A powerful Large Language Model is not enough. The smartest models still hallucinate, lack real-world knowledge, and can't remember your last conversation. The solution isn't a better prompt. It's a better system.
This e-book is your guide to mastering Context Engineering: the act of selecting, organizing, and managing the information fed into a large language model during inference (i.e. the “context” tokens) to optimize its performance and behavior. You'll learn the architectural patterns required to move beyond simple demos and build reliable, production-ready AI applications that think with real-world context, not just their training data.
The Context Engineering Guide covers:
