<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Rag on Girish Shekhar</title><link>https://blog.girishshekhar.com/tags/rag/</link><description>Recent content in Rag on Girish Shekhar</description><generator>Hugo -- 0.163.3</generator><language>en-us</language><lastBuildDate>Wed, 19 Apr 2023 00:00:00 +0000</lastBuildDate><atom:link href="https://blog.girishshekhar.com/tags/rag/index.xml" rel="self" type="application/rss+xml"/><item><title>Retrieval-Augmented Generation (RAG): Grounding LLMs in Reality</title><link>https://blog.girishshekhar.com/posts/llms-and-how-our-work-is-changing/5-retrieval-augmented-generation/</link><pubDate>Wed, 19 Apr 2023 00:00:00 +0000</pubDate><guid>https://blog.girishshekhar.com/posts/llms-and-how-our-work-is-changing/5-retrieval-augmented-generation/</guid><description>Retrieval-Augmented Generation (RAG) is one of the most important architectural patterns to emerge alongside Large Language Models. This post explains why RAG exists, how it works, and what problems it actually solves — without turning it into a tooling tutorial.</description></item></channel></rss>