Most AI agents start with someone writing a prompt from scratch. I wanted a better way.

So I built an Agent Creator. I describe the kind of agent I need, and it determines whether I actually need a new one, figures out how that agent should work, creates it, and adds it to the rest of my agent team.

Step-by-step

1. I describe what I need by telling the Agent Creator what I want the new agent to do.
2. It checks what already exists by reviewing my existing agents and skills. If something already does most of the job, it recommends improving or reusing that instead of creating another overlapping agent.
3. If a new skill is needed, it researches the role, including current best practices, common mistakes, useful tools, and what good work looks like in that area.
4. It creates the agent by defining its job, required information, outputs, available tools, and the steps it should follow.
5. It gives the agent the right skills by creating or reusing supporting skills, including examples, reference material, and checks that help it work consistently.
6. It sets clear boundaries so the agent knows what it should handle, what it should not handle, and when another agent should take over.
7. If the new agent belongs in an existing workflow, it adds the agent to the team by updating the handoffs so the other agents know when to use it.
8. Before finishing, it checks the agent’s work by running validation checks to confirm that the new agent follows the standards I’ve set for the whole team.

The result is that I don’t have to manually design every new agent from scratch. I can describe the kind of help I need, and one agent can research the role, create the new specialist, connect it to the rest of the system, and make sure it’s ready to use.

In other words, I built an AI agent that can help grow its own team.