Operator Stack
Workflow Jun 10, 2026 published

AI Automation Runbook Template

A practical runbook template for recurring AI automations so solo operators know how to run, monitor, stop, fix, and hand off the workflow.

A recurring AI automation needs more than a prompt. It needs a runbook that tells the operator what to do before, during, and after each run.

The runbook is the operating layer between a useful prototype and a workflow that can run without constant improvisation. It names the inputs, source checks, stop conditions, fallback steps, and handoff notes so the automation can move quickly without hiding risk.

What The Runbook Should Cover

Use the runbook for any workflow that runs more than once.

At minimum, document:

  • What the workflow does.
  • Who owns the workflow.
  • Which inputs are required.
  • Which sources or files must be checked.
  • Which parts are deterministic.
  • Which parts use AI judgment or summarization.
  • Which outputs require review.
  • When the workflow must stop.
  • What to restore if the workflow fails.
  • What changed since the last accepted run.

This keeps the workflow understandable even when the original builder is not present.

Copy This AI Automation Runbook

Place this file beside the workflow assets:

Workflow name:
Owner:
Purpose:
Run frequency:
Trigger:
Required inputs:
Optional inputs:
Source evidence required:
Private data boundaries:
AI-assisted steps:
Deterministic steps:
Expected output:
Review checklist:
Stop conditions:
Exception log location:
Change log location:
Rollback target:
Manual fallback:
Last accepted run:
Handoff notes:
Next review date:

The runbook should be short enough to use during a live run. If it becomes a long manual, split it into a setup guide, a run checklist, and a troubleshooting note.

Separate Run Steps From Review Steps

Do not mix the automation steps and the review steps.

Run steps explain how to produce the output:

  • Collect the input.
  • Check file names and required fields.
  • Run the prompt, script, or spreadsheet automation.
  • Save the generated output.
  • Save the source evidence.

Review steps explain whether the output can be used:

  • Compare the output to the acceptance criteria.
  • Check factual claims against cited sources.
  • Confirm disclosures or warnings are present when needed.
  • Confirm no private value was copied into an unsafe place.
  • Decide whether to publish, deliver, revise, or stop.

This separation prevents the workflow from treating a completed run as an approved result.

Add Stop Conditions

A useful runbook tells the automation when not to continue.

Use stop conditions such as:

  • Required input is missing.
  • Source evidence cannot be reached.
  • Output contains a factual claim that is not supported by the source.
  • Workflow requests a token, password, credential, or private value.
  • The current output conflicts with the last accepted run.
  • The operator has to rewrite most of the output by hand.
  • A public or client-facing claim needs review and no reviewer is available.

Stop conditions make the automation safer and easier to hand off. The operator should not have to decide from scratch every time something looks wrong.

The runbook should point to the working files that keep the automation controlled:

FilePurpose
Acceptance criteriaDefines what a good output must satisfy.
Source logRecords evidence used by the workflow.
Exception logRecords failures, repeated repairs, and unsafe outputs.
Change logRecords prompt, script, source, and review-rule updates.
Rollback planNames the last safe version and fallback process.
Handoff checklistExplains what another operator or client needs to know.

When these files are linked from one runbook, a future operator can understand the workflow without searching through chat history.

Keep A Last Accepted Run

Every runbook should point to one last accepted run.

Store:

  • Input sample.
  • Generated output.
  • Review notes.
  • Source evidence.
  • Final delivered or published artifact.
  • Prompt or script version.
  • Date and reviewer.

This makes future checks concrete. If the new output is weaker than the last accepted run, the operator has evidence for rollback, repair, or narrowing the workflow.

Use The Runbook To Decide What Can Be Productized

A runbook is also useful for monetization.

If the workflow can be run from the runbook by another operator, it may be ready to become a service SOP, checklist, template, or small product. If the runbook still depends on hidden judgment, undocumented source checks, or repeated manual rewriting, keep it as a reviewed service until the repeatable part is clearer.

The point is not to pretend the automation is fully autonomous. The point is to make the repeatable layer reliable enough that the remaining human work is visible, priced correctly, and safe.