With new agentic AI tools like OpenClaw, Cursor, Claude Code, and Google Antigravity appearing constantly, it’s easy to get caught up asking which one is best. But the tools will keep changing, their capabilities will converge, and their interfaces will improve. The more important question is what you are building underneath.
This is why I find the concept of an "AgentOS," a framing from Nufar Gaspar, so compelling. The idea is to stop building your work around a specific AI tool and instead build a system around reusable, portable layers. This allows you to use almost any agentic tool, as the agent becomes less important than the environment it operates in.
This personal operating system can be broken down into several key layers:
- Identity: Who you are, how you work, and what good output looks like for you.
- Context: The knowledge, documents, and background the system needs.
- Skills: Repeatable instructions for tasks you do often.
- Memory: Lessons and preferences the system should remember over time.
- Connections: Access to the tools, files, and systems needed to get work done.
- Job: A clear task that is worth delegating to an agent.
- Build: Turning that task into a working agent on top of your OS.
- Test & Verify: Checking the agent before you rely on it.
- Playbook: The operating manual for how your agents should work.
- Automations: Tasks that run without you watching every step.
This shift in perspective is especially critical for organizations. Many teams are asking, "Should we use tool A or tool B?" The better question is, "Are we building an infrastructure that allows us to move between tools without rebuilding everything from scratch?" In the agentic era, flexibility isn't a nice-to-have; it's what keeps you from starting over every few weeks.