Why UX Still Matters When AI Builds Software

A product can work correctly and still confuse the people using it. This is why faster building does not replace understanding people. AI means computer systems that can do work like answering questions. These tools can make software, but they still need clear direction. Teams must check more than whether the computer code works.

NN/g explains why UX work still matters in this process. UX means helping people reach their goals when using a product. Some plans for building with AI treat this work as written rules. Those rules can describe what the team already knows about users. But rules alone cannot discover needs that nobody has studied yet.

Teams also need to agree on which problems deserve their attention. The article suggests asking what people want to do and why. A team should understand a problem before choosing a way to solve it. Designers and product owners can then decide what should be built together. Good-looking screens do not show whether this decision was right.

After building, teams need to watch how people actually use the product. The article describes an example where new features attract little use. The software works, but unclear labels leave people confused. Checks for computer problems may not find this kind of difficulty. Watching people give up on tasks can show a different problem.

The answer is to include UX work before and after building. Teams can decide which changes need a designer to review them. They can also test important tasks with people who will use them. Written rules should support this work rather than become its only part. AI makes building faster, but people still need to judge its value.