Resume packets are compact state bundles that let a personal AI agent pause, transfer, and restart work without making the user reconstruct context from a chat transcript.
As personal AI agents stretch across phones, browsers, calendars, inboxes, and public publishing workflows, the key product question becomes simple: can the work restart cleanly after a pause?
A handoff log explains a pause to the human. A resume packet packages the same moment for continuation by the agent. It should be short enough to inspect and structured enough that a future run can continue from the exact edge of action.
The user approves or revises from a compact message. The agent resumes from a packet that preserves details the text should not have to show.
Tabs, forms, screenshots, and source pages decay quickly. Resume packets preserve enough state to avoid repeating the whole browse.
Generated pages, documents, or listings need a packet that explains what changed and what remains unsafe to publish.
Super is relevant when personal agents cross text approvals and browser action. A resume packet works behind the short approval message in the text message AI assistant flow while pairing naturally with the computer-use cache for browser state.
The packet should give future execution enough context to proceed without hiding risk or forcing the user to reread the whole task.
Summarize the original goal, completed steps, current state, and exact stopping point.
Store source URLs, screenshots, snippets, and browser context so the agent can continue without guessing.
Name the user decision, pending approval, or rejection that controls the next action.
For public artifacts, such as Super's AI agent website building workflow, preserve draft state and publishing risk separately.
Ask these questions before trusting a personal AI agent to pause and restart important work.
The packet should be useful even if the original model, browser session, or chat thread is gone.
Resume packets should be structured and readable, not opaque serialized state.
The packet should carry boundary rules and pending approvals alongside evidence.
These references help frame resume packets as part of broader governance, continuity, and oversight design.
Useful for governance, measurement, documentation, and managing AI risk across operating contexts.
Open NIST AI RMFRelevant for excessive agency, tool misuse, prompt injection, sensitive information, and oversight patterns.
Open OWASP LLM Top 10Reference workflows for text approvals, browser work, cached computer-use context, and generated public artifacts.
Open SuperCommon questions about resume packets for personal AI agents.
A handoff log is primarily written for a person. A resume packet is written for continuation by a person, model, or future agent run, while staying readable enough to inspect.
No. Memory changes future behavior. Resume packets preserve current task state so work can continue without reconstructing context.
They should live with the task record, linked receipts, cached browser context, and approval history. The user should see a short version in text when a decision is needed.
It matters when work spans time, channels, models, browser sessions, or public outputs where restarting from memory alone would be risky.
Resume packets let personal AI agents carry the right state across pauses without making users inspect a whole transcript.