Select Stage — Choosing What Goes Into the Context Window
~12 min read
Selecting (the book also calls this 'Reading') context means pulling previously-written information back INTO the context window when it's actually needed — from a tool, from memory, or from a knowledge base — based on relevance, recency, and importance.
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Key points
- •Selecting (the book also calls it 'Reading') context means pulling saved information INTO the context window when it's actually needed
- •3 sources: a tool (live call), memory (previously written facts), or a knowledge base (docs, vector DB)
- •Selection should be driven by relevance, recency, and importance — not 'include everything available'
- •Too little selected context starves the model; too much wastes tokens and can bury the genuinely relevant information in noise
- •This is the 'programming the RAM' half of the CPU/RAM analogy — deliberate selection, not indiscriminate inclusion