# AI Incident Response

## First Hour

1. Assign an incident owner and timestamp the record.
2. Contain the dangerous capability or narrow exposure.
3. Preserve versions, prompts, context, tool traces, outputs, logs, and customer-visible evidence.
4. Identify affected populations, time window, regions, tenants, and actions.
5. Verify rollback, disablement, permission revocation, or safe-mode behavior.
6. Record known facts separately from hypotheses.

## Analysis

Look beyond the model:

- input and data quality;
- prompt and policy composition;
- retrieval and freshness;
- tool selection, permissions, and side effects;
- parsing and UI transformation;
- model or provider changes;
- monitoring and alert thresholds;
- human approvals and escalation;
- organizational incentives and release process.

Preserve disagreement. Premature consensus can erase the condition that would reproduce the incident.

## After Recovery

- quantify customer and business impact;
- communicate when legal, contractual, safety, or trust obligations require it;
- create representative and neighboring regression cases;
- update risk slices, claims, monitors, SLOs, and release gates;
- test the recovery path, not only the original failure;
- assign owners and dates for unresolved conditions.
