RAG lacks context awareness, making it merely an advanced grep.

I keep seeing teams ship a "RAG system" that's really a vector database with a thin wrapper. They measure recall@10, ship to production, and then wonder why the model hallucinates on documents the retriever clearly found. The retriever is doing its job. The model is doing its job. What's missing is

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