# Sentry

NVIDIA released OpenShell, an open-source runtime that places an AI agent's access rights and governance in the infrastructure around it rather than relying on the agent to restrain itself. Long-running autonomous agents download code, request new privileges and touch more infrastructure, so risk compounds as they work. OpenShell uses a gateway, a supervisor running outside the sandbox, the sandbox itself and a policy prover to bound file, network and credential access; in the reference architecture, CoreWeave measured sandbox startup more than 3x faster on Vera than on x86, with a single rack supporting more than 11,000 concurrent agent environments.

NVIDIA released OpenShell, an open-source runtime that places an AI agent's access rights and governance in the infrastructure around it rather than relying on the agent to restrain itself. Long-running autonomous agents download code, request new privileges and touch more infrastructure, so risk compounds as they work. OpenShell uses a gateway, a supervisor running outside the sandbox, the sandbox itself and a policy prover to bound file, network and credential access; in the reference architecture, CoreWeave measured sandbox startup more than 3x faster on Vera than on x86, with a single rack supporting more than 11,000 concurrent agent environments.

NVIDIA announced NVIDIA Sentry at GTC Berlin, a security framework that runs on BlueField-4 DPUs and places monitoring and policy enforcement for AI agents' access to models, tools and data in a separate hardware trust domain beyond host software. Earlier agent security relied on software runtime boundaries, so an agent that escaped its sandbox could alter or disable its own restrictions; Sentry inspects agent-to-model traffic through the DOCA Tower transparent proxy and reads runtime state outside the host with DOCA Argus, containing agents at millisecond scale. The framework is planned for availability early next year, and developers can begin with DOCA Argus, DOCA Flow and other libraries and microservices to experiment with out-of-band observability and infrastructure enforcement.

NVIDIA announced NVIDIA Sentry at GTC Berlin, a security framework that runs on BlueField-4 DPUs and places monitoring and policy enforcement for AI agents' access to models, tools and data in a separate hardware trust domain beyond host software. Earlier agent security relied on software runtime boundaries, so an agent that escaped its sandbox could alter or disable its own restrictions; Sentry inspects agent-to-model traffic through the DOCA Tower transparent proxy and reads runtime state outside the host with DOCA Argus, containing agents at millisecond scale. The framework is planned for availability early next year, and developers can begin with DOCA Argus, DOCA Flow and other libraries and microservices to experiment with out-of-band observability and infrastructure enforcement.

The work introduces Sentry, a failure-management layer running alongside an LLM agent: when it detects a failure it retrieves matching lessons from an external playbook to guide recovery, verifies without access to task rewards whether the agent recovered, and stores a new lesson only if it did, while the full playbook never enters the agent's context; across multiple agentic benchmarks Sentry outperforms the strongest runtime-intervention baseline on every benchmark by 37% on average and the strongest context-evolution baseline by 39% on the two benchmarks where both are evaluated, combining Sentry with context evolution yields further gains, learned lessons transfer to held-out tasks, and controlled experiments show that exposing the full playbook to the agent lowers performance.

The work introduces Sentry, a failure-management layer running alongside an LLM agent: when it detects a failure it retrieves matching lessons from an external playbook to guide recovery, verifies without access to task rewards whether the agent recovered, and stores a new lesson only if it did, while the full playbook never enters the agent's context; across multiple agentic benchmarks Sentry outperforms the strongest runtime-intervention baseline on every benchmark by 37% on average and the strongest context-evolution baseline by 39% on the two benchmarks where both are evaluated, combining Sentry with context evolution yields further gains, learned lessons transfer to held-out tasks, and controlled experiments show that exposing the full playbook to the agent lowers performance.