The Approval Layer

Design the review, not just the label

Saying a person is in the loop does not describe what that person can see, decide, or stop. An approval step needs a purpose, enough context to make a decision, and a clear path when something is wrong.

Ask what the reviewer is checking. Accuracy? An exception? A promise to a customer? Give the reviewer the relevant source material, not just the AI's answer.

Consider four variables

Consequence of error: what happens if this output is wrong? A draft internal summary and a commitment sent to a customer deserve different treatment.

Reversibility: can the action be undone? Do not confuse an editable draft with a message already sent or a decision already acted on.

Detection lag: how long might a mistake go unnoticed? Design a way to surface problems rather than assuming someone will notice.

Volume: how much can the reviewer actually examine? A growing queue is a reason to redesign the process, not a reason to pretend that a click equals careful review.

Make escalation usable

Name the person who handles an exception and a backup when that person is unavailable. Define what stays paused while the question is unresolved. Keep a record of what was approved and by whom.

Reviewers need authority to reject an output, ask for context, or return to a manual process. Track corrections and recurring exceptions so the system can improve.

Keep the boundary explicit

Not every workflow needs the same controls. Any decision to allow unattended actions needs a risk-specific review; a generic sampling percentage is not a safety standard.

For regulated or high-consequence work, involve the responsible specialist before changing the approval process. This guide is a design conversation, not a substitute for those requirements. For the first task, write down: what may be drafted, what must be reviewed, and what must never proceed without a person.