Your AI agent can clone your entire repo before writing a single line of code, and nothing about that looks broken. It just doesn't scale. We're rebuilding that layer of the agentic SDLC, from how agents access code to how you track what they did. Explore GitLab's capabilities through interactive demos and hands-on experiences. https://lnkd.in/eWYqAjwt
GitLab
IT Services and IT Consulting
San Francisco, California 1,184,793 followers
Build software faster. The DevSecOps Platform enables your entire org to collaborate around your code. We're hiring.
About us
GitLab is the Intelligent Orchestration Platform where software teams and their AI agents stay in flow to amplify their capacity for innovation. Together, they automate repetitive tasks to plan, build, secure, test, deploy and maintain software. With GitLab, software teams spend less time on coordination overhead and more time on the next big idea. GitLab Duo Agent Platform provides AI agents that automate tasks across the software lifecycle. Agents handle code generation, security analysis, code review, CI/CD troubleshooting, and custom workflows — while teams maintain control through enterprise governance. Build what's next with us. Explore open roles and join our talent community: https://about.gitlab.com/jobs/
- Website
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https://about.gitlab.com/?utm_medium=social&utm_source=linkedin&utm_campaign=profile
External link for GitLab
- Industry
- IT Services and IT Consulting
- Company size
- 1,001-5,000 employees
- Headquarters
- San Francisco, California
- Type
- Public Company
- Founded
- 2014
Products
![Click here to view GitLab Duo]()
GitLab Duo
DevOps Software
A suite of AI-assisted features powering your workflows in every phase of the software development lifecycle. GitLab Duo has more capabilities than any other vendor, helping you secure code faster, improve collaboration, and reduce the security and compliance risks of AI adoption.
Locations
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268 Bush St
San Francisco, California, US
Employees at GitLab
Updates
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The Developer Show: Transcend Edition Miss the keynote? We've got you covered. Join us for a developer focused recap breaking down every announcement from today's keynote and what it actually means for how you build. We'll cover the news, translate it into practical impact for your workflow, and show live demos of the new capabilities in action. Save your spot and bring your questions, we're leaving room to answer them live.
The Developer Show: Transcend Edition
www.linkedin.com
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More model choice, delivered fast. GPT-6 Sol and Luna from OpenAI are now available on GitLab Duo Agent Platform, across all tiers and deployment models. Try them now.
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As agentic automation spreads from individual developers to entire engineering teams, what limits its reach is no longer what agents can do but how confidently an organization can extend it. GitLab 19.4 brings new agentic automation at lower cost, with the control platform owners need to scale it. Read the full 19.4 release notes:https://lnkd.in/ecSpUeVD 🚀
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"It's not what happens, it's how you deal with it." GitLab CISO Chaim Mazal joined the Lead the Team Podcast (Top 2% Globally) podcast to talk about the cybersecurity incident that tested him early in his career, and what it taught him about leading through a crisis. Listen to the full discussion with Ben Fanning for Chaim’s insight on how great leaders stay composed under pressure, build resilient teams, and respond when things don’t go according to plan. Link in comments.
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Two weeks from today, Transcend goes live from Bangalore and streams from wherever you are. https://lnkd.in/dpz6MWmG Coding is only 20% of the software lifecycle. What does it take to turn AI momentum into measurable value from code to deployment? Here’s a preview of some of what’s ahead at GitLab Transcend.
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Three open weight models are now available and hosted on GitLab Duo Agent Platform, so you can tune quality, latency, and cost per workload, within your guardrails. Learn more in the blog: https://lnkd.in/espM5xgX Open weight models can improve inference cost on many agentic tasks, giving teams up to 4x more calls per GitLab Credit, while keeping performance in line with frontier models. Admins still set the default model per feature and curate what teams can choose from, keeping full control even as the options expand.
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A subscription cap keeps total AI spend within budget, but it can't tell you which team spent it to help predict next quarter’s budget needs. Without per-person data, you can't set a fair cap, explain a spike, or show a department what it actually consumed. GitLab Credits usage visibility, now generally available, makes AI spend even more manageable with additional granularity and controls. Set a default cap for every user, override it for individuals, and show developers their own consumption. Export usage down to the billable event, including by user, activity, and timeframe, so you can share usage with teams and departments. Learn more in the blog. https://lnkd.in/efeHV2Rd
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Advanced AI models are handing engineering teams something we could only have hoped for a year ago. Building software that tests, inspects, and improves itself with verified remediation at machine speed. GitLab CISO Chaim Mazal breaks down what that takes in practice: know your attack surface, constrain execution, and close the loop from discovery to verified fix. Read his full take as he explains why defenders who build the right operating standard around advanced AI models will turn that advantage into more trustworthy software: https://lnkd.in/eZiTSKBy