The world is moving fast. In tech, it s moving 10x faster.
Some jobs are already disappearing because AI is more efficient.

Companies are now facing a choice: adapt or fall behind.

In the United States, they re approaching this systematically.
The U.S. Department of Labour launched a new portal to help both employers and employees build AI skills through apprenticeship programs.

In a discussion forum with @monatruong_murror , we talked about how AI can help us learn things that aren t naturally familiar to us, like programming.

The biggest challenge was/is:
Getting AI to guide you toward a solution, instead of just giving you the answer.

New AI models pop up every week. Some developer tools like @Cursor, @Zed, and @Kilo Code let you choose between different models, while more opinionated products like @Amp and @Tonkotsu default to 1 model.

Curious what the community recommends for coding tasks? Any preferences?

Not long ago, books/video tapes were the only way to learn. Then video entered the picture: courses, tutorials, and lectures made knowledge more accessible than ever.

Now? The internet is overflowing with millions of courses, books, and resources on every imaginable topic.

So the real question is:

There's one good saying that
"Anyone who stops learning is old, whether at twenty or eighty. Anyone who keeps learning stays young."

This is so authentic, especially in the tech world, when everything changes so fast.

Today, I came across an article on TechCrunch: The great computer science exodus (and where students are going instead).

It shows that UC campuses saw a drop in computer science enrollment for the first time since the dot-com crash (6% in 2025, 3% in 2024), but students are shifting to AI-focused programs.

I am attempting to observe what you use for coding. I have come across many tools on Product Hunt + Web, but I am fairly certain I have missed quite a bit.
I divided them into "traditional" and "specialised".

Traditional AI models:

DeepSeek

Hi folks!
I'm Anisha, a growth strategist, and we're building AI-powered learning that actually adapts to each person. I started out editing content, but now I'm all about making interactive learning accessible to everyone (because, let's be real, we've all sat through terrible training videos). When I'm not nerding out over AI and growth automation, you'll find me on the golf course -- I'm a professional golfer ranked in India's top 30! Nothing like a morning round to spark the best ideas. Super passionate about using AI to democratize great education.
We're launching on Product Hunt soon, and I'd love to know: what's your biggest pain point when using AI to build decks, slides, training, or lessons?

I recently installed @Augment Code based on an ad somewhere, and I'm super impressed, but haven't heard a peep about it in most channels. But it got me wondering what else I'm missing. This is a crowded field with a few frontrunners and a lot of more esoteric newcomers, but I want to know about the ones that blow your mind but hardly get any coverage.

Maybe it is only me, but I see certain categories of online products that seem to be like "copy-paste" and the market is overcrowded by them. (and they repeats in the PH charts too often as well)

They are especially these:

• AI writing tools

• social media apps (I do not think that something breath-taking can be developed there)

• productivity apps (trackers)

• fitness apps

I was recently talking with a group of founders, and we went around sharing tools we're using now. Posting my notes for our community here - would love to know what else people are using!

Voice AI toolkit:

- Vapi

I've been primarily using @Cursor as I like how it operates, enjoy that it's visual, and I am getting very comfortable with using it and being able to easily select different code bits and modify what I need....however....
I recently started using Gemini CLI in @Warp and I must say... I'm kinda liking it. I feel that it's able to do a lot more, faster without needing me to jump in. When I do jump in, it's simply to provide it guidence and direction.
I haven't done much with it yet, but I can see myslef now doing a combination of CLI and IDE development. I'm curious what everyone elses experience is! Or if you haven't used a CLI or IDE AI tool, why?
A bit of additional background, I'm not a develpoer but more of a "vibe coder" I can kinda understand different languages and don't mind diving into tech docs but I prefer AI do more of the coding than me :)

I've been primarily using @Cursor as I like how it operates, enjoy that it's visual, and I am getting very comfortable with using it and being able to easily select different code bits and modify what I need....however....
I recently started using Gemini CLI in @Warp and I must say... I'm kinda liking it. I feel that it's able to do a lot more, faster without needing me to jump in. When I do jump in, it's simply to provide it guidence and direction.
I haven't done much with it yet, but I can see myslef now doing a combination of CLI and IDE development. I'm curious what everyone elses experience is! Or if you haven't used a CLI or IDE AI tool, why?
A bit of additional background, I'm not a develpoer but more of a "vibe coder" I can kinda understand different languages and don't mind diving into tech docs but I prefer AI do more of the coding than me :)

Hey friends

We re excited to share that Tutoria AI will be launching here on Tuesday, September 30th

Tutoria makes language learning feel like real conversation, not memorizing grammar rules. With our AI tutor you ll be able to:

For years, "learn to code" was a golden rule for career growth. But with AI assistants writing entire functions, debugging code, and even generating full applications, is traditional coding knowledge still essential?

Will the future of development be prompt engineering rather than coding?

Will AI make deep knowledge of algorithms and system design more important, while reducing the need for syntax memorization?

If AI does the coding, what skills will become most valuable for future developers?

AI has the potential to boost your productivity 10x, even 100x. But only if you know how to actually use it.

That s why learning how to integrate it into your daily workflow isn t just useful. It s essential. It s quickly becoming one of the most valuable meta-skills in any role. No matter if you're a copywriter, a dev or a marketer.

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.