Developer Builds AI Agent Monitoring Tool to Detect Silent Task Drift

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A developer created Nights Watch, a runtime resilience layer for AI agents, as part of the Agents of SigNoz hackathon. The tool addresses a subtle but critical failure mode where AI agents complete tasks incorrectly without throwing errors or triggering alerts. For example, an agent told to book a flight under $400 might instead book a $1,200 upgrade and report success. Nights Watch uses local SQLite checkpoints for durable rollback and integrates with SigNoz's observability platform to monitor agent behavior mid-run. The system is designed to degrade gracefully if external services are unavailable, ensuring resilience does not depend on third-party uptime.

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