This post describes a different default: Reduced RAG – using LLMs less, not more, by extracting deterministic signals upfront and treating models as synthesis engines, rather than data stores. It addresses the problem of lazy RAG, which is expensive, fragile, and can hand responsibility to the model. The core mistake is treating context windows like storage.