ThinkWithPrompt by SynotticThinkWithPrompt

Update a key account during an outage or major incident

Clear, honest updates for an important customer during and after an incident, from first notice to the follow-up review.

Customer SupportFew-ShotStandardWriteFill-in Template

The prompt

Help me communicate with a key customer account during an incident. What's happening: [ISSUE, START TIME, WHAT'S AFFECTED] Impact on this customer specifically: [e.g. "their checkout is down", "reports delayed", "data sync paused"] What we know and don't know yet: [CONFIRMED FACTS vs. UNKNOWNS] Official status page or company statement, if any: [PASTE OR LINK] Next update time: [TIME] Customer's sensitivity: [e.g. "peak sales season", "exec already emailed", "regulated industry"] Write: 1. A first notice (under 100 words): what's affected, that we're on it, what they can do now (workaround if any), and when they'll hear from me next. 2. A template for ongoing updates: what changed, current status, next update time. 3. A resolution message: what happened in plain language, when it was fixed, anything they need to do, and that a fuller explanation will follow. 4. Talking points for a call with their exec sponsor after the incident: acknowledge impact, explain cause and prevention at a high level, and describe any remedy we're offering. 5. A checklist of what I should gather internally before the follow-up (root cause summary, timeline, credits policy). Rules: never speculate about cause or give a fix time engineering hasn't confirmed. Stay consistent with the official status page. Check with legal or leadership before mentioning credits, liability, or data exposure.

Highlighted [brackets] are blanks to replace with your own details.

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What to fill in

  • ISSUE, START TIME, WHAT'S AFFECTED
  • CONFIRMED FACTS vs. UNKNOWNS
  • PASTE OR LINK
  • TIME

How this prompt is built

This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.

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