Glossary · Term

RAG

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Definition

Plain language

Letting a model look things up in an external source and use what it finds to answer.

As stated in the literature

Retrieval-Augmented Generation, an inference pattern where a model retrieves relevant documents from an external store and conditions generation on them.

Also called: RAG poisoning

Why it matters: It lets a model stay accurate on fresh or proprietary information without retraining, and it makes answers auditable since you can see which documents were retrieved.

For example, a customer-support bot looks up the user's order in a database and the relevant help article before composing its reply.

Heard on the show

“And there's a whole research line — context-faithfulness — that treats exactly that behavior as the goal, because RAG exists to override stale or wrong parametric knowledge.”
Episode 247 — One Edited Photo, an Honest Caption, and a RAG System That Believes It

Mentioned in 6 episodes

  1. 247
    One Edited Photo, an Honest Caption, and a RAG System That Believes It
  2. 214
    The Medical AI Answer That's Accurate, Sourced, and Still Wrong
  3. 082
    Training a Deep Research Agent on 8,000 Synthetic Tasks: The Rubric Tree Trick
  4. 039
    When Smarter Agents Get Fooled by Three Extra Nodes in a Database
  5. 031
    When Your AI Assistant Won't Let Go of Old Facts About You
  6. 027
    When AI Agents Build the Serving Stack: A Bet on Bespoke Infrastructure

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