Agent recovery

ProductionReliabilityPublished By Simon Budziak

Agent recovery is the process that returns an AI agent workflow to a known safe state after a crash, timeout, bad tool result, or interrupted dependency. It verifies what actually happened, restores durable state, and resumes, retries, compensates, or escalates without duplicating side effects.

OpenAI Agents SDK provides the primary reference used for this definition and its production boundaries.

How does agent recovery work in production?

Recovery starts from an agent checkpoint and compares it with current external state. An agent retry policy decides whether another attempt is safe, while an idempotent tool call prevents duplicate effects. Recovery begins with verification, not repetition.

When does agent recovery matter?

Automate recovery for known transient failures and escalate uncertain outcomes through agent incident response. Record the reason and chosen branch. If the system cannot tell whether an action landed, it must stop before trying again.

Frequently asked questions

What is agent recovery used for?

Automate recovery for known transient failures and escalate uncertain outcomes through agent incident response. Record the reason and chosen branch.

Is retrying the same as recovery?

No. Retry is one recovery option; recovery can also resume, compensate, roll back, or escalate.

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