The observability of AI agents (whether in software or hardware) is underestimated; annual growth of 50% is projected, driven by the need for regulatory compliance and audits of the new models being released.
One trace, one story: The model that wasn’t guilty.
Our agents were failing heavy tasks. Everything pointed to the model: long silences, dead turns, zero output.
The trace told a different story. During the silence, the model wasn’t doing anything. Execution was stuck inside a tool step, waiting for a manual approval that no headless runtime could ever provide.
A deadlock disguised as a dumb model.
Without the trace, you switch models and pray. With it, one config change fixed the entire fleet.
That’s what observability is for.