PostgreSQL is the database of choice for modern application development, and Gary leverages its advanced feature set extensively. Beyond standard relational operations, this includes full-text search with custom dictionaries and ranking, JSONB operations for semi-structured data, and advanced indexing strategies including GIN and GiST indexes.

Performance tuning in PostgreSQL goes beyond basic query optimization. It encompasses connection pooling configuration, vacuum and autovacuum tuning, write-ahead log optimization, and monitoring with tools like pg_stat_statements. Each tuning engagement starts with profiling actual workload patterns rather than applying generic best practices.

PostgreSQL also serves as the backbone for AI-powered applications — storing embeddings alongside relational data using the pgvector extension, managing application state for agent systems, and providing transactional guarantees that ensure data consistency across complex multi-step AI workflows.