During September 2025, Karl enhanced the Borye/openpi repository by implementing a default idle filter for the DROID dataset training pipeline. He focused on data preprocessing and dataset management, using Python and Markdown to update both the codebase and documentation. The enhancement pre-filters training data by excluding idle timesteps, allowing the machine learning models to concentrate on active robot movements and potentially improving policy performance. Although the work was limited to a single feature and did not involve bug fixes, it demonstrated a targeted approach to improving data quality and laid the foundation for more robust robotics training workflows.