AgentFire is a reliability and endurance-testing platform for autonomous agents — essentially chaos engineering for AI agents. It compresses a simulated 24-hour production shift into minutes and tests whether an agent remains reliable as history and memory accumulate.
In the first incident, the agent diagnoses an expired authentication credential, remediates it, and verifies recovery. RawTree stores the full flight recorder of observations, tool calls, actions, and evaluations. Liquid AI then compiles that long history into compact durable experience, reducing roughly 13,000 tokens to about 378 tokens while preserving the full audit trail.
Later, a similar-looking incident occurs, but the real cause is database connection exhaustion. The agent retrieves the old authentication memory and incorrectly repeats the prior remediation, so AgentFire fails the run despite eventual recovery. After applying a general memory-safety rule — memory is evidence, not current truth — the same fire drill is rerun. The agent rejects the stale remediation, fixes the database issue, verifies recovery, and passes with zero unnecessary or unsafe actions.
Nimble provides real-world incident intelligence, OpenAI powers the agent under test, RawTree provides telemetry and replay, and Liquid AI compiles durable experience.
