During the month, contributed to the pytorch/executorch repository by delivering a client-facing integration that exposed the ET Tokenizer as a Buck Target. This work enabled clients to directly include the ET tokenizer in their applications, streamlining integration and accelerating onboarding for ET-based workflows. The technical approach involved Buck build integration and careful API surface design to ensure the tokenizer was accessible and maintainable for client use. Demonstrated skills in Python and full stack development, with a focus on change management for client-facing features. The result improved client usability, reduced integration effort, and aligned with the broader product roadmap objectives.