🤖

Series · Part 11 of 21

Practice
AI Demystified
Abhishek Saha
Abhishek Saha · 🤖 AI / ML

RAG Explained — How AI Knows What You Didn't Train It On

Retrieval-Augmented Generation lets LLMs answer questions about documents they've never seen. Here's how the pipeline works and when to use it.

#ai #rag #llm #vector-databases #embeddings

RAG lets AI answer questions about your data without retraining. Instead of relying on memory, the model looks up relevant documents on the fly and reads them before answering.

RAG— retrieval-augmented generation

Watch how a RAG system turns a question into a grounded answer — step by step.

💬
Query
🌌
Embed
🔍
Search
📄
Retrieve
✨
Generate
💬
USER
"What was our Q3 revenue growth rate?"
The raw question is captured and will be transformed into a vector the database can search.
Key insight: The AI never guesses. It answers exclusively from the retrieved document. No hallucination, no made-up facts.

Next up: RAG adds knowledge to AI. But what if you need to change the AI’s behavior — its tone, format, or style? That’s where fine-tuning comes in.

AI Demystified · 16 of 21 published

  1. 0 Grounding 5 Mental Models You Need Before Diving Into AI
  2. 1 Foundation What Happens When You Ask AI Something?
  3. 2 Foundation Transformers — The Architecture That Changed Everything
  4. 3 Foundation How AI Learns, Thinks, and Decides
  5. 4 Foundation How AI Reads Your Words
  6. 5 Foundation Why AI Forgets
  7. 6 Foundation Why AI Lies (And Doesn't Know It)
  8. 7 Foundation What AI Cannot Do
  9. 8 Foundation How AI Reasons (And Why It Sometimes Breaks)
  10. 9 Practice Prompt Engineering — How to Talk to AI
  11. 10 Practice Embeddings & Vector Databases — The Memory Layer of AI
  12. 11 Practice RAG Explained — How AI Knows What You Didn't Train It On
  13. 12 Practice Fine-tuning vs. Prompting — When to Use Which
  14. 13 Practice Do You Really Need GPT-4?
  15. 14 Practice Latency, Tokens, and Cost — The Physics of AI Products
  16. 15 Practice How Do You Know AI Is Actually Working?
  17. 16 Hands-On Coding Setup — Your AI Development Environment soon
  18. 17 Hands-On MCP Tool Calling — How AI Uses Tools soon
  19. 18 Hands-On AI Agents — Beyond Chatbots soon
  20. 19 Hands-On Build Your First Real AI App soon
  21. 20 Hands-On Token Optimization — Spend Less, Get More soon
← Part 10 Embeddings & Vector Databases — The Memory Layer of AI Part 12 → Fine-tuning vs. Prompting — When to Use Which

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