Originally published on AI Tech Connect.
The 40% bug nobody puts on the demo slide Most RAG demos look excellent. You type a question, the system reaches into a vector database, finds a relevant passage and the LLM writes a confident, well-cited answer. Demo over, deal closed, retrospective written. The trouble starts about three weeks later when a real user types a real question and gets a confident, well-cited answer that is built on the wrong document — and nobody on the team realises until a customer complaint lands. The honest number, repeated quietly inside production teams and now written up in the May 2026 production guide from lushbinary, is this: naive RAG pipelines fail at retrieval roughly 40% of the time. The LLM still answers. It is just answering from the wrong evidence. If you are a builder in Bengaluru shipping…
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