retrieval-augmented generation
Retrieval-augmented generation supplies retrieved material to a model before it answers.
Use this when An assistant must answer using private or changing application information.
without the term
“I want the chatbot to answer questions using our own docs and customer data instead of making stuff up. How do I feed it the right information?”
with the term · How do you ask a model for retrieval-augmented generation?
Build this grounded-answer flow. Test retrieval permissions, unsupported questions, and whether each answer claim is supported by its cited material.
What is retrieval-augmented generation?
The application searches its own data, passes the matching passages to the model, and asks for an answer based on them. Retrieval and the grounding of the answer are checked separately.
Why does retrieval-augmented generation matter when vibe coding?
A plausible answer can cite a passage that does not support its claim.
How do you do retrieval-augmented generation?
Enforce retrieval access rules and evaluate both retrieved evidence and the resulting answer.
What goes wrong with retrieval-augmented generation?
Using prompt instructions as the only tenant filter.