Adopting AI models is easy — scaling them requires shared open standards

This piece discusses how the operational lessons and community-driven standards developed while scaling cloud systems—exemplified by Kubernetes’ approaches to health checks, controlled rollouts, and consistent change management—are applicable to building and operating reliable AI-native applications; it emphasizes that although AI adds complexity, the underlying distributed-systems constraints and solutions remain familiar.