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Tag: Retrieval Augmented Generation
Content focused on RAG architectures, retrieval strategies, and real-world implementation challenges.
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Why Most RAG Architectures Break Under Real User Load
The demo worked. The production launch didn’t. The pattern is predictable. The RAG demo looks great in a room with five people. Then you hit 200 to 800 QPS and…
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Hybrid search vs vector search: what actually works in production
The painful pattern The vector-only demo looks great in a sandbox. Then you ship and support tickets pile up. Acronyms don’t resolve, filters don’t filter, legal asks for deterministic behavior,…
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Why your RAG pipeline is slow and expensive
Your RAG is slow because it moves too much data, hops across too many services, and pays LLMs to read junk. It is expensive for the same reasons. I see…
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When RAG Makes Your AI Worse: Hard Rules From Production
The trap Half the RAG projects I’m asked to review would be simpler, cheaper, and more reliable without a vector index. Teams add retrieval because every diagram on the internet…
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