Imagine your team just deployed a sleek RAG-based docs assistant for the SaaS platform you develop. In testing, it worked flawlessly. It knows your functionality and answers questions in three perfectly written paragraphs with no hallucinations. But two days after launch, a senior dev pokes you on Slack: "Hey man, the AI bot can't find anything on PX-9000-v2 configuration errors."You check the logs. The user queried the exact error code. Vector search, optimized for semantic meaning, returned documents about general error handling and configuration best practices, but the specific technical description for PX-9000-v2 was buried at position 50 in the retriever's results (or chunks) because its "semantic" distance was too far from the general concept of "error."