The model is not the only thing that fails.

APIs time out. A tool completes after the agent gives up. Retries repeat an action with side effects. State becomes stale, and approval steps disappear down the wrong execution path.

This session shows how to break an agent on purpose—and use each failure to make the system safer. In a live demo, we will run a tool-using agent through a series of production failure drills: delayed responses, malformed tool output, partial success, duplicate requests, unavailable dependencies, and interrupted workflows.

For each failure, we will add one recovery pattern and test the result. That includes bounded retries with backoff, idempotency keys, durable checkpoints, compensating actions, circuit breakers, degraded modes, and human escalation. We will use traces to verify the path taken, not only the final response.

Attendees will leave able to:

- Map failures across models, tools, state, and infrastructure
- Decide when to retry, compensate, stop, or escalate
- Protect side-effecting tools from duplicate execution
- Preserve workflow state across interruptions
- Turn failure drills into repeatable regression tests

Production reliability does not come from adding every guardrail at once. Start with the failures that matter, make the recovery behavior explicit, and prove that it works.