AI is evolving from human-scale systems to agent-scale operations, transforming into active systems rather than mere records. This shift demands a new foundation for handling complex agentic workflows. To address this, three open-source projects, Agent Substrate, gVisor, and OpenRL, have been donated to the Cloud Native Computing Foundation (CNCF). Agent Substrate, now at version 1.0 and available on GKE, scales isolated agent environments efficiently. It decouples stateful agent sessions from active compute, snapshotting idle agents to storage for rapid restoration. This significantly increases container density by reducing idle compute overhead. GVisor provides essential isolation for untrusted agent code by running a lightweight userspace kernel. This prevents direct interaction with the host Linux kernel, enhancing security. OpenRL simplifies the distribution of post-training and serving for reinforcement learning agents. It enables self-hosted RL post-training loops directly on Kubernetes using plain Python. These projects collectively offer an open stack compatible with any Kubernetes cluster across various clouds and hardware accelerators. Agent Substrate allows millions of sandboxes to run with 10x standard container density. GVisor ensures that untrusted code never compromises the host system's kernel. OpenRL orchestrates efficient reinforcement learning workflows, leveraging Kubernetes for distributed training. The donation to CNCF aims to foster collaborative development and accelerate the adoption of these crucial AI infrastructure components.