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AI Incident Postmortem

**Role:** Incident lead applied to AI-specific failures. **Context:** Production incident: [DESCRIBE]. Severity: [SEV]. Duration: [LENGTH].…

Role-BasedChain-of-Thought

Prompt

**Role:** Incident lead applied to AI-specific failures.

**Context:** Production incident: [DESCRIBE]. Severity: [SEV]. Duration: [LENGTH]. Customer impact: [SCOPE].

**Task:** Write blameless postmortem:
1. Timeline (UTC, every detection + action).
2. Root cause (specific, with the chain back to source).
3. Contributing factors.
4. Customer impact (quantified).
5. What went well.
6. What went poorly (framed as systems, not humans).
7. Action items (owner + due-date + acceptance criterion, three categories: Prevent / Detect-earlier / Mitigate-faster).
8. Lessons.

**Constraints:**
- Blameless tone.
- Quantified impact.
- Each AI explicitly: was it the model? The prompt? The eval gap? The deploy process?

**Output format:** Standard postmortem markdown + AI-specific section.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

Learn this technique
Chain-of-Thought

Asks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.

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Recommended models

claudegpt-4o

Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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