Evaluation Gates and Evidence — Proving Governance Happened
Two questions separate real AI governance from theater: can you stop a model that fails its checks from reaching production, and can you prove, after the fact, that the checks were done? The first is an evaluation gate; the second is evidence. Together they turn governance from a set of good intentions into something enforceable and auditable. This post is about the mechanics of gating AI systems on quality and automatically capturing the proof that it happened.
Two questions separate governance from theater: can you stop a model that fails its checks, and can you prove the checks happened? Evaluation gates that fail closed (with teeth and legitimacy), and evidence — the automatic audit trail that governance-as-code produces for free — for regulators, auditors, and incident reconstruction.