My agent was generating the same weekly security report for the same three clients every Monday. Same context. Same reasoning structure. Same output format. I was paying full Anthropic API price every single time. I checked the logs. Across 45 runs of three recurring workflow types — security audits, invoice processing, weekly reports — the structure of the generated plan was materially identical run after run. The LLM was re-deriving the same skeleton every time. 93% of the tokens I was spending were redundant. This isn't a prompt engineering problem. It's a structural one. The Problem With Stateless Frameworks Every major agent framework — LangChain, LangGraph, CrewAI, AutoGen — is stateless by default. There is no memory of previous executions at the plan level. Each invocation starts from zero. This is fine for one-off queries.…