The Laptop Return That Broke A RAG Pipeline
The New Stack, Friday, April 3rd, 2026
Stop RAG hallucinations. Learn how hybrid search uses vector similarity and SQL to ensure retrieval accuracy in AI applications.
A few months ago, one of our users filed a bug report that stuck with me. They had built a customer-support agent on top of a RAG (retrieval-augmented generation) pipeline. They encountered the following scenario: A user asked whether they could return a laptop purchased three weeks earlier. The agent retrieved a return policy document, quoted a 30-day window, and told the customer to ship it back. Perfectly confident answer. Completely wrong.
The document was real - it just happened to be from 2023, and the current policy has since changed to a 14-day window for electronics. Vector similarity has no notion of recency or scope, as the cosine distance between the query embedding and the 2023 policy was excellent. Why wouldn't it be? The words were almost identical.