The AI in Action Hackathon offered a compelling opportunity for developers to explore artificial intelligence. Running from May 6 to June 17, 2025, participants developed AI solutions and competed for a $50,000 prize pool. You can find more details about the contest and explore the projects.This hackathon stood out because of a unique collaborative effort, bringing together Google Cloud, MongoDB, and GitLab. The aim was to cultivate an environment for AI development by combining Google Cloud's AI and cloud tools, MongoDB's intelligent data platform for AI, and GitLab's intelligent DevSecOps platform to ship more secure software faster with AI. This partnership allowed developers to integrate these powerful tools, reflecting real-world project dynamics.This initiative sought to propel the developer community's growth, and collaboratively shape the future of DevSecOps. GitLab's specific focus in this hackathon was to inspire the creation of AI-enabled applications leveraging both GitLab and Google Cloud. Submissions were encouraged to include contributions to GitLab's product or develop functional components for the GitLab CI/CD Catalog.Ultimately, the AI in Action Hackathon became a vibrant stage for developer innovation. It ignited fresh ideas and equipped participants with tangible gains, including new skills, impactful projects for their portfolios, and new professional connections.Meet the winners: AI in action with GitLabCongratulations to all participants, and specifically to the contest winners. Here's a highlight of the projects that stood out for their deep GitLab integration.Pipeline Doctor: Proactive health for your CI/CD"As a software engineer, I frequently run into failed GitLab pipelines, often accompanied by cryptic and overwhelming logs. Pinpointing the root cause feels like searching for a needle in a haystack. Debugging becomes even more time-consuming when I have to rely on SREs for support." - the project's authorPipeline Doctor addresses this by using AI for advanced root cause analysis, swiftly diagnosing pipeline anomalies. It analyzes logs and changes to pinpoint errors, and could even explain security issues or predict bottlenecks. This means substantial productivity gains for developers, reclaiming time from troubleshooting to focus on new features. It also makes pipelines more reliable, aligning with goals for 80% faster CI builds and 90% less system maintenance. This project signifies a shift from reactive troubleshooting to proactive health monitoring.A truly impressive step towards more resilient pipelines.Agentic CICD: The future of automated DevSecOps"What if AI agents could handle most of the DevOps workload?”- the project’s authorAgentic CICD is set to profoundly elevate DevSecOps practices by automating code reviews, suggesting intelligent fixes, and optimizing testing and deployment decisions. These agents can evaluate real-time metrics, automate releases, and even initiate rollbacks without immediate human intervention, creating a self-improving feedback loop. This approach also enhances security by proactively identifying risks. The advantages for development teams are tangible: increased productivity, consistently higher software quality, and improved operational efficiency, accelerating development cycles and time-to-market. Agentic CICD cultivates a pipeline capable of self-healing and self-optimization, amplifying developer capabilities by automating routine tasks and providing intelligent insights.This project truly showcases the next generation of intelligent automation.Agent Anansi: Your intelligent companion in GitLab“As someone deeply passionate about DevOps and AI, I was frustrated by the fragmented and reactive nature of traditional CI/CD workflows. While automation is widespread, intelligence is often lacking.“ - the project's authorAgent Anansi, a name evoking the clever and resourceful spider from folklore, appears to be a versatile AI agent designed to enhance various GitLab workflows beyond the confines of CI/CD. GitLab's broader vision for AI agents includes systems that mirror familiar team roles and serve as foundational building blocks for highly customized agents. This intelligent companion is poised to enhance GitLab workflows by automating repetitive tasks like issue categorization, optimizing search functions, and performing intelligent data analysis. Similar to GitLab Duo's Chat Agent, Anansi could process natural language requests for information or debugging assistance. A compelling application could be an "AI mentor" suggesting personalized learning paths. The overall impact on collaboration and efficiency would be substantial, improving developer experience by minimizing manual tasks and reducing context-switching. It would also enhance collaboration by providing instant access to documentation and enabling direct actions through intelligent interaction. Agent Anansi functions as a personalized productivity co-pilot, moving beyond generic tool assistance to a truly personalized experience that increases individual developer efficiency and reduces cognitive load.A fantastic example of AI making daily development work smarter and more intuitive.The power of partnership: Google Cloud, MongoDB, and GitLab fuel innovationThe AI in Action Hackathon underscored the potency of strategic partnerships in driving innovation. Google Cloud served as a foundational pillar, providing its advanced AI tools, machine learning capabilities, and extensive cloud computing resources as the bedrock for all hackathon projects. MongoDB offered the indispensable intelligent data layer, and GitLab provided the DevSecOps platform essential for building, securing, and deploying these sophisticated AI-enabled applications. Participants were granted access to these powerful tools through free trials or credits, reducing the barriers for experimentation.The collaborative synergy among these partners was unmistakable in the multipartner structure of the hackathon. This environment allowed participants to explore a wide array of technologies and integration possibilities, enabling them to create innovative projects that addressed real-world problems.Getting to know GitLab's Duo Agent PlatformGitLab is reimagining software development, charting a future where humans and AI collaborate seamlessly. GitLab Duo Agent Platform allows users to build, customize, and connect AI agents to match their workflow. Developers are empowered to focus on strategic, creative challenges, as AI agents adeptly manage routine tasks such as providing project status updates, bug fixes, and code reviews concurrently.Duo Agent Platform is now in public beta for GitLab Premium and Ultimate customers on GitLab.com and self-managed environments.AI agents on the platform leverage comprehensive context from your GitLab projects, code, and requirements. They can also interoperate with other applications or data sources for expanded context and actionable assistance. The platform delivers extensible, customizable agentic AI: Users can create and customize agents and agentic flows that understand their specific work processes and organizational needs. Custom rules can be defined in natural language, ensuring agents perform precisely as configured. A catalog for custom skills, agents, and flows is also planned for future release.Duo Agent Platform is seamlessly integrated into your workflow, available in your IDE (Integrated Development Environment) or GitLab’s web UI. It currently supports VS Code and the JetBrains family of IDEs, with Visual Studio support planned. This ability to set custom rules for agents, such as specific formatting for code or adherence to language versions, is poised to accelerate reviews and enable swifter deployment of consistent, secure code.To get started, GitLab.com customers need to activate GitLab Duo beta features for their group, while self-managed customers need to enable these features for their GitLab Self-Managed instance. For those who are not yet GitLab customers, a GitLab Ultimate trial, including Duo Agent Platform, is available at no cost.Join the AI revolution: What's next for developersThe AI in Action Hackathon vividly showcased the transformative potential of artificial intelligence when applied to real-world software development challenges. For developers inspired by these breakthroughs, the journey into AI-powered DevSecOps has just started. Users are encouraged to explore and harness the power of GitLab Duo, which is engineered to substantially elevate productivity, enhance operational efficiency, and reduce security risks across the software development lifecycle. GitLab Duo offers a suite of integrated features, including intelligent Code Suggestions, an interactive Chat agent, AI-assisted Root Cause Analysis for CI/CD failures, and clear explanations for security vulnerabilities — all directly accessible within the platform.Beyond utilizing these powerful tools, developers are invited to contribute actively to the vibrant GitLab community. This hackathon is an integral part of GitLab's broader community engagement initiative, which encourages contributions to GitLab's open source community. By contributing, developers can directly shape the platform that millions use to deliver software faster and more securely. As a testament to GitLab's commitment to its community, contributors benefit from the very AI-powered tools, such as GitLab Duo, that they help build. Furthermore, GitLab recognizes and rewards community contributions through various programs, including the monthly Notable Contributor initiative and special recognition for Hackathon winners.The AI in Action Hackathon showcased how a robust trust infrastructure, combined with emerging AI use cases, is forging a path toward a more trustworthy and efficient digital future. GitLab is dedicated to accelerating the monthly delivery of potent new AI features, with a clear strategic trajectory toward becoming a premier agent orchestration platform. GitLab is poised to empower users to craft, tailor, and disseminate complex agent flows, enabling highly automated and intelligent workflows. The landscape of software development is rapidly transforming, becoming progressively autonomous, adaptive, and AI-driven.I can’t wait to see what you will build next with GitLab!