Designing Data and AI Systems That Hold Up in Production

Designing resilient data and AI systems for production environments requires a comprehensive architectural perspective. The article explores system-wide strategies for building robust agents and scaling AI responsibly. Key focus areas include architectural patterns, agent design principles, and responsible scaling practices to ensure systems maintain performance and reliability in real-world production deployments.