Vector databases promise to fix all your AI data issues, until you scale, and your costs soar. This talk shows you how to set up TiDB as a unified database for AI applications that need both regular queries and vector search. You'll learn why combining transactional and vector data in one system reduces complexity and costs, how to design your schema for both semantic search and analytical queries, and proven optimization techniques that maintain high performance as your data grows. You'll see benchmarks comparing TiDB's vector capabilities against specialized databases and understand when a unified approach saves you versus when you need specialized tools. You'll leave ready to build AI applications that scale without needing a team of database experts.