AgentOps is the operational layer for AI agents running in production. Unlike single LLM calls, agents make multiple chained decisions, invoke tools, and accumulate costs across steps — creating challenges that standard per-request monitoring can't address. Key capabilities include full run tracing, token/cost tracking, runtime guardrail enforcement, and model access governance. The post explains why reasoning errors compound, tool failures go silent, and policy violations only emerge from sequences of actions. It then presents Portkey's AI Gateway as a shared control plane that handles agent registration, model catalog governance, workspace-level spend caps, and framework-agnostic tracing across LangChain, LlamaIndex, OpenAI Agents SDK, and custom stacks.
