Run an AI Agent Rollback Drill Before the Agent Runs You

The goal

An AI agent rollback drill proves that a team can contain an agent, understand what it changed, repair affected systems, and restart safely. Do it before granting write access to customer, financial, publishing, identity, or production systems.

1. Map authority and side effects

List every credential, tool, data source, queue, scheduled task, webhook, model, and downstream system. Mark read, draft, approve, write, send, delete, and purchase permissions. Identify actions that cannot be cleanly reversed.

2. Define the incident

Use a safe staging scenario: the agent receives misleading input and begins creating duplicate records or preparing incorrect outbound messages. Inject one failed tool and one delayed queue so the drill tests partial completion.

3. Stop new work

Trigger the documented kill path. Disable schedules and webhooks, block new runs, pause workers, revoke or rotate scoped credentials, and quarantine pending actions. Do not delete evidence needed to understand the incident.

4. Establish the blast radius

From immutable logs, identify prompts, model and version, retrieved context, tool calls, human approvals, records changed, messages sent, queued jobs, and retries. Reconcile the agent log with each destination system.

5. Repair and communicate

Reverse reversible writes with idempotent scripts or reviewed procedures. Flag uncertain records instead of guessing. Notify system owners and affected people according to the incident plan. Preserve a decision log.

6. Restart behind a smaller boundary

Fix the cause, add a regression case, reduce permissions or scope, and replay in shadow mode. Require explicit approval before restoring write access. Set a monitoring window and named owner.

Pass criteria

The team can stop new actions within its target time, account for every side effect, revoke authority, preserve evidence, repair safely, and restart only after an independent reviewer signs off.