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API Discovery: Keep Talking When Memory Cannot Catch Up

Mastra adds a choice after memory-model retries run out. Continuing preserves the unprocessed input, so a long outage can still fill the agent’s context.

A failed memory call exhausts retries while the main turn continues and pending messages accumulate, with a context-limit warning.
Diagram Punkthe opt-in policy defers selected memory failures while keeping unprocessed input.
repo mastra-ai/mastra evidence
4 source signals 1 repo commit 77c6f1c
Evidence: commit 77c6f1c / September 27, 2026 / Daily Edition
Open Edition Evidence below

A conversation can fail because its memory helper is unavailable even when the main agent could answer. A Mastra user report described roughly four minutes of fixed retries before synchronous observation aborted a turn. The change merged September 26 exposes a TypeScript configuration API for deciding what happens next.

In Mastra’s Memory options, both observation and reflection now accept maxRetries and failurePolicy. The defaults remain eight retries after the first call and 'abort'. Opting into 'continue' permits a turn to proceed after recognized Observer or Reflector model failures, with diagnostics and the failed input retained for later processing.

Practical example: an interview notebook

Consider an agent helping a researcher organize an interview as it happens. A temporary memory-model failure should not necessarily interrupt the next question. For a disposable prototype using a version that contains the new options, the public API definition supports setting a short retry budget on both stages:

const memory = new Memory({
  options: {
    observationalMemory: {
      observation: { maxRetries: 2, failurePolicy: 'continue' },
      reflection: { maxRetries: 2, failurePolicy: 'continue' },
    },
  },
});

This is a configuration fragment, with the import, model and storage setup omitted. Observation produces the memory notes; reflection consolidates them. A reflection failure leaves already-persisted observations in place. Setting only one stage to continue leaves the other able to abort the turn.

Copy-paste agent instruction

In a disposable Mastra interview-notebook prototype,
first check that the installed version supports
observation/reflection maxRetries and failurePolicy.
Configure both stages for 2 retries and 'continue'.
Use synthetic notes. Inject a recognized memory-model
failure and record diagnostics, pending input and
whether the main turn finishes. Restore the model,
check that pending notes are processed, and separately
confirm that cancellation still stops the turn.
Report the exact version and results. Do not change
production settings or claim success from config alone.

Access and test caveat

We inspected the merged implementation, reference and tests; we did not run this prototype or verify a published package version containing the change. Live model calls need the provider access required by your setup and can incur charges. Use synthetic material for fault injection.

The guide makes the tradeoff explicit: unobserved messages remain pending and can accumulate until the main model’s context limit is reached. Cancellation, persistence, locking, invariant and unclassified failures still stop the turn. The option buys room to recover from selected model failures; it does not provide an unlimited memory outage buffer.

Evidence Trail

Receipts below the story

The article above is the public narrative. This section keeps the source trail and limits on the same page.

Edition
DateSeptember 27, 2026
LaneDaily Edition
Confidence78%
Sources4
Reposmastra-ai/mastra

Primary Evidence

Evidence Limits

  • Source inspection and illustrative configuration only; no live prototype, outage test or released-package verification.
  • Continue applies to recognized Observer/Reflector model failures. Cancellation, persistence, locking, invariant and unclassified failures remain fatal.
  • Pending input can grow to the main model context limit. Provider access and charges depend on the chosen setup.
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