The capability frontier of AI products is moving quickly, but users rarely experience model quality directly. They experience the interface that frames the task, the feedback loop, and the trust boundary.
A good interface for intelligence should not be a model hidden behind a text box. It should help people understand context, calibrate expectations, revise direction, and return to human judgment when the system becomes uncertain.
The questions I care about are practical:
- How does the product explain what the model is doing?
- How can users steer instead of starting over?
- How does the system represent uncertainty?
- Where does the division of labor between person and model happen?
The next generation of AI products will feel less like chat boxes and more like collaborative workspaces.