Fleet 2.7.0 is out.See what's new →
FleetFleet
Use case

AI Workflows for Incident Postmortems

The postmortem is due while the incident is still emotionally warm. The engineer who led the response — the only person with the full picture — is also the most exhausted, so the writeup slips a week, the details blur, and the document that ships is a timeline with the insight sanded off. Or worse: it assigns blame in language that teaches everyone to share less next time.

The raw material was all there at resolution time: the channel log, the timeline notes, the fix PRs. What's scarce is the synthesis energy, exactly when it's needed.

How it works with an agent fleet

A Fleet workflow drafts the postmortem from the incident's artifacts while they're fresh, a review step checks it for blamelessness and factual support, and the incident lead approves the final document.

Step Kind What it does
draft Document “Draft the blameless postmortem from the incident corpus: timeline, contributing factors, what worked, action items. Systems language, not people language.” Reads incidents/2026-06-meltdown/*.md.
review Review “Flag blame-coded language, claims unsupported by the timeline, and action items with no owner.”
lead-ok Approval gate Pauses the run for a human sign-off; records the approver, timestamp, and note.
publish Publish Shares the approved document at a link.

You build this once on the dashboard canvas; your self-hosted Fleet worker pulls the definition and runs it against your repository.

The lead's job shrinks from “write the document” to “correct the draft and approve” — an hour of judgment instead of a deferred afternoon of synthesis. The review step's blamelessness check is a real filter: “engineer X failed to” becomes a flag before it becomes culture damage.

The fleet pattern

Incident corpus → blameless draft → language + factuality review → incident-lead approval → publish. The postmortem ships in days while details are sharp, not weeks later when they've blurred.

Guardrails that matter here

  • The review step flags unsupported claims against the timeline — the postmortem says what the artifacts support
  • Blame-language filtering is an explicit review concern, protecting the reporting culture postmortems depend on
  • Action items without owners get flagged at the gate — the most common postmortem failure caught structurally

Who this is for

SRE and platform teams with a postmortem practice that's healthy in principle and chronically late in practice.

Frequently asked questions

Doesn't an AI-drafted postmortem lose the human insight?

The draft is the floor, not the ceiling: it assembles the timeline and the mechanically derivable factors so the lead's energy goes into the genuinely human part — the judgment about why, and what to change. The approval gate means nothing ships without that judgment applied.

What goes in the incident corpus?

Whatever the response produced: exported channel logs, timeline notes, the fix PR descriptions, monitoring screenshots' captions. Teams standardize a per-incident directory; the workflow points at it.

Run your first agent fleet

One binary. Five minutes. See every agent, coordinate every handoff, and keep a full audit trail of what your fleet did.