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AI Agent Compliance Logging
Last updated: 2026-09-24
Short answer: AI agent compliance logging preserves the records needed to review permissions, executions, outputs, failures, and evidence without exposing secrets. It supports compliance work but does not make a system compliant by itself.
Last reviewed: 2026-09-23. This page describes a reviewable evidence pattern and does not claim an outside result without upstream confirmation.
Scope and identity
Record the caller scope, tool, task boundary, timestamp, and relevant policy decision.
Execution and integrity
Preserve the observed result, status, canonical bytes, hash, provenance, and verifier response.
Retention and access
Document retention, redaction, access, deletion, and incident review rules for the records.
Evidence boundary
Separate a recorded execution from an external action that requires a provider confirmation.
Open a public execution receipt or call its verifier. The example reports verification_status: verified for the stored record. It is not proof of an unobserved external outcome.
Frequently asked questions
AI agent compliance logging
AI agent compliance logging preserves the records needed to review permissions, executions, outputs, failures, and evidence without exposing secrets. It supports compliance work but does not make a system compliant by itself.
What can a verifiable receipt prove?
It can show what the execution layer recorded and what its integrity checks verify. It cannot prove an unobserved outside outcome.
How can another reviewer check the record?
Open the public receipt, compare the tool, time, result, and status, then call the verifier. Keep outside confirmations separate from the execution record.