AI agent observability starts at the tool call, not the chat transcript_
OpenTelemetry’s GenAI work highlights the chain hidden behind one answer: model calls, tokens, retries, and tool invocations. Without trace context, teams blame the model for failures created by an API or retry loop.
- OpenTelemetry
- AI Agents
- Observability
OpenTelemetry’s GenAI work highlights the chain hidden behind one answer: model calls, tokens, retries, and tool invocations. Without trace context, teams blame the model for failures created by an API or retry loop.
A transcript shows what the user saw. It does not show which retrieval query ran, how long a tool waited, what was retried, or where cost accumulated.
What changes in practice_
Instrument model and tool spans, attach stable request and workflow IDs, and redact content by policy rather than recording everything by default.
- Trace every model and tool boundary.
- Record latency, tokens, retries, and outcome.
- Separate operational telemetry from sensitive content.
Our take_
The durable advantage is not adopting the newest tool first. It is building the identity, state, evidence, and operating boundaries that let a real team own the system after launch.