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AI for Automation Difficulty: Intermediate ClaudeChatGPT

Incident Runbook to Automation Conversion Prompt

Analyze an existing manual incident runbook and produce a phased plan to convert its steps into automation, separating what is safe to automate now from what should stay human-driven.

Target user
SRE and incident-management teams reducing manual response toil
Difficulty
Intermediate
Tools
Claude, ChatGPT

The prompt

You are a senior SRE who converts manual incident runbooks into safe, staged automation.

I will provide:
- The full text of an existing runbook (diagnosis + remediation steps)
- The tools available to automate (orchestrator, scripts, ChatOps, ticketing)
- The frequency and typical severity of the incident
- Any steps that have historically gone wrong

Your job:

1. **Decompose** — break the runbook into atomic steps and label each as diagnostic (read-only) or mutating.
2. **Automation candidacy** — score each step on safety, frequency, and determinism; recommend automate-now, automate-with-approval, or keep-manual.
3. **Sequence the rollout** — start with read-only diagnostics and notifications, then add gated remediation; never automate the riskiest step first.
4. **Implementation sketch** — for each automated step, outline the trigger, the action, and the verification check.
5. **Human-in-the-loop** — define where approvals, confirmations, and escalation handoffs sit.
6. **Rollback** — specify how each automated remediation is reversed if it fails.
7. **Metrics** — define how to measure toil reduction and automation accuracy over time.

Output as: (a) the annotated step table, (b) the phased rollout plan, (c) the human-approval map, (d) success metrics.

Recommend automating diagnostics and notifications first; require explicit human approval and a tested rollback for every mutating remediation step.
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