4 Cool AI Developer Tools I’ve Been Using Lately

4 min readAug 27, 2024

As a machine learning scientist, I’m always on the lookout for new tools that can improve my workflow and make my daily tasks more efficient. Recently, I’ve come across a few AI-powered tools that have become indispensable in my toolkit. Whether you’re coding, browsing, or working with large language models (LLMs), these tools can offer something exciting. Here are four cool AI developer tools that I’ve been using lately:

1. Arc Browser (arc.net)

Arc Browser — Image from Popular Science

Arc has become my new go-to browser, and it’s easy to see why. My productivity has gone through the roof. The built-in AI can handle tasks like searching within pages (Cmd + F) to answer questions about page content.

I often find myself deep-diving into research, and Arc helps me speed up this process. Whether I need to locate specific information quickly or get a summary of a complex page, Arc’s AI features allow me to navigate the web more efficiently. On top of the beautiful design, it’s now my default browser, and I can’t imagine going back to a traditional browser after this.

2. Warp Shell (warp.dev)

For years, I used iTerm2 for all my terminal needs. But then I discovered Warp, and I haven’t looked back. Warp’s standout feature is its natural language completions. LLM right in your shell — any machine. You can type commands in plain English, and Warp will suggest the correct terminal command, saving you from having to remember obscure flags or syntaxes.

Warp’s intuitive design and AI features have streamlined my terminal work, making it quicker and easier to get things done. Whether you’re managing servers, running scripts, or just navigating files, Warp is a powerful upgrade to the traditional terminal experience.

3. Cursor IDE (cursor.com)

As someone who’s spent countless hours in VS Code, I was initially skeptical about switching to another IDE. But after trying Cursor, I was hooked. Cursor is essentially a VS Code clone but with deep, amazing code completion and built-in context-aware chat.

Cursor’s AI features — Image by Geeky Gadgets

The AI-powered code completion in Cursor is next-level. It’s like having a pair of extra eyes constantly reviewing your code, offering suggestions that are both intelligent and contextually relevant. Plus, the integrated chat feature means you can ask for help or get explanations without leaving the IDE. It’s a game-changer for anyone who spends a lot of time coding. Farewell, VS Code.

4. Ollama (ollama.com)

One of the biggest challenges with LLMs is that they often require hefty infrastructure or cloud access. That’s where Ollama comes in. With Ollama, you can run local LLMs on your own machine — no cloud required. Even better, it supports 4-bit quantized Llama models that can run fast even on a laptop.

The ability to work with powerful language models offline is a game-changer, especially for those concerned about privacy or who need to work in environments without internet access. Ollama opens up a whole new world of possibilities for using LLMs in day-to-day tasks without relying on external resources.

Conclusion

These tools have revolutionized the way I work as a machine learning scientist. From enhancing my browsing experience to supercharging my coding sessions and enabling offline LLMs, each of these tools offers unique features that make my workflow smoother and more efficient. If you haven’t tried them yet, I highly recommend giving them a shot — they might just change the way you work too.

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