Agentic AI Foundation Adds Four Projects to Reach 10 in First Year

The Agentic AI Foundation announced four new hosted projects on October 22, 2026: Agent Skills, contributed by Anthropic; Open Responses, contributed by OpenAI; OpenEnv, contributed by Hugging Face; and OpenSandbox, contributed by Alibaba. The additions bring AAIF to 10 hosted projects in its first year, up from three launch projects in December 2025.

The announcement coincides with AGNTCon + MCPCon North America, taking place October 22 and 23, 2026, at the San Jose McEnery Convention Center. The new projects join the Agent2Agent (A2A) protocol, Agent Router, agentgateway, AGENTS.md, goose, and the Model Context Protocol (MCP) as AAIF projects under the foundation’s open, vendor-neutral governance. According to the foundation, the four projects address different layers of the agentic stack: how agents gain new skills, how applications talk to models across providers, how agents are trained and evaluated, and where agents run safely.

“A year ago, AAIF launched with three projects and a bet that agentic AI needed a neutral home to thrive. Today we host 10,” said Manik Surtani, CTO and co-founder of the Agentic AI Foundation. Surtani said four different companies chose to contribute the projects to neutral governance, giving the community one place to build shared standards, protocols, and infrastructure with no single company controlling the outcome.

Agent Skills

Agent Skills is an open format for giving agents new capabilities and domain expertise. Skills package instructions, scripts, and resources in a reusable manner that agents can load on demand. David Soria Parra, co-creator and lead maintainer of MCP at Anthropic, said Anthropic launched Agent Skills a year ago to give developers and enterprises an open standard for making agents more capable, and is donating it to AAIF so that anyone building with skills can shape what comes next.

In a foundation post welcoming the project, AAIF said the specification is open source under Apache 2.0 and CC BY 4.0, that more than 70 agent platforms already support it, and that over 1 million skills have been published with nearly 280 million installations. The post reports that a million skills were listed on the skills.sh registry in seven months, with skills used across software engineering, marketing, design, writing, and research. The foundation said Agent Skills will be guided under AAIF by a Technical Steering Committee with core maintainers drawn from multiple organizations who serve as individuals.

Open Responses

Open Responses is an open specification for building multi-provider, interoperable LLM interfaces, based on the OpenAI Responses API. The foundation said it defines a shared schema, consistent streaming events, and extensible tooling so developers can describe requests and outputs once and run them across model providers with minimal translation. Steve Coffey, a member of technical staff at OpenAI, said the project is joining AAIF to further its mission of helping developers build products on language models through simple, unified interfaces.

A foundation post on the specification describes a common format for the requests and responses exchanged through an API endpoint, covering tool calls and streaming responses. The specification permits extensions, identified by provider-specific names so features from different implementations do not conflict, and because it applies to the API, adopting it does not require changing or retraining a model. The post identifies two existing implementations: Databricks Model Serving exposes an Open Responses endpoint for Claude, Gemini, and Databricks-hosted open models, translating requests into each provider’s native format, and Vercel AI Gateway exposes an OpenResponses API that gives applications a common endpoint for accessing models through its gateway.

OpenEnv

The foundation describes OpenEnv as an open framework and community hub for creating reinforcement learning environments, built around a containerized service that exposes an agent interface, MCP, and the Gym training protocol used by training libraries. Ben Burtenshaw, a machine learning engineer at Hugging Face, said the committee behind OpenEnv is sharing what its members have built and used at Hugging Face, Microsoft, Reflection, Meta-PyTorch, Fleet, Mercor, RadixArk, Modal, Prime Intellect, and more.

A post by the OpenEnv maintainers describes the architecture: a client starts an episode with reset(), submits actions with step(), and can request state(), with results that include an observation, a numeric reward, episode completion status, and metadata. Some environments expose tools through MCP, allowing those tools to be used by external agents as well as during training. The post recounts that Turing built Calendar Gym on OpenEnv, and the team reported roughly 90% task success when tasks named explicit calendar identifiers, compared with roughly 40% when the same tasks used natural-language descriptions.

OpenEnv has a multi-company Technical Committee and a public AAIF proposal seeking a vendor-neutral home for the shared environment specification. According to the maintainers, roadmap priorities include connecting agent harnesses to training systems, validating environments, providing training recipes, and supporting task sampling, curriculum, and evaluation during training, with individual RFCs at different stages of review and implementation rather than a single upcoming release.

OpenSandbox

OpenSandbox is a general-purpose sandbox platform for AI applications, offering multi-language SDKs, unified sandbox APIs, and Docker and Kubernetes runtimes for use cases including coding agents, GUI agents, agent evaluation, AI code execution, and reinforcement learning training. “While OpenSandbox was created at Alibaba, we don’t want its future to be defined by a single company,” said Xiaobin Xu, head of development infrastructure at Alibaba.

A foundation post describing the project states that OpenSandbox is licensed under Apache 2.0 and that its sandbox protocol is a set of OpenAPI specifications with two main parts: a lifecycle API for creating, inspecting, pausing, resuming, renewing, snapshotting, and deleting a sandbox, and an execution API for running commands and code, working with files, keeping sessions open, and collecting resource measurements. An execution daemon named execd runs inside each sandbox and handles that work, and the Docker and Kubernetes runtime backends share the same lifecycle interface, with the Docker backend creating and managing a container directly and the Kubernetes backend creating a workload and its related resources.

Foundation Background

The Linux Foundation announced AAIF’s formation on December 9, 2025, with founding contributions of Anthropic’s Model Context Protocol, Block’s goose, and OpenAI’s AGENTS.md. Platinum members at formation were Amazon Web Services, Anthropic, Block, Bloomberg, Cloudflare, Google, Microsoft, and OpenAI, and the Linux Foundation said at the time that MCP had more than 10,000 published servers and that AGENTS.md had been adopted by more than 60,000 open source projects. AAIF describes itself as the neutral home for open standards, protocols, and infrastructure in agentic AI.