Trust is the hidden interface of every AI product
A practical framework for building AI features people can understand, correct, and confidently depend on.
Jul 29, 2026·9 min read
Accuracy is only the opening bid
A model can be accurate in aggregate and still feel unsafe in use. People need to know what happened, where uncertainty lives, and how to recover when the system is wrong.
Trust is created through the full interaction: clear scope, visible sources, reversible actions, and feedback that produces an observable improvement.
Build the correction loop first
Before optimizing the happy path, design how a person will catch and correct a poor result. This reveals the context your system must retain and gives evaluation a product-shaped target.