Brian interviews Derek Carr and Mrunal Patel, distinguished engineers at Red Hat, about OpenClaw Enterprise, the new open-source project that brings Red Hat, NVIDIA, and the OpenClaw community together to make persistent AI agents safe and manageable at enterprise scale. The work started with OpenShell, a deny-by-default sandbox the pair helped build with NVIDIA that treats every agent as potential malware. Agents never see credentials (a supervisor egress proxy injects them from outside), kernel features like Landlock restrict what they can touch, and when a blocked agent hits a wall, OpenShell can ask it why it tried, so a human can decide whether to allow the action now or never. Running real agents in that sandbox showed them that not everything should be untrusted. Memory, for example, is an enterprise record. That insight led them to OpenClaw’s own push to decompose agents into trusted and untrusted parts. OpenClaw Enterprise borrows the Hypershift hosted control plane pattern: gateways, memory, and session state live on a control plane cluster, while agent harnesses run in disposable OpenShell sandboxes on a data plane cluster, so a failed sandbox is simply replaced with full context. Enterprises set a permission ceiling; every new agent starts least privileged and grows only up to that limit, and blessed templates for roles like team Q&A, software co-development, and chief of staff make good agent setups repeatable instead of tribal knowledge. The guests also highlight multi-user agents, where colleagues steer the same agent together rather than flooding each other with AI-generated pull requests, and Skipper, the project’s own support agent that preserves the reasoning behind past decisions. The stack is model-agnostic and runs anywhere, including on self-hosted inference such as Dynamo or llm-d. With more than 3,000 pull requests merged since its September launch, the project is targeting a 1.0 release around year-end, with enterprise pilots and production rollouts expected in 2027.
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Derek Carr is a Senior Distinguished Engineer at Red Hat, where he has worked on OpenShift and in the Kubernetes community since 2014. He is a former member of the Kubernetes Steering Committee and has held long-running leadership roles in Kubernetes SIG Node and SIG Architecture. His recent work focuses on how enterprises can run AI agents safely on Kubernetes, including Red Hat’s work with NVIDIA’s OpenShell on kernel-enforced agent sandboxing.
Mrunal Patel is a Distinguished Engineer at Red Hat, where he has worked on Linux containers, Kubernetes, and OpenShift since 2011. He started the CRI-O container runtime, is a maintainer of runc and the OCI runtime specification, and serves as a chair and technical lead of Kubernetes SIG Node. With Derek, he is now applying deep container isolation expertise to secure execution for AI agents on Red Hat AI.
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