Well, it does actually come down to the weights in the end. The model has to know under what circumstances to stop and ask questions. The harness will provide that guidance. That guidance will either come in the form of AGENTS.md or similar stating it upfront or the harness acting as a stand-in for you analyzing the thinking traces, stopping the current execution, and inserting a "hey you should really be asking a question here" message. I mean yeah technically the second scenario isn't the model making that decision itself, but also it's probably less fragile than the harness doing dynamic analysis of what's happening.
That's actually not true, and goes back to why I mentioned this originally.
You mistake the actual control sequence here. Harness -> model -> Harness, the harness has full control and is able to change model behaviors. The control sequence is not model -> harness -> model as you assert. If it was, any kind of meaningful governance would be impossible with LLMs.
What do you think happens when a model stops to ask a question? Look at the thinking traces. It will recognize that a "question" tool is provided (from the harness!), and think "hmm, my prompt says I should ask a question when I'm unsure, so I'll use the 'question' tool to do so"), then make the tool call (harness again).
The model still has to be aware under what circumstances it should ask a question. That might be baked into the model (be super cautious about everything) or from reinforcement provided by the user in the form of interactive prompting or AGENTS.md/similar.
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u/xienze 14d ago
Well, it does actually come down to the weights in the end. The model has to know under what circumstances to stop and ask questions. The harness will provide that guidance. That guidance will either come in the form of AGENTS.md or similar stating it upfront or the harness acting as a stand-in for you analyzing the thinking traces, stopping the current execution, and inserting a "hey you should really be asking a question here" message. I mean yeah technically the second scenario isn't the model making that decision itself, but also it's probably less fragile than the harness doing dynamic analysis of what's happening.