Context Engineering: Treating the Model's Input as a Budget to Design

As context windows expanded to hundreds of thousands of tokens, developers shifted from crafting one perfect prompt to deliberately managing everything a model receives. This covers system instructions, retrieved documents, tool outputs, conversation history, and persistent memory. The article warns that stuffing a large window with irrelevant material dilutes attention and can reduce accuracy even when the needed information is present. It recommends selecting relevant retrieved chunks instead of full documents, pruning accumulated tool output and history in long agent loops, and keeping memory curated. The guidance is aimed at builders of retrieval-augmented generation systems and agents beyond the demo stage.