Observability
Cost and latency
Measure the economics and performance of every agent run.
Lesson overview
Cost and latency
Track model tokens, tool latency, total duration, retries, and cost per successful task. Tail latency matters because a small number of slow runs can dominate user experience.
Learning path
Theory → Example → Code → Practice → Quiz → Challenge → Completion
Step 1
Theory
Cost and latency
Track model tokens, tool latency, total duration, retries, and cost per successful task. Tail latency matters because a small number of slow runs can dominate user experience.
Step 2
Example
Example
Apply Cost and latency 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 Cost and latency.
Step 5
Quiz
Quiz coming soon.
Step 6
Challenge
Challenge
Design a production-ready solution for Cost and latency 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.