What is RAG?

Source: Dev.to

Introduction

Most AI models don’t actually “know” your data. They generate answers based on what they were trained on — which means they can be outdated, incorrect, or missing context.

Retrieval‑Augmented Generation (RAG)

That’s where RAG (Retrieval‑Augmented Generation) comes in.

How RAG works

RAG works in three steps:

1. Search – Find relevant information (documents, PDFs, databases).
2. Retrieve – Pull the most useful pieces.
3. Generate – Answer using that information.

Simple idea

• Normal AI → guesses.
• RAG → looks up info first, then answers.

Example

Ask: “What’s our company’s leave policy?”

• Without RAG – generic answer ❌
• With RAG – pulls actual company document ✅

Why it matters

• More accurate answers
• Uses real‑time / private data
• Reduces hallucinations
• Powers AI agents & copilots

Conclusion

If you’re building AI today, chances are you’re using RAG — even if you don’t realize it.