Launching today
AgentOS
Manage AI agents, tasks, workspaces from one control layer
65 followers
Manage AI agents, tasks, workspaces from one control layer
65 followers
Run AI agents like a company. AgentOS helps you coordinate workspaces, agents, tasks, jobs, approvals, and runtime visibility from one local-first control surface built on OpenClaw.
Products used by AgentOS
Explore the tech stack and tools that power AgentOS. See what products AgentOS uses for development, design, marketing, analytics, and more.
AI Agents 1
AI Agents 1
OpenClawThe AI that actually does things
5.0 (68 reviews)
We chose OpenClaw because it feels like a real orchestration kernel for agents, not just another chat UI.
It already provides the lower-level agent runtime, sessions, tools, models, and channels we wanted to build on top of.
AgentOS exists because we believe the next problem is not only running agents, but making them operationally manageable for humans. OpenClaw gives us the orchestration layer, and AgentOS adds the human control surface on top.
LLMs 1
LLMs 1
ChatGPT by OpenAIGet answers. Find inspiration. Be more productive.
4.9 (672 reviews)
We use ChatGPT Plus actively in our OpenClaw agent workflow as a practical way to access strong and cost-efficient models for planning, debugging, reasoning, and iteration.
It helps us build AgentOS faster, while reinforcing the main thesis: models are becoming easier to access, but managing many agents and projects still needs a human control layer.
General 1
General 1
OpenAI Codex CLIFrontier reasoning in the terminal
5.0 (19 reviews)
We chose Codex because it works well with the way we build: clear specs, repo-aware execution, fast iteration, and human review.
We actively use it for AgentOS development: implementation, refactors, cleanup, docs, and launch polish.
It also matches the philosophy behind AgentOS: agents should do real work, but humans still need visibility, control, and approval.