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The reranking insight is underrated. Most RAG implementations just grab top-k chunks and hope for the best, but that 15-20% accuracy gain from cross-encoder reranking is exactly where chatbot quality jumps from "kinda helpful" to actually useful. Been working with vector stores for a bit and the latency tradeoff you mentioned (200-500ms) is totally worth it when the alternative is hallucinating nonsense that tanks user trust. Also the point about logging vs real-time extraction is spot on, teams always underestimate how mcuh storage costs explode at scale.
The reranking insight is underrated. Most RAG implementations just grab top-k chunks and hope for the best, but that 15-20% accuracy gain from cross-encoder reranking is exactly where chatbot quality jumps from "kinda helpful" to actually useful. Been working with vector stores for a bit and the latency tradeoff you mentioned (200-500ms) is totally worth it when the alternative is hallucinating nonsense that tanks user trust. Also the point about logging vs real-time extraction is spot on, teams always underestimate how mcuh storage costs explode at scale.
Thanks for the input. Exactly, so much untapped potential in optimizing AI agents that most overlook.