It's RAG time: Retrieval-Augmented Generation

It's RAG time: Retrieval-Augmented Generation

From Linear Digressions by Katie Malone

March 2, 2026 · 17 min

About this episode

This episode discusses Retrieval-Augmented Generation (RAG) and its applications in generative AI.

Today we are going to talk about the feature with the worst acronym in generative AI: RAG, or Retrieval Augmented Generation. If you've ever used something like "Chat with My Docs," if you have an internal AI chatbot that has access to your company's documents, or you've created one yourself on some kind of personal project and uploaded a bunch of documents for the AI to use — you have encountered RAG, whether you know it or not. It's an extremely effective technique. Works super well for taking general purpose models like ChatGPT or Claude and turning them into AIs that are aware of all the specific information that makes them truly useful in a huge variety of situations. RAG is pretty interesting under the hood, so I thought it would be fun to spend a little while talking about it. You are listening to Linear Digressions. RAG was first introduced in this paper from Facebook Research in 2021: https://arxiv.org/pdf/2005.11401

People in this episode

Host: Katie Malone

Topics covered

  • Retrieval-Augmented Generation
  • generative AI
  • AI chatbots
  • information retrieval
  • machine learning

Keywords

  • RAG
  • Retrieval-Augmented Generation
  • generative AI
  • ChatGPT
  • AI chatbots
  • information retrieval

Mentioned in this episode

Organizations: Facebook Research

Products: ChatGPT, Claude

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