I joined Jason Giles on UserTesting’s Insights Unlocked podcast to talk about AI and product design. The trust discussion drew on a story from BuildOps, where our customer base is commercial contractors. From UserTesting’s episode write-up:

When Roger’s team spoke with technicians about ambitious AI capabilities, the initial response was decidedly practical.

“Just give us the basics first,” Roger recalled hearing. “Just make sure the app is reliable and it’s speedy and we can do what we do.”

Only after those needs were addressed did the conversation shift. When the team described an AI experience that could reduce tedious end-of-day typing, technicians saw the value.

That request for reliability was entirely compatible with wanting to get work done faster. Technicians were spending 10–20 minutes on job notes in their trucks after a day of hard, often sweaty physical work. When my team spoke with technicians, a feature idea came out of it:

From that customer research came an AI feature called Visit Summaries. Instead of typing everything, technicians can press a prominent microphone button and talk. AI cleans up the account and incorporates relevant context about the property, equipment, parts used, and so forth.

The sequence matters. The team did not begin with AI and search for somewhere to wedge it in. It began with observing a person experiencing friction and then finding a way AI could help.

When customers ask us to fix the basics, we should treat that as guidance for what to build next, including with AI.