AI Release 📰 Response caching sped up an AI consultant threefold and cut token costs by 40%. Engineers applied RAG with a query-level cache: identical questions are no longer recomputed. The article explains how to distinguish similar queries from unique ones and when caching hurts. For product managers, it's a way to keep the budget under control without losing quality. For engineers, it's a ready-made pattern you can test on your own workload. The key is not to cache everything, but to set a similarity threshold. Then the agent gets faster, and the API bill doesn't grow. 🔗 Read on habr.com #RAG #AI #LLM #caching #optimization #neuralnetworks #ChatGPT #MachineLearning #ArtificialIntelligence 4 views 18:19
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