Meta and Hugging Face are launching the OpenEnv Hub, a shared open community platform designed to accelerate the development of agentic AI systems. This initiative builds on the momentum of open-source tools like TRL, TorchForge, and verl, which have already demonstrated how to scale AI across complex compute infrastructures. Now, the focus shifts to the other critical pillar of agentic development: the developer ecosystem and the environments in which agents operate. Agentic environments define everything an AI agent needs to perform a task—tools, APIs, credentials, execution context—while excluding everything else. These environments provide clarity, enhance safety, and enable sandboxed control over agent behavior. They are essential for both training and deploying autonomous agents at scale. The core challenge lies in the fact that while large language models can generate actions, they need secure, well-defined access to tools and systems to execute them. Exposing a model to an unfiltered array of tools is neither practical nor safe. Agentic environments solve this by creating semantically clear, secure sandboxes that limit access to only what’s necessary for a given task. To address this, Meta and Hugging Face are introducing the OpenEnv Hub—a central repository where developers can create, share, and explore OpenEnv-compatible environments. The hub is designed to be a collaborative space for building the infrastructure that will power the next generation of open agents. Starting next week, developers can begin using the OpenEnv 0.1 Specification (RFC), a draft standard being developed with community input. The specification defines a consistent API for environments using standard methods like step(), reset(), and close(). This allows for interoperability across different systems and tools. The OpenEnv Hub is already integrated with key open-source projects, including TRL, SkyRL, and Unsloth, with more integrations in development. The goal is to create a unified post-training stack that supports scalable, safe, and efficient agentic development. The OpenEnv 0.1 spec is now available in the OpenEnv project repository, and the community is invited to contribute ideas, test implementations, and help shape the standard. A comprehensive notebook is also available, guiding users through the full workflow—from setting up an environment to integrating with existing tools—complete with a Google Colab version for easy access. Upcoming events include a live demo at the PyTorch Conference on October 23, and a community meetup focused on environments, reinforcement learning post-training, and agentic development. Developers are encouraged to join the conversation on Discord, explore the OpenEnv Hub on Hugging Face, and start building the environments that will define the future of open agents. Together, the open-source community, Meta, and Hugging Face are laying the foundation for a new era of AI—where agents are not just smart, but safe, controllable, and built on shared, open standards.