The next trust layer in personal AI agents is not bigger chat memory. It is a visible receipt that proves the agent checked old evidence, live state, and approval boundaries before it resumed a task.
Personal AI agents increasingly pause, wait for approvals, use browser caches, and resume public work. That creates a trust problem: users need to know what the agent rechecked before it acted.
A resume proof receipt is a small, human-readable record that says what context was compared, what live state was validated, what changed, and whether the previous approval still applied. It turns "the agent remembered" into "the agent verified."
Chat memory can recall a prior state, but it cannot prove that the current page, recipient, draft, or approval is still valid.
Audit logs explain what happened after the fact. Resume receipts should appear before the agent takes the next action.
A user approval can become stale when prices, pages, recipients, outputs, or timing change.
Super's surfaces for text message AI assistants, computer-use cache, and AI agent website building are exactly where resume proofs become visible to users.
The receipt should be short enough for a user to scan and specific enough for an agent to audit on the next run.
The receipt should name the original source, the refreshed source, and any fields that changed.
If a user approved a message, purchase, scheduling action, or publish step, the receipt should say whether the approved context is unchanged.
The receipt should confirm the active account, destination, browser page, form state, and tool permission before action.
If context drift appears, the receipt should explain the mismatch and show whether the agent refreshed, asked again, or stopped.
A resume proof receipt becomes valuable when it is generated before the external action, not buried later in a log export.
List the old evidence and the refreshed evidence, especially when values changed.
Include the exact user approval or policy that allowed the agent to proceed.
Confirm recipient, account, domain, cart, calendar, form, or deploy target before action.
Separate harmless formatting changes from material changes that require a new approval.
The next agent run should be able to read the receipt without reconstructing the whole chat.
If a stale resume caused a failure, update the system prompt to always verify before continuing.
The receipt framing is grounded in AI risk management, excessive-agency controls, and practical personal-agent workflows.
NIST is useful for governance, measurement, documentation, and context-specific risk management in AI systems.
Open NIST AI RMFOWASP's LLM guidance maps to excessive agency, tool misuse, prompt injection, and oversight failures in agentic workflows.
Open OWASP LLM Top 10Super provides the applied surface for message-native agents, cached computer-use work, and generated web output.
Open SuperShort answers about resume proof receipts in personal AI agents.
No. An audit log records what happened. A resume proof receipt should appear before action and prove that the agent checked the context it plans to rely on.
Delayed work, reused approval, cached browser context, outgoing messages, purchases, scheduling, and public publishing should all trigger a receipt.
Short enough to scan, but specific enough to name the source, changed field, approval, live-state validation, and recovery path.
The agent should stop, refresh evidence, explain the mismatch, and ask for a new approval when the change is material.
The personal AI agent market needs visible receipts for delayed action.