When code becomes abundant trust becomes scarce.
That is the argument GitLab CEO Bill Staples made in his recent essay: AI is collapsing the cost of producing software, and everything around production, including context, verification, governance, and evidence, becomes proportionally more important. Both security and collaboration are key elements to producing trust. AI widens what has to be trusted to include the agents that now write software along with the software that gets written.
That is why GitLab is joining the Open Secure AI Alliance, which brings together organizations to develop and share open technologies, techniques, and tools that help safeguard software and agents in the age of AI. We joined because we believe AI security is strongest when it can be inspected, tested, adapted, and improved by a broad community of defenders.
This is an extension of work GitLab is already doing in the open.
GitLab’s AI Gateway is a standalone service that provides access to AI features across GitLab.com, GitLab Dedicated, and self-managed instances. Its source code is public, and so are the agent workflow configurations running on AI Gateway, including configurations for code creation, code review, secrets false-positive detection, and security review.
These examples reflect an important principle: An AI system is more than the model behind it. Trust depends on the surrounding harness, workflows, controls, context, and evaluation. Open tooling makes it easier for defenders to understand how those pieces work, test them against real risks, and improve them over time.
We also believe enterprises need choice. Organizations should be able to use proprietary and secure open weight models, select the right model for the job, and make decisions about where and how AI systems operate. Model and cloud agnosticism helps preserve that flexibility, while an open ecosystem gives customers more options for building, governing, and securing AI.
Transparency also has to cover the risks. Our documentation on security threats in agentic systems sets out the attack paths that apply to our own agents and the controls that apply in each environment. We treat our agents as privileged actors: Each one runs with an explicit identity, constrained tools and permissions, and actions that can be audited. We share how this works through our documentation for composite identity, sandboxed execution, per-flow tool restrictions, and agent tool governance.
Through our participation in the Open Secure AI Alliance, GitLab has an opportunity to share practical work already underway across our AI and security teams and learn from the broader community. Our goal is not to position open weight and closed models as opposites. It is to help ensure that defenders have the transparency, control, and flexibility they need to build trustworthy AI systems.
AI security should be built in the open. Learn more about the Open Secure AI Alliance.
