Worked on the pytorch/xla repository over a two-month period, focusing on both testing and documentation improvements. Developed targeted Python and Shell-based tests to validate XLA graph execution control flags, integrating these into existing CI/CD pipelines to reduce regression risk and ensure robust validation of PT_XLA_DEBUG_LEVEL interactions. In a subsequent phase, enhanced documentation for tensor synchronization during ahead-of-time tracing, providing detailed guidance on debugging and troubleshooting synchronization issues. Leveraged technical writing and Markdown skills to clarify materialization behavior and align documentation with developer workflows, ultimately supporting more reliable AOT tracing and improving the overall developer experience within the PyTorch/XLA ecosystem.