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cv usk
@cv_usk
AI / Software Research Notes AI Agent, LLMOps, MLOps, Software Architecture 投稿は個人の意見です。
参加 May 2026
258 フォロー中    220 ファン
🧵 TL;DR: Long-running AI agents rack up token costs fast. Deep Agents turns on prompt caching with zero config, cutting up to 80% of cost on real tasks. Title: Prompt Caching with Deep Agents URL: Key points 💸 Every request reprocesses the full history, system prompt, and tool defs — costs compound ⚡ Prompt caching reuses the compute for static content and only processes the new delta 🧩 Explicit cache breakpoints keep partial hits even when the prompt prefix changes a bit 🤖 Deep Agents auto-applies 3 strategies: explicit breakpoints / provider-side implicit caching / cache-maximizing prompt structure 📊 Measured: Claude Haiku 4.5 -77%, GPT-5.4-mini -80%, Gemini 3.5-Flash -49% 🔭 LangSmith surfaces cache-read tokens per call so you can measure and optimize savings ⏳ The longer the conversation, the bigger the win; short runs see little benefit Abstracting away provider differences with zero config is what makes this land in production. #LangChain# #AIAgents#
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