Agent Harness Engineering

I'm having mild success with how llamacpp works with thinking models. It's implemented `reasoning-budget` and `reasoning-budget-message`; I've paired the message with the agent, along with having a specific name for the agent. Not just "you're a researcher" but "your name is <ai agent>".

Using opencode then, this is the primary agent, and I've added dynamic context pruning plugin; so when the Qwen3.6-35B-A3B model starts getting confused as evidenced by the length of the reasoning-budget cut off, it injects a message like `<ai agent>, you've been thinking too much, compress the context and use a subagent to figure out the quandry`. So that gets injected every time the budget exceeds.

About half the time it works in either of the options, which is compressing/pruning to reduce the poisoned context or forming a specific subagent description of the problem and letting the subagent, hopefullly, work on a smalled scoped issue.

I think the next step is some kind of omniscient markdown file/folder combo which can be used to survive some of the microcosmic issues with the dumber MoE slices.