Manage AI agents, tasks, workspaces from one control layer
AgentOS is a human operating layer for OpenClaw, providing a unified control surface to manage AI agents, tasks, and workspaces. Designed for operators who need to run, supervise, and scale AI labor across diverse integration environments, it transforms OpenClaw from a raw runtime into a legible, guided, and human-operable system. The core value proposition is allowing users to operate AI agents like a company, with structured task definitions, contextual memory, approval workflows, policy enforcement, and real-time execution visibility. By consolidating all agent activities, workspace states, and task progress into a single dashboard, AgentOS makes complex multi-agent operations accessible to real people doing real work.
Without AgentOS, OpenClaw agents operate with limited visibility and manual oversight, making it difficult for users to understand what agents are doing, what has changed, or what needs attention. This pain point is critical for operators running multiple agents across different integrations, as errors can go unnoticed and workflows become chaotic. AgentOS solves this by providing runtime visibility, approval gates, and guided workflows, ensuring that every agent action is transparent and controllable. For users who need to maintain human-in-the-loop control over critical decisions, the inability to see and approve actions in real time creates unnecessary risk and operational overhead. AgentOS addresses these issues by making agent operations legible and actionable, thereby reducing the burden of manual monitoring.
The first major feature group includes Guided Onboarding and the Workspace, Agent, and Task Wizards. Guided Onboarding provides a cleaner setup flow on top of OpenClaw, allowing users to go from zero to a working system faster. The wizards enable guided creation of workspaces, agents, and tasks using the full flexibility of OpenClaw underneath, simplifying complex configuration choices. This reduces the time and expertise needed to set up effective agent environments, ensuring that even new operators can achieve first success quickly. For example, a user can rapidly create a workspace tailored for research, define agents with specific roles, and assign tasks with contextual instructions, all without deep technical knowledge of the underlying runtime.
The second major feature group is the Human Control Surface combined with the Approval Layer. The Human Control Surface provides one clear interface for running agents, missions, and operations, designed specifically for human operators. It consolidates all agent activities, workspace states, and task progress into a single view, offering operational clarity. The Approval Layer adds review gates before critical actions are executed, keeping humans in control when it matters most. For instance, before an agent sends a message on Telegram or executes a file modification, the operator can inspect and approve the action. This human-in-the-loop mechanism prevents costly errors and builds trust in automated workflows, especially in high-stakes environments like customer communication or file management.
Publisher
A
admin
Launch Date2026-06-10
Pricingfree
Domain Authority
Ahrefs DR9/100