Building AI products by starting with customer problems may backfire. The speaker argues that with AI, you should explore what's possible with the technology first, then find the problems it actually solves, based on lessons from Google.
I was very much into like you know, start with customer problems. That's always the starting point. And I guess I may be like reacting a little bit to like parts of my career in other companies where is quite used to happen at Google quite a lot when I was there. Like just people would start with the tech, they start with the technology and like built things that were cool and that they thought were interesting, intellectually interesting and stuff. And like all the failed products resulted out of that. Like no one actually cared. It wasn't solving a real problem. With AI we don't do that necessarily. And I thought to like, okay, wrap my head around is this good or is it bad? And a lot of it is around the idea that like we don't really know what's possible with AI and we're learning all the time, we're getting new models all the time. The thing is moving at breakneck speed. It can help you a lot. When we were building it, we built a different thing first and didn't work and we thought it was gonna be easy. So these days I say to people like we've gotta be open minded. Maybe we start with is this thing possible? And if it's possible then we can map it to a customer problem we know exists for real.