00:00:00Ever since AI started coding well, a lot of people who had never coded before started building their own products.
00:00:05People started building apps that solved problems they were facing which they couldn't do previously because they lacked skills that were only limited to developers.
00:00:13But these weren't just hobbyist side projects.
00:00:15They turned into serious products and a lot of them started pulling in real revenue, not just in thousands but in millions of dollars.
00:00:21This all was able to happen because AI bridged the gap that was there before.
00:00:25But none of them got there just like that.
00:00:27They all followed a series of steps to make it work.
00:00:30They didn't use some workflow that nobody else can use.
00:00:32None of them had developer experience or had business experience.
00:00:36But every single one of them still made it.
00:00:38And surprisingly, their workflows weren't that special.
00:00:40They were just simpler and more clever than they seem.
00:00:43So the first project that gained massive popularity despite being entirely vibe coded is Medve.
00:00:48It's a healthcare platform with more than 500,000 active users.
00:00:52It covers a wide range of healthcare issues and provides not just tracking but also 24/7 expert support.
00:00:58The story goes that Matthew Gallagher, who was working alone, used AI tools to build this app from end to end.
00:01:04The company pulled in 400 $1 million in revenue in its first year and is on track to become a billion dollar company within this year.
00:01:11Despite having no experience in coding, he was able to build this app using AI tools.
00:01:15He didn't rely on a single tool.
00:01:17He picked each one for its strengths.
00:01:19He used Claude and Grok models primarily for coding, with ChatGPT as a secondary debugging tool.
00:01:24MidJourney handled image generation on the site and 11 Labs powered the audio calls, which removed the need for human call support entirely.
00:01:31But coding tools alone don't run a healthcare company.
00:01:34So instead of building pharmacies and shipping from scratch, he outsourced them to existing services.
00:01:39So that took the burden of maintaining stock and delivering off from him.
00:01:42The same went for professional consultancy.
00:01:44He outsources the consultancy as well, eliminating the need to be involved personally in that aspect as well.
00:01:49He treated every dependency as a service, not a hire.
00:01:52His own job was product judgment, figuring out what the market actually needed.
00:01:56But running solo has a cost.
00:01:58One day he broke production while he was away.
00:02:00Nobody else could handle it, and the company lost 200 customers in a single hour.
00:02:04Therefore, he hired two engineers, not to scale, but as a safety net, so the next outage wouldn't repeat that same loss.
00:02:10The real skill here is being a better judge of what to build, which tools to assemble, and when to stop.
00:02:15That comes from analyzing real user needs, not just collecting tools.
00:02:18Instead of building from scratch, he combined existing solutions in one place.
00:02:22And that's what actually brings customers and scales a company to a billion dollar valuation.
00:02:27We share everything we find on building products with AI on this channel.
00:02:30So if you want more videos on that, subscribe and keep an eye out for future videos.
00:02:34Now, CalAI is a product that might sound like just another fitness tracker, but instead of manually adding the food you ate and the calories it contains the way normal trackers work,
00:02:43you can just upload an image of whatever you're eating, and it converts that into calories and updates the database for you.
00:02:49It's available on both Android and iOS.
00:02:51It maintains a large database of foods and gives AI-powered suggestions so you can monitor your weight and other nutrition goals in one place with ease.
00:02:59This product was built by two teenagers who were still in high school at the time, which then later scaled to more employees.
00:03:04It pulled in over 5 million downloads in just 8 months and generated over 2 million dollars in revenue in a single month.
00:03:11It also held a strong 30% customer retention rate because most apps only gain users, but this one successfully retained them.
00:03:18It also holds a 4.8 rating on both the Play Store and the App Store.
00:03:21Now this idea wasn't new, similar apps already existed doing the same thing, but CalAI had a real advantage the others didn't.
00:03:27It was built in the age of LLMs and used models from Anthropic and OpenAI to push accuracy up.
00:03:33It also relied on a large open-source food database and reached around 90% accuracy, which is more than enough for most diet enthusiasts.
00:03:40What really boosted this app wasn't heavy spending on marketing.
00:03:44It caught the attention of fitness influencers who played a major role in promoting it, leading to the spike in the users.
00:03:50Then we have Wave AI which started with an idea so simple yet it made a real impact on users.
00:03:55It's an AI-powered note-taking app that transcribes and takes notes for all kinds of meetings and recordings.
00:04:01Now you might think there are already so many similar existing apps and the space for this is already so crowded,
00:04:06but Wave still broke through because it solves a problem people actually feel.
00:04:10During discussions, important details slip away and people need a reliable way to capture conversations across in-person and online meetings.
00:04:17It launched first as an iOS download, then scaled to Android and now it's available on every platform.
00:04:22The app was entirely vibe-coded and pulled in around $7 million in revenue.
00:04:27The founder is not a developer at all, yet he scaled it into a million-making company.
00:04:31He ran the entire project completely solo.
00:04:33Similar to how Medve operated, his infrastructure also leaned on third-party services instead of building everything from the ground up.
00:04:40He just integrated them into a friendly app and just focused on solving the problem in an interactive manner that made the user experience so much better.
00:04:47And this is what set this product apart from other similar existing ones.
00:04:51He used ChatGPT as his main tool and instead of asking it to build the whole app at once, he broke the application into smaller chunks.
00:04:58He prompted AI to write each part one by one.
00:05:01So strategic positioning, focused user experience and careful planning are what actually took him to that revenue level at speed.
00:05:07But before we move forwards, let's have a word by our sponsor, Scrimba.
00:05:10Most AI engineering courses are just someone talking over slides.
00:05:14However, with Scrimba, the experience is very different.
00:05:17Their web dev courses combine the video and code editor into one.
00:05:20Pause any time, edit the instructor's code directly and see what happens.
00:05:23No tab switching, no copy-pasting, that's how coding actually sticks.
00:05:27Their AI engineer path is what caught my attention.
00:05:30In under 12 hours, you go from zero to building real AI agents, learning RAG, context engineering and MCP all built with JavaScript so you don't have to learn Python first.
00:05:39They've even partnered with Mistral, Langchain and Hugging Face to bring real tooling into the lessons.
00:05:44And beyond AI, they've got full career paths for front-end, full-stack and back-end development with over 80 courses covering everything from React and Node to TypeScript and SQL.
00:05:53Use our link in the pinned comment to save an extra 20% on their pro plans.
00:05:58Get started today with their free courses and start building.
00:06:01Flypeter is another product built solely by AI which started as just a fun hobby project which then scaled to $500,000 a month.
00:06:08It is basically a browser-based flight simulator.
00:06:11He completely relied on AI tools for building and he was able to create the first version in just 30 minutes.
00:06:17The game scaled so fast that Elon Musk himself endorsed it.
00:06:20Its architecture was so well built that it was able to survive cyber attacks and started generating revenue at a serious scale.
00:06:26The whole thing was built using Cursor and it took the founder just 3 hours of working with Cursor to get the app about 80% done and in a state that it was ready to announce to the public letting them use it.
00:06:37His workflow itself was pretty simple.
00:06:39He started with one prompt and based on how the tool generated code and features, he iterated with new prompts.
00:06:44Each iteration added a feature or fixed an issue, one by one layering in the game mechanics along the way.
00:06:49The game performed well if one person was playing but scaling to multiplayer is where the project needed help.
00:06:55He was approached by the beta list founder to help him fix the multiplayer issue by adding WebRTC which solved the problem to some extent but it worked well only for two people.
00:07:04Therefore, the founder of Cursor himself reached out and they switched to WebSockets which actually solved the problem and unlocked real-time multiplayer for everyone.
00:07:12He launched the game as a free version but added a specific plane for $29.
00:07:17This helped it gain a lot of popularity and he made a significant amount of money in a short time.
00:07:22His stack was Cursor with Grok 3 as the backend model, Claude Sonnet 3.7 and ChatGpt for debugging.
00:07:28He's just an indie hacker with no game dev background.
00:07:30What got him there was determination and a systematic step-by-step debugging approach.
00:07:35Trendfeed is another product that gained rapid popularity amongst the users and made solid revenue.
00:07:40It's a marketing tool aimed at content creators focused on building and acquiring customers, growing a community around existing brands and lifting overall revenue for the creators.
00:07:49The project pulled in around $12,000 in just four weeks.
00:07:53It was entirely built with AI using Cursor with Sonnet, not through Claude code but directly inside Cursor.
00:07:58His build process was actually pretty straightforward.
00:08:01He started by analyzing the UI carefully and doing deep competitor research, even using AI to break down those competitors.
00:08:07Then he moved to data structure design, defining schemas with Cursor or Claude and iterated from there.
00:08:13On launch day, the app generated £5,500 in a single day which was a massive first day result.
00:08:19Even though the founder is non-technical and works in fields outside computer science, he shipped the whole thing using AI.
00:08:25The app is built on Next.js, React, ShadCN, Superbase and Vercel Stack, all the tech AI tools work the best with.
00:08:31Given how popular the product became in such a short time, it was surprising that he spent zero on marketing.
00:08:37Instead, he leaned entirely on TikTok, Instagram and YouTube to drive views and announce the product.
00:08:42His full build ran on Claude code and Cursor with Sonnet as the primary model.
00:08:46The flow itself was clean.
00:08:48He started with design, set up the core app structure, laid out onboarding and the main framework and repeated design patterns.
00:08:54Then he broke the app into modular components that AI could build and merge together.
00:08:59Also, if you are enjoying our content, consider pressing the hype button because it helps us create more content like this and reach out to more people.
00:09:06The next successful AI product that was entirely vibe coded is Aura.
00:09:10It is basically a site full of templates for beautiful websites with assets, components and skills all tailored towards strong design.
00:09:17The whole project was built by Meng To who was the person behind Aura.
00:09:21He posted on X that the product hit $15,000 in monthly recurring revenue or MRR and gained over 21.7 thousand users in just a month.
00:09:30He also shared that he now uses Cursor for design and he is no longer using Figma like in his previous workflow.
00:09:35His main point is that you shouldn't just vibe code, you should also vibe design because AI tends to generate basic UIs.
00:09:42So instead of letting it work on its own, you need to give it guiding templates to diversify the look.
00:09:47He recommends components from existing libraries like 21.dev.
00:09:51He also recommends not relying on a single model while building the app.
00:09:54Instead, it is more effective to start with Claude models because they are more powerful for coding tasks and if it fails to do the task, then switch to Gemini or GPT models when needed.
00:10:04Instead of going all in at once, he stresses building the app step by step with incremental changes.
00:10:09He recommends keeping the prompts simple by breaking the app into smaller parts and iterating on them one at a time.
00:10:15He also says prompts should ideally stay under 3 sentences so the AI stays focused.
00:10:19You don't need to dump all the documentation on the AI either.
00:10:22Instead, you should give it the minimal but correct context so it delivers what you actually want.
00:10:27This way, the agent will be able to focus more on the task at hand.
00:10:30In short, keep the agent setup simple and focused.
00:10:33Another product worth looking at is Sleek, which is a product that turns prompts into engaging websites.
00:10:38It generates the full design from a prompt, builds stunning visuals, creates mock-ups and allows code export.
00:10:43The product reached $10,000 MRR in 6 weeks and was built entirely using AI tools.
00:10:49The impressive part is that the developers hit that MRR without spending a single dollar on marketing.
00:10:54But what really sets Sleek apart is that they didn't start from zero.
00:10:58They had already built other design tools before, so they essentially repurposed their existing products into this one.
00:11:03They used a stack of Next.js, Superbase and Vercel, which AI tools already handle comfortably.
00:11:09They acquired all of their customers through X by making the use of its algorithm cleverly and announcing early access, which led to a strong launch.
00:11:16But here's the real reason the product succeeded.
00:11:19They had a clearly defined ideal customer profile, or ICP, from day one.
00:11:23Because of that, they understood exactly what their target users needed and could shape the product to fit.
00:11:28So whenever you build an app, define an ICP first.
00:11:31That's what separates successful apps from impressive ones that never make money.
00:11:35When your ICP is clear, you shape the product around a specific audience, identify the right customer, and build something they actually need and will pay for.
00:11:43And finally, there's SiteShore, another product built entirely with AI.
00:11:47It solved one of the biggest problems agents had at the time, which was hallucinating references, citations, and sources that turned out to be non-existent when checked.
00:11:55It's a platform where you input citations, and it verifies whether the AI-generated ones are actually correct.
00:12:01Even though it solved such a simple problem, it gained massive popularity.
00:12:05The site generated around $10,000 MRR and grew steadily.
00:12:09But the story doesn't stop there.
00:12:10The site was eventually acquired for a significant amount by Jenny AI, another AI-powered platform working in the same space.
00:12:17That makes it a strong example of how a simple but critical problem can turn into a valuable product.
00:12:22That brings us to the end of this video.
00:12:24If you'd like to support the channel and help us keep making videos like this, you can do so by using the super thanks button below.
00:12:30As always, thank you for watching and I'll see you in the next one.