Your model works. Your users do not trust it. They cannot tell what the system is doing, why it produced that answer, or what to do when it gets something wrong.

AI products fail on interface, not on capability. The design problems are specific: showing the reasoning without drowning people in it, handling the wrong answer as a normal state instead of an error, making a chat interface do real work, and giving people a way to correct the system that feels like control rather than repair.

That is the work I do. Recent AI product design includes an SEC compliance platform where legal teams have to be able to defend every output, an ML experiment tracking platform, and an AI-driven consumer fintech product.

Best fit if you have a working model or API and the interface around it is losing people.

Not a fit if you have not built the model yet. Design cannot make an unproven capability feel trustworthy.