As agents learn from corrections, the next trust question is not only whether they can remember permission. It is whether they can prove permission was narrowed, expired, or reversed before the next action.
Research note
Personal AI agents are moving from static prompts toward persistent operating memory. That memory includes rules about when to ask, when to proceed, what context is sensitive, and which channels are allowed. Every one of those rules creates a second problem: if the rule is wrong, how does the operator know it was actually removed?
Task logs show what an agent did. Rollback evidence shows that a future permission was changed back after review. That evidence matters when an agent remembers a correction too broadly or carries a temporary exception into the wrong week.
The receipt should show the agent's prior lane: proceed, batch, ask, or block.
The receipt should show the narrowed, expired, or reversed future behavior.
A similar task should prove the agent no longer acts with stale authority.
Super is positioned around personal AI agent control loops where approval can happen in the operator's fastest channel. The text message AI assistant use case is especially relevant for urgent reversals.
When rollback evidence involves browser work, attach the context trail. The computer-use cache and AI agent website workflow show why replayable proof is becoming part of agent trust.
Pattern
A useful rollback receipt contains the source correction, old permission, new permission, reviewer, test task, and next expected behavior. Without those fields, the operator only has faith that the agent forgot correctly.
Show the message, browser action, or task result that created the permission change in the first place.
State whether the rule was too broad, temporary, noisy, unsafe, or no longer aligned with the operator's preference.
Write the corrected boundary in operational language the agent can follow on the next task.
Run one similar task and capture whether the agent asks, batches, blocks, or proceeds with the repaired rule.
Where it appears
The operator changes what the agent should do.
The future permission changes.
The next task proves the rollback worked.
The system records how authority was repaired.
Checklist
FAQ
Yes. An audit log records an action. Rollback evidence records the repair of future authority after an operator changes or reverses a learned rule.
No. Corrections that affect preference wording may not need it. Corrections that change approval boundaries, privacy handling, external communication, or browser permissions should have it.
Some reversals are urgent. If an agent learned a risky rule, the operator should be able to reverse that authority in the channel they will actually see.
A personal AI agent that can learn should also prove it can unlearn. Rollback evidence turns consent repair into something operators can inspect.