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ZCode – Harness for GLM-5.2

zcode.z.ai

321–330 of 382 posts

Re: ZCode – Harness for GLM-5.2

#321

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But, it's still running on my desktop/laptop. I don't trust them to run on my machine. But, I guess I could run one VM with a desktop to contain the desktop app. Or, just keep using CLI agents.

Do you also run your browser in the VM? Why would an agent be less trusted than any other piece of software?

Seriously, you dont see any difference? A agent is non deterministic and may delete or change you data as a normal matter of operations. A browser, barring bugs or security issues, would not delete or modify the data you have outside the browser.

Re: ZCode – Harness for GLM-5.2

#323
post #9

Z.ai documents integrations with nearly all the popular CLI-based agents: https://docs.z.ai/devpack/tool/others If you're already used to your TUI coding agent, you don't need the desktop agent. Although it is nice that it is there for folks who prefer the Codex App/Claude App UI approach.

I believe the incentive here is more tokens. I recall limits being more generous with their inhouse harness

Re: ZCode – Harness for GLM-5.2

#324

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This is precisely what I've been working on targeting with https://dirge-code.github.io/ I've written up an explanation of what trips small models ups and how the harness can address that here https://yogthos.net/posts/2026-06-08-dirge-code.html

Very interesting work! I put some effort into getting it to work with models my hardware can actually run well and they just fall over immediately. gemma4 12b runs like molasses on my 2080 super but it was the only model able to, with your harness, actually do anything useful. It was the only useful thing I've gotten any model runnable with my hardware with any harness I've tried, very impressive! I suspect smaller m…

Thanks, glad to hear the harness is actually doing its job with smaller models on your end. There definitely seems to be a limit of how small a model can get before it can't do any practical work.

I find I tend to view agentic coding similarly to a genetic algorithm. The model is the mutator function, and the harness along with the tests acts as the selection function. Each round the model generates some plausible code, it gets tested against the constraints, the model gets feedback and iterates on it until it converges on something that's workable. So, the real trick is to make sure the environment is producing correct pressures to guide the model in the needed direction.

Another interesting project in this space I can recommend checking out is ATLAS https://github.com/itigges22/ATLAS

Re: ZCode – Harness for GLM-5.2

#325

Earlier quoted context omitted.

I don't even know what I would do with a desktop app. I'm running these things in headless VMs, so I can run them with `--dangerously-skip-permissions` or whatever. I don't trust them, even without that flag, on my desktop/laptop.

Might wanna check out https://github.com/LuD1161/agentjail - policy guardrails for coding agents. shameless self-plug. I've been dogfooding it for the last 3 weeks now.

Looks similar to https://github.com/nolabs-ai/nono. Maybe one day you can fill out https://github.com/LuD1161/agentjail/issues/10 with a comparison to that project too.

Re: ZCode – Harness for GLM-5.2

#326

Earlier quoted context omitted.

This is precisely what I've been working on targeting with https://dirge-code.github.io/ I've written up an explanation of what trips small models ups and how the harness can address that here https://yogthos.net/posts/2026-06-08-dirge-code.html

Do you have benchmarks comparing against Pi? The blog post doesn't include any hard numbers. For example, so far I haven't seen any evidence that LSP integration improves performance for small models vs using grep via a bash tool.

I haven't really seen anybody come up with a good test to show hard numbers on comparing agentic harnesses. It's a bit tricky to set up a definitive test given the whole non deterministic nature of LLMs. What I've been focusing on is watching the loop and seeing where model does things that it shouldn't have to. For example, I notice models doing stuff like writing python scripts to match parens for Clojure all the time using editors like Pi. So, having a mechanical way to repair parens, and when that fails, to give the model clear error regarding where syntax is broken removes that whole cycle.

As it stands, it's kind of subjective, you just have to try the harness and see if the model seems to be have better than with the other ones you've been using.

Re: ZCode – Harness for GLM-5.2

#327

Earlier quoted context omitted.

This is precisely what I've been working on targeting with https://dirge-code.github.io/ I've written up an explanation of what trips small models ups and how the harness can address that here https://yogthos.net/posts/2026-06-08-dirge-code.html

This is very impressive!

Thanks, it's been a fun and educational experience working on the project.

Re: ZCode – Harness for GLM-5.2

#329
post #286

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[flagged]

Which government are these? The ones you just made up?

Have you never heard of the Taliban?

Or, you know, our beloved and enlightened ally Saudi Arabia who hacked a journalist to death for mean words?

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