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esperenttoday at 7:29 AM1 replyview on HN

> example I have rules when using Pi to ask main agent to dispatch implementer agents in parallel using git worktrees. Some time it uses git worktrees, sometimes no

I've taken the approach that whenever this happens, it's my fault. The instructions were not clear enough, not direct enough, or more often, there's just too many of them.

I'm now at the point where my pi system prompt + agents + skills + tools starts out at just 7k context. It's all very clear and concise. I almost never have ambiguous responses like this, at least not bear the start of a session.

Combined with instructions to keep the main session as a coordinator and use subagents for all non trivial work, I can get a lot of work done before hitting 100k context and basically never go over 150k.

It's a stark contrast with Claude code where I was starting at about 35k context even after trimming my stuff down. It's hardly surprising if an agent doesn't know what to do if you dump 30k+ of context with all kinds of rules and workflows, most of them unrelated to the current tasks, before you even do anything.


Replies

azurewraithtoday at 11:52 AM

you're not wrong and trimming context is legitimately the first thing that everyone should do. even with context trimming and a tight prompt the model still makes judgement calls about which tools to use and when to stop.

that's fine 90% of the time... the state machine for the other 10% where the model's judgement call costs you an hour of debugging later (confidently fixed wrong, or overzealously) or stops a mostly automated thing because it got stuck on the wrong path.