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Human review triggers for AI agents.

A checklist-style page for routing ambiguity, authority gaps, sensitive state changes, memory promotion, and high-impact actions to human review.

Trust documentation Conceptual framework Reviewed 2026-06-13

Human review

Review should be a first-class system state.

Human review is not a last-minute escape hatch. It is the expected route when a system faces ambiguous authority, sensitive data, durable memory changes, high-impact action, or conflict between policy and task completion.

Claim boundary

This page describes a framework pattern and website content surface. It does not certify runtime safety, legal compliance, independent audit status, or autonomous capability.

Practical signals

Sensitive state change

Durable memory, access expansion, data movement, or external publication should trigger review.

Conflicting evidence

Contradictions require talk-back, quarantine, or review instead of silent synthesis.

High-impact consequence

Financial, legal, security, reputation, or safety impact requires explicit human routing.

How to apply it

  1. Detect the trigger

    Identify which review condition is present and why normal action is insufficient.

  2. Pause the mutation

    Avoid durable state changes until the reviewer approves the evidence path.

  3. Resume with bounds

    After review, act only inside the approved scope and log the decision.

Relevant next steps

Use the related pages below to move from concept to evidence, Trust Center disclosures, and direct contact without broadening the claim beyond what is documented.