Your RAG Pipeline Retrieves the Right Docs. Your LLM Still Gives the Wrong Answer. Here’s Why.

The retrieval step is solved. The assembly step is where production RAG actually fails. Illustration generated using AI There’s a moment every team hits after their RAG pipeline goes live. The vector search is tuned. Embedding quality is solid. Top-k retrieval looks reasonable in testing. Then a real user asks a real question, and the LLM confidently returns something wrong, not hallucinated from nothing, but wrong in an almost worse way: the right documents were retrieved, and the answer is still bad. This is not a retrieval problem. It’s a context assembly problem.