---
title: "Discussion on \"Everything you should know about RAG\" | Hashnode"
description: "Discussion on \"Everything you should know about RAG\". Imagine you're building an AI application and you need the LLM (Large Language Model) to answer questions using information it doesn't already know. Your first thought might be to put all of that info"
url: "https://hashnode.com/posts/everything-you-should-know-about-rag/6a50bb80e60d97b610526def"
---

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# [Everything you should know about RAG](https://axnsh.hashnode.dev/everything-you-should-know-about-rag?utm_source=hashnode&utm_medium=feed)

Imagine you're building an AI application and you need the LLM (Large Language Model) to answer questions using information it doesn't already know. Your first thought might be to put all of that info

Jul 10 · 10 min read · axnsh.hashnode.dev  
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-   [#ai](https://hashnode.com/tag/ai)
-   [#rag](https://hashnode.com/tag/rag)
-   [#llm](https://hashnode.com/tag/llm)
-   [#engineering](https://hashnode.com/tag/engineering)
-   [#agentic-ai](https://hashnode.com/tag/agentic-ai)
-   [#chaicode](https://hashnode.com/tag/chaicode)

## Written by

[Aansh Malhotra](https://hashnode.com/@axnsh)

@axnsh · Amritsar, India

  
[View profile](https://hashnode.com/@axnsh)

GenAI Engineer | Full Stack Developer | Building Scalable AI-Powered Web Apps |

## Responses 2

Markdown supported · ⌘↵ to post

[MLAI Digital](https://hashnode.com/@mlaidigital)

[Jul 16](https://hashnode.com/posts/everything-you-should-know-about-rag/6a50bb80e60d97b610526def/comment/6a587a6d468c64c87a8c9703)

Great overview of RAG and its role in building more reliable AI applications. One thing we've noticed is that success with RAG depends just as much on the quality of retrieval, chunking strategy, and keeping the knowledge base up to date as it does on the choice of LLM.

As more organizations move toward enterprise AI, understanding how RAG performs in real-world applications is becoming just as important as understanding its strengths. We've also been exploring topics around LLM evaluation and the factors that influence the reliability of AI applications.

Looking forward to seeing more perspectives on this.

[Aansh Malhotra](https://hashnode.com/@axnsh)

[Jul 20](https://hashnode.com/posts/everything-you-should-know-about-rag/6a50bb80e60d97b610526def/comment/6a587a6d468c64c87a8c9703#reply-6a5e722609d04f9869e679d5)

Thanks so much for reading! I really appreciate your support. More blogs are on the way!