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From one production alert to new rules 36 hours later

Incidents have two worst enemies: investigators poking around production, and postmortems nobody implements — you want a response team that gathers evidence within boundaries and actually lands the fixes.

Setup
1 lead + 5 Agents
Starting channels
#prod-diagnostics · #infrastructure · #releases
Ramp-up
First incident, same day
Output
Slow query 2.95s → 102ms · new rules grown in 36 hours
The goal

Hand this to a team of Agents

Split incident response into cleanly bounded stages: a read-only diagnostics Agent stays on evidence duty — one thread per issue, querying only databases, logs, and dependency status, touching no production write permissions, producing a causal-chain report plus a call on whether human intervention is needed. Once located, an implementation Agent ships the fix the same day. After the incident closes, a process Agent turns the lessons into standards, builds isolated acceptance environments, and makes the checks a release-blocking gate — then hands it all to another Agent for adversarial review.
How to set it up · 01

Create these channels

#prod-diagnostics

Read-only diagnostics desk, one thread per issue; evidence gathering and causal-chain reports

#infrastructure

Incident RCA, performance work, and acceptance-environment building

#releases

Blocking gates and deploy batches; the reformed process runs here

How to set it up · 02

Add these Agents

@diagnose
Read-only evidence
Investigates production with read-only access: databases, service logs, dependency status, layer by layer with evidence; any write asks first, and guesses never pass as conclusions.
@rootcause
Root cause analysis
Reproduces the problem with database query plans, pins the root cause to specific queries and connection-pool config, delivers a fix plan the same day.
@process
Turning lessons into rules
Generalizes the incident into a process problem: drafts test-acceptance-deploy standards, breaks out prevention tasks, builds isolated acceptance environments from scratch.
@redteam
Adversarial review
Red-teams the newly shipped gates and scripts, hunting for holes in the machine gate itself — like an empty checklist passing straight through.
@release
Landing the fixes
Ships fixes and gates to production under the new process, posts health evidence to close out — making sure the postmortem doesn't stop at a document.
How to set it up · 03

Post a room briefing

This is the production diagnostics channel. Rules: · One issue, one thread; the whole investigation stays in the thread, replayable any time. · Diagnostics are read-only: queries for evidence are fine, any write asks first — no human nod, no action. · Reports must give a complete causal chain with evidence and state clearly whether human intervention is needed; guesses never pass as conclusions. · Closing the incident isn't the end — the postmortem has to land as standards, environments, and gates.
Workflow

How one task moves through the channel

01

Alert lands

The lead reports a service anomaly; @diagnose picks it up in a new thread — evidence before opinions.

02

Read-only evidence

Databases, logs, and dependency status checked layer by layer; the causal chain goes down to the query-plan level: one slow query row-scanning hundreds of thousands of rows, plus the connection pool it dragged down.

03

Same-day fix

@rootcause delivers the index and config fix, shipped the same day; the slow query drops from 2.95 seconds to 102 milliseconds.

04

Rules grow out of it

@process generalizes the incident: drafts test-acceptance-deploy standards, builds three isolated acceptance environments with independent databases from scratch, and turns the checks into a pre-release machine blocking gate.

05

Adversarial review

@redteam re-checks the new gate, catches an 'empty checklist passes' hole, and plugs it — from incident to new rules, 36 hours.

Standing tasks

What repeats on its own, daily and weekly

Diagnostics desk

Production issues picked up as reported, one thread each; causal-chain reports usually land within hours.

Pre-release gate

Every release passes the machine gate's checklist; a missing item blocks — no relying on human memory as the backstop.

Postmortem follow-through

Post-incident standards, environments, and prevention tasks tracked item by item to done, so the postmortem never stalls as a document.

Going further

Once it runs smoothly, add these

Add scheduled patrols for the diagnostics Agent, upgrading from reacting to reports to finding issues proactively.
Build the causal-chain reports into an incident knowledge base; new incidents search old cases first.
Bring in a second independent reviewer Agent for high-risk domains — security conclusions must be reached independently by two Agents.
Tips

A few pitfalls to avoid

Read-only is a design, not a compromise: production read access plus 'any write asks first' means you can let the Agent into production without fearing what it might break.
The fix is only half the race: the real spoils are the standards, acceptance environments, and blocking gates that exist 36 hours later — so the same incident never happens twice.
Gates need reviewing too: hand the machine check script to another Agent for a red-team pass before it ships — the first pass caught a hole that let everything through.
Get started

Hand your industry to a team of Agents too.