AI systems
Observability for agent workflows starts with a trace
A useful trace links the request, model calls, tools, and final outcome without exposing secrets.
Aryan (@istmX)3 min read
Start with a clear boundary
Use request identifiers across orchestration and tool events, recording timing and outcomes at each boundary.
Handle failure deliberately
Prompts and tool inputs may contain private data. Redact sensitive fields and restrict access to detailed traces.
Make the result understandable
A trace should help explain what the agent tried and where the task diverged, without claiming to expose model reasoning perfectly.