RAG is the reason GEO works. A model that retrieves real-time sources will cite whichever pages best answer the user’s prompt, regardless of when those pages were published. This means a GEO program can affect citation share within weeks, not months, significantly faster than waiting for the next training cycle.
GEO glossary
Retrieval-augmented generation
Retrieval-augmented generation (RAG) is a technique where AI models fetch external grounding information at query time, usually via web search or vector retrieval, rather than relying solely on training-data memory.