Imagine if software wrote itself. It seems like a distant future, but with ongoing advancements in large language models and GitLab’s unified AI-powered DevSecOps platform, that future is quickly coming into focus. During our GitLab 17 launch event, we announced GitLab Duo Workflow, an autonomous AI agent that will transform how teams build, secure, deploy, and monitor software.
GitLab Duo Workflow moves beyond the current landscape of reactive, prompt-based AI assistants by creating an autonomous team member actively contributing to optimize every aspect of your software development lifecycle. Workflow distinguishes itself by leveraging GitLab’s unified data store, which seamlessly connects all relevant data, projects, repositories, and documentation. This allows Workflow to be an intelligent, always-on agent that constantly monitors your projects, anticipates potential production issues, automatically identifies and resolves vulnerabilities, optimizes your applications for peak performance, and streamlines onboarding by rapidly building customized remote development environments.
AI is transforming how secure software is created, maintained, updated, deployed, and monitored, enabling organizations to ship more software than ever before. GitLab Duo Workflow represents our first bold step towards AI-driven DevSecOps. We aim to empower developers to focus on high-level problem-solving, innovation, and value creation, while GitLab Duo handles repetitive tasks and optimization behind the scenes.
The vision for GitLab Duo Workflow
With GitLab Duo Workflow, we are laser-focused on tackling several key use cases to automate and optimize the software development process from end to end.
1. Development automated
Straight from the IDE, GitLab Duo Workflow helps plan and prioritize tasks tailored to individual projects and defined organizational processes. Using the requirements from a particular work item (whether an epic, issue, or task), Workflow produces an implementation plan that developers can review and refine. Then, Workflow works through the plan, generating or rewriting code to accomplish and meet the defined requirements. Workflow accomplishes this by operating within a GitLab Remote Development workspace, allowing it to safely and securely evaluate, write, and test code changes. This also ensures that Workflow produces code that both meets the requirements as well as passes all CI pipeline tests, including security scans. If the pipeline fails, Workflow automatically addresses issues and troubleshoots as needed, ensuring only high-quality code that meets your organization's standards is created and committed to your projects.
Once ready, Workflow will automatically create a merge request outlining its code changes and go through your merge request approval processes, including engaging with the code reviewer or maintainer. You can even ask Workflow to review your code and have it comment on your merge requests just as a human code reviewer would today. Even better, Workflow will implement those suggestions for you if you'd like it to. And this is only the start.
2. Intelligent continuous improvement
GitLab Duo Workflow will analyze your codebase in real time, suggesting architectural optimizations for enhanced efficiency, performance, and cost savings. Furthermore, it will proactively identify opportunities for code refactoring to improve scalability and address technical debt by suggesting changes to developers or automatically implementing them in a sandbox environment. Additionally, Workflow will dynamically manage cloud resources to prevent overprovisioning and ensure your applications always meet their performance targets.
3. Proactive security and compliance
Security and compliance are top priorities for any organization. GitLab Duo Workflow will automatically ask developers to apply patches, refactor insecure code, and adapt to emerging threats in real time. Moreover, Workflow will continuously assess security risks associated with your applications and production environments and assist you with implementing mitigating controls.
4. Self-optimizing performance
GitLab Duo Workflow will incorporate sophisticated feedback loops for continuous learning and improvement. By analyzing data from monitoring tools, user interactions, and business outcomes, it will continuously refine its view of your codebase to ensure that your application architectures are always aligned with your business needs. As we see with all AI, Workflow will constantly improve, catching and fixing its own mistakes as it learns to be a partner in your organization.
The future of AI is now
GitLab Duo Workflow represents an exciting leap forward, transitioning from AI that requires constant human prompting to AI that drives development workflows and processes, seeking human guidance when needed. With GitLab's unified, AI-driven interface spanning the DevSecOps lifecycle, organizations will be able to create a new generation of AI-powered applications with unparalleled speed, efficiency, and innovation, all while maintaining the highest standards of security and compliance. No tradeoffs.
Stay tuned for more updates and insights as we continue to push the boundaries of what's possible with AI in software development. Together, let's embrace the future of AI-driven DevSecOps and unlock the full potential of your teams and organizations.
If you are curious about AI-driven DevSecOps and want to be part of this journey, including access to the pre-release program, please sign up for our GitLab Duo Workflow waitlist.
