RAG stands for retrieval-augmented generation, which is a terrible name for a simple idea: <b>look it up first, then answer.</b> It is the single most effective fix for AI making things up, and it is not a cleverer model — it is a filing cabinet next to the desk.
A model has no facts inside it that you can look up, so asked about something specific it produces something plausible instead.
Ask it about a book that does not exist and it invents the book. Ask it about your school's timetable and it invents a timetable.
Before answering, the system searches a real source — a document, a database, a catalogue, the web — and puts the relevant page into the context window.
Then the model answers from that page, which is now on the desk.
Same model. Same question. Completely different answer, because this time there was something real to read.
You already do RAG by hand every time you paste your notes into the chat before asking a revision question. That is the whole technique.
It is also why an AI that can search the web gives better factual answers than one that cannot — not because it is smarter, but because it fetched.
Thirty seconds apart, same model. The only thing that changed was whether it looked before it spoke.
In our free course you get the invented answer first, then open the cabinet and ask again. The two answers sit side by side.
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