Most AI projects fail due to overlooked infrastructure requirements, not poor algorithms. Teams need comprehensive foundations for data flow, model serving, monitoring, security, and human oversight. Nine essential building blocks form the foundation of every successful modern AI system: intelligent data pipeline architecture, scalable model training infrastructure, vector databases and embedding management, API gateway and model serving architecture, comprehensive monitoring and observability, security and access control systems, evaluation and testing frameworks, MLOps and deployment pipelines, and human-in-the-loop integration. Specialized platforms like Galileo can accelerate AI system development by providing proven implementations of these essential components.