Mike Vizard talks with Kyle Sosnowski, VP Engineering, Cloud at Crusoe, about why AI inference workloads require infrastructure choices beyond default hyperscaler deployments. Sosnowski explains how GPU capacity, memory bandwidth, latency, observability and automation are reshaping cloud strategy as AI-native organizations adopt multi-cloud and neo-cloud environments. The conversation also covers agentic infrastructure management, GPU selection, edge inference, cost-effective token economics and why enterprises need purpose-built platforms to scale AI workloads efficiently.