Why sessions break continuity
Session continuity fails for structural reasons, not because the models are forgetful:
- State lives inside one product. Claude keeps its session history, ChatGPT keeps its own, Grok keeps its own, and none of it is portable as evidence. Move the job and the state stays behind, locked in the store of the AI that did the work.
- What survives is a summary. The next session inherits a retelling: compressed, written by the agent about itself, with failures and retries smoothed out. It reads fluently and verifies nothing.
- Done and claimed-done look identical. A step that ran and a step the summary says ran present the same way to the next session. It either redoes finished work or builds on work that never happened.
- Conversation continuity is not work continuity. A chat that remembers what you discussed is not a job whose executed steps can be checked. The conversation can be continuous while the work's state is unknown.
Continuity from the record
The alternative puts the state where neither session owns it. With work running through Zambo's executing layer, continuity works like this:
- Each call leaves a receipt as it runs. Tool name, arguments, observed result bytes and their hash, timestamp, saved by the executing layer at execution time, outside the agent's control.
- The run closes as one checkable set. A multi-step job closes under a single workflow commitment computed from its step receipt identifiers, so the next session can recompute the recorded set on its own and compare it against the steps the run claims.
- The next session verifies, then continues. It recomputes each receipt's hash over the saved result, the check the receipt verifier walkthrough steps through, and starts from the recorded state: the calls on record, the results saved with them, unchanged since they were saved, and any claimed step the record does not contain.
- The AI is interchangeable. Because the record lives outside every session store, in the open AER-1 format, the continuing session can be in a different AI entirely. Cross-AI memory is this same mechanism viewed from the memory side; context handoff is the moment it gets passed.
Continue your next session from the recorded state
- See one receipt: the live demo runs a real call and hands you its verifiable receipt, no signup. Open it in a different AI tomorrow and it still checks.
- Receipt a whole run: connect an agent over MCP at zambo.dev/mcp and every call in the run leaves a receipt as it executes. A Day Pass ($0.99) keeps a full day of runs receipted and seals a closed run so its record stays put.
- Keep the record in an open format: the receipts follow AER-1, an IETF Internet-Draft (draft-zambo-aer1-23), with public test vectors and independent implementations, so continuity never depends on one product keeping your sessions alive.
Resume: pick up where your AI left off
Sessions stop mid-task all the time: the window fills, the app closes, the workday ends, a different AI is better for the next step. Resume fails when the state of the job lives in the dead session's context, because the next session has to reconstruct it from a summary, or from your memory of the chat. It works when the job's state was written outside the session as it ran. Then picking up where the last AI left off is a read, not a reconstruction: open the record, check it, continue.
This page's example was run live on October 16, 2026. A first session started a named continuity thread, resume-demo-20261016 (thread 3d7810f8-c1e6-4091-abfd-c6436b6818e5), and ran two calls in it: a live_price lookup for BTC that returned $81,393.00 (receipt 54f066fd) and one for ETH that returned $2,431.47 (receipt 5ecb7841). That session then stopped. A second, fresh session opened the thread cold and was handed both steps with their receipt links and check links, oldest first, under the thread-start receipt e146216b. It continued the same job with a third call, a live_price lookup for SOL that returned $103.93 (receipt 9ab4bdf9). Every receipt named here reports verified at the public verify endpoint. The second session never saw the first session's context window. It did not need to: the record was the handoff.
To make your own work resumable: run it in a named thread, let each call leave its receipt as it executes, and when you switch sessions or AIs, open the thread instead of pasting a summary. The new session starts from checked state, and anything the old session claimed without a receipt shows up as a gap before it can become your problem.
AI agent session continuity: FAQ
What is AI agent session continuity?
AI agent session continuity is the ability of a new session to continue a job an earlier session started, with the recorded state of the work intact. The weak form is summary-based: the new session reads what the old session said about itself. The strong form is record-based: every call the earlier session ran left a verifiable receipt, the run closed under a single workflow commitment, and the new session recomputes that record before continuing. Summary-based continuity carries the story of the work. Record-based continuity carries the recorded state, in a form the next session can check.
How do I keep continuity when I switch between Claude, ChatGPT, and Grok?
Do not keep the record inside any of them. Each AI keeps its own session history, and none of those histories is portable as evidence: you can copy the words out, but the receiving AI cannot verify them. Run the work so each call leaves a verifiable receipt in an open format, and continuity stops depending on which AI you open next. The next session, in Claude, ChatGPT, Grok, Gemini, or Cursor, starts from the same record, recomputes it, and continues. The receipts follow the work; the AIs take turns.
What is cross-AI continuity?
Cross-AI continuity is continuity that survives a change of AI: work started with one assistant continues with another, without restarting and without trusting the first assistant's summary. It needs a record that lives outside both AIs and can be checked by either. Verifiable execution receipts in the AER-1 format, an IETF Internet-Draft (draft-zambo-aer1-23), are that record: the executing layer saves what each call returned, the receipt binds it under a hash, and any AI or person can verify it later by recomputing the hash. Continuity then becomes a property of the record, not of any one product's session store.
What happens to an AI agent's state when a session ends?
By default, it evaporates. The context window is discarded, and what survives is whatever the product saved: a transcript, maybe a summary. Neither carries proof of what the agent actually did, which steps ran, or what they returned. State survives in usable form only if it was written down outside the session as it happened. When each tool call leaves a receipt at execution time, the session's state is the set of those receipts plus the run's closing commitment, and that set can be handed to the next session, the next day, or a different AI, intact and checkable.
What is the best way to keep AI agent session continuity?
Keep the state where the sessions cannot rewrite it, in a form the next session can verify. Concretely: have the executing layer save one receipt per tool call as the work runs; close multi-step runs under a single workflow commitment over the step receipt identifiers, so the recorded set can be recomputed and compared against the steps the run claims; and start each new session by recomputing the record, so claimed steps with no receipt surface immediately. Tools that offer continuity as a stored summary fail the second test, because the new session must believe the summary. Continuity built on receipts passes it, because belief is replaced by recompute.
How do I pick up where my AI agent left off?
Open the record, not the chat. If the job ran in a named continuity thread, any new session, in the same AI or a different one, can open that thread and read the recorded steps with their verifiable receipts, oldest first, then continue from the last checked step. In the example above, a second session opened the thread cold, saw the first session's two price lookups with working check links, and added a third call to the same thread. If the job never ran in a recorded thread, there is nothing to resume from but summaries, and summaries are claims, not state.
My AI stopped mid-task. How do I resume its work?
Start from what is proven, not from what was planned. List the steps that left receipts; those are done, in the form the receipts show. Everything after the last receipt is unverified, however confident the last summary sounded, so re-run or re-check from that point instead of trusting the plan. A workflow closed under one commitment makes the boundary mechanical: recompute the root over the step receipt identifiers, and the steps that belong are exactly the steps that recompute. Resume is then just continuing the same record in a new session.
What is AI continuity?
AI continuity is the property that work survives the end of a session: a job started in one session, or with one AI, can be continued in another without restarting and without losing the recorded state of what already ran. Continuity carries context: the steps taken, the outputs saved, the thread a new session can open. It does not carry proof of correctness: a receipt in the record shows the saved result was not changed since it was saved, and continuity is what lets the next session stand on that record instead of on a summary.