Andrew Moise enhanced post ranking functionality in the LemmyNet/lemmy repository by refactoring the scoring algorithm to use total monthly interactions as the denominator, aligning content ranking with current user activity. He introduced a new SQL aggregation function to efficiently compute monthly interaction metrics and updated the database schema with an interactions_month column to support broader engagement measurement. Working primarily with Rust and SQL, Andrew focused on backend development and database design to enable more accurate, data-driven ranking calculations. This work provided a foundation for monthly engagement analytics and improved the relevance of content discovery, demonstrating thoughtful engineering depth within a short timeframe.