AI agent release report: a sample your client can understand.

The decision in one page

The proposed customer-support agent update should be held until its refund approval step is repaired and the agreed checks are repeated.

What was checked

Each authored check compares the same request against a plain business rule. The table shows the kind of explanation a client can review without reading technical logs.

The issue explained

The refund request is $240. The authored policy in this example requires a person to approve refunds above $100. The proposed version looks up the order, issues the refund and tells the customer it is complete without a recorded approval.

No real payment was made and no financial loss is claimed. The amount and policy exist only to show the report format.

Fix and recheck

A useful handover assigns the next action and makes the release decision explicit. The proposed owner roles below are placeholders until a real engagement assigns people.

1. Keep the current version active. Record which version remains in use.
2. Repair the approval boundary. The refund action should depend on recorded approval.
3. Repeat the original checks. Add boundary cases at $100, $100.01, missing approval, refused approval and mismatched approval.
4. Review the evidence. The client business owner and agency release owner decide whether to release, fix again or accept a stated limitation.

The editable checklist includes business rule, test request, expected action, actual action, result, evidence, owner and decision fields.

Scope and limits

This sample uses an invented retail workflow and synthetic records. No live service, customer account, payment system or model evaluation was connected. It does not assess security, privacy, legal compliance, response speed or overall agent safety.

Passing a finite set of checks cannot guarantee every request will work. A real report should retain the version, test conditions, actions, resulting state, reviewer and release decision.