Episode Transcript
[00:00:00] Speaker A: Foreign.
[00:00:05] Speaker B: Welcome to following the Gong, a podcast for Schreier Scholars, bringing you mentoring on demand from scholar alumni. I'm your host, Sean Goheen, and our guest today, joining us virtually from New York City, is Apple Software Engineering manager Brian rogowski, class of 1997. Brian, welcome to the show.
[00:00:25] Speaker A: Thank you, Sean. Great to be here. Sorry, one correction. I just have to say, not New York City, close to New Jersey. I have to give credit where credit's due, but I'm a Pennsylvania native. Like, I bet a lot of Penn Staters are.
[00:00:38] Speaker B: Absolutely. And you know, here at University park, we always joke about outside Philly, so we'll just say you're outside New York.
[00:00:44] Speaker A: City, then that's totally fine. I get that.
[00:00:50] Speaker B: So, Brian, a key storytelling tip is always to ground your story in a physical place.
So let's do that here by sharing your Penn State origin story. You said you're a Pennsylvania native, so how did you come to be a Penn State student?
[00:01:05] Speaker A: So I come from a long line of Penn Staters. I'm the youngest of three. My older brother and older sister both went there first, so I knew a lot about Penn State. I have cousins, older cousins as well. Just a lot of Penn Staters in our, in our extended family.
So I definitely knew that was on my radar. And I think I was first interested kind of in learning more. And I knew it was an engineering driven school. Very well known for most of his engineering degrees. My brother did engineering. Again, lots of engineering in our family. We thought, hey, like, you know, that's a great school. And I just, for lack of kind of better insight, I just thought, well, let me look at Penn State as a place where I could, if I decide to do engineering, I could do that very well and study, as we'll find out, it didn't quite turn out that way. Which makes it more interesting, maybe.
[00:02:01] Speaker B: Yeah, absolutely.
Ahead of time. You use the phrase quote a winding path to describe your academic journey. So can you talk about how you did settle on your major and find your way to what was then the Scholars Program?
[00:02:15] Speaker A: Yeah. So I did actually apply for the Scholars program as a freshman. Didn't get in, but that's okay. But I knew that there was a second chance as a junior. And like you said, I kind of felt like engineering was a good default for me to start in. So I went for the Engineering honors program also like my older brother. And, you know, I knew that was a well worn path to get into the Scholars program if I, if I continued. But it didn't Seem to fit. I like math, I like science, the engineering.
I took a couple courses that were really challenging and I didn't feel like they were right for me. I felt like I was doing the wrong thing. Engineering mechanics was particularly hard for. For those who might be listening every day for an hour and about two or three hours of homework, I think almost every day too.
And I knew then I either had to love this or. Or I wasn't going to be able to get through just the sheer amount of work.
And they didn't love it. But I looked around, I kind of made it my project, my first few years to try almost everything else. So the winding path was at one point I took back then, I'm sure it doesn't exist anymore, but there was this thing called the blue book.
Yeah. So blue book this stick.
And I went through almost every major college and major major within those colleges looking for what would fit.
Kind of, kind of ended up on a handful. And I just started going to those departments and talking to advisors and saying, hey, like, you know, what's, what's English? Like, what's philosophy? Like, what's environmental science or environmental engineering like? And I would continue to go to an advisor for my engineering path.
And, and long story short, I ended up getting the advice, what would you do if you didn't have to worry about a job or money or anything like that for your future career? What would you do if you could just learn what you wanted to learn? And that set me on a different path of kind of really exploring.
I ended up in that blue book finding an engineering, a master's level engineering class that was called human factors engineering. And I was like, what is this? And also they, the same program, Industrial engineering, studied psychology. Like, why would they study psychology? I had no idea that there was anything to it other than what you kind of imagine the clinical psychology area. So I explored that and then kind of landed in my junior year taking psychology courses in biological psychology and also kind of looking at a science degree and a psychology degree as a way to combine all my interests into one thing.
So that's the dual degree program that I kind of discovered and a minor in that to also look at science, technology and society, which is a really fun minor to take as well.
[00:05:16] Speaker B: That's really cool, being able to find kind of that blend there.
Now, Brian, I want you to put on your kind of your current role of being a hiring manager. So put that on. But then also thinking back to your experience here, your first roles out of Penn State were programmer Roles. So what did you do to leverage your psychology degree and what advice do you have for students who are in social sciences or even other hard sciences that aren't comp sci or ist who are looking to get into tech?
[00:05:51] Speaker A: Yeah, that's a great question. I love it as a hiring manager, but also kind of looking back.
So my, my path to get into it was I did take some comp sci courses. So first as an engineering major I think freshman year and then as part of the science degree program. So I took some envision and I think of one other kind of intermediate level programming and that got me a foundation. But the really stepping point for me was to get into research which I'll talk about later, I'm sure with the psychology department and they happen to need, in addition to doing their research in cognitive psychology, they needed a programmer to help program some camera systems that they had for their research.
So I got involved in that. I could practice the skills that I was learning in class and get some really valuable experience, real programming.
So I would say, you know, there's other things I did too.
Kind of a summer work experience programming in my last year and that was with the industrial engineering program. Again kind of that connection with engineering and it was with a company nearby and say college.
Um, so I would say get practical experience whether it's through your research. I mean if you can do it through your, your research for your, your scholars program, great. If not, try it on your own or try to get involved in technology in some way that fits.
Social psych and psychology for example, or sociology really are great entry points into the world of technology. Even though it may be counterintuitive, but when you think about what's happened in the years since I was in school, all the social networks, all these companies who have vast amounts of data and what they really need are data scientists, social scientists. People understand data and people.
So think of it that way. I think now if I was starting I would probably have even leaned more towards that. Get a foundation in programming, but also in the analysis, statistics, understanding data, understanding how to look at data and, and get information out of it that's valuable.
So yeah, there's lots of pathways that exist now, not just traditional computer science manager hat I don't normally hire for data scientists, but I hire a lot for software engineers. And I typically see really great people coming out of non traditional programs. Yes, I get a lot of the, you know, comp sci undergraduate and master's program candidates, but I often see people come from other kind of stem Majors, and that's a great path. Like I said, social scientists too. I know people who have gone into neuroscience, maybe even a PhD and then come back to computer science because of all the work they did that went into maybe creating neural networks to model their data or other things like that.
So again, I think there's a lot more pathways, especially with the rise of AI and machine learning, than the traditional ones right now.
[00:09:09] Speaker B: So, Brian, is it fair to say that it's important to know the numbers, but also kind of understand what is the real impact of that data and how it actually functions in the real world with people and emotions and all the unquantifiable parts of life?
[00:09:25] Speaker A: I think so, for sure, yeah. The qualitative. And I think there's actually roles in tech right now that are not programming, that are not even data scientists, that are maybe more like what I studied originally, human factors, or like qualitative research where you want to understand how people interact with the technology. Say it's their favorite app on their phone, and you want to understand better how to develop it to make it more interesting or more usable or more engaging. So that's definitely so many more pathways for, for that. And it's, it's less, more.
It's less about the numbers and more about the understanding of that data.
Awesome.
[00:10:14] Speaker B: So you kind of talked about research and we are going to talk about your thesis. But first, first I want to take a bit of a ride down memory lane to some maybe lower tech options that you were engaged with here. If you can talk about your experience with our cycling team.
[00:10:32] Speaker A: Oh, yeah. So that's a special time and a lot of fun.
So the cycling team, as most people probably know, at least when I was there, don't know what it's like now, was considered a club team, but we had riders who were at the top of their sport. I'm sure some of them were going towards the Olympics, definitely racing at the top level. I was not.
I had been mountain biking for several years on my own in high school, but definitely new to road biking.
So I tried both and they were able to get some phys ed credits out of it as well. So I could learn some of the science behind training as a cyclist. Rode with a pack of like, I think at one point, 20 different people in the club on the road and got involved in the first collegiate mountain bike race, which was a lot of fun. I don't know how I placed. I finished. I know for sure I did that.
And I think my strength was always going fast, downhill because plenty of people were better in shape than me going uphill. But I guess mountain biking a lot in the hills of Pennsylvania trained me for going fast and recklessly at some point.
So it was definitely a lot of fun.
I continued it through the whole time I was there, less so as I got further into my work and junior and senior year. But it was a great experience.
Races up and down the east coast, mostly around Penn State.
And I'd have to say of all the races I did, the most dangerous was the road races. Going very fast in a large group of people.
There was one crash in particular that was devastating. So it made me realize how important it is to really know the sport and to work as a team, even though in a lot of ways it's not like typically looked at as a team sport.
[00:12:36] Speaker B: Follow up for that in terms of your career then. Brian.
So a lot of times coding work and programming work can be individual, but you do operate within the broader context of a company or a team within that company.
Were there any lessons that you've drawn from your cycling to your professional roles?
[00:12:56] Speaker A: Yeah, that's a really interesting question. Um, I. I think so, yeah. I think that's a good way to put it is that, you know, technologists, often when you're, especially if you're kind of in software or data science, you're doing a lot of work alone, right? And cycling's like that. You're doing a lot of training, typically alone, you know, sometimes for hours on end or during a week, and you really have to push yourself. I think that's true in a lot of professions, but I think especially we're working with technology, working with screens, sometimes in a quiet room, not interacting with a lot of people. But then you have to kind of come out of that shell and say, hey, how can we work as a team? How can my work contribute to yours? And cycling especially if you look at road cycling, especially at the highest levels, which I never reached, but I heard about, you need to work as a team. There's often people who are pulling for one lead rider in their team. You see that in the Tour de France and top level races like that.
And that's to get that person ahead, but they're all working as a team to get their entire team ahead.
So I think that can definitely be a good analogy for working in technology. Sometimes you have a star player, sometimes you don't. Sometimes it's all just everyone pulling in the right direction, picking up the slack when the other person is maybe falling behind or not able to proceed. Right. And that's as a manager. And I think any kind of senior level role in technology you kind of want to see where's the next. We call them blockers or problems. Where's the next problem that I can solve? And often it's helping my teammate get unblocked, go to the next step that they need to do.
[00:14:39] Speaker B: So, Brian, obviously this is the Honors College podcast and we've referred to it. Let's talk honors thesis.
So first I want to hear what was your honors thesis experience, what you studied, what, what was the outcome? And then most importantly, how did that influence your career?
[00:14:56] Speaker A: Yeah, so I got involved with a psychology.
I was already looking at the psychology department, but I saw an opening. It's kind of a funny story. I think I saw an opening for basically an admin role for a professor David Rosenbaum. And I was like, great, let me just get any experience at all, even if it's just like know, looking up information or whatever.
And it was with cognitive psychology, which is what I was interested in most. So how the brain works. And for him it was a motor control, how you control muscles and joints and all of that.
So it really pivoted quickly when I talked to him and he realized I had programming experience. And going back to what we talked about before, I had enough experience to kind of help with the programming tasks that he wanted to do. So changed the role to what I actually was hoping to do anyways, which was work with programming and get research experience. And then I did that kind of lab work, got lab credit for it towards my psychology major and then also kind of learned enough to turn that into a thesis and did that my senior year in the same lab. So I had already known and the technology, how things worked and helped to develop some of it and knew what the research was about.
In a nutshell, I think this.
Granted, this is back in.
So I started in 93, back 94, 95. Technology was still very basic, but we created a virtual reality experiment. So the setup is a camera system that would track your movements, track the participants movements along a board. And then at the same time we look at a computer screen that had certain targets that they're. That they should reach for with their, with their virtual hand while they couldn't see their actual hand.
And this setup was really good for trying lots of different experiments within the lab.
So my particular thesis was to distort the virtual depiction of what they have and imagine just a stick figure. Right. It's very simple. This is, this is the 90s we weren't like doing full on, you know, VR or anything, but it was a stick figure representing a target and the arm that was being tracked. And there's a lot of research on distorting visual representations of, you know, computer compared to what someone sees. It goes back to using prisms way back, I think 50 years or more, where they would study prism glasses and see how someone could adapt to seeing a distorted visual representation of what they're actually doing. So this is kind of the 1990s equivalent of that.
And to put it into psychological terms, what we're trying to pull out of the data was can people adapt to different types of distortions? So one would imagine like a two by two screen and one would be kind of displacing the target either left or right or up and down, or maybe a combination of both. So spatially displaced from where it actually was on the, on physically on the board. And another was using some trig to displace the joint angle. So if you imagine like there's an angle that you get for your elbow, right, and the angle for this joint and if you kind of increase or decrease virtually that angle, it really feels weird. But you can adapt to it. And using those two kind of different distortions, we could try to pull out whether someone is in their adaptation, is basing it on spatial or joint based adaptation. And that has a lot to do with how we think of our brain kind of representing. And cognitive psychology is a lot about representation within the brain. How do we represent our movements in space.
And this has implications for everything from like sports and kind of understanding how people are learning, you know, difficult movements to therapy for people have some sort of problem with their limbs and have to, you know, go through physical therapy to kind of redevelop that those movements.
So it's really interesting short answer for the, the research we eventually found that, and this is published later, that the adaptation really occurs spatially. But there is deeper things going on with understanding where your joints are and that might have a different way of adapting. There's other senses that you have, but visually the adaptation is spatially oriented. So it's kind of interesting research a little bit in some ways maybe counters to some things that had been done done before, but now, you know, 20 years later, 30 years later is kind of, you know, incorporated into the existing research.
[00:20:28] Speaker B: That's really cool, Brian. And I love that, you know, it was almost 30 years ago and you just recited it like you turned it in last week. So that's really exciting.
Whether the process or the actual outcome.
Is there times that you've drawn on that in your career, whether directly programming or in your management experience?
[00:20:51] Speaker A: Yeah, well, I definitely drew on it to go to graduate school. So I did a few years working in industry actually doing software development back then a lot of web and database development and then going to grad school definitely helped me having that research experience later in my career, I think it was just making me comfortable with that whole kind of cycle developing something new from. I wouldn't say it was new. I was contributing to the code base, let's say of the, of how that worked and then doing new research and working with people, working with statistics afterwards and presenting my idea, both written and kind of, you know, in graduate school I did a lot more talks as well.
So I think that kind of got me comfortable to a level that I wouldn't have had had I skipped all of that.
Definitely. Again, kind of maybe counterintuitive to a lot of people, but software development is a very, it's a very collaborative thing, especially when you get to a large scale company and startups also, very much so, where everyone needs to discuss their ideas, present them, sometimes argue for them. Right. And that's much like a research proposal or a research paper where you say, you know, here's what I want to do or here's what I've done, here's what I think the results are of the interpretation is. And someone say, may say no, that's wrong. Like all this other research shows that that isn't going to be the case. And yet, you know, maybe you did something wrong and you have to defend your methodology and you defend your analysis.
I think that's really true in what I've done throughout my career, especially when there's real like time and money on the line. Right.
I love the research, but I think, I love the fact in industry that things that you do not only have effect on their customers like they should, but also if you don't do them well, you're company, especially a startup, can go downhill quickly. Right. So, so there's definitely that, that element of not only better get it right and you better be able to defend it, but you're better hope that you really are right and that it works out, which is. Is hard.
Yeah.
[00:23:20] Speaker B: So Brian, you mentioned that, you know, you, you graduate from Penn State from the scholars program with honors and you go out, you're working for a couple years and you decide to step out of the workforce and go to graduate school. And a lot of times when Folks do that. It's for an mba. But that wasn't what you did. Can you talk about your mindset and thought process of, like, how, you know, you got the income, then, you know, probably enjoying life, and then you decide to go back to school? What was, what was your mindset there?
[00:23:51] Speaker A: Yeah, yeah. I mean, it was. Things were going well. I was living in Westchester at that point, another great college town, working for a small startup, doing things. I actually was working with a learning startup, online learning, which was really interesting because it kind of aligned with some of the things I was passionate about with learning and cognition and technology.
But I just had this itch to kind of do something more. I guess that's the best way to put it.
[00:24:21] Speaker B: Typical scholar, right?
[00:24:23] Speaker A: Yeah, I guess.
And I had this idea that, oh, I should do what people I admired as an undergraduate in the research lab, they were all doing their PhDs, and I just kind of got an experience of that through them, that I said, oh, I could do this. Maybe I should be doing this. Maybe I should be teaching. Maybe I should be doing research.
So I had this in my head that that's what I was going to do, get my PhD, become a professor of psychology and. And cognitive science was kind of this newer way of looking at it, of combining AI and philosophy and all these different things with psychology.
And so I just said, that's what I'm going to do. I'm going to figure out how the mind works. I'm going to do all these ambitious things.
And. And so it was more from that standpoint. Yeah, I never had any idea of doing more in business that just. I knew that wasn't where my strengths would be.
So I thought I would do the PhD route. And I can tell you more about that if you want, but, yeah, that was definitely in some ways a good move, and in other ways, part of that winding path.
[00:25:37] Speaker B: Well, let's talk about that, Brian, because you go, you start into graduate school, but you are not a PhD. You decide at some point, hey, you know what? I actually want to stick with industry and not academia.
So what was your, you know, the cognitive process here? What was. What was going through your mind as. As you're deciding this and say, hey, you know what? I want to go back and be in on the business side and not the academic side.
[00:26:07] Speaker A: Yeah.
So it was a couple things. I. I love the program, and I love the professors that I was getting to learn from, and the program was a very quantitative program also in the Big Ten Indiana University. So quick plug. But Great program for psychology and especially for cognitive science. At that point, what I had learned, though, I think changed the way I looked at my own interests.
So I realized I was going down a very scientific, very rigorous path, even quantitative path, which is still not the mainstream for psychology. Maybe it's the mainstream for things like neuroscience and that, but the research is very hard.
All research is hard, right? It just, by definition, you're doing something new, but it's hard to make inferences back to this cognitive level.
A lot of research now has gone to the neuroscience level, where you can kind of look at what's firing in the brain and model, you know, things. Neuroscience and artificial intelligence kind of have merged in a lot of ways, but at that point it was.
I was on the level of kind of modeling behavior and learning and all these kind of more abstract things. And I felt it was a very difficult path. That was one. The other is I got exposed more and more to the game of the academic life, which is research and publishing, which is, again, a lot of writing, a lot of presentations.
And I had this itch just to build things.
I was like, I, maybe I was in the wrong program. I was in psychology and cognitive science, dual program. But maybe in hindsight, I should have gone into computer science and cognitive science because I kept saying, like, I'm building again. I was writing software to do experiments, mostly online experiments.
And it's like, I really want to build this thing that, you know, explains the data. I want to build something that is based off of the data that. And at one point I said to a professor, I think I really want to be in a major called cognitive engineering. Do we have that?
Jokingly?
And the answer was, that sounds great. Go do that. But no, it doesn't exist.
Because what I wanted, I realized I wanted to do is build things based on what we knew about how the brain works and how people learn.
And also I was learning about artificial intelligence and realizing, hey, this is where things are going. Like, this is the. Is the future of a lot of the research that had been done with humans is now being applied to how can we make computers smarter?
So that kind of put me in a. In a different direction. But I felt lost. I was, you know, for those people who are either an Undergraduate or, or PhD or Master's program, and you really have to pivot. That's what's called in, in startup tech world, changing drastically your. Your direction. Like, like it's scary and it's okay to be scared. I felt like I was going to have to Leave my, my home, leave my program, have no salary, have no job, start interviewing at who knows where for who knows what companies.
And I felt like I had to start over. So I found a few opportunities that combined AI and I applied to them.
A lot of it was through connections from graduate school, but others I just applied to directly and I landed in one in Pennsylvania in Williamsport, also a Penn State campus town and great startup. I still keep in touch with them, work there for a couple years. And they were looking at how to use technology to create some rule based AI, which is not the mainstream anymore either, but rule based AI for, for industry and a lot of defense contractors need these kinds of things to kind of develop AI training programs. So I got exposed to that and that's kind of where I was like, okay, I can do this now.
I can combine things I had learned, but also start creating things again. And that felt much better and like I was on the right track.
[00:30:33] Speaker B: Awesome.
So Brian, you mentioned that you had been in Westchester, Williamsport, not exactly the places you would necessarily think of for tech roles, but then you did ultimately shift to some major players out in Silicon Valley.
So what was that transition like and what advice would you have for scholars or others who are moving to tech hubs, whether that is the Bay Area, Austin or Pittsburgh even?
[00:31:03] Speaker A: Yeah, there are a lot more, like you mentioned, there are a lot more tech hubs than there were. When I was looking to move out to California was 2007. So definitely with Silicon Valley was still the premier place. I think New York City was like, you know, Silicon Alley.
It was okay. But other hubs around I think were just getting started really at that point.
But yeah, so I, I moved out there for personal reasons initially, but really then I realized, well, I should have been out here, out there a long time ago. Right. I should have made that, that leap. But I think there's definitely, you know, coming from the east coast, it's, it's a big, it's a big shift.
So again, don't, if you're, if you're looking at one of these other major hubs, I guess Pittsburgh's a probably pretty easy shift for, for a lot of people who grew up on the east coast or maybe even grew up in Pittsburgh, and that's great option.
But if you're looking for a major move, say to the West Coast, Colorado, Austin, you know, Seattle, these kind of places, you know that it's, it's again a big shift, but there's a lot of opportunities. I think that's still the case internationally, there are a lot more opportunities too. You know, now there's London, there's cities all over Europe, cities in Asia that are like huge tech hubs.
So really, if you were, you know, if I was giving the advice to someone starting right now, I'd say just go where you want to go and figure it out. And so that's a little bit of what I did back then, why I was kind of staying in Pennsylvania. I had an opportunity to go to Colorado and Boulder and I always think, well, that was the, you know, the path not taken. But I really wanted to be back in Pennsylvania after being in Indiana for, you know, for several years.
So go where you want to go and figure it out. That's one of the benefits of being in the tech industry is that it is so mobile and distributed.
It's great to be in a tech hub, but you don't have to be anymore.
And yes, it is easier to go into certain areas of technology by being in one of those hubs and working face to face, but if you want to live somewhere outside of those hubs, you can still do it and you can work remotely and that's, that's really awesome. One of the few, I think, benefits that came out of the whole experience of COVID is that we really now have, you know, remote working as, as a well established path for, for people to, to do.
[00:33:41] Speaker B: Absolutely.
So Brian, you go out to California and I want to hear about kind of your role with the. There's this intersection of music and tech and we haven't talked about music yet. So you land these roles with company called Federated Media and another one people might have heard of called Beats.
Can you talk about those experiences?
[00:34:04] Speaker A: Yeah, Federated Media. So just touch on that.
There is the original CEO of that company, John Patel, is a, a journalist by trade and very involved in technology. His idea, his thesis, if you will, for the company was to create ways for independent publishers of web content. Like the original idea of the web was that everyone could publish whatever they wanted on their own website.
And it was a very democratic process that we've gotten away from with the rise of, you know, all the companies that control our technology.
Our apps are the Facebook meta of the world, for example, but all of our apps have these kind of siloed experiences, right? For the most part.
But he got back to the idea of, well, what about all the publishers, Podcasters now would be today, but publishers online of their own blogs, their materials, their training, whatever they're doing and being able to support them through a network of technology.
So that was pretty cool thesis. I did that for about two years. I actually got to do some of the big data work that I was increasingly hearing about and getting involved in. So this is again 2010. So things like big data were just kind of really taking off. And by big data I mean there is, you know, the preponderance of data that we have, that's part of it, but, but also processing and analyzing that data using a network of computers rather than a single machine.
And that was a big shift in the technology realm around that time, still is today, but now it's a well established thing that everyone does.
But so it got a lot of exposure to that technology.
And then I, I knew though that the company was kind of going through a lot of shifts. It was still kind of a startup, but it had been around like seven years at that point.
And I think the market was changing.
So I looked around, had a great recruiter reach out to me and said, hey, there's this thing with music and AI and Dr. Dre is involved. And I was like, well, I know who that is.
And it's like, so there's money behind it and there is going to be a lot of publicity at the very least about this thing. It's like, okay, I'll go, you know what, I'll go to the interview. Like, I didn't have any expectations, but I met some great people, very collegiate, very friendly. And it was just down the road in San Francisco where I was currently living.
And yeah, it just fit. I was like, well, this again, it's going to be a lot of data, there's going to be AI, which I want to continue to learn more.
And it's going to be behavior like back to the psychology days. I give a lot of data. A lot of people using this app, a lot of very passionate people who will use a music app will have, there's a lot of opportunities to tailor it to their needs.
And also was going to use technology. Long story short, they eventually gave me an offer to start up a team to do big data engineering, to do all the trade, all the software to do all the data crunching that we need to do. So not exactly AI, but I was going to be AI adjacent, I guess, and work really closely with that team.
So I felt really good about that. And yeah, in a matter of months I had to hire as many people as I could and bring on contractors and ramp up and do as much as we could to get ready for launch, which happened in 2013. If I get my dates correct. And it was, it was both fun and scary and probably the hardest thing I had ever done and probably still have ever done in terms of my career.
It was down to the wire to be ready for, for launch.
But it was, it was a great experience.
[00:38:14] Speaker B: So Brian, you have this training as a programmer, you have the psychology background, but you start leading this team, you talk about hiring, you're doing all the things.
So how did you go about learning the skills that you needed now that you're in a managerial role, establishing a whole, you know, you're in the startup, there's not really a roadmap. So how did you set yourself up to be successful moving from an individual contributor to that team lead?
[00:38:44] Speaker A: Yeah, that is an amazing question to ask and for me to kind of think about because I think a lot of people that I manage now ask those kinds of questions. And when I interview people, they kind of either tell me what their path was or they have similar questions like how can they go from an individual contributor to a manager.
I think number one for me was observing good managers. And I had quite a lot going all the way back to my graduate undergraduate thesis advisors to like I mentioned Dr. Rosenbaum and Dr. Goldstone and my graduate work in the academic setting. It was really great, very, very involved in my work. But in industry, like I mentioned, I had a lot of different startups that I worked with and I got to learn from leaders in those companies and my direct managers and just kind of observing, what did they do? What was a one, did they have a one on one meeting? What was it like? What questions were they asking, what were they, you know, what were they encouraging me to do more of or less of. What was my annual review like?
I learned, try to learn from those good, good mentoring examples and one or two not so good ones as counter examples. Right. That's always, that's always good in research to have counter examples to anything you want to show.
So don't. Do you know what that person did to me? Because that sucked as an individual contributor.
Right. That was a horrible experience. And I have, you know, in some ways fond memories of the bad experience because I'm like, wow, you know, that's. In some ways I learned more from that than all the good experiences because I can bring that up and say, yeah, I'm going to avoid doing what, you know, I'm going to avoid giving someone bad feedback without any sort of justification. I'm going to avoid asking the same questions over and over again just because I Don't understand it like that other person did. You know, I'm going to take notes so that I don't understand something. I'll, I'll do my own, you know, analysis or research to try to try to learn it for next time, you know, And I think that's number one is learning from examples. Number two probably is, yes, it probably does help to read some of those managerial books that out there podcast now.
They're, they're great resources out there.
You know, even short summaries of those things can be useful. Like I subscribe to a couple apps that have summaries of books. I can at least get an inkling of what the overall idea is. Right. And I think that really does help.
And then I think just you're making the transition.
I've done it myself a few times, but also I've mentored people doing the transition from IC to manager. And I would say it really just takes someone who's open to being a listener. Right. And again, technology maybe is counterintuitive. Like you're just working with programming and computers. Like, you don't need to listen, but actually you need to listen even more because our work is, is collaborative. But it's also like if someone goes off the rails on their own for a whole day and then you realize, oh, no, that's the wrong thing. You shouldn't have been doing that. Like, is that their fault or the manager's fault? I, you know, it depends. You want to avoid people doing the wrong thing or wasting their time. Right. And that's just one example. So listening and being involved enough that you can direct their work, but not so involved that you're micromanaging them. Right. Again, something I learned. I hated being micromanaged. I actually like the manager who did less right. In terms of hand holding. And I could just figure it out even if, if I, you know, needed a little bit more time to figure it out myself. So anyways, hopefully that helps to answer the question.
[00:42:52] Speaker B: I think that was a great answer, Brian.
So you're at Beats and then notably a little about 10 years ago or so from when we're recording this, give or take, roughly little company called Apple. You probably have heard of them. As I sit here recording, using a MacBook, not sponsored, they acquired Beats.
So what was that transition? Like you're at this startup, you know, and then suddenly your company's bought out by one of the largest market cap companies in the entire world.
So how do you recommend that scholars or others approach when they're on that Purchased. End of an acquisition process.
[00:43:38] Speaker A: Yeah, buckle in. It's a roller coaster, I guess is a first piece of advice.
The second piece is be clear about what you want out of it.
I think when I was there, the initial excitement around the office was like, hey, this is huge. You know, I think part of it was this huge monetary payout which didn't really surface. Right. So if anyone's going here, you know, going into a startup hoping they're going to get bought and as a regular employee going to make, you know, millions and millions of dollars, I'm sorry, it doesn't usually happen that way. And when it did, it was before the laws change. I think in 2004 when like, you know, Google employees made millions that way, the tax laws and all the other laws have changed to make that a lot harder. Yes, it can happen.
But you know that initial excitement passes, right? And then you have to realize you're going to be offered a new role or this or a similar role at this much larger company.
And you have to ask yourself, does that company align with your values and what you're trying to do and what you want to do in your career? Are they going to hold you back?
For a lot of people I managed at that point, employees, they thought it wasn't the right fit for them and that was fine, you know, and I encouraged them to do what was right for them.
For me, I think it was the opportunity I wanted. I didn't know that I wanted, if that makes sense. Like I was just in startup world, in startup mode for so long, my entire career, that's all I really knew.
Yes, I think I interviewed for one or two big tech companies over the years, but never like really that seriously. Like, oh yeah, I'll go through the process, see what happens, learn from the, probably won't make it.
And I did that earlier on in my career, I think with Google, which I was excited about, but that's a whole nother story.
But then when I got to Apple, I was like, well, Apple doesn't really do big data, like what am I going to do? And I realized, oh wait, it's the best kept secret at the time. At least in the big tech. That yes, they do big data in much the same way as Google or some of the other companies, but they don't make a big deal about it. And that was, you know, a mind shift for me because I never thought in looking at job opportunities that I would end up at Apple. And now I realize, oh, but wait, they do align with my values. Because one of the reasons I went into Beats and not other streaming companies or other companies that, that did similar kind of like consumer apps was that they really were adamant about doing a subscription based app.
And to bring that into context, why that was important to me, a lot of the industry that I had looked at and job opportunities in the Bay Area were advertising based. And advertising based in itself is fine. Right. But when you are gearing your company to optimizing every ad dollar and ad sent, you're no longer providing a service for your customers, you're providing a service for the advertisers. And at least that is my opinion.
You know, it aligns well with Apple and has since the beginning.
Tim Cook has said things like that very adamantly, publicly.
So there's, there's definitely like with Beats Music, they, they, they said that same kind of thing. They were never going to do non subscription based, you know, advertising based music. And then with Apple I was like, okay, so this at least aligns with my values. It aligns with where my career could go in terms of increasing, you know, work as a manager and building a team again.
And it was just going to be a bigger platform. I was like, okay, well if I'm going to be doing this kind of thing, might as well try to reach more people and, and you know, have my work impact hopefully beneficially more people and have a lot more data to play with with a lot, you know, a lot bigger and better machines.
So it ended up working out, but it was definitely a big transition and one that I still look back and realize like how much of a transition it was from startup to, to big, you know, big company.
[00:48:06] Speaker B: So Brian, if you can put on your managerial hat here again, what advice do you have for current scholars and recent grads that are looking to break into a major household name like an Apple or a Google or any of the other ones that we all know from our daily lives.
[00:48:27] Speaker A: Yeah, I think a lot of people I see aspire to it and that's great.
Great for me as a hiring manager. Great for companies like Apple, but great for the industry that people are seeing the value of being in these bigger companies where we can kind of do more.
So I think if that's your goal, I kind of look at it a couple different ways. I think some people come right out of their undergrad or graduate program and say, you know, that's my goal. I want to work for a big tech company.
Great, try to get an internship. I see a lot of people coming out of internships are Doing really well.
It's kind of a win win situation for the company. And the intern, paid interns are norm now and that's good. There are some are interns.
It doesn't have to be at one of the big tech companies, obviously, if you can get that, that's great. But any internship I think is going to be a fantastic thing to have in your experience.
So there's kind of like that early career path trying to get into the big tech companies. I think that, you know, again, like strong fundamentals. Hey, if you can do research that's relevant, great.
You know, as a scholar, I think you're going to have even more connections.
So use those connections, if you have them to kind of, you know, get a referral from someone, you know, from a professor, from someone who's out in industry, if you can.
Personal referrals are always better, of course.
But you know, then there's a later career which is kind of my, my path is if, if you're, if you're not sure you want to work for a big, big company right away because there are downsides to it, but if you're not sure you want to do that, then work for smaller companies or do your own startup nowadays, like just, just work small and work your way up. Because when, you know, again, my bias is still, even after, I guess now I'm about evenly split almost between working for Apple and working for all the startups combined in my career in terms of time. But you know, the startups give you so many opportunities to do so many different things and in some ways you're forced to put as many hats on as you can. Right? Even as a software engineer, even as a traditional role like that.
And you're going to learn a lot of things fast because you're forced to at a big company. One of the downsides is I think you learn your area really well, but you won't necessarily be challenged to learn five different computer languages right off the bat. Like you'll be learning one or two that your team uses. Right. Right off the bat.
So there's, and same with technologies that, you know, whatever technologies you're using, you might be on a iOS team, not, hey, learn every single mobile application and develop this application for it now and have it done tomorrow. You know, like that's, that's a startup experience, right? That's, that's very different.
So it depends what you want to do and how you want to get experience.
And also, you know, do you want your career to kind of progress in a very Kind of, I don't know what the way to say, kind of a very steady way. And you can get that maybe more easily at a big company or if you want to, if you like chaos and winding paths and try different things, startups are definitely going to give you that. Right. And they will, or even medium sized companies will give you that ability to kind of try lots of different things.
Oh, oh, and to answer your question, if you go that startup route, then I think your application for the big tech company later on in your career is even stronger. Right. Because then they can see that you've learned a lot of different things and they can pick and choose what they want to apply to your role at that at the big company.
[00:52:34] Speaker B: Awesome.
So Brian, what other skills besides the internships should scholars work on developing now? Whether it's technical, people oriented or something else, if they want to have a career path that's even remotely similar towards.
[00:52:52] Speaker A: Yours, that's probably the hardest question you've asked me.
So thanks for that.
Yeah, besides internships and besides like you know, doing a research thesis that they learn something that's doesn't have to be valuable but just useful for them for their path.
Besides those two things.
Yeah, I mean if I, if I was putting my, you know, my, myself into the, the role of being an undergraduate again, I would probably have just started like a company right off the bat. Like not in a company or just, just create an app. Like if you want something to happen in the world, create it. It's. There's very little cost and you could probably raise enough to pay for your, you know, online cloud computing resources or whatever you need from friends and family. Like do a, do, you know, go around and ask for a little bit of investment. You can start a company. It's very easy to do that too. And there's all these different resources. Doesn't have to be anything.
LLCs are really cool in the way they work. So you can, you can start a company and just get experience.
That was not the norm of course when I was, that was extremely rare. But I did know a lot of people who were maybe a few years behind that would try a lot of projects on their own just for fun. Maybe they would eventually use it in something they did in a, you know, academic class or whatever. But even you don't want to just, just start doing something and get experience yourself, create a portfolio. I guess again that's maybe the norm in some majors, but in computer science or software or technology, that, that should be the norm now too.
It, I See that in, it's pretty cool. You know, create a website and just share what you're, you're working on, what your interests are.
Go to GitHub or some similar website and share your code with other people. Get involved in an open source project that you're, that you think has value or that you're passionate about.
So there's very, I mean you could also do the social stuff, do the podcasts, you know, you do do a blog.
Writing is still, I think the most underrated thing that anyone can do is develop your writing skill. Now I'm personally biased, but communication is still really important with technology. Like we've been talking about collaboration. So if you can learn to communicate well early on, that's going to help you right off the bat. And I think it's a really important thing if you're eventually want to lead projects or lead teams or even lead your own company.
[00:55:49] Speaker B: That is really good advice, Ryan.
Now I imagine all those things that you just described, a lot of that, your day job, you're behind a computer screen quite a bit.
So what does life look like for you outside of work? How do you find a sense of balance? Balance with your family, with your community, with just not being again behind a computer screen, knowing that that's such a large part of your profession.
[00:56:16] Speaker A: Yeah, that's always been a challenge.
It's easy just to stay here, especially early on in your career. In my career it was easier to just work long hours, mostly because I liked it, but sometimes because I felt I had to to get ahead.
I, I, for me right now, you know, my family, my kids are a big part of what I, what I spend my time, you know, baseball games, soccer game, soccer matches, other various things having to do with that. We mentioned cycling already. I'm still, when I, when I can stay active and in shape, I will go for, you know, two hour bike rides around the area.
There's some great trails and roads around here and yeah, I just try to get outside as much as I can.
But I think what I learned even all the way back to graduate school when I felt kind of lost and I think now even like on a more regular basis is have something that you're passionate about outside of work. It's so important.
It could be exercise. I mean we probably all should be doing that because we have a desk job. We should be balancing it with activity.
That's probably number one, getting up, sleep, of course, like all those basic things. But having something you're passionate about, it could be that sport you Know, like cycling or it could be reading, reading a bunch of books, or doing some outside hobby. Getting involved in your community.
I try to do some of those things all the time or just having that in the back of my mind. So when my mind's distracted and I just write down some ideas that I have, that's like, for me, realizing that there's something else going on in my life and I don't have to just focus on work 100%. Like, that's a. Actually makes my work life better, makes me more able to sit in front of that computer for those eight hours plus, but also makes me feel like there's a, There's a point to, to all of that. Right. That more than just the work itself.
[00:58:35] Speaker B: Work to live, not live to work.
[00:58:37] Speaker A: Right, Exactly.
[00:58:38] Speaker B: Yeah, Brian, I think that was all really solid advice, but I am no expert on any of the things we've talked about today.
So what kind of questions should have I asked? Should I have asked, but didn't, I guess. Or another way you could phrase this is. What questions do you often get from your interns, your direct reports, your mentees, or even your family or friends?
[00:59:06] Speaker A: Let me pick a couple of those from people I mentor. I would say the big question is, you know, how do they kind of progress their, their career?
Maybe again, a startup, maybe that's kind of happens because there's so much growth in a startup. You know, if you start and you're employee number five and then a year later you're, you know, there's, there's 25 more people that joined after you, there's a natural position maybe to manage a team or lead a group or something like that.
Big, big companies, it happens, but in a much more, you know, kind of slow and rigorous way.
So I get a lot, a lot of questions you probably should ask me about that. How, how, how do, how people progress in their careers.
And, and the answer would really briefly would be to continue to do good work, obviously, but do work that you're excited about because excitement actually drives career growth in most cases.
If you're not happy at a big company, you can almost always find another role that may be better for you. Right. So that would be one piece of advice.
Family and friends and other groups. Yeah, I don't know. Like a lot of people in technology, probably I get questions sometimes.
Sometimes I get complaints, and other times I just get blank stares when I talk about anything that I do.
So if you're, if someone's listening and wanting to talk to understand how that will Work with their family and friends. Just be prepared for all of that.
It is not the most public work that you will do. Right. Within your colleagues, they'll understand the code that you wrote and the application that you developed, but your friends and family may not care.
Or they may care, but they may not know how any of it works and may not want to know. You know, they just want to know. Oh, yeah, it magically gets all my data in this app and now I can, you know, track all of my running that I did last week. Right. So they, they don't want to know how it works. That's probably true for a lot of industries, but most, most especially for this technology thing that's kind of now with AI, it's like really even more magic. Right. It's. So be prepared to try to explain the magic that you're doing in very simplified terms, but not simplistic, but simple terms that people can relate to. Right. That they, they can outside of the tech scene.
Yeah, I don't know if that's.
Yeah. What other questions should you have asked me? I don't.
Yeah, there is.
You should ask me if there is. There is a future in computer, in computer programming.
So, Brian, is there a future in.
[01:02:14] Speaker B: Computer programming, especially with AI?
[01:02:17] Speaker A: Yes, I think there is, but I think it will drastically change in my lifetime.
Definitely. If anyone's listening to this as a, as a computer science undergrad, ask your professors, they'll probably tell you if they're honest, that things will drastically change. We don't know exactly how yet, but yeah, I will, I will try to.
You know that my. One of my passions outside of work is writing and some science fiction, so maybe I'll try to figure that out in a fictional form someday. But I do think we are at the beginning of something that is going to change the industry.
Will it mean that there's no more jobs in the future like the one I have? No, we're still going to need people, just like we're still going to need doctors, even though we might have, you know, AI assisted diagnosis.
We're still going to need teachers, even though we might have more AI involved in the classroom for, for, you know, helping people to, to learn and adapt to what they're, what they're doing. It's just going to be different.
I think the nuts and bolts of what I do for programming will be different, hopefully easier. But there's still a human element of deciding what should we do, why should we do it, how should we do it?
I don't think AI is ever going to replace those things again? Who knows? Maybe there'll be, you know, someday where that, that is equally coming from some general AI. But for the foreseeable future, if you ask me, I think the role will change, but the aspirations that we have of what we're doing with technology will be the same.
And it goes back to Steve Jobs and people like him who said there should be a human side to technology. And I strongly believe that the human side is going to be more needed. So if anything, technologists are going to need more of that social science background or that, you know, the, the, the understanding of people than they ever have before.
[01:04:41] Speaker B: You know, as you were talking, Brian, I kind of pictured like the changes in agriculture, especially us being a farm school here at Penn State. You know, there was a time when farmers were out planting things by hand, milking the cows by hand. Now you have machines that milk the cows, but the farmers have to run the machine. So that was kind of the analogy that was running through my head. Is that a fair.
You know, you went from pulling the crops yourself to okay, now you've got your donkey, now you've got the big John Deere combine. Like, you know, is that a fair analogy?
[01:05:16] Speaker A: I think that is one aspect of it, right. That our tools are getting so much better that we will be able to do more.
But that was true even before AI kind of came to the level that we have today. Now I think it's actually going out and saying, hey, let's create that farm and I'll do it for you.
Okay, that's the level that we're at now. I'll just create the farm, I'll order the machinery, I'll create the robot workers for you. I'll churn out the crops for the next umpteen years.
Yeah, if anything goes wrong, I'll check in. It's like, you know, so that's oversight, where someone might come along like, hey, you know, you can't just form, farm the same crops over and over again without something going wrong. Right. We need guardrails. You can't, like you're going to deplete the soil and all these things that maybe isn't obvious will happen at some point. We need, we need oversight. So it, yeah, there's a, there's a, a good analogy there To a lot of industries. The oversight, the human values, the, the why.
Right, that's, that's something that I don't see AI ever even understanding, let alone doing for us.
[01:06:35] Speaker B: Excellent.
So some rapid fire questions here at the End for you, Brian. Chance to brag. What is your biggest success to date?
[01:06:46] Speaker A: Having gone from nothing to the Beats music launch and getting acquired by Apple. And my career. Yeah. Family, of course. My two kids. My family.
[01:07:00] Speaker B: Awesome. On the flip side, what's the biggest transformational learning moment or mistake that you've had in your career and most importantly, what you learned from it.
[01:07:10] Speaker A: Yeah, going through a layoff at a startup in the Bay Area was hard, but I learned that I had to be my own advocate for my career and not to stick around at a, at a company going downhill for too long.
[01:07:28] Speaker B: Very good advice.
Brian, how do you approach mentorship both as a mentor and a mentee, especially being kind of mid career where you're at.
And how do you recommend students approach mentorship where they're at?
[01:07:42] Speaker A: Thank you for saying that. I'm mid career.
Don't know if that's true anymore, but sure, let's go with that.
Mentor, mentee.
So yeah, I mean I approach it as I think I said a little bit before. Listening is kind of number one, you know, but that's maybe obvious. Number two is I think trying to, you know, maybe it's the golden rule. I don't know. Like there, there's definitely like treat others as a mentor that you the way you would want to be treated as a mentee.
You know, there's, there's, there's a lot to be said for that as a manager. I try to practice that. Like I try to remember when I was purely an ic, what things frustrated me and not. And to create environments where that doesn't happen. Right. Or create environments where I could imagine myself doing my best work.
And that I see as my kind of number one goal is to kind of remove roadblocks and create a really good environment for people to do their best work more than anything.
And everything else kind of stems from that. So I think that applies to being a mentor as well.
Maybe it's not quite as hands on as a manager, but definitely a good thing to strive for.
[01:09:09] Speaker B: Excellent.
Brian, are there any professors or friends from your scholar days that you want to give a shout out to right now?
[01:09:19] Speaker A: Yeah, I would definitely like to shout out. I think I already did to Dr. Rosenbaum.
Gosh, there's so many professors. I had engineering.
My Advisor, I mentioned Dr. Patel, she was the one who gave that kind of key advice which set me in a different direction.
And yeah, there's so many people. I graduate school as well and I learned a lot from, you know, fellow students. There's too Many to mention, but there's a few that I've kept in touch with over the years as well. So I would guess there's.
There's a lot to be said for that kind of collaborative learning as well. And Penn State's a great place where you meet so many different people with so many different backgrounds, experiences, you know, different majors, even depending on the class. Right. So there's.
There's just a great environment there to learn from each other.
[01:10:28] Speaker B: Absolutely. Shout out to all the Lions and Hoosiers that impacted you on the two campuses.
[01:10:35] Speaker A: Yes, indeed.
[01:10:37] Speaker B: What is a final piece of advice that you want to leave for scholars? You know, know, think of what this is. The. The Instagram reel that we capture to highlight the episode. Brian, what do you. What do you want people to remember?
[01:10:53] Speaker A: Just remember that no matter what path you take, there is.
There's always a way you'll find what's important to you. I think that's kind of key. And it may not make sense, you know, to kind of paraphrase what, again, Steve Jobs has said in some. Some of his speeches. It may only make sense when you look back, but that's okay.
That's actually kind of what makes life interesting.
[01:11:20] Speaker B: Excellent.
If a scholar wants to reach out to you and keep this conversation going, Brian, what's the best way to do that?
[01:11:29] Speaker A: Reach out on LinkedIn. I'm fairly responsive there.
I really am not on any other social media these days with all the climate of things going on there.
I used to say Twitter, but Twitter doesn't really exist anymore, so I'm off of that platform.
There's my personal website, if you just want to learn more about me as well. And, yeah, just feel free to reach out.
[01:11:59] Speaker B: Great.
And I know you said one of the questions earlier was the hardest question I asked, but I think it's going to be this one. If you were a flavor of Berkey Cranberry ice cream, which would you be? And as a scholar alum, Brian, most importantly, why would you be that flavor?
[01:12:15] Speaker A: Oh, okay.
So Mint Nittany is. So first of all, I love mint chocolate chip ice cream.
I've loved it since I was a undergraduate.
But why? The why is because it reminds me of what. One of the things I used to do as an undergraduate at the main campus is hike up to Mount Nittany and gain that perspective.
I think back then it was a lot of trees, but you could see the stadiums.
You could see a lot of the campus.
So I would say it's cool to get that perspective every once in a while and get out into nature and realize we're part of something bigger.
[01:13:04] Speaker B: That was a very, very deep answer. I really like that, Brian. And that's the one that has. It's mint, but it has Oreos in it, right?
[01:13:13] Speaker A: A mint Nittany. It does, yes. Yeah.
[01:13:17] Speaker B: Great choice. Great choice.
So thank you, Brian, for joining and sharing your insights. I know I learned a lot in our discussion about trying to the intersection of technology and people, and I hope you watching or listening did as well. Before I let you have the last word, for those of you watching or listening, if you're watching the video version, be sure you subscribe, like, leave us a comment, all those good YouTube things. If you're engaging with the audio version, be sure to follow the podcast app, you know, whichever one you're using. Spotify, Apple podcasts, especially here for Brian working at Apple.
And be sure to, you know, leave us a rating with that. Brian, I'll let you close this out with a final word from you.
[01:14:00] Speaker A: Thank you so much for the opportunity. I really appreciate it. And to all the scholars out there, good luck with your work and endeavors and do something interesting.
