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如果您近期在从事大型Agent系统的开发，或调试龙虾🦞，您应该已经感受到一个很具体的问题：当下的Agent（如OpenClaw）缺乏持久化的状态机与能力沉淀机制。在单次会话中，Agent或许能依靠长上下文、复杂的Prompt链和外部工具调用勉强跑通一个工作流；但在下一次面临相似任务时，它依然需要从零开始执行搜索、试错与规划。经验作为一种瞬态数据，随着上下文窗口的清空而消散，未能转化为系统级的可用 ...