Developed and delivered a parallel task decomposition feature for the google/adk-samples repository, introducing an agent-based design pattern that enables complex announcement workflows to be split into parallel sub-tasks. This approach improved the reliability and speed of multi-channel announcements across email, Slack, and Google Calendar by reducing orchestration complexity and end-to-end latency. The work involved refactoring the existing architecture to support parallel processing, leveraging Python and cloud computing concepts. Collaboration was demonstrated through co-authored commits, emphasizing cross-team development. The feature contributed to more scalable campaign management and enhanced user experience, showcasing skills in AI development and agent-based systems.