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只做内容生成(脚本/关键词),执行流是 ",["$","code",null,{"children":"task.py"}]," 写死的 5 阶段顺序管线,失败策略是跳过/中止,无动态重规划"]}]]}],["$","tr",null,{"children":[["$","td",null,{"children":"2. 多 Agent"}],["$","td",null,{"children":["无。是 workflow 不是 agent——Orchestrator+Worker 的",["$","strong",null,{"children":"类比物"}],"存在(task.py 编排 + services 各司其职),但通信是函数调用,无协议、无状态共享"]}]]}],["$","tr",null,{"children":[["$","td",null,{"children":"3. 上下文管理"}],["$","td",null,{"children":["不存在。所有 LLM 调用都是",["$","strong",null,{"children":"单轮无状态"}],"的(一次 prompt 一次响应),没有对话历史,也就没有截断/压缩问题"]}]]}],["$","tr",null,{"children":[["$","td",null,{"children":"4. Human-in-the-loop"}],["$","td",null,{"children":"仅参数层(WebUI 配置确认),无运行中干预、无 checkpoint 恢复(state.py 存的是进度状态,不是决策断点)"}]]}],["$","tr",null,{"children":[["$","td",null,{"children":"5. 评估框架"}],["$","td",null,{"children":["pytest 878 个测试是",["$","strong",null,{"children":"代码正确性"}],"测试,不是 agent 评估(无 trajectory、无工具调用质量追踪)"]}]]}],["$","tr",null,{"children":[["$","td",null,{"children":"6. Tool 检索"}],["$","td",null,{"children":["无 tool use。provider 是",["$","strong",null,{"children":"用户静态选择"}],"(video_source 参数),不是模型动态路由"]}]]}],["$","tr",null,{"children":[["$","td",null,{"children":"7. Streaming"}],["$","td",null,{"children":"LLM 输出不流式;任务进度靠轮询 state(唯一有真实讨论空间的一项)"}]]}]]}]]}]}] 24:["$","p",null,{"children":[["$","strong",null,{"children":"面试官如果懂行,不会从 MPT 的 PR 里期待 agent 架构研究"}],"——他们期待的是生产工程能力(计费安全、失败语义、降级设计、开源协作),而你的 PR 恰好满格。拿着 7 维度框架硬套 MPT 做出\"深度分析\",懂行的面试官反而会怀疑你的判断力:把 workflow 当 agent 分析,是概念混淆。"]}] 25:["$","hr",null,{}] 26:["$","h2",null,{"className":"content-header","id":"真问题你的-agent-深度证据链目前是空的","children":[["$","a",null,{"className":"break-words","href":"#真问题你的-agent-深度证据链目前是空的","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"}]]}]}]}],"真问题:你的 agent 深度证据链目前是空的"]}] 27:["$","p",null,{"children":["停止 PR 投递后,你的叙事资产是:MPT 双 PR(生产工程线)+ 即将做的 LiveTalking(实时音视频线)——",["$","strong",null,{"children":"两条都不是 agent 架构线"}],"。如果目标 JD 是\"AI Agent 工程师\",这才是缺口。三个补法,按性价比排序:"]}] 28:["$","h3",null,{"className":"content-header","id":"1-把-7-维度框架用在正确的对象上","children":[["$","a",null,{"className":"break-words","href":"#1-把-7-维度框架用在正确的对象上","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"}]]}]}]}],"1. 把 7 维度框架用在正确的对象上"]}] 29:["$","p",null,{"children":"分析 MPT 时作为\"workflow vs agent 光谱\"的定位工具:一句话版本是\"MPT 位于光谱最左端(固定管线),LLM 只是内容生成器;若引入规划层,最自然的位置是 task.py 编排器之前(素材策略规划:根据主题决定检索还是生成、按 BGM 节奏规划片段时长),改造成本约一个新 service + VideoParams 扩展,且不破坏现有管线\"。"}] 2a:["$","p",null,{"children":[["$","strong",null,{"children":"能说清\"为什么这里不需要 agent\"比硬说\"这里有 agent\"更显研究深度"}],"——知道何时不用 agent,是 agent 工程师的第一课。"]}] 2b:["$","h3",null,{"className":"content-header","id":"2-livetalking-才是-7-维度的主战场","children":[["$","a",null,{"className":"break-words","href":"#2-livetalking-才是-7-维度的主战场","aria-hidden":"true","tabIndex":"-1","children":["$","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"}],["$","path",null,{"d":"M11.603 7.963a.75.75 0 0 0-.977 1.138 2.5 2.5 0 0 1 .142 3.667l-3 3a2.5 2.5 0 0 1-3.536-3.536l1.225-1.224a.75.75 0 0 0-1.061-1.06l-1.224 1.224a4 4 0 1 0 5.656 5.656l3-3a4 4 0 0 0-.225-5.865Z"}]]}]}]}],"2. LiveTalking 才是 7 维度的主战场"]}] 2c:["$","p",null,{"children":"实时数字人天然覆盖维度 3(流式上下文)、7(streaming 与中间状态)、4(打断 = HITL 变体)、1(对话轮次内的即时决策)。做之前用这 7 维度做架构分析(正是你贴的这个模板的用途),PR 叙事自然长出 agent 肌肉。"}] 2d:["$","h3",null,{"className":"content-header","id":"3-如果-agent-线必须马上有东西","children":[["$","a",null,{"className":"break-words","href":"#3-如果-agent-线必须马上有东西","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"}]]}]}]}],"3. 如果 agent 线必须马上有东西"]}] 2e:["$","p",null,{"children":["比第三个 PR 更快的是一篇",["$","strong",null,{"children":"分析文档"}],"——挑一个真 agent 项目(比如 OpenClaw/LiveTalking)做 7 维度缺陷分析发成博客/issue。分析能力不需要 PR 来证明,但需要一个载体。"]}] 2f:["$","hr",null,{}] 30:["$","h2",null,{"className":"content-header","id":"面试话术如果被问你的-pr-没体现-agent-研究","children":[["$","a",null,{"className":"break-words","href":"#面试话术如果被问你的-pr-没体现-agent-研究","aria-hidden":"true","tabIndex":"-1","children":["$","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"}],["$","path",null,{"d":"M11.603 7.963a.75.75 0 0 0-.977 1.138 2.5 2.5 0 0 1 .142 3.667l-3 3a2.5 2.5 0 0 1-3.536-3.536l1.225-1.224a.75.75 0 0 0-1.061-1.06l-1.224 1.224a4 4 0 1 0 5.656 5.656l3-3a4 4 0 0 0-.225-5.865Z"}]]}]}]}],"面试话术(如果被问\"你的 PR 没体现 agent 研究\")"]}] 31:["$","blockquote",null,{"children":["$","p",null,{"children":"\"MPT 本来就不是 agent——它是固定管线的 workflow,LLM 在里面只是内容生成器,我不认为应该为了简历好看往 workflow 里塞 agent。我的这个 PR 体现的是另一层:生产环境对外部付费 API 的失败语义建模。agent 架构的能力我用两个方式证明:一是能精确说清 MPT 在 workflow→agent 光谱上的位置、以及在哪里引入规划层是值得的哪里是过度设计;二是 LiveTalking 的实时链路实践(流式、状态可见性、打断)——那是 agent 维度真正存在的地方。\""}]}] 32:["$","div",null,{"className":"pt-6 pb-6 text-sm text-gray-700 dark:text-gray-300","children":[["$","a",null,{"className":"break-words","target":"_blank","rel":"nofollow","href":"https://mobile.twitter.com/search?q=https%3A%2F%2Ftechlog-18328.app.workbuddy.host%2Fblog%2Fworkflow-vs-agent-7-dimensions","children":"Discuss on Twitter"}]," • ",["$","a",null,{"className":"break-words","target":"_blank","rel":"noopener noreferrer","href":"https://github.com/joker1point/techlog/blob/main/data/blog/workflow-vs-agent-7-dimensions.mdx","children":"View on GitHub"}]]}] 33:["$","div",null,{"className":"pt-6 pb-6 text-center text-gray-700 dark:text-gray-300","id":"comment","children":["$","$L35",null,{"slug":"workflow-vs-agent-7-dimensions"}]}] 34:["$","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","ai",{"className":"text-primary-500 hover:text-primary-600 dark:hover:text-primary-400 mr-3 text-sm font-medium uppercase","href":"/tags/ai.html","children":"ai"}],["$","$L5","agent",{"className":"text-primary-500 hover:text-primary-600 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