I mean, is your day job at a bank or an oil company or a manufacturer? Do you use consumer AI as part of your workflow? Does your company have any kind of objectives?

We've all been there. What's pissing you off right now?

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.

I've been having a lot of fun exploring AI and using tools like @Cursor, @bolt.new, @Lovable, and @Warp to learn how to build and make some apps for myself! I'm also noticing a tremendous amount of growth in folks creating their own apps using these same tools which has me wondering... if a company wanted to acquire someone's app or tool that was built via vibe coding, would it matter how it was built? Does the method of how it was built impact the valuation?
In my idealistic eyes, I'd like to think it doesn't. As an acquisition is often much more than just the tech but also the user base, brand, and even team behind the product. If anything I think that acquiring a product that has been "vibe coded" and putting them into capable engineering hands would only enhance the product...or a least make the code base cleaner.
I also believe that talent that is able to create stunning products with AI is currently a small percentage of folks, and that companies should be investing in acquiring that talent (either independently or via product acquisition) so that they can stay ahead in innovation while learning how to implement AI tools more efficiently in their orgs.
Very curious to hear what you all think!

Gaze into your crystal ball and share what you think is going to happen with AI in 2025! Will this be the year of the vibecoder? Is there an industry that you think will be transformed by AI? Whether you're predicting revolutionary breakthroughs or subtle shifts, drop your predictions in the comments!

I've been using @Google Chrome for years and honestly never thought much about changing. It just always seemed like the best and easiest option. Lately though, I've been feeling like maybe I'm missing out. Chrome doesn't feel like the no-brainer pick anymore, and I'm seeing more and more interesting browsers out there.

Currently, @Horse is my top pick. This is the one I'm most interested in trying out, but it also seems like a pretty different approach. I don't necessarily want my productivity to dip, but that may just be inevitable whenever switching.

At this point, all of the AI coding assistants are in the same neighborhood. Decent at "advanced autocomplete", OK at code generation sometimes, and most are somewhere in the process of incorporating code context mechanisms. But what's next? Agentic behavior? Something else?
My pet prediction is that we will see the emergence of a new programming language that's designed for use with AI and can be translated to a variety of popular languages. (Or if we're cursed, just javascript )

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.

Hello Everyone!

We're building a personalized language-learning app inspired by our own experiences and frustrations with the one-size-fits-all approach of traditional apps. Our goal is to offer customized and adaptive learning paths, powered by user data and tailored to individual interests, goals, and motivations.

I won t go into full pitch mode just yet, but we d love to start a discussion around this question:

• What s your biggest pain point or frustration with current language-learning apps?

The best technology is invisible until you need it, then it s indispensable. What we realized after building Shift

When we created Shift, we set out to solve a problem that was driving us crazy: why do we have to leave what we re doing just to get AI help?

What started as a simple idea has turned into something that sounds ridiculous, but bear with us: we ve reimagined the humble Shift key as potentially the most valuable colleague you ll never meet.

The best technology is invisible until you need it, then it s indispensable. What we realized after building Shift

When we created Shift, we set out to solve a problem that was driving us crazy: why do we have to leave what we re doing just to get AI help?

What started as a simple idea has turned into something that sounds ridiculous, but bear with us: we ve reimagined the humble Shift key as potentially the most valuable colleague you ll never meet.

I used it for a year or two, but eventually went back to iTerm because I found the UX to be over-complicated and slowed me down. (Also, I'm a dinosaur with too much muscle memory to overcome...) But the AI features were interesting, so I'm curious what ya'll see as alternatives, or if you think I should give it another shot.

I used it for a year or two, but eventually went back to iTerm because I found the UX to be over-complicated and slowed me down. (Also, I'm a dinosaur with too much muscle memory to overcome...) But the AI features were interesting, so I'm curious what ya'll see as alternatives, or if you think I should give it another shot.

Well I definitely didn't see this coming. Digg is coming back!

https://x.com/digg/status/189724...

I've been having a lot of fun exploring AI and using tools like @Cursor, @bolt.new, @Lovable, and @Warp to learn how to build and make some apps for myself! I'm also noticing a tremendous amount of growth in folks creating their own apps using these same tools which has me wondering... if a company wanted to acquire someone's app or tool that was built via vibe coding, would it matter how it was built? Does the method of how it was built impact the valuation?
In my idealistic eyes, I'd like to think it doesn't. As an acquisition is often much more than just the tech but also the user base, brand, and even team behind the product. If anything I think that acquiring a product that has been "vibe coded" and putting them into capable engineering hands would only enhance the product...or a least make the code base cleaner.
I also believe that talent that is able to create stunning products with AI is currently a small percentage of folks, and that companies should be investing in acquiring that talent (either independently or via product acquisition) so that they can stay ahead in innovation while learning how to implement AI tools more efficiently in their orgs.
Very curious to hear what you all think!

Has anyone out there been seriously trying claude 3.7 in Cursor? How is it?

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.