When an agent goes wrong, the hardest part isn't fixing it — it's reproducing it: you usually know the result was wrong, but not at which step, which tool call, or which branch it diverged. That's exactly what observability solves. OpenTelemetry's answer is three pillars: traces (the full path a request/task takes), metrics (aggregatable measurements of throughput, latency, token usage), and logs (discrete event records), all correlated by a shared context. As a CNCF project, its spec is defined cross-language and versioned semantically, meaning whether your agent is Python, Go, or TypeScript, it can report and query with the same semantics. Codex listing Tracing and Observability and usage as standalone modules shows 'observable' has moved from a nice-to-have to a first-class citizen of agent platforms.
For Zero to Pro Agent Harness learners, observability is the first gate to 'production-ready': the course treats 'every tool call and sub-task has a correlatable trace' as a hard pre-deployment requirement — without traces, you can't trace back a failure, and the agent becomes an unaccountable black box. OpenTelemetry's cross-language standard gives you a foundation you don't have to reinvent. For Zero to Codex learners, at minimum learn two things early: read a task's token consumption and step trajectory, and locate the exact step in a trace when something fails. Observability isn't 'an ops concern' — it's the baseline for every agent developer.