Course ยท Pro

Production AgentOps

By Wanderson Leandro de Oliveira

Building an agent that works once in a notebook is the easy part. Production AgentOps is about everything that separates a demo from a system you can trust with real users and real money: how do you know it's actually good, how do you test something that gives a different answer every time you ask, how do you see inside it when it fails at 3am, how do you keep it from being turned against you, and how do you run it reliably while keeping cost and blast radius under control. This is the fourth and final course in the AI Agents Engineering track, and it assumes you already know how to build an agent โ€” this course is about operating one. You will build evaluation pipelines with golden datasets and LLM-as-judge, write tests for non-deterministic systems with fake providers and chaos injection, instrument agents with structured logging and tracing, close a real authorization vulnerability in a production-shaped codebase, design deployment architecture with CI/CD and canary releases, and apply reliability patterns and cost controls used by teams running agents at scale. The course closes with a capstone that ties together everything from all four courses in the track into a single production-readiness design.

Course content

Evaluating Agents

Testing Agent Systems

Observability and Debugging

Securing Production Agents

Deploying and Operating Agents

Reliability, Cost, and Governance