In this article, you will learn how context engineering and memory engineering solve different problems in agentic AI systems, and how the two disciplines meet at the point where retrieved memory enters the context window.
Topics we will cover include:
What context engineering involves, including selective inclusion, structural placement, and compression, and why it matters for reasoning quality within a single inference call.
What memory engineering involves, including write policy design, storage layer selection, retrieval strategy, and maintenance, and how these shape long-term reliability.
How memory and context engineering meet at the retrieval boundary, and the two most common failure modes that occur when this boundary is not managed well.
