Gitlab Inc.GTLB

GitLab states implementation of AI including agentic AI in its services may cause reputational harm and other adverse effects.

“• The implementation of AI, including agentic AI, and machine learning technologies in our services may result in reputational harm, liability, increased expenditures, or other adverse consequences to our business operations.”

GitLab offers intelligent orchestration to enable teams to orchestrate AI agents across the software lifecycle.

“AI has accelerated individual coding, but teams lose momentum coordinating across planning, testing, security, deployment, and operations. Fragmented toolchains and tool-specific AI agents create bottlenecks that slow software delivery. GitLab's intelligent orchestration helps solve this by enabling teams to orchestrate AI agents to execute tasks autonomously across the software lifecycle while maintaining quality, security, and speed.”

GitLab notes AI-specific attack vectors and agentic AI changing security practices for threat actors and defenders.

“Techniques used to obtain unauthorized access or to sabotage systems change frequently, including novel AI-specific attack vectors and vulnerabilities. The use of agentic AI is changing the fundamental ways that we secure and defend our platform and operations as both threat actors and security teams are using AI to industrialize their attacks. Traditional perimeter controls and static security rules are no longer the most effective security mechanisms and we, in alignment with our industry, are reinforcing our defensive capabilities in areas such as, but not limited to, behavioral analysis, automated detection response, and zero-trust. However, we may be unable to fully anticipate these techniques or implement adequate preventative measures. If an actual or perceived security breach occurs, the market perception of our security measures could be harmed, and we could lose sales and customers. If we are, or are perceived to be, not in compliance with data protection, consumer privacy, or other legal or regulatory requirements or operational norms bearing on the collection, processing, storage, or other treatment of data records, including personal data, our reputation and operating performance may suffer. Further, we need to continually monitor and remain compliant with all applicable changes in local, state, national, or international legal or regulatory requirements. Any significant violations of data privacy could result in the loss of business, litigation, and regulatory i”

GitLab states implementing AI including agentic AI may cause reputational harm, liability or adverse business consequences.

“The implementation of AI, including agentic AI, and machine learning technologies in our services may result in reputational harm, liability, increased expenditures, or other adverse consequences to our business operations.”

GitLab has implemented AI capabilities including agentic AI as part of its GitLab Duo suite.

“We have implemented AI capabilities throughout GitLab’s services, including as part of the GitLab Duo suite of AI features. AI, and particularly agentic AI, has become increasingly central to our business strategy. The technologies underpinning these features exist in a rapidly-evolving regulatory and commercial environment which presents regulatory, litigation, ethical, reputational, and financial risks.”

GitLab offers agentic AI features via the GitLab Duo Agent Platform to automate software development.

“Some of our AI-powered features, including those offered through the GitLab Duo Agent Platform, are designed to automate elements of the software development lifecycle based on user-defined goals and context. As the prevalence and scrutiny of such agentic AI systems increases, we may face regulatory, litigation, ethical, reputational, and financial risks.”

GitLab expanded context for AI agents with GitLab Orbit in public beta.

“• Expanded context for AI agents with GitLab Orbit, available in public beta, by connecting code, work items, pipelines, deployments, and production signals into a unified context graph, helping agents respond up to 11x faster with up to 45x fewer hallucinations in internal testing.”

GitLab offers intelligent orchestration to enable teams to orchestrate AI agents across the software lifecycle.

“AI has accelerated individual coding, but teams lose momentum coordinating across planning, testing, security, deployment, and operations. Fragmented toolchains and tool-specific AI agents create bottlenecks that slow software delivery. GitLab's intelligent orchestration helps solve this by enabling teams to orchestrate AI agents to execute tasks autonomously across the software lifecycle while maintaining quality, security, and speed.”

GitLab cites risks from novel AI-specific attack vectors and agentic AI changing security practices.

“Techniques used to obtain unauthorized access or to sabotage systems change frequently, including novel AI-specific attack vectors and vulnerabilities. The use of agentic AI is changing the fundamental ways that we secure and defend our platform and operations as both threat actors and security teams are using AI to industrialize their attacks. Traditional perimeter controls and static security rules are no longer the most effective security mechanisms and we, in alignment with our industry, are reinforcing our defensive capabilities in areas such as, but not limited to, behavioral analysis, automated detection response, and zero-trust. However, we may be unable to fully anticipate these techniques or implement adequate preventative measures. If an actual or perceived security breach occurs, the market perception of our security measures could be harmed, and we could lose sales and customers. If we are, or are perceived to be, not in compliance with data protection, consumer privacy, or other legal or regulatory requirements or operational norms bearing on the collection, processing, storage, or other treatment of data records, including personal data, our reputation and operating performance may suffer. Further, we need to continually monitor and remain compliant with all applicable changes in local, state, national, or international legal or regulatory requirements. Any significant violations of data privacy could result in the loss of business, litigation, and regulatory i”

GitLab notes regulatory, litigation and other risks from its agentic AI features including GitLab Duo Agent Platform.

“Some of our AI-powered features, including those offered through the GitLab Duo Agent Platform, are designed to automate elements of the software development lifecycle based on user-defined goals and context. As the prevalence and scrutiny of such agentic AI systems increases, we may face regulatory, litigation, ethical, reputational, and financial risks.”

GitLab reports traction from its GitLab Duo Agent Platform in the agentic era.

““The agentic era is creating structural tailwinds for GitLab, and Q1 showed it clearly with accelerating platform activity and promising traction from GitLab Duo Agent Platform,” said Bill Staples, GitLab chief executive officer. “GitLab is the only platform that spans the full software lifecycle with one control plane, one data model, and cloud and AI model neutrality. As our largest customers come to us with new needs around security, governance, and orchestration at machine scale, we are evolving GitLab to be the trusted enterprise platform for software creation in the AI era.””

GitLab extended agentic AI with new automated features and broadened access to GitLab Duo Agent Platform.

“• Extended agentic AI across the software lifecycle with new automated security remediation, pipeline configuration, and delivery analytics, and broadened access to GitLab Duo Agent Platform for free tier users, including flat-rate agentic code reviews and spending caps for predictable cost controls.”

GitLab announced collaborations with AWS and Google Cloud for its Duo Agent Platform.

“• Announced collaborations with AWS and Google Cloud to bring agentic DevSecOps to enterprise teams, enabling joint customers to power GitLab Duo Agent Platform with Amazon Bedrock or Vertex AI using the models, governance, and cloud commitments they already have in place.”

GitLab states the agentic era presents its largest company opportunity.

“The agentic era affords GitLab the largest opportunity in our history as a company, and we're making the structural and strategic decisions to meet it.”

GitLab is rewiring internal processes with AI agents and plans to right-size roles.

“4. We're rewiring internal processes with AI agents, automating the reviews, approvals, and handoffs to speed us up, and plan to right-size roles across the company to follow suit.”

GitLab discusses how the agentic era will multiply demand for software.

“2- The agentic era multiplies demand for software. Software has been the force multiplier behind nearly every business transformation of the last two decades. The constraint was the cost and time of producing and managing it. That constraint is collapsing. As the cost of producing software collapses, demand for it will expand. Last year, the developer platform market used to be measured in tens of dollars per user per month, this year it is hundreds/user/month and headed to thousands. Not only is the value of software for builders increasing, but we believe there will be more software and builders than ever, and we will serve an increasing volume of both.”

GitLab notes the agentic era increases importance of engineers as problem solvers.

“3- The consequential work belongs to engineers. Engineering has always been about more than writing code. Great engineers are problem solvers and builders who care about system design, distributed systems, reasoning through failures, safely integrating new capability into critical systems, and making decisions under ambiguity. These are exactly the skills the agentic era needs more of, especially as the volume of software increases. The supply of deep technical problems is multiplying, and the engineers who can solve them will be among the scarcest and most valuable talent in the market. Our core users’ roles are evolving, their importance is only increasing.”

GitLab describes its orchestration service for coordinating agents in the agentic era.

“5- Orchestration across the full lifecycle. A single agent that writes code or opens a merge request produces activity. Enterprises don't need agent activity. They need running software that moves the business forward. Orchestration is the layer that gets you there. It coordinates agents across the lifecycle, assigning work, managing state, passing context, resolving conflicts, enforcing policy, and keeping a human in the loop when it matters. CI/CD is one of the components getting reimagined. The GitLab pipeline was designed to take human-rate commits and ship them safely; in the agentic era our orchestration service becomes the runtime that coordinates agents, validates the work and enforces guardrails, and drives change all the way to production at machine rate.”

GitLab is building governance features into its platform for the agentic era.

“7- Governance built into the core. Governance is what lets enterprises move fast in the agentic era. Like a race car, it doesn't matter how fast you can go if you can't maintain control. As agents take on more of the work, enterprises need a platform that can enforce who's allowed to do what, prove what happened and why, and keep sensitive code and data where it belongs. We're building identity, audit, policy, and deployment flexibility as core platform services that every agent, pipeline, and merge request runs through by default, rather than a separate product layered on top.”

GitLab enables orchestration of AI agents across planning, testing, security, deployment, and operations.

“AI has accelerated individual coding, but teams lose momentum coordinating across planning, testing, security, deployment, and operations. Fragmented toolchains and tool-specific AI agents create bottlenecks that slow software delivery. GitLab's intelligent orchestration helps solve this by enabling teams to orchestrate AI agents to execute tasks autonomously across the software lifecycle while maintaining quality, security, and speed.”

GitLab is an intelligent orchestration platform where teams and AI agents work together seamlessly.

“DevOps combines software development and IT operations to shorten development cycles and enable rapid, continuous software delivery. GitLab pioneered the DevSecOps platform, replacing "do it yourself" with a single platform spanning the entire software development lifecycle. Today, GitLab is an intelligent orchestration platform built on three foundational pillars, where software teams and their AI agents work together seamlessly:”

GitLab enables teams to orchestrate multiple AI agents across the software development lifecycle.

“• Workflows: Teams and AI agents working together. GitLab enables teams to orchestrate multiple AI agents that work in parallel across teams and projects on complex tasks spanning the entire software development lifecycle, with teams defining the rules and guardrails that guide agent behavior.”

GitLab offers Duo Agent Platform to orchestrate AI agents for autonomous tasks across the software lifecycle.

“GitLab Duo Agent Platform enables intelligent orchestration of teams and AI agents across the software lifecycle. With Duo Agent Platform, teams orchestrate AI agents that execute tasks autonomously across planning, development, security, and deployment. This eliminates the need for manual handoffs between software lifecycle stages that slow delivery in fragmented toolchains. Teams maintain control and visibility while AI agents handle repetitive tasks, enabling continuous execution across multiple projects and releases simultaneously. GitLab Duo Agent Platform embodies our three-pillar architecture for intelligent orchestration, combining collaborative workflows between teams and agents, comprehensive lifecycle context, and enterprise governance to transform how organizations deliver software.”

GitLab offers usage-based credits for its Duo Agent Platform AI capabilities.

“Usage-based pricing (GitLab Credits) applies specifically to GitLab Duo Agent Platform capabilities. As AI agent activity varies significantly based on project complexity, team workflows, and automation levels, customers can choose between on-demand credits that align costs directly with consumption, or monthly commitment pools with shared credit allocation across teams. Credits provide transparency into AI costs and enable teams to scale agent usage aligned with business value.”

GitLab expects customer expansion through adoption of its Duo Agent Platform.

“• Drive increased expansion within our existing customer base. As customers realize the benefits of a single platform approach, they often expand their usage by adding users, adopting additional capabilities, or upgrading subscription tiers. We also expect to drive expansion through GitLab Credits as customers scale their adoption of GitLab Duo Agent Platform and AI agent capabilities. As a result, for fiscal year 2026 and fiscal year 2025, our Dollar-Based Net Retention Rate was 118% and 123%, respectively. We intend to continue focusing on customer success”

GitLab announces general availability of Duo Agent Platform for agentic AI.

“• Announced the general availability of GitLab Duo Agent Platform, enabling intelligent orchestration and agentic AI automation across the software lifecycle with an organization’s full context, standards, and guardrails.”

GitLab notes regulatory and other risks from its agentic AI features including GitLab Duo.

“Some of our AI-powered features, including those offered through the GitLab Duo Agent Platform, are designed to automate elements of the software development lifecycle based on user-defined goals and context. As the prevalence and scrutiny of such agentic AI systems increases, we may face regulatory, litigation, ethical, reputational, and financial risks.”

GitLab expanded Duo Agent Platform with AI agents, catalog, and integrations including Claude, OpenAI, Gemini.

“• Expanded GitLab Duo Agent Platform with purpose-built AI agents, launched the AI Catalog for custom agent creation, and delivered integrations with external agents such as Claude Code, OpenAI Codex and Google Gemini.”

GitLab expanded Duo Agent Platform with AI agents, launched AI Catalog, and added external agent integrations.

“• Expanded GitLab Duo Agent Platform with purpose-built AI agents, launched the AI Catalog for custom agent creation, and delivered integrations with external agents such as Claude Code, OpenAI Codex and Google Gemini.”

GitLab notes regulatory, litigation, ethical and financial risks from its AI-powered features and agentic AI systems.

“Some of our AI-powered features, including those offered through the GitLab Duo Agent Platform, are designed to automate elements of the software development lifecycle based on user-defined goals and context. As the prevalence and scrutiny of such agentic AI systems increases, we may face regulatory, litigation, ethical, reputational, and financial risks.”

GitLab announced public beta launch of GitLab Duo Agent Platform integrating multiple AI agents.

“• Announced the public beta launch of GitLab Duo Agent Platform, an extensible AI orchestration platform designed for human-AI collaboration across the software development lifecycle. The platform integrates with Anthropic Claude Code, Cursor, Amazon Q, Google Gemini CLI, and opencode, enabling developers to collaborate with AI agents that autonomously handle complex development tasks using rich project context for more intelligent AI outcomes.”

GitLab jointly developed GitLab Duo with Amazon Q AI solution with AWS.

“to bring together a new, jointly developed artificial intelligence, or AI, solution named GitLab Duo with Amazon Q. This solution combines the power of AWS’ agentic AI capabilities with GitLab’s comprehensive DevSecOps platform. We also benefit from strategic alliance partnerships which resell GitLab to large enterprise customers, and our strong channel partnerships ranging from large global systems integrators to regional digital transformation specialists and volume resellers.”

GitLab announced partnership with AWS to jointly develop GitLab Duo with Amazon Q AI solution.

“• Grow and invest in our partner network. We have been investing in our global partner ecosystem, composed of hyperscalers and cloud providers, including Google Cloud and AWS, technology and independent software vendor partners, global resellers, and system integrators. For example, in the fourth quarter of fiscal year 2025, we announced a promising partnership with AWS to jointly develop a new AI solution called GitLab Duo with Amazon Q, which brings together AWS’ agentic AI capabilities with GitLab’s comprehensive AI-powered DevSecOps platform. We plan to continue investing in building out our partner program to expand our distribution footprint, broaden the awareness of The DevSecOps platform, and more efficiently add new customers. We will also continue to invest in building out our partnerships to deliver transformation services to help our enterprise customers accelerate the deployment of The DevSecOps platform.”