Caitlin Kalinowski: belief

Transcript context

…Okay. She's a friend. So she told me that, here's what she said about you, that, "Your brilliance as a leader lies in hiring exceptional teams. I'd be curious about the kinds of people that she finds indispensable in an era where everyone is concerned about their jobs." So talk about what you've learned about just what you look for when you're hiring folks for your team. Yeah. I'm lucky that I've had a lot of time, a lot of reps basically on hiring people. And so I have a strategy of hiring great people. When you're hiring for zero to one and new things or new industries, and that's what we're facing, I think with AI and robots, certainly it's very new, you can't count on having entirely people who've done the exact same thing in past lives because it doesn't exist. The exact same thing doesn't exist. Maybe you've got roboticists who've built a thousand robots, but nobody that I'm aware of has built the type of robot that can move through the world the way I'm interested in, in the millions, because it hasn't been done. So you have to start thinking about how do you build a team that can do something new? And the nice thing is actually in robotics, self-driving cars, autonomous vehicles is a really good place to look because you've got the sensing stack and you've got a lot of the safety trade-offs actually. And it's a lot of the hard engineering, the hardcore engineering. So that's a place that I looked. Obviously, you want some hardcore roboticists who can do robot design from scratch. And these are really people, even though they might have a degree in something, they're really hybrid people. They're generalist people. So one of the key principles I'm looking for is a lot of really strong generalists who can adapt what they've learned in other fields to a new field and people with a lot of experience building. You want some people who have experience building the thing that you're building that's new and some people who have experience scaling other things to [inaudible 01:20:14]. So you need to look at that. And then with young people, this is where it gets really fun, Lenny, is the only AI native people essentially who use AI so natively that it's baked into their engineering process are 20 years old or 21 years old or 28. I mean, it's very hard to find someone who's in their 30s who can be truly fully AI native. And so we need these folks to teach us how to think. And I've had the opportunity to work with a few folks in that age range. They're approaching their problem solving completely differently because they're using AI from the ground up for everything and they're much faster actually and it's really fun to watch. So figuring out how to get these AI natives to teach us, the rest of us, how they think about AI when it's, you know, we are, you and I, I think I can say are digital natives where we grew up, maybe there wasn't internet when we were really young, but we are the generation that had the first internet. We were teenagers. And we are the generation that had the first cell phones really in scale. We're an important generation because we had the first, I remember freshman year at Stanford we had the first databases that you could access and you could share movies on, I think is what we did, and music on or whatever it was, but this was new. e first, I remember freshman year at Stanford we had the first databases that you could access and you could share movies on, I think is what we did, and music on or whatever it was, but this was new. And so we were native in these things and that gave us a lot of oomph in creating new technologies for it. But we have to accept that we're not native in these new technologies and you really want some folks who are hungry and excited and want to learn who do have these skills.…

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