Trainer lets you train AI agents by simply recording a task once — no prompts, no labeled data. It captures every click, keystroke, and intent as you work, then turns that workflow into a reusable agent that can repeat the process reliably. Trainer doesn't rely on fixed coordinates or pixel positions; it builds a semantic understanding of the UI (what the element is, surrounding context, labels, and the intent behind the action) so the agent can still find the right element when buttons move or layouts shift. Works at the level of intent, not rigid steps, so it can adapt when small variations appear in the flow.