[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"article-openclaw-13-chinese-tech-giants-race-en":3,"tags-openclaw-13-chinese-tech-giants-race-en":31,"related-lang-openclaw-13-chinese-tech-giants-race-en":40,"related-posts-openclaw-13-chinese-tech-giants-race-en":44,"series-ai-agent-7a31948c-45f8-4d6d-b73d-c0ef8ae4bd3a":81},{"id":4,"title":5,"content":6,"summary":7,"source":8,"source_url":9,"author":10,"image_url":11,"keywords":12,"language":19,"translated_content":10,"views":20,"is_premium":21,"created_at":22,"updated_at":22,"cover_image":11,"published_at":23,"rewrite_status":24,"rewrite_error":10,"rewritten_from_id":25,"slug":26,"category":27,"related_article_id":28,"status":29,"google_indexed_at":30,"x_posted_at":10,"tweet_text":10,"title_rewritten_at":10,"title_original":10,"key_takeaways":10,"topic_cluster_id":10,"embedding":10,"is_canonical_seed":21},"7a31948c-45f8-4d6d-b73d-c0ef8ae4bd3a","OpenClaw走红：13家大厂为何都在跟进","\u003Cp>2026 年最热的 AI 话题，已经不再是聊天机器人能写多长的回答，而是它能不能真的替你点鼠标、填表、下单、开设备。被网友叫作“\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fopenclaw\" target=\"_blank\" rel=\"noopener\">OpenClaw\u003C\u002Fa>”的开源智能体，正在把这件事变成现实，也把腾讯、字节、华为云等厂商拉进了同一条赛道。\u003C\u002Fp>\u003Cp>这股热度之所以夸张，是因为它碰到的不是一个单点功能，而是一个入口问题：谁掌握了 AI 操作电脑、应用和设备的入口，谁就有机会把办公、客服、运维、零售和个人助理这些场景串起来。\u003C\u002Fp>\u003Cp>如果你还在把 OpenClaw 理解成“更会聊天的机器人”，那就低估它了。它更像一个能执行任务的通用操作层，目标不是回答问题，而是把问题直接做完。\u003C\u002Fp>\u003Ch2>OpenClaw到底火在哪\u003C\u002Fh2>\u003Cp>OpenClaw 最吸引人的地方，不是“会说”，而是“会做”。它能读取界面、识别按钮、执行点击和输入，还能把一连串动作拆成任务流，自动完成原本需要人盯着屏幕做的事情。对开发者来说，这意味着很多原来要写脚本、接 API、调 RPA 的工作，可以换成更自然的任务编排方式。\u003C\u002Fp>\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1775057481628-k0yu.png\" alt=\"OpenClaw走红：13家大厂为何都在跟进\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\u003Cp>这也是为什么它会被很多人拿来和传统自动化工具比较。传统工具擅长固定流程，OpenClaw 这类智能体更擅长处理界面变化、步骤分支和临时任务，尤其适合那些“流程看起来简单，实际经常变”的工作。\u003C\u002Fp>\u003Cul>\u003Cli>它处理的是界面级任务，不是只调用后端接口。\u003C\u002Fli>\u003Cli>它适合桌面软件、网页系统和混合办公场景。\u003C\u002Fli>\u003Cli>它能把人工操作压缩成可复用的任务链。\u003C\u002Fli>\u003Cli>它对没有标准 API 的旧系统尤其有价值。\u003C\u002Fli>\u003C\u002Ful>\u003Cp>从产品定位看，OpenClaw 不是在和聊天模型拼谁更会写文案，而是在和自动化平台抢谁来控制用户的工作流。这个差别很大，因为前者卖的是内容能力，后者卖的是执行能力。\u003C\u002Fp>\u003Cp>也正因为如此，OpenClaw 的讨论才会从开发者社区一路扩散到企业采购、办公软件、云平台和硬件厂商。大家看中的不是一个 demo，而是一个新的入口层。\u003C\u002Fp>\u003Ch2>为什么大厂都想插一脚\u003C\u002Fh2>\u003Cp>腾讯、字节、华为云等厂商之所以会跟进，本质上是因为智能体正在改写软件分发方式。过去，用户先打开应用，再在应用里完成任务。现在，用户更希望直接对 AI 说“把这份表发给财务”“把订单状态同步到系统里”“把会议纪要整理进知识库”，然后让系统自动执行。\u003C\u002Fp>\u003Cp>这会直接影响企业软件的入口。如果 AI 成了默认入口，谁提供底层执行能力，谁就更接近用户的高频工作场景。对云厂商来说，这是云资源、模型调用、企业服务一起卖的机会。对互联网大厂来说，这是把办公、协作、内容、客服重新串成一套工作流的机会。\u003C\u002Fp>\u003Cp>从商业角度看，这种跟进并不奇怪。真正值钱的不是某个单独模型，而是围绕模型建立的执行网络：账号体系、权限控制、日志审计、任务编排、设备接入、数据回流。OpenClaw 这种项目一旦成熟，就会逼着厂商重新思考自家产品的边界。\u003C\u002Fp>\u003Cblockquote>“The future of AI is not about replacing humans, it’s about augmenting human capabilities.” — Satya Nadella\u003C\u002Fblockquote>\u003Cp>这句话虽然不是专门为 OpenClaw 说的，但很贴近这波趋势。微软 CEO \u003Ca href=\"https:\u002F\u002Fwww.microsoft.com\u002Fen-us\u002Fceo\" target=\"_blank\" rel=\"noopener\">Satya Nadella\u003C\u002Fa> 早就把 AI 的重点放在“增强人类能力”上，而不是单纯生成内容。OpenClaw 这类智能体，正是把这种思路落到操作层面的产物。\u003C\u002Fp>\u003Cp>如果把它放到企业里看，价值就更清楚了。一个能操作系统的智能体，能替代的不是一句回答，而是一串重复动作。对很多团队来说，这比再提升一点模型分数更有现实意义。\u003C\u002Fp>\u003Ch2>和传统自动化工具比，差别有多大\u003C\u002Fh2>\u003Cp>OpenClaw 之所以被追捧，是因为它和传统自动化工具的能力边界不同。RPA 工具依赖固定流程和稳定界面，规则一变就要改脚本；智能体则更接近“看着屏幕做事”，界面变化时还有机会重新判断下一步。\u003C\u002Fp>\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1775057502655-ib1f.png\" alt=\"OpenClaw走红：13家大厂为何都在跟进\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\u003Cp>但这不意味着它已经可以完全替代传统方案。真正成熟的企业自动化，通常还是要把三类能力拼在一起：稳定接口负责高可靠执行，界面智能体负责补位，人工审核负责兜底。OpenClaw 更像是把最后那块“界面补丁”做得更聪明。\u003C\u002Fp>\u003Cul>\u003Cli>传统 RPA 更适合固定表单和稳定流程。\u003C\u002Fli>\u003Cli>OpenClaw 更适合界面常变、步骤复杂的任务。\u003C\u002Fli>\u003Cli>API 自动化速度更快，前提是系统开放接口。\u003C\u002Fli>\u003Cli>智能体方案容错更高，但对模型推理和环境识别要求也更高。\u003C\u002Fli>\u003C\u002Ful>\u003Cp>拿实际场景说，财务报销、客服工单、后台审核、内容分发、设备巡检都可能受益。前两类任务往往接口不统一，后两类任务又经常涉及网页、桌面程序和外设，正好是 OpenClaw 这类工具发力的地方。\u003C\u002Fp>\u003Cp>这也解释了为什么大家突然开始讨论“养小龙虾”这种说法。它听起来像玩梗，背后其实是一个很现实的判断：未来很多岗位不一定消失，但会变成“人管一群智能体”。\u003C\u002Fp>\u003Ch2>数据、成本与落地，才是胜负手\u003C\u002Fh2>\u003Cp>如果只看热度，OpenClaw 很容易让人误以为它已经赢了。但真正决定成败的，是成本、稳定性和合规。一个能跑 demo 的智能体，和一个能在企业里 7x24 小时处理任务的系统，差距非常大。\u003C\u002Fp>\u003Cp>企业最先关心的通常不是“它会不会做”，而是“它出错怎么办”。一旦智能体开始操作真实账号、真实设备、真实订单，权限、审计、回滚、风控就都要跟上。没有这些，AI 自动化越强，风险也越大。\u003C\u002Fp>\u003Cp>从部署方式看，厂商跟进 OpenClaw 还有一个明显动机：把能力做成本地化、私有化和云上托管的组合方案。这样一来，既能满足大客户对数据安全的要求，也能把模型调用和任务执行绑定到自己的平台上。\u003C\u002Fp>\u003Cul>\u003Cli>\u003Ca href=\"https:\u002F\u002Fcloud.tencent.com\u002F\" target=\"_blank\" rel=\"noopener\">腾讯云\u003C\u002Fa>、\u003Ca href=\"https:\u002F\u002Fwww.volcengine.com\u002F\" target=\"_blank\" rel=\"noopener\">火山引擎\u003C\u002Fa>、\u003Ca href=\"https:\u002F\u002Fwww.huaweicloud.com\u002F\" target=\"_blank\" rel=\"noopener\">华为云\u003C\u002Fa>都在抢企业入口。\u003C\u002Fli>\u003Cli>\u003Ca href=\"https:\u002F\u002Fwww.microsoft.com\u002Fen-us\u002Fmicrosoft-copilot\" target=\"_blank\" rel=\"noopener\">Microsoft Copilot\u003C\u002Fa>已经证明，办公入口可以被 AI 重写。\u003C\u002Fli>\u003Cli>\u003Ca href=\"https:\u002F\u002Fwww.anthropic.com\u002Fclaude\" target=\"_blank\" rel=\"noopener\">Claude\u003C\u002Fa>和\u003Ca href=\"https:\u002F\u002Fopenai.com\u002Fchatgpt\" target=\"_blank\" rel=\"noopener\">ChatGPT\u003C\u002Fa>正在把“会说”推向“会用工具”。\u003C\u002Fli>\u003Cli>OpenClaw 这类项目把重点进一步推到“会操作界面”。\u003C\u002Fli>\u003C\u002Ful>\u003Cp>对开发者来说，真正值得关注的不是某一家厂商宣布接入，而是这类工具会不会形成统一的任务协议、权限模型和评估标准。一旦标准出现，智能体就会像今天的云服务一样，成为基础设施的一部分。\u003C\u002Fp>\u003Cp>如果没有标准，市场就会碎成一堆各自兼容各自的私有方案，最后还是企业买单，开发者也要重复适配。\u003C\u002Fp>\u003Ch2>结论：OpenClaw争的不是热搜，是入口\u003C\u002Fh2>\u003Cp>OpenClaw 的意义，不在于它名字有多好记，也不在于网友把它叫成“小龙虾”。它真正重要的地方，是把 AI 从“回答问题”推进到“完成任务”，并且把这个能力放到了桌面、网页和设备控制这些高频场景里。\u003C\u002Fp>\u003Cp>接下来最值得盯的，不是又有多少厂商宣布支持，而是三件事：谁先把权限和审计做扎实，谁先把任务成功率拉到企业可用水平，谁先把智能体和现有办公系统真正接起来。谁做到这一步，谁就不只是跟风，而是在定义下一代工作入口。\u003C\u002Fp>\u003Cp>如果你是开发者，现在最该做的事不是围观热度，而是去试一套真实任务流：一个报表、一个工单、一个桌面操作链。因为下一轮竞争，拼的很可能不是模型参数，而是谁能把“点一下”变成“自动做完”。\u003C\u002Fp>","OpenClaw把AI从“会说话”推到“会操作”，腾讯、字节、华为云等13家厂商跟进，争的是办公与设备控制入口。","zhuanlan.zhihu.com","https:\u002F\u002Fzhuanlan.zhihu.com\u002Fp\u002F2020858520665342170",null,"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1775057481628-k0yu.png",[13,14,15,16,17,18],"OpenClaw","智能体","RPA","企业自动化","腾讯","华为云","en",1,false,"2026-04-01T09:45:45.221387+00:00","2026-04-01T09:45:45.104+00:00","done","7885097a-4252-42be-b598-63317154989d","openclaw-13-chinese-tech-giants-race-en","ai-agent","33f9de67-5cba-48ab-a7a9-a1ad4d7964aa","published","2026-04-09T09:00:54.766+00:00",[32,33,34,36,38,39],{"name":14,"slug":14},{"name":16,"slug":16},{"name":15,"slug":35},"rpa",{"name":13,"slug":37},"openclaw",{"name":17,"slug":17},{"name":18,"slug":18},{"id":28,"slug":41,"title":42,"language":43},"openclaw-13-chinese-tech-giants-race-zh","OpenClaw走紅：13家大廠為何跟進","zh",[45,51,57,63,69,75],{"id":46,"slug":47,"title":48,"cover_image":49,"image_url":49,"created_at":50,"category":27},"c5d4bc11-1f4d-438c-b644-a8498826e1ab","claude-agent-dreaming-outcomes-multiagent-en","Claude给Agent加了“做梦”功能","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778868649463-f5qv.png","2026-05-15T18:10:25.29539+00:00",{"id":52,"slug":53,"title":54,"cover_image":55,"image_url":55,"created_at":56,"category":27},"fda44d24-7baf-4d91-a7f9-bbfecae20a27","switch-ai-outputs-markdown-to-html-en","How to Switch AI Outputs from Markdown to HTML","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778743249827-wmsr.png","2026-05-14T07:20:22.631724+00:00",{"id":58,"slug":59,"title":60,"cover_image":61,"image_url":61,"created_at":62,"category":27},"064275f5-4282-47c3-8e4a-60fe8ac99246","anthropic-cat-wu-proactive-ai-assistants-en","Anthropic’s Cat Wu on proactive AI assistants","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778735465548-a92i.png","2026-05-14T05:10:31.723441+00:00",{"id":64,"slug":65,"title":66,"cover_image":67,"image_url":67,"created_at":68,"category":27},"423ac8ad-2886-42a9-8dd8-78e5d43a1574","how-to-run-hermes-agent-on-discord-en","How to Run Hermes Agent on Discord","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778724656141-i30t.png","2026-05-14T02:10:35.727086+00:00",{"id":70,"slug":71,"title":72,"cover_image":73,"image_url":73,"created_at":74,"category":27},"776a562c-99a6-4a6b-93a0-9af40300f3f2","why-ragflow-is-the-right-open-source-rag-engine-to-self-host-en","Why RAGFlow is the right open-source RAG engine to self-host","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778674254587-0pxn.png","2026-05-13T12:10:25.721583+00:00",{"id":76,"slug":77,"title":78,"cover_image":79,"image_url":79,"created_at":80,"category":27},"322ec8bc-61d3-4c80-bb9e-a19941e137c6","how-to-add-temporal-rag-in-production-en","How to Add Temporal RAG in Production","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778667085221-0mox.png","2026-05-13T10:10:31.619892+00:00",[82,87,92,97,102,107,112,117,122,127],{"id":83,"slug":84,"title":85,"created_at":86},"03db8de8-8dc2-4ac1-9cf7-898782efbb1f","anthropic-claude-ai-agent-task-automation-en","Anthropic's Claude AI Agent: A New Era of Task Automation","2026-03-25T16:25:06.513026+00:00",{"id":88,"slug":89,"title":90,"created_at":91},"045d1abc-190d-4594-8c95-91e2a26f0c5a","googles-2026-ai-agent-report-decoded-en","Google’s 2026 AI Agent Report, Decoded","2026-03-26T11:15:23.046616+00:00",{"id":93,"slug":94,"title":95,"created_at":96},"e64aba21-254b-4f93-aa21-837484bb52ec","kimi-k25-review-stronger-still-not-legend-en","Kimi K2.5 review: stronger, still not a 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