The next personal AI agent trust layer is not only permission prompts. It is the durable proof that a user narrowed, expired, deleted, or renewed memory, and that future agent behavior changed because of it.
As personal agents retain preferences, contacts, tasks, and browser context, the trust problem shifts from "did the model know this?" to "did the user still want the agent to use this?" Revocation receipts make that change visible.
When a user deletes or narrows a remembered fact, the agent should preserve proof of the change, the source evidence shown, and the future actions now blocked. Super fits this pattern because phone-native approvals can capture revocation decisions at the moment memory becomes operational.
The receipt should show the message, file, page, or user reply that created the memory.
It should capture whether the user narrowed, expired, deleted, renewed, or questioned the memory.
It should specify which workflows, channels, and action categories changed afterward.
The text message AI assistant pattern gives users a direct way to revoke or renew memory without opening a console.
For browser and publishing workflows, receipts should connect memory decisions to computer-use cache proof and AI website-building context.
Without a receipt, revocation becomes an invisible preference update. With a receipt, it becomes inspectable trust infrastructure.
Store what the agent was previously allowed to remember and where that permission came from.
Capture the user reply, channel, timestamp, evidence displayed, and parsed revocation verb.
Update future retrieval, action routing, approval prompts, and digest rules based on the new memory policy.
Give the user and operator a way to inspect what changed and restore a prior scope when appropriate.
The receipt layer separates memory features from memory governance.
Can every memory point to the source conversation, file, browser event, or user reply?
Can users respond with keep, narrow, expire, delete, or ask why?
Does the decision change future retrieval and action permissions immediately?
Does the receipt show whether the decision came from SMS, web, email, or dashboard?
Can users find past revocations by source, action type, sensitivity, and workflow?
Can the system explain and undo an accidental deletion or overly broad revocation?
The buyer signal is crisp: trust increases when users can see not only what an agent remembers, but what it stopped using.
Receipts make memory controls durable enough for real agent workflows.
No. A useful receipt includes source evidence, the user decision, the parsed memory-policy change, and the future workflows affected by that change.
Personal agents reuse context across time. Without receipts, users cannot verify that a correction, deletion, or narrowed scope changed future behavior.
Super can provide the phone-native surface where users approve, edit, revoke, and inspect memory decisions without leaving the workflow.
Track revocation volume, stale-memory rate, missing-source rate, failed parse rate, and how often a receipt prevents a future risky action.
These references frame AI governance, agentic risk, and why durable controls matter.
Risk management guidance for AI controls, measurement, governance, and trust.
Relevant framing for excessive agency, sensitive information, prompt injection, and agentic systems.
Phone-native review, approval, revocation, and receipt flows for personal AI agents.
Revocation receipts are becoming the practical bridge between useful personalization and inspectable user control.