i think the language primitives map well to the natural desire to use these tools across networks and in concurrent workloads.
another Go harness i keep up to date with is: https://github.com/boldsoftware/shelley (exe.dev team)
For some reason they're comparing their harness running on Astra xhigh to Codex with Astra max?
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Also worth noting that OpenAI just added support for async tool calling to their harness, which isn't 1:1 with this approach, but is slowly ramping up in being able to provide something similar.
A big part of why Codex uses so many tokens is that it basically hot loops on polling tasks it starts for... absolutely no good reason: https://www.reddit.com/r/codex/comments/1wdlp7q/weve_discove...
I fixed it on my fork of Codex too, also back in Jan/Feb – I keep this patch rebased, for anyone who wants it: https://github.com/tekacs/codex/commit/9ffcf8db9078eae43d411...
It results in token savings similar in scale to those displayed here by Unreal.
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My harness has used a slightly fancier version of the approach that Unreal is using since ~Feb, and... it definitely works excellently, but it's also assuredly smoother with Astra and other recent models that are more aware of async tool calling.
What a good time for harness design. Just while OpenCode is growing up a bit and focusing on their harness. I’m delighted to see people focusing on good general solid harness design principles.
Someone make an OpenCode API (the best general agent end UI API I know) compatible server for it!
Sucks that I haven’t upgraded my client to V2 yet and I don’t really want to build on an outdated API . ..
It says that it removes tokens wasted while a model is waiting on synchronous tool calls. What tokens exactly is Pi using when waiting?
>Computer software, namely, game engine software for video game development and operation; Computer software, namely, software development tools for the creation of computer-generated imagery and graphics for the production of video games; Computer software, namely, software development tools for the creation of computer-generated imagery and graphics for the production of content for virtual worlds and 3D platforms; Computer software, namely, software development tools for the creation of computer-generated imagery and graphics for the production of motion pictures, television shows, videos, 3D animations, 3D simulations, 3D visualizations, virtual reality motion pictures, virtual reality television shows; Computer software, namely, software development tools for the creation of computer-generated imagery and graphics for the production of virtual reality video games; Virtual reality game software; Virtual reality software for creating multimedia content; Augmented reality game software; Augmented reality software for use in mobile devices for integrating electronic data with real world environments for the purposes of entertainment
Fractal tool discovery: tool taxonomy where an agent can "drill deeper" to find what specific tool it's looking for. Helps if/when polluting context with a zillion (mostly unnecessary) tools.
Leveraging splay trees: this is my favorite data structure and I think relatively unused in the context of agents/harnesses. A lot of times, recently-used workflows/tool-chains will be used again, so having those at the top of the search hierarchy is an awesome optimization.
Virtual containerized notebooks: models working in sandboxed (WASI) Python notebooks is incredible. Even local models (if given enough time) will usually converge on a good solution. Being able to mount tools/resources/fs is again, imo quite untapped. Some problems here are running native things (thing numpy/pandas) in containers is a nightmare (or impossible).
Anyway, happy to see other folks seriously doing stuff in this space. If anyone wants to collaborate on anything don't hesitate to reach out :) I'm also actively looking for a job or some contract gigs.
Fun times ahead.