作者讨论了代理内存及其相关成本的问题，特别是每次新会话中重读上下文的费用。他们强调，虽然遗忘令人烦恼，但重复的成本——反复处理相同的信息——更为麻烦，并且随着代理效用的增加而增加。作者认为，大多数多模态上下文提供商 (MCP) 专注于事务性动词，而不是持久性上下文存储，这导致需要每次交互都重新建立上下文的代理产生高昂的 token 成本。这与向量存储修剪上下文的潜力形成对比，尽管作者指出检索通常会带回不相关的块，仍然会产生成本。 AI
影响 强调了当前 AI 代理架构中潜在的低效率和成本，指出了上下文管理和内存方面的改进领域。
排序理由 该条目是关于 AI 代理用户体验和成本的个人反思，而不是正式的公告或研究论文。
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