Pierre Lechal focused on maintaining and stabilizing the DeepTrackAI/DeepTrack2 repository, addressing critical issues in test reliability and workflow reproducibility. Over two months, he resolved two bugs by reverting changes that had introduced instability, specifically restoring the original data transformation method in the test suite and reverting a Jupyter notebook rename to preserve compatibility for cell counting workflows. His work emphasized Python, Jupyter, and unit testing, ensuring deterministic test behavior and preventing downstream breakages for researchers. By prioritizing clean, auditable rollbacks and minimizing disruption, Pierre delivered targeted engineering solutions that improved the reliability and maintainability of the DeepTrack2 codebase.