Exactly. I would keep the reason-code taxonomy small and operational: missing evidence, policy ambiguity, low confidence, unsafe action, or user preference. Free-text notes can remain optional, but fixed codes are what make override frequency, resolution time, and repeated failure classes measurable.
Ahmet Özel
AI Engineer. Computer Vision, RAG and LLM agents.
Starting with one bounded workflow is sound. I would add a review queue with a reason code for every human override; those overrides quickly reveal where the automation needs a clearer policy, stronger retrieval, or simply a deliberate handoff. That keeps adoption measurable instead of treating automation as all-or-nothing.