During September 2025, Li Ding focused on improving experiment traceability in the NVIDIA-NeMo/Megatron-Bridge repository by addressing a critical issue with WandB configuration logging. Using Python and leveraging skills in configuration management and unit testing, Li replaced the previous YAML-based serialization with direct dictionary conversion to ensure the complete experiment configuration was accurately logged to Weights & Biases. This approach eliminated gaps in telemetry and reduced configuration drift across runs. Li also updated unit tests to validate the new logging path and prevent regressions, resulting in more reliable experiment reproducibility and enhanced maintainability of the configuration logging pipeline.