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the real gains ought come from looking at where tool calls fail and then (a) improve the tool and (b) improve the instruction.
I saw something that framed this as inner-loop / outer-loop and how subagents are increasingly a better way to prevent context pollution
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Unless it's super straight-forward, it generally works better for me to have the option to edit the instruction so I pass that into an issue that I can edit before assigning. I do often do subtask decomposition instructions though - it doesn't all have to be hitl within a consistent task. Context matters then though, so I try to define my tasks so that context stays under 100k tokens.
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I'm on my 4th iteration of my local forge skill and on the 3rd of my set of dependency analysis templates (I basically have specific ones for each framework / language and some get tuned for things that I review often). The only thing that stays relatively static are my standard prompt templates for "do this", "test that", "examine this", "answer the effen question". It would be better if I had something more structural to this than reminding myself that "hey maybe I can make some time this week to orchestrate a bot retro".
I need deeper traces if I'm to improve things with all these new models in the mix though. Sometimes it's obvious and I can just add a line that prevents specific behavior. But based on the paper, the real gains ought come from looking at where tool calls fail and then (a) improve the tool and (b) improve the instruction.