RAG is simpler than you think (but most people get it wrong)
If you understand these 4 types, everything clicks πŸ‘‡
🧠 Naive RAG
Retrieve β†’ send to LLM β†’ answer
Good starting point, but accuracy is limited.
πŸ”€ Hybrid RAG
Keyword + semantic search
This is what most real-world systems use.
πŸ”— Graph RAG
Understands relationships between data.
Useful for complex queries.
πŸ€– Agentic RAG
Plans β†’ retrieves β†’ reasons β†’ iterates
This is where things are heading.
⚑ Key insight:
Better AI β‰  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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Divyanshu Gupta
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RAG is simpler than you think (but most people get it wrong)
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