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Guides/Memory

Memory for Agent Loops

Short answer

Long-running loops need memory strategy: what to keep, what to summarize, what to retrieve, and what to forget.

Reviewed 2026-07-14
Community project documentation
Memory categories checked against the linked Mem0 article

The recommendation is adapted into a bounded keep, summarize, retrieve, and forget decision table rather than treated as a product endorsement.

Open evidence source
Site evidence · maintained by TianMingAI · reviewed 2026-07-21

What should persist between runs, and what should be re-read from the live project instead of trusted from memory?

What we tested

We separated stable project instructions from one-run evidence. Package manager, validation commands, boundaries, and ownership rules belong in maintained instructions; current failures, diffs, command output, and blockers belong in a dated run note and must be refreshed.

Observed result

The split kept durable rules compact while preventing a previous run's conclusion from replacing current repository state. The next iteration could retrieve the last decision, but it still had to re-run validation and resolve conflicts against live files and configuration.

What this does not prove

The exercise does not compare memory products or establish an optimal retention period. Auto memory, instruction files, retrieval stores, and conversation history have different precedence and privacy behavior that must be checked in the chosen runtime.

Why it matters

Without a memory plan, a loop either forgets what it learned or drowns in context. Deciding up front what to persist and what to drop keeps loops both coherent and affordable.

Practical checklist

  • Keep durable facts (goal, constraints, decisions)
  • Summarize long histories instead of re-sending them
  • Retrieve only the observations relevant to the next step
  • Forget stale or one-off detail

Example

A multi-day refactor loop keeps a short “decisions so far” note, retrieves the files touched this session, and summarizes everything else — rather than re-reading the whole repo each run.

Common failure modes

No persistence, so the loop relearns each run
Unbounded context growth
Retrieving irrelevant memory that distracts the agent

Practical evidence

Keep, summarize, retrieve, or forget

Keep

Current goal, constraints, accepted decisions, unresolved blockers, and approval state.

Summarize

Long run histories and completed investigation paths whose detail is no longer needed every turn.

Retrieve

The few prior errors, files, or decisions relevant to the next concrete action.

Forget

Superseded hypotheses, one-off logs, stale branches, and details contradicted by current source state.

Stale-memory failure

A saved note says a test is flaky, so the loop ignores a new deterministic failure. Current repository evidence must override the old note.

Related templates

Sources & further reading