AI features that survive contact with users
The demo is the easy part. What matters is what happens when the model is wrong, and whether the user can tell.
Building an impressive AI demo has become straightforward. Building one that people keep using has not, and the difference is almost entirely in how the feature behaves when it is wrong.
Assume it will be wrong in public
Design the failure case first. Can the user see what the system did? Can they correct it? Does the correction stick, or will it make the same mistake tomorrow?
Put it where the work already happens
A separate chat panel asks people to change their habits. The features that stick tend to sit inside an existing workflow — drafting the reply they were about to write, filling the form they were about to complete.
Show your working
Cite the source when the answer came from a document
Say when confidence is low rather than guessing fluently
Make the edit path as fast as accepting the suggestion
Never present a generated figure as though it were retrieved
Decide what it must never do
Write down the actions the system may not take without a human — sending, paying, deleting, promising. That list is a product decision, not a technical one, and it is much cheaper to make before launch than after.