Off: I'm wondering if now when more JS finds place on our machines and bundle size is 2nd place for most, would a revival of prepack or projects in the same vein would be worth it, especially with agents.

I'm trying right now the ACP with my own agent and I'm of mixed opinions but that's maybe because I care how my agent works. I believe that for the agent view a plain buffer with small ui elements would be the best ui for an agent conversation but I may have been spoiled by their text threads. I may spin a personal fork but the thought of tens of mins of compile time isn't that attractive.

Edit: I realized I started moving to terminal based editors like helix due to agents: claude -> codex -> custom pi, with the open sourcing of warp I was considering making a native integration for warp + pi but now I'm thinking zed's text threads (~17k lines) + pi might be a better way, any thoughts or ideas?

The changes I've made locally are:

- Added a discuss mode with almost on tools except read file, ask tool, web search only based no heuristics + being able to switch from discuss to plan mode.

Experiments:

- hashline: it doesn't bring that much benefit over the default with gpt-5.4.

- tried scribe [0]: It seems worth it as it saves context space but in worst case scenarios it fails by reading the whole file, probably worth it but I would need to experiment more with it and probably rewrite some parts.

The nice thing about opencode is that it uses sqlite and you can do experiments and then go through past conversation through code, replay and compare.

[0] https://github.com/sibyllinesoft/scribe

I feel that if you want to build a coding agent / harness the first thing you should do is to build an evaluation framework to track performance for coding by having your internal metrics and task performance, instead I see most coding agents just fiddle with adding features that don't improve the core ability of a coding agent.

What I'm asking and the response from AI through an intermediary lose some context (the prompt), it's like the telephone game where the data becomes more and more distorted, that's why people don't have an issue with their own AI generated answers.

Another issue is that when I'm talking with someone and parsing through what they've said I'm considering them, as a person, taking all available context (some of this might happen unconsciously).

In any case I don't think there is an easy solution to the problem.

Some time ago while I was experimenting with writing Debian benchmarks[0], I found that by completely avoiding strings, using Uint8Arrays, and manually managing bounds/memory, I could squeeze out performance that almost made you forget you were writing JavaScript. I never ended up submitting a PR, but it was pretty eye-opening.

At one point I went into a rabbit hole and tried to build something similar on my own, but it got complicated very quickly given my limited compiler knowledge. That’s why I always thought Prepack[1] was such a cool idea.

[0] https://benchmarksgame-team.pages.debian.net/benchmarksgame/... [1] https://github.com/facebookarchive/prepack

That said, I remember writing myself a note a few years ago to avoid Python projects. I had to clean up code from all over the company and make it ready for production. Everyone had their own Python version, dependencies missing from requirements.txt, three way conflicts between 2 dependencies and the python version, wildly different styles, and a habit of pulling in as many libraries as possible [1]. Even recalling those memories makes my stomach turn.

I believe constraints make a project shine and be maintainable. I'd prefer if you throw at me a real python instead of a python project.

[1] Yes, I'm aware of containers, I was the unlucky guy writing them.