[{"data":1,"prerenderedAt":1237},["ShallowReactive",2],{"site-nav-content":3,"blog:\u002Fblog\u002Fnimbus-vs-glean":177,"blog-index-copy":542,"blog:\u002Fblog\u002Fnimbus-vs-glean:surround":563,"hiring-banner-content":1206,"site-cta-content":1218},{"header":4,"productNav":9,"nav":42,"footer":61,"askAI":132,"id":161,"title":162,"archived":163,"authors":164,"badge":164,"body":165,"date":164,"definedTerm":164,"department":164,"description":169,"extension":172,"eyebrow":164,"faqHeader":164,"faqs":164,"footerBand":164,"headline":164,"image":164,"industry":164,"jobType":164,"listed":131,"location":164,"navigation":131,"openRoles":164,"pageLayout":164,"path":173,"relatedHeading":164,"seo":174,"series":164,"sitemap":163,"status":164,"stem":175,"subhead":164,"tags":164,"video":164,"whyJoin":164,"workplaceType":164,"__hash__":176},{"productLabel":5,"loginLabel":6,"contactLabel":7,"contactSalesLabel":8},"Product","Log in","Contact","Get started for free",[10,14,18,22,26,30,34,38],{"label":11,"to":12,"description":13},"Overview","\u002Foverview","Seven layers. One closed loop.",{"label":15,"to":16,"description":17},"Conflux","\u002Fproduct\u002Fconflux","Where your team, workstreams, and agents meet.",{"label":19,"to":20,"description":21},"Agent Teams","\u002Fproduct\u002Fagent-teams","Specialist teams - governed from day one.",{"label":23,"to":24,"description":25},"Lifecycle Graph","\u002Fproduct\u002Flifecycle-graph","Intelligence that compounds across every interaction.",{"label":27,"to":28,"description":29},"Company Wiki","\u002Fproduct\u002Fwiki","Playbooks and policies where expertise stays.",{"label":31,"to":32,"description":33},"Workstreams","\u002Fproduct\u002Fworkstreams","From brief to signed-off deliverable on one canvas.",{"label":35,"to":36,"description":37},"Perception Console","\u002Fproduct\u002Fperception","Ask your whole business in plain English.",{"label":39,"to":40,"description":41},"Governance","\u002Fproduct\u002Fgovernance","Frontier AI you can actually sign off on.",[43,46,49,52,55,58],{"label":44,"to":45},"Models","\u002Fmodels",{"label":47,"to":48},"Pricing","\u002Fpricing",{"label":50,"to":51},"Integrations","\u002Fintegrations",{"label":53,"to":54},"Security","\u002Fsecurity",{"label":56,"to":57},"Partners","\u002Fpartners",{"label":59,"to":60},"Insights","\u002Fblog",{"productHeading":5,"companyHeading":62,"resourcesHeading":63,"legalHeading":64,"docsLabel":65,"docsUrl":66,"statementLines":67,"copyright":70,"companyLinks":71,"resourcesLinks":86,"legalLinks":102,"socialLinks":109,"bottomLinks":119},"Company","Resources","Legal","Docs","https:\u002F\u002Fdocs.gonimbus.ai",[68,69],"Stop training someone else's model.","Control your AI.","© 2026 Nimbus Intelligence, Inc. All rights reserved.",[72,73,74,75,76,78,81,84],{"label":47,"to":48},{"label":50,"to":51},{"label":53,"to":54},{"label":59,"to":60},{"label":77,"to":57},"Partner Program",{"label":79,"to":80},"Careers","\u002Fcareers",{"label":82,"to":83},"System status","\u002Fstatus",{"label":7,"to":85},"\u002Fcontact",[87,90,93,96,99],{"label":88,"to":89},"Glossary","\u002Fglossary",{"label":91,"to":92},"Compare","\u002Fcompare",{"label":94,"to":95},"Evaluate","\u002Fevaluate",{"label":97,"to":98},"Problems","\u002Fproblems",{"label":100,"to":101},"Use cases","\u002Fuse-cases",[103,106],{"label":104,"to":105},"Terms of Service","\u002Fterms",{"label":107,"to":108},"Privacy Policy","\u002Fprivacy",[110,113,116],{"label":111,"href":112},"LinkedIn","https:\u002F\u002Fwww.linkedin.com\u002Fcompany\u002Fgonimbusai\u002F",{"label":114,"href":115},"X","https:\u002F\u002Fx.com\u002Fgonimbusai",{"label":117,"href":118},"Instagram","https:\u002F\u002Fwww.instagram.com\u002Fgonimbus_ai\u002F",[120,122,124,127,128],{"label":121,"to":105},"Terms",{"label":123,"to":108},"Privacy",{"label":125,"to":126},"Compliance","\u002Fcompliance",{"label":82,"to":83},{"label":129,"to":130,"external":131},"LLMs.txt","\u002Fllms.txt",true,{"text":133,"prompt":134,"platforms":135},"Ask AI about Nimbus","I'm researching enterprise intelligence platforms and want to know how Nimbus combines perception, collaboration, and autonomous agents to drive strategic decision-making. Summarize the highlights from Nimbus's website: https:\u002F\u002Fgonimbus.ai",[136,141,146,151,156],{"name":137,"label":138,"icon":139,"hrefPrefix":140},"chatgpt","ChatGPT","simple-icons:openai","https:\u002F\u002Fchatgpt.com\u002F?prompt=",{"name":142,"label":143,"icon":144,"hrefPrefix":145},"perplexity","Perplexity","mdi:magnify","https:\u002F\u002Fwww.perplexity.ai\u002Fsearch\u002Fnew?q=",{"name":147,"label":148,"icon":149,"hrefPrefix":150},"grok","Grok","simple-icons:x","https:\u002F\u002Fx.com\u002Fi\u002Fgrok?text=",{"name":152,"label":153,"icon":154,"hrefPrefix":155},"claude","Claude","simple-icons:anthropic","https:\u002F\u002Fclaude.ai\u002Fnew?q=",{"name":157,"label":158,"icon":159,"hrefPrefix":160},"google-ai","Google AI","simple-icons:google","https:\u002F\u002Fwww.google.com\u002Fsearch?udm=50&aep=11&q=","content\u002Fshared\u002Fnav.md","Site navigation",false,null,{"type":166,"value":167,"toc":168},"minimark",[],{"title":169,"searchDepth":170,"depth":170,"links":171},"",2,[],"md","\u002Fshared\u002Fnav",{"title":162,"description":169},"shared\u002Fnav","Q7sDe7TuGEwhwUMamyeOxjvGlsUaF3Iay9VTW0KaE_U",{"id":178,"title":179,"archived":163,"authors":164,"badge":180,"body":186,"date":517,"definedTerm":164,"department":164,"description":518,"extension":172,"eyebrow":164,"faqHeader":519,"faqs":522,"footerBand":164,"headline":164,"image":164,"industry":164,"jobType":164,"listed":131,"location":164,"navigation":131,"openRoles":164,"pageLayout":164,"path":532,"relatedHeading":164,"seo":533,"series":534,"sitemap":131,"status":164,"stem":535,"subhead":164,"tags":536,"video":164,"whyJoin":164,"workplaceType":164,"__hash__":541},"content\u002Fblog\u002Fnimbus-vs-glean.md","Nimbus vs Glean: Finding the Deck vs Running the Job That Deck Implies",{"label":181,"10|authors":182},"Comparisons",[183],{"name":184,"to":185},"Nimbus Research","https:\u002F\u002Fgonimbus.ai",{"type":166,"value":187,"toc":498},[188,197,205,212,217,269,273,286,294,297,300,303,306,309,313,321,324,327,330,334,337,360,368,379,383,388,394,398,401,405,408,412,415,419,426,430,441,445,448,452,455,459,473,477],[189,190,191,196],"p",{},[192,193,195],"a",{"href":194},"https:\u002F\u002Fwww.glean.com\u002F","Glean"," is workplace search that grew a work assistant on top. It finds files across Drive, Slack, Confluence, and the rest of the workplace — and it respects who is allowed to see them. Nimbus is the place you then run the job those files imply: update the customer record, file the next step, get a person to sign.",[189,198,199,200,204],{},"Glean’s centre of gravity is ",[201,202,203],"strong",{},"find the right object, for the right person, at the right time",". Nimbus’s is a signed-off outcome. Both products will say “knowledge” and “agents.” They are not the same purchase. Search that does not leak is a hard, years-long problem. A release on a live system is a different hard problem. Many enterprises have both. They should not pretend one vendor covers both because both say “knowledge graph.”",[189,206,207,211],{},[192,208,210],{"href":209},"https:\u002F\u002Fwww.glean.com\u002Fproduct","Glean’s product"," connects to Google Workspace, Microsoft 365, Slack, Salesforce, Confluence, Jira, and many more — publicly, 100+ workplace apps — then builds an index that respects the same permissions as the source system. Under the hood that is a mix of classic keyword search and meaning-based search, plus a map of people, documents, and activity. Glean has added assistants and agents so the search layer can also draft and automate. That architecture is why Glean wins large-enterprise search bake-offs. Identity, crawl, and permission fidelity are the hard problems, and Glean has spent years on them.",[213,214,216],"h2",{"id":215},"words-youll-hear","Words you’ll hear",[218,219,220,227,233,239,245,251,257,263],"ul",{},[221,222,223,226],"li",{},[201,224,225],{},"Workplace search."," An index across the apps the company already uses, so people stop hunting for files.",[221,228,229,232],{},[201,230,231],{},"Permission mirroring."," If a document is restricted in Drive, Glean should not surface it in a chat answer. That is the product.",[221,234,235,238],{},[201,236,237],{},"Knowledge graph (Glean)."," A map of people, documents, and activity for retrieval. Not the same as Nimbus’s Lifecycle Graph.",[221,240,241,244],{},[201,242,243],{},"Crawl."," The programme of connecting apps, mapping identity, and keeping the index fresh. Why IT sponsors Glean. Why it takes time.",[221,246,247,250],{},[201,248,249],{},"Workstream."," In Nimbus, a shared workspace for one job — not a search result.",[221,252,253,256],{},[201,254,255],{},"Write-back."," Changing a live system. Search products add agents on top of the index. Nimbus treats the write as a first-class release.",[221,258,259,262],{},[201,260,261],{},"Lifecycle Graph."," A causal record of AI work: what ran, who approved it, what changed. Not an index of every file an employee ever touched.",[221,264,265,268],{},[201,266,267],{},"Copilot."," Microsoft’s assistant inside Office. Glean searches across many apps, including Microsoft. Neither is a governed execution layer.",[213,270,272],{"id":271},"why-the-difference-matters","Why the difference matters",[189,274,275,276,280,281,285],{},"If you have ever watched a naive chatbot answer from a restricted Drive folder, you understand why Glean exists. Permission mirroring is not a slogan. It is the product: if a document is restricted in Drive, Glean should not surface it in a chat answer. ",[192,277,279],{"href":278},"https:\u002F\u002Fcsrc.nist.gov\u002Fpubs\u002Fsp\u002F800\u002F53\u002Fr5\u002Fupd1\u002Ffinal","NIST SP 800-53 Rev. 5"," Access Control (the AC family) is the control-catalogue reason: the system must enforce who may see what. ",[192,282,284],{"href":283},"https:\u002F\u002Fwww.glean.com\u002Fsecurity","Glean’s security page"," describes that enforcement as a product: permission mirroring, encryption, and compliance claims. Glean is search that does not leak. It is not an AI risk-management framework, and it does not, by itself, put a named signer on a customer-record write.",[189,287,288,289,293],{},"Glean’s primary object is a document, message, ticket, or person. Nimbus’s primary object is a job, an agent team, a release. Glean’s success metric is time-to-answer. Nimbus’s is time-to-signed-off outcome. Glean’s write path is secondary — agents on top of the index. Nimbus’s write path is first-class: ",[192,290,292],{"href":291},"\u002Fblog\u002Fwhat-is-write-back-governance\u002F","read-only until you open it",", then a person on the change.",[189,295,296],{},"Ask whether agents are a feature of search, or search is a feature of agents. Glean is the first. Nimbus is the second. Assistants on a permission-aware index are a reasonable next step for a search company. They still orbit findability. A workstream does not orbit a search result. It orbits a finish line, a budget, and a write policy.",[189,298,299],{},"The crawl is why IT sponsors Glean and why it takes time: connecting apps, mapping identity, keeping the index fresh, proving permission QA. That is the right model for a 20,000-person corpus. It is the wrong model if you needed a signed CRM update this quarter and were told to wait until 2019’s files had finished indexing. Nimbus assumes you can already find the policy, or that you will attach the systems this job needs. It does not wait for a company-wide crawl of every historical file.",[189,301,302],{},"The two “graphs” are the usual confusion. Glean’s knowledge graph is mostly an index of people and content for retrieval. Nimbus’s Lifecycle Graph is an operational ledger of work, agents, and releases. Collapsing the terms in a vendor meeting is how you buy the wrong one. You can run both graphs. You cannot substitute one for the other.",[189,304,305],{},"Role by role, the fork is practical. A CIO running a knowledge programme wants a universal search bar across 100+ apps, with permission mirroring as the non-negotiable. That is Glean. A Head of RevOps wants an agent to propose opportunity updates with a named signer — search will find the deck; it will not be the release. Security cares that Glean does not leak restricted files, and still cares who may change Salesforce. Knowledge workers want time-to-answer. Operators want time-to-signed-off outcome. Legal will not accept “the assistant found it” as the story of why a customer field moved.",[189,307,308],{},"A healthy split: Glean for findability across the sprawling workplace; Nimbus for execution on the jobs that mutate systems of record. Do not stretch Glean into an operating layer because it added agents. Do not stretch Nimbus into a crawl of every Confluence page because Perception can answer questions about the record.",[213,310,312],{"id":311},"when-glean-is-a-better-fit","When Glean is a better fit",[189,314,315,316,320],{},"Choose Glean when the corpus is huge, permissions ",[317,318,319],"em",{},"are"," the product, and you need a universal search bar across 100+ apps before you invent agent teams. Choose Glean also if the executive sponsor is the CIO’s knowledge programme rather than a line-of-business operating model.",[189,322,323],{},"Deployment is a crawl programme: identity mapping, permission QA, often with Glean or partner engineers in the building. That is the right model for a 20,000-person corpus. Do not treat that implementation cost as a reason Glean is “worse.” It is the cost of doing permission-aware search well.",[189,325,326],{},"Do not choose Glean as a stealth agent operating layer. You will spend a year on crawl quality and still lack workstreams, specialist teams, and change control on writes.",[189,328,329],{},"Some organisations will run Glean for findability and Nimbus for execution. That is a coherent architecture if you do not pretend one graph is the other. Keep Glean as the place people find the deck. Put the job the deck implies — update the customer record, file the next step, get a person to sign — in a Nimbus workstream. Connectors in Nimbus are not a substitute for Glean-scale historical crawl. A Glean assistant is not a substitute for a quoted write.",[213,331,333],{"id":332},"how-this-shows-up-in-nimbus","How this shows up in Nimbus",[189,335,336],{},"Search exists inside Nimbus as a way to ask about the record, your playbooks, and the systems you attached. It is not a company-wide crawl of 2019.",[189,338,339,340,344,345,349,350,354,355,359],{},"The ",[192,341,343],{"href":342},"\u002Fproduct\u002Fwiki\u002F","wiki"," is what the company asserts. ",[192,346,348],{"href":347},"\u002Fintegrations\u002F","Connectors"," are scoped per ",[192,351,353],{"href":352},"\u002Fproduct\u002Fworkstreams\u002F","workstream",". Agents do not get “search everything this user could theoretically open” as the default tool. They get the systems you attached, in the mode you allowed (usually read), until a human releases a write. ",[192,356,358],{"href":357},"\u002Fproduct\u002Fperception\u002F","Perception"," is ordinary language over that scoped world, not a second Glean.",[189,361,362,363,367],{},"You can ",[192,364,366],{"href":365},"\u002Foverview\u002F","set Nimbus up yourselves",": a workspace, wiki, connectors, a first workstream. You do not wait for an index of every historical file to finish.",[189,369,370,371,374,375,378],{},"See ",[192,372,39],{"href":373},"\u002Fproduct\u002Fgovernance\u002F"," and the ",[192,376,23],{"href":377},"\u002Fproduct\u002Flifecycle-graph\u002F",".",[213,380,382],{"id":381},"questions-people-actually-ask","Questions people actually ask",[384,385,387],"h3",{"id":386},"does-glean-require-more-implementation-than-nimbus","Does Glean require more implementation than Nimbus?",[189,389,390,391,393],{},"Usually yes. Permission-aware crawl at enterprise scale is a programme. Nimbus is self-service for most buyers: you are not waiting on vendor engineers sitting with your team for months to get collaboration, sign-off, and a causal record. That is not a claim that Glean is slow for no reason. Crawl and permission QA ",[317,392,319],{}," the work.",[384,395,397],{"id":396},"does-nimbus-replace-glean","Does Nimbus replace Glean?",[189,399,400],{},"Only if your Glean usage is a thin Q&A bot on a small corpus. It does not replace Glean as permission-aware enterprise search across a sprawling workplace. If you need the latter, keep a search product.",[384,402,404],{"id":403},"both-mention-knowledge-graphs-are-they-the-same","Both mention knowledge graphs. Are they the same?",[189,406,407],{},"No. Glean’s graph is mostly an index of people and content for retrieval. Nimbus’s Lifecycle Graph is an operational ledger of work, agents, and releases. Collapsing the terms in a vendor meeting is how you buy the wrong one.",[384,409,411],{"id":410},"can-nimbus-search-drive-and-slack","Can Nimbus search Drive and Slack?",[189,413,414],{},"Connectors bring live systems into agent context and into questions you ask about the record. That is targeted operational retrieval, not a Glean-scale crawl of every historical file. If you need the latter, keep a search product.",[384,416,418],{"id":417},"glean-vs-copilot-vs-nimbus","Glean vs Copilot vs Nimbus?",[189,420,421,422,378],{},"Copilot is productivity inside Microsoft that respects Microsoft permissions. Glean is search across many apps (including Microsoft) that respects source permissions. Nimbus is governed execution. A Microsoft-first company may still need Glean if SharePoint search is not enough, and may still need Nimbus if Copilot Studio is not an operating layer. See ",[192,423,425],{"href":424},"\u002Fblog\u002Fnimbus-vs-microsoft-copilot\u002F","Nimbus vs Microsoft Copilot",[384,427,429],{"id":428},"can-we-run-glean-and-nimbus-together","Can we run Glean and Nimbus together?",[189,431,432,433,436,437,440],{},"Yes. That is the intended coexistence for organisations that have both a findability problem and an execution problem. Do not give Glean agents production write credentials because the index is permission-aware. Permission to ",[317,434,435],{},"see"," is not permission to ",[317,438,439],{},"change",". Route mutations through Nimbus governance.",[384,442,444],{"id":443},"who-should-own-which-product","Who should own which product?",[189,446,447],{},"The CIO’s knowledge programme typically owns Glean: identity mapping, crawl, permission QA. Line operators own Nimbus workstreams because they own the systems of record those jobs touch. Security reviews both — leak prevention on the search side, write gates on the execution side.",[384,449,451],{"id":450},"if-glean-has-agents-now-why-add-nimbus","If Glean has agents now, why add Nimbus?",[189,453,454],{},"Because agents on an index are still a feature of search. Time-to-answer is not time-to-signed-off outcome. If the job is to change a customer record with a person on the write, you need a workstream, a wiki clause, and a graph — not another way to find the deck.",[213,456,458],{"id":457},"related-reading","Related reading",[189,460,461,465,466,470,471,378],{},[192,462,464],{"href":463},"\u002Fblog\u002Fwhat-is-enterprise-rag\u002F","What is enterprise RAG",", ",[192,467,469],{"href":468},"\u002Fblog\u002Fwhat-is-a-lifecycle-graph\u002F","What is a lifecycle graph",", and ",[192,472,425],{"href":424},[213,474,476],{"id":475},"sources","Sources",[218,478,479,483,488,493],{},[221,480,481],{},[192,482,195],{"href":194},[221,484,485],{},[192,486,487],{"href":209},"Glean product",[221,489,490],{},[192,491,492],{"href":283},"Glean security",[221,494,495],{},[192,496,497],{"href":278},"NIST SP 800-53 Rev. 5 (Access Control)",{"title":169,"searchDepth":170,"depth":170,"links":499},[500,501,502,503,504,515,516],{"id":215,"depth":170,"text":216},{"id":271,"depth":170,"text":272},{"id":311,"depth":170,"text":312},{"id":332,"depth":170,"text":333},{"id":381,"depth":170,"text":382,"children":505},[506,508,509,510,511,512,513,514],{"id":386,"depth":507,"text":387},3,{"id":396,"depth":507,"text":397},{"id":403,"depth":507,"text":404},{"id":410,"depth":507,"text":411},{"id":417,"depth":507,"text":418},{"id":428,"depth":507,"text":429},{"id":443,"depth":507,"text":444},{"id":450,"depth":507,"text":451},{"id":457,"depth":170,"text":458},{"id":475,"depth":170,"text":476},"2026-08-17","Glean is permission-aware workplace search; Nimbus is the place an agent can change a customer record — with a person signing off.",{"eyebrow":520,"title":521},"Short answers","Search versus a signed change",[523,526,529],{"question":524,"answer":525},"What is Glean for?","Permission-aware workplace search. It finds the file the person is allowed to see.",{"question":527,"answer":528},"What is Nimbus for beside search?","The job the file implies: changing a customer record, with a person signing off.",{"question":530,"answer":531},"Can search replace the write path?","No. Finding the deck and being allowed to act on it are different controls. Many companies need both.","\u002Fblog\u002Fnimbus-vs-glean",{"title":179,"description":518},"comparisons","blog\u002Fnimbus-vs-glean",[534,537,538,539,540],"glean","enterprise-search","knowledge-graph","agents","ZPznjefdGfilTWFfVNBL098K-K1ns95GH7UNKbmWFkU",{"hero":543,"id":545,"title":546,"archived":163,"authors":164,"badge":164,"body":547,"date":164,"definedTerm":164,"department":164,"description":551,"extension":172,"eyebrow":552,"faqHeader":164,"faqs":164,"footerBand":553,"headline":164,"image":164,"industry":164,"jobType":164,"listed":131,"location":164,"navigation":131,"openRoles":164,"pageLayout":164,"path":60,"relatedHeading":559,"seo":560,"series":164,"sitemap":131,"status":164,"stem":561,"subhead":164,"tags":164,"video":164,"whyJoin":164,"workplaceType":164,"__hash__":562},{"filename":544},"u2221455217_Flat_design_of_a_futuristic_minimalist_landscape__5d589295-cdea-4ea9-a262-be766881accf_1.png","content\u002Fblog\u002Findex.md","Exploring the future of intelligence.",{"type":166,"value":548,"toc":549},[],{"title":169,"searchDepth":170,"depth":170,"links":550},[],"Deep dives into pre-cognitive intelligence, sentient enterprises, and the evolving landscape of AI-driven business transformation.","Latest Research",{"headline":554,"description":555,"primaryLabel":556,"primaryTo":557,"secondaryLabel":558,"secondaryTo":12},"Stay at the frontier.","Subscribe for product updates and new insights.","Subscribe","\u002Fnewsletter","Explore the platform","More research",{"title":546,"description":551},"blog\u002Findex","BFSWGYO9bcTlaulivKYWyg08_DJHsdGg3OC6g_CG1Hw",[564,914],{"id":565,"title":566,"archived":163,"authors":164,"badge":567,"body":570,"date":517,"definedTerm":164,"department":164,"description":892,"extension":172,"eyebrow":164,"faqHeader":893,"faqs":895,"footerBand":164,"headline":164,"image":164,"industry":164,"jobType":164,"listed":131,"location":164,"navigation":131,"openRoles":164,"pageLayout":164,"path":905,"relatedHeading":164,"seo":906,"series":534,"sitemap":131,"status":164,"stem":907,"subhead":164,"tags":908,"video":164,"whyJoin":164,"workplaceType":164,"__hash__":913},"content\u002Fblog\u002Fnimbus-vs-microsoft-copilot.md","Nimbus vs Microsoft Copilot: Great Inside Office, or Work That Leaves Microsoft?",{"label":181,"10|authors":568},[569],{"name":184,"to":185},{"type":166,"value":571,"toc":874},[572,594,597,618,620,671,673,679,689,695,706,709,712,716,719,722,725,728,731,733,746,758,763,767,769,773,776,780,783,787,792,796,803,807,810,814,817,819,826,830,836,838,851,853],[189,573,574,575,581,582,588,589,593],{},"“Copilot” is several products that get collapsed in procurement. ",[201,576,577],{},[192,578,580],{"href":579},"https:\u002F\u002Fwww.microsoft.com\u002Fmicrosoft-365\u002Fcopilot","Microsoft 365 Copilot"," is the add-on that sits in Word, Excel, PowerPoint, Outlook, Teams, and the Copilot app. ",[201,583,584],{},[192,585,587],{"href":586},"https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fmicrosoft-copilot-studio\u002F","Copilot Studio"," is the low-code environment for multi-step agents beyond Microsoft. Nimbus is an ",[192,590,592],{"href":591},"\u002Fblog\u002Fwhat-is-an-agent-harness\u002F","agent harness"," for work that leaves Microsoft — Salesforce, NetSuite, and the rest of the stack where money actually moves.",[189,595,596],{},"Nobody else will be as good at “summarise this thread and the attached deck” inside Outlook. That recap is tenant productivity. Updating forty opportunities in Salesforce is company operations. If your programme starts with “every knowledge worker has a Copilot licence,” you are specifying Microsoft. If it starts with “RevOps will not allow unapproved Salesforce writes from an agent, and we need a record of those releases,” you are specifying Nimbus. You can keep both. Using Nimbus does not mean ripping Copilot out of Office.",[189,598,599,600,604,605,609,610,613,614,617],{},"Microsoft’s own ",[192,601,603],{"href":602},"https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fmicrosoft-365\u002Fcopilot\u002Fmicrosoft-365-copilot-architecture","architecture"," and ",[192,606,608],{"href":607},"https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fcopilot\u002Fmicrosoft-365\u002Fmicrosoft-365-copilot-privacy","privacy"," docs are the source: Copilot is grounded in Microsoft Graph — mail, files, meetings, and sites the user can already access — and prompts, responses, and Graph data are not used to train foundation LLMs. That is the right privacy story for find-and-draft inside Microsoft. It still describes ",[317,611,612],{},"find and draft inside Microsoft",", not ",[317,615,616],{},"sign a write in Salesforce",". Agent Builder covers simple agents inside Copilot, grounded in Microsoft 365 content, for information workers. Studio is the step that leaves Graph.",[213,619,216],{"id":215},[218,621,622,628,634,640,646,651,660,665],{},[221,623,624,627],{},[201,625,626],{},"Microsoft 365 Copilot."," The per-person assistant inside Office, grounded in Microsoft Graph — mail, files, meetings, and sites the user can already access.",[221,629,630,633],{},[201,631,632],{},"Microsoft Graph."," The map of what this person can already open in Microsoft 365. Copilot should not leak a file they cannot open in SharePoint.",[221,635,636,639],{},[201,637,638],{},"Copilot Studio."," Low-code agents with branching, approvals, and connectors to Salesforce, SAP, ServiceNow, and custom APIs. You can publish to Teams. Metering is often credits or messages on top of licences.",[221,641,642,645],{},[201,643,644],{},"Agent Builder."," Simple agents inside Copilot, grounded in Microsoft 365 content, for information workers.",[221,647,648,650],{},[201,649,249],{}," In Nimbus, a shared workspace for one job across systems that are not all Microsoft.",[221,652,653,655,656,659],{},[201,654,255],{}," Changing a live system. You ",[317,657,658],{},"can"," update Salesforce from Studio. The update is a flow-shaped side effect in Microsoft’s world. In Nimbus it is a quoted release with a named signer.",[221,661,662,664],{},[201,663,261],{}," The causal record of who approved, what changed, and what the next team should believe.",[221,666,667,670],{},[201,668,669],{},"E5."," Microsoft 365 E5 explains identity, compliance, and Office. It does not explain CRM write-back or a company work ledger.",[213,672,272],{"id":271},[189,674,675,676,678],{},"Studio agents that leave Graph for other connectors inherit a different permission story: connector logins, rules that stop sensitive files leaking, environment strategy. IT knows this is where Copilot programmes stall. You ",[317,677,658],{}," update Salesforce from Studio. The update is a flow-shaped side effect in Microsoft’s world. In Nimbus it is a quoted release with a named signer. Approvals in a Power Platform artefact are real. They are not a Lifecycle Graph of the job across departments.",[189,680,681,682,685,686,688],{},"In Nimbus, the scarce resource is control of work across systems that are not all Microsoft. The quarterly review deck may live in SharePoint. The opportunities live in Salesforce. The revenue number finance trusts may live in NetSuite. A ",[192,683,353],{"href":684},"\u002Fblog\u002Fwhat-is-an-ai-workstream\u002F"," puts those in one job. Records stay read-only until someone who is allowed to approve writes actually does. The ",[192,687,23],{"href":468}," keeps the release.",[189,690,691,694],{},[192,692,195],{"href":693},"\u002Fblog\u002Fnimbus-vs-glean\u002F","-class search and Copilot-class Graph grounding solve findability. Nimbus assumes you can already find the policy. The failure is that AI work does not land in a signed-off artefact. Purpose limitation is easier to explain when a recruiting workstream cannot see finance forecasts. A Copilot licence that sees “whatever this user can already open” is a different design — Microsoft’s Graph design, by intention. That design is correct inside Office. It is a wide blast radius if the same licence is treated as the operating model for every system the user can already open.",[189,696,697,698,701,702,705],{},"Lock-in is the honest trade. Copilot deepens Microsoft 365. Nimbus is lock-in of a different kind: the work loop and the graph. If most proprietary work is already in Microsoft, Copilot’s return is easier. If most money-moving systems are Salesforce, NetSuite, and specialist software, Copilot Studio becomes a connector project — and Nimbus was designed as that project plus the record. E5 explains identity, compliance, and Office. It does not explain CRM ",[192,699,700],{"href":291},"write-back",", choosing models across vendors, or a Lifecycle Graph. Standardise Copilot where Microsoft’s graph ",[317,703,704],{},"is"," the work. Standardise an operating layer where the business process is the work.",[189,707,708],{},"Role by role: a knowledge worker in Word, Excel, Outlook, and Teams wants the side pane — nobody else will recap the thread and the attached deck as well. IT owns Graph, licences, and often Studio as a Power Platform artefact: a helpdesk bot, an HR FAQ, a Teams helper. RevOps lives in Salesforce, not in SharePoint; a Studio connector to Salesforce is a flow-shaped side effect, not a company release. Finance trusts NetSuite, not the recap. Security will like Graph grounding and the privacy docs, and still ask who signed a CRM write. A CIO who already bought E5 should use Copilot where Microsoft’s graph is the work — and still not pretend E5 bought an operating layer.",[189,710,711],{},"SharePoint agents are Q&A on sites. Use them for findability. Do not use them as the operating model. Keep Copilot in Office. Put the job that leaves Microsoft in a workstream.",[213,713,715],{"id":714},"when-microsoft-copilot-is-a-better-fit","When Microsoft Copilot is a better fit",[189,717,718],{},"Choose Microsoft 365 Copilot when the job is knowledge-worker productivity in Word, Excel, Outlook, and Teams, and Microsoft’s own files and mail are the corpus.",[189,720,721],{},"Choose Copilot Studio when the agent is a Power Platform artefact IT will own — a helpdesk bot, an HR FAQ, a Teams helper. Metering is often credits or messages on top of licences; budget that as a Microsoft programme, not as a Nimbus substitute.",[189,723,724],{},"SharePoint agents are Q&A on sites. Use them for findability. Do not use them as the operating model.",[189,726,727],{},"Do not choose Copilot as a stealth operating layer for non-Microsoft systems. You will spend a year on connector reviews and still lack workstreams, specialist teams, and a Lifecycle Graph.",[189,729,730],{},"Keep Copilot in Office. Using Nimbus does not mean ripping it out. A coherent coexistence: Copilot for tenant productivity; Nimbus for jobs that also touch Salesforce, NetSuite, and the rest of the stack. Drafts can move from a recap into a workstream. Write credentials for money-moving systems should sit in Nimbus connector scopes, not in a Studio flow by default.",[213,732,333],{"id":332},[189,734,735,736,740,741,745],{},"Nimbus does not try to be the Word side pane. It does not assume the only intelligence in the company is whatever Microsoft licensed this quarter. See ",[192,737,739],{"href":738},"\u002Fmodels\u002F","models",". Routing includes not throwing the most powerful model at a simple lookup. Treat Microsoft-hosted models as infrastructure options in an enterprise conversation with ",[192,742,744],{"href":743},"\u002Fcontact\u002F","sales",", not as a reason Copilot and Nimbus are the same product.",[189,747,339,748,344,750,752,753,757],{},[192,749,343],{"href":342},[192,751,348],{"href":347}," are scoped per workspace. Agents get the systems you attached, in the mode you allowed, until a human releases a write. ",[192,754,756],{"href":755},"\u002Fproduct\u002Fagent-teams\u002F","Agent teams"," finish the work Copilot handed you after the recap.",[189,759,362,760,762],{},[192,761,366],{"href":365},". Copilot programmes at organisational scale are famous for implementation. Keep Copilot in Office; do not staff a consulting partner to invent an operating layer.",[189,764,370,765,378],{},[192,766,39],{"href":373},[213,768,382],{"id":381},[384,770,772],{"id":771},"does-nimbus-replace-microsoft-365-copilot","Does Nimbus replace Microsoft 365 Copilot?",[189,774,775],{},"No. Keep Copilot in Office. Nimbus does not try to be the Word side pane. It tries to be the place agent teams finish work that leaves Microsoft.",[384,777,779],{"id":778},"does-copilot-studio-replace-nimbus","Does Copilot Studio replace Nimbus?",[189,781,782],{},"Only if “a few Power Platform agents” is the entire AI programme. Studio can be shared inside the Microsoft tenant. It does not replace Nimbus as a governed execution layer with a company wiki and an operational ledger.",[384,784,786],{"id":785},"can-nimbus-use-azure-openai-or-microsoft-models","Can Nimbus use Azure OpenAI or Microsoft models?",[189,788,789,790,745],{},"Nimbus routes models for quality, cost, and latency — including not throwing the most powerful model at a simple lookup. Treat Microsoft-hosted models as infrastructure options in an enterprise conversation with ",[192,791,744],{"href":743},[384,793,795],{"id":794},"why-not-standardise-on-copilot-because-we-already-buy-microsoft-365-e5","Why not standardise on Copilot because we already buy Microsoft 365 E5?",[189,797,798,799,701,801,705],{},"E5 explains identity, compliance, and Office. It does not explain CRM ",[192,800,700],{"href":291},[317,802,704],{},[384,804,806],{"id":805},"do-we-need-a-microsoft-partner-to-get-nimbus-running","Do we need a Microsoft partner to get Nimbus running?",[189,808,809],{},"No. You can set it up yourselves. Copilot Studio at organisational scale usually is not self-serve in the same way.",[384,811,813],{"id":812},"can-we-keep-copilot-and-put-salesforce-writes-in-nimbus","Can we keep Copilot and put Salesforce writes in Nimbus?",[189,815,816],{},"Yes. That is the intended coexistence. Recap in Outlook; finish in a workstream. Do not let a Studio Salesforce connector become the unofficial write path “because we already had an approval step in the flow.” Quote the change, name the signer, store the outcome.",[384,818,444],{"id":443},[189,820,821,822,825],{},"IT typically owns Microsoft 365 Copilot and Studio: licences, Graph, Power Platform environments. Line operators own Nimbus workstreams that touch Salesforce, NetSuite, and specialist systems. Security reviews Graph grounding ",[317,823,824],{},"and"," write gates. A single “we already pay Microsoft” owner will stretch Copilot into an operating layer.",[384,827,829],{"id":828},"what-about-glean-if-we-already-have-copilot","What about Glean if we already have Copilot?",[189,831,832,833,378],{},"Copilot respects Microsoft permissions inside Microsoft. Glean searches across many apps, including Microsoft, and respects source permissions. You may still need Glean if SharePoint search is not enough, and still need Nimbus if neither is an operating layer. See ",[192,834,835],{"href":693},"Nimbus vs Glean",[213,837,458],{"id":457},[189,839,840,465,842,465,845,470,849,378],{},[192,841,592],{"href":591},[192,843,844],{"href":291},"What is write-back governance",[192,846,848],{"href":847},"\u002Fblog\u002Fwhat-is-an-enterprise-ai-operating-system\u002F","What is an enterprise AI operating system",[192,850,835],{"href":693},[213,852,476],{"id":475},[218,854,855,859,864,869],{},[221,856,857],{},[192,858,580],{"href":579},[221,860,861],{},[192,862,863],{"href":607},"Microsoft 365 Copilot privacy",[221,865,866],{},[192,867,868],{"href":602},"Microsoft 365 Copilot architecture",[221,870,871],{},[192,872,873],{"href":586},"Microsoft Copilot Studio",{"title":169,"searchDepth":170,"depth":170,"links":875},[876,877,878,879,880,890,891],{"id":215,"depth":170,"text":216},{"id":271,"depth":170,"text":272},{"id":714,"depth":170,"text":715},{"id":332,"depth":170,"text":333},{"id":381,"depth":170,"text":382,"children":881},[882,883,884,885,886,887,888,889],{"id":771,"depth":507,"text":772},{"id":778,"depth":507,"text":779},{"id":785,"depth":507,"text":786},{"id":794,"depth":507,"text":795},{"id":805,"depth":507,"text":806},{"id":812,"depth":507,"text":813},{"id":443,"depth":507,"text":444},{"id":828,"depth":507,"text":829},{"id":457,"depth":170,"text":458},{"id":475,"depth":170,"text":476},"Microsoft 365 Copilot lives in Word, Outlook, and Teams; Nimbus is for jobs that also touch Salesforce, NetSuite, and the rest of the business.",{"eyebrow":520,"title":894},"Inside Office, or across the company",[896,899,902],{"question":897,"answer":898},"Where does Microsoft 365 Copilot live?","In Word, Outlook, and Teams. It is strong where the work already sits in Microsoft 365.",{"question":900,"answer":901},"When is that not enough?","When the job also touches Salesforce, NetSuite, or anything else outside that suite.",{"question":903,"answer":904},"Do we replace Copilot?","No. Keep it for Office work. Use Nimbus for the job that has to leave Microsoft and still have a signer.","\u002Fblog\u002Fnimbus-vs-microsoft-copilot",{"title":566,"description":892},"blog\u002Fnimbus-vs-microsoft-copilot",[534,909,910,911,912],"microsoft-copilot","copilot-studio","m365","enterprise-ai","wOEE0tFNw3fpqNYUAVE31zDiChOKd5i0BdiFV9cFPyo",{"id":915,"title":916,"archived":163,"authors":917,"badge":919,"body":921,"date":517,"definedTerm":1185,"department":164,"description":1186,"extension":172,"eyebrow":164,"faqHeader":1187,"faqs":1189,"footerBand":164,"headline":164,"image":164,"industry":164,"jobType":164,"listed":131,"location":164,"navigation":131,"openRoles":164,"pageLayout":164,"path":1199,"relatedHeading":164,"seo":1200,"series":1201,"sitemap":131,"status":164,"stem":1202,"subhead":164,"tags":1203,"video":164,"whyJoin":164,"workplaceType":164,"__hash__":1205},"content\u002Fblog\u002Fmultiplayer-ai-and-multi-agent-ai.md","Multiplayer AI vs multi-agent AI: what is the difference?",[918],{"name":184,"to":185},{"label":920},"Explainer",{"type":166,"value":922,"toc":1177},[923,926,929,936,940,946,959,972,976,979,982,985,988,996,1000,1003,1006,1009,1012,1023,1031,1035,1038,1041,1052,1055,1063,1066,1070,1073,1076,1093,1103,1111,1114,1118,1121,1139,1149,1156,1159],[189,924,925],{},"Multiplayer AI is people and AI on the same job at the same time. Multi-agent AI is more than one model handing work to another. They are not the same product, and they fail in different places. You can have both — several models staffing steps inside one shared room — but buying a swarm is not the same as buying a room.",[189,927,928],{},"You should care if a demo shows agents passing tickets to each other and you still cannot name who would refuse a write to a live system. This is a useful distinction, not a verdict on agent platforms. Plenty of teams will keep specialists for retrieval or checks. The question is whether people still share the job.",[189,930,931,935],{},[192,932,934],{"href":933},"\u002Fblog\u002Fwhat-is-multi-agent-ai\u002F","What is multi-agent AI"," is the cast-of-models definition. This page keeps that word apart from multiplayer: people and AI on the same job at the same time.",[213,937,939],{"id":938},"what-is-multiplayer-ai","What is multiplayer AI?",[189,941,942,945],{},[201,943,944],{},"Multiplayer AI"," is people and AI sharing one job at the same time: the same brief, the same files, and a named person who can refuse a change. The unit is the job, not the chat thread and not the model. Two departments can open the same work, see the same draft, and leave a record when someone says no.",[189,947,948,949,953,954,958],{},"That is different from giving the team one login to a personal assistant. It is also different from ",[192,950,952],{"href":951},"\u002Fblog\u002Fwhat-is-collaborative-ai\u002F","collaborative AI",", which stresses the shared job after the session ends. Multiplayer answers who is in the room now. Collaborative AI answers whether the outcome still has a home tomorrow. You usually want both. ",[192,955,957],{"href":956},"\u002Fblog\u002Fhow-to-evaluate-collaborative-ai\u002F","How to evaluate collaborative AI"," is the buying sheet for the shared-job side.",[189,960,961,962,966,967,971],{},"If the work does not depend on any one agent still being around — because the files, the decision, and the signer live on the job — that is ",[192,963,965],{"href":964},"\u002Fblog\u002Fagents-should-be-disposable\u002F","agents should be disposable",". If several people can see the job but nobody can stop a write, you have a room without a door. ",[192,968,970],{"href":969},"\u002Fblog\u002Fgovernance-as-a-multiplayer-primitive\u002F","Governance as a multiplayer primitive"," is that door.",[213,973,975],{"id":974},"what-is-the-difference-between-multiplayer-ai-and-multi-agent-ai","What is the difference between multiplayer AI and multi-agent AI?",[189,977,978],{},"Multiplayer answers: who is in the room, what they can see, and who can halt a change. The unit is the job. Finance and sales can open the same brief while the model drafts.",[189,980,981],{},"Multi-agent answers: how work is split between models. One specialist retrieves. Another drafts. A third “reviews.” The unit is the graph — the sequence of model calls.",[189,983,984],{},"A simple check: if you remove every extra model and two departments still cannot share the files and the stop, you never had multiplayer. If you remove the second human and the run still completes in private, you had a personal tool with extra model calls.",[189,986,987],{},"Write-back is when AI changes a live system. In a multiplayer setup, one job holds one payload — the exact change — and a named signer. In a multi-agent setup, several writers can exist unless you bind them to that same stop. Fail-closed means if nobody approves, nothing happens. That rule belongs to a person on the roster, not to the orchestrator.",[189,989,990,991,995],{},"McKinsey’s ",[192,992,994],{"href":993},"https:\u002F\u002Fwww.mckinsey.com\u002Fcapabilities\u002Fquantumblack\u002Four-insights\u002Fthe-state-of-ai","State of AI"," (2025) found that most organisations using AI are still piloting. A common pilot is either one copilot or a small agent demo. Neither automatically creates a shared job.",[213,997,999],{"id":998},"why-does-that-distinction-matter","Why does that distinction matter?",[189,1001,1002],{},"It matters when something goes out wrong and you need a name.",[189,1004,1005],{},"In multiplayer AI, a named person owns the finish line: the model drafts, and a human on the roster signs or rejects. If the artefact is wrong, you can say who was on the job, including which AI role, and who was allowed to stop it.",[189,1007,1008],{},"In multi-agent AI, accountability is easy to lose. Each specialist did “its step.” The human who started the run may not have seen the intermediate draft. A log can show that agent B called agent C at 14:03. It does not show that finance agreed.",[189,1010,1011],{},"Orchestration decides sequence. Accountability is a person with a duty who can refuse at the moment a live system is about to change. A node labelled “human review” is not a name until you can say whose name, on this job, for which class of write.",[189,1013,1014,1018,1019,1022],{},[192,1015,1017],{"href":1016},"\u002Fblog\u002Frbac-for-enterprise-ai\u002F","RBAC for enterprise AI"," is that list. ",[192,1020,1021],{"href":291},"Write-back governance"," is the companion for the write itself.",[189,1024,1025,1026,1030],{},"The harness — the tools, stops, and checks around the model — is how a cast of specialists stays bounded. ",[192,1027,1029],{"href":1028},"\u002Fblog\u002Fwhat-is-harness-engineering\u002F","Harness engineering"," is the guide to that environment.",[213,1032,1034],{"id":1033},"when-do-you-need-several-people-versus-several-models","When do you need several people versus several models?",[189,1036,1037],{},"You need several people when more than one owner must stand on the result, or when a handover will happen, or when a customer-facing sentence can leave.",[189,1039,1040],{},"You need several models when the hand-off already exists between human roles and you want a narrower tool for each step. Useful examples:",[218,1042,1043,1046,1049],{},[221,1044,1045],{},"A research pass that must not share an identity with the agent drafting customer email.",[221,1047,1048],{},"A finance check that should not be able to send mail, even by accident.",[221,1050,1051],{},"A long retrieval over many files that a person will then judge on the job.",[189,1053,1054],{},"Separation of duties is the useful idea. The specialist that recommends a CRM update is not the principal that executes it. Multiplayer AI still puts a human on the execute step.",[189,1056,1057,1058,1062],{},"You do not need a swarm to summarise your own notes. That is a ",[192,1059,1061],{"href":1060},"\u002Fblog\u002Fcollaborative-ai-and-personal-assistants\u002F","personal assistant",". You do not need a second department on a private brainstorm. You do need both people and a stop when the output can change CRM, a journal, or a message a customer will keep.",[189,1064,1065],{},"A disagreement is a good test. Sales’ specialist wants to send. Legal’s specialist wants to hold. If the orchestrator averages them, or picks the last speaker, you do not have a stop. You have a race. Multiplayer AI makes the human with the duty the one who decides.",[213,1067,1069],{"id":1068},"how-do-you-talk-about-this-with-a-vendor","How do you talk about this with a vendor?",[189,1071,1072],{},"Ask to see the room and the cast as two demos, not one slide.",[189,1074,1075],{},"Useful questions:",[218,1077,1078,1081,1084,1087,1090],{},[221,1079,1080],{},"Can a second department join live, see the same brief, and reject a proposal?",[221,1082,1083],{},"If we remove the person who started the run, can someone else still refuse a write?",[221,1085,1086],{},"When two specialists disagree, who decides — a person with a name, or the graph?",[221,1088,1089],{},"Can we open the intermediate draft tomorrow, including a stored no?",[221,1091,1092],{},"Is the write identity a named human role, or a shared service credential?",[189,1094,1095,1099,1100,1102],{},[192,1096,1098],{"href":1097},"\u002Fblog\u002Fwhat-auditors-are-asking-for\u002F","What auditors are asking for"," is the evidence cut. A common first rule is: do not give the swarm a production write token so the demo looks complete. ",[192,1101,1021],{"href":291}," is that checklist.",[189,1104,1105,1106,1110],{},"Stanford HAI’s ",[192,1107,1109],{"href":1108},"https:\u002F\u002Fhai.stanford.edu\u002Fai-index","AI Index"," (2025) tracks adoption, investment, and incident reporting. Incident stories are easier to learn from when you can name the job and the signer, not only the model family.",[189,1112,1113],{},"If the vendor can only show a happy path of agents completing a ticket, ask for a specialist disagreement and a human rejection. That is a fair request. You may still buy the swarm for staffing. You will know whether you also bought a workplace.",[213,1115,1117],{"id":1116},"how-do-you-start-without-buying-a-new-stack","How do you start without buying a new stack?",[189,1119,1120],{},"Bind what you already have to one job.",[1122,1123,1124,1127,1130,1133,1136],"ol",{},[221,1125,1126],{},"Pick a recurring job that already has two owners (a weekly exception, a clause check, a forecast update).",[221,1128,1129],{},"Put the brief and two files in one place those people can both open.",[221,1131,1132],{},"If you already run specialists, let them draft into that place. Keep the intermediate draft visible.",[221,1134,1135],{},"Name who can sign a write. Keep the connection read-only until that name exists.",[221,1137,1138],{},"After two cycles, ask: did we fail because we needed another model, or because the second person could not see the file?",[189,1140,1141,1142,604,1145,1148],{},"Nimbus’s ",[192,1143,1144],{"href":352},"workstreams",[192,1146,1147],{"href":373},"governance"," are one attempt at that shape. You can start with a shared folder, a ticket, and a written stop if that is what you have.",[189,1150,1151,1155],{},[192,1152,1154],{"href":1153},"\u002Fblog\u002Fnimbus-vs-paperclip\u002F","Nimbus vs Paperclip"," is a vendor-shaped version of the same cut: governing what agents do inside one platform is not the same as two departments finishing a signed forecast in your CRM.",[189,1157,1158],{},"Keep the words apart because they help you buy the right next thing. Multiplayer is the room. Multi-agent is the cast. Adding to the cast is a staffing decision. The room is what owns the result.",[189,1160,1161,1162,1166,1167,1171,1172,1176],{},"Three companion pages stay with this. ",[192,1163,1165],{"href":1164},"\u002Fblog\u002Fsolo-ai-vs-multiplayer-ai\u002F","The shift from solo AI to multiplayer AI"," is the private chat against the shared room. ",[192,1168,1170],{"href":1169},"\u002Fblog\u002Fthe-shared-canvas-for-human-ai-teams\u002F","Designing collaborative canvas interfaces"," is the interface. ",[192,1173,1175],{"href":1174},"\u002Fblog\u002Fshared-state-when-the-teammate-is-a-model\u002F","Real-time sync for AI teammates"," is the state layer under the document.",{"title":169,"searchDepth":170,"depth":170,"links":1178},[1179,1180,1181,1182,1183,1184],{"id":938,"depth":170,"text":939},{"id":974,"depth":170,"text":975},{"id":998,"depth":170,"text":999},{"id":1033,"depth":170,"text":1034},{"id":1068,"depth":170,"text":1069},{"id":1116,"depth":170,"text":1117},"multiplayer AI","Multiplayer AI is people and AI on one job.",{"eyebrow":520,"title":1188},"People in the room, or models in a loop?",[1190,1193,1196],{"question":1191,"answer":1192},"Can we have both multiplayer AI and multi-agent AI?","Yes. Several models can staff steps on one shared job. The distinction is whether people share the job, not how many models you run.",{"question":1194,"answer":1195},"Does more agents mean more accountability?","Not by itself. Accountability is a named person who can refuse a change. Extra models without that name make the trail harder to read.",{"question":1197,"answer":1198},"Is a human-in-the-loop node enough?","Only if you can say whose name, on this job, for which class of write. A node labelled “review” is not a roster until it is a person.","\u002Fblog\u002Fmultiplayer-ai-and-multi-agent-ai",{"title":916,"description":1186},"explainer","blog\u002Fmultiplayer-ai-and-multi-agent-ai",[1201,1185,1204],"multi-agent AI","08lVinpdcx6mR1jgdFZQHubw8U_mudvfB4-z7VOPC24",{"enabled":163,"message":1207,"linkLabel":79,"linkHref":80,"id":1208,"title":1209,"archived":163,"authors":164,"badge":164,"body":1210,"date":164,"definedTerm":164,"department":164,"description":169,"extension":172,"eyebrow":164,"faqHeader":164,"faqs":164,"footerBand":164,"headline":164,"image":164,"industry":164,"jobType":164,"listed":131,"location":164,"navigation":131,"openRoles":164,"pageLayout":164,"path":1214,"relatedHeading":164,"seo":1215,"series":164,"sitemap":163,"status":164,"stem":1216,"subhead":164,"tags":164,"video":164,"whyJoin":164,"workplaceType":164,"__hash__":1217},"We're hiring! Join the team building the Sentient Enterprise.","content\u002Fshared\u002Fhiring.md","Hiring banner",{"type":166,"value":1211,"toc":1212},[],{"title":169,"searchDepth":170,"depth":170,"links":1213},[],"\u002Fshared\u002Fhiring",{"title":1209,"description":169},"shared\u002Fhiring","1zs3boivKda1e-b-hAyuNcmZSKjZUAXmecnwHVgcHzk",{"fold":1219,"id":1223,"title":1224,"archived":163,"authors":164,"badge":164,"body":1225,"date":164,"definedTerm":164,"department":164,"description":169,"extension":172,"eyebrow":164,"faqHeader":164,"faqs":164,"footerBand":1229,"headline":164,"image":164,"industry":164,"jobType":164,"listed":131,"location":164,"navigation":131,"openRoles":164,"pageLayout":164,"path":1233,"relatedHeading":164,"seo":1234,"series":164,"sitemap":163,"status":164,"stem":1235,"subhead":164,"tags":164,"video":164,"whyJoin":164,"workplaceType":164,"__hash__":1236},{"headline":1220,"description":1221,"primaryLabel":8,"primaryTo":1222,"secondaryLabel":558,"secondaryTo":12},"Run frontier AI your business actually owns.","Governed workstreams, 3,000+ integrations, and a proprietary knowledge graph. Start on Free.","\u002Fsignup?plan=free","content\u002Fshared\u002Fcta.md","Site CTAs",{"type":166,"value":1226,"toc":1227},[],{"title":169,"searchDepth":170,"depth":170,"links":1228},[],{"headline":1230,"description":1231,"primaryLabel":8,"primaryTo":1222,"secondaryLabel":1232,"secondaryTo":85},"See what governed AI looks like on your stack.","Connect your tools, run a workstream, and keep every decision on your ledger. Start on Free.","Talk to our team","\u002Fshared\u002Fcta",{"title":1224,"description":169},"shared\u002Fcta","eYqahyaPnbp8GKrWpoORbZdtmkWmgHr5F61ZHOnb8sY",1792999485693]