Write a bug escalation engineering can act on without chasing me
An internal escalation to engineering or tier 2 with impact, reproduction steps, environment, and evidence engineers can act on immediately.
The prompt
Write an internal escalation of a customer issue to engineering or tier 2 support.
Issue in the customer's words: [SUMMARY]
Customer and plan/tier: [ACCOUNT TYPE - e.g. "enterprise, 400 seats"]
Steps to reproduce: [WHAT I DID - or "could not reproduce"]
Expected vs. actual result: [DETAILS]
Environment: [browser/app version, OS, device, region, account ID]
Evidence: [error messages, screenshots, log lines, timestamps with time zone]
What I already tried: [TROUBLESHOOTING DONE]
How many customers are affected: [COUNT or linked tickets]
Workaround available? [YES - describe / NO]
SLA or commitment at stake: [e.g. "contract response time 4 hours", renewal date]
Write the escalation with:
1. A one-line title: component + symptom + scope.
2. Impact summary: who is affected, how badly, and since when.
3. Suggested priority with a one-line justification based on impact and urgency, not on how loud the customer is.
4. Reproduction steps, evidence, and environment, as a numbered list.
5. What has been ruled out.
6. Exactly what I need back (fix, ETA, workaround, or a customer-safe explanation) and by when.
Keep it factual and under 300 words. Mark anything I haven't confirmed as [UNVERIFIED]. Do not guess at a root cause; list hypotheses separately if useful.
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore Customer Support prompts
What to fill in
- SUMMARY
- ACCOUNT TYPE - e.g. "enterprise, 400 seats"
- WHAT I DID - or "could not reproduce"
- DETAILS
- browser/app version, OS, device, region, account ID
- TROUBLESHOOTING DONE
- COUNT or linked tickets
- YES - describe / NO
- e.g. "contract response time 4 hours", renewal date
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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