Context Engineering for LLM Applications

Production reference for building reliable, efficient LLM-powered systems. Context engineering is the discipline of curating what enters the model's attention window — not prompt writing, but holistic management of system prompts, tool definitions, retrieved documents, message history, and tool outputs.

The Attention Budget

Context is a finite resource with diminishing returns. Every token added depletes an attention budget shared across all content. The engineering goal is the smallest high-signal token set that achieves the desired outcome.

Critical attention pattern — lost-in-the-middle: Information buried in the center of context receives 10-40% lower recall accuracy than content at the beginning or end. Always place critical instructions and key facts at the start or end of context.