What to Trace When the Agent Is the Program

When an agent run goes wrong, there is usually no stack trace and no way to reproduce it by running it again. The failure lives in the shape of the run: which tool it reached for, how many times it retried, where it looped, what it decided after the third attempt. That makes tracing less of an ops nicety and more of the primary debugging surface for agentic systems. The hard part is knowing what to actually emit. Span every LLM call and you get noise. Span only the entry point and you learn nothing. Parseable joins us to work through both the why and the how, using Temporal Workflows as the instrumentation point, since the Workflow is already the agent loop and already knows every step that ran. We cover the Temporal plugin that ships Workflow and Activity events as OpenTelemetry traces and queryable logs, custom agent events emitted from inside the Workflow and guarded so replay does not duplicate them, and the export path that moves Temporal Cloud Workflow History into object storage for analytics and audit. Parseable is Parquet and object-storage native, so Workflow History lands there in the format it is going to be queried in anyway. We get into what a live trace is good for, when it is the wrong tool, and what teams should be keeping from the runs they are already generating.