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  • This is nice! I tried it for a bit and it was indeed quite fast. Are you looking for contributors, or are you building this as a personal tool? I ran into some issues when attempting to use different models, though: gpt-5.5 on Azure doesn't work, even with the OpenAI compatible endpoint, because "max_tokens" has been replaced with "max_completion_tokens". And it doesn't appear possible to pass through custom headers, so I wasn't able to specify reasoning_effort for deepseek models.
    by wkcheng
  • Funny this comes out today. I was just about to start to write one in rust. It's amazing having opencode slowly leak memory and end up becoming 6gbs on a large project and then get slower and slower.

    Will check this out! Seems cool!

    by 360MustangScope
  • I had Claude Code build me one of these as well, though I added Dirac's line hashing for edits etc. Also used Rust, and I had this idea that I should use plugins so it can self-edit by implementing in hooks but in the end, I just have it create exhaust information about improvements into a separate file and just update the source code and recompile. The source code is in a fixed place so it can just rewrite and build the agent itself. I use it with DeepSeek 4 Flash running on 2x RTX 6000 Pros which I get some 138 tok/s on.

    To be honest, I just plagiarized Pi, Dirac, OpenCode. Any new tricks in this one that I can steal?

    by arjie
  • Are agent harnesses the new web framework?

    Everyone wants to write one, building a new one is easy to start with, but tough to get to “prod ready” and the landscape is littered with failed attempts?

    Certainly feels like it.

    This is really good though; works well and at least has a clearly articulated raison d'être.

    by noodletheworld
  • "RAM footprint: ~8MB on an empty session, ~12MB when working"

    I like this, Claude Code is using multiple gigabytes, which is really annoying on lowend laptops

    by throwa356262
  • I understand the need for memory footprint in some situations, but what's the point of seeking performance for a software that mostly calls LLMs and waits?
    by rullopat
  • Thanks, I've been tooling away in my spare time on my own version of this -- both to get a deeper understanding of agents (everyone suggests writing your own) and to help learn Rust. I'd like to retain `pi`'s configurability though, the ability to self-mutate and generate new tools is incredibly useful, particularly because I don't think any of these things should have access to arbitrary code execution through `bash` (of course, if they have access to, say, `edit` and `cargo run` they still have arbitrary code exec, but...) (so I tend to generate tools on the fly when I encounter something the no-bash agent needs to do).
    by frio
  • I (somewhat jokingly) wrote one recently too... https://github.com/pnegahdar/nano in under 200 lines. Repl, sessions, non-interactive, approvals, etc

    The smarter the models get the less the harnesses matter (outside of devx).

    Maybe one day I'll run it through swebech.

    by parhamn

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