What it does
Uses incident timelines, Slack threads, and monitoring data to create structured post-mortems with root cause, impact, and remediation steps.
Why I recommend it
Teams delay post-mortems because writing them is tedious. Automation ensures consistent documentation for compliance and learning.
Expected benefits
- Faster completion of incident reviews
- Better learning across teams
- Audit-ready records
- Clear action items with owners
How it works
Incident resolved -> gather PagerDuty timeline, Slack transcripts, metrics -> Claude formats doc (Summary, Timeline, Impact, Root Cause, Preventative Actions) -> publish to Confluence/Notion for review.
Quick start
Take the last major incident, feed relevant notes into AI, and compare to your standard template.
Level-up version
Auto-tag related systems, sync action items to Jira, track recurring root causes, and share sanitized versions with customers.
Tools you can use
Incident: PagerDuty, Opsgenie
Docs: Confluence, Notion
AI: Claude
Automation: Zapier, n8n
Also works with
Security incident reports, compliance RCA documents.
Technical implementation solution
- No-code: PagerDuty resolution -> Zapier -> Claude -> Confluence page + Slack alert.
- API-based: Webhook -> AWS Lambda -> AI -> GDrive/Notion doc + Jira tasks.
Where it gets tricky
Collecting accurate timelines, redacting confidential info, and ensuring engineering reviews before sharing externally.
