The Exchanges

Q What was it like building this out in step with Jeff Bezos and Andy Jassy? What were the biggest lessons that you learned from them?

A Well, the first lesson I learned when I got there, never put a PowerPoint presentation in front of anybody. I will, we did not use PowerPoint. And I don't know if you've heard that before, but we did not use PowerPoint inside. Everything was a written document. You had to be prolific at writing. And telling a story. Things were a storytelling inside the company, and I will never forget the first meeting I did with Andy, and I, they, he walked in with some of his leaders, and we were, we were a smaller team, but I had a beautiful PowerPoint. Nobody would even look at it. I was like, I was just mortified, but I never made that mistake again. Um, so I, I had to actually realize they were a company that dove really deep into the details. And you had to be more prepared. I think my brain worked harder when I was there because I had to go relearn things I'd forgotten as a leader running a public sector business. Like, they would ask me very detailed things about contracting and compliance and why. They wanted to know why and understand why I was asking for something and what it would achieve and what would be the risk. And you, you know, your brain, you just really have to Be on top of your game constantly, and I feel like they helped me stay on top of my game, and I learned that What you write down and how you tell that story needs to be crisp. Don't use a bunch of extra words. Tell…

AI assessment note: “Well, the first lesson I learned when I got there, never put a PowerPoint”

Q before the cameras started rolling, but you noticed this, I noticed this, more tech figures are going to DC. They're learning how to dress. It's really nice to see something other than a sweaty t-shirt and to see some suits. So how do you also help these companies and how do you prepare them to come to DC? Do you tell them what to wear, where to go buy Close.

A Well, I, I laugh. I was sharing, Molly and I were talking before, and when I was at Microsoft, I shared with you in the 10 years I was there, which was 2000 to 2010. I never ever wore blue jeans. I mean, I would have been mortified to walk into any customer, the White House or a lawmaker. It was just very formal. And every man wore a tie, a jacket, women mainly, they wore, they wore pants and all, but it was a lot of, it was a lot of suit dresses too. And I just didn't know the difference. It was just how I was taught. And when I first started AWS, I did struggle at AWS. I would have to say, You can't come in flip-flops, and I will re, I remember, uh, the guy who ran our infrastructure, I love him to death, but I go and pick him up at the airport, he's going into the CIA, and he's literally got on blue jeans, like a Hawaiian shirt, and flip-flops, and he has no other clothes.

AI assessment note: “I would have to say, You can't come in flip-flops”

Q Cloud evolved into a multi-cloud environment, so you don't have dependency on one or the other, and you can have your data in multiple places in case there's an outage or something like that. Do you think something similar will Occur in AI? Do you think people will stick to one model in the future, or do you think we'll keep separate uh,, ah, use cases for different things?

A I think we'll keep separate use cases. You can't change human behavior, and human behavior when it comes to buying tech, is they're constantly looking. It's one of the, it's a great thing for the industry, um, the tech industry overall, It's not always great for commercial industry. You see over and over companies that buy too much tech, and what I mean, they want to experiment a lot, and if they, then they kind of say, whoa, I gotta back to optimization. I gotta look at all of the technology services I own, and am I really using them? This is just tech debt. This has been going on for years, and it takes companies a long time to get rid of their tech debt, and also if they've created an application On a platform. And then they're like, well, now I've got to move it. And that becomes very challenging, especially for large enterprises or governments. But in AI, I, yeah, I predict that we are so early in what is being created and how quickly it's being created. I think our, first of all, we're having process, we're having trouble processing just what's happened in the last few years, but it's even going to go faster. So you're going to see more models created. You're going to see more, Solutions created. More adoption, because as humans, we're going to learn as leaders. We're going to really, um, determine what's the best model we use with our employees to teach them how to take …

AI assessment note: “I think we'll keep separate use cases. You can't change human behavior”

Q How do you build the internal team out for that? Are you pulling from public sector? Are you training people? How do you get the type of, and like, what kind of expertise do you look for?

A I found when I built this business, it was very different than my business at Microsoft. In fact, I, I love my team at Microsoft. They were so good. I've been, I've honestly, I, I say, when I look at myself, I think one of the things my superpowers has been building good teams. I just have a, I have, I love people, and I like to make sure those human connections make sense in building out a team, and that there's good synergy and energy, and I also look for people that have a burn in their belly for that industry. I used to say, For every leader that I hired, like my state and local, my education, my intel, I tried to find somebody that loved that industry as much as I love the work I was doing. And I know that kind of sounds silly, but when I saw that in their eyes, in the way they behaved, I knew if they were smart, they were diving deep, and they wanted to deliver results, that they were, you know, that they were, they were, I was moving in the right direction. But at Microsoft, we had very more, I would call it transactional leaders back then. Not in a bad way. They were very good, but we had tools and products that they took, and they put it to work. They sold it into government, and that was their job. So they configured, you know, an enterprise agreement. They configured something specific, and they had to be able to talk about what the tool did, but it was more transact…

AI assessment note: “I also look for people that have a burn in their belly for that industry.”

Q I want to go into all of the sectors that you touched upon within that, because I think there, there is, the government is so large and there's so much nuance to everything that you touch. So when you were at AWS, you worked with financial services, energy, telecom, aerospace, and satellites. What Like, what did you learn between having to communicate with all these different types of groups?

A Well, one of the things I'll share, I have always loved working in public sector, and it is not for the faint heart, because I share with everybody, you know, commercial is just so much easier to interact with because their contracting processes, just the hoops you have to go through, security and compliance, everything you have to pass in order to actually even do the work. But one of the greatest things about public sector is just what you said. I always used to say, well, if I'm tired of defense, I'll go to intel. If I'm tired of intel, I'll go talk to agriculture. If I'm tired of ag, I'll go to HUD or transportation. So it's a diverse group of agencies and customers that you really actually get to learn so much about different industries. And if you're curious and you have agency, you can go in and really understand these industries in a big way. Which also helps a business in their commercial side, because in government, there's so much connection points with how things get built with, with commercial industry, and if you just think about defense in NASA, how a satellite or a spaceship gets built, or a defense weapon, all these things come from commercial. They used to be built, um, what we used to call GOTS, which was government off the shelf or custom built, And now you see more commercially built. And I think we were, I'd like to say that at AWS, we were key for governm…

AI assessment note: “it's a diverse group of agencies and customers that you really actually get to learn”

Q I could continue to talk to you about all these topics for like hours, but we need to talk about the General Catalyst Institute. So why did you and Hamant decide to launch this?

A Well, again, another great leader that I've had the opportunity to work with, um, in my career. Just so blessed, and, and HT is such a great leader. He is a GOAT of investing. I used to say Andy and Jeff were the GOAT in retail and cloud, and now I've got this amazing, uh, leader in investing. And, you know, I got to meet Hamant because I was recruited to be on one of the boards that they started called Commure. And I got to know him there, and he said, oh, you should meet some of the team, and then I met Paul Kwan, who runs our global resilience. I was like, whoa, they're doing public sector and all these industries I love, and Hamant said, you should be an advisor to us. They have this program that they bring former executives on as advisors, so I worked for about 18 months doing advisement and helped do four investments. I brought, um, Some investments to the table, so I kind of learned the investment side, and then Hamant and I talked about, he goes, you know, you should think about coming on here full-time, and I was like, do what, because I don't feel like my superpower is investment. I am not, like I see, I'm a, I'm more of a builder. I like to help companies build, versus like that day-to-day investment is not what kind of gets me out of bed every day. But I love seeing what we invest in and making them successful. And one of the things we talked about was They have a g…

AI assessment note: “most of these companies are in highly regulated industries. And with AI coming on”