Context Engineering

The context window is finite. What goes into it — and in what order — determines the quality of every output. Context engineering is the practice of deliberately designing the information architecture of the context window.

The Context Budget

Every context window has a token budget. Allocate it deliberately:

• System prompt: The foundational instructions (typically 5-20% of the budget)
• Retrieved context: Documents, data, and information pulled in for the current task
• Conversation history: Previous turns in the conversation
• User input: The current request
• Working space: Room for the model to generate its response These compete for space. More retrieved context means less conversation history. A longer system prompt means less room for everything else.

Information Architecture in Context

Order matters. The model pays different amounts of attention to different positions:

• Beginning: High attention. Put your most important instructions here.
• Middle: Lower attention. This is where information can get lost in long contexts.
• End: High attention. The most recent information (user input) naturally goes here.
• Adjacent to the task: Information placed right before the user's question gets more attention than information earlier in the context.

Context Selection

Not everything should go into the context. Design selection criteria:

• Relevance: Does this information help answer the current question?
• Recency: Is this the most up-to-date information available?