[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"sanity-tDnTtc-586upxEtueViJ3l4OGumYIqU0K8k673qvRo4":3},{"data":4,"sourceMap":-1},{"meta":5,"resource":1706},{"navigation":6,"sidebarCta":1703},[7,608,945,1237],{"category":8,"children":30},{"_createdAt":9,"_id":10,"_rev":11,"_type":12,"_updatedAt":13,"description":14,"slug":26,"title":29},"2023-12-15T07:48:26Z","ece32b3e-5ee5-4c3a-ac4a-d4755589db88","V4QUz6N4dC6YqomOXxeO57","resourceCategory","2023-12-22T09:37:11Z",[15],{"_key":16,"_type":17,"children":18,"markDefs":24,"style":25},"d80a3b7e8d24","block",[19],{"_key":20,"_type":21,"marks":22,"text":23},"e5e62b01ddc30","span",[],"Learn best practices and insights for better knowledge sharing, collaboration, and upskilling.",[],"normal",{"_type":27,"current":28},"slug","productivity","Productivity",[31,356,490],{"_createdAt":32,"_id":33,"_rev":34,"_type":35,"_updatedAt":36,"description":37,"resources":46,"slug":355,"title":67},"2023-12-15T07:41:58Z","0ca51bf8-d32c-48e1-8efa-348a85a48be6","dpQ2IysUm09sCEUZjQNSh4","resourceSubcategory","2023-12-15T10:25:20Z",[38],{"_key":39,"_type":17,"children":40,"markDefs":45,"style":25},"d95d27c4d401",[41],{"_key":42,"_type":21,"marks":43,"text":44},"1dbf7b77457b",[],"Best practices and insights for better knowledge sharing.",[],[47,69,86,103,120,137,154,171,188,205,222,239,256,273,289,306,322,339],{"image":48,"link":53,"preface":54,"publishedAt":55,"slug":56,"subcategory":58,"title":68},{"_type":49,"asset":50},"image",{"_ref":51,"_type":52},"image-da6d5e7dbb60d45e09576d349130b902786bd9ba-1200x630-png","reference",null,"Knowledge management (KM) is crucial for enterprises to capture, store, and access institutional knowledge, leading to increased productivity, better collaboration, and improved onboarding. A robust KM system relies on a centralized, validated knowledge base and must offer key features like Content Health checks, SME designation, and deep integrations with developer tools. When selecting a platform, such as Stack Internal or its competitors, prioritize solutions that are easy to adopt and promote continuous knowledge sharing and accuracy through community validation and gamification.","2025-11-30T13:04:00.000Z",{"_type":27,"current":57},"how-to-select-the-best-knowledge-management-software",{"_createdAt":32,"_id":33,"_rev":34,"_type":35,"_updatedAt":36,"description":59,"slug":65,"title":67},[60],{"_key":39,"_type":17,"children":61,"markDefs":64,"style":25},[62],{"_key":42,"_type":21,"marks":63,"text":44},[],[],{"_type":27,"current":66},"knowledge-sharing","Knowledge Sharing","How to select the best knowledge management software",{"image":70,"link":53,"preface":73,"publishedAt":74,"slug":75,"subcategory":77,"title":85},{"_type":49,"asset":71},{"_ref":72,"_type":52},"image-bf814ca3ecc58ae2000f7724ee8448db8e42cf5e-1200x630-png","Learn how leveraging your organization's internal knowledge can lead to more streamlined collaboration, enhanced knowledge distribution, and improved operational efficiency.","2025-08-06T08:47:00.000Z",{"_type":27,"current":76},"how-centralized-knowledge-base-helps-deliver-more-business-value",{"_createdAt":32,"_id":33,"_rev":34,"_type":35,"_updatedAt":36,"description":78,"slug":84,"title":67},[79],{"_key":39,"_type":17,"children":80,"markDefs":83,"style":25},[81],{"_key":42,"_type":21,"marks":82,"text":44},[],[],{"_type":27,"current":66},"How a centralized knowledge base helps your organization deliver more business value",{"image":87,"link":53,"preface":90,"publishedAt":91,"slug":92,"subcategory":94,"title":102},{"_type":49,"asset":88},{"_ref":89,"_type":52},"image-ff0d7f58bfd81858a059afe6b5fa3e5ae20b3186-2400x1260-png","Because technology is constantly changing, your knowledge base needs to change, too. ","2024-12-09T19:33:04.409Z",{"_type":27,"current":93},"how-to-keep-your-knowledge-base-up-to-date",{"_createdAt":32,"_id":33,"_rev":34,"_type":35,"_updatedAt":36,"description":95,"slug":101,"title":67},[96],{"_key":39,"_type":17,"children":97,"markDefs":100,"style":25},[98],{"_key":42,"_type":21,"marks":99,"text":44},[],[],{"_type":27,"current":66},"How to keep your knowledge base up-to-date",{"image":104,"link":53,"preface":107,"publishedAt":108,"slug":109,"subcategory":111,"title":119},{"_type":49,"asset":105},{"_ref":106,"_type":52},"image-e75ae24f1d0aa77005b5d8dcdfb1443114b17d5d-1200x630-png","This article covers standard operating procedures (SOP) and their impact on productivity, along with a free SOP template.","2024-10-09T16:09:59.022Z",{"_type":27,"current":110},"standard-operating-procedure",{"_createdAt":32,"_id":33,"_rev":34,"_type":35,"_updatedAt":36,"description":112,"slug":118,"title":67},[113],{"_key":39,"_type":17,"children":114,"markDefs":117,"style":25},[115],{"_key":42,"_type":21,"marks":116,"text":44},[],[],{"_type":27,"current":66},"How to write a standard operating procedure",{"image":121,"link":53,"preface":124,"publishedAt":125,"slug":126,"subcategory":128,"title":136},{"_type":49,"asset":122},{"_ref":123,"_type":52},"image-b717c137ec77f73a82a914936013902ed0ac9a77-1200x630-png","Technical debt might be the most widely relatable problem in software engineering. We collected ideas for paying it down and then keeping it at bay, with special attention to how this world is changing in the era of GenAI.","2024-09-23T16:27:36.969Z",{"_type":27,"current":127},"prevent-reduce-tech-debt",{"_createdAt":32,"_id":33,"_rev":34,"_type":35,"_updatedAt":36,"description":129,"slug":135,"title":67},[130],{"_key":39,"_type":17,"children":131,"markDefs":134,"style":25},[132],{"_key":42,"_type":21,"marks":133,"text":44},[],[],{"_type":27,"current":66},"10 tips to reduce and prevent tech debt",{"image":138,"link":53,"preface":141,"publishedAt":142,"slug":143,"subcategory":145,"title":153},{"_type":49,"asset":139},{"_ref":140,"_type":52},"image-4b14134e6575791ee0dd6101ed3cbe3ddde5ea58-1200x630-png","Even with the assistance of GenAI-powered coding tools, developers still struggle to find answers to their questions without interrupting their workflows or wasting time with rework. ","2024-08-14T14:20:50.625Z",{"_type":27,"current":144},"your-developers-deserve-better-insights-from-the-2024-developer-survey",{"_createdAt":32,"_id":33,"_rev":34,"_type":35,"_updatedAt":36,"description":146,"slug":152,"title":67},[147],{"_key":39,"_type":17,"children":148,"markDefs":151,"style":25},[149],{"_key":42,"_type":21,"marks":150,"text":44},[],[],{"_type":27,"current":66},"Your developers deserve better: Insights from the 2024 Developer Survey",{"image":155,"link":53,"preface":158,"publishedAt":159,"slug":160,"subcategory":162,"title":170},{"_type":49,"asset":156},{"_ref":157,"_type":52},"image-60dc33eb9da7469b002fd42c7aa0213702fb56e7-2400x1260-png","Knowledge sharing is a critical aspect of both organizational and personal growth.","2024-02-16T09:40:09.857Z",{"_type":27,"current":161},"empowering-teams-unleashing-the-power-of-knowledge-sharing",{"_createdAt":32,"_id":33,"_rev":34,"_type":35,"_updatedAt":36,"description":163,"slug":169,"title":67},[164],{"_key":39,"_type":17,"children":165,"markDefs":168,"style":25},[166],{"_key":42,"_type":21,"marks":167,"text":44},[],[],{"_type":27,"current":66},"Empowering teams: Unleashing the power of knowledge sharing",{"image":172,"link":53,"preface":175,"publishedAt":176,"slug":177,"subcategory":179,"title":187},{"_type":49,"asset":173},{"_ref":174,"_type":52},"image-e5f880431edbff01c46624bf53d49806a8f37ead-2400x1260-png","Discover the key insights for crafting the perfect knowledge base article.","2023-12-19T15:26:45.289Z",{"_type":27,"current":178},"create-effective-knowledge-base-articles",{"_createdAt":32,"_id":33,"_rev":34,"_type":35,"_updatedAt":36,"description":180,"slug":186,"title":67},[181],{"_key":39,"_type":17,"children":182,"markDefs":185,"style":25},[183],{"_key":42,"_type":21,"marks":184,"text":44},[],[],{"_type":27,"current":66},"How to create effective knowledge base articles ",{"image":189,"link":53,"preface":192,"publishedAt":193,"slug":194,"subcategory":196,"title":204},{"_type":49,"asset":190},{"_ref":191,"_type":52},"image-175107111dea829b50e5e180613d6154342413f9-1200x630-png","In this article, we’ll tell you everything you need to know about internal knowledge bases, from what they are and why they’re important to how you can set up your internal knowledge base and start reaping the benefits of knowledge sharing.","2023-12-19T14:22:21.119Z",{"_type":27,"current":195},"internal-knowledge-bases",{"_createdAt":32,"_id":33,"_rev":34,"_type":35,"_updatedAt":36,"description":197,"slug":203,"title":67},[198],{"_key":39,"_type":17,"children":199,"markDefs":202,"style":25},[200],{"_key":42,"_type":21,"marks":201,"text":44},[],[],{"_type":27,"current":66},"Everything you need to know about internal knowledge bases",{"image":206,"link":53,"preface":209,"publishedAt":210,"slug":211,"subcategory":213,"title":221},{"_type":49,"asset":207},{"_ref":208,"_type":52},"image-eaf3ba32b32a664acdea298476a4e2ad9fcdb8d7-1200x630-png","This article will help you understand what a knowledge base is; how to build, grow, and maintain it; and the transformative impact it can have on your organization.","2023-12-15T10:11:33.217Z",{"_type":27,"current":212},"knowledge-base-101",{"_createdAt":32,"_id":33,"_rev":34,"_type":35,"_updatedAt":36,"description":214,"slug":220,"title":67},[215],{"_key":39,"_type":17,"children":216,"markDefs":219,"style":25},[217],{"_key":42,"_type":21,"marks":218,"text":44},[],[],{"_type":27,"current":66},"Knowledge base 101: Building a foundation for knowledge management",{"image":223,"link":53,"preface":226,"publishedAt":227,"slug":228,"subcategory":230,"title":238},{"_type":49,"asset":224},{"_ref":225,"_type":52},"image-81443a036d390bbf513fe9fb7864142aa56dc2cb-1200x630-png","To tackle burnout challenges, enhancing knowledge management workflows is crucial. Applying Agile methodologies can alleviate gridlock and friction for developers.","2023-03-10T21:05:00.000Z",{"_type":27,"current":229},"applying-agile-to-engineering-knowledge-management",{"_createdAt":32,"_id":33,"_rev":34,"_type":35,"_updatedAt":36,"description":231,"slug":237,"title":67},[232],{"_key":39,"_type":17,"children":233,"markDefs":236,"style":25},[234],{"_key":42,"_type":21,"marks":235,"text":44},[],[],{"_type":27,"current":66},"Applying agile to engineering knowledge management: practical tips and takeaways",{"image":240,"link":53,"preface":243,"publishedAt":244,"slug":245,"subcategory":247,"title":255},{"_type":49,"asset":241},{"_ref":242,"_type":52},"image-de24b2d5c84019d229e37c741db6ae3ac48da55e-2000x1500-png","A guide to help companies develop collaborative, knowledge-sharing cultures to help them thrive in a volatile workplace landscape.","2022-08-18T14:00:00.000Z",{"_type":27,"current":246},"best-practices-for-knowledge-sharing",{"_createdAt":32,"_id":33,"_rev":34,"_type":35,"_updatedAt":36,"description":248,"slug":254,"title":67},[249],{"_key":39,"_type":17,"children":250,"markDefs":253,"style":25},[251],{"_key":42,"_type":21,"marks":252,"text":44},[],[],{"_type":27,"current":66},"Break down silos and foster collaboration: Best practices for knowledge sharing",{"image":257,"link":53,"preface":260,"publishedAt":261,"slug":262,"subcategory":264,"title":272},{"_type":49,"asset":258},{"_ref":259,"_type":52},"image-a419d4ef110b76dea73ca301794742c893a87413-1200x630-png","The insights, tools, and metrics you need for sustainable knowledge management","2022-05-10T12:30:48+0000",{"_type":27,"current":263},"craft-a-knowledge-management-strategy",{"_createdAt":32,"_id":33,"_rev":34,"_type":35,"_updatedAt":36,"description":265,"slug":271,"title":67},[266],{"_key":39,"_type":17,"children":267,"markDefs":270,"style":25},[268],{"_key":42,"_type":21,"marks":269,"text":44},[],[],{"_type":27,"current":66},"Craft a knowledge management strategy",{"image":274,"link":53,"preface":276,"publishedAt":277,"slug":278,"subcategory":280,"title":288},{"_type":49,"asset":275},{"_ref":225,"_type":52},"We posed this question to our Sales Engineers and they came back with some great insights","2022-02-14T14:10:48+0000",{"_type":27,"current":279},"we-posed-this-question-to-our-sales-engineers-and-they",{"_createdAt":32,"_id":33,"_rev":34,"_type":35,"_updatedAt":36,"description":281,"slug":287,"title":67},[282],{"_key":39,"_type":17,"children":283,"markDefs":286,"style":25},[284],{"_key":42,"_type":21,"marks":285,"text":44},[],[],{"_type":27,"current":66},"How does Stack Internal enable intelligent swarming?",{"image":290,"link":53,"preface":293,"publishedAt":294,"slug":295,"subcategory":297,"title":305},{"_type":49,"asset":291},{"_ref":292,"_type":52},"image-b32d0e5dd4d7e016050b0fb850058b17f847dad9-1200x630-png","What Innovative Organizations and Highly Productive Engineering Teams Have in Common: High Knowledge Reuse","2021-04-23T18:42:05+0000",{"_type":27,"current":296},"knowledge-reuse-examples",{"_createdAt":32,"_id":33,"_rev":34,"_type":35,"_updatedAt":36,"description":298,"slug":304,"title":67},[299],{"_key":39,"_type":17,"children":300,"markDefs":303,"style":25},[301],{"_key":42,"_type":21,"marks":302,"text":44},[],[],{"_type":27,"current":66},"How highly productive teams use knowledge reuse",{"image":307,"link":53,"preface":309,"publishedAt":310,"slug":311,"subcategory":313,"title":321},{"_type":49,"asset":308},{"_ref":259,"_type":52},"Knowledge reuse is a recycling process; an individual or group reuses knowledge gained and shared by someone else.","2021-04-23T16:39:55+0000",{"_type":27,"current":312},"what-is-knowledge-reuse",{"_createdAt":32,"_id":33,"_rev":34,"_type":35,"_updatedAt":36,"description":314,"slug":320,"title":67},[315],{"_key":39,"_type":17,"children":316,"markDefs":319,"style":25},[317],{"_key":42,"_type":21,"marks":318,"text":44},[],[],{"_type":27,"current":66},"What is knowledge reuse?",{"image":323,"link":53,"preface":326,"publishedAt":327,"slug":328,"subcategory":330,"title":338},{"_type":49,"asset":324},{"_ref":325,"_type":52},"image-b2bba0c747c7251f6456335f00ce2b83222e0c27-1200x628-png","What can a knowledge management system do for your organization","2021-04-14T15:27:30+0000",{"_type":27,"current":329},"adopt-a-knowledge-management-system",{"_createdAt":32,"_id":33,"_rev":34,"_type":35,"_updatedAt":36,"description":331,"slug":337,"title":67},[332],{"_key":39,"_type":17,"children":333,"markDefs":336,"style":25},[334],{"_key":42,"_type":21,"marks":335,"text":44},[],[],{"_type":27,"current":66},"Adopt a knowledge management system for your organization",{"image":340,"link":53,"preface":342,"publishedAt":343,"slug":344,"subcategory":346,"title":354},{"_type":49,"asset":341},{"_ref":325,"_type":52},"Learn the basics of knowledge management systems","2021-04-14T15:06:24+0000",{"_type":27,"current":345},"increase-your-knowledge-of-knowledge-management",{"_createdAt":32,"_id":33,"_rev":34,"_type":35,"_updatedAt":36,"description":347,"slug":353,"title":67},[348],{"_key":39,"_type":17,"children":349,"markDefs":352,"style":25},[350],{"_key":42,"_type":21,"marks":351,"text":44},[],[],{"_type":27,"current":66},"The basics of knowledge sharing & knowledge management systems",{"_type":27,"current":66},{"_createdAt":357,"_id":358,"_rev":359,"_type":35,"_updatedAt":360,"description":361,"resources":370,"slug":489,"title":388},"2023-12-15T07:43:47Z","93c0f227-6380-4d69-b339-e7f29df44aec","28Ey2N6aiyTS8vMpxYnsT9","2023-12-19T08:26:00Z",[362],{"_key":363,"_type":17,"children":364,"markDefs":369,"style":25},"9dac58718383",[365],{"_key":366,"_type":21,"marks":367,"text":368},"88accedbff31",[],"Best practices and insights for better collaboration.",[],[371,390,407,424,441,458,475],{"image":372,"link":53,"preface":375,"publishedAt":376,"slug":377,"subcategory":379,"title":389},{"_type":49,"asset":373},{"_ref":374,"_type":52},"image-ce49b2ce43e031907044cc4b70d8c86d1aba6144-1200x630-png","In this article, we’ll explore the benefits of an async workstyle and explain how to collaborate seamlessly across time zones and locations, drive productivity by letting employees work how they want, and offer top-tier talent the flexibility they value above anything else (even salary). ","2024-01-24T15:19:00.000Z",{"_type":27,"current":378},"collaborate-anytime-anywhere",{"_createdAt":357,"_id":358,"_rev":359,"_type":35,"_updatedAt":360,"description":380,"slug":386,"title":388},[381],{"_key":363,"_type":17,"children":382,"markDefs":385,"style":25},[383],{"_key":366,"_type":21,"marks":384,"text":368},[],[],{"_type":27,"current":387},"collaboration","Collaboration","Collaborate anytime, anywhere: Embracing asynchronous communication",{"image":391,"link":53,"preface":394,"publishedAt":395,"slug":396,"subcategory":398,"title":406},{"_type":49,"asset":392},{"_ref":393,"_type":52},"image-355724e82b69639ddf22554b2dcf5488a34602c6-1200x630-png","What’s your true productivity story? A 5-step framework for engineering managers, team leaders, and executives.\n","2022-08-18T14:47:57.685Z",{"_type":27,"current":397},"protect-your-engineering-teams-brainpower",{"_createdAt":357,"_id":358,"_rev":359,"_type":35,"_updatedAt":360,"description":399,"slug":405,"title":388},[400],{"_key":363,"_type":17,"children":401,"markDefs":404,"style":25},[402],{"_key":366,"_type":21,"marks":403,"text":368},[],[],{"_type":27,"current":387},"Protect your engineering team’s brainpower",{"image":408,"link":53,"preface":411,"publishedAt":412,"slug":413,"subcategory":415,"title":423},{"_type":49,"asset":409},{"_ref":410,"_type":52},"image-9986cbcaa7042e422b4a947d5725ce2545100bac-1200x630-png","Too many notifications and other workday distractions can knock a productive day right off the rails. Here are three of the most common developer distractions to look out for—and some tips for how to banish them from your daily routine.","2022-07-19T17:55:00.000Z",{"_type":27,"current":414},"reclaim-your-flow-state",{"_createdAt":357,"_id":358,"_rev":359,"_type":35,"_updatedAt":360,"description":416,"slug":422,"title":388},[417],{"_key":363,"_type":17,"children":418,"markDefs":421,"style":25},[419],{"_key":366,"_type":21,"marks":420,"text":368},[],[],{"_type":27,"current":387},"Reclaim your flow state: 3 developer distractions to eliminate ",{"image":425,"link":53,"preface":428,"publishedAt":429,"slug":430,"subcategory":432,"title":440},{"_type":49,"asset":426},{"_ref":427,"_type":52},"image-75dfd777d162b3df6c67ac60d7c84c3ac10a8a3f-1200x627-png","How knowledge sharing helps organizations follow the Three Ways of DevOps","2022-06-28T13:46:30.600Z",{"_type":27,"current":431},"devops-handbook-companion-guide",{"_createdAt":357,"_id":358,"_rev":359,"_type":35,"_updatedAt":360,"description":433,"slug":439,"title":388},[434],{"_key":363,"_type":17,"children":435,"markDefs":438,"style":25},[436],{"_key":366,"_type":21,"marks":437,"text":368},[],[],{"_type":27,"current":387},"The DevOps Handbook Companion Guide",{"image":442,"link":53,"preface":445,"publishedAt":446,"slug":447,"subcategory":449,"title":457},{"_type":49,"asset":443},{"_ref":444,"_type":52},"image-83b37a0d3cab0f24492b9d6f4733aefb93b15038-1280x720-jpg","We sat down with acclaimed author Gene Kim to discuss the second edition of the DevOps Handbook","2022-04-27T18:37:42+0000",{"_type":27,"current":448},"ama-with-gene-kim-devops-handbook",{"_createdAt":357,"_id":358,"_rev":359,"_type":35,"_updatedAt":360,"description":450,"slug":456,"title":388},[451],{"_key":363,"_type":17,"children":452,"markDefs":455,"style":25},[453],{"_key":366,"_type":21,"marks":454,"text":368},[],[],{"_type":27,"current":387},"Highlights from our AMA with Gene Kim, co-author of The DevOps Handbook",{"image":459,"link":53,"preface":462,"publishedAt":463,"slug":464,"subcategory":466,"title":474},{"_type":49,"asset":460},{"_ref":461,"_type":52},"image-08477964984a1fb7144149e9cada3ea90545f264-1200x630-png","A great DX provides the right tools and technologies for your team’s success, removes productivity blockers, and helps new team members jumpstart their contributions.","2022-02-07T15:32:00.000Z",{"_type":27,"current":465},"invest-in-developer-experience",{"_createdAt":357,"_id":358,"_rev":359,"_type":35,"_updatedAt":360,"description":467,"slug":473,"title":388},[468],{"_key":363,"_type":17,"children":469,"markDefs":472,"style":25},[470],{"_key":366,"_type":21,"marks":471,"text":368},[],[],{"_type":27,"current":387},"Invest in developer experience (DX) to empower your team’s best work",{"image":53,"link":53,"preface":476,"publishedAt":477,"slug":478,"subcategory":480,"title":488},"If you aren't familiar with Low-Context DevOps, watch this free 27-minute on-demand webinar.","2020-06-15T17:36:49+0000",{"_type":27,"current":479},"low-context-devops",{"_createdAt":357,"_id":358,"_rev":359,"_type":35,"_updatedAt":360,"description":481,"slug":487,"title":388},[482],{"_key":363,"_type":17,"children":483,"markDefs":486,"style":25},[484],{"_key":366,"_type":21,"marks":485,"text":368},[],[],{"_type":27,"current":387},"Low context DevOps: Helping DevOps find answers faster",{"_type":27,"current":387},{"_createdAt":491,"_id":492,"_rev":493,"_type":35,"_updatedAt":494,"description":495,"resources":504,"slug":607,"title":522},"2023-12-15T07:44:53Z","db58d08e-de3e-449e-86cd-b8454bcd6887","dpQ2IysUm09sCEUZjWemJ2","2023-12-20T07:18:22Z",[496],{"_key":497,"_type":17,"children":498,"markDefs":503,"style":25},"ac376eb6c861",[499],{"_key":500,"_type":21,"marks":501,"text":502},"bef969d5edd3",[],"Best practices and insights for better upskilling.",[],[505,524,541,558,573,590],{"image":506,"link":53,"preface":509,"publishedAt":510,"slug":511,"subcategory":513,"title":523},{"_type":49,"asset":507},{"_ref":508,"_type":52},"image-5c9c8741432dfb3f44511fabb973e93c6f26331e-1200x630-png","Learning is the foundation of successful, resilient teams. Here’s how leaders can make learning a core part of company culture.","2022-08-16T14:20:48.141Z",{"_type":27,"current":512},"prioritize-learning",{"_createdAt":491,"_id":492,"_rev":493,"_type":35,"_updatedAt":494,"description":514,"slug":520,"title":522},[515],{"_key":497,"_type":17,"children":516,"markDefs":519,"style":25},[517],{"_key":500,"_type":21,"marks":518,"text":502},[],[],{"_type":27,"current":521},"upskilling","Upskilling","Want resilient, high-performing development teams? Prioritize learning.",{"image":525,"link":53,"preface":528,"publishedAt":529,"slug":530,"subcategory":532,"title":540},{"_type":49,"asset":526},{"_ref":527,"_type":52},"image-a174d3f59ca6349e4eae2cc9507391603549a691-1200x848-jpg","Creating a team structure that balances a few key subject-matter experts with a broader pool of generalists can help establish a seamless workflow.","2022-08-15T16:09:00.000Z",{"_type":27,"current":531},"managing-effective-teams-choosing-the-right-mix-of-generalists-and-specialists",{"_createdAt":491,"_id":492,"_rev":493,"_type":35,"_updatedAt":494,"description":533,"slug":539,"title":522},[534],{"_key":497,"_type":17,"children":535,"markDefs":538,"style":25},[536],{"_key":500,"_type":21,"marks":537,"text":502},[],[],{"_type":27,"current":521},"Managing effective teams: Choosing the right mix of generalists and specialists",{"image":542,"link":53,"preface":545,"publishedAt":546,"slug":547,"subcategory":549,"title":557},{"_type":49,"asset":543},{"_ref":544,"_type":52},"image-4afe9b9217a331fa82bd414a2699b12226ef0257-1200x628-png","In this eBook, we will show you how to reduce the skill gap in your developer teams through upskilling and reskilling.","2022-04-04T14:20:00.000Z",{"_type":27,"current":548},"in-this-ebook-we-will-show-you-how-to-reduce-the-skill",{"_createdAt":491,"_id":492,"_rev":493,"_type":35,"_updatedAt":494,"description":550,"slug":556,"title":522},[551],{"_key":497,"_type":17,"children":552,"markDefs":555,"style":25},[553],{"_key":500,"_type":21,"marks":554,"text":502},[],[],{"_type":27,"current":521},"Reducing the developer skill gap through upskilling and reskilling",{"image":559,"link":53,"preface":560,"publishedAt":561,"slug":562,"subcategory":564,"title":572},{"_type":49},"Listen to a recap of the Q&A we had with our guest, Katy Tynan, Principal Analyst at Forrester.","2022-03-01T14:28:47+0000",{"_type":27,"current":563},"how-to-build-a-learning-culture-within-an-agile-organization",{"_createdAt":491,"_id":492,"_rev":493,"_type":35,"_updatedAt":494,"description":565,"slug":571,"title":522},[566],{"_key":497,"_type":17,"children":567,"markDefs":570,"style":25},[568],{"_key":500,"_type":21,"marks":569,"text":502},[],[],{"_type":27,"current":521},"How to build a learning culture within an Agile organization: A Q&A with our guest, Katy Tynan, Principal Analyst at Forrester",{"image":574,"link":53,"preface":577,"publishedAt":578,"slug":579,"subcategory":581,"title":589},{"_type":49,"asset":575},{"_ref":576,"_type":52},"image-74ccf334246b6b3beadd13c94f599589174a6b97-1200x1200-png","This eBook will show you how to reduce the skill gap by creating an upskilling and reskilling program for your teams via the Agile learning process.","2021-09-02T14:19:00.000Z",{"_type":27,"current":580},"how-developer-teams-can-use-agile-learning-to-close",{"_createdAt":491,"_id":492,"_rev":493,"_type":35,"_updatedAt":494,"description":582,"slug":588,"title":522},[583],{"_key":497,"_type":17,"children":584,"markDefs":587,"style":25},[585],{"_key":500,"_type":21,"marks":586,"text":502},[],[],{"_type":27,"current":521},"How developer teams can use Agile learning to close the skill gap",{"image":591,"link":53,"preface":594,"publishedAt":595,"slug":596,"subcategory":598,"title":606},{"_type":49,"asset":592},{"_ref":593,"_type":52},"image-19bd811c2d48278f62871f2bedb67e91e30c25c1-1200x630-png","This eBook will show you how to build an upskilling and reskilling culture with Stack Internal.","2021-08-25T20:22:53+0000",{"_type":27,"current":597},"building-an-upskilling-and-reskilling-culture-with",{"_createdAt":491,"_id":492,"_rev":493,"_type":35,"_updatedAt":494,"description":599,"slug":605,"title":522},[600],{"_key":497,"_type":17,"children":601,"markDefs":604,"style":25},[602],{"_key":500,"_type":21,"marks":603,"text":502},[],[],{"_type":27,"current":521},"Building an upskilling and reskilling culture with Stack Internal",{"_type":27,"current":521},{"category":609,"children":626},{"_createdAt":610,"_id":611,"_rev":612,"_type":12,"_updatedAt":613,"description":614,"slug":623,"title":625},"2023-12-15T07:48:58Z","ef0e02bc-df9c-4b7c-b754-59031956a409","V4QUz6N4dC6YqomOXxeNhk","2023-12-22T09:37:07Z",[615],{"_key":616,"_type":17,"children":617,"markDefs":622,"style":25},"3b813b0feaaa",[618],{"_key":619,"_type":21,"marks":620,"text":621},"19247c5330ab0",[],"Get AI industry insights and learn how to effectively leverage AI in your organization.",[],{"_type":27,"current":624},"ai","AI\u002FML",[627,745,861],{"_createdAt":628,"_id":629,"_rev":630,"_type":35,"_updatedAt":631,"resources":632,"slug":744,"title":641},"2024-05-23T14:36:12Z","24a526f4-a1cb-4327-b323-54d10b6b3736","PLUpFbYpTCZBjS13wRt5jp","2024-05-23T14:38:37Z",[633,643,655,667,678,689,700,711,722,733],{"image":53,"link":53,"preface":634,"publishedAt":635,"slug":636,"subcategory":638,"title":642},"Learn what an AI context layer does, how it differs from a wiki, when your team needs one, and what engineering leaders should look for when evaluating one.","2026-09-25T17:00:00.000Z",{"_type":27,"current":637},"what-is-an-ai-context-layer",{"_createdAt":628,"_id":629,"_rev":630,"_type":35,"_updatedAt":631,"slug":639,"title":641},{"_type":27,"current":640},"stack-overflow-ai","Stack Overflow + AI","What Is an AI Context layer? A plain-English guide for engineering leaders",{"image":644,"link":53,"preface":648,"publishedAt":649,"slug":650,"subcategory":652,"title":654},{"_type":49,"alt":645,"asset":646},"Stack Overflow Business interface demonstrating knowledge sourced from multiple platforms, enhanced with trust signals and expert validation.",{"_ref":647,"_type":52},"image-22381c316132daf6573ce8a6cc4829303ee1a1de-1200x630-png","In this article, we’ll walk through each stage of building a production-grade knowledge pipeline: capture, validate, organize, govern, and deliver. We’ll get real about what each stage actually costs to build and maintain, so you can make clear-eyed decisions about where your engineering capacity is best spent.","2026-07-31T16:00:00.000Z",{"_type":27,"current":651},"the-trap-of-building-in-house-why-context-infrastructure-is-harder-than-it-looks",{"_createdAt":628,"_id":629,"_rev":630,"_type":35,"_updatedAt":631,"slug":653,"title":641},{"_type":27,"current":640},"The trap of building in-house: Why context infrastructure is harder than it looks",{"image":656,"link":53,"preface":660,"publishedAt":661,"slug":662,"subcategory":664,"title":666},{"_type":49,"alt":657,"asset":658},"Stack Internal product screenshot demonstrating a 'trusted knowledge layer' through UI ",{"_ref":659,"_type":52},"image-7e54f9938576b10b70476fea3933f2025dfd5662-1200x630-png","Stack Internal transforms your daily work into a living memory that’s shared with the rest of your team. Now anyone can create and share their knowledge in a Stack Internal workspace for free by visiting stackinternal.com. ","2026-07-30T15:19:07.767Z",{"_type":27,"current":663},"anyone-can-start-building-verified-knowledge-with-stack-internal",{"_createdAt":628,"_id":629,"_rev":630,"_type":35,"_updatedAt":631,"slug":665,"title":641},{"_type":27,"current":640},"Anyone can start building verified knowledge with Stack Internal",{"image":668,"link":53,"preface":671,"publishedAt":672,"slug":673,"subcategory":675,"title":677},{"_type":49,"asset":669},{"_ref":670,"_type":52},"image-4451b8eba01eca7c5c385c0978b2d7a1e955ec36-1200x630-png","AI agents need more than generic intelligence: They require deep, verified internal context to make decisions that align with your organization's standards, architecture, and history.","2026-04-29T17:29:25.485Z",{"_type":27,"current":674},"agentic-ai-is-rewriting-the-software-development-playbook",{"_createdAt":628,"_id":629,"_rev":630,"_type":35,"_updatedAt":631,"slug":676,"title":641},{"_type":27,"current":640},"How agentic AI is rewriting the software development playbook",{"image":679,"link":53,"preface":682,"publishedAt":683,"slug":684,"subcategory":686,"title":688},{"_type":49,"asset":680},{"_ref":681,"_type":52},"image-a7cd1d8fa61db8a4fb8b80c5332a2502ef8b681f-1200x630-png","Learn the true costs of building a production-grade knowledge pipeline. We break down the ingest, convert, score, validate, and deliver stages to help you decide where to best commit your engineering capacity.","2026-04-29T00:54:21.693Z",{"_type":27,"current":685},"the-hidden-costs-of-building-an-internal-ai-context-layer",{"_createdAt":628,"_id":629,"_rev":630,"_type":35,"_updatedAt":631,"slug":687,"title":641},{"_type":27,"current":640},"The hidden costs of building an internal AI context layer",{"image":690,"link":53,"preface":693,"publishedAt":694,"slug":695,"subcategory":697,"title":699},{"_type":49,"asset":691},{"_ref":692,"_type":52},"image-8d8ae7a963ffa58e19151eec46f004b9b93baa27-2400x1260-png","AI models are only as good as the data they’re trained on, and many organizations are unknowingly feeding their models bad data.","2025-10-09T16:31:29.023Z",{"_type":27,"current":696},"don-t-let-bad-data-derail-your-ai-projects",{"_createdAt":628,"_id":629,"_rev":630,"_type":35,"_updatedAt":631,"slug":698,"title":641},{"_type":27,"current":640},"Don’t let bad data derail your AI projects",{"image":701,"link":53,"preface":704,"publishedAt":705,"slug":706,"subcategory":708,"title":710},{"_type":49,"asset":702},{"_ref":703,"_type":52},"image-7824871bbcd8ce9a135470a4f246df6cec66f7cb-1200x630-png","For developers, LLMs can answer questions, but they can't create new knowledge.","2024-10-29T18:25:09.069Z",{"_type":27,"current":707},"ai-answers-aren-t-knowledge",{"_createdAt":628,"_id":629,"_rev":630,"_type":35,"_updatedAt":631,"slug":709,"title":641},{"_type":27,"current":640},"AI answers aren’t knowledge",{"image":712,"link":53,"preface":715,"publishedAt":716,"slug":717,"subcategory":719,"title":721},{"_type":49,"asset":713},{"_ref":714,"_type":52},"image-fe81d295f9f32f71bb2eb0bd1f4f9492378256d2-2400x1260-png","The journey to functional AI maturity is not a linear one. Gauge your current capabilities and identify actionable next steps to get to the next stage in your AI journey with our AI Maturity Matrix.","2024-07-24T00:32:38.650Z",{"_type":27,"current":718},"ai-maturity-matrix",{"_createdAt":628,"_id":629,"_rev":630,"_type":35,"_updatedAt":631,"slug":720,"title":641},{"_type":27,"current":640},"Stack Overflow's AI Maturity Matrix",{"image":723,"link":53,"preface":726,"publishedAt":727,"slug":728,"subcategory":730,"title":732},{"_type":49,"asset":724},{"_ref":725,"_type":52},"image-dbee7e2f2fd2473d0fb26f79efdc8cfd19bc0697-1200x630-png","According to expert research, data quality is the most important factor that determines the performance of an LLM. And from our (admittedly biased) perspective, there’s no better method for organizing and optimizing your data than Stack Overflow for Teams. ","2024-04-30T18:45:45.647Z",{"_type":27,"current":729},"why-stack-overflow-for-teams-is-made-for-genai",{"_createdAt":628,"_id":629,"_rev":630,"_type":35,"_updatedAt":631,"slug":731,"title":641},{"_type":27,"current":640},"5 reasons why Stack Overflow for Teams is made for GenAI",{"image":734,"link":53,"preface":737,"publishedAt":738,"slug":739,"subcategory":741,"title":743},{"_type":49,"asset":735},{"_ref":736,"_type":52},"image-0668cac8ceefd7784ed6604524909400c5c88f5b-2400x1260-png","In this article, we’ll delve into the advantages and drawbacks of AI code generation tools.","2024-02-16T16:59:18.853Z",{"_type":27,"current":740},"better-together-getting-the-most-value-from-ai-code-generation-tools",{"_createdAt":628,"_id":629,"_rev":630,"_type":35,"_updatedAt":631,"slug":742,"title":641},{"_type":27,"current":640},"Better together: Getting the most value from AI code generation tools",{"_type":27,"current":640},{"_createdAt":746,"_id":747,"_rev":748,"_type":35,"_updatedAt":749,"resources":750,"slug":860,"title":762},"2023-12-20T13:14:02Z","c18a6a4e-32f6-4b21-ad23-67d6add15691","28Ey2N6aiyTS8vMpxi1iIF","2023-12-22T09:36:20Z",[751,764,772,783,794,805,816,827,838,849],{"image":752,"link":53,"preface":53,"publishedAt":756,"slug":757,"subcategory":759,"title":763},{"_type":49,"alt":753,"asset":754},"Stack Overflow graphic featuring the text: \"Why Your AI Almost Works: What the 2026 Developer Survey Says About Business Context.\"",{"_ref":755,"_type":52},"image-d2bb08a529b83c49eb83bcd298c014fbc2ccbbef-1200x630-png","2027-11-01T15:57:00.000Z",{"_type":27,"current":758},"2026-developer-survey-for-business-leaders",{"_createdAt":746,"_id":747,"_rev":748,"_type":35,"_updatedAt":749,"slug":760,"title":762},{"_type":27,"current":761},"ai-insights","AI Insights & Trends","What the 2026 Developer Survey says about business context",{"image":53,"link":53,"preface":765,"publishedAt":766,"slug":767,"subcategory":769,"title":771},"Devs don’t trust AI tools that don’t work. Community-validated data could change that.","2026-03-09T20:00:56.091Z",{"_type":27,"current":768},"why-community-validated-data-matters-more-than-ever",{"_createdAt":746,"_id":747,"_rev":748,"_type":35,"_updatedAt":749,"slug":770,"title":762},{"_type":27,"current":761},"Why community-validated data matters more than ever",{"image":773,"link":53,"preface":776,"publishedAt":777,"slug":778,"subcategory":780,"title":782},{"_type":49,"asset":774},{"_ref":775,"_type":52},"image-06c7e43d0662512e857a82bc99cfd261c888c06e-2160x1134-png","We’ve consolidated six key learnings from this year’s survey—what the data says, trends from year’s past, why it matters—along with actionable takeaways for business leaders in any organization.","2025-09-15T12:00:00.000Z",{"_type":27,"current":779},"2025-stack-overflow-developer-survey-for-leaders",{"_createdAt":746,"_id":747,"_rev":748,"_type":35,"_updatedAt":749,"slug":781,"title":762},{"_type":27,"current":761},"2025 Stack Overflow Developer Survey: A TL;DR for Leaders",{"image":784,"link":53,"preface":787,"publishedAt":788,"slug":789,"subcategory":791,"title":793},{"_type":49,"asset":785},{"_ref":786,"_type":52},"image-f32aa79a5d44883638ea0c9217d2320de1a611ac-1200x630-png","Learn why the quality of your data is the primary factor influencing the success and ROI of your AI initiatives.","2025-05-05T22:03:50.719Z",{"_type":27,"current":790},"why-high-quality-data-is-essential-for-agentic-ai",{"_createdAt":746,"_id":747,"_rev":748,"_type":35,"_updatedAt":749,"slug":792,"title":762},{"_type":27,"current":761},"Why high-quality data is essential for agentic AI",{"image":795,"link":53,"preface":798,"publishedAt":799,"slug":800,"subcategory":802,"title":804},{"_type":49,"asset":796},{"_ref":797,"_type":52},"image-6214b2aca33d53ebd8928e77a773937a33b50f93-1200x630-png","In 2024, developers remain fractured when it comes to trust in AI.","2024-08-19T19:50:17.097Z",{"_type":27,"current":801},"your-developers-need-smarter-ai-tools",{"_createdAt":746,"_id":747,"_rev":748,"_type":35,"_updatedAt":749,"slug":803,"title":762},{"_type":27,"current":761},"Your developers need smarter AI tools",{"image":806,"link":53,"preface":809,"publishedAt":810,"slug":811,"subcategory":813,"title":815},{"_type":49,"asset":807},{"_ref":808,"_type":52},"image-47bb89190ff771b2c72a3fb1653d9d2a32ec69a7-2400x1256-png","Learn more about the 5 critical phases of AI adoption and discover the importance an enterprise-grade knowledge sharing platform plays in maximizing your chances for AI success.","2024-03-04T15:28:56.511Z",{"_type":27,"current":812},"gartner-ai-adoption-phases",{"_createdAt":746,"_id":747,"_rev":748,"_type":35,"_updatedAt":749,"slug":814,"title":762},{"_type":27,"current":761},"Become an AI-First Organization: 5 Critical AI Adoption Phases",{"image":817,"link":53,"preface":820,"publishedAt":821,"slug":822,"subcategory":824,"title":826},{"_type":49,"asset":818},{"_ref":819,"_type":52},"image-3d28ff509cec6f7c8910eb104cf602b921655f89-2400x1260-png","Knowledge-based systems are a crucial part of knowledge representation within AI. ","2023-11-03T16:45:28.702Z",{"_type":27,"current":823},"knowledge-based-system",{"_createdAt":746,"_id":747,"_rev":748,"_type":35,"_updatedAt":749,"slug":825,"title":762},{"_type":27,"current":761},"What is a knowledge-based system?",{"image":828,"link":53,"preface":831,"publishedAt":832,"slug":833,"subcategory":835,"title":837},{"_type":49,"asset":829},{"_ref":830,"_type":52},"image-ebc2ea186f537c9631f61f1e4a9ec2584d597029-2400x1260-png","Before you can dive into the details of what to do with the answers or art your GenAI is creating, you need a robust foundation to ensure it’s operating well. To help, we’ve come up with four key areas you’ll need to understand to make the most of the time and resources you invest. ","2023-10-11T16:59:34.585Z",{"_type":27,"current":834},"ai-hype-is-exhausting-here-are-four-things-that-matter-for-your-organization",{"_createdAt":746,"_id":747,"_rev":748,"_type":35,"_updatedAt":749,"slug":836,"title":762},{"_type":27,"current":761},"AI Hype is exhausting. Here are four things that matter for your organization.",{"image":839,"link":53,"preface":842,"publishedAt":843,"slug":844,"subcategory":846,"title":848},{"_type":49,"asset":840},{"_ref":841,"_type":52},"image-735ff6ebe15ff79bee64cfd6962b387623ece498-2400x1260-png","Organizations adopting GenAI face pressure, requiring executives to carefully manage security risks for safeguarding.","2023-10-10T18:39:13.480Z",{"_type":27,"current":845},"top-overlooked-genai-security-risks-for-businesses",{"_createdAt":746,"_id":747,"_rev":748,"_type":35,"_updatedAt":749,"slug":847,"title":762},{"_type":27,"current":761},"Top overlooked GenAI security risks for businesses",{"image":850,"link":53,"preface":853,"publishedAt":854,"slug":855,"subcategory":857,"title":859},{"_type":49,"asset":851},{"_ref":852,"_type":52},"image-042e81fc6d3b41389f45073bd785d18e3cecd3ab-1281x720-png","This webinar explores Stack Overflow's AI journey, sharing valuable lessons learned along the way.","2023-10-05T23:57:00.000Z",{"_type":27,"current":856},"stack-overflows-ai-journey-webinar",{"_createdAt":746,"_id":747,"_rev":748,"_type":35,"_updatedAt":749,"slug":858,"title":762},{"_type":27,"current":761},"Stack Overflow’s AI Journey: Lessons learned on the road to GenAI - from concept to reality",{"_type":27,"current":761},{"_createdAt":862,"_id":863,"_rev":864,"_type":35,"_updatedAt":862,"resources":865,"slug":944,"title":877},"2024-05-23T14:36:47Z","23d8b485-71d3-4c8f-9fe3-b543522948da","PLUpFbYpTCZBjS13wRsN5x",[866,879,889,900,911,922,933],{"image":867,"link":53,"preface":870,"publishedAt":871,"slug":872,"subcategory":874,"title":878},{"_type":49,"asset":868},{"_ref":869,"_type":52},"image-f8a7b306da2842407d4a7f0fe43ac8b79489c16b-2400x1260-png","Now that GenAI applications are top-of-mind across so many industries, we can see another set of benefits of a clean, centralized knowledge base: an opportunity for vastly improved AI training, leading to more powerful solutions and more satisfied users. ","2025-03-10T17:28:45.132Z",{"_type":27,"current":873},"how-your-knowledge-base-can-improve-ai-model-performance",{"_createdAt":862,"_id":863,"_rev":864,"_type":35,"_updatedAt":862,"slug":875,"title":877},{"_type":27,"current":876},"ai-tips-recommendations","AI Tips & Recommendations","How your knowledge base can improve AI model performance",{"image":880,"link":53,"preface":883,"publishedAt":91,"slug":884,"subcategory":886,"title":888},{"_type":49,"asset":881},{"_ref":882,"_type":52},"image-98abe953a93426b57885a310913d062a4c6cea9e-12000x6293-jpg","The landscape of artificial intelligence is evolving at an unprecedented pace, and data remains the central resource fueling its growth.",{"_type":27,"current":885},"get-your-data-house-in-order-preparing-for-a-future-with-ai",{"_createdAt":862,"_id":863,"_rev":864,"_type":35,"_updatedAt":862,"slug":887,"title":877},{"_type":27,"current":876},"Get your (data) house in order: Preparing for a future with AI",{"image":890,"link":53,"preface":893,"publishedAt":894,"slug":895,"subcategory":897,"title":899},{"_type":49,"asset":891},{"_ref":892,"_type":52},"image-c292cb557b89d1476beb6203260041e0e2e61f46-1200x630-png","In this article, we explore why it’s hard to evaluate the return on AI investments and how to identify metrics that can more accurately reflect ROI.","2024-07-17T16:33:58.586Z",{"_type":27,"current":896},"how-to-demonstrate-roi-for-your-genai-projects",{"_createdAt":862,"_id":863,"_rev":864,"_type":35,"_updatedAt":862,"slug":898,"title":877},{"_type":27,"current":876},"How to demonstrate ROI for your GenAI projects",{"image":901,"link":53,"preface":904,"publishedAt":905,"slug":906,"subcategory":908,"title":910},{"_type":49,"asset":902},{"_ref":903,"_type":52},"image-e89bfd863368149e21f60703683e808efb5f06e6-1200x630-png","In this article, we’ll explain what a CoP is, unpack why they’re so valuable for AI projects, and offer some practical tips for building one.","2024-04-12T17:31:07.598Z",{"_type":27,"current":907},"why-your-ai-project-needs-a-community-of-practice-and-how-to-build-one",{"_createdAt":862,"_id":863,"_rev":864,"_type":35,"_updatedAt":862,"slug":909,"title":877},{"_type":27,"current":876},"Why your AI project needs a community of practice and how to build one",{"image":912,"link":53,"preface":915,"publishedAt":916,"slug":917,"subcategory":919,"title":921},{"_type":49,"asset":913},{"_ref":914,"_type":52},"image-eb23abaa1827cdeacc2dcb1faaf111b8e122ffa4-1200x630-png","If you start building AI without a clear purpose and a clear definition of what you hope to gain out of it, your hard work may be for nothing.","2024-04-09T18:22:31.792Z",{"_type":27,"current":918},"how-to-set-goals-for-ai-initiatives",{"_createdAt":862,"_id":863,"_rev":864,"_type":35,"_updatedAt":862,"slug":920,"title":877},{"_type":27,"current":876},"How to set goals for AI initiatives",{"image":923,"link":53,"preface":926,"publishedAt":927,"slug":928,"subcategory":930,"title":932},{"_type":49,"asset":924},{"_ref":925,"_type":52},"image-ec4af220dc0e34ddb65a36d061fdb2eda6104206-2400x1260-png","Does it make sense for you to build your own GenAI model, buy a third-party solution out of the box, or use an open-source model as your foundation and tune it to your needs? ","2024-04-03T16:01:23.201Z",{"_type":27,"current":929},"build-buy-or-borrow-where-to-invest-your-genai-resources",{"_createdAt":862,"_id":863,"_rev":864,"_type":35,"_updatedAt":862,"slug":931,"title":877},{"_type":27,"current":876},"Build, buy, or borrow? Where to invest your GenAI resources",{"image":934,"link":53,"preface":937,"publishedAt":938,"slug":939,"subcategory":941,"title":943},{"_type":49,"asset":935},{"_ref":936,"_type":52},"image-22cdcb91782ed309d5292a7ff0cfca9998662ef0-2400x1260-png","Everybody wants to be an AI-first organization, but not everyone is quite sure what that means or what it requires.","2024-03-25T17:50:04.398Z",{"_type":27,"current":940},"practical-recommendations-for-ai-adoption-success",{"_createdAt":862,"_id":863,"_rev":864,"_type":35,"_updatedAt":862,"slug":942,"title":877},{"_type":27,"current":876},"From enthusiasm to execution: Practical recommendations for AI adoption success",{"_type":27,"current":876},{"category":946,"children":966},{"_createdAt":947,"_id":948,"_rev":949,"_system":950,"_type":12,"_updatedAt":953,"description":954,"slug":963,"title":965},"2023-12-15T07:49:22Z","e825d2a9-8466-4b9f-89f5-8451aee54b23","7O0oo7qM6iD0NUdEGlwVIT",{"base":951},{"id":948,"rev":952},"3vmxkk46kHuWSrwZ2KfCpt","2025-12-02T13:37:47Z",[955],{"_key":956,"_type":17,"children":957,"markDefs":962,"style":25},"b4c8edc0c090",[958],{"_key":959,"_type":21,"marks":960,"text":961},"4ebd8aa8fb060",[],"Explore Stack Overflow for Teams guides, demos, insights, and more.",[],{"_type":27,"current":964},"guides-insights","Guides and Insights",[967,1070,1217],{"_createdAt":968,"_id":969,"_rev":970,"_type":35,"_updatedAt":971,"description":972,"resources":981,"slug":1069,"title":1000},"2023-12-15T07:45:22Z","b17f083c-c5c3-454a-8637-a43266a16073","OiBIvEn2E80LUXPpAl7fu7","2024-01-05T11:33:15Z",[973],{"_key":974,"_type":17,"children":975,"markDefs":980,"style":25},"ebc305f70f93",[976],{"_key":977,"_type":21,"marks":978,"text":979},"eeaf853c8f940",[],"Explore Stack Overflow for Teams product guides.",[],[982,1002,1019,1036,1053],{"image":983,"link":53,"preface":987,"publishedAt":988,"slug":989,"subcategory":991,"title":1001},{"_type":49,"alt":984,"asset":985},"Screenshot of a \"Stack Internal\" chat interface with the text \"Get trusted answers\" and a large orange play button overlay.",{"_ref":986,"_type":52},"image-c82382b18206dc8900e6989bff59d2441ed7d73f-1200x630-png","See Stack Internal in action in this recorded product demo. ","2026-09-22T19:55:22.117Z",{"_type":27,"current":990},"recorded-product-demo",{"_createdAt":968,"_id":969,"_rev":970,"_type":35,"_updatedAt":971,"description":992,"slug":998,"title":1000},[993],{"_key":974,"_type":17,"children":994,"markDefs":997,"style":25},[995],{"_key":977,"_type":21,"marks":996,"text":979},[],[],{"_type":27,"current":999},"guides","Product Guides","Move Beyond Context: Give Your Teams and AI Verified Knowledge",{"image":1003,"link":53,"preface":1006,"publishedAt":1007,"slug":1008,"subcategory":1010,"title":1018},{"_type":49,"asset":1004},{"_ref":1005,"_type":52},"image-c74c9fb7b3cdb605ea25e40bdeb51b890d8aa9d6-2400x1260-png","Have a question about Stack Overflow Internal? Start here.","2024-03-13T16:55:01.651Z",{"_type":27,"current":1009},"faq",{"_createdAt":968,"_id":969,"_rev":970,"_type":35,"_updatedAt":971,"description":1011,"slug":1017,"title":1000},[1012],{"_key":974,"_type":17,"children":1013,"markDefs":1016,"style":25},[1014],{"_key":977,"_type":21,"marks":1015,"text":979},[],[],{"_type":27,"current":999},"Frequently asked questions",{"image":1020,"link":53,"preface":1023,"publishedAt":1024,"slug":1025,"subcategory":1027,"title":1035},{"_type":49,"asset":1021},{"_ref":1022,"_type":52},"image-9d94796a87461c00dd277b8ef8c5930d45f6a768-3919x2224-png","Communities strengthen collaboration, break down silos, and boost productivity. In our time developing and nurturing technical communities online at Stack Overflow, we’ve seen firsthand how people contribute and participate more when they feel a sense of belonging and responsibility to a community. These same principles can strengthen teams in your organization by introducing communities of practice.","2023-09-08T21:36:19.299Z",{"_type":27,"current":1026},"unlocking-the-business-value-of-communities-of-practice-webinar",{"_createdAt":968,"_id":969,"_rev":970,"_type":35,"_updatedAt":971,"description":1028,"slug":1034,"title":1000},[1029],{"_key":974,"_type":17,"children":1030,"markDefs":1033,"style":25},[1031],{"_key":977,"_type":21,"marks":1032,"text":979},[],[],{"_type":27,"current":999},"Unlocking the business value of Communities of Practice",{"image":1037,"link":53,"preface":1040,"publishedAt":1041,"slug":1042,"subcategory":1044,"title":1052},{"_type":49,"asset":1038},{"_ref":1039,"_type":52},"image-e92eacc42e4d3d868408a7df430d25b1a1c394a8-1200x673-png","The ebook will explore why organizations use Stack Internal in addition to Stack Overflow's public platform. ","2022-03-18T17:31:12+0000",{"_type":27,"current":1043},"why-do-we-need-stack-overflow-for-teams",{"_createdAt":968,"_id":969,"_rev":970,"_type":35,"_updatedAt":971,"description":1045,"slug":1051,"title":1000},[1046],{"_key":974,"_type":17,"children":1047,"markDefs":1050,"style":25},[1048],{"_key":977,"_type":21,"marks":1049,"text":979},[],[],{"_type":27,"current":999},"We already use Stack Overflow's public site. Why do we need Stack Internal?",{"image":1054,"link":53,"preface":1056,"publishedAt":1057,"slug":1058,"subcategory":1060,"title":1068},{"_type":49,"asset":1055},{"_ref":508,"_type":52},"The ebook will explore how companies improve best practices in each of the six phases of the Software Development Lifecycle with the help of Stack Internal","2021-10-21T19:31:53+0000",{"_type":27,"current":1059},"stack-overflow-for-teams-at-every-stage-of-the-software",{"_createdAt":968,"_id":969,"_rev":970,"_type":35,"_updatedAt":971,"description":1061,"slug":1067,"title":1000},[1062],{"_key":974,"_type":17,"children":1063,"markDefs":1066,"style":25},[1064],{"_key":977,"_type":21,"marks":1065,"text":979},[],[],{"_type":27,"current":999},"Stack Internal at every stage of the Software Development Lifecycle",{"_type":27,"current":999},{"_createdAt":1071,"_id":1072,"_rev":1073,"_type":35,"_updatedAt":1074,"description":1075,"resources":1084,"slug":1216,"title":1102},"2023-12-15T07:46:29Z","a86ae02f-25b7-442b-aa0b-cce4b1ca6719","dpQ2IysUm09sCEUZjaUnEj","2023-12-22T09:36:56Z",[1076],{"_key":1077,"_type":17,"children":1078,"markDefs":1083,"style":25},"1d9197d72d14",[1079],{"_key":1080,"_type":21,"marks":1081,"text":1082},"bd25c0557beb",[],"Explore Stack Overflow for Teams use cases.",[],[1085,1104,1120,1134,1151,1168,1185,1202],{"image":1086,"link":53,"preface":1089,"publishedAt":1090,"slug":1091,"subcategory":1093,"title":1103},{"_type":49,"asset":1087},{"_ref":1088,"_type":52},"image-5671b202f6b1a81abac537aeb2d0ca707e740e35-1200x630-png","Our bidirectional MCP server connects trusted Stack Internal knowledge to the IDE, LLM, or agent platform of your choice. This guide provides examples of prompts that we hope will help make your next big project and team handoff a breeze.","2025-12-18T10:10:00.000-05:00",{"_type":27,"current":1092},"search-and-curate-trusted-knowledge-with-the-stack-internal-mcp-server",{"_createdAt":1071,"_id":1072,"_rev":1073,"_type":35,"_updatedAt":1074,"description":1094,"slug":1100,"title":1102},[1095],{"_key":1077,"_type":17,"children":1096,"markDefs":1099,"style":25},[1097],{"_key":1080,"_type":21,"marks":1098,"text":1082},[],[],{"_type":27,"current":1101},"use-cases","Use Cases","Guide: Search and curate trusted knowledge in flow with the Stack Internal MCP server",{"image":1105,"link":53,"preface":1107,"publishedAt":1108,"slug":1109,"subcategory":1111,"title":1119},{"_type":49,"asset":1106},{"_ref":508,"_type":52},"Learn how to use Stack Internal to minimize blockers and achieve milestones faster during your next digital transformation initiative.","2023-06-27T00:44:00.000Z",{"_type":27,"current":1110},"accelerate-your-digital-transformation-guide",{"_createdAt":1071,"_id":1072,"_rev":1073,"_type":35,"_updatedAt":1074,"description":1112,"slug":1118,"title":1102},[1113],{"_key":1077,"_type":17,"children":1114,"markDefs":1117,"style":25},[1115],{"_key":1080,"_type":21,"marks":1116,"text":1082},[],[],{"_type":27,"current":1101},"Use case guide: Accelerate your digital transformation",{"image":53,"link":53,"preface":1121,"publishedAt":1122,"slug":1123,"subcategory":1125,"title":1133},"With a dedicated knowledge hub used by both technical and business teams, Stack Internal empowers an empathetic, high-touch sales process.","2023-02-06T22:56:43.167Z",{"_type":27,"current":1124},"how-sales-engineers-stay-in-sync",{"_createdAt":1071,"_id":1072,"_rev":1073,"_type":35,"_updatedAt":1074,"description":1126,"slug":1132,"title":1102},[1127],{"_key":1077,"_type":17,"children":1128,"markDefs":1131,"style":25},[1129],{"_key":1080,"_type":21,"marks":1130,"text":1082},[],[],{"_type":27,"current":1101},"How Stack Overflow’s sales engineers stay in sync during complex deal cycles",{"image":1135,"link":53,"preface":1138,"publishedAt":1139,"slug":1140,"subcategory":1142,"title":1150},{"_type":49,"asset":1136},{"_ref":1137,"_type":52},"image-f8457c1a051a6b304d78e62875c02976f2b20180-1200x630-png","Using our own solution, Stack Internal, we tap into the power of community-driven knowledge sharing for optimal situational agility.","2023-02-03T18:08:25.796Z",{"_type":27,"current":1141},"how-stack-overflows-product-support-team-resolves-tickets",{"_createdAt":1071,"_id":1072,"_rev":1073,"_type":35,"_updatedAt":1074,"description":1143,"slug":1149,"title":1102},[1144],{"_key":1077,"_type":17,"children":1145,"markDefs":1148,"style":25},[1146],{"_key":1080,"_type":21,"marks":1147,"text":1082},[],[],{"_type":27,"current":1101},"How Stack Overflow’s product support team resolves tickets in minutes rather than weeks",{"image":1152,"link":53,"preface":1155,"publishedAt":1156,"slug":1157,"subcategory":1159,"title":1167},{"_type":49,"asset":1153},{"_ref":1154,"_type":52},"image-aa417ac4822ff7d0626a8804f1725bf63e8c6fdb-2268x1272-png","Learn how to use an internal developer portal to enhance developer productivity and happiness.","2022-08-26T18:30:00.000Z",{"_type":27,"current":1158},"backstage-internal-developer-portal-webinar",{"_createdAt":1071,"_id":1072,"_rev":1073,"_type":35,"_updatedAt":1074,"description":1160,"slug":1166,"title":1102},[1161],{"_key":1077,"_type":17,"children":1162,"markDefs":1165,"style":25},[1163],{"_key":1080,"_type":21,"marks":1164,"text":1082},[],[],{"_type":27,"current":1101},"Webinar: Using developer portals to enhance developer happiness (and productivity)",{"image":1169,"link":53,"preface":1172,"publishedAt":1173,"slug":1174,"subcategory":1176,"title":1184},{"_type":49,"asset":1170},{"_ref":1171,"_type":52},"image-501e265e2eb83e1b2922471dc864c05f52fe5f78-1630x601-png","Bringing in any new platform or tool takes some pre-work. Following these steps to build the case for Stack Internal makes it easier to show the value it will bring to your team and organization.","2022-06-27T14:10:10.099Z",{"_type":27,"current":1175},"bringing-stack-overflow-for-teams-into-your-organization",{"_createdAt":1071,"_id":1072,"_rev":1073,"_type":35,"_updatedAt":1074,"description":1177,"slug":1183,"title":1102},[1178],{"_key":1077,"_type":17,"children":1179,"markDefs":1182,"style":25},[1180],{"_key":1080,"_type":21,"marks":1181,"text":1082},[],[],{"_type":27,"current":1101},"Bringing Stack Internal into your organization",{"image":1186,"link":53,"preface":1189,"publishedAt":1190,"slug":1191,"subcategory":1193,"title":1201},{"_type":49,"asset":1187},{"_ref":1188,"_type":52},"image-c36aa1882fbe8efa305e8baaff1457d4a80d78e1-1280x720-png","Hear how Progressive Insurance visualizes their Stack Internal data to reveal cross team collaboration","2021-12-10T19:16:07+0000",{"_type":27,"current":1192},"making-the-invisible-visible-with-progressive-insurance",{"_createdAt":1071,"_id":1072,"_rev":1073,"_type":35,"_updatedAt":1074,"description":1194,"slug":1200,"title":1102},[1195],{"_key":1077,"_type":17,"children":1196,"markDefs":1199,"style":25},[1197],{"_key":1080,"_type":21,"marks":1198,"text":1082},[],[],{"_type":27,"current":1101},"Making the Invisible, Visible with Progressive Insurance",{"image":53,"link":53,"preface":1203,"publishedAt":1204,"slug":1205,"subcategory":1207,"title":1215},"Expensify is a company of generalists with loosely organized teams. To support this, they have an internal value called #writeitdown that encourages everyone to create scalable and accessible knowledge trails for others - technical and non-technical. Join Lauren Reid and Stephanie Elliott from Expensify and Tanya Helin from Stack Overflow as they discuss the benefits of this type of culture and how Stack Internal enables it.","2021-08-10T13:14:28+0000",{"_type":27,"current":1206},"writeitdown-culture-bridges-the-gap",{"_createdAt":1071,"_id":1072,"_rev":1073,"_type":35,"_updatedAt":1074,"description":1208,"slug":1214,"title":1102},[1209],{"_key":1077,"_type":17,"children":1210,"markDefs":1213,"style":25},[1211],{"_key":1080,"_type":21,"marks":1212,"text":1082},[],[],{"_type":27,"current":1101},"How a #WriteItDown culture bridges the gap between technical and non-technical roles",{"_type":27,"current":1101},{"_createdAt":1218,"_id":1219,"_rev":1220,"_type":35,"_updatedAt":1221,"resources":1222,"slug":1236,"title":1234},"2025-12-15T10:29:11Z","513d033a-0f92-4b20-a2de-94a15401d17f","Y9U97RKQ35bjCtSlBNuk69","2025-12-15T10:29:19Z",[1223],{"image":1224,"link":53,"preface":1227,"publishedAt":1228,"slug":1229,"subcategory":1231,"title":1235},{"_type":49,"asset":1225},{"_ref":1226,"_type":52},"image-3b920779e08111524e1935809e658a602a450ad1-2400x1260-png","In this on-demand webinar, discover how Stack Internal can improve the trust, quality, and output of your AI.","2025-12-10T10:30:00.000-08:00",{"_type":27,"current":1230},"build-smarter-ai-with-trusted-internal-knowledge",{"_createdAt":1218,"_id":1219,"_rev":1220,"_type":35,"_updatedAt":1221,"slug":1232,"title":1234},{"_type":27,"current":1233},"webinars","Webinars","Build smarter AI with trusted internal knowledge",{"_type":27,"current":1233},{"category":1238,"children":1258},{"_createdAt":1239,"_id":1240,"_rev":1241,"_system":1242,"_type":12,"_updatedAt":1245,"description":1246,"slug":1255,"title":1257},"2023-12-15T07:50:02Z","8e415c68-bdae-450d-abda-a7b330bdf9cb","66bNz0mmUxbMe9OZ0bbNam",{"base":1243},{"id":1240,"rev":1244},"28Ey2N6aiyTS8vMpxi1lTp","2025-11-18T13:56:17Z",[1247],{"_key":1248,"_type":17,"children":1249,"markDefs":1254,"style":25},"a5377ba125bf",[1250],{"_key":1251,"_type":21,"marks":1252,"text":1253},"14ea9c9d9f0a0",[],"A place for Stack Internal admins and end-users to learn tips and best practices.",[],{"_type":27,"current":1256},"academy","Customer Academy",[1259,1410,1628],{"_createdAt":1260,"_id":1261,"_rev":1262,"_type":35,"_updatedAt":1263,"resources":1264,"slug":1409,"title":1276},"2023-12-15T07:52:51Z","344cca18-3f8c-46aa-8731-643e594f7048","ejz6Pq3OnBuSEtH3SncBv8","2024-02-06T12:24:36Z",[1265,1278,1289,1300,1311,1321,1332,1343,1354,1365,1376,1387,1398],{"image":1266,"link":53,"preface":1269,"publishedAt":1270,"slug":1271,"subcategory":1273,"title":1277},{"_type":49,"asset":1267},{"_ref":1268,"_type":52},"image-9862ecb5a61326024cb9534d5e1833571cc3d130-2400x1261-png","Being a moderator for Stack Overflow for Teams is a unique and multifaceted role that requires a diverse set of skills and responsibilities. As an online community platform designed to facilitate knowledge sharing and problem-solving, Stack Overflow for Teams relies heavily on its moderators to maintain the community.","2024-09-10T10:24:50.232Z",{"_type":27,"current":1272},"day-in-the-life-teams-mod",{"_createdAt":1260,"_id":1261,"_rev":1262,"_type":35,"_updatedAt":1263,"slug":1274,"title":1276},{"_type":27,"current":1275},"get-started","Get Started","A day in the life of a Stack Overflow for Teams Moderator",{"image":1279,"link":53,"preface":1282,"publishedAt":1283,"slug":1284,"subcategory":1286,"title":1288},{"_type":49,"asset":1280},{"_ref":1281,"_type":52},"image-fd292ab0f27d29b0af7e48bec35b0dde73e31c05-1200x630-png","You may be familiar with Stack Overflow or have even found the answer to a question amongst the thousands of answers from millions of developers and technical experts across the globe. But if you're scratching your head because you’re not familiar with Stack Internal and are wondering how it can be a resource as you tackle your day-to-day responsibilities, there's no need to fret - we’ve got you covered with this super simple user guide.","2023-10-24T16:17:00.000Z",{"_type":27,"current":1285},"how-to-use-stack-overflow-for-teams",{"_createdAt":1260,"_id":1261,"_rev":1262,"_type":35,"_updatedAt":1263,"slug":1287,"title":1276},{"_type":27,"current":1275},"Guide: How to use Stack Internal",{"image":1290,"link":53,"preface":1293,"publishedAt":1294,"slug":1295,"subcategory":1297,"title":1299},{"_type":49,"asset":1291},{"_ref":1292,"_type":52},"image-f99d67ff371d844130c2afffe7aea86b826b6d9b-2400x1260-png","We’ve curated ten of the most frequently asked questions about Stack Overflow for Teams to save you time and get your team up and running faster.","2023-03-15T15:42:31.203Z",{"_type":27,"current":1296},"10-tips-for-using-stack-overflow-for-teams",{"_createdAt":1260,"_id":1261,"_rev":1262,"_type":35,"_updatedAt":1263,"slug":1298,"title":1276},{"_type":27,"current":1275},"10 tips for using Stack Overflow for Teams",{"image":1301,"link":53,"preface":1304,"publishedAt":1305,"slug":1306,"subcategory":1308,"title":1310},{"_type":49,"asset":1302},{"_ref":1303,"_type":52},"image-7a37a1095dfc6d87ffe23d519b32422a70b775ad-2400x1260-png","We asked Stack Overflow’s adoption community of practice to share a definitive set of tagging best practices that you can take back to your team.","2022-12-17T01:44:00.000Z",{"_type":27,"current":1307},"tagging-best-practices-applying-tags",{"_createdAt":1260,"_id":1261,"_rev":1262,"_type":35,"_updatedAt":1263,"slug":1309,"title":1276},{"_type":27,"current":1275},"Best practices for tag lifecycle management: Applying tags",{"image":1312,"link":53,"preface":1304,"publishedAt":1315,"slug":1316,"subcategory":1318,"title":1320},{"_type":49,"asset":1313},{"_ref":1314,"_type":52},"image-c69302b4223ef640b47a7034338803cfbbe7a4fc-2400x1260-png","2022-11-02T00:44:36.622Z",{"_type":27,"current":1317},"tagging-best-practices-strategy-and-maintenance",{"_createdAt":1260,"_id":1261,"_rev":1262,"_type":35,"_updatedAt":1263,"slug":1319,"title":1276},{"_type":27,"current":1275},"Best practices for tag lifecycle management: Tag strategy and maintenance",{"image":1322,"link":53,"preface":1325,"publishedAt":1326,"slug":1327,"subcategory":1329,"title":1331},{"_type":49,"asset":1323},{"_ref":1324,"_type":52},"image-51de7a98f08c9f84e95e8ac23f25ffd1b8f5ff8f-1200x630-png","We’ll explain the big problems inaccurate knowledge can cause, how to determine if your knowledge base is inaccurate, and discuss how you can solve this common challenge.","2022-03-17T22:25:33+0000",{"_type":27,"current":1328},"how-do-you-stack-up",{"_createdAt":1260,"_id":1261,"_rev":1262,"_type":35,"_updatedAt":1263,"slug":1330,"title":1276},{"_type":27,"current":1275},"Knowledge base health: how do you stack up?",{"image":1333,"link":53,"preface":1336,"publishedAt":1337,"slug":1338,"subcategory":1340,"title":1342},{"_type":49,"asset":1334},{"_ref":1335,"_type":52},"image-9449b415944187a6c31c38f5a48ee31d0eac13a3-1200x630-png","An overview of the roles that can be assigned to users within the Stack Overflow for Teams knowledge sharing and collaboration platform.","2021-12-10T11:53:30+0000",{"_type":27,"current":1339},"teams-enterprise-user-roles",{"_createdAt":1260,"_id":1261,"_rev":1262,"_type":35,"_updatedAt":1263,"slug":1341,"title":1276},{"_type":27,"current":1275},"Introduction to user roles – Enterprise plan",{"image":1344,"link":53,"preface":1347,"publishedAt":1348,"slug":1349,"subcategory":1351,"title":1353},{"_type":49,"asset":1345},{"_ref":1346,"_type":52},"image-b7a87742b6652c9814b6f547bd700d44d50ab0c8-2400x1260-png","You’ve decided to try Stack Overflow for Teams. Awesome! You now have a private space to capture and reuse company knowledge using popular Stack Overflow features, reimagined for organizational teams.","2021-10-21T15:00:16+0000",{"_type":27,"current":1350},"teams-succeed-in-your-first-two-weeks",{"_createdAt":1260,"_id":1261,"_rev":1262,"_type":35,"_updatedAt":1263,"slug":1352,"title":1276},{"_type":27,"current":1275},"How to succeed in your first two weeks of Stack Overflow for Teams",{"image":1355,"link":53,"preface":1358,"publishedAt":1359,"slug":1360,"subcategory":1362,"title":1364},{"_type":49,"asset":1356},{"_ref":1357,"_type":52},"image-5b9f93980c67d414ff4f887c963159907c00c7c5-1200x630-png","We'll show you how to craft a great question and response with Stack Overflow for Teams including how to add a tag and search for an existing question or answer. ","2021-03-03T14:27:21+0000",{"_type":27,"current":1361},"how-to-ask-and-answer",{"_createdAt":1260,"_id":1261,"_rev":1262,"_type":35,"_updatedAt":1263,"slug":1363,"title":1276},{"_type":27,"current":1275},"How to ask and answer a question",{"image":1366,"link":53,"preface":1369,"publishedAt":1370,"slug":1371,"subcategory":1373,"title":1375},{"_type":49,"asset":1367},{"_ref":1368,"_type":52},"image-98fbbcae2da180cdcd2bcde1950d09a0a01f852f-1200x630-png","Stack Overflow for Teams Enterprise: SME Training","2021-01-05T17:40:03+0000",{"_type":27,"current":1372},"sme-training",{"_createdAt":1260,"_id":1261,"_rev":1262,"_type":35,"_updatedAt":1263,"slug":1374,"title":1276},{"_type":27,"current":1275},"Your role as Subject Matter Expert",{"image":1377,"link":53,"preface":1380,"publishedAt":1381,"slug":1382,"subcategory":1384,"title":1386},{"_type":49,"asset":1378},{"_ref":1379,"_type":52},"image-d410677f6a2f494aeebb5c7ac631f53ee454b322-1200x630-png","This PDF Guide includes important information for Teams admins.","2021-01-05T17:38:58+0000",{"_type":27,"current":1383},"admin-training",{"_createdAt":1260,"_id":1261,"_rev":1262,"_type":35,"_updatedAt":1263,"slug":1385,"title":1276},{"_type":27,"current":1275},"Getting started as a Teams admin",{"image":1388,"link":53,"preface":1391,"publishedAt":1392,"slug":1393,"subcategory":1395,"title":1397},{"_type":49,"asset":1389},{"_ref":1390,"_type":52},"image-c0bc4f358f6fe0b6338fc6a70a3511a45c47592d-1200x630-png","A quick PDF guide to help you plan a successful launch.","2021-01-05T17:10:07+0000",{"_type":27,"current":1394},"launch-planning-enterprise",{"_createdAt":1260,"_id":1261,"_rev":1262,"_type":35,"_updatedAt":1263,"slug":1396,"title":1276},{"_type":27,"current":1275},"Your launch planning guide",{"image":1399,"link":53,"preface":1402,"publishedAt":1403,"slug":1404,"subcategory":1406,"title":1408},{"_type":49,"asset":1400},{"_ref":1401,"_type":52},"image-0db0ccc24234280cf2ce58fc0a8b1510e08033b0-1200x630-png","The Slack integration with Stack Overflow for Teams empowers team members to find information without leaving their current workstreams.","2020-06-12T12:17:50+0000",{"_type":27,"current":1405},"slack-integration-overview",{"_createdAt":1260,"_id":1261,"_rev":1262,"_type":35,"_updatedAt":1263,"slug":1407,"title":1276},{"_type":27,"current":1275},"Why companies use Stack Overflow for Teams alongside Slack",{"_type":27,"current":1275},{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"resources":1415,"slug":1627,"title":1427},"2023-12-15T07:54:16Z","cb5c920f-8bd2-45f4-8431-4ab51bd6c456","ejz6Pq3OnBuSEtH3SncD75","2024-02-06T12:25:07Z",[1416,1429,1437,1445,1456,1465,1476,1487,1498,1509,1519,1530,1541,1552,1562,1573,1583,1594,1605,1616],{"image":1417,"link":53,"preface":1420,"publishedAt":1421,"slug":1422,"subcategory":1424,"title":1428},{"_type":49,"asset":1418},{"_ref":1419,"_type":52},"image-b76dca79b1f6248e0d70748087de370ae36ffd1c-3392x1930-png","Bring Stack Internal content closer to where employees work through the Moveworks AI Assistant. ","2025-08-06T22:05:08.616Z",{"_type":27,"current":1423},"stack-overflow-and-moveworks",{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"slug":1425,"title":1427},{"_type":27,"current":1426},"features","Dive Deeper into Features","Stack Overflow and Moveworks Integration",{"image":53,"link":53,"preface":1430,"publishedAt":1431,"slug":1432,"subcategory":1434,"title":1436},"SME Auto-Assign introduces a more systematic approach to SME management in Stack Overflow for Teams. This guide covers setup and ongoing SME Auto-Assign Management.","2024-12-04T16:55:00.000Z",{"_type":27,"current":1433},"sme-auto-setup",{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"slug":1435,"title":1427},{"_type":27,"current":1426},"Guide: SME Auto-Assign Setup",{"image":53,"link":53,"preface":1438,"publishedAt":1439,"slug":1440,"subcategory":1442,"title":1444},"This guide explains how to use Articles and Questions effectively, detailing when and why one should be used instead of the other and how you can strategically pair multiple kinds of knowledge content to add value to your growing community and ensure knowledge is lasting and reusable.","2024-09-16T14:26:53.125Z",{"_type":27,"current":1441},"user-guide-q-and-a-versus-articles",{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"slug":1443,"title":1427},{"_type":27,"current":1426},"Guide: Q&A versus Articles",{"image":1446,"link":53,"preface":1449,"publishedAt":1450,"slug":1451,"subcategory":1453,"title":1455},{"_type":49,"asset":1447},{"_ref":1448,"_type":52},"image-adfab25668694a61aae5fc16d052b82720950a20-2400x1260-png","Learn how the Stack Internal homepage makes it easier to share knowledge, collaborate with peers, and gain new insights.","2024-03-08T01:44:00.000Z",{"_type":27,"current":1452},"new-stack-overflow-for-teams-homepage-guide",{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"slug":1454,"title":1427},{"_type":27,"current":1426},"Guide to making the most of the homepage",{"image":1457,"link":53,"preface":1459,"publishedAt":1450,"slug":1460,"subcategory":1462,"title":1464},{"_type":49,"asset":1458},{"_ref":1448,"_type":52},"Learn how the new Stack Overflow for Teams homepage makes it easier to share knowledge, collaborate with peers, and gain new insights.",{"_type":27,"current":1461},"questions-and-answers-versus-articles",{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"slug":1463,"title":1427},{"_type":27,"current":1426},"How questions and answers",{"image":1466,"link":53,"preface":1469,"publishedAt":1470,"slug":1471,"subcategory":1473,"title":1475},{"_type":49,"asset":1467},{"_ref":1468,"_type":52},"image-530177e9232a5b3c16ec5273d8917247d4dbea2e-1360x764-png","Communities on Stack Internal is a new way to bring people and knowledge together around a specific domain to share valuable resources and collaborate in focused ways.","2023-11-16T14:00:00.000Z",{"_type":27,"current":1472},"connect-with-communities-on-teams",{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"slug":1474,"title":1427},{"_type":27,"current":1426},"Connect with Communities",{"image":1477,"link":53,"preface":1480,"publishedAt":1481,"slug":1482,"subcategory":1484,"title":1486},{"_type":49,"asset":1478},{"_ref":1479,"_type":52},"image-61a48924612642a9df71c4f345dae62e102386e6-512x251-png","Great tech cultures are built on communities of practice where people can share what they know, find out what they don’t, and learn from one another. Learn how to develop, integrate, and nurture communities of practice in your organization.","2023-09-14T14:20:00.000Z",{"_type":27,"current":1483},"the-playbook-to-unlock-the-business-value-of-communities-of-practice",{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"slug":1485,"title":1427},{"_type":27,"current":1426},"The playbook to unlock the business value of Communities of Practice",{"image":1488,"link":53,"preface":1491,"publishedAt":1492,"slug":1493,"subcategory":1495,"title":1497},{"_type":49,"asset":1489},{"_ref":1490,"_type":52},"image-baa456373e9bbe575c87e9e9f4a40b0410aa70c1-1200x600-png","Learn how Connectivity helps you track and grow cross-functional collaboration and knowledge sharing in Stack Overflow for Teams.","2023-08-10T13:00:00.000Z",{"_type":27,"current":1494},"visualize-knowledge-flows-with-connectivity",{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"slug":1496,"title":1427},{"_type":27,"current":1426},"Visualize knowledge flows with Connectivity",{"image":1499,"link":53,"preface":1502,"publishedAt":1503,"slug":1504,"subcategory":1506,"title":1508},{"_type":49,"asset":1500},{"_ref":1501,"_type":52},"image-9aea6db136b0f531f95a9f07bd740fab08e5b4f0-2400x1260-png","Stack Overflow introduces its latest version of its API, with new and improved functionality, design, and documentation.","2023-05-17T14:00:00.000Z",{"_type":27,"current":1505},"new-modern-api-for-stack-overflow-for-teams",{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"slug":1507,"title":1427},{"_type":27,"current":1426},"An overview of the Stack Internal API",{"image":1510,"link":53,"preface":1513,"publishedAt":1294,"slug":1514,"subcategory":1516,"title":1518},{"_type":49,"asset":1511},{"_ref":1512,"_type":52},"image-d48a7d592e6a422bf32094f452d7c157e31f9f5e-2400x1260-png","Learn how to set up Stack Overflow for Teams notifications so that they're surfacing the knowledge you need, when and where you need it.",{"_type":27,"current":1515},"setting-up-notifications",{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"slug":1517,"title":1427},{"_type":27,"current":1426},"Make notifications work for your team",{"image":1520,"link":53,"preface":1523,"publishedAt":1524,"slug":1525,"subcategory":1527,"title":1529},{"_type":49,"asset":1521},{"_ref":1522,"_type":52},"image-09537c1831469091622f5e5b6cfc48316ffe7c57-1120x548-png","Empower your team to spend less time on issues and more time building great products with our out-of-the-box integration with Jira. This integration helps to enhance your existing agile and software development workflow with more knowledge surfaced at the right time. ","2022-03-15T17:16:54+0000",{"_type":27,"current":1526},"jira-integration-demo",{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"slug":1528,"title":1427},{"_type":27,"current":1426},"Jira integration demo",{"image":1531,"link":53,"preface":1534,"publishedAt":1535,"slug":1536,"subcategory":1538,"title":1540},{"_type":49,"asset":1532},{"_ref":1533,"_type":52},"image-668bdd8b2417769af06459bb761b11115d3ed541-630x450-png","Our integration with Microsoft Teams allows users to quickly access knowledge and capture it for reuse without switching between applications or disrupting team members. We provide a native Stack Overflow for Teams experience within Microsoft Teams and help to enhance your existing workstreams, resolve blockages faster, and accelerate development time.","2022-03-15T17:01:30+0000",{"_type":27,"current":1537},"microsoft-teams-integration-demo",{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"slug":1539,"title":1427},{"_type":27,"current":1426},"Microsoft Teams integration demo",{"image":1542,"link":53,"preface":1545,"publishedAt":1546,"slug":1547,"subcategory":1549,"title":1551},{"_type":49,"asset":1543},{"_ref":1544,"_type":52},"image-ff8f8187de908e9124077365b9ede48c2735656c-1200x628-png","Our Content Health feature helps intelligently identify and surface potentially outdated or inaccurate knowledge. ","2022-03-02T21:39:13+0000",{"_type":27,"current":1548},"introduction-to-content-health",{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"slug":1550,"title":1427},{"_type":27,"current":1426},"Introduction to Content Health and its new capabilities",{"image":1553,"link":53,"preface":1336,"publishedAt":1556,"slug":1557,"subcategory":1559,"title":1561},{"_type":49,"asset":1554},{"_ref":1555,"_type":52},"image-1e1b70788e6393935e9924c8fd5f3da6a3f64710-1200x630-png","2021-12-09T11:19:15+0000",{"_type":27,"current":1558},"teams-business-user-roles",{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"slug":1560,"title":1427},{"_type":27,"current":1426},"Introduction to user roles – Business plan",{"image":1563,"link":53,"preface":1566,"publishedAt":1567,"slug":1568,"subcategory":1570,"title":1572},{"_type":49,"asset":1564},{"_ref":1565,"_type":52},"image-e4c6d28e234594513591152907156e83a29cdf6a-1200x628-png","A step-by-step guide for using Content Health to keep your knowledge base up-to-date and reliable","2021-11-17T17:10:01+0000",{"_type":27,"current":1569},"how-to-keep-your-knowledge-base-healthy-with-content",{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"slug":1571,"title":1427},{"_type":27,"current":1426},"How to keep your knowledge base healthy with Content Health",{"image":1574,"link":53,"preface":1576,"publishedAt":1577,"slug":1578,"subcategory":1580,"title":1582},{"_type":49,"asset":1575},{"_ref":1281,"_type":52},"To build great products, you need great discovery. Sometimes that means looking at old code or projects that never made it out the door to learn and evolve. Being able to find answers to questions on specific PRs, Gists and Commits, you’ll spend less time digging and more time building. See how our GitHub Enterprise integration works in this quick demo.","2021-03-29T21:08:41+0000",{"_type":27,"current":1579},"github-integration-demo",{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"slug":1581,"title":1427},{"_type":27,"current":1426},"GitHub integration demo",{"image":1584,"link":53,"preface":1587,"publishedAt":1588,"slug":1589,"subcategory":1591,"title":1593},{"_type":49,"asset":1585},{"_ref":1586,"_type":52},"image-100c8d180459948466e3642078952e7bb3ad065e-1200x630-png","Grouping questions, answers, and Articles together into a Collection is one of the key benefits of our Business and Enterprise plans. Find out how to create a Collection and add content to make accessing information easier than ever.","2021-03-03T14:28:57+0000",{"_type":27,"current":1590},"grouping-questions-answers-and-articles-together",{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"slug":1592,"title":1427},{"_type":27,"current":1426},"How to create a Collection",{"image":1595,"link":53,"preface":1598,"publishedAt":1599,"slug":1600,"subcategory":1602,"title":1604},{"_type":49,"asset":1596},{"_ref":1597,"_type":52},"image-98e00ffa2b14aa149ef25391a4e15c49cbb557bd-1200x630-png","With our Business and Enterprise plans your Team has access to Articles - a way to store longer-form content like project docs, how-to-guides, and so much more. Watch the quick video below to see how Articles works.","2021-03-03T14:25:07+0000",{"_type":27,"current":1601},"how-to-write-an-article",{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"slug":1603,"title":1427},{"_type":27,"current":1426},"How to write an Article",{"image":1606,"link":53,"preface":1609,"publishedAt":1610,"slug":1611,"subcategory":1613,"title":1615},{"_type":49,"asset":1607},{"_ref":1608,"_type":52},"image-5c3f7f7fad95c5375865037f42de9d3fb74a4672-1200x630-png","Make your team even more efficient by helping them find and share knowledge without leaving Slack. See how the new Ask on Stack Overflow for Teams experience in Slack works in this quick 90-second video.","2021-02-09T18:42:12+0000",{"_type":27,"current":1612},"slack-v3-demo",{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"slug":1614,"title":1427},{"_type":27,"current":1426},"Our latest Slack integration",{"image":1617,"link":53,"preface":1620,"publishedAt":1621,"slug":1622,"subcategory":1624,"title":1626},{"_type":49,"asset":1618},{"_ref":1619,"_type":52},"image-27e606f00859104dc5b905e87d28e96b4d6c27ab-1200x630-png","In this video, we show off our newest feature for Stack Internal, Articles.","2020-08-19T20:08:10+0000",{"_type":27,"current":1623},"see-articles-in-action",{"_createdAt":1411,"_id":1412,"_rev":1413,"_type":35,"_updatedAt":1414,"slug":1625,"title":1427},{"_type":27,"current":1426},"See Articles in action",{"_type":27,"current":1426},{"_createdAt":1629,"_id":1630,"_rev":1631,"_type":35,"_updatedAt":1632,"resources":1633,"slug":1702,"title":1645},"2023-12-15T07:53:12Z","605d6f38-ef1d-4cc6-b269-5f534d2dac20","ejz6Pq3OnBuSEtH3SncDNz","2024-02-06T12:25:15Z",[1634,1647,1658,1669,1680,1691],{"image":1635,"link":53,"preface":1638,"publishedAt":1639,"slug":1640,"subcategory":1642,"title":1646},{"_type":49,"asset":1636},{"_ref":1637,"_type":52},"image-4af00a6d252190c95997914b7b1ba7ddeb680092-1200x630-png","Learn how to leverage the new Tags page to decrease your site's median time-to-answer and unblock your team.","2023-12-08T01:44:00.000Z",{"_type":27,"current":1641},"speed-up-time-to-answer-with-tags",{"_createdAt":1629,"_id":1630,"_rev":1631,"_type":35,"_updatedAt":1632,"slug":1643,"title":1645},{"_type":27,"current":1644},"adoption","Drive Adoption","Guide: Speed up time-to-answer with the new Tags page",{"image":1648,"link":53,"preface":1651,"publishedAt":1652,"slug":1653,"subcategory":1655,"title":1657},{"_type":49,"asset":1649},{"_ref":1650,"_type":52},"image-00b2428096446e86f74ca77fdce3b0f13bfb8082-2400x1260-png","Make Stack Internal work wonders for your team with these best practices. This success kit gives you best practices and guidance to maximize the impact.","2023-05-01T18:36:00.000Z",{"_type":27,"current":1654},"make-teams-work-wonders",{"_createdAt":1629,"_id":1630,"_rev":1631,"_type":35,"_updatedAt":1632,"slug":1656,"title":1645},{"_type":27,"current":1644},"Stack Internal adoption success kit",{"image":1659,"link":53,"preface":1662,"publishedAt":1663,"slug":1664,"subcategory":1666,"title":1668},{"_type":49,"asset":1660},{"_ref":1661,"_type":52},"image-5406c2c5728a7045879dee386529f3c4cb568d5b-1600x900-png","This playbook will cover the components of good onboarding, the importance of rapid learning from Day One, and measuring onboarding success with Stack Internal.","2021-09-10T15:44:57+0000",{"_type":27,"current":1665},"onboarding-new-hires-with-stack-overflow-for-teams-playbook",{"_createdAt":1629,"_id":1630,"_rev":1631,"_type":35,"_updatedAt":1632,"slug":1667,"title":1645},{"_type":27,"current":1644},"Onboarding new hires with Stack Internal Playbook",{"image":1670,"link":53,"preface":1673,"publishedAt":1674,"slug":1675,"subcategory":1677,"title":1679},{"_type":49,"asset":1671},{"_ref":1672,"_type":52},"image-defe79b06db3442197fe5e7bb9964c346f5379a0-1127x903-png","To really get going with Stack Overflow for Teams, there are certain steps you should take in those critical first few weeks. These steps revolve around 3 key factors: change management, community growth, and community health measurement. ","2021-06-25T18:51:02+0000",{"_type":27,"current":1676},"to-really-get-going-with-stack-overflow-for-teams",{"_createdAt":1629,"_id":1630,"_rev":1631,"_type":35,"_updatedAt":1632,"slug":1678,"title":1645},{"_type":27,"current":1644},"Enabling rapid platform adoption",{"image":1681,"link":53,"preface":1684,"publishedAt":1685,"slug":1686,"subcategory":1688,"title":1690},{"_type":49,"asset":1682},{"_ref":1683,"_type":52},"image-c137c0ba95ce2b1ce6d53d2dc84dc33b22f81d5c-1200x630-png","To get your people talking on Teams, try creating an internal newsletter. This template will make that process as quick and easy as possible. ","2021-04-09T11:33:57+0000",{"_type":27,"current":1687},"internal-newsletters",{"_createdAt":1629,"_id":1630,"_rev":1631,"_type":35,"_updatedAt":1632,"slug":1689,"title":1645},{"_type":27,"current":1644},"Boost engagement with an internal newsletter (Template) ",{"image":1692,"link":53,"preface":1695,"publishedAt":1696,"slug":1697,"subcategory":1699,"title":1701},{"_type":49,"asset":1693},{"_ref":1694,"_type":52},"image-6b32a8b0318c47db5227f949b4dec44e89a31071-2344x1049-jpg","You don’t have to rely on your memory or Slack’s search capabilities to do great work. With the power of your team’s collective wisdom in an easy-to-search and easy-to-find location, you’ll be able to access information and get back to doing what you do best.","2021-02-17T16:13:40+0000",{"_type":27,"current":1698},"stack-vs.-slack-a-users-guide",{"_createdAt":1629,"_id":1630,"_rev":1631,"_type":35,"_updatedAt":1632,"slug":1700,"title":1645},{"_type":27,"current":1644},"Stack or Slack: A user’s guide",{"_type":27,"current":1644},{"body":1704,"title":1705},"Subscribe to receive Stack Internal content around knowledge sharing, collaboration, and AI.","Stay updated",{"_createdAt":1707,"_id":1708,"_rev":1709,"_system":1710,"_type":1713,"_updatedAt":1714,"author":53,"body":1715,"category":1848,"chapters":1856,"displayContents":2672,"estimatedReadingTime":2673,"headers":2674,"image":2675,"linkedResources":53,"product":2677,"publishedAt":756,"related":2733,"resourceType":5607,"sidebarCta":5616,"slug":5617,"subcategory":5618,"tags":5620,"title":763,"visible":2672},"2026-10-26T15:57:16Z","47d538ea-60fa-4561-aaac-08f7c6194069","t1dTUgrS4HcS7e8NDTkJRg",{"base":1711},{"id":1708,"rev":1712},"G7USs0ErMAs1wCqV757MbB","resource","2026-11-13T21:07:52Z",[1716,1736,1744,1752,1759,1767,1777,1785,1793,1800,1809,1817,1825,1833,1840],{"_key":1717,"_type":17,"children":1718,"markDefs":1732,"style":25},"824a86d90d2a",[1719,1723,1728],{"_key":1720,"_type":21,"marks":1721,"text":1722},"3690377c5354",[],"Developer confidence in AI has increased over the last year, according to our ",{"_key":1724,"_type":21,"marks":1725,"text":1727},"260194e0b92d",[1726],"6bbba3dbccfb","2026 Developer Survey.",{"_key":1729,"_type":21,"marks":1730,"text":1731},"75d6ae2712b1",[]," This is great news from an adoption standpoint. However, this also comes with some caveats and opportunities for improvement.",[1733],{"_key":1726,"_type":1734,"href":1735},"link","https:\u002F\u002Fsurvey.stackoverflow.co\u002F2026",{"_key":1737,"_type":17,"children":1738,"markDefs":1743,"style":25},"d0c09da6cc8b",[1739],{"_key":1740,"_type":21,"marks":1741,"text":1742},"e1e3614f595a",[],"",[],{"_key":1745,"_type":17,"children":1746,"markDefs":1751,"style":25},"e01ee1f1b972",[1747],{"_key":1748,"_type":21,"marks":1749,"text":1750},"94b7e66b5dd3",[],"Practitioners tend to lean away from using AI when it comes to tasks that require more subjective judgment and human communication. This is entirely understandable. If a developer uses incorrect information, it can have big consequences. They want to do their job well, and that means being careful with the data they use. The possibility of incorrect AI outputs make it hard for teams to move from individual use to scaling agentic workflows across teams.",[],{"_key":1753,"_type":17,"children":1754,"markDefs":1758,"style":25},"d98ed5130990",[1755],{"_key":1756,"_type":21,"marks":1757,"text":1742},"1dabe9594a15",[],[],{"_key":1760,"_type":17,"children":1761,"markDefs":1766,"style":25},"a867d4e6321b",[1762],{"_key":1763,"_type":21,"marks":1764,"text":1765},"34a445ad337a",[],"The 2026 Developer Survey released in October surveyed over 30K technologists across 169 countries with 103 questions in five categories: work, AI, technology, community, and knowledge. In this guide, we will uncover some of the key data from this survey around:",[],{"_key":1768,"_type":17,"children":1769,"level":1774,"listItem":1775,"markDefs":1776,"style":25},"0fbc4a600baa",[1770],{"_key":1771,"_type":21,"marks":1772,"text":1773},"5301b389fe78",[],"What unreliable AI really costs",1,"bullet",[],{"_key":1778,"_type":17,"children":1779,"level":1774,"listItem":1775,"markDefs":1784,"style":25},"0d44dff7d9d2",[1780],{"_key":1781,"_type":21,"marks":1782,"text":1783},"c32b1ac46bed",[],"Why the fix is providing better context",[],{"_key":1786,"_type":17,"children":1787,"level":1774,"listItem":1775,"markDefs":1792,"style":25},"00105c28c9ae",[1788],{"_key":1789,"_type":21,"marks":1790,"text":1791},"dbd10d6a2618",[],"Why the true AI return on investment is outcomes",[],{"_key":1794,"_type":17,"children":1795,"markDefs":1799,"style":25},"ecdc2c8c55c8",[1796],{"_key":1797,"_type":21,"marks":1798,"text":1742},"0e9c9522df2f",[],[],{"_key":1801,"_type":17,"children":1802,"markDefs":1808,"style":25},"4a631292f8ac",[1803],{"_key":1804,"_type":21,"marks":1805,"text":1807},"98ff1f268d6b",[1806],"strong","Key takeaways:",[],{"_key":1810,"_type":17,"children":1811,"level":1774,"listItem":1775,"markDefs":1816,"style":25},"a4c6e3632959",[1812],{"_key":1813,"_type":21,"marks":1814,"text":1815},"933371d07181",[],"Unreliable AI outputs have a hidden tax on businesses.",[],{"_key":1818,"_type":17,"children":1819,"level":1774,"listItem":1775,"markDefs":1824,"style":25},"e7daf565c3cc",[1820],{"_key":1821,"_type":21,"marks":1822,"text":1823},"46371da7550b",[],"A lack of foundational context is a core problem for teams using AI. Practitioners have more confidence in answers from verifiable sources.",[],{"_key":1826,"_type":17,"children":1827,"level":1774,"listItem":1775,"markDefs":1832,"style":25},"ec84ea4c3986",[1828],{"_key":1829,"_type":21,"marks":1830,"text":1831},"f9f563213505",[],"Outcomes are the true value of AI integration that leaders should focus on, and better outcomes start with shared organizational knowledge that can be verified.",[],{"_key":1834,"_type":17,"children":1835,"markDefs":1839,"style":25},"f1ad6b949b0b",[1836],{"_key":1837,"_type":21,"marks":1838,"text":1742},"0f860a6a19da",[],[],{"_key":1841,"_type":17,"children":1842,"markDefs":1847,"style":25},"792056e43226",[1843],{"_key":1844,"_type":21,"marks":1845,"text":1846},"e64543ffce12",[],"Each section concludes with practical guidance for every key buyer or decision maker from CIOs and Engineering VPs to CISOs and FinOps leaders. The goal is to help improve the practitioner experience with AI integration, allowing teams to use the tools they prefer, connect with the subject matter experts, and set goals focused on business outcomes.",[],{"_createdAt":610,"_id":611,"_rev":612,"_type":12,"_updatedAt":613,"description":1849,"slug":1855,"title":625},[1850],{"_key":616,"_type":17,"children":1851,"markDefs":1854,"style":25},[1852],{"_key":619,"_type":21,"marks":1853,"text":621},[],[],{"_type":27,"current":624},[1857,1898,1995,2140,2374,2562],{"_key":1858,"_type":1859,"body":1860,"slug":1895,"title":1897},"638b48392253","chapter",[1861,1869,1876,1881,1888],{"_key":1862,"_type":17,"children":1863,"markDefs":1868,"style":25},"e68852600399",[1864],{"_key":1865,"_type":21,"marks":1866,"text":1867},"e1e0a02ac20d",[],"The 2026 Developer Survey shows that the tech workforce is using AI: 77% use AI tools daily, and 55% of daily AI users used AI at least two or more hours per day in their work. But despite leadership hoping it will increase team productivity, teams are slowed down by incorrect or inconsistent outputs. As a result, developers end up using valuable time and resources filling in the missing organizational context, like who owns an answer or whether that answer is current and has been validated, to get the information they need to keep working. Someone verifying every output due to missing context is where the anticipated value of AI can leak in an enterprise environment. It’s ultimately a verification and context problem.",[],{"_key":1870,"_type":17,"children":1871,"markDefs":1875,"style":25},"b8ad3c29efce",[1872],{"_key":1873,"_type":21,"marks":1874,"text":1742},"7ae34822c26e",[1806],[],{"_key":1877,"_type":49,"alt":1878,"asset":1879},"60055a19bc20","Frequency of AI tool usage across four categories: AI coding assistants, general-purpose chat tools, AI agents or automated workflows, and internal tools.",{"_ref":1880,"_type":52},"image-f3bc86b5b53766937cc1f99841cbdbec1f85e1ca-883x578-png",{"_key":1882,"_type":17,"children":1883,"markDefs":1887,"style":25},"0aa2d104fa0c",[1884],{"_key":1885,"_type":21,"marks":1886,"text":1742},"2e5f2a0041c3",[],[],{"_key":1889,"_type":17,"children":1890,"markDefs":1894,"style":25},"621736d13e3e",[1891],{"_key":1892,"_type":21,"marks":1893,"text":1742},"71b6c9356b49",[],[],{"_type":27,"current":1896},"confidence-in-ai-outputs","Confidence in AI outputs",{"_key":1899,"_type":1859,"body":1900,"slug":1992,"title":1994},"8c085654213a",[1901,1920,1927,1935,1942,1950,1957,1962,1969,1977,1984],{"_key":1902,"_type":17,"children":1903,"markDefs":1917,"style":25},"c9da94afb446",[1904,1908,1913],{"_key":1905,"_type":21,"marks":1906,"text":1907},"fa9820ff1aac",[],"The cost of AI hallucinations or near-miss outputs doesn’t show up as a clear line item. ",{"_key":1909,"_type":21,"marks":1910,"text":1912},"ab4fad21ecac",[1911],"3456078b0561","Value is lost through hours",{"_key":1914,"_type":21,"marks":1915,"text":1916},"ad24248b55e9",[]," spent rechecking, reworking, and re-prompting on outputs.",[1918],{"_key":1911,"_type":1734,"href":1919},"https:\u002F\u002Fsurvey.stackoverflow.co\u002F2026\u002Fknowledge\u002Fdata\u002Fknowledge-a",{"_key":1921,"_type":17,"children":1922,"markDefs":1926,"style":25},"ecbf6a69d36e",[1923],{"_key":1924,"_type":21,"marks":1925,"text":1742},"36e5ae2b76c1",[],[],{"_key":1928,"_type":17,"children":1929,"markDefs":1934,"style":25},"a822428b8211",[1930],{"_key":1931,"_type":21,"marks":1932,"text":1933},"ff23fd50d86c",[],"The data this year shows that a majority indicate trusting AI at various levels, and 48% specifically trust it when they can easily verify the AI output. When rating the importance of being able to quickly check these sources while working, the top-rated sources were code repos, customer or sales support docs, and internal documentation.",[],{"_key":1936,"_type":17,"children":1937,"markDefs":1941,"style":25},"c4f95ab75c71",[1938],{"_key":1939,"_type":21,"marks":1940,"text":1742},"2ae75c5e46b9",[],[],{"_key":1943,"_type":17,"children":1944,"markDefs":1949,"style":25},"218e327f7c08",[1945],{"_key":1946,"_type":21,"marks":1947,"text":1948},"1d370f3755a0",[],"This makes sense. AI tools can increase efficiency by handling routine work well enough to make it worth keeping in a workflow. But the outputs aren't quite reliable enough for harder tasks when there is a risk of damaging or expensive errors. This is why usage continues to increase while confidence remains conditional.",[],{"_key":1951,"_type":17,"children":1952,"markDefs":1956,"style":25},"f4d17c244260",[1953],{"_key":1954,"_type":21,"marks":1955,"text":1742},"83fdaa281116",[],[],{"_key":1958,"_type":49,"alt":1959,"asset":1960},"5935055a87a1","Top AI mistakes: Plausible but wrong code, hard-to-review generated code, missing context, hallucinated package\u002Fconfig, and incorrect\u002Fstale knowledge.",{"_ref":1961,"_type":52},"image-2afaf4bb77dbaee6de672f59f3780df0329a0045-883x534-png",{"_key":1963,"_type":17,"children":1964,"markDefs":1968,"style":25},"5060900962f7",[1965],{"_key":1966,"_type":21,"marks":1967,"text":1742},"f56b6c58c647",[],[],{"_key":1970,"_type":17,"children":1971,"markDefs":1976,"style":25},"adf34ffd8110",[1972],{"_key":1973,"_type":21,"marks":1974,"text":1975},"b62d250a0924",[],"The top disruptive issues caused by AI in the workplace are plausible-but-wrong code, hard-to-review code, and missing context. Poor debugging paths and security or privacy issues stemming from AI are additional sources of lost team time due to unreliable AI responses. Further complicating things for teams, incorrect outputs that are prematurely relied on often get caught later in the review process or after something has already been shipped and breaks, causing more rework and delays.",[],{"_key":1978,"_type":17,"children":1979,"markDefs":1983,"style":25},"9f804046ede9",[1980],{"_key":1981,"_type":21,"marks":1982,"text":1742},"0ef6abf4deeb",[],[],{"_key":1985,"_type":17,"children":1986,"markDefs":1991,"style":25},"00d8b5c6ba12",[1987],{"_key":1988,"_type":21,"marks":1989,"text":1990},"88857735c27e",[],"These AI frustrations eventually become a budget problem. When incorrect outputs, hallucinations, and slow reviews pile up, increased work time takes away from the productivity gains an AI tool was meant to deliver. When net gains can’t be shown, it’s hard to justify value or keep working on a project that isn’t leading to the desired outcome fast enough.",[],{"_type":27,"current":1993},"what-unreliable-ai-actually-costs","What unreliable AI actually costs",{"_key":1996,"_type":1859,"body":1997,"slug":2137,"title":2139},"65777158b3b6",[1998,2006,2013,2021,2026,2034,2041,2049,2056,2061,2068,2075,2083,2090,2098,2105,2113,2125],{"_key":1999,"_type":17,"children":2000,"markDefs":2005,"style":25},"6c03f6b05fa5",[2001],{"_key":2002,"_type":21,"marks":2003,"text":2004},"57bdbc3a9b16",[],"If you ask a developer what slows them down the most, it isn't writing code. It’s the time it takes to track down the context they need to find the correct information when they notice an inaccurate AI response. This is the context tax that isn’t budgeted for. AI is supposed to save employees time, but for a lot of enterprise teams, the time they are losing because of unreliable AI results is spent tracking down verifiable information.",[],{"_key":2007,"_type":17,"children":2008,"markDefs":2012,"style":25},"3b81781afe9d",[2009],{"_key":2010,"_type":21,"marks":2011,"text":1742},"80b910fdaf98",[],[],{"_key":2014,"_type":17,"children":2015,"markDefs":2020,"style":25},"fcd001e78cc0",[2016],{"_key":2017,"_type":21,"marks":2018,"text":2019},"f9557fceef2b",[],"Context tax shows up in three places within a workflow: discoverability (can you find what you are looking for easily?), quality (is the information you find accurate?), and workflow integrations (does up-to-date information reach you, your agent, or where you are working when you need it?).",[],{"_key":2022,"_type":49,"alt":2023,"asset":2024},"c9c4546ac874","Top sources for work-related answers: Coworkers\u002Fteammates, code\u002Fcomments, internal docs\u002Fwikis, internal chat tools, official docs.",{"_ref":2025,"_type":52},"image-526897769321e52a8823b5f33aca2a4b7aa3dbfe-883x614-png",{"_key":2027,"_type":17,"children":2028,"markDefs":2033,"style":25},"c1acaf42e7e8",[2029],{"_key":2030,"_type":21,"marks":2031,"text":2032},"6986783f0587",[],"Consider the typical working day for a developer. They pick up a ticket that touches on a service they aren’t familiar with, so they search the company wiki and find two pieces of documentation that contradict one another. Then they find a chat from last year that references a design that is no longer current. So they ask an AI assistant and get an answer that was sourced from an outdated web page. They Slack a senior engineer to verify which piece of information is correct, but by the time they have an answer they can validate, half of their morning is gone. Even worse, none of this was captured anywhere, so another person will likely repeat this same process.",[],{"_key":2035,"_type":17,"children":2036,"markDefs":2040,"style":25},"faf28c98b117",[2037],{"_key":2038,"_type":21,"marks":2039,"text":1742},"e1b434c2b9ab",[],[],{"_key":2042,"_type":17,"children":2043,"markDefs":2048,"style":25},"3082f02dd1fe",[2044],{"_key":2045,"_type":21,"marks":2046,"text":2047},"6d6f8d9a8656",[],"Developers still tend to find ways around blocks to be more efficient and use AI tools they trust more than others. This further suggests that a verifiable source of knowledge is the missing layer in most workflows.",[],{"_key":2050,"_type":17,"children":2051,"markDefs":2055,"style":25},"758723dcc682",[2052],{"_key":2053,"_type":21,"marks":2054,"text":1742},"78cba5b7905e",[],[],{"_key":2057,"_type":49,"alt":2058,"asset":2059},"da7565cc800a","How developers manage AI context: Notes, new chat, team documentation, ask teammates, manually pick files, search multiple tools, copy\u002Fpaste between tools. ",{"_ref":2060,"_type":52},"image-5e248d613477abc88adba4393bc12d17fdc6c3e5-883x630-png",{"_key":2062,"_type":17,"children":2063,"markDefs":2067,"style":25},"42211d309eff",[2064],{"_key":2045,"_type":21,"marks":2065,"text":2066},[],"\n\nOur survey shows that whether or not organizations maintain controls of AI for their teams varies widely. 24% of respondents say their organization provides AI tools and guidance, while 11% expect tools to be used for some tasks, and 10% measure AI use as part of performance reviews. On the other hand, 30% or organizations leave AI tool decisions up to individuals, 17.3% say different teams choose their own AI tools, 32.8% say their org uses a few approved tools, and 15% encourage AI use but don’t have consistent practices.",[],{"_key":2069,"_type":17,"children":2070,"markDefs":2074,"style":25},"c26ca6f1b001",[2071],{"_key":2072,"_type":21,"marks":2073,"text":1742},"3bbe366ba14f",[],[],{"_key":2076,"_type":17,"children":2077,"markDefs":2082,"style":25},"b79a0579b4d9",[2078],{"_key":2079,"_type":21,"marks":2080,"text":2081},"68e4d1642e9b",[],"This shows that nearly half of developers work somewhere AI use is either left to individuals or encouraged without consistent practices in place. The best path forward to save time and standardize processes is to make sure the approved path is also the easiest to use. This means integrating shared organizational context that can be validated, kept current, and accessed by the teams and tools that need it.",[],{"_key":2084,"_type":17,"children":2085,"markDefs":2089,"style":25},"dd64c7923e5b",[2086],{"_key":2087,"_type":21,"marks":2088,"text":1742},"b76110ab8217",[],[],{"_key":2091,"_type":17,"children":2092,"markDefs":2097,"style":25},"29561bf11db6",[2093],{"_key":2094,"_type":21,"marks":2095,"text":2096},"992acc550a83",[],"For finance leaders, this is essential to understand: search-time savings is a leading metric that can be estimated but not easily tracked. When the time lost searching for missing context isn’t measured or at least acknowledged, it can’t be fixed. Once it is noticed, fixing it requires setting standards for what trusted context should look like, where it should be stored, and how it should be maintained going forward.",[],{"_key":2099,"_type":17,"children":2100,"markDefs":2104,"style":25},"c0c70eeae3ff",[2101],{"_key":2102,"_type":21,"marks":2103,"text":1742},"afa4df5ce37e",[],[],{"_key":2106,"_type":17,"children":2107,"markDefs":2112,"style":25},"41174ce1426c",[2108],{"_key":2109,"_type":21,"marks":2110,"text":2111},"69083020427d",[1806],"What to do next: make checking AI faster",[],{"_key":2114,"_type":17,"children":2115,"markDefs":2124,"style":25},"bce79906eb39",[2116,2120],{"_key":2117,"_type":21,"marks":2118,"text":2119},"12cd59410784",[1806],"Standardize context and use tools that integrate with what developers already use: ",{"_key":2121,"_type":21,"marks":2122,"text":2123},"53e57aaa681c",[],"Your AI toolset should work with what your team is already utilizing. Approve access to assistants and agents that integrate well, and invest in one governed source of organizational knowledge they all draw from.",[],{"_key":2126,"_type":17,"children":2127,"markDefs":2136,"style":25},"d6b8c98a9869",[2128,2132],{"_key":2129,"_type":21,"marks":2130,"text":2131},"07d4617b9f2a",[1806],"Treat pilot cancellations as a sign that you need more company-specific knowledge:",{"_key":2133,"_type":21,"marks":2134,"text":2135},"e1b80b62214e",[]," Before cancelling a pilot over quality, ask whether the tool had access to the organizational context it needed.",[],{"_type":27,"current":2138},"the-content-tax","The content tax",{"_key":2141,"_type":1859,"body":2142,"slug":2371,"title":2373},"0f3f1c68679c",[2143,2151,2158,2165,2170,2178,2185,2197,2209,2221,2233,2245,2252,2264,2276,2288,2300,2312,2319,2335,2347,2359],{"_key":2144,"_type":17,"children":2145,"markDefs":2150,"style":25},"94318607d912",[2146],{"_key":2147,"_type":21,"marks":2148,"text":2149},"6d9e62dd87ad",[],"79% of developers say that source attribution is important when trusting an AI answer. Further, developers tend to have confidence in knowledge sourced from colleagues the most. 72% say that coworkers are the most-used source for work related answers. ",[],{"_key":2152,"_type":17,"children":2153,"markDefs":2157,"style":25},"0b5bb7f9c5b4",[2154],{"_key":2155,"_type":21,"marks":2156,"text":1742},"02aa0c0fe602",[],[],{"_key":2159,"_type":17,"children":2160,"markDefs":2164,"style":25},"be909a1ab0de",[2161],{"_key":2147,"_type":21,"marks":2162,"text":2163},[],"It’s clear that established relationships and successful track records are where workers place their trust when it comes to organizational knowledge. Information sourced from AI does not get this benefit of the doubt because, understandably, developers want to know where the AI sourced the answer from before relying on it. According to our survey, the top barriers to verifiable information are Incomplete info (63%), knowledge only living in people's heads (61%), and outdated information (56%).",[],{"_key":2166,"_type":49,"alt":2167,"asset":2168},"9e34e0bbed16","What makes information trustworthy: Up to date, from a trusted source, matches other sources, clear and complete, includes sources.",{"_ref":2169,"_type":52},"image-305415eacac264c2cc810d8beb0673b84a5b4ab4-883x590-png",{"_key":2171,"_type":17,"children":2172,"markDefs":2177,"style":25},"ae5104593037",[2173],{"_key":2174,"_type":21,"marks":2175,"text":2176},"7caff22a6e0a",[],"Five signals determine when information can be trusted:",[],{"_key":2179,"_type":17,"children":2180,"markDefs":2184,"style":25},"5b58e112f1cc",[2181],{"_key":2182,"_type":21,"marks":2183,"text":1742},"883b91719599",[],[],{"_key":2186,"_type":17,"children":2187,"markDefs":2196,"style":25},"07b7b0b97a32",[2188,2192],{"_key":2189,"_type":21,"marks":2190,"text":2191},"7025c1b06c07",[1806],"Source visibility.",{"_key":2193,"_type":21,"marks":2194,"text":2195},"cc24e50a6f36",[]," Can I see where this came from?",[],{"_key":2198,"_type":17,"children":2199,"markDefs":2208,"style":25},"4ff4c93b404a",[2200,2204],{"_key":2201,"_type":21,"marks":2202,"text":2203},"9f8ef6fafd4b",[1806],"Recency.",{"_key":2205,"_type":21,"marks":2206,"text":2207},"0670f5dbe2ef",[]," Is it current or has it been replaced by something else?",[],{"_key":2210,"_type":17,"children":2211,"markDefs":2220,"style":25},"4687e522485c",[2212,2216],{"_key":2213,"_type":21,"marks":2214,"text":2215},"d716971b85f5",[1806],"Ownership.",{"_key":2217,"_type":21,"marks":2218,"text":2219},"82c5b57b909a",[]," Do I know who created it or who is accountable for it?",[],{"_key":2222,"_type":17,"children":2223,"markDefs":2232,"style":25},"fb134b65d1a6",[2224,2228],{"_key":2225,"_type":21,"marks":2226,"text":2227},"9e6eb8a22f13",[1806],"Permissions.",{"_key":2229,"_type":21,"marks":2230,"text":2231},"e03f45b9a52e",[]," Am I, or is this agent, allowed to see and act on it?",[],{"_key":2234,"_type":17,"children":2235,"markDefs":2244,"style":25},"c1f1ab8d0e72",[2236,2240],{"_key":2237,"_type":21,"marks":2238,"text":2239},"56f2f89c51dc",[1806],"Validation.",{"_key":2241,"_type":21,"marks":2242,"text":2243},"94e1f2343de7",[]," Has someone with the right expertise confirmed it?\n\nTo meet this standard for humans and AI agents with consistency, more than a wiki is required. Creating an organizational context that will ultimately improve the quality of AI tool outputs is done in five phases.",[],{"_key":2246,"_type":17,"children":2247,"markDefs":2251,"style":25},"b3ef93a65b51",[2248],{"_key":2249,"_type":21,"marks":2250,"text":1742},"20f623943189",[],[],{"_key":2253,"_type":17,"children":2254,"level":1774,"listItem":1775,"markDefs":2263,"style":25},"2c3f2ccdabdc",[2255,2259],{"_key":2256,"_type":21,"marks":2257,"text":2258},"454c9737acde",[1806],"Capture.",{"_key":2260,"_type":21,"marks":2261,"text":2262},"d6c14f2aa174",[]," Pull knowledge from where work already happens (chat threads, tickets, wikis, repositories, and AI tools) and break it into reusable units, keeping each unit’s source attached.",[],{"_key":2265,"_type":17,"children":2266,"level":1774,"listItem":1775,"markDefs":2275,"style":25},"c8532bd56820",[2267,2271],{"_key":2268,"_type":21,"marks":2269,"text":2270},"8042aeb55af6",[1806],"Validate.",{"_key":2272,"_type":21,"marks":2273,"text":2274},"161f74812fe0",[]," Attach trust signals to every response, such as authorship, recency, usage, and conflict detection, and route critical gaps or conflicts to the right subject matter expert. This is where a trusted knowledge layer and verified data come in.",[],{"_key":2277,"_type":17,"children":2278,"level":1774,"listItem":1775,"markDefs":2287,"style":25},"f378a125788d",[2279,2283],{"_key":2280,"_type":21,"marks":2281,"text":2282},"079e214b7ead",[1806],"Organize.",{"_key":2284,"_type":21,"marks":2285,"text":2286},"a881cdc4b8a7",[]," Scope knowledge to the right projects, teams, and agents so each sees what is relevant and nothing more.",[],{"_key":2289,"_type":17,"children":2290,"level":1774,"listItem":1775,"markDefs":2299,"style":25},"093a29ce4768",[2291,2295],{"_key":2292,"_type":21,"marks":2293,"text":2294},"d971f8d1119e",[1806],"Govern.",{"_key":2296,"_type":21,"marks":2297,"text":2298},"7bb07cccc3d2",[]," Manage permissions for people, teams, and agents centrally, with curation activity and audit trails.",[],{"_key":2301,"_type":17,"children":2302,"level":1774,"listItem":1775,"markDefs":2311,"style":25},"445e65a189d0",[2303,2307],{"_key":2304,"_type":21,"marks":2305,"text":2306},"1a19acf23ec3",[1806],"Deliver.",{"_key":2308,"_type":21,"marks":2309,"text":2310},"52ce1cdee7b2",[]," Put validated knowledge into the tools developers already use, and into agents, through standard interfaces such as MCP and APIs.",[],{"_key":2313,"_type":17,"children":2314,"markDefs":2318,"style":25},"abd681206ac3",[2315],{"_key":2316,"_type":21,"marks":2317,"text":1742},"dffff871269f",[],[],{"_key":2320,"_type":17,"children":2321,"markDefs":2334,"style":25},"ef2fcb90eb08",[2322,2326,2330],{"_key":2323,"_type":21,"marks":2324,"text":2325},"ae4bd51c22cb",[],"This all matters because permissions and ownership are the biggest trust signals for practitioners, while also carrying extra weight for CISOs and compliance and risk leaders. When an agent acts on information or when an AI answer is integrated into a workflow, the team needs to be able to show where that information came from and who owns it. This will reduce the time spent verifying answers, which in turn makes teams more productive so they drive real outcomes for the business.\n\n",{"_key":2327,"_type":21,"marks":2328,"text":2329},"0f670b27d3db",[1806],"What to do next: build context, keep it current, and use it everywhere. Put search time on the budget.",{"_key":2331,"_type":21,"marks":2332,"text":2333},"41991fa3cd8b",[]," Estimate the hours your teams spend finding information each week and track that number over time. It is the clearest business-case metric for knowledge investment.",[],{"_key":2336,"_type":17,"children":2337,"markDefs":2346,"style":25},"39ff02be576d",[2338,2342],{"_key":2339,"_type":21,"marks":2340,"text":2341},"e78f7c121be9",[1806],"Capture knowledge where work happens.",{"_key":2343,"_type":21,"marks":2344,"text":2345},"5d9f49b981a4",[]," Don’t ask developers to write documentation in yet another tool. Capture decisions and answers from the chat, tickets, and repositories they already use.",[],{"_key":2348,"_type":17,"children":2349,"markDefs":2358,"style":25},"11af36265464",[2350,2354],{"_key":2351,"_type":21,"marks":2352,"text":2353},"a454db2f32cc",[1806],"Make visibility the default.",{"_key":2355,"_type":21,"marks":2356,"text":2357},"6b9d8a2bfbeb",[]," Every answer a human or agent receives should have a clear path to track to a source, recency, owner, and validation status.",[],{"_key":2360,"_type":17,"children":2361,"markDefs":2370,"style":25},"80803eea302b",[2362,2366],{"_key":2363,"_type":21,"marks":2364,"text":2365},"b1cf79548ea4",[1806],"Connect practitioners to human subject matter experts.",{"_key":2367,"_type":21,"marks":2368,"text":2369},"82f6515e91f7",[]," Route only real gaps and conflicts to subject matter experts, then capture their answer so it is asked once, not weekly.",[],{"_type":27,"current":2372},"the-verified-context-standard","The verified context standard",{"_key":2375,"_type":1859,"body":2376,"slug":2559,"title":2561},"e6f3ae51662e",[2377,2385,2392,2400,2407,2415,2422,2430,2437,2445,2453,2458,2466,2473,2481,2489,2496,2504,2511,2523,2535,2547],{"_key":2378,"_type":17,"children":2379,"markDefs":2384,"style":25},"e9ddd54cfa9d",[2380],{"_key":2381,"_type":21,"marks":2382,"text":2383},"fce8fe836763",[],"As AI spend keeps increasing, it’s tempting to look at it purely on the basis of cost per token or cost per seat. The real focus should be on outcomes.",[],{"_key":2386,"_type":17,"children":2387,"markDefs":2391,"style":25},"f5333b304178",[2388],{"_key":2389,"_type":21,"marks":2390,"text":1742},"db4eaba18589",[],[],{"_key":2393,"_type":17,"children":2394,"markDefs":2399,"style":25},"3b91c111b90c",[2395],{"_key":2396,"_type":21,"marks":2397,"text":2398},"320f2289fe2e",[],"AI is a tool your team is using to get more done faster or at least more efficiently. The results you get from using these tools are where the value lies. Without outcomes that meet your goals, the cost would be a drain on your business and cost per seat wouldn’t matter at all.",[],{"_key":2401,"_type":17,"children":2402,"markDefs":2406,"style":25},"d7845d163a34",[2403],{"_key":2404,"_type":21,"marks":2405,"text":1742},"cba5b00da934",[],[],{"_key":2408,"_type":17,"children":2409,"markDefs":2414,"style":25},"b4582dd4b433",[2410],{"_key":2411,"_type":21,"marks":2412,"text":2413},"dd81fa0c482a",[],"For teams that use AI, outcomes are reliant on the quality of the results they get. That quality relies entirely on improving organizational access to a knowledge base that can be relied on by every team using any AI tool.",[],{"_key":2416,"_type":17,"children":2417,"markDefs":2421,"style":25},"8fdffc95b9d3",[2418],{"_key":2419,"_type":21,"marks":2420,"text":1742},"b2960c91ad06",[],[],{"_key":2423,"_type":17,"children":2424,"markDefs":2429,"style":25},"3a9b3a4ec237",[2425],{"_key":2426,"_type":21,"marks":2427,"text":2428},"9495102bb2a6",[],"With this in mind, there are two important questions that finance and procurement leaders should focus on besides the cost per token:",[],{"_key":2431,"_type":17,"children":2432,"markDefs":2436,"style":25},"133bcd29fe4b",[2433],{"_key":2434,"_type":21,"marks":2435,"text":1742},"64c9a3682f17",[],[],{"_key":2438,"_type":17,"children":2439,"level":1774,"listItem":1775,"markDefs":2444,"style":25},"4fa3ba83e52f",[2440],{"_key":2441,"_type":21,"marks":2442,"text":2443},"634c5e19a6a2",[],"Does the cost change how developers are working?",[],{"_key":2446,"_type":17,"children":2447,"level":1774,"listItem":1775,"markDefs":2452,"style":25},"bec5fcff1512",[2448],{"_key":2449,"_type":21,"marks":2450,"text":2451},"fd2f3f4db997",[],"What about our current workflows is holding teams back from improving AI output quality?",[],{"_key":2454,"_type":49,"alt":2455,"asset":2456},"b771bb5f0d7e","Does cost change how developers prompt? 75% for \"Yes, to improve output quality,\" 38% for \"Yes, to reduce cost,\" and 16% for \"No.\"",{"_ref":2457,"_type":52},"image-92e820cf7fe638b58c8f11b2286c103dc06f5839-883x433-png",{"_key":2459,"_type":17,"children":2460,"markDefs":2465,"style":25},"3c15afbaccf3",[2461],{"_key":2462,"_type":21,"marks":2463,"text":2464},"2c66570d702e",[],"Most developers are working across multiple tools every week, including more than one AI tool. On top of that, the business tech stack keeps growing and changing.",[],{"_key":2467,"_type":17,"children":2468,"markDefs":2472,"style":25},"f0daf0e3388b",[2469],{"_key":2470,"_type":21,"marks":2471,"text":1742},"32c6b8cc60d6",[],[],{"_key":2474,"_type":17,"children":2475,"markDefs":2480,"style":25},"3920a546bddc",[2476],{"_key":2477,"_type":21,"marks":2478,"text":2479},"dc7e1004cd9a",[],"Our survey shows that 19.7% of practitioners are using 1 tool, while the majority at nearly 75% are using between two and five different AI tools.",[],{"_key":2482,"_type":17,"children":2483,"markDefs":2488,"style":25},"f1f87cd2c088",[2484],{"_key":2485,"_type":21,"marks":2486,"text":2487},"6c41aebdd435",[],"Teams need room to evolve their tech stack as needs and goals shift. When all of your team’s tools are sourcing answers from the same validated, permission-aware source of information, the specific AI tools used matters less. With context in place your team can use the AI they prefer and new tools are more easily adopted as needed.",[],{"_key":2490,"_type":17,"children":2491,"markDefs":2495,"style":25},"7cb406a25f0e",[2492],{"_key":2493,"_type":21,"marks":2494,"text":1742},"5f69a7021a8c",[],[],{"_key":2497,"_type":17,"children":2498,"markDefs":2503,"style":25},"171032432ea9",[2499],{"_key":2500,"_type":21,"marks":2501,"text":2502},"2dab68cb8b52",[],"The goal is ensuring that any technology you and your team use is context-aware enough to need fewer corrections because it has been provided with validated and current information from the start.",[],{"_key":2505,"_type":17,"children":2506,"markDefs":2510,"style":25},"6b93756949cb",[2507],{"_key":2508,"_type":21,"marks":2509,"text":1742},"6c5cce8d9d40",[],[],{"_key":2512,"_type":17,"children":2513,"markDefs":2522,"style":25},"265a71c7340d",[2514,2518],{"_key":2515,"_type":21,"marks":2516,"text":2517},"fb60c2d8d3f6",[1806],"What to do next: focus on outcomes, not tokens. Retire usage as a success metric.",{"_key":2519,"_type":21,"marks":2520,"text":2521},"70d840f619ff",[]," Tokens consumed, prompts sent, and seats activated measure activity. Set goals on cycle time, correction and rework rates, search time saved, and incidents avoided.",[],{"_key":2524,"_type":17,"children":2525,"markDefs":2534,"style":25},"62e769518f28",[2526,2530],{"_key":2527,"_type":21,"marks":2528,"text":2529},"69e7b6a2beba",[1806],"Don’t tie performance reviews to AI usage.",{"_key":2531,"_type":21,"marks":2532,"text":2533},"80c27c537aa1",[]," Measuring individuals on how much AI they use rewards volume over value and pushes developers to use AI where it doesn’t help. Measure team outcomes instead.",[],{"_key":2536,"_type":17,"children":2537,"markDefs":2546,"style":25},"14352f7b8932",[2538,2542],{"_key":2539,"_type":21,"marks":2540,"text":2541},"b0de6218c4ef",[1806],"Forecast spend against outcomes.",{"_key":2543,"_type":21,"marks":2544,"text":2545},"1ffcaff7733e",[]," Pair usage limits with outcome reporting, so spend can increase where results justify it rather than being capped across the board.",[],{"_key":2548,"_type":17,"children":2549,"markDefs":2558,"style":25},"5f3bf5a94df9",[2550,2554],{"_key":2551,"_type":21,"marks":2552,"text":2553},"7ff19607cce4",[1806],"Standardize the context layer.",{"_key":2555,"_type":21,"marks":2556,"text":2557},"51bb76ddfd2c",[]," Keep the assistant and agent layer flexible, and make the shared knowledge layer the stable, governed foundation.",[],{"_type":27,"current":2560},"why-the-outcomes-drive-the-real-value-of-ai","Why the outcomes drive the real value of AI",{"_key":2563,"_type":1859,"body":2564,"slug":2669,"title":2671},"a0be84f34a55",[2565,2573,2580,2588,2595,2603,2610,2622,2634,2646,2654],{"_key":2566,"_type":17,"children":2567,"markDefs":2572,"style":25},"5b21c1db8c70",[2568],{"_key":2569,"_type":21,"marks":2570,"text":2571},"7f72c59d2a9d",[],"Reliability, context, and cost each route to three different leadership seats looking at AI from a buyer perspective. The CIO sees pilots that stall. The CTO and platform leaders see teams losing hours to search and rework each week. The CFO and procurement leaders see spend that is hard to tie to results.",[],{"_key":2574,"_type":17,"children":2575,"markDefs":2579,"style":25},"1f0ef019071c",[2576],{"_key":2577,"_type":21,"marks":2578,"text":1742},"03bebaa0e6de",[],[],{"_key":2581,"_type":17,"children":2582,"markDefs":2587,"style":25},"0aafda7acb52",[2583],{"_key":2584,"_type":21,"marks":2585,"text":2586},"3dbd5940a953",[],"All three need a foundation of reliable context to ensure AI is driving outcomes and not more problems.",[],{"_key":2589,"_type":17,"children":2590,"markDefs":2594,"style":25},"1d3b18c718cd",[2591],{"_key":2592,"_type":21,"marks":2593,"text":1742},"353ad8b4c2db",[],[],{"_key":2596,"_type":17,"children":2597,"markDefs":2602,"style":25},"6e2beb2c0648",[2598],{"_key":2599,"_type":21,"marks":2600,"text":2601},"ca18f80d71e6",[],"The solution is implementing a verifiable knowledge layer:",[],{"_key":2604,"_type":17,"children":2605,"markDefs":2609,"style":25},"5bbd8837e1fd",[2606],{"_key":2607,"_type":21,"marks":2608,"text":1742},"3fb9a6f52234",[],[],{"_key":2611,"_type":17,"children":2612,"level":1774,"listItem":1775,"markDefs":2621,"style":25},"5f6a8b8b8b89",[2613,2617],{"_key":2614,"_type":21,"marks":2615,"text":2616},"71098b3f1939",[1806],"Verification built in.",{"_key":2618,"_type":21,"marks":2619,"text":2620},"029ad5eb5fa8",[]," Output arrives grounded in validated knowledge, so checking it takes seconds, not hours.",[],{"_key":2623,"_type":17,"children":2624,"level":1774,"listItem":1775,"markDefs":2633,"style":25},"18ffcc3ca82c",[2625,2629],{"_key":2626,"_type":21,"marks":2627,"text":2628},"f15d76c3c9bd",[1806],"Established knowledge.",{"_key":2630,"_type":21,"marks":2631,"text":2632},"07a13c73e1b0",[]," Every answer, for every human and agent, carries its source, recency, owner, permissions, and validation status.",[],{"_key":2635,"_type":17,"children":2636,"level":1774,"listItem":1775,"markDefs":2645,"style":25},"ce2420b3b6be",[2637,2641],{"_key":2638,"_type":21,"marks":2639,"text":2640},"4339e124898f",[1806],"Outcome-based measurement.",{"_key":2642,"_type":21,"marks":2643,"text":2644},"d80aafa2fa22",[]," Success is measured in better outcomes for the actual business, less search time, and predictable spend, not tokens or seats.",[],{"_key":2647,"_type":17,"children":2648,"markDefs":2653,"style":25},"a04b3c8c1788",[2649],{"_key":2650,"_type":21,"marks":2651,"text":2652},"e2c5488cf5db",[],"Stack Internal was built to solve these challenges as a trusted knowledge layer that synthesizes and verifies organizational context across your business. This knowledge is then delivered to teams and into the tools they already use, through integrations such as Slack, Microsoft Teams, Jira, Confluence, and GitHub, and to agents through MCP and API.",[],{"_key":2655,"_type":17,"children":2656,"markDefs":2666,"style":25},"42ccad875314",[2657,2662],{"_key":2658,"_type":21,"marks":2659,"text":2661},"e93aff333fcc",[2660],"f708d40d568c","Talk with an expert",{"_key":2663,"_type":21,"marks":2664,"text":2665},"f2dd44734c02",[]," today to learn more about how adding a knowledge layer to your organization would improve AI workflows and drive better outcomes.",[2667],{"_key":2660,"_type":1734,"href":2668},"https:\u002F\u002Fstackoverflow.co\u002Finternal\u002F",{"_type":27,"current":2670},"valuable-ai-outcomes-start-with-the-right-context","Valuable AI outcomes start with the right context",true,2,[],{"_type":49,"alt":753,"asset":2676},{"_ref":755,"_type":52},{"_createdAt":2678,"_id":2679,"_rev":2680,"_system":2681,"_type":2684,"_updatedAt":2685,"abbr":2686,"color":2687,"descriptionShort":2704,"features":2705,"inflection":2721,"marketo":2721,"name":2722,"nameFull":2723,"plans":2724,"slug":2731},"2022-02-25T09:59:05Z","339bc91a-69c6-4a69-8add-a12977a22ad5","aUGu5vJZMW8mvj74UZYZiv",{"base":2682},{"id":2679,"rev":2683},"PhasGW24ij3IO6Qup2krVc","product","2026-09-30T15:45:20Z","SOI",{"_type":2688,"alpha":1774,"hex":2689,"hsl":2690,"hsv":2695,"rgb":2699},"color","#2b2d6e",{"_type":2691,"a":1774,"h":2692,"l":2693,"s":2694},"hslaColor",238.2089552238806,0.30000000000000004,0.4379084967320261,{"_type":2696,"a":1774,"h":2692,"s":2697,"v":2698},"hsvaColor",0.6090909090909091,0.43137254901960786,{"_type":2700,"a":1774,"b":2701,"g":2702,"r":2703},"rgbaColor",110,45,43,"Where developers & technologists share private knowledge with coworkers.",[2706,2709,2712,2715,2718],{"_key":2707,"_ref":2708,"_type":52},"1d36a6b63dc4","7c088242-c7bb-4d91-93db-6f7a042b1484",{"_key":2710,"_ref":2711,"_type":52},"f335b465079d","productFeatureCategory-integrations",{"_key":2713,"_ref":2714,"_type":52},"47ec4cc75ac7","productFeatureCategory-admin-support",{"_key":2716,"_ref":2717,"_type":52},"0c915c1f0429","productFeatureCategory-security",{"_key":2719,"_ref":2720,"_type":52},"e3e4701a58d6","productFeatureCategory-community","Stack Internal","Internal","Stack Overflow Internal",[2725,2728],{"_key":2726,"_ref":2727,"_type":52},"5d394ab03849","090566fe-d9d8-4014-bd3d-725502428be6",{"_key":2729,"_ref":2730,"_type":52},"ec5f82035b82","95303e50-2a79-4bcf-b317-f0fc0e44a8ef",{"_type":27,"current":2732},"internal",[2734,3382,4288,4603],{"_createdAt":2735,"_id":2736,"_rev":2737,"_system":2738,"_type":1713,"_updatedAt":2741,"body":2742,"category":3360,"linkedResources":3368,"preface":634,"product":3372,"publishedAt":635,"resourceType":3373,"seo":3377,"slug":3380,"subcategory":3381,"title":642,"visible":2672},"2026-09-25T05:08:52Z","be6d7623-12d6-4e97-b1b9-0ded3fe62594","PWOrJnGaGoyU2ieI3SE3QQ",{"base":2739},{"id":2736,"rev":2740},"wQ5C5CHMEZVRbtGEw7zc9R","2026-09-29T17:50:57Z",[2743,2751,2758,2766,2774,2782,2790,2797,2805,2814,2821,2829,2836,2844,2851,2859,2866,2874,2881,2889,2896,2904,2911,2918,2925,2933,2940,2948,2956,2964,2972,2980,2987,2995,3002,3009,3017,3024,3032,3040,3047,3055,3063,3070,3078,3085,3093,3100,3108,3116,3123,3131,3139,3146,3154,3162,3169,3177,3185,3192,3200,3208,3215,3223,3231,3238,3246,3254,3261,3269,3277,3284,3292,3300,3312,3324,3336,3348],{"_key":2744,"_type":17,"children":2745,"markDefs":2750,"style":25},"a4bd7d3a48b2",[2746],{"_key":2747,"_type":21,"marks":2748,"text":2749},"617fca70bfe0",[],"If you’re an engineering leader working with AI, you’re probably struggling with token spend, agents getting distracted, or AI mistakes. You think a context layer may be the thing you need, but you’re not entirely sure what that entails. It’s been touted as the key to success for AI strategies, the make or break for AI-assisted work—but so have many other AI-era buzzwords. You may be asking yourself:",[],{"_key":2752,"_type":17,"children":2753,"markDefs":2757,"style":25},"b7df5b02242e",[2754],{"_key":2755,"_type":21,"marks":2756,"text":1742},"d41d7f7fe6f0",[],[],{"_key":2759,"_type":17,"children":2760,"level":1774,"listItem":1775,"markDefs":2765,"style":25},"8c8e9af6d81b",[2761],{"_key":2762,"_type":21,"marks":2763,"text":2764},"0279566aaa2b",[],"What does an AI context layer do?",[],{"_key":2767,"_type":17,"children":2768,"level":1774,"listItem":1775,"markDefs":2773,"style":25},"23cb31a846b0",[2769],{"_key":2770,"_type":21,"marks":2771,"text":2772},"a796384c3886",[],"How do I know I need an AI context layer?",[],{"_key":2775,"_type":17,"children":2776,"level":1774,"listItem":1775,"markDefs":2781,"style":25},"74c1fe5b7732",[2777],{"_key":2778,"_type":21,"marks":2779,"text":2780},"25ba9286c87b",[],"How is an AI context layer different from a Wiki or document library?",[],{"_key":2783,"_type":17,"children":2784,"level":1774,"listItem":1775,"markDefs":2789,"style":25},"3b25a0821cd9",[2785],{"_key":2786,"_type":21,"marks":2787,"text":2788},"c7bed76eac51",[],"What should I look for in an AI context layer?",[],{"_key":2791,"_type":17,"children":2792,"markDefs":2796,"style":25},"14b9f170e9d0",[2793],{"_key":2794,"_type":21,"marks":2795,"text":1742},"668c9d830949",[],[],{"_key":2798,"_type":17,"children":2799,"markDefs":2804,"style":25},"d59015f733bb",[2800],{"_key":2801,"_type":21,"marks":2802,"text":2803},"6609763628f6",[],"Luckily, we’ve got the answers to all of your AI context layer questions. In this article, you’ll learn what an AI context layer is, how it differs from traditional knowledge management systems, and why it’s so important for AI strategies. Plus, we’ll help you diagnose whether an AI context layer is right for you and what to keep in mind when sourcing, procuring, and onboarding one.",[],{"_key":2806,"_type":17,"children":2807,"markDefs":2812,"style":2813},"7615d59e6363",[2808],{"_key":2809,"_type":21,"marks":2810,"text":2811},"8dc3b47cf34c",[],"What is an AI context layer?",[],"h1",{"_key":2815,"_type":17,"children":2816,"markDefs":2820,"style":25},"28f0fc3f1f9c",[2817],{"_key":2818,"_type":21,"marks":2819,"text":1742},"639799358693",[],[],{"_key":2822,"_type":17,"children":2823,"markDefs":2828,"style":25},"ebb2c617dbed",[2824],{"_key":2825,"_type":21,"marks":2826,"text":2827},"b268a0f32c77",[],"An AI context layer is the intermediary between your organization’s raw knowledge and your AI tools or LLMs. It serves as a filter and translator for raw data and unorganized information. In practice, an AI context layer retrieves and supplies relevant, trusted, and governed context to your AI tools and agents, allowing them to produce better answers and act on consistently reliable information. Its purpose is to ensure that AI uses verified, decision-grade knowledge, rather than passing unfiltered or outdated source material directly to the model.",[],{"_key":2830,"_type":17,"children":2831,"markDefs":2835,"style":25},"a20d45d1beb0",[2832],{"_key":2833,"_type":21,"marks":2834,"text":1742},"0bf736d66c5c",[],[],{"_key":2837,"_type":17,"children":2838,"markDefs":2843,"style":25},"d8b7c4e4c96e",[2839],{"_key":2840,"_type":21,"marks":2841,"text":2842},"b30af7e3de97",[],"How is an AI context layer different from traditional knowledge management systems like a Wiki or document library?",[],{"_key":2845,"_type":17,"children":2846,"markDefs":2850,"style":25},"f71b2337a707",[2847],{"_key":2848,"_type":21,"marks":2849,"text":1742},"9e16f9a8ce21",[],[],{"_key":2852,"_type":17,"children":2853,"markDefs":2858,"style":25},"b4292b1e0299",[2854],{"_key":2855,"_type":21,"marks":2856,"text":2857},"9fc95bce7f31",[],"An AI context layer is different from traditional knowledge management systems because it processes knowledge for use by people and AI agents. In traditional knowledge management systems like Wikis and document libraries, information is simply stored and organized. While an AI context layer also stores and organizes company knowledge, the major difference is in how it prepares, surfaces, and delivers this knowledge to people and AI tools. Unlike traditional knowledge management systems, an AI context layer ingests information from multiple sources—like your Slack, documents, or PRs—and processes it for efficient retrieval and consumption by AI tools. This improves search precision, enables granular trust and access controls, and reduces distraction and token spend by minimizing the context sent to an AI agent.",[],{"_key":2860,"_type":17,"children":2861,"markDefs":2865,"style":25},"4db69eb6245c",[2862],{"_key":2863,"_type":21,"marks":2864,"text":1742},"e0caf9c734b8",[],[],{"_key":2867,"_type":17,"children":2868,"markDefs":2873,"style":2813},"0ed5d5ecabdc",[2869],{"_key":2870,"_type":21,"marks":2871,"text":2872},"494e7bcfbd46",[],"Why is an AI context layer important?",[],{"_key":2875,"_type":17,"children":2876,"markDefs":2880,"style":25},"38317be247ee",[2877],{"_key":2878,"_type":21,"marks":2879,"text":1742},"de7ead547140",[],[],{"_key":2882,"_type":17,"children":2883,"markDefs":2888,"style":25},"9a7a14ef33a7",[2884],{"_key":2885,"_type":21,"marks":2886,"text":2887},"ea2c9080bf05",[],"An AI context layer is important because the quality of your AI outputs is dependent on the quality—and relevance—of the information your AI receives. Instead of forcing your AI to rely on incomplete or unverified enterprise data, an AI context layer gives your AI targeted, trusted context to work with and allows your AI to write back to the source, making sure you always have up-to-date knowledge available.",[],{"_key":2890,"_type":17,"children":2891,"markDefs":2895,"style":25},"4e782bca831c",[2892],{"_key":2893,"_type":21,"marks":2894,"text":1742},"71b4ae28ca50",[],[],{"_key":2897,"_type":17,"children":2898,"markDefs":2903,"style":25},"36b1ea3532cc",[2899],{"_key":2900,"_type":21,"marks":2901,"text":2902},"a061db27bb01",[],"Without an AI context layer, AI tools must spend tokens to search and surface the context they need to complete a task and, often, that context is incomplete or unverified. When AI acts upon this incomplete or unverified information, it can hallucinate, get distracted by irrelevant context, or make mistakes—ones that are costly. It can be disastrous when humans use incomplete, outdated, or incorrect information in their work, often leading to broken code or security breaches. But AI—especially autonomous agents—move at machine speed, meaning the mistakes it makes from bad context compounds and grows exponentially, often too fast for the human-in-the-loop to catch it. An AI context layer stops these mistakes from happening by controlling what context your AI has access to, making sure only reliable, correct, and relevant information is surfaced.",[],{"_key":2905,"_type":17,"children":2906,"markDefs":2910,"style":25},"eec79f6ac6e0",[2907],{"_key":2908,"_type":21,"marks":2909,"text":1742},"6ed308af3e87",[],[],{"_key":2912,"_type":17,"children":2913,"markDefs":2917,"style":2813},"18ea2db9e1a3",[2914],{"_key":2915,"_type":21,"marks":2916,"text":2772},"6bb9c3e89d82",[],[],{"_key":2919,"_type":17,"children":2920,"markDefs":2924,"style":25},"21a6a4cc096b",[2921],{"_key":2922,"_type":21,"marks":2923,"text":1742},"ff60aa7070ae",[],[],{"_key":2926,"_type":17,"children":2927,"markDefs":2932,"style":25},"eee459409eba",[2928],{"_key":2929,"_type":21,"marks":2930,"text":2931},"bf75e14105f6",[],"You need an AI context layer if you’re using AI in a real-world, business environment. This is especially true if your AI tools are embedded into multiple use cases across your organization, like engineering, product, ops, and finance. If you’re not sure whether or not you need an AI context layer, here are a few things to ask yourself:",[],{"_key":2934,"_type":17,"children":2935,"markDefs":2939,"style":25},"a6187013cb1f",[2936],{"_key":2937,"_type":21,"marks":2938,"text":1742},"764d337bc746",[],[],{"_key":2941,"_type":17,"children":2942,"level":1774,"listItem":1775,"markDefs":2947,"style":25},"5566ae2c97f8",[2943],{"_key":2944,"_type":21,"marks":2945,"text":2946},"1f46859e32b3",[],"Does my company have proprietary knowledge that is necessary for our work? Does AI need access to this proprietary knowledge to correctly and reliably complete its work?",[],{"_key":2949,"_type":17,"children":2950,"level":1774,"listItem":1775,"markDefs":2955,"style":25},"c1acc6a8a983",[2951],{"_key":2952,"_type":21,"marks":2953,"text":2954},"c9c8ae373860",[],"Is it difficult for my teams and AI tools to find and act on relevant information? Is my institutional knowledge scattered across multiple docs, tools, and message threads?",[],{"_key":2957,"_type":17,"children":2958,"level":1774,"listItem":1775,"markDefs":2963,"style":25},"80956da3f6ee",[2959],{"_key":2960,"_type":21,"marks":2961,"text":2962},"c464fc877631",[],"Do my AI tools get distracted by irrelevant information?",[],{"_key":2965,"_type":17,"children":2966,"level":1774,"listItem":1775,"markDefs":2971,"style":25},"5b728927fc6c",[2967],{"_key":2968,"_type":21,"marks":2969,"text":2970},"8e91da8f3269",[],"Do my AI tools struggle when trying to understand my company’s raw data? Do my AI tools expend unnecessary tokens trying to surface or digest my company’s raw data?",[],{"_key":2973,"_type":17,"children":2974,"level":1774,"listItem":1775,"markDefs":2979,"style":25},"0ad7a252bac3",[2975],{"_key":2976,"_type":21,"marks":2977,"text":2978},"40e0c6b0cc39",[],"Do I often distrust the output of my AI tools? Am I constantly double-checking or needing to verify the outputs of my AI tools?",[],{"_key":2981,"_type":17,"children":2982,"markDefs":2986,"style":25},"16a73cf013fa",[2983],{"_key":2984,"_type":21,"marks":2985,"text":1742},"ec364ae7a614",[],[],{"_key":2988,"_type":17,"children":2989,"markDefs":2994,"style":25},"b243b1b57fd3",[2990],{"_key":2991,"_type":21,"marks":2992,"text":2993},"00f736df528a",[],"If you said yes to any of these questions, you need an AI context layer.",[],{"_key":2996,"_type":17,"children":2997,"markDefs":3001,"style":25},"18f6a3d3e4fe",[2998],{"_key":2999,"_type":21,"marks":3000,"text":1742},"90a7dd877b57",[],[],{"_key":3003,"_type":17,"children":3004,"markDefs":3008,"style":2813},"3a8cc9245530",[3005],{"_key":3006,"_type":21,"marks":3007,"text":2788},"2d4998bf03f1",[],[],{"_key":3010,"_type":17,"children":3011,"markDefs":3016,"style":25},"969457896241",[3012],{"_key":3013,"_type":21,"marks":3014,"text":3015},"b55e5238d5b4",[],"Not every AI context layer is made the same. Here is what you should look for when sourcing an AI context layer:",[],{"_key":3018,"_type":17,"children":3019,"markDefs":3023,"style":25},"8891433773f0",[3020],{"_key":3021,"_type":21,"marks":3022,"text":1742},"d02661fe7a1d",[],[],{"_key":3025,"_type":17,"children":3026,"markDefs":3031,"style":25},"2c863b1503c8",[3027],{"_key":3028,"_type":21,"marks":3029,"text":3030},"93d4a22be6c0",[1806],"Trusted, traceable knowledge",[],{"_key":3033,"_type":17,"children":3034,"markDefs":3039,"style":25},"7d395bf7d1a6",[3035],{"_key":3036,"_type":21,"marks":3037,"text":3038},"e49540d1cfa0",[],"Every answer should be tied to its source and show provenance, recency, approval status, conflicts, and uncertainty. Look for trust signals such as authorship, validation, usage, and source history—not just raw search results.",[],{"_key":3041,"_type":17,"children":3042,"markDefs":3046,"style":25},"0345b7665600",[3043],{"_key":3044,"_type":21,"marks":3045,"text":1742},"6cff05065f48",[],[],{"_key":3048,"_type":17,"children":3049,"markDefs":3054,"style":25},"f06e20d50dcd",[3050],{"_key":3051,"_type":21,"marks":3052,"text":3053},"877bb0db8c5c",[1806],"Strong ingestion and knowledge transformation",[],{"_key":3056,"_type":17,"children":3057,"markDefs":3062,"style":25},"3b8ea56a5b46",[3058],{"_key":3059,"_type":21,"marks":3060,"text":3061},"287be920a791",[],"It should accept content from varied enterprise systems and handle ingestion, transformation, scanning, masking, mapping, and extraction before making knowledge retrievable. The goal is to turn raw enterprise content into precise, decision-grade knowledge.",[],{"_key":3064,"_type":17,"children":3065,"markDefs":3069,"style":25},"868a9305071e",[3066],{"_key":3067,"_type":21,"marks":3068,"text":1742},"6868b8c849be",[],[],{"_key":3071,"_type":17,"children":3072,"markDefs":3077,"style":25},"0e94244cff91",[3073],{"_key":3074,"_type":21,"marks":3075,"text":3076},"7a49fbcb713c",[1806],"Write-back and knowledge updates",[],{"_key":3079,"_type":17,"children":3080,"markDefs":3084,"style":25},"71a4a52f1136",[3081],{"_key":3082,"_type":21,"marks":3083,"text":1742},"517593b4aff5",[],[],{"_key":3086,"_type":17,"children":3087,"markDefs":3092,"style":25},"c7b916005503",[3088],{"_key":3089,"_type":21,"marks":3090,"text":3091},"6f2b6df92a06",[],"A good context layer should help teams keep knowledge current, not just retrieve what is already there. Look for a write-back capability that lets people propose corrections, add missing context, and turn lessons from AI-assisted work into updates to the right source or governed knowledge unit. Those changes should go through appropriate review, permissions, and version history, with clear provenance and a way to resolve conflicts. Ask how quickly approved updates become available to search and agents, and whether stale or superseded information is retired rather than repeatedly resurfaced.",[],{"_key":3094,"_type":17,"children":3095,"markDefs":3099,"style":25},"ca1a7779569e",[3096],{"_key":3097,"_type":21,"marks":3098,"text":1742},"c38f81641ebb",[],[],{"_key":3101,"_type":17,"children":3102,"markDefs":3107,"style":25},"ea824407a1d1",[3103],{"_key":3104,"_type":21,"marks":3105,"text":3106},"58c9fab3eca7",[1806],"Granular retrieval",[],{"_key":3109,"_type":17,"children":3110,"markDefs":3115,"style":25},"b567798dbe45",[3111],{"_key":3112,"_type":21,"marks":3113,"text":3114},"8156423ea2cb",[],"A good context layer breaks documents into standardized knowledge units rather than treating each document as an indivisible block. Granularity enables more precise search, trust scoring, access control, conflict detection, and smaller context windows.",[],{"_key":3117,"_type":17,"children":3118,"markDefs":3122,"style":25},"cfa0e73c0f28",[3119],{"_key":3120,"_type":21,"marks":3121,"text":1742},"e27e68c7a124",[],[],{"_key":3124,"_type":17,"children":3125,"markDefs":3130,"style":25},"06aadfcc0f11",[3126],{"_key":3127,"_type":21,"marks":3128,"text":3129},"82ce200b2573",[1806],"Context quality management",[],{"_key":3132,"_type":17,"children":3133,"markDefs":3138,"style":25},"707190e2c9fc",[3134],{"_key":3135,"_type":21,"marks":3136,"text":3137},"49fa0d39351d",[],"A good context layer gives visibility into stale content, missing sources, conflicting facts, low-confidence areas, unverified sources, and incomplete connectors. The system should help users fix context problems instead of merely reporting that an answer is uncertain.",[],{"_key":3140,"_type":17,"children":3141,"markDefs":3145,"style":25},"4e9e984a177f",[3142],{"_key":3143,"_type":21,"marks":3144,"text":1742},"7cddcd2a3e06",[],[],{"_key":3147,"_type":17,"children":3148,"markDefs":3153,"style":25},"fb2d17869920",[3149],{"_key":3150,"_type":21,"marks":3151,"text":3152},"1acf26f59e53",[1806],"Efficient context delivery",[],{"_key":3155,"_type":17,"children":3156,"markDefs":3161,"style":25},"a83c74996ee3",[3157],{"_key":3158,"_type":21,"marks":3159,"text":3160},"6edd004f2410",[],"It should rank relevant sources, compress context, reduce unnecessary retrieval, and minimize token usage and latency. Efficiency should be measurable through metrics such as cost, wall-clock time, source lookups, and tokens used.",[],{"_key":3163,"_type":17,"children":3164,"markDefs":3168,"style":25},"f3c72dcdbb6d",[3165],{"_key":3166,"_type":21,"marks":3167,"text":1742},"8ad9261589ad",[],[],{"_key":3170,"_type":17,"children":3171,"markDefs":3176,"style":25},"436e82084900",[3172],{"_key":3173,"_type":21,"marks":3174,"text":3175},"3f6ddd3ca806",[1806],"Governance and access control",[],{"_key":3178,"_type":17,"children":3179,"markDefs":3184,"style":25},"a7e9684932d3",[3180],{"_key":3181,"_type":21,"marks":3182,"text":3183},"6c24a1734d11",[],"Verify that permissions apply at the knowledge level and that agents receive only information the requesting user is authorized to access. Auditability, role-based access control, and protection against unverified or malicious inputs are important requirements for agent-facing systems.",[],{"_key":3186,"_type":17,"children":3187,"markDefs":3191,"style":25},"f121155a329e",[3188],{"_key":3189,"_type":21,"marks":3190,"text":1742},"ddaa0a6abb7d",[],[],{"_key":3193,"_type":17,"children":3194,"markDefs":3199,"style":25},"d86fe5867f7a",[3195],{"_key":3196,"_type":21,"marks":3197,"text":3198},"0df42806a341",[1806],"Durable, governed memory",[],{"_key":3201,"_type":17,"children":3202,"markDefs":3207,"style":25},"96e8e30a8962",[3203],{"_key":3204,"_type":21,"marks":3205,"text":3206},"a1b25acc0705",[],"If the layer supports agent memory, look for controlled memory writes, deduplication, reconciliation when new evidence supersedes old conclusions, confidence decay, compaction, and user inspection. Memory should improve over time without silently accumulating incorrect or contradictory information.",[],{"_key":3209,"_type":17,"children":3210,"markDefs":3214,"style":25},"526f9da18339",[3211],{"_key":3212,"_type":21,"marks":3213,"text":1742},"372d2577103d",[],[],{"_key":3216,"_type":17,"children":3217,"markDefs":3222,"style":25},"21d1bbe631fa",[3218],{"_key":3219,"_type":21,"marks":3220,"text":3221},"8da0b5dc263a",[1806],"Evaluation and observable performance",[],{"_key":3224,"_type":17,"children":3225,"markDefs":3230,"style":25},"d7a3fd969da2",[3226],{"_key":3227,"_type":21,"marks":3228,"text":3229},"315046400968",[],"Require repeatable evaluations using real workflows, comparing performance with and without the context layer. Measure answer quality, source correctness, hallucination rate, confidence calibration, completion rate, correction effort, cost, latency, and retrieval behavior.",[],{"_key":3232,"_type":17,"children":3233,"markDefs":3237,"style":25},"1c9bba6e7f8e",[3234],{"_key":3235,"_type":21,"marks":3236,"text":1742},"de6a6aee114a",[],[],{"_key":3239,"_type":17,"children":3240,"markDefs":3245,"style":25},"517ad880d34c",[3241],{"_key":3242,"_type":21,"marks":3243,"text":3244},"0b2ce21a59d9",[1806],"Agent and workflow integrations",[],{"_key":3247,"_type":17,"children":3248,"markDefs":3253,"style":25},"24cb7695b681",[3249],{"_key":3250,"_type":21,"marks":3251,"text":3252},"a71e21da3f95",[],"Check for APIs and integrations that let agents retrieve governed context inside their workflows, including support for MCP or comparable interfaces. Operational visibility—such as distributed tracing across the user interface, backend, retrieval layer, and model calls—is also valuable for diagnosing latency and failures.",[],{"_key":3255,"_type":17,"children":3256,"markDefs":3260,"style":25},"777e60bcf725",[3257],{"_key":3258,"_type":21,"marks":3259,"text":1742},"639bcff12d6a",[],[],{"_key":3262,"_type":17,"children":3263,"markDefs":3268,"style":25},"04660d3a9902",[3264],{"_key":3265,"_type":21,"marks":3266,"text":3267},"8916e45f9063",[1806],"Clear product boundaries",[],{"_key":3270,"_type":17,"children":3271,"markDefs":3276,"style":25},"da3fe64a1e69",[3272],{"_key":3273,"_type":21,"marks":3274,"text":3275},"227f8c736cf4",[],"Confirm what is generally available versus roadmap functionality, which connectors are supported, how deployment and security work, and what a realistic proof of concept can deliver. Avoid evaluating a context layer solely on vision; require a concrete evaluation plan and measurable success criteria.",[],{"_key":3278,"_type":17,"children":3279,"markDefs":3283,"style":25},"3992f1760283",[3280],{"_key":3281,"_type":21,"marks":3282,"text":1742},"347535a7d9bd",[],[],{"_key":3285,"_type":17,"children":3286,"markDefs":3291,"style":2813},"97c1bc49b465",[3287],{"_key":3288,"_type":21,"marks":3289,"text":3290},"115c29c8fcf2",[],"TLDR; What engineering leaders should know about the AI context layer",[],{"_key":3293,"_type":17,"children":3294,"markDefs":3299,"style":25},"a9e1b292373d",[3295],{"_key":3296,"_type":21,"marks":3297,"text":3298},"d240d5e22e76",[],"The AI context layer is the missing infrastructure between your enterprise knowledge and your AI tools. Here is what you need to know.",[],{"_key":3301,"_type":17,"children":3302,"level":1774,"listItem":1775,"markDefs":3311,"style":25},"7f72364f2cd4",[3303,3307],{"_key":3304,"_type":21,"marks":3305,"text":3306},"5ebc7147c181",[1806],"What it is.",{"_key":3308,"_type":21,"marks":3309,"text":3310},"5deb789ce381",[]," An AI context layer is an intermediary that filters, structures, and translates raw enterprise knowledge into trusted, governed context that AI tools and agents can actually use. It sits between your knowledge sources and your AI consumers, so models receive the right information at the right time rather than everything at once or nothing at all.",[],{"_key":3313,"_type":17,"children":3314,"level":1774,"listItem":1775,"markDefs":3323,"style":25},"962b48a374fd",[3315,3319],{"_key":3316,"_type":21,"marks":3317,"text":3318},"fcc81070c30a",[1806],"How it differs from a wiki or document library.",{"_key":3320,"_type":21,"marks":3321,"text":3322},"be330282571e",[]," Traditional knowledge systems store content for humans to browse and read. An AI context layer actively processes and delivers knowledge for AI consumption, handling retrieval, relevance ranking, access control, and format translation so AI tools do not have to figure any of that out themselves.",[],{"_key":3325,"_type":17,"children":3326,"level":1774,"listItem":1775,"markDefs":3335,"style":25},"fc5d9d701ecf",[3327,3331],{"_key":3328,"_type":21,"marks":3329,"text":3330},"3fdb63126174",[1806],"Why it matters.",{"_key":3332,"_type":21,"marks":3333,"text":3334},"6042b11903ec",[]," AI models are only as good as the context they receive. Poor or missing context produces hallucinations and compounding errors that propagate at machine speed across workflows, code, and decisions before anyone catches them.",[],{"_key":3337,"_type":17,"children":3338,"level":1774,"listItem":1775,"markDefs":3347,"style":25},"5657ca20da55",[3339,3343],{"_key":3340,"_type":21,"marks":3341,"text":3342},"677072735782",[1806],"Quick signals that you need one.",{"_key":3344,"_type":21,"marks":3345,"text":3346},"c1ef5f123cf8",[]," Your institutional knowledge is scattered across tools, wikis, and repos with no coherent layer on top. Your AI tools spend tokens fishing for context or returning generic answers. Trust in AI outputs is low because no one can trace where the information came from.",[],{"_key":3349,"_type":17,"children":3350,"level":1774,"listItem":1775,"markDefs":3359,"style":25},"29ded7b21e6f",[3351,3355],{"_key":3352,"_type":21,"marks":3353,"text":3354},"c5ac03b9bdb2",[1806],"What to evaluate when sourcing one.",{"_key":3356,"_type":21,"marks":3357,"text":3358},"9e7e53f07ebe",[]," Look for traceable and trusted knowledge sourcing, granular retrieval that surfaces the right chunk rather than whole documents, governance and access controls that respect existing permissions, efficient context delivery that minimises token overhead, and measurable evaluation criteria so you can track quality over time.",[],{"_createdAt":610,"_id":611,"_rev":612,"_type":12,"_updatedAt":613,"description":3361,"slug":3367,"title":625},[3362],{"_key":616,"_type":17,"children":3363,"markDefs":3366,"style":25},[3364],{"_key":619,"_type":21,"marks":3365,"text":621},[],[],{"_type":27,"current":624},[3369],{"_key":3370,"_ref":3371,"_type":52},"a53441c474ba","2125ae42-7585-4f98-84ef-96d3a6779e9b",{"_ref":2679,"_type":52},[3374],{"_key":3375,"_ref":3376,"_type":52},"bfcd6ffc74ca","04eba8a8-29cf-463d-8914-d7dd35ef3d48",{"_type":3378,"seoDescription":634,"seoTitle":3379},"seo","What Is an AI Context Layer? Guide for Engineering Leaders",{"_type":27,"current":637},{"_ref":629,"_type":52},{"_createdAt":3383,"_id":3384,"_rev":3385,"_system":3386,"_type":1713,"_updatedAt":3390,"body":3391,"category":4262,"image":4270,"linkedResources":4272,"preface":648,"product":4282,"publishedAt":649,"resourceType":4283,"slug":4286,"subcategory":4287,"title":654,"visible":2672},"2026-07-30T21:09:27Z","06a4104f-b5f0-4344-818a-c051ce532591","TawFgYEWdUPkQ6jXbxefHP",{"base":3387},{"id":3388,"rev":3389},"drafts.06a4104f-b5f0-4344-818a-c051ce532591","14cdcb39-a334-4441-95bd-28509c1b9f42","2026-07-31T13:00:07Z",[3392,3401,3409,3416,3424,3431,3439,3446,3458,3465,3481,3489,3497,3504,3512,3519,3527,3534,3546,3553,3569,3576,3584,3591,3599,3606,3618,3625,3633,3641,3649,3656,3664,3671,3679,3686,3698,3705,3713,3720,3728,3735,3747,3759,3766,3774,3781,3798,3805,3813,3820,3840,3848,3856,3863,3875,3887,3907,3914,3922,3929,3937,3945,3953,3960,3968,3975,3987,3999,4019,4031,4038,4046,4054,4062,4069,4077,4084,4096,4108,4115,4123,4130,4138,4146,4154,4161,4169,4176,4192,4199,4207,4214,4222,4229,4237,4244],{"_key":3393,"_type":17,"children":3394,"markDefs":3399,"style":3400},"6655b2176e2d",[3395],{"_key":3396,"_type":21,"marks":3397,"text":3398},"8d709882fd5c",[],"The build vs. buy trap",[],"h2",{"_key":3402,"_type":17,"children":3403,"markDefs":3408,"style":25},"2dc867f692e5",[3404],{"_key":3405,"_type":21,"marks":3406,"text":3407},"3e62c4d38261",[],"Most engineering teams capable of building an internal AI knowledge system think they should build one. Stand up a vector database, wire in a few API connectors, point a retrieval-augmented generation (RAG) pipeline at your internal docs, and you have a working context layer for your AI agents. Easy peasy, right?",[],{"_key":3410,"_type":17,"children":3411,"markDefs":3415,"style":25},"02fa20167d0d",[3412],{"_key":3413,"_type":21,"marks":3414,"text":1742},"5008663753ac",[],[],{"_key":3417,"_type":17,"children":3418,"markDefs":3423,"style":25},"b423850036cf",[3419],{"_key":3420,"_type":21,"marks":3421,"text":3422},"048cd00cc52e",[],"Six months later, it’s a platform team’s full-time job.",[],{"_key":3425,"_type":17,"children":3426,"markDefs":3430,"style":25},"1b77f8affaed",[3427],{"_key":3428,"_type":21,"marks":3429,"text":1742},"710a91d8f630",[],[],{"_key":3432,"_type":17,"children":3433,"markDefs":3438,"style":25},"3116dfd35121",[3434],{"_key":3435,"_type":21,"marks":3436,"text":3437},"19bb2f674967",[],"This is the latest iteration of the build vs. buy trap, and it can ensnare the strongest engineering teams. The mistake isn’t in the initial assessment of complexity: building a vector database really is straightforward. The mistake is in conflating building a vector database with building a governed knowledge pipeline. You’re talking about two entirely different classes of infrastructure problems: one is a database project; the other is a trust, compliance, and continuous-maintenance challenge that compounds with every new source, every stale document, and every AI agent you add to the stack.",[],{"_key":3440,"_type":17,"children":3441,"markDefs":3445,"style":25},"c4ee837496ba",[3442],{"_key":3443,"_type":21,"marks":3444,"text":1742},"5761fac81714",[],[],{"_key":3447,"_type":17,"children":3448,"markDefs":3457,"style":25},"a7e0b39b8bfa",[3449,3453],{"_key":3450,"_type":21,"marks":3451,"text":3452},"c3ba20fb8855",[],"This mistake is where enterprise AI tends to break down. Your agents aren’t failing because your models are wrong or insufficiently beefy. They’re failing because the knowledge they’re retrieving is uncaptured, unscored, and unvalidated. The problem isn’t a lack of information: you’re actually drowning in information, because you’re accumulating data faster than ever before. But you have no way of knowing which information to trust. No amount of prompt engineering can fix that problem, which is why ",{"_key":3454,"_type":21,"marks":3455,"text":3456},"c468aa74a3fe",[1806],"Stack Overflow is building a production-grade knowledge pipeline for the enterprise, with the new experience launching later this year.",[],{"_key":3459,"_type":17,"children":3460,"markDefs":3464,"style":25},"441b79ad395b",[3461],{"_key":3462,"_type":21,"marks":3463,"text":1742},"f0cb650508ca",[],[],{"_key":3466,"_type":17,"children":3467,"markDefs":3480,"style":25},"4dee6fae3a9d",[3468,3472,3476],{"_key":3469,"_type":21,"marks":3470,"text":3471},"ad0afee62a49",[],"In this article, we’ll walk through each stage of building a production-grade knowledge pipeline: ",{"_key":3473,"_type":21,"marks":3474,"text":3475},"81edb356c346",[1806],"capture, validate, organize, govern, and deliver",{"_key":3477,"_type":21,"marks":3478,"text":3479},"399963b7d635",[],". We’ll get real about what each stage actually costs to build and maintain, so you can make clear-eyed decisions about where your engineering capacity is best spent.",[],{"_key":3482,"_type":17,"children":3483,"markDefs":3488,"style":3400},"71096f0c60b6",[3484],{"_key":3485,"_type":21,"marks":3486,"text":3487},"a15382b709e5",[],"Capture: Turning scattered knowledge into living memory",[],{"_key":3490,"_type":17,"children":3491,"markDefs":3496,"style":25},"29250d49f722",[3492],{"_key":3493,"_type":21,"marks":3494,"text":3495},"b362c0b0ab59",[],"The first stage of any knowledge pipeline is capture: connecting to your sources, pulling in content, and structuring that raw content into something durable a downstream system can actually work with. In practice, this means writing and maintaining connectors for every platform your organization uses to create and store knowledge: Slack, GitHub, Jira, Confluence, Notion, SharePoint, Google Drive, internal wikis, meetings, agent sessions, and whatever bespoke CMS your documentation team adopted three years ago.",[],{"_key":3498,"_type":17,"children":3499,"markDefs":3503,"style":25},"9d473f48dbbe",[3500],{"_key":3501,"_type":21,"marks":3502,"text":1742},"20a12ac05a3b",[],[],{"_key":3505,"_type":17,"children":3506,"markDefs":3511,"style":25},"ef3889ddbddd",[3507],{"_key":3508,"_type":21,"marks":3509,"text":3510},"9bd1c5bdbe0e",[],"This is where most teams hit the cold start problem. Before a knowledge pipeline can deliver any value, it needs content, and for most organizations that content is scattered across dozens of systems, in dozens of formats, at varying levels of freshness and authority. Capture is the work of bridging that gap, and it begins before a single AI agent can benefit from any of it.",[],{"_key":3513,"_type":17,"children":3514,"markDefs":3518,"style":25},"9bf293028274",[3515],{"_key":3516,"_type":21,"marks":3517,"text":1742},"408125ce9e56",[],[],{"_key":3520,"_type":17,"children":3521,"markDefs":3526,"style":25},"c3aaa4d20c46",[3522],{"_key":3523,"_type":21,"marks":3524,"text":3525},"d501c7a7d8a3",[],"Writing an initial connector isn’t the hard part. The hard part is everything that comes next: keeping connectors current as vendor APIs evolve, handling authentication token rotation, managing pagination for large corpora, deduplicating content that lives in multiple systems, and extracting consistent metadata—author, creation date, last modified, team ownership, version—across every source.",[],{"_key":3528,"_type":17,"children":3529,"markDefs":3533,"style":25},"6b0491422d44",[3530],{"_key":3531,"_type":21,"marks":3532,"text":1742},"619b370bed41",[],[],{"_key":3535,"_type":17,"children":3536,"markDefs":3545,"style":25},"2c67a5d7d02a",[3537,3541],{"_key":3538,"_type":21,"marks":3539,"text":3540},"ad5bb4a98d2e",[1806],"Capture is more than ingestion.",{"_key":3542,"_type":21,"marks":3543,"text":3544},"edf8b237c1a7",[]," Raw documents are written for human readers who have context, who can skim, and who can infer meaning from structure. Agents can’t do those things. If you feed an agent a raw Slack thread or a stale PR comment, it will often retrieve the right document but the wrong section—or worse, content that’s adjacent to the answer but doesn’t actually answer it.",[],{"_key":3547,"_type":17,"children":3548,"markDefs":3552,"style":25},"405069c9da82",[3549],{"_key":3550,"_type":21,"marks":3551,"text":1742},"d807a0d52d73",[],[],{"_key":3554,"_type":17,"children":3555,"markDefs":3568,"style":25},"542d9e8c722f",[3556,3560,3564],{"_key":3557,"_type":21,"marks":3558,"text":3559},"38f0ecb46bee",[],"This is why Stack Internal platform’s capture layer does more than simply store a copy of the source. The fundamental unit of our capture layer is a ",{"_key":3561,"_type":21,"marks":3562,"text":3563},"d4c596d5990f",[1806],"knowledge node",{"_key":3565,"_type":21,"marks":3566,"text":3567},"f60c0f32641f",[],": a living record that carries the substance of what’s known, where it came from, who owns it, how it relates to other knowledge, and how much to trust it. The system stores a transformed, durable, provenance-tagged extract: the meaningful parts, separated from the noise, kept current as new information arrives.",[],{"_key":3570,"_type":17,"children":3571,"markDefs":3575,"style":25},"a460120a5f60",[3572],{"_key":3573,"_type":21,"marks":3574,"text":1742},"639a7f7bc336",[],[],{"_key":3577,"_type":17,"children":3578,"markDefs":3583,"style":25},"2c9c8a7d2ffe",[3579],{"_key":3580,"_type":21,"marks":3581,"text":3582},"9c52f54f3ddf",[],"If the source tool disappears tomorrow, the knowledge stays put. This is what separates capture from retrieval. Retrieval finds things that already exist somewhere. Capture holds knowledge as its own durable asset, structured into a connected map of what the organization actually knows: decisions, rationale, ownership, and relationships, not just documents.",[],{"_key":3585,"_type":17,"children":3586,"markDefs":3590,"style":25},"6ebf8b9a3597",[3587],{"_key":3588,"_type":21,"marks":3589,"text":1742},"ed779d4ba0a2",[],[],{"_key":3592,"_type":17,"children":3593,"markDefs":3598,"style":25},"5d161e669c6d",[3594],{"_key":3595,"_type":21,"marks":3596,"text":3597},"1f1f132cdfd8",[],"A knowledge node is an independent record that already contains the good stuff: the substance, the provenance, the relationships to other knowledge. Whether you swap out your wiki, sunset a chat tool, or migrate to a new ticketing system, your actual organizational knowledge doesn’t move or disappear. The underlying source can churn freely with your vendor stack, while the durable layer underneath remains intact.",[],{"_key":3600,"_type":17,"children":3601,"markDefs":3605,"style":25},"9e5e77a307e3",[3602],{"_key":3603,"_type":21,"marks":3604,"text":1742},"b5997cbb9279",[],[],{"_key":3607,"_type":17,"children":3608,"markDefs":3617,"style":25},"57ab291ec69c",[3609,3613],{"_key":3610,"_type":21,"marks":3611,"text":3612},"2ef39fe4a5dd",[1806],"The maintenance burden compounds.",{"_key":3614,"_type":21,"marks":3615,"text":3616},"baf50146f3d6",[]," Every source connector is a long-term commitment. API versions change, authentication schemes rotate, and rate limits tighten. A connector that works today requires ongoing engineering attention to continue working tomorrow—not because it was built badly, but because the systems it connects to are themselves evolving. At scale, of course, this becomes a significant, recurring burden on a platform team.",[],{"_key":3619,"_type":17,"children":3620,"markDefs":3624,"style":25},"e6583d35b767",[3621],{"_key":3622,"_type":21,"marks":3623,"text":1742},"5445e4940568",[],[],{"_key":3626,"_type":17,"children":3627,"markDefs":3632,"style":25},"a32ee9d2ced5",[3628],{"_key":3629,"_type":21,"marks":3630,"text":3631},"f42a473af025",[],"The alternative is to treat capture as a solved problem: a persistent, always-on connector framework and memory layer that structures everything into knowledge nodes automatically. This enables your engineers to write to a single stable interface rather than maintaining a fleet of bespoke integrations. Stack Internal’s platform allows teams to automate ingestion at scale, submitting content programmatically from any source without having to manage the underlying connector infrastructure.",[],{"_key":3634,"_type":17,"children":3635,"markDefs":3640,"style":3400},"d70d037da74f",[3636],{"_key":3637,"_type":21,"marks":3638,"text":3639},"31e91e20d053",[],"Validate: Where trust actually gets built",[],{"_key":3642,"_type":17,"children":3643,"markDefs":3648,"style":25},"b742e1ccd0fc",[3644],{"_key":3645,"_type":21,"marks":3646,"text":3647},"b038b69b3559",[],"Capturing knowledge isn’t all you need to produce a production-grade pipeline. The biggest mistake enterprises make in building internal AI context layers is treating all captured content as equally trustworthy when it simply isn’t.",[],{"_key":3650,"_type":17,"children":3651,"markDefs":3655,"style":25},"0db504cee8ba",[3652],{"_key":3653,"_type":21,"marks":3654,"text":1742},"a330f2eff4ea",[],[],{"_key":3657,"_type":17,"children":3658,"markDefs":3663,"style":25},"efff08d01c0b",[3659],{"_key":3660,"_type":21,"marks":3661,"text":3662},"c5517d05a4a6",[],"Some knowledge is authoritative and current. Some lives in outdated drafts, contradicted by something more recent, or a decision that was reversed and never marked as such. Without a differentiating mechanism, agents will confidently surface low-quality knowledge alongside high-quality knowledge. At machine speed, with ten agents acting on the same stale information simultaneously, that’s more than an inconvenience. It’s a potential outage, compliance failure, or rollback in production.",[],{"_key":3665,"_type":17,"children":3666,"markDefs":3670,"style":25},"e8f0c26a9aec",[3667],{"_key":3668,"_type":21,"marks":3669,"text":1742},"d48e39cada47",[],[],{"_key":3672,"_type":17,"children":3673,"markDefs":3678,"style":25},"d8d53a6d2417",[3674],{"_key":3675,"_type":21,"marks":3676,"text":3677},"78f872a51b14",[],"Stack Internal platform’s validation layer closes this gap. It works in two complementary modes: implicit trust, which is automatic, and explicit trust, which is the human-in-the-loop fallback for when stakes are high enough that getting it wrong is costly.",[],{"_key":3680,"_type":17,"children":3681,"markDefs":3685,"style":25},"b34832ac9cd2",[3682],{"_key":3683,"_type":21,"marks":3684,"text":1742},"a9233b37205a",[],[],{"_key":3687,"_type":17,"children":3688,"markDefs":3697,"style":25},"149bfcdfd2ba",[3689,3693],{"_key":3690,"_type":21,"marks":3691,"text":3692},"5f7a6c6597b3",[1806],"Implicit trust is the differentiator.",{"_key":3694,"_type":21,"marks":3695,"text":3696},"f0572aabd162",[]," Every knowledge node carries a trust score, and that score is not a binary flag or an upvote count. It’s a multi-signal, living assessment: who authored it and how authoritative they are, how often it’s been consulted and acted on, how recently it was created or updated, where it came from, and whether it conflicts with other knowledge. Most knowledge earns trust automatically, no human required. Things like a merged PR from a principal engineer, a finalized policy document with a named owner, or a decision confirmed in a Jira ticket carry their own authority from signals already present in the system.",[],{"_key":3699,"_type":17,"children":3700,"markDefs":3704,"style":25},"06b1b1848404",[3701],{"_key":3702,"_type":21,"marks":3703,"text":1742},"68066c4851b0",[],[],{"_key":3706,"_type":17,"children":3707,"markDefs":3712,"style":25},"e9da8157061d",[3708],{"_key":3709,"_type":21,"marks":3710,"text":3711},"60e5d2eea1bf",[],"Trust also decays. A node that was accurate six months ago may not be accurate today, and the system knows the difference. When a node falls below a confidence threshold, it surfaces a lightweight revalidation request to the right owner—one tap to confirm, not a full review session.",[],{"_key":3714,"_type":17,"children":3715,"markDefs":3719,"style":25},"18afc67f904a",[3716],{"_key":3717,"_type":21,"marks":3718,"text":1742},"c7de2b65f506",[],[],{"_key":3721,"_type":17,"children":3722,"markDefs":3727,"style":25},"b9de44028780",[3723],{"_key":3724,"_type":21,"marks":3725,"text":3726},"e21c93993d47",[],"The Stack Internal platform surfaces that trust through two mechanisms, available everywhere a search response is returned (web chat, API, MCP):",[],{"_key":3729,"_type":17,"children":3730,"markDefs":3734,"style":25},"f47d38f78eab",[3731],{"_key":3732,"_type":21,"marks":3733,"text":1742},"15fa87d7ed5b",[],[],{"_key":3736,"_type":17,"children":3737,"level":1774,"listItem":1775,"markDefs":3746,"style":25},"c2bdfba3bd96",[3738,3742],{"_key":3739,"_type":21,"marks":3740,"text":3741},"4b56cc767e90",[1806],"Trust labels",{"_key":3743,"_type":21,"marks":3744,"text":3745},"011f2fa1c052",[],": A simple, fast-to-interpret signal—validated or not validated—removes ambiguity at the point of use.",[],{"_key":3748,"_type":17,"children":3749,"level":1774,"listItem":1775,"markDefs":3758,"style":25},"cb68b8917c67",[3750,3754],{"_key":3751,"_type":21,"marks":3752,"text":3753},"63da9e42dfe7",[1806],"Trust signals",{"_key":3755,"_type":21,"marks":3756,"text":3757},"9b6c752392ab",[],": The human-readable “why” behind the label: who wrote it and their SME status, whether it’s corroborated by multiple sources, whether it’s thinly sourced from a single doc, or whether there’s simply no matching record at all. Surfacing a clear gap is infinitely more useful than false certainty.",[],{"_key":3760,"_type":17,"children":3761,"markDefs":3765,"style":25},"48890604cff1",[3762],{"_key":3763,"_type":21,"marks":3764,"text":1742},"5395486df9e9",[],[],{"_key":3767,"_type":17,"children":3768,"markDefs":3773,"style":25},"27d4c105474f",[3769],{"_key":3770,"_type":21,"marks":3771,"text":3772},"5d63228df520",[],"Underneath these mechanisms, a machine-facing trust score powers the things users don’t see directly: search ranking that prioritizes validated, current knowledge for high-impact queries; safer grounding-source selection for chat and agent answers; and automation logic that decides when content can flow through untouched versus when it needs to be routed for review. The user-facing experience is built around evidence and transparency. The score is what makes ranking and automation trustworthy behind the scenes.",[],{"_key":3775,"_type":17,"children":3776,"markDefs":3780,"style":25},"549057a03f19",[3777],{"_key":3778,"_type":21,"marks":3779,"text":1742},"3f9e99d8507e",[],[],{"_key":3782,"_type":17,"children":3783,"markDefs":3797,"style":25},"7a9cc4d11eaa",[3784,3788,3792],{"_key":3785,"_type":21,"marks":3786,"text":3787},"3b935bb4dd7d",[1806],"Explicit trust is the fallback, not the default.",{"_key":3789,"_type":21,"marks":3790,"text":3791},"3e23e341024c",[]," The design philosophy here is that the system should ideally never need to ask a human for anything, and the bar for pulling a human in gets higher as the system matures. Every interruption is treated as a signal that the automatic layer isn’t working well enough yet. The health metric to drive down over time is simply, ",{"_key":3793,"_type":21,"marks":3794,"text":3796},"514c9105e374",[3795],"em","How many times did we interrupt a human today?",[],{"_key":3799,"_type":17,"children":3800,"markDefs":3804,"style":25},"4ee6478d0d12",[3801],{"_key":3802,"_type":21,"marks":3803,"text":1742},"ce7c8b77629a",[],[],{"_key":3806,"_type":17,"children":3807,"markDefs":3812,"style":25},"7c406ce84016",[3808],{"_key":3809,"_type":21,"marks":3810,"text":3811},"fc8528da3fec",[],"When escalation does happen, it follows a gradient: a one-tap event-triggered prompt (\"looks like you changed direction here—want to capture it?\"), in-context correction, gap-filling, stale-node revalidation, and a knowledge inbox for deliberate admin curation. One way to think about it is that AI accelerates while humans authorize.",[],{"_key":3814,"_type":17,"children":3815,"markDefs":3819,"style":25},"06d0bea0acaf",[3816],{"_key":3817,"_type":21,"marks":3818,"text":1742},"3b454592639b",[],[],{"_key":3821,"_type":17,"children":3822,"markDefs":3839,"style":25},"20edd8130193",[3823,3827,3831,3835],{"_key":3824,"_type":21,"marks":3825,"text":3826},"ebf3efd4caa6",[1806],"Why this can’t be bolted on with off-the-shelf evaluation alone:",{"_key":3828,"_type":21,"marks":3829,"text":3830},"8b844b26a3e1",[]," Standard evaluation frameworks measure what’s easy to measure: fluency, coherence, basic relevance. They don’t reliably capture whether a piece of knowledge is well-scoped, faithful to its source, or genuinely useful to the person who needs it. Getting ",{"_key":3832,"_type":21,"marks":3833,"text":3834},"38ef557ed5c1",[3795],"that",{"_key":3836,"_type":21,"marks":3837,"text":3838},"b1850a8e3229",[]," right requires custom evaluation logic layered on top of standard evaluators, with score explanations a reviewer can act on without rereading the source material. That’s not a one-time setup, either; it requires continuous tuning as the knowledge base evolves.",[],{"_key":3841,"_type":17,"children":3842,"markDefs":3847,"style":3400},"1ca72de00365",[3843],{"_key":3844,"_type":21,"marks":3845,"text":3846},"2745be8f8867",[],"Organize: Knowledge that lives at the right altitude",[],{"_key":3849,"_type":17,"children":3850,"markDefs":3855,"style":25},"0aaaa256c33c",[3851],{"_key":3852,"_type":21,"marks":3853,"text":3854},"77448ef7f8b7",[],"Capturing and validating knowledge solves nothing if all that knowledge drains into one undifferentiated pool. For instance, a decision made by an individual engineer about their own service shouldn’t carry the same weight or the same audience as a company-wide architectural commitment. The organize layer gives knowledge the right altitude, structured into three nested scopes, each auto-populated from the capture layer rather than requiring anyone to manually file things away.",[],{"_key":3857,"_type":17,"children":3858,"markDefs":3862,"style":25},"1094cb5e5423",[3859],{"_key":3860,"_type":21,"marks":3861,"text":1742},"12987dc73c32",[],[],{"_key":3864,"_type":17,"children":3865,"level":1774,"listItem":1775,"markDefs":3874,"style":25},"0562b8625ef3",[3866,3870],{"_key":3867,"_type":21,"marks":3868,"text":3869},"574f42fbaaad",[1806],"Personal scope",{"_key":3871,"_type":21,"marks":3872,"text":3873},"f08a84812dd6",[],": Private, individual-owned knowledge. This is a developer’s professional memory: the architecture decision only a few people were present for, the context they keep re-explaining to their AI tools every session. Agents can access this memory on the individual’s behalf.",[],{"_key":3876,"_type":17,"children":3877,"level":1774,"listItem":1775,"markDefs":3886,"style":25},"1f558f15e402",[3878,3882],{"_key":3879,"_type":21,"marks":3880,"text":3881},"99b41e0430dd",[1806],"Team scope",{"_key":3883,"_type":21,"marks":3884,"text":3885},"53e168a7c3f8",[],": Shared context for a team and its agents, seeded by one champion and adopted organically as the rest of the team finds it useful.",[],{"_key":3888,"_type":17,"children":3889,"level":1774,"listItem":1775,"markDefs":3906,"style":25},"59e803f78309",[3890,3894,3898,3902],{"_key":3891,"_type":21,"marks":3892,"text":3893},"63ffc8e96c80",[1806],"Org scope",{"_key":3895,"_type":21,"marks":3896,"text":3897},"d2a0cbc9d48a",[],": What the company has actually committed to. This is the human-validated, admin-governed, high-trust content agents read when they need to know how the organization ",{"_key":3899,"_type":21,"marks":3900,"text":3901},"985f10d5f4ca",[3795],"actually",{"_key":3903,"_type":21,"marks":3904,"text":3905},"07d061880137",[]," works, as opposed to how one team or one person thinks it works.",[],{"_key":3908,"_type":17,"children":3909,"markDefs":3913,"style":25},"920611129b48",[3910],{"_key":3911,"_type":21,"marks":3912,"text":1742},"d1474d6740e7",[],[],{"_key":3915,"_type":17,"children":3916,"markDefs":3921,"style":25},"7dabf0d235a4",[3917],{"_key":3918,"_type":21,"marks":3919,"text":3920},"935c5327fd9e",[],"Agents are not a separate scope sitting outside this structure. They operate inside personal, team, and org scopes and inherit the permission boundary of whichever context they’re acting in. That means a developer’s personal knowledge never leaks to their team unless they explicitly choose to share it, and an agent can never see more than a human operating in the same context would be allowed to see. Permissions are defined once in the control plane and enforced architecturally across the board.",[],{"_key":3923,"_type":17,"children":3924,"markDefs":3928,"style":25},"b55a50d63da1",[3925],{"_key":3926,"_type":21,"marks":3927,"text":1742},"408582ab1c75",[],[],{"_key":3930,"_type":17,"children":3931,"markDefs":3936,"style":25},"29bce1f64f23",[3932],{"_key":3933,"_type":21,"marks":3934,"text":3935},"661e9ee1ca59",[],"This scoped structure is also what makes adoption work from the bottom up instead of requiring a top-down rollout. Knowledge starts personal, proves useful, gets promoted to a team, and—once it’s been through validation—graduates to org scope.",[],{"_key":3938,"_type":17,"children":3939,"markDefs":3944,"style":3400},"5fd78e60a256",[3940],{"_key":3941,"_type":21,"marks":3942,"text":3943},"108f3b9282b0",[],"Govern: The control surface enterprise buyers actually need",[],{"_key":3946,"_type":17,"children":3947,"markDefs":3952,"style":25},"882c3ea0f794",[3948],{"_key":3949,"_type":21,"marks":3950,"text":3951},"c19d231be954",[],"Govern is the management layer and the proof of value for everything upstream. It has to be both a UI and fully programmatic, because enterprise buyers need to script permissions, export audit logs to their SIEM (security information and event management), configure agent guardrails via API, and pull observability into their own dashboards.",[],{"_key":3954,"_type":17,"children":3955,"markDefs":3959,"style":25},"fb7ea0f1ef56",[3956],{"_key":3957,"_type":21,"marks":3958,"text":1742},"80017d51e7cb",[],[],{"_key":3961,"_type":17,"children":3962,"markDefs":3967,"style":25},"bf27e3015343",[3963],{"_key":3964,"_type":21,"marks":3965,"text":3966},"c8c6b20b4180",[],"The govern layer has four foundational capabilities:",[],{"_key":3969,"_type":17,"children":3970,"markDefs":3974,"style":25},"a10e157b2690",[3971],{"_key":3972,"_type":21,"marks":3973,"text":1742},"9b1be3294902",[],[],{"_key":3976,"_type":17,"children":3977,"level":1774,"listItem":1775,"markDefs":3986,"style":25},"a2126b33c82f",[3978,3982],{"_key":3979,"_type":21,"marks":3980,"text":3981},"64b7edda83ff",[1806],"Access and permissions",{"_key":3983,"_type":21,"marks":3984,"text":3985},"1f439a169cdd",[]," with IDP integration and bulk provisioning. It’s a structural property of the system that agents can’t see information they don’t have permission to view.",[],{"_key":3988,"_type":17,"children":3989,"level":1774,"listItem":1775,"markDefs":3998,"style":25},"8850241cee73",[3990,3994],{"_key":3991,"_type":21,"marks":3992,"text":3993},"c6ffcde4398a",[1806],"Agent guardrails",{"_key":3995,"_type":21,"marks":3996,"text":3997},"49cabf3c6824",[]," are a per-context policy engine that marks each action class as human-approved, autonomous, or prohibited. They allow CTOs to approve agents that read from and write to organizational knowledge, instead of keeping them sandboxed indefinitely.",[],{"_key":4000,"_type":17,"children":4001,"level":1774,"listItem":1775,"markDefs":4018,"style":25},"3af4e2e93712",[4002,4006,4010,4014],{"_key":4003,"_type":21,"marks":4004,"text":4005},"17b8b45fa117",[1806],"Audit trail",{"_key":4007,"_type":21,"marks":4008,"text":4009},"dd0298731cc5",[]," makes every change to the knowledge graph traceable from day one—who added knowledge, who validated it, who deprecated it, which agent read it, when, and what action followed—",{"_key":4011,"_type":21,"marks":4012,"text":4013},"6f4ed1c279d2",[3795],"and",{"_key":4015,"_type":21,"marks":4016,"text":4017},"f43f5f8f206e",[]," exportable for compliance tooling.",[],{"_key":4020,"_type":17,"children":4021,"level":1774,"listItem":1775,"markDefs":4030,"style":25},"527c8cc04a13",[4022,4026],{"_key":4023,"_type":21,"marks":4024,"text":4025},"ad95009a1487",[1806],"Observability",{"_key":4027,"_type":21,"marks":4028,"text":4029},"4a7934825df2",[]," includes knowledge health, gap concentration, agent interaction logs, and business impact, visible to both human administrators and AI governance teams.",[],{"_key":4032,"_type":17,"children":4033,"markDefs":4037,"style":25},"940c021b3b9f",[4034],{"_key":4035,"_type":21,"marks":4036,"text":1742},"af872bca5caa",[],[],{"_key":4039,"_type":17,"children":4040,"markDefs":4045,"style":25},"8bf99996454c",[4041],{"_key":4042,"_type":21,"marks":4043,"text":4044},"d16f04ced61c",[],"As AI agents take on more consequential roles like answering support queries, informing product decisions, and drafting communications, the ability to trace any AI output back to a specific piece of validated content, approved by a named reviewer on a specific date, stops being a nice-to-have and becomes a compliance requirement. Organizations operating under GDPR, SOC 2, HIPAA, and internal governance frameworks need that trail to exist by design. This is also what makes the personal scope motion safe at the individual level.",[],{"_key":4047,"_type":17,"children":4048,"markDefs":4053,"style":3400},"1a7b7fcd1157",[4049],{"_key":4050,"_type":21,"marks":4051,"text":4052},"970d4e9c271f",[],"Deliver: Getting trusted knowledge to where work happens",[],{"_key":4055,"_type":17,"children":4056,"markDefs":4061,"style":25},"a78c446f872d",[4057],{"_key":4058,"_type":21,"marks":4059,"text":4060},"b8a067af7de3",[],"Validated, organized, governed knowledge that nobody encounters is a filing cabinet: packed with useful information that’s totally inaccessible as long as the drawer stays closed. Deliver is the layer that gets trusted knowledge to humans and agents at the moment they need it—in the IDE, in a PR, in Slack, in an agent’s context window—without requiring anyone to open another tab or change their behavior.",[],{"_key":4063,"_type":17,"children":4064,"markDefs":4068,"style":25},"2df6830f2a85",[4065],{"_key":4066,"_type":21,"marks":4067,"text":1742},"0fa5e8be1487",[],[],{"_key":4070,"_type":17,"children":4071,"markDefs":4076,"style":25},"cee17e2c5506",[4072],{"_key":4073,"_type":21,"marks":4074,"text":4075},"b7c725d85c5a",[],"There are two delivery modes:",[],{"_key":4078,"_type":17,"children":4079,"markDefs":4083,"style":25},"322dedc46596",[4080],{"_key":4081,"_type":21,"marks":4082,"text":1742},"0fe56051c1f5",[],[],{"_key":4085,"_type":17,"children":4086,"level":1774,"listItem":1775,"markDefs":4095,"style":25},"63be4108248f",[4087,4091],{"_key":4088,"_type":21,"marks":4089,"text":4090},"1887edc8be79",[1806],"Explicit delivery",{"_key":4092,"_type":21,"marks":4093,"text":4094},"3b16a225af25",[],": When a user asks a question, Stack Internal’s platform returns the best available answer at any confidence level, always with a trust score, a provenance trail, and a clear signal of what’s missing or uncertain.",[],{"_key":4097,"_type":17,"children":4098,"level":1774,"listItem":1775,"markDefs":4107,"style":25},"e8e248811de5",[4099,4103],{"_key":4100,"_type":21,"marks":4101,"text":4102},"cc39f083fb79",[1806],"Proactive delivery",{"_key":4104,"_type":21,"marks":4105,"text":4106},"c848010c03a5",[],": Stack Internal’s platform surfaces relevant knowledge before anyone asks for it. An engineer opens a new service; the system already knows what they’re working on, knows a similar team hit a specific bottleneck six months ago, and surfaces the workaround and the person who owns it. We’re solving the \"I really wish I had known that a week ago\" problem before it happens.",[],{"_key":4109,"_type":17,"children":4110,"markDefs":4114,"style":25},"8aff0b8528e7",[4111],{"_key":4112,"_type":21,"marks":4113,"text":1742},"48dcb5e0e58c",[],[],{"_key":4116,"_type":17,"children":4117,"markDefs":4122,"style":25},"92f44690ddab",[4118],{"_key":4119,"_type":21,"marks":4120,"text":4121},"f901a40087b4",[],"The Model Context Protocol (MCP) makes this layer composable rather than bespoke. Instead of every agent or application building its own retrieval integration—its own data model, its own freshness guarantees, its own approach to trust signals—MCP provides a single, standardized interface that any compliant AI tool can query. That means agents always query the current, validated state of the knowledge graph, not a snapshot from whenever they were last deployed. Updates propagate automatically without redeployment or manual syncing.",[],{"_key":4124,"_type":17,"children":4125,"markDefs":4129,"style":25},"162237f0a32a",[4126],{"_key":4127,"_type":21,"marks":4128,"text":1742},"d8207a3844d9",[],[],{"_key":4131,"_type":17,"children":4132,"markDefs":4137,"style":25},"dff41392585a",[4133],{"_key":4134,"_type":21,"marks":4135,"text":4136},"03fed7718a20",[],"The bidirectional nature of this layer matters, too. The system isn’t just pushing validated content out; agents are flagging content for review, surfacing gaps, and feeding signals back into capture and validation. This way, agents that can’t confidently answer questions become pipeline input, an opportunity for improvement rather than a silent failure. And because MCP is a standard, an internal knowledge base delivered this way can be composed with other MCP servers—think customer data, product telemetry, and external intelligence feeds—to give agents a far richer view than any single knowledge source can provide.",[],{"_key":4139,"_type":17,"children":4140,"markDefs":4145,"style":3400},"b40349b8d495",[4141],{"_key":4142,"_type":21,"marks":4143,"text":4144},"220fd94d1fa9",[],"The agentic enterprise needs a single source of truth",[],{"_key":4147,"_type":17,"children":4148,"markDefs":4153,"style":25},"18ce181f1b25",[4149],{"_key":4150,"_type":21,"marks":4151,"text":4152},"5af36859a3fd",[],"As AI agents move from experimental to operational—handling decisions, automating workflows, acting on behalf of engineers and product teams—the quality of the knowledge they act on becomes a business-critical infrastructure concern. Capture, validate, organize, govern, and deliver represent a complete, production-grade knowledge pipeline. Each stage is individually tractable; a strong engineering team could build all of it.",[],{"_key":4155,"_type":17,"children":4156,"markDefs":4160,"style":25},"98f7a629f426",[4157],{"_key":4158,"_type":21,"marks":4159,"text":1742},"396d53e6874d",[],[],{"_key":4162,"_type":17,"children":4163,"markDefs":4168,"style":25},"03fea232bbeb",[4164],{"_key":4165,"_type":21,"marks":4166,"text":4167},"31d68bada2a3",[],"But should they?",[],{"_key":4170,"_type":17,"children":4171,"markDefs":4175,"style":25},"cc9cea472db5",[4172],{"_key":4173,"_type":21,"marks":4174,"text":1742},"350d3a755af4",[],[],{"_key":4177,"_type":17,"children":4178,"markDefs":4191,"style":25},"2f70d907e76a",[4179,4183,4187],{"_key":4180,"_type":21,"marks":4181,"text":4182},"f07fce5f956d",[],"That answer depends on what your engineering organization is actually ",{"_key":4184,"_type":21,"marks":4185,"text":4186},"a32a2363a639",[3795],"for",{"_key":4188,"_type":21,"marks":4189,"text":4190},"a4b9263093a4",[],". If your competitive advantage lies in the quality of your internal knowledge infrastructure, owning this pipeline is a legitimate strategic investment. But for most organizations—product companies, developer platforms, enterprises whose core offering is something other than knowledge infrastructure—this pipeline just needs to work reliably and continuously, without consuming engineering cycles that should go toward the product customers actually pay for.",[],{"_key":4193,"_type":17,"children":4194,"markDefs":4198,"style":25},"fabef99799cd",[4195],{"_key":4196,"_type":21,"marks":4197,"text":1742},"a83455543936",[],[],{"_key":4200,"_type":17,"children":4201,"markDefs":4206,"style":25},"965391c04bdc",[4202],{"_key":4203,"_type":21,"marks":4204,"text":4205},"c8fee6a26264",[],"The hidden costs of the build-it-yourself approach are obvious in retrospect, but easy to miss when you’re just getting started: connector maintenance as APIs evolve, trust-model tuning as content categories shift, SME workflows that need to scale with headcount, governance requirements that arrive the moment an auditor asks for a trail, delivery-layer updates as new agent frameworks emerge. And none of these are one-time costs. They compound with the sophistication of your AI stack.",[],{"_key":4208,"_type":17,"children":4209,"markDefs":4213,"style":25},"ca58333b7945",[4210],{"_key":4211,"_type":21,"marks":4212,"text":1742},"652717fbbc22",[],[],{"_key":4215,"_type":17,"children":4216,"markDefs":4221,"style":25},"dc4af2530f2d",[4217],{"_key":4218,"_type":21,"marks":4219,"text":4220},"27b8d59e74cc",[],"The Stack Internal platform is built to absorb those costs: capture that runs on a stable connector framework instead of a fleet of bespoke integrations, validation that earns trust automatically before it ever asks a human, organization that scopes knowledge correctly without manual filing, governance with audit and guardrails as foundation rather than roadmap, and delivery that’s MCP-native by default. The platform lets infrastructure run quietly in the background, the way infrastructure should.",[],{"_key":4223,"_type":17,"children":4224,"markDefs":4228,"style":25},"12a65ac93987",[4225],{"_key":4226,"_type":21,"marks":4227,"text":1742},"66b4b8f85ac9",[],[],{"_key":4230,"_type":17,"children":4231,"markDefs":4236,"style":25},"586177d49e76",[4232],{"_key":4233,"_type":21,"marks":4234,"text":4235},"5a9ee62fbf73",[],"The build vs. buy decision for knowledge infrastructure is ultimately a question about organizational focus. Building a vector database is easily achievable. Building a governed, trusted knowledge pipeline is not. Teams that recognize that distinction early spend their engineering capacity on what actually differentiates them from competitors, rather than reinventing knowledge infrastructure.",[],{"_key":4238,"_type":17,"children":4239,"markDefs":4243,"style":25},"7221aff24eab",[4240],{"_key":4241,"_type":21,"marks":4242,"text":1742},"a27572fc946f",[],[],{"_key":4245,"_type":17,"children":4246,"markDefs":4260,"style":25},"69b544117f19",[4247,4251,4256],{"_key":4248,"_type":21,"marks":4249,"text":4250},"057b428071aa",[],"Interested in seeing how Stack Internal handles the full pipeline? Learn more about Stack Internal  ",{"_key":4252,"_type":21,"marks":4253,"text":4255},"8abbbadbe9f8",[4254],"f70ae675b017","here",{"_key":4257,"_type":21,"marks":4258,"text":4259},"ae229e3741d8",[],".",[4261],{"_key":4254,"_type":1734,"href":2668},{"_createdAt":610,"_id":611,"_rev":612,"_type":12,"_updatedAt":613,"description":4263,"slug":4269,"title":625},[4264],{"_key":616,"_type":17,"children":4265,"markDefs":4268,"style":25},[4266],{"_key":619,"_type":21,"marks":4267,"text":621},[],[],{"_type":27,"current":624},{"_type":49,"alt":645,"asset":4271},{"_ref":647,"_type":52},[4273,4276,4279],{"_key":4274,"_ref":4275,"_type":52},"5a160849c94d","769329ff-b7a2-46dc-b9f2-872c75689c2b",{"_key":4277,"_ref":4278,"_type":52},"c488d327c87c","b63e62d7-d78d-4957-98ca-f5c00e08ed3c",{"_key":4280,"_ref":4281,"_type":52},"543c64e49be9","e74572d5-a167-4f88-8ab8-88b5df48ad51",{"_ref":2679,"_type":52},[4284],{"_key":4285,"_ref":3376,"_type":52},"109de8ef1db2",{"_type":27,"current":651},{"_ref":629,"_type":52},{"_createdAt":4289,"_id":4275,"_rev":4290,"_system":4291,"_type":1713,"_updatedAt":4294,"author":4295,"body":4299,"category":4579,"image":4587,"linkedResources":4589,"preface":660,"product":4597,"publishedAt":661,"resourceType":4598,"slug":4601,"subcategory":4602,"title":666,"visible":2672},"2026-07-30T15:20:16Z","deQ2gQeYcozkSPE4orIql4",{"base":4292},{"id":4275,"rev":4293},"6BF5MjQwEIiONhShq7xKc3","2026-11-12T23:10:52Z",[4296],{"_key":4297,"_ref":4298,"_type":52},"21a50ac4b438","wp-author-321",[4300,4308,4320,4328,4336,4344,4353,4371,4379,4387,4395,4403,4411,4419,4427,4435,4443,4451,4459,4489,4497,4505,4513,4521,4529,4537,4544,4562],{"_key":4301,"_type":17,"children":4302,"markDefs":4307,"style":25},"4cab9d14f72a",[4303],{"_key":4304,"_type":21,"marks":4305,"text":4306},"de7646bfe73e",[],"While most platforms stick to storing or retrieving your content, Stack Internal helps you and your AI agents make higher quality decisions by delivering knowledge that is context-aware, vetted by experts, and grounded in traceable evidence. We’ve built Stack Internal using the core curation mechanism that Stack Overflow has been scaling for nearly two decades. Now, we’ve built upon that foundation and enhanced it to fit an AI-first world, putting that trusted mechanism directly into the tools and AI agents your teams already use. Your organization won’t forget what it knows. With Stack Internal, your organization’s memory is always learning and improving so the next person, team, or agent gets decision-grade knowledge.",[],{"_key":4309,"_type":17,"children":4310,"markDefs":4319,"style":25},"bbb3703578db",[4311,4315],{"_key":4312,"_type":21,"marks":4313,"text":4314},"80aef8d69e7a",[1806],"Today, we are announcing the general availability of Stack Internal. ",{"_key":4316,"_type":21,"marks":4317,"text":4318},"a3401ad97d69",[],"Now anyone can create and share their knowledge in a Stack Internal workspace for free by visiting stackinternal.com.",[],{"_key":4321,"_type":17,"children":4322,"markDefs":4327,"style":3400},"547e42531c4c",[4323],{"_key":4324,"_type":21,"marks":4325,"text":4326},"ea8471ebb286",[],"What’s new",[],{"_key":4329,"_type":17,"children":4330,"markDefs":4335,"style":25},"c95273a7f918",[4331],{"_key":4332,"_type":21,"marks":4333,"text":4334},"2404cf4960b2",[],"In July, we introduced the Stack Internal platform to existing customers, giving them new ways to use their Stack Internal Community knowledge through Chat, API, and MCP. On September 30, we are opening the platform to more people: anyone can create a free Starter workspace, while organizations gain new options for bringing in knowledge from their own systems and governing how it is used. This release also expands source coverage and adds tools for expert validation, permissions, and usage visibility. Below is what is available and how to get started.",[],{"_key":4337,"_type":17,"children":4338,"markDefs":4343,"style":3400},"90f1f6289c8f",[4339],{"_key":4340,"_type":21,"marks":4341,"text":4342},"8a193cfa4570",[],"What you can do",[],{"_key":4345,"_type":17,"children":4346,"markDefs":4351,"style":4352},"0bd1c6a27b1a",[4347],{"_key":4348,"_type":21,"marks":4349,"text":4350},"4d60e49c454c",[],"Create a free workspace",[],"h3",{"_key":4354,"_type":17,"children":4355,"markDefs":4368,"style":25},"4efb5b44d804",[4356,4360,4365],{"_key":4357,"_type":21,"marks":4358,"text":4359},"a87d561584e6",[],"Anyone can get started with Stack Internal by creating a Starter workspace. It’s a free way to connect to your top three data sources, capture and store verified knowledge from those sources, and even collaborate with a couple of teammates. Start transforming your daily work into living memory. ",{"_key":4361,"_type":21,"marks":4362,"text":4364},"43a4c805029d",[4363],"9c0ad34a4fb8","See what plan works best for you",{"_key":4366,"_type":21,"marks":4367,"text":4259},"8cc23acea6cf",[],[4369],{"_key":4363,"_type":1734,"href":4370},"https:\u002F\u002Fstackoverflow.co\u002Finternal\u002Fpricing\u002F",{"_key":4372,"_type":17,"children":4373,"markDefs":4378,"style":4352},"6fd651371ee2",[4374],{"_key":4375,"_type":21,"marks":4376,"text":4377},"47f0eeafed8c",[],"Bring data in from anywhere",[],{"_key":4380,"_type":17,"children":4381,"markDefs":4386,"style":25},"0ed06eef0577",[4382],{"_key":4383,"_type":21,"marks":4384,"text":4385},"bf7d34ebf3e7",[],"We have expanded our integrations to safely bring more of your knowledge into your workspace. Ingest critical context persistently from our out-of-the-box connectors. The new Microsoft Teams connector captures learnings from standard, private, and shared channels. And our Slack and Google Docs connectors now respect source permissions, allowing you to ingest restricted and private content securely. With this release, you can ingest knowledge from any source or tool your team uses via our new ingestion API. From wikis, repos, and ticketing tools, we’ve got you covered.",[],{"_key":4388,"_type":17,"children":4389,"markDefs":4394,"style":4352},"c0939dda7924",[4390],{"_key":4391,"_type":21,"marks":4392,"text":4393},"c9b78dd7dc77",[],"Inspect traceable evidence",[],{"_key":4396,"_type":17,"children":4397,"markDefs":4402,"style":25},"2c046b2bc09c",[4398],{"_key":4399,"_type":21,"marks":4400,"text":4401},"594c731a8c9b",[],"Stack Internal evaluates knowledge using signals such as provenance, recency, expertise, corroboration, and human validation. For AI agents, those signals can be translated into a machine-facing trust score so they pull the best answers. The system also automatically flags conflicting information at response time, converting team know-how into validated institutional knowledge.",[],{"_key":4404,"_type":17,"children":4405,"markDefs":4410,"style":4352},"6071c5f160fc",[4406],{"_key":4407,"_type":21,"marks":4408,"text":4409},"e3d32a88de8e",[],"Get expert validation",[],{"_key":4412,"_type":17,"children":4413,"markDefs":4418,"style":25},"b06d7db4fcb3",[4414],{"_key":4415,"_type":21,"marks":4416,"text":4417},"433dd905c2cc",[],"It also automatically detects Subject Matter Experts (SMEs) based on topics. When a critical knowledge gap arises, users and AI agents can trigger an SME validation workflow that notifies the right expert directly in Slack. SMEs can then confirm or update answers in Slack, or they can manage these validation requests through the platform interface.",[],{"_key":4420,"_type":17,"children":4421,"markDefs":4426,"style":4352},"3a4c826988fa",[4422],{"_key":4423,"_type":21,"marks":4424,"text":4425},"2733c2d26c9a",[],"Deliver trusted knowledge anywhere",[],{"_key":4428,"_type":17,"children":4429,"markDefs":4434,"style":25},"f38a6a58e5d6",[4430],{"_key":4431,"_type":21,"marks":4432,"text":4433},"596d2c9b54a6",[],"With our MCP Server, you can push trusted, Stack Internal knowledge into Claude, Codex, Cursor, or any other tool or agent your team uses. The code, answers, or solutions are grounded in your organization’s verified know-how, not just what a model guessed.",[],{"_key":4436,"_type":17,"children":4437,"markDefs":4442,"style":4352},"001d0dbb4db3",[4438],{"_key":4439,"_type":21,"marks":4440,"text":4441},"425e2c21ce76",[],"Access enterprise governance",[],{"_key":4444,"_type":17,"children":4445,"markDefs":4450,"style":25},"809c04cd1ffc",[4446],{"_key":4447,"_type":21,"marks":4448,"text":4449},"06833eb51d63",[],"Establishing trust requires robust governance, so we’re introducing custom roles and permissions. Administrators can appoint knowledge managers and reporting analysts, while managing who can view audit log data or delete content. We have added full activity tracking and self-serve exportable audit trails to provide clear source provenance for every agent decision. To track platform engagement, a new knowledge health and usage dashboard lets you view metrics like Helpful Answer Rate and Daily Active Users.",[],{"_key":4452,"_type":17,"children":4453,"markDefs":4458,"style":4352},"b3f8424ea1dd",[4454],{"_key":4455,"_type":21,"marks":4456,"text":4457},"88f4d7c3d352",[],"Activate your community knowledge",[],{"_key":4460,"_type":17,"children":4461,"markDefs":4484,"style":25},"54181bb1a21f",[4462,4466,4471,4475,4480],{"_key":4463,"_type":21,"marks":4464,"text":4465},"9be9c08398d5",[],"In our recent Stack Internal Community ",{"_key":4467,"_type":21,"marks":4468,"text":4470},"0c0fda396037",[4469],"b941b24a3b53","2026.6",{"_key":4472,"_type":21,"marks":4473,"text":4474},"732cc06dd760",[]," release, we laid a stronger foundation for enterprise trust by delivering centralized admin security controls, including header-enforced API keys, configurable rate limits, and automated lifecycle tools like article expiration to prevent knowledge decay. Building on this momentum, our September 30 release (",{"_key":4476,"_type":21,"marks":4477,"text":4479},"16b997093562",[4478],"c08f97cf6022","2026.7",{"_key":4481,"_type":21,"marks":4482,"text":4483},"24c65219f664",[],") unlocks even richer administrative control and API functionality across your community instance. On the API front, 2026.7 introduces new v3 endpoints for aggregate reputation leaderboards, badge catalog discovery, and user activity filtering for answers and comments, alongside a scoped content-import API that enables seamless migration of questions, answers, and articles with full author attribution.",[4485,4487],{"_key":4469,"_type":1734,"href":4486},"https:\u002F\u002Fsupport.stackenterprise.co\u002Fsupport\u002Fsolutions\u002Farticles\u002F22000294371-stack-internal-enterprise-release-notes#release-2026.6-(sep-2%2C-2026)",{"_key":4478,"_type":1734,"href":4488},"https:\u002F\u002Fsupport.stackenterprise.co\u002Fsupport\u002Fsolutions\u002Farticles\u002F22000294371-stack-internal-enterprise-release-notes#release-2026.7-(september-30%2C-2026)",{"_key":4490,"_type":17,"children":4491,"markDefs":4496,"style":3400},"3de91f5923cb",[4492],{"_key":4493,"_type":21,"marks":4494,"text":4495},"ba2725d6cfa3",[],"What’s next",[],{"_key":4498,"_type":17,"children":4499,"markDefs":4504,"style":25},"ccfac4aeb615",[4500],{"_key":4501,"_type":21,"marks":4502,"text":4503},"1e73e9895e3f",[],"Today, Stack Internal brings knowledge from the places your team works into the tools where people and agents need it. We are building the other half of that cycle too: a way to improve your organization’s knowledge flywheel, so what people learn while working is accessible for the rest of the organization to use.",[],{"_key":4506,"_type":17,"children":4507,"markDefs":4512,"style":25},"18d31cdc9e7b",[4508],{"_key":4509,"_type":21,"marks":4510,"text":4511},"94b777d7d66d",[],"Imagine an engineer working in their IDE and finding a fix to a problem that does not yet exist in your knowledge layer. That knowledge should not disappear when the chat or AI session ends. People should be able to bring it back into Stack Internal effortlessly, preserve the evidence behind it, and decide who can use it, so that the next person or agent that runs into this problem has decision-grade knowledge within seconds.",[],{"_key":4514,"_type":17,"children":4515,"markDefs":4520,"style":25},"47b071d32686",[4516],{"_key":4517,"_type":21,"marks":4518,"text":4519},"91a46e51949e",[],"We are also building 'Scopes' to make those contextual boundaries more useful. You might keep working knowledge in an individual space, share a decision with your project team, then make approved guidance available across the organization. Each step should be intentional, with clear control over who can see the knowledge and which people or agents can use it. The same principle applies when a team’s information needs to stay within that team.",[],{"_key":4522,"_type":17,"children":4523,"markDefs":4528,"style":25},"a205e01e8664",[4524],{"_key":4525,"_type":21,"marks":4526,"text":4527},"6108cd9b7e68",[],"Over time, we want Stack Internal to make aging knowledge and conflicting sources easier to spot, involve the right experts, and surface relevant knowledge before someone thinks to search. The platform already helps bring knowledge in and deliver it where it is needed. We are building toward a system that learns from the people and agents using it.",[],{"_key":4530,"_type":17,"children":4531,"markDefs":4536,"style":25},"cedee7bf37ba",[4532],{"_key":4533,"_type":21,"marks":4534,"text":4535},"c462490a2144",[],"Stay tuned. We can't wait to show you what we've built.",[],{"_key":4538,"_type":17,"children":4539,"markDefs":4543,"style":25},"29ea9ab1685f",[4540],{"_key":4541,"_type":21,"marks":4542,"text":1742},"302f68775268",[],[],{"_key":4545,"_type":17,"children":4546,"markDefs":4559,"style":25},"b78e9b76de14",[4547,4551,4555],{"_key":4548,"_type":21,"marks":4549,"text":4550},"e702d658ab8b",[],"Ready to try Stack Internal? ",{"_key":4552,"_type":21,"marks":4553,"text":4350},"7df0dbca19a4",[4554],"a45956c175be",{"_key":4556,"_type":21,"marks":4557,"text":4558},"860f624219dd",[]," and start with the knowledge your team already has.",[4560],{"_key":4554,"_type":1734,"href":4561},"http:\u002F\u002Fstackinternal.com\u002Fsignup",{"_key":4563,"_type":17,"children":4564,"markDefs":4576,"style":25},"953e8ec361e8",[4565,4569,4573],{"_key":4566,"_type":21,"marks":4567,"text":4568},"3f155d4aa4bc",[],"Already a Stack Internal customer? Sign in to your workspace or contact your account team about enabling the platform. Check out the guide ",{"_key":4570,"_type":21,"marks":4571,"text":4255},"45c730a85329",[4572],"d92292962581",{"_key":4574,"_type":21,"marks":4575,"text":4259},"b047b2c60fbc",[],[4577],{"_key":4572,"_type":1734,"href":4578},"https:\u002F\u002Fsupport.stackinternal.com\u002Fsupport\u002Fsolutions\u002Farticles\u002F22000296017-getting-started-with-stack-internal",{"_createdAt":610,"_id":611,"_rev":612,"_type":12,"_updatedAt":613,"description":4580,"slug":4586,"title":625},[4581],{"_key":616,"_type":17,"children":4582,"markDefs":4585,"style":25},[4583],{"_key":619,"_type":21,"marks":4584,"text":621},[],[],{"_type":27,"current":624},{"_type":49,"alt":657,"asset":4588},{"_ref":659,"_type":52},[4590,4592,4595],{"_key":4591,"_ref":4278,"_type":52},"24888798d2bc",{"_key":4593,"_ref":4594,"_type":52},"46504ba6be4c","c66d2ecc-ddad-4847-82e9-e8e9730a5978",{"_key":4596,"_ref":4281,"_type":52},"9f9582d56ec9",{"_ref":2679,"_type":52},[4599],{"_key":4600,"_ref":3376,"_type":52},"d0e945dcd6e8",{"_type":27,"current":663},{"_ref":629,"_type":52},{"_createdAt":4604,"_id":4605,"_rev":4606,"_system":4607,"_type":1713,"_updatedAt":4610,"body":4611,"category":5583,"displayMinimal":2672,"image":5591,"linkedResources":5593,"preface":671,"product":5601,"publishedAt":672,"resourceType":5602,"slug":5605,"subcategory":5606,"title":677,"visible":2672},"2026-04-29T17:30:44Z","3de288b0-5dfa-4b76-9cf6-68b1b4cb19ec","HuDCXJpX86rGPuT3ZkGv2j",{"base":4608},{"id":4605,"rev":4609},"emZKQHDZAHJQnZeDjt2Aq0","2026-04-30T17:51:00Z",[4612,4620,4636,4652,4663,4671,4679,4720,4728,4760,4786,4845,4895,4903,4911,4919,4931,4943,4948,4956,4967,4989,4993,5001,5012,5023,5027,5035,5046,5076,5080,5088,5099,5110,5114,5122,5133,5153,5157,5165,5173,5181,5189,5207,5215,5240,5248,5256,5264,5272,5280,5292,5304,5316,5328,5340,5358,5366,5374,5386,5398,5410,5431,5443,5451,5459,5466,5474,5486,5506,5518,5530,5542,5554,5566],{"_key":4613,"_type":17,"children":4614,"markDefs":4619,"style":4352},"df4d4bb13785",[4615],{"_key":4616,"_type":21,"marks":4617,"text":4618},"a8a9979332e9",[1806],"Key takeaways",[],{"_key":4621,"_type":17,"children":4622,"level":1774,"listItem":1775,"markDefs":4635,"style":25},"85f1eda00260",[4623,4627,4631],{"_key":4624,"_type":21,"marks":4625,"text":4626},"d85420a98e8e",[],"The software development lifecycle is evolving from a human-driven, sequential process into an ",{"_key":4628,"_type":21,"marks":4629,"text":4630},"452ebd276091",[1806],"agentic SDLC (ASDLC)",{"_key":4632,"_type":21,"marks":4633,"text":4634},"447acb7e1ba7",[]," in which AI agents autonomously plan, code, test, and iterate alongside human engineers.",[],{"_key":4637,"_type":17,"children":4638,"level":1774,"listItem":1775,"markDefs":4651,"style":25},"72f4444533a6",[4639,4643,4647],{"_key":4640,"_type":21,"marks":4641,"text":4642},"1185a891187a",[],"AI agents need more than generic intelligence: They require ",{"_key":4644,"_type":21,"marks":4645,"text":4646},"fd06eb9ead60",[1806],"deep, verified internal context",{"_key":4648,"_type":21,"marks":4649,"text":4650},"466528c7f67c",[]," to make decisions that align with your organization's standards, architecture, and history.",[],{"_key":4653,"_type":17,"children":4654,"level":1774,"listItem":1775,"markDefs":4662,"style":25},"cc77bedccdd8",[4655,4658],{"_key":4656,"_type":21,"marks":4657,"text":2721},"df0616183f76",[1806],{"_key":4659,"_type":21,"marks":4660,"text":4661},"141cae08d282",[]," is the trusted knowledge layer that feeds your agentic workflow with company-specific context, reducing hallucinations, cutting rework, and accelerating delivery.",[],{"_key":4664,"_type":17,"children":4665,"markDefs":4670,"style":3400},"9c10206260f3",[4666],{"_key":4667,"_type":21,"marks":4668,"text":4669},"7dbf0782e351",[1806],"The SDLC is having its biggest moment since agile",[],{"_key":4672,"_type":17,"children":4673,"markDefs":4678,"style":25},"c0ae5a4e53ad",[4674],{"_key":4675,"_type":21,"marks":4676,"text":4677},"ee3e9608d75c",[],"The software development lifecycle (SDLC) is a structured framework that guides engineering teams through the end-to-end process of planning, building, testing, and deploying software. It breaks development into defined phases (typically encompassing requirements gathering, design, implementation, testing, and maintenance) to bring predictability and consistency to complex projects. Though the framework has evolved from waterfall to agile to DevOps, it’s always been a human-driven process.",[],{"_key":4680,"_type":17,"children":4681,"markDefs":4713,"style":25},"e3490d4efe72",[4682,4686,4691,4695,4700,4704,4709],{"_key":4683,"_type":21,"marks":4684,"text":4685},"ff57b92752aa",[],"That’s changing fast. ",{"_key":4687,"_type":21,"marks":4688,"text":4690},"3bc7b41294cf",[4689],"c9e0cf91d18b","AI agents",{"_key":4692,"_type":21,"marks":4693,"text":4694},"931452ea260c",[]," are autonomous collaborators capable of planning features, writing and refactoring code, generating tests, and flagging integration issues, all without waiting for a human to prompt each step. According to Anthropic's ",{"_key":4696,"_type":21,"marks":4697,"text":4699},"3c24ad952f8a",[4698],"06f614e12c83","2026 Agentic Coding report",{"_key":4701,"_type":21,"marks":4702,"text":4703},"72ee161d2e31",[],", we’re entering an era in which AI agents can perform complex engineering tasks with minimal human intervention. Meanwhile, ",{"_key":4705,"_type":21,"marks":4706,"text":4708},"78d25e8f00e0",[4707],"f85c32bc15fb","PwC predicts",{"_key":4710,"_type":21,"marks":4711,"text":4712},"8d9441a0ff4a",[]," that more than half of engineering teams will run a fully agentic SDLC by 2027.",[4714,4716,4718],{"_key":4689,"_type":1734,"href":4715},"https:\u002F\u002Fstackoverflow.blog\u002F2025\u002F04\u002F17\u002Fwait-what-is-agentic-ai\u002F",{"_key":4698,"_type":1734,"href":4717},"https:\u002F\u002Fresources.anthropic.com\u002Fhubfs\u002F2026%20Agentic%20Coding%20Trends%20Report.pdf",{"_key":4707,"_type":1734,"href":4719},"https:\u002F\u002Fwww.pwc.com\u002Fm1\u002Fen\u002Fpublications\u002F2026\u002Fdocs\u002Fgen-ai-survey.pdf",{"_key":4721,"_type":17,"children":4722,"markDefs":4727,"style":3400},"e8184f362278",[4723],{"_key":4724,"_type":21,"marks":4725,"text":4726},"64071e0377e2",[1806],"What is the agentic software development lifecycle (ASDLC)?",[],{"_key":4729,"_type":17,"children":4730,"markDefs":4759,"style":25},"19ff5c79d226",[4731,4735,4739,4743,4747,4751,4755],{"_key":4732,"_type":21,"marks":4733,"text":4734},"6ee4f6c0ae3f",[],"The ",{"_key":4736,"_type":21,"marks":4737,"text":4738},"e728090dfeb3",[1806],"agentic software development lifecycle (ASDLC)",{"_key":4740,"_type":21,"marks":4741,"text":4742},"e555b8490619",[]," is a new software delivery model in which AI agents act as autonomous collaborators throughout every phase of development, from requirements gathering through maintenance. The traditional SDLC depends on humans to execute each phase, but the ASDLC delegates that execution to AI agents that can reason, plan, use tools, call APIs, write and run code, and self-correct based on feedback. Humans shift from ",{"_key":4744,"_type":21,"marks":4745,"text":4746},"1ac3d443e948",[3795],"doing",{"_key":4748,"_type":21,"marks":4749,"text":4750},"233ab5c25601",[]," to ",{"_key":4752,"_type":21,"marks":4753,"text":4754},"596dbd35efc0",[3795],"directing",{"_key":4756,"_type":21,"marks":4757,"text":4758},"4c218442cbc5",[],": setting intent, reviewing outputs, and validating decisions.",[],{"_key":4761,"_type":17,"children":4762,"markDefs":4781,"style":25},"1658b7a6f6db",[4763,4768,4772,4777],{"_key":4764,"_type":21,"marks":4765,"text":4767},"56cce9343cef",[4766],"5067acd67378","EPAM",{"_key":4769,"_type":21,"marks":4770,"text":4771},"392a6a3c02ae",[],"'s Agentic Development Lifecycle (ADLC) framework describes this paradigm shift as a move from “humans code everything” to “humans express intent and agents execute.” ",{"_key":4773,"_type":21,"marks":4774,"text":4776},"65b7cfddc2a2",[4775],"ad4dc930c2e7","McKinsey",{"_key":4778,"_type":21,"marks":4779,"text":4780},"8aef2a38c1bb",[],"'s research on the agentic organization echoes this framing: The most forward-thinking teams are redesigning their workflows around AI agency, not just adding AI tools on top of existing processes.",[4782,4784],{"_key":4766,"_type":1734,"href":4783},"https:\u002F\u002Fwww.epam.com\u002Finsights\u002Fai\u002Fblogs\u002Fagentic-development-lifecycle-explained",{"_key":4775,"_type":1734,"href":4785},"https:\u002F\u002Fwww.mckinsey.com\u002Fcapabilities\u002Fpeople-and-organizational-performance\u002Four-insights\u002Fthe-agentic-organization-contours-of-the-next-paradigm-for-the-ai-era",{"_key":4787,"_type":4788,"rows":4789},"7a7b557a598d","table",[4790,4797,4803,4809,4815,4821,4827,4833,4839],{"_key":4791,"_type":4792,"cells":4793},"476af885-c132-40b0-a9dc-9105b6a34f2d","tableRow",[4794,4795,4796],"Dimension","Traditional SDLC","Agentic SDLC",{"_key":4798,"_type":4792,"cells":4799},"61a104de-185d-47ec-b7cb-134d14a01929",[4800,4801,4802],"Who writes the code","Human engineers","AI agents (with human oversight)",{"_key":4804,"_type":4792,"cells":4805},"be749a0b-83b8-48b6-a616-e9e1c324f625",[4806,4807,4808],"Process type","Sequential or iterative, human-paced","Continuous, self-improving",{"_key":4810,"_type":4792,"cells":4811},"29f75236-1355-4352-838b-47fa5e5a982f",[4812,4813,4814],"Decision-making","Human-led at each phase","Agent-led, human-validated",{"_key":4816,"_type":4792,"cells":4817},"3eb725d8-72b1-4c6d-af5e-3d95fc66defb",[4818,4819,4820],"Knowledge source","Team documentation, institutional knowledge","Verified internal knowledge bases",{"_key":4822,"_type":4792,"cells":4823},"6d81ef1b-c5c5-40a0-8dcc-8e465568b591",[4824,4825,4826],"Speed","Sprint-based, weeks to months","Near-continuous delivery",{"_key":4828,"_type":4792,"cells":4829},"5847084f-e4eb-4ad6-bfc2-e348a1083481",[4830,4831,4832],"Error correction","Manual QA and code review","Autonomous testing and agent self-correction",{"_key":4834,"_type":4792,"cells":4835},"3fffe246-4954-4685-b0ed-f204a56faadf",[4836,4837,4838],"Scalability","Limited by team headcount","Scales with compute and context",{"_key":4840,"_type":4792,"cells":4841},"681c0365-0b92-4fe4-8b23-3c8f7b16e1f6",[4842,4843,4844],"Risk","Human error, knowledge silos","Hallucinations, context gaps, misaligned outputs",{"_key":4846,"_type":17,"children":4847,"markDefs":4887,"style":25},"d4bcad55b61f",[4848,4852,4857,4861,4866,4870,4875,4879,4883],{"_key":4849,"_type":21,"marks":4850,"text":4851},"6e19ddb7655d",[],"The limiting factor in any ASDLC implementation isn't agent capability. Instead, it’s ",{"_key":4853,"_type":21,"marks":4854,"text":4856},"b544174608ea",[4855],"471c8e5804e9","the quality of the training data",{"_key":4858,"_type":21,"marks":4859,"text":4860},"2d7f882b6ec4",[],", whether that data is ",{"_key":4862,"_type":21,"marks":4863,"text":4865},"5a924078e0ee",[4864],"e17e1559c5bb","community-validated",{"_key":4867,"_type":21,"marks":4868,"text":4869},"81ac9c08fee3",[],", and ",{"_key":4871,"_type":21,"marks":4872,"text":4874},"7cd1a2f7b2e4",[4873],"285005f946b6","the all-important context",{"_key":4876,"_type":21,"marks":4877,"text":4878},"31ce16e4f848",[]," behind engineering decisions. An agent that writes code without understanding your internal architecture, naming conventions, legacy decisions, or compliance requirements will produce outputs that are technically correct but organizationally wrong. That's where a knowledge layer like ",{"_key":4880,"_type":21,"marks":4881,"text":2721},"b1118a32d167",[4882],"fa5cba34a263",{"_key":4884,"_type":21,"marks":4885,"text":4886},"cfa27aa4b9bc",[]," becomes mission-critical.",[4888,4890,4892,4894],{"_key":4855,"_type":1734,"href":4889},"https:\u002F\u002Fstackoverflow.co\u002Finternal\u002Fresources\u002Fwhy-high-quality-data-is-essential-for-agentic-ai\u002F",{"_key":4864,"_type":1734,"href":4891},"https:\u002F\u002Fstackoverflow.co\u002Finternal\u002Fresources\u002Fwhy-community-validated-data-matters-more-than-ever\u002F",{"_key":4873,"_type":1734,"href":4893},"https:\u002F\u002Fstackoverflow.blog\u002F2026\u002F03\u002F12\u002Fenterprise-ai-needs-more-than-foundation-models\u002F",{"_key":4882,"_type":1734,"href":2668},{"_key":4896,"_type":17,"children":4897,"markDefs":4902,"style":3400},"511961d58eb1",[4898],{"_key":4899,"_type":21,"marks":4900,"text":4901},"9a45000aa73e",[1806],"The 6 phases of ASDLC (and what changes at each one)",[],{"_key":4904,"_type":17,"children":4905,"markDefs":4910,"style":25},"18f2be434e60",[4906],{"_key":4907,"_type":21,"marks":4908,"text":4909},"84c09022a3d5",[],"Adapting the classic six-phase SDLC framework—planning, analysis, design, implementation, testing, and integration\u002Fmaintenance—reveals how profoundly agentic AI transforms each stage.",[],{"_key":4912,"_type":17,"children":4913,"markDefs":4918,"style":4352},"ff3aef7cac44",[4914],{"_key":4915,"_type":21,"marks":4916,"text":4917},"5b5912e172c3",[1806],"Phase 1: Planning",[],{"_key":4920,"_type":17,"children":4921,"markDefs":4930,"style":25},"202d2c20d768",[4922,4926],{"_key":4923,"_type":21,"marks":4924,"text":4925},"3ebd993c73be",[1806],"Traditional SDLC:",{"_key":4927,"_type":21,"marks":4928,"text":4929},"4cf3ec5e4b4e",[]," Product managers and engineering leads define scope, estimate timelines, allocate resources, and document requirements in tickets and PRDs. This phase is largely manual, meeting-heavy, and dependent on institutional knowledge held by senior engineers.",[],{"_key":4932,"_type":17,"children":4933,"markDefs":4942,"style":25},"da95bf8522be",[4934,4938],{"_key":4935,"_type":21,"marks":4936,"text":4937},"fdb70e8b1409",[1806],"In the ASDLC:",{"_key":4939,"_type":21,"marks":4940,"text":4941},"145a7d4ef3fd",[]," AI agents can assist in generating project plans from high-level prompts, surfacing related prior work, flagging architectural conflicts before any code is written, and estimating complexity based on historical velocity data.",[],{"_key":4944,"_type":4945,"points":4946},"2326cb40b069","keyPoints",[4947],"Where Stack Internal fits: For agents to produce accurate plans, they need to understand your codebase structure, your team conventions, and the rationale behind your past architectural decisions. Stack Internal's Ingestion engine surfaces verified internal Q&A, documentation, and discussions from your engineering community, giving agents the organizational memory they need to plan intelligently.",{"_key":4949,"_type":17,"children":4950,"markDefs":4955,"style":4352},"a8954eaea9fc",[4951],{"_key":4952,"_type":21,"marks":4953,"text":4954},"bf611a63d073",[1806],"Phase 2: Analysis",[],{"_key":4957,"_type":17,"children":4958,"markDefs":4966,"style":25},"1f0d468f6a76",[4959,4962],{"_key":4960,"_type":21,"marks":4961,"text":4925},"b5e7a4bddb19",[1806],{"_key":4963,"_type":21,"marks":4964,"text":4965},"c4a498aefdf7",[]," Business analysts and architects translate business requirements into technical specifications. This involves deep interviews, whiteboard sessions, and documentation reviews. It’s a work-intensive process that can take weeks.",[],{"_key":4968,"_type":17,"children":4969,"markDefs":4986,"style":25},"cc9be3d42e9a",[4970,4973,4977,4982],{"_key":4971,"_type":21,"marks":4972,"text":4937},"841d53860df5",[1806],{"_key":4974,"_type":21,"marks":4975,"text":4976},"38520645dc4d",[]," Agents can parse existing documentation, prior tickets, API contracts, and internal wikis to automatically generate technical specs, identify gaps in requirements, and propose solution approaches. A ",{"_key":4978,"_type":21,"marks":4979,"text":4981},"f9082cadde73",[4980],"08dff707b349","KPMG",{"_key":4983,"_type":21,"marks":4984,"text":4985},"331a82963848",[]," report found that agentic AI can compress the analysis phase from weeks to hours for well-instrumented teams.",[4987],{"_key":4980,"_type":1734,"href":4988},"https:\u002F\u002Fkpmg.com\u002Fkpmg-us\u002Fcontent\u002Fdam\u002Fkpmg\u002Fpdf\u002F2025\u002Fagentic-ai-is-revolutionizing-software-development-1.pdf",{"_key":4990,"_type":4945,"points":4991},"a8f913d91b62",[4992],"Where Stack Internal fits: Standard LLMs don't know your systems. They can't analyze requirements against your proprietary data models, internal APIs, or legacy codebase constraints. Stack Internal provides the grounded, human-verified knowledge these agents need to produce specific analysis that's relevant to your specific environment, rather than a generic best practice.",{"_key":4994,"_type":17,"children":4995,"markDefs":5000,"style":4352},"9fd0cca956bf",[4996],{"_key":4997,"_type":21,"marks":4998,"text":4999},"eebb9b00d3c6",[1806],"Phase 3: Design",[],{"_key":5002,"_type":17,"children":5003,"markDefs":5011,"style":25},"d16986e99505",[5004,5007],{"_key":5005,"_type":21,"marks":5006,"text":4925},"1ab5b11a2718",[1806],{"_key":5008,"_type":21,"marks":5009,"text":5010},"4b00b8aafaa9",[]," Senior engineers and architects design system components, data flows, and interfaces. Designs are produced in isolation, often divorced from institutional knowledge of why previous decisions were made.",[],{"_key":5013,"_type":17,"children":5014,"markDefs":5022,"style":25},"493f81c9c25f",[5015,5018],{"_key":5016,"_type":21,"marks":5017,"text":4937},"bea332fbed5c",[1806],{"_key":5019,"_type":21,"marks":5020,"text":5021},"80dcc2d6a20b",[]," Agents can generate architecture proposals, evaluate multiple design patterns against internal constraints, and flag potential conflicts with existing services. Every part of the process is informed by your organization's design history.",[],{"_key":5024,"_type":4945,"points":5025},"7f4e83cb2629",[5026],"Where Stack Internal fits: Architecture decisions don't happen in a vacuum. An agent designing a new microservice needs to understand how similar services were built in the past, which patterns were tried and abandoned, and which standards are currently enforced. Stack Internal makes this institutional memory accessible and queryable.",{"_key":5028,"_type":17,"children":5029,"markDefs":5034,"style":4352},"4b15055b167d",[5030],{"_key":5031,"_type":21,"marks":5032,"text":5033},"86cf82916233",[1806],"Phase 4: Implementation",[],{"_key":5036,"_type":17,"children":5037,"markDefs":5045,"style":25},"dfd35b4f02da",[5038,5041],{"_key":5039,"_type":21,"marks":5040,"text":4925},"d050274589b3",[1806],{"_key":5042,"_type":21,"marks":5043,"text":5044},"e230056bbdb3",[]," Engineers write code according to specs, following (or not!) internal coding standards, style guides, and architectural patterns. Quality varies by individual, and knowledge tends to be siloed.",[],{"_key":5047,"_type":17,"children":5048,"markDefs":5073,"style":25},"aaf3aa7f3fa1",[5049,5052,5056,5061,5065,5069],{"_key":5050,"_type":21,"marks":5051,"text":4937},"6ca016ae1573",[1806],{"_key":5053,"_type":21,"marks":5054,"text":5055},"40ab807f96b6",[]," AI agents write, refactor, and document code. This is the phase where ",{"_key":5057,"_type":21,"marks":5058,"text":5060},"43d819c18d5d",[5059],"e964db3d446a","the shift from the traditional SDLC",{"_key":5062,"_type":21,"marks":5063,"text":5064},"254db224aeb7",[]," is most dramatic and most risky. Agents are highly capable of generating syntactically correct code, but they are much less reliable when it comes to generating ",{"_key":5066,"_type":21,"marks":5067,"text":5068},"b8cf4227f5d8",[3795],"organizationally correct",{"_key":5070,"_type":21,"marks":5071,"text":5072},"1299162209eb",[]," code—unless, of course, they have access to the context behind your codebase and architecture decisions.",[5074],{"_key":5059,"_type":1734,"href":5075},"https:\u002F\u002Fstackoverflow.blog\u002F2026\u002F02\u002F24\u002Fdogfood-so-nutritious-it-s-building-the-future-of-sdlcs\u002F",{"_key":5077,"_type":4945,"points":5078},"417da4026eb7",[5079],"Where Stack Internal fits: This is Stack Internal's highest-impact use case. When an agent implements a feature, it should automatically know things like: What internal libraries should it use? What naming conventions apply? What authentication patterns are standard here? Stack Internal feeds agents this ground-truth context, drawn from your team's own verified knowledge. The result? Developers who can confidently orchestrate agents that deliver compliant, production-ready code.",{"_key":5081,"_type":17,"children":5082,"markDefs":5087,"style":4352},"676f5a95640d",[5083],{"_key":5084,"_type":21,"marks":5085,"text":5086},"a05d7156cb6d",[1806],"Phase 5: Testing",[],{"_key":5089,"_type":17,"children":5090,"markDefs":5098,"style":25},"64ece2a41ab7",[5091,5094],{"_key":5092,"_type":21,"marks":5093,"text":4925},"ac40849eec09",[1806],{"_key":5095,"_type":21,"marks":5096,"text":5097},"2e00a95399ec",[]," QA engineers write test cases, run regression suites, and report bugs. Testing is often a bottleneck, performed at the end of the cycle when changes are most expensive to make.",[],{"_key":5100,"_type":17,"children":5101,"markDefs":5109,"style":25},"bd44f8622373",[5102,5105],{"_key":5103,"_type":21,"marks":5104,"text":4937},"e618f7f6bff3",[1806],{"_key":5106,"_type":21,"marks":5107,"text":5108},"a1d66fb24820",[]," Agents generate unit tests, integration tests, and edge case scenarios in parallel with implementation. They can also evaluate test coverage, identify gaps, and re-run tests automatically after code changes, shifting quality left.",[],{"_key":5111,"_type":4945,"points":5112},"3306394afa4c",[5113],"Where Stack Internal fits: Effective testing requires knowing what your system is supposed to do—including undocumented behaviors, known edge cases, and prior bugs. Stack Internal gives agents access to your team's historical testing knowledge, including past incident postmortems, known failure modes, and QA conventions that have been validated by your engineers.",{"_key":5115,"_type":17,"children":5116,"markDefs":5121,"style":4352},"33bd506150b3",[5117],{"_key":5118,"_type":21,"marks":5119,"text":5120},"94a13e21ec35",[1806],"Phase 6: Integration and maintenance",[],{"_key":5123,"_type":17,"children":5124,"markDefs":5132,"style":25},"346da25ace4d",[5125,5128],{"_key":5126,"_type":21,"marks":5127,"text":4925},"98397177e112",[1806],{"_key":5129,"_type":21,"marks":5130,"text":5131},"9eb105e605f6",[]," Deployment is a high-stakes event. Maintenance involves human engineers monitoring logs, responding to incidents, and manually patching issues. Knowledge about system behavior lives primarily in the heads of the people who built it. If those people forget the details or move on to other roles, that context-rich knowledge is lost.",[],{"_key":5134,"_type":17,"children":5135,"markDefs":5151,"style":25},"66078ac5b8c3",[5136,5139,5143,5147],{"_key":5137,"_type":21,"marks":5138,"text":4937},"a769523c543f",[1806],{"_key":5140,"_type":21,"marks":5141,"text":5142},"378b02268df7",[]," Agents can continuously monitor deployed systems, detect anomalies, propose patches, and even initiate rollback procedures. ",{"_key":5144,"_type":21,"marks":5145,"text":4981},"2507c2aece0b",[5146],"0fe9357031de",{"_key":5148,"_type":21,"marks":5149,"text":5150},"01f498f40326",[]," identifies this as one of the highest-value ASDLC phases because agentic AI can dramatically reduce mean time to resolution (MTTR).",[5152],{"_key":5146,"_type":1734,"href":4988},{"_key":5154,"_type":4945,"points":5155},"55a173ffee95",[5156],"Where Stack Internal fits: Incident response depends on knowing how the system was designed, what changed recently, and what fixes have been tried before. Stack Internal's searchable knowledge base gives agents (and the engineers who oversee them) instant access to the institutional memory needed to diagnose and resolve issues quickly.",{"_key":5158,"_type":17,"children":5159,"markDefs":5164,"style":3400},"ed4ac770a386",[5160],{"_key":5161,"_type":21,"marks":5162,"text":5163},"e4a8e3af8d94",[1806],"Real-world proof: How HP is doing it",[],{"_key":5166,"_type":17,"children":5167,"markDefs":5172,"style":25},"cae470e95191",[5168],{"_key":5169,"_type":21,"marks":5170,"text":5171},"61e368191b49",[],"HP's modernization of its software development lifecycle offers one of the clearest examples of ASDLC principles in production.",[],{"_key":5174,"_type":17,"children":5175,"markDefs":5180,"style":25},"8239ba4408ad",[5176],{"_key":5177,"_type":21,"marks":5178,"text":5179},"95343a85fd10",[],"Partnering with Stack Overflow, HP integrated Stack Overflow's MCP (model context protocol) Server to connect AI coding agents with Stack Overflow's trusted, community-verified knowledge base. As a result, agents could draw on accurate, high-quality technical knowledge at the point of code generation, reducing hallucinations and improving output quality.",[],{"_key":5182,"_type":17,"children":5183,"markDefs":5188,"style":25},"d2d1b764117f",[5184],{"_key":5185,"_type":21,"marks":5186,"text":5187},"ec3f17e6d8e0",[],"Rather than relying on LLMs trained on generic web data, HP's agents were grounded in verified knowledge specific to the tools, frameworks, and patterns their teams actually use.",[],{"_key":5190,"_type":17,"children":5191,"markDefs":5204,"style":25},"57d19f6c1eef",[5192,5196,5201],{"_key":5193,"_type":21,"marks":5194,"text":5195},"c93f34d0881b",[],"Read about ",{"_key":5197,"_type":21,"marks":5198,"text":5200},"3e1d640d7288",[5199],"ce45bd9334bd","how HP is modernizing their SDLCS with Stack Overflow’s MCP Server",{"_key":5202,"_type":21,"marks":5203,"text":4259},"a33508a6d2f5",[],[5205],{"_key":5199,"_type":1734,"href":5206},"https:\u002F\u002Fstackoverflow.blog\u002F2025\u002F12\u002F12\u002Fhow-stack-overflow-s-mcp-server-is-helping-hp-modernize-the-software-development-lifecycle\u002F",{"_key":5208,"_type":17,"children":5209,"markDefs":5214,"style":3400},"2613b99946d7",[5210],{"_key":5211,"_type":21,"marks":5212,"text":5213},"359f70e94c24",[1806],"The context gap: Why most ASDLC implementations stall",[],{"_key":5216,"_type":17,"children":5217,"markDefs":5238,"style":25},"bfd62973e9a8",[5218,5222,5226,5230,5234],{"_key":5219,"_type":21,"marks":5220,"text":5221},"210d155302df",[],"The promise of the ASDLC is enormous, but for many teams, the reality is frustrating. Agents hallucinate. They suggest drawing from unapproved libraries. They design services that conflict with existing systems. They write code that passes tests but violates internal standards no one bothered to document in a machine-readable format. ",{"_key":5223,"_type":21,"marks":5224,"text":4776},"8f016843ec61",[5225],"1554f29d8f3d",{"_key":5227,"_type":21,"marks":5228,"text":5229},"5b43f5588270",[],"'s research on agentic organizations identifies ",{"_key":5231,"_type":21,"marks":5232,"text":5233},"6e914cc45244",[1806],"context deprivation",{"_key":5235,"_type":21,"marks":5236,"text":5237},"3c26deb5bd45",[]," as the primary reason agentic AI underperforms in enterprise settings.",[5239],{"_key":5225,"_type":1734,"href":4785},{"_key":5241,"_type":17,"children":5242,"markDefs":5247,"style":25},"8b162aa98562",[5243],{"_key":5244,"_type":21,"marks":5245,"text":5246},"49ea90a7632e",[],"Standard LLMs are trained on public data, which means they know a lot about software development in general and almost almost nothing about your development environment in particular. Your internal APIs, your architectural decisions, your incident history, your team conventions, your compliance requirements—a generic model has no access to that kind of knowledge.",[],{"_key":5249,"_type":17,"children":5250,"markDefs":5255,"style":25},"591c9159735c",[5251],{"_key":5252,"_type":21,"marks":5253,"text":5254},"a8087eb0102f",[],"Closing this gap requires a new kind of infrastructure: a trusted, continuously updated, human-verified knowledge layer that sits between your internal data and your agents. That's what Stack Internal is built to do.",[],{"_key":5257,"_type":17,"children":5258,"markDefs":5263,"style":3400},"9a08d2c159ba",[5259],{"_key":5260,"_type":21,"marks":5261,"text":5262},"3371d42d2aa3",[1806],"Stack Internal: The knowledge layer your ASDLC needs",[],{"_key":5265,"_type":17,"children":5266,"markDefs":5271,"style":25},"64bd1eae0343",[5267],{"_key":5268,"_type":21,"marks":5269,"text":5270},"200d03f25aaa",[],"Stack Internal transforms your organization's collective engineering knowledge—questions asked and answered, decisions made and documented, solutions validated in production—into a structured, searchable, agent-accessible knowledge base.",[],{"_key":5273,"_type":17,"children":5274,"markDefs":5279,"style":25},"fe9b10e627d5",[5275],{"_key":5276,"_type":21,"marks":5277,"text":5278},"d2a5989497a5",[],"Here's how it enables each layer of the ASDLC:",[],{"_key":5281,"_type":17,"children":5282,"level":1774,"listItem":1775,"markDefs":5291,"style":25},"43bc6e1873c8",[5283,5287],{"_key":5284,"_type":21,"marks":5285,"text":5286},"d277dee5c3d4",[1806],"Ingestion:",{"_key":5288,"_type":21,"marks":5289,"text":5290},"676f8ee735d3",[]," Stack Internal automatically converts content from your internal knowledge sources—wikis, PDFs, code comments, documentation, Q&A threads—into structured, human-verified answers that are accessible the moment an agent needs them.",[],{"_key":5293,"_type":17,"children":5294,"level":1774,"listItem":1775,"markDefs":5303,"style":25},"fc68a8e7a5c0",[5295,5299],{"_key":5296,"_type":21,"marks":5297,"text":5298},"2b5471fa0451",[1806],"Human-verified context:",{"_key":5300,"_type":21,"marks":5301,"text":5302},"e79e2fc10a5e",[]," Unlike raw data scraped from internal systems, Stack Internal applies community validation signals (votes, accepted answers, expert contributions) to ensure agents receive community-validated contextual knowledge.",[],{"_key":5305,"_type":17,"children":5306,"level":1774,"listItem":1775,"markDefs":5315,"style":25},"8a2960616b12",[5307,5311],{"_key":5308,"_type":21,"marks":5309,"text":5310},"3feae80d7799",[1806],"MCP Server integration:",{"_key":5312,"_type":21,"marks":5313,"text":5314},"3f490263857a",[]," Through Stack Overflow's Model Context Protocol Server, agents can query Stack Internal directly during code generation, design, or debugging. The MCP server pulls organization-specific knowledge into the agent's context window in real time.",[],{"_key":5317,"_type":17,"children":5318,"level":1774,"listItem":1775,"markDefs":5327,"style":25},"e9d7ff966b2c",[5319,5323],{"_key":5320,"_type":21,"marks":5321,"text":5322},"3362c1cbc283",[1806],"Fewer hallucinations:",{"_key":5324,"_type":21,"marks":5325,"text":5326},"99d222ab5021",[]," When agents operate on grounded, company-specific knowledge, the rate of organizationally incorrect outputs drops significantly. Fewer hallucinations mean less rework, faster reviews, and higher-quality deployments.",[],{"_key":5329,"_type":17,"children":5330,"level":1774,"listItem":1775,"markDefs":5339,"style":25},"9b1d99825854",[5331,5335],{"_key":5332,"_type":21,"marks":5333,"text":5334},"b400d4c1c761",[1806],"Fewer rewrites:",{"_key":5336,"_type":21,"marks":5337,"text":5338},"ce4fd01afdb5",[]," Engineers spend less time correcting agents that didn't know about internal patterns, because those patterns are explicitly available, correctly attributed, and continuously maintained.",[],{"_key":5341,"_type":17,"children":5342,"markDefs":5356,"style":25},"a0ac208dc64e",[5343,5347,5352],{"_key":5344,"_type":21,"marks":5345,"text":5346},"95794a9fce7a",[],"According to ",{"_key":5348,"_type":21,"marks":5349,"text":5351},"0b21b2a852c9",[5350],"bcfd1231fef9","PwC",{"_key":5353,"_type":21,"marks":5354,"text":5355},"43cd9b5c3837",[],"'s ASDLC roadmap, internal knowledge infrastructure is a foundational requirement, not a nice-to-have, for teams aiming to operate a fully agentic pipeline by 2027.",[5357],{"_key":5350,"_type":1734,"href":4719},{"_key":5359,"_type":17,"children":5360,"markDefs":5365,"style":25},"6d93b4b47c2a",[5361],{"_key":5362,"_type":21,"marks":5363,"text":5364},"62be4e71dde2",[1806],"Getting started: A practical path to ASDLC readiness",[],{"_key":5367,"_type":17,"children":5368,"markDefs":5373,"style":25},"c828ed132d37",[5369],{"_key":5370,"_type":21,"marks":5371,"text":5372},"058894660f32",[],"Fortunately, the move to ASDLC doesn't require a wholesale reinvention of your existing processes. It starts with organizational knowledge.",[],{"_key":5375,"_type":17,"children":5376,"markDefs":5385,"style":25},"6125ae815769",[5377,5381],{"_key":5378,"_type":21,"marks":5379,"text":5380},"9fe8b3f6d1ef",[1806],"Step 1: Audit your internal knowledge:",{"_key":5382,"_type":21,"marks":5383,"text":5384},"58284e28d06b",[]," Where does your team's engineering knowledge live today? Is it findable, structured, and trustworthy? Identify gaps that allow room for an AI agent to make erroneous decisions.",[],{"_key":5387,"_type":17,"children":5388,"markDefs":5397,"style":25},"a3b51d0bfb82",[5389,5393],{"_key":5390,"_type":21,"marks":5391,"text":5392},"29b3c50c65cb",[1806],"Step 2: Establish a knowledge infrastructure:",{"_key":5394,"_type":21,"marks":5395,"text":5396},"fd57d04a702b",[]," Implementing a platform like Stack Internal centralizes, validates, and maintains your engineering knowledge in a format agents can consume.",[],{"_key":5399,"_type":17,"children":5400,"markDefs":5409,"style":25},"7a87a72ebefd",[5401,5405],{"_key":5402,"_type":21,"marks":5403,"text":5404},"4617a9802322",[1806],"Step 3: Pilot agentic workflows in low-risk phases:",{"_key":5406,"_type":21,"marks":5407,"text":5408},"26deef25d694",[]," Start with testing or documentation automation: phases where agent errors are relatively easy to catch and the productivity upside is immediate.",[],{"_key":5411,"_type":17,"children":5412,"markDefs":5429,"style":25},"50c2e82de2fc",[5413,5417,5421,5426],{"_key":5414,"_type":21,"marks":5415,"text":5416},"b5e8f9969b38",[1806],"Step 4: Connect agents to internal context via MCP:",{"_key":5418,"_type":21,"marks":5419,"text":5420},"0ba85e0723b0",[]," Use Stack Overflow's MCP Server to give your agents real-time access to Stack Internal's knowledge base during code generation, ",{"_key":5422,"_type":21,"marks":5423,"text":5425},"397dc29cad6e",[5424],"c2888235e3fa","as HP did",{"_key":5427,"_type":21,"marks":5428,"text":4259},"1639d04048b7",[],[5430],{"_key":5424,"_type":1734,"href":5206},{"_key":5432,"_type":17,"children":5433,"markDefs":5442,"style":25},"a59e988469ff",[5434,5438],{"_key":5435,"_type":21,"marks":5436,"text":5437},"ef825539e3e6",[1806],"Step 5: Expand and iterate:",{"_key":5439,"_type":21,"marks":5440,"text":5441},"7604e6bd91d2",[]," As agent reliability improves with better context, expand agentic workflows to implementation, design, and planning phases. Track hallucination rates and rework cycles to give you a sense of ASDLC health.",[],{"_key":5444,"_type":17,"children":5445,"markDefs":5450,"style":3400},"abe616901ff9",[5446],{"_key":5447,"_type":21,"marks":5448,"text":5449},"6445c1ae9140",[1806],"The bottom line",[],{"_key":5452,"_type":17,"children":5453,"markDefs":5458,"style":25},"a53139c26ffa",[5454],{"_key":5455,"_type":21,"marks":5456,"text":5457},"3f6d7f1ee12f",[],"Forward-thinking engineering orgs are already running fully agentic SDLCs. Those that do so successfully have invested the effort to build the knowledge infrastructure those agents need to perform. By making your organization's trusted engineering knowledge available to the agents building your software, Stack Internal turns the promise of ASDLC into a reality.",[],{"_key":5460,"_type":17,"children":5461,"markDefs":5465,"style":25},"7e7e38da7f66",[5462],{"_key":5463,"_type":21,"marks":5464,"text":1742},"deb9f3f2afe0",[],[],{"_key":5467,"_type":17,"children":5468,"markDefs":5473,"style":3400},"c4cfa11c7270",[5469],{"_key":5470,"_type":21,"marks":5471,"text":5472},"6aca86a63f71",[1806],"FAQ",[],{"_key":5475,"_type":17,"children":5476,"markDefs":5485,"style":25},"39ab2602a25e",[5477,5481],{"_key":5478,"_type":21,"marks":5479,"text":5480},"05828d1b1805",[1806],"What is the Agentic Software Development Lifecycle (ASDLC)? ",{"_key":5482,"_type":21,"marks":5483,"text":5484},"3b1e07d8237d",[],"The ASDLC is a model of software delivery in which AI agents autonomously perform tasks across development phases, from planning and coding to testing and maintenance. Humans set intent and validate outputs rather than executing every step manually.",[],{"_key":5487,"_type":17,"children":5488,"markDefs":5505,"style":25},"1d6ebf72bae8",[5489,5493,5497,5501],{"_key":5490,"_type":21,"marks":5491,"text":5492},"569ec87fa3cb",[1806],"How is ASDLC different from traditional SDLC?",{"_key":5494,"_type":21,"marks":5495,"text":5496},"4622fe531324",[]," In a traditional SDLC, humans write code, make architectural decisions, and manually move work through each phase. In ASDLC, AI agents handle execution while humans focus on direction, review, and oversight. The key difference lies in ",{"_key":5498,"_type":21,"marks":5499,"text":5500},"d42f6cb12dbe",[3795],"who",{"_key":5502,"_type":21,"marks":5503,"text":5504},"f75c71ec6ada",[]," (or what) does the work, as well as how continuously that work flows.",[],{"_key":5507,"_type":17,"children":5508,"markDefs":5517,"style":25},"e00eb2852753",[5509,5513],{"_key":5510,"_type":21,"marks":5511,"text":5512},"a43b3adc83d5",[1806],"What is an AI agent in software development?",{"_key":5514,"_type":21,"marks":5515,"text":5516},"d33b84ae059c",[]," An AI agent is an autonomous system that can reason, plan, use tools, call APIs, generate and run code, and self-correct based on feedback — all without being explicitly programmed for each step. In software development, agents can perform tasks like writing a function, generating tests, or diagnosing a production bug.",[],{"_key":5519,"_type":17,"children":5520,"markDefs":5529,"style":25},"a29e49a6c0d9",[5521,5525],{"_key":5522,"_type":21,"marks":5523,"text":5524},"d60c001c4d02",[1806],"What is a Model Context Protocol (MCP) Server?",{"_key":5526,"_type":21,"marks":5527,"text":5528},"d73391431384",[]," An MCP Server is a standardized interface that allows AI agents to query external knowledge sources—like Stack Internal—in real time during a task. Rather than relying solely on publicly available training data, agents can pull live, context-specific information through MCP integrations.",[],{"_key":5531,"_type":17,"children":5532,"markDefs":5541,"style":25},"bd1ea2b3494c",[5533,5537],{"_key":5534,"_type":21,"marks":5535,"text":5536},"8f570c7ee293",[1806],"Why do AI agents hallucinate in enterprise software development?",{"_key":5538,"_type":21,"marks":5539,"text":5540},"c846e31541d5",[]," Hallucinations, or outputs that sound plausible but are incorrect or invented, usually happen when agents lack sufficient context about the specific environment they’re operating in. In enterprise settings, this typically means the agent doesn't have access to information like internal APIs, architectural patterns, naming conventions, or past decisions. Providing agents with verified internal context via a platform like Stack Internal is an effective way to reduce hallucination rates.",[],{"_key":5543,"_type":17,"children":5544,"markDefs":5553,"style":25},"e42b9888de84",[5545,5549],{"_key":5546,"_type":21,"marks":5547,"text":5548},"47bea2f2a960",[1806],"What is Stack Internal?",{"_key":5550,"_type":21,"marks":5551,"text":5552},"7201e315b3a3",[]," Stack Internal is Stack Overflow's enterprise knowledge platform. It ingests, validates, and delivers your organization's engineering knowledge in a format accessible to both humans and AI agents, acting as the trusted knowledge layer that enables agentic workflows to produce organizationally correct outputs.",[],{"_key":5555,"_type":17,"children":5556,"markDefs":5565,"style":25},"05a49a3bf835",[5557,5561],{"_key":5558,"_type":21,"marks":5559,"text":5560},"2023646b21cf",[1806],"What does \"human-verified knowledge\" mean?",{"_key":5562,"_type":21,"marks":5563,"text":5564},"786205c39c40",[]," Human-verified knowledge refers to answers, documentation, and solutions that have been reviewed, validated, and endorsed by the engineers and experts within your organization. It’s opposed to raw content scraped from internal systems that may be outdated, incomplete, or contradictory. Stack Internal's Ingestion applies community validation signals to surface the most trustworthy content.",[],{"_key":5567,"_type":17,"children":5568,"markDefs":5581,"style":25},"404f3839e171",[5569,5573,5577],{"_key":5570,"_type":21,"marks":5571,"text":5572},"72968402cba9",[3795],"Ready to build the knowledge foundation your ASDLC needs? Explore how ",{"_key":5574,"_type":21,"marks":5575,"text":2721},"bd31ede043e9",[3795,5576],"2dba0e91e350",{"_key":5578,"_type":21,"marks":5579,"text":5580},"07ec5b363d06",[3795]," can ground your AI agents in the context that makes them accurate, reliable, and organizationally aligned.",[5582],{"_key":5576,"_type":1734,"href":2668},{"_createdAt":610,"_id":611,"_rev":612,"_type":12,"_updatedAt":613,"description":5584,"slug":5590,"title":625},[5585],{"_key":616,"_type":17,"children":5586,"markDefs":5589,"style":25},[5587],{"_key":619,"_type":21,"marks":5588,"text":621},[],[],{"_type":27,"current":624},{"_type":49,"asset":5592},{"_ref":670,"_type":52},[5594,5596,5598],{"_key":5595,"_ref":4278,"_type":52},"e37b6905c9dd",{"_key":5597,"_ref":4281,"_type":52},"4f63dcf7d13a",{"_key":5599,"_ref":5600,"_type":52},"ac36534e56c5","5430ff75-25d6-4bc2-96fb-4b86938b7e04",{"_ref":2679,"_type":52},[5603],{"_key":5604,"_ref":3376,"_type":52},"025a33265e52",{"_type":27,"current":674},{"_ref":629,"_type":52},[5608],{"_createdAt":5609,"_id":5610,"_rev":5611,"_type":5612,"_updatedAt":5609,"slug":5613,"title":5615},"2022-03-11T15:30:18Z","b4721a78-6640-4834-b1fd-d2f6e434a4f4","5hruNpCYOLH4jmW0dcDsbT","resourceType",{"_type":27,"current":5614},"ebook","eBook",[],{"_type":27,"current":758},{"_createdAt":746,"_id":747,"_rev":748,"_type":35,"_updatedAt":749,"slug":5619,"title":762},{"_type":27,"current":761},[5614]]