Coding agents have changed how I build. Constantly switching between the terminal and an IDE started to feel inefficient, so I wanted a better terminal-first setup where I could manage multiple agent sessions and make quick edits without the overhead of a full IDE. So I built Helm for myself: https://github.com/samirkhoja/helm

This is really cool. I'll be checking it out!

Seems to solve most of my issues with my current workflow. My primary personal development machine is my WSL ubuntu install on my windows gaming PC and the tooling outside of the mac ecosystem has been really limited.

Awesome! Let me know if you run into any issues with the setup.

I know there's no such thing as a unique name anymore, but https://helm.sh/ is rather popular.

Hot take - Local LLM computing will move to stationary, always on devices (Mac mini & studio). Developers and users will move to lighter, portable devices to interface with their long running agent workers (MacBook Airs & iPads).

I personally do this and I can imagine a world in which it is popular with privacy/sovereignty enthusiasts. I have doubts that this share of people will be significant enough for many companies to cater their products to this model - but if anyone will, it will be Apple - and it would yield them a few extra Mac Studio sales and likely make much more profit than selling the same service.

Bros trying to bring thin clients back again.

Codex built my old startup in a weekend. What took me a few months to build 2+ years ago can now be done with coding agents in 2 days. The last couple months feel like a step change with Codex and Claude.

How do others feel about the pace of innovation in AI? Is there ever a reason to slow down advancements in a given field?

Speed and performance improvements like this are why VSCode has passed Atom and other editors over time.

Very similar to a consensus network. That is probably the future of LLM agents.

This was a quick experiment on creating multiple LLM (GPT) agents with their own objective to see if outputs can be improved.

I can see this being useful as a specialized (fine-tuned) LLM in a chain of LLMs for full autonomy

Autonomous agents could be the next evolution of AI, extending the capabilities of LLMs. Interested to see which agent implementations seem the most promising today.