RAG Is Not a Database Query

Mon, 21 Oct 2024 00:00:00 +0000

Retrieval-Augmented Generation has become the default answer to “how do we make an LLM answer questions about our data.” The concept is simple enough to explain in one slide: embed your documents, store them in a vector database, retrieve the relevant ones at query time, pass them to the LLM.

The problem is that the one-slide version produces one-slide-quality results. Good RAG systems are significantly harder to build than the demos suggest, and the failures are often subtle — the system produces confident, plausible-sounding answers that are wrong in ways that are hard to detect without systematic evaluation.

Vector-Search on dplabs — Software Engineering & Technology Consultancy

RAG Is Not a Database Query