Comet Artifacts is a tool designed to help machine learning teams manage and iterate on datasets and models throughout their experimentation pipelines by enabling efficient logging, versioning, and tracking. Using the example of PetCam, an app aiming to identify pets in photos, the article illustrates how Comet Artifacts can be employed to debug performance issues in a classification model by isolating difficult datasets and analyzing model predictions. By tracking artifacts, which are collections of artifact versions, teams can maintain a comprehensive record of experiments, models, and datasets, thereby facilitating reproducibility and data reuse across projects. The tool's ability to incrementally update artifacts and preserve metadata allows for seamless integration within machine learning workflows, enhancing the team's ability to derive insights and improve model accuracy.