The new guide from Cockroach Labs, "Built for AI: Scaling IAM, Metadata Management, and Vector Search on One Database," offers a comprehensive look at addressing the challenges of scaling AI infrastructure. As AI moves beyond experimentation into powering customer experiences and business models, robust infrastructure becomes crucial to handle increased traffic, global user bases, and regulatory compliance. The guide discusses the friction caused by siloed systems such as IAM, transactional databases, vector stores, and NoSQL databases and advocates for a unified approach using CockroachDB's distributed SQL platform. It highlights three critical trade-offs in AI infrastructure: balancing scale with consistency in IAM, managing rich metadata queries at scale, and integrating vector search with transactional data without compromising performance. The guide also emphasizes CockroachDB's resilience and performance under real-world conditions, providing insights into how leading AI companies overcome these challenges. By unifying AI and operational workloads, the guide presents best practices for developing scalable, resilient, and compliant AI systems, ultimately enhancing developer efficiency and improving business outcomes.