Worked on enhancing the Activation Graph visualization in the harvard-edge/cs249r_book repository, focusing on improving node label clarity and spacing within Module 02. Used Python and data visualization techniques to refine the user interface, making activation flows easier to interpret for debugging and analysis. The approach prioritized code maintainability and developer experience, ensuring that all changes were isolated to the visualization layer without affecting existing APIs. No bugs were addressed during this period, as efforts centered on feature quality and readability. Demonstrated skills in Python programming, UI/UX visualization, and Git-based workflow, contributing a single, well-documented feature commit.