RAG (Retrieval-Augmented Generation)

RAG is the technique behind most AI answer engines: the system retrieves relevant documents first, then generates an answer grounded in them.

This retrieval step is why your content can be cited at all — the model is pulling in outside sources rather than relying only on training.

Why it matters: GEO is essentially optimising to be one of the documents the retrieval step selects.