In this article, you will learn what AgentOps is, how it differs from traditional LLM monitoring, and how to build a production-ready observability stack for autonomous AI agents.

Topics we will cover include:

The five core pillars of AgentOps and why standard logging is insufficient for autonomous agents.

How to instrument a working research agent with full session tracking, cost attribution, and failure detection using the AgentOps platform.

How to debug common agent failure patterns using session replay, and how to govern costs and enforce safety at the operational layer.