Context Engineering Is a Real-Time Packing Problem, Not Just Prompt Writing

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The term 'context engineering' has emerged to describe how developers manage what information goes into a language model's input on each call during an agent run. Unlike prompt engineering, which involves a one-time system prompt decision, context engineering requires actively choosing what to include or discard every turn under a strict token budget. A model's context window functions more like a cache than memory — content must continuously earn its place, and evicting the wrong information carries real costs. Research has also shown that stuffing the window with excess content can hurt retrieval accuracy, particularly when key facts end up buried in the middle of a long input. The core discipline is therefore a packing problem: deciding what fits, what gets dropped, and understanding the consequences of dropping the wrong thing mid-run.

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