Researchers have used agentic reinforcement learning to train a 4-billion parameter Qwen model specifically for database query optimization. The resulting AI generates query plans that execute 81% faster than those created by PostgreSQL, demonstrating the potential of specialized AI agents to significantly enhance database performance.