Context Engineering

Context engineering expands the scope of prompt engineering to include everything that goes into the model’s context window: not just instructions, but retrieved documents, conversation history, tool results, user profile data, and structured data from external systems. As models have grown more capable of reasoning over long contexts, what you include — and how you organize it — has become one of the most consequential design decisions in AI product development. For behavior architects, context engineering is about matching the model’s available information to the task it needs to perform: too little context and the model guesses; too much and important signal gets buried. Thinking carefully about context design is often more impactful than fine-tuning prompt wording.