Forrester defines context engineering as designing and delivering structured context to AI systems. It covers information, semantics, tools, memory and policies that shape agent behavior. Four elements make it up: retrieval-augmented generation, function calls, memory management and context models. ContextOps is the operational discipline for managing context assets and flows across their lifecycle. It extends DataOps, MLOps and AIOps principles into the context layer. Forrester argues the next phase of enterprise AI depends on platformizing context engineering. Shared context services and reusable assets are needed rather than siloed implementations. ContextOps provides the foundation to keep context trusted, governed and scalable. The winners in agentic AI will build better context platforms, not just deploy more agents.