What is Retrieval-Augmented Generation (RAG)?
Retrieval-Augmented Generation (RAG) is an architecture where an AI system first retrieves relevant documents from an external source — a search index, vector database, or live web search — and then generates its answer conditioned on those documents. RAG is what powers cited AI search: Perplexity, ChatGPT with search, and Google AI Overviews all retrieve a candidate set of pages, rank them for relevance and trust, and synthesize an answer from the top passages. Understanding RAG explains why being retrievable and extractable, not just authoritative, determines whether your content gets cited.
Why it matters for Reddit marketing
RAG reframes visibility: it's a two-stage funnel. First your content must be retrieved into the candidate set; then a specific passage must be selected for the answer. Optimizing only for authority without optimizing for retrieval and extraction loses at the first stage.
How RedditGrow helps
RedditGrow improves your odds at the retrieval stage by building presence on the high-trust sources RAG systems draw from, and at the extraction stage by helping you contribute clear, quotable answers that models can lift verbatim.