The fastest way to learn is to run two competing bets | Jay Parikh (EVP CoreAI, Microsoft)

Brett Berson (0:05)

I think you have such an interesting, given your set of experiences, likely have an interesting point of view on building teams and technology through these different points in the last 30 years. If you think about the role as there's the people and direction you're setting, it's like one hat, and there are many hats. But let's say one hat is all the people stuff of running an engineering organization, and you have all the technology strategy pieces, and those two sit next to each other.

I'm really curious when you think about engineering leadership in Internet, mobile, cloud, AI. What does it mean on any part of those S-curves to be leading, managing, setting direction, particularly over the last few years where it feels like it's never been harder to orient in technology?

Jay Parikh (0:54)

It's never as clean in the inside as it looks from the outside.

I always joke about from everybody thinks is like, oh, you built Facebook. I was like, trust me, the first few years, you didn't want to look at a curtain. Right. It was just the brute force that we had there. But again, it comes back to the people. It's like, I don't think of it just as people. I think about all of this is like one system. I think that's where people, technologists, our managers and others get this wrong. I think with me, I've always straddled this kind of, not just, yes, I've done a lot in engineering, but product design, being a CEO, go to market sales. In fact, my first role at Akamai, believe it or not, was to help them out with technical sales because they didn't have anybody else. I was like, I'll do that.

So I was out there trying to help the team close deals for a while, and then they pulled me into doing BizDev to help us build out the network. Then I went back into engineering and product, but I wore multiple hats there in terms of engineer, PM, product marketer, engineering leader, director, VP, etc. So I've always thought about it not just as like, oh, engineering, like to me, ultimately, you've got to get value to your end users. We all play different roles, and Facebook, I had different roles, and especially running and being the head of all of engineering, I had to think differently about the whole system.

Brett Berson (2:22)

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

Jay Parikh (2:27)

Yes. So for me, there's five things maybe that come together. One is you have to build a high performing team. So that is all about how do you recruit the top people, and then thinking about 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, et cetera.

Second, then, is the, in some ways, 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 1,051 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 and the North Star, 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 drum beat of execution. People get lost in this, I think, because 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 me, for a long time, Brett, I really focused on this week-over-week progress.

And you can have big type of products or projects that may take a year or two to actually materialize, but you need to demonstrate week-over-week progress. That is going to be something that is objective quantifiable that you're looking at how you're doing, whether it be doing efficiency work, doing stuff that accrues revenue or grows users, or retention, whatever it might be. But that drum beat has to be just everywhere in the organization where there is this week-over-week, sometimes day-over-day if you are in a really intense period. But that's number three. Number four is, as an organization scales, as you're running a service for longer and longer, you need to have this moment or this thing in your culture that cares about the toil and about the headwinds that are created and knows how to go and collect that stuff and squish it down or get rid of it. Because this stuff, especially now with AI, we're building, we're growing, we're iterating, we're experimenting way faster than we ever have. If you don't go back and have a culture where you are, in some ways, fighting allergic, recognizing that this toil can't just infinitely keep accruing or piling up for you, then that just is going to slow you down and all sorts of things spiral. Then the fifth thing is, being convicted and also being intentional about building a great culture.