Observability
Tracing agent runs
Connect model calls, tools, policies, and outcomes into one trace.
Lesson overview
Tracing
Assign a run ID to every task. Each model call, tool call, result, approval, and error should reference that ID.
This makes multi-step failures diagnosable instead of opaque.
Learning path
Theory → Example → Code → Practice → Quiz → Challenge → Completion
Step 1
Theory
Tracing
Assign a run ID to every task. Each model call, tool call, result, approval, and error should reference that ID.
This makes multi-step failures diagnosable instead of opaque.
Step 2
Example
Example
Apply Tracing agent runs to a realistic production scenario and trace the decision step by step.
Step 3
Code
Code
Add implementation notes or a runnable example for this concept.
Step 4
Practice
Practice
Write down the inputs, expected output, constraints, and one failure case for Tracing agent runs.
Step 5
Quiz
Quiz coming soon.
Step 6
Challenge
Challenge
Design a production-ready solution for Tracing agent runs and explain one important trade-off.
Complete every stage
Work through every step in order, then the lesson will be marked complete.
Each chapter and subtopic has its own public URL under /ai-agent.