@lidangzzz: I told you last year that using RAG and vector databases is a dead end. The correct approach is: 1. Use memory correctly; 2. Properly chunk content, index it well, and summarize it; 3. Give the agent proper search tools...
Summary
The author criticizes the RAG and vector database approach, proposing that the correct methods include using memory correctly, chunking and indexing, summarizing, providing search tools for agents, and using SRAM-only inference services such as Groq and Cerebras.
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Cached at: 07/04/26, 02:47 PM
I told you last year that using RAG and vector databases is a dead end. The right approach is:
- Use memory correctly;
- Properly chunk content, index it well, and do good summarization;
- Give agents search tools, and let the agent or even multi-agent perform fuzzy search on its own;
- Use faster, SRAM-only inference model providers I’ve recommended dozens of times, like Groq, Cerebras, and others.
Any of these is orders of magnitude better than blindly chunking, blindly feeding into a vector database, and blindly doing RAG.
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