Trainer: Train AI agents by recording screen demonstrations instead of writing prompts

Trainer doesn't rely on fixed coordinates or pixel positions.

During recording, it builds a semantic understanding of the UI what the element is (button, input, menu), the surrounding context, labels, and the intent behind the action.

If a button moves, the layout changes, or spacing shifts, the agent can still find the right element based on meaning rather than position.

It captures every click, keystroke, and intent as you work, then turns that workflow into a reusable agent that can repeat the process reliably.

Built for automating real-world tasks through demonstration instead of manual configuration, making AI agents practical and accessible for everyday work.