Feidias focused on stabilizing and enhancing scalable workload capabilities within the AI-Hypercomputer/xpk repository, balancing risk reduction with feature delivery. He implemented Task-as-a-Service support for DWS clusters, updating workload annotation handling and Kueue configuration to enable dynamic pod resizing. To address deployment stability, he reverted previous TAS integration by rolling back conditional logic and configuration references. Feidias also improved the robustness of the tcpx_decorator by adding a volume mount and introduced comprehensive unit tests for annotations, tolerations, and environment variables. His work leveraged Python, Kubernetes, and CI/CD practices, resulting in safer, faster iteration cycles and improved test coverage across the codebase.