Mar 17 • 🎓 Tutorials & How-To’s
RAG is simpler than you think (but most people get it wrong)
If you understand these 4 types, everything clicks 👇
🧠 Naive RAG
Retrieve → send to LLM → answer
Good starting point, but accuracy is limited.
🔀 Hybrid RAG
Keyword + semantic search
This is what most real-world systems use.
🔗 Graph RAG
Understands relationships between data.
Useful for complex queries.
🤖 Agentic RAG
Plans → retrieves → reasons → iterates
This is where things are heading.
⚡ Key insight:
Better AI ≠ bigger model
Better AI = better retrieval
If you're building anything with LLMs,focus more on retrieval than prompts.
That’s the real leverage.
What are you currently using?
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RAG is simpler than you think (but most people get it wrong)
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