The Exchanges

Q So, I mean, maybe building on that, how do you define excellence in engineering leadership?

A Yeah, so for me, there's, like, five things maybe that come together. One is, you know, you, you have to build a high-performing team, so that is all about how do you recruit the top people, you know, and then thinking about, like, the composition of the team, right, because you need to think about, do you want, how many early career folks do you want, how many specialists do you want, how many generalists do you want, how many senior tech lead type of people do you want, senior ICs, etc. Second, then, is The, in some ways, like, setting that strategy, setting that vision, like, where is that North Star going? But it's got to be at the right level, because if it's too high level, then it's too opaque. People don't know what to do with it. If you're, as an engineering leader, dictating, like, all of the 1051 OKRs for the team, then the team doesn't think on its own. So you've got to come with the right level of that abstraction of the strategy division, the North Star, or kind of maybe the Higher level metrics or goals that you have, whether it be revenue or users or whatever it might be. Then thirdly is that in my world, it's really important to have this cadence, this drumbeat of execution. And people get lost in this, I think, because, you know, you're an executive, you delegate this stuff, but you really have to set the tempo of the organization that you want it to. So for m…

AI assessment note: “there's, like, five things maybe that come together. One is... build a high-performing team”

Q And so in the, in the Facebook days, what are like the canonical examples of what was a big bet at the time?

A I mean, it was at every layer of the stack, right? I mean, it was when we were, you know, we didn't build hardware and that was like a big bet to go build hardware. We started In some ways simple with one type of server, and then we took a big bet to get all of the other pieces of a kind of the typical SKUs for storage and database and networking and all of those done in a very, very short period of time. There was other bets in terms of, like, how we handled different storage systems, and those were things that would give us that proverbial, like, 10 X improvement, either in cost or performance or scale. There was other things that we did from a product perspective, working with, you know, the videos team or working with the messaging team, and these were, like, disruptive bets to bring a new product experience, but it required kind of changing a lot of layers of the whole stack, right, together, not independently. And so those were things that, you know, they would take a year maybe or more to, to do that. And some of these then just, you know, these are, became things that we cannot fail at at some point, right? And we had to really, really make sure that those were, there was other places where we, you know, we took multiple bets in the same area and kind of had these run parallel to see which one would be best. Sometimes we ended up blending some of these. Other times ther…

AI assessment note: “we didn't build hardware and that was like a big bet to go build hardware”

Q building products, you know, it was sort of the dawn of the internet. Then you had mobile, cloud, and AI as sort of maybe the, the most important technology changes with many things underneath that. What's sort of interesting about building teams and building technology in the steepest part of the S-curve? What's different about that than maybe when you're asymptoting a little bit or things are, um, more legible?

A I think there's a few things which is, you know, and when I look at, let's say Akamai or, or Facebook, when you're in that growth and or you're kind of in the steep part of the S-curve and you're learning really Quickly, and adapting really quickly, and things are changing really quickly on you. Spending time, because you get really busy doing all the things, right, like building some technology thing, meeting with customers, etc. But that steep part also then requires you, it will expose, and you will see kind of where you have holes from a talent perspective. Whether do you have the, the, the right managers, or do you have the right technical, like, expertise in this layer of the stack, or this thing. So in some ways, being, I would say, kind of proactive about that, so if I look at what happened when I got to, when I got to Facebook was, you know, we were just like, wow, a few hundred engineers when I joined, and the stack was arguably pretty, pretty simple.

AI assessment note: “that steep part also then requires you, it will expose... where you have holes”

Q remove sort of this last chapter of Microsoft and you look back at the, the previous couple of decades. What's like the, the period that comes to mind? And maybe you could tell a little bit about the story of like w what What you figured out, how you evolved, why it sort of was so formative in terms of who you are today as a, as an engineering leader?

A Yeah, I would say, and you know, maybe right up front is Whether it be, um, you know, being maybe just a glutton for punishment or not, I always seem to go running after hard, like, hard problems, right? It's just something where, when it's, I'm sort of addicted to it, or I'm just like, I fall into it, I don't know. So for me, and I talk about this in these S-curves, right? So for me, it's like maximizing my professional Time and being on that steep part of the S curve is what I always think about, right? And when I feel like it's starting to curve or arc, bend over, like, flatten, then I'm always trying to find, like, the next thing, right? Many a times that's been afforded in the same company, and other times it's required to change, right? Because I don't want to waste and spend my time on any part of that flat curve for me. Um, so Maximizing kind of that time spent on the steep part of the S-curve is something that I think about and I, like, I'm really, like, intently focused on, right? So that is, you know, and some of these are like, you know they're, all different chapters in, in, in my career. But to give you a specific example where I think I would say I grew up a lot as a leader was the First, probably four or five years when I was at Akamai, right, because I joined and there was maybe a few dozen people when I joined the company. And, you know, this was a company tha…

AI assessment note: “I grew up a lot as a leader was the First, probably four or five years”

Q probably a few other variables, but like how do you think about driving and maybe a way to sort of frame it as if I'm working on your team 10 years ago at Facebook and I'm working on your team today at Microsoft, are the cultures of those teams surprisingly similar or stratospherically different? And what is then the input driver to that and how much of it is you?

A So I would say The inputs to those things, you captured a bunch of them, right? Because you do have to think about the people that you have, right? It's like hiring, you know, the best people you can, whatever competencies you need, and then also developing people as people are growing their career, maybe they're moving roles, maybe they're out of, you know, fresh out of school, and they're trying to grow as an IC or as a manager, whatever it might be. So those two go hand in hand. It's the development of the org. Number two, I think it comes back to, sure, you can have the strategy, you can have a roadmap, you can have all of that really dialed in, but then it's like the execution of that, right? And it's like the ways of working the execution, the delivery of that. You can start with values, right? You can embody certain values, and lots of companies have, you know, great values, customer obsession, or like move fast, or whatever it might be. Those can not be very deep. Those can be just things that people put on posters on a wall somewhere, but how are those embodied in terms of the behaviors and the, you know, minute by minute, hour by hour, I'd say, interactions between people. So when I talk about culture, it's really that, you know, the connection of people to other people in the organization and how they are really driving that execution, and more importantly, that lear…

AI assessment note: “The inputs to those things, you captured a bunch of them, right?”

Q What's the period in your multi-decade career Where the team you were working with was the fastest you've ever experienced, and what was going on in that moment, or that three months, or six months, or the like, what's the story around it?

A I think there's multiple examples. I think it just depends on the kind of the part of the system that we were, we were building, right? I mean, we have teams now in Core AI and, and, and Microsoft that, you know, that I support, that I work with, that, Are shipping daily, sometimes multiple times a day, and, you know, some of this stuff is, like, newer products, so they don't have lots of tech debt and whatnot, but these are not big teams. These are super small teams, and they are just really quick in terms of, like, understanding kind of where the customer's at, bringing kind of high taste designs, and, you know, with AI now, we can crank out a lot of things, fix a lot of things very quickly, right? So, This is a, these are organizations, these are teams that are moving, I think, super fast for our scale and for our type of customers that we serve. You know, in other places, like, being able to, and, and whether it be at, you know, Facebook or other companies, being able to have these small teams, and, and for me, it's like, it doesn't make sense to me, like, large teams don't make, move fast. It's just, like, not possible to me, right? So, It's all about how do you get, if you have a large team, how do you get this broken down into what, you know, I call, we call the work chart, not the org chart. Just get rid of that nonsense around the org chart. Have this thing and emphasi…

AI assessment note: “I think there's multiple examples. I think it just depends on the kind”