Worked on improving code hygiene and maintainability in both the Intel-tensorflow/tensorflow and openxla/xla repositories by addressing rule-kind naming collisions within critical data-embedding components. Focused on backend development using Python and Bazel, the developer implemented a targeted rename of the rule kind from _gen_source to _memfile_embed_data_gen_source. This change ensured unique and consistent naming conventions across both codebases, preventing future conflicts and simplifying code audits. The approach emphasized cross-repository traceability through explicit commit messages and revision identifiers, supporting long-term maintainability. The work combined build systems expertise with a methodical focus on code clarity and standardized development practices.