What Is RAG, Actually?

Name: What Is RAG, Actually?
Uploaded: 2026-07-24T17:45:31.000Z
Duration: 26 s
Channel: LangChain
Description: LangChain staff explain Retrieval Augmented Generation (RAG) as a technique that allows AI models to retrieve relevant information from external sources to provide more accurate answers. RAG enables models to access company documents and internal knowledge bases not present in their training data.

LangChain24 July 2026Watch on YouTube

Part of series

Ep. 9 · Augmented Generation Hindi

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What you'll learn

You learn what Retrieval Augmented Generation (RAG) is through a simple analogy
You see how RAG treats an AI model as an open book test instead of requiring it to memorize everything
You discover why models have no built in context on your company docs, customer history, or internal knowledge base
You learn how RAG retrieves relevant information and drops it into context right before the model answers

Frequently asked questions

What is Retrieval Augmented Generation (RAG)?

RAG is a technique that lets AI models retrieve relevant information from external sources to provide more accurate answers.

Why does an AI model have no context on company documents?

Because the model is trained on public data and therefore has no built in context on company docs, customer history, or internal knowledge bases.

How does RAG work in practice?

RAG retrieves relevant information and drops it into context right before the model answers, allowing the model to respond based on that information.

Topics

rag retrieval augmented generation langchain ai fundamentals prompt engineering

Description from the channel

Amy and Sean from LangChain explain retrieval augmented generation with a simple analogy: RAG gives a model an open book test instead of asking it to memorize everything. Since a model is trained on public data, it has no built in context on your company docs, customer history, or internal knowledge base, so RAG retrieves what is relevant and drops it into context right before the model answers. This is a clip from our full conversation where Amy and Sean answer the most commonly searched questions about AI agents, from the basics like what is an agent, what is RAG, and what is MCP, to harder questions like why agents hallucinate, how to evaluate them, and what LangChain actually does. #AIexplained #langchain