Glossary
Retrieval-Augmented Generation (RAG)
Retrieval-augmented generation is an architecture that fetches relevant documents at query time and passes them to a language model, which then answers from that material. It was introduced in a 2020 research paper and is the mechanism behind AI answers that carry live citations to specific web pages.
In plain terms
The engine searches first and writes second. Your page has to survive the search step before the writing step can quote it.
Why it matters for B2B
RAG is why publishing still matters in an AI world. If your content is not retrievable at query time, no amount of brand strength puts it into the answer.
How to apply it
- Make pages individually retrievable: one topic, one URL, a descriptive title.
- Write self-contained sections that make sense when read out of context.
- Remove barriers to retrieval — gating, script-only rendering, blocked crawlers.
Sources
Related terms
Back to the full glossary (25 terms).
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