How to Design Effective Human Oversight Controls for AI Email Agents

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AI agents that send emails or outbound messages pose unique risks because, unlike code changes, sent messages cannot be recalled once they reach a recipient's inbox. A practical framework grades every outbound action on three axes — reversibility, blast radius, and stakes — assigning it a risk level from low (G1) to critical (G3). Controls are then matched to each grade, reserving human approval gates only for situations where a person can realistically intervene in time. For lower-risk sends, a 30-to-120-second delay with a one-click undo option provides strong protection without burdening reviewers with constant confirmation prompts. The approach aims to avoid two common failures: auto-sending with no safety net, and over-gating that causes humans to rubber-stamp approvals without genuine review.

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