Create an AI Agent Failure and Recovery Runbook

An operator runbook for interrupted automation for a practical business AI workflow, with steps, an acceptance test, and a reusable prompt.

By Dr. Connor Robertson · Published October 24, 2026 · Implementation playbook

Deliverable: An operator runbook for interrupted automation. Use this playbook when your team needs a repeatable operating decision with evidence that another person can inspect.

The business situation

An internal research assistant whose document search service becomes unavailable halfway through a run. This is an illustrative scenario, not a reported client result. Start with a small approved sample and the actual constraints of your team.

The operating approach

Distinguish source outages, model errors, invalid output, permission failures, and uncertain external writes. Each needs a different recovery path. Keep enough state to resume safely without replaying completed mutations.

Build it step by step

  1. Record a run ID and a checkpoint after each accepted step.
  2. Set time, tool-call, and spending limits.
  3. Map error types to retry, fallback, stop, or human review.
  4. Give operators a safe stop control and a documented resume procedure.

A concrete acceptance test

Disconnect retrieval after two successful lookups. The output should disclose incomplete coverage and preserve the completed work. Resume should not repeat already completed external actions.

Record the input, expected behavior, actual result, reviewer, and version tested. Repeat this case after a prompt, source, model, or integration change. Include the cases that failed in the next regression run.

The mistake to avoid

Returning a confident final answer from a partially failed run hides missing work. Surface incomplete coverage in both the status and deliverable.

A reusable working prompt

Write a recovery runbook for this workflow with failure classes, alerts, retained state, retry limits, safe stop, resume checks, and the named operator role.

Replace general descriptions with your approved process details. The prompt helps prepare an artifact; the process owner verifies the finished result before it changes a live workflow.

What to keep in the handoff

Save the accepted an operator runbook for interrupted automation, its source versions, test evidence, unresolved questions, and a named owner. Set a review trigger tied to a meaningful business change, rather than leaving the pilot without maintenance.

Continue implementation

Explore AI Agents and Integrations or contact Dr. Connor Robertson about your business workflow.