Why Agent Observability Is Hard
Metrics, logs, and traces were built for human operators. Autonomous agents demand a new observability primitive: the reasoning trace.
Classical observability answers three questions: what happened, where did it happen, and how long did it take? These are sufficient when a human interprets the output. They are insufficient when the consumer is another machine that must decide what to do next.
An agent observability system must answer a fourth question: why did the agent believe this was the right action? This requires reasoning traces: structured records of observations, hypotheses, evaluations, and decisions.
Reasoning traces are not just logs. They must be queryable, comparable, and evaluable. We need to ask: given the same situation, would the agent make the same decision? If not, what changed?
Vigilo experiments with this primitive. It watches host-level signals directly and organizes them around episodes and decisions rather than services and spans -- a fast per-event alert path plus a slower correlating pass, not a traces/metrics/logs pipeline. The goal is to make agent-adjacent behavior inspectable, debuggable, and ultimately improvable.