[{"data":1,"prerenderedAt":806},["ShallowReactive",2],{"/en-us/blog/developing-gitlab-duo-how-we-are-dogfooding-our-ai-features":3,"navigation-en-us":42,"banner-en-us":452,"footer-en-us":462,"blog-post-authors-en-us-David O'Regan":703,"blog-related-posts-en-us-developing-gitlab-duo-how-we-are-dogfooding-our-ai-features":718,"assessment-promotions-en-us":759,"next-steps-en-us":796},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":28,"isFeatured":12,"meta":29,"navigation":12,"path":30,"publishedDate":20,"seo":31,"stem":36,"tagSlugs":37,"__hash__":41},"blogPosts/en-us/blog/developing-gitlab-duo-how-we-are-dogfooding-our-ai-features.yml","Developing Gitlab Duo How We Are Dogfooding Our Ai Features",[7],"david-oregan",null,"ai-ml",{"slug":11,"featured":12,"template":13},"developing-gitlab-duo-how-we-are-dogfooding-our-ai-features",true,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"Developing GitLab Duo: How we are dogfooding our AI features","As part of our blog series, we share real-world examples of how we integrate AI throughout our software development lifecycle and how we use metrics to gauge their success.",[18],"David O'Regan","https://res.cloudinary.com/about-gitlab-com/image/upload/v1750098360/Blog/Hero%20Images/Blog/Hero%20Images/blog-hero-banner-1-0178-820x470-fy25_7JlF3WlEkswGQbcTe8DOTB_1750098360821.png","2024-05-20","***Generative AI marks a monumental shift in the software development industry, making it easier to develop, secure, and operate software. Our new blog series, written by our product and engineering teams, gives you an inside look at how we create, test, and deploy the AI features you need integrated throughout the enterprise. Get to know new capabilities within GitLab Duo and how they will help DevSecOps teams deliver better results for customers.***\n\n[GitLab Duo](https://about.gitlab.com/gitlab-duo-agent-platform/), our suite of AI-powered features, has transformed our internal engineering workflows, driving efficiency gains across our development process. As strong proponents of dogfooding and transparency, we wanted to showcase how our teams leverage AI, including standouts like GitLab Duo Code Suggestions and GitLab Duo Chat, daily to streamline development processes, reduce manual effort, and enhance productivity. You'll learn about the benefits we've experienced for highly technical teams like engineering to less technical teams such as technical writing and product management.\n\n> Discover the future of AI-driven software development with our GitLab 17 virtual launch event. [Watch today!](https://about.gitlab.com/eighteen/)\n\n## Real-world use cases\n\nOur teams have integrated [GitLab Duo's many features](https://about.gitlab.com/gitlab-duo-agent-platform/#features) into their daily routines. Here are some examples of how GitLab Duo is helping them carry out everyday activities.\n\n### Summarization and documentation\n- **Streamline the code review process:** Staff Backend Developer [Gosia Ksionek](https://about.gitlab.com/company/team/#mksionek) showcases the practical benefits of AI in her workflow by using GitLab Duo to streamline the code review process. She effectively utilizes GitLab Duo to [summarize merge requests](https://youtu.be/3SIhe8dgFEc), making it easier and faster to review code changes. In addition to summarizing merge requests, Gosia also leverages GitLab Duo to [answer coding questions](https://www.youtube.com/watch?v=6n0I53XsjTc) and [explain complex code snippets](https://www.youtube.com/watch?v=3m2YRxa1SCY). This enhances her productivity and helps her better understand and manage intricate codebases. Through these demonstrations, Gosia highlights how GitLab Duo can significantly improve efficiency and clarity in the development process, making it an invaluable tool for developers.\n\n\u003Ccenter>\n\nWatch Gosia use GitLab Duo Merge Request Summary:\n\n\u003C!-- blank line -->\n\u003Cfigure class=\"video_container\">\n  \u003Ciframe src=\"https://www.youtube.com/embed/3SIhe8dgFEc?si=Q8JG3Ix3K_THhbpv\" frameborder=\"0\" allowfullscreen=\"true\"> \u003C/iframe>\n\u003C/figure>\n\u003C!-- blank line -->\n\nWatch Gosia use GitLab Duo to answer coding questions:\n\u003C!-- blank line -->\n\u003Cfigure class=\"video_container\">\n  \u003Ciframe src=\"https://www.youtube.com/embed/6n0I53XsjTc?si=LA9VBHrgXpfJImSL\" frameborder=\"0\" allowfullscreen=\"true\"> \u003C/iframe>\n\u003C/figure>\n\u003C!-- blank line -->\n\nWatch Gosia use GitLab Duo to explain complex code snippets:\n\n\u003C!-- blank line -->\n\u003Cfigure class=\"video_container\">\n  \u003Ciframe src=\"https://www.youtube.com/embed/3m2YRxa1SCY?si=oms3szKwZoz-4yeq\" frameborder=\"0\" allowfullscreen=\"true\"> \u003C/iframe>\n\u003C/figure>\n\u003C!-- blank line -->\n\n\u003C/center>\n\n- **Condense comment threads:** [Bartek Marnane](https://about.gitlab.com/company/team/#bmarnane), Vice President of Expansion Software Development, uses GitLab Duo to condense lengthy comment threads into concise summaries, ensuring all relevant details are captured when updating issue descriptions.\n\n- **Create new documentation:** [Taylor McCaslin](https://about.gitlab.com/company/team/#tmccaslin), Group Manager, Product - Data Science Section, leveraged GitLab Duo to [create new documentation for GitLab Duo itself](https://docs.gitlab.com/ee/user/ai_features.html), exemplifying a meta use case that enhances clarity and consistency and greatly reduces the time to document new features.\n\n- **Craft release notes:** [Amanda Rueda](https://about.gitlab.com/company/team/#amandarueda), Senior Product Manager for Product Planning, uses GitLab Duo to [craft brief, impactful summaries for release notes](https://gitlab.com/groups/gitlab-org/-/epics/10267), highlighting changes and their value to users. By using well-crafted prompts like below, Amanda supercharges her workflow and ensures that each release note is clear, concise, and user-focused, enhancing the overall communication and user experience:\u003Cbr>\u003Cbr>\n*“Please create a two sentence summary of this change, which can be used for our release notes. The tone should be conversational and should be in second person. The summary should include a description of the problem or change and be tied to the value we are creating for you, the user.”*\n\u003Cbr>\u003Cbr>\n    - Here are some examples of release notes co-created with GitLab Duo:\n      - [Expanded options for sorting your Roadmap](https://gitlab.com/gitlab-org/gitlab/-/issues/460492)\n      - [Issue Board Clarity now with Milestone & Iteration](https://gitlab.com/gitlab-org/gitlab/-/issues/25758)\n      - [Design Management Features Extended to Product Teams](https://gitlab.com/gitlab-org/gitlab/-/issues/438829)\n\n- **Optimize docs site navigation:** [Suzanne Selhorn](https://about.gitlab.com/company/team/#sselhorn), Staff Technical Writer, tapped GitLab Duo to [optimize the left navigation of documentation](https://docs.gitlab.com/ee/user/get_started/get_started_projects.html) by providing a workflow-based order of pages. Suzanne provided a list of features to GitLab Duo, which generated the optimal order, updating the left navigation to match. GitLab Duo also drafted the [Getting Started](https://docs.gitlab.com/ee/user/get_started/get_started_planning_work.html) documentation much faster than were she to use traditional, manual approaches.\n\n### Goal setting and team alignment\n- **Draft and refine OKRs:** [François Rosé](https://about.gitlab.com/company/team/#francoisrose), Engineering manager, Create:Code Review Backend, finds [GitLab Duo Chat](https://about.gitlab.com/blog/gitlab-duo-chat-now-generally-available/) invaluable for drafting and refining OKRs. By articulating objectives more clearly and effectively, François enhances goal setting and team alignment. Using Chat, François ensures that each OKR is precise, actionable, and aligned with the team's goals, thereby improving overall team performance and cohesion. Here is an example prompt he uses:\u003Cbr>\u003Cbr>\n\n    *\"Here is an OKR I am thinking of creating:*\n\n    *Objective: Retrospect on retrospectives, to foster a thriving team*\n\n    *KR: Measure retrospective satisfaction from 100% of team members*\n\n    *KR: Identify 3 improvements to the async retrospectives*\n\n    *KR: Implement 1 improvement*\n\n    *Please provide direct feedback on how to improve the formulation of this objective and these key results.\"*\n\u003Cbr>\u003Cbr>\n\n- **Streamlined hiring and recruitment processes:** Chat helped [Denys Mishunov](https://about.gitlab.com/company/team/#dmishunov), Staff Frontend Engineer, formulate a clear and concise text for updating the email template for technical interview candidates. The team collaborated on refining the communication to ensure candidates receive all necessary information using a merge request. This example showcased the practical application of AI tools in enhancing communication processes within the hiring workflow.\n\n### Incident response and configuration\n- **Summarize production incidents:** [Steve Xuereb](https://about.gitlab.com/company/team/#sxuereb), Staff Site Reliability Engineer, employs GitLab Duo to summarize production incidents and create detailed incident reviews, streamlining the documentation process.\n\n- **Create boilerplate `.gitlab-ci.yml` files:**  Steve also uses Chat to create boilerplate `.gitlab-ci.yml` files, which significantly sped up his workflow. [Chat](https://docs.gitlab.com/ee/user/gitlab_duo_chat.html) serves as a valuable partner for suggesting ideas. Additionally, [Code Explanation](https://docs.gitlab.com/ee/user/ai_features.html#code-explanation) provides detailed answers that are helpful during incidents, enhancing his productivity and understanding of the codebase.\n\n### Code generation and testing\n- **Full-stack development:** [Peter Hegman](https://about.gitlab.com/company/team/#peterhegman), Senior Frontend Engineer, has been using [Code Suggestions for his JavaScript and Ruby development](https://gitlab.com/gitlab-org/gitlab/-/issues/435783#note_1731321963). This highlights that Code Suggestions has become a powerful tool for developers moving across a full technical stack.\n- **Generate Python scripts:** Denys conducted [an experiment using GitLab Duo for a non-GitLab task](https://gitlab.com/gitlab-org/ai-powered/ai-framework/ai-experimentation). This example highlights the flexibility and utility of our AI tools beyond typical software development tasks.\n\n\u003Ccenter>\nWatch how Denys uses GitLab Duo to generate Python scripts to fetch content data and store it locally:\n\n\u003C!-- blank line -->\n\u003Cfigure class=\"video_container\">\n  \u003Ciframe src=\"https://www.youtube.com/embed/30ZTtk4K5yU?si=p5ZcFLg6dTZL5gFE\" frameborder=\"0\" allowfullscreen=\"true\"> \u003C/iframe>\n\u003C/figure>\n\u003C!-- blank line -->\n\n\u003C/center>\n\n### Research and support\n- **Generate test source code:**  [Michael Friedrich](https://about.gitlab.com/company/team/#dnsmichi), Senior Developer Advocate, uses GitLab Duo to generate test source code for CI/CD components. This approach has been shared in various talks and presentations, such as the recent Open Source @ Siemens event ([public slides](https://go.gitlab.com/duA2Fc)). Using GitLab Duo in this manner helps ensure that the code is consistent, well-documented, and aligned with our best practices. Check out his [Rust example](https://gitlab.com/components/rust#contributing).\n\n![Rust example](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750098367/Blog/Content%20Images/Blog/Content%20Images/image2_aHR0cHM6_1750098367547.png)\n\n- **Streamline research tasks:** Our team members consistently turn to Chat when they have questions about GitLab features, streamlining their research and support tasks. Michael shared, \"When I have a question about GitLab features, I default to using Chat instead of opening 100 browser tabs. This workflow helps me assist users on our community forum efficiently. For instance, I recently [helped a user with SSH deployment](https://forum.gitlab.com/t/how-to-make-ssh-deployment-more-clear-in-gitlab/102051/4?u=dnsmichi) using this method.\" Using Chat not only saves time but also provides quick, accurate information, enhancing the support we offer to our community.\n\n### Feature testing\n- **Test new features:** Our engineers use GitLab Duo to test new features like [Markdown support in Code Suggestions](https://gitlab.com/gitlab-org/gitlab/-/issues/443365). One of our team members noted, \"I need to test Markdown support in Code Suggestions for writing blog posts and GitLab docs in VS Code. I saw it was merged for 17.0.\" By testing these features internally, we ensure they meet our quality standards before release.\n\n### Understanding external codebases\n- **Explain external projects:** GitLab Duo's `/explain` feature is particularly useful for understanding external projects imported into GitLab. This capability was highlighted in a recent livestream he did with open source expert Eddie Jaoude. Michael let us know, \"I use `/explain` on external projects to understand the source code. I pitched this idea for learning about open source projects, dependencies, etc. during the livestream.\" This feature is invaluable for developers who need to quickly grasp the functionality and dependencies of unfamiliar codebases, significantly improving their efficiency and understanding.\n\n\u003Ccenter>\nWatch Michael demo `/explain` during a livestream with Eddie Jaoude:\n\u003C!-- blank line -->\n\u003Cfigure class=\"video_container\">\n  \u003Ciframe src=\"https://www.youtube.com/embed/L2Mx8hOhkEE?si=R7W3v4EDqeJCaPOw\" frameborder=\"0\" allowfullscreen=\"true\"> \u003C/iframe>\n\u003C/figure>\n\u003C!-- blank line -->\n\n\u003C/center>\n\n## GitLab Duo's benefits\n\nThe integration of GitLab Duo has brought about numerous positive impacts, significantly enhancing our engineering and product development workflows:\n\n- Many tasks that previously required manual intervention are now automated, freeing up valuable time for our engineers. For example, summarizing long threads and creating boilerplate code are now more efficient, allowing our team to focus on more complex issues.\n- The time taken to document and summarize issues has decreased, allowing for quicker information dissemination and decision-making.\n- With AI-assisted code suggestions and explanations, our teams produce higher quality code with fewer errors and faster debugging processes. The integration of GitLab Duo into incident reviews and coding assistance has led to more efficient and effective code reviews.\n- Administrative tasks, such as drafting OKRs and creating release notes, have been streamlined.\nGitLab Duo has helped to not only improve our efficiency but also to enhance the quality and speed of our development processes, illustrating the transformative power of AI in software development.\n\n## What's next?\n\nWe are committed to further integrating AI into our workflows and continuously improving GitLab Duo features based on internal feedback and evolving needs. The ongoing collection of use cases and metrics with the [AI Impact analytics dashboard](https://about.gitlab.com/blog/developing-gitlab-duo-ai-impact-analytics-dashboard-measures-the-roi-of-ai/) will guide enhancements and ensure that GitLab Duo remains at the forefront of AI-driven development tools.\n\n![Dogfooding Duo - AI analytics dashboard](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750098367/Blog/Content%20Images/Blog/Content%20Images/image1_aHR0cHM6_1750098367547.png)\n\n> [Get started using GitLab Duo today with our free trial.](https://about.gitlab.com/gitlab-duo-agent-platform/#free-trial)\n\n## Read more \"Developing GitLab Duo\"\n\n- [Developing GitLab Duo: AI Impact analytics dashboard measures the ROI of AI](https://about.gitlab.com/blog/developing-gitlab-duo-ai-impact-analytics-dashboard-measures-the-roi-of-ai/)\n- [Developing GitLab Duo: How we validate and test AI models at scale](https://about.gitlab.com/blog/developing-gitlab-duo-how-we-validate-and-test-ai-models-at-scale/)\n- [Developing GitLab Duo: Secure and thoroughly test AI-generated code](https://about.gitlab.com/blog/how-gitlab-duo-helps-secure-and-thoroughly-test-ai-generated-code/)\n- [Developing GitLab Duo: Blending AI and Root Cause Analysis to fix CI/CD pipelines](https://about.gitlab.com/blog/developing-gitlab-duo-blending-ai-and-root-cause-analysis-to-fix-ci-cd/)",[23,24,25,26,27],"AI/ML","code review","features","DevSecOps platform","workflow","yml",{},"/en-us/blog/developing-gitlab-duo-how-we-are-dogfooding-our-ai-features",{"title":15,"description":16,"ogTitle":15,"ogDescription":16,"noIndex":32,"ogImage":19,"ogUrl":33,"ogSiteName":34,"ogType":35,"canonicalUrls":33},false,"https://about.gitlab.com/blog/developing-gitlab-duo-how-we-are-dogfooding-our-ai-features","https://about.gitlab.com","article","en-us/blog/developing-gitlab-duo-how-we-are-dogfooding-our-ai-features",[38,39,25,40,27],"aiml","code-review","devsecops-platform","9F3RLUXWpGGvz-3twjX6G2oCuaYVW_SGdrYJpqLJOyI",{"data":43},{"logo":44,"freeTrial":49,"sales":54,"login":59,"items":64,"search":372,"minimal":403,"duo":422,"switchNav":431,"pricingDeployment":442},{"config":45},{"href":46,"dataGaName":47,"dataGaLocation":48},"/","gitlab logo","header",{"text":50,"config":51},"Get free trial",{"href":52,"dataGaName":53,"dataGaLocation":48},"https://gitlab.com/-/trial_registrations/new?glm_source=about.gitlab.com&glm_content=default-saas-trial/","free trial",{"text":55,"config":56},"Talk to sales",{"href":57,"dataGaName":58,"dataGaLocation":48},"/sales/","sales",{"text":60,"config":61},"Sign in",{"href":62,"dataGaName":63,"dataGaLocation":48},"https://gitlab.com/users/sign_in/","sign in",[65,92,187,192,293,353],{"text":66,"config":67,"cards":69},"Platform",{"dataNavLevelOne":68},"platform",[70,76,84],{"title":66,"description":71,"link":72},"The intelligent orchestration platform for DevSecOps",{"text":73,"config":74},"Explore our Platform",{"href":75,"dataGaName":68,"dataGaLocation":48},"/platform/",{"title":77,"description":78,"link":79},"GitLab Duo Agent Platform","Agentic AI for the entire software lifecycle",{"text":80,"config":81},"Meet GitLab Duo",{"href":82,"dataGaName":83,"dataGaLocation":48},"/gitlab-duo-agent-platform/","gitlab duo agent platform",{"title":85,"description":86,"link":87},"Why GitLab","See the top reasons enterprises choose GitLab",{"text":88,"config":89},"Learn more",{"href":90,"dataGaName":91,"dataGaLocation":48},"/why-gitlab/","why gitlab",{"text":93,"left":12,"config":94,"link":96,"lists":100,"footer":169},"Product",{"dataNavLevelOne":95},"solutions",{"text":97,"config":98},"View all Solutions",{"href":99,"dataGaName":95,"dataGaLocation":48},"/solutions/",[101,125,148],{"title":102,"description":103,"link":104,"items":109},"Automation","CI/CD and automation to accelerate deployment",{"config":105},{"icon":106,"href":107,"dataGaName":108,"dataGaLocation":48},"AutomatedCodeAlt","/solutions/delivery-automation/","automated software delivery",[110,114,117,121],{"text":111,"config":112},"CI/CD",{"href":113,"dataGaLocation":48,"dataGaName":111},"/solutions/continuous-integration/",{"text":77,"config":115},{"href":82,"dataGaLocation":48,"dataGaName":116},"gitlab duo agent platform - product menu",{"text":118,"config":119},"Source Code Management",{"href":120,"dataGaLocation":48,"dataGaName":118},"/solutions/source-code-management/",{"text":122,"config":123},"Automated Software Delivery",{"href":107,"dataGaLocation":48,"dataGaName":124},"Automated software delivery",{"title":126,"description":127,"link":128,"items":133},"Security","Deliver code faster without compromising security",{"config":129},{"href":130,"dataGaName":131,"dataGaLocation":48,"icon":132},"/solutions/application-security-testing/","security and compliance","ShieldCheckLight",[134,138,143],{"text":135,"config":136},"Application Security Testing",{"href":130,"dataGaName":137,"dataGaLocation":48},"Application security testing",{"text":139,"config":140},"Software Supply Chain Security",{"href":141,"dataGaLocation":48,"dataGaName":142},"/solutions/supply-chain/","Software supply chain security",{"text":144,"config":145},"Software Compliance",{"href":146,"dataGaName":147,"dataGaLocation":48},"/solutions/software-compliance/","software compliance",{"title":149,"link":150,"items":155},"Measurement",{"config":151},{"icon":152,"href":153,"dataGaName":154,"dataGaLocation":48},"DigitalTransformation","/solutions/visibility-measurement/","visibility and measurement",[156,160,164],{"text":157,"config":158},"Visibility & Measurement",{"href":153,"dataGaLocation":48,"dataGaName":159},"Visibility and Measurement",{"text":161,"config":162},"Value Stream Management",{"href":163,"dataGaLocation":48,"dataGaName":161},"/solutions/value-stream-management/",{"text":165,"config":166},"Analytics & Insights",{"href":167,"dataGaLocation":48,"dataGaName":168},"/solutions/analytics-and-insights/","Analytics and insights",{"title":170,"items":171},"GitLab for",[172,177,182],{"text":173,"config":174},"Enterprise",{"href":175,"dataGaLocation":48,"dataGaName":176},"/enterprise/","enterprise",{"text":178,"config":179},"Small Business",{"href":180,"dataGaLocation":48,"dataGaName":181},"/small-business/","small business",{"text":183,"config":184},"Public Sector",{"href":185,"dataGaLocation":48,"dataGaName":186},"/solutions/public-sector/","public sector",{"text":188,"config":189},"Pricing",{"href":190,"dataGaName":191,"dataGaLocation":48,"dataNavLevelOne":191},"/pricing/","pricing",{"text":193,"config":194,"link":196,"lists":200,"feature":280},"Resources",{"dataNavLevelOne":195},"resources",{"text":197,"config":198},"View all resources",{"href":199,"dataGaName":195,"dataGaLocation":48},"/resources/",[201,234,252],{"title":202,"items":203},"Getting started",[204,209,214,219,224,229],{"text":205,"config":206},"Install",{"href":207,"dataGaName":208,"dataGaLocation":48},"/install/","install",{"text":210,"config":211},"Quick start guides",{"href":212,"dataGaName":213,"dataGaLocation":48},"/get-started/","quick setup checklists",{"text":215,"config":216},"Learn",{"href":217,"dataGaLocation":48,"dataGaName":218},"https://university.gitlab.com/","learn",{"text":220,"config":221},"Product documentation",{"href":222,"dataGaName":223,"dataGaLocation":48},"https://docs.gitlab.com/","product documentation",{"text":225,"config":226},"Best practice videos",{"href":227,"dataGaName":228,"dataGaLocation":48},"/getting-started-videos/","best practice videos",{"text":230,"config":231},"Integrations",{"href":232,"dataGaName":233,"dataGaLocation":48},"/integrations/","integrations",{"title":235,"items":236},"Discover",[237,242,247],{"text":238,"config":239},"Customer success stories",{"href":240,"dataGaName":241,"dataGaLocation":48},"/customers/","customer success stories",{"text":243,"config":244},"Blog",{"href":245,"dataGaName":246,"dataGaLocation":48},"/blog/","blog",{"text":248,"config":249},"Remote",{"href":250,"dataGaName":251,"dataGaLocation":48},"https://handbook.gitlab.com/handbook/company/culture/all-remote/","remote",{"title":253,"items":254},"Connect",[255,260,265,270,275],{"text":256,"config":257},"GitLab Services",{"href":258,"dataGaName":259,"dataGaLocation":48},"/services/","services",{"text":261,"config":262},"Community",{"href":263,"dataGaName":264,"dataGaLocation":48},"/community/","community",{"text":266,"config":267},"Forum",{"href":268,"dataGaName":269,"dataGaLocation":48},"https://forum.gitlab.com/","forum",{"text":271,"config":272},"Events",{"href":273,"dataGaName":274,"dataGaLocation":48},"/events/","events",{"text":276,"config":277},"Partners",{"href":278,"dataGaName":279,"dataGaLocation":48},"/partners/","partners",{"backgroundColor":281,"textColor":282,"text":283,"image":284,"link":288},"#2f2a6b","#fff","Insights for the future of software development",{"altText":285,"config":286},"the source promo card",{"src":287},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1758208064/dzl0dbift9xdizyelkk4.svg",{"text":289,"config":290},"Read the latest",{"href":291,"dataGaName":292,"dataGaLocation":48},"/the-source/","the source",{"text":294,"config":295,"lists":297},"Company",{"dataNavLevelOne":296},"company",[298],{"items":299},[300,305,311,313,318,323,328,333,338,343,348],{"text":301,"config":302},"About",{"href":303,"dataGaName":304,"dataGaLocation":48},"/company/","about",{"text":306,"config":307,"footerGa":310},"Jobs",{"href":308,"dataGaName":309,"dataGaLocation":48},"/jobs/","jobs",{"dataGaName":309},{"text":271,"config":312},{"href":273,"dataGaName":274,"dataGaLocation":48},{"text":314,"config":315},"Leadership",{"href":316,"dataGaName":317,"dataGaLocation":48},"/company/team/e-group/","leadership",{"text":319,"config":320},"Team",{"href":321,"dataGaName":322,"dataGaLocation":48},"/company/team/","team",{"text":324,"config":325},"Handbook",{"href":326,"dataGaName":327,"dataGaLocation":48},"https://handbook.gitlab.com/","handbook",{"text":329,"config":330},"Investor relations",{"href":331,"dataGaName":332,"dataGaLocation":48},"https://ir.gitlab.com/","investor relations",{"text":334,"config":335},"Trust Center",{"href":336,"dataGaName":337,"dataGaLocation":48},"/security/","trust center",{"text":339,"config":340},"AI Transparency Center",{"href":341,"dataGaName":342,"dataGaLocation":48},"/ai-transparency-center/","ai transparency center",{"text":344,"config":345},"Newsletter",{"href":346,"dataGaName":347,"dataGaLocation":48},"/company/contact/#contact-forms","newsletter",{"text":349,"config":350},"Press",{"href":351,"dataGaName":352,"dataGaLocation":48},"/press/","press",{"text":354,"config":355,"lists":356},"Contact us",{"dataNavLevelOne":296},[357],{"items":358},[359,362,367],{"text":55,"config":360},{"href":57,"dataGaName":361,"dataGaLocation":48},"talk to sales",{"text":363,"config":364},"Support portal",{"href":365,"dataGaName":366,"dataGaLocation":48},"https://support.gitlab.com","support portal",{"text":368,"config":369},"Customer portal",{"href":370,"dataGaName":371,"dataGaLocation":48},"https://customers.gitlab.com/customers/sign_in/","customer portal",{"close":373,"login":374,"suggestions":381},"Close",{"text":375,"link":376},"To search repositories and projects, login to",{"text":377,"config":378},"gitlab.com",{"href":62,"dataGaName":379,"dataGaLocation":380},"search login","search",{"text":382,"default":383},"Suggestions",[384,386,390,392,396,400],{"text":77,"config":385},{"href":82,"dataGaName":77,"dataGaLocation":380},{"text":387,"config":388},"Code Suggestions (AI)",{"href":389,"dataGaName":387,"dataGaLocation":380},"/solutions/code-suggestions/",{"text":111,"config":391},{"href":113,"dataGaName":111,"dataGaLocation":380},{"text":393,"config":394},"GitLab on AWS",{"href":395,"dataGaName":393,"dataGaLocation":380},"/partners/technology-partners/aws/",{"text":397,"config":398},"GitLab on Google Cloud",{"href":399,"dataGaName":397,"dataGaLocation":380},"/partners/technology-partners/google-cloud-platform/",{"text":401,"config":402},"Why GitLab?",{"href":90,"dataGaName":401,"dataGaLocation":380},{"freeTrial":404,"mobileIcon":409,"desktopIcon":414,"secondaryButton":417},{"text":405,"config":406},"Start free trial",{"href":407,"dataGaName":53,"dataGaLocation":408},"https://gitlab.com/-/trials/new/","nav",{"altText":410,"config":411},"Gitlab Icon",{"src":412,"dataGaName":413,"dataGaLocation":408},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1758203874/jypbw1jx72aexsoohd7x.svg","gitlab icon",{"altText":410,"config":415},{"src":416,"dataGaName":413,"dataGaLocation":408},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1758203875/gs4c8p8opsgvflgkswz9.svg",{"text":418,"config":419},"Get Started",{"href":420,"dataGaName":421,"dataGaLocation":408},"https://gitlab.com/-/trial_registrations/new?glm_source=about.gitlab.com/get-started/","get started",{"freeTrial":423,"mobileIcon":427,"desktopIcon":429},{"text":424,"config":425},"Learn more about GitLab Duo",{"href":82,"dataGaName":426,"dataGaLocation":408},"gitlab duo",{"altText":410,"config":428},{"src":412,"dataGaName":413,"dataGaLocation":408},{"altText":410,"config":430},{"src":416,"dataGaName":413,"dataGaLocation":408},{"button":432,"mobileIcon":437,"desktopIcon":439},{"text":433,"config":434},"/switch",{"href":435,"dataGaName":436,"dataGaLocation":408},"#contact","switch",{"altText":410,"config":438},{"src":412,"dataGaName":413,"dataGaLocation":408},{"altText":410,"config":440},{"src":441,"dataGaName":413,"dataGaLocation":408},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1773335277/ohhpiuoxoldryzrnhfrh.png",{"freeTrial":443,"mobileIcon":448,"desktopIcon":450},{"text":444,"config":445},"Back to pricing",{"href":190,"dataGaName":446,"dataGaLocation":408,"icon":447},"back to pricing","GoBack",{"altText":410,"config":449},{"src":412,"dataGaName":413,"dataGaLocation":408},{"altText":410,"config":451},{"src":416,"dataGaName":413,"dataGaLocation":408},{"title":453,"button":454,"config":459},"See how agentic AI transforms software delivery",{"text":455,"config":456},"Watch GitLab Transcend now",{"href":457,"dataGaName":458,"dataGaLocation":48},"/events/transcend/virtual/","transcend event",{"layout":460,"icon":461,"disabled":12},"release","AiStar",{"data":463},{"text":464,"source":465,"edit":471,"contribute":476,"config":481,"items":486,"minimal":692},"Git is a trademark of Software Freedom Conservancy and our use of 'GitLab' is under license",{"text":466,"config":467},"View page source",{"href":468,"dataGaName":469,"dataGaLocation":470},"https://gitlab.com/gitlab-com/marketing/digital-experience/about-gitlab-com/","page source","footer",{"text":472,"config":473},"Edit this page",{"href":474,"dataGaName":475,"dataGaLocation":470},"https://gitlab.com/gitlab-com/marketing/digital-experience/about-gitlab-com/-/blob/main/content/","web ide",{"text":477,"config":478},"Please contribute",{"href":479,"dataGaName":480,"dataGaLocation":470},"https://gitlab.com/gitlab-com/marketing/digital-experience/about-gitlab-com/-/blob/main/CONTRIBUTING.md/","please contribute",{"twitter":482,"facebook":483,"youtube":484,"linkedin":485},"https://twitter.com/gitlab","https://www.facebook.com/gitlab","https://www.youtube.com/channel/UCnMGQ8QHMAnVIsI3xJrihhg","https://www.linkedin.com/company/gitlab-com",[487,534,587,631,658],{"title":188,"links":488,"subMenu":503},[489,493,498],{"text":490,"config":491},"View plans",{"href":190,"dataGaName":492,"dataGaLocation":470},"view plans",{"text":494,"config":495},"Why Premium?",{"href":496,"dataGaName":497,"dataGaLocation":470},"/pricing/premium/","why premium",{"text":499,"config":500},"Why Ultimate?",{"href":501,"dataGaName":502,"dataGaLocation":470},"/pricing/ultimate/","why ultimate",[504],{"title":505,"links":506},"Contact Us",[507,510,512,514,519,524,529],{"text":508,"config":509},"Contact sales",{"href":57,"dataGaName":58,"dataGaLocation":470},{"text":363,"config":511},{"href":365,"dataGaName":366,"dataGaLocation":470},{"text":368,"config":513},{"href":370,"dataGaName":371,"dataGaLocation":470},{"text":515,"config":516},"Status",{"href":517,"dataGaName":518,"dataGaLocation":470},"https://status.gitlab.com/","status",{"text":520,"config":521},"Terms of use",{"href":522,"dataGaName":523,"dataGaLocation":470},"/terms/","terms of use",{"text":525,"config":526},"Privacy statement",{"href":527,"dataGaName":528,"dataGaLocation":470},"/privacy/","privacy statement",{"text":530,"config":531},"Cookie preferences",{"dataGaName":532,"dataGaLocation":470,"id":533,"isOneTrustButton":12},"cookie preferences","ot-sdk-btn",{"title":93,"links":535,"subMenu":543},[536,539],{"text":26,"config":537},{"href":75,"dataGaName":538,"dataGaLocation":470},"devsecops platform",{"text":540,"config":541},"AI-Assisted Development",{"href":82,"dataGaName":542,"dataGaLocation":470},"ai-assisted development",[544],{"title":545,"links":546},"Topics",[547,552,557,562,567,572,577,582],{"text":548,"config":549},"CICD",{"href":550,"dataGaName":551,"dataGaLocation":470},"/topics/ci-cd/","cicd",{"text":553,"config":554},"GitOps",{"href":555,"dataGaName":556,"dataGaLocation":470},"/topics/gitops/","gitops",{"text":558,"config":559},"DevOps",{"href":560,"dataGaName":561,"dataGaLocation":470},"/topics/devops/","devops",{"text":563,"config":564},"Version Control",{"href":565,"dataGaName":566,"dataGaLocation":470},"/topics/version-control/","version control",{"text":568,"config":569},"DevSecOps",{"href":570,"dataGaName":571,"dataGaLocation":470},"/topics/devsecops/","devsecops",{"text":573,"config":574},"Cloud Native",{"href":575,"dataGaName":576,"dataGaLocation":470},"/topics/cloud-native/","cloud native",{"text":578,"config":579},"AI for Coding",{"href":580,"dataGaName":581,"dataGaLocation":470},"/topics/devops/ai-for-coding/","ai for coding",{"text":583,"config":584},"Agentic AI",{"href":585,"dataGaName":586,"dataGaLocation":470},"/topics/agentic-ai/","agentic ai",{"title":588,"links":589},"Solutions",[590,592,594,599,603,606,610,613,615,618,621,626],{"text":135,"config":591},{"href":130,"dataGaName":135,"dataGaLocation":470},{"text":124,"config":593},{"href":107,"dataGaName":108,"dataGaLocation":470},{"text":595,"config":596},"Agile development",{"href":597,"dataGaName":598,"dataGaLocation":470},"/solutions/agile-delivery/","agile delivery",{"text":600,"config":601},"SCM",{"href":120,"dataGaName":602,"dataGaLocation":470},"source code management",{"text":548,"config":604},{"href":113,"dataGaName":605,"dataGaLocation":470},"continuous integration & delivery",{"text":607,"config":608},"Value stream management",{"href":163,"dataGaName":609,"dataGaLocation":470},"value stream management",{"text":553,"config":611},{"href":612,"dataGaName":556,"dataGaLocation":470},"/solutions/gitops/",{"text":173,"config":614},{"href":175,"dataGaName":176,"dataGaLocation":470},{"text":616,"config":617},"Small business",{"href":180,"dataGaName":181,"dataGaLocation":470},{"text":619,"config":620},"Public sector",{"href":185,"dataGaName":186,"dataGaLocation":470},{"text":622,"config":623},"Education",{"href":624,"dataGaName":625,"dataGaLocation":470},"/solutions/education/","education",{"text":627,"config":628},"Financial services",{"href":629,"dataGaName":630,"dataGaLocation":470},"/solutions/finance/","financial services",{"title":193,"links":632},[633,635,637,639,642,644,646,648,650,652,654,656],{"text":205,"config":634},{"href":207,"dataGaName":208,"dataGaLocation":470},{"text":210,"config":636},{"href":212,"dataGaName":213,"dataGaLocation":470},{"text":215,"config":638},{"href":217,"dataGaName":218,"dataGaLocation":470},{"text":220,"config":640},{"href":222,"dataGaName":641,"dataGaLocation":470},"docs",{"text":243,"config":643},{"href":245,"dataGaName":246,"dataGaLocation":470},{"text":238,"config":645},{"href":240,"dataGaName":241,"dataGaLocation":470},{"text":248,"config":647},{"href":250,"dataGaName":251,"dataGaLocation":470},{"text":256,"config":649},{"href":258,"dataGaName":259,"dataGaLocation":470},{"text":261,"config":651},{"href":263,"dataGaName":264,"dataGaLocation":470},{"text":266,"config":653},{"href":268,"dataGaName":269,"dataGaLocation":470},{"text":271,"config":655},{"href":273,"dataGaName":274,"dataGaLocation":470},{"text":276,"config":657},{"href":278,"dataGaName":279,"dataGaLocation":470},{"title":294,"links":659},[660,662,664,666,668,670,672,676,681,683,685,687],{"text":301,"config":661},{"href":303,"dataGaName":296,"dataGaLocation":470},{"text":306,"config":663},{"href":308,"dataGaName":309,"dataGaLocation":470},{"text":314,"config":665},{"href":316,"dataGaName":317,"dataGaLocation":470},{"text":319,"config":667},{"href":321,"dataGaName":322,"dataGaLocation":470},{"text":324,"config":669},{"href":326,"dataGaName":327,"dataGaLocation":470},{"text":329,"config":671},{"href":331,"dataGaName":332,"dataGaLocation":470},{"text":673,"config":674},"Sustainability",{"href":675,"dataGaName":673,"dataGaLocation":470},"/sustainability/",{"text":677,"config":678},"Diversity, inclusion and belonging (DIB)",{"href":679,"dataGaName":680,"dataGaLocation":470},"/diversity-inclusion-belonging/","Diversity, inclusion and belonging",{"text":334,"config":682},{"href":336,"dataGaName":337,"dataGaLocation":470},{"text":344,"config":684},{"href":346,"dataGaName":347,"dataGaLocation":470},{"text":349,"config":686},{"href":351,"dataGaName":352,"dataGaLocation":470},{"text":688,"config":689},"Modern Slavery Transparency Statement",{"href":690,"dataGaName":691,"dataGaLocation":470},"https://handbook.gitlab.com/handbook/legal/modern-slavery-act-transparency-statement/","modern slavery transparency statement",{"items":693},[694,697,700],{"text":695,"config":696},"Terms",{"href":522,"dataGaName":523,"dataGaLocation":470},{"text":698,"config":699},"Cookies",{"dataGaName":532,"dataGaLocation":470,"id":533,"isOneTrustButton":12},{"text":701,"config":702},"Privacy",{"href":527,"dataGaName":528,"dataGaLocation":470},[704],{"id":705,"title":706,"body":8,"config":707,"content":709,"description":8,"extension":28,"meta":713,"navigation":12,"path":714,"seo":715,"stem":716,"__hash__":717},"blogAuthors/en-us/blog/authors/david-oregan.yml","David Oregan",{"template":708},"BlogAuthor",{"name":18,"config":710},{"headshot":711,"ctfId":712},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1749659853/Blog/Author%20Headshots/oregand-headshot.png","oregand",{},"/en-us/blog/authors/david-oregan",{},"en-us/blog/authors/david-oregan","CX5gLc3Gs5FrmvpMNVkBtC5zRi3vj8l3wJGnW0iSa6Y",[719,733,746],{"content":720,"config":731},{"heroImage":721,"title":722,"description":723,"authors":724,"date":726,"category":9,"tags":727,"body":730},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772643639/sapu29gmlgtwvhggmj6k.png","Extend GitLab Duo Agent Platform: Connect any tool with MCP","Learn how to connect external tools to GitLab Duo Agent Platform using MCP. Step-by-step setup with three practical workflow demos.",[725],"Albert Rabassa","2026-03-05",[9,728,729],"product","tutorial","Managing software development often means juggling multiple tools: tracking issues in Jira, writing code in your IDE, and collaborating through GitLab. Context switching between these platforms disrupts focus and slows down delivery.\n\nWith GitLab Duo Agent Platform's [MCP](https://about.gitlab.com/topics/ai/model-context-protocol/) support, you can now connect Jira or any tool that supports MCP directly to your AI-powered development environment. Query issues, update tickets, and sync your workflow — all through natural language, without ever leaving your IDE.\n\n## What you'll learn\n\nIn this tutorial, we'll walk you through:\n\n* **Setting up the Jira/Atlassian OAuth application** for secure authentication\n* **Configuring GitLab Duo Agent Platform** as an MCP client\n* **Three practical use cases** demonstrating real-world workflows\n\n## Prerequisites\n\nBefore getting started, ensure you have the following:\n\n| Requirement | Details |\n| ---- | ----- |\n| **GitLab instance** | GitLab 18.8+ with Duo Agent Platform enabled |\n| **Jira account** | Jira Cloud instance with admin access to create OAuth applications |\n| **IDE** | Visual Studio Code with GitLab Workflow extension installed |\n| **MCP support** | MCP support enabled in GitLab |\n\n\n## Understanding the architecture\n\nGitLab Duo Agent Platform acts as an **MCP client**, connecting to the Atlassian MCP server to access your Jira project management data. Atlassian  MCP server handles authentication, translates natural language requests into API calls, and returns structured data back to GitLab Duo Agent Platform — all while maintaining security and audit controls.\n\n## Part 1: Configure Jira OAuth application\n\nTo securely connect GitLab Duo Agent Platform to your Jira instance, you'll need to create an OAuth 2.0 application in the Atlassian Developer Console. This grants to GitLab the MCP server authorized access to your Jira data.\n\n### Setup steps\n\nIf you prefer to configure manually, follow these steps:\n\n1. **Navigate to the Atlassian Developer Console**\n\n   * Go to [developer.atlassian.com/console/myapps](https://developer.atlassian.com/console/myapps)\n\n   * Sign in with your Atlassian account\n\n2. **Create a new OAuth 2.0 app**\n\n   * Click **Create** → **OAuth 2.0 integration**\n\n   * Enter a name (e.g., \"gitlab-dap-mcp\")\n\n   * Accept the terms and click **Create**\n\n3. **Configure permissions**\n\n   * Navigate to **Permissions** in the left sidebar.\n\n   * Add **Jira API** and configure the following scopes:\n\n     * `read:jira-work` — Read issues, projects, and boards\n\n     * `write:jira-work` — Create and update issues\n\n     * `read:jira-user` — Read user information\n\n4. **Set up authorization**\n\n   * Go to **Authorization** in the left sidebar\n\n   * Add a callback URL for your environment (`https://gitlab.com/oauth/callback`)\n\n   * Save your changes\n\n5. **Retrieve credentials**\n\n   * Navigate to **Settings**\n\n   * Copy your **Client ID** and **Client Secret**\n\n   * Store these securely — you'll need them for the MCP configuration\n\n\n### Interactive walkthrough: Jira OAuth setup\n\nClick on the image below to get started.\n\n\n[![Jira OAuth setup tour](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772644850/wnzfoq43nkkfmgdqldmr.png)](https://gitlab.navattic.com/jira-oauth-setup)\n\n\n## Part 2: Configure GitLab Duo Agent Platform MCP client\n\nWith your OAuth credentials ready, you can now configure GitLab Duo Agent Platform to connect to the Atlassian MCP server.\n\n### Create your MCP configuration file\n\nCreate the MCP configuration file in your GitLab project at `.gitlab/duo/mcp.json`:\n\n\n```json\n{\n  \"mcpServers\": {\n    \"atlassian\": {\n      \"type\": \"http\",\n      \"url\": \"https://mcp.atlassian.com/v1/mcp\",\n      \"auth\": {\n        \"type\": \"oauth2\",\n        \"clientId\": \"YOUR_CLIENT_ID\",\n        \"clientSecret\": \"YOUR_CLIENT_SECRET\",\n        \"authorizationUrl\": \"https://auth.atlassian.com/oauth/authorize\",\n        \"tokenUrl\": \"https://auth.atlassian.com/oauth/token\"\n      },\n      \"approvedTools\": true\n    }\n  }\n}\n```\n\nReplace `YOUR_CLIENT_ID` and `YOUR_CLIENT_SECRET` with the credentials you generated in Part 1.\n\n### Enable MCP in GitLab\n\n1. Navigate to your **Group Settings** → **GitLab Duo** → **Configuration**\n2. Make sure “Allow external MCP tools” is checked\n\n### Verify the connection\n\nOpen your project in VS Code and ask in GitLab Duo Agent Platform chat:\n\n```text\nWhat MCP tools do you have access to?\n```\n\nThen\n\n```text\nTest the MCP JIRA configuration in this project\n```\n\nAt this point you'll be redirected from the IDE to the MCP Atlassian website to approve access:\n\n![Redirect to MCP Atlassian website](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772643461/z5acqjgguh0damnnde9g.png \"Redirect to MCP Atlassian website\")\n\n\u003Cbr>\u003C/br>\n\n![Approve access](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772643461/rwowamm8nsubhpixtn3i.png \"Approve access\")\n\n\u003Cbr>\u003C/br>\n\n![Select your JIRA instance and approve](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772643461/chuzqd0jeptfwvoj7wjr.png \"Select your JIRA instance and approve\")\n\n\u003Cbr>\u003C/br>\n\n![Success!](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772643462/bsgti5iste2bzck19o5y.png \"Success!\")\n\n\u003Cbr>\u003C/br>\n\n### Verify with the MCP Dashboard\n\nGitLab also provides a built-in **MCP Dashboard** directly in your IDE for this.\n\nIn VS Code or VSCodium, open the Command Palette (`Cmd+Shift+P` on macOS, `Ctrl+Shift+P` on Windows/Linux) and search for **\"GitLab: Show MCP Dashboard\"**. The dashboard opens in a new editor tab and gives you:\n\n* **Connection status** for each configured MCP server\n* **Available tools** exposed by the server (e.g., `jira_get_issue`, `jira_create_issue`)\n* **Server logs** so you can see exactly which tools are being called in real time\n\n![MCP servers dashboard and status](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772643462/mmvdfchucacsydivowvn.png \"MCP servers dashboard and status\")\n\n\u003Cbr>\u003C/br>\n\n![Server details and permissions](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772643462/tcocgdvovp2dl42pvfn8.png \"Server details and permissions\")\n\n\u003Cbr>\u003C/br>\n\n\n![MCP Server logs](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772643466/mougvqqk1bozchaufsci.png \"MCP Server logs\")\n\n\u003Cbr>\u003C/br>\n\n### Interactive walkthrough: Testing MCP\n\n\u003Ciframe src=\"https://player.vimeo.com/video/1170005495?badge=0&autopause=0& player_id=0&app_id=58479\" frameborder=\"0\" allow=\"autoplay; fullscreen; picture-in-picture; clipboard-write; encrypted-media; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" style=\"position:absolute;top:0;left:0;width:100%;height:100%;\" title=\"Testing MCP\">\u003C/iframe>\u003Cscript src=\"https://player.vimeo.com/api/player.js\">\u003C/script>\n\n## Part 3: Use cases in action\n\nNow that your integration is configured, let's explore three practical workflows that demonstrate the power of connecting Jira to GitLab Duo Agent Platform.\n\n### Planning assistant\n\n**Scenario:** You're preparing for sprint planning and need to quickly assess the backlog, understand priorities, and identify blockers.\n\nThis demo shows you how to:\n\n* Query the backlog\n* Identify unassigned high-priority issues\n* Get AI-powered sprint recommendations\n\n#### Example prompts\n\nTry these prompts in GitLab Duo Agent Platform Chat:\n\n```text\nList all the unassigned issues in JIRA for project GITLAB\n```\n\n```text\nSuggest the two top issues to prioritize and summarize them. Assign them to me.\n```\n\n### Interactive walkthrough: Project planning\n\n\u003Ciframe src=\"https://player.vimeo.com/video/1170005462?badge=0&autopause=0&player_id=0&app_id=58479\" frameborder=\"0\" allow=\"autoplay; fullscreen; picture-in-picture; clipboard-write; encrypted-media; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" style=\"position:absolute;top:0;left:0;width:100%;height:100%;\" title=\"Project Planning\">\u003C/iframe>\u003Cscript src=\"https://player.vimeo.com/api/player. js\">\u003C/script>\n\n### Issue triage and creation from code\n\n**Scenario:** While reviewing code, you discover a bug and want to create a Jira issue with relevant context — without leaving your IDE.\n\nThis demo walks you through:\n\n* Identifying a bug while coding\n* Creating a detailed Jira issue via natural language\n* Auto-populating issue fields with code context\n* Linking the issue to your current branch\n\n#### Example prompts\n\n```text\nSearch in JIRA for a bug related to: Null pointer exception in PaymentService.processRefund().\nIf it does not exist create it with all the context needed from the code. Find possible blockers that this bug may cause.\n```\n\n```text\nCreate a new branch called issue-gitlab-18, checkout, and link it to the issue we just created. Assign the JIRA issue to me and mark it as in-progress.\n```\n\n### Interactive walkthrough: Bug review and task automation\n\n\u003Ciframe src=\"https://player.vimeo.com/video/1170005368?badge=0&autopause=0& player_id=0&app_id=58479\" frameborder=\"0\" allow=\"autoplay; fullscreen; picture-in-picture; clipboard-write; encrypted-media; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" style=\"position:absolute;top:0;left:0;width:100%;height:100%;\" title=\"Bug Review\">\u003C/iframe>\u003Cscript src=\"https://player.vimeo.com/api/player.js\">\u003C/script>\n\n### Cross-system incident investigation\n\n**Scenario:** A production incident occurs, and you need to correlate information from Jira (incident ticket), GitLab Project Management, your codebase, and merge requests to identify the root cause.\n\nThis demo demonstrates:\n\n* Fetching incident details from Jira\n* Correlating with recent merge requests in GitLab\n* Identifying potentially related code changes\n* Generating an incident timeline\n* Design a remediation plan and create it as a work item in GitLab\n\n#### Example prompts\n\n```text\n\"We have a production incident INC-1 about checkout failures. Can you help me investigate with all available context?\"\n```\n\n```text\nCreate a timeline of events for incident INC-1 including related Jira issues and recent deployments\n```\n\n```text\nPropose a remediation plan\n```\n\n### Interactive walkthrough: Cross-system troubleshooting and remediation\n\n\u003Ciframe src=\"https://player.vimeo.com/video/1170005413?badge=0&autopause=0& player_id=0&app_id=58479\" frameborder=\"0\" allow=\"autoplay; fullscreen; picture-in-picture; clipboard-write; encrypted-media; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" style=\"position:absolute;top:0;left:0;width:100%;height:100%;\" title=\"Cross System Investigation\">\u003C/iframe>\u003Cscript src=\"https://player.vimeo.com/api/player.js\">\u003C/script>\n\n## Troubleshooting\n\nThese are some common setup issues and quick fixes:\n\n| Issue | Solution |\n| ----- | ----- |\n| \"MCP server not found\" | Verify the `mcp.json` file is in the correct location and properly formatted |\n| \"Authentication failed\" | Re-check your OAuth credentials and ensure scopes are correctly configured in Atlassian |\n| \"No Jira tools available\" | Restart VS Code after updating `mcp.json` and ensure MCP is enabled in GitLab |\n| \"Connection timeout\" | Check your network connectivity to `mcp.atlassian.com` |\n\n\u003Cbr/> For detailed troubleshooting, see the [GitLab MCP clients documentation](https://docs.gitlab.com/user/gitlab_duo/model_context_protocol/mcp_clients/).\n\n\n## Security considerations\n\nWhen integrating Jira with GitLab Duo Agent Platform:\n\n* **OAuth tokens** — Make sure credentials remain secure\n* **Principle of least privilege** — Only grant the minimum required Jira scopes\n* **Token rotation** — Regularly rotate your OAuth credentials as part of security hygiene\n\n\n## Summary\n\nConnecting GitLab Duo Agent Platform to different tools through MCP transforms how you interact with your development lifecycle. In this article, you have learned how to:\n\n* **Query issues naturally** — Ask questions about your backlog, sprints, and incidents in natural language.\n* **Create and update issues on all your DevSecOps environment** — File bugs and update tickets without leaving your IDE.\n* **Correlate across systems** — Combine Jira data with GitLab project management, merge requests, and pipelines for complete visibility.\n* **Reduce context switching** — Keep your focus on code while staying connected to project management.\n\nThis integration exemplifies the power of MCP: standardized, secure access to your tools through AI, enabling developers to work more efficiently without sacrificing governance or security.\n\n\n## Read more\n\n* [GitLab Duo Agent Platform adds support for Model Context Protocol](https://about.gitlab.com/blog/duo-agent-platform-with-mcp/)\n\n* [What is Model Context Protocol?](https://about.gitlab.com/topics/ai/model-context-protocol/)\n\n* [Agentic AI guides and resources](https://about.gitlab.com/blog/agentic-ai-guides-and-resources/)\n\n* [GitLab MCP clients documentation](https://docs.gitlab.com/user/gitlab_duo/model_context_protocol/mcp_clients/)\n\n* [Get started with GitLab Duo Agent Platform: The complete guide](https://about.gitlab.com/blog/gitlab-duo-agent-platform-complete-getting-started-guide/)",{"featured":32,"template":13,"slug":732},"extend-gitlab-duo-agent-platform-connect-any-tool-with-mcp",{"content":734,"config":744},{"title":735,"description":736,"authors":737,"heroImage":739,"date":740,"body":741,"category":9,"tags":742},"10 AI prompts to speed your team’s software delivery","Eliminate review backlogs, security delays, and coordination overhead with ready-to-use AI prompts covering every stage of the software lifecycle.",[738],"Chandler Gibbons","https://res.cloudinary.com/about-gitlab-com/image/upload/v1772632341/duj8vaznbhtyxxhodb17.png","2026-03-04","AI-assisted coding tools are helping developers generate code faster than ever. So why aren’t teams _shipping_ faster?\n\nBecause coding is only 20% of the software delivery lifecycle, the remaining 80% becomes the bottleneck: code review backlogs grow, security scanning can’t keep pace, documentation falls behind, and manual coordination overhead increases.\n\nThe good news is that the same AI capabilities that accelerate individual coding can eliminate these team-level delays. You just need to apply AI across your entire software lifecycle, not only during the coding phase.\n\nBelow are 10 ready-to-use prompts from the [GitLab Duo Agent Platform Prompt Library](https://about.gitlab.com/gitlab-duo/prompt-library/) that help teams overcome common obstacles to faster software delivery. Each prompt addresses a specific slowdown that emerges when individual productivity increases without corresponding improvements in team processes.\n\n## How do you move code review from bottleneck to accelerator?\nDevelopers generate merge requests faster with AI assistance, but human reviewers can quickly become overwhelmed as code review cycles stretch from hours to days. AI can handle routine review tasks, freeing reviewers to focus on architecture and business logic instead of catching basic logical errors and API contract violations.\n\n### Review MR for logical errors\n**Complexity**: Beginner\n\n**Category**: Code Review\n\n**Prompt from library**:\n\n\n```text\nReview this MR for logical errors, edge cases, and potential bugs: [MR URL or paste code]\n```\n\n**Why it helps**: Automated linters catch syntax issues, but logical errors require understanding intent. This prompt catches bugs before human reviewers even look at the code, reducing review cycles from multiple rounds to often just one approval.\n\n### Identify breaking changes in MR\n**Complexity**: Beginner\n\n**Category**: Code Review\n\n**Prompt from library**:\n\n\n```text\nDoes this MR introduce any breaking changes?\n\nChanges:\n[PASTE CODE DIFF]\n\nCheck for:\n1. API signature changes\n2. Removed or renamed public methods\n3. Changed return types\n4. Modified database schemas\n5. Breaking configuration changes\n```\n\n**Why it helps**: Breaking changes discovered during deployment can cause rollbacks and incidents. This prompt shifts that discovery left to the MR stage, when fixes are faster and less expensive.\n\n## How can you shift security left without slowing down?\nSecurity scans generate hundreds of findings. Security teams manually triage each one while developers wait for approval to deploy. Most findings are false positives or low-risk issues, but identifying the real threats requires expertise and time. AI can prioritize findings by actual exploitability and auto-remediate common vulnerabilities, allowing security teams to focus on the threats that matter.\n\n### Analyze security scan results\n**Complexity**: Intermediate\n\n**Category**: Security\n\n**Agent**: Duo Security Analyst\n\n**Prompt from library**:\n\n\n```text\n@security_analyst Analyze these security scan results:\n\n[PASTE SCAN OUTPUT]\n\nFor each finding:\n1. Assess real risk vs false positive\n2. Explain the vulnerability\n3. Suggest remediation\n4. Prioritize by severity\n```\n\n**Why it helps**: Most security scan findings are false positives or low-risk issues. This prompt helps security teams focus on the findings that actually matter, reducing remediation time from weeks to days.\n\n### Review code for security issues\n**Complexity**: Intermediate\n\n**Category**: Security\n\n**Agent**: Duo Security Analyst\n\n**Prompt from library**:\n\n```text\n@security_analyst Review this code for security issues:\n\n[PASTE CODE]\n\nCheck for:\n1. Injection vulnerabilities\n2. Authentication/authorization flaws\n3. Data exposure risks\n4. Insecure dependencies\n5. Cryptographic issues\n```\n\n**Why it helps**: Traditional security reviews happen after code is written. This prompt enables developers to find and fix security issues before creating an MR, eliminating the back and forth that delays deployments.\n\n## How do you keep documentation current as code changes?\nCode changes faster than documentation. Onboarding new developers takes weeks because docs are outdated or missing. Teams know documentation is important, but it always gets deferred when deadlines approach. Automating documentation generation and updates as part of your standard workflow ensures docs stay current without adding manual work.\n\n### Generate release notes from MRs\n**Complexity**: Beginner\n\n**Category**: Documentation\n\n**Prompt from library**:\n\n```text\nGenerate release notes for these merged MRs:\n[LIST MR URLs or paste titles]\n\nGroup by:\n1. New features\n2. Bug fixes\n3. Performance improvements\n4. Breaking changes\n5. Deprecations\n```\n\n**Why it helps**: Manual release note compilation takes hours and often includes errors or omissions. Automated generation ensures every release has comprehensive notes without adding work to your release process.\n\n### Update documentation after code changes\n**Complexity**: Beginner\n\n**Category**: Documentation\n\n**Prompt from library**:\n\n```text\nI changed this code:\n\n[PASTE CODE CHANGES]\n\nWhat documentation needs updating? Check:\n1. README files\n2. API documentation\n3. Architecture diagrams\n4. Onboarding guides\n```\n\n**Why it helps**: Documentation drift happens because teams forget which docs need updates after code changes. This prompt makes documentation maintenance part of your development workflow, not a separate task that gets deferred.\n\n## How do you break down planning complexity?\nLarge features get stuck in planning. Teams spend weeks in meetings trying to scope work and identify dependencies. The complexity feels overwhelming, and it's hard to know where to start. AI can systematically decompose complex work into concrete, implementable tasks with clear dependencies and acceptance criteria, transforming weeks of planning into focused implementation.\n\n### Break down epic into issues\n**Complexity**: Intermediate\n\n**Category**: Documentation\n\n**Agent**: Duo Planner\n\n**Prompt from library**:\n\n```text\nBreak down this epic into implementable issues:\n\n[EPIC DESCRIPTION]\n\nConsider:\n1. Technical dependencies\n2. Reasonable issue sizes\n3. Clear acceptance criteria\n4. Logical implementation order\n```\n\n**Why it helps**: This prompt transforms a week of planning meetings into 30 minutes of AI-assisted decomposition followed by team review. Teams start implementation sooner with clearer direction.\n\n## How can you expand test coverage without expanding effort?\nDevelopers are writing code faster, but if testing doesn't keep pace, test coverage decreases and bugs slip through. Writing comprehensive tests manually is time-consuming, and developers often miss edge cases under deadline pressure. Generating tests automatically means developers can review and refine rather than write from scratch, maintaining quality without sacrificing velocity.\n\n### Generate unit tests\n**Complexity**: Beginner\n\n**Category**: Testing\n\n**Prompt from library**:\n\n```text\nGenerate unit tests for this function:\n\n[PASTE FUNCTION]\n\nInclude tests for:\n1. Happy path\n2. Edge cases\n3. Error conditions\n4. Boundary values\n5. Invalid inputs\n```\n\n**Why it helps**: Writing tests manually is time consuming, and developers often miss edge cases. This prompt generates thorough test suites in seconds, which developers can review and adjust rather than write from scratch.\n\n### Review test coverage gaps\n**Complexity**: Beginner\n\n**Category**: Testing\n\n**Prompt from library**:\n\n```text\nAnalyze test coverage for [MODULE/COMPONENT]:\n\nCurrent coverage: [PERCENTAGE]\n\nIdentify:\n1. Untested functions/methods\n2. Uncovered edge cases\n3. Missing error scenario tests\n4. Integration points without tests\n5. Priority areas to test next\n```\n\n**Why it helps**: This prompt reveals blind spots in your test suite before they cause production incidents. Teams can systematically improve coverage where it matters most.\n\n## How do you reduce mean time to resolution when debugging?\nProduction incidents take hours to diagnose. Developers wade through logs and stack traces while customers experience downtime. Every minute of debugging is a minute of lost productivity and potential revenue. AI can accelerate root cause analysis by parsing complex error messages and suggesting specific fixes, cutting diagnostic time from hours to minutes.\n\n### Debug failing pipeline\n**Complexity**: Beginner\n\n**Category**: Debugging\n\n**Prompt from library**:\n\n```text\nThis pipeline is failing:\n\nJob: [JOB NAME]\nStage: [STAGE]\nError: [PASTE ERROR MESSAGE/LOG]\n\nHelp me:\n1. Identify the root cause\n2. Suggest a fix\n3. Explain why it started failing\n4. Prevent similar issues\n```\n\n**Why it helps**: CI/CD failures block entire teams. This prompt diagnoses failures in seconds instead of the 15-30 minutes developers typically spend investigating, keeping deployment velocity high.\n\n## Moving from individual gains to team acceleration\nThese prompts represent a shift in how teams apply AI to software delivery. Rather than focusing solely on individual developer productivity, they address the coordination, quality, and knowledge-sharing challenges that actually constrain team velocity.\n\nThe [complete prompt library](https://about.gitlab.com/gitlab-duo/prompt-library/) contains more than 100 prompts across all stages of the software lifecycle: planning, development, security, testing, deployment, and operations. Each prompt is tagged by complexity level (Beginner, Intermediate, Advanced) and categorized by use case, making it easy to find the right starting point for your team.\n\nStart with prompts tagged “Beginner” that address your team’s most pressing obstacles. As your team builds confidence, explore intermediate and advanced prompts that enable more sophisticated workflows. The goal is not just faster coding — it's faster, safer, higher-quality software delivery from planning through production.",[23,743],"DevOps platform",{"featured":32,"template":13,"slug":745},"10-ai-prompts-to-speed-your-teams-software-delivery",{"content":747,"config":757},{"title":748,"description":749,"heroImage":750,"authors":751,"date":753,"body":754,"category":9,"tags":755},"AI can detect vulnerabilities, but who governs risk?","AI-assisted vulnerability detection is developing fast, but the harder challenges of enforcement, governance, and supply chain security require a holistic platform.","https://res.cloudinary.com/about-gitlab-com/image/upload/v1772195014/ooezwusxjl1f7ijfmbvj.png",[752],"Omer Azaria","2026-02-27","Anthropic recently announced Claude Code Security, an AI system that detects vulnerabilities and proposes fixes. The market reacted immediately, with security stocks dipping as investors questioned whether AI might replace traditional AppSec tools. The question on everyone's mind: If AI can write code and secure it, is application security about to become obsolete?\n\nIf security only meant scanning code, the answer might be yes. But enterprise security has never been about detection alone.\n\nOrganizations are not asking whether AI can find vulnerabilities. They are asking three much harder questions: \n\n* Is what we are about to ship safe?  \n* Has our risk posture changed as environments evolve and dependencies, third-party services, tools, and infrastructure continuously shift?  \n* How do we govern a codebase that is increasingly assembled by AI and third-party sources, and that we are still accountable for? \n\nThose questions require a platform answer: Detection surfaces risk, but governance determines what happens next. \n\n[GitLab](https://about.gitlab.com/) is the orchestration layer built to govern the software lifecycle end-to-end. It gives teams the enforcement, visibility, and auditability they need to keep pace with the speed of AI-assisted development.\n\n## Trusting AI requires governing risk\n\nAI systems are rapidly getting better at identifying vulnerabilities and suggesting fixes. This is a meaningful and welcome advancement, but analysis is not accountability.\n\nAI cannot enforce company policy or define acceptable risk on its own. Humans must set the boundaries, policies, and guardrails that agents operate within, establishing separation of duties, ensuring audit trails, and maintaining consistent controls across thousands of repositories and teams. Trust in agents comes not from autonomy alone, but from clearly defined governance set by people. \n\nIn an [agentic world](https://about.gitlab.com/topics/agentic-ai/), where software is increasingly written and modified by autonomous systems, governance becomes more important, not less. The more autonomy organizations grant to AI, the stronger the governance must be.\n\nGovernance is not friction. It is the foundation that makes AI-assisted development trustworthy at scale.\n\n## LLMs see code, but platforms see context\n\nA large language model ([LLM](https://about.gitlab.com/blog/what-is-a-large-language-model-llm/)) evaluates code in isolation. An enterprise application security platform understands context. This difference matters because risk decisions are contextual:\n\n* Who authored the change?  \n* How critical is the application to the business?  \n* How does it interact with infrastructure and dependencies?  \n* Does the vulnerability exist in code that is actually reachable in production, or is it buried in a dependency that never executes?  \n* Is it actually exploitable in production, given how the application runs, its APIs, and the environment around it?\n\nSecurity decisions depend on this context. Without it, detection produces noisy alerts that slow down development rather than reducing risk. With it, organizations can triage quickly and manage risk effectively. Context evolves continuously as software changes, which means governance cannot be a one-time decision. \n\n## Static scans can’t keep up with dynamic risk\n\nSoftware risk is dynamic. Dependencies change, environments evolve, and systems interact in ways no single analysis can fully predict. A clean scan at one moment does not guarantee safety at release.\n\nEnterprise security depends on continuous assurance: controls embedded directly into development workflows that evaluate risk as software is built, tested, and deployed.\n\nDetection provides insight. Governance provides trust. Continuous governance is what allows organizations to ship safely at scale.\n\n## Governing the agentic future\n\nAI is reshaping how software is created. The question is no longer whether teams will use AI, but how safely they can scale it.\n\nSoftware today is assembled as much as it is written, from AI-generated code, open-source libraries, and third-party dependencies that span thousands of projects. Governing what ships across all of those sources is the hardest and most consequential part of application security, and it is the part that no developer-side tool is built to address. \n\nAs an intelligent orchestration platform, GitLab is built to address this problem. GitLab Ultimate embeds governance, policy enforcement, security scanning, and auditability directly into the workflows where software is planned, built, and shipped, so security teams can govern at the speed of AI. \n\nAI will accelerate development dramatically. The organizations that benefit most from AI will not be those with the smartest assistants alone, but those that build trust through strong governance.\n\n> To learn how GitLab helps organizations [govern and ship AI-generated code](https://about.gitlab.com/solutions/software-compliance/?utm_medium=blog&utm_campaign=eg_global_x_x_security_en_) safely, [talk to our team today](https://about.gitlab.com/sales/?utm_medium=blog&utm_campaign=eg_global_x_x_security_en_)\n\n\n ## Related reading\n\n - [Integrating AI with DevOps for enhanced security](https://about.gitlab.com/topics/devops/ai-enhanced-security/)\n - [The GitLab AI Security Framework for security leaders](https://about.gitlab.com/blog/the-gitlab-ai-security-framework-for-security-leaders/)\n - [Improve AI security in GitLab with composite identities](https://about.gitlab.com/blog/improve-ai-security-in-gitlab-with-composite-identities/)",[23,756],"security",{"featured":12,"template":13,"slug":758},"ai-can-detect-vulnerabilities-but-who-governs-risk",{"promotions":760},[761,774,785],{"id":762,"categories":763,"header":764,"text":765,"button":766,"image":771},"ai-modernization",[9],"Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":767,"config":768},"Get your AI maturity score",{"href":769,"dataGaName":770,"dataGaLocation":246},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":772},{"src":773},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":775,"categories":776,"header":777,"text":765,"button":778,"image":782},"devops-modernization",[728,571],"Are you just managing tools or shipping innovation?",{"text":779,"config":780},"Get your DevOps maturity score",{"href":781,"dataGaName":770,"dataGaLocation":246},"/assessments/devops-modernization-assessment/",{"config":783},{"src":784},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":786,"categories":787,"header":788,"text":765,"button":789,"image":793},"security-modernization",[756],"Are you trading speed for security?",{"text":790,"config":791},"Get your security maturity score",{"href":792,"dataGaName":770,"dataGaLocation":246},"/assessments/security-modernization-assessment/",{"config":794},{"src":795},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":797,"blurb":798,"button":799,"secondaryButton":804},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":800,"config":801},"Get your free trial",{"href":802,"dataGaName":53,"dataGaLocation":803},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":508,"config":805},{"href":57,"dataGaName":58,"dataGaLocation":803},1777309965087]