AI Agent
One Line of Code That Can 10× Your Agent Costs: KV-Cache-Friendly Agent Design
Agents running slow and expensive? The problem often lies in a broken KV Cache. This article starts with the fundamentals of KV Cache and lays out three golden rules: keep system prompts and tool definitions byte-level fixed, always append dynamic information to the end, and use standard API formats instead of hand-crafting your own. Using Qwen3, DeepSeek, and Claude as examples, it analyzes how different models differ in chain-of-thought feedback and what cache killers to watch out for, helping you build cache observability so that both first-token latency and your bill go down.