[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"article-anthropic-managed-agents-enterprise-ai-work-en":3,"tags-anthropic-managed-agents-enterprise-ai-work-en":30,"related-lang-anthropic-managed-agents-enterprise-ai-work-en":41,"related-posts-anthropic-managed-agents-enterprise-ai-work-en":45,"series-ai-agent-9c8f9f53-4f81-4be8-a7ee-871a02acb9b0":82},{"id":4,"title":5,"content":6,"summary":7,"source":8,"source_url":9,"author":10,"image_url":11,"keywords":12,"language":18,"translated_content":10,"views":19,"is_premium":20,"created_at":21,"updated_at":21,"cover_image":11,"published_at":22,"rewrite_status":23,"rewrite_error":10,"rewritten_from_id":24,"slug":25,"category":26,"related_article_id":27,"status":28,"google_indexed_at":29,"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":20},"9c8f9f53-4f81-4be8-a7ee-871a02acb9b0","Anthropic’s Managed Agents Targets Enterprise AI Work","\u003Cp>Anthropic says its annualized recurring revenue has passed \u003Cstrong>$30 billion\u003C\u002Fstrong>, and it is using that momentum to push deeper into enterprise automation. On Wednesday, the company announced \u003Ca href=\"https:\u002F\u002Fwww.anthropic.com\" target=\"_blank\" rel=\"noopener\">Claude Managed Agents\u003C\u002Fa>, a product meant to take on the annoying, expensive part of building AI agents: the infrastructure around the model.\u003C\u002Fp>\u003Cp>That matters because most companies do not struggle to get a chatbot to answer a question. They struggle to make an AI system run tasks for hours, keep state, call tools safely, and stay inside the permissions a business can live with. Anthropic is trying to package that work so teams can ship agents without assembling the whole stack themselves.\u003C\u002Fp>\u003Ch2>What Anthropic is actually shipping\u003C\u002Fh2>\u003Cp>Claude Managed Agents gives developers a prebuilt setup for agentic apps on the \u003Ca href=\"https:\u002F\u002Fwww.anthropic.com\u002Fapi\" target=\"_blank\" rel=\"noopener\">Claude API\u003C\u002Fa>. Anthropic says the product includes the surrounding software that agents need to act on behalf of users, plus a sandboxed environment where those agents can spin up projects in isolation.\u003C\u002Fp>\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1775779795044-birh.png\" alt=\"Anthropic’s Managed Agents Targets Enterprise AI Work\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\u003Cp>In plain English, Anthropic is selling the plumbing, not just the model. That includes a memory system, tool access controls, and the infrastructure needed to let agents run for long stretches in the cloud. The company is betting that this is where enterprise teams burn the most time and money.\u003C\u002Fp>\u003Cul>\u003Cli>\u003Cstrong>ARR:\u003C\u002Fstrong> more than $30 billion annualized recurring revenue\u003C\u002Fli>\u003Cli>\u003Cstrong>Growth:\u003C\u002Fstrong> roughly 3x higher than December 2025, per Anthropic\u003C\u002Fli>\u003Cli>\u003Cstrong>Runtime:\u003C\u002Fstrong> agents can run autonomously for hours in the cloud\u003C\u002Fli>\u003Cli>\u003Cstrong>Controls:\u003C\u002Fstrong> developers can toggle permissions for tool access\u003C\u002Fli>\u003Cli>\u003Cstrong>Environment:\u003C\u002Fstrong> built-in sandbox for software projects\u003C\u002Fli>\u003C\u002Ful>\u003Cp>That package is aimed at companies that already know what they want agents to do, but do not want to build the \u003Ca href=\"\u002Fnews\u002Fdistsim-distributed-systems-on-your-laptop-en\">distributed systems\u003C\u002Fa> behind them. Anthropic’s pitch is that the hard engineering work gets abstracted away, while product teams stay focused on the business logic.\u003C\u002Fp>\u003Ch2>Why Anthropic thinks this matters now\u003C\u002Fh2>\u003Cp>Anthropic’s enterprise business has been growing fast, and much of that growth has come through the \u003Ca href=\"https:\u002F\u002Fwww.anthropic.com\u002Fclaude\" target=\"_blank\" rel=\"noopener\">Claude Platform\u003C\u002Fa>, which lets developers access the company’s models through an API. The new product is a direct attempt to turn model usage into a fuller enterprise platform, with more of the operational burden handled by Anthropic itself.\u003C\u002Fp>\u003Cp>Angela Jiang, Anthropic’s head of product for the Claude Platform, told WIRED that the company sees a gap between what Claude can do and what businesses are actually doing with it. Her framing is simple: the models are ready for more than most teams have built so far.\u003C\u002Fp>\u003Cblockquote>“When it comes to actually deploying and running agents at scale, that is a complex distributed-systems engineering problem,” says Katelyn Lesse, head of engineering for the Claude Platform.\u003C\u002Fblockquote>\u003Cp>That quote gets to the heart of the product. Enterprises do not fail on the demo. They fail on reliability, permissions, monitoring, and the slow grind of making software behave the same way every time. Anthropic is now selling a shortcut around that pain.\u003C\u002Fp>\u003Cp>There is also a business reason for the timing. Anthropic and \u003Ca href=\"https:\u002F\u002Fopenai.com\" target=\"_blank\" rel=\"noopener\">OpenAI\u003C\u002Fa> are both pushing harder into enterprise products as they prepare for possible public listings. OpenAI already has its own agent platform, and Anthropic clearly does not want to be seen as only a model provider while rivals own the workflow layer.\u003C\u002Fp>\u003Ch2>How it compares with what teams build today\u003C\u002Fh2>\u003Cp>Before Managed Agents, a company that wanted Claude to do real work usually had to assemble a stack around the model. That meant orchestration code, memory handling, permissions, tool integrations, and monitoring. Some teams built those pieces in-house. Others stitched them together with open-source frameworks and a lot of custom code.\u003C\u002Fp>\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1775779798525-us13.png\" alt=\"Anthropic’s Managed Agents Targets Enterprise AI Work\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Anthropic’s new product tries to compress that effort into something more packaged. The comparison is less about raw model quality and more about the amount of engineering needed before an agent can safely touch real work. That is where the differences start to show up.\u003C\u002Fp>\u003Cul>\u003Cli>\u003Ca href=\"https:\u002F\u002Fwww.anthropic.com\u002Fclaude-code\" target=\"_blank\" rel=\"noopener\">Claude Code\u003C\u002Fa> already lets developers use Claude inside coding workflows, but Managed Agents goes after broader enterprise automation\u003C\u002Fli>\u003Cli>\u003Ca href=\"https:\u002F\u002Fopenai.com\u002Findex\u002Fintroducing-agentkit\u002F\" target=\"_blank\" rel=\"noopener\">OpenAI’s agent tools\u003C\u002Fa> focus on building agent workflows, while Anthropic is emphasizing managed infrastructure and runtime control\u003C\u002Fli>\u003Cli>\u003Ca href=\"https:\u002F\u002Fwww.notion.so\" target=\"_blank\" rel=\"noopener\">Notion\u003C\u002Fa> used the product in a demo to automate client onboarding, showing how a real app can hand off repetitive work to an agent\u003C\u002Fli>\u003Cli>\u003Ca href=\"https:\u002F\u002Fwww.anthropic.com\u002Fnews\" target=\"_blank\" rel=\"noopener\">Anthropic’s news page\u003C\u002Fa> shows a steady push toward enterprise features, not a one-off product launch\u003C\u002Fli>\u003C\u002Ful>\u003Cp>In the WIRED demo, Notion product manager Eric Liu showed how a Claude Managed Agent could work through a long list of onboarding tasks inside Notion. The interesting part was not the flashy output. It was the control panel on the Claude side, where the team could inspect what the agents were doing and which tools they were using.\u003C\u002Fp>\u003Cp>That kind of visibility is what companies need before they let agents touch customer data, internal systems, or anything tied to revenue. If Anthropic can make that layer easier, it has a real shot at becoming more than a model vendor.\u003C\u002Fp>\u003Ch2>The bigger bet: agents as enterprise software\u003C\u002Fh2>\u003Cp>Wall Street has already started worrying that AI vendors could eat into the market for traditional software-as-a-service companies. Anthropic’s move adds fuel to that concern, because Managed Agents is aimed at the exact layer where SaaS products often make money: workflow automation.\u003C\u002Fp>\u003Cp>Still, the product also shows how much room remains before AI agents become standard enterprise software. Anthropic may have strong models and fast-growing revenue, but most businesses will not hand over important processes until they trust the runtime, the permissions model, and the audit trail.\u003C\u002Fp>\u003Cp>That means the next test is practical, not philosophical. Can Anthropic make agents dependable enough that a finance team, support org, or operations group will let them run for hours without constant babysitting? If the answer is yes, the company could turn Claude into a serious backend for enterprise work. If not, Managed Agents becomes another useful demo with a narrow audience.\u003C\u002Fp>\u003Cp>My read: Anthropic is aiming at the layer where AI products either become indispensable or stay experimental. Over the next year, the real signal will be whether companies like Notion move from demos to production workflows at scale. If that happens, the market will stop talking about Claude as a model and start treating it like infrastructure.\u003C\u002Fp>\u003Cp>For more on the developer side of AI tooling, see our coverage of \u003Ca href=\"\u002Fnews\u002Fclaude-code-vs-openai-agent-tools\">Claude Code vs. OpenAI’s agent stack\u003C\u002Fa> and the rise of managed enterprise AI systems.\u003C\u002Fp>","Anthropic says its new Claude Managed Agents can cut setup work for enterprise AI, as ARR tops $30 billion and rivals race ahead.","www.wired.com","https:\u002F\u002Fwww.wired.com\u002Fstory\u002Fanthropic-launches-claude-managed-agents\u002F",null,"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1775779795044-birh.png",[13,14,15,16,17],"Anthropic","Claude Managed Agents","enterprise AI","AI agents","Claude Platform","en",0,false,"2026-04-10T00:09:41.341458+00:00","2026-04-10T00:09:41.271+00:00","done","7bdcd360-a759-4fc3-9020-89d3911daeb4","anthropic-managed-agents-enterprise-ai-work-en","ai-agent","a0793170-f21f-4450-9d77-43cc7e43b192","published","2026-04-10T09:00:23.653+00:00",[31,33,35,37,39],{"name":14,"slug":32},"claude-managed-agents",{"name":13,"slug":34},"anthropic",{"name":15,"slug":36},"enterprise-ai",{"name":17,"slug":38},"claude-platform",{"name":16,"slug":40},"ai-agents",{"id":27,"slug":42,"title":43,"language":44},"anthropic-managed-agents-enterprise-ai-work-zh","Anthropic 推出 Managed Agents 攻…","zh",[46,52,58,64,70,76],{"id":47,"slug":48,"title":49,"cover_image":50,"image_url":50,"created_at":51,"category":26},"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":53,"slug":54,"title":55,"cover_image":56,"image_url":56,"created_at":57,"category":26},"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":59,"slug":60,"title":61,"cover_image":62,"image_url":62,"created_at":63,"category":26},"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":65,"slug":66,"title":67,"cover_image":68,"image_url":68,"created_at":69,"category":26},"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":71,"slug":72,"title":73,"cover_image":74,"image_url":74,"created_at":75,"category":26},"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":77,"slug":78,"title":79,"cover_image":80,"image_url":80,"created_at":81,"category":26},"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",[83,88,93,98,103,108,113,118,123,128],{"id":84,"slug":85,"title":86,"created_at":87},"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":89,"slug":90,"title":91,"created_at":92},"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":94,"slug":95,"title":96,"created_at":97},"e64aba21-254b-4f93-aa21-837484bb52ec","kimi-k25-review-stronger-still-not-legend-en","Kimi K2.5 review: stronger, still not a legend","2026-03-27T07:15:55.385951+00:00",{"id":99,"slug":100,"title":101,"created_at":102},"30dfb781-a1b2-4add-aebe-b3df40247c37","claude-code-controls-mac-desktop-en","Claude Code now controls your Mac desktop","2026-03-28T03:01:59.384091+00:00",{"id":104,"slug":105,"title":106,"created_at":107},"254405b6-7833-4800-8e13-f5196deefbe6","cloudflare-100x-faster-ai-agent-sandbox-en","Cloudflare’s 100x Faster AI Agent Sandbox","2026-03-28T03:09:44.356437+00:00",{"id":109,"slug":110,"title":111,"created_at":112},"04f29b7f-9b91-4306-89a7-97d725e6e1ba","openai-backs-isara-agent-swarm-bet-en","OpenAI backs Isara’s agent-swarm bet","2026-03-28T03:15:27.849766+00:00",{"id":114,"slug":115,"title":116,"created_at":117},"3b0bf479-e4ae-4703-9666-721a7e0cdb91","openai-plan-automated-ai-researcher-en","OpenAI’s plan for an automated AI researcher","2026-03-28T03:17:42.312819+00:00",{"id":119,"slug":120,"title":121,"created_at":122},"fe91bce0-b85d-4efa-a207-24ae9939c29f","harness-engineering-ai-agent-reliability-2026","Harness Engineering: From Bridle to Operating System, The Missing Link in AI Agent Reliability","2026-03-31T06:36:55.648751+00:00",{"id":124,"slug":125,"title":126,"created_at":127},"67dc66da-ca46-4aa5-970b-e997a39fe109","openai-codex-plugin-claude-code-en","OpenAI puts Codex inside Claude Code","2026-04-01T09:21:55.381386+00:00",{"id":129,"slug":130,"title":131,"created_at":132},"7a09007d-820f-43b3-8607-8ad1bfcb94c8","mcp-explained-from-prompts-to-production-en","MCP Explained: From Prompts to Production","2026-04-01T09:24:40.089177+00:00"]