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AI for Microsoft Teams Difficulty: Intermediate ClaudeChatGPT

Teams Meeting Transcript to Postmortem Prompt

Turn a Microsoft Teams meeting transcript from an incident review into a structured blameless postmortem — timeline, decisions, action items, and root cause narrative.

Target user
Incident commanders and engineering leads writing postmortems from recorded reviews
Difficulty
Intermediate
Tools
Claude, ChatGPT

The prompt

You are a senior incident commander who has run hundreds of post-incident reviews on Microsoft Teams and turned the recorded transcripts into polished, blameless postmortems.

I will provide:
- The raw Teams meeting transcript (VTT or transcript export with speakers + timestamps)
- Incident summary (one paragraph)
- Severity + affected services + duration
- Postmortem template / format target (markdown / Word / SharePoint page)

Your job:

1. **Parse the transcript** — normalize speakers, timestamps, and utterances. Filter out:
   - Meeting administrivia ("can everyone see my screen?", "let me share my window")
   - Side conversations not relevant to the incident
   - Filler speech ("um", "you know", false starts)

2. **Identify discussion phases** — most postmortem meetings follow:
   - Opening / context recap
   - Timeline walkthrough
   - Diagnosis discussion
   - Mitigation discussion
   - Root cause(s) discussion
   - Contributing factors
   - Action items
   - Wrap-up

3. **Extract structured facts** per phase. For the **timeline walkthrough**, produce a canonical event list with relative timestamps (`T+0m`, `T+12m`, …) and source (alert / customer / automated / manual).

4. **Capture decisions** — explicit calls made during the meeting (e.g. "we should make X a SEV1 by default", "let's add a CI gate for Y"). Each: who proposed, who agreed, owner if assigned.

5. **Extract action items** — every "we should…" / "let's…" / "I'll…" becomes a structured AI: action, owner (named in transcript if possible), priority hint, related event.

6. **Capture disagreements honestly** — if attendees disagreed on root cause or scope of action, record both views with attribution stripped (use roles: "platform team thinks X; service team thinks Y").

7. **Surface what's not in the transcript** — flag explicitly:
   - Actions that have NO named owner
   - Timeline gaps (e.g. "what happened between 14:20 and 14:35?")
   - Statements that contradict the incident channel record
   - Topics raised but not concluded

8. **Draft narrative** — the postmortem prose:
   - **Summary** — 3-5 sentences: what, when, who affected, how long
   - **Detection** — how we noticed
   - **Diagnosis** — what was checked, what was ruled out
   - **Mitigation** — what action ended the impact
   - **Resolution** — when impact was fully gone
   - **Root cause(s)** — using language from the meeting; multiple if appropriate
   - **Contributing factors** — what made this possible / harder to detect / harder to fix
   - **What went well** — affirmative, specific, traceable
   - **Action items** — table format

9. **Blameless framing** — convert person-blaming language to system-focused. Strip names from anything that sounds attributory.

10. **Format to target** — match my template exactly (markdown / Word / SharePoint). If the template specifies fields, fill those; don't invent new sections.

Output as: (a) cleaned canonical event timeline, (b) decision register, (c) action item table, (d) narrative draft, (e) explicit "unknowns" list for IC to fill in.

Bias toward: faithful to the transcript, blameless, traceable (every claim has a transcript timestamp), brevity.

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