In just six weeks, we took the llm-d open-source project from idea to release, navigating unexpected GitHub organization and repository name changes, as well as registry organization updates—while keeping CI/CD pipelines running without interruption. With 100 contributors restricted to non-cluster-admin permissions in Kubernetes, we implemented a namespace onboarding system and a GPU reservation system to ensure smooth operations. Using Kubernetes' Pipelines as Code and GitHub integration, we automated the entire process from code commit to AI model deployment, scaling across multiple clusters. In this talk, we’ll show how we adapted to these challenges, maintained pipeline continuity, and ensured proper access control across contributors. If you’re looking for strategies to manage non-cluster-admin users, automate complex workflows, and overcome unexpected disruptions in CI/CD, this session will provide actionable insights on how we pulled it all off in just six weeks.