Worked on the laminlabs/lamindb repository to deliver a new API enhancement focused on data integrity in feature management. Developed the FeatureManager.set_values() method using Python, replacing the previous add_values() approach to introduce categorical type validation and prevent dtype mismatches. Updated documentation and usage examples to clarify the new validation semantics and warn about potential risks with the old method. This backend development effort improved the reliability of data management workflows, particularly in production pipelines, by ensuring that categorical feature annotations maintain their intended data types. The work emphasized robust API design and careful attention to data quality throughout the process.