Andrew Moise enhanced post ranking functionality for the LemmyNet/lemmy repository by refactoring the scoring algorithm to use total monthly interactions, ensuring rankings reflect current user activity. He introduced a new SQL aggregation function to efficiently compute monthly engagement metrics and updated the database schema with an interactions_month column to support broader analytics. Working primarily with Rust and SQL, Andrew focused on backend development and data-driven design, enabling more relevant content discovery and improved user engagement. His work demonstrated a thoughtful approach to backend refactoring and analytics, laying the groundwork for ongoing improvements in monthly engagement measurement and ranking accuracy.