Observability is what turns a production agent from a black box into a system you can operate. Once an agent is live, you need to see every step it takes, what each call cost, how long it took, and where it went wrong — before a user or a finance report tells you.
These posts cover the instrumentation that makes agents debuggable at scale: tracing multi-step runs end to end, structured logging that captures decisions rather than just outputs, and monitoring that keeps cost and latency curves honest as traffic grows.
Topics include distributed tracing for agent runs, token-cost and latency monitoring, detecting quality drift and silent failures, alerting on anomalies, and the dashboards that let a team catch a regression in hours instead of weeks. The recurring point is that agents fail differently from ordinary software — quietly, probabilistically, and expensively — so the observability you ship matters as much as the agent itself.