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0 0 1.061 1.06l1.224-1.224a4 4 0 0 0-5.656-5.656l-3 3a4 4 0 0 0 .225 5.865.75.75 0 0 0 .977-1.138 2.5 2.5 0 0 1-.142-3.667l3-3Z"}],["$","path",null,{"d":"M11.603 7.963a.75.75 0 0 0-.977 1.138 2.5 2.5 0 0 1 .142 3.667l-3 3a2.5 2.5 0 0 1-3.536-3.536l1.225-1.224a.75.75 0 0 0-1.061-1.06l-1.224 1.224a4 4 0 1 0 5.656 5.656l3-3a4 4 0 0 0-.225-5.865Z"}]]}]}]}],"(一)整体开发现状及核心痛点"]}] 25:["$","p",null,{"children":"对应问题:行业新概念、新框架不断涌现,但个人开发的AI Agent存在开发效率低(慢)、功能不完善(笨)、运行不稳定、不按设计逻辑执行的问题,照搬新架构无法解决上述核心痛点。"}] 26:["$","p",null,{"children":"核心解决方向:遵循AI Agent开发核心原则,不盲目跟风,聚焦问题本质迭代优化。"}] 27:["$","h3",null,{"className":"content-header","id":"二初代-plan-and-execute-三层架构主agent编排子agent分工","children":[["$","a",null,{"className":"break-words","href":"#二初代-plan-and-execute-三层架构主agent编排子agent分工","aria-hidden":"true","tabIndex":"-1","children":["$","span",null,{"className":"content-header-link","children":["$","svg",null,{"className":"h-5 linkicon w-5","fill":"currentColor","viewBox":"0 0 20 20","xmlns":"http://www.w3.org/2000/svg","children":[["$","path",null,{"d":"M12.232 4.232a2.5 2.5 0 0 1 3.536 3.536l-1.225 1.224a.75.75 0 0 0 1.061 1.06l1.224-1.224a4 4 0 0 0-5.656-5.656l-3 3a4 4 0 0 0 .225 5.865.75.75 0 0 0 .977-1.138 2.5 2.5 0 0 1-.142-3.667l3-3Z"}],["$","path",null,{"d":"M11.603 7.963a.75.75 0 0 0-.977 1.138 2.5 2.5 0 0 1 .142 3.667l-3 3a2.5 2.5 0 0 1-3.536-3.536l1.225-1.224a.75.75 0 0 0-1.061-1.06l-1.224 1.224a4 4 0 1 0 5.656 5.656l3-3a4 4 0 0 0-.225-5.865Z"}]]}]}]}],"(二)初代 Plan and Execute 三层架构(主Agent编排+子Agent分工)"]}] 28:["$","p",null,{"children":"对应问题:小改动成本高、主Agent越权执行子任务,与工业界成功架构不符,实用性不足。"}] 29:["$","p",null,{"children":"解决方案:Skill替代冗余Sub Agent,将子Agent的提示词转为Skill动态注入,砍掉主副Agent通信成本,实现架构压平、降低Token开销、提升运行性能。"}] 2a:["$","h3",null,{"className":"content-header","id":"三架构压平后skill替代sub-agent","children":[["$","a",null,{"className":"break-words","href":"#三架构压平后skill替代sub-agent","aria-hidden":"true","tabIndex":"-1","children":["$","span",null,{"className":"content-header-link","children":["$","svg",null,{"className":"h-5 linkicon w-5","fill":"currentColor","viewBox":"0 0 20 20","xmlns":"http://www.w3.org/2000/svg","children":[["$","path",null,{"d":"M12.232 4.232a2.5 2.5 0 0 1 3.536 3.536l-1.225 1.224a.75.75 0 0 0 1.061 1.06l1.224-1.224a4 4 0 0 0-5.656-5.656l-3 3a4 4 0 0 0 .225 5.865.75.75 0 0 0 .977-1.138 2.5 2.5 0 0 1-.142-3.667l3-3Z"}],["$","path",null,{"d":"M11.603 7.963a.75.75 0 0 0-.977 1.138 2.5 2.5 0 0 1 .142 3.667l-3 3a2.5 2.5 0 0 1-3.536-3.536l1.225-1.224a.75.75 0 0 0-1.061-1.06l-1.224 1.224a4 4 0 1 0 5.656 5.656l3-3a4 4 0 0 0-.225-5.865Z"}]]}]}]}],"(三)架构压平后(Skill替代Sub Agent)"]}] 2b:["$","p",null,{"children":"对应问题:长任务运行中出现三大核心问题——步骤合并跳过、规则失效、输出同质化,根源是大模型上下文注意力分布不均。"}] 2c:["$","p",null,{"children":"解决方案:分两步优化,针对性解决不同问题:"}] 2d:["$","ol",null,{"children":[["$","li",null,{"children":["$","p",null,{"children":"Restatement机制解决注意力问题:通过To-do List不断重申任务,将关键信息放在模型注意力强的位置;区分信息放置逻辑,静态规则放入System Prompt、动态信息放入上下文尾端,确保关键信息不被忽略。"}]}],["$","li",null,{"children":["$","p",null,{"children":"Sub Agent回归解决输出同质化:重新引入Sub Agent,为任务提供干净的上下文窗口,屏蔽无关历史信息,破解创意生成同质化的问题。"}]}]]}] 2e:["$","h2",null,{"className":"content-header","id":"三总结","children":[["$","a",null,{"className":"break-words","href":"#三总结","aria-hidden":"true","tabIndex":"-1","children":["$","span",null,{"className":"content-header-link","children":["$","svg",null,{"className":"h-5 linkicon w-5","fill":"currentColor","viewBox":"0 0 20 20","xmlns":"http://www.w3.org/2000/svg","children":[["$","path",null,{"d":"M12.232 4.232a2.5 2.5 0 0 1 3.536 3.536l-1.225 1.224a.75.75 0 0 0 1.061 1.06l1.224-1.224a4 4 0 0 0-5.656-5.656l-3 3a4 4 0 0 0 .225 5.865.75.75 0 0 0 .977-1.138 2.5 2.5 0 0 1-.142-3.667l3-3Z"}],["$","path",null,{"d":"M11.603 7.963a.75.75 0 0 0-.977 1.138 2.5 2.5 0 0 1 .142 3.667l-3 3a2.5 2.5 0 0 1-3.536-3.536l1.225-1.224a.75.75 0 0 0-1.061-1.06l-1.224 1.224a4 4 0 1 0 5.656 5.656l3-3a4 4 0 0 0-.225-5.865Z"}]]}]}]}],"三、总结"]}] 2f:["$","p",null,{"children":"AI Agent开发的核心的是\"聚焦问题、迭代优化\",架构演进的本质是针对性解决各阶段的核心痛点(效率、稳定性、同质化等),而非盲目追求热门框架;通过Skill注入、Restatement机制、Sub Agent合理运用,可有效解决开发及运行中的核心问题。"}] 30:["$","div",null,{"className":"pt-6 pb-6 text-sm text-gray-700 dark:text-gray-300","children":[["$","a",null,{"className":"break-words","target":"_blank","rel":"nofollow","href":"https://mobile.twitter.com/search?q=https%3A%2F%2Ftechlog-18328.app.workbuddy.host%2Fblog%2Fagent-architecture-evolution-skill-restatement","children":"Discuss on Twitter"}]," • ",["$","a",null,{"className":"break-words","target":"_blank","rel":"noopener noreferrer","href":"https://github.com/joker1point/techlog/blob/main/data/blog/agent-architecture-evolution-skill-restatement.mdx","children":"View on GitHub"}]]}] 31:["$","div",null,{"className":"pt-6 pb-6 text-center text-gray-700 dark:text-gray-300","id":"comment","children":["$","$L33",null,{"slug":"agent-architecture-evolution-skill-restatement"}]}] 32:["$","footer",null,{"children":[["$","div",null,{"className":"divide-gray-200 text-sm leading-5 font-medium xl:col-start-1 xl:row-start-2 xl:divide-y dark:divide-gray-700","children":[["$","div",null,{"className":"py-4 xl:py-8","children":[["$","h2",null,{"className":"text-xs tracking-wide text-gray-500 uppercase dark:text-gray-400","children":"Tags"}],["$","div",null,{"className":"flex flex-wrap","children":[["$","$L5","agent",{"className":"text-primary-500 hover:text-primary-600 dark:hover:text-primary-400 mr-3 text-sm font-medium 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