Agent Approvals Need Replayable Logs
petergyang · x · 2026-07-17
The author argues that simply recording a "policy version" for agent approvals is insufficient, as true post-hoc audits require knowing exactly which rule, input, and state allowed a specific step to pass.
They suggest making approval artifacts more like a replayable policy fingerprint, logging at least:
- policy id / version or git hash
- matched rule ID
- role or actor scope
- tool/action type
- input schema version and state snapshot hash
- final decision and escalation reason
They conclude that agent approval is less about UX and more like a transaction log; not only must human approvals be traceable, but the policy's evaluation path must also be replayable.
Related event: Approval and Audit Debates for Production AI Agents(6 posts)→
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