt that would spit out the answer for the user. How No Code Tools Can Fit In (With some example solutions you can build) With that being said, you don't necessarily need to do all of the above by coding yourself, with Python libraries or otherwise. However, I will say that having that high level overview will help IMMENSELY when it comes to using no-code tools to do the actual work for you. Regardless, here are a few common solutions you might build for clients as well as some no-code tools you can use to build them out. Ex. Solution 1: AI Chatbots for SMEs (Small and Medium Enterprises) This involves creating chatbots that handle user queries, lead gen, and so forth with AI, and will use the principles of RAG at heart. After getting the required data from your client (i.e. product catalogues, previous support tickets, FAQ, internal documentation), you upload this into your knowledge base and write a prompt that makes sense for your use case. One no-code tool that does this well is MyAskAI. The beauty of it especially for building external chatbots is the ability to quickly ingest entire websites into your knowledge base via a sitemap, and bulk uploading files. Essentially, they've covered the entire grunt work required to do this manually. Finally, you can create a inline or chat widget on your client's website with a few lines of HTML, or altneratively integrate it with a Slack/Teams chatbot (if you are going for an internal Q&A chatbot approach). Other tools you could use include Botpress and Voiceflow, however these are less for RAG and more for building out complete chatbot flows that may or may not incorporate LLMs. Both apps are essentially GUIs that eliminate the pain and tears and trying to implement complex flows manually, and both natively incoporate AI intents and a knowledge base feature. Ex. Solution 2: Internal Apps Similar to the first example, except we go beyond making just chatbots but tools such as report generation and really any sort of internal tool or automations that may incorporate LLM's. For instance, you can have a tool that automatically generates replies to inbound emails based on your client's knowledge base. Or an automation that does the same thing but for replies to Instagram comments. Another example could be a tool that generates a description and screeenshot based on a URL (useful for directory sites, made one for my own :P). Getting into more advanced implementations of LLMs, we can have tools that can generate entire drafts of reports (think 80+ pages), based not only on data from a knowledge base but also the writing style, format, and author voice of previous reports. One good tool to create content generation panels for your clients would be MindStudio. You can train LLM's via prompt engineering in a structured way with your own data to essentially fine tune them for whatever text you need it to generate. Furthermore, it has a GUI where you can dictate the entire AI flow. You can also upload data sources via multiple formats, including PDF, CSV, and Docx. For automations that require interactions between multiple apps, I recommend the OG zapier/make.com if you want a no-code solution. For instance, for the automatic email reply generator, I can have a trigger such that when an email is received, a custom AI reply is generated by MyAskAI, and finally a draft is created in my email client. Or, for an automation where I can create a social media posts on multiple platforms based on a RSS feed (news feed), I can implement this directly in Zapier with their native GPT action (see screenshot) As for more complex LLM flows that may require multiple layers of LLMs, data sources, and APIs working together to generate a single response i.e. a long form 100 page report, I would recommend tools such as Stack AI or Flowise (open-source alternative) to build these solutions out. Essentially, you get most of the functions and features of Python packages such as Langchain and LlamaIndex in a GUI. See screenshot for an example of a flow How the hell are you supposed to find clients? With all that being said, none of this matters if you can't find anyone to sell to. You will have to do cold sales, one way or the other, especially if you are brand new to the game. And what better way to sell your AI services than with AI itself? If we want to integrate AI into the cold outreach process, first we must identify what it's good at doing, and that's obviously writing a bunch of text, in a short amount of time. Similar to the solutions that an AAA can build for its clients, we can take advantage of the same principles in our own sales processes. How to do outreach Once you've identified your niche and their pain points/opportunities for automation, you want to craft a compelling message in which you can send via cold email and cold calls to get prospects booked on demos/consultations. I won't get into too much detail in terms of exactly how to write emails or calling scripts, as there are millions of resources to help with this, but I will tell you a few key points you want to keep in mind when doing outreach for your AAA. First, you want to keep in mind that many businesses are still hesitant about AI and may not understand what it really is or how it can benefit their operations. However, we can take advantage of how mass media has been reporting on AI this past year- at the very least people are AWARE that sooner or later they may have to implement AI into their businesses to stay competitive. We want to frame our message in a way that introduces generative AI as a technology that can have a direct, tangible, and positive impact on their business. Although it may be hard to quantify, I like to include estimates of man-hours saved or costs saved at least in my final proposals to prospects. Times are TOUGH right now, and money is expensive, so you need to have a compelling reason for businesses to get on board. Once you've gotten your messaging down, you will want to create a list of prospects to contact. Tools you can use to find prospects include Apollo.io, reply.io, zoominfo (expensive af), and Linkedin Sales Navigator. What specific job titles, etc. to target will depend on your niche but for smaller companies this will tend to be the owner. For white collar niches, i.e. law, the professional that will be directly benefiting from the tool (i.e. partners) may be better to contact. And for larger organizations you may want to target business improvement and digital transformation leads/directors- these are the people directly in charge of projects like what you may be proposing. Okay- so you have your message, and your list, and now all it comes down to is getting the good word out. I won't be going into the details of how to send these out, a quick Google search will give you hundreds of resources for cold outreach methods. However, personalization is key and beyond simple dynamic variables you want to make sure you can either personalize your email campaigns directly with AI (SmartWriter.ai is an example of a tool that can do this), or at the very least have the ability to import email messages programmatically. Alternatively, ask ChatGPT to make you a Python Script that can take in a list of emails, scrape info based on their linkedin URL or website, and all pass this onto a GPT prompt that specifies your messaging to generate an email. From there, send away. How tf do I close? Once you've got some prospects booked in on your meetings, you will need to close deals with them to turn them into clients. Call #1: Consultation Tying back to when I mentioned you want to take a consultant-first appraoch, you will want to listen closely to their goals and needs and understand their pain points. This would be the first call, and typically I would provide a high level overview of different solutions we could build to tacke these. It really helps to have a presentation available, so you can graphically demonstrate key points and key technologies. I like to use Plus AI for this, it's basically a Google Slides add-on that can generate slide decks for you. I copy and paste my default company messaging, add some key points for the presentation, and it comes out with pretty decent slides. Call #2: Demo The second call would involve a demo of one of these solutions, and typically I'll quickly prototype it with boilerplate code I already have, otherwise I'll cook something up in a no-code tool. If you have a niche where one type of solution is commonly demanded, it helps to have a general demo set up to be able to handle a larger volume of calls, so you aren't burning yourself out. I'll also elaborate on how the final product would look like in comparison to the demo. Call #3 and Beyond: Once the initial consultation and demo is complete, you will want to alleviate any remaining concerns from your prospects and work with them to reach a final work proposal. It's crucial you lay out exactly what you will be building (in writing) and ensure the prospect understands this. Furthermore, be clear and transparent with timelines and communication methods for the project. In terms of pricing, you want to take this from a value-based approach. The same solution may be worth a lot more to client A than client B. Furthermore, you can create "add-ons" such as monthly maintenance/upgrade packages, training sessions for employeees, and so forth, separate from the initial setup fee you would charge. How you can incorporate AI into marketing your businesses Beyond cold sales, I highly recommend creating a funnel to capture warm leads. For instance, I do this currently with my AI tools directory, which links directly to my AI agency and has consistent branding throughout. Warm leads are much more likely to close (and honestly, much nicer to deal with). However, even without an AI-related website, at the very least you will want to create a presence on social media and the web in general. As with any agency, you will want basic a professional presence. A professional virtual address helps, in addition to a Google Business Profile (GBP) and TrustPilot. a GBP (especially for local SEO) and Trustpilot page also helps improve the looks of your search results immensely. For GBP, I recommend using ProfilePro, which is a chrome extension you can use to automate SEO work for your GBP. Aside from SEO optimzied business descriptions based on your business, it can handle Q/A answers, responses, updates, and service descriptions based on local keywords. Privacy and Legal Concerns of the AAA Model Aside from typical concerns for agencies relating to service contracts, there are a few issues (especially when using no-code tools) that will need to be addressed to run a successful AAA. Most of these surround privacy concerns when working with proprietary data. In your terms with your client, you will want to clearly define hosting providers and any third party tools you will be using to build their solution, and a DPA with these third parties listed as subprocessors if necessary. In addition, you will want to implement best practices like redacting private information from data being used for building solutions. In terms of addressing concerns directly from clients, it helps if you host your solutions on their own servers (not possible with AI tools), and address the fact only ChatGPT queries in the web app, not OpenAI API calls, will be used to train OpenAI's models (as reported by mainstream media). The key here is to be open and transparent with your clients about ALL the tools you are using, where there data will be going, and make sure to get this all in writing. have fun, and keep an open mind Before I finish this post, I just want to reiterate the fact that this is NOT an easy way to make money. Running an AI agency will require hours and hours of dedication and work, and constantly rearranging your schedule to meet prospect and client needs. However, if you are looking for a new business to run, and have a knack for understanding business operations and are genuinely interested in the pracitcal applications of generative AI, then I say go for it. The time is ticking before AAA becomes the new dropshipping or SMMA, and I've a firm believer that those who set foot first and establish themselves in this field will come out top. And remember, while 100 thousand people may read this post, only 2 may actually take initiative and start.

26 Ways to Make Money as a Startup Founder (for coders & noncoders)
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johnrushxThis week

26 Ways to Make Money as a Startup Founder (for coders & noncoders)

I've launched 24 projects (here is the proof johnrush.me). None of my projects is making millions a month, but many of them make over $1k a month, some do over $10k, and few do even more. I'd not recommend anyone to start by trying to build a unicorn. Better start simple. Aim for $2-4k a month first. Once you get there, either scale it or start a new project with large TAM. From my own experience, the 26 Ways to Make Money as a Startup Founder: One-Feature SaaS. Extract a feature from a popular tool and build a micro SaaS around it. Idea: A SaaS that only offers automated email follow-ups. Launchpads. Develop a launch platform for a specific industry. Idea: A launchpad for growth tools. SEO Tools. Create a tool that focuses on a single aspect of SEO. Idea: A tool that generates alt texts for images. Productized Services. Offer standardized services that are repeatable. Idea: design, coding or social media management. Marketplace Platforms. Create a platform that connects buyers and sellers, earning transaction fees. Idea: An online marketplace for domains. Membership Sites. A subscription-based site with exclusive content. Idea: A founder 0-to-1 site. White Labeling. A product that other businesses can rebrand as their own. Idea: A white-labeled website builder. Selling Data. Provide anonymized data insights to companies. Idea: Selling user behavior data. Affiliate Marketing. Promote products/services and earn commissions on sales. Idea: Recommending hosting services on a tech blog. Selling Leads. Generate and sell business leads. Idea: Selling leads who raised a fresh seed round. Niche Social Networks. Create a paid community around a specific interest. Idea: A network for SEO experts. Sell Domains. Buy and sell domain names for profit. Virtual Products. Sell digital products like templates or graphics. Idea: Website themes for nextjs or boilerplates. On-Demand Services. Build a platform for gigs like delivery or tutoring. Idea: An app for freelance tutors. Niche Job Boards. Start a job board focused on a specific industry. Idea: A job board for remote tech jobs. Crowdsourced Content. Create a user-generated content platform and monetize through ads. Idea: Site to share startup hacks. Buy and Flip Businesses. Purchase underperforming businesses, improve them, and sell for profit. Idea: Acquiring a low-traffic blog, optimizing it, and selling. AI-Powered agents. Develop AI tools that solve specific business problems. Idea: An AI tool that automates customer support. Microservices. Offer small, specialized tools, sdks or APIs. Idea: An api for currency conversion. Influencer Platforms. Create a platform connecting influencers with brands. Idea: Connect AI influencers with AI founders. Niche Directories. Build a paid directory for a specific industry. Idea: A directory of developers who can train models. E-Learning Platforms. Build a platform for educators to sell courses. Idea: A site where AI experts sell AI courses. Virtual assistants. Hire them and sell on subscription. No-Code Tools. Create tools that allow non-technical users to build things. Idea: A no-code website builder for bakeries. Labor arbitrage. Idea: Connect support agents from Portugal with US clients and charge commission.

Switching Gears: Implementing AI for My Agency’s Marketing After a Decade
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Alarming_Management3This week

Switching Gears: Implementing AI for My Agency’s Marketing After a Decade

Hi there, I’ve been running a software development and design agency for the last 10 years, mainly focusing on building custom solutions for businesses and SaaS. For the last 2 years, I’ve consistently recommended that clients use AI technologies, especially for social media and content creation to generate traffic. Funny enough, I wasn’t practicing what I preached. Most of my client projects came from platforms like Upwork and word-of-mouth referrals from clients or people from networking events. Background I started my journey in 2014, switching from an employee to a freelancer. Within the first 10 months, my initial projects grew beyond what I could handle alone, prompting me to hire additional developers. This shift turned my role from a full-stack developer to a team lead and developer. Over the years, my focus has been a blend of tech and product. About five years ago, I realized the importance of design, leading me to adding designers to the agency to provide full-cycle service development—from product ideation and design to development, testing, launch, and support. I still continue to set up dedicated teams for some clients, maintaining a strong technical role as a tech lead, solution architect, and head product designer. To enhance my skills, I even completed UI/UX design courses to offer better product solutions. Despite these changes, building products has always been the easy part. The challenge was ensuring these client products didn’t end up in the graveyard due to poor product-market fit, often caused by inadequate marketing and sales strategies but more often just absence of them. (we are talking about startup and first time founders here 🙂 ) My Journey and Observations Advising Clients: I often found myself advising clients on increasing traffic for their SaaS products and crafting strategic marketing plans. Learning: I’ve gained most of my knowledge from consuming internet materials, courses, and blog posts and learning from successful client project launches. Realization: Despite giving this advice, I wasn’t applying these strategies to my own business, leading to low visits to my agency’s website. Initial Solution: Hiring a Marketer Hiring: I brought in a marketer with a solid background in content creating and interview video editing from an educational organization. Goal: The aim was to increase website visits through a comprehensive marketing strategy. Outcome: Although the content produced was high-quality and useful for pitching services, it didn’t lead to significant traffic increases. Issue: The marketer focused more on content creation rather than distribution channels, which limited effectiveness. Shift to AI-Driven Strategy Experiment: I decided to try using AI for content creation and distribution, which aligns with my agency’s specialization in design-driven development and AI integrations. Implementation plan: I will be generating all content with minimal edits using AI and implementing a strategic backlinking approach. Backlinking Strategy Initial Plan: I initially thought of hiring a specialist for backlinks. Realization: The costs and profiles of freelancers didn’t seem promising. Solution: I found AI-driven services for backlinks, which seem more efficient and cost-effective. Plan: My plan is to use these tools for programmatic SEO-driven AI-generated articles and third-party backlinking services over the next two to three months. Current Approach Management: This approach can be managed and executed by 1 person and monitored weekly, reducing human error and optimizing efficiency. I will start it myself and then replace myself with an editor with managing skills. Reflection: It’s a bit ironic and funny that it took me 10 years to start implementing these strategies in my own agency business, but I now feel more confident with AI and automation in place. Why Increase Website Visitors? You might ask, why do I want to increase the number of visitors to the site, and how can I ensure these visitors will be qualified? Hands-On Experience: To gain hands-on experience and perform this exercise effectively. Introduce Packaged Services: I want to introduce a set of low-cost packaged services tailored for non-technical people who want to build things for themselves - the DIY kits for non-technical folks. These services will provide a foundational template for them to build upon on top of existing established solutions such as Wix, Square Why am I Posting and Sharing Here? You might also wonder, why am I posting it here and sharing this? Well, I'm doing this more for myself. Most of my career, the things I’ve done have been behind the curtains. With this small project, I want to make it public to see the reaction of the community. Perhaps there will be good and smart suggestions offered, and maybe some insights or highlights of tools I wasn’t aware of or didn’t consider. I’ll keep sharing updates on this journey of website promotion, marketing, and SEO. My current goal is to reach 2,000 visits per month, which is a modest start. Looking forward to any thoughts or advice from this community! Disclaimer: This content was not generated by AI, but it was edited by it 😛

Unmasking Fake Testimonials on a YC backed company
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Far-Amphibian3043This week

Unmasking Fake Testimonials on a YC backed company

As developers, marketeers and builders, we often rely on trusted platforms to guide us in finding tools that meet our unique needs. Recently, I stumbled upon Overlap, a site marketed as a haven for collaboration tools. Its sleek interface and glowing testimonials initially convinced me I had found a gem. But as I dug deeper, I uncovered a jaw-dropping reality: their testimonials featured stock images, all of which were easily identified through a quick reverse image search. Even more shocking was the realization that Overlap is a Y Combinator-backed company—an organization renowned for nurturing some of the most innovative startups in the world. With significant funding at their disposal, the decision to cut corners with fake testimonials felt like a slap in the face to their user base. They could easily afford a robust testimonial platform, yet chose a path that undermined their credibility. As developers, marketeers and builders, we often rely on trusted platforms to guide us in finding tools that meet our unique needs. Recently, I stumbled upon Overlap, a site marketed as a haven for video AI tools. Its sleek interface and glowing testimonials initially convinced me I had found a gem. But as I dug deeper, I uncovered a jaw-dropping reality: their testimonials featured stock images, all of which were easily identified through a quick reverse image search. Even more shocking was the realization that Overlap is a Y Combinator-backed company—an organization renowned for nurturing some of the most innovative startups in the world. With significant funding at their disposal, the decision to cut corners with fake testimonials felt like a slap in the face to their user base. They could easily afford a robust testimonial platform, yet chose a path that undermined their credibility. A screenshot of Overlap's landing page https://preview.redd.it/zosmdl0v01ce1.png?width=1000&format=png&auto=webp&s=83ced4af92ca284486281f00b020f1f0114b4fcd This discovery was nothing short of a wake-up call. For a developer-focused website—an audience that prizes authenticity and technical precision above all else—faking testimonials with stock photos isn’t just misleading, it’s a catastrophic betrayal of trust. It left me questioning the integrity of their entire operation and serves as a stark reminder for businesses everywhere: your audience notices when you’re not authentic, and they won’t forgive it easily. Position of Fake Testimonials One of the stock images https://preview.redd.it/a7ugasrw01ce1.png?width=341&format=png&auto=webp&s=5261df741f1198a92e537f1e61640e7d6ec60a7f Lessons for Startup Founders and Developers This experience offers several critical lessons for startup founders and developers alike: Authenticity is Non-Negotiable: In a competitive market, trust and transparency can make or break your brand. Fake testimonials might provide a short-term boost, but the long-term damage to credibility far outweighs any temporary gains. Invest in Genuine Solutions: If you have the resources, like a Y Combinator-backed company, prioritize tools and practices that enhance authenticity. Platforms like RapidFeedback allow businesses to dynamically update reviews and manage feedback efficiently. Leverage Real User Feedback: Authentic testimonials not only build trust but also provide actionable insights into your product’s strengths and weaknesses. This feedback loop can be invaluable for refining and growing your business. Understand Your Audience: Developers value precision, integrity, and honesty. Catering to this audience requires a commitment to these principles in every aspect of your business. Let’s ensure that the tools we build and the businesses we run prioritize authenticity. In the long run, a commitment to transparency and user trust will always yield greater rewards than any shortcut could provide. Why Fake Testimonials Are a Problem Fake testimonials damage your brand in more ways than one: Loss of Credibility: Developers are a discerning audience. Trust is everything, and losing it can be catastrophic for your reputation. Hurt User Experience: Knowing a platform misrepresents itself makes users skeptical about its features and promises. Missed Opportunities: Genuine feedback can provide valuable insights for growth and improvement, which fake testimonials completely overlook. A Smarter Way: Authentic Testimonials with RapidFeedback This experience reminded me of why tools like RapidFeedback are invaluable. RapidFeedback helps businesses maintain authenticity by dynamically updating reviews and images in real time. Here’s why it stands out: Real-Time Updates: Reviews are fetched and displayed dynamically, ensuring they’re always up-to-date. Dashboard Management: Businesses can monitor and manage good vs. bad reviews from a centralized dashboard, enabling them to address concerns promptly. Authenticity Guaranteed: Dynamic updates ensure that testimonials reflect real users and their experiences, which builds trust and credibility. Lessons for Developers and Businesses If there’s one takeaway from my Overlap experience, it’s this: authenticity isn’t optional. Whether you’re building tools for developers or selling consumer products, your audience values transparency. Using tools like RapidFeedback ensures your business maintains trust while gaining actionable insights to grow. Let’s commit to prioritizing honesty in our work. Because in the end, authentic relationships with users are what truly drive success.

How a Small Startup in Asia Secured a Contract with the US Department of Homeland Security
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Royal_Rest8409This week

How a Small Startup in Asia Secured a Contract with the US Department of Homeland Security

Uzair Javaid, a Ph.D. with a passion for data privacy, co-founded Betterdata to tackle one of AI's most pressing challenges: protecting privacy while enabling innovation. Recently, Betterdata secured a lucrative contract with the US Department of Homeland Security, 1 of only 4 companies worldwide to do so and the only one in Asia. Here's how he did it: The Story So what's your story? I grew up in Peshawar, Pakistan, excelling in coding despite studying electrical engineering. Inspired by my professors, I set my sights on studying abroad and eventually earned a Ph.D. scholarship at NUS Singapore, specializing in data security and privacy. During my research, I ethically hacked Ethereum and published 15 papers—three times the requirement. While wrapping up my Ph.D., I explored startup ideas and joined Entrepreneur First, where I met Kevin Yee. With his expertise in generative models and mine in privacy, we founded Betterdata. Now, nearly three years in, we’ve secured a major contract with the U.S. Department of Homeland Security—one of only four companies globally and the only one from Asia. The Startup In a nutshell, what does your startup do? Betterdata is a startup that uses AI and synthetic data generation to address two major challenges: data privacy and the scarcity of high-quality data for training AI models. By leveraging generative models and privacy-enhancing technologies, Betterdata enables businesses, such as banks, to use customer data without breaching privacy regulations. The platform trains AI on real data, learns its patterns, and generates synthetic data that mimics the real thing without containing any personal or sensitive information. This allows companies to innovate and develop AI solutions safely and ethically, all while tackling the growing need for diverse, high-quality data in AI development. How did you conduct ideation and validation for your startup? The initial idea for Betterdata came from personal experience. During my Ph.D., I ethically hacked Ethereum’s blockchain, exposing flaws in encryption-based data sharing. This led me to explore AI-driven deep synthesis technology—similar to deepfakes but for structured data privacy. With GDPR impacting 28M+ businesses, I saw a massive opportunity to help enterprises securely share data while staying compliant. To validate the idea, I spoke to 50 potential customers—a number that strikes the right balance. Some say 100, but that’s impractical for early-stage founders. At 50, patterns emerge: if 3 out of 10 mention the same problem, and this repeats across 50, you have 10–15 strong signals, making it a solid foundation for an MVP. Instead of outbound sales, which I dislike, we used three key methods: Account-Based Marketing (ABM)—targeting technically savvy users with solutions for niche problems, like scaling synthetic data for banks. Targeted Content Marketing—regular customer conversations shaped our thought leadership and outreach. Raising Awareness Through Partnerships—collaborating with NUS, Singapore’s PDPC, and Plug and Play to build credibility and educate the market. These strategies attracted serious customers willing to pay, guiding Betterdata’s product development and market fit. How did you approach the initial building and ongoing product development? In the early stages, we built synthetic data generation algorithms and a basic UI for proof-of-concept, using open-source datasets to engage with banks. We quickly learned that banks wouldn't share actual customer data due to privacy concerns, so we had to conduct on-site installations and gather feedback to refine our MVP. Through continuous consultation with customers, we discovered real enterprise data posed challenges, such as missing values, which led us to adapt our prototype accordingly. This iterative approach of listening to customer feedback and observing their usage allowed us to improve our product, enhance UX, and address unmet needs while building trust and loyalty. Working closely with our customers also gives us a data advantage. Our solution’s effectiveness depends on customer data, which we can't fully access, but bridging this knowledge gap gives us a competitive edge. The more customers we test on, the more our algorithms adapt to diverse use cases, making it harder for competitors to replicate our insights. My approach to iteration is simple: focus solely on customer feedback and ignore external noise like trends or advice. The key question for the team is: which customer is asking for this feature or solution? As long as there's a clear answer, we move forward. External influences, such as AI hype, often bring more confusion than clarity. True long-term success comes from solving real customer problems, not chasing trends. Customers may not always know exactly what they want, but they understand their problems. Our job is to identify these problems and solve them in innovative ways. While customers may suggest specific features, we stay focused on solving the core issue rather than just fulfilling their exact requests. The idea aligns with the quote often attributed to Henry Ford: "If I asked people what they wanted, they would have said faster horses." The key is understanding their problems, not just taking requests at face value. How do you assess product-market fit? To assess product-market fit, we track two key metrics: Customers' Willingness to Pay: We measure both the quantity and quality of meetings with potential customers. A high number of meetings with key decision-makers signals genuine interest. At Betterdata, we focused on getting meetings with people in banks and large enterprises to gauge our product's resonance with the target market. How Much Customers Are Willing to Pay: We monitor the price customers are willing to pay, especially in the early stages. For us, large enterprises, like banks, were willing to pay a premium for our synthetic data platform due to the growing need for privacy tech. This feedback guided our product refinement and scaling strategy. By focusing on these metrics, we refined our product and positioned it for scaling. What is your business model? We employ a structured, phase-driven approach for out business model, as a B2B startup. I initially struggled with focusing on the core value proposition in sales, often becoming overly educational. Eventually, we developed a product roadmap with models that allowed us to match customer needs to specific offerings and justify our pricing. Our pricing structure includes project-based pilots and annual contracts for successful deployments. At Betterdata, our customer engagement unfolds across three phases: Phase 1: Trial and Benchmarking \- We start with outreach and use open-source datasets to showcase results, offering customers a trial period to evaluate the solution. Phase 2: Pilot or PoC \- After positive trial results, we conduct a PoC or pilot using the customer’s private data, with the understanding that successful pilots lead to an annual contract. Phase 3: Multi-Year Contracts \- Following a successful pilot, we transition to long-term commercial contracts, focusing on multi-year agreements to ensure stability and ongoing partnerships. How do you do marketing for your brand? We take a non-conventional approach to marketing, focusing on answering one key question: Which customers are willing to pay, and how much? This drives our messaging to show how our solution meets their needs. Our strategy centers around two main components: Building a network of lead magnets \- These are influential figures like senior advisors, thought leaders, and strategic partners. Engaging with institutions like IMDA, SUTD, and investors like Plug and Play helps us gain access to the right people and foster warm introductions, which shorten our sales cycle and ensure we’re reaching the right audience. Thought leadership \- We build our brand through customer traction, technology evidence, and regulatory guidelines. This helps us establish credibility in the market and position ourselves as trusted leaders in our field. This holistic approach has enabled us to navigate diverse market conditions in Asia and grow our B2B relationships. By focusing on these areas, we drive business growth and establish strong trust with stakeholders. What's your advice for fundraising? Here are my key takeaways for other founders when it comes to fundraising: Fundraise When You Don’t Need To We closed our seed round in April 2023, a time when we weren't actively raising. Founders should always be in fundraising mode, even when they're not immediately in need of capital. Don’t wait until you have only a few months of runway left. Keep the pipeline open and build relationships. When the timing is right, execution becomes much easier. For us, our investment came through a combination of referrals and inbound interest. Even our lead investor initially rejected us, but after re-engaging, things eventually fell into place. It’s crucial to stay humble, treat everyone with respect, and maintain those relationships for when the time is right. Be Mindful of How You Present Information When fundraising, how you present information matters a lot. We created a comprehensive, easily digestible investment memo, hosted on Notion, which included everything an investor might need—problem, solution, market, team, risks, opportunities, and data. The goal was for investors to be able to get the full picture within 30 minutes without chasing down extra details. We also focused on making our financial model clear and meaningful, even though a 5-year forecast might be overkill at the seed stage. The key was clarity and conciseness, and making it as easy as possible for investors to understand the opportunity. I learned that brevity and simplicity are often the best ways to make a memorable impact. For the pitch itself, keep it simple and focus on 4 things: problem, solution, team, and market. If you can summarize each of these clearly and concisely, you’ll have a compelling pitch. Later on, you can expand into market segments, traction, and other metrics, but for seed-stage, focus on those four areas, and make sure you’re strong in at least three of them. If you do, you'll have a compelling case. How do you run things day-to-day? i.e what's your operational workflow and team structure? Here's an overview of our team structure and process: Internally: Our team is divided into two main areas: backend (internal team) and frontend (market-facing team). There's no formal hierarchy within the backend team. We all operate as equals, defining our goals based on what needs to be developed, assigning tasks, and meeting weekly to share updates and review progress. The focus is on full ownership of tasks and accountability for getting things done. I also contribute to product development, identifying challenges and clearing obstacles to help the team move forward. Backend Team: We approach tasks based on the scope defined by customers, with no blame or hierarchy. It's like a sports team—sometimes someone excels, and other times they struggle, but we support each other and move forward together. Everyone has the creative freedom to work in the way that suits them best, but we establish regular meetings and check-ins to ensure alignment and progress. Frontend Team: For the market-facing side, we implement a hierarchy because the market expects this structure. If I present myself as "CEO," it signals authority and credibility. This distinction affects how we communicate with the market and how we build our brand. The frontend team is split into four main areas: Business Product (Software Engineering) Machine Learning Engineering R&D The C-suite sits at the top, followed by team leads, and then the executors. We distill market expectations into actionable tasks, ensuring that everyone is clear on their role and responsibilities. Process: We start by receiving market expectations and defining tasks based on them. Tasks are assigned to relevant teams, and execution happens with no communication barriers between team members. This ensures seamless collaboration and focused execution. The main goal is always effectiveness—getting things done efficiently while maintaining flexibility in how individuals approach their work. In both teams, there's an emphasis on accountability, collaboration, and clear communication, but the structure varies according to the nature of the work and external expectations.

Where Do I Find Like-Minded, Unorthodox Co-founders? [Tech]
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madscholarThis week

Where Do I Find Like-Minded, Unorthodox Co-founders? [Tech]

After more than 20 years in the tech industry I'm pretty fed up. I've been at it non-stop, so the burnout was building up for a while. Eventually, it's gotten so bad that it was no longer a question whether I need to take a break; I knew that I had to, for the sake of myself and loved ones. A few months ago I quit my well-paying, mid-level mgmt job to have some much-needed respite. I can't say that I've fully recovered, but I'm doing a bit better, so I'm starting to think about what's next. That said, the thoughts of going back into the rat race fill me with dread and anxiety. I've had an interesting career - I spent most of it in startups doing various roles from an SWE to a VP Eng, including having my own startup adventures for a couple of years. The last 4.5 years of my career have been in one of the fastest growing tech companies - it was a great learning experience, but also incredibly stressful, toxic and demoralizing. It's clear to me that I'm not cut out for the corporate world -- the ethos contradicts with my personality and beliefs -- but it's not just. I've accumulated "emotional scars" from practically every place I worked at and it made me loathe the industry to the degree that if I ever have another startup, it'd have to be by my own -- unorthodox -- ideals, even if it means a premature death due to lack of funding. I was young, stupid and overly confident when I had my first startup. I tried to do it "by the book" and dance to the tune of investors. While my startup failed for other, unrelated reasons, it gave me an opportunity to peak behind the curtain, experience the power dynamics, and get a better understanding to how the game is played - VCs and other person of interest have popularized the misconception that if a company doesn't scale, it would stagnate and eventually regress and die. This is nonsense. This narrative was created because it would make the capitalist pigs obsolete - they need companies to go through the entire alphabet before forcing them to sell or IPO. The sad reality is that the most entrepreneurs still believe in this paradigm and fall into the VC's honeypot traps. It's true that many businesses cannot bootstrap or scale without VC money, but it's equally true that far too many companies pivot/scale prematurely (and enshitify their product in the process) due to external pressures fueled by pure greed. This has a top-bottom effect - enshitification doesn't only effect users, but it also heavily effects the processes and structrures of companies, which can explain why the average tenure in tech is only \~2 years. I think that we live in an age where self-starting startups are more feasible than ever. It's not just the rise of AI and automation, but also the plethora of tools, services, and open-source projects that are available to all for free. On the one hand, this is fantastic, but on the other, the low barrier-to-entry creates oversaturation of companies which makes research & discovery incredibly hard - it is overwhelming to keep up with the pace and distill the signal from the noise, and there's a LOT of noise - there's not enough metaphorical real-estate for the graveyard of startups that will be defunct in the very near future. I'd like to experiment with startups again, but I don't want to navigate through this complex mine field all by myself - I want to find a like-minded co-founder who shares the same ideals as I do. It goes without saying that being on the same page isn't enough - I also want someone who's experienced, intelligent, creative, productive, well-rounded, etc. At the moment, I don't have anyone in my professional network who has/wants what it takes. I can look into startup bootcamps/accelerators like YC et al., and sure enough, I'll find talented individuals, but it'd be a mismatch from the get-go. For shits and giggles, this is (very roughly) how I envision the ideal company: Excellent work life balance: the goal is not to make a quick exit, become filthy rich, and turn into a self-absorbed asshole bragging about how they got so succesful. The goal is to generate a steady revenue stream while not succumbing to social norms that encourage greed. The entire purpose is to reach humble financial indepedence while maintaining a stress-free (as one possibly can) work environment. QOL should always be considered before ARR. Bootstraping: no external money. Not now, not later. No quid pro quo. No shady professionals or advisors. Company makes it or dies trying. Finances: very conservative to begin with - the idea is to play it safe and build a long fucking runaway before hiring. Spend every penny mindfully and frugally. Growth shouldn't be too quick & reckless. The business will be extremely efficient in spending. The only exception to the rule is crucial infrastructure and wages to hire top talent and keep salaries competitive and fair. Hiring: fully remote. Global presence, where applicable. Headcount will be limited to the absolute bare minimum. The goal is to run with a skeleton crew of the best generalists out there - bright, self-sufficient, highly motivated, autodidact, and creative individuals. Hiring the right people is everything and should be the company's top priority. Compensation & Perks: transperent and fair, incentivizing exceptional performance with revenue sharing bonuses. The rest is your typical best-in-class perks: top tier health/dental/vision insurance, generous PTO with mandatory required minimum, parental leave, mental wellness, etc. Process: processes will be extremely efficient, automated to the max, documented, unbloated, and data-driven through and through. Internal knowledge & data metrics will be accessible and transparent to all. Employees get full autonomy of their respective areas and are fully in charge of how they spend their days as long as they have agreed-upon, coherent, measurable metrics of success. Meetings will be reduced to the absolute minimum and would have to be justified and actionable - the ideal is that most communications will be done in written form, while face-to-face will be reserved for presentations/socializing. I like the Kaizen philosophy to continuously improve and optimize processes. Product: As previously stated, "data-driven through and through". Mindful approach to understand cost/benefit. Deliberate and measured atomic improvements to avoid feature creep and slow down the inevitable entropy. Most importantly, client input should be treated with the utmost attention but should never be the main driver for the product roadmap. This is a very controversial take, but sometimes it's better to lose a paying customer than to cave to their distracting/unreasonable/time-consuming demands. People Culture: ironicaly, this would be what most companies claim to have, but for realsies. Collaborative, open, blameless environment. People are treated like actual grown ups with flat structure, full autonomy, and unwavering trust. Socializing and bonding is highly encourged, but never required. Creativity and ingenuity is highly valued - people are encouraged to work on side projects one day of the week. Values: I can write a lot about it, but it really boils down to being kind and humble. We all know what happened with "don't be evil". It's incredibly hard to retain values over time, esp. when there are opposing views within a company. I don't know how to solve it, but I believe that there should be some (tried and true) internal checks & balances from the get go to ensure things are on track. I never mentioned what this hypothetical startup does. Sure, there's another very relevant layer of domain experience fit, but this mindset allows one to be a bit more fluid because the goal is not to disrupt an industry or "make the world a better place"; it's to see work for what it truly is - a mean to an end. It's far more important for me to align with a co-founder on these topics than on an actual idea or technical details. Pivoting and rebranding are so common that many VCs outweigh the make up and chemistry of the founding team (and their ability to execute) over the feasibility of their ideas.  To wrap this long-winded post, I'm not naive or disillusioned - utopias aren't real and profitable companies who operate at a 70-80% rate of what I propose are the real unicorns, but despite them being a tiny minority, I think they are the real forward thinkers of the industry. I might be wrong, but I hope that I'm right and that more and more startups will opt towards long-term sustainability over the promise of short-term gains because the status quo really stinks for most people. What do you folks think? Does anyone relate? Where can I find others like me? P.S I thought about starting a blog writing about these topics in length (everything that is wrong with tech & what can be done to improve it), but I have the Impostor Syndrom and I'm too self-conscious about how I come off. If you somehow enjoyed reading through that and would love to hear more of my thoughts and experiences in greater detail, please let me know. P.P.S If you have a company that is close to what I'm describing and you're hiring, let me know!

Why the value of writing code and other digital services is going to zero
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BalloonWheelieThis week

Why the value of writing code and other digital services is going to zero

I must preface this with a trigger warning because I make some statements in this post that might be upsetting to some. This post discusses my experience building in the new era of entrepreneurship, which is one where the founder is the center of the universe, and the consultants, overpriced SaaS, and corporate swamp creatures are replaced by single-user custom software, bots, and self-hosted automations. If you work in the legacy economy, I really don't intend to stress you out or say things you are doing are quickly becoming irrelevant, but I must share the reality of how I am operating, because I would like to hear from others who are doing the same, or desire to do the same. I am currently operating with the belief that AI-powered tools are going to make 1-person million dollar businesses much more common. Building anything digital is becoming extremely easy, cheap, and quick to implement. The value of code and digital tools is approaching zero, or at most 5% of what it currently is. Right now, the most powerful AI tools are aimed at developers, so folks who have some technical and business ability basically have nothing holding them back aside from the speed of their brain right now. I happen to be a part of the cohort, and am building like there is no tomorrow, but I don't believe this cohort is actually all that big. The next hurdle to unlock the new era of entrepreneurship is empowering every entrepreneur to build at the same pace that is currently locked behind having technical ability. This cohort is huge (millions, if the number of people in this sub is any indication). This post is aimed at them (you?). If you are part of this cohort, what is holding you back from launching a new product for near-zero cost? What is too complicated, too expensive, too unknown for you to be able to build your new/current business at maximum speed? I look forward to seeing the replies, I hope some insights shared can help the community, and be a catalyst for more tools to enable non-technical founders to launch. I will now share some of how I am testing, launching, and selling as a one-man-show. This will be a little bit technical, but if the output of any layer of my stack is something you want, please comment because maybe someone will build a cheap way of accessing it without needing to manage the code yourself. \#1 BOTS I cannot overstate how much leverage bots have created for me. I run all of my bots locally and interface with with via Telegram. Bots do things like: \- watch social media pages, forums, subreddits, etc related to my customers and notify me of what is going on, and suggest SEO blog posts that could be published to capture traffic related to the topic. with a single message, my bot will generate a blog post, send it to me for review, apply edits i suggest, and then publish it live, all from within telegram \- pay attention to all my key metrics/analytics, and attempt to find insights/corrolations (ex. there is a lot of traffic on this page, blog post, video, etc. here's why, and how we can take advantage of it to drive business goals) \- repurposing content. i have dozens of social media profiles that are 100% run by bots, they are all related to my customer niches and will do things like post news, snippets from my blogs, interact with human creators in the niche, etc. this builds my audience automatically which I can then advertise to/try to convert into paying customers, since they are interested in the things my bot is posting and become followers, it's like automated qualified lead gen 24/7 across every social platform and every niche I care about. you may be thinking by now that this post is made by a bot, but you will have to trust me that this is 100% hand-written by my sleep-deprived brain. let's continue: \#2 replacing every SaaS with a shitty version of it designed for what i need out of it it's absurd that we pay ten's of dollars per seat per month for basic digital functions like chat (slack), CRM (active camppaign, sales force, hubspot, etc), email stuff (mailchip, etc), link sharing (linktree, etc), website builders (wix, squarespace, etc), etc. all of these SaaS tools are overpriced and overbuilt. I believe many of them are going to be caught in the innovators dilemma and will go to 0. I don't use any of these anymore, I build and self-host my own shitty version of each of them that does only what i need out of the tool. for example, my CRM doesn't have a fancy drag and drop email builder and 10000 3rd party plugins, because i dont need any of that shit I just need to segment and communicate with my customers. if i need more features, i can generate them on the fly. \#3 working alone I have worked with cofounders in the past, raised money from investors, hired consultants, burned money and time, suffered sleepless nights from stress caused by other people not delivering, trying to convince others they are wrong, or they are pushing the company off a cliff, waste waste waste. no more of that. In the new age of entrepreneurship, the BUILDER (you and I) are the ones creating the value, and AI empowers us to do it alone. this might seem daunting, but there is no business problem that can't be solved with a detailed discussion sesh with chatgpt, no facts that can't be found with perplexity, and no task that can't be automated with claude. there is no need for anymore swamp creatures. you are the start and the end point, you don't need to rely on anyone else for anything. this may sound ignorant, but this is the conclusion I have come to believe, and it continues to be proven every day my businesses progress with me being the only human involved. This is getting quite long so I'll cut it here. I look forward to hearing about how you are operating in this new era and hopefully getting inspired/learning some new ideas to add to my current stack.

I realized that AI will create equal footing for non-technical / non-coders compared to coders
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MatanNahmaniThis week

I realized that AI will create equal footing for non-technical / non-coders compared to coders

Hey fellow entrepreneurs, I started my current entrepreneurial journey following the advice to “build something that solves a problem you have.” As a coder, I wanted to code faster/better/stronger/etc. So I tried out dozens of AI coding tools to see the state of the market.  I took the best components I saw and started making my own flavor of tool, but sort of shelved it because as a coder I felt that the results were a bit alien (such as getting the AI to follow my code style, write idiomatic code, or refactor the same way I would.) I concluded that building AI coding tools for coders is tricky because as coders we’re so particular about the specifics of our code. Meanwhile, my absolutely non-technical friend was hitting me up to help him build a website for a new real-estate company that he’s launching, and he wanted my help. I really respect his hustle, but I was swamped trying to figure out my own product/market, so I told him he could use my AI coder and I would try to help out when he got stuck. He didn’t get stuck though, not once, and he launched his site over the weekend. I was truly shocked he did it all on his own, so I asked him to share his logs. It was wild – he managed to code a more or less state of the art website (good design, SEO, well-structured source code, Google Analytics, mailing lists. etc.) with absolutely no help. It cost him less than $100 in AI credits, instead of the price quotes of $20,000 - $50,000 from freelancers and agencies. Now I’m seriously pursuing AI coding tools again, but this time with a new passion: AI for non-coder / non-technical people is a 100x game changer. I think 2025 is going to be the year of the entrepreneur, where there will be a hundred times the businesses started because what held people back before was the lack of a technical co-founder or the cash to compensate engineers. Now it costs next to nothing to get started. I’m curious if anyone else has had a similar realization? Anyway, I’ve put the link below to my GitHub if you want to try it (open source, you pay for AI credits). But the main reason for my post is that I feel like I’m living in this new world of realization that being a human on earth is going to get a LOT more interesting in the coming years. There’s literally no excuse to take a job you hate, and nothing stopping people from launching a business. For anyone interested in checking it out or providing feedback you can search for kodu ai on github or kodu ai on google Best of luck to everyone on your entrepreneurial journey! P.s not sure if this is the right flair

Made $19.2k this month, and just surpassed $1000 the last 24 hours. What I did and what's next.
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dams96This week

Made $19.2k this month, and just surpassed $1000 the last 24 hours. What I did and what's next.

It's the first time I hit $1000+ in 24 hours and I had no one to share it with (except you guys). I'm quite proud of my journey, and I would have thought that making $1000 in a day would make me ecstatic, but actually it's not the case. Not sure if it's because my revenue has grown by increment step so I had time to "prepare" myself to achieve this at one point, or just that I'm nowhere near my goal of 100k/month so that I'm not that affected by it. But it's crazy to think that my goal was to make 100$ daily at the end of 2024. So for those who don't know me (I guess most of you), I build mobile apps and ship them as fast as I can. Most of them are in the AI space. I already made a post here on how I become a mobile app developer so you can check it for more details, but essentially here's what I did : Always loved creating my own things and solve problems Built multiple YouTube channels since I was 15 (mobile gaming actually) that all worked great (but it was too niche so not that scalable, didn't like that) Did a few businesses here and there (drop shopping, selling merch to school, etc) Finished my master's degree in engineering about 2 years ago Worked a moment in a famous watch industry company and saw my potential. The combo of health issues, fixed salary (although it was quite a lot), and me wanting to be an entrepreneur made me leave the company. Created a TikTok account in mobile tech (got 10+ million views the 1st 3 days), manage to grow it to 200k subs in about 3 months Got plenty of collabs for promoting mobile apps (between $500 - $2000 for a collab) Said fuck it I should do my own apps and market them on my TikTok instead of doing collabs Me wanting to build my own apps happened around May-June 2023. Started my TikTok in Feb 2023. At this point I had already 150k+ subs on TikTok. You guys need to know that I suck at coding big time. During my studies I tried to limit as much as I could coding because I was a lazy bast*rd, even though I knew it would come to bite me in the ass one day. But an angel appeared to me in broad daylight, that angel was called GPT-4. I subscribed for 20$/month to get access, and instantly I saw the potential of AI and how much it could help me. Last year GPT-4 was ahead of its time and could already code me basic apps. I had already a mac so I just downloaded Xcode and that was it. My 1st app was a wallpaper app, and I kid you not 90% of it was made by AI. Yes sometimes I had to try again and again with different prompts but it was still so much faster compared to if I had to learn coding from scratch and write code with my own hands. The only thing I didn't do was implement the in app purchase, from which I find a guy on Fiverr to do it for me for 50$. After about 2 months of on-off coding, my first app was ready to be launched. So it was launched, had a great successful launch without doing any videos at that point (iOS 17 was released and my app was the first one alongside another one to offer live wallpapers for iOS 17. I knew that there was a huge app potential there when iOS 17 was released in beta as Apple changed their live wallpaper feature). I Then made a video a few weeks after on my mobile tiktok channel, made about 1 million views in 48 hours, brought me around 40k additional users. Was top 1 chart in graphism and design category for a few weeks (in France, as I'm French so my TikTok videos are in French). And was top 100 in that same category in 120+ countries. Made about 500$ ? Okay that was trash, but I had no idea to monetize the app correctly at that point. It was still a huge W to me and proved me that I could successfully launch apps. Then I learned ASO (App Store Optimization) in depth, searched on internet, followed mobile app developers on Twitter, checked YouTube videos, you name it. I was eager to learn more. I needed more. Then I just iterated, build my 2nd app in less than a month, my 3rd in 3 weeks and so on. I just build my 14th app in 3 days and is now in review. Everytime I manage to reuse some of my other app's code in my new one, which is why I can build them so much faster now. I know how to monetize my app better by checking out my competitors. I learn so much by just "spying" other apps. Funnily enough, I only made this one Tiktok video on my main account to promote my app. For all my other apps, I didn't do a single video where I showcase it, the downloads has only been thanks to ASO. I still use AI everyday. I'm still not good at coding (a bit better than when I started). I use AI to create my app icons (midjourney or the new AI model Flux which is great). I use figma + midjourney to create my App Store screenshots (and they actually look quite good). I use GPT-4o and Claude 3.5 Sonnet to code most of my apps features. I use gpt-4o to localize my app (if you want to optimize the number of downloads I strongly suggest localizing your app, it takes me about 10 minutes thanks to AI). Now what are my next goals ? To achieve the 100k/month I need to change my strategy a little. Right now the $20k/month comes from purely organic downloads, I didn't do any paid advertising. It will be hard for me to keep on launching new apps and rely on ASO to reach the 100k mark. The best bet to reach 100k is to collab with content creators and they create a viral video showcasing your app. Depending on the app it's not that easy, luckily some of my apps can be viral so I will need to find the right content creators. Second way is to try tiktok/meta ads, I can check (have checked) all the ads that have been made by my competitors (thank you EU), so what I would do is copy their ad concept and create similar ads than them. Some of them have millions in ad budget so I know they create high converting ads, so you don't need to try to create an ad creative from scratch. My only big fear is to get banned by Apple (for no reason of mine). In just a snap of a finger they can just ban you from the platform, that shit scares me. And you pretty much can't do anything. So that's about it for me. I'm quite proud of myself not going to lie. Have been battling so many health issues these past years where I just stay in bed all day I'm surprised to be able to make it work. Anyways feel free to ask questions. I hope it was interesting for some of you at least. PS: My new app was just approved by app review, let the app gods favor me and bring me many downloads ! Also forgot to talk about a potential $100k+ acquisition of one of my apps, but if that ever happens I'll make a post on it.

AI Will Make You Extremely Rich or Kill Your Business in 2024
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AntsyNursery58This week

AI Will Make You Extremely Rich or Kill Your Business in 2024

Preface: I'm a solo-founder in the AI space and previously worked as an ML scientist; the new advancements in AI that I'm seeing are going to impact everyone here. It doesn't matter if you're just starting out, or a bootstrapped brick and mortar founder, or even a VC backed hard tech founder. Last year was when the seeds were laid, and this is the year we'll see them bloom. There will be an onslaught of advancements that take place that are borderline inconceivable due to the nature of exponential progress. This will change every single vertical. I'm making this post because I think AI execution strategy will make or break businesses. Dramatically. Over $50B was put into AI startups in 2023 alone. This figure excludes the hundreds of billions poured into AI from enterprises. So, let's follow the money: &#x200B; 1) AI enterprise software. There's a lot to unpack here and this is what I’m currently working on. AI enterprise software will encompass everything from hyper personalized email outbound to AI cold calls to AI that A/B tests ads on synthetic data to vertical specific software. The impact of the former is relatively self explanatory, so I'll focus on the latter. To illustrate vertical specific AI software, I'll use a simple example in the legal space. Lawyers typically have to comb through thousands of pages of documents. Now, using an LLM + a VDB, an AI can instantly answer all of those questions while surfacing the source and highlighting the specific answer in the contract/document. There are dozens of AI startups for this use case alone. This saves lawyers an immense amount of time and allows them to move faster. Firms that adopt this have a fundamental advantage over law firms that don't adopt this. This was 2023 technology. I'm seeing vertical AI software getting built by my friends in areas from construction, to real estate, to even niche areas like chimney manufacturing. This will exist everywhere. Now, this can be extrapolated much further to be applicable to systems that can do reports and even browse the Internet. This brings me to my next point. &#x200B; 2) AI information aggregation and spread. My gut tells me that this will have a crescendo moment in the future with hardware advancements (Rabbit, Tab, etc.). You won't have to google things because it will be surfaced to you. It's predictive in nature. The people who can get information the fastest will grow their business the fastest. This part is semi-speculative, but due to the nature of LLMs being so expensive to train, I have a strong feeling that large institutions will have access to the \fastest\ and \best\ models that can do this quicker than you and I can. This is why it's important to stay on top. &#x200B; 3) AI content generation This is relevant to running advertisements and any digital marketing aspect of your business. If you can rapidly make content faster than your competitors to put in social media, you will outpace your competitors rapidly. I think most folks are familiar with MidJourney, Stable diffusion, etc. but don't know how to use it. You can generate consistent models for a clothing brand or generate images of a product that you would normally need to hire a professional photographer to take. There's also elevenlabs which is relatively easy to use and can be used to make an MP3 clip as a narration for an ad; this is something I've already done. I'm also still shocked by how many people are unfamiliar with tools like Pika which can do video generation. You could imagine companies having fleets of digital influencers that they control or conjuring up the perfect ad for a specific demographic using a combination of all of the aforementioned tools. &#x200B; In summary, if you feel like I'm being hyperbolic or propagating science fiction fantasies, you're likely already behind. I truly recommend that everyone stays up to date on these advancements as much as possible. If your competitor comes across an AI tool that can increase their ROAS by 5x they can crush you. If your competitor uses a tool that increases the rate at which they receive and aggregate information by 200% (modest estimate) they will crush you. If your competitors have a tool that can reduce their employee size, then they will use it. They'll fire their employees to cut costs and reinvest the money back into their business. It will compound to the point where you're outpaced, and this isn't a level of innovation we've seen since the birth of the industrial revolution. Your customers can get stolen overnight, or you can steal your competition’s customers overnight. TL;DR: This is an opportunity for entrepreneurs to scale faster than they could have possibly imagined, but this also comes with the potential for your company to be obliterated. We've never seen advancements that can have this drastic of an impact this quickly. Adoption will happen fast, and first movers will have a disproportionate and compounding advantage. Watch guides, meet with startups, follow the news, and get rich.

How I went from $27 to $3K as a solopreneur still in a 9-5
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jottrledThis week

How I went from $27 to $3K as a solopreneur still in a 9-5

My journey started back in November 2023. I was scrolling through Twitter and YouTube and saw a word that I had never come across before. Solopreneur. The word caught my eye. Mainly because I was pretty sure I knew what it meant even though it's not a word you'll find in the dictionary. I liked what it was describing. A solo entrepreneur. A one man business. It completely resonated with me. As a software engineer by trade I'm used to working alone, especially since the pandemic hit and we were forced to work remotely. See, I always wanted to ditch the 9-5 thing but thought that was too big and too scary for a single person to do. Surely you would need a lot of money to get started, right? Surely you would need investors? The whole concept seemed impossible to me. That was until I found all the success stories. I became obsessed with the concept of solopreneurship. As I went further down the rabbit hole I found people like Justin Welsh, Kieran Drew and Marc Louvion to name a few. All of whom have one person businesses making huge money every year. So I thought, if they can do it, why can't I? People like this have cleared the pathway for those looking to escape the 9-5 grind. I decided 2024 would be the year I try this out. My main goal for the year? Build a one man business, earn my first $ online and learn a sh\*t ton along the way. My main goal in general? Build my business to $100K per year, quit my 9-5 and live with freedom. From December 2023 to February 2024 I began brainstorming ideas. I was like a lost puppy looking for his ball. How on earth did people find good ideas? I began writing everything and anything that came to mind down in my notes app on my phone. By February I would have approximately 70 ideas. Each as weird and whacky as the other. I was skeptical though. If I went through all the trouble of building a product for one of these ideas how would I know if anyone would even be interested in using it? I got scared and took a break for a week. All these ideas seemed too big and the chance that they would take off into the atmosphere was slim (in my mind anyways). I was learning more and more about solopreneurship as the weeks went on so I decided to build a product centered around everything I was learning about. The idea was simple. Enter a business idea and use AI to give the user details about how to market it, who their target customers were, what to write on their landing page, etc. All for a measly $27 per use. I quickly built it and launched on March 3rd 2024. I posted about it on Indie Hackers, Reddit and Hacker News. I was so excited about the prospect of earning my first internet $! Surely everyone wanted to use my product! Nope...all I got was crickets. I was quickly brought back down to earth. That was until 5 days later. I looked at my phone and had a new Stripe notification! Cha-ching! My first internet $. What a feeling! That was goal number 1 complete. It would be another 6 days before I would get my second sale...and then another 15 days to get my third. It was an emotional rollercoaster. I went from feeling like quitting the 9-5 was actually possible to thinking that maybe the ups and downs aren't worth it. On one hand I had made my first internet dollar so I should my ecstatic, and don't get me wrong, I was but I wanted more. More validation that I could do this long term. By May I was starting to give up on the product. I had learned so much in the past few months about marketing, SEO, building an audience, etc. and I wanted to build something that I thought could have more success so I focused on one critical thing that I had learned about. What was it? Building a product that had SEO potential. A product that I knew hundreds of people were looking for. See this was my thinking - If I could find a keyword that people were searching for on Google hundreds/thousands of times every month and it was easy to rank high on search engines then I would go all in (in SEO land this equates to a Keyword that has a Keyword Difficulty of = 500). I began researching and found that the keyword "micro saas ideas" was being searched for around 600 times each month. Micro Saas was something that really interested me. It was perfect for solopreneurs. Small software products that 1 person could build. What's not to like if you're in the game of software and solopreneurship? Researching keywords like this became like a game for me. I was hooked. I was doing it every day, finding gems that were being searched for hundreds and thousands of times every month that still had potential. That's when I came up with my next product idea. I decided to create a database of Micro Saas Ideas all with this sort of SEO potential. See if you can build a product that you know people are looking for then that's all the validation you need. So I put this theory to the test. I created a database of Micro Saas Ideas with SEO Potential and launched it in June 2024. This time it was different. I made $700 in the first week of launching. A large contrast to my previous failed attempt at becoming the worlds greatest solopreneur. Since launch I have grown the product to $3K and I couldn't be happier. I know what you're saying, $3K isn't a lot. But it's validation. It's validation that I can earn $ online. Validation that I can grow a business and it gives me hope that one day I'll be able to quit that 9-5 grind. My plan is to keep growing the business. I expect there to be a few challenges up ahead but I'll tackle them as I go and learn from the failures and successes. I have a newsletter where I share Micro Saas Ideas with SEO potential every week which I'll leave below in the first comment. Feel free to come along for the ride. If not I hope this post brings you some value If you're thinking about starting as a solopreneur, stop thinking and start doing, you won't regret it.

[CASE STUDY] From 217/m to $2,836/m in 9 months - Sold for $59,000; I grow and monetise web traffic of 5, 6, 7 figures USD valued passive income content sites [AMA]
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[CASE STUDY] From 217/m to $2,836/m in 9 months - Sold for $59,000; I grow and monetise web traffic of 5, 6, 7 figures USD valued passive income content sites [AMA]

Hello Everyone (VERY LONG CASE STUDY AHEAD) - 355% return in 9 months Note: I own a 7-figures USD valued portfolio of 41+ content sites that generates 5-6 figures USD a month in passive income. This is my first time posting in this sub and my goal is to NOT share generic advice but precise numbers, data and highly refined processes so you can also get started with this business yourself or if you already have an existing business, drive huge traffic to it and scale it substantially (get more customers). I will use a case study to explain the whole process. As most of us are entrepreneurs here, explaining an actual project would be more meaningful. In this case study I used AI assisted content to grow an existing site from $217/m to $2,836/m in 9 months (NO BACKLINKS) and sold it for $59,000. ROI of 3 months: 355% Previous case studies (before I give an overview of the model) Amazon Affiliate Content Site: $371/m to $19,263/m in 14 MONTHS - $900K CASE STUDY \[AMA\] Affiliate Website from $267/m to $21,853/m in 19 months (CASE STUDY - Amazon?) \[AMA\] Amazon Affiliate Website from $0 to $7,786/month in 11 months Amazon Affiliate Site from $118/m to $3,103/m in 8 MONTHS (SOLD it for $62,000+) Note: You can check pinned posts on my profile. Do go through the comments as well as a lot of questions are answered in those. However, if you still have any questions, feel free to reach out. This is an \[AMA\]. Quick Overview of the Model Approach: High traffic, niche specific, informative content websites that monetise its traffic through highly automated methods like display ads and affiliate. The same model can be applied to existing businesses to drive traffic and get customers. Main idea: Make passive income in a highly automated way Easy to understand analogy You have real estate (here you have digital asset like a website) You get rental income (here you get ads and affiliate income with no physical hassle, in case you have a business like service, product etc. then you can get customers for that too but if not, it's alright) Real estate has value (this digital asset also has value that can be appreciated with less effort) Real estate can be sold (this can be sold too but faster) IMPORTANT NOTE: Search traffic is the BEST way to reach HUGE target audience and it's important when it comes to scaling. This essentially means that you can either monetise that via affiliate, display etc. or if you have a business then you can reach a bigger audience to scale. Overview of this website's valuation (then and now: Oct. 2022 and June 2023) Oct 2022: $217/m Valuation: $5,750.5 (26.5x) - set it the same as the multiple it was sold for June 2023: $2,836/m Traffic and revenue trend: growing fast Last 3 months avg: $2,223 Valuation now: $59,000 (26.5x) Description: The domain was registered in 2016, it grew and then the project was left unattended. I decided to grow it again using properly planned AI assisted content. Backlink profile: 500+ Referring domains (Ahrefs). Backlinks mean the sites linking back to you. This is important when it comes to ranking. Summary of Results of This Website - Before and After Note: If the terms seem technical, do not worry. I will explain them in detail later. Still if you have any questions. Feel free to comment or reach out. |Metric|Oct 2022|June 2023|Difference|Comments| |:-|:-|:-|:-|:-| |Articles|314|804|\+490|AI Assisted content published in 3 months| |Traffic|9,394|31,972|\+22,578|Organic| |Revenue|$217|$2,836|\+$2,619|Multiple sources| |RPM (revenue/1000 web traffic)|23.09|$88.7|\+$65.61|Result of Conversion rate optimisation (CRO). You make changes to the site for better conversions| |EEAT (expertise, experience, authority and trust of website)|2 main authors|8 authors|6|Tables, video ads and 11 other fixations| |CRO|Nothing|Tables, video ads |Tables, video ads and 11 other fixations || &#x200B; Month by Month Growth |Month|Revenue|Steps| |:-|:-|:-| |Sept 2022|NA|Content Plan| |Oct 2022|$217|Content Production| |Nov 2022|$243|Content production + EEAT authors| |Dec 2022|$320|Content production + EEAT authors| |Jan 2023|$400|Monitoring| |Feb 2023|$223|Content production + EEAT authors| |Mar 2023|$2,128|CRO & Fixations| |April 2023|$1,609|CRO & Fixations| |May 2023|$2,223|Content production + EEAT authors| |June 2023|$2,836|CRO and Fixations| |Total|$10,199|| &#x200B; What will I share Content plan and Website structure Content Writing Content Uploading, formatting and onsite SEO Faster indexing Conversion rate optimisation Guest Posting EEAT (Experience, Expertise, Authority, Trust) Costing ROI The plans moving forward with these sites &#x200B; Website Structure and Content Plan This is probably the most important important part of the whole process. The team spends around a month just to get this right. It's like defining the direction of the project. Description: Complete blueprint of the site's structure in terms of organisation of categories, subcategories and sorting of articles in each one of them. It also includes the essential pages. The sorted articles target main keyword, relevant entities and similar keywords. This has to be highly data driven and we look at over 100 variables just to get it right. It's like beating Google's algorithm to ensure you have a blueprint for a site that will rank. It needs to be done right. If there is a mistake, then even if you do everything right - it's not going to work out and after 8-16 months you will realise that everything went to waste. Process For this project, we had a niche selected already so we didn't need to do a lot of research pertaining to that. We also knew the topic since the website was already getting good traffic on that. We just validated from Ahrefs, SEMRUSH and manual analysis if it would be worth it to move forward with that topic. &#x200B; Find entities related to the topic: We used Ahrefs and InLinks to get an idea about the related entities (topics) to create a proper topical relevance. In order to be certain and have a better idea, we used ChatGPT to find relevant entities as well \> Ahrefs (tool): Enter main keyword in keywords explorer. Check the left pain for popular topics \> Inlinks (tool): Enter the main keyword, check the entity maps \> ChatGPT (tool): Ask it to list down the most important and relevant entities in order of their priority Based on this info, you can map out the most relevant topics that are semantically associated to your main topic Sorting the entities in topics (categories) and subtopics (subcategories): Based on the information above, cluster them properly. The most relevant ones must be grouped together. Each group must be sorted into its relevant category. \> Example: Site about cycling. \> Categories/entities: bicycles, gear and equipment, techniques, safety, routes etc. \> The subcategories/subentities for let's say "techniques" would be: Bike handling, pedaling, drafting etc. Extract keywords for each subcategory/subentity: You can do this using Ahrefs or Semrush. Each keyword would be an article. Ensure that you target the similar keywords in one article. For example: how to ride a bicycle and how can I ride a bicycle will be targeted by one article. Make the more important keyword in terms of volume and difficulty as the main keyword and the other one(s) as secondary Define main focus vs secondary focus: Out of all these categories/entities - there will be one that you would want to dominate in every way. So, focus on just that in the start. This will be your main focus. Try to answer ALL the questions pertaining to that. You can extract the questions using Ahrefs. \> Ahrefs > keywords explorer \> enter keyword \> Questions \> Download the list and cluster the similar ones. This will populate your main focus category/entity and will drive most of the traffic. Now, you need to write in other categories/subentities as well. This is not just important, but crucial to complete the topical map loop. In simple words, if you do this Google sees you as a comprehensive source on the topic - otherwise, it ignores you and you don't get ranked Define the URLs End result: List of all the entities and sub-entities about the main site topic in the form of categories and subcategories respectively. A complete list of ALL the questions about the main focus and at around 10 questions for each one of the subcategories/subentities that are the secondary focus Content Writing So, now that there's a plan. Content needs to be produced. Pick out a keyword (which is going to be a question) and... Answer the question Write about 5 relevant entities Answer 10 relevant questions Write a conclusion Keep the format the same for all the articles. Content Uploading, formatting and onsite SEO Ensure the following is taken care of: H1 Permalink H2s H3s Lists Tables Meta description Socials description Featured image 2 images in text \\Schema Relevant YouTube video (if there is) Note: There are other pointers link internal linking in a semantically relevant way but this should be good to start with. Faster Indexing Indexing means Google has read your page. Ranking only after this step has been done. Otherwise, you can't rank if Google hasn't read the page. Naturally, this is a slow process. But, we expedite it in multiple ways. You can use RankMath to quickly index the content. Since, there are a lot of bulk pages you need a reliable method. Now, this method isn't perfect. But, it's better than most. Use Google Indexing API and developers tools to get indexed. Rank Math plugin is used. I don't want to bore you and write the process here. But, a simple Google search can help you set everything up. Additionally, whenever you post something - there will be an option to INDEX NOW. Just press that and it would be indexed quite fast. Conversion rate optimisation Once you get traffic, try adding tables right after the introduction of an article. These tables would feature a relevant product on Amazon. This step alone increased our earnings significantly. Even though the content is informational and NOT review. This still worked like a charm. Try checking out the top pages every single day in Google analytics and add the table to each one of them. Moreover, we used EZOIC video ads as well. That increased the RPM significantly as well. Both of these steps are highly recommended. Overall, we implemented over 11 fixations but these two contribute the most towards increasing the RPM so I would suggest you stick to these two in the start. Guest Posting We made additional income by selling links on the site as well. However, we were VERY careful about who we offered a backlink to. We didn't entertain any objectionable links. Moreover, we didn't actively reach out to anyone. We had a professional email clearly stated on the website and a particularly designated page for "editorial guidelines" A lot of people reached out to us because of that. As a matter of fact, the guy who bought the website is in the link selling business and plans to use the site primarily for selling links. According to him, he can easily make $4000+ from that alone. Just by replying to the prospects who reached out to us. We didn't allow a lot of people to be published on the site due to strict quality control. However, the new owner is willing to be lenient and cash it out. EEAT (Experience, Expertise, Authority, Trust) This is an important ranking factor. You need to prove on the site that your site has authors that are experienced, have expertise, authority and trust. A lot of people were reaching out to publish on our site and among them were a few established authors as well. We let them publish on our site for free, added them on our official team, connected their socials and shared them on all our socials. In return, we wanted them to write 3 articles each for us and share everything on all the social profiles. You can refer to the tables I shared above to check out the months it was implemented. We added a total of 6 writers (credible authors). Their articles were featured on the homepage and so were their profiles. Costing Well, we already had the site and the backlinks on it. Referring domains (backlinks) were already 500+. We just needed to focus on smart content and content. Here is the summary of the costs involved. Articles: 490 Avg word count per article: 1500 Total words: 735,000 (approximately) Cost per word: 2 cents (includes research, entities, production, quality assurance, uploading, formatting, adding images, featured image, alt texts, onsite SEO, publishing/scheduling etc.) Total: $14,700 ROI (Return on investment) Earning: Oct 22 - June 23 Earnings: $10,199 Sold for: $59,000 Total: $69,199 Expenses: Content: $14,700 Misc (hosting and others): $500 Total: $15,200 ROI over a 9 months period: 355.25% The plans moving forward This website was a part of a research and development experiment we did. With AI, we wanted to test new waters and transition more towards automation. Ideally, we want to use ChatGPT or some other API to produce these articles and bulk publish on the site. The costs with this approach are going to be much lower and the ROI is much more impressive. It's not the the 7-figures projects I created earlier (as you may have checked the older case studies on my profile), but it's highly scalable. We plan to refine this model even further, test more and automate everything completely to bring down our costs significantly. Once we have a model, we are going to scale it to 100s of sites. The process of my existing 7-figures websites portfolio was quite similar. I tested out a few sites, refined the model and scaled it to over 41 sites. Now, the fundamentals are the same however, we are using AI in a smarter way to do the same but at a lower cost, with a smaller team and much better returns. The best thing in my opinion is to run numerous experiments now. Our experimentation was slowed down a lot in the past since we couldn't write using AI but now it's much faster. The costs are 3-6 times lower so when it used to take $50-100k to start, grow and sell a site. Now you can pump 3-6 more sites for the same budget. This is a good news for existing business owners as well who want to grow their brand. Anyway, I am excited to see the results of more sites. In the meantime, if you have any questions - feel free to let me know. Best of luck for everything. Feel free to ask questions. I'd be happy to help. This is an AMA.

[Ultimate List] A list of Marketing Tools That I’ve tested over the years and found helpful to do better marketing with less work. More than 50 Tools To Help you with Marketing, Copywriting & Sales!
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[Ultimate List] A list of Marketing Tools That I’ve tested over the years and found helpful to do better marketing with less work. More than 50 Tools To Help you with Marketing, Copywriting & Sales!

Starting to focus on marketing for your business, You will come across the same tools mentioned over and over by marketers. I would like to mention here tools that you might haven’t seen going viral in the community but actually will help you grow faster and efficiently. Starting off with My favourite Marketing Channel! #Email Marketing For SMBs Convertkit / Mailerlite / Mailchimp - These 3 Platforms are the best options for SMBs and entrepreneurs just starting out with email marketing. All 3 have free plans up to 1,000 subscribers. Scribe - Email Signature Tool, Create Great Email signatures for your emails. Liramail - Most Email marketing platforms don’t offer great email templates. This tool will help you build great email templates with drag and drop. Quick mail Auto-Warmer - Most Businesses at the beginning don’t know what to do when open rate drops. You need to use an email warmer like this to keep it up. #Email Marketing For Big Businesses SendGrid - Overall Email Marketing Tools, this tool is best for brands that have huge email lists and email marketing is the key marketing channel. Braze - This tool is leading in email marketing for large Email senders. When I was working for agencies, this was one of the best email marketing tools I had used. NeoCertified - Protect your emails for spammers and threats. To keep your email list healthy, this is a must have! Sparkloop - Referral Marketing For Email Campaigns. Email can generate great huge amount of referrals for you and Sparkloop makes it easier. #Cold Emails & Lead Generation Hunter - A Great Tool to scrape emails from domain names. The tool comes with a green free plan but Pro plan is worth the amount of features it provides. Icyleads - It’s better than Hunter as it’s heavily focused on the sales and prospecting to help you derive great results from your campaigns. Mailshake - Beginner Friend Cold Email Tool with Great features like email list warming. #Communication Tools Twilio - One do the best customer engagement platform used by Companies like Stripe and mine too. Chatlio - Use Live chat feature on your website with slack integration. My favourite easier to catch up on conversations through slack integration. Intercom - Used by Most Marketers, Industry Leading customer communication platform. Great for beginners! Chatwoot - Another Amazing Communication Tool but the best part is they have a great free plan useful for new businesses. Loom - Communicate with your audience through Videos. Loom is great for SaaS and to show human interaction to close new visitors effectively. #CRM Outseta - This tool provides great CRM and their billing system is better than other tools out their which makes it stands out! Hubspot - I don’t think this tool needs an introduction because Hubspot’s CRM is the best in industry. Salesflare - This CRM is a great alternative to hubspot as it’s beginner friendly and helpful for SMBs. #SEO Tools Ahrefs - One of the best SEO tool in the industry. They also just launched a bunch of free tools to help SEO beginners. Screaming frog - The only website crawler I have used since I bought my first domain. It’s the best! Ubersuggest- The Tool by Neil Patel is the best SEO tool for you. (I’m Joking, it’s the worst) Contentking - This tool is good at Real-time SEO Auditing, they do a lot of Marketing work through Newsletters. If you are subscribed to any SEO newsletter. You may have seen this tool. SEOquake & Semrush - SEOquake is a great tool to conduct on-page analysis, SERP, and much more. Great tool but it’s owned by Semrush. You should go for Semrush because that tool will cover all SEO aspects for you. #Content Marketing Buzzsumo - This tool is great for content research and but you may find the regular emails pretty annoying sometimes. Contentrow - Analyse Your Content and find it’s strength. Highly recommended who are weak at content structuring like me. Grammarly - If you are not a native English speaker like me, you might think you need it or not. You need it for sure for grammar corrections. #Graphic Design Tools Visme - At agencies, Infographics can be more effective than usual postscript. Visme is a graphic design tool focused on infographics and designs related to B2B and B2C. It’s great for agencies! Glorify - A Graphic Design Tool focused on E-commerce, filled with Designs useful for E-commerce store owners. Canva - All-in-one Industry leading Graphic Design Tool that everyone knows and every template is overused now. Adobe Creative Cloud ( previously Sparkpost) - It’s a great alternative to Canva filled with Amazing Stock images to use in your visuals but the only backlash is the exports in this tool are not high quality. Snaps - A Canva Alternative that might not have overused templates for your Social Accounts. #Advertising Tools Plai - It’s a great PPC tool to create Ads for Instagram and Tiktok. Wordstream - It’s an industry leading PPC Tool, great for Ad Grading and auditing. AdEspresso - This Is a tool by Hootsuite. They have a lot of Data sourced at the backend, which helps in Ad optimisation through this tool. That’s the reason I recommend this tool. #Video Editing Tools Veed Studio - I have been using Veed from last year. It’s one of the best Video Marketing Tool Optimized for Instagram & Tiktok. Synthesia - It’s a new AI video generation platform. From last few months, if you have seen marketing agencies including Videos in Emails. The chances are that’s not a Agency member taking but AI generated Human. Motionbox - It’s also a great video editing tool focused on video editing for Digital Marketers. Jitter Video - It’s a great motion design tool. Comes with great templates, the only place where other tools I mentioned lacks. It’s great and beginner friendly. #Copywriting Jasper AI - Google’s John Mueller says AI generated content is banned on Search but I think with Jasper AI you can generate SEO optimised Content but you have to put in some efforts like at least give 30 minutes for editing the Copy by yourself. Copy AI - Another AI tool to help you write better copy. This one is more focused on helping you write copy suitable for Ads and Social media campaigns. Hemingway App - To help you write more clearly and Bold. This tool is better than Grammarly if you look for writing perspective and it’s free. #Social Media Management App I’ve used a Lot of SMM Tools and that’s why going to mention all of them with a short review. Sprout social - The Best with deep insights coverage. Hootsuite - Great Scheduling tool just under sprout social. Later - Heavily Focused on Instagram from beginning and Now Tiktok too. SkedSocial - It’s like a Later alternative with great addition features like link-in-bio. Facebook’s Business Manager- Great but sometimes bugs can make a huge issue for you and customer support is like dead. Tweet Hunter & Hypefury- Both are Twitter Scheduling tools growing very fast on platform and are great for growth. Buffer - It’s a great tool but I haven’t seen any new updates to help with management. Zoho Social - It’s a great SMM tool and if you use other marketing solutions from Zoho. It’s a must have! #Market Research Tool • SparkToro - That’s the only one I have ever used. It’s great for audience research and comes with great customer service. Founded by Rand Fishkin, it’s one of the best research tool. #Influencer Marketing & UGC InfluenceGrid - A free search engine To find Tiktok & Instagram Influencers for your campaigns. Tiktok Creative Center- TikTok’s in-built tool called “Creative Center” is the best to find content trends, audience demographics and much more. Archive - Find Instagram Stories and Posts mentioning Your brands and use them as Ads for your business Marketing. #Landing Page Builders Leadpages - Its a great landing page builder because the integration and drag-and-drop features makes it easier to work with! Cardd co - A Great Landing page builder with easy step up but it lacks the copywriting and tracking features. Instapage - It’s one of the best out and I think the overall product is effective enough to help you stand out with your landing page. Unbounce - It’s a great alternative to Instapage due its well polished landing page templates that might be helpful for you. #Community Building Mighty Networks - A Great Community building platform, and you can also sell courses within the platform. Circle so - A great alternative to Mighty networks focused on Communities specifically. We are currently using for small community Of ours. #Sales Tools Drift - You can get much more out of Drift than just sales tools but The Sales solutions provided in Drift are one of the best. Salesforce - It’s the industry Sales solution provider. A go-to and have various pricing plans making it suitable for majority of SMBs. #Social Proof Tools People don’t have enough time to search across internet to decide to trust you after seeing your Ad first time. That’s what you might be facing too. Here are two tools I absolutely love for social proof! Use Proof - Show Recent Activities occurring on your website and build the trust of your visitors. Testimonial to - Gather Testimonials across Social Media platforms related to your business with this tool. Capture tweets and comments mentioning your brands and mention them. #Analytics Tools Plausible Analytics- A privacy friendly Analytics alternative to Google Analytics if you hate Analytics 4 like me. Mixpanel - Product Analytics and funnel reports better than Google Analytics. #Reddit Marketing Gummysearch- This tool will help To find your target audience on Reddit and interact with them with its help and close your new customers. Howitzer- It’s another pretty similar tool to Gummysearch focused on Reddit cold outreach to get clients and new customers. Both are great but Gummysearch provides better customer support while Howtizer is helpful on a large scale Reddit Marketing. #Text Marketing Klaviyo - It’s an email + SMS marketing tool, it’s taking up space in marketing industry very quickly as an industry leader due to its great integrations but you need to learn the platform usage to maximise the outcome. Cartloop - This tool provides great text marketing solutions with integration with Spotify and other e-commerce marketing tools. Attentive Mobile - This is my favourite Text marketing tool due to the interactive dashboard + they have a library of Text marketing examples to help you out with your campaigns. #Other Tools I have used throughout my journey! Triple Whale - It’s a great E-commerce marketing tools with Triple pixel to help you track your campaigns more efficiently. Fastory - To create well optimized Instagram & Tiktok Stories for your business. Jotform - Online Form Builder with integrations with leading marketing tools. Gated - As an entrepreneur and marketer, you may receive a bunch of unwanted emails. Use Gated to get rid of them and receive useful mails only! ClickUp- The main Tool for Project Management, one of the best and highly recommended. Riverside - Forget Zoom or Google Meet, For your Podcast Interviews and Marketing conferences. You need riverside with great video quality and recording features. Manychat- Automate your Instagram DMs and interact with your followers more efficiently + sell out your products/ services when you are offline. Calendy - To schedule meetings with your ideal clients. ServiceProviderPro - It’s a client portal for SEO & Growing Agencies, very helpful in scaling agencies. SendCheckit - Compare your Email Subject Lines with 100,000+ others in the database for free. Otter AI - Using AI track your meetings more effectively, you can easily edit, annotate and share notes from the meetings. Ryte - Optimise your website User experience with this tool focused on UX aspects + SEO too. PhantomBuster - Scrape LinkedIn Profile and Data from Facebook/LinkedIn groups. I clearly love this tool! #Honourable Mentions Zapier - The Only tool you need to integrate your favourite tool with a new effective tool. Elementor - That’s what I use for web design and it’s great! Marketer Hire - To hire world class marketers to work with you. InShot & Capcut - I create Instagram Reels and TikTok’s and life without these tools isn’t possible. Nira - It’s a great tool to Manage your workspace and this tool has launched many marketing templates in-built helpful for marketers and also entrepreneurs. X - The tool you love that wasn’t mentioned here is valuable and I honour that tool and share that if you would like to! I mean thanks for reading what I have curated all over my life as a marketer. I share 5 Marketing Tools, 5 Marketing Resources and 1 Free Resourceevery week in my newsletter, you can subscribe here to receive that for free. Also, You can read an expanded list of email marketing tools in this Reddit post!

100 best ai sustainable business ideas in 2025
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Low_Philosopher1792This week

100 best ai sustainable business ideas in 2025

AI in Renewable Energy AI-powered smart solar panel optimization Predictive maintenance for wind turbines AI-driven energy storage management AI-based microgrid optimization Smart grid energy forecasting AI-powered water desalination efficiency AI-driven carbon footprint reduction software AI-powered hydropower efficiency monitoring AI for geothermal energy exploration AI-driven green hydrogen production optimization AI in Waste Management & Recycling AI-based waste sorting robots Smart recycling bins with AI recognition AI-powered food waste management AI-driven upcycling marketplace AI-enabled e-waste management solutions AI-powered sustainable packaging optimization AI-driven landfill management systems AI-powered plastic waste tracking and reduction AI-based waste-to-energy conversion AI-driven composting automation AI in Water Conservation AI-powered leak detection and water conservation AI-driven smart irrigation systems AI-based flood prediction and mitigation AI-powered ocean plastic cleanup robots AI-driven rainwater harvesting optimization AI-based groundwater level monitoring AI-powered desalination energy efficiency AI-driven smart water meters AI-powered wastewater treatment optimization AI-based water pollution monitoring AI in Sustainable Agriculture AI-driven precision farming AI-powered vertical farming automation AI-based pest and disease prediction AI-powered livestock health monitoring AI-driven soil health analysis AI-powered regenerative agriculture analytics AI-driven smart greenhouses AI-powered crop rotation optimization AI-based carbon farming solutions AI-powered sustainable aquaculture AI in Transportation & Mobility AI-powered electric vehicle (EV) battery optimization AI-driven smart traffic management AI-powered EV charging station optimization AI-based sustainable urban mobility planning AI-powered drone delivery for carbon reduction AI-driven logistics and supply chain sustainability AI-powered smart public transport systems AI-driven sustainable aviation fuel optimization AI-powered bicycle-sharing optimization AI-driven AI carpooling and ride-sharing efficiency AI in Green Manufacturing AI-powered energy-efficient manufacturing AI-driven supply chain sustainability analytics AI-based material waste reduction AI-powered sustainable fashion production AI-driven predictive demand to reduce overproduction AI-powered eco-friendly textile manufacturing AI-driven 3D printing for sustainable manufacturing AI-powered emission reduction in factories AI-driven green construction material optimization AI-based lifecycle assessment for eco-products AI in Carbon Offsetting & Climate Action AI-powered carbon credit marketplaces AI-driven tree planting optimization AI-based carbon capture efficiency enhancement AI-powered reforestation tracking and monitoring AI-driven climate risk prediction AI-powered environmental compliance software AI-driven sustainable investment analysis AI-based corporate sustainability tracking AI-powered carbon accounting and reporting AI-driven decarbonization roadmaps for businesses AI in Sustainable Smart Cities AI-powered urban energy efficiency monitoring AI-driven AI-powered smart lighting for cities AI-based pollution monitoring and reduction AI-driven green building automation AI-powered smart HVAC energy optimization AI-driven urban tree canopy management AI-powered digital twins for sustainable city planning AI-based urban noise pollution monitoring AI-powered public waste management optimization AI-driven citizen engagement for sustainability AI in Eco-Friendly Consumer Solutions AI-powered sustainable shopping assistant AI-driven personal carbon footprint tracking app AI-powered second-hand marketplace optimization AI-driven sustainable food delivery services AI-powered ethical supply chain transparency AI-driven zero-waste grocery stores AI-powered green subscription services AI-driven sustainable tourism planning AI-powered smart home energy efficiency optimization AI-driven personal finance for sustainability investments AI in Sustainable Healthcare & Well-being AI-powered climate impact on health analytics AI-driven sustainable hospital management AI-based predictive disease outbreak prevention AI-powered mental health solutions for eco-anxiety AI-driven green pharmaceutical production AI-powered sustainable medical waste management AI-based air quality health impact monitoring AI-driven climate-friendly diet and nutrition planning AI-powered fitness and well-being optimization for sustainability AI-driven telemedicine to reduce healthcare emissions These AI-driven sustainable business ideas offer high growth potential while making a positive impact on the planet. Let me know if you want details on a specific idea or need help with implementation strategies!

Why the value of writing code and other digital services is going to zero
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BalloonWheelieThis week

Why the value of writing code and other digital services is going to zero

I must preface this with a trigger warning because I make some statements in this post that might be upsetting to some. This post discusses my experience building in the new era of entrepreneurship, which is one where the founder is the center of the universe, and the consultants, overpriced SaaS, and corporate swamp creatures are replaced by single-user custom software, bots, and self-hosted automations. If you work in the legacy economy, I really don't intend to stress you out or say things you are doing are quickly becoming irrelevant, but I must share the reality of how I am operating, because I would like to hear from others who are doing the same, or desire to do the same. I am currently operating with the belief that AI-powered tools are going to make 1-person million dollar businesses much more common. Building anything digital is becoming extremely easy, cheap, and quick to implement. The value of code and digital tools is approaching zero, or at most 5% of what it currently is. Right now, the most powerful AI tools are aimed at developers, so folks who have some technical and business ability basically have nothing holding them back aside from the speed of their brain right now. I happen to be a part of the cohort, and am building like there is no tomorrow, but I don't believe this cohort is actually all that big. The next hurdle to unlock the new era of entrepreneurship is empowering every entrepreneur to build at the same pace that is currently locked behind having technical ability. This cohort is huge (millions, if the number of people in this sub is any indication). This post is aimed at them (you?). If you are part of this cohort, what is holding you back from launching a new product for near-zero cost? What is too complicated, too expensive, too unknown for you to be able to build your new/current business at maximum speed? I look forward to seeing the replies, I hope some insights shared can help the community, and be a catalyst for more tools to enable non-technical founders to launch. I will now share some of how I am testing, launching, and selling as a one-man-show. This will be a little bit technical, but if the output of any layer of my stack is something you want, please comment because maybe someone will build a cheap way of accessing it without needing to manage the code yourself. \#1 BOTS I cannot overstate how much leverage bots have created for me. I run all of my bots locally and interface with with via Telegram. Bots do things like: \- watch social media pages, forums, subreddits, etc related to my customers and notify me of what is going on, and suggest SEO blog posts that could be published to capture traffic related to the topic. with a single message, my bot will generate a blog post, send it to me for review, apply edits i suggest, and then publish it live, all from within telegram \- pay attention to all my key metrics/analytics, and attempt to find insights/corrolations (ex. there is a lot of traffic on this page, blog post, video, etc. here's why, and how we can take advantage of it to drive business goals) \- repurposing content. i have dozens of social media profiles that are 100% run by bots, they are all related to my customer niches and will do things like post news, snippets from my blogs, interact with human creators in the niche, etc. this builds my audience automatically which I can then advertise to/try to convert into paying customers, since they are interested in the things my bot is posting and become followers, it's like automated qualified lead gen 24/7 across every social platform and every niche I care about. you may be thinking by now that this post is made by a bot, but you will have to trust me that this is 100% hand-written by my sleep-deprived brain. let's continue: \#2 replacing every SaaS with a shitty version of it designed for what i need out of it it's absurd that we pay ten's of dollars per seat per month for basic digital functions like chat (slack), CRM (active camppaign, sales force, hubspot, etc), email stuff (mailchip, etc), link sharing (linktree, etc), website builders (wix, squarespace, etc), etc. all of these SaaS tools are overpriced and overbuilt. I believe many of them are going to be caught in the innovators dilemma and will go to 0. I don't use any of these anymore, I build and self-host my own shitty version of each of them that does only what i need out of the tool. for example, my CRM doesn't have a fancy drag and drop email builder and 10000 3rd party plugins, because i dont need any of that shit I just need to segment and communicate with my customers. if i need more features, i can generate them on the fly. \#3 working alone I have worked with cofounders in the past, raised money from investors, hired consultants, burned money and time, suffered sleepless nights from stress caused by other people not delivering, trying to convince others they are wrong, or they are pushing the company off a cliff, waste waste waste. no more of that. In the new age of entrepreneurship, the BUILDER (you and I) are the ones creating the value, and AI empowers us to do it alone. this might seem daunting, but there is no business problem that can't be solved with a detailed discussion sesh with chatgpt, no facts that can't be found with perplexity, and no task that can't be automated with claude. there is no need for anymore swamp creatures. you are the start and the end point, you don't need to rely on anyone else for anything. this may sound ignorant, but this is the conclusion I have come to believe, and it continues to be proven every day my businesses progress with me being the only human involved. This is getting quite long so I'll cut it here. I look forward to hearing about how you are operating in this new era and hopefully getting inspired/learning some new ideas to add to my current stack.

I spent 18 hours every week tracking marketing trends and latest news. Here are my predictions for 2024
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lazymentorsThis week

I spent 18 hours every week tracking marketing trends and latest news. Here are my predictions for 2024

1/ Securing Digital Footprint becomes #1 Priority For Chronically Online Users, Protecting their digital footprint will become one of the main things. We saw influencers getting cancelled over Old Content and Brands used Old Travis Kelce Tweets, we saw what could happen without digital footprint protection. Online Engagement Precautions will be taken again with Twitter & IG showing your usernames above ‘Algorithm Suggested Content’. What you like is more visible to other people in UI Design of these apps, another reason behind why Digital Footprint preservation will matter a lot in 2024. This will impact likes to viewership ratio on your organic and paid content. &#x200B; 2/  TikTok wants Long Videos with Storytelling As I was writing this report, TikTok also released their What’s Next 2024 Report. It focuses heavily on how the audiences on the app demand better storytelling and from the examples in the report, you can judge what TikTok wants. They also rolled out a 30-minute video upload limit. Engaging Content over 1-Minute Mark to keep the audiences longer on the app. I highlighted in the first trend, every social media platform wants the same thing, more time spent. 3/ Use of Shop the Look While Streaming Netflix or Amazon Prime. This year’s one of the most successful TV series, The Bear caused Men to go mad for the T-Shirt worn by Jeremy Allen White in the show. Showing us how TV Shows influence or encourage us to dress in a particular way. It’s nothing new, TV Shows like Friends & Gossip Girl influenced all demographics when they came out. But now, Streamings Services such as Roku & Amazon enable consumers to shop the look while watching the TV Shows. Many Brands will jump on these opportunities in upcoming months. 4/ Brands in Comments & Memes are the new norm By Summer 2024, Most Online Users & Creators will no longer feel too excited or answered when they see your brand in the comments. Why? It’s becoming too common for Brands to show in comments under viral content about them. Or Brands being funny with Internet Culture Trends is known to most users. The Saturation of Every Brand being funny and being present leads to increased competition of levitating the content quality. &#x200B; 5/ Marketers decrease their focus on Traffic & Views With AI recommendations taking over, The Structure of content distributing on social media is changing, the same goes for SEO. Conversational AIs are changing how web traffic is distributed to publishers. An Increased focus on managing the conversion rate and landing page relevancy will be the main focus. 6/ OOH is kind of making a comeback. First, US OOH Ads Industry grew 1.1% in Q3 2023. Second, Outfront Media reported slight revenue increase in Q3 as Billboard Ad Revenue grew in Q3. Many Brands in UK are also aligning more toward traditional media Channels. With Burger King in UK focusing on only OOH for Christmas this year and Fashion Brands like SSENSE launching Billboards as Branding Play. 7/ Rise of Curation Continues This Year, we witnessed success of Pinterest Shuffles App, Gen-Z loved it. Similar Success with formats like IG photo dump & TikTok ‘My Fav Finds’ Carousels being the center of Gen-Z Content. Just look at this recent trend and tell me Curation isn’t personal to Online Teens. Spotify won with their idea of curating Songs with Astrology-type signs. The Fashion Products with Curated Emojis and Stickers on them, that scrappy curated approach is predicted to grow in 2024, data from Pinterest. 8/ Use of AI to Trace Consumers in the wild This year we saw a huge trend of people using Image/ face recognition tools to find or dig dirt about famous people. The biggest example was Dillion Dannis exposing Multiple images of Logan Paul’s girlfriend using AI tools. (Which was Obviously bad) But next year, I believe with better rules, big brands like Adidas or Nike will be able to find worldwide micro-influencers & Online Consumers seen wearing adidas. And partnering with them on a large scale through automated outreach. 9/ More Cartoons than Influencer-Brand Products. All the Cartoon shows are seeing huge rise on IG and TikTok, Shaun the sheep is viral, Snoopy was big this year, Sesame Street’s TikTok is working. Aussie Show Bluey is making a huge spark in the US. More Brand collaborations are on the road. Why? Cartoons have built a very consistent identity and they have social channels. I know many see Cartoons as Kids Content but on social, looking at TikTok Account of Sesame Street & Snoopy. Last month, Powerpuff Girls launched a collaboration with Nike. &#x200B; 10/ The Best Trend to get people off social media &#x200B; Try to get people off the social media apps, build your own loops. You can’t rely on social and you clearly shouldn’t burn out trying to win on social and streaming with Paid Ads or without them. This matters a lot because data shares most of your customers buy from you once or twice a year. And then they interact with your content, how bad will you feel if the only thing they remember as your content is being on TikTok. Nothing about your brand. 11/ The Internet Aesthetic will Die for Cafes & Restaurants When I wrote my post about Instagram Marketing, I mentioned this issue of Every Account looking the same. In reality, It isn’t limited to IG Feeds, This Creator points out the same Problem, mentioning the aesthetic Standards from Internet are changing how new businesses approach their whole business. More Content from Cafes & Restaurants need to be around their people and neighbourhood. 12/ Echo Chambers & Sonic Influence All Podcasts are Echo Chambers because if people wanted a new perspective in form of value. We would have chosen debates, but we chose Podcasts to find new value while being in comfort. People are now looking for more value in comfort than ever, Podcasts will continue to rise. 13/ Clever AI Integration to Better Customer Journeys in B2B & B2C Marketing Agencies can provide clever solutions to B2B Companies, and help them overcome the tag of Boring Ads only. How? Ogilvy India created an AI Ad Campaign for Cadbury, allowing SMBs to have the Bollywood Actor endorse them. They used the AI voice generation allowing businesses to alter the voice and have Shah Rukh Khan endorse their shop. A similar approach was taken by IPG India, An AI Ad with Shah Rukh Khan allowing everyone to add their face in the Branded Content. &#x200B; If I sounded like an Old head in this report or I missed on some elements like Programmatic Advertising and PPC. I will try to include better analysis and new content about future trends. You can find the post shared with examples & research, linked here.

I tested hundreds of marketing tools in the last three years and these 50 made it to the list. I'll sum up my top 50 marketing tools with one or two sentences + give you pricings.
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SpicyCopyThis week

I tested hundreds of marketing tools in the last three years and these 50 made it to the list. I'll sum up my top 50 marketing tools with one or two sentences + give you pricings.

Hey guys, I'm working in a growth marketing agency. Marketing tools are 30% of what we do, so we use them a lot and experiment with the new ones as much as possible. There are thousands of tools and it's easy to get lost, so I wanted to share the tools we use most on a daily basis. And divide the list into 14 categories. I thought this could be handy for Entrepreneurs subreddit. Why adopt tools? I see marketing tools as tireless colleagues. If you can't hire an employee, choosing the right tool can solve your problems, because they Are super cheap. Work 7/24 for you. Don’t make mistakes. Don’t need management. (or needless management) Help you to automate the majority of your lead gen process. Onwards to the list. (With the pricings post ended up quite long, you can find a link in the end if you want to check the prices) Email marketing tools #1 ActiveCampaign is armed with the most complicated email automation features and has the most intuitive user experience. It feels like you already know how to use it. \#2 Autopilot is visual marketing automation and customer journey tool that helps you acquire, nurture based on behaviors, interest etc. #3 Mailjet: This is the tool we use to send out bulky email campaigns such as newsletters. It doesn't have sexy features like others but does its job for a cheap price. Email address finders #4 Skrapp finds email of your contacts by name and company. It also works with LinkedIn Sales Navigator and can extract thousands of emails in bulk + have a browser add-on. #5 Hunter: Similar to Skrapp but doesn't work with LinkedIn Sales Navigator directly. In addition, there are email templates and you can set up email campaigns. Prospecting and outreach tools #6 Prospect combines the personal emails, follow-up calls, other social touches and helps you create multichannel campaigns.  #7 Reply is a more intuitive version of Prospect. It is easy to learn and use; their UX makes you feel good and sufficient.  CRM tools #8 Salesflare helps you to stop managing your data and start managing your customers. Not yet popular as Hubspot and etc but the best solution for smaller B2B businesses. (we're fans) \#9 Hubspot: The most popular CRM for good reason and has a broader product range you can adopt in your next steps. Try this if you have a bulky list of customers because it is free. #10 Pardot: Pardot is by Salesforce, it's armed with features that can close the gap between marketing and sales. Sales Tools #11 Salesforce is the best sales automation and lead management software. It helps you to create complicated segmentations and run, track, analyze campaigns from the same dashboard. #12 LinkedIn Sales Navigator gives you full access to LinkedIn's user database. You can even find a kidnapped CEO if you know how to use it with other marketing automation tools like Skrapp. #13 Pipedrive is a simple tool and excels in one thing. It tracks your leads and tells you when to take the next action. It makes sales easier. #14 Qwilr creates great-looking docs, at speed. You can design perfect proposals, quotes, client updates, and more in a flash. We use it a lot to close deals, it's effective. #15 Crystalknows is an add-on that tells you anyone’s personality on LinkedIn and gives you a detailed approach specific to that person. It's eerily accurate. #16 Leadfeeder shows you the companies that visited your website. Tells how they found you and what they’re interested in. It has a free version. Communication Tools #17 Intercom is a sweet and smart host that welcomes your visitors when you’re not home. It’s one of the best chatbot tools in the market. #18 Drift is famous for its conversational marketing features and more sales-focused than Intercom. #19 Manychat is a chatbot that helps you create high converting Facebook campaigns. #20 Plann3r helps you create your personalized meeting page. You can schedule meetings witch clients, candidates, and prospects. #21 Loom is a video messaging tool, it helps you to be more expressive and create closer relationships. #22 Callpage collects your visitors’ phone number and connects you with them in seconds. No matter where you are. Landing page tools #23 Instapage is the best overall landing page builder. It has a broad range of features and even squirrel can build a compelling landing page with templates. No coding needed. #24 Unbounce can do everything that Instapage does and lets you build a great landing page without a developer. But it's less intuitive. Lead generation / marketing automation tools #25 Phantombuster is by far the most used lead generation software in our tool kit. It extracts data, emails, sends requests, customized messages, and does many things on autopilot in any platform. You can check this, this and this if you want to see it in action. #26 Duxsoup is a Google Chrome add-on and can also automate some of LinkedIn lead generation efforts like Phantombuster. But not works in the cloud. #27 Zapier is a glue that holds all the lead generation tools together. With Zapier, You can connect different marketing tools and no coding required. Conversion rate optimization tools #28 Hotjar tracks what people are doing on your website by recording sessions and capturing mouse movements. Then it gives you a heatmap. #29 UsabilityHub shows your page to a digital crowd and measures the first impressions and helps you to validate your ideas. #30 Optinmonster is a top tier conversion optimization tool. It helps you to capture leads and enables you to increase conversions rates with many features. #31 Notifia is one mega tool of widgets that arms your website with the wildest social proof and lead capturing tactics. #32 Sumo is a much simpler version of Notifia. But Sumo has everything to help you capture leads and build your email lists. Web scrapers #33 Data Miner is a Google Chrome browser extension that helps you scrape data from web pages and into a CSV file or Excel spreadsheet. #34 Webscraper does the same thing as Data Miner; however, it is capable of handling more complex tasks. SEO and Content #35 Grammarly: Your English could be your first language and your grammar could be better than Shakespeare. Grammarly still can make your writing better. #36 Hemingwayapp is a copywriting optimization tool that gives you feedback about your copy and improves your readability score, makes your writing bolder and punchier. Free. #37 Ahrefs is an all-rounder search engine optimization tool that helps you with off-page, on-page or technical SEO. #38 SurferSEO makes things easier for your on-page SEO efforts. It’s a tool that analyzes top Google results for specific keywords and gives you a content brief based on that data. Video editing and design tools #39 Canva is a graphic design platform that makes everything easy. It has thousands of templates for anything from Facebook ads, stylish presentations to business cards.  #40 Kapwing is our go-to platform for quick video edits. It works on the browser and can help you to create stylish videos, add subtitles, resize videos, create memes, or remove backgrounds. #41 Animoto can turn your photos and video clip into beautiful video slideshows. It comes handy when you want to create an advertising material but don’t have a budget. Advertising tools #42 AdEspresso lets you create and test multiple ads with few clicks. You can optimize your FB, IG, and Google ads from this tool and measure your ads with in-depth analytics. #43 AdRoll is an AI-driven platform that connects and coordinates marketing efforts across ads, email, and online stores. Other tools #44 Replug helps you to shorten, track, optimize your links with call-to-actions, branded links, and retargeting pixels #45 Draw.io = Mindmaps, schemes, and charts. With Draw.io, you can put your brain in a digital paper in an organized way. #46 Built With is a tool that finds out what websites are built with. So you can see what tools they're using and so on. #47 Typeform can turn data collection into an experience with Typeform. This tool helps you to engage your audience with conversational forms or surveys and help you to collect more data. #48 Livestorm helped us a lot, especially in COVID-19 tiles. It’s a webinar software that works on your browser, mobile, and desktop. #49 Teachable \- If you have an online course idea but hesitating because of the production process, Teachable can help you. It's easy to configure and customizable for your needs. #50 Viral Loops provides a revolutionary referral marketing solution for modern marketers. You can create and run referral campaigns in a few clicks with templates. Remember, most of these tools have a free trial or free version. Going over them one by one can teach you a lot and help you grow your business with less work power in the early stages of your business. I hope you enjoyed the read and can find some tools to make things easier! Let me know about your favorite tools in the comments, so I can try them out. \------ If you want to check the prices and see a broader explanation about the tools, you can go here.

We create AI software and provide AI automation for companies. Here is a list of the best AI tools for sales IMHO
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IntellectualAINCThis week

We create AI software and provide AI automation for companies. Here is a list of the best AI tools for sales IMHO

Here are some AI tools that are useful for sales. I tried to touch as many different parts of the sales process so the tools are all quite different but all useful for sales. I tried to include some of the best and underrated AI tools. Most of them are free so check them out if you want. I did not include ChatGPT as it can basically be used for anything with the right prompts. So these tools will be more research-oriented. A quick disclaimer – I work for the company Idealink where we create custom ChatGPT for businesses and other AI products. Apollo AI Seamless AI CoPilot AI Lavender AI Regie AI Gemini Plusdocs Make Midjourney Fireflies AI Apollo AI - Find potential customers Apollo is a platform for sales and business development. It offers a range of tools to find and engage with ideal customers. The platform has an extensive B2B database and features that streamline the sales process from prospecting to closing deals. Key Features: Extensive B2B Database: Apollo boasts a large, accurate database of over 275 million contacts, providing a wealth of potential leads and opportunities for sales teams. Data Enrichment and Lead Insights: The platform offers data enrichment capabilities, ensuring CRM systems are continuously updated with detailed and actionable lead information. AI-Driven Sales Engagement: Apollo's AI technology assists in crafting effective communication and prioritizing high-value leads, enhancing the overall sales engagement process. Comprehensive Sales Tools: The platform provides an integrated suite of tools for email, call, and social media engagement, combined with analytics and automation features to streamline the sales cycle. Tailored Solutions for Teams: Apollo offers customized solutions for different team types, including sales and business development, founders, and marketing teams, addressing specific needs and goals. Seamless AI - Sale process made easier Seamless.AI is an innovative B2B sales lead generation solution that allows sales teams to efficiently connect with their ideal customers. The platform's features provide accurate and up-to-date contact information and integrate easily with existing sales and marketing tools. Key Features: Real-Time Search Engine: Seamless.AI uses AI to scour the web in real time, ensuring the contact information for sales leads is current and accurate. Comprehensive Integration: Easily integrates with popular CRMs and sales tools like Salesforce, HubSpot, and LinkedIn Sales Navigator, enhancing productivity and eliminating manual data entry. Chrome Extension: Enhances web browsing experience for sales teams, allowing them to build lead lists directly from their browser. Pitch Intelligence and Writer: Tools for crafting effective sales messages and marketing content, personalized for each potential customer. Data Enrichment and Autopilot: Keeps customer data current and automates lead-building, supporting consistent lead generation. Buyer Intent Data and Job Changes: Offers insights into potential customers' buying intentions and keeps track of significant job changes within key accounts. CoPilot AI - Helps sales reps manage leads CoPilot AI is an advanced AI-powered sales support platform designed for B2B sales teams and agencies to drive consistent revenue growth. The tool focuses on using LinkedIn for sales prospecting, engagement, and conversion. Key Features: LinkedIn Lead Generation: Targets and automates outreach to high-intent LinkedIn leads, enhancing efficiency and scalability in lead generation. Personalized Messaging Automation: Facilitates sending of personalized, one-click messages at scale, maintaining a human touch in digital interactions. Sales Conversion Insights: Offers tools to understand and adapt to prospects' communication styles, improving the likelihood of conversion. Sales Process Optimization: Provides analytics to evaluate and refine sales strategies, identifying opportunities for improvement in the sales funnel. Industry Versatility: Adapts to diverse industries, offering tailored solutions for B2B sales, marketing, HR, and financial services sectors. Collaborative Team Tools: Enables team synchronization and collaboration, boosting productivity and synergy in sales teams Lavender AI - Email AI assistant Lavender AI is an AI-powered email tool that helps users write better emails. It provides real-time feedback and personalized suggestions to optimize email communication efficiency. Key Features: Email Coaching and Scoring: Lavender evaluates emails using AI and a vast database of email interactions, offering a score and tips for improvement. It identifies factors that might reduce the likelihood of receiving a reply, helping users refine their email content. Personalization Assistant: This feature integrates prospect data directly into the user's email platform, suggesting personalization strategies based on recipient data and personality insights to foster deeper connections. Adaptive Improvement: Lavender's scoring and recommendations evolve in real-time with changing email behaviors and practices, thanks to its generative AI and extensive data analysis, ensuring users always follow the best practices. Data-Driven Managerial Insights: The platform provides managers with valuable insights derived from actual email interactions, aiding them in coaching their teams more effectively based on real performance and communication trends. Broad Integration Capability: Lavender integrates with various email and sales platforms including Gmail, Outlook, and others, making it versatile for different user preferences and workflows. Regie AI - Great for business intelligence Regie.ai simplifies the sales prospecting process for businesses, using GenAI and automation to improve interactions with prospects. The platform offers tools like Auto-Pilot for automatic prospecting and meeting scheduling, Co-Pilot for sales rep support, and integrations with various CRM and sales engagement platforms. It also includes a Chrome Extension and CMS for content management and customization. Key Features: Automated Prospecting with Auto-Pilot: Regie.ai's Auto-Pilot feature autonomously prospects and schedules meetings, using Generative AI for Sales Agents to enhance outbound sales efforts. Audience Discovery and Content Generation: The platform identifies target accounts not in the CRM, generating relevant, on-brand content for each message, thus ensuring efficiency in list building and message personalization. Outbound Prioritization and Dynamic Engagement: It utilizes engagement and intent data to prioritize outreach to in-market prospects and adjust engagement strategies based on buyer responsiveness. Full Funnel Brand Protection and Analytics: Regie.ai ensures consistent use of marketing-approved language in all sales outreach and provides insights into campaign and document performance, thereby safeguarding brand integrity throughout the sales funnel. Gemini - AI powered conversational platform Gemini is a large language model chatbot developed by Google AI. It can generate text, translate languages, write different creative text formats, and answer your questions in an informative way. It is still under development but has learned to perform many kinds of tasks. Key features: Generate different creative text formats of text content (poems, code, scripts, musical pieces, email, letters, etc.) Answer your questions in an informative way, even if they are open ended, challenging, or strange. Translate languages Follow your instructions and complete your requests thoughtfully. Plusdocs (Plus AI) - AI tool for presentations Plus AI is a versatile tool that helps improve presentations and integrates with Slides in a simple and intuitive way. It simplifies slide creation and customization by converting text into slides and utilizing AI for various languages. Key Features: Text-to-Slide Conversion: Plus AI excels in transforming textual content into visually appealing slides, streamlining the presentation creation process. Multilingual AI Support: The tool is equipped to handle various languages, making it adaptable for a global user base. Professional Design Options: Users have access to professionally designed slide layouts, enabling the creation of polished presentations with ease. Customization and AI Design: Plus AI allows for extensive customization, including the use of AI for designing and editing slides, ensuring unique and personalized presentations. Live Snapshots and Templates: The tool offers live snapshots for real-time updates and a wide range of templates for quick and effective slide creation. Make - AI automation Make is a powerful visual platform that allows users to build and automate tasks, workflows, apps, and systems. It offers an intuitive, no-code interface that empowers users across various business functions to design and implement complex processes without the need for developer resources. Key Features: No-Code Visual Workflow Builder: Make's core feature is its user-friendly interface that allows for the creation of intricate workflows without coding expertise, making it accessible to a wide range of users. Extensive App Integration: The platform boasts compatibility with over 1000 apps, facilitating seamless connections and data sharing across diverse tools and systems. Custom Automation Solutions: Make enables personalized automation strategies, fitting various business needs from marketing automation to IT workflow control. Template Library: Users can jumpstart their automation projects with a vast collection of pre-built templates, which are customizable to fit specific workflow requirements. Enterprise-Level Solutions: Make offers advanced options for larger organizations, including enhanced security, single sign-on, custom functions, and dedicated support. Midjourney - Making sales content Midjourney is an AI-based image generation tool that changes the way we visualise and create digital art. It offers a lot of artistic possibilities, allowing users to create stunning images from text prompts. This innovative service caters to artists, designers, and anyone seeking to bring their creative visions to life. Key Features: Advanced AI Image Generation: Midjourney's core strength lies in its powerful AI algorithms, which interpret text prompts to generate detailed, high-quality images. This feature allows users to explore an endless array of visual concepts and styles. User-driven Customization: The tool offers significant control over the image creation process, enabling users to guide the AI with specific instructions, ensuring that the final output aligns closely with their vision. Diverse Artistic Styles: Midjourney can mimic various artistic styles, from classical to contemporary, providing users with a wide range of aesthetic options for their creations. Collaboration and Community Features: The platform fosters a community of users who can share, critique, and collaborate on artistic projects, enriching the creative experience. Fireflies AI - Sales meeting assistant Fireflies.ai is a powerful tool for improving team productivity and efficiency in managing meetings and voice conversations. It offers a range of features to simplify the process of capturing, organizing, and analyzing meeting content. Key Features: Automatic Meeting Transcription: Fireflies.ai can transcribe meetings held on various video-conferencing platforms and dialers. The tool captures both video and audio, providing transcripts quickly and efficiently. AI-Powered Search and Summarization: It allows users to review long meetings in a fraction of the time, highlighting key action items, tasks, and questions. Users can filter and focus on specific topics discussed in meetings. Improved Collaboration: The tool enables adding comments, pins, and reactions to specific conversation parts. Users can create and share soundbites and integrate meeting notes with popular collaboration apps such as Slack, Notion, and Asana. Conversation Intelligence: Fireflies.ai offers insights into meetings by tracking metrics like speaker talk time and sentiment. It helps in coaching team members and improving performance in sales, recruiting, and other internal processes. Workflow Automation: The AI assistant from Fireflies.ai can log call notes and activities in CRMs, create tasks through voice commands, and share meeting recaps instantly across various platforms. Comprehensive Knowledge Base: It compiles all voice conversations into an easily accessible and updatable knowledge base, with features to organize meetings into channels and set custom privacy controls. I’ll keep updating this little guide, so add your comments and I’ll try to add more tools. This is all just a personal opinion, so it’s completely cool if you disagree with it. Btw here is the link to the full blog post about all the AI tools in a bit more depth.

boring passive site... now 42k monthly visitors and $2540 MRR
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boring passive site... now 42k monthly visitors and $2540 MRR

people underestimate SEO... It is evergreen... passive... digital real estate. it can do magic... if you are consistent. Especially now with AI you can 2X your traffic growth and automate 85% of the work. For the past 6 months... we've been building an online directory. we just reached $2540 MRR... with SEO only... from a complete zero. I did share this on other subreddits. Maybe this gives ideas to someone. \+ This can be easily replicated if you have a website lol Current metrics: $2540 MRR - businesses pay us to list on the directory + display ads + pay to be featured. 43k monthly visitors - in the past couple of weeks our SEO growth is a hockey stick. DR (Domain Rating) 35 - it took us 2.5 months to get to that. 51 okay-ish quality referring domains (90% of them are do-follow) and 1.6k backlinks. There are probably 3 main pillars I try to focus on: keywords --> which then is the basis for ALL the content pieces we do blogs, landing pages, about us pages, competitor comparisons etc --> we use a DIY excel file to automate content production at scale. backlinks --> boost DR --> one of the main things to boost ranking on google. website health --> this is technical stuff like internal and external linking, schemas, canonical tags, alt texts, load speeds, compressed images, meta descriptions, titles etc --> do this once... and do it GOOD. $0.07 per SEO optimised blog at scale with AI Yep... we've literally built our own SEO blog tool... and it is a Spreadsheet with bunch of app scripts :D NOTE that we add a little bit of human touch to those blogs that are picked up by Google rank top in 25 How it works... is that we paste in bunch of links (other websites, blogs, news articles) and with a click of a button we can get up to 2000 SEO optimised content pieces... from an Excel file... $0.07 per blog. The spreadsheet is integrated with Chat gpt (obviously). We use GPT-4 for meta descriptions, titles, transforming the content from text to html code since it is more powerful, and GPT-4o for content itself because it is cheaper and faster for "general text". The spreadsheet repurposes content. The spreadsheet generates: Meta descriptions and titles FAQs sections - DON'T skip FAQ sections! They are a must for SEO. On Ahrefs... there is a section of questions people are searching about your keyword... that's your FAQs It can find contextual youtube videos (links to those videos) - to show google that our content is not "just text" thus higher quality. Screenshots and images of the original source (the website link we inputed) I then download a csv version of the excel and import it into our Webflow. The csv file column names match our webflow CMS field names. tbh... we didn't even know that it can be done with a spreadsheet. We "tried" building it because every other tool we were using is (1) expensive from $0.59 per SEO content piece (2) they didn't provide the scale we wanted (3) we wanted more control over the output. Focus on DR 35+ backlinks... easier We bought backlinks only once... rest of the backlinks was a manual work from us. Bunch of free listing databases (about 65% of our backlinks) You can comment on open forums with your link to get a backlink (be careful tho) Post a blog on Medium com --> DR 94 backlink (takes time to Index) If you pay for Notion you can get a DR 94 backlink from Notion If you use Beehiiv you can get a DR 86 backlink from Beehiiv Google product stacking (Google sites, Google notes etc) --> backlink from almighty Google itself A lot of work goes into backlinks because they are THAT important. I have tried bunch of "black hat" strategies as well... but note that all of these strategies won't work if you don't index the primary source from where your backlink is coming from. BIG search volume and low KD Key things I'm looking for in keywords: I use Ahrefs Keyword research tool... it is literally free BIG search volume - 2k+ is oaky-ish for a single keyword EASY to rank - KD (keyword difficulty) below 15 Look for long tail keywords (these are golden nuggets since they have a VERY clear search intent) - "how to edit..." "how to change..." "how to delete..." "how to paint..." I hope you got the idea. on Ahrefs you can use "\" to get BIG volume long tail keywords... like this "my keyword\". Ahrefs then populates the "\" with the tail. Check SERP (Search Engine Result Page) for your keywords - it shows current top 10 pages for those KWs. Check their content. Can you improve it? Have they missed anything? Keyword gap from your competitors - shows EASY keywords that your competitors have missed and also shows what keywords overlap with you. Also one cool thing... if you don't type any keywords on Ahrefs and press "Enter"... you can browse all the keywords out there... it is magical. Once we have the keywords, we run our spreadsheet. And that's pretty much it. I hope that you can get some ideas from this little silly project. Also... if you have any questions about this... I might share the SEO blog automation excel file/help if people are interested...

I run an AI automation agency (AAA). My honest overview and review of this new business model
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I run an AI automation agency (AAA). My honest overview and review of this new business model

I started an AI tools directory in February, and then branched off that to start an AI automation agency (AAA) in June. So far I've come across a lot of unsustainable "ideas" to make money with AI, but at the same time a few diamonds in the rough that aren't fully tapped into yet- especially the AAA model. Thought I'd share this post to shine light into this new business model and share some ways you could potentially start your own agency, or at the very least know who you are dealing with and how to pick and choose when you (inevitably) get bombarded with cold emails from them down the line. Foreword Running an AAA does NOT involve using AI tools directly to generate and sell content directly. That ship has sailed, and unless you are happy with $5 from Fiverr every month or so, it is not a real business model. Cry me a river but generating generic art with AI and slapping it onto a T-shirt to sell on Etsy won't make you a dime. At the same time, the AAA model will NOT require you to have a deep theoretical knowledge of AI, or any academic degree, as we are more so dealing with the practical applications of generative AI and how we can implement these into different workflows and tech-stacks, rather than building AI models from the ground up. Regardless of all that, common sense and a willingness to learn will help (a shit ton), as with anything. Keep in mind - this WILL involve work and motivation as well. The mindset that AI somehow means everything can be done for you on autopilot is not the right way to approach things. The common theme of businesses I've seen who have successfully implemented AI into their operations is the willingess to work with AI in a way that augments their existing operations, rather than flat out replace a worker or team. And this is exactly the train of thought you need when working with AI as a business model. However, as the field is relatively unsaturated and hype surrounding AI is still fresh for enterprises, right now is the prime time to start something new if generative AI interests you at all. With that being said, I'll be going over three of the most successful AI-adjacent businesses I've seen over this past year, in addition to some tips and resources to point you in the right direction. so.. WTF is an AI Automation Agency? The AI automation agency (or as some YouTubers have coined it, the AAA model) at its core involves creating custom AI solutions for businesses. I have over 1500 AI tools listed in my directory, however the feedback I've received from some enterprise users is that ready-made SaaS tools are too generic to meet their specific needs. Combine this with the fact virtually no smaller companies have the time or skills required to develop custom solutions right off the bat, and you have yourself real demand. I would say in practice, the AAA model is quite similar to Wordpress and even web dev agencies, with the major difference being all solutions you develop will incorporate key aspects of AI AND automation. Which brings me to my second point- JUST AI IS NOT ENOUGH. Rather than reducing the amount of time required to complete certain tasks, I've seen many AI agencies make the mistake of recommending and (trying to) sell solutions that more likely than not increase the workload of their clients. For example, if you were to make an internal tool that has AI answer questions based on their knowledge base, but this knowledge base has to be updated manually, this is creating unnecessary work. As such I think one of the key components of building successful AI solutions is incorporating the new (Generative AI/LLMs) with the old (programmtic automation- think Zapier, APIs, etc.). Finally, for this business model to be successful, ideally you should target a niche in which you have already worked and understand pain points and needs. Not only does this make it much easier to get calls booked with prospects, the solutions you build will have much greater value to your clients (meaning you get paid more). A mistake I've seen many AAA operators make (and I blame this on the "Get Rich Quick" YouTubers) is focusing too much on a specific productized service, rather than really understanding the needs of businesses. The former is much done via a SaaS model, but when going the agency route the only thing that makes sense is building custom solutions. This is why I always take a consultant-first approach. You can only build once you understand what they actually need and how certain solutions may impact their operations, workflows, and bottom-line. Basics of How to Get Started Pick a niche. As I mentioned previously, preferably one that you've worked in before. Niches I know of that are actively being bombarded with cold emails include real estate, e-commerce, auto-dealerships, lawyers, and medical offices. There is a reason for this, but I will tell you straight up this business model works well if you target any white-collar service business (internal tools approach) or high volume businesses (customer facing tools approach). Setup your toolbox. If you wanted to start a pressure washing business, you would need a pressure-washer. This is no different. For those without programming knowledge, I've seen two common ways AAA get setup to build- one is having a network of on-call web developers, whether its personal contacts or simply going to Upwork or any talent sourcing agency. The second is having an arsenal of no-code tools. I'll get to this more in a second, but this works beecause at its core, when we are dealing with the practical applications of AI, the code is quite simple, simply put. Start cold sales. Unless you have a network already, this is not a step you can skip. You've already picked a niche, so all you have to do is find the right message. Keep cold emails short, sweet, but enticing- and it will help a lot if you did step 1 correctly and intimately understand who your audience is. I'll be touching base later about how you can leverage AI yourself to help you with outreach and closing. The beauty of gen AI and the AAA model You don't need to be a seasoned web developer to make this business model work. The large majority of solutions that SME clients want is best done using an API for an LLM for the actual AI aspect. The value we create with the solutions we build comes with the conceptual framework and design that not only does what they need it to but integrates smoothly with their existing tech-stack and workflow. The actual implementation is quite straightforward once you understand the high level design and know which tools you are going to use. To give you a sense, even if you plan to build out these apps yourself (say in Python) the large majority of the nitty gritty technical work has already been done for you, especially if you leverage Python libraries and packages that offer high level abstraction for LLM-related functions. For instance, calling GPT can be as little as a single line of code. (And there are no-code tools where these functions are simply an icon on a GUI). Aside from understanding the capabilities and limitations of these tools and frameworks, the only thing that matters is being able to put them in a way that makes sense for what you want to build. Which is why outsourcing and no-code tools both work in our case. Okay... but how TF am I suppposed to actually build out these solutions? Now the fun part. I highly recommend getting familiar with Langchain and LlamaIndex. Both are Python libraires that help a lot with the high-level LLM abstraction I mentioned previously. The two most important aspects include being able to integrate internal data sources/knowledge bases with LLMs, and have LLMs perform autonomous actions. The two most common methods respectively are RAG and output parsing. RAG (retrieval augmented Generation) If you've ever seen a tool that seemingly "trains" GPT on your own data, and wonder how it all works- well I have an answer from you. At a high level, the user query is first being fed to what's called a vector database to run vector search. Vector search basically lets you do semantic search where you are searching data based on meaning. The vector databases then retrieves the most relevant sections of text as it relates to the user query, and this text gets APPENDED to your GPT prompt to provide extra context to the AI. Further, with prompt engineering, you can limit GPT to only generate an answer if it can be found within this extra context, greatly limiting the chance of hallucination (this is where AI makes random shit up). Aside from vector databases, we can also implement RAG with other data sources and retrieval methods, for example SQL databses (via parsing the outputs of LLM's- more on this later). Autonomous Agents via Output Parsing A common need of clients has been having AI actually perform tasks, rather than simply spitting out text. For example, with autonomous agents, we can have an e-commerce chatbot do the work of a basic customer service rep (i.e. look into orders, refunds, shipping). At a high level, what's going on is that the response of the LLM is being used programmtically to determine which API to call. Keeping on with the e-commerce example, if I wanted a chatbot to check shipping status, I could have a LLM response within my app (not shown to the user) with a prompt that outputs a random hash or string, and programmatically I can determine which API call to make based on this hash/string. And using the same fundamental concept as with RAG, I can append the the API response to a final prompt that would spit out the answer for the user. How No Code Tools Can Fit In (With some example solutions you can build) With that being said, you don't necessarily need to do all of the above by coding yourself, with Python libraries or otherwise. However, I will say that having that high level overview will help IMMENSELY when it comes to using no-code tools to do the actual work for you. Regardless, here are a few common solutions you might build for clients as well as some no-code tools you can use to build them out. Ex. Solution 1: AI Chatbots for SMEs (Small and Medium Enterprises) This involves creating chatbots that handle user queries, lead gen, and so forth with AI, and will use the principles of RAG at heart. After getting the required data from your client (i.e. product catalogues, previous support tickets, FAQ, internal documentation), you upload this into your knowledge base and write a prompt that makes sense for your use case. One no-code tool that does this well is MyAskAI. The beauty of it especially for building external chatbots is the ability to quickly ingest entire websites into your knowledge base via a sitemap, and bulk uploading files. Essentially, they've covered the entire grunt work required to do this manually. Finally, you can create a inline or chat widget on your client's website with a few lines of HTML, or altneratively integrate it with a Slack/Teams chatbot (if you are going for an internal Q&A chatbot approach). Other tools you could use include Botpress and Voiceflow, however these are less for RAG and more for building out complete chatbot flows that may or may not incorporate LLMs. Both apps are essentially GUIs that eliminate the pain and tears and trying to implement complex flows manually, and both natively incoporate AI intents and a knowledge base feature. Ex. Solution 2: Internal Apps Similar to the first example, except we go beyond making just chatbots but tools such as report generation and really any sort of internal tool or automations that may incorporate LLM's. For instance, you can have a tool that automatically generates replies to inbound emails based on your client's knowledge base. Or an automation that does the same thing but for replies to Instagram comments. Another example could be a tool that generates a description and screeenshot based on a URL (useful for directory sites, made one for my own :P). Getting into more advanced implementations of LLMs, we can have tools that can generate entire drafts of reports (think 80+ pages), based not only on data from a knowledge base but also the writing style, format, and author voice of previous reports. One good tool to create content generation panels for your clients would be MindStudio. You can train LLM's via prompt engineering in a structured way with your own data to essentially fine tune them for whatever text you need it to generate. Furthermore, it has a GUI where you can dictate the entire AI flow. You can also upload data sources via multiple formats, including PDF, CSV, and Docx. For automations that require interactions between multiple apps, I recommend the OG zapier/make.com if you want a no-code solution. For instance, for the automatic email reply generator, I can have a trigger such that when an email is received, a custom AI reply is generated by MyAskAI, and finally a draft is created in my email client. Or, for an automation where I can create a social media posts on multiple platforms based on a RSS feed (news feed), I can implement this directly in Zapier with their native GPT action (see screenshot) As for more complex LLM flows that may require multiple layers of LLMs, data sources, and APIs working together to generate a single response i.e. a long form 100 page report, I would recommend tools such as Stack AI or Flowise (open-source alternative) to build these solutions out. Essentially, you get most of the functions and features of Python packages such as Langchain and LlamaIndex in a GUI. See screenshot for an example of a flow How the hell are you supposed to find clients? With all that being said, none of this matters if you can't find anyone to sell to. You will have to do cold sales, one way or the other, especially if you are brand new to the game. And what better way to sell your AI services than with AI itself? If we want to integrate AI into the cold outreach process, first we must identify what it's good at doing, and that's obviously writing a bunch of text, in a short amount of time. Similar to the solutions that an AAA can build for its clients, we can take advantage of the same principles in our own sales processes. How to do outreach Once you've identified your niche and their pain points/opportunities for automation, you want to craft a compelling message in which you can send via cold email and cold calls to get prospects booked on demos/consultations. I won't get into too much detail in terms of exactly how to write emails or calling scripts, as there are millions of resources to help with this, but I will tell you a few key points you want to keep in mind when doing outreach for your AAA. First, you want to keep in mind that many businesses are still hesitant about AI and may not understand what it really is or how it can benefit their operations. However, we can take advantage of how mass media has been reporting on AI this past year- at the very least people are AWARE that sooner or later they may have to implement AI into their businesses to stay competitive. We want to frame our message in a way that introduces generative AI as a technology that can have a direct, tangible, and positive impact on their business. Although it may be hard to quantify, I like to include estimates of man-hours saved or costs saved at least in my final proposals to prospects. Times are TOUGH right now, and money is expensive, so you need to have a compelling reason for businesses to get on board. Once you've gotten your messaging down, you will want to create a list of prospects to contact. Tools you can use to find prospects include Apollo.io, reply.io, zoominfo (expensive af), and Linkedin Sales Navigator. What specific job titles, etc. to target will depend on your niche but for smaller companies this will tend to be the owner. For white collar niches, i.e. law, the professional that will be directly benefiting from the tool (i.e. partners) may be better to contact. And for larger organizations you may want to target business improvement and digital transformation leads/directors- these are the people directly in charge of projects like what you may be proposing. Okay- so you have your message, and your list, and now all it comes down to is getting the good word out. I won't be going into the details of how to send these out, a quick Google search will give you hundreds of resources for cold outreach methods. However, personalization is key and beyond simple dynamic variables you want to make sure you can either personalize your email campaigns directly with AI (SmartWriter.ai is an example of a tool that can do this), or at the very least have the ability to import email messages programmatically. Alternatively, ask ChatGPT to make you a Python Script that can take in a list of emails, scrape info based on their linkedin URL or website, and all pass this onto a GPT prompt that specifies your messaging to generate an email. From there, send away. How tf do I close? Once you've got some prospects booked in on your meetings, you will need to close deals with them to turn them into clients. Call #1: Consultation Tying back to when I mentioned you want to take a consultant-first appraoch, you will want to listen closely to their goals and needs and understand their pain points. This would be the first call, and typically I would provide a high level overview of different solutions we could build to tacke these. It really helps to have a presentation available, so you can graphically demonstrate key points and key technologies. I like to use Plus AI for this, it's basically a Google Slides add-on that can generate slide decks for you. I copy and paste my default company messaging, add some key points for the presentation, and it comes out with pretty decent slides. Call #2: Demo The second call would involve a demo of one of these solutions, and typically I'll quickly prototype it with boilerplate code I already have, otherwise I'll cook something up in a no-code tool. If you have a niche where one type of solution is commonly demanded, it helps to have a general demo set up to be able to handle a larger volume of calls, so you aren't burning yourself out. I'll also elaborate on how the final product would look like in comparison to the demo. Call #3 and Beyond: Once the initial consultation and demo is complete, you will want to alleviate any remaining concerns from your prospects and work with them to reach a final work proposal. It's crucial you lay out exactly what you will be building (in writing) and ensure the prospect understands this. Furthermore, be clear and transparent with timelines and communication methods for the project. In terms of pricing, you want to take this from a value-based approach. The same solution may be worth a lot more to client A than client B. Furthermore, you can create "add-ons" such as monthly maintenance/upgrade packages, training sessions for employeees, and so forth, separate from the initial setup fee you would charge. How you can incorporate AI into marketing your businesses Beyond cold sales, I highly recommend creating a funnel to capture warm leads. For instance, I do this currently with my AI tools directory, which links directly to my AI agency and has consistent branding throughout. Warm leads are much more likely to close (and honestly, much nicer to deal with). However, even without an AI-related website, at the very least you will want to create a presence on social media and the web in general. As with any agency, you will want basic a professional presence. A professional virtual address helps, in addition to a Google Business Profile (GBP) and TrustPilot. a GBP (especially for local SEO) and Trustpilot page also helps improve the looks of your search results immensely. For GBP, I recommend using ProfilePro, which is a chrome extension you can use to automate SEO work for your GBP. Aside from SEO optimzied business descriptions based on your business, it can handle Q/A answers, responses, updates, and service descriptions based on local keywords. Privacy and Legal Concerns of the AAA Model Aside from typical concerns for agencies relating to service contracts, there are a few issues (especially when using no-code tools) that will need to be addressed to run a successful AAA. Most of these surround privacy concerns when working with proprietary data. In your terms with your client, you will want to clearly define hosting providers and any third party tools you will be using to build their solution, and a DPA with these third parties listed as subprocessors if necessary. In addition, you will want to implement best practices like redacting private information from data being used for building solutions. In terms of addressing concerns directly from clients, it helps if you host your solutions on their own servers (not possible with AI tools), and address the fact only ChatGPT queries in the web app, not OpenAI API calls, will be used to train OpenAI's models (as reported by mainstream media). The key here is to be open and transparent with your clients about ALL the tools you are using, where there data will be going, and make sure to get this all in writing. have fun, and keep an open mind Before I finish this post, I just want to reiterate the fact that this is NOT an easy way to make money. Running an AI agency will require hours and hours of dedication and work, and constantly rearranging your schedule to meet prospect and client needs. However, if you are looking for a new business to run, and have a knack for understanding business operations and are genuinely interested in the pracitcal applications of generative AI, then I say go for it. The time is ticking before AAA becomes the new dropshipping or SMMA, and I've a firm believer that those who set foot first and establish themselves in this field will come out top. And remember, while 100 thousand people may read this post, only 2 may actually take initiative and start.

The power of AI chatbots for business efficiency
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The power of AI chatbots for business efficiency

Let's talk about a game-changer in the world of customer support: AI chatbots. These intelligent virtual assistants are transforming how businesses handle customer inquiries and support tasks. Today, I want to discuss their utility for businesses and a how platforms like Datasavvy.chat, is simplifying the chatbot creation process. AI chatbots are not just another tech trend; they're a fundamental shift in how businesses interact with customers. From addressing FAQs to guiding users through transactions, chatbots can handle a diverse array of tasks efficiently and effectively. AI chatbots offer a myriad of benefits for businesses: 24/7 Availability: Chatbots don't sleep. They provide round-the-clock support, ensuring that customers can get assistance whenever they need it. Efficiency: By automating repetitive tasks, chatbots free up human agents to focus on more complex inquiries, improving overall efficiency and productivity. Scalability: As your business grows, so do the demands on your customer support team. Chatbots can scale effortlessly to handle increased volumes of inquiries without compromising quality. Data Insights: Chatbots can collect valuable data on customer interactions, preferences, and pain points. This data can be leveraged to optimize processes, improve customer satisfaction, and drive business decisions. Consistency: Chatbots deliver consistent responses, ensuring that every customer receives the same level of service regardless of the time or day. In conclusion, AI chatbots are invaluable tools for businesses looking to streamline their customer support operations and enhance the overall customer experience. And platforms like Datasavvy.chat are making it easier than ever for businesses to leverage this technology to their advantage. Are you ready to revolutionize your customer support? Dive into the world of AI chatbots and discover the difference they can make for your business!What are your thoughts on AI chatbots? Have you had any experiences, good or bad, with them in customer support? Let's discuss!

boring passive site... now 42k monthly visitors and $2540 MRR
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boring passive site... now 42k monthly visitors and $2540 MRR

people underestimate SEO... It is evergreen... passive... digital real estate. it can do magic... if you are consistent. Especially now with AI you can 2X your traffic growth and automate 85% of the work. For the past 6 months... we've been building an online directory. we just reached $2540 MRR... with SEO only... from a complete zero. I did share this on other subreddits. Maybe this gives ideas to someone. \+ This can be easily replicated if you have a website lol Current metrics: $2540 MRR - businesses pay us to list on the directory + display ads + pay to be featured. 43k monthly visitors - in the past couple of weeks our SEO growth is a hockey stick. DR (Domain Rating) 35 - it took us 2.5 months to get to that. 51 okay-ish quality referring domains (90% of them are do-follow) and 1.6k backlinks. There are probably 3 main pillars I try to focus on: keywords --> which then is the basis for ALL the content pieces we do blogs, landing pages, about us pages, competitor comparisons etc --> we use a DIY excel file to automate content production at scale. backlinks --> boost DR --> one of the main things to boost ranking on google. website health --> this is technical stuff like internal and external linking, schemas, canonical tags, alt texts, load speeds, compressed images, meta descriptions, titles etc --> do this once... and do it GOOD. $0.07 per SEO optimised blog at scale with AI Yep... we've literally built our own SEO blog tool... and it is a Spreadsheet with bunch of app scripts :D NOTE that we add a little bit of human touch to those blogs that are picked up by Google rank top in 25 How it works... is that we paste in bunch of links (other websites, blogs, news articles) and with a click of a button we can get up to 2000 SEO optimised content pieces... from an Excel file... $0.07 per blog. The spreadsheet is integrated with Chat gpt (obviously). We use GPT-4 for meta descriptions, titles, transforming the content from text to html code since it is more powerful, and GPT-4o for content itself because it is cheaper and faster for "general text". The spreadsheet repurposes content. The spreadsheet generates: Meta descriptions and titles FAQs sections - DON'T skip FAQ sections! They are a must for SEO. On Ahrefs... there is a section of questions people are searching about your keyword... that's your FAQs It can find contextual youtube videos (links to those videos) - to show google that our content is not "just text" thus higher quality. Screenshots and images of the original source (the website link we inputed) I then download a csv version of the excel and import it into our Webflow. The csv file column names match our webflow CMS field names. tbh... we didn't even know that it can be done with a spreadsheet. We "tried" building it because every other tool we were using is (1) expensive from $0.59 per SEO content piece (2) they didn't provide the scale we wanted (3) we wanted more control over the output. Focus on DR 35+ backlinks... easier We bought backlinks only once... rest of the backlinks was a manual work from us. Bunch of free listing databases (about 65% of our backlinks) You can comment on open forums with your link to get a backlink (be careful tho) Post a blog on Medium com --> DR 94 backlink (takes time to Index) If you pay for Notion you can get a DR 94 backlink from Notion If you use Beehiiv you can get a DR 86 backlink from Beehiiv Google product stacking (Google sites, Google notes etc) --> backlink from almighty Google itself A lot of work goes into backlinks because they are THAT important. I have tried bunch of "black hat" strategies as well... but note that all of these strategies won't work if you don't index the primary source from where your backlink is coming from. BIG search volume and low KD Key things I'm looking for in keywords: I use Ahrefs Keyword research tool... it is literally free BIG search volume - 2k+ is oaky-ish for a single keyword EASY to rank - KD (keyword difficulty) below 15 Look for long tail keywords (these are golden nuggets since they have a VERY clear search intent) - "how to edit..." "how to change..." "how to delete..." "how to paint..." I hope you got the idea. on Ahrefs you can use "\" to get BIG volume long tail keywords... like this "my keyword\". Ahrefs then populates the "\" with the tail. Check SERP (Search Engine Result Page) for your keywords - it shows current top 10 pages for those KWs. Check their content. Can you improve it? Have they missed anything? Keyword gap from your competitors - shows EASY keywords that your competitors have missed and also shows what keywords overlap with you. Also one cool thing... if you don't type any keywords on Ahrefs and press "Enter"... you can browse all the keywords out there... it is magical. Once we have the keywords, we run our spreadsheet. And that's pretty much it. I hope that you can get some ideas from this little silly project. Also... if you have any questions about this... I might share the SEO blog automation excel file/help if people are interested...

AI Automation Agency, the Future for Solopreneurs?
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MoneyPizza1231This week

AI Automation Agency, the Future for Solopreneurs?

I want to take a moment to discuss AI automation agencies. If they are any good for new entrepreneurs. Or on the flip side what is wrong with them. &#x200B; Normally when you see something promising to make you thousands of dollars, for very little work, you run the other way. But you see I am not most people, and I love stuff like this. So, when I saw, AI Automation Agencies (AAA) promising to make me thousands of dollars, I ran straight down that rabbit hole. With no hesitation… It was a new term and idea, that I had already played around with. Due to the inherent nature of businesses and AI at the time. It was 100% an opportunity with a potential market down the line. What is an AI Automation Agency? On the surface, an AAA is using AI to automate and augment business processes. With a combination of using no code AI tools, AI LLMs, and simple automation process tools (Zapier). The whole premise of the AAA is to help companies reduce expenses and increase profits. Whether that is through improving business processes or cutting out easy-to-replace jobs. AAAs are all about optimizing your business (The best way to think about it). Run through a quick scenario with me: Say you are a simple e-commerce store, selling your favorite product. I show up, as an AAA, promising to automate your customer service platform. I can build you a fully automated customer service chatbot, and help you answer specific customer questions with AI. With the promises of a faster, more efficient, and more effective customer service platform. Being able to perform 80% of your current team’s work. Would you take the offer? It is a no-brainer, right? That is the premise behind this business model. Make businesses more effective. Which in turn makes them more profitable. A win-win for everyone. Take a look at some of the products an AAA might sell. Robotic Process Automation: Automating repetitive tasks in a business. AI- Power Analytics: Helping businesses understand and act on insights in their data. Sentiment Analysis: Analyzing how customers think and feel about products and markets. Customer Service: AI chatbots for customer questions. Productivity: Help augment processes with AI to cut down on time. Any process in a business that you fully understand you can augment and or automate with AI. And guess what? It is an open market but for good reason… Too Good to be True? The reason that this new business model is wide open is quite funny. No business cares about AI right now. Businesses are too focused to worry about AI and its upsides. Focused on the day-to-day operations, and not worried about AI. Make a few cold calls, and see how many leads you get… At the moment the offer does not resonate with potential clients. Meaning you need to have a massive advertising budget to get any leads. Because no one cares or sees any benefit, they will just brush you off. Which becomes an endless cycle of paid ads, and constant cold calling, just to find any business. So why is this model even popular? The gurus…that’s why. They have the budget for ads and get clients from their videos. Effectively throwing money at the problem. At least until it works. Do not get me wrong, AI automation is going to change businesses. But not right now. The whole growth of this business model is being pushed by influencers and gurus. People that can afford the cost of the startup. Telling others that it is a feasible one-person business. That anyone with no money can do, with a few simple steps. And that is just not the case. This has been a trend for any new profitable and “easy” business model. The gurus get there first, promote the model, show how simple it is, and rope everyone in. Eventually up selling a course on how to do it, or maybe even a community. You’ve seen it with ChatGPT, Facebook ads, SMMA, and so much more. It is a constant cycle that you need to be aware of. The End Result Good news, there is an alternative. It is using a combination of SMMA and AAA. Gathering leads using SMMA. Creating a great offer for your niche. And selling them on the service you can provide through marketing. Then once they are sold, you upsell them on AI automation. Easy to start, low cost, and super effective. Although unproven. It makes complete sense why it would work. It is beginner friendly, with plenty of SMMA tutorials online. With low barriers to entry. Making it a very inciting opportunity. AAA is going to be the future of business. It is a million-dollar opportunity for anyone. But with most startups, it takes skills and capital. With a façade of being easy to operate and start, pushed by gurus. More entrepreneur hopefuls find themselves debating starting an AAA. And guess what, it isn’t a good idea… Do your research to understand the market you want to enter, and how your business is going to operate. And don’t fall for get-rich-quick schemes. Ps. Check out this video if you want to learn more…

Only 2 months of cash in the Bank for my business but was able to save it with the help of AI.
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CALLIRDAN90This week

Only 2 months of cash in the Bank for my business but was able to save it with the help of AI.

Hi there! I’m excited to share something very personal with you. We needed to book at least 2 appointments per day in the next 60 days, or my business would fail. We were already trying two acquisition channels, LinkedIn and email. The problem with these channels was that the positive response rate was very low in both. So I decided to focus on LinkedIn and get the attention of the lead by sending videos directly to them via LinkedIn messages. (You can send videos to your connections on LinkedIn if you use your cell phone.) This wasn’t new, but I added a small twist to get the lead’s attention. All the covers of the videos had a picture of me holding a sign with the person’s name and an interesting phrase. This showed some okay results, but the rest of the video was not personalized. Only the picture on the cover was. I even developed a Chrome extension for this because I thought this would be the answer and that I would book tons of appointments.  But after more trial and outreach, my leads responded, telling me that because the video itself wasn’t personalized for them, they felt like I didn’t put enough effort in, so they would not book a call with me. So after investing time and effort into my “new bright idea” and getting developers to make the Chrome extension, I was back to square one with no results. A few weeks went by, and after researching online, I found an online course from a guy who promised to teach me how to book 30+ appointments per month, guaranteed (at the time, I was making 2 or 3 appointments per week, maximum). He promised that I would only pay if he actually booked appointments for me and even offered to give me money if his course didn’t work for me. I never paid attention to internet gurus, but the offer was actually not bad, so I looked into this guy’s website. I found out he had hundreds of reviews from people who had taken his course and were talking amazing things about it. The more I read, the more excited I got. I booked a call that day and talked to a salesperson. The call was very short, and he promised I would get at least 2 appointments per day, easily. He seemed a bit cocky and told me that I just needed to trust him and the 100+ reviews from people who had taken the course. He didn’t share details, a proposal, or anything. I asked the price, and he told me it was close to $10k. (Not kidding, this was the price.) Then he told me that I would make the money back in no time with the clients I would get following his course, and that if it didn’t work, he would give me the money back. But I needed to follow everything the course said for at least 6 months. I had never paid $10k for anything in my life; it was extremely expensive for me. Also, my salary from my business was not in dollars but in a currency that was worth much less than the dollar. I continued to research more and more, but no other course was close to the number of reviews and promises that this guy had. I got desperate and told myself that I would bet everything on this course. If it worked for so many others, surely it would work for me. I got a loan from the bank and paid for the course. You might read this and think it was the most stupid thing ever, but the reality is that after 2 months in the course (I did the course as fast as I could), I learned a lot. The course was not bad; it was very extensive—probably more than 200 hours or so—and they taught a lot of things. I don’t think it was worth $10k for me, but I can see how for other people it might be worth that. Now, to the question you’re all thinking: did it get me the 2 appointments I needed per day? The answer is no. Here’s the thing: most of the techniques they taught were innovative and disruptive, but the focus was always on personalization, and they didn’t teach any way to automate the personalization. (I think, at the time they made the course, the tools didn’t exist yet.) So they taught how to do everything manually, and it took a lot—a lot of time and effort. And most annoyingly: an incredible amount of time doing operational things. I did get 2 appointments on some days, but it wasn’t consistent, and I didn’t have the time to spend 14 hours a day doing everything manually or the money to hire someone to do this for me. (I needed to also spend time delivering our service to our current clients; otherwise, they would leave.) I told them this, and they were very reasonable. After some negotiation, they gave me part of the money back. (To be fair, there was a lot of value in the course, so asking for the full $10k back would have been excessive because, in the end, it really taught me a lot of things I didn’t know.) So in the end, I spent $10k and 200+ hours on an online course, spent time and effort developing a Chrome extension, and was still not able to hit the meetings I needed. Money in the business was running out, and I needed to do something fast, or I was doomed. After investing time and effort in tools, research, and spending $10k and over 200 hours on a course that didn’t deliver the consistent results I needed, I was at a crossroads. My businesses were running out of money, and I knew I needed to find a solution quickly, or everything I had worked for would collapse. It was during this time of desperation that I started exploring other options. One night, while scrolling through the internet, I stumbled upon a 2024 article about how AI was being used to revolutionize various industries. It wasn’t directly related to appointment booking, but it sparked an idea in my mind. What if I could use AI to automate the personalization process that I had learned in the course? It seemed like a long shot, but I had nothing to lose. I started researching AI tools and technologies—YouTube videos, podcasts, pretty much everything related to AI—desperate to find something that could help me scale my outreach without investing too much time, while still maintaining the personalization that was so important. After a lot of trial and error, I found a few tools that showed promise. All of these tools were extremely new. Some of them had just launched the versions I needed just weeks ago. I can say I researched and tested more than 50 AI startups, experimenting with them, testing different approaches, checking prices (the problem was that most of them were cheap but became very expensive when applying the volume I needed to get results), and gradually refining my process. It wasn’t an overnight success, but for the first time, I felt like I was onto something that could truly work. The idea of combining AI personalization with volume was something new, and it gave me hope that I could finally book the meetings I needed without burning out. One day, I sent a video of myself talking—completely AI-generated—to my family chat group and waited for their response. None of them noticed it wasn’t actually me. At that moment, I said to myself: “Okay, I am ready to test this in the real world and see if it works.” Like everything in life, focus is key. As I mentioned earlier, we were already trying outbound strategies on LinkedIn and email, but I decided to narrow my focus to LinkedIn and specifically to video outreach. My goal was to stand out from the crowd, where most people were using text or sending generic videos. I knew that if my videos were 100% personalized, it would make a strong impression on my leads. I focused on two key metrics during my tests: Time spent on manual personalized outreach vs. AI-generated personalized outreach. Positive reply rate for non-personalized manual outreach vs. AI-generated personalized outreach. I ran a test using a sample of 50 one-minute videos sent to 50 leads, and here are the results: Time Spent to Make the Videos: Manual Process: It took me up to 10 hours to create and send 50 personalized videos. This included looking good on camera, brushing my hair, choosing appropriate clothing, ensuring proper lighting, not messing up the script, using a camera holder, recharging the phone, pausing to drink water, avoiding external sounds, being in an appropriate room, downloading the videos, deleting the videos that were not good, and sending the final ones. On average, it took me at least 12.5 minutes per one-minute video. AI Process: With AI, it took me just 32 seconds to create the exact same one-minute personalized video—without saying a word or recording a second of footage. In total, I could make and send the same 50 personalized videos in just 27 minutes. Result: The AI process was 24 times faster. Completely crazy! Positive Reply Rate: Non-Personalized Script (Manual): Using a good script without personalization (no name, job title, city, company, etc.) resulted in a positive reply rate of 4-6% on LinkedIn, including follow-ups. Personalized Script (AI): Using the same script but adding personalized details like the lead's name, company, city, and job title resulted in a positive reply rate of 15-20%, including follow-ups. Result: AI personalization led to 3x (three times) more replies. The best part was the responses. Almost everyone who replied thanked me for taking the time to research them, congratulated me on my speech, and appreciated the personalization and eloquence of my message.  These metrics were a complete breakthrough for me. I researched online to see if anyone else had done something similar, but I couldn’t find anything close. After achieving these metrics, booking the two appointments I desperately needed became easy. In fact, in the last 10 weeks, I’ve been able to consistently book 3-4 appointments per day. This success allowed me to train someone in my company to handle the process, freeing me up to focus on other aspects of the business and ultimately saving it. With the AI appointment machine we built, I even have free time now—time that I’ve been using to develop a methodology and tech tools that I now teach to others. I named the methodology Clip2Lead as a reference to the first Chrome extension I developed that didn’t work but ended up being the first step toward everything that followed. I’ve condensed everything I learned and throughout my experiences into a simple and short FREE training where I cover the entire AI appointment booking process. This includes how to find leads, create scripts, set up follow-up sequences, generate AI videos, clone your voice, compare non-AI metrics with AI metrics, and even navigate AI safety controls. I also offer Chrome extensions that helped me automate the process even further, so you can spend your time closing deals or focusing on other acquisition channels, while your AI machine for booking appointments runs with minimal effort from you. If you’re interested please get in touch with me and thank you for taking the time to read my personal story.

AI Voice Platform Comparison for Small Business Use Cases
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Glad-Syllabub6777This week

AI Voice Platform Comparison for Small Business Use Cases

We provide AI voice agent consultation and solutions in Upwork. One of clients’ frequent questions is which platform is best/perfect for their use cases, like lead qualification, AI receptionist, customer support, etc. This post provides our thoughts on this question. Our overall feeling is that the AI agent technology is still not there yet. It seems close but there are many corner cases the AI bot doesn't handle well. Four major players in the AI voice platforms: Bland ($65M funding) Retell ($4.6M funding) Synthflow ($7.4M funding) VAPI ($20M funding) We will only talk about Bland, Retell and VAPI. We firstly tried Synthflow and found the UI was buggy (the prompt editor froze for 20 seconds to 30 seconds when we were editing the prompt). Currently we don't use it anymore. Recommended use cases based on Upwork jobs we delivered: Bland. We recommend Bland for lead qualification as the lead qualification has a strict conversation flow (like asking questions, extracting variables, and making webhook calls). Clients/contractors can draw flow diagrams to build AI voice agents. We also find Bland is not a good fit for a small business with a monthly budget less than 5K. The reason is that common tools (like warm transfer, SMS sending) for AI voice agents are only available to enterprise clients. But warm transfers are critical for small businesses. Retell. We recommend Retell for customer support in contact centers. Retell has the best voice among competitors. One use case we build in Retell is the live translator in the ambulance call center. We tried the same prompt with the same LLM setup in VAPI. We found Retell performs way better than VAPI in terms of the translation quality and reliability. Another common scenario in the customer support domain is to have 3-way merge so that the agent can tell the summary to the transfer number while the caller can hear the conversation. VAPI. We recommend VAPI for AI receptionists and phone answering use cases. We can write a prompt and ask LLM to do the magic if callers ask questions not included in the prompt. We can set up custom tools to trigger automation (like update CRM) and warm transfer to connect to the stakeholders. One feeling we have is that VAPI is way more complicated than the other two platforms. If you don’t have developer experience and have a budget to hire a contractor, it is better to try Retell as Retell has many integrations. If you have any other questions or we miss anything, feel free to comment. We like to explore AI voice agent space together.

ChatGPT, Claude.ai and Perplexity for my Youtube Business
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ImpossibleBell4759This week

ChatGPT, Claude.ai and Perplexity for my Youtube Business

I use ChatGPT, Claude. ai and Perplexity for my Youtube Software Review Businesses. I run OVER 20 Youtube Faceless Software Review channels, and those AI tools basically help me with ideas, titles and descriptions. I like how simple is it to use those AI tools and crank out ideas, titles and descriptions in less than 20 minutes. ChatGPT, Claude. ai and Perplexity save me so much time. Managing all those Youtube channels is an all day event. I also save time by not editing and not scripting my videos. I do software reviews and I crank out 3 videos per hour. I can use software to automate some of the videos, but they don't get the same effect, so I do every video with original content. I'm thinking about using Elevenlabs. com so I can have access to hundreds of voices that I can use for my videos. I like their "Speech to Speech" technology. The only problem with Elevenlabs is that I have to do some editing to make it work... and I hate editing. I rather just record my video and upload it to Youtube. I might have to skip on Elevenlabs and the editing, because I need to crank out at least 20 videos per day. It seems like a lot but I focus on 12 hours a day and 3 videos per hour. 12 hours times 3 videos= 36 videos per day. But I only need 20 videos in the 12 hours, so I know I can meet my quota for the day. I'm looking at 20 videos per day times roughly 30 days is 600 videos per month. My goal is to finish the year with at least $100,000 in "CASH" after taxes, paying rent, buying food and having all my bills paid. So, I need to make $273.97 per day times 365 days= $100,000. The most I've made was off 1 video with only 600 views and I made over $3,300. I wasn't even monetized by Youtube. I made all that money from software commissions alone. I don't care about being monetized by Youtube what so ever. With Youtube monetized payouts you need millions of views to make money, with software commissions ranging from 20%- 40% I don't need Youtube revenue. I've broken my Youtube business plan down into bite sized pieces so that I know I can achieve my Goals. CHEERS!

I Recreated An AI Phone Calling Agent That Automated Scheduling And Patient Inquiries For A  Hospital
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Will_feverThis week

I Recreated An AI Phone Calling Agent That Automated Scheduling And Patient Inquiries For A Hospital

AI has been killing it as of recent when it comes to automating repetitive tasks in businesses, and I've been even more fascinated by how AI voice agents have been impacting various industries. I recently came across a case study about a voice agent that helped a hospital with appointment scheduling, cost reduction and much more. Motivated by the potential of this technology, I decided to build a similar system to see how it could be adapted for other industries. I've added the case study below so that you could see the direct impact this technology is having and how fast it is advancing in todays world. Case Study A multi-specialty hospital was facing a range of operational challenges such as high administrative load, limited 24/7 availability, high operation costs, patient follow ups, answering routine questions and long call wait times. Solution To solve these problems, the hospital implemented an AI voice agent capable of handling various aspects of patient interaction and operations such as: Automated Appointment Scheduling: AI agents seamlessly handled patient appointments, rescheduling, and cancellations. This reduced manual effort by 75%, increased appointment adherence by 30%, and allowed patients to reschedule with ease. 24/7 Multilingual Patient Support: The AI agents utilized advanced Natural Language Processing (NLP) to communicate in six languages. This feature eased communication barriers, leading to a significant boost in guest satisfaction. Handling Patient Inquiries: AI agents answered FAQs about hospital services, procedures, insurance, and general health queries with speed and accuracy, improving the overall patient experience. This reduced the burden on front-desk staff by 60%. Proactive Patient Follow-Ups: The Voice AI agents automated follow-up calls for patients post-treatment, providing reminders for medication, check-ups, and future appointments, improving patient engagement and adherence to treatment plans. Enhanced Call Routing: AI agents routed patient calls based on specific needs without requiring additional staff. This eliminated long waits, improved call response times by 60%, and allowed staff to focus on more critical tasks. Elimination of IVR Systems: The hospital replaced outdated touch-tone IVRs with AI agents that routed calls efficiently without requiring patients to wait in long queues or be transferred among departments. This resulted in a 55% reduction in average call-handling times. Outcome The adoption of AI agents resulted in measurable improvements across various operational and patient care metrics: The hospital achieved a 55% reduction in operational costs by decreasing reliance on human agents for routine tasks and minimizing the need for additional staff. Patient satisfaction scores improved by 35% as a result of faster response times, personalized communication, and proactive patient engagement. Automation of appointment scheduling, follow-ups, and call routing increased overall operational efficiency by 75%. The AI agents supported 12 languages which bridged communication gaps with non-English speaking patients, further enhancing the patient experience. The AI agents reduced call center wait times by 60%, significantly improving patient support and reducing frustration. Appointment reminders and follow-up messages sent by AI agents contributed to a 30% reduction in missed appointments By implementing the AI voice agent, the hospital business enhanced its customer communication and scheduling, while significantly reducing operational costs. I’d love to hear some of your thoughts on this technology and how you see it impacting your and/or other industries.

I run an AI automation agency (AAA). My honest overview and review of this new business model
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AI_Scout_OfficialThis week

I run an AI automation agency (AAA). My honest overview and review of this new business model

I started an AI tools directory in February, and then branched off that to start an AI automation agency (AAA) in June. So far I've come across a lot of unsustainable "ideas" to make money with AI, but at the same time a few diamonds in the rough that aren't fully tapped into yet- especially the AAA model. Thought I'd share this post to shine light into this new business model and share some ways you could potentially start your own agency, or at the very least know who you are dealing with and how to pick and choose when you (inevitably) get bombarded with cold emails from them down the line. Foreword Running an AAA does NOT involve using AI tools directly to generate and sell content directly. That ship has sailed, and unless you are happy with $5 from Fiverr every month or so, it is not a real business model. Cry me a river but generating generic art with AI and slapping it onto a T-shirt to sell on Etsy won't make you a dime. At the same time, the AAA model will NOT require you to have a deep theoretical knowledge of AI, or any academic degree, as we are more so dealing with the practical applications of generative AI and how we can implement these into different workflows and tech-stacks, rather than building AI models from the ground up. Regardless of all that, common sense and a willingness to learn will help (a shit ton), as with anything. Keep in mind - this WILL involve work and motivation as well. The mindset that AI somehow means everything can be done for you on autopilot is not the right way to approach things. The common theme of businesses I've seen who have successfully implemented AI into their operations is the willingess to work with AI in a way that augments their existing operations, rather than flat out replace a worker or team. And this is exactly the train of thought you need when working with AI as a business model. However, as the field is relatively unsaturated and hype surrounding AI is still fresh for enterprises, right now is the prime time to start something new if generative AI interests you at all. With that being said, I'll be going over three of the most successful AI-adjacent businesses I've seen over this past year, in addition to some tips and resources to point you in the right direction. so.. WTF is an AI Automation Agency? The AI automation agency (or as some YouTubers have coined it, the AAA model) at its core involves creating custom AI solutions for businesses. I have over 1500 AI tools listed in my directory, however the feedback I've received from some enterprise users is that ready-made SaaS tools are too generic to meet their specific needs. Combine this with the fact virtually no smaller companies have the time or skills required to develop custom solutions right off the bat, and you have yourself real demand. I would say in practice, the AAA model is quite similar to Wordpress and even web dev agencies, with the major difference being all solutions you develop will incorporate key aspects of AI AND automation. Which brings me to my second point- JUST AI IS NOT ENOUGH. Rather than reducing the amount of time required to complete certain tasks, I've seen many AI agencies make the mistake of recommending and (trying to) sell solutions that more likely than not increase the workload of their clients. For example, if you were to make an internal tool that has AI answer questions based on their knowledge base, but this knowledge base has to be updated manually, this is creating unnecessary work. As such I think one of the key components of building successful AI solutions is incorporating the new (Generative AI/LLMs) with the old (programmtic automation- think Zapier, APIs, etc.). Finally, for this business model to be successful, ideally you should target a niche in which you have already worked and understand pain points and needs. Not only does this make it much easier to get calls booked with prospects, the solutions you build will have much greater value to your clients (meaning you get paid more). A mistake I've seen many AAA operators make (and I blame this on the "Get Rich Quick" YouTubers) is focusing too much on a specific productized service, rather than really understanding the needs of businesses. The former is much done via a SaaS model, but when going the agency route the only thing that makes sense is building custom solutions. This is why I always take a consultant-first approach. You can only build once you understand what they actually need and how certain solutions may impact their operations, workflows, and bottom-line. Basics of How to Get Started Pick a niche. As I mentioned previously, preferably one that you've worked in before. Niches I know of that are actively being bombarded with cold emails include real estate, e-commerce, auto-dealerships, lawyers, and medical offices. There is a reason for this, but I will tell you straight up this business model works well if you target any white-collar service business (internal tools approach) or high volume businesses (customer facing tools approach). Setup your toolbox. If you wanted to start a pressure washing business, you would need a pressure-washer. This is no different. For those without programming knowledge, I've seen two common ways AAA get setup to build- one is having a network of on-call web developers, whether its personal contacts or simply going to Upwork or any talent sourcing agency. The second is having an arsenal of no-code tools. I'll get to this more in a second, but this works beecause at its core, when we are dealing with the practical applications of AI, the code is quite simple, simply put. Start cold sales. Unless you have a network already, this is not a step you can skip. You've already picked a niche, so all you have to do is find the right message. Keep cold emails short, sweet, but enticing- and it will help a lot if you did step 1 correctly and intimately understand who your audience is. I'll be touching base later about how you can leverage AI yourself to help you with outreach and closing. The beauty of gen AI and the AAA model You don't need to be a seasoned web developer to make this business model work. The large majority of solutions that SME clients want is best done using an API for an LLM for the actual AI aspect. The value we create with the solutions we build comes with the conceptual framework and design that not only does what they need it to but integrates smoothly with their existing tech-stack and workflow. The actual implementation is quite straightforward once you understand the high level design and know which tools you are going to use. To give you a sense, even if you plan to build out these apps yourself (say in Python) the large majority of the nitty gritty technical work has already been done for you, especially if you leverage Python libraries and packages that offer high level abstraction for LLM-related functions. For instance, calling GPT can be as little as a single line of code. (And there are no-code tools where these functions are simply an icon on a GUI). Aside from understanding the capabilities and limitations of these tools and frameworks, the only thing that matters is being able to put them in a way that makes sense for what you want to build. Which is why outsourcing and no-code tools both work in our case. Okay... but how TF am I suppposed to actually build out these solutions? Now the fun part. I highly recommend getting familiar with Langchain and LlamaIndex. Both are Python libraires that help a lot with the high-level LLM abstraction I mentioned previously. The two most important aspects include being able to integrate internal data sources/knowledge bases with LLMs, and have LLMs perform autonomous actions. The two most common methods respectively are RAG and output parsing. RAG (retrieval augmented Generation) If you've ever seen a tool that seemingly "trains" GPT on your own data, and wonder how it all works- well I have an answer from you. At a high level, the user query is first being fed to what's called a vector database to run vector search. Vector search basically lets you do semantic search where you are searching data based on meaning. The vector databases then retrieves the most relevant sections of text as it relates to the user query, and this text gets APPENDED to your GPT prompt to provide extra context to the AI. Further, with prompt engineering, you can limit GPT to only generate an answer if it can be found within this extra context, greatly limiting the chance of hallucination (this is where AI makes random shit up). Aside from vector databases, we can also implement RAG with other data sources and retrieval methods, for example SQL databses (via parsing the outputs of LLM's- more on this later). Autonomous Agents via Output Parsing A common need of clients has been having AI actually perform tasks, rather than simply spitting out text. For example, with autonomous agents, we can have an e-commerce chatbot do the work of a basic customer service rep (i.e. look into orders, refunds, shipping). At a high level, what's going on is that the response of the LLM is being used programmtically to determine which API to call. Keeping on with the e-commerce example, if I wanted a chatbot to check shipping status, I could have a LLM response within my app (not shown to the user) with a prompt that outputs a random hash or string, and programmatically I can determine which API call to make based on this hash/string. And using the same fundamental concept as with RAG, I can append the the API response to a final prompt that would spit out the answer for the user. How No Code Tools Can Fit In (With some example solutions you can build) With that being said, you don't necessarily need to do all of the above by coding yourself, with Python libraries or otherwise. However, I will say that having that high level overview will help IMMENSELY when it comes to using no-code tools to do the actual work for you. Regardless, here are a few common solutions you might build for clients as well as some no-code tools you can use to build them out. Ex. Solution 1: AI Chatbots for SMEs (Small and Medium Enterprises) This involves creating chatbots that handle user queries, lead gen, and so forth with AI, and will use the principles of RAG at heart. After getting the required data from your client (i.e. product catalogues, previous support tickets, FAQ, internal documentation), you upload this into your knowledge base and write a prompt that makes sense for your use case. One no-code tool that does this well is MyAskAI. The beauty of it especially for building external chatbots is the ability to quickly ingest entire websites into your knowledge base via a sitemap, and bulk uploading files. Essentially, they've covered the entire grunt work required to do this manually. Finally, you can create a inline or chat widget on your client's website with a few lines of HTML, or altneratively integrate it with a Slack/Teams chatbot (if you are going for an internal Q&A chatbot approach). Other tools you could use include Botpress and Voiceflow, however these are less for RAG and more for building out complete chatbot flows that may or may not incorporate LLMs. Both apps are essentially GUIs that eliminate the pain and tears and trying to implement complex flows manually, and both natively incoporate AI intents and a knowledge base feature. Ex. Solution 2: Internal Apps Similar to the first example, except we go beyond making just chatbots but tools such as report generation and really any sort of internal tool or automations that may incorporate LLM's. For instance, you can have a tool that automatically generates replies to inbound emails based on your client's knowledge base. Or an automation that does the same thing but for replies to Instagram comments. Another example could be a tool that generates a description and screeenshot based on a URL (useful for directory sites, made one for my own :P). Getting into more advanced implementations of LLMs, we can have tools that can generate entire drafts of reports (think 80+ pages), based not only on data from a knowledge base but also the writing style, format, and author voice of previous reports. One good tool to create content generation panels for your clients would be MindStudio. You can train LLM's via prompt engineering in a structured way with your own data to essentially fine tune them for whatever text you need it to generate. Furthermore, it has a GUI where you can dictate the entire AI flow. You can also upload data sources via multiple formats, including PDF, CSV, and Docx. For automations that require interactions between multiple apps, I recommend the OG zapier/make.com if you want a no-code solution. For instance, for the automatic email reply generator, I can have a trigger such that when an email is received, a custom AI reply is generated by MyAskAI, and finally a draft is created in my email client. Or, for an automation where I can create a social media posts on multiple platforms based on a RSS feed (news feed), I can implement this directly in Zapier with their native GPT action (see screenshot) As for more complex LLM flows that may require multiple layers of LLMs, data sources, and APIs working together to generate a single response i.e. a long form 100 page report, I would recommend tools such as Stack AI or Flowise (open-source alternative) to build these solutions out. Essentially, you get most of the functions and features of Python packages such as Langchain and LlamaIndex in a GUI. See screenshot for an example of a flow How the hell are you supposed to find clients? With all that being said, none of this matters if you can't find anyone to sell to. You will have to do cold sales, one way or the other, especially if you are brand new to the game. And what better way to sell your AI services than with AI itself? If we want to integrate AI into the cold outreach process, first we must identify what it's good at doing, and that's obviously writing a bunch of text, in a short amount of time. Similar to the solutions that an AAA can build for its clients, we can take advantage of the same principles in our own sales processes. How to do outreach Once you've identified your niche and their pain points/opportunities for automation, you want to craft a compelling message in which you can send via cold email and cold calls to get prospects booked on demos/consultations. I won't get into too much detail in terms of exactly how to write emails or calling scripts, as there are millions of resources to help with this, but I will tell you a few key points you want to keep in mind when doing outreach for your AAA. First, you want to keep in mind that many businesses are still hesitant about AI and may not understand what it really is or how it can benefit their operations. However, we can take advantage of how mass media has been reporting on AI this past year- at the very least people are AWARE that sooner or later they may have to implement AI into their businesses to stay competitive. We want to frame our message in a way that introduces generative AI as a technology that can have a direct, tangible, and positive impact on their business. Although it may be hard to quantify, I like to include estimates of man-hours saved or costs saved at least in my final proposals to prospects. Times are TOUGH right now, and money is expensive, so you need to have a compelling reason for businesses to get on board. Once you've gotten your messaging down, you will want to create a list of prospects to contact. Tools you can use to find prospects include Apollo.io, reply.io, zoominfo (expensive af), and Linkedin Sales Navigator. What specific job titles, etc. to target will depend on your niche but for smaller companies this will tend to be the owner. For white collar niches, i.e. law, the professional that will be directly benefiting from the tool (i.e. partners) may be better to contact. And for larger organizations you may want to target business improvement and digital transformation leads/directors- these are the people directly in charge of projects like what you may be proposing. Okay- so you have your message, and your list, and now all it comes down to is getting the good word out. I won't be going into the details of how to send these out, a quick Google search will give you hundreds of resources for cold outreach methods. However, personalization is key and beyond simple dynamic variables you want to make sure you can either personalize your email campaigns directly with AI (SmartWriter.ai is an example of a tool that can do this), or at the very least have the ability to import email messages programmatically. Alternatively, ask ChatGPT to make you a Python Script that can take in a list of emails, scrape info based on their linkedin URL or website, and all pass this onto a GPT prompt that specifies your messaging to generate an email. From there, send away. How tf do I close? Once you've got some prospects booked in on your meetings, you will need to close deals with them to turn them into clients. Call #1: Consultation Tying back to when I mentioned you want to take a consultant-first appraoch, you will want to listen closely to their goals and needs and understand their pain points. This would be the first call, and typically I would provide a high level overview of different solutions we could build to tacke these. It really helps to have a presentation available, so you can graphically demonstrate key points and key technologies. I like to use Plus AI for this, it's basically a Google Slides add-on that can generate slide decks for you. I copy and paste my default company messaging, add some key points for the presentation, and it comes out with pretty decent slides. Call #2: Demo The second call would involve a demo of one of these solutions, and typically I'll quickly prototype it with boilerplate code I already have, otherwise I'll cook something up in a no-code tool. If you have a niche where one type of solution is commonly demanded, it helps to have a general demo set up to be able to handle a larger volume of calls, so you aren't burning yourself out. I'll also elaborate on how the final product would look like in comparison to the demo. Call #3 and Beyond: Once the initial consultation and demo is complete, you will want to alleviate any remaining concerns from your prospects and work with them to reach a final work proposal. It's crucial you lay out exactly what you will be building (in writing) and ensure the prospect understands this. Furthermore, be clear and transparent with timelines and communication methods for the project. In terms of pricing, you want to take this from a value-based approach. The same solution may be worth a lot more to client A than client B. Furthermore, you can create "add-ons" such as monthly maintenance/upgrade packages, training sessions for employeees, and so forth, separate from the initial setup fee you would charge. How you can incorporate AI into marketing your businesses Beyond cold sales, I highly recommend creating a funnel to capture warm leads. For instance, I do this currently with my AI tools directory, which links directly to my AI agency and has consistent branding throughout. Warm leads are much more likely to close (and honestly, much nicer to deal with). However, even without an AI-related website, at the very least you will want to create a presence on social media and the web in general. As with any agency, you will want basic a professional presence. A professional virtual address helps, in addition to a Google Business Profile (GBP) and TrustPilot. a GBP (especially for local SEO) and Trustpilot page also helps improve the looks of your search results immensely. For GBP, I recommend using ProfilePro, which is a chrome extension you can use to automate SEO work for your GBP. Aside from SEO optimzied business descriptions based on your business, it can handle Q/A answers, responses, updates, and service descriptions based on local keywords. Privacy and Legal Concerns of the AAA Model Aside from typical concerns for agencies relating to service contracts, there are a few issues (especially when using no-code tools) that will need to be addressed to run a successful AAA. Most of these surround privacy concerns when working with proprietary data. In your terms with your client, you will want to clearly define hosting providers and any third party tools you will be using to build their solution, and a DPA with these third parties listed as subprocessors if necessary. In addition, you will want to implement best practices like redacting private information from data being used for building solutions. In terms of addressing concerns directly from clients, it helps if you host your solutions on their own servers (not possible with AI tools), and address the fact only ChatGPT queries in the web app, not OpenAI API calls, will be used to train OpenAI's models (as reported by mainstream media). The key here is to be open and transparent with your clients about ALL the tools you are using, where there data will be going, and make sure to get this all in writing. have fun, and keep an open mind Before I finish this post, I just want to reiterate the fact that this is NOT an easy way to make money. Running an AI agency will require hours and hours of dedication and work, and constantly rearranging your schedule to meet prospect and client needs. However, if you are looking for a new business to run, and have a knack for understanding business operations and are genuinely interested in the pracitcal applications of generative AI, then I say go for it. The time is ticking before AAA becomes the new dropshipping or SMMA, and I've a firm believer that those who set foot first and establish themselves in this field will come out top. And remember, while 100 thousand people may read this post, only 2 may actually take initiative and start.

ChatGPT, Claude.ai and Perplexity for my Youtube Business
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ImpossibleBell4759This week

ChatGPT, Claude.ai and Perplexity for my Youtube Business

I use ChatGPT, Claude. ai and Perplexity for my Youtube Software Review Businesses. I run OVER 20 Youtube Faceless Software Review channels, and those AI tools basically help me with ideas, titles and descriptions. I like how simple is it to use those AI tools and crank out ideas, titles and descriptions in less than 20 minutes. ChatGPT, Claude. ai and Perplexity save me so much time. Managing all those Youtube channels is an all day event. I also save time by not editing and not scripting my videos. I do software reviews and I crank out 3 videos per hour. I can use software to automate some of the videos, but they don't get the same effect, so I do every video with original content. I'm thinking about using Elevenlabs. com so I can have access to hundreds of voices that I can use for my videos. I like their "Speech to Speech" technology. The only problem with Elevenlabs is that I have to do some editing to make it work... and I hate editing. I rather just record my video and upload it to Youtube. I might have to skip on Elevenlabs and the editing, because I need to crank out at least 20 videos per day. It seems like a lot but I focus on 12 hours a day and 3 videos per hour. 12 hours times 3 videos= 36 videos per day. But I only need 20 videos in the 12 hours, so I know I can meet my quota for the day. I'm looking at 20 videos per day times roughly 30 days is 600 videos per month. My goal is to finish the year with at least $100,000 in "CASH" after taxes, paying rent, buying food and having all my bills paid. So, I need to make $273.97 per day times 365 days= $100,000. The most I've made was off 1 video with only 600 views and I made over $3,300. I wasn't even monetized by Youtube. I made all that money from software commissions alone. I don't care about being monetized by Youtube what so ever. With Youtube monetized payouts you need millions of views to make money, with software commissions ranging from 20%- 40% I don't need Youtube revenue. I've broken my Youtube business plan down into bite sized pieces so that I know I can achieve my Goals. CHEERS!

AI Voice Platform Comparison for Small Business Use Cases
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Glad-Syllabub6777This week

AI Voice Platform Comparison for Small Business Use Cases

We provide AI voice agent consultation and solutions in Upwork. One of clients’ frequent questions is which platform is best/perfect for their use cases, like lead qualification, AI receptionist, customer support, etc. This post provides our thoughts on this question. Our overall feeling is that the AI agent technology is still not there yet. It seems close but there are many corner cases the AI bot doesn't handle well. Four major players in the AI voice platforms: Bland ($65M funding) Retell ($4.6M funding) Synthflow ($7.4M funding) VAPI ($20M funding) We will only talk about Bland, Retell and VAPI. We firstly tried Synthflow and found the UI was buggy (the prompt editor froze for 20 seconds to 30 seconds when we were editing the prompt). Currently we don't use it anymore. Recommended use cases based on Upwork jobs we delivered: Bland. We recommend Bland for lead qualification as the lead qualification has a strict conversation flow (like asking questions, extracting variables, and making webhook calls). Clients/contractors can draw flow diagrams to build AI voice agents. We also find Bland is not a good fit for a small business with a monthly budget less than 5K. The reason is that common tools (like warm transfer, SMS sending) for AI voice agents are only available to enterprise clients. But warm transfers are critical for small businesses. Retell. We recommend Retell for customer support in contact centers. Retell has the best voice among competitors. One use case we build in Retell is the live translator in the ambulance call center. We tried the same prompt with the same LLM setup in VAPI. We found Retell performs way better than VAPI in terms of the translation quality and reliability. Another common scenario in the customer support domain is to have 3-way merge so that the agent can tell the summary to the transfer number while the caller can hear the conversation. VAPI. We recommend VAPI for AI receptionists and phone answering use cases. We can write a prompt and ask LLM to do the magic if callers ask questions not included in the prompt. We can set up custom tools to trigger automation (like update CRM) and warm transfer to connect to the stakeholders. One feeling we have is that VAPI is way more complicated than the other two platforms. If you don’t have developer experience and have a budget to hire a contractor, it is better to try Retell as Retell has many integrations. If you have any other questions or we miss anything, feel free to comment. We like to explore AI voice agent space together.

How I went from $27 to $3K as a solopreneur still in a 9-5
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jottrledThis week

How I went from $27 to $3K as a solopreneur still in a 9-5

My journey started back in November 2023. I was scrolling through Twitter and YouTube and saw a word that I had never come across before. Solopreneur. The word caught my eye. Mainly because I was pretty sure I knew what it meant even though it's not a word you'll find in the dictionary. I liked what it was describing. A solo entrepreneur. A one man business. It completely resonated with me. As a software engineer by trade I'm used to working alone, especially since the pandemic hit and we were forced to work remotely. See, I always wanted to ditch the 9-5 thing but thought that was too big and too scary for a single person to do. Surely you would need a lot of money to get started, right? Surely you would need investors? The whole concept seemed impossible to me. That was until I found all the success stories. I became obsessed with the concept of solopreneurship. As I went further down the rabbit hole I found people like Justin Welsh, Kieran Drew and Marc Louvion to name a few. All of whom have one person businesses making huge money every year. So I thought, if they can do it, why can't I? People like this have cleared the pathway for those looking to escape the 9-5 grind. I decided 2024 would be the year I try this out. My main goal for the year? Build a one man business, earn my first $ online and learn a sh\*t ton along the way. My main goal in general? Build my business to $100K per year, quit my 9-5 and live with freedom. From December 2023 to February 2024 I began brainstorming ideas. I was like a lost puppy looking for his ball. How on earth did people find good ideas? I began writing everything and anything that came to mind down in my notes app on my phone. By February I would have approximately 70 ideas. Each as weird and whacky as the other. I was skeptical though. If I went through all the trouble of building a product for one of these ideas how would I know if anyone would even be interested in using it? I got scared and took a break for a week. All these ideas seemed too big and the chance that they would take off into the atmosphere was slim (in my mind anyways). I was learning more and more about solopreneurship as the weeks went on so I decided to build a product centered around everything I was learning about. The idea was simple. Enter a business idea and use AI to give the user details about how to market it, who their target customers were, what to write on their landing page, etc. All for a measly $27 per use. I quickly built it and launched on March 3rd 2024. I posted about it on Indie Hackers, Reddit and Hacker News. I was so excited about the prospect of earning my first internet $! Surely everyone wanted to use my product! Nope...all I got was crickets. I was quickly brought back down to earth. That was until 5 days later. I looked at my phone and had a new Stripe notification! Cha-ching! My first internet $. What a feeling! That was goal number 1 complete. It would be another 6 days before I would get my second sale...and then another 15 days to get my third. It was an emotional rollercoaster. I went from feeling like quitting the 9-5 was actually possible to thinking that maybe the ups and downs aren't worth it. On one hand I had made my first internet dollar so I should my ecstatic, and don't get me wrong, I was but I wanted more. More validation that I could do this long term. By May I was starting to give up on the product. I had learned so much in the past few months about marketing, SEO, building an audience, etc. and I wanted to build something that I thought could have more success so I focused on one critical thing that I had learned about. What was it? Building a product that had SEO potential. A product that I knew hundreds of people were looking for. See this was my thinking - If I could find a keyword that people were searching for on Google hundreds/thousands of times every month and it was easy to rank high on search engines then I would go all in (in SEO land this equates to a Keyword that has a Keyword Difficulty of = 500). I began researching and found that the keyword "micro saas ideas" was being searched for around 600 times each month. Micro Saas was something that really interested me. It was perfect for solopreneurs. Small software products that 1 person could build. What's not to like if you're in the game of software and solopreneurship? Researching keywords like this became like a game for me. I was hooked. I was doing it every day, finding gems that were being searched for hundreds and thousands of times every month that still had potential. That's when I came up with my next product idea. I decided to create a database of Micro Saas Ideas all with this sort of SEO potential. See if you can build a product that you know people are looking for then that's all the validation you need. So I put this theory to the test. I created a database of Micro Saas Ideas with SEO Potential and launched it in June 2024. This time it was different. I made $700 in the first week of launching. A large contrast to my previous failed attempt at becoming the worlds greatest solopreneur. Since launch I have grown the product to $3K and I couldn't be happier. I know what you're saying, $3K isn't a lot. But it's validation. It's validation that I can earn $ online. Validation that I can grow a business and it gives me hope that one day I'll be able to quit that 9-5 grind. My plan is to keep growing the business. I expect there to be a few challenges up ahead but I'll tackle them as I go and learn from the failures and successes. I have a newsletter where I share Micro Saas Ideas with SEO potential every week which I'll leave below in the first comment. Feel free to come along for the ride. If not I hope this post brings you some value If you're thinking about starting as a solopreneur, stop thinking and start doing, you won't regret it.

5 no-code tools to build your website fast and easy.
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alexanderolssenThis week

5 no-code tools to build your website fast and easy.

Hey, reddittors👋 Want to build a website but don't know how to code? 🥺 No problem! There are a number of no-code tools available that can help you create a professional-looking website without any coding knowledge. 👇 Carrd Carrd is a free website builder that allows you to create simple, one-page websites, profile pages, portfolios and forms with super-easy-to learn editor. It's a great option for people who want to create a website quickly and easily without having to learn how to code. Carrd has 16 website design elements, such as text, audio, video, images, buttons, tables, galleries, and code embeds that can be used to define the structure of your website. Pros: Easy to use, affordable (free/$19 per year plans), variety of templates, widgets (PayPal, Gumroad, Stripe, Typeform, etc), responsive out of the box, has some basic animations. Cons: Lack of design freedom, hard to build a scalable website, most of the templates looks design outdated, not suitable for blogs and online stores. Best for: Solo entrepreneurs, Artists, Photographers, Copywriters, SMB’s with no design/development background. Framer Primarily aimed at designers, Framer is a no-code tool that let’s you create highly-customized websites that vary from simple landing pages to multi-page company websites. It has all the necessary building blocks and features to create any website your company might need. It’s even has an AI websites builder built in! Pros: Complete design freedom, powerful animation engine, content management system (CMS), Easy to pick up for designers, plenty of learning resources, code embeds, SEO settings, affordable ($19/month), collaboration (you can invite team to work with you on the website simultaneously), library of prebuilt components, Figma-to-Framer plugin that lets you copy-paste designs into Framer with ease. Cons: Learning curve, not the best pick for bulky websites. Best for: Freelance designers & agencies, In-house design teams WordPress WordPress is a free and open-source content management system (CMS). It is the most popular website builder in the world, powering over 455 million websites. It has all features you might need to build a landing page, multi-page website, blogs, ecommerce stores, gated content websites, etc. Pros: Tons of learning materials, highly customizable, SEO-friendly, scalability, lots of plugins and themes, large community Cons: Security vulnerabilities, learning curve, website maintenance required, performance issues, dependency on plugins. Best for: Freelance designers & agencies, In-house design teams, solo entrepreneurs, SMB’s, bloggers. &#x200B; Wix Wix is a popular website builder that has gained immense popularity for its user-friendly interface and a wide range of features designed to cater to both beginners and experienced web creators. Offering an array of customizable templates, drag-and-drop functionality, and an impressive app market, Wix empowers users to bring their online visions to life without requiring extensive technical knowledge. Pros: Easy-to-use, robust learning resources, scalability, huge template library, e-commerce tools, feature-rich (app market, appointment booking, etc) Cons: Limited design flexibility, \\\\not so flexible, websites may be slow, bad customer support, limited SEO features Best for: Freelance designers & agencies, In-house design teams, solo entrepreneurs, SMB’s. &#x200B; Webflow Webflow is a no-code platform that lets you build any type of website visually, from marketing landing pages to multi-page corporate websites, gated content websites, blogs, portfolios, and ecommerce stores. It is a powerful and versatile tool that is suitable for a variety of users, including businesses that care about design and want to move quickly. Pros: Absolute design freedom, Robust learning resources, SEO-friendly, scalability, huge template library, large and supportive community, Integrations, Advanced SEO control, custom code, website export, powerful animation engine and CMS. Cons: learning curve, not for massive ecommerce stores, high pricing, Webflow support. Best for: Freelance designers & agencies, In-house design teams, solo entrepreneurs, SMB’s. &#x200B; Bonus tools: Hubspot landing pages — Marketing-oriented landing page builder. Instapage — Great for businesses that use paid advertising, as it offers A/B testing and heatmaps to help you optimize your landing pages for better results Unicorn Platform — SaaS-oriented landing page builder. \---------- Resume: If you have a budget and need a tool with strong design capabilities, scalability, and speed of build, then Webflow is a good choice. Framer is a great option for teams with a single designer, as it is easy for designers to learn and use. Or try Unicorn Platform, if you're running a SaaS business on your own and tight on a budget. No matter which tool you choose, you can create a well-designed website by using the extensive template library that each tool offers. These templates can be customized to fit your specific needs and branding.

This founder was about to shut down his startup and open a restaurant. He pivoted the business and grew it to $45m ARR in 12 months. What else have you seen grow that fast?
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CountryPitifulThis week

This founder was about to shut down his startup and open a restaurant. He pivoted the business and grew it to $45m ARR in 12 months. What else have you seen grow that fast?

I heard that Jasper scaled to $45m ARR in 12 months...with a team of 8. For context, they are one of the fastest-growing companies ever. Grew from $0 to $45m ARR in 12 months (then raised $125m at a $1.5b valuation). As a fellow founder, their story is really inspiring to me (curious about what others think): In December 2020, Dave Rogenmoser and his co-founders were on the brink of shutting down their business. They'd spent 3+ years building a conversion optimization software called Proof...and it was flatlining. A few weeks prior they had to make the painful decision to let go of half their team. Competition and churn had completely eroded growth. Things were painful. 8 years of work left them with a string of startups that never quite made it: 2 failed software businesses (couldn't make money*) A SMB marketing agency (maxed out at $25k/mo*) An online course company (hard to get big*) The Pivot: In January 2021, they had an idea to use Chat GPT-3, the generative AI model released 6 months earlier, to write high-converting Facebook ads. Within 30 days, they launched the business. With the skeleton crew remaining from the last startup, they scaled the business to $45m ARR and 70,000+ customers without hiring a single new person. Soon after, they raised $125m at a $1.5b valuation. Dave Rogenmoser, CEO at Jasper, had some great one-liners in a few podcasts I listened to on the business. Here are some of his learnings: Right Skill, Wrong Vehicle: He spent 8 years building marketing businesses which gave this team the knowledge and confidence to spend $1m/mo on sales and marketing to scale the business to $45m ARR in year 1. Launch Fast & Iterate Quickly: The team agreed that if the business didn't work in 30 days, they'd shut it down. Dave says, "If you have been working on a problem for more than 18 months and haven't found Product market fit (PMF), odds are you won't...Make the hard pivot."* Ride A Big Wave: Generative AI technology is a new technology that is changing the way we work. But it's not just text. It's images, voice, etc. Identify new customer segments (e.g., Municipalities, Banks, Lawyers, etc.), learn their problems, and apply this novel technology to solve them. What other businesses have you seen scale like this? I've never seen a SaaS business grow that fast. I meet interesting founders 2x per week and share the learnings here.

I’m building a “DesignPickle” for all things Funnels. Would love your feedback...
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Gluteous_MaximusThis week

I’m building a “DesignPickle” for all things Funnels. Would love your feedback...

Hey Entrepreneurs, Early next year I’m rolling out a productized service business along the lines of Design Pickle, but instead of design assets, we create on-demand marketing assets: Things like landing pages, lead magnets, email campaigns, etc. This is NOT an agency with client engagements, etc.  It is an on-demand, menu-item style fulfillment platform where we do a few predefined things really, really well, and as much as possible try to reduce the complexity (and required customer inputs) so that creating your next killer Funnel is as easy as ordering dinner on Skip the Dishes. Below I’ve laid out our current thinking (we’re still distilling this into a deck), just so you have the full context.  And at the end, I pose 5 feedback questions. So if this “deck” seems interesting to you, then I’d love to get your feedback at the end 🙂 Thanks! And here goes... \--- The current elevator pitch:  We will research your business, your market and your competitors to develop a killer Lead Magnet, Landing Page, Ad Creatives and a 30-Day Email Drip campaign designed to turn your traffic into a rabid, lifelong buyer tribe (that you can email for years... like having your own, on-demand cash printer).  The overall thesis:  While AI is getting continually better at creating things like one-off graphics, article content, and so on - we do not think it can deeply understand market psychology, what keeps your customers up at night, or the underlying emotions that drive purchase decisions at the individual level, for your specific offer(s). Moreover, it’s also this psychological aspect of marketing where most businesses simply do not have the talent, resources or frankly the experience to create high-performing funnels themselves, regardless of how much "automation" they might have at their fingertips. And that’s because this is where you need to know who your customer really is, and what they’re actually buying (hint: not your features). Few marketers focus on these fundamentals, let alone understand the selling process. This is also why tools like ClickFunnels, HighLevel, LeadPages, etc. while very helpful, can only help with the logistics of selling. It’s still on each business to figure out how to actually tell their story, capture demand, and sell effectively. This is why a productized service that nails market research, competitor analysis & world-class copywriting that can actually turn cold traffic into lifelong customers is going to be a no-brainer for a business that’s currently struggling to actually get a steady flow of online sales. This is not something we see AI replacing effectively, any time soon. Current gaps & unknowns:  At a top level, I’m not overly worried about validation or viability; there are several existing competitors, and obviously the automation platforms have substantial customer bases (ClickFunnels etc). There will be a certain cohort that will want experts to do the actual thinking for them, storytelling, etc. Even if it’s a relatively small cohort, given the CLTV of a service like this, it still makes for a decent sized business. But where I’m less confident is in who our ideal customer actually is... Yes, basically every direct-response internet business needs an effective funnel that can sell. Whether you’re an Enterprise SaaS platform or a solopreneur launching your first $39 ebook, you will benefit from a killer funnel. As a “DesignPickle” type service though, here’s the challenges I see with each core customer category... B2B SaaS: While sales decisions are still emotional, it’s more about account-based considerations; people usually aren’t spending their own money, so it’s more about not looking stupid vs. gaining some benefit. Harder to systemize. Very high stakes. Consumer / SMB SaaS: While I think in general these are ideal customers, there will be resistance to leaning in hard on personality (and personal brand); founders usually want to sell at some point, so if they become the face of the platform, then boosting performance with a high-personality funnel might ironically make it a harder business to sell. SaaS founders are also generally very technical and stereotypically avoid marketing like the plague. Ecommerce: Most DTC brands think of funnels as an extension of their FB ad campaigns; few see their customers as a long-term audience that can become a significant asset. However, certain lifestyle / luxury brands might differ. Online Courses / Coaches: Of all the customer profiles, this group probably has the most appreciation for the effectiveness of marketing psychology, copywriting, etc. and would get the value prop quickly. The problem is that most won’t have the budget or traction to outsource asset creation. This is the “poorest” segment of the market. Service Businesses: Agencies, consultancies, and so on would greatly benefit from having a strong personal brand + storytelling premise (funnel). However, they’re also the worst offenders when it comes to never practicing what they preach / do for others. Client work soaks up all their resources. Local & Brick/Mortar: Generally speaking most local businesses are going to have smaller audiences (email lists under 2K subs), where funnel ops might have limited value long-term due to a lack of scale. And for larger B&M brands with franchises across various locations, you get into stakeholder friction; messaging usually gets watered down to basic corporate-speak as a result. Now, to be clear, I still see a ton of opportunity in each of those main customer categories as well, but I like to be clear-eyed about the overall resistance each niche will have - mainly because this helps to refine messaging to an ideal customer profile within them. In this case though, so far, nothing’s really jumping out at me as a clear “winner” at a category level. So far, what I’m thinking is our ICP might be situational / conditional. For example: A business has a funnel / is invested in the process, but it’s not working yet A business sees their competitor killing it with a funnel, and they’re ultra motivated to do it even better A business has one funnel that’s working awesome, and everything else they try sucks (so they can’t scale / expand) Etc. Basically, our most ideal customer might be ANY type of business who gets it, who’s tried to do this themselves, and now needs the pros to come in and fix things. \--- This is where your feedback would be incredibly valuable... First, if you’ve made it all the way down to this point - thanks for enduring my rambling mess above! But I did think the context might be helpful. Based on our overall biz plan & go-to-market considerations discussed above, if you run a business (or work with one) that might benefit from something like this, I’d love to ask a few questions... What is the nature of your business? (What do you sell)? What do you find hardest about selling to your online audience? Have you built a funnel in the past / are you running one currently? If not, what’s stopping you from building a high-performing funnel? If you had a “magic marketing lamp” where a genie could create ONE amazing marketing asset for you (eg. a killer landing page, video ad, launch strategy, etc), but you could only use it ONCE, what would you have the genie do for you? Please reply below as a comment, or DM me if you’d prefer to keep answers anonymous.  Thanks so much And again, apologies for the novel... Cheers

Best AI tools to help company productivity?
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Best AI tools to help company productivity?

Hey guys! I recently did a big restructuring of my production company and moving away from smaller businesses ad’s and moving up to working with larger marketing agencies. My partner and I are brainstorming ways to automate or at least improve certain parts of our business as we also start to expand our team & to improve ease of labour as our turn around times tend to have to be pretty quick. The main things we’re looking to improve is in: • Sales/out reach strategy: we are constantly reaching out to new agencies in different parts of the world. I am already used to manually making a plan for each company we reach out to but it can be very time consuming. I don’t know if there is even a tool that could help with this haha. Even if it helps with pointers! • Organizing/visualizing spreadsheets: we deal with spreadsheets on what we spend per production and how we distribute our total budget per department. If there is anyway to ease the workflow for our managers and on top of that also allow us to expand easier without having to look for someone who is very efficient on excel or spending more time and money on the training. • Scheduling: We already have so much to organize day per day, im not sure if there is any tool or ai system that could help in regards to scheduling meetings, organizing priorities or even just deadlines for certain projects. Example: we need to schedule everything from pre production deadlines (meetings with talent, agency, and crew) production deadlines, & post production deadlines. I’m sure there is other small things I am missing but those are the three main things! There is just so many things i saw on the internet that are “ai powered” or “ai improved workflow” that all claim are the best or some just use chat gpt so its essentially all the same thing. I thought id ask on here to see if anyone has actually tried and could recommend some ai tools out there! Cheers,

As a soloproneur, here is how I'm scaling with AI and GPT-based tools
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As a soloproneur, here is how I'm scaling with AI and GPT-based tools

Being a solopreneur has its fair share of challenges. Currently I've got businesses in ecommerce, agency work, and affiliate marketing, and one undeniable truth remains: to truly scale by yourself, you need more than just sheer will. That's where I feel technology, especially AI, steps in. As such, I wanted some AI tools that have genuinely made a difference in my own work as a solo business operator. No fluff, just tried-and-true tools and platforms that have worked for me. The ability for me to scale alone with AI tools that take advantage of GPT in one way, or another has been significant and really changed my game over the past year. They bring in an element of adaptability and intelligence and work right alongside “traditional automation”. Whether you're new to this or looking to optimize your current setup, I hope this post helps. FYI I used multiple prompts with GPT-4 to draft this using my personal notes. Plus AI (add-on for google slides/docs) I handle a lot of sales calls and demos for my AI automation agency. As I’m providing a custom service rather than a product, every client has different pain points and as such I need to make a new slide deck each time. And making slides used to be a huge PITA and pretty much the bane of my existence until slide deck generators using GPT came out. My favorite so far has been PlusAI, which works as a plugin for Google Slides. You pretty much give it a rough idea, or some key points and it creates some slides right within Google Slides. For me, I’ve been pasting the website copy or any information on my client, then telling PlusAI the service I want to propose. After the slides are made, you have a lot of leeway to edit the slides again with AI, compared to other slide generators out there. With 'Remix', I can switch up layouts if something feels off, and 'Rewrite' is there to gently nudge the AI in a different direction if I ever need it to. It's definitely given me a bit of breathing space in a schedule that often feels suffocating. echo.win (web-based app) As a solopreneur, I'm constantly juggling roles. Managing incoming calls can be particularly challenging. Echo.win, a modern call management platform, has become a game-changer for my business. It's like having a 24/7 personal assistant. Its advanced AI understands and responds to queries in a remarkably human way, freeing up my time. A standout feature is the Scenario Builder, allowing me to create personalized conversation flows. Live transcripts and in-depth analytics help me make data-driven decisions. The platform is scalable, handling multiple simultaneous calls and improving customer satisfaction. Automatic contact updates ensure I never miss an important call. Echo.win's pricing is reasonable, offering a personalized business number, AI agents, unlimited scenarios, live transcripts, and 100 answered call minutes per month. Extra minutes are available at a nominal cost. Echo.win has revolutionized my call management. It's a comprehensive, no-code platform that ensures my customers are always heard and never missed MindStudio by YouAi (web app/GUI) I work with numerous clients in my AI agency, and a recurring task is creating chatbots and demo apps tailored to their specific needs and connected to their knowledge base/data sources. Typically, I would make production builds from scratch with libraries such as LangChain/LlamaIndex, however it’s quite cumbersome to do this for free demos. As each client has unique requirements, it means I'm often creating something from scratch. For this, I’ve been using MindStudio (by YouAi) to quickly come up with the first iteration of my app. It supports multiple AI models (GPT, Claude, Llama), let’s you upload custom data sources via multiple formats (PDF, CSV, Excel, TXT, Docx, and HTML), allows for custom flows and rules, and lets you to quickly publish your apps. If you are in their developer program, YouAi has built-in payment infrastructure to charge your users for using your app. Unlike many of the other AI builders I’ve tried, MindStudio basically lets me dictate every step of the AI interaction at a high level, while at the same time simplifying the behind-the-scenes work. Just like how you'd sketch an outline or jot down main points, you start with a scaffold or decide to "remix" an existing AI, and it will open up the IDE. I often find myself importing client data or specific project details, and then laying out the kind of app or chatbot I'm looking to prototype. And once you've got your prototype you can customize the app as much as you want. LLamaIndex (Python framework) As mentioned before, in my AI agency, I frequently create chatbots and apps for clients, tailored to their specific needs and connected to their data sources. LlamaIndex, a data framework for LLM applications, has been a game-changer in this process. It allows me to ingest, structure, and access private or domain-specific data. The major difference over LangChain is I feel like LlamaIndex does high level abstraction much better.. Where LangChain unnecessarily abstracts the simplest logic, LlamaIndex actually has clear benefits when it comes to integrating your data with LLMs- it comes with data connectors that ingest data from various sources and formats, data indexes that structure data for easy consumption by LLMs, and engines that provide natural language access to data. It also includes data agents, LLM-powered knowledge workers augmented by tools, and application integrations that tie LlamaIndex back into the rest of the ecosystem. LlamaIndex is user-friendly, allowing beginners to use it with just five lines of code, while advanced users can customize and extend any module to fit their needs. To be completely honest, to me it’s more than a tool- at its heart it’s a framework that ensures seamless integration of LLMs with data sources while allowing for complete flexibility compared to no-code tools. GoCharlie (web app) GoCharlie, the first AI Agent product for content creation, has been a game-changer for my business. Powered by a proprietary LLM called Charlie, it's capable of handling multi-input/multi-output tasks. GoCharlie's capabilities are vast, including content repurposing, image generation in 4K and 8K for various aspect ratios, SEO-optimized blog creation, fact-checking, web research, and stock photo and GIF pull-ins. It also offers audio transcriptions for uploaded audio/video files and YouTube URLs, web scraping capabilities, and translation. One standout feature is its multiple input capability, where I can attach a file (like a brand brief from a client) and instruct it to create a social media campaign using brand guidelines. It considers the file, prompt, and website, and produces multiple outputs for each channel, each of which can be edited separately. Its multi-output feature allows me to write a prompt and receive a response, which can then be edited further using AI. Overall, very satisfied with GoCharlie and in my opinion it really presents itself as an effective alternative to GPT based tools. ProfilePro (chrome extension) As someone overseeing multiple Google Business Profiles (GBPs) for my various businesses, I’ve been using ProfilePro by Merchynt. This tool stood out with its ability to auto-generate SEO-optimized content like review responses and business updates based on minimal business input. It works as a Chrome extension, and offers suggestions for responses automatically on your GBP, with multiple options for the tone it will write in. As a plus, it can generate AI images for Google posts, and offer suggestions for services and service/product descriptions. While it streamlines many GBP tasks, it still allows room for personal adjustments and refinements, offering a balance between automation and individual touch. And if you are like me and don't have dedicated SEO experience, it can handle ongoing optimization tasks to help boost visibility and drive more customers to profiles through Google Maps and Search

I run an AI automation agency (AAA). My honest overview and review of this new business model
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I run an AI automation agency (AAA). My honest overview and review of this new business model

I started an AI tools directory in February, and then branched off that to start an AI automation agency (AAA) in June. So far I've come across a lot of unsustainable "ideas" to make money with AI, but at the same time a few diamonds in the rough that aren't fully tapped into yet- especially the AAA model. Thought I'd share this post to shine light into this new business model and share some ways you could potentially start your own agency, or at the very least know who you are dealing with and how to pick and choose when you (inevitably) get bombarded with cold emails from them down the line. Foreword Running an AAA does NOT involve using AI tools directly to generate and sell content directly. That ship has sailed, and unless you are happy with $5 from Fiverr every month or so, it is not a real business model. Cry me a river but generating generic art with AI and slapping it onto a T-shirt to sell on Etsy won't make you a dime. At the same time, the AAA model will NOT require you to have a deep theoretical knowledge of AI, or any academic degree, as we are more so dealing with the practical applications of generative AI and how we can implement these into different workflows and tech-stacks, rather than building AI models from the ground up. Regardless of all that, common sense and a willingness to learn will help (a shit ton), as with anything. Keep in mind - this WILL involve work and motivation as well. The mindset that AI somehow means everything can be done for you on autopilot is not the right way to approach things. The common theme of businesses I've seen who have successfully implemented AI into their operations is the willingess to work with AI in a way that augments their existing operations, rather than flat out replace a worker or team. And this is exactly the train of thought you need when working with AI as a business model. However, as the field is relatively unsaturated and hype surrounding AI is still fresh for enterprises, right now is the prime time to start something new if generative AI interests you at all. With that being said, I'll be going over three of the most successful AI-adjacent businesses I've seen over this past year, in addition to some tips and resources to point you in the right direction. so.. WTF is an AI Automation Agency? The AI automation agency (or as some YouTubers have coined it, the AAA model) at its core involves creating custom AI solutions for businesses. I have over 1500 AI tools listed in my directory, however the feedback I've received from some enterprise users is that ready-made SaaS tools are too generic to meet their specific needs. Combine this with the fact virtually no smaller companies have the time or skills required to develop custom solutions right off the bat, and you have yourself real demand. I would say in practice, the AAA model is quite similar to Wordpress and even web dev agencies, with the major difference being all solutions you develop will incorporate key aspects of AI AND automation. Which brings me to my second point- JUST AI IS NOT ENOUGH. Rather than reducing the amount of time required to complete certain tasks, I've seen many AI agencies make the mistake of recommending and (trying to) sell solutions that more likely than not increase the workload of their clients. For example, if you were to make an internal tool that has AI answer questions based on their knowledge base, but this knowledge base has to be updated manually, this is creating unnecessary work. As such I think one of the key components of building successful AI solutions is incorporating the new (Generative AI/LLMs) with the old (programmtic automation- think Zapier, APIs, etc.). Finally, for this business model to be successful, ideally you should target a niche in which you have already worked and understand pain points and needs. Not only does this make it much easier to get calls booked with prospects, the solutions you build will have much greater value to your clients (meaning you get paid more). A mistake I've seen many AAA operators make (and I blame this on the "Get Rich Quick" YouTubers) is focusing too much on a specific productized service, rather than really understanding the needs of businesses. The former is much done via a SaaS model, but when going the agency route the only thing that makes sense is building custom solutions. This is why I always take a consultant-first approach. You can only build once you understand what they actually need and how certain solutions may impact their operations, workflows, and bottom-line. Basics of How to Get Started Pick a niche. As I mentioned previously, preferably one that you've worked in before. Niches I know of that are actively being bombarded with cold emails include real estate, e-commerce, auto-dealerships, lawyers, and medical offices. There is a reason for this, but I will tell you straight up this business model works well if you target any white-collar service business (internal tools approach) or high volume businesses (customer facing tools approach). Setup your toolbox. If you wanted to start a pressure washing business, you would need a pressure-washer. This is no different. For those without programming knowledge, I've seen two common ways AAA get setup to build- one is having a network of on-call web developers, whether its personal contacts or simply going to Upwork or any talent sourcing agency. The second is having an arsenal of no-code tools. I'll get to this more in a second, but this works beecause at its core, when we are dealing with the practical applications of AI, the code is quite simple, simply put. Start cold sales. Unless you have a network already, this is not a step you can skip. You've already picked a niche, so all you have to do is find the right message. Keep cold emails short, sweet, but enticing- and it will help a lot if you did step 1 correctly and intimately understand who your audience is. I'll be touching base later about how you can leverage AI yourself to help you with outreach and closing. The beauty of gen AI and the AAA model You don't need to be a seasoned web developer to make this business model work. The large majority of solutions that SME clients want is best done using an API for an LLM for the actual AI aspect. The value we create with the solutions we build comes with the conceptual framework and design that not only does what they need it to but integrates smoothly with their existing tech-stack and workflow. The actual implementation is quite straightforward once you understand the high level design and know which tools you are going to use. To give you a sense, even if you plan to build out these apps yourself (say in Python) the large majority of the nitty gritty technical work has already been done for you, especially if you leverage Python libraries and packages that offer high level abstraction for LLM-related functions. For instance, calling GPT can be as little as a single line of code. (And there are no-code tools where these functions are simply an icon on a GUI). Aside from understanding the capabilities and limitations of these tools and frameworks, the only thing that matters is being able to put them in a way that makes sense for what you want to build. Which is why outsourcing and no-code tools both work in our case. Okay... but how TF am I suppposed to actually build out these solutions? Now the fun part. I highly recommend getting familiar with Langchain and LlamaIndex. Both are Python libraires that help a lot with the high-level LLM abstraction I mentioned previously. The two most important aspects include being able to integrate internal data sources/knowledge bases with LLMs, and have LLMs perform autonomous actions. The two most common methods respectively are RAG and output parsing. RAG (retrieval augmented Generation) If you've ever seen a tool that seemingly "trains" GPT on your own data, and wonder how it all works- well I have an answer from you. At a high level, the user query is first being fed to what's called a vector database to run vector search. Vector search basically lets you do semantic search where you are searching data based on meaning. The vector databases then retrieves the most relevant sections of text as it relates to the user query, and this text gets APPENDED to your GPT prompt to provide extra context to the AI. Further, with prompt engineering, you can limit GPT to only generate an answer if it can be found within this extra context, greatly limiting the chance of hallucination (this is where AI makes random shit up). Aside from vector databases, we can also implement RAG with other data sources and retrieval methods, for example SQL databses (via parsing the outputs of LLM's- more on this later). Autonomous Agents via Output Parsing A common need of clients has been having AI actually perform tasks, rather than simply spitting out text. For example, with autonomous agents, we can have an e-commerce chatbot do the work of a basic customer service rep (i.e. look into orders, refunds, shipping). At a high level, what's going on is that the response of the LLM is being used programmtically to determine which API to call. Keeping on with the e-commerce example, if I wanted a chatbot to check shipping status, I could have a LLM response within my app (not shown to the user) with a prompt that outputs a random hash or string, and programmatically I can determine which API call to make based on this hash/string. And using the same fundamental concept as with RAG, I can append the the API response to a final prompt that would spit out the answer for the user. How No Code Tools Can Fit In (With some example solutions you can build) With that being said, you don't necessarily need to do all of the above by coding yourself, with Python libraries or otherwise. However, I will say that having that high level overview will help IMMENSELY when it comes to using no-code tools to do the actual work for you. Regardless, here are a few common solutions you might build for clients as well as some no-code tools you can use to build them out. Ex. Solution 1: AI Chatbots for SMEs (Small and Medium Enterprises) This involves creating chatbots that handle user queries, lead gen, and so forth with AI, and will use the principles of RAG at heart. After getting the required data from your client (i.e. product catalogues, previous support tickets, FAQ, internal documentation), you upload this into your knowledge base and write a prompt that makes sense for your use case. One no-code tool that does this well is MyAskAI. The beauty of it especially for building external chatbots is the ability to quickly ingest entire websites into your knowledge base via a sitemap, and bulk uploading files. Essentially, they've covered the entire grunt work required to do this manually. Finally, you can create a inline or chat widget on your client's website with a few lines of HTML, or altneratively integrate it with a Slack/Teams chatbot (if you are going for an internal Q&A chatbot approach). Other tools you could use include Botpress and Voiceflow, however these are less for RAG and more for building out complete chatbot flows that may or may not incorporate LLMs. Both apps are essentially GUIs that eliminate the pain and tears and trying to implement complex flows manually, and both natively incoporate AI intents and a knowledge base feature. Ex. Solution 2: Internal Apps Similar to the first example, except we go beyond making just chatbots but tools such as report generation and really any sort of internal tool or automations that may incorporate LLM's. For instance, you can have a tool that automatically generates replies to inbound emails based on your client's knowledge base. Or an automation that does the same thing but for replies to Instagram comments. Another example could be a tool that generates a description and screeenshot based on a URL (useful for directory sites, made one for my own :P). Getting into more advanced implementations of LLMs, we can have tools that can generate entire drafts of reports (think 80+ pages), based not only on data from a knowledge base but also the writing style, format, and author voice of previous reports. One good tool to create content generation panels for your clients would be MindStudio. You can train LLM's via prompt engineering in a structured way with your own data to essentially fine tune them for whatever text you need it to generate. Furthermore, it has a GUI where you can dictate the entire AI flow. You can also upload data sources via multiple formats, including PDF, CSV, and Docx. For automations that require interactions between multiple apps, I recommend the OG zapier/make.com if you want a no-code solution. For instance, for the automatic email reply generator, I can have a trigger such that when an email is received, a custom AI reply is generated by MyAskAI, and finally a draft is created in my email client. Or, for an automation where I can create a social media posts on multiple platforms based on a RSS feed (news feed), I can implement this directly in Zapier with their native GPT action (see screenshot) As for more complex LLM flows that may require multiple layers of LLMs, data sources, and APIs working together to generate a single response i.e. a long form 100 page report, I would recommend tools such as Stack AI or Flowise (open-source alternative) to build these solutions out. Essentially, you get most of the functions and features of Python packages such as Langchain and LlamaIndex in a GUI. See screenshot for an example of a flow How the hell are you supposed to find clients? With all that being said, none of this matters if you can't find anyone to sell to. You will have to do cold sales, one way or the other, especially if you are brand new to the game. And what better way to sell your AI services than with AI itself? If we want to integrate AI into the cold outreach process, first we must identify what it's good at doing, and that's obviously writing a bunch of text, in a short amount of time. Similar to the solutions that an AAA can build for its clients, we can take advantage of the same principles in our own sales processes. How to do outreach Once you've identified your niche and their pain points/opportunities for automation, you want to craft a compelling message in which you can send via cold email and cold calls to get prospects booked on demos/consultations. I won't get into too much detail in terms of exactly how to write emails or calling scripts, as there are millions of resources to help with this, but I will tell you a few key points you want to keep in mind when doing outreach for your AAA. First, you want to keep in mind that many businesses are still hesitant about AI and may not understand what it really is or how it can benefit their operations. However, we can take advantage of how mass media has been reporting on AI this past year- at the very least people are AWARE that sooner or later they may have to implement AI into their businesses to stay competitive. We want to frame our message in a way that introduces generative AI as a technology that can have a direct, tangible, and positive impact on their business. Although it may be hard to quantify, I like to include estimates of man-hours saved or costs saved at least in my final proposals to prospects. Times are TOUGH right now, and money is expensive, so you need to have a compelling reason for businesses to get on board. Once you've gotten your messaging down, you will want to create a list of prospects to contact. Tools you can use to find prospects include Apollo.io, reply.io, zoominfo (expensive af), and Linkedin Sales Navigator. What specific job titles, etc. to target will depend on your niche but for smaller companies this will tend to be the owner. For white collar niches, i.e. law, the professional that will be directly benefiting from the tool (i.e. partners) may be better to contact. And for larger organizations you may want to target business improvement and digital transformation leads/directors- these are the people directly in charge of projects like what you may be proposing. Okay- so you have your message, and your list, and now all it comes down to is getting the good word out. I won't be going into the details of how to send these out, a quick Google search will give you hundreds of resources for cold outreach methods. However, personalization is key and beyond simple dynamic variables you want to make sure you can either personalize your email campaigns directly with AI (SmartWriter.ai is an example of a tool that can do this), or at the very least have the ability to import email messages programmatically. Alternatively, ask ChatGPT to make you a Python Script that can take in a list of emails, scrape info based on their linkedin URL or website, and all pass this onto a GPT prompt that specifies your messaging to generate an email. From there, send away. How tf do I close? Once you've got some prospects booked in on your meetings, you will need to close deals with them to turn them into clients. Call #1: Consultation Tying back to when I mentioned you want to take a consultant-first appraoch, you will want to listen closely to their goals and needs and understand their pain points. This would be the first call, and typically I would provide a high level overview of different solutions we could build to tacke these. It really helps to have a presentation available, so you can graphically demonstrate key points and key technologies. I like to use Plus AI for this, it's basically a Google Slides add-on that can generate slide decks for you. I copy and paste my default company messaging, add some key points for the presentation, and it comes out with pretty decent slides. Call #2: Demo The second call would involve a demo of one of these solutions, and typically I'll quickly prototype it with boilerplate code I already have, otherwise I'll cook something up in a no-code tool. If you have a niche where one type of solution is commonly demanded, it helps to have a general demo set up to be able to handle a larger volume of calls, so you aren't burning yourself out. I'll also elaborate on how the final product would look like in comparison to the demo. Call #3 and Beyond: Once the initial consultation and demo is complete, you will want to alleviate any remaining concerns from your prospects and work with them to reach a final work proposal. It's crucial you lay out exactly what you will be building (in writing) and ensure the prospect understands this. Furthermore, be clear and transparent with timelines and communication methods for the project. In terms of pricing, you want to take this from a value-based approach. The same solution may be worth a lot more to client A than client B. Furthermore, you can create "add-ons" such as monthly maintenance/upgrade packages, training sessions for employeees, and so forth, separate from the initial setup fee you would charge. How you can incorporate AI into marketing your businesses Beyond cold sales, I highly recommend creating a funnel to capture warm leads. For instance, I do this currently with my AI tools directory, which links directly to my AI agency and has consistent branding throughout. Warm leads are much more likely to close (and honestly, much nicer to deal with). However, even without an AI-related website, at the very least you will want to create a presence on social media and the web in general. As with any agency, you will want basic a professional presence. A professional virtual address helps, in addition to a Google Business Profile (GBP) and TrustPilot. a GBP (especially for local SEO) and Trustpilot page also helps improve the looks of your search results immensely. For GBP, I recommend using ProfilePro, which is a chrome extension you can use to automate SEO work for your GBP. Aside from SEO optimzied business descriptions based on your business, it can handle Q/A answers, responses, updates, and service descriptions based on local keywords. Privacy and Legal Concerns of the AAA Model Aside from typical concerns for agencies relating to service contracts, there are a few issues (especially when using no-code tools) that will need to be addressed to run a successful AAA. Most of these surround privacy concerns when working with proprietary data. In your terms with your client, you will want to clearly define hosting providers and any third party tools you will be using to build their solution, and a DPA with these third parties listed as subprocessors if necessary. In addition, you will want to implement best practices like redacting private information from data being used for building solutions. In terms of addressing concerns directly from clients, it helps if you host your solutions on their own servers (not possible with AI tools), and address the fact only ChatGPT queries in the web app, not OpenAI API calls, will be used to train OpenAI's models (as reported by mainstream media). The key here is to be open and transparent with your clients about ALL the tools you are using, where there data will be going, and make sure to get this all in writing. have fun, and keep an open mind Before I finish this post, I just want to reiterate the fact that this is NOT an easy way to make money. Running an AI agency will require hours and hours of dedication and work, and constantly rearranging your schedule to meet prospect and client needs. However, if you are looking for a new business to run, and have a knack for understanding business operations and are genuinely interested in the pracitcal applications of generative AI, then I say go for it. The time is ticking before AAA becomes the new dropshipping or SMMA, and I've a firm believer that those who set foot first and establish themselves in this field will come out top. And remember, while 100 thousand people may read this post, only 2 may actually take initiative and start.

What Are the Top Small Business Trends You Must Know for 2024 ?
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brycetychsenThis week

What Are the Top Small Business Trends You Must Know for 2024 ?

Are you excited about the new business horizons in 2024? Well, you should be! The small business landscape is evolving faster than anything right now, and here are the trends you absolutely need to know to keep your business game strong. Sustainable Swag In a world where eco-friendliness is the new black, businesses are carrying the badge of sustainability. From eco-packaging to carbon-neutral practices, customers are giving the side-eye to anything less green. So, if you want to be at the top, consider adopting some planet-friendly practices. Remote Work Revolution Office who? The 9-to-5 grind is getting a makeover, and the dress code is PJs. Remote work is no longer just a trend; it's a lifestyle. So, if your business can embrace the virtual office, you might just find your team doing the hustle and bustle with productivity. Tech-Tastic Ventures The future is now, and it's filled with tech wonders. Augmented reality (AR), artificial intelligence (AI), and all things tech are the new developments in this sector. Businesses incorporating these innovations are riding the digital wave straight to success. Personalization Party No one likes generic. Customers want products and services tailor-made just for them. So, businesses are using data to give customers an experience that feels as customized as a handmade suit. Say goodbye to one-size-fits-all! Community Crusaders In a world full of noise, community is the superhero we all need. Businesses are realizing the power of building a network around their brand. Whether it's through social media, events, or exclusive memberships, creating a community is like having an army of brand advocates. 2024 is the year to unleash your small business swagger. Embrace these trends, adapt with flair, and let your entrepreneurial spirit soar. Remember to sprinkle some personality into your business strategy—people love a brand with a sense of humor and a human touch!

Please rate my business idea aimed at emerging markets
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Whole_Ad_9002This week

Please rate my business idea aimed at emerging markets

Imagine a single platform that transforms your business operations effortlessly. Think of it like a Swiss Army knife for your business. First Steps (Every Business Needs These): Our website builder is your first step online. Just pick what you want, drag it where you need it, and you've got a professional website or online store. No tech skills needed. Perfect for getting your business visible to customers. Our security tool comes next because every business needs protection. It's like a security guard for your files and data, keeping hackers out and making sure you never lose important work. Think of it as insurance for your digital business. Cybersecurity and backups combined. Growing Business Needs: As your team grows, our digital office keeps everyone connected. Email, chat, share files, and track projects in one place. It's like having everyone in the same room, even when working remotely. This becomes essential once you have more than a few people. When paperwork starts piling up, our AI helper steps in. It's like having a smart assistant who learns your business and helps everyone get more done - handling routine tasks, summarizing meetings, and suggesting better ways to work. Scaling Up (For Established Businesses): Once you're handling lots of data, our eco-friendly cloud storage becomes crucial. Your business gets fast, reliable storage while helping the environment. We use servers powered by renewable energy, so you can grow sustainably. Our data transfer tool becomes important when you're working with multiple systems and need to move files around. It's like having a digital moving service that safely carries your files between different cloud services. With 20+ services to connect to cloud to cloud or on prem to cloud, its easy and fast. Advanced Needs: When your business processes get complex, our workflow automation tool helps you set up automatic systems for repetitive tasks. It's like training a robot to handle your routine work while your team focuses on growth. Simple no-code automation when you need it. Everything works on its own, but they're designed to work even better together. And since it's all in one place, you only need one password and one monthly bill. Most businesses save about half their tech costs by switching to our platform. Cost Benefits: Single subscription replaces multiple vendor contracts Reduces IT overhead by 40-60% on average No need for expensive technical specialists Predictable monthly costs Scales pricing with your usage

AI SaaS: A website to fine-tune LLM model according to your requirements
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Dangerous_Ferret3362This week

AI SaaS: A website to fine-tune LLM model according to your requirements

Hey fellow entrepreneurs and AI enthusiasts! I'm exploring a business idea and would love your thoughts and feedback. The concept is a SaaS platform that allows users to easily fine-tune large language models (LLMs) on their own datasets without needing deep technical expertise. Here's the gist: The Problem: Many businesses and researchers want to leverage LLMs for specific use cases, but fine-tuning these models requires significant technical knowledge and resources. The Solution: A user-friendly web platform where users can: Choose from popular LLM architectures Upload their own dataset or input text Configure fine-tuning parameters through an intuitive interface Automatically fine-tune the model on our GPU infrastructure Download the fine-tuned model or use it via API Key Features: No coding required Scalable cloud infrastructure Support for various fine-tuning techniques (prompt tuning, adapter tuning, full fine-tuning) Job monitoring and results visualization API access for integrated use in applications Target Market: Researchers without extensive ML engineering resources Startups building AI-powered products Enterprises looking to customize LLMs for internal use Monetization: Tiered subscription model based on usage (compute time, model size, etc.) + potential enterprise contracts for high-volume users. I'd really appreciate your thoughts on: Is this solving a real pain point? Would you use a service like this? Why or why not? What features would make this a must-have for you? Any foreseeable obstacles or considerations I'm missing? Suggestions for go-to-market strategy? Thank you!

Seeking Feedback: Would a No-Code AI Solution Benefit Your Business?
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chrisparkerofficialThis week

Seeking Feedback: Would a No-Code AI Solution Benefit Your Business?

I'm currently working on an AI startup, with the goal of providing small-medium businesses a seamless and intuitive way to integrate AI into operations without the need for any coding or tech expertise. We're designing an auto machine learning application that's user-friendly and tailored to the unique needs of small businesses. Before we scale, I would really appreciate any insights and feedback. Here are a few questions that would be helpful to get answers to: Pain Points: Are there specific tasks or processes in your operations that you think could be automated or enhanced using AI? This could be anything from customer service chatbots, inventory management, sales forecasting, or anything else you might think of. Features: What features would you want in a no-code AI solution? Perhaps easy integration with existing software? Drag-and-drop model training? Pre-built models for common tasks? Training & Support: How important would training and support be for you in implementing and using an AI solution? Would you prefer video tutorials, live-chat support, or hands-on workshops? Pricing: Would you be willing to invest in such a tool? If so, what would be a reasonable price point for you? We're considering a tiered model based on usage, with a potential starting point of $X/month. Does that sound feasible? Trial Period: Would a free trial period be beneficial for you? How long would you need to assess the tool's impact on your business? Data Concerns: How comfortable are you with sharing data with an AI application? What privacy and security measures would make you feel at ease? Your feedback is really useful. We're building this solution with you in mind, and your insights will guide the next steps. In appreciation for your time and input, we're offering a special discount for early adopters from this community once we launch. Just drop a comment below, and I'll make sure to get in touch when we are ready. Many Thanks, Chris Parker

Dev with AI and No-code Experience - Social Startup
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CraftBrewskiThis week

Dev with AI and No-code Experience - Social Startup

Hi fellow startup folks! I am actively seeking an AI-learned, no-code web/app co-founder to support a social startup. Target market is very active on a few different platforms, where they glean a bit of knowledge and support. The problem (opportunity) that I have identified for this group is to build a single platform that will provide them with 100% of the support and experience that they currently crave from multiple, unrelated platforms. My research has shown that this group will easily understand our product offering and should / may be easy to convert. Initial goal is to build and release an MVP and start sharing it with the target market. The MVP will be bulit via a no-code application. Our product will pull APIs from a few trusted data-centric and market-related sources and roll those into a social format that will be fun and interactive. Lots of other cool things, too, but to be discussed later. It will be somewhat similar to the CodeMap . io concept, but with a social/interactive focus. CodeMap is built on Bubble (no-code). A little about me: I live in Denver, Colorado. Married with three dogs. 20+ year Operations and Program Management experience in aerospace (satellites) and renewables (hydropower). I have started a few businesses over the years - some profitable, some not - ranging from e-commerce, affiliate marketing, SaaS, etc. I solely built each of the businesses, but have leaned that I’m better at the Operations and execution side of business, rather than being in the weeds with programming (mainly because I’m not a programmer!). I’m looking forward to (hopefully) interacting with some of you on this project! Cheers!

Business Strategy Trends for 2024
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aidenleepingweiiThis week

Business Strategy Trends for 2024

As we gear up for 2024, it's time to gaze into the crystal ball and see what's reshaping the world of business strategy. From cutting-edge technology to how people are shopping, it's all happening. So let's check out the latest trends that are going to dominate the business world! Going Green and Doing Good Yep, you heard it right—being eco-friendly and socially responsible is all the rage. Businesses are jumping on the sustainability train, whether it's by using recycled materials or giving back to the community. It's not just good for the planet—it's good for business too! Tech Takeover From fancy AI to blockchain innovations, businesses are embracing all things digital. It's not just about staying up to date—it's about using technology to make things easier, faster, and way more amazing. Work from Anywhere Who says you have to be stuck in an office all day? Today, businesses are all about flexibility. Whether you're working from home, a coffee shop, or a hammock on the beach, it's all good. Remote work is here to stay, and people are loving the freedom it brings. Treat Yo' Customers Want to stand out in a sea of competition? It's all about making your customers feel special. Whether it's personalized recommendations or killer customer service, businesses are pulling out all the stops to keep folks coming back for more. Roll with the Punches In today's fast-paced world, you've got to be quick on your feet. That's why businesses are ditching rigid plans and embracing agile strategies. It's all about being able to adapt to whatever curveballs the world throws your way. Click, Buy, and Repeat Online shopping is getting bigger. Businesses are getting creative with their online offerings, whether it's through slick new websites, social media shenanigans, or funky new delivery options. The future of shopping is digital! Conclusion: The lowdown on what's shaking up the world of business strategy in 2024. Whether it's going green, embracing tech, or keeping customers happy, there's plenty of excitement on the horizon.

AI SaaS: A website to fine-tune LLM model according to your requirements
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Dangerous_Ferret3362This week

AI SaaS: A website to fine-tune LLM model according to your requirements

Hey fellow entrepreneurs and AI enthusiasts! I'm exploring a business idea and would love your thoughts and feedback. The concept is a SaaS platform that allows users to easily fine-tune large language models (LLMs) on their own datasets without needing deep technical expertise. Here's the gist: The Problem: Many businesses and researchers want to leverage LLMs for specific use cases, but fine-tuning these models requires significant technical knowledge and resources. The Solution: A user-friendly web platform where users can: Choose from popular LLM architectures Upload their own dataset or input text Configure fine-tuning parameters through an intuitive interface Automatically fine-tune the model on our GPU infrastructure Download the fine-tuned model or use it via API Key Features: No coding required Scalable cloud infrastructure Support for various fine-tuning techniques (prompt tuning, adapter tuning, full fine-tuning) Job monitoring and results visualization API access for integrated use in applications Target Market: Researchers without extensive ML engineering resources Startups building AI-powered products Enterprises looking to customize LLMs for internal use Monetization: Tiered subscription model based on usage (compute time, model size, etc.) + potential enterprise contracts for high-volume users. I'd really appreciate your thoughts on: Is this solving a real pain point? Would you use a service like this? Why or why not? What features would make this a must-have for you? Any foreseeable obstacles or considerations I'm missing? Suggestions for go-to-market strategy? Thank you!

What Are the Top Small Business Trends You Must Know for 2024 ?
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brycetychsenThis week

What Are the Top Small Business Trends You Must Know for 2024 ?

Are you excited about the new business horizons in 2024? Well, you should be! The small business landscape is evolving faster than anything right now, and here are the trends you absolutely need to know to keep your business game strong. Sustainable Swag In a world where eco-friendliness is the new black, businesses are carrying the badge of sustainability. From eco-packaging to carbon-neutral practices, customers are giving the side-eye to anything less green. So, if you want to be at the top, consider adopting some planet-friendly practices. Remote Work Revolution Office who? The 9-to-5 grind is getting a makeover, and the dress code is PJs. Remote work is no longer just a trend; it's a lifestyle. So, if your business can embrace the virtual office, you might just find your team doing the hustle and bustle with productivity. Tech-Tastic Ventures The future is now, and it's filled with tech wonders. Augmented reality (AR), artificial intelligence (AI), and all things tech are the new developments in this sector. Businesses incorporating these innovations are riding the digital wave straight to success. Personalization Party No one likes generic. Customers want products and services tailor-made just for them. So, businesses are using data to give customers an experience that feels as customized as a handmade suit. Say goodbye to one-size-fits-all! Community Crusaders In a world full of noise, community is the superhero we all need. Businesses are realizing the power of building a network around their brand. Whether it's through social media, events, or exclusive memberships, creating a community is like having an army of brand advocates. 2024 is the year to unleash your small business swagger. Embrace these trends, adapt with flair, and let your entrepreneurial spirit soar. Remember to sprinkle some personality into your business strategy—people love a brand with a sense of humor and a human touch!

Digital Analytics and Marketing
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Chou789This week

Digital Analytics and Marketing

I'm a Data Analyst with wide range of experience in this niche. Looking for partner to bring me clients and get a cut on the charges, i.e act as a agency connecting businesses with developers. Lately, I see that Developer costs in US/EU is skyrocketing and hiring a decent Data Analyst costs a fortune for companies, small companies can't even think of getting one. Already working with several small businesses and see that many small businesses have need somebody to play around their data but since it's a costly affair, mostly small businesses stick with Excel and Google Sheets as their database and don't leverage the potential of automation, now with AI/LLM, having proper data strategy is important. We can team up and provide reach these low hanging fruits. What i do: Data Reporting: Move clients current data systems from Excel, Google Sheets into Database/Datawarehouse Integrate data from different sources like Pipedrive, Google Ads, Facebook Ads, Shopify etc and create automated custom reports on the data. Digital Marketing: For Shopify/Ecommernce site owners - Google Analytics Reporting Answer questions like Where is my traffic coming from, which traffic is working, how long they are staying in site, which products are working, product views to purchase ratio etc Custom Desktop Applications Custom: Have a custom idea? Let's discuss. DM me. Thanks. PS: Potential customers include ones who can't hire $50-$150/hr full time developers but want one at part time/freelancing type where they can get things done quickly/validating their ideas without burning their business.

TASVerify
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doubleHelixSpiralThis week

TASVerify

The Opportunity: $10,000 to Launch the Future of Information Verification TrueAlphaSpiral (TAS) is seeking $10,000 in seed funding to develop a working prototype of our revolutionary verification system that will transform how businesses validate the accuracy and trustworthiness of information. The Problem In today's digital landscape: 76% of businesses report significant costs from inaccurate information AI systems frequently produce plausible but factually incorrect content ("hallucinations") Traditional verification tools use outdated binary (true/false) assessments that miss critical nuance Our Solution TrueAlphaSpiral is a next-generation verification system that: Analyzes content across multiple dimensions (factual, ethical, logical, experiential) Self-improves through innovative cybernetic feedback loops Provides specialized verification for high-value industries (healthcare, finance, media) Why $10,000 Now? Your seed investment will directly fund: Prototype Development ($6,000): Build a working demonstration of our core verification technology Technical Documentation ($2,000): Create essential materials for future development partners Initial Testing ($2,000): Validate our approach with pilot users in medical information verification 90-Day Roadmap With your funding, we will deliver: | Month | Milestone | Deliverable | |-------|-----------|-------------| | 1 | Core Algorithm Implementation | Functioning verification algorithm | | 2 | Basic API & Documentation | Developer documentation & test API | | 3 | Medical Verification Prototype | Demonstration with medical test cases | Market & Growth Potential Immediate Market: Medical content verification ($2.8B annual market) Expansion Markets: Financial services, media, and AI governance Total Addressable Market: $47.5B by 2028 Return on Investment Your $10,000 seed investment will: Secure 1.5% equity in TrueAlphaSpiral Position you for priority participation in our $500K pre-seed round (Q4 2025) Provide preferential terms in our $3M seed round (Q2 2026) Why Us, Why Now? Founding Team: Expertise in AI verification, cybernetics, and domain-specific knowledge Timing: Critical market need as AI content proliferates across industries Proven Concept: Preliminary results show 37% better accuracy than existing solutions Next Steps Initial $10,000 funding transfer to begin development Weekly progress updates and milestone reviews Demo day in 90 days to showcase working prototype

AI SaaS: A website to fine-tune LLM model according to your requirements
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Dangerous_Ferret3362This week

AI SaaS: A website to fine-tune LLM model according to your requirements

Hey fellow entrepreneurs and AI enthusiasts! I'm exploring a business idea and would love your thoughts and feedback. The concept is a SaaS platform that allows users to easily fine-tune large language models (LLMs) on their own datasets without needing deep technical expertise. Here's the gist: The Problem: Many businesses and researchers want to leverage LLMs for specific use cases, but fine-tuning these models requires significant technical knowledge and resources. The Solution: A user-friendly web platform where users can: Choose from popular LLM architectures Upload their own dataset or input text Configure fine-tuning parameters through an intuitive interface Automatically fine-tune the model on our GPU infrastructure Download the fine-tuned model or use it via API Key Features: No coding required Scalable cloud infrastructure Support for various fine-tuning techniques (prompt tuning, adapter tuning, full fine-tuning) Job monitoring and results visualization API access for integrated use in applications Target Market: Researchers without extensive ML engineering resources Startups building AI-powered products Enterprises looking to customize LLMs for internal use Monetization: Tiered subscription model based on usage (compute time, model size, etc.) + potential enterprise contracts for high-volume users. I'd really appreciate your thoughts on: Is this solving a real pain point? Would you use a service like this? Why or why not? What features would make this a must-have for you? Any foreseeable obstacles or considerations I'm missing? Suggestions for go-to-market strategy? Thank you!

🛒7 Strategies to Increase Retail Store Footfall post-COVID | Ultimate Blueprint & Guide 📈
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bnk3r_This week

🛒7 Strategies to Increase Retail Store Footfall post-COVID | Ultimate Blueprint & Guide 📈

Hello fellow marketers/entrepreneurs! Covid has had a gobsmacking effect on all retail promotions and marketing efforts. For people with retail businesses that thrive on footfall, it has been an uphill battle, but markets of the world are slowly resuming action. Knowing the footfall to your retail store can help you decide how many products you need to stock, which days of the week are best for promotions, and what type of promotional offers work well. The pandemic has drastically impacted customer behavior and customer loyalty is plunging. People prefer shopping online to brick-and-mortar purchases, and consumers are limiting their spending on a range of items - investing only in essentials is the norm now (McKinsey). We found some companies like Target having programs like Cartwheel that offer 5% to 50% off specific items when customers shop in-store to increase foot traffic. Strategies like these ultimately add up, an ICSC report cites that 69% of customers who went to collect their orders eventually bought additional items. I've put together a detailed list of 7 strategies to boost footfall to stores post COVID, I hope they come in handy! Abide by COVID-19 Protocols for a Safer Environment Be well-informed of the COVID-19 protocols. Don't implement this merely under the government norms, instead take extra measures to show customers that you care! Have an automated entrance Deploy hygiene counters Fix thermal sensors in the entrance Have an isolation space for those showing symptoms of the coronavirus To see more check this link for the entire list! Run Catchy In-Store Promotions Discounts are a perfect way to attract new customers and retain existing ones. When you want to increase customer traffic in a brick-and-mortar store, give customers an offer that only works inside the store. Surprise your consumers with free samples of your products. This would allow them to try some new brands and products. If you’d want to reduce your excess stock post the quarantine time, try running a multi-buy campaign. Digital Signages - Enhance In-store Shopping Experience Digital signage is a type of advertising that uses a video screen to display marketing messages. They can be used for attracting customers, conveying information, and promoting merchandise. Retail outlets in malls that have fashion sections can display the latest trends on their screens so customers know what’s new. This helps them pick out something they might like quickly. Some restaurants showcase menus on screens while others even project live cooking shows! These displays help with menu navigation too; helping a diner decide between chicken tikka masala or steak tartare by showing pictures of both dishes at once. Leverage Beacon Notification to Attract Customers to Your Store The beacon technology is a way to implement a tracking system indoors. A beacon is an inaudible signal that can be tracked and act as the trigger for other events like sending notifications about deals, discounts, or new products. Beacon technology helps with driving footfalls by giving customers an indoor mapping experience of your store's inventory. This ensures they always know where they are going and what’s around them. The navigation reminds them of their proximity to items on display so there’s never any confusion over whether something is nearby or farther off. Train your Salespeople to Become the Shopper's Friend Educating your salespersons on how to be consumers’ friends is important. They should be knowledgeable about what products are popular and in-demand so that they can help the customers find exactly what they want while at the same time giving guidance on how to save money by telling them where discounts and deals can be found. Reconceptualize Checkout Counters Customers abandon their purchases because of long lines at the checkout. With the pandemic out there, this could be one of the reasons why the retail foot traffic is diminishing. Include contactless payments that can be automated or replace your existing POS setup. Encourage BOPIS (Buy Online Pick-up In-store) To implement BOPIS for your retail store, you need to have a centralized platform that allows you to manage orders, sales, and customers. This helps you to deliver a personalized customer experience. In combination with BOPIS, another way to promote footfall into the store and drive sales in retail is by bringing your website in-store. And this will be a good move if you have multiple stores and not all the stock in one place. This is because, when you know how to calculate footfall in retail it can help you with many retail metrics like: How to plan your store for peak footfall times? How much stock you need in the store and how often you'll need to restock it? What products are selling well on an hourly basis? This is so crucial information for retailers that will help inform decisions about where to place certain items or which ones may be more popular than others etc. When stores should have promotions (if they want), discounts, and raise weekend sales? We've put together an elaborate, research-based White Paper that covers these segments: How have pandemics catalyzed technological innovations Customer sentiment and behavior during COVID-19 An omnichannel customer engagement strategy to drive sales in retail and footfall The ultimate roadmap to increase retail footfalls How to build the perfect loyalty program to turn foot traffic into brand ambassadors? You can find the same over here, hope my team's effort comes in handy to some of y'all that could improve your store visits, cheers!

Digital Analytics and Marketing
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Chou789This week

Digital Analytics and Marketing

I'm a Data Analyst with wide range of experience in this niche. Looking for partner to bring me clients and get a cut on the charges, i.e act as a agency connecting businesses with developers. Lately, I see that Developer costs in US/EU is skyrocketing and hiring a decent Data Analyst costs a fortune for companies, small companies can't even think of getting one. Already working with several small businesses and see that many small businesses have need somebody to play around their data but since it's a costly affair, mostly small businesses stick with Excel and Google Sheets as their database and don't leverage the potential of automation, now with AI/LLM, having proper data strategy is important. We can team up and provide reach these low hanging fruits. What i do: Data Reporting: Move clients current data systems from Excel, Google Sheets into Database/Datawarehouse Integrate data from different sources like Pipedrive, Google Ads, Facebook Ads, Shopify etc and create automated custom reports on the data. Digital Marketing: For Shopify/Ecommernce site owners - Google Analytics Reporting Answer questions like Where is my traffic coming from, which traffic is working, how long they are staying in site, which products are working, product views to purchase ratio etc Custom Desktop Applications Custom: Have a custom idea? Let's discuss. DM me. Thanks. PS: Potential customers include ones who can't hire $50-$150/hr full time developers but want one at part time/freelancing type where they can get things done quickly/validating their ideas without burning their business.

Critique my business ideas
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FocusOutrageous9685This week

Critique my business ideas

So I have some business ideas that I would like to confront to you in order to have feedback. The point is to give me your completely honest opinion and try to find some potential problems. 1 - Digital marketing automation for green ecommerce stores Marketing has always been a problem for everyone in business more particularly for niche businesses. It's tough for them because people who will buy their product are generally harder to find. Also these products are way more expensive than other so it may be clever for them to focus more on marketing. Since the green and sustainable industry is growing at a very fast rate such as AI, I would like to hear your opinion on the idea of automating marketing for these type of businesses. 2 - AI Mental Health platform The mental health issues will gain more and more importance in the future. We now live in a world that isn't as safe as before and with the rise of social media we can predict that mental health issues will be more frequent especially for young people. PH, Instagram, Tiktok all of these are just bad for everyone and so an AI mental health plateform where people can chat with AI, discuss in anonymous forums and use integrated tools to reduce screen time and manage addiction I think would be a good idea. I haven't really thought about how to make money but as I write I was thinking about either a freemium model or integrate products from stores and kind of get affiliation, getting money when people buy the product. 3 - A car enthusiast website Everyday around 5000 millionaires are created so obviously the high end car industry is growing at a fairly fast rate. My idea would be to create a network where people would pay to ride in a supercar. There would be a map where people would look for cars in their area and chat with the owner basically. 4 - Marketing agency for real estate agents This is self explanatory. Common pain points include managing client communication, nurturing leads, following up on inquiries, and staying top-of-mind with potential buyers and sellers. Effective email automation can help with sending personalized follow-ups, reminders, newsletters, and market updates. It would be a subscription based business basically.

WE JUST GOT $2,500 in angel investment for our AI Cold Calling Startup! Hooray! Looking for web dev + digital marketing agencies to partner with.
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GrowthGetThis week

WE JUST GOT $2,500 in angel investment for our AI Cold Calling Startup! Hooray! Looking for web dev + digital marketing agencies to partner with.

Hey y'all. The AI cold calling startup I've been working on for 3-4 months now just got a $2,500 angel investment, and we have 2 current customers, a credit card processing broker and a hospital equipment rental company based out of Texas. We have around $1,500 revenue so far, but we're having lots of trouble fulfilling the contracts because our tech just isn't "there" yet. I'm the Chief Tech Officer, and I'm also running some operations. The other main person in this is the CEO who has a strong sales background and came up with the idea. I've been working purely remotely, and it's great having some income because I'm stuck at home because I'm disabled, basically... We're using 11labs, openai, google speech to text, and a sh\*tty online dialer right now to run the first MVP which runs locally on our "botrunners" computers, and we're developing a web app with django python + javascript react. Our plan is, after we get the webapp working better, to hire more botrunners for $3 per hour from countries like Phillipines and India, and we're going to try to track all the actions the botrunners take to be able to train the AI to run it fully automated. The biggest problem we're facing right now with the tech is reducing latency, it started at 27 seconds to get a response and I've been able to get it down to 6 seconds, but people are still hanging up. We're trying several ways to mitigate this, including having pre-rendered speech playing something like "Okay" or "As an artificial representative, I'm still learning to be quicker on the pickup. We appreciate your patience." One of the industries we want to target is international web development and digital marketing companies, and we want to use the bot to cold-call businesses to pitch them our services. The goal is to replace $30 an hour cold-callers from the USA with $3 per hour total-cost automation. Apparently the CEO was given a $5 million valuation from the strength of the MVP from a VC. Our investment so far was at a $300k valuation tho. It's exciting. Trying to get Twilio working to be able to make calls programmatically instead of using our hacky workaround. Let me know if you have any questions, or feedback. Looking for digital marketing and web dev agencies to partner with to test the next stage of our business model. Thanks. I just wanted to share this awesome news!

Please rate my business idea aimed at emerging markets
reddit
LLM Vibe Score0
Human Vibe Score1
Whole_Ad_9002This week

Please rate my business idea aimed at emerging markets

Imagine a single platform that transforms your business operations effortlessly. Think of it like a Swiss Army knife for your business. First Steps (Every Business Needs These): Our website builder is your first step online. Just pick what you want, drag it where you need it, and you've got a professional website or online store. No tech skills needed. Perfect for getting your business visible to customers. Our security tool comes next because every business needs protection. It's like a security guard for your files and data, keeping hackers out and making sure you never lose important work. Think of it as insurance for your digital business. Cybersecurity and backups combined. Growing Business Needs: As your team grows, our digital office keeps everyone connected. Email, chat, share files, and track projects in one place. It's like having everyone in the same room, even when working remotely. This becomes essential once you have more than a few people. When paperwork starts piling up, our AI helper steps in. It's like having a smart assistant who learns your business and helps everyone get more done - handling routine tasks, summarizing meetings, and suggesting better ways to work. Scaling Up (For Established Businesses): Once you're handling lots of data, our eco-friendly cloud storage becomes crucial. Your business gets fast, reliable storage while helping the environment. We use servers powered by renewable energy, so you can grow sustainably. Our data transfer tool becomes important when you're working with multiple systems and need to move files around. It's like having a digital moving service that safely carries your files between different cloud services. With 20+ services to connect to cloud to cloud or on prem to cloud, its easy and fast. Advanced Needs: When your business processes get complex, our workflow automation tool helps you set up automatic systems for repetitive tasks. It's like training a robot to handle your routine work while your team focuses on growth. Simple no-code automation when you need it. Everything works on its own, but they're designed to work even better together. And since it's all in one place, you only need one password and one monthly bill. Most businesses save about half their tech costs by switching to our platform. Cost Benefits: Single subscription replaces multiple vendor contracts Reduces IT overhead by 40-60% on average No need for expensive technical specialists Predictable monthly costs Scales pricing with your usage

AI-Powered Tool to Detect and Mask PII in Documents
reddit
LLM Vibe Score0
Human Vibe Score1
hoa_nguyen95This week

AI-Powered Tool to Detect and Mask PII in Documents

Hi, everyone! 👋 I’ve been working on an idea for an application that could be a game-changer for data privacy and compliance: The Concept Imagine an app where users can upload a PDF or DOC/DOCX file, and with the power of AI, it scans the document for Personally Identifiable Information (PII). Once identified, the app automatically masks (censors) all the PII and generates a new, sanitized version of the document. Why This Matters In today’s data-driven world, sharing documents is routine, but protecting sensitive information is critical. Businesses, freelancers, and even everyday users often need to redact PII for privacy reasons or compliance with regulations like GDPR, HIPAA, or CCPA. Current Challenges: Manual redaction is time-consuming and error-prone. The Solution: This app ensures quick, accurate, and automated PII redaction, saving time while enhancing data security. Potential Features File Support: PDF, DOC/DOCX, and maybe more formats in the future. AI-Powered Detection: Identify PII such as names, addresses, phone numbers, SSNs, and email addresses. Customization: Users could define additional sensitive terms to be masked. Audit Logs: For compliance, generate a report of what was redacted. Integration: Plug into cloud storage services like Google Drive or Dropbox for seamless workflows. My Questions for the Community Use Cases: What industries or professionals do you think would benefit most from this? Features: Are there additional features or considerations I’m overlooking? Competition: Do you know of similar tools already on the market, and how could this app differentiate itself? Challenges: What technical or market challenges should I anticipate when building and launching this product? I’d love to hear your thoughts, feedback, or ideas for collaboration. If you’re interested in discussing this further, let me know! Thanks in advance for your time and input.

WE JUST GOT $2,500 in angel investment for our AI Cold Calling Startup! Hooray! Looking for web dev + digital marketing agencies to partner with.
reddit
LLM Vibe Score0
Human Vibe Score1
GrowthGetThis week

WE JUST GOT $2,500 in angel investment for our AI Cold Calling Startup! Hooray! Looking for web dev + digital marketing agencies to partner with.

Hey y'all. The AI cold calling startup I've been working on for 3-4 months now just got a $2,500 angel investment, and we have 2 current customers, a credit card processing broker and a hospital equipment rental company based out of Texas. We have around $1,500 revenue so far, but we're having lots of trouble fulfilling the contracts because our tech just isn't "there" yet. I'm the Chief Tech Officer, and I'm also running some operations. The other main person in this is the CEO who has a strong sales background and came up with the idea. I've been working purely remotely, and it's great having some income because I'm stuck at home because I'm disabled, basically... We're using 11labs, openai, google speech to text, and a sh\*tty online dialer right now to run the first MVP which runs locally on our "botrunners" computers, and we're developing a web app with django python + javascript react. Our plan is, after we get the webapp working better, to hire more botrunners for $3 per hour from countries like Phillipines and India, and we're going to try to track all the actions the botrunners take to be able to train the AI to run it fully automated. The biggest problem we're facing right now with the tech is reducing latency, it started at 27 seconds to get a response and I've been able to get it down to 6 seconds, but people are still hanging up. We're trying several ways to mitigate this, including having pre-rendered speech playing something like "Okay" or "As an artificial representative, I'm still learning to be quicker on the pickup. We appreciate your patience." One of the industries we want to target is international web development and digital marketing companies, and we want to use the bot to cold-call businesses to pitch them our services. The goal is to replace $30 an hour cold-callers from the USA with $3 per hour total-cost automation. Apparently the CEO was given a $5 million valuation from the strength of the MVP from a VC. Our investment so far was at a $300k valuation tho. It's exciting. Trying to get Twilio working to be able to make calls programmatically instead of using our hacky workaround. Let me know if you have any questions, or feedback. Looking for digital marketing and web dev agencies to partner with to test the next stage of our business model. Thanks. I just wanted to share this awesome news!

Digital Analytics and Marketing
reddit
LLM Vibe Score0
Human Vibe Score1
Chou789This week

Digital Analytics and Marketing

I'm a Data Analyst with wide range of experience in this niche. Looking for partner to bring me clients and get a cut on the charges, i.e act as a agency connecting businesses with developers. Lately, I see that Developer costs in US/EU is skyrocketing and hiring a decent Data Analyst costs a fortune for companies, small companies can't even think of getting one. Already working with several small businesses and see that many small businesses have need somebody to play around their data but since it's a costly affair, mostly small businesses stick with Excel and Google Sheets as their database and don't leverage the potential of automation, now with AI/LLM, having proper data strategy is important. We can team up and provide reach these low hanging fruits. What i do: Data Reporting: Move clients current data systems from Excel, Google Sheets into Database/Datawarehouse Integrate data from different sources like Pipedrive, Google Ads, Facebook Ads, Shopify etc and create automated custom reports on the data. Digital Marketing: For Shopify/Ecommernce site owners - Google Analytics Reporting Answer questions like Where is my traffic coming from, which traffic is working, how long they are staying in site, which products are working, product views to purchase ratio etc Custom Desktop Applications Custom: Have a custom idea? Let's discuss. DM me. Thanks. PS: Potential customers include ones who can't hire $50-$150/hr full time developers but want one at part time/freelancing type where they can get things done quickly/validating their ideas without burning their business.

Please rate my business idea aimed at emerging markets
reddit
LLM Vibe Score0
Human Vibe Score1
Whole_Ad_9002This week

Please rate my business idea aimed at emerging markets

Imagine a single platform that transforms your business operations effortlessly. Think of it like a Swiss Army knife for your business. First Steps (Every Business Needs These): Our website builder is your first step online. Just pick what you want, drag it where you need it, and you've got a professional website or online store. No tech skills needed. Perfect for getting your business visible to customers. Our security tool comes next because every business needs protection. It's like a security guard for your files and data, keeping hackers out and making sure you never lose important work. Think of it as insurance for your digital business. Cybersecurity and backups combined. Growing Business Needs: As your team grows, our digital office keeps everyone connected. Email, chat, share files, and track projects in one place. It's like having everyone in the same room, even when working remotely. This becomes essential once you have more than a few people. When paperwork starts piling up, our AI helper steps in. It's like having a smart assistant who learns your business and helps everyone get more done - handling routine tasks, summarizing meetings, and suggesting better ways to work. Scaling Up (For Established Businesses): Once you're handling lots of data, our eco-friendly cloud storage becomes crucial. Your business gets fast, reliable storage while helping the environment. We use servers powered by renewable energy, so you can grow sustainably. Our data transfer tool becomes important when you're working with multiple systems and need to move files around. It's like having a digital moving service that safely carries your files between different cloud services. With 20+ services to connect to cloud to cloud or on prem to cloud, its easy and fast. Advanced Needs: When your business processes get complex, our workflow automation tool helps you set up automatic systems for repetitive tasks. It's like training a robot to handle your routine work while your team focuses on growth. Simple no-code automation when you need it. Everything works on its own, but they're designed to work even better together. And since it's all in one place, you only need one password and one monthly bill. Most businesses save about half their tech costs by switching to our platform. Cost Benefits: Single subscription replaces multiple vendor contracts Reduces IT overhead by 40-60% on average No need for expensive technical specialists Predictable monthly costs Scales pricing with your usage

Ideas or niche for AI business?
reddit
LLM Vibe Score0
Human Vibe Score1
NearestNeighbrThis week

Ideas or niche for AI business?

Hey everyone! I'm a mathematician specialized in AI and I'm currently looking to start an innovative business or project. I was wondering if anyone here has experience with processes, machines, sensors, or any other systems that generate some amount of data that, in your opinion, isn't being fully utilized or could benefit from AI. I’m particularly interested in niche and specific cases that might not be widely known by the general public. I'm asking you because I believe that the diverse professional experiences within this community may reveal hidden opportunities. To give you some context: I have experience working on AI projects across different fields like healthcare, robotics, finance, and more. My specialization lies in forecasting. Mi current role is basically to make (or assist in making) strategic decisions based on the results of forecasting different events, metrics, indicators, ... I have no prior businesses, but I’m currently enrolled in a startup and business incubator program to help develop and refine my ideas. My plan is to apply to top incubators and accelerators if I can develop a decent business concept. I’m looking for an online business or project that requires relatively little capital to start, as I’m a "recent" graduate. I’m based in Spain, near the Mediterranean, though I'm not looking to center my business idea specifically around this. Any specific suggestions or insights based on your professional experiences would be incredibly valuable. If you have experience with underutilized data-generating processes, machines, or sensors, or know of a niche application where AI could be transformative, I’d love to hear your thoughts! Thanks so much!

Critique my business ideas
reddit
LLM Vibe Score0
Human Vibe Score0.5
FocusOutrageous9685This week

Critique my business ideas

So I have some business ideas that I would like to confront to you in order to have feedback. The point is to give me your completely honest opinion and try to find some potential problems. 1 - Digital marketing automation for green ecommerce stores Marketing has always been a problem for everyone in business more particularly for niche businesses. It's tough for them because people who will buy their product are generally harder to find. Also these products are way more expensive than other so it may be clever for them to focus more on marketing. Since the green and sustainable industry is growing at a very fast rate such as AI, I would like to hear your opinion on the idea of automating marketing for these type of businesses. 2 - AI Mental Health platform The mental health issues will gain more and more importance in the future. We now live in a world that isn't as safe as before and with the rise of social media we can predict that mental health issues will be more frequent especially for young people. PH, Instagram, Tiktok all of these are just bad for everyone and so an AI mental health plateform where people can chat with AI, discuss in anonymous forums and use integrated tools to reduce screen time and manage addiction I think would be a good idea. I haven't really thought about how to make money but as I write I was thinking about either a freemium model or integrate products from stores and kind of get affiliation, getting money when people buy the product. 3 - A car enthusiast website Everyday around 5000 millionaires are created so obviously the high end car industry is growing at a fairly fast rate. My idea would be to create a network where people would pay to ride in a supercar. There would be a map where people would look for cars in their area and chat with the owner basically. 4 - Marketing agency for real estate agents This is self explanatory. Common pain points include managing client communication, nurturing leads, following up on inquiries, and staying top-of-mind with potential buyers and sellers. Effective email automation can help with sending personalized follow-ups, reminders, newsletters, and market updates. It would be a subscription based business basically.

Please rate my business idea aimed at emerging markets
reddit
LLM Vibe Score0
Human Vibe Score1
Whole_Ad_9002This week

Please rate my business idea aimed at emerging markets

Imagine a single platform that transforms your business operations effortlessly. Think of it like a Swiss Army knife for your business. First Steps (Every Business Needs These): Our website builder is your first step online. Just pick what you want, drag it where you need it, and you've got a professional website or online store. No tech skills needed. Perfect for getting your business visible to customers. Our security tool comes next because every business needs protection. It's like a security guard for your files and data, keeping hackers out and making sure you never lose important work. Think of it as insurance for your digital business. Cybersecurity and backups combined. Growing Business Needs: As your team grows, our digital office keeps everyone connected. Email, chat, share files, and track projects in one place. It's like having everyone in the same room, even when working remotely. This becomes essential once you have more than a few people. When paperwork starts piling up, our AI helper steps in. It's like having a smart assistant who learns your business and helps everyone get more done - handling routine tasks, summarizing meetings, and suggesting better ways to work. Scaling Up (For Established Businesses): Once you're handling lots of data, our eco-friendly cloud storage becomes crucial. Your business gets fast, reliable storage while helping the environment. We use servers powered by renewable energy, so you can grow sustainably. Our data transfer tool becomes important when you're working with multiple systems and need to move files around. It's like having a digital moving service that safely carries your files between different cloud services. With 20+ services to connect to cloud to cloud or on prem to cloud, its easy and fast. Advanced Needs: When your business processes get complex, our workflow automation tool helps you set up automatic systems for repetitive tasks. It's like training a robot to handle your routine work while your team focuses on growth. Simple no-code automation when you need it. Everything works on its own, but they're designed to work even better together. And since it's all in one place, you only need one password and one monthly bill. Most businesses save about half their tech costs by switching to our platform. Cost Benefits: Single subscription replaces multiple vendor contracts Reduces IT overhead by 40-60% on average No need for expensive technical specialists Predictable monthly costs Scales pricing with your usage

AI-Powered Tool to Detect and Mask PII in Documents
reddit
LLM Vibe Score0
Human Vibe Score1
hoa_nguyen95This week

AI-Powered Tool to Detect and Mask PII in Documents

Hi, everyone! 👋 I’ve been working on an idea for an application that could be a game-changer for data privacy and compliance: The Concept Imagine an app where users can upload a PDF or DOC/DOCX file, and with the power of AI, it scans the document for Personally Identifiable Information (PII). Once identified, the app automatically masks (censors) all the PII and generates a new, sanitized version of the document. Why This Matters In today’s data-driven world, sharing documents is routine, but protecting sensitive information is critical. Businesses, freelancers, and even everyday users often need to redact PII for privacy reasons or compliance with regulations like GDPR, HIPAA, or CCPA. Current Challenges: Manual redaction is time-consuming and error-prone. The Solution: This app ensures quick, accurate, and automated PII redaction, saving time while enhancing data security. Potential Features File Support: PDF, DOC/DOCX, and maybe more formats in the future. AI-Powered Detection: Identify PII such as names, addresses, phone numbers, SSNs, and email addresses. Customization: Users could define additional sensitive terms to be masked. Audit Logs: For compliance, generate a report of what was redacted. Integration: Plug into cloud storage services like Google Drive or Dropbox for seamless workflows. My Questions for the Community Use Cases: What industries or professionals do you think would benefit most from this? Features: Are there additional features or considerations I’m overlooking? Competition: Do you know of similar tools already on the market, and how could this app differentiate itself? Challenges: What technical or market challenges should I anticipate when building and launching this product? I’d love to hear your thoughts, feedback, or ideas for collaboration. If you’re interested in discussing this further, let me know! Thanks in advance for your time and input.

GenAI_Agents
github
LLM Vibe Score0.563
Human Vibe Score0.24210481455988786
NirDiamantMar 28, 2025

GenAI_Agents

🌟 Support This Project: Your sponsorship fuels innovation in GenAI agent development. Become a sponsor to help maintain and expand this valuable resource! GenAI Agents: Comprehensive Repository for Development and Implementation 🚀 Welcome to one of the most extensive and dynamic collections of Generative AI (GenAI) agent tutorials and implementations available today. This repository serves as a comprehensive resource for learning, building, and sharing GenAI agents, ranging from simple conversational bots to complex, multi-agent systems. 📫 Stay Updated! 🚀Cutting-edgeUpdates 💡ExpertInsights 🎯Top 0.1%Content Join over 15,000 of AI enthusiasts getting unique cutting-edge insights and free tutorials! Plus, subscribers get exclusive early access and special 33% discounts to my book and the upcoming RAG Techniques course! Introduction Generative AI agents are at the forefront of artificial intelligence, revolutionizing the way we interact with and leverage AI technologies. This repository is designed to guide you through the development journey, from basic agent implementations to advanced, cutting-edge systems. 📚 Learn to Build Your First AI Agent Your First AI Agent: Simpler Than You Think This detailed blog post complements the repository by providing a complete A-Z walkthrough with in-depth explanations of core concepts, step-by-step implementation, and the theory behind AI agents. It's designed to be incredibly simple to follow while covering everything you need to know to build your first working agent from scratch. 💡 Plus: Subscribe to the newsletter for exclusive early access to tutorials and special discounts on upcoming courses and books! Our goal is to provide a valuable resource for everyone - from beginners taking their first steps in AI to seasoned practitioners pushing the boundaries of what's possible. By offering a range of examples from foundational to complex, we aim to facilitate learning, experimentation, and innovation in the rapidly evolving field of GenAI agents. Furthermore, this repository serves as a platform for showcasing innovative agent creations. Whether you've developed a novel agent architecture or found an innovative application for existing techniques, we encourage you to share your work with the community. Related Projects 📚 Dive into my comprehensive guide on RAG techniques to learn about integrating external knowledge into AI systems, enhancing their capabilities with up-to-date and relevant information retrieval. 🖋️ Explore my Prompt Engineering Techniques guide for an extensive collection of prompting strategies, from fundamental concepts to advanced methods, improving your ability to communicate effectively with AI language models. A Community-Driven Knowledge Hub This repository grows stronger with your contributions! Join our vibrant Discord community — the central hub for shaping and advancing this project together 🤝 GenAI Agents Discord Community Whether you're a novice eager to learn or an expert ready to share your knowledge, your insights can shape the future of GenAI agents. Join us to propose ideas, get feedback, and collaborate on innovative implementations. For contribution guidelines, please refer to our CONTRIBUTING.md file. Let's advance GenAI agent technology together! 🔗 For discussions on GenAI, agents, or to explore knowledge-sharing opportunities, feel free to connect on LinkedIn. Key Features 🎓 Learn to build GenAI agents from beginner to advanced levels 🧠 Explore a wide range of agent architectures and applications 📚 Step-by-step tutorials and comprehensive documentation 🛠️ Practical, ready-to-use agent implementations 🌟 Regular updates with the latest advancements in GenAI 🤝 Share your own agent creations with the community GenAI Agent Implementations Explore our extensive list of GenAI agent implementations, sorted by categories: 🌱 Beginner-Friendly Agents Simple Conversational Agent LangChain PydanticAI Overview 🔎 A context-aware conversational AI maintains information across interactions, enabling more natural dialogues. Implementation 🛠️ Integrates a language model, prompt template, and history manager to generate contextual responses and track conversation sessions. Simple Question Answering Agent Overview 🔎 Answering (QA) agent using LangChain and OpenAI's language model understands user queries and provides relevant, concise answers. Implementation 🛠️ Combines OpenAI's GPT model, a prompt template, and an LLMChain to process user questions and generate AI-driven responses in a streamlined manner. Simple Data Analysis Agent LangChain PydanticAI Overview 🔎 An AI-powered data analysis agent interprets and answers questions about datasets using natural language, combining language models with data manipulation tools for intuitive data exploration. Implementation 🛠️ Integrates a language model, data manipulation framework, and agent framework to process natural language queries and perform data analysis on a synthetic dataset, enabling accessible insights for non-technical users. 🔧 Framework Tutorial: LangGraph Introduction to LangGraph: Building Modular AI Workflows Overview 🔎 This tutorial introduces LangGraph, a powerful framework for creating modular, graph-based AI workflows. Learn how to leverage LangGraph to build more complex and flexible AI agents that can handle multi-step processes efficiently. Implementation 🛠️ Step-by-step guide on using LangGraph to create a StateGraph workflow. The tutorial covers key concepts such as state management, node creation, and graph compilation. It demonstrates these principles by constructing a simple text analysis pipeline, serving as a foundation for more advanced agent architectures. Additional Resources 📚 Blog Post 🎓 Educational and Research Agents ATLAS: Academic Task and Learning Agent System Overview 🔎 ATLAS demonstrates how to build an intelligent multi-agent system that transforms academic support through AI-powered assistance. The system leverages LangGraph's workflow framework to coordinate multiple specialized agents that provide personalized academic planning, note-taking, and advisory support. Implementation 🛠️ Implements a state-managed multi-agent architecture using four specialized agents (Coordinator, Planner, Notewriter, and Advisor) working in concert through LangGraph's workflow framework. The system features sophisticated workflows for profile analysis and academic support, with continuous adaptation based on student performance and feedback. Additional Resources 📚 YouTube Explanation Blog Post Scientific Paper Agent - Literature Review Overview 🔎 An intelligent research assistant that helps users navigate, understand, and analyze scientific literature through an orchestrated workflow. The system combines academic APIs with sophisticated paper processing techniques to automate literature review tasks, enabling researchers to efficiently extract insights from academic papers while maintaining research rigor and quality control. Implementation 🛠️ Leverages LangGraph to create a five-node workflow system including decision making, planning, tool execution, and quality validation nodes. The system integrates the CORE API for paper access, PDFplumber for document processing, and advanced language models for analysis. Key features include a retry mechanism for robust paper downloads, structured data handling through Pydantic models, and quality-focused improvement cycles with human-in-the-loop validation options. Additional Resources 📚 YouTube Explanation Blog Post Chiron - A Feynman-Enhanced Learning Agent Overview 🔎 An adaptive learning agent that guides users through educational content using a structured checkpoint system and Feynman-style teaching. The system processes learning materials (either user-provided or web-retrieved), verifies understanding through interactive checkpoints, and provides simplified explanations when needed, creating a personalized learning experience that mimics one-on-one tutoring. Implementation 🛠️ Uses LangGraph to orchestrate a learning workflow that includes checkpoint definition, context building, understanding verification, and Feynman teaching nodes. The system integrates web search for dynamic content retrieval, employs semantic chunking for context processing, and manages embeddings for relevant information retrieval. Key features include a 70% understanding threshold for progression, interactive human-in-the-loop validation, and structured output through Pydantic models for consistent data handling. Additional Resources 📚 YouTube Explanation 💼 Business and Professional Agents Customer Support Agent (LangGraph) Overview 🔎 An intelligent customer support agent using LangGraph categorizes queries, analyzes sentiment, and provides appropriate responses or escalates issues. Implementation 🛠️ Utilizes LangGraph to create a workflow combining state management, query categorization, sentiment analysis, and response generation. Essay Grading Agent (LangGraph) Overview 🔎 An automated essay grading system using LangGraph and an LLM model evaluates essays based on relevance, grammar, structure, and depth of analysis. Implementation 🛠️ Utilizes a state graph to define the grading workflow, incorporating separate grading functions for each criterion. Travel Planning Agent (LangGraph) Overview 🔎 A Travel Planner using LangGraph demonstrates how to build a stateful, multi-step conversational AI application that collects user input and generates personalized travel itineraries. Implementation 🛠️ Utilizes StateGraph to define the application flow, incorporates custom PlannerState for process management. GenAI Career Assistant Agent Overview 🔎 The GenAI Career Assistant demonstrates how to create a multi-agent system that provides personalized guidance for careers in Generative AI. Using LangGraph and Gemini LLM, the system delivers customized learning paths, resume assistance, interview preparation, and job search support. Implementation 🛠️ Leverages a multi-agent architecture using LangGraph to coordinate specialized agents (Learning, Resume, Interview, Job Search) through TypedDict-based state management. The system employs sophisticated query categorization and routing while integrating with external tools like DuckDuckGo for job searches and dynamic content generation. Additional Resources 📚 YouTube Explanation Project Manager Assistant Agent Overview 🔎 An AI agent designed to assist in project management tasks by automating the process of creating actionable tasks from project descriptions, identifying dependencies, scheduling work, and assigning tasks to team members based on expertise. The system includes risk assessment and self-reflection capabilities to optimize project plans through multiple iterations, aiming to minimize overall project risk. Implementation 🛠️ Leverages LangGraph to orchestrate a workflow of specialized nodes including task generation, dependency mapping, scheduling, allocation, and risk assessment. Each node uses GPT-4o-mini for structured outputs following Pydantic models. The system implements a feedback loop for self-improvement, where risk scores trigger reflection cycles that generate insights to optimize the project plan. Visualization tools display Gantt charts of the generated schedules across iterations. Additional Resources 📚 YouTube Explanation Contract Analysis Assistant (ClauseAI) Overview 🔎 ClauseAI demonstrates how to build an AI-powered contract analysis system using a multi-agent approach. The system employs specialized AI agents for different aspects of contract review, from clause analysis to compliance checking, and leverages LangGraph for workflow orchestration and Pinecone for efficient clause retrieval and comparison. Implementation 🛠️ Implements a sophisticated state-based workflow using LangGraph to coordinate multiple AI agents through contract analysis stages. The system features Pydantic models for data validation, vector storage with Pinecone for clause comparison, and LLM-based analysis for generating comprehensive contract reports. The implementation includes parallel processing capabilities and customizable report generation based on user requirements. Additional Resources 📚 YouTube Explanation E2E Testing Agent Overview 🔎 The E2E Testing Agent demonstrates how to build an AI-powered system that converts natural language test instructions into executable end-to-end web tests. Using LangGraph for workflow orchestration and Playwright for browser automation, the system enables users to specify test cases in plain English while handling the complexity of test generation and execution. Implementation 🛠️ Implements a structured workflow using LangGraph to coordinate test generation, validation, and execution. The system features TypedDict state management, integration with Playwright for browser automation, and LLM-based code generation for converting natural language instructions into executable test scripts. The implementation includes DOM state analysis, error handling, and comprehensive test reporting. Additional Resources 📚 YouTube Explanation 🎨 Creative and Content Generation Agents GIF Animation Generator Agent (LangGraph) Overview 🔎 A GIF animation generator that integrates LangGraph for workflow management, GPT-4 for text generation, and DALL-E for image creation, producing custom animations from user prompts. Implementation 🛠️ Utilizes LangGraph to orchestrate a workflow that generates character descriptions, plots, and image prompts using GPT-4, creates images with DALL-E 3, and assembles them into GIFs using PIL. Employs asynchronous programming for efficient parallel processing. TTS Poem Generator Agent (LangGraph) Overview 🔎 An advanced text-to-speech (TTS) agent using LangGraph and OpenAI's APIs classifies input text, processes it based on content type, and generates corresponding speech output. Implementation 🛠️ Utilizes LangGraph to orchestrate a workflow that classifies input text using GPT models, applies content-specific processing, and converts the processed text to speech using OpenAI's TTS API. The system adapts its output based on the identified content type (general, poem, news, or joke). Music Compositor Agent (LangGraph) Overview 🔎 An AI Music Compositor using LangGraph and OpenAI's language models generates custom musical compositions based on user input. The system processes the input through specialized components, each contributing to the final musical piece, which is then converted to a playable MIDI file. Implementation 🛠️ LangGraph orchestrates a workflow that transforms user input into a musical composition, using ChatOpenAI (GPT-4) to generate melody, harmony, and rhythm, which are then style-adapted. The final AI-generated composition is converted to a MIDI file using music21 and can be played back using pygame. Content Intelligence: Multi-Platform Content Generation Agent Overview 🔎 Content Intelligence demonstrates how to build an advanced content generation system that transforms input text into platform-optimized content across multiple social media channels. The system employs LangGraph for workflow orchestration to analyze content, conduct research, and generate tailored content while maintaining brand consistency across different platforms. Implementation 🛠️ Implements a sophisticated workflow using LangGraph to coordinate multiple specialized nodes (Summary, Research, Platform-Specific) through the content generation process. The system features TypedDict and Pydantic models for state management, integration with Tavily Search for research enhancement, and platform-specific content generation using GPT-4. The implementation includes parallel processing for multiple platforms and customizable content templates. Additional Resources 📚 YouTube Explanation Business Meme Generator Using LangGraph and Memegen.link Overview 🔎 The Business Meme Generator demonstrates how to create an AI-powered system that generates contextually relevant memes based on company website analysis. Using LangGraph for workflow orchestration, the system combines Groq's Llama model for text analysis and the Memegen.link API to automatically produce brand-aligned memes for digital marketing. Implementation 🛠️ Implements a state-managed workflow using LangGraph to coordinate website content analysis, meme concept generation, and image creation. The system features Pydantic models for data validation, asynchronous processing with aiohttp, and integration with external APIs (Groq, Memegen.link) to create a complete meme generation pipeline with customizable templates. Additional Resources 📚 YouTube Explanation Murder Mystery Game with LLM Agents Overview 🔎 A text-based detective game that utilizes autonomous LLM agents as interactive characters in a procedurally generated murder mystery. Drawing inspiration from the UNBOUNDED paper, the system creates unique scenarios each time, with players taking on the role of Sherlock Holmes to solve the case through character interviews and deductive reasoning. Implementation 🛠️ Leverages two LangGraph workflows - a main game loop for story/character generation and game progression, and a conversation sub-graph for character interactions. The system uses a combination of LLM-powered narrative generation, character AI, and structured game mechanics to create an immersive investigative experience with replayable storylines. Additional Resources 📚 YouTube Explanation 📊 Analysis and Information Processing Agents Memory-Enhanced Conversational Agent Overview 🔎 A memory-enhanced conversational AI agent incorporates short-term and long-term memory systems to maintain context within conversations and across multiple sessions, improving interaction quality and personalization. Implementation 🛠️ Integrates a language model with separate short-term and long-term memory stores, utilizes a prompt template incorporating both memory types, and employs a memory manager for storage and retrieval. The system includes an interaction loop that updates and utilizes memories for each response. Multi-Agent Collaboration System Overview 🔎 A multi-agent collaboration system combining historical research with data analysis, leveraging large language models to simulate specialized agents working together to answer complex historical questions. Implementation 🛠️ Utilizes a base Agent class to create specialized HistoryResearchAgent and DataAnalysisAgent, orchestrated by a HistoryDataCollaborationSystem. The system follows a five-step process: historical context provision, data needs identification, historical data provision, data analysis, and final synthesis. Self-Improving Agent Overview 🔎 A Self-Improving Agent using LangChain engages in conversations, learns from interactions, and continuously improves its performance over time through reflection and adaptation. Implementation 🛠️ Integrates a language model with chat history management, response generation, and a reflection mechanism. The system employs a learning system that incorporates insights from reflection to enhance future performance, creating a continuous improvement loop. Task-Oriented Agent Overview 🔎 A language model application using LangChain that summarizes text and translates the summary to Spanish, combining custom functions, structured tools, and an agent for efficient text processing. Implementation 🛠️ Utilizes custom functions for summarization and translation, wrapped as structured tools. Employs a prompt template to guide the agent, which orchestrates the use of tools. An agent executor manages the process, taking input text and producing both an English summary and its Spanish translation. Internet Search and Summarize Agent Overview 🔎 An intelligent web research assistant that combines web search capabilities with AI-powered summarization, automating the process of gathering information from the internet and distilling it into concise, relevant summaries. Implementation 🛠️ Integrates a web search module using DuckDuckGo's API, a result parser, and a text summarization engine leveraging OpenAI's language models. The system performs site-specific or general searches, extracts relevant content, generates concise summaries, and compiles attributed results for efficient information retrieval and synthesis. Multi agent research team - Autogen Overview 🔎 This technique explores a multi-agent system for collaborative research using the AutoGen library. It employs agents to solve tasks collaboratively, focusing on efficient execution and quality assurance. The system enhances research by distributing tasks among specialized agents. Implementation 🛠️ Agents are configured with specific roles using the GPT-4 model, including admin, developer, planner, executor, and quality assurance. Interaction management ensures orderly communication with defined transitions. Task execution involves collaborative planning, coding, execution, and quality checking, demonstrating a scalable framework for various domains. Additional Resources 📚 comprehensive solution with UI Blogpost Sales Call Analyzer Overview 🔎 An intelligent system that automates the analysis of sales call recordings by combining audio transcription with advanced natural language processing. The analyzer transcribes audio using OpenAI's Whisper, processes the text using NLP techniques, and generates comprehensive reports including sentiment analysis, key phrases, pain points, and actionable recommendations to improve sales performance. Implementation 🛠️ Utilizes multiple components in a structured workflow: OpenAI Whisper for audio transcription, CrewAI for task automation and agent management, and LangChain for orchestrating the analysis pipeline. The system processes audio through a series of steps from transcription to detailed analysis, leveraging custom agents and tasks to generate structured JSON reports containing insights about customer sentiment, sales opportunities, and recommended improvements. Additional Resources 📚 YouTube Explanation Weather Emergency & Response System Overview 🔎 A comprehensive system demonstrating two agent graph implementations for weather emergency response: a real-time graph processing live weather data, and a hybrid graph combining real and simulated data for testing high-severity scenarios. The system handles complete workflow from data gathering through emergency plan generation, with automated notifications and human verification steps. Implementation 🛠️ Utilizes LangGraph for orchestrating complex workflows with state management, integrating OpenWeatherMap API for real-time data, and Gemini for analysis and response generation. The system incorporates email notifications, social media monitoring simulation, and severity-based routing with configurable human verification for low/medium severity events. Additional Resources 📚 YouTube Explanation Self-Healing Codebase System Overview 🔎 An intelligent system that automatically detects, diagnoses, and fixes runtime code errors using LangGraph workflow orchestration and ChromaDB vector storage. The system maintains a memory of encountered bugs and their fixes through vector embeddings, enabling pattern recognition for similar errors across the codebase. Implementation 🛠️ Utilizes a state-based graph workflow that processes function definitions and runtime arguments through specialized nodes for error detection, code analysis, and fix generation. Incorporates ChromaDB for vector-based storage of bug patterns and fixes, with automated search and retrieval capabilities for similar error patterns, while maintaining code execution safety through structured validation steps. Additional Resources 📚 YouTube Explanation DataScribe: AI-Powered Schema Explorer Overview 🔎 An intelligent agent system that enables intuitive exploration and querying of relational databases through natural language interactions. The system utilizes a fleet of specialized agents, coordinated by a stateful Supervisor, to handle schema discovery, query planning, and data analysis tasks while maintaining contextual understanding through vector-based relationship graphs. Implementation 🛠️ Leverages LangGraph for orchestrating a multi-agent workflow including discovery, inference, and planning agents, with NetworkX for relationship graph visualization and management. The system incorporates dynamic state management through TypedDict classes, maintains database context between sessions using a db_graph attribute, and includes safety measures to prevent unauthorized database modifications. Memory-Enhanced Email Agent (LangGraph & LangMem) Overview 🔎 An intelligent email assistant that combines three types of memory (semantic, episodic, and procedural) to create a system that improves over time. The agent can triage incoming emails, draft contextually appropriate responses using stored knowledge, and enhance its performance based on user feedback. Implementation 🛠️ Leverages LangGraph for workflow orchestration and LangMem for sophisticated memory management across multiple memory types. The system implements a triage workflow with memory-enhanced decision making, specialized tools for email composition and calendar management, and a self-improvement mechanism that updates its own prompts based on feedback and past performance. Additional Resources 📚 Blog Post 📰 News and Information Agents News TL;DR using LangGraph Overview 🔎 A news summarization system that generates concise TL;DR summaries of current events based on user queries. The system leverages large language models for decision making and summarization while integrating with news APIs to access up-to-date content, allowing users to quickly catch up on topics of interest through generated bullet-point summaries. Implementation 🛠️ Utilizes LangGraph to orchestrate a workflow combining multiple components: GPT-4o-mini for generating search terms and article summaries, NewsAPI for retrieving article metadata, BeautifulSoup for web scraping article content, and Asyncio for concurrent processing. The system follows a structured pipeline from query processing through article selection and summarization, managing the flow between components to produce relevant TL;DRs of current news articles. Additional Resources 📚 YouTube Explanation Blog Post AInsight: AI/ML Weekly News Reporter Overview 🔎 AInsight demonstrates how to build an intelligent news aggregation and summarization system using a multi-agent architecture. The system employs three specialized agents (NewsSearcher, Summarizer, Publisher) to automatically collect, process and summarize AI/ML news for general audiences through LangGraph-based workflow orchestration. Implementation 🛠️ Implements a state-managed multi-agent system using LangGraph to coordinate the news collection (Tavily API), technical content summarization (GPT-4), and report generation processes. The system features modular architecture with TypedDict-based state management, external API integration, and markdown report generation with customizable templates. Additional Resources 📚 YouTube Explanation Journalism-Focused AI Assistant Overview 🔎 A specialized AI assistant that helps journalists tackle modern journalistic challenges like misinformation, bias, and information overload. The system integrates fact-checking, tone analysis, summarization, and grammar review tools to enhance the accuracy and efficiency of journalistic work while maintaining ethical reporting standards. Implementation 🛠️ Leverages LangGraph to orchestrate a workflow of specialized components including language models for analysis and generation, web search integration via DuckDuckGo's API, document parsing tools like PyMuPDFLoader and WebBaseLoader, text splitting with RecursiveCharacterTextSplitter, and structured JSON outputs. Each component works together through a unified workflow to analyze content, verify facts, detect bias, extract quotes, and generate comprehensive reports. Blog Writer (Open AI Swarm) Overview 🔎 A multi-agent system for collaborative blog post creation using OpenAI's Swarm package. It leverages specialized agents to perform research, planning, writing, and editing tasks efficiently. Implementation 🛠️ Utilizes OpenAI's Swarm Package to manage agent interactions. Includes an admin, researcher, planner, writer, and editor, each with specific roles. The system follows a structured workflow: topic setting, outlining, research, drafting, and editing. This approach enhances content creation through task distribution, specialization, and collaborative problem-solving. Additional Resources 📚 Swarm Repo Podcast Internet Search and Generate Agent 🎙️ Overview 🔎 A two step agent that first searches the internet for a given topic and then generates a podcast on the topic found. The search step uses a search agent and search function to find the most relevant information. The second step uses a podcast generation agent and generation function to create a podcast on the topic found. Implementation 🛠️ Utilizes LangGraph to orchestrate a two-step workflow. The first step involves a search agent and function to gather information from the internet. The second step uses a podcast generation agent and function to create a podcast based on the gathered information. 🛍️ Shopping and Product Analysis Agents ShopGenie - Redefining Online Shopping Customer Experience Overview 🔎 An AI-powered shopping assistant that helps customers make informed purchasing decisions even without domain expertise. The system analyzes product information from multiple sources, compares specifications and reviews, identifies the best option based on user needs, and delivers recommendations through email with supporting video reviews, creating a comprehensive shopping experience. Implementation 🛠️ Uses LangGraph to orchestrate a workflow combining Tavily for web search, Llama-3.1-70B for structured data analysis and product comparison, and YouTube API for review video retrieval. The system processes search results through multiple nodes including schema mapping, product comparison, review identification, and email generation. Key features include structured Pydantic models for consistent data handling, retry mechanisms for robust API interactions, and email delivery through SMTP for sharing recommendations. Additional Resources 📚 YouTube Explanation Car Buyer AI Agent Overview 🔎 The Smart Product Buyer AI Agent demonstrates how to build an intelligent system that assists users in making informed purchasing decisions. Using LangGraph and LLM-based intelligence, the system processes user requirements, scrapes product listings from websites like AutoTrader, and provides detailed analysis and recommendations for car purchases. Implementation 🛠️ Implements a state-based workflow using LangGraph to coordinate user interaction, web scraping, and decision support. The system features TypedDict state management, async web scraping with Playwright, and integrates with external APIs for comprehensive product analysis. The implementation includes a Gradio interface for real-time chat interaction and modular scraper architecture for easy extension to additional product categories. Additional Resources 📚 YouTube Explanation 🎯 Task Management and Productivity Agents Taskifier - Intelligent Task Allocation & Management Overview 🔎 An intelligent task management system that analyzes user work styles and creates personalized task breakdown strategies, born from the observation that procrastination often stems from task ambiguity among students and early-career professionals. The system evaluates historical work patterns, gathers relevant task information through web search, and generates customized step-by-step approaches to optimize productivity and reduce workflow paralysis. Implementation 🛠️ Leverages LangGraph for orchestrating a multi-step workflow including work style analysis, information gathering via Tavily API, and customized plan generation. The system maintains state through the process, integrating historical work pattern data with fresh task research to output detailed, personalized task execution plans aligned with the user's natural working style. Additional Resources 📚 YouTube Explanation Grocery Management Agents System Overview 🔎 A multi-agent system built with CrewAI that automates grocery management tasks including receipt interpretation, expiration date tracking, inventory management, and recipe recommendations. The system uses specialized agents to extract data from receipts, estimate product shelf life, track consumption, and suggest recipes to minimize food waste. Implementation 🛠️ Implements four specialized agents using CrewAI - a Receipt Interpreter that extracts item details from receipts, an Expiration Date Estimator that determines shelf life using online sources, a Grocery Tracker that maintains inventory based on consumption, and a Recipe Recommender that suggests meals using available ingredients. Each agent has specific tools and tasks orchestrated through a crew workflow. Additional Resources 📚 YouTube Explanation 🔍 Quality Assurance and Testing Agents LangGraph-Based Systems Inspector Overview 🔎 A comprehensive testing and validation tool for LangGraph-based applications that automatically analyzes system architecture, generates test cases, and identifies potential vulnerabilities through multi-agent inspection. The inspector employs specialized AI testers to evaluate different aspects of the system, from basic functionality to security concerns and edge cases. Implementation 🛠️ Integrates LangGraph for workflow orchestration, multiple LLM-powered testing agents, and a structured evaluation pipeline that includes static analysis, test case generation, and results verification. The system uses Pydantic for data validation, NetworkX for graph representation, and implements a modular architecture that allows for parallel test execution and comprehensive result analysis. Additional Resources 📚 YouTube Explanation Blog Post EU Green Deal FAQ Bot Overview 🔎 The EU Green Deal FAQ Bot demonstrates how to build a RAG-based AI agent that helps businesses understand EU green deal policies. The system processes complex regulatory documents into manageable chunks and provides instant, accurate answers to common questions about environmental compliance, emissions reporting, and waste management requirements. Implementation 🛠️ Implements a sophisticated RAG pipeline using FAISS vectorstore for document storage, semantic chunking for preprocessing, and multiple specialized agents (Retriever, Summarizer, Evaluator) for query processing. The system features query rephrasing for improved accuracy, cross-reference with gold Q&A datasets for answer validation, and comprehensive evaluation metrics to ensure response quality and relevance. Additional Resources 📚 YouTube Explanation Systematic Review Automation System + Paper Draft Creation Overview 🔎 A comprehensive system for automating academic systematic reviews using a directed graph architecture and LangChain components. The system generates complete, publication-ready systematic review papers, automatically processing everything from literature search through final draft generation with multiple revision cycles. Implementation 🛠️ Utilizes a state-based graph workflow that handles paper search and selection (up to 3 papers), PDF processing, and generates a complete academic paper with all standard sections (abstract, introduction, methods, results, conclusions, references). The system incorporates multiple revision cycles with automated critique and improvement phases, all orchestrated through LangGraph state management. Additional Resources 📚 YouTube Explanation 🌟 Special Advanced Technique 🌟 Sophisticated Controllable Agent for Complex RAG Tasks 🤖 Overview 🔎 An advanced RAG solution designed to tackle complex questions that simple semantic similarity-based retrieval cannot solve. This approach uses a sophisticated deterministic graph as the "brain" 🧠 of a highly controllable autonomous agent, capable of answering non-trivial questions from your own data. Implementation 🛠️ • Implement a multi-step process involving question anonymization, high-level planning, task breakdown, adaptive information retrieval and question answering, continuous re-planning, and rigorous answer verification to ensure grounded and accurate responses. Getting Started To begin exploring and building GenAI agents: Clone this repository: Navigate to the technique you're interested in: Follow the detailed implementation guide in each technique's notebook. Contributing We welcome contributions from the community! If you have a new technique or improvement to suggest: Fork the repository Create your feature branch: git checkout -b feature/AmazingFeature Commit your changes: git commit -m 'Add some AmazingFeature' Push to the branch: git push origin feature/AmazingFeature Open a pull request Contributors License This project is licensed under a custom non-commercial license - see the LICENSE file for details. ⭐️ If you find this repository helpful, please consider giving it a star! Keywords: GenAI, Generative AI, Agents, NLP, AI, Machine Learning, Natural Language Processing, LLM, Conversational AI, Task-Oriented AI

AITreasureBox
github
LLM Vibe Score0.447
Human Vibe Score0.1014145151561518
superiorluMar 28, 2025

AITreasureBox

AI TreasureBox English | 中文 Collect practical AI repos, tools, websites, papers and tutorials on AI. Translated from ChatGPT, picture from Midjourney. Catalog Repos Tools Websites Report&Paper Tutorials Repos updated repos and stars every 2 hours and re-ranking automatically. | No. | Repos | Description | | ----:|:-----------------------------------------|:------------------------------------------------------------------------------------------------------| | 1|🔥codecrafters-io/build-your-own-x !2025-03-28364681428|Master programming by recreating your favorite technologies from scratch.| | 2|sindresorhus/awesome !2025-03-28353614145|😎 Awesome lists about all kinds of interesting topics| | 3|public-apis/public-apis !2025-03-28334299125|A collective list of free APIs| | 4|kamranahmedse/developer-roadmap !2025-03-2831269540|Interactive roadmaps, guides and other educational content to help developers grow in their careers.| | 5|vinta/awesome-python !2025-03-28238581114|A curated list of awesome Python frameworks, libraries, software and resources| | 6|practical-tutorials/project-based-learning !2025-03-28222661124|Curated list of project-based tutorials| | 7|tensorflow/tensorflow !2025-03-281888714|An Open Source Machine Learning Framework for Everyone| | 8|Significant-Gravitas/AutoGPT !2025-03-2817391338|An experimental open-source attempt to make GPT-4 fully autonomous.| | 9|jackfrued/Python-100-Days !2025-03-2816305141|Python - 100天从新手到大师| | 10|AUTOMATIC1111/stable-diffusion-webui !2025-03-2815011553|Stable Diffusion web UI| | 11|huggingface/transformers !2025-03-2814207850|🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.| | 12|ollama/ollama !2025-03-28135166151|Get up and running with Llama 2, Mistral, Gemma, and other large language models.| | 13|f/awesome-chatgpt-prompts !2025-03-2812212738 |This repo includes ChatGPT prompt curation to use ChatGPT better.| | 14|justjavac/free-programming-books-zhCN !2025-03-2811316119|📚 免费的计算机编程类中文书籍,欢迎投稿| | 15|krahets/hello-algo !2025-03-2811107930|《Hello 算法》:动画图解、一键运行的数据结构与算法教程。支持 Python, Java, C++, C, C#, JS, Go, Swift, Rust, Ruby, Kotlin, TS, Dart 代码。简体版和繁体版同步更新,English version ongoing| | 16|yt-dlp/yt-dlp !2025-03-28105801114|A feature-rich command-line audio/video downloader| | 17|langchain-ai/langchain !2025-03-2810449479|⚡ Building applications with LLMs through composability ⚡| | 18|goldbergyoni/nodebestpractices !2025-03-281021629|✅ The Node.js best practices list (July 2024)| | 19|puppeteer/puppeteer !2025-03-289018212|JavaScript API for Chrome and Firefox| | 20|pytorch/pytorch !2025-03-288833938|Tensors and Dynamic neural networks in Python with strong GPU acceleration| | 21|neovim/neovim !2025-03-288781482|Vim-fork focused on extensibility and usability| | 22|🔥🔥langgenius/dify !2025-03-2887342639 |One API for plugins and datasets, one interface for prompt engineering and visual operation, all for creating powerful AI applications.| | 23|mtdvio/every-programmer-should-know !2025-03-28867069|A collection of (mostly) technical things every software developer should know about| | 24|open-webui/open-webui !2025-03-2886025159|User-friendly WebUI for LLMs (Formerly Ollama WebUI)| | 25|ChatGPTNextWeb/NextChat !2025-03-288231521|✨ Light and Fast AI Assistant. Support: Web | | 26|supabase/supabase !2025-03-287990956|The open source Firebase alternative.| | 27|openai/whisper !2025-03-287905542|Robust Speech Recognition via Large-Scale Weak Supervision| | 28|home-assistant/core !2025-03-287773219|🏡 Open source home automation that puts local control and privacy first.| | 29|tensorflow/models !2025-03-28774694|Models and examples built with TensorFlow| | 30| ggerganov/llama.cpp !2025-03-287731836 | Port of Facebook's LLaMA model in C/C++ | | 31|3b1b/manim !2025-03-287641918|Animation engine for explanatory math videos| | 32|microsoft/generative-ai-for-beginners !2025-03-287623860|12 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/| | 33|nomic-ai/gpt4all !2025-03-28729285 |gpt4all: an ecosystem of open-source chatbots trained on a massive collection of clean assistant data including code, stories and dialogue| | 34|comfyanonymous/ComfyUI !2025-03-2872635111|The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface.| | 35|bregman-arie/devops-exercises !2025-03-2872225209|Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git, Kubernetes, Terraform, OpenStack, SQL, NoSQL, Azure, GCP, DNS, Elastic, Network, Virtualization. DevOps Interview Questions| | 36|elastic/elasticsearch !2025-03-28721419|Free and Open, Distributed, RESTful Search Engine| | 37|🔥n8n-io/n8n !2025-03-2872093495|Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.| | 38|fighting41love/funNLP !2025-03-287200422|The Most Powerful NLP-Weapon Arsenal| | 39|hoppscotch/hoppscotch !2025-03-287060134|Open source API development ecosystem - https://hoppscotch.io (open-source alternative to Postman, Insomnia)| | 40|abi/screenshot-to-code !2025-03-286932817|Drop in a screenshot and convert it to clean HTML/Tailwind/JS code| | 41|binary-husky/gptacademic !2025-03-28680374|Academic Optimization of GPT| | 42|d2l-ai/d2l-zh !2025-03-286774142|Targeting Chinese readers, functional and open for discussion. The Chinese and English versions are used for teaching in over 400 universities across more than 60 countries| | 43|josephmisiti/awesome-machine-learning !2025-03-286739215|A curated list of awesome Machine Learning frameworks, libraries and software.| | 44|grafana/grafana !2025-03-286725414|The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.| | 45|python/cpython !2025-03-286602218|The Python programming language| | 46|apache/superset !2025-03-286519020|Apache Superset is a Data Visualization and Data Exploration Platform| | 47|xtekky/gpt4free !2025-03-28639391 |decentralizing the Ai Industry, free gpt-4/3.5 scripts through several reverse engineered API's ( poe.com, phind.com, chat.openai.com etc...)| | 48|sherlock-project/sherlock !2025-03-286332536|Hunt down social media accounts by username across social networks| | 49|twitter/the-algorithm !2025-03-28630586 |Source code for Twitter's Recommendation Algorithm| | 50|keras-team/keras !2025-03-28627835|Deep Learning for humans| | 51|openai/openai-cookbook !2025-03-28625136 |Examples and guides for using the OpenAI API| | 52|immich-app/immich !2025-03-286238670|High performance self-hosted photo and video management solution.| | 53|AppFlowy-IO/AppFlowy !2025-03-286173528|Bring projects, wikis, and teams together with AI. AppFlowy is an AI collaborative workspace where you achieve more without losing control of your data. The best open source alternative to Notion.| | 54|scikit-learn/scikit-learn !2025-03-286158212|scikit-learn: machine learning in Python| | 55|binhnguyennus/awesome-scalability !2025-03-286117021|The Patterns of Scalable, Reliable, and Performant Large-Scale Systems| | 56|labmlai/annotateddeeplearningpaperimplementations !2025-03-285951726|🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠| | 57|OpenInterpreter/open-interpreter !2025-03-285894710|A natural language interface for computers| | 58|lobehub/lobe-chat !2025-03-285832054|🤖 Lobe Chat - an open-source, extensible (Function Calling), high-performance chatbot framework. It supports one-click free deployment of your private ChatGPT/LLM web application.| | 59|meta-llama/llama !2025-03-28579536|Inference code for Llama models| | 60|nuxt/nuxt !2025-03-28566437|The Intuitive Vue Framework.| | 61|imartinez/privateGPT !2025-03-28555192|Interact with your documents using the power of GPT, 100% privately, no data leaks| | 62|Stirling-Tools/Stirling-PDF !2025-03-285500846|#1 Locally hosted web application that allows you to perform various operations on PDF files| | 63|PlexPt/awesome-chatgpt-prompts-zh !2025-03-285459720|ChatGPT Chinese Training Guide. Guidelines for various scenarios. Learn how to make it listen to you| | 64|dair-ai/Prompt-Engineering-Guide !2025-03-285451025 |🐙 Guides, papers, lecture, notebooks and resources for prompt engineering| | 65|ageitgey/facerecognition !2025-03-28544382|The world's simplest facial recognition api for Python and the command line| | 66|CorentinJ/Real-Time-Voice-Cloning !2025-03-285384814|Clone a voice in 5 seconds to generate arbitrary speech in real-time| | 67|geekan/MetaGPT !2025-03-285375376|The Multi-Agent Meta Programming Framework: Given one line Requirement, return PRD, Design, Tasks, Repo | | 68|gpt-engineer-org/gpt-engineer !2025-03-285367419|Specify what you want it to build, the AI asks for clarification, and then builds it.| | 69|lencx/ChatGPT !2025-03-2853653-3|🔮 ChatGPT Desktop Application (Mac, Windows and Linux)| | 70|deepfakes/faceswap !2025-03-28535672|Deepfakes Software For All| | 71|langflow-ai/langflow !2025-03-285319584|Langflow is a low-code app builder for RAG and multi-agent AI applications. It’s Python-based and agnostic to any model, API, or database.| | 72|commaai/openpilot !2025-03-28529759|openpilot is an operating system for robotics. Currently, it upgrades the driver assistance system on 275+ supported cars.| | 73|clash-verge-rev/clash-verge-rev !2025-03-2852848124|Continuation of Clash Verge - A Clash Meta GUI based on Tauri (Windows, MacOS, Linux)| | 74|All-Hands-AI/OpenHands !2025-03-285150675|🙌 OpenHands: Code Less, Make More| | 75|xai-org/grok-1 !2025-03-28502504|Grok open release| | 76|meilisearch/meilisearch !2025-03-284999122|A lightning-fast search API that fits effortlessly into your apps, websites, and workflow| | 77|🔥browser-use/browser-use !2025-03-2849910294|Make websites accessible for AI agents| | 78|jgthms/bulma !2025-03-28496783|Modern CSS framework based on Flexbox| | 79|facebookresearch/segment-anything !2025-03-284947116|The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.| |!green-up-arrow.svg 80|hacksider/Deep-Live-Cam !2025-03-2848612146|real time face swap and one-click video deepfake with only a single image (uncensored)| |!red-down-arrow 81|mlabonne/llm-course !2025-03-284860934|Course with a roadmap and notebooks to get into Large Language Models (LLMs).| | 82|PaddlePaddle/PaddleOCR !2025-03-284785530|Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)| | 83|alist-org/alist !2025-03-284732618|🗂️A file list/WebDAV program that supports multiple storages, powered by Gin and Solidjs. / 一个支持多存储的文件列表/WebDAV程序,使用 Gin 和 Solidjs。| | 84|infiniflow/ragflow !2025-03-2847027129|RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.| | 85|Avik-Jain/100-Days-Of-ML-Code !2025-03-284679312|100 Days of ML Coding| | 86|v2ray/v2ray-core !2025-03-28458706|A platform for building proxies to bypass network restrictions.| | 87|hiyouga/LLaMA-Factory !2025-03-284555881|Easy-to-use LLM fine-tuning framework (LLaMA, BLOOM, Mistral, Baichuan, Qwen, ChatGLM)| | 88|Asabeneh/30-Days-Of-Python !2025-03-284544930|30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw| | 89|type-challenges/type-challenges !2025-03-284488511|Collection of TypeScript type challenges with online judge| | 90|lllyasviel/Fooocus !2025-03-284402716|Focus on prompting and generating| | 91|RVC-Boss/GPT-SoVITS !2025-03-284327738|1 min voice data can also be used to train a good TTS model! (few shot voice cloning)| | 92|rasbt/LLMs-from-scratch !2025-03-284320667|Implementing a ChatGPT-like LLM from scratch, step by step| | 93|oobabooga/text-generation-webui !2025-03-284302012 |A gradio web UI for running Large Language Models like LLaMA, llama.cpp, GPT-J, OPT, and GALACTICA.| | 94|vllm-project/vllm !2025-03-2842982102|A high-throughput and memory-efficient inference and serving engine for LLMs| | 95|dani-garcia/vaultwarden !2025-03-284297121|Unofficial Bitwarden compatible server written in Rust, formerly known as bitwarden_rs| | 96|microsoft/autogen !2025-03-284233049|Enable Next-Gen Large Language Model Applications. Join our Discord: https://discord.gg/pAbnFJrkgZ| | 97|jeecgboot/JeecgBoot !2025-03-284205920|🔥「企业级低代码平台」前后端分离架构SpringBoot 2.x/3.x,SpringCloud,Ant Design&Vue3,Mybatis,Shiro,JWT。强大的代码生成器让前后端代码一键生成,无需写任何代码! 引领新的开发模式OnlineCoding->代码生成->手工MERGE,帮助Java项目解决70%重复工作,让开发更关注业务,既能快速提高效率,帮助公司节省成本,同时又不失灵活性。| | 98|Mintplex-Labs/anything-llm !2025-03-284186955|A full-stack application that turns any documents into an intelligent chatbot with a sleek UI and easier way to manage your workspaces.| | 99|THUDM/ChatGLM-6B !2025-03-28410192 |ChatGLM-6B: An Open Bilingual Dialogue Language Model| | 100|hpcaitech/ColossalAI !2025-03-28406902|Making large AI models cheaper, faster and more accessible| | 101|Stability-AI/stablediffusion !2025-03-28406337|High-Resolution Image Synthesis with Latent Diffusion Models| | 102|mingrammer/diagrams !2025-03-28405063|🎨 Diagram as Code for prototyping cloud system architectures| | 103|Kong/kong !2025-03-28404616|🦍 The Cloud-Native API Gateway and AI Gateway.| | 104|getsentry/sentry !2025-03-284040913|Developer-first error tracking and performance monitoring| | 105| karpathy/nanoGPT !2025-03-284034613 |The simplest, fastest repository for training/finetuning medium-sized GPTs| | 106|fastlane/fastlane !2025-03-2840014-1|🚀 The easiest way to automate building and releasing your iOS and Android apps| | 107|psf/black !2025-03-28399765|The uncompromising Python code formatter| | 108|OpenBB-finance/OpenBBTerminal !2025-03-283972074 |Investment Research for Everyone, Anywhere.| | 109|2dust/v2rayNG !2025-03-283943415|A V2Ray client for Android, support Xray core and v2fly core| | 110|apache/airflow !2025-03-283937314|Apache Airflow - A platform to programmatically author, schedule, and monitor workflows| | 111|KRTirtho/spotube !2025-03-283902746|🎧 Open source Spotify client that doesn't require Premium nor uses Electron! Available for both desktop & mobile!| | 112|coqui-ai/TTS !2025-03-283889719 |🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production| | 113|ggerganov/whisper.cpp !2025-03-283882116|Port of OpenAI's Whisper model in C/C++| | 114|ultralytics/ultralytics !2025-03-283866951|NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite| | 115|typst/typst !2025-03-283863914|A new markup-based typesetting system that is powerful and easy to learn.| | 116|streamlit/streamlit !2025-03-283845828|Streamlit — A faster way to build and share data apps.| | 117|LC044/WeChatMsg !2025-03-283836931|提取微信聊天记录,将其导出成HTML、Word、Excel文档永久保存,对聊天记录进行分析生成年度聊天报告,用聊天数据训练专属于个人的AI聊天助手| | 118|lm-sys/FastChat !2025-03-283822112 |An open platform for training, serving, and evaluating large languages. Release repo for Vicuna and FastChat-T5.| | 119|NaiboWang/EasySpider !2025-03-283819013|A visual no-code/code-free web crawler/spider易采集:一个可视化浏览器自动化测试/数据采集/爬虫软件,可以无代码图形化的设计和执行爬虫任务。别名:ServiceWrapper面向Web应用的智能化服务封装系统。| | 120|microsoft/DeepSpeed !2025-03-283765816 |A deep learning optimization library that makes distributed training and inference easy, efficient, and effective| | 121|QuivrHQ/quivr !2025-03-28376067|Your GenAI Second Brain 🧠 A personal productivity assistant (RAG) ⚡️🤖 Chat with your docs (PDF, CSV, ...) & apps using Langchain, GPT 3.5 / 4 turbo, Private, Anthropic, VertexAI, Ollama, LLMs, that you can share with users ! Local & Private alternative to OpenAI GPTs & ChatGPT powered by retrieval-augmented generation.| | 122|freqtrade/freqtrade !2025-03-283757817 |Free, open source crypto trading bot| | 123|suno-ai/bark !2025-03-28373178 |🔊 Text-Prompted Generative Audio Model| | 124|🔥cline/cline !2025-03-2837307282|Autonomous coding agent right in your IDE, capable of creating/editing files, executing commands, and more with your permission every step of the way.| | 125|LAION-AI/Open-Assistant !2025-03-28372712 |OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.| | 126|penpot/penpot !2025-03-283716217|Penpot: The open-source design tool for design and code collaboration| | 127|gradio-app/gradio !2025-03-283713320|Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!| | 128|FlowiseAI/Flowise !2025-03-283667135 |Drag & drop UI to build your customized LLM flow using LangchainJS| | 129|SimplifyJobs/Summer2025-Internships !2025-03-28366506|Collection of Summer 2025 tech internships!| | 130|TencentARC/GFPGAN !2025-03-28365027 |GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.| | 131|ray-project/ray !2025-03-283626819|Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.| | 132|babysor/MockingBird !2025-03-28360498|🚀AI拟声: 5秒内克隆您的声音并生成任意语音内容 Clone a voice in 5 seconds to generate arbitrary speech in real-time| | 133|unslothai/unsloth !2025-03-283603691|5X faster 50% less memory LLM finetuning| | 134|zhayujie/chatgpt-on-wechat !2025-03-283600124 |Wechat robot based on ChatGPT, which uses OpenAI api and itchat library| | 135|upscayl/upscayl !2025-03-283599824|🆙 Upscayl - Free and Open Source AI Image Upscaler for Linux, MacOS and Windows built with Linux-First philosophy.| | 136|freeCodeCamp/devdocs !2025-03-28359738|API Documentation Browser| | 137|XingangPan/DragGAN !2025-03-28359043 |Code for DragGAN (SIGGRAPH 2023)| | 138|2noise/ChatTTS !2025-03-283543922|ChatTTS is a generative speech model for daily dialogue.| | 139|google-research/google-research !2025-03-28352207 |Google Research| | 140|karanpratapsingh/system-design !2025-03-28351003|Learn how to design systems at scale and prepare for system design interviews| | 141|lapce/lapce !2025-03-28350855|Lightning-fast and Powerful Code Editor written in Rust| | 142| microsoft/TaskMatrix !2025-03-2834500-3 | Talking, Drawing and Editing with Visual Foundation Models| | 143|chatchat-space/Langchain-Chatchat !2025-03-283442020|Langchain-Chatchat (formerly langchain-ChatGLM), local knowledge based LLM (like ChatGLM) QA app with langchain| | 144|unclecode/crawl4ai !2025-03-283434163|🔥🕷️ Crawl4AI: Open-source LLM Friendly Web Crawler & Scrapper| | 145|Bin-Huang/chatbox !2025-03-283374733 |A desktop app for GPT-4 / GPT-3.5 (OpenAI API) that supports Windows, Mac & Linux| | 146|milvus-io/milvus !2025-03-283366525 |A cloud-native vector database, storage for next generation AI applications| | 147|mendableai/firecrawl !2025-03-2833297128|🔥 Turn entire websites into LLM-ready markdown| | 148|pola-rs/polars !2025-03-283269320|Fast multi-threaded, hybrid-out-of-core query engine focussing on DataFrame front-ends| | 149|Pythagora-io/gpt-pilot !2025-03-28325321|PoC for a scalable dev tool that writes entire apps from scratch while the developer oversees the implementation| | 150|hashicorp/vault !2025-03-28320797|A tool for secrets management, encryption as a service, and privileged access management| | 151|shardeum/shardeum !2025-03-28319580|Shardeum is an EVM based autoscaling blockchain| | 152|Chanzhaoyu/chatgpt-web !2025-03-28319242 |A demonstration website built with Express and Vue3 called ChatGPT| | 153|lllyasviel/ControlNet !2025-03-283186413 |Let us control diffusion models!| | 154|google/jax !2025-03-28317727|Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more| | 155|facebookresearch/detectron2 !2025-03-28315987|Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.| | 156|myshell-ai/OpenVoice !2025-03-28315233|Instant voice cloning by MyShell| | 157|TheAlgorithms/C-Plus-Plus !2025-03-283151411|Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.| | 158|hiroi-sora/Umi-OCR !2025-03-283138129|OCR图片转文字识别软件,完全离线。截屏/批量导入图片,支持多国语言、合并段落、竖排文字。可排除水印区域,提取干净的文本。基于 PaddleOCR 。| | 159|mudler/LocalAI !2025-03-283127815|🤖 The free, Open Source OpenAI alternative. Self-hosted, community-driven and local-first. Drop-in replacement for OpenAI running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. It allows to generate Text, Audio, Video, Images. Also with voice cloning capabilities.| | 160|facebookresearch/fairseq !2025-03-28312124 |Facebook AI Research Sequence-to-Sequence Toolkit written in Python.| | 161|alibaba/nacos !2025-03-28310559|an easy-to-use dynamic service discovery, configuration and service management platform for building cloud native applications.| | 162|yunjey/pytorch-tutorial !2025-03-28310326|PyTorch Tutorial for Deep Learning Researchers| | 163|v2fly/v2ray-core !2025-03-28307448|A platform for building proxies to bypass network restrictions.| | 164|mckaywrigley/chatbot-ui !2025-03-283067714|The open-source AI chat interface for everyone.| | 165|TabbyML/tabby !2025-03-28305949 |Self-hosted AI coding assistant| | 166|deepseek-ai/awesome-deepseek-integration !2025-03-283053193|| | 167|danielmiessler/fabric !2025-03-283028914|fabric is an open-source framework for augmenting humans using AI.| | 168|xinntao/Real-ESRGAN !2025-03-283026623 |Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.| | 169|paul-gauthier/aider !2025-03-283014642|aider is GPT powered coding in your terminal| | 170|tatsu-lab/stanfordalpaca !2025-03-28299022 |Code and documentation to train Stanford's Alpaca models, and generate the data.| | 171|DataTalksClub/data-engineering-zoomcamp !2025-03-282971817|Free Data Engineering course!| | 172|HeyPuter/puter !2025-03-282967014|🌐 The Internet OS! Free, Open-Source, and Self-Hostable.| | 173|mli/paper-reading !2025-03-282962314|Classic Deep Learning and In-Depth Reading of New Papers Paragraph by Paragraph| | 174|linexjlin/GPTs !2025-03-28295568|leaked prompts of GPTs| | 175|s0md3v/roop !2025-03-28295286 |one-click deepfake (face swap)| | 176|JushBJJ/Mr.-Ranedeer-AI-Tutor !2025-03-2829465-1 |A GPT-4 AI Tutor Prompt for customizable personalized learning experiences.| | 177|opendatalab/MinerU !2025-03-282927074|A one-stop, open-source, high-quality data extraction tool, supports PDF/webpage/e-book extraction.一站式开源高质量数据提取工具,支持PDF/网页/多格式电子书提取。| | 178|mouredev/Hello-Python !2025-03-282920720|Curso para aprender el lenguaje de programación Python desde cero y para principiantes. 75 clases, 37 horas en vídeo, código, proyectos y grupo de chat. Fundamentos, frontend, backend, testing, IA...| | 179|Lightning-AI/pytorch-lightning !2025-03-28292039|Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.| | 180|crewAIInc/crewAI !2025-03-282919344|Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.| | 181|facebook/folly !2025-03-282916612|An open-source C++ library developed and used at Facebook.| | 182|google-ai-edge/mediapipe !2025-03-28291519|Cross-platform, customizable ML solutions for live and streaming media.| | 183| getcursor/cursor !2025-03-282892025 | An editor made for programming with AI| | 184|chatanywhere/GPTAPIfree !2025-03-282856424|Free ChatGPT API Key, Free ChatGPT API, supports GPT-4 API (free), ChatGPT offers a free domestic forwarding API that allows direct connections without the need for a proxy. It can be used in conjunction with software/plugins like ChatBox, significantly reducing interface usage costs. Enjoy unlimited and unrestricted chatting within China| | 185|meta-llama/llama3 !2025-03-28285552|The official Meta Llama 3 GitHub site| | 186|tinygrad/tinygrad !2025-03-282845811|You like pytorch? You like micrograd? You love tinygrad! ❤️| | 187|google-research/tuningplaybook !2025-03-282841514|A playbook for systematically maximizing the performance of deep learning models.| | 188|huggingface/diffusers !2025-03-282830222|🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.| | 189|tokio-rs/tokio !2025-03-28282408|A runtime for writing reliable asynchronous applications with Rust. Provides I/O, networking, scheduling, timers, ...| | 190|RVC-Project/Retrieval-based-Voice-Conversion-WebUI !2025-03-282823817|Voice data !2025-03-282822612|Jan is an open source alternative to ChatGPT that runs 100% offline on your computer| | 192|openai/CLIP !2025-03-282814720|CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image| | 193|🔥khoj-ai/khoj !2025-03-2828112313|Your AI second brain. A copilot to get answers to your questions, whether they be from your own notes or from the internet. Use powerful, online (e.g gpt4) or private, local (e.g mistral) LLMs. Self-host locally or use our web app. Access from Obsidian, Emacs, Desktop app, Web or Whatsapp.| | 194| acheong08/ChatGPT !2025-03-2828054-2 | Reverse engineered ChatGPT API | | 195|iperov/DeepFaceLive !2025-03-28279345 |Real-time face swap for PC streaming or video calls| | 196|eugeneyan/applied-ml !2025-03-28278471|📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.| | 197|XTLS/Xray-core !2025-03-282778213|Xray, Penetrates Everything. Also the best v2ray-core, with XTLS support. Fully compatible configuration.| | 198|feder-cr/JobsApplierAIAgent !2025-03-282776410|AutoJobsApplierAI_Agent aims to easy job hunt process by automating the job application process. Utilizing artificial intelligence, it enables users to apply for multiple jobs in an automated and personalized way.| | 199|mindsdb/mindsdb !2025-03-282750631|The platform for customizing AI from enterprise data| | 200|DataExpert-io/data-engineer-handbook !2025-03-282721611|This is a repo with links to everything you'd ever want to learn about data engineering| | 201|exo-explore/exo !2025-03-282721633|Run your own AI cluster at home with everyday devices 📱💻 🖥️⌚| | 202|taichi-dev/taichi !2025-03-2826926-1|Productive, portable, and performant GPU programming in Python.| | 203|mem0ai/mem0 !2025-03-282689134|The memory layer for Personalized AI| | 204|svc-develop-team/so-vits-svc !2025-03-28268096 |SoftVC VITS Singing Voice Conversion| | 205|OpenBMB/ChatDev !2025-03-28265624|Create Customized Software using Natural Language Idea (through Multi-Agent Collaboration)| | 206|roboflow/supervision !2025-03-282632010|We write your reusable computer vision tools. 💜| | 207|drawdb-io/drawdb !2025-03-282626913|Free, simple, and intuitive online database design tool and SQL generator.| | 208|karpathy/llm.c !2025-03-28261633|LLM training in simple, raw C/CUDA| | 209|airbnb/lottie-ios !2025-03-28261431|An iOS library to natively render After Effects vector animations| | 210|openai/openai-python !2025-03-282607713|The OpenAI Python library provides convenient access to the OpenAI API from applications written in the Python language.| | 211|academic/awesome-datascience !2025-03-28259876|📝 An awesome Data Science repository to learn and apply for real world problems.| | 212|harry0703/MoneyPrinterTurbo !2025-03-282576618|Generate short videos with one click using a large model| | 213|gabime/spdlog !2025-03-282571511|Fast C++ logging library.| | 214|ocrmypdf/OCRmyPDF !2025-03-2825674217|OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched| | 215|Vision-CAIR/MiniGPT-4 !2025-03-28256170 |Enhancing Vision-language Understanding with Advanced Large Language Models| | 216|Stability-AI/generative-models !2025-03-28255936|Generative Models by Stability AI| | 217|DS4SD/docling !2025-03-282555662|Get your docs ready for gen AI| | 218|PostHog/posthog !2025-03-282533227|🦔 PostHog provides open-source product analytics, session recording, feature flagging and A/B testing that you can self-host.| | 219|nrwl/nx !2025-03-282509612|Smart Monorepos · Fast CI| | 220|continuedev/continue !2025-03-282500737|⏩ the open-source copilot chat for software development—bring the power of ChatGPT to VS Code| | 221|opentofu/opentofu !2025-03-28247968|OpenTofu lets you declaratively manage your cloud infrastructure.| | 222|invoke-ai/InvokeAI !2025-03-28247293|InvokeAI is a leading creative engine for Stable Diffusion models, empowering professionals, artists, and enthusiasts to generate and create visual media using the latest AI-driven technologies. The solution offers an industry leading WebUI, supports terminal use through a CLI, and serves as the foundation for multiple commercial products.| | 223|deepinsight/insightface !2025-03-282471615 |State-of-the-art 2D and 3D Face Analysis Project| | 224|apache/flink !2025-03-28246865|Apache Flink| | 225|ComposioHQ/composio !2025-03-28246436|Composio equips agents with well-crafted tools empowering them to tackle complex tasks| | 226|Genesis-Embodied-AI/Genesis !2025-03-282458314|A generative world for general-purpose robotics & embodied AI learning.| | 227|stretchr/testify !2025-03-28243184|A toolkit with common assertions and mocks that plays nicely with the standard library| | 228| yetone/openai-translator !2025-03-28242921 | Browser extension and cross-platform desktop application for translation based on ChatGPT API | | 229|frappe/erpnext !2025-03-282425211|Free and Open Source Enterprise Resource Planning (ERP)| | 230|songquanpeng/one-api !2025-03-282410034|OpenAI 接口管理 & 分发系统,支持 Azure、Anthropic Claude、Google PaLM 2 & Gemini、智谱 ChatGLM、百度文心一言、讯飞星火认知、阿里通义千问、360 智脑以及腾讯混元,可用于二次分发管理 key,仅单可执行文件,已打包好 Docker 镜像,一键部署,开箱即用. OpenAI key management & redistribution system, using a single API for all LLMs, and features an English UI.| | 231| microsoft/JARVIS !2025-03-28240604 | a system to connect LLMs with ML community | | 232|google/flatbuffers !2025-03-28239965|FlatBuffers: Memory Efficient Serialization Library| | 233|microsoft/graphrag !2025-03-282398928|A modular graph-based Retrieval-Augmented Generation (RAG) system| | 234|rancher/rancher !2025-03-28239675|Complete container management platform| | 235|bazelbuild/bazel !2025-03-282384618|a fast, scalable, multi-language and extensible build system| | 236|modularml/mojo !2025-03-28238236 |The Mojo Programming Language| | 237|danny-avila/LibreChat !2025-03-282378753|Enhanced ChatGPT Clone: Features OpenAI, GPT-4 Vision, Bing, Anthropic, OpenRouter, Google Gemini, AI model switching, message search, langchain, DALL-E-3, ChatGPT Plugins, OpenAI Functions, Secure Multi-User System, Presets, completely open-source for self-hosting. More features in development| |!green-up-arrow.svg 238|🔥🔥🔥Shubhamsaboo/awesome-llm-apps !2025-03-28237391211|Collection of awesome LLM apps with RAG using OpenAI, Anthropic, Gemini and opensource models.| |!red-down-arrow 239|microsoft/semantic-kernel !2025-03-282373611|Integrate cutting-edge LLM technology quickly and easily into your apps| |!red-down-arrow 240|TheAlgorithms/Rust !2025-03-28236995|All Algorithms implemented in Rust| | 241|stanford-oval/storm !2025-03-28236326|An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.| | 242|openai/gpt-2 !2025-03-28232483|Code for the paper "Language Models are Unsupervised Multitask Learners"| | 243|labring/FastGPT !2025-03-282319445|A platform that uses the OpenAI API to quickly build an AI knowledge base, supporting many-to-many relationships.| | 244|pathwaycom/llm-app !2025-03-2822928-10|Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.| | 245|warpdotdev/Warp !2025-03-282286825|Warp is a modern, Rust-based terminal with AI built in so you and your team can build great software, faster.| | 246|🔥agno-agi/agno !2025-03-2822833298|Agno is a lightweight library for building Multimodal Agents. It exposes LLMs as a unified API and gives them superpowers like memory, knowledge, tools and reasoning.| | 247|qdrant/qdrant !2025-03-282275214 |Qdrant - Vector Database for the next generation of AI applications. Also available in the cloud https://cloud.qdrant.io/| | 248|ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code !2025-03-282271815|500 AI Machine learning Deep learning Computer vision NLP Projects with code| | 249|stanfordnlp/dspy !2025-03-282268321|Stanford DSPy: The framework for programming—not prompting—foundation models| | 250|PaddlePaddle/Paddle !2025-03-28226246|PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)| | 251|zulip/zulip !2025-03-28225464|Zulip server and web application. Open-source team chat that helps teams stay productive and focused.| | 252|Hannibal046/Awesome-LLM !2025-03-282240721|Awesome-LLM: a curated list of Large Language Model| | 253|facefusion/facefusion !2025-03-282218812|Next generation face swapper and enhancer| | 254|Mozilla-Ocho/llamafile !2025-03-28220624|Distribute and run LLMs with a single file.| | 255|yuliskov/SmartTube !2025-03-282201614|SmartTube - an advanced player for set-top boxes and tvs running Android OS| | 256|haotian-liu/LLaVA !2025-03-282201316 |Large Language-and-Vision Assistant built towards multimodal GPT-4 level capabilities.| | 257|ashishps1/awesome-system-design-resources !2025-03-282189367|This repository contains System Design resources which are useful while preparing for interviews and learning Distributed Systems| | 258|Cinnamon/kotaemon !2025-03-28218248|An open-source RAG-based tool for chatting with your documents.| | 259|CodePhiliaX/Chat2DB !2025-03-282179757|🔥🔥🔥AI-driven database tool and SQL client, The hottest GUI client, supporting MySQL, Oracle, PostgreSQL, DB2, SQL Server, DB2, SQLite, H2, ClickHouse, and more.| | 260|blakeblackshear/frigate !2025-03-282177113|NVR with realtime local object detection for IP cameras| | 261|facebookresearch/audiocraft !2025-03-28217111|Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable music generation LM with textual and melodic conditioning.| | 262|karpathy/minGPT !2025-03-28216567|A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training| | 263|grpc/grpc-go !2025-03-282159510|The Go language implementation of gRPC. HTTP/2 based RPC| | 264|HumanSignal/label-studio !2025-03-282137618|Label Studio is a multi-type data labeling and annotation tool with standardized output format| | 265|yoheinakajima/babyagi !2025-03-28212764 |uses OpenAI and Pinecone APIs to create, prioritize, and execute tasks, This is a pared-down version of the original Task-Driven Autonomous Agent| | 266|deepseek-ai/DeepSeek-Coder !2025-03-282118210|DeepSeek Coder: Let the Code Write Itself| | 267|BuilderIO/gpt-crawler !2025-03-282118010|Crawl a site to generate knowledge files to create your own custom GPT from a URL| | 268| openai/chatgpt-retrieval-plugin !2025-03-2821152-1 | Plugins are chat extensions designed specifically for language models like ChatGPT, enabling them to access up-to-date information, run computations, or interact with third-party services in response to a user's request.| | 269|microsoft/OmniParser !2025-03-282113123|A simple screen parsing tool towards pure vision based GUI agent| | 270|black-forest-labs/flux !2025-03-282107219|Official inference repo for FLUX.1 models| | 271|ItzCrazyKns/Perplexica !2025-03-282099154|Perplexica is an AI-powered search engine. It is an Open source alternative to Perplexity AI| | 272|microsoft/unilm !2025-03-28209876|Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities| | 273|Sanster/lama-cleaner !2025-03-282077614|Image inpainting tool powered by SOTA AI Model. Remove any unwanted object, defect, people from your pictures or erase and replace(powered by stable diffusion) any thing on your pictures.| | 274|assafelovic/gpt-researcher !2025-03-282057222|GPT based autonomous agent that does online comprehensive research on any given topic| | 275|PromtEngineer/localGPT !2025-03-28204230 |Chat with your documents on your local device using GPT models. No data leaves your device and 100% private.| | 276|elastic/kibana !2025-03-28203482|Your window into the Elastic Stack| | 277|fishaudio/fish-speech !2025-03-282033222|Brand new TTS solution| | 278|mlc-ai/mlc-llm !2025-03-282028110 |Enable everyone to develop, optimize and deploy AI models natively on everyone's devices.| | 279|deepset-ai/haystack !2025-03-282005320|🔍 Haystack is an open source NLP framework to interact with your data using Transformer models and LLMs (GPT-4, ChatGPT and alike). Haystack offers production-ready tools to quickly build complex question answering, semantic search, text generation applications, and more.| | 280|tree-sitter/tree-sitter !2025-03-28200487|An incremental parsing system for programming tools| | 281|Anjok07/ultimatevocalremovergui !2025-03-281999811|GUI for a Vocal Remover that uses Deep Neural Networks.| | 282|guidance-ai/guidance !2025-03-28199622|A guidance language for controlling large language models.| | 283|ml-explore/mlx !2025-03-28199619|MLX: An array framework for Apple silicon| | 284|mlflow/mlflow !2025-03-281995314|Open source platform for the machine learning lifecycle| | 285|ml-tooling/best-of-ml-python !2025-03-28198631|🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.| | 286|BerriAI/litellm !2025-03-281981862|Call all LLM APIs using the OpenAI format. Use Bedrock, Azure, OpenAI, Cohere, Anthropic, Ollama, Sagemaker, HuggingFace, Replicate (100+ LLMs)| | 287|LazyVim/LazyVim !2025-03-281981320|Neovim config for the lazy| | 288|wez/wezterm !2025-03-281976018|A GPU-accelerated cross-platform terminal emulator and multiplexer written by @wez and implemented in Rust| | 289|valkey-io/valkey !2025-03-281970416|A flexible distributed key-value datastore that supports both caching and beyond caching workloads.| | 290|LiLittleCat/awesome-free-chatgpt !2025-03-28196185|🆓免费的 ChatGPT 镜像网站列表,持续更新。List of free ChatGPT mirror sites, continuously updated.| | 291|Byaidu/PDFMathTranslate !2025-03-281947645|PDF scientific paper translation with preserved formats - 基于 AI 完整保留排版的 PDF 文档全文双语翻译,支持 Google/DeepL/Ollama/OpenAI 等服务,提供 CLI/GUI/Docker| | 292|openai/swarm !2025-03-281947111|Educational framework exploring ergonomic, lightweight multi-agent orchestration. Managed by OpenAI Solution team.| | 293|HqWu-HITCS/Awesome-Chinese-LLM !2025-03-281921423|Organizing smaller, cost-effective, privately deployable open-source Chinese language models, including related datasets and tutorials| | 294|stitionai/devika !2025-03-28190903|Devika is an Agentic AI Software Engineer that can understand high-level human instructions, break them down into steps, research relevant information, and write code to achieve the given objective. Devika aims to be a competitive open-source alternative to Devin by Cognition AI.| | 295|OpenBMB/MiniCPM-o !2025-03-28190887|MiniCPM-o 2.6: A GPT-4o Level MLLM for Vision, Speech and Multimodal Live Streaming on Your Phone| | 296|samber/lo !2025-03-281904815|💥 A Lodash-style Go library based on Go 1.18+ Generics (map, filter, contains, find...)| | 297|chroma-core/chroma !2025-03-281895221 |the AI-native open-source embedding database| | 298|DarkFlippers/unleashed-firmware !2025-03-28189278|Flipper Zero Unleashed Firmware| | 299|brave/brave-browser !2025-03-281892710|Brave browser for Android, iOS, Linux, macOS, Windows.| | 300| tloen/alpaca-lora !2025-03-28188641 | Instruct-tune LLaMA on consumer hardware| | 301|VinciGit00/Scrapegraph-ai !2025-03-281884618|Python scraper based on AI| | 302|gitroomhq/postiz-app !2025-03-281879110|📨 Schedule social posts, measure them, exchange with other members and get a lot of help from AI 🚀| | 303|PrefectHQ/prefect !2025-03-281878715|Prefect is a workflow orchestration tool empowering developers to build, observe, and react to data pipelines| | 304|ymcui/Chinese-LLaMA-Alpaca !2025-03-28187723 |Chinese LLaMA & Alpaca LLMs| | 305|kenjihiranabe/The-Art-of-Linear-Algebra !2025-03-28187335|Graphic notes on Gilbert Strang's "Linear Algebra for Everyone"| | 306|joonspk-research/generativeagents !2025-03-28187288|Generative Agents: Interactive Simulacra of Human Behavior| | 307|renovatebot/renovate !2025-03-28186820|Universal dependency update tool that fits into your workflows.| | 308|gventuri/pandas-ai !2025-03-28186109 |Pandas AI is a Python library that integrates generative artificial intelligence capabilities into Pandas, making dataframes conversational| | 309|thingsboard/thingsboard !2025-03-28185184|Open-source IoT Platform - Device management, data collection, processing and visualization.| | 310|ente-io/ente !2025-03-28184722|Fully open source, End to End Encrypted alternative to Google Photos and Apple Photos| | 311|serengil/deepface !2025-03-281840113|A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python| | 312|Raphire/Win11Debloat !2025-03-281840132|A simple, easy to use PowerShell script to remove pre-installed apps from windows, disable telemetry, remove Bing from windows search as well as perform various other changes to declutter and improve your windows experience. This script works for both windows 10 and windows 11.| | 313|Avaiga/taipy !2025-03-28179235|Turns Data and AI algorithms into production-ready web applications in no time.| | 314|microsoft/qlib !2025-03-281784231|Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.| | 315|CopilotKit/CopilotKit !2025-03-281778571|Build in-app AI chatbots 🤖, and AI-powered Textareas ✨, into react web apps.| | 316|QwenLM/Qwen-7B !2025-03-281766017|The official repo of Qwen-7B (通义千问-7B) chat & pretrained large language model proposed by Alibaba Cloud.| | 317|w-okada/voice-changer !2025-03-28176078 |リアルタイムボイスチェンジャー Realtime Voice Changer| | 318|rlabbe/Kalman-and-Bayesian-Filters-in-Python !2025-03-281756011|Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.| | 319|Mikubill/sd-webui-controlnet !2025-03-28174794 |WebUI extension for ControlNet| | 320|jingyaogong/minimind !2025-03-2817380116|「大模型」3小时完全从0训练26M的小参数GPT,个人显卡即可推理训练!| | 321|apify/crawlee !2025-03-28172696|Crawlee—A web scraping and browser automation library for Node.js to build reliable crawlers. In JavaScript and TypeScript. Extract data for AI, LLMs, RAG, or GPTs. Download HTML, PDF, JPG, PNG, and other files from websites. Works with Puppeteer, Playwright, Cheerio, JSDOM, and raw HTTP. Both headful and headless mode. With proxy rotation.| | 322|apple/ml-stable-diffusion !2025-03-28172395|Stable Diffusion with Core ML on Apple Silicon| | 323| transitive-bullshit/chatgpt-api !2025-03-28172095 | Node.js client for the official ChatGPT API. | | 324|teableio/teable !2025-03-281719222|✨ The Next Gen Airtable Alternative: No-Code Postgres| | 325| xx025/carrot !2025-03-28170900 | Free ChatGPT Site List | | 326|microsoft/LightGBM !2025-03-28170723|A fast, distributed, high-performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.| | 327|VikParuchuri/surya !2025-03-28169827|Accurate line-level text detection and recognition (OCR) in any language| | 328|deepseek-ai/Janus !2025-03-281692825|Janus-Series: Unified Multimodal Understanding and Generation Models| | 329|ardalis/CleanArchitecture !2025-03-28168823|Clean Architecture Solution Template: A starting point for Clean Architecture with ASP.NET Core| | 330|neondatabase/neon !2025-03-28166466|Neon: Serverless Postgres. We separated storage and compute to offer autoscaling, code-like database branching, and scale to zero.| | 331|kestra-io/kestra !2025-03-281661313|⚡ Workflow Automation Platform. Orchestrate & Schedule code in any language, run anywhere, 500+ plugins. Alternative to Zapier, Rundeck, Camunda, Airflow...| | 332|Dao-AILab/flash-attention !2025-03-281659720|Fast and memory-efficient exact attention| | 333|RPCS3/rpcs3 !2025-03-281655712|PS3 emulator/debugger| | 334|meta-llama/llama-recipes !2025-03-28165486|Scripts for fine-tuning Llama2 with composable FSDP & PEFT methods to cover single/multi-node GPUs. Supports default & custom datasets for applications such as summarization & question answering. Supporting a number of candid inference solutions such as HF TGI, VLLM for local or cloud deployment.Demo apps to showcase Llama2 for WhatsApp & Messenger| | 335|emilwallner/Screenshot-to-code !2025-03-28165180|A neural network that transforms a design mock-up into a static website.| | 336|datawhalechina/llm-cookbook !2025-03-281650922|面向开发者的 LLM 入门教程,吴恩达大模型系列课程中文版| | 337|e2b-dev/awesome-ai-agents !2025-03-281643923|A list of AI autonomous agents| | 338|QwenLM/Qwen2.5 !2025-03-281641114|Qwen2.5 is the large language model series developed by Qwen team, Alibaba Cloud.| | 339|dair-ai/ML-YouTube-Courses !2025-03-28164114|📺 Discover the latest machine learning / AI courses on YouTube.| | 340|pybind/pybind11 !2025-03-28163620|Seamless operability between C++11 and Python| | 341|graphdeco-inria/gaussian-splatting !2025-03-281627116|Original reference implementation of "3D Gaussian Splatting for Real-Time Radiance Field Rendering"| | 342|meta-llama/codellama !2025-03-28162531|Inference code for CodeLlama models| | 343|TransformerOptimus/SuperAGI !2025-03-28161292 | SuperAGI - A dev-first open source autonomous AI agent framework. Enabling developers to build, manage & run useful autonomous agents quickly and reliably.| | 344|microsoft/onnxruntime !2025-03-28161169|ONNX Runtime: cross-platform, high-performance ML inferencing and training accelerator| | 345|IDEA-Research/Grounded-Segment-Anything !2025-03-281601411 |Marrying Grounding DINO with Segment Anything & Stable Diffusion & BLIP - Automatically Detect, Segment and Generate Anything with Image and Text Inputs| | 346|ddbourgin/numpy-ml !2025-03-28160054|Machine learning, in numpy| | 347|eosphoros-ai/DB-GPT !2025-03-281585225|Revolutionizing Database Interactions with Private LLM Technology| | 348|Stability-AI/StableLM !2025-03-28158310 |Stability AI Language Models| | 349|openai/evals !2025-03-28157935 |Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.| | 350|THUDM/ChatGLM2-6B !2025-03-28157500|ChatGLM2-6B: An Open Bilingual Chat LLM | | 351|sunner/ChatALL !2025-03-28156761 |Concurrently chat with ChatGPT, Bing Chat, Bard, Alpaca, Vincuna, Claude, ChatGLM, MOSS, iFlytek Spark, ERNIE and more, discover the best answers| | 352|abseil/abseil-cpp !2025-03-28156656|Abseil Common Libraries (C++)| | 353|NVIDIA/open-gpu-kernel-modules !2025-03-28156531|NVIDIA Linux open GPU kernel module source| | 354|letta-ai/letta !2025-03-281563718|Letta (formerly MemGPT) is a framework for creating LLM services with memory.| | 355|typescript-eslint/typescript-eslint !2025-03-28156211|✨ Monorepo for all the tooling which enables ESLint to support TypeScript| | 356|umijs/umi !2025-03-28156211|A framework in react community ✨| | 357|AI4Finance-Foundation/FinGPT !2025-03-281561215|Data-Centric FinGPT. Open-source for open finance! Revolutionize 🔥 We'll soon release the trained model.| | 358|amplication/amplication !2025-03-28156022|🔥🔥🔥 The Only Production-Ready AI-Powered Backend Code Generation| | 359|KindXiaoming/pykan !2025-03-28155477|Kolmogorov Arnold Networks| | 360|arc53/DocsGPT !2025-03-28154900|GPT-powered chat for documentation, chat with your documents| | 361|influxdata/telegraf !2025-03-28154502|Agent for collecting, processing, aggregating, and writing metrics, logs, and other arbitrary data.| | 362|microsoft/Bringing-Old-Photos-Back-to-Life !2025-03-28154084|Bringing Old Photo Back to Life (CVPR 2020 oral)| | 363|GaiZhenbiao/ChuanhuChatGPT !2025-03-2815394-2|GUI for ChatGPT API and many LLMs. Supports agents, file-based QA, GPT finetuning and query with web search. All with a neat UI.| | 364|Zeyi-Lin/HivisionIDPhotos !2025-03-281529710|⚡️HivisionIDPhotos: a lightweight and efficient AI ID photos tools. 一个轻量级的AI证件照制作算法。| | 365| mayooear/gpt4-pdf-chatbot-langchain !2025-03-281529518 | GPT4 & LangChain Chatbot for large PDF docs | | 366|1Panel-dev/MaxKB !2025-03-2815277148|? Based on LLM large language model knowledge base Q&A system. Ready to use out of the box, supports quick integration into third-party business systems. Officially produced by 1Panel| | 367|ai16z/eliza !2025-03-281526811|Conversational Agent for Twitter and Discord| | 368|apache/arrow !2025-03-28151684|Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing| | 369|princeton-nlp/SWE-agent !2025-03-281516119|SWE-agent: Agent Computer Interfaces Enable Software Engineering Language Models| | 370|mlc-ai/web-llm !2025-03-281509311 |Bringing large-language models and chat to web browsers. Everything runs inside the browser with no server support.| | 371|guillaumekln/faster-whisper !2025-03-281507117 |Faster Whisper transcription with CTranslate2| | 372|overleaf/overleaf !2025-03-28150316|A web-based collaborative LaTeX editor| | 373|triton-lang/triton !2025-03-28150169|Development repository for the Triton language and compiler| | 374|soxoj/maigret !2025-03-281500410|🕵️‍♂️ Collect a dossier on a person by username from thousands of sites| | 375|alibaba/lowcode-engine !2025-03-28149841|An enterprise-class low-code technology stack with scale-out design / 一套面向扩展设计的企业级低代码技术体系| | 376|espressif/esp-idf !2025-03-28148545|Espressif IoT Development Framework. Official development framework for Espressif SoCs.| | 377|pgvector/pgvector !2025-03-281484913|Open-source vector similarity search for Postgres| | 378|datawhalechina/leedl-tutorial !2025-03-28148246|《李宏毅深度学习教程》(李宏毅老师推荐👍),PDF下载地址:https://github.com/datawhalechina/leedl-tutorial/releases| | 379|xcanwin/KeepChatGPT !2025-03-28147972 |Using ChatGPT is more efficient and smoother, perfectly solving ChatGPT network errors. No longer do you need to frequently refresh the webpage, saving over 10 unnecessary steps| | 380|m-bain/whisperX !2025-03-281471313|WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization)| | 381|HumanAIGC/AnimateAnyone !2025-03-2814706-1|Animate Anyone: Consistent and Controllable Image-to-Video Synthesis for Character Animation| |!green-up-arrow.svg 382|naklecha/llama3-from-scratch !2025-03-281469024|llama3 implementation one matrix multiplication at a time| |!red-down-arrow 383| fauxpilot/fauxpilot !2025-03-28146871 | An open-source GitHub Copilot server | | 384|LlamaFamily/Llama-Chinese !2025-03-28145111|Llama Chinese Community, the best Chinese Llama large model, fully open source and commercially available| | 385|BradyFU/Awesome-Multimodal-Large-Language-Models !2025-03-281450121|Latest Papers and Datasets on Multimodal Large Language Models| | 386|vanna-ai/vanna !2025-03-281449819|🤖 Chat with your SQL database 📊. Accurate Text-to-SQL Generation via LLMs using RAG 🔄.| | 387|bleedline/aimoneyhunter !2025-03-28144845|AI Side Hustle Money Mega Collection: Teaching You How to Utilize AI for Various Side Projects to Earn Extra Income.| | 388|stefan-jansen/machine-learning-for-trading !2025-03-28144629|Code for Machine Learning for Algorithmic Trading, 2nd edition.| | 389|state-spaces/mamba !2025-03-28144139|Mamba: Linear-Time Sequence Modeling with Selective State Spaces| | 390|vercel/ai-chatbot !2025-03-281434614|A full-featured, hackable Next.js AI chatbot built by Vercel| | 391|steven-tey/novel !2025-03-281428410|Notion-style WYSIWYG editor with AI-powered autocompletions| | 392|unifyai/ivy !2025-03-281409348|Unified AI| | 393|chidiwilliams/buzz !2025-03-281402411 |Buzz transcribes and translates audio offline on your personal computer. Powered by OpenAI's Whisper.| | 394|lukas-blecher/LaTeX-OCR !2025-03-28139769|pix2tex: Using a ViT to convert images of equations into LaTeX code.| | 395|openai/tiktoken !2025-03-28139599|tiktoken is a fast BPE tokeniser for use with OpenAI's models.| | 396|nocobase/nocobase !2025-03-281391522|NocoBase is a scalability-first, open-source no-code/low-code platform for building business applications and enterprise solutions.| | 397|neonbjb/tortoise-tts !2025-03-28139010 |A multi-voice TTS system trained with an emphasis on quality| | 398|yamadashy/repomix !2025-03-281382036|📦 Repomix (formerly Repopack) is a powerful tool that packs your entire repository into a single, AI-friendly file. Perfect for when you need to feed your codebase to Large Language Models (LLMs) or other AI tools like Claude, ChatGPT, and Gemini.| | 399|adobe/react-spectrum !2025-03-28136766|A collection of libraries and tools that help you build adaptive, accessible, and robust user experiences.| | 400|THUDM/ChatGLM3 !2025-03-28136684|ChatGLM3 series: Open Bilingual Chat LLMs | | 401|NVIDIA/NeMo !2025-03-28134837|A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)| | 402|BlinkDL/RWKV-LM !2025-03-28134346 |RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it combines the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.| | 403| fuergaosi233/wechat-chatgpt !2025-03-28133330 | Use ChatGPT On Wechat via wechaty | | 404|udecode/plate !2025-03-28133325|A rich-text editor powered by AI| | 405|xenova/transformers.js !2025-03-281331219|State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server!| | 406|stas00/ml-engineering !2025-03-281325615|Machine Learning Engineering Guides and Tools| | 407| wong2/chatgpt-google-extension !2025-03-2813241-1 | A browser extension that enhances search engines with ChatGPT, this repos will not be updated from 2023-02-20| | 408|mrdbourke/pytorch-deep-learning !2025-03-281317520|Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.| | 409|Koenkk/zigbee2mqtt !2025-03-28131544|Zigbee 🐝 to MQTT bridge 🌉, get rid of your proprietary Zigbee bridges 🔨| | 410|vercel-labs/ai !2025-03-281298528|Build AI-powered applications with React, Svelte, and Vue| | 411|netease-youdao/QAnything !2025-03-28129318|Question and Answer based on Anything.| | 412|huggingface/trl !2025-03-281289622|Train transformer language models with reinforcement learning.| | 413|microsoft/BitNet !2025-03-28128503|Official inference framework for 1-bit LLMs| | 414|mediar-ai/screenpipe !2025-03-281283915|24/7 local AI screen & mic recording. Build AI apps that have the full context. Works with Ollama. Alternative to Rewind.ai. Open. Secure. You own your data. Rust.| | 415|Skyvern-AI/skyvern !2025-03-281277612|Automate browser-based workflows with LLMs and Computer Vision| | 416|pytube/pytube !2025-03-28126591|A lightweight, dependency-free Python library (and command-line utility) for downloading YouTube Videos.| | 417|official-stockfish/Stockfish !2025-03-28126574|UCI chess engine| | 418|sgl-project/sglang !2025-03-281260143|SGLang is a structured generation language designed for large language models (LLMs). It makes your interaction with LLMs faster and more controllable.| | 419|plasma-umass/scalene !2025-03-28125535|Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals| | 420|danswer-ai/danswer !2025-03-28125503|Ask Questions in natural language and get Answers backed by private sources. Connects to tools like Slack, GitHub, Confluence, etc.| | 421|OpenTalker/SadTalker !2025-03-28125226|[CVPR 2023] SadTalker:Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation| | 422|facebookresearch/AnimatedDrawings !2025-03-28123693 |Code to accompany "A Method for Animating Children's Drawings of the Human Figure"| | 423|activepieces/activepieces !2025-03-28123609|Your friendliest open source all-in-one automation tool ✨ Workflow automation tool 100+ integration / Enterprise automation tool / Zapier Alternative| | 424|ggerganov/ggml !2025-03-28121992 |Tensor library for machine learning| | 425|bytebase/bytebase !2025-03-28121694|World's most advanced database DevOps and CI/CD for Developer, DBA and Platform Engineering teams. The GitLab/GitHub for database DevOps.| | 426| willwulfken/MidJourney-Styles-and-Keywords-Reference !2025-03-28120971 | A reference containing Styles and Keywords that you can use with MidJourney AI| | 427|Huanshere/VideoLingo !2025-03-281207013|Netflix-level subtitle cutting, translation, alignment, and even dubbing - one-click fully automated AI video subtitle team | | 428|OpenLMLab/MOSS !2025-03-28120330 |An open-source tool-augmented conversational language model from Fudan University| | 429|llmware-ai/llmware !2025-03-281200727|Providing enterprise-grade LLM-based development framework, tools, and fine-tuned models.| | 430|PKU-YuanGroup/Open-Sora-Plan !2025-03-28119362|This project aim to reproduce Sora (Open AI T2V model), but we only have limited resource. We deeply wish the all open source community can contribute to this project.| | 431|ShishirPatil/gorilla !2025-03-28119332 |Gorilla: An API store for LLMs| | 432|NVIDIA/Megatron-LM !2025-03-281192716|Ongoing research training transformer models at scale| | 433|illacloud/illa-builder !2025-03-28119192|Create AI-Driven Apps like Assembling Blocks| | 434|marimo-team/marimo !2025-03-281191521|A reactive notebook for Python — run reproducible experiments, execute as a script, deploy as an app, and version with git.| | 435|smol-ai/developer !2025-03-28119111 | With 100k context windows on the way, it's now feasible for every dev to have their own smol developer| | 436|Lightning-AI/litgpt !2025-03-28118878|Pretrain, finetune, deploy 20+ LLMs on your own data. Uses state-of-the-art techniques: flash attention, FSDP, 4-bit, LoRA, and more.| | 437|openai/shap-e !2025-03-28118474 |Generate 3D objects conditioned on text or images| | 438|eugeneyan/open-llms !2025-03-28118451 |A list of open LLMs available for commercial use.| | 439|andrewyng/aisuite !2025-03-28118124|Simple, unified interface to multiple Generative AI providers| | 440|hajimehoshi/ebiten !2025-03-28117816|Ebitengine - A dead simple 2D game engine for Go| | 441|kgrzybek/modular-monolith-with-ddd !2025-03-28117493|Full Modular Monolith application with Domain-Driven Design approach.| | 442|h2oai/h2ogpt !2025-03-2811736-1 |Come join the movement to make the world's best open source GPT led by H2O.ai - 100% private chat and document search, no data leaks, Apache 2.0| | 443|owainlewis/awesome-artificial-intelligence !2025-03-28117332|A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.| | 444|DataTalksClub/mlops-zoomcamp !2025-03-28116643|Free MLOps course from DataTalks.Club| | 445|Rudrabha/Wav2Lip !2025-03-281163410|This repository contains the codes of "A Lip Sync Expert Is All You Need for Speech to Lip Generation In the Wild", published at ACM Multimedia 2020.| | 446|aishwaryanr/awesome-generative-ai-guide !2025-03-281152810|A one stop repository for generative AI research updates, interview resources, notebooks and much more!| | 447|karpathy/micrograd !2025-03-28115146|A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API| | 448|InstantID/InstantID !2025-03-28115111|InstantID : Zero-shot Identity-Preserving Generation in Seconds 🔥| | 449|facebookresearch/seamlesscommunication !2025-03-28114434|Foundational Models for State-of-the-Art Speech and Text Translation| | 450|anthropics/anthropic-cookbook !2025-03-281140112|A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.| | 451|mastra-ai/mastra !2025-03-281139240|the TypeScript AI agent framework| | 452|NVIDIA/TensorRT !2025-03-28113864|NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.| | 453|plandex-ai/plandex !2025-03-28113645|An AI coding engine for complex tasks| | 454|RUCAIBox/LLMSurvey !2025-03-28112735 |A collection of papers and resources related to Large Language Models.| | 455|kubeshark/kubeshark !2025-03-28112711|The API traffic analyzer for Kubernetes providing real-time K8s protocol-level visibility, capturing and monitoring all traffic and payloads going in, out and across containers, pods, nodes and clusters. Inspired by Wireshark, purposely built for Kubernetes| | 456|electric-sql/pglite !2025-03-28112617|Lightweight Postgres packaged as WASM into a TypeScript library for the browser, Node.js, Bun and Deno from https://electric-sql.com| | 457|lightaime/camel !2025-03-281124441 |🐫 CAMEL: Communicative Agents for “Mind” Exploration of Large Scale Language Model Society| | 458|huggingface/lerobot !2025-03-281120184|🤗 LeRobot: State-of-the-art Machine Learning for Real-World Robotics in Pytorch| | 459|normal-computing/outlines !2025-03-28111657|Generative Model Programming| | 460|libretro/RetroArch !2025-03-28110701|Cross-platform, sophisticated frontend for the libretro API. Licensed GPLv3.| | 461|THUDM/CogVideo !2025-03-28110599|Text-to-video generation: CogVideoX (2024) and CogVideo (ICLR 2023)| | 462|bentoml/OpenLLM !2025-03-28110495|An open platform for operating large language models (LLMs) in production. Fine-tune, serve, deploy, and monitor any LLMs with ease.| | 463|vosen/ZLUDA !2025-03-28110429|CUDA on AMD GPUs| | 464|dair-ai/ML-Papers-of-the-Week !2025-03-28110304 |🔥Highlighting the top ML papers every week.| | 465|WordPress/gutenberg !2025-03-28110212|The Block Editor project for WordPress and beyond. Plugin is available from the official repository.| | 466|microsoft/data-formulator !2025-03-281099827|🪄 Create rich visualizations with AI| | 467|LibreTranslate/LibreTranslate !2025-03-28109887|Free and Open Source Machine Translation API. Self-hosted, offline capable and easy to setup.| | 468|block/goose !2025-03-281097737|an open-source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM| | 469|getumbrel/llama-gpt !2025-03-28109553|A self-hosted, offline, ChatGPT-like chatbot. Powered by Llama 2. 100% private, with no data leaving your device.| | 470|HigherOrderCO/HVM !2025-03-28109182|A massively parallel, optimal functional runtime in Rust| | 471|databrickslabs/dolly !2025-03-2810812-3 | A large language model trained on the Databricks Machine Learning Platform| | 472|srush/GPU-Puzzles !2025-03-28108014|Solve puzzles. Learn CUDA.| | 473|Z3Prover/z3 !2025-03-28107952|The Z3 Theorem Prover| | 474|UFund-Me/Qbot !2025-03-281079313 |Qbot is an AI-oriented quantitative investment platform, which aims to realize the potential, empower AI technologies in quantitative investment| | 475|langchain-ai/langgraph !2025-03-281077336|| | 476|lz4/lz4 !2025-03-28107647|Extremely Fast Compression algorithm| | 477|magic-research/magic-animate !2025-03-28107160|MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model| | 478|PaperMC/Paper !2025-03-281071410|The most widely used, high performance Minecraft server that aims to fix gameplay and mechanics inconsistencies| | 479|getomni-ai/zerox !2025-03-281071015|Zero shot pdf OCR with gpt-4o-mini| |!green-up-arrow.svg 480|🔥NirDiamant/GenAIAgents !2025-03-2810693318|This repository provides tutorials and implementations for various Generative AI Agent techniques, from basic to advanced. It serves as a comprehensive guide for building intelligent, interactive AI systems.| |!red-down-arrow 481|Unstructured-IO/unstructured !2025-03-28106889|Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.| | 482|apache/thrift !2025-03-28106610|Apache Thrift| | 483| TheR1D/shellgpt !2025-03-28106097 | A command-line productivity tool powered by ChatGPT, will help you accomplish your tasks faster and more efficiently | | 484|TheRamU/Fay !2025-03-281060312 |Fay is a complete open source project that includes Fay controller and numeral models, which can be used in different applications such as virtual hosts, live promotion, numeral human interaction and so on| | 485|zyronon/douyin !2025-03-28105566|Vue3 + Pinia + Vite5 仿抖音,Vue 在移动端的最佳实践 . Imitate TikTok ,Vue Best practices on Mobile| | 486|THU-MIG/yolov10 !2025-03-28105485|YOLOv10: Real-Time End-to-End Object Detection| | 487|idootop/mi-gpt !2025-03-281052522|? Transform XiaoAi speaker into a personal voice assistant with ChatGPT and DouBao integration.| | 488|SakanaAI/AI-Scientist !2025-03-281051310|The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑‍🔬| | 489|szimek/sharedrop !2025-03-28105101|Easy P2P file transfer powered by WebRTC - inspired by Apple AirDrop| | 490|salesforce/LAVIS !2025-03-28103942 |LAVIS - A One-stop Library for Language-Vision Intelligence| | 491|aws/amazon-sagemaker-examples !2025-03-28103654|Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.| | 492|artidoro/qlora !2025-03-28103402 |QLoRA: Efficient Finetuning of Quantized LLMs| | 493|lllyasviel/stable-diffusion-webui-forge !2025-03-281029314| a platform on top of Stable Diffusion WebUI (based on Gradio) to make development easier, optimize resource management, and speed up inference| | 494|NielsRogge/Transformers-Tutorials !2025-03-28102487|This repository contains demos I made with the Transformers library by HuggingFace.| | 495|kedro-org/kedro !2025-03-28102371|Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.| | 496| chathub-dev/chathub !2025-03-28102301 | All-in-one chatbot client | | 497|microsoft/promptflow !2025-03-28101612|Build high-quality LLM apps - from prototyping, testing to production deployment and monitoring.| | 498|mistralai/mistral-src !2025-03-28101372|Reference implementation of Mistral AI 7B v0.1 model.| | 499|burn-rs/burn !2025-03-28101183|Burn - A Flexible and Comprehensive Deep Learning Framework in Rust| | 500|AIGC-Audio/AudioGPT !2025-03-28101150 |AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head| | 501|facebookresearch/dinov2 !2025-03-281011210 |PyTorch code and models for the DINOv2 self-supervised learning method.| | 502|RockChinQ/LangBot !2025-03-281008455|😎丰富生态、🧩支持扩展、🦄多模态 - 大模型原生即时通信机器人平台 🤖 | | 503|78/xiaozhi-esp32 !2025-03-281008180|Build your own AI friend| | 504|cumulo-autumn/StreamDiffusion !2025-03-28100761|StreamDiffusion: A Pipeline-Level Solution for Real-Time Interactive Generation| | 505|DataTalksClub/machine-learning-zoomcamp !2025-03-28100664|The code from the Machine Learning Bookcamp book and a free course based on the book| | 506|nerfstudio-project/nerfstudio !2025-03-28100343|A collaboration friendly studio for NeRFs| | 507|cupy/cupy !2025-03-28100344|NumPy & SciPy for GPU| | 508|NVIDIA/TensorRT-LLM !2025-03-281000823|TensorRT-LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and build TensorRT engines that contain state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT-LLM also contains components to create Python and C++ runtimes that execute those TensorRT engines.| | 509|wasp-lang/open-saas !2025-03-2899665|A free, open-source SaaS app starter for React & Node.js with superpowers. Production-ready. Community-driven.| | 510|huggingface/text-generation-inference !2025-03-2899383|Large Language Model Text Generation Inference| | 511|jxnl/instructor !2025-03-2899224|structured outputs for llms| | 512|GoogleCloudPlatform/generative-ai !2025-03-2899086|Sample code and notebooks for Generative AI on Google Cloud| | 513|manticoresoftware/manticoresearch !2025-03-2898799|Easy to use open source fast database for search | | 514|langfuse/langfuse !2025-03-28985134|🪢 Open source LLM engineering platform. Observability, metrics, evals, prompt management, testing, prompt playground, datasets, LLM evaluations -- 🍊YC W23 🤖 integrate via Typescript, Python / Decorators, OpenAI, Langchain, LlamaIndex, Litellm, Instructor, Mistral, Perplexity, Claude, Gemini, Vertex| | 515|keephq/keep !2025-03-2897949|The open-source alert management and AIOps platform| | 516|sashabaranov/go-openai !2025-03-2897843|OpenAI ChatGPT, GPT-3, GPT-4, DALL·E, Whisper API wrapper for Go| | 517|autowarefoundation/autoware !2025-03-2897766|Autoware - the world's leading open-source software project for autonomous driving| | 518|anthropics/courses !2025-03-2897269|Anthropic's educational courses| | 519|popcorn-official/popcorn-desktop !2025-03-2896853|Popcorn Time is a multi-platform, free software BitTorrent client that includes an integrated media player ( Windows / Mac / Linux ) A Butter-Project Fork| | 520|getmaxun/maxun !2025-03-28968515|🔥 Open-source no-code web data extraction platform. Turn websites to APIs and spreadsheets with no-code robots in minutes! [In Beta]| | 521|wandb/wandb !2025-03-2896763|🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.| | 522|karpathy/minbpe !2025-03-2895353|Minimal, clean, code for the Byte Pair Encoding (BPE) algorithm commonly used in LLM tokenization.| | 523|bigscience-workshop/petals !2025-03-2895142|🌸 Run large language models at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading| | 524|OthersideAI/self-operating-computer !2025-03-2894931|A framework to enable multimodal models to operate a computer.| | 525|mshumer/gpt-prompt-engineer !2025-03-2894911|| | 526| BloopAI/bloop !2025-03-2894710 | A fast code search engine written in Rust| | 527|BlinkDL/ChatRWKV !2025-03-289467-1 |ChatRWKV is like ChatGPT but powered by RWKV (100% RNN) language model, and open source.| | 528|timlrx/tailwind-nextjs-starter-blog !2025-03-2894677|This is a Next.js, Tailwind CSS blogging starter template. Comes out of the box configured with the latest technologies to make technical writing a breeze. Easily configurable and customizable. Perfect as a replacement to existing Jekyll and Hugo individual blogs.| | 529|google/benchmark !2025-03-2893634|A microbenchmark support library| | 530|facebookresearch/nougat !2025-03-2893603|Implementation of Nougat Neural Optical Understanding for Academic Documents| | 531|modelscope/facechain !2025-03-2893536|FaceChain is a deep-learning toolchain for generating your Digital-Twin.| | 532|DrewThomasson/ebook2audiobook !2025-03-2893388|Convert ebooks to audiobooks with chapters and metadata using dynamic AI models and voice cloning. Supports 1,107+ languages!| | 533|RayTracing/raytracing.github.io !2025-03-2893035|Main Web Site (Online Books)| | 534|QwenLM/Qwen2.5-VL !2025-03-28930249|Qwen2.5-VL is the multimodal large language model series developed by Qwen team, Alibaba Cloud.| | 535|WongKinYiu/yolov9 !2025-03-2892201|Implementation of paper - YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information| | 536|alibaba-damo-academy/FunASR !2025-03-28920222|A Fundamental End-to-End Speech Recognition Toolkit and Open Source SOTA Pretrained Models.| | 537|Visualize-ML/Book4Power-of-Matrix !2025-03-2891931|Book4 'Power of Matrix' | | 538|dice2o/BingGPT !2025-03-289185-1 |Desktop application of new Bing's AI-powered chat (Windows, macOS and Linux)| | 539|browserbase/stagehand !2025-03-28917621|An AI web browsing framework focused on simplicity and extensibility.| | 540|FlagOpen/FlagEmbedding !2025-03-28914111|Dense Retrieval and Retrieval-augmented LLMs| | 541|Const-me/Whisper !2025-03-2890979|High-performance GPGPU inference of OpenAI's Whisper automatic speech recognition (ASR) model| | 542|lucidrains/denoising-diffusion-pytorch !2025-03-2890942|Implementation of Denoising Diffusion Probabilistic Model in Pytorch| | 543|Chainlit/chainlit !2025-03-28904422|Build Conversational AI in minutes ⚡️| | 544|togethercomputer/OpenChatKit !2025-03-2890160 |OpenChatKit provides a powerful, open-source base to create both specialized and general purpose chatbots for various applications| | 545|Stability-AI/StableStudio !2025-03-2889631 |Community interface for generative AI| | 546|voicepaw/so-vits-svc-fork !2025-03-2889482 |so-vits-svc fork with realtime support, improved interface and more features.| | 547|pymc-devs/pymc !2025-03-2889413|Bayesian Modeling and Probabilistic Programming in Python| | 548|espnet/espnet !2025-03-2889302|End-to-End Speech Processing Toolkit| | 549|kedacore/keda !2025-03-2888991|KEDA is a Kubernetes-based Event Driven Autoscaling component. It provides event driven scale for any container running in Kubernetes| | 550|open-mmlab/Amphion !2025-03-28886911|Amphion (/æmˈfaɪən/) is a toolkit for Audio, Music, and Speech Generation. Its purpose is to support reproducible research and help junior researchers and engineers get started in the field of audio, music, and speech generation research and development.| | 551|gorse-io/gorse !2025-03-2888451|Gorse open source recommender system engine| | 552|adams549659584/go-proxy-bingai !2025-03-288768-1 |A Microsoft New Bing demo site built with Vue3 and Go, providing a consistent UI experience, supporting ChatGPT prompts, and accessible within China| | 553|open-mmlab/mmsegmentation !2025-03-2887513|OpenMMLab Semantic Segmentation Toolbox and Benchmark.| | 554|bytedance/monolith !2025-03-2887223|ByteDance's Recommendation System| | 555|LouisShark/chatgptsystemprompt !2025-03-2887216|store all agent's system prompt| | 556|brexhq/prompt-engineering !2025-03-2887080 |Tips and tricks for working with Large Language Models like OpenAI's GPT-4.| | 557|erincatto/box2d !2025-03-2886841|Box2D is a 2D physics engine for games| | 558|🔥microsoft/ai-agents-for-beginners !2025-03-288669323|10 Lessons to Get Started Building AI Agents| | 559|nashsu/FreeAskInternet !2025-03-2886102|FreeAskInternet is a completely free, private and locally running search aggregator & answer generate using LLM, without GPU needed. The user can ask a question and the system will make a multi engine search and combine the search result to the ChatGPT3.5 LLM and generate the answer based on search results.| | 560|goldmansachs/gs-quant !2025-03-2885981|Python toolkit for quantitative finance| | 561|srbhr/Resume-Matcher !2025-03-2885800|Open Source Free ATS Tool to compare Resumes with Job Descriptions and create a score to rank them.| | 562|facebookresearch/ImageBind !2025-03-2885681 |ImageBind One Embedding Space to Bind Them All| | 563|ashawkey/stable-dreamfusion !2025-03-2885481 |A pytorch implementation of text-to-3D dreamfusion, powered by stable diffusion.| | 564|meetecho/janus-gateway !2025-03-2885232|Janus WebRTC Server| | 565|google/magika !2025-03-2885003|Detect file content types with deep learning| | 566|huggingface/chat-ui !2025-03-2884871 |Open source codebase powering the HuggingChat app| | 567|EleutherAI/lm-evaluation-harness !2025-03-28843012|A framework for few-shot evaluation of autoregressive language models.| | 568|jina-ai/reader !2025-03-2884089|Convert any URL to an LLM-friendly input with a simple prefix https://r.jina.ai/| | 569|microsoft/TypeChat !2025-03-288406-1|TypeChat is a library that makes it easy to build natural language interfaces using types.| | 570|thuml/Time-Series-Library !2025-03-28839715|A Library for Advanced Deep Time Series Models.| | 571|OptimalScale/LMFlow !2025-03-2883882|An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Model for All.| | 572|baptisteArno/typebot.io !2025-03-2883845|💬 Typebot is a powerful chatbot builder that you can self-host.| | 573|jzhang38/TinyLlama !2025-03-2883504|The TinyLlama project is an open endeavor to pretrain a 1.1B Llama model on 3 trillion tokens.| | 574|fishaudio/Bert-VITS2 !2025-03-2883472|vits2 backbone with multilingual-bert| | 575|OpenBMB/XAgent !2025-03-2882683|An Autonomous LLM Agent for Complex Task Solving| | 576|Acly/krita-ai-diffusion !2025-03-2882387|Streamlined interface for generating images with AI in Krita. Inpaint and outpaint with optional text prompt, no tweaking required.| | 577|jasonppy/VoiceCraft !2025-03-2882151|Zero-Shot Speech Editing and Text-to-Speech in the Wild| | 578|SJTU-IPADS/PowerInfer !2025-03-2881693|High-speed Large Language Model Serving on PCs with Consumer-grade GPUs| | 579|modelscope/DiffSynth-Studio !2025-03-28814713|Enjoy the magic of Diffusion models!| | 580|o3de/o3de !2025-03-2881443|Open 3D Engine (O3DE) is an Apache 2.0-licensed multi-platform 3D engine that enables developers and content creators to build AAA games, cinema-quality 3D worlds, and high-fidelity simulations without any fees or commercial obligations.| | 581|zmh-program/chatnio !2025-03-2881325|🚀 Next Generation AI One-Stop Internationalization Solution. 🚀 下一代 AI 一站式 B/C 端解决方案,支持 OpenAI,Midjourney,Claude,讯飞星火,Stable Diffusion,DALL·E,ChatGLM,通义千问,腾讯混元,360 智脑,百川 AI,火山方舟,新必应,Gemini,Moonshot 等模型,支持对话分享,自定义预设,云端同步,模型市场,支持弹性计费和订阅计划模式,支持图片解析,支持联网搜索,支持模型缓存,丰富美观的后台管理与仪表盘数据统计。| | 582|leptonai/searchwithlepton !2025-03-2880632|Building a quick conversation-based search demo with Lepton AI.| | 583|sebastianstarke/AI4Animation !2025-03-2880620|Bringing Characters to Life with Computer Brains in Unity| | 584|wangrongding/wechat-bot !2025-03-2880528|🤖一个基于 WeChaty 结合 DeepSeek / ChatGPT / Kimi / 讯飞等Ai服务实现的微信机器人 ,可以用来帮助你自动回复微信消息,或者管理微信群/好友,检测僵尸粉等...| | 585|openvinotoolkit/openvino !2025-03-2880528|OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference| | 586|steven2358/awesome-generative-ai !2025-03-28802610|A curated list of modern Generative Artificial Intelligence projects and services| | 587|adam-maj/tiny-gpu !2025-03-2880234|A minimal GPU design in Verilog to learn how GPUs work from the ground up| | 588| anse-app/chatgpt-demo !2025-03-2880180 | A demo repo based on OpenAI API (gpt-3.5-turbo) | | 589| acheong08/EdgeGPT !2025-03-288015-1 |Reverse engineered API of Microsoft's Bing Chat | | 590|ai-collection/ai-collection !2025-03-2879994 |The Generative AI Landscape - A Collection of Awesome Generative AI Applications| | 591|GreyDGL/PentestGPT !2025-03-2879953 |A GPT-empowered penetration testing tool| | 592|delta-io/delta !2025-03-2879112|An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs| | 593|dataelement/bisheng !2025-03-2879085|Bisheng is an open LLM devops platform for next generation AI applications.| | 594|e2b-dev/e2b !2025-03-2878447 |Vercel for AI agents. We help developers to build, deploy, and monitor AI agents. Focusing on specialized AI agents that build software for you - your personal software developers.| | 595|01-ai/Yi !2025-03-2878311|A series of large language models trained from scratch by developers @01-ai| | 596|Plachtaa/VALL-E-X !2025-03-287830-1|An open source implementation of Microsoft's VALL-E X zero-shot TTS model. The demo is available at https://plachtaa.github.io| | 597|abhishekkrthakur/approachingalmost !2025-03-2878204|Approaching (Almost) Any Machine Learning Problem| | 598|pydantic/pydantic-ai !2025-03-28781041|Agent Framework / shim to use Pydantic with LLMs| | 599|rany2/edge-tts !2025-03-2877901|Use Microsoft Edge's online text-to-speech service from Python WITHOUT needing Microsoft Edge or Windows or an API key| | 600|CASIA-IVA-Lab/FastSAM !2025-03-2877881|Fast Segment Anything| | 601|netease-youdao/EmotiVoice !2025-03-2877817|EmotiVoice 😊: a Multi-Voice and Prompt-Controlled TTS Engine| | 602|lllyasviel/IC-Light !2025-03-2877804|More relighting!| | 603|kroma-network/tachyon !2025-03-287774-1|Modular ZK(Zero Knowledge) backend accelerated by GPU| | 604|deep-floyd/IF !2025-03-2877731 |A novel state-of-the-art open-source text-to-image model with a high degree of photorealism and language understanding| | 605|oumi-ai/oumi !2025-03-2877705|Everything you need to build state-of-the-art foundation models, end-to-end.| | 606|reorproject/reor !2025-03-2877681|AI note-taking app that runs models locally.| | 607|lightpanda-io/browser !2025-03-28775813|Lightpanda: the headless browser designed for AI and automation| | 608|xiangsx/gpt4free-ts !2025-03-287755-1|Providing a free OpenAI GPT-4 API ! This is a replication project for the typescript version of xtekky/gpt4free| | 609|IDEA-Research/GroundingDINO !2025-03-28773311|Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"| | 610|bunkerity/bunkerweb !2025-03-2877326|🛡️ Make your web services secure by default !| | 611|vikhyat/moondream !2025-03-2877057|tiny vision language model| | 612|firmai/financial-machine-learning !2025-03-287703-1|A curated list of practical financial machine learning tools and applications.| | 613|n8n-io/self-hosted-ai-starter-kit !2025-03-28765121|The Self-hosted AI Starter Kit is an open-source template that quickly sets up a local AI environment. Curated by n8n, it provides essential tools for creating secure, self-hosted AI workflows.| | 614|intel-analytics/ipex-llm !2025-03-2876507|Accelerate local LLM inference and finetuning (LLaMA, Mistral, ChatGLM, Qwen, Baichuan, Mixtral, Gemma, etc.) on Intel CPU and GPU (e.g., local PC with iGPU, discrete GPU such as Arc, Flex and Max). A PyTorch LLM library that seamlessly integrates with llama.cpp, HuggingFace, LangChain, LlamaIndex, DeepSpeed, vLLM, FastChat, ModelScope, etc.| | 615|jrouwe/JoltPhysics !2025-03-28764510|A multi core friendly rigid body physics and collision detection library. Written in C++. Suitable for games and VR applications. Used by Horizon Forbidden West.| | 616|THUDM/CodeGeeX2 !2025-03-2876270|CodeGeeX2: A More Powerful Multilingual Code Generation Model| | 617|meta-llama/llama-stack !2025-03-2875866|Composable building blocks to build Llama Apps| | 618|sweepai/sweep !2025-03-287530-1|Sweep is an AI junior developer| | 619|lllyasviel/Omost !2025-03-2875301|Your image is almost there!| | 620|ahmedbahaaeldin/From-0-to-Research-Scientist-resources-guide !2025-03-2875050|Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.| | 621|dair-ai/ML-Papers-Explained !2025-03-2875050|Explanation to key concepts in ML| | 622|zaidmukaddam/scira !2025-03-28750110|Scira (Formerly MiniPerplx) is a minimalistic AI-powered search engine that helps you find information on the internet. Powered by Vercel AI SDK! Search with models like Grok 2.0.| | 623|Portkey-AI/gateway !2025-03-28749416|A Blazing Fast AI Gateway. Route to 100+ LLMs with 1 fast & friendly API.| | 624|web-infra-dev/midscene !2025-03-28748729|An AI-powered automation SDK can control the page, perform assertions, and extract data in JSON format using natural language.| | 625|zilliztech/GPTCache !2025-03-2874801 |GPTCache is a library for creating semantic cache to store responses from LLM queries.| | 626|niedev/RTranslator !2025-03-2874742|RTranslator is the world's first open source real-time translation app.| |!green-up-arrow.svg 627|roboflow/notebooks !2025-03-2874666|Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.| |!red-down-arrow 628|openlm-research/openllama !2025-03-2874652|OpenLLaMA, a permissively licensed open source reproduction of Meta AI’s LLaMA 7B trained on the RedPajama dataset| | 629|LiheYoung/Depth-Anything !2025-03-2874155|Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data| | 630|enso-org/enso !2025-03-2874040|Hybrid visual and textual functional programming.| | 631|bigcode-project/starcoder !2025-03-287401-1 |Home of StarCoder: fine-tuning & inference!| | 632|git-ecosystem/git-credential-manager !2025-03-2873975|Secure, cross-platform Git credential storage with authentication to GitHub, Azure Repos, and other popular Git hosting services.| | 633|OpenGVLab/InternVL !2025-03-2873634|[CVPR 2024 Oral] InternVL Family: A Pioneering Open-Source Alternative to GPT-4V. 接近GPT-4V表现的可商用开源模型| | 634|WooooDyy/LLM-Agent-Paper-List !2025-03-2873551|The paper list of the 86-page paper "The Rise and Potential of Large Language Model Based Agents: A Survey" by Zhiheng Xi et al.| | 635|lencx/Noi !2025-03-2873157|🦄 AI + Tools + Plugins + Community| | 636|udlbook/udlbook !2025-03-2873075|Understanding Deep Learning - Simon J.D. Prince| | 637|OpenBMB/MiniCPM !2025-03-2872841|MiniCPM-2B: An end-side LLM outperforms Llama2-13B.| | 638|jaywalnut310/vits !2025-03-2872815 |VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech| | 639|xorbitsai/inference !2025-03-28727528|Replace OpenAI GPT with another LLM in your app by changing a single line of code. Xinference gives you the freedom to use any LLM you need. With Xinference, you're empowered to run inference with any open-source language models, speech recognition models, and multimodal models, whether in the cloud, on-premises, or even on your laptop.| | 640|PWhiddy/PokemonRedExperiments !2025-03-2872492|Playing Pokemon Red with Reinforcement Learning| | 641|Canner/WrenAI !2025-03-28723213|🤖 Open-source AI Agent that empowers data-driven teams to chat with their data to generate Text-to-SQL, charts, spreadsheets, reports, and BI. 📈📊📋🧑‍💻| | 642|miurla/morphic !2025-03-2872258|An AI-powered answer engine with a generative UI| | 643|ml-explore/mlx-examples !2025-03-2872168|Examples in the MLX framework| | 644|PKU-YuanGroup/ChatLaw !2025-03-2872010|Chinese Legal Large Model| | 645|NVIDIA/cutlass !2025-03-2871883|CUDA Templates for Linear Algebra Subroutines| | 646|FoundationVision/VAR !2025-03-28717444|[GPT beats diffusion🔥] [scaling laws in visual generation📈] Official impl. of "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction"| | 647|ymcui/Chinese-LLaMA-Alpaca-2 !2025-03-2871561|Chinese LLaMA-2 & Alpaca-2 LLMs| | 648|nadermx/backgroundremover !2025-03-2871514 |Background Remover lets you Remove Background from images and video using AI with a simple command line interface that is free and open source.| | 649|onuratakan/gpt-computer-assistant !2025-03-28714514|gpt-4o for windows, macos and ubuntu| | 650|graviraja/MLOps-Basics !2025-03-2871326|| | 651|Future-House/paper-qa !2025-03-287118-1|High accuracy RAG for answering questions from scientific documents with citations| | 652|open-mmlab/mmagic !2025-03-2871102 |OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox| | 653|bhaskatripathi/pdfGPT !2025-03-2870941 |PDF GPT allows you to chat with the contents of your PDF file by using GPT capabilities. The only open source solution to turn your pdf files in a chatbot!| | 654|ollama/ollama-python !2025-03-28709117|Ollama Python library| | 655|facebookresearch/DiT !2025-03-2870376|Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"| | 656|geekyutao/Inpaint-Anything !2025-03-2870262 |Inpaint anything using Segment Anything and inpainting models.| | 657|AbdullahAlfaraj/Auto-Photoshop-StableDiffusion-Plugin !2025-03-2870160 |A user-friendly plug-in that makes it easy to generate stable diffusion images inside Photoshop using Automatic1111-sd-webui as a backend.| | 658|apple/corenet !2025-03-2869990|CoreNet: A library for training deep neural networks| | 659|openstatusHQ/openstatus !2025-03-2869926|🏓 The open-source synthetic monitoring platform 🏓| | 660|weaviate/Verba !2025-03-2869772|Retrieval Augmented Generation (RAG) chatbot powered by Weaviate| | 661|meshery/meshery !2025-03-2869630|Meshery, the cloud native manager| | 662|OpenTalker/video-retalking !2025-03-2869530|[SIGGRAPH Asia 2022] VideoReTalking: Audio-based Lip Synchronization for Talking Head Video Editing In the Wild| | 663|digitalinnovationone/dio-lab-open-source !2025-03-28689013|Repositório do lab "Contribuindo em um Projeto Open Source no GitHub" da Digital Innovation One.| | 664|jianchang512/ChatTTS-ui !2025-03-2868842|一个简单的本地网页界面,直接使用ChatTTS将文字合成为语音,同时支持对外提供API接口。| | 665|patchy631/ai-engineering-hub !2025-03-28686434|In-depth tutorials on LLMs, RAGs and real-world AI agent applications.| | 666|gunnarmorling/1brc !2025-03-2868512|1️⃣🐝🏎️ The One Billion Row Challenge -- A fun exploration of how quickly 1B rows from a text file can be aggregated with Java| | 667|Azure-Samples/azure-search-openai-demo !2025-03-2868482 |A sample app for the Retrieval-Augmented Generation pattern running in Azure, using Azure Cognitive Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences.| | 668|mit-han-lab/streaming-llm !2025-03-2868382|Efficient Streaming Language Models with Attention Sinks| | 669|InternLM/InternLM !2025-03-2868352|InternLM has open-sourced a 7 billion parameter base model, a chat model tailored for practical scenarios and the training system.| | 670|dependency-check/DependencyCheck !2025-03-2868191|OWASP dependency-check is a software composition analysis utility that detects publicly disclosed vulnerabilities in application dependencies.| | 671|Soulter/AstrBot !2025-03-28678643|✨易上手的多平台 LLM 聊天机器人及开发框架✨。支持 QQ、QQ频道、Telegram、微信平台(Gewechat, 企业微信)、内置 Web Chat,OpenAI GPT、DeepSeek、Ollama、Llama、GLM、Gemini、OneAPI、LLMTuner,支持 LLM Agent 插件开发,可视化面板。一键部署。支持 Dify 工作流、代码执行器、Whisper 语音转文字。| | 672|react-native-webview/react-native-webview !2025-03-2867792|React Native Cross-Platform WebView| | 673|modelscope/agentscope !2025-03-28676916|Start building LLM-empowered multi-agent applications in an easier way.| | 674|mylxsw/aidea !2025-03-2867381|AIdea is a versatile app that supports GPT and domestic large language models,also supports "Stable Diffusion" text-to-image generation, image-to-image generation, SDXL 1.0, super-resolution, and image colorization| | 675|langchain-ai/ollama-deep-researcher !2025-03-28668635|Fully local web research and report writing assistant| | 676|threestudio-project/threestudio !2025-03-2866653|A unified framework for 3D content generation.| | 677|gaomingqi/Track-Anything !2025-03-2866631 |A flexible and interactive tool for video object tracking and segmentation, based on Segment Anything, XMem, and E2FGVI.| | 678|spdustin/ChatGPT-AutoExpert !2025-03-2866570|🚀🧠💬 Supercharged Custom Instructions for ChatGPT (non-coding) and ChatGPT Advanced Data Analysis (coding).| | 679|HariSekhon/DevOps-Bash-tools !2025-03-2866463|1000+ DevOps Bash Scripts - AWS, GCP, Kubernetes, Docker, CI/CD, APIs, SQL, PostgreSQL, MySQL, Hive, Impala, Kafka, Hadoop, Jenkins, GitHub, GitLab, BitBucket, Azure DevOps, TeamCity, Spotify, MP3, LDAP, Code/Build Linting, pkg mgmt for Linux, Mac, Python, Perl, Ruby, NodeJS, Golang, Advanced dotfiles: .bashrc, .vimrc, .gitconfig, .screenrc, tmux..| | 680|modelscope/swift !2025-03-28661530|ms-swift: Use PEFT or Full-parameter to finetune 200+ LLMs or 15+ MLLMs| | 681|langchain-ai/opengpts !2025-03-2866080|This is an open source effort to create a similar experience to OpenAI's GPTs and Assistants API| | 682| yihong0618/xiaogpt !2025-03-2865131 | Play ChatGPT with xiaomi ai speaker | | 683| civitai/civitai !2025-03-2865111 | Build a platform where people can share their stable diffusion models | | 684|KoljaB/RealtimeSTT !2025-03-28649513|A robust, efficient, low-latency speech-to-text library with advanced voice activity detection, wake word activation and instant transcription.| | 685|qunash/chatgpt-advanced !2025-03-2864910 | A browser extension that augments your ChatGPT prompts with web results.| | 686|Licoy/ChatGPT-Midjourney !2025-03-2864850|🎨 Own your own ChatGPT+Midjourney web service with one click| | 687|friuns2/BlackFriday-GPTs-Prompts !2025-03-2864744|List of free GPTs that doesn't require plus subscription| | 688|PixarAnimationStudios/OpenUSD !2025-03-2864700|Universal Scene Description| | 689|linyiLYi/street-fighter-ai !2025-03-2864630 |This is an AI agent for Street Fighter II Champion Edition.| | 690|run-llama/rags !2025-03-2864380|Build ChatGPT over your data, all with natural language| | 691|frdel/agent-zero !2025-03-2864154|Agent Zero AI framework| | 692|microsoft/DeepSpeedExamples !2025-03-2863911 |Example models using DeepSpeed| | 693|k8sgpt-ai/k8sgpt !2025-03-2863882|Giving Kubernetes Superpowers to everyone| | 694|open-metadata/OpenMetadata !2025-03-2863514|OpenMetadata is a unified platform for discovery, observability, and governance powered by a central metadata repository, in-depth lineage, and seamless team collaboration.| | 695|google/gemma.cpp !2025-03-2863163|lightweight, standalone C++ inference engine for Google's Gemma models.| | 696|RayVentura/ShortGPT !2025-03-286314-1|🚀🎬 ShortGPT - An experimental AI framework for automated short/video content creation. Enables creators to rapidly produce, manage, and deliver content using AI and automation.| | 697|openai/consistencymodels !2025-03-2862940 |Official repo for consistency models.| | 698|yangjianxin1/Firefly !2025-03-2862924|Firefly: Chinese conversational large language model (full-scale fine-tuning + QLoRA), supporting fine-tuning of Llma2, Llama, Baichuan, InternLM, Ziya, Bloom, and other large models| | 699|enricoros/big-AGI !2025-03-2862665|Generative AI suite powered by state-of-the-art models and providing advanced AI/AGI functions. It features AI personas, AGI functions, multi-model chats, text-to-image, voice, response streaming, code highlighting and execution, PDF import, presets for developers, much more. Deploy on-prem or in the cloud.| | 700|aptos-labs/aptos-core !2025-03-2862633|Aptos is a layer 1 blockchain built to support the widespread use of blockchain through better technology and user experience.| | 701|wenda-LLM/wenda !2025-03-286262-1 |Wenda: An LLM invocation platform. Its objective is to achieve efficient content generation tailored to specific environments while considering the limited computing resources of individuals and small businesses, as well as knowledge security and privacy concerns| | 702|Project-MONAI/MONAI !2025-03-2862603|AI Toolkit for Healthcare Imaging| | 703|HVision-NKU/StoryDiffusion !2025-03-2862470|Create Magic Story!| | 704|deepseek-ai/DeepSeek-LLM !2025-03-2862463|DeepSeek LLM: Let there be answers| | 705|Tohrusky/Final2x !2025-03-2862393|2^x Image Super-Resolution| | 706|OpenSPG/KAG !2025-03-28619611|KAG is a logical form-guided reasoning and retrieval framework based on OpenSPG engine and LLMs. It is used to build logical reasoning and factual Q&A solutions for professional domain knowledge bases. It can effectively overcome the shortcomings of the traditional RAG vector similarity calculation model.| | 707|Moonvy/OpenPromptStudio !2025-03-2861861 |AIGC Hint Word Visualization Editor| | 708|levihsu/OOTDiffusion !2025-03-2861761|Official implementation of OOTDiffusion| | 709|tmc/langchaingo !2025-03-2861729|LangChain for Go, the easiest way to write LLM-based programs in Go| | 710|vladmandic/automatic !2025-03-2861374|SD.Next: Advanced Implementation of Stable Diffusion and other Diffusion-based generative image models| | 711|clovaai/donut !2025-03-2861231 |Official Implementation of OCR-free Document Understanding Transformer (Donut) and Synthetic Document Generator (SynthDoG), ECCV 2022| | 712|Shaunwei/RealChar !2025-03-286121-1|🎙️🤖Create, Customize and Talk to your AI Character/Companion in Realtime(All in One Codebase!). Have a natural seamless conversation with AI everywhere(mobile, web and terminal) using LLM OpenAI GPT3.5/4, Anthropic Claude2, Chroma Vector DB, Whisper Speech2Text, ElevenLabs Text2Speech🎙️🤖| | 713|microsoft/TinyTroupe !2025-03-2861142|LLM-powered multiagent persona simulation for imagination enhancement and business insights.| | 714| rustformers/llm !2025-03-2861010 | Run inference for Large Language Models on CPU, with Rust| | 715|firebase/firebase-ios-sdk !2025-03-2860950|Firebase SDK for Apple App Development| | 716|vespa-engine/vespa !2025-03-2860824|The open big data serving engine. https://vespa.ai| | 717|n4ze3m/page-assist !2025-03-28607610|Use your locally running AI models to assist you in your web browsing| | 718|Dooy/chatgpt-web-midjourney-proxy !2025-03-2860646|chatgpt web, midjourney, gpts,tts, whisper 一套ui全搞定| | 719|ethereum-optimism/optimism !2025-03-2860213|Optimism is Ethereum, scaled.| | 720|sczhou/ProPainter !2025-03-2859971|[ICCV 2023] ProPainter: Improving Propagation and Transformer for Video Inpainting| | 721|MineDojo/Voyager !2025-03-2859951 |An Open-Ended Embodied Agent with Large Language Models| | 722|lavague-ai/LaVague !2025-03-2859800|Automate automation with Large Action Model framework| | 723|SevaSk/ecoute !2025-03-2859770 |Ecoute is a live transcription tool that provides real-time transcripts for both the user's microphone input (You) and the user's speakers output (Speaker) in a textbox. It also generates a suggested response using OpenAI's GPT-3.5 for the user to say based on the live transcription of the conversation.| | 724|google/mesop !2025-03-2859661|| | 725|pengxiao-song/LaWGPT !2025-03-2859542 |Repo for LaWGPT, Chinese-Llama tuned with Chinese Legal knowledge| | 726|fr0gger/Awesome-GPT-Agents !2025-03-2859434|A curated list of GPT agents for cybersecurity| | 727|google-deepmind/graphcast !2025-03-2859412|| | 728|comet-ml/opik !2025-03-28594126|Open-source end-to-end LLM Development Platform| | 729|SciPhi-AI/R2R !2025-03-28594033|A framework for rapid development and deployment of production-ready RAG systems| | 730|SkalskiP/courses !2025-03-2859272 |This repository is a curated collection of links to various courses and resources about Artificial Intelligence (AI)| | 731|QuivrHQ/MegaParse !2025-03-2859122|File Parser optimised for LLM Ingestion with no loss 🧠 Parse PDFs, Docx, PPTx in a format that is ideal for LLMs.| | 732|pytorch-labs/gpt-fast !2025-03-2858971|Simple and efficient pytorch-native transformer text generation in !2025-03-2858886|Curated list of chatgpt prompts from the top-rated GPTs in the GPTs Store. Prompt Engineering, prompt attack & prompt protect. Advanced Prompt Engineering papers.| | 734|nilsherzig/LLocalSearch !2025-03-2858852|LLocalSearch is a completely locally running search aggregator using LLM Agents. The user can ask a question and the system will use a chain of LLMs to find the answer. The user can see the progress of the agents and the final answer. No OpenAI or Google API keys are needed.| | 735|kuafuai/DevOpsGPT !2025-03-285874-2|Multi agent system for AI-driven software development. Convert natural language requirements into working software. Supports any development language and extends the existing base code.| | 736|myshell-ai/MeloTTS !2025-03-2858486|High-quality multi-lingual text-to-speech library by MyShell.ai. Support English, Spanish, French, Chinese, Japanese and Korean.| | 737|OpenGVLab/LLaMA-Adapter !2025-03-2858421 |Fine-tuning LLaMA to follow Instructions within 1 Hour and 1.2M Parameters| | 738|volcengine/verl !2025-03-28582563|veRL: Volcano Engine Reinforcement Learning for LLM| | 739|a16z-infra/companion-app !2025-03-2858171|AI companions with memory: a lightweight stack to create and host your own AI companions| | 740|HumanAIGC/OutfitAnyone !2025-03-285816-1|Outfit Anyone: Ultra-high quality virtual try-on for Any Clothing and Any Person| | 741|josStorer/RWKV-Runner !2025-03-2857472|A RWKV management and startup tool, full automation, only 8MB. And provides an interface compatible with the OpenAI API. RWKV is a large language model that is fully open source and available for commercial use.| | 742|648540858/wvp-GB28181-pro !2025-03-2857414|WEB VIDEO PLATFORM是一个基于GB28181-2016标准实现的网络视频平台,支持NAT穿透,支持海康、大华、宇视等品牌的IPC、NVR、DVR接入。支持国标级联,支持rtsp/rtmp等视频流转发到国标平台,支持rtsp/rtmp等推流转发到国标平台。| | 743|ToonCrafter/ToonCrafter !2025-03-2857345|a research paper for generative cartoon interpolation| | 744|PawanOsman/ChatGPT !2025-03-2857191|OpenAI API Free Reverse Proxy| | 745|apache/hudi !2025-03-2857091|Upserts, Deletes And Incremental Processing on Big Data.| | 746| nsarrazin/serge !2025-03-2857081 | A web interface for chatting with Alpaca through llama.cpp. Fully dockerized, with an easy to use API| | 747|homanp/superagent !2025-03-2857021|🥷 Superagent - Build, deploy, and manage LLM-powered agents| | 748|ramonvc/freegpt-webui !2025-03-2856910|GPT 3.5/4 with a Chat Web UI. No API key is required.| | 749|baichuan-inc/baichuan-7B !2025-03-2856901|A large-scale 7B pretraining language model developed by BaiChuan-Inc.| | 750|Azure/azure-sdk-for-net !2025-03-2856792|This repository is for active development of the Azure SDK for .NET. For consumers of the SDK we recommend visiting our public developer docs at https://learn.microsoft.com/dotnet/azure/ or our versioned developer docs at https://azure.github.io/azure-sdk-for-net.| | 751|mnotgod96/AppAgent !2025-03-2856643|AppAgent: Multimodal Agents as Smartphone Users, an LLM-based multimodal agent framework designed to operate smartphone apps.| | 752|microsoft/TaskWeaver !2025-03-2856243|A code-first agent framework for seamlessly planning and executing data analytics tasks.| | 753| yetone/bob-plugin-openai-translator !2025-03-285600-1 | A Bob Plugin base ChatGPT API | | 754|PrefectHQ/marvin !2025-03-2855840 |A batteries-included library for building AI-powered software| | 755|microsoft/promptbase !2025-03-2855832|All things prompt engineering| | 756|fullstackhero/dotnet-starter-kit !2025-03-2855560|Production Grade Cloud-Ready .NET 8 Starter Kit (Web API + Blazor Client) with Multitenancy Support, and Clean/Modular Architecture that saves roughly 200+ Development Hours! All Batteries Included.| | 757|deepseek-ai/DeepSeek-Coder-V2 !2025-03-2855435|DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence| | 758|aiwaves-cn/agents !2025-03-2855391|An Open-source Framework for Autonomous Language Agents| | 759|microsoft/Mastering-GitHub-Copilot-for-Paired-Programming !2025-03-2855158|A 6 Lesson course teaching everything you need to know about harnessing GitHub Copilot and an AI Paired Programing resource.| | 760|allenai/OLMo !2025-03-2854506|Modeling, training, eval, and inference code for OLMo| | 761|apify/crawlee-python !2025-03-2854493|Crawlee—A web scraping and browser automation library for Python to build reliable crawlers. Extract data for AI, LLMs, RAG, or GPTs. Download HTML, PDF, JPG, PNG, and other files from websites. Works with BeautifulSoup, Playwright, and raw HTTP. Both headful and headless mode. With proxy rotation.| | 762|k2-fsa/sherpa-onnx !2025-03-28541520|Speech-to-text, text-to-speech, and speaker recongition using next-gen Kaldi with onnxruntime without Internet connection. Support embedded systems, Android, iOS, Raspberry Pi, RISC-V, x86_64 servers, websocket server/client, C/C++, Python, Kotlin, C#, Go, NodeJS, Java, Swift| | 763|TEN-framework/TEN-Agent !2025-03-28541411|TEN Agent is a realtime conversational AI agent powered by TEN. It seamlessly integrates the OpenAI Realtime API, RTC capabilities, and advanced features like weather updates, web search, computer vision, and Retrieval-Augmented Generation (RAG).| | 764|google/gemmapytorch !2025-03-2854010|The official PyTorch implementation of Google's Gemma models| | 765|snakers4/silero-vad !2025-03-2853858|Silero VAD: pre-trained enterprise-grade Voice Activity Detector| | 766|livekit/agents !2025-03-2853836|Build real-time multimodal AI applications 🤖🎙️📹| | 767|pipecat-ai/pipecat !2025-03-28537811|Open Source framework for voice and multimodal conversational AI| | 768|EricLBuehler/mistral.rs !2025-03-28536324|Blazingly fast LLM inference.| | 769|asg017/sqlite-vec !2025-03-28535810|Work-in-progress vector search SQLite extension that runs anywhere.| | 770|albertan017/LLM4Decompile !2025-03-2853563|Reverse Engineering: Decompiling Binary Code with Large Language Models| | 771|Permify/permify !2025-03-2853235|An open-source authorization as a service inspired by Google Zanzibar, designed to build and manage fine-grained and scalable authorization systems for any application.| | 772|imoneoi/openchat !2025-03-2853171|OpenChat: Advancing Open-source Language Models with Imperfect Data| | 773|mosaicml/composer !2025-03-2853140|Train neural networks up to 7x faster| | 774|dsdanielpark/Bard-API !2025-03-285277-1 |The python package that returns a response of Google Bard through API.| | 775|lxfater/inpaint-web !2025-03-2852552|A free and open-source inpainting & image-upscaling tool powered by webgpu and wasm on the browser。| | 776|leanprover/lean4 !2025-03-2852441|Lean 4 programming language and theorem prover| | 777|AILab-CVC/YOLO-World !2025-03-2852415|Real-Time Open-Vocabulary Object Detection| | 778|openchatai/OpenChat !2025-03-2852260 |Run and create custom ChatGPT-like bots with OpenChat, embed and share these bots anywhere, the open-source chatbot console.| | 779|mufeedvh/code2prompt !2025-03-28519414|A CLI tool to convert your codebase into a single LLM prompt with source tree, prompt templating, and token counting.| | 780|biobootloader/wolverine !2025-03-2851700 |Automatically repair python scripts through GPT-4 to give them regenerative abilities.| | 781|huggingface/parler-tts !2025-03-2851671|Inference and training library for high-quality TTS models.| | 782|Akegarasu/lora-scripts !2025-03-2851308 |LoRA training scripts use kohya-ss's trainer, for diffusion model.| | 783|openchatai/OpenCopilot !2025-03-285128-3|🤖 🔥 Let your users chat with your product features and execute things by text - open source Shopify sidekick| | 784|e2b-dev/fragments !2025-03-2851228|Open-source Next.js template for building apps that are fully generated by AI. By E2B.| | 785|microsoft/SynapseML !2025-03-2851132|Simple and Distributed Machine Learning| | 786|aigc-apps/sd-webui-EasyPhoto !2025-03-285108-1|📷 EasyPhoto | | 787|ChaoningZhang/MobileSAM !2025-03-2850944|This is the official code for Faster Segment Anything (MobileSAM) project that makes SAM lightweight| | 788|huggingface/alignment-handbook !2025-03-2850932|Robust recipes for to align language models with human and AI preferences| | 789|alpkeskin/mosint !2025-03-2850920|An automated e-mail OSINT tool| | 790|TaskingAI/TaskingAI !2025-03-2850891|The open source platform for AI-native application development.| | 791|lipku/metahuman-stream !2025-03-28507615|Real time interactive streaming digital human| | 792|OpenInterpreter/01 !2025-03-2850530|The open-source language model computer| | 793|open-compass/opencompass !2025-03-28505111|OpenCompass is an LLM evaluation platform, supporting a wide range of models (InternLM2,GPT-4,LLaMa2, Qwen,GLM, Claude, etc) over 100+ datasets.| | 794|xxlong0/Wonder3D !2025-03-2850491|A cross-domain diffusion model for 3D reconstruction from a single image| | 795|pytorch/torchtune !2025-03-2850342|A Native-PyTorch Library for LLM Fine-tuning| | 796|SuperDuperDB/superduperdb !2025-03-2850192|🔮 SuperDuperDB: Bring AI to your database: Integrate, train and manage any AI models and APIs directly with your database and your data.| | 797|WhiskeySockets/Baileys !2025-03-2850057|Lightweight full-featured typescript/javascript WhatsApp Web API| | 798| mpociot/chatgpt-vscode !2025-03-2849890 | A VSCode extension that allows you to use ChatGPT | | 799|OpenGVLab/DragGAN !2025-03-2849880|Unofficial Implementation of DragGAN - "Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold" (DragGAN 全功能实现,在线Demo,本地部署试用,代码、模型已全部开源,支持Windows, macOS, Linux)| | 800|microsoft/LLMLingua !2025-03-2849824|To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss.| | 801|Zipstack/unstract !2025-03-2849745|No-code LLM Platform to launch APIs and ETL Pipelines to structure unstructured documents| | 802|OpenBMB/ToolBench !2025-03-2849621|An open platform for training, serving, and evaluating large language model for tool learning.| | 803|Fanghua-Yu/SUPIR !2025-03-2849593|SUPIR aims at developing Practical Algorithms for Photo-Realistic Image Restoration In the Wild| | 804|GaiaNet-AI/gaianet-node !2025-03-2849360|Install and run your own AI agent service| | 805|qodo-ai/qodo-cover !2025-03-284922-1|Qodo-Cover: An AI-Powered Tool for Automated Test Generation and Code Coverage Enhancement! 💻🤖🧪🐞| | 806|Zejun-Yang/AniPortrait !2025-03-2849042|AniPortrait: Audio-Driven Synthesis of Photorealistic Portrait Animation| | 807|lvwzhen/law-cn-ai !2025-03-2848901 |⚖️ AI Legal Assistant| | 808|developersdigest/llm-answer-engine !2025-03-2848740|Build a Perplexity-Inspired Answer Engine Using Next.js, Groq, Mixtral, Langchain, OpenAI, Brave & Serper| | 809|Plachtaa/VITS-fast-fine-tuning !2025-03-2848640|This repo is a pipeline of VITS finetuning for fast speaker adaptation TTS, and many-to-many voice conversion| | 810|espeak-ng/espeak-ng !2025-03-2848601|eSpeak NG is an open source speech synthesizer that supports more than hundred languages and accents.| | 811|ant-research/CoDeF !2025-03-2848581|[CVPR'24 Highlight] Official PyTorch implementation of CoDeF: Content Deformation Fields for Temporally Consistent Video Processing| | 812|deepseek-ai/DeepSeek-V2 !2025-03-2848512|| | 813|XRPLF/rippled !2025-03-2848210|Decentralized cryptocurrency blockchain daemon implementing the XRP Ledger protocol in C++| | 814|AutoMQ/automq !2025-03-28478721|AutoMQ is a cloud-first alternative to Kafka by decoupling durability to S3 and EBS. 10x cost-effective. Autoscale in seconds. Single-digit ms latency.| | 815|AILab-CVC/VideoCrafter !2025-03-2847800|VideoCrafter1: Open Diffusion Models for High-Quality Video Generation| | 816|nautechsystems/nautilustrader !2025-03-2847702|A high-performance algorithmic trading platform and event-driven backtester| | 817|kyegomez/swarms !2025-03-2847563|The Enterprise-Grade Production-Ready Multi-Agent Orchestration Framework Join our Community: https://discord.com/servers/agora-999382051935506503| | 818|Deci-AI/super-gradients !2025-03-2847310 |Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.| | 819|QwenLM/Qwen2.5-Coder !2025-03-2847236|Qwen2.5-Coder is the code version of Qwen2.5, the large language model series developed by Qwen team, Alibaba Cloud.| | 820|SCIR-HI/Huatuo-Llama-Med-Chinese !2025-03-2847191 |Repo for HuaTuo (华驼), Llama-7B tuned with Chinese medical knowledge| | 821|togethercomputer/RedPajama-Data !2025-03-2846841 |code for preparing large datasets for training large language models| | 822|mishushakov/llm-scraper !2025-03-2846704|Turn any webpage into structured data using LLMs| | 823|1rgs/jsonformer !2025-03-2846663 |A Bulletproof Way to Generate Structured JSON from Language Models| | 824|anti-work/shortest !2025-03-2846565|QA via natural language AI tests| | 825|dnhkng/GlaDOS !2025-03-2846510|This is the Personality Core for GLaDOS, the first steps towards a real-life implementation of the AI from the Portal series by Valve.| | 826|Nukem9/dlssg-to-fsr3 !2025-03-2846380|Adds AMD FSR3 Frame Generation to games by replacing Nvidia DLSS-G Frame Generation (nvngx_dlssg).| | 827|BuilderIO/ai-shell !2025-03-2846373 |A CLI that converts natural language to shell commands.| | 828|facebookincubator/AITemplate !2025-03-2846220 |AITemplate is a Python framework which renders neural network into high performance CUDA/HIP C++ code. Specialized for FP16 TensorCore (NVIDIA GPU) and MatrixCore (AMD GPU) inference.| | 829|terraform-aws-modules/terraform-aws-eks !2025-03-2846030|Terraform module to create AWS Elastic Kubernetes (EKS) resources 🇺🇦| | 830|timescale/pgai !2025-03-2845915|A suite of tools to develop RAG, semantic search, and other AI applications more easily with PostgreSQL| | 831|awslabs/multi-agent-orchestrator !2025-03-2845788|Flexible and powerful framework for managing multiple AI agents and handling complex conversations| | 832|sanchit-gandhi/whisper-jax !2025-03-2845771 |Optimised JAX code for OpenAI's Whisper Model, largely built on the Hugging Face Transformers Whisper implementation| | 833|NVIDIA/NeMo-Guardrails !2025-03-2845755|NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.| | 834|PathOfBuildingCommunity/PathOfBuilding !2025-03-2845480|Offline build planner for Path of Exile.| | 835|UX-Decoder/Segment-Everything-Everywhere-All-At-Once !2025-03-2845412 |Official implementation of the paper "Segment Everything Everywhere All at Once"| | 836|build-trust/ockam !2025-03-2845171|Orchestrate end-to-end encryption, cryptographic identities, mutual authentication, and authorization policies between distributed applications – at massive scale.| | 837|google-research/timesfm !2025-03-2845135|TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.| | 838|luosiallen/latent-consistency-model !2025-03-2844842|Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference| | 839|NVlabs/neuralangelo !2025-03-2844740|Official implementation of "Neuralangelo: High-Fidelity Neural Surface Reconstruction" (CVPR 2023)| | 840|kyegomez/tree-of-thoughts !2025-03-2844720 |Plug in and Play Implementation of Tree of Thoughts: Deliberate Problem Solving with Large Language Models that Elevates Model Reasoning by atleast 70%| | 841|sjvasquez/handwriting-synthesis !2025-03-2844720 |Handwriting Synthesis with RNNs ✏️| | 842| madawei2699/myGPTReader !2025-03-2844420 | A slack bot that can read any webpage, ebook or document and summarize it with chatGPT | | 843|OpenBMB/AgentVerse !2025-03-2844413|🤖 AgentVerse 🪐 provides a flexible framework that simplifies the process of building custom multi-agent environments for large language models (LLMs).| | 844|argmaxinc/WhisperKit !2025-03-2844395|Swift native speech recognition on-device for iOS and macOS applications.| | 845|landing-ai/vision-agent !2025-03-2844346|Vision agent| | 846|InternLM/xtuner !2025-03-2844273|An efficient, flexible and full-featured toolkit for fine-tuning large models (InternLM, Llama, Baichuan, Qwen, ChatGLM)| | 847|google-deepmind/alphageometry !2025-03-284421-1|Solving Olympiad Geometry without Human Demonstrations| | 848|ostris/ai-toolkit !2025-03-2844093|Various AI scripts. Mostly Stable Diffusion stuff.| | 849|LLM-Red-Team/kimi-free-api !2025-03-2844004|🚀 KIMI AI 长文本大模型白嫖服务,支持高速流式输出、联网搜索、长文档解读、图像解析、多轮对话,零配置部署,多路token支持,自动清理会话痕迹。| | 850|argilla-io/argilla !2025-03-2843991|Argilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency.| | 851|spring-projects/spring-ai !2025-03-28438419|An Application Framework for AI Engineering| | 852|alibaba-damo-academy/FunClip !2025-03-2843555|Open-source, accurate and easy-to-use video clipping tool, LLM based AI clipping intergrated | | 853|yisol/IDM-VTON !2025-03-2843541|IDM-VTON : Improving Diffusion Models for Authentic Virtual Try-on in the Wild| | 854|fchollet/ARC-AGI !2025-03-2843368|The Abstraction and Reasoning Corpus| | 855|MahmoudAshraf97/whisper-diarization !2025-03-2843064|Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper| | 856|Speykious/cve-rs !2025-03-2843047|Blazingly 🔥 fast 🚀 memory vulnerabilities, written in 100% safe Rust. 🦀| | 857|Blealtan/efficient-kan !2025-03-2842770|An efficient pure-PyTorch implementation of Kolmogorov-Arnold Network (KAN).| | 858|smol-ai/GodMode !2025-03-284249-1|AI Chat Browser: Fast, Full webapp access to ChatGPT / Claude / Bard / Bing / Llama2! I use this 20 times a day.| | 859|openai/plugins-quickstart !2025-03-284235-4 |Get a ChatGPT plugin up and running in under 5 minutes!| | 860|Doriandarko/maestro !2025-03-2842260|A framework for Claude Opus to intelligently orchestrate subagents.| | 861|philz1337x/clarity-upscaler !2025-03-2842204|Clarity-Upscaler: Reimagined image upscaling for everyone| | 862|facebookresearch/co-tracker !2025-03-2842142|CoTracker is a model for tracking any point (pixel) on a video.| | 863|xlang-ai/OpenAgents !2025-03-2842031|OpenAgents: An Open Platform for Language Agents in the Wild| | 864|alibaba/higress !2025-03-28419514|🤖 AI Gateway | | 865|ray-project/llm-numbers !2025-03-2841920 |Numbers every LLM developer should know| | 866|fudan-generative-vision/champ !2025-03-2841820|Champ: Controllable and Consistent Human Image Animation with 3D Parametric Guidance| | 867|NVIDIA/garak !2025-03-2841795|the LLM vulnerability scanner| | 868|leetcode-mafia/cheetah !2025-03-2841740 |Whisper & GPT-based app for passing remote SWE interviews| | 869|ragapp/ragapp !2025-03-2841710|The easiest way to use Agentic RAG in any enterprise| | 870|collabora/WhisperSpeech !2025-03-2841692|An Open Source text-to-speech system built by inverting Whisper.| | 871|Facico/Chinese-Vicuna !2025-03-2841520 |Chinese-Vicuna: A Chinese Instruction-following LLaMA-based Model| | 872|openai/grok !2025-03-2841381|| | 873|CrazyBoyM/llama3-Chinese-chat !2025-03-2841361|Llama3 Chinese Repository with modified versions, and training and deployment resources| | 874|luban-agi/Awesome-AIGC-Tutorials !2025-03-2841301|Curated tutorials and resources for Large Language Models, AI Painting, and more.| | 875|damo-vilab/AnyDoor !2025-03-2841192|Official implementations for paper: Anydoor: zero-shot object-level image customization| | 876|raspberrypi/pico-sdk !2025-03-2841072|| | 877|mshumer/gpt-llm-trainer !2025-03-284097-1|| | 878|metavoiceio/metavoice-src !2025-03-284076-1|AI for human-level speech intelligence| | 879|intelowlproject/IntelOwl !2025-03-2840763|IntelOwl: manage your Threat Intelligence at scale| | 880|a16z-infra/ai-getting-started !2025-03-2840682|A Javascript AI getting started stack for weekend projects, including image/text models, vector stores, auth, and deployment configs| | 881|MarkFzp/mobile-aloha !2025-03-2840641|Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation| | 882| keijiro/AICommand !2025-03-2840380 | ChatGPT integration with Unity Editor | | 883|Tencent/HunyuanDiT !2025-03-2840214|Hunyuan-DiT : A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding| | 884|hengyoush/kyanos !2025-03-2840061|Visualize the time packets spend in the kernel, watch & analyze in command line.| | 885|agiresearch/AIOS !2025-03-2840045|AIOS: LLM Agent Operating System| | 886|truefoundry/cognita !2025-03-2839773|RAG (Retrieval Augmented Generation) Framework for building modular, open source applications for production by TrueFoundry| | 887|X-PLUG/MobileAgent !2025-03-2839557|Mobile-Agent: Autonomous Multi-Modal Mobile Device Agent with Visual Perception| | 888|jackMort/ChatGPT.nvim !2025-03-2839231|ChatGPT Neovim Plugin: Effortless Natural Language Generation with OpenAI's ChatGPT API| | 889|microsoft/RD-Agent !2025-03-28388422|Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automate these high-value generic R&D processes through our open source R&D automation tool RD-Agent, which let AI drive data-driven AI.| | 890|Significant-Gravitas/Auto-GPT-Plugins !2025-03-283882-1 |Plugins for Auto-GPT| | 891|apple/ml-mgie !2025-03-2838770|| | 892|OpenDriveLab/UniAD !2025-03-2838727|[CVPR 2023 Best Paper] Planning-oriented Autonomous Driving| | 893|llSourcell/DoctorGPT !2025-03-2838640|DoctorGPT is an LLM that can pass the US Medical Licensing Exam. It works offline, it's cross-platform, & your health data stays private.| | 894|FlagAI-Open/FlagAI !2025-03-2838601|FlagAI (Fast LArge-scale General AI models) is a fast, easy-to-use and extensible toolkit for large-scale model.| | 895|krishnaik06/Roadmap-To-Learn-Generative-AI-In-2024 !2025-03-2838513|Roadmap To Learn Generative AI In 2024| | 896|SysCV/sam-hq !2025-03-2838491|Segment Anything in High Quality| | 897|google/security-research !2025-03-2838420|This project hosts security advisories and their accompanying proof-of-concepts related to research conducted at Google which impact non-Google owned code.| | 898|shroominic/codeinterpreter-api !2025-03-2838330|Open source implementation of the ChatGPT Code Interpreter 👾| | 899|Yonom/assistant-ui !2025-03-2838308|React Components for AI Chat 💬 🚀| | 900|nucleuscloud/neosync !2025-03-2838262|Open source data anonymization and synthetic data orchestration for developers. Create high fidelity synthetic data and sync it across your environments.| | 901|ravenscroftj/turbopilot !2025-03-2838230 |Turbopilot is an open source large-language-model based code completion engine that runs locally on CPU| | 902|NVlabs/Sana !2025-03-28380810|SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformer| | 903|huggingface/distil-whisper !2025-03-2838061|Distilled variant of Whisper for speech recognition. 6x faster, 50% smaller, within 1% word error rate.| | 904|Codium-ai/AlphaCodium !2025-03-2837971|code generation tool that surpasses most human competitors in CodeContests| | 905|fixie-ai/ultravox !2025-03-2837710|A fast multimodal LLM for real-time voice| | 906|unit-mesh/auto-dev !2025-03-28375715|🧙‍AutoDev: The AI-powered coding wizard with multilingual support 🌐, auto code generation 🏗️, and a helpful bug-slaying assistant 🐞! Customizable prompts 🎨 and a magic Auto Dev/Testing/Document/Agent feature 🧪 included! 🚀| | 907|Marker-Inc-Korea/AutoRAG !2025-03-2837432|AutoML tool for RAG| | 908|deepseek-ai/DeepSeek-VL !2025-03-283734-1|DeepSeek-VL: Towards Real-World Vision-Language Understanding| | 909|hiyouga/ChatGLM-Efficient-Tuning !2025-03-283692-1|Fine-tuning ChatGLM-6B with PEFT | | 910| Yue-Yang/ChatGPT-Siri !2025-03-2836921 | Shortcuts for Siri using ChatGPT API gpt-3.5-turbo model | | 911|0hq/WebGPT !2025-03-2836901 |Run GPT model on the browser with WebGPU. An implementation of GPT inference in less than ~2000 lines of vanilla Javascript.| | 912|cvg/LightGlue !2025-03-2836903|LightGlue: Local Feature Matching at Light Speed (ICCV 2023)| | 913|deanxv/coze-discord-proxy !2025-03-2836791|代理Discord-Bot对话Coze-Bot,实现API形式请求GPT4对话模型/微调模型| | 914|MervinPraison/PraisonAI !2025-03-2836764|PraisonAI application combines AutoGen and CrewAI or similar frameworks into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customisation, and efficient human-agent collaboration.| | 915|Ironclad/rivet !2025-03-2836345 |The open-source visual AI programming environment and TypeScript library| | 916|BasedHardware/OpenGlass !2025-03-2835851|Turn any glasses into AI-powered smart glasses| | 917|ricklamers/gpt-code-ui !2025-03-2835840 |An open source implementation of OpenAI's ChatGPT Code interpreter| | 918|whoiskatrin/chart-gpt !2025-03-2835830 |AI tool to build charts based on text input| | 919|github/CopilotForXcode !2025-03-2835788|Xcode extension for GitHub Copilot| | 920|hemansnation/God-Level-Data-Science-ML-Full-Stack !2025-03-2835570 |A collection of scientific methods, processes, algorithms, and systems to build stories & models. This roadmap contains 16 Chapters, whether you are a fresher in the field or an experienced professional who wants to transition into Data Science & AI| | 921|pytorch/torchchat !2025-03-2835461|Run PyTorch LLMs locally on servers, desktop and mobile| | 922| Kent0n-Li/ChatDoctor !2025-03-2835451 | A Medical Chat Model Fine-tuned on LLaMA Model using Medical Domain Knowledge | | 923|xtekky/chatgpt-clone !2025-03-283519-1 |ChatGPT interface with better UI| | 924|jupyterlab/jupyter-ai !2025-03-2835120|A generative AI extension for JupyterLab| | 925|pytorch/torchtitan !2025-03-2835064|A native PyTorch Library for large model training| | 926|minimaxir/simpleaichat !2025-03-2835031|Python package for easily interfacing with chat apps, with robust features and minimal code complexity.| | 927|srush/Tensor-Puzzles !2025-03-2834930|Solve puzzles. Improve your pytorch.| | 928|Helicone/helicone !2025-03-2834918|🧊 Open source LLM-Observability Platform for Developers. One-line integration for monitoring, metrics, evals, agent tracing, prompt management, playground, etc. Supports OpenAI SDK, Vercel AI SDK, Anthropic SDK, LiteLLM, LLamaIndex, LangChain, and more. 🍓 YC W23| | 929|run-llama/llama-hub !2025-03-2834740|A library of data loaders for LLMs made by the community -- to be used with LlamaIndex and/or LangChain| | 930|NExT-GPT/NExT-GPT !2025-03-2834700|Code and models for NExT-GPT: Any-to-Any Multimodal Large Language Model| | 931|souzatharsis/podcastfy !2025-03-2834661|An Open Source Python alternative to NotebookLM's podcast feature: Transforming Multimodal Content into Captivating Multilingual Audio Conversations with GenAI| | 932|Dataherald/dataherald !2025-03-2834450|Interact with your SQL database, Natural Language to SQL using LLMs| | 933|iryna-kondr/scikit-llm !2025-03-2834350 |Seamlessly integrate powerful language models like ChatGPT into scikit-learn for enhanced text analysis tasks.| | 934|Netflix/maestro !2025-03-2834230|Maestro: Netflix’s Workflow Orchestrator| | 935|CanadaHonk/porffor !2025-03-2833560|A from-scratch experimental AOT JS engine, written in JS| | 936|hustvl/Vim !2025-03-2833323|Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model| | 937|pashpashpash/vault-ai !2025-03-2833250 |OP Vault ChatGPT: Give ChatGPT long-term memory using the OP Stack (OpenAI + Pinecone Vector Database). Upload your own custom knowledge base files (PDF, txt, etc) using a simple React frontend.| | 938|tencentmusic/supersonic !2025-03-28330611|SuperSonic is the next-generation BI platform that integrates Chat BI (powered by LLM) and Headless BI (powered by semantic layer) paradigms.| | 939|billmei/every-chatgpt-gui !2025-03-2832981|Every front-end GUI client for ChatGPT| | 940|microsoft/torchgeo !2025-03-2832772|TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data| | 941|LLMBook-zh/LLMBook-zh.github.io !2025-03-28326110|《大语言模型》作者:赵鑫,李军毅,周昆,唐天一,文继荣| | 942|dvlab-research/MiniGemini !2025-03-2832601|Official implementation for Mini-Gemini| | 943|rashadphz/farfalle !2025-03-2832460|🔍 AI search engine - self-host with local or cloud LLMs| | 944|Luodian/Otter !2025-03-2832450|🦦 Otter, a multi-modal model based on OpenFlamingo (open-sourced version of DeepMind's Flamingo), trained on MIMIC-IT and showcasing improved instruction-following and in-context learning ability.| | 945|AprilNEA/ChatGPT-Admin-Web !2025-03-2832370 | ChatGPT WebUI with user management and admin dashboard system| | 946|MarkFzp/act-plus-plus !2025-03-2832365|Imitation Learning algorithms with Co-traing for Mobile ALOHA: ACT, Diffusion Policy, VINN| | 947|ethen8181/machine-learning !2025-03-2832310|🌎 machine learning tutorials (mainly in Python3)| | 948|opengeos/segment-geospatial !2025-03-2832312 |A Python package for segmenting geospatial data with the Segment Anything Model (SAM)| | 949|iusztinpaul/hands-on-llms !2025-03-283225-2|🦖 𝗟𝗲𝗮𝗿𝗻 about 𝗟𝗟𝗠𝘀, 𝗟𝗟𝗠𝗢𝗽𝘀, and 𝘃𝗲𝗰𝘁𝗼𝗿 𝗗𝗕𝘀 for free by designing, training, and deploying a real-time financial advisor LLM system ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 𝘷𝘪𝘥𝘦𝘰 & 𝘳𝘦𝘢𝘥𝘪𝘯𝘨 𝘮𝘢𝘵𝘦𝘳𝘪𝘢𝘭𝘴| | 950|ToTheBeginning/PuLID !2025-03-2832221|Official code for PuLID: Pure and Lightning ID Customization via Contrastive Alignment| | 951|neo4j-labs/llm-graph-builder !2025-03-2832164|Neo4j graph construction from unstructured data using LLMs| | 952|OpenGVLab/InternGPT !2025-03-2832150 |InternGPT (iGPT) is an open source demo platform where you can easily showcase your AI models. Now it supports DragGAN, ChatGPT, ImageBind, multimodal chat like GPT-4, SAM, interactive image editing, etc. Try it at igpt.opengvlab.com (支持DragGAN、ChatGPT、ImageBind、SAM的在线Demo系统)| | 953|PKU-YuanGroup/Video-LLaVA !2025-03-2832060 |Video-LLaVA: Learning United Visual Representation by Alignment Before Projection| | 954|DataTalksClub/llm-zoomcamp !2025-03-2832030|LLM Zoomcamp - a free online course about building an AI bot that can answer questions about your knowledge base| | 955|gptscript-ai/gptscript !2025-03-2832010|Natural Language Programming| |!green-up-arrow.svg 956|isaac-sim/IsaacLab !2025-03-28320113|Unified framework for robot learning built on NVIDIA Isaac Sim| |!red-down-arrow 957|ai-boost/Awesome-GPTs !2025-03-2832003|Curated list of awesome GPTs 👍.| | 958|huggingface/safetensors !2025-03-2831901|Simple, safe way to store and distribute tensors| | 959|linyiLYi/bilibot !2025-03-2831771|A local chatbot fine-tuned by bilibili user comments.| | 960| project-baize/baize-chatbot !2025-03-283168-1 | Let ChatGPT teach your own chatbot in hours with a single GPU! | | 961|Azure-Samples/cognitive-services-speech-sdk !2025-03-2831280|Sample code for the Microsoft Cognitive Services Speech SDK| | 962|microsoft/Phi-3CookBook !2025-03-2831231|This is a Phi-3 book for getting started with Phi-3. Phi-3, a family of open AI models developed by Microsoft. Phi-3 models are the most capable and cost-effective small language models (SLMs) available, outperforming models of the same size and next size up across a variety of language, reasoning, coding, and math benchmarks.| | 963|neuralmagic/deepsparse !2025-03-2831180|Sparsity-aware deep learning inference runtime for CPUs| | 964|sugarforever/chat-ollama !2025-03-2831000|ChatOllama is an open source chatbot based on LLMs. It supports a wide range of language models, and knowledge base management.| | 965|amazon-science/chronos-forecasting !2025-03-2830974|Chronos: Pretrained (Language) Models for Probabilistic Time Series Forecasting| | 966|damo-vilab/i2vgen-xl !2025-03-2830902|Official repo for VGen: a holistic video generation ecosystem for video generation building on diffusion models| | 967|google-deepmind/gemma !2025-03-2830733|Open weights LLM from Google DeepMind.| | 968|iree-org/iree !2025-03-2830733|A retargetable MLIR-based machine learning compiler and runtime toolkit.| | 969|NVlabs/VILA !2025-03-2830724|VILA - a multi-image visual language model with training, inference and evaluation recipe, deployable from cloud to edge (Jetson Orin and laptops)| | 970|microsoft/torchscale !2025-03-2830661|Foundation Architecture for (M)LLMs| | 971|openai/openai-realtime-console !2025-03-2830656|React app for inspecting, building and debugging with the Realtime API| | 972|daveshap/OpenAIAgentSwarm !2025-03-2830610|HAAS = Hierarchical Autonomous Agent Swarm - "Resistance is futile!"| | 973|microsoft/PromptWizard !2025-03-2830555|Task-Aware Agent-driven Prompt Optimization Framework| | 974|CVI-SZU/Linly !2025-03-2830490 |Chinese-LLaMA basic model; ChatFlow Chinese conversation model; NLP pre-training/command fine-tuning dataset| | 975|cohere-ai/cohere-toolkit !2025-03-2830130|Toolkit is a collection of prebuilt components enabling users to quickly build and deploy RAG applications.| | 976|adamcohenhillel/ADeus !2025-03-2830131|An open source AI wearable device that captures what you say and hear in the real world and then transcribes and stores it on your own server. You can then chat with Adeus using the app, and it will have all the right context about what you want to talk about - a truly personalized, personal AI.| | 977|Lightning-AI/LitServe !2025-03-2830132|Lightning-fast serving engine for AI models. Flexible. Easy. Enterprise-scale.| | 978|potpie-ai/potpie !2025-03-2829973|Prompt-To-Agent : Create custom engineering agents for your codebase| | 979|ant-design/x !2025-03-28299529|Craft AI-driven interfaces effortlessly 🤖| | 980|meta-llama/PurpleLlama !2025-03-2829832|Set of tools to assess and improve LLM security.| | 981|williamyang1991/RerenderAVideo !2025-03-2829800|[SIGGRAPH Asia 2023] Rerender A Video: Zero-Shot Text-Guided Video-to-Video Translation| | 982|baichuan-inc/Baichuan-13B !2025-03-2829790|A 13B large language model developed by Baichuan Intelligent Technology| | 983|Stability-AI/stable-audio-tools !2025-03-2829761|Generative models for conditional audio generation| | 984|li-plus/chatglm.cpp !2025-03-2829720|C++ implementation of ChatGLM-6B & ChatGLM2-6B & ChatGLM3 & more LLMs| | 985|NVIDIA/GenerativeAIExamples !2025-03-2829546|Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.| | 986|Josh-XT/AGiXT !2025-03-2829521 |AGiXT is a dynamic AI Automation Platform that seamlessly orchestrates instruction management and complex task execution across diverse AI providers. Combining adaptive memory, smart features, and a versatile plugin system, AGiXT delivers efficient and comprehensive AI solutions.| | 987|MrForExample/ComfyUI-3D-Pack !2025-03-2829515|An extensive node suite that enables ComfyUI to process 3D inputs (Mesh & UV Texture, etc) using cutting edge algorithms (3DGS, NeRF, etc.)| | 988|olimorris/codecompanion.nvim !2025-03-28295111|✨ AI-powered coding, seamlessly in Neovim. Supports Anthropic, Copilot, Gemini, Ollama, OpenAI and xAI LLMs| | 989|salesforce/CodeT5 !2025-03-282940-1 |Home of CodeT5: Open Code LLMs for Code Understanding and Generation| | 990|facebookresearch/ijepa !2025-03-2829391|Official codebase for I-JEPA, the Image-based Joint-Embedding Predictive Architecture. First outlined in the CVPR paper, "Self-supervised learning from images with a joint-embedding predictive architecture."| | 991|eureka-research/Eureka !2025-03-2829351|Official Repository for "Eureka: Human-Level Reward Design via Coding Large Language Models"| | 992|NVIDIA/trt-llm-rag-windows !2025-03-282934-1|A developer reference project for creating Retrieval Augmented Generation (RAG) chatbots on Windows using TensorRT-LLM| | 993|gmpetrov/databerry !2025-03-282930-1|The no-code platform for building custom LLM Agents| | 994|AI4Finance-Foundation/FinRobot !2025-03-28291946|FinRobot: An Open-Source AI Agent Platform for Financial Applications using LLMs 🚀 🚀 🚀| | 995|nus-apr/auto-code-rover !2025-03-2829013|A project structure aware autonomous software engineer aiming for autonomous program improvement| | 996|deepseek-ai/DreamCraft3D !2025-03-2828921|[ICLR 2024] Official implementation of DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior| | 997|mlabonne/llm-datasets !2025-03-2828848|High-quality datasets, tools, and concepts for LLM fine-tuning.| | 998|facebookresearch/jepa !2025-03-2828712|PyTorch code and models for V-JEPA self-supervised learning from video.| | 999|facebookresearch/habitat-sim !2025-03-2828604|A flexible, high-performance 3D simulator for Embodied AI research.| | 1000|xenova/whisper-web !2025-03-2828581|ML-powered speech recognition directly in your browser| | 1001|cvlab-columbia/zero123 !2025-03-2828530|Zero-1-to-3: Zero-shot One Image to 3D Object: https://zero123.cs.columbia.edu/| | 1002|yuruotong1/autoMate !2025-03-28285121|Like Manus, Computer Use Agent(CUA) and Omniparser, we are computer-using agents.AI-driven local automation assistant that uses natural language to make computers work by themselves| | 1003|muellerberndt/mini-agi !2025-03-282845-1 |A minimal generic autonomous agent based on GPT3.5/4. Can analyze stock prices, perform network security tests, create art, and order pizza.| | 1004|allenai/open-instruct !2025-03-2828432|| | 1005|CodingChallengesFYI/SharedSolutions !2025-03-2828360|Publicly shared solutions to Coding Challenges| | 1006|hegelai/prompttools !2025-03-2828220|Open-source tools for prompt testing and experimentation, with support for both LLMs (e.g. OpenAI, LLaMA) and vector databases (e.g. Chroma, Weaviate).| | 1007|mazzzystar/Queryable !2025-03-2828222|Run CLIP on iPhone to Search Photos.| | 1008|Doubiiu/DynamiCrafter !2025-03-2828173|DynamiCrafter: Animating Open-domain Images with Video Diffusion Priors| | 1009|SamurAIGPT/privateGPT !2025-03-282805-1 |An app to interact privately with your documents using the power of GPT, 100% privately, no data leaks| | 1010|facebookresearch/Pearl !2025-03-2827951|A Production-ready Reinforcement Learning AI Agent Library brought by the Applied Reinforcement Learning team at Meta.| | 1011|intuitem/ciso-assistant-community !2025-03-2827954|CISO Assistant is a one-stop-shop for GRC, covering Risk, AppSec and Audit Management and supporting +70 frameworks worldwide with auto-mapping: NIST CSF, ISO 27001, SOC2, CIS, PCI DSS, NIS2, CMMC, PSPF, GDPR, HIPAA, Essential Eight, NYDFS-500, DORA, NIST AI RMF, 800-53, 800-171, CyFun, CJIS, AirCyber, NCSC, ECC, SCF and so much more| | 1012|facebookresearch/audio2photoreal !2025-03-2827840|Code and dataset for photorealistic Codec Avatars driven from audio| | 1013|Azure/azure-rest-api-specs !2025-03-2827770|The source for REST API specifications for Microsoft Azure.| | 1014|SCUTlihaoyu/open-chat-video-editor !2025-03-2827690 |Open source short video automatic generation tool| | 1015|Alpha-VLLM/LLaMA2-Accessory !2025-03-2827642|An Open-source Toolkit for LLM Development| | 1016|johnma2006/mamba-minimal !2025-03-2827601|Simple, minimal implementation of the Mamba SSM in one file of PyTorch.| | 1017|nerfstudio-project/gsplat !2025-03-2827576|CUDA accelerated rasterization of gaussian splatting| | 1018|Physical-Intelligence/openpi !2025-03-28274617|| | 1019|leptonai/leptonai !2025-03-2827246|A Pythonic framework to simplify AI service building| |!green-up-arrow.svg 1020|joanrod/star-vector !2025-03-28271149|StarVector is a foundation model for SVG generation that transforms vectorization into a code generation task. Using a vision-language modeling architecture, StarVector processes both visual and textual inputs to produce high-quality SVG code with remarkable precision.| |!red-down-arrow 1021|jqnatividad/qsv !2025-03-2827092|CSVs sliced, diced & analyzed.| | 1022|FranxYao/chain-of-thought-hub !2025-03-2826991|Benchmarking large language models' complex reasoning ability with chain-of-thought prompting| | 1023|princeton-nlp/SWE-bench !2025-03-2826965|[ICLR 2024] SWE-Bench: Can Language Models Resolve Real-world Github Issues?| | 1024|elastic/otel-profiling-agent !2025-03-2826930|The production-scale datacenter profiler| | 1025|src-d/hercules !2025-03-2826900|Gaining advanced insights from Git repository history.| | 1026|lanqian528/chat2api !2025-03-2826695|A service that can convert ChatGPT on the web to OpenAI API format.| | 1027|ishan0102/vimGPT !2025-03-2826681|Browse the web with GPT-4V and Vimium| | 1028|TMElyralab/MuseV !2025-03-2826650|MuseV: Infinite-length and High Fidelity Virtual Human Video Generation with Visual Conditioned Parallel Denoising| | 1029|georgia-tech-db/eva !2025-03-2826600 |AI-Relational Database System | | 1030|kubernetes-sigs/controller-runtime !2025-03-2826590|Repo for the controller-runtime subproject of kubebuilder (sig-apimachinery)| | 1031|gptlink/gptlink !2025-03-2826550 |Build your own free commercial ChatGPT environment in 10 minutes. The setup is simple and includes features such as user management, orders, tasks, and payments| | 1032|pytorch/executorch !2025-03-2826534|On-device AI across mobile, embedded and edge for PyTorch| | 1033|NVIDIA/nv-ingest !2025-03-2826290|NVIDIA Ingest is an early access set of microservices for parsing hundreds of thousands of complex, messy unstructured PDFs and other enterprise documents into metadata and text to embed into retrieval systems.| | 1034|SuperTux/supertux !2025-03-2826081|SuperTux source code| | 1035|abi/secret-llama !2025-03-2826050|Fully private LLM chatbot that runs entirely with a browser with no server needed. Supports Mistral and LLama 3.| | 1036|liou666/polyglot !2025-03-2825841 |Desktop AI Language Practice Application| | 1037|janhq/nitro !2025-03-2825821|A fast, lightweight, embeddable inference engine to supercharge your apps with local AI. OpenAI-compatible API| | 1038|deepseek-ai/DeepSeek-Math !2025-03-2825825|DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models| | 1039|anthropics/prompt-eng-interactive-tutorial !2025-03-2825781|Anthropic's Interactive Prompt Engineering Tutorial| | 1040|microsoft/promptbench !2025-03-2825741|A unified evaluation framework for large language models| | 1041|baaivision/Painter !2025-03-2825580 |Painter & SegGPT Series: Vision Foundation Models from BAAI| | 1042|OpenPipe/OpenPipe !2025-03-2825581|Turn expensive prompts into cheap fine-tuned models| | 1043|TracecatHQ/tracecat !2025-03-2825531|😼 The AI-native, open source alternative to Tines / Splunk SOAR.| | 1044|JoshuaC215/agent-service-toolkit !2025-03-2825528|Full toolkit for running an AI agent service built with LangGraph, FastAPI and Streamlit| | 1045|databricks/dbrx !2025-03-2825460|Code examples and resources for DBRX, a large language model developed by Databricks| | 1046|lamini-ai/lamini !2025-03-2825271 |Official repo for Lamini's data generator for generating instructions to train instruction-following LLMs| | 1047|mshumer/gpt-author !2025-03-282510-1|| | 1048|TMElyralab/MusePose !2025-03-2824971|MusePose: a Pose-Driven Image-to-Video Framework for Virtual Human Generation| | 1049|Kludex/fastapi-tips !2025-03-2824974|FastAPI Tips by The FastAPI Expert!| | 1050|openai/simple-evals !2025-03-2824813|| | 1051|iterative/datachain !2025-03-2824732|AI-data warehouse to enrich, transform and analyze data from cloud storages| | 1052|girafe-ai/ml-course !2025-03-2824703|Open Machine Learning course| | 1053|kevmo314/magic-copy !2025-03-2824620 |Magic Copy is a Chrome extension that uses Meta's Segment Anything Model to extract a foreground object from an image and copy it to the clipboard.| | 1054|Eladlev/AutoPrompt !2025-03-2824432|A framework for prompt tuning using Intent-based Prompt Calibration| | 1055|OpenBMB/CPM-Bee !2025-03-282434-1 |A bilingual large-scale model with trillions of parameters| | 1056|IDEA-Research/T-Rex !2025-03-2824310|T-Rex2: Towards Generic Object Detection via Text-Visual Prompt Synergy| | 1057|microsoft/genaiscript !2025-03-2824202|Automatable GenAI Scripting| | 1058|paulpierre/RasaGPT !2025-03-2824090 |💬 RasaGPT is the first headless LLM chatbot platform built on top of Rasa and Langchain. Built w/ Rasa, FastAPI, Langchain, LlamaIndex, SQLModel, pgvector, ngrok, telegram| | 1059|ashishpatel26/LLM-Finetuning !2025-03-2823911|LLM Finetuning with peft| | 1060|SoraWebui/SoraWebui !2025-03-2823570|SoraWebui is an open-source Sora web client, enabling users to easily create videos from text with OpenAI's Sora model.| | 1061|6drf21e/ChatTTScolab !2025-03-2823491|🚀 一键部署(含离线整合包)!基于 ChatTTS ,支持音色抽卡、长音频生成和分角色朗读。简单易用,无需复杂安装。| | 1062|Azure/PyRIT !2025-03-2823343|The Python Risk Identification Tool for generative AI (PyRIT) is an open access automation framework to empower security professionals and machine learning engineers to proactively find risks in their generative AI systems.| | 1063|tencent-ailab/V-Express !2025-03-2823201|V-Express aims to generate a talking head video under the control of a reference image, an audio, and a sequence of V-Kps images.| | 1064|THUDM/CogVLM2 !2025-03-2823170|GPT4V-level open-source multi-modal model based on Llama3-8B| | 1065|dvmazur/mixtral-offloading !2025-03-2823001|Run Mixtral-8x7B models in Colab or consumer desktops| | 1066|semanser/codel !2025-03-2822950|✨ Fully autonomous AI Agent that can perform complicated tasks and projects using terminal, browser, and editor.| | 1067|mshumer/gpt-investor !2025-03-2822590|| | 1068|aixcoder-plugin/aiXcoder-7B !2025-03-2822550|official repository of aiXcoder-7B Code Large Language Model| | 1069|Azure-Samples/graphrag-accelerator !2025-03-2822503|One-click deploy of a Knowledge Graph powered RAG (GraphRAG) in Azure| | 1070|emcf/engshell !2025-03-2821830 |An English-language shell for any OS, powered by LLMs| | 1071|hncboy/chatgpt-web-java !2025-03-2821771|ChatGPT project developed in Java, based on Spring Boot 3 and JDK 17, supports both AccessToken and ApiKey modes| | 1072|openai/consistencydecoder !2025-03-2821692|Consistency Distilled Diff VAE| | 1073|Alpha-VLLM/Lumina-T2X !2025-03-2821681|Lumina-T2X is a unified framework for Text to Any Modality Generation| | 1074|bghira/SimpleTuner !2025-03-2821612|A general fine-tuning kit geared toward Stable Diffusion 2.1, Stable Diffusion 3, DeepFloyd, and SDXL.| | 1075|JiauZhang/DragGAN !2025-03-2821530 |Implementation of DragGAN: Interactive Point-based Manipulation on the Generative Image Manifold| | 1076|cgpotts/cs224u !2025-03-2821390|Code for Stanford CS224u| | 1077|PKU-YuanGroup/MoE-LLaVA !2025-03-2821300|Mixture-of-Experts for Large Vision-Language Models| | 1078|darrenburns/elia !2025-03-2820831|A snappy, keyboard-centric terminal user interface for interacting with large language models. Chat with ChatGPT, Claude, Llama 3, Phi 3, Mistral, Gemma and more.| | 1079|ageerle/ruoyi-ai !2025-03-28207898|RuoYi AI 是一个全栈式 AI 开发平台,旨在帮助开发者快速构建和部署个性化的 AI 应用。| | 1080|NVIDIA/gpu-operator !2025-03-2820510|NVIDIA GPU Operator creates/configures/manages GPUs atop Kubernetes| | 1081|BAAI-Agents/Cradle !2025-03-2820481|The Cradle framework is a first attempt at General Computer Control (GCC). Cradle supports agents to ace any computer task by enabling strong reasoning abilities, self-improvment, and skill curation, in a standardized general environment with minimal requirements.| | 1082|microsoft/aici !2025-03-2820080|AICI: Prompts as (Wasm) Programs| | 1083|PRIS-CV/DemoFusion !2025-03-2820040|Let us democratise high-resolution generation! (arXiv 2023)| | 1084|apple/axlearn !2025-03-2820012|An Extensible Deep Learning Library| | 1085|naver/mast3r !2025-03-2819685|Grounding Image Matching in 3D with MASt3R| | 1086|liltom-eth/llama2-webui !2025-03-281958-1|Run Llama 2 locally with gradio UI on GPU or CPU from anywhere (Linux/Windows/Mac). Supporting Llama-2-7B/13B/70B with 8-bit, 4-bit. Supporting GPU inference (6 GB VRAM) and CPU inference.| | 1087|GaParmar/img2img-turbo !2025-03-2819582|One-step image-to-image with Stable Diffusion turbo: sketch2image, day2night, and more| | 1088|Niek/chatgpt-web !2025-03-2819560|ChatGPT web interface using the OpenAI API| | 1089|huggingface/cookbook !2025-03-2819421|Open-source AI cookbook| | 1090|pytorch/ao !2025-03-2819241|PyTorch native quantization and sparsity for training and inference| | 1091|emcie-co/parlant !2025-03-2819053|The behavior guidance framework for customer-facing LLM agents| | 1092|ymcui/Chinese-LLaMA-Alpaca-3 !2025-03-2818980|中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3| | 1093|Nutlope/notesGPT !2025-03-2818811|Record voice notes & transcribe, summarize, and get tasks| | 1094|InstantStyle/InstantStyle !2025-03-2818791|InstantStyle: Free Lunch towards Style-Preserving in Text-to-Image Generation 🔥| | 1095|idaholab/moose !2025-03-2818771|Multiphysics Object Oriented Simulation Environment| | 1096|The-OpenROAD-Project/OpenROAD !2025-03-2818351|OpenROAD's unified application implementing an RTL-to-GDS Flow. Documentation at https://openroad.readthedocs.io/en/latest/| | 1097|alibaba/spring-ai-alibaba !2025-03-281831121|Agentic AI Framework for Java Developers| | 1098|ytongbai/LVM !2025-03-2817990|Sequential Modeling Enables Scalable Learning for Large Vision Models| | 1099|microsoft/sample-app-aoai-chatGPT !2025-03-2817981|[PREVIEW] Sample code for a simple web chat experience targeting chatGPT through AOAI.| | 1100|AI-Citizen/SolidGPT !2025-03-2817830|Chat everything with your code repository, ask repository level code questions, and discuss your requirements. AI Scan and learning your code repository, provide you code repository level answer🧱 🧱| | 1101|YangLing0818/RPG-DiffusionMaster !2025-03-2817784|Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs (PRG)| | 1102|kyegomez/BitNet !2025-03-2817710|Implementation of "BitNet: Scaling 1-bit Transformers for Large Language Models" in pytorch| | 1103|eloialonso/diamond !2025-03-2817671|DIAMOND (DIffusion As a Model Of eNvironment Dreams) is a reinforcement learning agent trained in a diffusion world model.| | 1104|flowdriveai/flowpilot !2025-03-2817250|flow-pilot is an openpilot based driver assistance system that runs on linux, windows and android powered machines.| | 1105|xlang-ai/OSWorld !2025-03-2817200|OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments| | 1106|linyiLYi/snake-ai !2025-03-2817031|An AI agent that beats the classic game "Snake".| | 1107|baaivision/Emu !2025-03-2816991|Emu Series: Generative Multimodal Models from BAAI| | 1108|kevmo314/scuda !2025-03-2816870|SCUDA is a GPU over IP bridge allowing GPUs on remote machines to be attached to CPU-only machines.| | 1109|SharifiZarchi/IntroductiontoMachineLearning !2025-03-2816701|دوره‌ی مقدمه‌ای بر یادگیری ماشین، برای دانشجویان| | 1110|google/maxtext !2025-03-2816670|A simple, performant and scalable Jax LLM!| | 1111|ml-explore/mlx-swift-examples !2025-03-2816471|Examples using MLX Swift| | 1112|unitreerobotics/unitreerlgym !2025-03-2816256|| | 1113|collabora/WhisperFusion !2025-03-2815901|WhisperFusion builds upon the capabilities of WhisperLive and WhisperSpeech to provide a seamless conversations with an AI.| | 1114|lichao-sun/Mora !2025-03-2815520|Mora: More like Sora for Generalist Video Generation| | 1115|GoogleCloudPlatform/localllm !2025-03-2815370|Run LLMs locally on Cloud Workstations| | 1116|TencentARC/BrushNet !2025-03-2815330|The official implementation of paper "BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion"| | 1117|ai-christianson/RA.Aid !2025-03-2815288|Develop software autonomously.| | 1118|stephansturges/WALDO !2025-03-2815170|Whereabouts Ascertainment for Low-lying Detectable Objects. The SOTA in FOSS AI for drones!| | 1119|skills/copilot-codespaces-vscode !2025-03-2815112|Develop with AI-powered code suggestions using GitHub Copilot and VS Code| | 1120|andrewnguonly/Lumos !2025-03-2814920|A RAG LLM co-pilot for browsing the web, powered by local LLMs| | 1121|TeamNewPipe/NewPipeExtractor !2025-03-2814811|NewPipe's core library for extracting data from streaming sites| | 1122|mhamilton723/FeatUp !2025-03-2814770|Official code for "FeatUp: A Model-Agnostic Frameworkfor Features at Any Resolution" ICLR 2024| | 1123|AnswerDotAI/fsdpqlora !2025-03-2814671|Training LLMs with QLoRA + FSDP| | 1124|jgravelle/AutoGroq !2025-03-2814330|| | 1125|OpenGenerativeAI/llm-colosseum !2025-03-2814130|Benchmark LLMs by fighting in Street Fighter 3! The new way to evaluate the quality of an LLM| | 1126|microsoft/vscode-ai-toolkit !2025-03-2814000|| | 1127|McGill-NLP/webllama !2025-03-2813930|Llama-3 agents that can browse the web by following instructions and talking to you| | 1128|lucidrains/self-rewarding-lm-pytorch !2025-03-2813760|Implementation of the training framework proposed in Self-Rewarding Language Model, from MetaAI| | 1129|ishaan1013/sandbox !2025-03-2813650|A cloud-based code editing environment with an AI copilot and real-time collaboration.| | 1130|goatcorp/Dalamud !2025-03-2813275|FFXIV plugin framework and API| | 1131|Lightning-AI/lightning-thunder !2025-03-2813151|Make PyTorch models Lightning fast! Thunder is a source to source compiler for PyTorch. It enables using different hardware executors at once.| | 1132|PKU-YuanGroup/MagicTime !2025-03-2813052|MagicTime: Time-lapse Video Generation Models as Metamorphic Simulators| | 1133|SakanaAI/evolutionary-model-merge !2025-03-2813000|Official repository of Evolutionary Optimization of Model Merging Recipes| | 1134|a-real-ai/pywinassistant !2025-03-2812950|The first open source Large Action Model generalist Artificial Narrow Intelligence that controls completely human user interfaces by only using natural language. PyWinAssistant utilizes Visualization-of-Thought Elicits Spatial Reasoning in Large Language Models.| | 1135|TraceMachina/nativelink !2025-03-2812630|NativeLink is an open source high-performance build cache and remote execution server, compatible with Bazel, Buck2, Reclient, and other RBE-compatible build systems. It offers drastically faster builds, reduced test flakiness, and significant infrastructure cost savings.| | 1136|MLSysOps/MLE-agent !2025-03-2812500|🤖 MLE-Agent: Your intelligent companion for seamless AI engineering and research. 🔍 Integrate with arxiv and paper with code to provide better code/research plans 🧰 OpenAI, Ollama, etc supported. 🎆 Code RAG| | 1137|wpilibsuite/allwpilib !2025-03-2811610|Official Repository of WPILibJ and WPILibC| | 1138|elfvingralf/macOSpilot-ai-assistant !2025-03-2811470|Voice + Vision powered AI assistant that answers questions about any application, in context and in audio.| | 1139|langchain-ai/langchain-extract !2025-03-2811210|🦜⛏️ Did you say you like data?| | 1140|FoundationVision/GLEE !2025-03-2811120|【CVPR2024】GLEE: General Object Foundation Model for Images and Videos at Scale| | 1141|Profluent-AI/OpenCRISPR !2025-03-2810990|AI-generated gene editing systems| | 1142|zju3dv/EasyVolcap !2025-03-2810821|[SIGGRAPH Asia 2023 (Technical Communications)] EasyVolcap: Accelerating Neural Volumetric Video Research| | 1143|PaddlePaddle/PaddleHelix !2025-03-2810560|Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集| | 1144|myshell-ai/JetMoE !2025-03-289800|Reaching LLaMA2 Performance with 0.1M Dollars| | 1145|likejazz/llama3.np !2025-03-289770|llama3.np is pure NumPy implementation for Llama 3 model.| | 1146|mustafaaljadery/gemma-2B-10M !2025-03-289500|Gemma 2B with 10M context length using Infini-attention.| | 1147|HITsz-TMG/FilmAgent !2025-03-289382|Resources of our paper "FilmAgent: A Multi-Agent Framework for End-to-End Film Automation in Virtual 3D Spaces". New versions in the making!| | 1148|aws-samples/amazon-bedrock-samples !2025-03-289362|This repository contains examples for customers to get started using the Amazon Bedrock Service. This contains examples for all available foundational models| | 1149|Akkudoktor-EOS/EOS !2025-03-2893154|This repository features an Energy Optimization System (EOS) that optimizes energy distribution, usage for batteries, heat pumps& household devices. It includes predictive models for electricity prices (planned), load forecasting& dynamic optimization to maximize energy efficiency & minimize costs. Founder Dr. Andreas Schmitz (YouTube @akkudoktor)| Tip: | symbol| rule | | :----| :---- | |🔥 | 256 1k| |!green-up-arrow.svg !red-down-arrow | ranking up / down| |⭐ | on trending page today| [Back to Top] Tools | No. | Tool | Description | | ----:|:----------------------------------------------- |:------------------------------------------------------------------------------------------- | | 1 | ChatGPT | A sibling model to InstructGPT, which is trained to follow instructions in a prompt and provide a detailed response | | 2 | DALL·E 2 | Create original, realistic images and art from a text description | | 3 | Murf AI | AI enabled, real people's voices| | 4 | Midjourney | An independent research lab that produces an artificial intelligence program under the same name that creates images from textual descriptions, used in Discord | 5 | Make-A-Video | Make-A-Video is a state-of-the-art AI system that generates videos from text | | 6 | Creative Reality™ Studio by D-ID| Use generative AI to create future-facing videos| | 7 | chat.D-ID| The First App Enabling Face-to-Face Conversations with ChatGPT| | 8 | Notion AI| Access the limitless power of AI, right inside Notion. Work faster. Write better. Think bigger. | | 9 | Runway| Text to Video with Gen-2 | | 10 | Resemble AI| Resemble’s AI voice generator lets you create human–like voice overs in seconds | | 11 | Cursor| Write, edit, and chat about your code with a powerful AI | | 12 | Hugging Face| Build, train and deploy state of the art models powered by the reference open source in machine learning | | 13 | Claude | A next-generation AI assistant for your tasks, no matter the scale | | 14 | Poe| Poe lets you ask questions, get instant answers, and have back-and-forth conversations with AI. Gives access to GPT-4, gpt-3.5-turbo, Claude from Anthropic, and a variety of other bots| [Back to Top] Websites | No. | WebSite |Description | | ----:|:------------------------------------------ |:---------------------------------------------------------------------------------------- | | 1 | OpenAI | An artificial intelligence research lab | | 2 | Bard | Base Google's LaMDA chatbots and pull from internet | | 3 | ERNIE Bot | Baidu’s new generation knowledge-enhanced large language model is a new member of the Wenxin large model family | | 4 | DALL·E 2 | An AI system that can create realistic images and art from a description in natural language | | 5 | Whisper | A general-purpose speech recognition model | | 6| CivitAI| A platform that makes it easy for people to share and discover resources for creating AI art| | 7|D-ID| D-ID’s Generative AI enables users to transform any picture or video into extraordinary experiences| | 8| Nvidia eDiff-I| Text-to-Image Diffusion Models with Ensemble of Expert Denoisers | | 9| Stability AI| The world's leading open source generative AI company which opened source Stable Diffusion | | 10| Meta AI| Whether it be research, product or infrastructure development, we’re driven to innovate responsibly with AI to benefit the world | | 11| ANTHROPIC| AI research and products that put safety at the frontier | [Back to Top] Reports&Papers | No. | Report&Paper | Description | |:---- |:-------------------------------------------------------------------------------------------------------------- |:---------------------------------------------------- | | 1 | GPT-4 Technical Report | GPT-4 Technical Report | | 2 | mli/paper-reading | Deep learning classics and new papers are read carefully paragraph by paragraph. | | 3 | labmlai/annotateddeeplearningpaperimplementations| A collection of simple PyTorch implementations of neural networks and related algorithms, which are documented with explanations | | 4 | Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models | Talking, Drawing and Editing with Visual Foundation Models | | 5 | OpenAI Research | The latest research report and papers from OpenAI | | 6 | Make-A-Video: Text-to-Video Generation without Text-Video Data|Meta's Text-to-Video Generation| | 7 | eDiff-I: Text-to-Image Diffusion Models with Ensemble of Expert Denoisers| Nvidia eDiff-I - New generation of generative AI content creation tool | | 8 | Training an Assistant-style Chatbot with Large Scale Data Distillation from GPT-3.5-Turbo | 2023 GPT4All Technical Report | | 9 | Segment Anything| Meta Segment Anything | | 10 | LLaMA: Open and Efficient Foundation Language Models| LLaMA: a collection of foundation language models ranging from 7B to 65B parameters| | 11 | papers-we-love/papers-we-love |Papers from the computer science community to read and discuss| | 12 | CVPR 2023 papers |The most exciting and influential CVPR 2023 papers| [Back to Top] Tutorials | No. | Tutorial | Description| |:---- |:---------------------------------------------------------------- | --- | | 1 | Coursera - Machine Learning | The Machine Learning Specialization Course taught by Dr. Andrew Ng| | 2 | microsoft/ML-For-Beginners | 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all| | 3 | ChatGPT Prompt Engineering for Developers | This short course taught by Isa Fulford (OpenAI) and Andrew Ng (DeepLearning.AI) will teach how to use a large language model (LLM) to quickly build new and powerful applications | | 4 | Dive into Deep Learning |Targeting Chinese readers, functional and open for discussion. The Chinese and English versions are used for teaching in over 400 universities across more than 60 countries | | 5 | AI Expert Roadmap | Roadmap to becoming an Artificial Intelligence Expert in 2022 | | 6 | Computer Science courses |List of Computer Science courses with video lectures| | 7 | Machine Learning with Python | Machine Learning with Python Certification on freeCodeCamp| | 8 | Building Systems with the ChatGPT API | This short course taught by Isa Fulford (OpenAI) and Andrew Ng (DeepLearning.AI), you will learn how to automate complex workflows using chain calls to a large language model| | 9 | LangChain for LLM Application Development | This short course taught by Harrison Chase (Co-Founder and CEO at LangChain) and Andrew Ng. you will gain essential skills in expanding the use cases and capabilities of language models in application development using the LangChain framework| | 10 | How Diffusion Models Work | This short course taught by Sharon Zhou (CEO, Co-founder, Lamini). you will gain a deep familiarity with the diffusion process and the models which carry it out. More than simply pulling in a pre-built model or using an API, this course will teach you to build a diffusion model from scratch| | 11 | Free Programming Books For AI |📚 Freely available programming books for AI | | 12 | microsoft/AI-For-Beginners |12 Weeks, 24 Lessons, AI for All!| | 13 | hemansnation/God-Level-Data-Science-ML-Full-Stack |A collection of scientific methods, processes, algorithms, and systems to build stories & models. This roadmap contains 16 Chapters, whether you are a fresher in the field or an experienced professional who wants to transition into Data Science & AI| | 14 | datawhalechina/prompt-engineering-for-developers |Chinese version of Andrew Ng's Big Model Series Courses, including "Prompt Engineering", "Building System", and "LangChain"| | 15 | ossu/computer-science |🎓 Path to a free self-taught education in Computer Science!| | 16 | microsoft/Data-Science-For-Beginners | 10 Weeks, 20 Lessons, Data Science for All! | |17 |jwasham/coding-interview-university !2023-09-29268215336 |A complete computer science study plan to become a software engineer.| [Back to Top] Thanks If this project has been helpful to you in any way, please give it a ⭐️ by clicking on the star.

airspace-hugo
github
LLM Vibe Score0.551
Human Vibe Score0.45061592683949336
themefisherMar 28, 2025

airspace-hugo

Airspace Hugo This theme is suitable for a wide variety of businesses, including marketing, photography, and development enterprises. 👀Demo | Page Speed (95%)🚀 🔑Key Features 📄 9+ Pre-Designed Pages 🌐 Multiple language support (Fr, En) 📊 Google Analytics support 🎨 CSS and JS bundle with Hugo Pipe 🎨 Bootstrap Based ⚙️ Netlify settings predefine 👥 Multiple authors available ✉️ Contact form support 🔄 GDPR consent support 🗺️ Google Maps support 🎉 Fun factors counter 🚀 Google Page Speed optimized 🌐 Open Graph meta tag 🐦 Twitter Card meta tag 📄 9+ Pre-Designed Pages 🏠 Home Page 📚 Blog Page 📝 Blog Single Page 📄 Project Page 🛠️ Services 💰 Pricing ❓ FAQ ℹ️ About Page 📞 Contact Page 🖥️Local development Or Check out Full Documentation. ⚙️Deployment and hosting Follow the steps. 🐞Reporting Issues We use GitHub Issues as the official bug tracker for the Airspace Template. Please Search existing issues. Someone may have already reported the same problem. If your problem or idea has not been addressed yet, feel free to open a new issue. 📱Submit Your Website To Our Showcase Are you using Airspace Hugo theme? Submit it to our showcase. Our showcase aims to demonstrate to the world what amazing websites people like you have created utilizing our Hugo themes and to show that Hugo has tremendous capabilities as a Static Site Generator. View all the websites powered by Airspace Hugo from here. Submit your Airspace Hugo powered website. 📄License Copyright &copy; Designed by Themefisher & Developed by Gethugothemes Code License: Released under the MIT license. Image license: The images are only for demonstration purposes. They have their licenses. We don't have permission to share those images. 🙏Special Thanks Bootstrap Jquery Ionicons Magnific Popup Shuffle Slick Slider Google Fonts All Contributors 👨‍💻Hire Us Besides developing unique, blazing-fast Hugo themes, we also provide customized services. We specialize in creating affordable, high-quality static websites based on Hugo. If you need to customize the theme or complete website development from scratch, you can hire us. Check Our Services 💎Premium Themes By Us | | | | |:---:|:---:|:---:| | Get 55+ Premium Hugo Themes Bundle | Bigspring | Navigator |

obsei
github
LLM Vibe Score0.545
Human Vibe Score0.10175553624190911
obseiMar 27, 2025

obsei

Note: Obsei is still in alpha stage hence carefully use it in Production. Also, as it is constantly undergoing development hence master branch may contain many breaking changes. Please use released version. Obsei (pronounced "Ob see" | /əb-'sē/) is an open-source, low-code, AI powered automation tool. Obsei consists of - Observer: Collect unstructured data from various sources like tweets from Twitter, Subreddit comments on Reddit, page post's comments from Facebook, App Stores reviews, Google reviews, Amazon reviews, News, Website, etc. Analyzer: Analyze unstructured data collected with various AI tasks like classification, sentiment analysis, translation, PII, etc. Informer: Send analyzed data to various destinations like ticketing platforms, data storage, dataframe, etc so that the user can take further actions and perform analysis on the data. All the Observers can store their state in databases (Sqlite, Postgres, MySQL, etc.), making Obsei suitable for scheduled jobs or serverless applications. !Obsei diagram Future direction - Text, Image, Audio, Documents and Video oriented workflows Collect data from every possible private and public channels Add every possible workflow to an AI downstream application to automate manual cognitive workflows Use cases Obsei use cases are following, but not limited to - Social listening: Listening about social media posts, comments, customer feedback, etc. Alerting/Notification: To get auto-alerts for events such as customer complaints, qualified sales leads, etc. Automatic customer issue creation based on customer complaints on Social Media, Email, etc. Automatic assignment of proper tags to tickets based content of customer complaint for example login issue, sign up issue, delivery issue, etc. Extraction of deeper insight from feedbacks on various platforms Market research Creation of dataset for various AI tasks Many more based on creativity 💡 Installation Prerequisite Install the following (if not present already) - Install Python 3.7+ Install PIP Install Obsei You can install Obsei either via PIP or Conda based on your preference. To install latest released version - Install from master branch (if you want to try the latest features) - Note: all option will install all the dependencies which might not be needed for your workflow, alternatively following options are available to install minimal dependencies as per need - pip install obsei[source]: To install dependencies related to all observers pip install obsei[sink]: To install dependencies related to all informers pip install obsei[analyzer]: To install dependencies related to all analyzers, it will install pytorch as well pip install obsei[twitter-api]: To install dependencies related to Twitter observer pip install obsei[google-play-scraper]: To install dependencies related to Play Store review scrapper observer pip install obsei[google-play-api]: To install dependencies related to Google official play store review API based observer pip install obsei[app-store-scraper]: To install dependencies related to Apple App Store review scrapper observer pip install obsei[reddit-scraper]: To install dependencies related to Reddit post and comment scrapper observer pip install obsei[reddit-api]: To install dependencies related to Reddit official api based observer pip install obsei[pandas]: To install dependencies related to TSV/CSV/Pandas based observer and informer pip install obsei[google-news-scraper]: To install dependencies related to Google news scrapper observer pip install obsei[facebook-api]: To install dependencies related to Facebook official page post and comments api based observer pip install obsei[atlassian-api]: To install dependencies related to Jira official api based informer pip install obsei[elasticsearch]: To install dependencies related to elasticsearch informer pip install obsei[slack-api]:To install dependencies related to Slack official api based informer You can also mix multiple dependencies together in single installation command. For example to install dependencies Twitter observer, all analyzer, and Slack informer use following command - How to use Expand the following steps and create a workflow - Step 1: Configure Source/Observer Twitter Youtube Scrapper Facebook Email Google Maps Reviews Scrapper AppStore Reviews Scrapper Play Store Reviews Scrapper Reddit Reddit Scrapper Note: Reddit heavily rate limit scrappers, hence use it to fetch small data during long period Google News Web Crawler Pandas DataFrame Step 2: Configure Analyzer Note: To run transformers in an offline mode, check transformers offline mode. Some analyzer support GPU and to utilize pass device parameter. List of possible values of device parameter (default value auto): auto: GPU (cuda:0) will be used if available otherwise CPU will be used cpu: CPU will be used cuda:{id} - GPU will be used with provided CUDA device id Text Classification Text classification: Classify text into user provided categories. Sentiment Analyzer Sentiment Analyzer: Detect the sentiment of the text. Text classification can also perform sentiment analysis but if you don't want to use heavy-duty NLP model then use less resource hungry dictionary based Vader Sentiment detector. NER Analyzer NER (Named-Entity Recognition) Analyzer: Extract information and classify named entities mentioned in text into pre-defined categories such as person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc Translator PII Anonymizer Dummy Analyzer Dummy Analyzer: Does nothing. Its simply used for transforming the input (TextPayload) to output (TextPayload) and adding the user supplied dummy data. Step 3: Configure Sink/Informer Slack Zendesk Jira ElasticSearch Http Pandas DataFrame Logger This is useful for testing and dry running the pipeline. Step 4: Join and create workflow source will fetch data from the selected source, then feed it to the analyzer for processing, whose output we feed into a sink to get notified at that sink. Step 5: Execute workflow Copy the code snippets from Steps 1 to 4 into a python file, for example example.py and execute the following command - Demo We have a minimal streamlit based UI that you can use to test Obsei. !Screenshot Watch UI demo video Check demo at (Note: Sometimes the Streamlit demo might not work due to rate limiting, use the docker image (locally) in such cases.) To test locally, just run To run Obsei workflow easily using GitHub Actions (no sign ups and cloud hosting required), refer to this repo. Companies/Projects using Obsei Here are some companies/projects (alphabetical order) using Obsei. To add your company/project to the list, please raise a PR or contact us via email. Oraika: Contextually understand customer feedback 1Page: Giving a better context in meetings and calls Spacepulse: The operating system for spaces Superblog: A blazing fast alternative to WordPress and Medium Zolve: Creating a financial world beyond borders Utilize: No-code app builder for businesses with a deskless workforce Articles Sr. No. Title Author 1 AI based Comparative Customer Feedback Analysis Using Obsei Reena Bapna 2 LinkedIn App - User Feedback Analysis Himanshu Sharma Tutorials Sr. No. Workflow Colab Binder 1 Observe app reviews from Google play store, Analyze them by performing text classification and then Inform them on console via logger PlayStore Reviews → Classification → Logger 2 Observe app reviews from Google play store, PreProcess text via various text cleaning functions, Analyze them by performing text classification, Inform them to Pandas DataFrame and store resultant CSV to Google Drive PlayStore Reviews → PreProcessing → Classification → Pandas DataFrame → CSV in Google Drive 3 Observe app reviews from Apple app store, PreProcess text via various text cleaning function, Analyze them by performing text classification, Inform them to Pandas DataFrame and store resultant CSV to Google Drive AppStore Reviews → PreProcessing → Classification → Pandas DataFrame → CSV in Google Drive 4 Observe news article from Google news, PreProcess text via various text cleaning function, Analyze them via performing text classification while splitting text in small chunks and later computing final inference using given formula Google News → Text Cleaner → Text Splitter → Classification → Inference Aggregator 💡Tips: Handle large text classification via Obsei Documentation For detailed installation instructions, usages and examples, refer to our documentation. Support and Release Matrix Linux Mac Windows Remark Tests ✅ ✅ ✅ Low Coverage as difficult to test 3rd party libs PIP ✅ ✅ ✅ Fully Supported Conda ❌ ❌ ❌ Not Supported Discussion forum Discussion about Obsei can be done at community forum Changelogs Refer releases for changelogs Security Issue For any security issue please contact us via email Stargazers over time Maintainers This project is being maintained by Oraika Technologies. Lalit Pagaria and Girish Patel are maintainers of this project. License Copyright holder: Oraika Technologies Overall Apache 2.0 and you can read License file. Multiple other secondary permissive or weak copyleft licenses (LGPL, MIT, BSD etc.) for third-party components refer Attribution. To make project more commercial friendly, we void third party components which have strong copyleft licenses (GPL, AGPL etc.) into the project. Attribution This could not have been possible without these open source softwares. Contribution First off, thank you for even considering contributing to this package, every contribution big or small is greatly appreciated. Please refer our Contribution Guideline and Code of Conduct. Thanks so much to all our contributors

He makes $750 a day 'Vibe Coding' Apps (using Replit, ChatGPT, Upwork)
youtube
LLM Vibe Score0.379
Human Vibe Score0.77
Greg IsenbergMar 21, 2025

He makes $750 a day 'Vibe Coding' Apps (using Replit, ChatGPT, Upwork)

Billy Howell shares his strategy for making money by building and selling custom web applications using AI tools like Replit. He demonstrates the process by finding projects on Upwork, creating a product requirements document with ChatGPT, and using Replit to automatically generate a functional web application. Billy explains that this approach is less risky than building SaaS products because it validates demand before significant development work. Timestamps: 00:00 - Intro 02:19 - Searching for App Ideas on Upwork 11:04 - Using ChatGPT for PRD Creation 12:22 - Why choose Replit for Development 15:15 - Building Prototype with Replit 19:53 - Areas of Concern when building with AI coders 23:30 - Earning Potential on Upwork 27:55 - The process for selling these Apps 32:03 - Comparing Different Business Models 35:40 - Huge opportunity: Unbundling SaaS 37:44 - Testing App 39:39 - How to standout on Upwork 40:35 - Integrating v0 UI to Replit Key Points • Billy Howell explains his method of "vibe coding" - using AI tools like Replit to quickly build and sell custom web applications • The process involves finding clients on Upwork who need solutions, creating a prototype, and selling it before building the complete app • Billy demonstrates how to use Repl.it with AI assistance to rapidly build a case management system for a nonprofit • The approach focuses on creating simple CRUD (Create, Read, Update, Delete) applications rather than complex systems 1) The "Sell First, Build Later" Framework Billy's #1 rule: Find someone to BUY your app BEFORE you build it. Most developers get this backward - they build something cool then struggle to find users. The secret? Don't market. SELL. How? Look for people ALREADY trying to pay for solutions 2) Upwork Gold Mining Strategy Billy's exact process: • Search Upwork for jobs mentioning expensive SaaS tools (Airtable, HubSpot, etc) • Look for simple CRUD apps (data entry, visualization) • Build a quick prototype in Repl.it • Send a Loom video demo to potential clients His first sale? $750 replacing an Airtable solution! 3) The Vibe Coding Tech Stack Billy's weapons of choice: • Replit for rapid prototyping (zero setup friction!) • ChatGPT to format requirements into PRDs • V0 for beautiful UI mockups • ShadCN components for clean interfaces The magic combo: Feed requirements to Replit + "build me this app" = working prototype in MINUTES. 4) What to Avoid When Vibe Coding Not all projects are created equal! Watch out for: • Payment processing (risky) • DocuSign integrations (complex) • Calendar functionality (AI struggles with time zones) • Anything changing data in other apps Start with simple CRUD apps that store and display information. 5) The Real Money-Making Model Billy's approach isn't just about one-off projects: • Initial build: $750-2,500 • Charge for hosting • Recurring revenue from feature requests • Get referrals to similar businesses One recent client is now reselling his solution to other companies in the same industry! 6) Why This Beats Building a SaaS Building a traditional SaaS = "nightmare money pit" according to Billy. With vibe coding consulting: • De-risk by getting paid upfront • Learn across multiple projects • No marketing costs • Discover validated problems • Build a portfolio of solutions Six figures on Upwork is VERY doable. 7) The 60-Second Sales Pitch Billy's exact closing technique: • Find job posting • Make mockup in V0 or Replit • Record 1-minute Loom: "I'm Billy, I make apps. I know you wanted Airtable, but I made this custom for you." • Personalize with company name • Send and repeat Simple. Effective. PROFITABLE. The future of coding isn't about knowing every framework—it's about SOLVING PROBLEMS quickly. Anyone can do this with the right tools and approach. Notable Quotes: "The number one thing is how to sell an app that you've built... And the secret is not to market. It's just to sell it." - Billy Howell "We start, we need to find someone to buy the app before we build it. That's where most people get this wrong, is they build something and then try to sell it or try to get users." - Billy Howell LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ BoringAds — ads agency that will build you profitable ad campaigns http://boringads.com/ BoringMarketing — SEO agency and tools to get your organic customers http://boringmarketing.com/ Startup Empire — a membership for builders who want to build cash-flowing businesses https://www.startupempire.co FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND BILLY ON SOCIAL X/Twitter: https://x.com/billyjhowell Youtube: https://www.youtube.com/@billyjhowell

ai-builder
github
LLM Vibe Score0.508
Human Vibe Score0.11051158244693815
thewebalchemistMar 12, 2025

ai-builder

AI-Driven Website Generator Description: The AI-Driven Website Generator is a project that aims to simplify the website creation process by utilizing AI technology, specifically GPT-3, to automatically generate customized landing pages for businesses. With this generator, you can quickly create visually appealing and responsive landing pages by providing a business name or specific instructions. The generator starts by taking input in the form of a business name or a set of instructions provided by the user. It then utilizes GPT-3 to analyze the input and generate the necessary HTML, CSS, and JavaScript code required to create a functional landing page. The generated code is designed to be compatible with modern web browsers and responsive across different devices. Key Features: Automatic generation of landing pages using AI technology. Customizable output based on business names or user instructions. Responsive and visually appealing user interfaces generated with Tailwind CSS. Efficient and streamlined website creation process. Flexibility to incorporate additional features or components as needed. How It Works The website generator utilizes the power of GPT-3 to analyze the input provided and generate the necessary HTML, CSS, and JavaScript code required to create a functional landing page. The generated code is designed to be compatible with modern web browsers and responsive across different devices. Contributing Contributions to the AI-Driven Website Generator project are welcome! If you have any ideas, suggestions, or bug reports, please feel free to open an issue or submit a pull request. Your contributions will help enhance the functionality and performance of the generator. License This project is licensed under the MIT License. Feel free to modify and distribute it according to the terms of the license. With the AI-Driven Website Generator, you can revolutionize the website creation process by harnessing the power of AI to generate customized landing pages effortlessly. Say goodbye to manual coding and design work, and experience the convenience and speed of generating professional-looking landing pages with just a few clicks.

Mastering-AI-for-Entrepreneurs-9-Free-Courses
github
LLM Vibe Score0.203
Human Vibe Score0
Softtechhub1Feb 1, 2025

Mastering-AI-for-Entrepreneurs-9-Free-Courses

Mastering-AI-for-Entrepreneurs-9-Free-Courses Introduction: The Entrepreneur's AI RevolutionArtificial Intelligence (AI) is changing the way we do business. It's not just for tech giants anymore. Small businesses and startups are using AI to work smarter, not harder. As an entrepreneur, you need to understand AI to stay ahead.Why AI is a must-have skill for entrepreneursAI is everywhere. It's in the apps we use, the products we buy, and the services we rely on. Businesses that use AI are seeing big improvements:They're making better decisions with data-driven insightsThey're automating routine tasks, freeing up time for creativityThey're personalizing customer experiences, boosting satisfaction and salesIf you're not using AI, you're falling behind. But here's the good news: you don't need to be a tech wizard to harness the power of AI.Breaking the barriers to AI learningThink AI is too complex? Think again. You don't need a computer science degree to understand and use AI in your business. Many AI tools are designed for non-technical users. They're intuitive and user-friendly.The best part? You can learn about AI for free. There are tons of high-quality courses available at no cost. These courses are designed for busy entrepreneurs like you. They cut through the jargon and focus on practical applications.What to expect from this articleWe've handpicked nine free courses that will turn you into an AI-savvy entrepreneur. Each course is unique, offering different perspectives and skills. We'll cover:What makes each course specialWhat you'll learnHow it applies to your businessWho it's best suited forReady to dive in? Let's explore these game-changing courses that will boost your AI knowledge and give your business an edge.1. Google AI Essentials: A Beginner's Guide to Practical AIWhy This Course Is EssentialGoogle AI Essentials is perfect if you're just starting out. It's designed for people who don't have a tech background. The course focuses on how AI can help you in your day-to-day work, not on complex theories.What You'll LearnThis course is all about making AI work for you. You'll discover how to:Use AI to boost your productivity. Generate ideas, create content, and manage tasks more efficiently.Streamline your workflows. Learn how AI can help with everyday tasks like drafting emails and organizing your schedule.Use AI responsibly. Understand the potential biases in AI and how to use it ethically.Key TakeawaysYou'll earn a certificate from Google. This looks great on your resume or LinkedIn profile.You'll learn how to work alongside AI tools to get better results in your business.You'll gain practical skills you can use right away to improve your work.Get StartedEnroll in Google AI Essentials2. Introduction to Generative AI: A Quick Start for EntrepreneursWhy This Course Works for Busy EntrepreneursThis course is short and sweet. In just 30 minutes, you'll get a solid grasp of generative AI. It's perfect if you're short on time but want to understand the basics.What You'll LearnThe fundamentals of generative AI: what it is, how it works, and its limitsHow generative AI differs from other types of AIReal-world applications of generative AI in businessHow It Helps Your BusinessAfter this course, you'll be able to:Make smarter decisions about using AI tools in your businessSpot opportunities where generative AI could solve problems or create valueUnderstand the potential and limitations of this technologyGet StartedEnroll in Introduction to Generative AI3. Generative AI with Large Language Models: Advanced Skills for EntrepreneursWhy This Course Stands OutThis course digs deeper into the technical side of AI. It's ideal if you have some coding experience and want to understand how AI models work under the hood.What You'll LearnYou'll gain key skills for working with Large Language Models (LLMs):How to gather and prepare data for AI modelsChoosing the right model for your needsEvaluating model performance and improving resultsYou'll also learn about:The architecture behind transformer models (the tech powering many AI tools)Techniques for fine-tuning models to your specific business needsWho Should Take This CourseThis course is best for entrepreneurs who:Have basic Python programming skillsUnderstand the fundamentals of machine learningWant to go beyond using AI tools to actually building and customizing themGet StartedEnroll in Generative AI with Large Language Models4. AI for Everyone by Andrew Ng: Simplifying AI for Business LeadersWhy It's Perfect for BeginnersAndrew Ng is a leading figure in AI education. He's known for making complex topics easy to understand. This course is designed for non-technical learners. You don't need any coding or math skills to benefit from it.What You'll LearnHow AI works at a high levelHow to spot problems in your business that AI can solveWays to assess how AI might impact your business processes and strategiesWhy Entrepreneurs Love This CourseIt explains AI concepts in plain English, without technical jargonYou can complete it in just 8 hours, fitting it into your busy scheduleIt focuses on the business value of AI, not just the technologyGet StartedStart with AI for Everyone on Coursera5. Generative AI: Introduction and ApplicationsWhy This Course Is Ideal for EntrepreneursThis course offers a broad view of generative AI applications. You'll learn about AI in text, image, audio, and more. It's packed with hands-on experience using popular AI tools.What You'll LearnThe basics and history of generative AI technologiesHow different industries are using AI, from marketing to creative projectsPractical skills through labs using tools like ChatGPT, DALL-E, and Stable DiffusionHow It Stands OutYou'll hear from real AI practitioners about their experiencesThe course teaches you how to use generative AI to innovate and improve efficiency in your businessGet StartedEnroll in Generative AI: Introduction and Applications6. Generative AI for Everyone by Andrew Ng: Unlocking ProductivityWhy This Course Is a Must-HaveThis course focuses on using generative AI tools for everyday business tasks. It's all about boosting your productivity and efficiency.What You'll LearnHands-on exercises to integrate AI tools into your daily workReal examples of how businesses are using generative AI to save time and moneyTechniques for prompt engineering to get better results from AI toolsHow It Helps EntrepreneursYou'll learn to automate repetitive tasks, freeing up time for strategic thinkingYou'll discover new ways to use AI tools in your business processesYou'll gain confidence in experimenting with AI to solve business challengesGet StartedGo deeper with DeepLearning.AI7. Generative AI for Business Leaders by LinkedIn LearningWhy This Course Focuses on Business ApplicationsThis course is tailored for leaders who want to integrate AI into their business operations. It provides practical insights for improving workflows and decision-making.What You'll LearnStrategies for using AI to optimize your business operationsHow to save time and resources with AI-powered toolsPractical methods for implementing AI in your company, regardless of sizeKey BenefitsThe course is designed for busy professionals, allowing you to learn at your own paceYou'll gain insights you can apply immediately to your businessIt covers both the potential and the limitations of AI in business settingsGet StartedLevel up on LinkedIn Learning8. AI for Beginners by Microsoft: A Structured Learning PathWhy This Course Builds a Strong AI FoundationMicrosoft's AI for Beginners is a comprehensive 12-week program. It covers core AI concepts in a structured, easy-to-follow format. The course combines theoretical knowledge with hands-on practice through quizzes and labs.What You'll LearnThe basics of AI, machine learning, and data scienceStep-by-step guidance to build a strong knowledge basePractical applications of AI in various business contextsHow to Approach This CourseDedicate 2-3 hours per week to complete the curriculumUse the structured format to gradually build your confidence in AI conceptsApply what you learn to real business scenarios as you progressGet StartedBuild foundations with Microsoft9. AI for Business Specialization by UPenn: Strategic Thinking with AIWhy This Course Is Perfect for Business LeadersThis specialization focuses on AI's transformative impact on core business functions. It covers how AI is changing marketing, finance, and operations.What You'll LearnHow to build an AI strategy tailored to your business needsWays to leverage AI to drive innovation across different departmentsTechniques for integrating AI into your business modelHow to Make the Most of This CourseTake detailed notes on how each module applies to your own business challengesUse the specialization to develop a long-term AI vision for your companyNetwork with other business leaders taking the course to share insights and experiencesGet StartedScale up with UPenn's business focusConclusion: Your Path to Becoming an AI-powered EntrepreneurWe've covered nine fantastic free courses that can transform you into an AI-savvy entrepreneur. Let's recap:Google AI Essentials: Perfect for beginners, focusing on practical AI applications.Introduction to Generative AI: A quick start to understand the basics of generative AI.Generative AI with Large Language Models: For those ready to dive into the technical side.AI for Everyone: A non-technical introduction to AI's business impact.Generative AI: Introduction and Applications: A broad look at generative AI across industries.Generative AI for Everyone: Focused on boosting productivity with AI tools.Generative AI for Business Leaders: Tailored for integrating AI into business operations.AI for Beginners: A structured path to build a strong AI foundation.AI for Business Specialization: Strategic thinking about AI in business functions.Remember, you don't need to tackle all these courses at once. Start small and build your knowledge gradually. Pick the course that aligns best with your current needs and business goals.Embracing AI is not just about staying competitive; it's about opening new doors for innovation and growth. These courses will help you see opportunities where AI can solve problems, improve efficiency, and create value for your business.The AI revolution is happening now. The sooner you start learning, the better positioned you'll be to lead in this new era. Each step you take in understanding AI is a step towards future-proofing your business.So, what are you waiting for? Choose a course, dive in, and start your journey to becoming an AI-powered entrepreneur today. The future of your business may depend on it.MORE ARTICLES FOR YOUHumanizzer Fastpass Bundle – OTO1 to OTO4: Get (Humanizzer + All OTOs) Fastpass for Massive 75% Discount Available Limited-Time OneHumanizzer Review: Build Lifelike Human AI Agents That Talk, Listen & Engage Face-To-Face!—In Your Voice, Just Like You!EasyListDetox App Review: A Windows tool with Giveaway Rights for effortlessly cleaning your email lists of duplicates, invalid, and disposable addresses. Simple, efficient, and time-savingAI Copy Kit Review: Google’s Latest AI Tech Tensorflow (Tf) Create Jaw-Dropping And Advanced Ultra HD Videos, Ultra Shorts, 4K Images, Voiceovers, and Any Other GPT 4-Powered Amazing Content In Minutes Without Any Complicated Tools!From Good to Great: 15 Books to Inspire Personal and Business TransformationFTC Affiliate Commission Disclaimer: Some links in this article may earn us a commission if you make a purchase. This doesn't affect our recommendations.

I built an AI Agent in 43 min to automate my workflows (Zero Coding)
youtube
LLM Vibe Score0.459
Human Vibe Score0.88
Greg IsenbergJan 31, 2025

I built an AI Agent in 43 min to automate my workflows (Zero Coding)

In this episode, Max Brodeur-Urbas, Gumloop's CEO, where we dive deep into how to build AI agents and how to automate any workflow. We cover various use cases, from automated sales outreach to content generation. Max shows us how Gumloop makes complex automations accessible to everyone by having user-friendly UI/UX, intuitive workflow buildouts, and easy custom integration creation. Timestamps: 00:00 - Intro 02:29 - Gumloop Workflow Overview 05:00 - Example: Lead Automation Workflow 10:23 - Templates for Workflows 12:21 - Example: YouTube to Blog Post Automation Workflow 21:03 - Gumloop Interfaces Demonstration 21:40 - Example: Media Ad Library Analyzer Automation Workflow 24:38 - Using Gumloop for SaaS Products 26:25 - Example: Analyze Daily Calendar Automation Workflow 27:47 - Output of Media Ad Library Analyzer Automation Workflow 28:43 - Cost of Running Gumloop 30:34 - Custom Node Builder Demonstration 34:18 - Gumloop Chrome Extension 37:06 - Final thoughts on business automation Gumloop Templates: https://www.gumloop.com/templates Key Points: • Demonstration of Gumloop's automation platform for building AI-powered workflows • Showcase of features including custom nodes, Chrome extension, and interface builder • Real-world examples of automated processes for sales, recruitment, and content generation • Discussion of practical business applications and cost-effectiveness of automation: Key Features Demonstrated: • Visual workflow builder • AI-powered content generation • Custom integration creation • Chrome extension functionality • Interface builder for non-technical users • Webhook integration capabilities 1) Gumloop is a visual workflow builder that lets you create powerful AI automations by connecting "nodes" - think Zapier meets ChatGPT, but WAY more powerful. Key features that stood out: 2) SUBFLOWS: Create reusable workflow components Build once, use everywhere Share with team members Perfect for complex operations Makes scaling easier 3) The YouTube Blog Post Generator is INSANE: Takes any YT video link Extracts transcript Generates TLDR summary Creates full blog post Adds video embed Posts to CMS Cost? About $1.62 per post 4) Competitor Ad Analysis automation: Scrapes competitor FB/IG ads Uses Gemini to analyze videos/images Generates strategy insights Sends beautiful email reports Runs on schedule Save 40+ hours/month 5) Custom Node Builder = game changer Create your own integrations No coding required AI helps write the code Share with your team Endless possibilities 6) Chrome Extension feature: Turn any workflow into a 1-click tool Works on any webpage Perfect for LinkedIn outreach Data enrichment Email automation 7) Why this matters: Most companies (even $1B+ ones) are still doing things manually that could be automated. The competitive advantage isn't just having AI - it's automating your workflows at scale. 8) Pricing & Getting Started: Free to try No CC required 1000 free credits with tutorial Build custom workflows Join their community Notable Quotes: "If you can list it as a list of steps, like for an intern, you would hand off a little sticky note being like, you do these 15 things in a row and that's the entire workflow, then you can 100% automate it." - Max "Being in business is a game of unfair advantages... And that means it's always about how do you save time as founders and executive teams." - Greg LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ BoringAds — ads agency that will build you profitable ad campaigns http://boringads.com/ BoringMarketing — SEO agency and tools to get your organic customers http://boringmarketing.com/ Startup Empire - a membership for builders who want to build cash-flowing businesses https://www.startupempire.co FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND MAX ON SOCIAL Gumloop: https://www.gumloop.com X/Twitter: https://x.com/maxbrodeururbas?lang=en LinkedIn: https://www.linkedin.com/in/max-brodeur-urbas-1a4b25172/

I ranked every AI Coder: Bolt vs. Cursor vs. Replit vs Lovable
youtube
LLM Vibe Score0.399
Human Vibe Score0.77
Greg IsenbergJan 24, 2025

I ranked every AI Coder: Bolt vs. Cursor vs. Replit vs Lovable

v0 vs windsurf vs replit vs bolt vs lovable vs tempolabs - which one should you use? Ras Mic breaks down the AI coding platforms based on how tech-savvy you are and how much control you want. He splits the tools into three groups: no-code options for non-techies, hybrid platforms for those with a mix of skills, and advanced tools for developers. None of them are quite ready for full-on production yet, but the video highlights what each one does best—whether it’s integrations, teamwork, or deployment features. Timestamps: 00:00 - Intro 01:00 - Overview of Popular Tools 02:29 - Technical vs. non-technical user classification 05:37 - Production readiness discussion 09:50 - Mapping Tools to User Profiles 12:52 - Platform comparisons and strengths 15:15 - Pricing discussion 16:43 - AI agents in coding platforms 19:04 - Final Recommendations and User Alignment Key Points: • Comprehensive comparison of major AI coding platforms (Lovable, Bolt, V0, Replit, Tempo Labs, Onlook, Cursor, Windsurf) • Tools categorized by technical expertise required and level of control offered • None of the platforms are 100% production-ready, but Replit and Tempo Labs are closest • All platforms offer similar base pricing ($20-30/month) with generous free tiers 1) First, understand the 3 MAJOR CATEGORIES of AI coding tools: • No-code (non-technical friendly) • Middle-ground (hybrid) • Technical (developer-focused) Your choice depends on TWO key factors: How much control you want Your technical expertise 2) THE CONTROL SPECTRUM Less Control → More Control • Lovable (basic control) • Bolt/V0 (code tweaking) • Replit (file management) • Tempo/Onlook (design control) • Cursor/Windsurf (full code control) 3) PRODUCTION READINESS STATUS Most honest take: None are 100% there yet, but some are close: Top contenders: • Replit • Tempo Labs Runner-ups: • Bolt • Lovable Pro tip: Start building now to be ready when they mature! 4) BEST TOOLS BY USER TYPE Non-technical: • Lovable • Bolt Product-minded non-technical: • Tempo Labs • Replit Technical folks: • Cursor • Windsurf 5) WINNING FEATURES BY PLATFORM Integrations: Lovable (crushing it!) Replit Tempo Labs Collaboration: Tempo Labs Replit Deployment: All solid, but Tempo needs work 6) PRICING INSIDER TIP All platforms hover around $20-30/month for basic tiers SECRET: They ALL have generous free tiers! Pro tip: Test drive everything before committing to paid plans 7) FINAL ADVICE Build a simple todo app on each platform Use free tiers to test Choose based on: Your technical comfort Desired level of control Specific project needs Remember: There's no "perfect" tool - just the right one for YOU! Notable Quotes: "None of the tools are there yet. I cannot confidently say you can build something to production easily, simply without a ton of roadblocks." - Ras Mic "Control is not for everybody. Did you like the assumptions that AI product was making for you? Or do you want to be able to tell it exactly what to do?" - Ras Mic LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ BoringAds — ads agency that will build you profitable ad campaigns http://boringads.com/ BoringMarketing — SEO agency and tools to get your organic customers http://boringmarketing.com/ Startup Empire - a membership for builders who want to build cash-flowing businesses https://www.startupempire.co FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND MIC ON SOCIAL X/Twitter: https://x.com/rasmickyy Youtube: https://www.youtube.com/@rasmic

internet-tools-collection
github
LLM Vibe Score0.236
Human Vibe Score0.009333333333333334
bogdanmosicaJan 23, 2025

internet-tools-collection

Internet Tools Collection A collection of tools, website and AI for entrepreneurs, web designers, programmers and for everyone else. Content by category Artificial Intelligence Developers Design Entrepreneur Video Editing Stock videos Stock Photos Stock music Search Engine Optimization Blog Posts Resume Interviews No code website builder No code game builder Side Hustle Browser Extensions Other Students Artificial Intelligence Jasper - The Best AI Writing Assistant [](https://www.jasper.ai/) Create content 5x faster with artificial intelligence. Jasper is the highest quality AI copywriting tool with over 3,000 5-star reviews. Best for writing blog posts, social media content, and marketing copy. AutoDraw [](https://www.autodraw.com/) Fast drawing for everyone. AutoDraw pairs machine learning with drawings from talented artists to help you draw stuff fast. Rytr - Best AI Writer, Content Generator & Writing Assistant [](https://rytr.me/) Rytr is an AI writing assistant that helps you create high-quality content, in just a few seconds, at a fraction of the cost! Neevo - Neevo [](https://www.neevo.ai/) Kinetix Tech [](https://kinetix.tech/) Kinetix is a no-code 3D creation tool powered by Artificial Intelligence. The web-based platform leverages AI motion capture to convert a video into a 3D animation and lets you customize your avatars and environments. We make 3D animation accessible to every creator so they can create engaging stories. LALAL.AI: 100% AI-Powered Vocal and Instrumental Tracks Remover [](https://www.lalal.ai/) Split vocal and instrumental tracks quickly and accurately with LALAL.AI. Upload any audio file and receive high-quality extracted tracks in a few seconds. Copy.ai: Write better marketing copy and content with AI [](https://www.copy.ai/) Get great copy that sells. Copy.ai is an AI-powered copywriter that generates high-quality copy for your business. Get started for free, no credit card required! Marketing simplified! OpenAI [](https://openai.com/) OpenAI is an AI research and deployment company. Our mission is to ensure that artificial general intelligence benefits all of humanity. DALL·E 2 [](https://openai.com/dall-e-2/) DALL·E 2 is a new AI system that can create realistic images and art from a description in natural language. Steve.ai - World’s fastest way to create Videos [](https://www.steve.ai/) Steve.AI is an online Video making software that helps anyone to create Videos and animations in seconds. Octie.ai - Your A.I. ecommerce marketing assistant [](https://octie.ai/) Write emails, product descriptions, and more, with A.I. Created by Octane AI. hypnogram.xyz [](https://hypnogram.xyz/) Generate images from text descriptions using AI FakeYou. Deep Fake Text to Speech. [](https://fakeyou.com/) FakeYou is a text to speech wonderland where all of your dreams come true. Craiyon, formerly DALL-E mini [](https://www.craiyon.com/) Craiyon, formerly DALL-E mini, is an AI model that can draw images from any text prompt! Deck Rocks - Create Pictch Decks [](https://www.deck.rocks/) Writely | Using AI to Improve Your Writing [](https://www.writelyai.com/) Making the art of writing accessible to all Writesonic AI Writer - Best AI Writing Assistant [](https://writesonic.com/) Writesonic is an AI writer that's been trained on top-performing SEO content, high-performing ads, and converting sales copy to help you supercharge your writing and marketing efforts. Smart Copy - AI Copywriting Assistant | Unbounce [](https://unbounce.com/product/smart-copy/) Generate creative AI copy on-the-spot across your favourite tools Synthesia | #1 AI Video Generation Platform [](https://www.synthesia.io/) Create AI videos by simply typing in text. Easy to use, cheap and scalable. Make engaging videos with human presenters — directly from your browser. Free demo. NVIDIA Canvas: Turn Simple Brushstrokes into Realistic Images [](https://www.nvidia.com/en-us/studio/canvas/) Create backgrounds quickly, or speed up your concept exploration so you can spend more time visualizing ideas with the help of NVIDIA Canvas. Hotpot.ai - Hotpot.ai [](https://hotpot.ai/) Hotpot.ai makes graphic design and image editing easy. AI tools allow experts and non-designers to automate tedious tasks while attractive, easy-to-edit templates allow anyone to create device mockups, social media posts, marketing images, app icons, and other work graphics. Klaviyo: Marketing Automation Platform for Email & SMS [](https://www.klaviyo.com/) Klaviyo, an ecommerce marketing automation platform for email marketing and sms syncs your tech stack with your website store to scale your business. Search listening tool for market, customer & content research - AnswerThePublic [](https://answerthepublic.com/) Use our free tool to get instant, raw search insights, direct from the minds of your customers. Upgrade to a paid plan to monitor for new ways that people talk & ask questions about your brand, product or topic. Topic Mojo [](https://topicmojo.com/) Discover unique & newest queries around any topic and find what your customers are searching for. Pulling data from 50+ sources to enhance your topic research. AI Image Enlarger | Enlarge Image Without Losing Quality! [](https://imglarger.com/) AI Image Enlarger is a FREE online image enlarger that could upscale and enhance small images automatically. Make jpg/png pictures big without losing quality. Midjourney [](https://www.midjourney.com/app/) Kaedim - AI for turning 2D images to 3D models [](https://www.kaedim3d.com/webapp) AI for turning 2D images, sketches and photos to 3D models in seconds. Overdub: Ultra realistic text to speech voice cloning - Descript [](https://www.descript.com/overdub) Create a text to speech model of your voice. Try a live demo. Getting Started [](https://magenta.tensorflow.org/get-started) Resources to learn about Magenta Photosonic AI Art Generator | Create Unique Images with AI [](https://photosonic.writesonic.com/) Transform your imagination into stunning digital art with Photosonic - the AI art generator. With its creative suggestions, this Writesonic's AI image generator can help unleash your inner artist and share your creations with the world. Image Computer [](https://image.computer/) Most downloaded Instagram Captions App (+more creator tools) [](https://captionplus.app/) Join 3 Million+ Instagram Creators who use CaptionPlus to find Instagram Captions, Hashtags, Feed Planning, Reel Ideas, IG Story Design and more. Writecream - Best AI Writer & Content Generator - Writecream [](https://www.writecream.com/) Sentence Rewriter is a free tool to reword a sentence, paragraph and even entire essays in a short amount of time. Hypotenuse AI: AI Writing Assistant and Text Generator [](https://www.hypotenuse.ai/) Turn a few keywords into original, insightful articles, product descriptions and social media copy with AI copywriting—all in just minutes. Try it free today. Text to Speach Listnr: Generate realistic Text to Speech voiceovers in seconds [](https://www.listnr.tech/) AI Voiceover Generator with over 600+ voiceovers in 80+ languages, go from Text to Voice in seconds. Get started for Free! Free Text to Speech: Online, App, Software, Commercial license with Natural Sounding Voices. [](https://www.naturalreaders.com/) Free text to speech online app with natural voices, convert text to audio and mp3, for personal and commercial use Developers OverAPI.com | Collecting all the cheat sheets [](https://overapi.com/) OverAPI.com is a site collecting all the cheatsheets,all! Search Engine For Devs [](https://you.com/) Spline - Design tool for 3D web browser experiences [](https://spline.design/) Create web-based 3D browser experiences Image to HTML CSS converter. Convert image to HTML CSS with AI: Fronty [](https://fronty.com/) Fronty - Image to HTML CSS code converter. Convert image to HTML powered by AI. Sketchfab - The best 3D viewer on the web [](https://sketchfab.com/) With a community of over one million creators, we are the world’s largest platform to publish, share, and discover 3D content on web, mobile, AR, and VR. Railway [](https://railway.app/) Railway is an infrastructure platform where you can provision infrastructure, develop with that infrastructure locally, and then deploy to the cloud. JSON Crack - Crack your data into pieces [](https://jsoncrack.com/) Simple visualization tool for your JSON data. No forced structure, paste your JSON and view it instantly. Locofy.ai - ship your products 3-4x faster — with low code [](https://www.locofy.ai/) Turn your designs into production-ready frontend code for mobile apps and web. Ship products 3-4x faster with your existing design tools, tech stacks & workflows. Oh Shit, Git!?! [](https://ohshitgit.com/) Carbon | Create and share beautiful images of your source code [](https://carbon.now.sh/) Carbon is the easiest way to create and share beautiful images of your source code. GPRM : GitHub Profile ReadMe Maker [](https://gprm.itsvg.in/) Best Profile Generator, Create your perfect GitHub Profile ReadMe in the best possible way. Lots of features and tools included, all for free ! HubSpot | Software, Tools, and Resources to Help Your Business Grow Better [](https://www.hubspot.com/) HubSpot’s integrated CRM platform contains the marketing, sales, service, operations, and website-building software you need to grow your business. QuickRef.ME - Quick Reference Cheat Sheet [](https://quickref.me/) Share quick reference and cheat sheet for developers massCode | A free and open source code snippets manager for developers [](https://masscode.io/) Code snippets manager for developers, developed using web technologies. Snyk | Developer security | Develop fast. Stay secure. [](https://snyk.io/) Snyk helps software-driven businesses develop fast and stay secure. Continuously find and fix vulnerabilities for npm, Maven, NuGet, RubyGems, PyPI and more. Developer Roadmaps [](https://roadmap.sh/) Community driven roadmaps, articles, guides, quizzes, tips and resources for developers to learn from, identify their career paths, know what they don't know, find out the knowledge gaps, learn and improve. CSS Generators Get Waves – Create SVG waves for your next design [](https://getwaves.io/) A free SVG wave generator to make unique SVG waves for your next web design. Choose a curve, adjust complexity, randomize! Box Shadows [](https://box-shadow.dev/) Tridiv | CSS 3D Editor [](http://tridiv.com/) Tridiv is a web-based editor for creating 3D shapes in CSS Glassmorphism CSS Generator - Glass UI [](https://ui.glass/generator/) Generate CSS and HTML components using the glassmorphism design specifications based on the Glass UI library. Blobmaker - Make organic SVG shapes for your next design [](https://www.blobmaker.app/) Make organic SVG shapes for your next design. Modify the complexity, contrast, and color, to generate unique SVG blobs every time. Keyframes.app [](https://keyframes.app/) cssFilters.co - Custom and Instagram like photo filters for CSS [](https://www.cssfilters.co/) Visual playground for generating CSS for custom and Instagram like photo filters. Experiment with your own uploaded photo or select one from the Unsplash collection. CSS Animations Animista - CSS Animations on Demand [](https://animista.net/) Animista is a CSS animation library and a place where you can play with a collection of ready-made CSS animations and download only those you will use. Build Internal apps Superblocks | Save 100s of developer hours on internal tools [](https://www.superblocks.com/) Superblocks is the fast, easy and secure way for developers to build custom internal tools fast. Connect your databases & APIs. Drag and drop UI components. Extend with Python or Javascript. Deploy in 1-click. Secure and Monitor using your favorite tools Budibase | Build internal tools in minutes, the easy way [](https://budibase.com/) Budibase is a modern, open source low-code platform for building modern internal applications in minutes. Retool | Build internal tools, remarkably fast. [](https://retool.com/) Retool is the fast way to build internal tools. Drag-and-drop our building blocks and connect them to your databases and APIs to build your own tools, instantly. Connects with Postgres, REST APIs, GraphQL, Firebase, Google Sheets, and more. Built by developers, for developers. Trusted by startups and Fortune 500s. Sign up for free. GitHub Repositories GitHub - vasanthk/how-web-works: What happens behind the scenes when we type www.google.com in a browser? [](https://github.com/vasanthk/how-web-works) What happens behind the scenes when we type www.google.com in a browser? - GitHub - vasanthk/how-web-works: What happens behind the scenes when we type www.google.com in a browser? GitHub - kamranahmedse/developer-roadmap: Interactive roadmaps, guides and other educational content to help developers grow in their careers. [](https://github.com/kamranahmedse/developer-roadmap) Interactive roadmaps, guides and other educational content to help developers grow in their careers. - GitHub - kamranahmedse/developer-roadmap: Interactive roadmaps, guides and other educational content to help developers grow in their careers. GitHub - apptension/developer-handbook: An opinionated guide on how to become a professional Web/Mobile App Developer. [](https://github.com/apptension/developer-handbook) An opinionated guide on how to become a professional Web/Mobile App Developer. - GitHub - apptension/developer-handbook: An opinionated guide on how to become a professional Web/Mobile App Developer. ProfileMe.dev | Create an amazing GitHub profile in minutes [](https://www.profileme.dev/) ProfileMe.dev | Create an amazing GitHub profile in minutes GitHub - Kristories/awesome-guidelines: A curated list of high quality coding style conventions and standards. [](https://github.com/Kristories/awesome-guidelines) A curated list of high quality coding style conventions and standards. - GitHub - Kristories/awesome-guidelines: A curated list of high quality coding style conventions and standards. GitHub - tiimgreen/github-cheat-sheet: A list of cool features of Git and GitHub. [](https://github.com/tiimgreen/github-cheat-sheet) A list of cool features of Git and GitHub. Contribute to tiimgreen/github-cheat-sheet development by creating an account on GitHub. GitHub - andreasbm/web-skills: A visual overview of useful skills to learn as a web developer [](https://github.com/andreasbm/web-skills) A visual overview of useful skills to learn as a web developer - GitHub - andreasbm/web-skills: A visual overview of useful skills to learn as a web developer GitHub - Ebazhanov/linkedin-skill-assessments-quizzes: Full reference of LinkedIn answers 2022 for skill assessments (aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning, power-point) linkedin excel test lösungen, linkedin machine learning test LinkedIn test questions and answers [](https://github.com/Ebazhanov/linkedin-skill-assessments-quizzes) Full reference of LinkedIn answers 2022 for skill assessments (aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning, power-point) linkedin excel test lösungen, linkedin machine learning test LinkedIn test questions and answers - GitHub - Ebazhanov/linkedin-skill-assessments-quizzes: Full reference of LinkedIn answers 2022 for skill assessments (aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning, power-point) linkedin excel test lösungen, linkedin machine learning test LinkedIn test questions and answers Blockchain/Crypto Dashboards [](https://dune.com/) Blockchain ecosystem analytics by and for the community. Explore and share data from Ethereum, xDai, Polygon, Optimism, BSC and Solana for free. Introduction - The Anchor Book v0.24.0 [](https://book.anchor-lang.com/introduction/introduction.html) Crypto & Fiat Exchange Super App | Trade, Save & Spend | hi [](https://hi.com/) Buy, Trade, Send and Earn Crypto & Fiat. Deposit Bitcoin, ETH, USDT and other cryptos and start earning. Get the hi Debit Card and Multi-Currency IBAN Account. Moralis Web3 - Enterprise-Grade Web3 APIs [](https://moralis.io/) Bridge the development gap between Web2 and Web3 with Moralis’ powerful Web3 APIs. Mirror [](https://mirror.xyz/) Built on web3 for web3, Mirror’s robust publishing platform pushes the boundaries of writing online—whether it’s the next big white paper or a weekly community update. Makerdao [](https://blog.makerdao.com/) Sholi — software for Investors & Traders / Sholi MetriX [](https://sholi.io/) Sholi — software for Investors & Traders / Sholi MetriX Stock Trading Quiver Quantitative [](https://www.quiverquant.com/) Quiver Quantitative Chart Prime - The only tool you'll need for trading assets across all markets [](https://chartprime.com/) ChartPrime offers a toolkit that will take your trading game to the next level. Visit our site for a full rundown of features and helpful tutorials. Learning Hacker Rank [](https://www.hackerrank.com/) Coderbyte | Code Screening, Challenges, & Interview Prep [](https://coderbyte.com/) Improve your coding skills with our library of 300+ challenges and prepare for coding interviews with content from leading technology companies. Competitive Programming | Participate & Learn | CodeChef [](https://www.codechef.com/) Learn competitive programming with the help of CodeChef's coding competitions. Take part in these online coding contests to level up your skills Learn to Code - for Free | Codecademy [](https://www.codecademy.com/) Learn the technical skills to get the job you want. Join over 50 million people choosing Codecademy to start a new career (or advance in their current one). Free Code Camp [](https://www.freecodecamp.org/) Learn to Code — For Free Sololearn: Learn to Code [](https://www.sololearn.com/home) Join Now to learn the basics or advance your existing skills Mimo: The coding app you need to learn to code! Python, HTML, JavaScript [](https://getmimo.com/) Join more than 17 million learners worldwide. Learn to code for free. Learn Python, JavaScript, CSS, SQL, HTML, and more with our free code learning app. Free for developers [](https://free-for.dev/#/) Your Career in Web Development Starts Here | The Odin Project [](https://www.theodinproject.com/) The Odin Project empowers aspiring web developers to learn together for free Code Learning Games CheckiO - coding games and programming challenges for beginner and advanced [](https://checkio.org/) CheckiO - coding websites and programming games. Improve your coding skills by solving coding challenges and exercises online with your friends in a fun way. Exchanges experience with other users online through fun coding activities Coding for Kids | Game-Based Programming | CodeMonkey [](https://www.codemonkey.com/) CodeMonkey is a leading coding for kids program. Through its award-winning courses, millions of students learn how to code in real programming languages. Coding Games and Programming Challenges to Code Better [](https://www.codingame.com/) CodinGame is a challenge-based training platform for programmers where you can play with the hottest programming topics. Solve games, code AI bots, learn from your peers, have fun. Learn VIM while playing a game - VIM Adventures [](https://vim-adventures.com/) VIM Adventures is an online game based on VIM's keyboard shortcuts. It's the "Zelda meets text editing" game. So come have some fun and learn some VIM! CodeCombat - Coding games to learn Python and JavaScript [](https://codecombat.com/) Learn typed code through a programming game. Learn Python, JavaScript, and HTML as you solve puzzles and learn to make your own coding games and websites. Design Useberry - Codeless prototype analytics [](https://www.useberry.com/) User testing feedback & rich insights in minutes, not months! Figma: the collaborative interface design tool. [](https://www.figma.com/) Build better products as a team. Design, prototype, and gather feedback all in one place with Figma. Dribbble - Discover the World’s Top Designers & Creative Professionals [](https://dribbble.com/) Find Top Designers & Creative Professionals on Dribbble. We are where designers gain inspiration, feedback, community, and jobs. Your best resource to discover and connect with designers worldwide. Photopea | Online Photo Editor [](https://www.photopea.com/) Photopea Online Photo Editor lets you edit photos, apply effects, filters, add text, crop or resize pictures. Do Online Photo Editing in your browser for free! Toools.design – An archive of 1000+ Design Resources [](https://www.toools.design/) A growing archive of over a thousand design resources, weekly updated for the community. Discover highly useful design tools you never thought existed. All Online Tools in One Box | 10015 Tools [](https://10015.io/) All online tools you need in one box for free. Build anything online with “all-in-one toolbox”. All tools are easy-to-use, blazing fast & free. Phase - Digital Design Reinvented| Phase [](https://phase.com/) Design and prototype websites and apps visually and intuitively, in a new powerful product reworked for the digital age. Animated Backgrounds [](https://animatedbackgrounds.me/) A Collection of 30+ animated backgrounds for websites and blogs.With Animated Backgrounds, set a simple, elegant background animations on your websites and blogs. Trianglify.io · Low Poly Pattern Generator [](https://trianglify.io/) Trianglify.io is a tool for generating low poly triangle patterns that can be used as wallpapers and website assets. Cool Backgrounds [](https://coolbackgrounds.io/) Explore a beautifully curated selection of cool backgrounds that you can add to blogs, websites, or as desktop and phone wallpapers. SVG Repo - Free SVG Vectors and Icons [](https://www.svgrepo.com/) Free Vectors and Icons in SVG format. ✅ Download free mono or multi color vectors for commercial use. Search in 300.000+ Free SVG Vectors and Icons. Microcopy - Short copy text for your website. [](https://www.microcopy.me/) Search micro UX copy text: slogans, headlines, notifications, CTA, error messages, email, account preferences, and much more. 3D icons and icon paks - Free3Dicon [](https://free3dicon.com/) All 3D icons you need in one place. This is a collection of free, beautiful, trending 3D icons, that you can use in any project. Love 3D Icon [](https://free3dicons.com/) Downloads free 3D icons GIMP - GNU Image Manipulation Program [](https://www.gimp.org/) GIMP - The GNU Image Manipulation Program: The Free and Open Source Image Editor blender.org - Home of the Blender project - Free and Open 3D Creation Software [](https://www.blender.org/) The Freedom to Create 3D Design Software | 3D Modeling on the Web | SketchUp [](https://www.sketchup.com/) SketchUp is a premier 3D design software that truly makes 3D modeling for everyone, with a simple to learn yet robust toolset that empowers you to create whatever you can imagine. Free Logo Maker - Create a Logo in Seconds - Shopify [](https://www.shopify.com/tools/logo-maker) Free logo maker tool to generate custom design logos in seconds. This logo creator is built for entrepreneurs on the go with hundreds of templates, free vectors, fonts and icons to design your own logo. The easiest way to create business logos online. All your design tools in one place | Renderforest [](https://www.renderforest.com/) Time to get your brand noticed. Create professional videos, logos, mockups, websites, and graphics — all in one place. Get started now! Prompt Hero [](https://prompthero.com/) Type Scale - A Visual Calculator [](https://type-scale.com/) Preview and choose the right type scale for your project. Experiment with font size, scale and different webfonts. DreamFusion: Text-to-3D using 2D Diffusion [](https://dreamfusion3d.github.io/) DreamFusion: Text-to-3D using 2D Diffusion, 2022. The branding style guidelines documents archive [](https://brandingstyleguides.com/) Welcome to the brand design manual documents directory. Search over our worldwide style assets handpicked collection, access to PDF documents for inspiration. Super designer | Create beautiful designs with a few clicks [](https://superdesigner.co/) Create beautiful designs with a few clicks. Simple design tools to generate unique patterns, backgrounds, 3D shapes, colors & images for social media, websites and more Readymag—a design tool to create websites without coding [](https://readymag.com/) Meet the most elegant, simple and powerful web-tool for designing websites, presentations, portfolios and all kinds of digital publications. ffflux: Online SVG Fluid Gradient Background Generator | fffuel [](https://fffuel.co/ffflux/) SVG generator to make fluid gradient backgrounds that feel organic and motion-like. Perfect to add a feeling of motion and fluidity to your web designs. Generate unique SVG design assets | Haikei [](https://haikei.app/) A web-based design tool to generate unique SVG design assets for websites, social media, blog posts, desktop and mobile wallpapers, posters, and more! Our generators let you discover, customize, randomize, and export generative SVG design assets ready to use with your favorite design tools. UI/UX - Inspirational Free Website Builder Software | 10,000+ Free Templates [](https://nicepage.com/) Nicepage is your website builder software breaking limitations common for website builders with revolutionary freehand positioning. 7000+ Free Templates. Easy Drag-n-Drop. No coding. Mobile-friendly. Clean HTML. Super designer | Create beautiful designs with a few clicks [](https://superdesigner.co/) Create beautiful designs with a few clicks. Simple design tools to generate unique patterns, backgrounds, 3D shapes, colors & images for social media, websites and more Pika – Create beautiful mockups from screenshots [](https://pika.style/) Quickly create beautiful website and device mockup from screenshot. Pika lets you capture website screenshots form URL, add device and browser frames, customize background and more LiveTerm [](https://liveterm.vercel.app/) Minimal Gallery – Web design inspiration [](https://minimal.gallery/) For the love of beautiful, clean and functional websites. Awwwards - Website Awards - Best Web Design Trends [](https://www.awwwards.com/) Awwwards are the Website Awards that recognize and promote the talent and effort of the best developers, designers and web agencies in the world. Design Systems For Figma [](https://www.designsystemsforfigma.com/) A collection of Design Systems for Figma from all over the globe. Superside: Design At Scale For Ambitious Brands [](https://www.superside.com/) We are an always-on design company. Get a team of dedicated designers, speedy turnarounds, magical creative collaboration tech and the top 1% of global talent. UXArchive - Made by Waldo [](https://uxarchive.com/) UXArchive the world's largest library of mobile user flows. Be inspired to design the best user experiences. Search by Muzli [](https://search.muz.li/) Search, discover, test and create beautiful color palettes for your projects Siteinspire | Web Design Inspiration [](https://www.siteinspire.com/) SAVEE [](https://savee.it/) The best way to save and share inspiration. A little corner of the internet to find good landing page copywriting examples [](https://greatlandingpagecopy.com/) A little corner of the internet to find great landing page copywriting examples. The Best Landing Page Examples For Design Inspiration - SaaS Landing Page [](https://saaslandingpage.com/) SaaS Landing Page showcases the best landing page examples created by top-class SaaS companies. Get ideas and inspirations for your next design project. Websites Free templates Premium Bootstrap Themes and Templates: Download @ Creative Tim [](https://www.creative-tim.com/) UI Kits, Templates and Dashboards built on top of Bootstrap, Vue.js, React, Angular, Node.js and Laravel. Join over 2,014,387+ creatives to access all our products! Free Bootstrap Themes, Templates, Snippets, and Guides - Start Bootstrap [](https://startbootstrap.com/) Start Bootstrap develops free to download, open source Bootstrap 5 themes, templates, and snippets and creates guides and tutorials to help you learn more about designing and developing with Bootstrap. Free Website Templates [](https://freewebsitetemplates.com/) Get your free website templates here and use them on your website without needing to link back to us. One Page Love - One Page Website Inspiration and Templates [](https://onepagelove.com/) One Page Love is a One Page website design gallery showcasing the best Single Page websites, templates and resources. Free CSS | 3400 Free Website Templates, CSS Templates and Open Source Templates [](https://www.free-css.com/) Free CSS has 3400 free website templates, all templates are free CSS templates, open source templates or creative commons templates. Free Bootstrap Themes and Website Templates | BootstrapMade [](https://bootstrapmade.com/) At BootstrapMade, we create beautiful website templates and bootstrap themes using Bootstrap, the most popular HTML, CSS and JavaScript framework. Free and Premium Bootstrap Themes, Templates by Themesberg [](https://themesberg.com/) Free and Premium Bootstrap themes, templates, admin dashboards and UI kits used by over 38820 web developers and software companies HTML, Vue.js and React templates for startup landing pages - Cruip [](https://cruip.com/) Cruip is a gallery of premium and free HTML, Vue.js and React templates for startups and SaaS. Free Website Templates Download | WordPress Themes - W3Layouts [](https://w3layouts.com/) Want to download free website templates? W3Layouts WordPress themes and website templates are built with responsive web design techniques. Download now! Free HTML Landing Page Templates and UI Kits | UIdeck [](https://uideck.com/) Free HTML Landing Page Templates, Bootstrap Themes, React Templates, HTML Templates, Tailwind Templates, and UI Kits. Create Online Graphics Snappa - Quick & Easy Graphic Design Software [](https://snappa.com/) Snappa makes it easy to create any type of online graphic. Create & publish images for social media, blogs, ads, and more! Canva [](https://www.canva.com/) Polotno Studio - Make graphical designs [](https://studio.polotno.com) Free online design editor. Create images for social media, youtube previews, facebook covers Free Logo Maker: Design Custom Logos | Adobe Express [](https://www.adobe.com/express/create/logo) The Adobe Express logo maker is instant, intuitive, and intelligent. Use it to generate a wide range of possibilities for your own logo. Photo Editor: Fotor – Free Online Photo Editing & Image Editor [](https://www.fotor.com/) Fotor's online photo editor helps you edit photos with free online photo editing tools. Crop photos, resize images, and add effects/filters, text, and graphics in just a few clicks. Photoshop online has never been easier with Fotor's free online photo editor. VistaCreate – Free Graphic Design Software with 70,000+ Free Templates [](https://create.vista.com/) Looking for free graphic design software? Easily create professional designs with VistaCreate, a free design tool with powerful features and 50K+ ready-made templates Draw Freely | Inkscape [](https://inkscape.org/) Inkscape is professional quality vector graphics software which runs on Linux, Mac OS X and Windows desktop computers. Visual & Video Maker Trusted By 11 Million Users - Piktochart [](https://piktochart.com/) With Piktochart, you can create professional-looking infographics, flyers, posters, charts, videos, and more. No design experience needed. Start for free. The Web's Favorite Online Graphic Design Tool | Stencil [](https://getstencil.com/) Stencil is a fantastically easy-to-use online graphic design tool and image editor built for business owners, social media marketers, and bloggers. Pablo by Buffer - Design engaging images for your social media posts in under 30 seconds [](https://pablo.buffer.com/) Buffer makes it super easy to share any page you're reading. Keep your Buffer topped up and we automagically share them for you through the day. Free Online Graphic Design Software | Create stunning designs in seconds. [](https://desygner.com/) Easy drag and drop graphic design tool for anyone to use with 1000's of ready made templates. Create & print professional business cards, flyers, social posts and more. Color Pallet Color Palettes for Designers and Artists - Color Hunt [](https://colorhunt.co/) Discover the newest hand-picked color palettes of Color Hunt. Get color inspiration for your design and art projects. Coolors - The super fast color palettes generator! [](https://coolors.co/) Generate or browse beautiful color combinations for your designs. Get color palette inspiration from nature - colorpalettes.earth [](https://colorpalettes.earth/) Color palettes inspired by beautiful nature photos Color Palette Generator - Create Beautiful Color Schemes [](https://colors.muz.li/) Search, discover, test and create beautiful color palettes for your projects A Most Useful Color Picker | 0to255 [](https://0to255.com/) Find lighter and darker colors based on any color. Discover why over two million people have used 0to255 to choose colors for their website, logo, room interior, and print design projects. Colour Contrast Checker [](https://colourcontrast.cc/) Check the contrast between different colour combinations against WCAG standards Fonts Google Fonts [](https://fonts.google.com/) Making the web more beautiful, fast, and open through great typography Fonts In Use – Type at work in the real world. [](https://fontsinuse.com/) A searchable archive of typographic design, indexed by typeface, format, and topic. Wordmark - Helps you choose fonts! [](https://wordmark.it/) Wordmark helps you choose fonts by quickly displaying your text with your fonts. OH no Type Company [](https://ohnotype.co/) OH no Type Co. Retail and custom typefaces. Life’s a thrill, fonts are chill! Illustrations Illustrations | unDraw [](https://undraw.co/illustrations) The design project with open-source illustrations for any idea you can imagine and create. Create beautiful websites, products and applications with your color, for free. Design Junction [](https://designjunction.xyz/) Design Junction is a one-stop resource library for Designers and Creatives with curated list of best resources handpicked from around the web Humaaans: Mix-&-Match illustration library [](https://www.humaaans.com/) Mix-&-match illustrations of people with a design library for InVIsion Studio and Sketch. Stubborn - Free Illustrations Generator [](https://stubborn.fun/) Free illustrations generator for Figma and Sketch. Get the opportunity to design your characters using symbols and styles. Open Peeps, Hand-Drawn Illustration Library [](https://www.openpeeps.com/) Open Peeps is a hand-drawn illustration library to create scenes of people. You can use them in product illustration, marketing, comics, product states, user flows, personas, storyboarding, quinceañera invitations, or whatever you want! ⠀ Reshot | Free icons & illustrations [](https://www.reshot.com/) Design freely with instant downloads of curated SVG icons and vector illustrations. All free with commercial licensing. No attribution required. Blush: Illustrations for everyone [](https://blush.design/) Blush makes it easy to add free illustrations to your designs. Play with fully customizable graphics made by artists across the globe. Mockups Angle 4 - 5000+ Device Mockups for Figma, Sketch and XD [](https://angle.sh/) Vector mockups for iPhone, iPad, Android and Mac devices, including the new iPhone 13, Pro, Pro Max and Mini. Perfect for presenting your apps. Huge library of components, compositions, wallpapers and plugins made for Figma, Sketch and XD. Make Mockups, Logos, Videos and Designs in Seconds [](https://placeit.net/) Get unlimited downloads on all our 100K templates! You can make a logo, video, mockup, flyer, business card and social media image in seconds right from your browser. Free and premium tools for graphic designers | Lstore Graphics [](https://www.ls.graphics/) Free and premium mockups, UI/UX tools, scene creators for busy designers Logo Design & Brand Identity Platform for Entrepreneurs | Looka [](https://looka.com/) Logojoy is now Looka! Design a Logo, make a website, and create a Brand Identity you’ll love with the power of Artificial Intelligence. 100% free to use. Create stunning product mockups easily and online - Smartmockups [](https://smartmockups.com/) Smartmockups enables you to create stunning high-resolution mockups right inside your browser within one interface across multiple devices. Previewed - Free mockup generator for your app [](https://previewed.app/) Join Previewed to create stunning 3D image shots and animations for your app. Choose from hundreds of ready made mockups, or create your own. Free Design Software - Graphic Online Maker - Glorify [](https://www.glorify.com/) Create professional and high converting social media posts, ads, infographics, presentations, and more with Glorify, a free design software & graphic maker. Other BuiltWith Technology Lookup [](https://builtwith.com/) Web technology information profiler tool. Find out what a website is built with. Compress JPEG Images Online [](https://compressjpeg.com/) Compress JPEG images and photos for displaying on web pages, sharing on social networks or sending by email. PhotoRoom - Remove Background and Create Product Pictures [](https://www.photoroom.com/) Create product and portrait pictures using only your phone. Remove background, change background and showcase products. Magic Eraser - Remove unwanted things from images in seconds [](https://www.magiceraser.io/) Magic Eraser - Use AI to remove unwanted things from images in seconds. Upload an image, mark the bit you need removed, download the fixed up image. Compressor.io - optimize and compress JPEG photos and PNG images [](https://compressor.io/) Optimize and compress JPEG, PNG, SVG, GIF and WEBP images online. Compress, resize and rename your photos for free. Remove Video Background – Unscreen [](https://www.unscreen.com/) Remove the background of any video - 100% automatically, online & free! Goodbye Greenscreen. Hello Unscreen. Noun Project: Free Icons & Stock Photos for Everything [](https://thenounproject.com/) Noun Project features the most diverse collection of icons and stock photos ever. Download SVG and PNG. Browse over 5 million art-quality icons and photos. Design Principles [](https://principles.design/) An Open Source collection of Design Principles and methods Shapefest™ - A massive library of free 3D shapes [](https://www.shapefest.com/) A massive free library of beautifully rendered 3D shapes. 160,000+ high resolution PNG images in one cohesive library. Learning UX Degreeless.design - Everything I Learned in Design School [](https://degreeless.design/) This is a list of everything I've found useful in my journey of learning design, and an ongoing list of things I think you should read. For budding UX, UI, Interaction, or whatever other title designers. UX Tools | Practical UX skills and tools [](https://uxtools.co/) Lessons and resources from two full-time product designers. Built For Mars [](https://builtformars.com/) On a mission to help the world build better user experiences by demystifying UX. Thousands of hours of research packed into UX case studies. Case Study Club – Curated UX Case Study Gallery [](https://www.casestudy.club/) Case Study Club is the biggest curated gallery of the best UI/UX design case studies. Get inspired by industry-leading designers, openly sharing their UX process. The Guide to Design [](https://start.uxdesign.cc/) A self-guided class to help you get started in UX and answer key questions about craft, design, and career Uxcel - Where design careers are built [](https://app.uxcel.com/explore) Available on any device anywhere in the world, Uxcel is the best way to improve and learn UX design online in just 5 minutes per day. UI & UX Design Tips by Jim Raptis. [](https://www.uidesign.tips/) Learn UI & UX Design with practical byte-sized tips and in-depth articles from Jim Raptis. Entrepreneur Instant Username Search [](https://instantusername.com/#/) Instant Username Search checks out if your username is available on more than 100 social media sites. Results appear instantly as you type. Flourish | Data Visualization & Storytelling [](https://flourish.studio/) Beautiful, easy data visualization and storytelling PiPiADS - #1 TikTok Ads Spy Tool [](https://www.pipiads.com/) PiPiADS is the best tiktok ads spy tool .We provide tiktok advertising,advertising on tiktok,tiktok ads examples,tiktok ads library,tiktok ads best practices,so you can understand the tiktok ads cost and master the tiktok ads 2021 and tiktok ads manager. Minea - The best adspy for product search in ecommerce and dropshipping [](https://en.minea.com/) Minea is the ultimate e-commerce product search tool. Minea tracks all ads on all networks. Facebook Ads, influencer product placements, Snapspy, all networks are tracked. Stop paying adspy 149€ for one network and discover Minea. AdSpy [](https://adspy.com/) Google Trends [](https://trends.google.com/) ScoreApp: Advanced Quiz Funnel Marketing | Make a Quiz Today [](https://www.scoreapp.com/) ScoreApp makes quiz funnel marketing easy, so you can attract relevant warm leads, insightful data and increase your sales. Try for free today Mailmodo - Send Interactive Emails That Drive Conversions [](https://www.mailmodo.com/) Use Mailmodo to create and send interactive emails your customers love. Drive conversions and get better email ROI. Sign up for a free trial now. 185 Top E-Commerce Sites Ranked by User Experience Performance – Baymard Institute [](https://baymard.com/ux-benchmark) See the ranked UX performance of the 185 largest e-commerce sites in the US and Europe. The chart summarizes 50,000+ UX performance ratings. Metricool - Analyze, manage and measure your digital content [](https://metricool.com/) Social media scheduling, web analytics, link in bio and reporting. Metricool is free per live for one brand. START HERE Visualping: #1 Website change detection, monitoring and alerts [](https://visualping.io/) More than 1.5 millions users monitor changes in websites with Visualping, the No1 website change detection, website checker, webpage change monitoring and webpage change detection tool. Gumroad – Sell what you know and see what sticks [](https://gumroad.com/) Gumroad is a powerful, but simple, e-commerce platform. We make it easy to earn your first dollar online by selling digital products, memberships and more. Product Hunt – The best new products in tech. [](https://www.producthunt.com/) Product Hunt is a curation of the best new products, every day. Discover the latest mobile apps, websites, and technology products that everyone's talking about. 12ft Ladder [](https://12ft.io/) Show me a 10ft paywall, I’ll show you a 12ft ladder. namecheckr | Social and Domain Name Availability Search For Brand Professionals [](https://www.namecheckr.com/) Social and Domain Name Availability Search For Brand Professionals Excel AI Formula Generator - Excelformulabot.com [](https://excelformulabot.com/) Transform your text instructions into Excel formulas in seconds with the help of AI. Z-Library [](https://z-lib.org/) Global Print On Demand Platform | Gelato [](https://www.gelato.com/) Create and sell custom products online. With local production in 33 countries, easy integration, and 24/7 customer support, Gelato is an all-in-one platform. Freecycle: Front Door [](https://freecycle.org/) Free eBooks | Project Gutenberg [](https://www.gutenberg.org/) Project Gutenberg is a library of free eBooks. Convertio — File Converter [](https://convertio.co/) Convertio - Easy tool to convert files online. More than 309 different document, image, spreadsheet, ebook, archive, presentation, audio and video formats supported. Namechk [](https://namechk.com/) Crazy Egg Website — Optimization | Heatmaps, Recordings, Surveys & A/B Testing [](https://www.crazyegg.com/) Use Crazy Egg to see what's hot and what's not, and to know what your web visitors are doing with tools, such as heatmaps, recordings, surveys, A/B testing & more. Ifttt [](https://ifttt.com/) Also Asked [](https://alsoasked.com/) Business Name Generator - Easily create Brandable Business Names - Namelix [](https://namelix.com/) Namelix uses artificial intelligence to create a short, brandable business name. Search for domain availability, and instantly generate a logo for your new business Merch Informer [](https://merchinformer.com/) Headline Generator [](https://www.title-generator.com/) Title Generator: create 700 headlines with ONE CLICK: Content Ideas + Catchy Headlines + Ad Campaign E-mail Subject Lines + Emotional Titles. Simple - Efficient - One Click Make [](https://www.make.com/en) Create and add calculator widgets to your website | CALCONIC_ [](https://www.calconic.com/) Web calculator builder empowers you to choose from a pre-made templates or build your own calculator widgets from a scratch without any need of programming knowledge Boost Your Views And Subscribers On YouTube - vidIQ [](https://vidiq.com/) vidIQ helps you acquire the tools and knowledge needed to grow your audience faster on YouTube and beyond. Learn More Last Pass [](https://www.lastpass.com/) Starter Story: Learn How People Are Starting Successful Businesses [](https://www.starterstory.com/) Starter Story interviews successful entrepreneurs and shares the stories behind their businesses. In each interview, we ask how they got started, how they grew, and how they run their business today. How To Say No [](https://www.starterstory.com/how-to-say-no) Saying no is hard, but it's also essential for your sanity. Here are some templates for how to say no - so you can take back your life. Think with Google - Discover Marketing Research & Digital Trends [](https://www.thinkwithgoogle.com/) Uncover the latest marketing research and digital trends with data reports, guides, infographics, and articles from Think with Google. ClickUp™ | One app to replace them all [](https://clickup.com/) Our mission is to make the world more productive. To do this, we built one app to replace them all - Tasks, Docs, Goals, and Chat. The Manual [](https://manual.withcompound.com/) Wealth-planning resources for founders and startup employees Software for Amazon FBA Sellers & Walmart Sellers | Helium 10 [](https://www.helium10.com/) If you're looking for the best software for Amazon FBA & Walmart sellers on the market, check out Helium 10's capabilities online today! Buffer: All-you-need social media toolkit for small businesses [](https://buffer.com/) Use Buffer to manage your social media so that you have more time for your business. Join 160,000+ small businesses today. CPGD — The Consumer Packaged Goods Directory [](https://www.cpgd.xyz/) The Consumer Packaged Goods Directory is a platform to discover new brands and resources. We share weekly trends in our newsletter and partner with services to provide vetted, recommended platforms for our Directory brands. Jungle Scout [](https://www.junglescout.com/) BuzzSumo | The World's #1 Content Marketing Platform [](https://buzzsumo.com/) BuzzSumo powers the strategies of 500k+ marketers, with content marketing data on 8b articles, 42m websites, 300t engagements, 500k journalists & 492m questions. Login - Capital [](https://app.capital.xyz/) Raise, hold, spend, and send funds — all in one place. Marketing Pictory – Video Marketing Made Easy - Pictory.ai [](https://pictory.ai/) Pictory's powerful AI enables you to create and edit professional quality videos using text, no technical skills required or software to download. Tolstoy | Communicate with interactive videos [](https://www.gotolstoy.com/) Start having face-to-face conversations with your customers. Create Email Marketing Your Audience Will Love - MailerLite [](https://www.mailerlite.com/) Email marketing tools to grow your audience faster and drive revenue smarter. Get free access to premium features with a 30-day trial! Sign up now! Hypefury - Schedule & Automate Social Media Marketing [](https://hypefury.com/) Save time on social media while creating more value, and growing your audience faster. Schedule & automate your social media experience! Klaviyo: Marketing Automation Platform for Email & SMS [](https://www.klaviyo.com/) Klaviyo, an ecommerce marketing automation platform for email marketing and sms syncs your tech stack with your website store to scale your business. Online Email & Lead Scraper | Klean Leads [](https://www.kleanleads.com/) Klean Leads is an online email scraper & email address finder. Use it to book more appointments, get more replies, and close more sales. PhantomBuster [](https://phantombuster.com/) Call to Action Examples - 300+ CTA Phrases [](https://ctaexamples.com/) See the best CTA example in every situation covered by the library of 300+ CTA goals. Use the examples to create your own CTAs in minutes. Creative Center: one-stop creative solution for TikTok [](https://ads.tiktok.com/business/creativecenter/pc/en?from=001010) Come to get your next great idea for TikTok. Here you can find the best performing ads, viral videos, and trending hashtags across regions and verticals. Groove.cm GrooveFunnels, GrooveMail with CRM and Digital Marketing Automation Platform - Groove.cm with GrooveFunnels, GroovePages, GrooveKart [](https://groove.cm/) Groove is a website creator, page builder, sales funnel maker, membership site platform, email autoresponder, blog tool, shopping cart system, ecommerce store solution, affiliate manager, video marketing software and more apps to help build your online business. SurveyMonkey: The World’s Most Popular Free Online Survey Tool [](https://www.surveymonkey.com/) Use SurveyMonkey to drive your business forward by using our free online survey tool to capture the voices and opinions of the people who matter most to you. Video Maker | Create Videos Online | Promo.com [](https://promo.com/) Free customizable video maker to help boost your business. Video creator for ads, social media, product and explainer videos, and for anything else you need! beehiiv — The newsletter platform built for growth [](https://www.beehiiv.com/) Access the best tools available in email, helping your newsletter scale and monetize like never before. GetResponse | Professional Email Marketing for Everyone [](https://www.getresponse.com/) No matter your level of expertise, we have a solution for you. At GetResponse, it's email marketing done right. Start your free account today! Search Email Newsletter Archives : Email Tuna [](https://emailtuna.com/) Explore newsletters without subscribing. Get email design ideas, discount coupon codes and exclusive newsletters deals. Database of email newsletters archived from all over the internet. Other Tools Simplescraper — Scrape Websites and turn them into APIs [](https://simplescraper.io/) Web scraping made easy — a powerful and free Chrome extension for scraping websites in your browser, automated in the cloud, or via API. No code required. Exploding Topics - Discover the hottest new trends. [](https://explodingtopics.com/) See new market opportunities, trending topics, emerging technology, hot startups and more on Exploding Topics. Scribe | Visual step-by-step guides [](https://scribehow.com/) By capturing your process while you work, Scribe automatically generates a visual guide, ready to share with the click of a button. Get It Free – The internet's BEST place to find free stuff! [](https://getitfree.us/) The internet's BEST place to find free stuff! Inflact by Ingramer – Marketing toolkit for Instagram [](https://inflact.com/) Sell on Instagram, build your audience, curate content with the right set of tools. Free Online Form Builder & Form Creator | Jotform [](https://www.jotform.com/) We believe the right form makes all the difference. Go from busywork to less work with powerful forms that use conditional logic, accept payments, generate reports, and automate workflows. Manage Your Team’s Projects From Anywhere | Trello [](https://trello.com/en) Trello is the ultimate project management tool. Start up a board in seconds, automate tedious tasks, and collaborate anywhere, even on mobile. TikTok hashtag generator - tiktokhashtags.com [](https://tiktokhashtags.com/) Find out which are the best hashtags for your TikTok post. Create Infographics, Reports and Maps - Infogram [](https://infogram.com/) Infogram is an easy to use infographic and chart maker. Create and share beautiful infographics, online reports, and interactive maps. Make your own here. Confetto - Create Instagram content in minutes [](https://www.confet.to/) Confetto is an all-in-one social media marketing tool built for SMBs and Social Media Managers. Confetto helps you create high-quality content for your audience that maximizes your reach and engagement on social media. Design, copy-write, plan and schedule content all in one place. Find email addresses in seconds • Hunter (Email Hunter) [](https://hunter.io/) Hunter is the leading solution to find and verify professional email addresses. Start using Hunter and connect with the people that matter for your business. PlayPhrase.me: Site for cinema archaeologists. [](https://playphrase.me/) Travel and explore the world of cinema. Largest collection of video quotes from movies on the web. #1 Free SEO Tools → SEO Review Tools [](https://www.seoreviewtools.com/) SEO Review Tools: 42+ Free Online SEO Tools build with ❤! → Rank checker → Domain Authority Checker → Keyword Tool → Backlink Checker Podcastle: Seamless Podcast Recording & Editing [](https://podcastle.ai/) Podcastle is the simplest way to create professional-quality podcasts. Record, edit, transcribe, and export your content with the power of AI, in an intuitive web-based platform. Save Ads from TikTok & Facebook Ad Library - Foreplay [](https://www.foreplay.co/) The best way to save ads from TikTok Creative Center and Facebook Ad Library, Organize them into boards and share ad inspiration with your team. Supercharge your creative strategy. SiteRight - Automate Your Business [](https://www.siteright.co/) SiteRight combines the abilities of multiple online resources into a single dashboard allowing you to have full control over how you manage your business. Diffchecker - Compare text online to find the difference between two text files [](https://www.diffchecker.com/) Diffchecker will compare text to find the difference between two text files. Just paste your files and click Find Difference! Yout.com [](https://yout.com/) Yout.com allows you to record videos from YouTube, FaceBook, SoundCloud, VK and others too many formats with clipping. Intuitively easy to use, with Yout the Internet DVR, with a bit of extra. AI Content Generation | Competitor Analysis - Predis.ai [](https://predis.ai/) Predis helps brands and influencers communicate better on social media by providing AI-powered content strategy analysis, content and hashtag recommendations. Castr | #1 Live Video Streaming Solution With Video Hosting [](https://castr.io/) Castr is a live video streaming solution platform that delivers enterprise-grade live videos globally with CDN. Live event streaming, video hosting, pre-recorded live, multi stream – all in one place using Castr. Headliner - Promote your podcast, radio show or blog with video [](https://www.headliner.app/) Easily create videos to promote your podcast, radio show or blog. Share to Instagram, Facebook, Twitter, YouTube, Linkedin and anywhere video lives Create Presentations, Infographics, Design & Video | Visme [](https://www.visme.co/) Create professional presentations, interactive infographics, beautiful design and engaging videos, all in one place. Start using Visme today. Designrr - Create eBooks, Kindle books, Leadmagnets, Flipbooks and Blog posts from your content in 2 minutes [](https://designrr.io/) Upload any web page, MS Word, Video, Podcast or YouTube and it will create a stunning ebook and convert it to pdf, epub, Kindle or Flipbook. Quick and Easy to use. Full Training, 24x7 Support and Facebook Group Included. SwipeWell | Swipe File Software [](https://www.swipewell.app/) The only Chrome extension dedicated to helping you save, organize, and reference marketing examples (so you never feel stumped). Tango | Create how-to guides, in seconds [](https://www.tango.us/) Tango takes the pain out of documenting processes by automatically generating how-to guides while you work. Empower your team to do their best work. Ad Creative Bank [](https://www.theadcreativebank.com/) Get inspired by ads from across industries, learn new best practices, and start thinking creatively about your brand’s digital creative. Signature Hound • Free Email Signature and Template Generator [](https://signaturehound.com/) Our email signature generator is free and easy to use. Our customizable templates work with Gmail, Outlook, Office 365, Apple Mail and more. Organize All Of Your Marketing In One Place - CoSchedule [](https://coschedule.com/) Get more done in less time with the only work management software for marketers. B Ok - Books [](https://b-ok.xyz/categories) OmmWriter [](https://ommwriter.com/) Ommwriter Rebrandly | Custom URL Shortener, Branded Link Management, API [](https://www.rebrandly.com/) URL Shortener with custom domains. Shorten, brand and track URLs with the industry-leading link management platform. Free to try. API, Short URL, Custom Domains. Common Tools [](https://www.commontools.org/) Book Bolt [](https://bookbolt.io/) Zazzle [](https://www.zazzle.com/) InspiroBot [](https://inspirobot.me/) Download Free Cheat Sheets or Create Your Own! - Cheatography.com: Cheat Sheets For Every Occasion [](https://cheatography.com/) Find thousands of incredible, original programming cheat sheets, all free to download. No Code Chatbot Platform | Free Chatbot Platform | WotNot [](https://wotnot.io/) WotNot is the best no code chatbot platform to build AI bot easily without coding. Deploy bots and live chat on the Website, Messenger, WhatsApp, and more. SpyFu - Competitor Keyword Research Tools for Google Ads PPC & SEO [](https://www.spyfu.com/) Systeme.io - The only tool you need to launch your online business [](https://systeme.io/) Systeme.io has all the tools you need to grow your online business. Click here to create your FREE account! Productivity Temp Mail [](https://temp-mail.org/en/) The Visual Collaboration Platform for Every Team | Miro [](https://miro.com/) Scalable, secure, cross-device and enterprise-ready team collaboration whiteboard for distributed teams. Join 35M+ users from around the world. Grammarly: Free Online Writing Assistant [](https://www.grammarly.com/) Millions trust Grammarly’s free writing app to make their online writing clear and effective. Getting started is simple — download Grammarly’s extension today. Rize · Maximize Your Productivity [](https://rize.io/) Rize is a smart time tracker that improves your focus and helps you build better work habits. Motion | Manage calendars, meetings, projects & tasks in one app [](https://www.usemotion.com/) Automatically prioritize tasks, schedule meetings, and resolve calendar conflicts. Used by over 10k CEOs and professionals to improve focus, get more done, and streamline workday. Notion – One workspace. Every team. [](https://www.notion.so/) We’re more than a doc. Or a table. Customize Notion to work the way you do. Loom: Async Video Messaging for Work | Loom [](https://www.loom.com/) Record your screen, share your thoughts, and get things done faster with async video. Zapier | Automation that moves you forward [](https://zapier.com/) Workflow automation for everyone. Zapier automates your work across 5,000+ app integrations, so you can focus on what matters. Rows — The spreadsheet with superpowers [](https://rows.com/) Combine the power of a spreadsheet with built-in integrations from your business apps. Automate workflows and build tools that make work simpler. Free Online Form Builder | Tally [](https://tally.so/) Tally is the simplest way to create free forms & surveys. Create any type of form in seconds, without knowing how to code, and for free. Highbrow | Learn Something New Every Day. Join for Free! 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PDF Tools Free PDF, Video, Image & Other Online Tools - TinyWow [](https://tinywow.com/) Smallpdf.com - A Free Solution to all your PDF Problems [](https://smallpdf.com/) Smallpdf - the platform that makes it super easy to convert and edit all your PDF files. Solving all your PDF problems in one place - and yes, free. Sejda helps with your PDF tasks [](https://www.sejda.com/) Sejda helps with your PDF tasks. Quick and simple online service, no installation required! Split, merge or convert PDF to images, alternate mix or split scans and many other. iLovePDF | Online PDF tools for PDF lovers [](https://www.ilovepdf.com/) iLovePDF is an online service to work with PDF files completely free and easy to use. Merge PDF, split PDF, compress PDF, office to PDF, PDF to JPG and more! Text rewrite QuillBot [](https://quillbot.com/) Pre Post SEO : Online SEO Tools [](https://www.prepostseo.com/) Free Online SEO Tools: plagiarism checker, grammar checker, image compressor, website seo checker, article rewriter, back link checker Wordtune | Your personal writing assistant & editor [](https://www.wordtune.com/) Wordtune is the ultimate AI writing tool that rewrites, rephrases, and rewords your writing! Trusted by over 1,000,000 users, Wordtune strengthens articles, academic papers, essays, emails and any other online content. Aliexpress alternatives CJdropshipping - Dropshipping from Worldwide to Worldwide! [](https://cjdropshipping.com/) China's reliable eCommerce dropshipping fulfillment supplier, helps small businesses ship worldwide, dropship and fulfillment services that are friendly to start-ups and small businesses, Shopify dropshipping. SaleHoo [](https://www.salehoo.com/) Alibaba.com: Manufacturers, Suppliers, Exporters & Importers from the world's largest online B2B marketplace [](https://www.alibaba.com/) Find quality Manufacturers, Suppliers, Exporters, Importers, Buyers, Wholesalers, Products and Trade Leads from our award-winning International Trade Site. Import & Export on alibaba.com Best Dropshipping Suppliers for US + EU Products | Spocket [](https://www.spocket.co/) Spocket allows you to easily start dropshipping top products from US and EU suppliers. Get started for free and see why Spocket consistently gets 5 stars. Best dropshipping supplier to the US [](https://www.usadrop.com/) THE ONLY AMERICAN-MADE FULFILLMENT CENTER IN CHINA. Our knowledge of the Worldwide dropshipping market and the Chinese Supply-Chain can't be beat! 阿里1688 [](https://www.1688.com/) 阿里巴巴(1688.com)是全球企业间(B2B)电子商务的著名品牌,为数千万网商提供海量商机信息和便捷安全的在线交易市场,也是商人们以商会友、真实互动的社区平台。目前1688.com已覆盖原材料、工业品、服装服饰、家居百货、小商品等12个行业大类,提供从原料--生产--加工--现货等一系列的供应产品和服务 Dropshipping Tools Oberlo | Where Self Made is Made [](https://www.oberlo.com/) Start selling online now with Shopify. All the videos, podcasts, ebooks, and dropshipping tools you'll need to build your online empire. Klaviyo: Marketing Automation Platform for Email & SMS [](https://www.klaviyo.com/) Klaviyo, an ecommerce marketing automation platform for email marketing and sms syncs your tech stack with your website store to scale your business. SMSBump | SMS Marketing E-Commerce App for Shopify [](https://smsbump.com/) SMSBump is an SMS marketing & automation app for Shopify. Segment customers, recover orders, send campaign text messages with a 35%+ click through rate. AfterShip: The #1 Shipment Tracking Platform [](https://www.aftership.com/) Order status lookup, branded tracking page, and multi-carrier tracking API for eCommerce. Supports USPS, FedEx, UPS, and 900+ carriers worldwide. #1 Dropshipping App | Zendrop [](https://zendrop.com/) Start and scale your own dropshipping business with Zendrop. Sell and easily fulfill your orders with the fastest shipping in the industry. Best Dropshipping Suppliers for US + EU Products | Spocket [](https://www.spocket.co/) Spocket allows you to easily start dropshipping top products from US and EU suppliers. Get started for free and see why Spocket consistently gets 5 stars. Video Editing Jitter • The simplest motion design tool on the web. [](https://jitter.video/) Animate your designs easily. Export your creations as videos or GIFs. All in your browser. 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Kapwing — Reach more people with your content [](https://www.kapwing.com/) Kapwing is a collaborative, online content creation platform that you can use to edit video and create content. Join over 10 million modern creators who trust Kapwing to create, edit, and grow their content on every channel. Panzoid [](https://panzoid.com/) Powerful, free online apps and community for creating beautiful custom content. Google Web Designer - Home [](https://webdesigner.withgoogle.com/) Kapwing — Reach more people with your content [](https://www.kapwing.com/) Kapwing is a collaborative, online content creation platform that you can use to edit video and create content. Join over 10 million modern creators who trust Kapwing to create, edit, and grow their content on every channel. ClipDrop [](https://clipdrop.co/) Create professional visuals without a photo studio CapCut [](https://www.capcut.com/) CapCut is an all-in-one online video editing software which makes creation, upload & share easier, with frame by frame track editor, cloud drive etc. VEED - Online Video Editor - Video Editing Made Simple [](https://www.veed.io/) Make stunning videos with a single click. Cut, trim, crop, add subtitles and more. Online, no account needed. Try it now, free. VEED Free Video Maker | Create & Edit Your Videos Easily - Animoto [](https://animoto.com/k/welcome) Create, edit, and share videos with our online video maker. Combine your photos, video clips, and music to make quality videos in minutes. Get started free! Runway - Online Video Editor | Everything you need to make content, fast. [](https://runwayml.com/) Discover advanced video editing capabilities to take your creations to the next level. CreatorKit - A.I. video creator for marketers [](https://creatorkit.com/) Create videos with just one click, using our A.I. video editor purpose built for marketers. Create scroll stopping videos, Instagram stories, Ads, Reels, and TikTok videos. Pixar in a Box | Computing | Khan Academy [](https://www.khanacademy.org/computing/pixar) 3D Video Motions Plask - AI Motion Capture and 3D Animation Tool [](https://plask.ai/) Plask is an all-in-one browser-based AI motion capture tool and animation editor that anybody can use, from motion designers to every day content creators. Captions Captions [](https://www.getcaptions.app/) Say hello to Captions, the only camera and editing app that automatically transcribes, captions and clips your talking videos for you. Stock videos Pexels [](https://www.pexels.com/) Pixabay [](https://pixabay.com/) Mixkit - Awesome free assets for your next video project [](https://mixkit.co/) Download Free Stock Video Footage, Stock Music & Premiere Pro Templates for your next video editing project. All assets can be downloaded for free! Free Stock Video Footage HD 4K Download Royalty-Free Clips [](https://www.videvo.net/) Download free stock video footage with over 300,000 video clips in 4K and HD. We also offer a wide selection of music and sound effect files with over 180,000 clips available. Click here to download royalty-free licensing videos, motion graphics, music and sound effects from Videvo today. Free Stock Video Footage HD Royalty-Free Videos Download [](https://mazwai.com/) Download free stock video footage with clips available in HD. Click here to download royalty-free licensing videos from Mazwai now. Royalty Free Stock Video Footage Clips | Vidsplay.com [](https://www.vidsplay.com/) Royalty Free Stock Video Footage Clips Free Stock Video Footage, Royalty Free Videos for Download [](https://coverr.co/) Download royalty free (for personal and commercial use), unique and beautiful video footage for your website or any project. No attribution required. Stock Photos Beautiful Free Images & Pictures | Unsplash [](https://unsplash.com/) Beautiful, free images and photos that you can download and use for any project. Better than any royalty free or stock photos. When we share, everyone wins - Creative Commons [](https://creativecommons.org/) Creative Commons licenses are 20! Honoring 20 years of open sharing using CC licenses, join us in 2022 to celebrate Better Sharing — advancing universal access to knowledge and culture, and fostering creativity, innovation, and collaboration. Help us reach our goal of raising $15 million for a future of Better Sharing.  20 Years of Better … Read More "When we share, everyone wins" Food Pictures • Foodiesfeed • Free Food Photos [](https://www.foodiesfeed.com/) Download 2000+ food pictures ⋆ The best free food photos for commercial use ⋆ CC0 license Free Stock Photos and Images for Websites & Commercial Use [](https://burst.shopify.com/) Browse thousands of beautiful copyright-free images. All our pictures are free to download for personal and commercial use, no attribution required. EyeEm | Authentic Stock Photography and Royalty-Free Images [](https://www.eyeem.com/) Explore high-quality, royalty-free stock photos for commercial use. License individual images or save money with our flexible subscription and image pack plans. picjumbo: Free Stock Photos [](https://picjumbo.com/) Free stock photos and images for your projects and websites.️ Beautiful 100% free high-resolution stock images with no watermark. Free Stock Photos, Images, and Vectors [](https://www.stockvault.net/) 139.738 free stock photos, textures, backgrounds and graphics for your next project. No attribution required. Free Stock Photos, PNGs, Templates & Mockups | rawpixel [](https://www.rawpixel.com/) Free images, PNGs, stickers, backgrounds, wallpapers, graphic templates and PSD mockups. All safe to use with commercial licenses. Free Commercial Stock Photos & Royalty Free Images | PikWizard [](https://pikwizard.com/) Free images, videos & free stock photos. Unlimited downloads ✓ Royalty-free Images ✓Copyright-free for commercial use ✓ No Attribution Required Design Bundles [](https://designbundles.net/) Stock music Royalty Free Music for video creators | Epidemic Sound [](https://www.epidemicsound.com/) Download premium Royalty free Music and SFX! Our free trial gives you access to over 35,000 tracks and 90,000 sound effects for video, streaming and more! Royalty-Free Music & SFX for Video Creators | Artlist [](https://artlist.io/) Explore the ultimate royalty-free music & sound effects catalogs for unlimited use in YouTube videos, social media & films created by inspiring indie artists worldwide. The go-to music licensing choice for all creators Royalty Free Audio Tracks - Envato Elements [](https://elements.envato.com/audio) Download Royalty Free Stock Audio Tracks for your next project from Envato Elements. Premium, High Quality handpicked Audio files ideal for any genre. License popular music for videos • Lickd [](https://lickd.co/) The only place you can license popular music for videos. Access 1M+ mainstream tracks, plus high-quality stock music for content creators NCS (NoCopyrightSounds) - free music for content creators [](https://ncs.io/) NCS is a Record Label dedicated to giving a platform to the next generation of Artists in electronic music, representing genres from house to dubstep via trap, drum & bass, electro pop and more. Search Engine Optimization Keyword Tool For Monthly Search Volume, CPC & Competition [](https://keywordseverywhere.com/) Keywords Everywhere is a browser add-on for Chrome & Firefox that shows search volume, CPC & competition on multiple websites. Semrush - Online Marketing Can Be Easy [](https://www.semrush.com/) Turn the algorithm into a friend. Make your business visible online with 55+ tools for SEO, PPC, content, social media, competitive research, and more. DuckDuckGo — Privacy, simplified. [](https://duckduckgo.com/) The Internet privacy company that empowers you to seamlessly take control of your personal information online, without any tradeoffs. SEO Software for 360° Analysis of Your Website [](https://seranking.com/) Leading SEO software for business owners, agencies, and SEO specialists. Track your rankings, monitor competitors, spot technical errors, and more. Skyrocket your organic traffic with Surfer [](https://surferseo.com/) Use Surfer to research, write, optimize, and audit! Everything you need to create a comprehensive content strategy that yields real results is right here. Ahrefs - SEO Tools & Resources To Grow Your Search Traffic [](https://ahrefs.com/) You don't have to be an SEO pro to rank higher and get more traffic. Join Ahrefs – we're a powerful but easy to learn SEO toolset with a passionate community. Neon Tools [](https://neontools.io/) Google Index Search [](https://lumpysoft.com/) Google Index Search SEO Backlink Checker & Link Building Toolset | Majestic.com [](https://majestic.com/) Develop backlink strategies with our Link Intelligence data, build the strongest SEO backlink campaigns to drive organic traffic and boost your rankings today. PageOptimizer Pro [](https://pageoptimizer.pro/) Plans Services SEO Consulting Learn SEO About Blog POP SEO Community Podcast Support POP On Page Workshops With Kyle Roof POP Chrome Extension Guide Tutorial Videos Frequently Asked Questions Best Practices Login Cancel Anytime Plans Services SEO Consulting Learn SEO About Blog POP SEO Community Podcast Support POP On Page… Keyword Chef - Keywords for Publishers [](https://keywordchef.com/) Rank Insanely Fast for Keywords Your Competition Can’t Find “Every long-tail keyword I find ends up ranking within a day” – Dane Eyerly, Owner at TextGoods.com Keyword Chef automatically finds and filters keywords for you. Real-time SERP analysis lets you find keywords nearly guaranteed to rank. Try for free → Let’s face it, most keyword tools ... Read more Notifier - Social Listening for Social Media and More! [](https://notifier.so/) Track keywords. Market your product for free. Drive the conversation. Easy. Free Trial. No obligation ever. Simple. Fast. Trusted by Top Companies. Free Keyword Research Tool from Wordtracker [](https://www.wordtracker.com/) The best FREE alternative to the Keyword Planner. Use Wordtracker to reveal 1000s of profitable longtail keywords with up to 10,000 results per search Blog Posts The 60 Hottest Front-end Tools of 2021 | CSS-Tricks - CSS-Tricks [](https://css-tricks.com/hottest-front-end-tools-in-2021/) A complete list of the most popular front-end tools in 2021, according to the Web Tools Weekly newsletter. See which resources made the list. Resume ResumeGlow - AI Powered Resume Builder [](https://resumeglow.com/) Get hired fast with a resume that grabs attention. Designed by a team of HR experts and typographers. Customizable templates with more than a million possible Create Your Job-winning Resume - (Free) Resume maker · Resume.io [](https://resume.io/) Free online resume maker, allows you to create a perfect Resume or Cover Letter in 5 minutes. See how easy it is to write a professional resume - apply for jobs today! Rezi - The Leading AI-Powered Free Resume Builder [](https://www.rezi.ai/) Rezi’s award-winning AI-powered resume builder is trusted by hundreds of thousands of job seekers. Create your perfect resume in minutes with Rezi. Create a Perfect Resume | Free Resume Builder | Resumaker.ai [](https://resumaker.ai/) Create your professional resume with this online resume maker. Choose a designer-made template and grab any employer attention in seconds. Trusted AI Resume Maker Helps You Get Hired Fast [](https://skillroads.com/) Reach a 96.4% success rate in the job hunt race with the best resume creator. Our innovative technologies and 24/7 support help you to become a perfect candidate for any job. Do not lose your chance to become the One. Kickresume | Best Online Resume & Cover Letter Builder [](https://www.kickresume.com/) Create your best resume yet. Online resume and cover letter builder used by 1,300,000 job seekers worldwide. Professional templates approved by recruiters. ResumeMaker.Online | Create a Professional Resume for Free [](https://www.resumemaker.online/) Save time with the easiest-to-use Resume Maker Online. Create an effective resume in just minutes and land your dream job. No Sign-up required, start now! Interviews Interview Warmup - Grow with Google [](https://grow.google/certificates/interview-warmup/) A quick way to prepare for your next interview. Practice key questions, get insights about your answers, and get more comfortable interviewing. No code website builder Carrd - Simple, free, fully responsive one-page sites for pretty much anything [](https://carrd.co/) A free platform for building simple, fully responsive one-page sites for pretty much anything. Webflow: Create a custom website | No-code website builder [](https://webflow.com/) Create professional, custom websites in a completely visual canvas with no code. Learn how to create a website by trying Webflow for free! Google Sites: Sign-in [](https://sites.google.com/) FlutterFlow - Build beautiful, modern apps incredibly fast! [](https://flutterflow.io/) FlutterFlow lets you build apps incredibly fast in your browser. Build fully functional apps with Firebase integration, API support, animations, and more. Export your code or even easier deploy directly to the app stores! Free Website Builder: Build a Free Website or Online Store | Weebly [](https://www.weebly.com/) Weebly’s free website builder makes it easy to create a website, blog, or online store. Find customizable templates, domains, and easy-to-use tools for any type of business website. Glide • No Code App Builder • Nocode Application Development [](https://www.glideapps.com/) Create the apps your business needs, without coding, waiting or overpaying. Get started for free and build an app today Adalo - Build Your Own No Code App [](https://www.adalo.com/) Adalo makes creating apps as easy as putting together a slide deck. Turn your idea into a real native app — no code needed! Siter.io - The collaborative web design tool, no-code website builder [](https://siter.io/) Siter.io is a visual website builder for designers. Prototype, design, and create responsive websites in the browser. Work together with your team in one place. Elementor: #1 Free WordPress Website Builder | Elementor.com [](https://elementor.com/) Elementor is the platform web creators choose to build professional WordPress websites, grow their skills, and build their business. Start for free today! No code app builder | Bravo Studio [](https://www.bravostudio.app/) Your no-code mobile app builder for iOS and Android. Create MVP’s, validate ideas and publish on App Store and Google Play Store. Home [](https://typedream.com/) The simplest way to build a website with no-code, as easy as writing on Notion. Try Typedream for free and upgrade for custom domains, collaborators, and unlimited pages. Free Website Builder | Create a Free Website | Wix.com [](https://www.wix.com/) Create a website with Wix’s robust website builder. With 900+ strategically designed templates and advanced SEO and marketing tools, build your brand online today. Free responsive Emails & Landing Pages drag-and-drop Editor | BEE [](https://beefree.io/) Free responsive emails and landing pages editor. With BEE drag-and-drop builders embedded in many software applications you can start designing now! Home [](https://typedream.com/) The simplest way to build a website with no-code, as easy as writing on Notion. Try Typedream for free and upgrade for custom domains, collaborators, and unlimited pages. Ownit Connected Checkout [](https://www.ownit.co/) Ownit Connected Checkout Bookmark.com | No-code Website Builder to Start Your Business [](https://www.bookmark.com/) Our AI powered platform ensures your business is future proof. Try Bookmark for free. The best way to build web apps without code | Bubble [](https://bubble.io/) Bubble introduces a new way to build software. It’s a no-code tool that lets you build SaaS platforms, marketplaces and CRMs without code. Bubble hosts all web apps on its cloud platform. Responsive Web Design | Website Creation | Editor X [](https://www.editorx.com/) Experience the future of website design with responsive layouts, CSS precision and smooth drag and drop. Create a Website for Free. Tilda Website Builder [](https://tilda.cc/) Create a website, online store, landing page with Tilda intuitive website builder. Build your site from hundreds of pre-designed templates and publish it today. No code required. No-code headless commerce and websites | Unstack Inc. [](https://www.unstack.com/) Deploy high performance eCommerce storefronts and websites without the engineering overhead using Unstack's no-code CMS Best Drag-and-Drop Website Builder | Jemi [](https://jemi.so/) The modern website builder for creatives, entrepreneurs, and dreamers. Build a beautiful link in bio site, portfolio, or landing page in minutes. No-code website builder that works like Notion [](https://popsy.co/) Create a beautiful no-code website in minutes. Popsy works just like Notion but is built from the ground up for building websites. Choose a free template. Edit content just like in Notion. Customize styles without code. Free Notion icons and illustrations. Unbounce - The Landing Page Builder & Platform [](https://unbounce.com/) Grow your relevance, leads, and sales with Unbounce. Use Unbounce to easily create and optimize landing pages for your small business and boost conversions with AI insights. Low-code Front-end Design & Development Platform | TeleportHQ [](https://teleporthq.io/) Front-end development platform, with a visual builder and headless content modelling capabilities. Static website creation, and UI development tools. Other tools used in no code website MemberSpace - Turn any part of your website into members-only with just a few clicks [](https://www.memberspace.com/) Create memberships on your website for anything you want like courses, video tutorials, member directories, and more while having 100% control over look & feel. Triggre | The number one true no-code platform to run your business [](https://www.triggre.com/) The best no-code platform to create highly advanced business applications in hours, without programming. Try it now for free! 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teach-AI-in-business
github
LLM Vibe Score0.443
Human Vibe Score0.018525334165293606
aenyneJan 9, 2025

teach-AI-in-business

Teaching AI in Business ![HitCount] I am collecting material for teaching AI-related issues to non-tech people. The links should provide for a general understanding of AI without going too deep into technical issues. Please contribute! Make this Issue your First Issue I am collecting material for teaching AI-related issues to non-tech people. The links should have provide for a general understanding of AI without going too deep into technical issues. Please contribute! Kindly use only those Resources with NO CODE NEW Check out also the AI Wiki NEW Online Videos & Courses | Link to Issue | Description | |---|---| | Top Trending Technologies | Youtube Channel to master top trending technologyies including artificial intelligence | | AI4All | AI 4 All is a resource for AI facilitators to bring AI to scholars and students | | Elements of AI | Elements of AI is a free open online course to teach AI principles | | Visual Introduction to Machine Learning | Visual introduction to Machine Learning is a beautiful website that gives a comprehensive introduction and easily understood first encounter with machine learning | | CS50's Introduction to Artificial Intelligence with Python | Learn to use machine learning in Python in this introductory course on artificial intelligence.| | Crash course for AI | This is a fun video series that introduces students and educators to Artificial Intelligence and also offers additional more advanced videos. Learn about the basics, neural networks, algorithms, and more. | Youtuber Channel Machine Learning Tutorial | Youtube Channel Turorial Teachable Machine for beginner | | Artificial Intelligence (AI) |Learn the fundamentals of Artificial Intelligence (AI), and apply them. Design intelligent agents to solve real-world problems including, search, games, machine learning, logic, and constraint satisfaction problems | | AI For Everyone by Andrew Ng | AI For Everyone is a course especially for people from a non-technical background to understand AI strategies | | How far is too far? The age of AI| This is a Youtube Orignals series by Robert Downey| | Fundamentals of Artificial Intelligence|This course is for absolute beginners with no technical knowledge.| | Bandit Algorithm (Online Machine Learning)|No requirement of technical knowledge, but a basic understending of Probability Ttheory would help| | An Executive's Guide to AI|This is an interactive guide to teaching business professionals how they might employ artificial intelligence in their business| | AI Business School|Series of videos that teach how AI may be incorporated in various business industries| | Artificial Intelligence Tutorial for Beginners | This video will provide you with a comprehensive and detailed knowledge of Artificial Intelligence concepts with hands-on examples. | | Indonesian Machine Learning Tutorial | Turorial Teachable Machine to train a computer for beginner | | Indonesian Youtube Playlist AI Tutorial | Youtube Playlist AI Tutorial For Beginner | | Artificial Intelligence Search Methods For Problem Solving By Prof. Deepak Khemani|These video lectures are for absolute beginners with no technical knowledge| | AI Basics Tutorial | This video starts from the very basics of AI and ML, and finally has a hands-on demo of the standard MNIST Dataset Number Detection model using Keras and Tensorflow.| | Simple brain.js Tutorial | This video explains a very simple javascript AI library called brain.js so you can easily run AI in the browser.| | Google AI| A complete kit for by google official for non-tech guy to start all over from basics, till advanced | | Microsoft AI for Beginners| A self-driven curriculum by Microsoft, which includes 24 lessons on AI. | Train Your Own AI | Link to Issue | Description | |---|---| | Teachable Machine | Use Teachable Machine to train a computer to recognize your own images, sounds, & poses | | eCraft2Learn | Resource and interactive space (Snap, a visual programming environment like Scratch) to learn how to create AI programs | | Google Quick Draw | Train an AI to guess from drawings| | Deepdream Generator| Merge Pictures to Deep Dreams using the Deepdream Generator| | Create ML|Quickly build and train Core ML models on your Mac with no code.| | What-If Tool|Visually probe the behavior of trained machine learning models, with minimal coding.| | Metaranx|Use and build artificial intelligence tools to analyze and make decisions about your data. Drag-and-drop. No code.| | obviously.ai|The total process of building ML algorithms, explaining results, and predicting outcomes in one single click.| Articles | By & Title | Description | |---|---| | Artificial Intelligence | Wikipedia Page of AI | | The Non-Technical AI Guide | One of the good blog post that could help AI more understandable for people without technical background | | LIAI | A detailed introduction to AI and neural networks | | Layman's Intro | A layman's introduction to AI | | AI and Machine Learning: A Nontechnical Overview | AI and Machine Learning: A Nontechnical Overview from OREILLY themselves is a guide to learn anyone everything they need to know about AI, focussed on non-tech people | | What business leaders need to know about artifical intelligence|Short article that summarizes the essential aspects of AI that business leaders need to understand| | How Will No-Code Impact the Future of Conversational AI | A humble explanation to the current state of converstational AI i.e.Chatbots and how it coul evolve with the current trend of no coding. | | Investopedia | Basic explanation of what AI is in a very basic and comprehensive way | | Packtpub | A non programmer’s guide to learning Machine learning | | Builtin | Artificial Intelligence.What is Artificial Intelligence? How Does AI Work? | | Future Of Life | Benefits & Risks of Artificial Intelligence | | NSDM India -Arpit | 100+ AI Tools For Non-Coders That Will Make Your Marketing Better. | | AI in Marketing for Startups & Non-technical Marketers | A practical guide for non-technical people | | Blog - Machine Learning MAstery | Blogs and Articles by Jason Browniee on ML | | AI Chatbots without programming| Chatbots are increasingly in demand among global businesses. This course will teach you how to build, analyze, deploy and monetize chatbots - with the help of IBM Watson and the power of AI.| Book Resources for Further Reading | Author | Book | Description & Notes | |---|---|---| | Ethem Alpaydin|Machine Learning: The New AI | Graph Theory with Applications to Engineering & Computer Science. A concise overview of machine learning—computer programs that learn from data—which underlies applications that include recommendation systems, face recognition, and driverless cars. | | Charu C. Aggarwal| Neural Networks and Deep Learning | This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. | | Hal Daumé III | A Course in Machine Learning | The purpose of this book is to provide a gentle and pedagogically organized introduction to the field. A second goal of this book is to provide a view of machine learning that focuses on ideas and models, not on math. | | Ian Goodfellow and Yoshua Bengio and Aaron Courville| Deep Learning | The book starts with a discussion on machine learning basics, including the applied mathematics and algorithms needed to effectively study deep learning from an academic perspective. There is no code covered in the book, making it perfect for a non-technical AI enthusiast. | | Peter Harrington|Machine Learning in Action| (Source: https://github.com/kerasking/book-1/blob/master/ML%20Machine%20Learning%20in%20Action.pdf) This book acts as a guide to walk newcomers through the techniques needed for machine learning as well as the concepts behind the practices.| | Jeff Heaton| Artificial Intelligence for Humans |This book helps its readers get an overview and understanding of AI algorithms. It is meant to teach AI for those who don’t have an extensive mathematical background. The readers need to have only a basic knowledge of computer programming and college algebra.| | John D. Kelleher, Brian Mac Namee and Aoife D'Arcy|Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies (The MIT Press)|This book covers all the fundamentals of machine learning, diving into the theory of the subject and using practical applications, working examples, and case studies to drive the knowledge home.| | Deepak Khemani| [A First Course in Artificial Intelligence] | It is an introductory course on Artificial Intelligence, a knowledge-based approach using agents all across and detailed, well-structured algorithms with proofs. This book mainly follows a bottom-up approach exploring the basic strategies needed problem-solving on the intelligence part. | | Maxim Lapan | Deep Reinforcement Learning Hands-On - Second Edition | Deep Reinforcement Learning Hands-On, Second Edition is an updated and expanded version of the bestselling guide to the very latest reinforcement learning (RL) tools and techniques. It provides you with an introduction to the fundamentals of RL, along with the hands-on ability to code intelligent learning agents to perform a range of practical tasks. | | Tom M Mitchell | Machine Learning | This book covers the field of machine learning, which is the study of algorithms that allow computer programs to automatically improve through experience. The book is intended to support upper level undergraduate and introductory level graduate courses in machine learning. | | John Paul Mueller and Luca Massaron|Machine Learning For Dummies|This book aims to get readers familiar with the basic concepts and theories of machine learning and how it applies to the real world. And "Dummies" here refers to absolute beginners with no technical background.The book introduces a little coding in Python and R used to teach machines to find patterns and analyze results. From those small tasks and patterns, we can extrapolate how machine learning is useful in daily lives through web searches, internet ads, email filters, fraud detection, and so on. With this book, you can take a small step into the realm of machine learning and we can learn some basic coding in Pyton and R (if interested)| | Michael Nielsen| Neural Networks and Deep Learning |Introduction to the core principles of Neural Networks and Deep Learning in AI| | Simon Rogers and Mark Girolami| A Course in Machine Learning |A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations of Bayesian analysis in the simplest of settings, and goes all the way to the frontiers of the subject such as infinite mixture models, GPs, and MCMC.| |Peter Norvig| Paradigm of Artificial Intelligence Programming |Paradigms of AI Programming is the first text to teach advanced Common Lisp techniques in the context of building major AI systems. By reconstructing authentic, complex AI programs using state-of-the-art Common Lisp, the book teaches students and professionals how to build and debug robust practical programs, while demonstrating superior programming style and important AI concepts.| | Stuart Russel & Peter Norvig | Artificial Intelligence: A Modern Approach, 3rd Edition | This is the prescribed text book for my Introduction to AI university course. It starts off explaining all the basics and definitions of what AI is, before launching into agents, algorithms, and how to apply them. Russel is from the University of California at Berkeley. Norvig is from Google.| | Richard S. Sutton and Andrew G. Barto| Reinforcement Learning: An Introduction |Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment.| | Alex Smola and S.V.N. Vishwanathan | Introduction to Machine Learning | Provides the reader with an overview of the vast applications of ML, including some basic tools of statistics and probability theory. Also includes discussions on sophisticated ideas and concepts. | | Shai Shalev-Shwartz and Shai Ben-David | Understanding Machine Learning From Theory to Algorithms |The primary goal of this book is to provide a rigorous, yet easy to follow, introduction to the main concepts underlying machine learning. | | Chandra S.S.V | Artificial Intelligence and Machine Learning | This book is primarily intended for undergraduate and postgraduate students of computer science and engineering. This textbook covers the gap between the difficult contexts of Artificial Intelligence and Machine Learning. It provides the most number of case studies and worked-out examples. In addition to Artificial Intelligence and Machine Learning, it also covers various types of learning like reinforced, supervised, unsupervised and statistical learning. It features well-explained algorithms and pseudo-codes for each topic which makes this book very useful for students. | | Oliver Theobald|Machine Learning For Absolute Beginners: A Plain English Introduction|This is an absolute beginners ML guide.No mathematical background is needed, nor coding experience — this is the most basic introduction to the topic for anyone interested in machine learning.“Plain” language is highly valued here to prevent beginners from being overwhelmed by technical jargon. Clear, accessible explanations and visual examples accompany the various algorithms to make sure things are easy to follow.| | Tom Taulli | Artificial Intelligence Basics: A Non-Technical Introduction | This book equips you with a fundamental grasp of Artificial Intelligence and its impact. It provides a non-technical introduction to important concepts such as Machine Learning, Deep Learning, Natural Language Processing, Robotics and more. Further the author expands on the questions surrounding the future impact of AI on aspects that include societal trends, ethics, governments, company structures and daily life. | |Cornelius Weber, Mark Elshaw, N. Michael Mayer| Reinforcement Learning |Learning is a very important aspect. This book is on reinforcement learning which involves performing actions to achieve a goal. The first 11 chapters of this book describe and extend the scope of reinforcement learning.| |John D. Kelleher, Brian Mac Namee, Aoife D'arcy| Algorithms, Worked Examples, and Case Studies | A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. |

How to Get Rich with AI: The Complete Beginner’s Blueprint
youtube
LLM Vibe Score0.466
Human Vibe Score0.92
Liam OttleyOct 24, 2024

How to Get Rich with AI: The Complete Beginner’s Blueprint

🚀 FREE 6 MONTH ROADMAP: https://b.link/fzslezrl 📚 Join the #1 community for AI entrepreneurs and connect with 100,000+ members: https://b.link/dvlv77f6 📈 We help industry experts, entrepreneurs & developers build and scale their AI Agency: https://b.link/bcm31sqg 🤝 Need Al solutions built? Work with me: https://b.link/hmr6o3uz 🛠 Build Al agents without coding: https://b.link/7htw9o3k 🚀 Apply to Join My Team at Morningside AI: https://tally.so/r/wbYr52 Interview w/ Isaiah: https://youtu.be/8EIQy0XJW4w My Plan to Scale Morningside: https://youtu.be/YnhD9pEiMVQ How to Price AI Services: https://youtu.be/1L0ghc5ofLo Discover the complete beginner's blueprint to getting rich with AI, even if you're starting from scratch. In this video, I’ve compiled the exact steps and best strategies that I used to run 5 successful AI businesses. If you want to learn how to start an AI Automation Agency (AAA) or AI business, this video guides you through the essential skills and tools you need to thrive in the AI industry. Timestamps: 0:00 - What We’re Covering 0:59 - Three Parts of This Video 1:43 - Current State of the Economy 3:31 - The AI Landscape 4:12 - Business #1 6:19 - Business #2 8:03 - Business #3 10:15 - Business #4 11:43 - Business #5 13:37 - Where to Start 16:32 - 3 Phases of AI Business 17:13 - Phase #1 18:56 - Phase #2 20:27 - Phase #3 22:42 - 6 Month Plan 24:23 - Final Note

How To Service Your First AI Automation Agency Client In 2024 (Make.com)
youtube
LLM Vibe Score0.368
Human Vibe Score0.48
Nick SaraevAug 13, 2024

How To Service Your First AI Automation Agency Client In 2024 (Make.com)

GET THE FREE GAMMA + TEMPLATES HERE 🙏 https://gamma.app/docs/How-to-Successfully-Service-Your-First-Automation-Client-in-2024-3xpyq1tyhppm1jv JOIN MY AUTOMATION COMMUNITY & GET YOUR FIRST CUSTOMER, GUARANTEED 👑 https://www.skool.com/makerschool/about SUMMARY ⤵️ Complete guide on servicing your first AI automation agency client in 2024. I run you through the workflow from end-to-end, including pre-project, kickoff, onboarding, progress updates, delivery emails, and upsells. WHAT TO WATCH NEXT 🍿 How I Hit $25K/Mo Selling Automation: https://youtube.com/watch?v=T7qAiuWDwLw My $21K/Mo Make.com Proposal System: https://youtube.com/watch?v=UVLeX600irk Generate Content Automatically With AI: https://youtube.com/watch?v=P2Y_DVW1TSQ MY SOFTWARE, TOOLS, & DEALS (some of these give me kickbacks—thank you!) 🚀 INSTANTLY: https://link.nicksaraev.com/instantly-short 📧 ANYMAIL FINDER: https://link.nicksaraev.com/amf-short 👻 PHANTOMBUSTER: https://link.nicksaraev.com/pb-short ✅ CLICKUP: https://link.nicksaraev.com/clickup-short 📈 RIZE: https://link.nicksaraev.com/rize-short (use promo code NICK for addn 25% off) WHAT TO WATCH NEXT 🍿 HOW I HIT $25K/MO SELLING AUTOMATION: https://youtube.com/watch?v=T7qAiuWDwLw MY $21K/MO MAKE.COM PROPOSAL SYSTEM: https://youtube.com/watch?v=UVLeX600irk GENERATE CONTENT AUTOMATICALLY WITH AI: https://youtube.com/watch?v=P2Y_DVW1TSQ FOLLOW ME ✍🏻 My content writing agency: https://1secondcopy.com 🦾 My automation agency: https://leftclick.ai 🕊️ My Twitter/X: https://twitter.com/nicksaraev 🤙 My blog (followed by the founder of HubSpot!): https://nicksaraev.com WHY ME? If this is your first watch—hi, I’m Nick! TLDR: I spent five years building automated businesses with Make.com (most notably 1SecondCopy, a content company that hit 7 figures). Today a lot of people talk about automation, but I’ve noticed that very few have practical, real world success making money with it. So this channel is me chiming in and showing you what real systems that make real revenue look like! Hopefully I can help you improve your business, and in doing so, the rest of your life :-) Please like, subscribe, and leave me a comment if you have a specific request! Thanks. Timestamps 0:00 Introduction to Servicing Your Automation Client 0:39 The Importance of Client Retention 2:03 Understanding Your Role as a Service Provider 2:54 The Significance of Client Acquisition Time 8:06 Setting Expectations with the Client 14:53 Implementing a Structured Onboarding Process 16:11 Testing the Flow of the Project 18:18 Delivering Progress Updates to Clients 19:13 Utilizing Templates for Project Efficiency 22:32 Utilizing Project Update and Delivery Templates 25:46 Enhancing Client Relationships with Delivery Templates 28:12 Importance of Service in Service Provider Role

AI Tools for Small Business - 7 Ways Small Business Can Use AI Today
youtube
LLM Vibe Score0.346
Human Vibe Score0.47
Philip VanDusenMar 26, 2024

AI Tools for Small Business - 7 Ways Small Business Can Use AI Today

Extended 30 Day HighLevel Trial: https://www.gohighlevel.com/philipvandusen So, how can small businesses leverage all the AI tools that are flooding the market? There is so much it’s overwhelming! As small businesses navigate the competitive landscape, AI technologies offer a lifeline, enabling smarter decisions, enhanced customer connections, and expansion into new markets. From revolutionizing content creation with tools like ChatGPT to transforming social media strategies and personalizing email marketing, AI is redefining how small businesses engage with their audience. We’ll dive deep into using AI for marketing automation, competitor insights, local SEO mastery, engaging customers through chatbots, and converting website visitors into loyal customers. With practical insights and our sponsor HighLevel's platform, small businesses can now leverage AI tools to optimize their operations and marketing efforts. Keywords: AI Tools, Small Business, Growth, AI Technologies, Smarter Decisions, Customer Connections, Markets, Content Creation, ChatGPT, Social Media Strategies, Email Marketing, Personalizing, CRM, Marketing Automation, Competitor Insights, Local SEO, Chatbots, Converting Website Visitors, Operations, HighLevel #ai #smallbusiness #marketing WEBSITE https://www.philipvandusen.com BRAND•MUSE NEWSLETTER https://www.philipvandusen.com/muse BONFIRE: The Mastermind Community for Established Creative Pros https://philipvandusen.com/bonfire CREATIVE PROFESSIONAL COACHING https://philipvandusen.com/oneonone BRAND CONSULTING https://philipvandusen.com/brand-consulting BRAND STRATEGY 101 COURSE https://philipvandusen.com/bs101 BRAND DESIGN MASTERS PODCAST https://podcast.branddesignmasters.com/subscribe YOUTUBE https://www.youtube.com/c/philipvandusen LINKEDIN https://www.linkedin.com/in/philipvandusen/ THREADS https://www.threads.net/@philipvandusen FACEBOOK https://www.facebook.com/philipvandusen.agency/ INSTAGRAM https://www.instagram.com/philipvandusen/ BRAND DESIGN MASTERS FACEBOOK GROUP https://www.facebook.com/groups/branddesignmasters/ AFFILIATE PARTNERS: Bring Your Own Laptop - Adobe Training with Daniel Scott https://www.byol.me/philip GO HIGHLEVEL: https://www.gohighlevel.com/philipvandusen Tubebuddy https://www.tubebuddy.com/philipvandusen Philip VanDusen is a branding consultant and the owner of a brand strategy and design agency based in New Jersey. Philip is a highly accomplished creative executive and expert in brand strategy, graphic design, marketing and creative management. Philip provides design, branding, marketing, career and business advice to creative professionals, entrepreneurs and companies on building successful brands for themselves and the clients and customers they serve.

How to Start an AI Business in 2025 - STEP BY STEP
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LLM Vibe Score0.45
Human Vibe Score0.72
Liam OttleyMar 3, 2024

How to Start an AI Business in 2025 - STEP BY STEP

📚 Join the #1 community for AI entrepreneurs and connect with 100,000+ members: https://bit.ly/3uRIRB3 📈 We help industry experts, entrepreneurs & developers build and scale their AI Agency: https://b.link/9kmmllts 🤝 Need AI Solutions Built? Work with me: https://b.link/qv62vqy6 ⚒️ Build AI Agents Without Coding: https://agentivehub.com/ 🚀 Apply to Join My Team at Morningside AI: https://tally.so/r/wbYr52 NOTE ON AI LIAM: AI Liam has been shut down and replaced with a free course that is updated frequently on my Free Skool community. At Morningside we no longer had the bandwidth to continue updating AI Liam with the features and info it needed, so have opted for a free course instead: https://bit.ly/3uRIRB3 I also do weekly Q&As so you can ask me questions directly! I'll see you inside, Liam 💪🏼 Learn How to Start an Online AI Business as a Beginner in 2024 with my complete, step by step guide. Making money with AI and making money with ChatGPT are huge opportunities in the online business space, but knowing whether to start an AI education business, AI Automation Agency, AI consulting business, AI SaaS or become an AI freelancer can be difficult as a beginner. If you're interested in becoming an AI entrepreneur in 2024 and starting your own AI business, this video is the one for you! I cover five different types of AI business ideas that you can start to make money online with AI, and how to get started with each. Other Resources/Links Mentioned 🔗 GPTs Complete Guide: https://youtu.be/Hh2zqaf0Fvg?si=oq5Emaf-co3nXzID Prompt Engineering Beginners Guide: https://youtu.be/ydjRYmM19DY?si=adwasE8fULHzcUYh Prompt Engineering Advanced Guide: https://youtu.be/-XivIt5oSw?si=dmhA1doWEjPI5ni Custom Tooling w/ Relevance AI: https://youtu.be/_sNGuQz-LyY?si=AJAnexuw9kDU30fF Dave's Channel (FOR AI FREELANCERS): https://www.youtube.com/@daveebbelaar Timestamps: 0:00 - Intro 3:06 - Why Listen to Me? 6:43 - Chapter 1: Is AI Business Right For You? 7:30 - Is Entrepreneurship Right For You? 11:01 - Do I Need to be a Developer? 12:01 - How Much Time do I Need to Invest? 13:57 - Why Start an AI Business? 19:58 - Chapter 2: 5 Types of AI Businesses 20:32 - AI Business #1 25:17 - AI Business #2 30:33 - AI Business #3 36:37 - AI Business #4 39:27 - AI Business #5 41:34 - How AI Businesses Are Connected 52:52 - Chapter 3: AI Business Core Skills 53:21 - Skill #1 59:52 - Skill #2 1:10:25 - Skill #3 1:22:41 - Skill #4 1:24:50 - Skill #5 1:27:49 - Skill #6 1:29:18 - Chapter 4: Step-by-Step Launch Guide

13 Best AI Tools For Startups & Entrepreneurs [2024]
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LLM Vibe Score0.401
Human Vibe Score0.33
Business SolutionDec 15, 2023

13 Best AI Tools For Startups & Entrepreneurs [2024]

Here are the best AI tools for startups and entrepreneurs: Bubble ▶ Bubble free plan: https://businessolution.org/get/bubble/ Taskade ▶ Taskade free plan : https://businessolution.org/get/taskade/ Process Street ▶ Process Street free trial: https://businessolution.org/get/process-street/ CustomGPT ▶ Try CustomGPT for free: https://businessolution.org/get/customgpt/ MeetGeek ▶ MeetGeek free plan: https://businessolution.org/get/meetgeek-ai/ Mixo ▶ Try Mixo for free: https://businessolution.org/get/mixo/ Tidio ▶ Tidio free plan (+20% OFF): https://businessolution.org/get/tidio/ AdCreative.ai ▶ AdCreative.ai 25% OFF: https://businessolution.org/get/adcreative/ LeadFuze ▶ LeadFuze free trial: https://businessolution.org/get/leadfuze/ HubSpot ▶ HubSpot free plan: https://businessolution.org/get/hubspot/ ClickFunnels 2.0 ▶ ClickFunnels 2.0 free trial: https://businessolution.org/get/clickfunnels-2-0/ GoHire ▶ GoHire free trial: https://businessolution.org/get/gohire-2/ DeepBrain ▶ Try DeepBrain for free: https://businessolution.org/get/deepbrain/ Timestamps: 0:00 – AI Tools for Startups 0:17 – Bubble.io 2:26 – Taskade 4:35 – Process Street 6:20 – CustomGPT 7:44 – MeetGeek 8:31 – Mixo 9:09 – Tidio 10:15 – AdCreative.ai 11:34 – LeadFuze 12:51 – HubSpot 14:48 – ClickFunnels 2.0 16:10 – GoHire 17:25 – DeepBrain 👉‍ See all 17 AI tools for startups in this article: https://businessolution.org/ai-tools-for-startups/ In today's fast-paced and competitive business landscape, startups are constantly seeking innovative ways to gain a competitive edge and drive growth. Enter the realm of artificial intelligence (AI) tools for startups – a game-changing technology that holds the potential to revolutionize how new businesses operate, strategize, and scale. From automating repetitive tasks to unlocking valuable insights from data, AI tools offer startups an unprecedented opportunity to streamline operations, enhance decision-making, and deliver exceptional customer experiences. Imagine having access to intelligent algorithms that can analyze market trends, predict consumer behavior, and optimize resource allocation with unparalleled accuracy. These AI tools can empower startups to make data-driven decisions with confidence while freeing up valuable time and resources for creative problem-solving and strategic planning. By harnessing the power of AI technology, startups can navigate the complexities of today's business environment with agility, precision, and scalability like never before. Join us as we delve into the world of AI tools for startups and explore how this transformative technology is poised to reshape the entrepreneurial landscape in profound ways.

5 Genius Ways to Make Money From Home (Using AI)
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Human Vibe Score0.77
Charlie ChangNov 15, 2023

5 Genius Ways to Make Money From Home (Using AI)

Check out Fundrise to get started with investing in pre-IPO blue-chip companies that are leading the AI industry: http://fundrise.com/charliechang #fundrisetestimonial #fundrisepartner In this video, I'm going to share 5 genius ways to make money online, using AI (that are all proven). I'll also give you a clear outline and show you exactly how to leverage these new AI opportunities to make money online. ► Daily advice and BTS on my Instagram: https://www.instagram.com/charliechang/ ► Get access to my FREE side hustle courses: https://www.sidehustlemastery.com My favorite business must-haves: 💳 Best business credit cards: https://yourbestcreditcards.com/card-finder/?ccid=2004 🏦 Novo (best business bank): https://startupwise.com/novo 🖥️ Best AI website builder ($3/month using code CHARLIECHANG): https://hostinger.com/charliechang ⚙️ Northwest (best $39 LLC formation service): https://startupwise.com/northwestLLC 🥇 Hire top 1% overseas talent: https://paired.so Whether it's optimizing businesses, doing social media management, or investing in pre-IPO tech companies, there are so many interesting opportunities that are out there for you guys to take advantage of. I highly encourage every aspiring entrepreneur out there to find a way to use AI because this can absolutely change the efficiency and output of your business. If you liked the video, and you want to see more videos on AI and making money, check out my videos: How To Use ChatGPT To Learn ANY Skill Quickly (Tutorial): https://www.youtube.com/watch?v=vYvOTGk7hOA 5 Passive Income Ideas - How I ACTUALLY Make $35K/Week in 2023 https://youtu.be/TVLgIKMOYJ0 I hope you guys found this video helpful, and if you did please share it with a friend or family member who you think could benefit and also LIKE and SUBSCRIBE for more videos like this in the future! Thank you for watching and I hope you have a wonderful rest of your day! – Charlie #AI #Money #SideHustle Timeline: 0:00 - Introduction 0:28 - Social Media Management Business 3:11 - AI Optimization Agency 5:41 - Investing in Pre-IPO AI Companies With Fundrise 8:12 - Building an E-commerce Business 10:00 - AI Automated Affiliate Marketing Business 11:12 - Conclusion 11:40 - Outro Disclaimer: Some of the links above may be affiliate links, which means that if you click on them I may receive a small commission. The retailers and financial services companies pay the commission at no cost to you, and this helps to support our channel and keep our videos free. Thank you! In addition, I am not a financial advisor. Charlie Chang does not provide tax, legal or accounting advice. The ideas presented in this video are for entertainment purposes only. Please do your own due diligence before making any financial decisions. ► My Instagram: https://www.instagram.com/charliechang/

How I'd Learn AI in 2025 (if I could start over)
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LLM Vibe Score0.406
Human Vibe Score0.92
Dave EbbelaarAug 4, 2023

How I'd Learn AI in 2025 (if I could start over)

Here's the roadmap that I would follow to learn artificial intelligence (AI). 📚 Get the FREE roadmap here ➡️ https://bit.ly/data-alchemy Already got tech skills and want to start as a freelancer? 🛠️ Let me show you how: https://www.datalumina.com/data-freelancer?utmsource=youtube&utmmedium=video&utmcampaign=youtubevideotraffic&utmcontent=How%20I%27d%20Learn%20AI%20in%202024%20%28if%20I%20could%20start%20over%29 ⏱️ Timestamps 00:00 Introduction 00:34 Why learn AI? 01:28 Code vs. Low/No-code approach 02:27 Misunderstandings about AI 03:27 Ask yourself this question 04:19 What makes this approach different 05:42 Step 1: Set up your environment 06:54 Step 2: Learn Python and key libraries 08:02 Step 3: Learn Git and GitHub Basics 08:35 Step 4: Work on projects and portfolio 13:12 Step 5: Specialize and share knowledge 14:31 Step 6: Continue to learn and upskill 15:39 Step 7: Monetize your skills 16:53: What is Data Alchemy? 🛠️ Explore ProjectPro https://bit.ly/3q837w8 👋🏻 About Me Hey there! I'm Dave, an AI Engineer and the founder of Datalumina, where our mission is to facilitate entrepreneurial and technological proficiency in professionals and businesses. Through my videos here on this channel, my posts on LinkedIn, and courses on Skool, I share practical strategies and tools to navigate the complexities of data, artificial intelligence, and entrepreneurship. ✔️ How I manage my business and dev projects https://try.web.clickup.com/datalumina 📥 Datalumina's Newsletter https://www.datalumina.com/newsletter #ai #roadmap #datalumina 📌 Video Description In this video, Dave shares a comprehensive and actionable roadmap for anyone looking to start their journey into the exciting world of artificial intelligence (AI) in 2024. Whether you're a complete beginner or someone looking to pivot your career towards AI, this video lays out a step-by-step guide that demystifies the process of learning AI from the ground up. Dave highlights the significance of AI in today's tech landscape and addresses common misconceptions that newcomers might have. With a focus on practical learning, the video emphasizes the importance of choosing between a code-centric or a low/no-code approach, making AI accessible to a broader audience. Dave's unique approach involves asking a critical question that shapes the learning path, ensuring that viewers embark on a journey tailored to their goals and interests. The roadmap detailed in the video covers essential steps such as setting up your learning environment, mastering Python and key libraries crucial for AI, understanding the basics of Git and GitHub, and the importance of working on projects to build a strong portfolio. Dave also talks about the importance of specialization and the continuous process of learning and upskilling in fields like generative AI, large language models, chatbots, and machine learning. Furthermore, Dave shares insights on how to monetize your AI skills, turning your passion into a profession. The video concludes with an introduction to Data Alchemy, a concept that encapsulates the transformative power of AI knowledge. For those eager to dive into the AI world, Dave offers a free roadmap accessible through the link provided in the video description. This invaluable resource serves as a compass for navigating the complexities of AI learning, making it an essential watch for anyone interested in artificial intelligence, machine learning, and related technologies.

Best AI Tools for Accountants
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LLM Vibe Score0.36
Human Vibe Score0.21
Miles EducationJun 28, 2023

Best AI Tools for Accountants

We’re pretty sure, these great AI tools will help you in the long run. Let’s have a look at their importance: VIC.AI: AI-powered Accounting Made Effortless! Their advanced algorithms are trained on vast invoice data, eliminating the need for templates or memorization. Accurate from day one, their Autopilot technology seamlessly integrates AI for streamlined invoicing.😇 Indy: AI-Powered Accounting Made Fast and Affordable! Freelancers, businesses, and entrepreneurs can tackle accounting tasks up to 20x faster than traditional software. Create income statements and financial statements in a fraction of the time, all at a lower cost than traditional accountants.🤔 Docyt: AI-Powered Accounting Automation for Faster Decision Making. Digitize financial data, automate workflows, and make faster decisions. Reduce costs and simplify bookkeeping and back-office tasks.😲 Blue Dot is an innovative market leader with a cutting-edge financial platform. Their all-in-one Tax Compliance Platform combines digitization, tax compliance, and automation to analyze employee spend data for VAT, Taxable Employee Benefits, and Corporate Income Tax.🥹 Comment below the names of the AI tools that you use for accounting.👇👇 #aitoolsforaccountants #aitools #ai #technology #upskill #cpa #uscpa #CPAexam #cpajobs #CPAscope #MilesEducation #workintheus #talent #fyp #explore #accounting #accountants #accountancy #cpacoursereview #jobopportunities #CPAplacement #CPAsalary #success #career

How to use Copy.ai | Best AI writing software for small business (Copy.ai tutorial)
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LLM Vibe Score0.377
Human Vibe Score0.53
Stewart GauldMay 26, 2023

How to use Copy.ai | Best AI writing software for small business (Copy.ai tutorial)

In this AI writing software tutorial, I share how to use Copy AI to save your business time and money in 2023. AI writing software or AI writing assistance is growing at an exponential rate. One of the most popular AI tools that leverage Open AI is Copy AI. Rather than spending hours manually creating written content for blogs, social media, emails, reports and more, you can leverage the support of AI. AI allows you to create unique and personalised content in minutes. With the support of Copy AI, you can multiply the speed of your writing activities and process. 👉 Get started with Copy AI here (My favourite AI writer) ➜ https://www.copy.ai/?via=stewart-gauld *(This Copy AI link is an affiliate link, which means we will get a commission if you upgrade to a paid plan (with no extra cost to you) through this link, and this helps support our channel so we thank you in advance!) ► Looking for a simple, understandable and actionable road map for setting up your small business online? Start here and get our all-in-one small business playbook 📚: 👉 https://godigitalnow.store/products/go-digital-now-the-ultimate-small-business-playbook-ebook ► Here are some relevant resources to help you in your business journey with AI: Check out our top 6 AI writing software here: https://stewartgauld.com/best-ai-writing-software/ Read my complete Copy AI review article here: https://stewartgauld.com/copy-ai-review/ Learn how to use ChatGPT for business here: https://youtu.be/d8RnjRshcE8 Read about my top 11 AI tools for small businesses: https://stewartgauld.com/best-ai-tools/ ► Today we navigate through the below chapters for this Copy AI tutorial: 0:00 Intro 01:37 Getting started 02:36 Copy AI pricing 03:22 Copy AI dashboard 03:58 Templates 04:36 Chat by Copy AI 04:59 Prompt ideas and templates 06:08 Content editor 06:58 How to create a blog with AI 10:06 Optimize with chat AI 10:57 Copy AI tools 11:38 Managing projects 12:04 How to use templates 13:34 Outro ► Are you interested in joining our small business community? Join us to receive actionable tips, tutorials and tools to grow your small business online (Subscribe to our email list) or join our exclusive community here: https://mailchi.mp/71ac3fcdbfdf/stewart-gauld Let me know if you found this Copy AI tutorial helpful. Also, if you require any help or support, make sure to get in touch with us today. Thanks for watching and enjoy! #AI #AIwritingsoftware #copyai

The future of AI
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LLM Vibe Score0.471
Human Vibe Score0.61
GaryVeeMay 9, 2023

The future of AI

When voice and ai hit scale … shits gonna get interesting… — Thanks for watching! Join My Discord!: https://www.garyvee.com/discord Check out another series on my channel: Keynotes: https://www.youtube.com/watch?v=6vCDlmhRmBo&list=PLfA33-E9P7FCEF1izpctGGoak841XYzrJ NFTs: https://www.youtube.com/watch?v=AwMJ6bScB2s&list=PLfA33-E9P7FAcvsVSFqzSuJhHu3SkW2Ma Business Meetings: https://www.youtube.com/watch?v=wILI_VV6z4Y&list=PLfA33-E9P7FCTIY62wkqZ-E1cwpc2hxBJ Gary Vaynerchuk Original Films: https://youtube.com/playlist?list=PLfA33-E9P7FAvnrOcgy4MvIcCXxoyjuku Trash Talk: https://youtube.com/playlist?list=PLfA33-E9P7FDelN4bXFgtJuczC9HHmm2- WeeklyVee: https://youtube.com/playlist?list=PLfA33-E9P7FBPjdQcF6uedz9fdk8XKn-b — Gary Vaynerchuk is a serial entrepreneur, and serves as the Chairman of VaynerX, the CEO of VaynerMedia and the Creator & CEO of VeeFriends. Gary is considered one of the leading global minds on what’s next in culture, relevance and the internet. Known as “GaryVee” he is described as one of the most forward thinkers in business – he acutely recognizes trends and patterns early to help others understand how these shifts impact markets and consumer behavior. Whether its emerging artists, esports, NFT investing or digital communications, Gary understands how to bring brand relevance to the forefront. He is a prolific angel investor with early investments in companies such as Facebook, Twitter, Tumblr, Venmo, Snapchat, Coinbase and Uber. Gary is an entrepreneur at heart — he builds businesses. Today, he helps Fortune 1000 brands leverage consumer attention through his full service advertising agency, VaynerMedia which has offices in NY, LA, London, Mexico City, LATAM and Singapore. VaynerMedia is part of the VaynerX holding company which also includes VaynerProductions, VaynerNFT, Gallery Media Group, The Sasha Group, Tracer, VaynerSpeakers, VaynerTalent, and VaynerCommerce. Gary is also the Co-Founder of VaynerSports, Resy and Empathy Wines. Gary guided both Resy and Empathy to successful exits — both were sold respectively to American Express and Constellation Brands. He’s also a Board Member at Candy Digital, Co-Founder of VCR Group, Co-Founder of ArtOfficial, and Creator & CEO of VeeFriends. Gary was recently named to the Fortune list of the Top 50 Influential people in the NFT industry. In addition to running multiple businesses, Gary documents his life daily as a CEO through his social media channels which has more than 34 million followers and garnishes over 272 million monthly impressions/views across all platforms. His podcast ‘The GaryVee Audio Experience’ ranks among the top podcasts globally. He is a five-time New York Times Best-Selling Author and one of the most highly sought after public speakers. Gary serves on the board of MikMak, Bojangles Restaurants, and Pencils of Promise. He is also a longtime Well Member of Charity:Water.

Start An AI T-Shirt Business Side Hustle FULL STRATEGY
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LLM Vibe Score0.391
Human Vibe Score0.61
Wholesale TedApr 10, 2023

Start An AI T-Shirt Business Side Hustle FULL STRATEGY

Learn how to use Midjourney to create amazing AI art to sell onto t-shirts for a profit! ► Get my FREE $10,000 Print On Demand ebook: https://wholesaleted.com/4-step ► Get my Automated Ecom course + AI Art training: https://theecommclubhouse.com ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ IMPORTANT DISCLAIMER - PLEASE READ: 🙏 All content on my channel is my personal opinion. I am NOT a lawyer, accountant or financial advisor. I do not have any professional licenses. My opinions are not a replacement for the guidance of a professionally trained and licensed individual. Some links in the description may be affiliate links. This means that I may get a commission if you click on the link and purchase something. Using those links are optional but they are always appreciated. Thank you 🙏 ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ WATCH MY MOST POPULAR VIDEOS: ►► How I Make $1,000/Day From 5 Sources Of Income: https://youtu.be/jCqIGxA5S-k ►► How To Start An Etsy Print On Demand Store For Free: https://youtu.be/7ZlZFPBWC74 ►► The REAL Reason I Became A Millionaire: https://youtu.be/70itsEHS-EM ►► Best Side Hustles To Start With No Money: https://youtu.be/fQTsmtXBkew RECOMMENDED WATCHING - Having Realistic Expectations In Business: ►► https://www.youtube.com/playlist?list=PLjNYIrpZp6BhzPiUJUUrpfIaFTlcZKF5n ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ WHOLESALE TED AFFILIATE LINKS A lot of people have requested that I posted my affiliate links so that they can register through them as a thank-you for my free tutorial content on YouTube. Thank you so much for your support! If you would like to use my affiliate links, I would greatly appreciate it as it enables me to keep making YouTube videos for free: ►► Get A FREE Trial To Shopify: https://wholesaleted.com/go/free-shopify-trial ►► Get My Favorite Graphic Design App Canva: https://wholesaleted.com/go/canva ►► Get The Etsy Research App Alura: https://wholesaleted.com/go/alura ►► Use Printify's Print On Demand App Like I Do: https://wholesaleted.com/go/printify ►► Use Printful's Print On Demand App Like I Do: https://wholesaleted.com/go/printful ►► Get My Favorite Lifestyle Photos On Placeit: https://wholesaleted.com/go/placeit Please note: an affiliate link tracks whether you click on the link, and register and/or make a purchase. If you do, I may get a commission. Using affiliate links is optional but again, it enables me to keep making my YouTube tutorial content free & I greatly appreciate the support, thank you! ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ FOLLOW ME ON SOCIAL MEDIA! ►► Follow Sarah on TikTok: https://www.tiktok.com/@sarahchrisp ►► Follow Sarah's Adventures on Instagram: https://www.instagram.com/sarahchrispy/ ►► Like us on Facebook: https://www.facebook.com/wholesaleted/ ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ VIDEO CHAPTERS: 0:00 - The Easiest Way To Make Money From AI T-Shirt Designs 3:16 - How To Open & Use Midjourney 3:54 - The Best Midjourney Settings For Generating T-Shirt Images 5:43 - How To Prompt & Generate T-Shirt Images With Midjourney 8:16 - The Fast Way To Fix Image Glitches 9:00 - How To Make The Image Background Transparent 9:33 - Use AI To Upscale Your AI Art Into High Resolution 10:27 - Turn Your AI Art Into T-Shirts To Sell For A Profit ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ WHY SUBSCRIBE TO WHOLESALE TED? Hey there I am Sarah (aka Ted). My goal is to help new entrepreneurs grow & scale a business that is right for THEM! Yes - the business that is right for THEM. Because I believe that time is the most valuable thing we have, and that we should spend it doing things that we love: and what I love may be different to what you love. Which is why on this channel I share: Examples & case studies of businesses that I enjoy (such as Print On Demand ecommerce businesses) and sharing my tips & strategies I've learned along the way. Examples & case studies of other businesses that entrepreneurs love running (even if I personally wouldn't find it fun myself!) Plus a sprinkle of entrepreneurial motivation thrown in too! I hope my actionable content can help you: whether you're running your own online business, or are in the process of building one, and want some tactical advice to help you along the way. If that is you, subscribe today! 🔥