The Secure Kernel for
Cognitive Architectures
The universal protocol for identifying autonomous agents and enforcing policy verdicts across any platform.
Built on standard infrastructure
Kernel Capabilities
The core primitives required to run safe, compliant, and scalable cognitive architectures.
Identity-First Compute
Processes cannot execute without identity. Every agent is spawned with a cryptographically verifiable X.509 certificate that asserts its tenant, role, and capabilities before it can consume a single cycle.
Sandboxed Execution
Memory and tool access are strictly isolated. Agents run in secure WASM-style sandboxes where they cannot access memory or resources not explicitly granted by their Capability Set.
Standardized Policy Enforcement
'The Gavel' kernel module intercepts all agent outputs using PVS-1. Policies are defined once in the kernel and enforced globally across all agents, preventing standard bypass techniques.
The Pillars of a True Agent OS
A visual workflow builder is not an operating system. A true Agent OS provides the kernel-level primitives required for enterprise deployment.
Kernel-Level Control
The OS serves as a central brain that orchestrates execution. It decouples the agent's logic from the underlying LLM models and API providers.
Model Agnostic
Switch between OpenAI, Anthropic, or local Llama models without code changes.
Resource Quotas
Limit token usage and API costs per agent process.
Full State Versioning
Unlike simple chat logs, a true OS snapshots the entire state: variables, code versions, prompts, and memory.
Time Travel
Roll back an agent to a previous state to debug a hallucination.
Forking
Branch an agent's memory to test two different instruction sets in parallel.
Human-Interface Layer
Autonomous doesn't mean unmanaged. The OS must provide "sudo" privileges for human supervisors.
HITL Interrupts
Pause execution to request human approval for sensitive actions.
Steerability
Inject new context into a running agent without restarting it.
Frequently Asked Questions
Understanding the Agent OS paradigm and how it differs from traditional approaches.
An Agent Operating System is infrastructure that manages the runtime environment for autonomous AI agents—handling state, permissions, scheduling, and observability the way Linux handles processes for applications. It provides kernel-level primitives that enable agents to persist, react, and scale in production.
Unlike traditional scripts that run top-to-bottom and exit, autonomous agents loop, wait, react, and persist. Without an OS layer, developers must build their own memory managers, permission systems, and schedulers for every agent. This infrastructure debt is the primary bottleneck in scaling AI systems today.
A true Agent OS provides four kernel-level capabilities: State & Memory (managing context and long-term memory), Permissions (sandboxing what agents can access), Scheduling (handling async tasks and keeping agents alive efficiently), and Observability (tracing thought processes to debug issues).
Full state versioning captures an agent's complete state—variables, code versions, prompts, and memory—at any point in time. Time travel debugging lets you roll back an agent to a previous state to understand and fix hallucinations or unexpected behavior. Forking lets you branch an agent's memory to test different approaches in parallel.
A visual workflow builder helps you design agent logic. An Agent OS provides the underlying infrastructure that actually runs, manages, and secures agents in production. It's the difference between a flowchart tool and an actual operating system—one describes what should happen, the other makes it happen reliably.
A model-agnostic Agent OS lets you switch between LLM providers—OpenAI, Anthropic, local Llama models—without changing your agent code. The OS abstracts the model layer, so your agents aren't locked to a single provider and can optimize for cost, latency, or capability as needed.
From Concept to Control Plane
The principles of an Agent OS are the foundation for the next generation of AI infrastructure. We are building AControlLayer, the first enterprise-grade control plane that fully implements this vision.
Stay on the Cutting Edge
Join our mailing list for updates on autonomous infrastructure.