Vibe coding seems to be everywhere right now, people are building apps just by prompting AI.

But I m curious if anyone here has actually made money from something they vibe coded, especially people who didn t come from a coding background.

I've been a professional developer for 10+ years (WordPress ecosystem, and React, TypeScript, Node, the whole stack).

Now I'm building my own SaaS and I'm genuinely torn.

I've been talking to dozens of PMs over the last few weeks who prototype with Lovable, Bolt, Figma Make, V0, etc. Same frustrations keep surfacing.

• Output looks a bit generic: looks like a demo, not your actual product

• Context loss: explain your product in ChatGPT/Claude, then re-explain in Lovable, then again somewhere else

• No edge case thinking: AI executes prompts literally, doesn't challenge or expand on them

The core issue I keep seeing: these tools are interface builders. They're great when you already know exactly what to build. But the hard part, thinking through the flows, the states, the edge cases, where users will actually get stuck, that's still entirely on you.

Wherever you code (online, CLI, or IDE), everyone has some love, hate or horror vibe coding stories, from building a prod-ready app in minutes to the whole repo got wiped. Would love to hear your story.

Hi ProductHunt community,

This term has been coined by someone and there are already more than 80 products that you could put in this category. Looking at the numbers, it's growing pretty fast.

Building my app with AI tools, zero coding background. The magic part - I can ship features in hours. The scary part - I have no idea if the code is actually good.

Right now my "QA process" is:

- Does it work when I tap around?

- Did anything break that worked before?

Hey everyone,

I've built my product around traditional SaaS pricing (monthly tiers), but I m starting to wonder if that model is getting outdated, especially with more AI-powered and compute-heavy tools entering the market.
That shift requires real architectural changes, instrumentation, metering, billing logic, and UI changes, not just pricing tweaks. It s something I m starting to seriously think about for my own product.

In particular, AI usage has real COGs (every prompt costs money), and I m seeing more platforms experimenting with usage-based models, or hybrids like SaaS base + usage + overage.

For those of you building AI or compute-intensive tools:

AI dev tools are moving stupid fast. Every few weeks, there s a new must-use. Some stick. Most don t.

Some vibe coders are developing full products with @ChatGPT by OpenAI+ @Replit. Others swear by @Cursor + @Claude by Anthropic . A few are mixing @Lovable , @v0 by Vercel , and @bolt.new . New and shipping way faster than expected.

I ve been refining my own vibe stack lately.
Building with @Google Antigravity at the core. It keeps the flow clean when things get messy.

Share your current Vibe Stack:

AI dev tools are evolving crazy fast , every few weeks there s a new must-try for vibe coders.

Some people are building full products with @ChatGPT by OpenAI and @Replit , others swear by @Cursor and @Claude by Anthropic , and a few are mixing @Lovable + @v0 by Vercel + @bolt.new to ship apps in record time.

I ve been refining my own vibe stack lately, trying to find that sweet spot between speed, control, and creativity.
It made me wonder ,what does your setup look like right now?

Vibe coding tools have been making huge improvements, but things can always get better.

What blockers are you still running into? What has no one solved yet? What do you wish you could do, but can't yet?

I might be missing some but I've been pretty much in love with @Lovable, @Cursor, @bolt.new and have been trying to use @Replit more and I honestly haven't touched @BASE44 too much but have heard good things. @chrismessina has nudged me to use @Windsurf for whenever I build another Raycast Extension!
Currently I use:
- @bolt.new / @Lovable
- @Cursor
- @Warp
Curious what everyone thinks is the top one so far!

I'm super curious how everyone starts to vibe code? In the beginning I would simply jump into @bolt.new or @Cursor and just do a prompt and continue refining with the AI. I quickly realized this created a lot of issues as I didn't think about the structure, tech stack, and how I wanted the features to interact with each other and how the way I was building things would impact the user experience. I now do the following:

• Write down a simple problem statement: "what am I trying to solve?"

• Write down a simple solution statement: "what does the thing I'm building do (to solve the problem)"

• Share the above with @ChatGPT by OpenAI and word vomit my thoughts, ideas, how I want the user to interact with my app, etc and ASK ChatGPT to turn everything I said and want into an easy to understand directive and instructions for an Engineer.

• I then take the Engineer instructions and give it to a new chat in ChatGPT and ask it to turn those instructions into a prompt for an AI engineer and to break up the project into sections so that each time we focus on a section the app is shippable and keeps things easy to work on.

• I take the output and paste it into my notes. I then give it to Cursor.

• Once in Cursor, I create a new project folder and got at it!

Curious what everyone else does and if you've experience any things to avoid or must do

I'm super curious how everyone starts to vibe code? In the beginning I would simply jump into @bolt.new or @Cursor and just do a prompt and continue refining with the AI. I quickly realized this created a lot of issues as I didn't think about the structure, tech stack, and how I wanted the features to interact with each other and how the way I was building things would impact the user experience. I now do the following:

• Write down a simple problem statement: "what am I trying to solve?"

• Write down a simple solution statement: "what does the thing I'm building do (to solve the problem)"

• Share the above with @ChatGPT by OpenAI and word vomit my thoughts, ideas, how I want the user to interact with my app, etc and ASK ChatGPT to turn everything I said and want into an easy to understand directive and instructions for an Engineer.

• I then take the Engineer instructions and give it to a new chat in ChatGPT and ask it to turn those instructions into a prompt for an AI engineer and to break up the project into sections so that each time we focus on a section the app is shippable and keeps things easy to work on.

• I take the output and paste it into my notes. I then give it to Cursor.

• Once in Cursor, I create a new project folder and got at it!

Curious what everyone else does and if you've experience any things to avoid or must do

Recently I've worked with a group of non-corders trying to "vibe code" their apps with AI.
While knowing code is clearly not a must these days, it helps to get technical.
People who were familiar with basic software engineering concepts were 10x more likely to success and get better results.
So, with the hope of providing value to the non-coders people, I've created a quick roadmap for the basic terms and concepts you should be familiar with.

• Requirements: Building apps with AI is all about being able to clearly guide AI and express your app features and requirements.
  You need to be able to express those ideas and explain them as you d explain to a human developer. Think like a Technical Product Manager.

• Frontend: The face of your app.
  It's what your users see and interact with. It could be a website, a mobile app, or a desktop app. Most popular frontend libraries and frameworks are React, Next.js.

• UIs: They are the buttons, the forms, the modals, the tooltips, etc. In React, the UI is built with components. For design & styling, Tailwind CSS is the most popular library.
  For animations, Framer Motion is the most popular library.

• Packages & npm: Apps are not built from scratch.
  They are built on top of existing libraries and frameworks, like lego blocks.

  The most popular package manager is npm. For example, "react-hook-form" is a famous package that helps you build forms.

• Backend: The backend is the part of your app that runs on the server.

  It's where you store your data, your business logic.

  e.g: If you want to send an email, or process payments - this is where you'll do it.

  Vibe tip: Use minimal backends with serverless functions.

• Database: The database is where you store your data.

  It's where you store your users, your projects, your tasks, etc. Think of it as a big spreadsheet.

  I recommend using a database that is integrated with your frontend.

  For example: Fine, or Supabase.

• API: Real-life apps almost always need to integrate with other apps.

  For example: if you want to send email, or get weather data, or integrate with AI - it's all done through APIs.

• Hosting & Deployment: For your app to be accessible to the public, you need to host it.

  The code is usually hosted on GitHub, and deployed to platforms like Fine, Vercel, Netlify.

Finally, being comfortable with code is helpful - even if not a must.

AI often makes minor mistakes (like importing a wrong package), and if you re not afraid of reviewing code - you will get better results faster.

Recently I've worked with a group of non-corders trying to "vibe code" their apps with AI.
While knowing code is clearly not a must these days, it helps to get technical.
People who were familiar with basic software engineering concepts were 10x more likely to success and get better results.
So, with the hope of providing value to the non-coders people, I've created a quick roadmap for the basic terms and concepts you should be familiar with.

• Requirements: Building apps with AI is all about being able to clearly guide AI and express your app features and requirements.
  You need to be able to express those ideas and explain them as you d explain to a human developer. Think like a Technical Product Manager.

• Frontend: The face of your app.
  It's what your users see and interact with. It could be a website, a mobile app, or a desktop app. Most popular frontend libraries and frameworks are React, Next.js.

• UIs: They are the buttons, the forms, the modals, the tooltips, etc. In React, the UI is built with components. For design & styling, Tailwind CSS is the most popular library.
  For animations, Framer Motion is the most popular library.

• Packages & npm: Apps are not built from scratch.
  They are built on top of existing libraries and frameworks, like lego blocks.

  The most popular package manager is npm. For example, "react-hook-form" is a famous package that helps you build forms.

• Backend: The backend is the part of your app that runs on the server.

  It's where you store your data, your business logic.

  e.g: If you want to send an email, or process payments - this is where you'll do it.

  Vibe tip: Use minimal backends with serverless functions.

• Database: The database is where you store your data.

  It's where you store your users, your projects, your tasks, etc. Think of it as a big spreadsheet.

  I recommend using a database that is integrated with your frontend.

  For example: Fine, or Supabase.

• API: Real-life apps almost always need to integrate with other apps.

  For example: if you want to send email, or get weather data, or integrate with AI - it's all done through APIs.

• Hosting & Deployment: For your app to be accessible to the public, you need to host it.

  The code is usually hosted on GitHub, and deployed to platforms like Fine, Vercel, Netlify.

Finally, being comfortable with code is helpful - even if not a must.

AI often makes minor mistakes (like importing a wrong package), and if you re not afraid of reviewing code - you will get better results faster.

Recently I've worked with a group of non-corders trying to "vibe code" their apps with AI.
While knowing code is clearly not a must these days, it helps to get technical.
People who were familiar with basic software engineering concepts were 10x more likely to success and get better results.
So, with the hope of providing value to the non-coders people, I've created a quick roadmap for the basic terms and concepts you should be familiar with.

• Requirements: Building apps with AI is all about being able to clearly guide AI and express your app features and requirements.
  You need to be able to express those ideas and explain them as you d explain to a human developer. Think like a Technical Product Manager.

• Frontend: The face of your app.
  It's what your users see and interact with. It could be a website, a mobile app, or a desktop app. Most popular frontend libraries and frameworks are React, Next.js.

• UIs: They are the buttons, the forms, the modals, the tooltips, etc. In React, the UI is built with components. For design & styling, Tailwind CSS is the most popular library.
  For animations, Framer Motion is the most popular library.

• Packages & npm: Apps are not built from scratch.
  They are built on top of existing libraries and frameworks, like lego blocks.

  The most popular package manager is npm. For example, "react-hook-form" is a famous package that helps you build forms.

• Backend: The backend is the part of your app that runs on the server.

  It's where you store your data, your business logic.

  e.g: If you want to send an email, or process payments - this is where you'll do it.

  Vibe tip: Use minimal backends with serverless functions.

• Database: The database is where you store your data.

  It's where you store your users, your projects, your tasks, etc. Think of it as a big spreadsheet.

  I recommend using a database that is integrated with your frontend.

  For example: Fine, or Supabase.

• API: Real-life apps almost always need to integrate with other apps.

  For example: if you want to send email, or get weather data, or integrate with AI - it's all done through APIs.

• Hosting & Deployment: For your app to be accessible to the public, you need to host it.

  The code is usually hosted on GitHub, and deployed to platforms like Fine, Vercel, Netlify.

Finally, being comfortable with code is helpful - even if not a must.

AI often makes minor mistakes (like importing a wrong package), and if you re not afraid of reviewing code - you will get better results faster.