When an agent misbehaves, there are three places the fix can live: in the model (retrain or fine-tune), in the moment (correct it in conversation and hope), or in the definition. We settled on the third, and the mechanism is almost embarrassingly simple: a short, readable rule appended to the agent’s definition file, written by a refiner agent that reads the live transcript.
The properties this buys are the properties text has always had:
- You can read the policy. The agent’s accumulated corrections are a list of plain-language rules, not weights. Anyone can audit what the agent has been taught.
- You can diff it. Every behavioral change is a commit. “Why did the
agent start doing X?” has a
git blameanswer. - You can revert it. When a correction stops being true — the upstream bug got fixed, the style guide changed — you delete a paragraph instead of retraining a model.
The refiner reads the transcript where the misbehavior happened, drafts the narrowest rule that would have prevented it, and appends it. Rules accumulate; stale ones get pruned in review. The refiner has been refined by itself, seven entries deep — the mechanism is stable under self-application.
The second-order effect matters more than the mechanism: this is what makes agents teachable by non-programmers. One of our users runs a paid consulting practice on agents she corrects entirely in conversation — the agent’s own prompt tells it where its knowledge files live and instructs it to edit them on request. A correction given once lands in a file and applies to every output thereafter. The high-stakes phrasing rules her domain requires — the kind a general assistant gets wrong every time and cannot durably learn — were taught once, in plain English, and have held since.
Fine-tuning has its place. But for the long tail of “don’t do that again” — which is most of what teaching an agent actually is — a diffable text rule beats a gradient update on every axis that matters operationally: latency of the fix, auditability, reversibility, and who is allowed to do the teaching.