Janet Kuo and Yuan Tang discuss the evolution of AI Conformance in Kubernetes. Initially, AI workloads ran on Kubernetes, but vendors implemented infrastructure inconsistently, causing fragmentation worries. Janet proposed the AI Conformance Program to address this, collaborating with Yuan and others. The AI Working Group was formed to establish vendor-neutral AI infrastructure standards and ensure interoperability. This group successfully defined requirements and launched a certification program, moving AI to a first-class Kubernetes use case. AI Conformance's prominence reflects its increasing importance as a mainstream infrastructure concern for platforms. The Working Group achieved its initial goals, leading AI Conformance to become a permanent subproject under SIG Architecture. This move signifies AI's need for ongoing architectural governance within Kubernetes. The subproject aims to keep standards current and vendor-neutral, adapting to AI's rapid evolution. They balance AI's speed with Kubernetes' stability through tiered graduation models and focusing on core infrastructure. There's a strong parallel with DRA development, suggesting a deeper integration into Kubernetes architecture. Interested contributors can join meetings, contribute to proposal reviews, or help with automated testing. The rapid community adoption highlights the industry's demand for unified, vendor-neutral AI standards on Kubernetes.