What’s Your Story: Nicole Forsgren

GEHRKE: We’ve talked a little bit beforehand, but you’ve had this amazing career in tech. How did you actually … tell us a bit about how you grew up, and how did you end up in tech?

NICOLE FORSGREN: Yeah, it’s, you know, it’s, kind of, this ridiculous story. I grew up in a little farm town and ended up going to college and thought I would just be there a year or two because …

GEHRKE: Little farm town in?

FORSGREN: In Idaho.

GEHRKE: In Idaho?

FORSGREN: Yeah. So across the street from a potato field. My grandpa was a potato farmer. And where I’m from, girls—a lot of girls—go to college but not usually for very long. You kind of go to school to get married. And so I was majoring in psych and family science.

GEHRKE: So in high school, you didn’t know anything about or you weren’t excited about tech yet or anything?

FORSGREN: I don’t think I knew much about it, right.

GEHRKE: OK.

FORSGREN: So, I mean, we had a computer at home. My dad was a civil engineer. But I had only ever used it to write papers. I knew WordPerfect because back then WordPerfect was, kind of, the thing.

GEHRKE: Yeah, right. So it was a PC?

FORSGREN: It was a PC. It had, you know, reveal codes, which …

GEHRKE: It was DOS, just not Windows yet, right, or was it Windows?

FORSGREN: I think it was DOS back then. Yeah. And that was …

GEHRKE: And so connector interfaces and everything?

FORSGREN: Yeah,we had all the interfaces. And we had a typing class in high school, but that, that was it. And then I went on to college, and a couple of months into my freshman year, my dad, who I was really close with … so I grew up as a tomboy. I was always mountain biking up in the mountains. I was always just, like, dirty and, kind of, just playing around. I was very much a tomboy. Two days after Thanksgiving, he was in a snowmobile accident and in a coma, and suddenly, I sat back and I realized that, you know, all the things that I thought I was going to be able to rely on, like, you know, if I ever needed to fall back on my family or my dad or pay for things, for some reason, like, that was what stood out to me for some reason. You know, I was in college on a volleyball scholarship, and, like, I was paying for things and it was OK. But for some reason, that was what stood out at me—because I was the oldest of four children. The youngest was 11 years younger than me. So I was like, if anything happens, I think I just felt that responsibility, was that I was going to need to have money. And one of the girls on the practice team, I think in just a totally random comment, said that she could make money in her degree.

GEHRKE: Because you hadn’t chosen that as the …

FORSGREN: Yeah, it just, sort of, came … ooh, because when we went to college, it was, I was going to get married and so then I wouldn’t need money, right. Because I didn’t choose a degree for that. I want to say it was within a couple of days of my dad’s accident—so he was still in a coma; he was still hurt—and it was a very side comment she had made. And I remember hearing it, kind of, in the back, and I, kind of, perked up, and I was like, “What do you mean you can make money with your degree?” She said, “Oh, yeah, when I graduate”—with a two-year degree—”I can make $40,000 a year.”

GEHRKE: So she wasn’t at … was she at your university, or she was at a different …?

FORSGREN: So I went to a JC first because we don’t really go to college. And I was like, oh, $40,000. And I remember thinking, well, if I stay in psych and family science, to be able to make that kind of money, I would need to be a high school teacher, which requires a master’s degree. And so I talked to her just a little bit, and I said, “Well, what’s your degree?” She said computer information systems. I said, “Well, do you like it?” She said, “Yeah, it’s really cool. It’s computers.” I said, “Oh, and what can you make again?” She said about $40,000. I was like, “Cool.” And I just remember looking up that degree and going into finding, you know, I just found the counselors in that degree and telling them I wanted to change my major.

GEHRKE: Oh, wow, that’s a huge decision. I mean, first of all, did your father recover?

FORSGREN: So he ended up coming out of his coma within a couple of months, but he was brain damaged for the next few years. And he passed just after I graduated from college.

GEHRKE: I’m sorry to hear that. But then … so you went ahead and changed your major and went into …?

FORSGREN: I changed my major—without ever having a computer class …

GEHRKE: Right.

FORSGREN: … to CIS, which is, now I know, computers and business. That summer, I applied for an internship and got it. [LAUGHS]

GEHRKE: After your freshman year?

FORSGREN: After my freshman year.

GEHRKE: Wow. What kind of internship? Where was it?

FORSGREN: It was in mainframes for computer hospital systems. And so I showed up, and they thought I was full time, which I was not. I just interviewed well apparently. And so they threw me the manual and the documentation.

GEHRKE: What kind of mainframe was it? Do you remember what kind of machine it was?

FORSGREN: Yeah, it was AS/400s, and it was programing RPG and CLI, and it was for …

GEHRKE: Beautiful languages. [LAUGHS]

FORSGREN: They were. I loved it. And it was Siemens, um—SMS MedSeries 4 was the company, later acquired by Siemens. And it was a wonderful team, and I spent the first week reading the documentation and proofreading the documentation [LAUGHS], and then I just, kind of, dove in.

GEHRKE: So proofreading? You mean you discovered a bunch of bugs?

FORSGREN: There were a lot of typos, a couple of bugs, right. Because I just, kind of, had to figure it out as I went.

GEHRKE: Wow. So it’s not like somebody did preparing with you at the beginning? You were just handed the manual, and then you went with it?

FORSGREN: I was just handed the manual, and then I went with it. I had to …

GEHRKE: Wow, it’s an amazing self-starter.

FORSGREN: … figure out one or two things, and then I just dove in, and then I went back that next year and had my first RPG class. [LAUGHS]

GEHRKE: Wow. They were teaching RPG in college?

FORSGREN: Yeah. So this was … my freshman year was ’97-’98, and then my sophomore year was ’98-’99, so it was a JC, and they were, kind of, gearing up one or two classes in anticipation of the Y2K bug.

GEHRKE: Right.

FORSGREN: And so mainframes …

GEHRKE: Oh, I remember that. Yes …

FORSGREN: …and financial and hospital systems …

GEHRKE: Everybody thought the world was ending or at least some people were thinking the world would end.

FORSGREN: They were so worried about it. And so they had brought back one or two mainframe languages to help with the Y2K crisis. And so that summer, I did hospital systems. The next summer, I did, um, it was a company called Assist Cayenta, and it was, like, it was financial systems and ordering systems. That’s how I started my career, in, like, it was a version of mainframes.

GEHRKE: And then did you get that high-paying job afterwards?

FORSGREN: Yeah. So I had a full-time offer, but by then, I decided to go for my four-year degree. Transferred to Utah State, which was within a few hours from home. I still had to, kind of, stay closer to home because the family, and I wanted to, you know, make sure I was close for my dad. But then I did a six-month internship at IBM. I was a software engineer, and then they hired me full time when, again, I was a software engineer, so …

GEHRKE: But you basically finished the two-year college, then went to Utah State. Finished a four-year degree.

FORSGREN: Finished a four-year degree. Again, there I was … they called it business information systems—now it’s management information systems—at Utah State. It was a very technical degree, so I was doing network engineering. I was doing databases. I was doing, you know, C++. All my programing classes were all in the computer science department. When I got hired at IBM, they hired me as a software engineer. I was working on large-scale enterprise storage systems.

GEHRKE: Which language did you program in then?

FORSGREN: There, I was doing some C++. I was doing a little bit of C. I was doing some Java, and I was doing a little bit of their firmware.

GEHRKE: Wow.

FORSGREN: And then I eventually ended up managing some of their systems, so I did some Bash, and then eventually, I even got a hardware patent, so I—it was kind of everything! 

GEHRKE: Wow. So what is the patent about?

FORSGREN: It’s a way to, kind of, further obfuscate for cold boot attacks. This really, kind of, fantastic article came out showing that if you take compressed air and turn the can upside down, you can freeze some of the bits in chips.

GEHRKE: Right.

FORSGREN: And then if you rip the chip out, you can read what’s on the chip.

GEHRKE: Oh, wow.

FORSGREN: Because it freezes all the elect—

GEHRKE: Super interesting.

FORSGREN: … all the electrons on the chip. And we were like, well, this is ridiculous because it’s only frozen for 2 to 5 seconds. But then if you rip it out and you drop it in, like, liquid nitrogen, then you can read it for 2 to 5 minutes.

GEHRKE: Right.

FORSGREN: Like, well, again, this is ridiculous. But if you’ve entered in a password, then it’s stored in plaintext. Well, it’s not ridiculous if you get your way into a lab—and at the time, I was working in a large lab—because you’ve entered in the password for one computer, one of the servers, one of the stored servers, and you’ve destroyed the, you know, you’ve broken the disk for that one server, but the password is going to be the same for every single server in the lab.

GEHRKE: OK.

FORSGREN: And so we realized that this is a serious, you know, problem that’s a threat vector for a lab. And it’s pretty easy to get into labs, right. Like, you can just, you can follow anybody in. And so we wrote a patent that kind of further obfuscates and it hides where passwords are stored through malloc() calls.

GEHRKE: I see, so … I see. So the location of the password was then somewhat obfuscated and not so easy to find.

FORSGREN: Well, so the location of passwords but also additional plaintext strings and other strings are obfuscated through, kind of, throughout the pieces of, like, different areas of chips.

GEHRKE: This was motivated by the hardware but then implemented in software?

FORSGREN: Yeah.

GEHRKE: OK, wow, that’s super interesting.

FORSGREN: So part of hardware and part of software.

GEHRKE: I mean, just imagine this career, right, in … I guess in high school you’re playing volleyball?

FORSGREN: In high school and college, I was playing volleyball. Ended up getting hurt, so I didn’t play volleyball longer.

GEHRKE: OK. But then switched to, you know …

FORSGREN: Switched to tech.

GEHRKE: MIS, and …

FORSGREN: Yeah, switched to MIS.

GEHRKE: Patent.

FORSGREN: Patent—and shoutout to, you know, my coauthors on the patent, Ben Donie, Andreas Koster. They were great because we all just, kind of, ended up brainstorming one day. And it was this, kind of, windy path, but it was, I think, it was interesting because at the time, you know, I originally went into tech because I thought I would really need money but ended up falling in love with it, right. I’ve had a lot of fun along the way.

GEHRKE: So what did you fall in love with with tech? What really gets you going on tech?

FORSGREN: I love the fact that there are hard, interesting problems that you can solve lots of different ways. And if I can’t solve it initially and if I can’t solve it the first time, I can just kind of spin it around or pivot it in different ways and then just solve it again.

GEHRKE: So it’s this notion that you have this not only hard problems—because in math, you have lots of hard problems, as well—but here there’s the experimentation with it and the trial and error or …?

FORSGREN: The experimentation and the fact that it’s applied and the fact that I can build something and watch it work. Math I liked. And math, up to a point, I was pretty good at math, and I could kind of see how the equations were supposed to work. Computers and programs helped because I could really see how it was working.

GEHRKE: Yeah, I think that, I mean, I can so much relate to this because that’s how I fell in love with computing, because you have this machine here and it basically can do everything, right. And I mean, we will get later to AI. What we see with the current AI systems, right, you can see that, you know, it can be nearly intelligent or it is intelligent, right. And so it’s just amazing to have that kind of machine below you or with you to help you and to be able to train it and program it. And so, you were at IBM …

FORSGREN: So I was at IBM.

GEHRKE: … and now you’re at MSR (Microsoft Research).

FORSGREN: And now I’m at MSR.

GEHRKE: So what’s the bridge in between?

FORSGREN: Oh, so also, kind of, a windy path, but it’s interesting because as I look back, I guess it makes sense to me. So then I had an opportunity to go get a PhD, and I actually started doing, kind of, large data, like, NL, you know, natural language. You know, how do we want to think about, you know, analyzing sentiment analysis, analyzing, you know, those types of, you know, big questions like when are people lying, when are people not lying, machine learning problems. But I was also working at IBM at the time. Because I, like, continued to like, you know, working on systems and working on large problems. So I was doing both at the same time, and I ended up doing usability study … completely randomly. And …

GEHRKE: What was the study on? What did you study?

FORSGREN: So we did a usability study for sysadmins. And it was interesting because at the time, IBM was trying to build, like, a GUI for large-scale sysadmins. And so Todd Eischeid and I did the usability study. We wrote up the findings for IBM; we shared them. And, you know, we found that in some cases, they would use this frontend user interface and it was fine. And in some cases, they were like, “I don’t know,” right, “like I could click this button, but it really makes me nervous.” And we’re like, “It’s OK. It’s a sandbox. This is fake. You can click the button. I’m curious to see what the next step is.” And they were like, “It’s just so risky.” And it struck me as being, sort of, interesting because, like, there were just cases where risk and complexity really interfered with our ability to trust a system or to trust a GUI. And so we wrote this up and we shared it, and IBM was like, eh, you know, we used user-centered guidelines; we used, you know, user-centered design guidelines. We were like, but the same guidelines can’t work for complex systems and complex distributed systems that can work for laptops. And …

GEHRKE: Because in one way, I affect this one machine here, but in the other way, I affect this row of machines, and I know how many this actually is.

FORSGREN: Right. And they really wanted to see the command line interface and the backend data, and they really wanted to verify. And so you really had this difference between not just risk and complexity but also expertise. You know, there were some cases where you could hide complexity and other cases where it just wasn’t appropriate, right. And, you know, simultaneously, I’m working on these really, really large projects with IBM, and people are just, kind of, burning out. And I thought, you know, there has to be something to this, right. And there were kind of rumors as I was going to tech conferences still of, you know, this new-fangled way to make software and, kind of, reduce burden. And so I just pivoted. I changed my research project to start studying what now we know of as DevOps.

GEHRKE: Maybe we will get to this in a little bit, but I’m so impressed by, you know, you go to college, do A. Something happens. You do B, and don’t look back. Same thing here, right? You’re a successful developer at IBM. You have this event which says, wow, I should study this intensively, and you go and get a PhD, right. I mean, it’s just super impressive. How do you do that?

FORSGREN: It’s, I will say, it’s not always super straightforward, [LAUGHTER] but there are times when I, kind of, sit and I’m like, I’m getting one or two signals. I really want to take a half-step back and say, here’s an opportunity. Should I take the opportunity, or should I not? There have been one or two times where I’m not sure, you know, but there have been times where I’m like, I need to jump, and I can reevaluate in six months or a year, but I’m going to take this now. And I will say about 90 percent of the time I have been absolutely on.

GEHRKE: I find this so fascinating because we all are faced with different opportunities and chances in our lives. How do you evaluate this? Do you have, like, a checklist? Do you go back and ruminate and meditate on the mountain? Or what’s your method?

FORSGREN: I actually have a spreadsheet. [LAUGHS]

GEHRKE: OK.

FORSGREN: But I don’t always follow it. So what I like to do is identify, like, what are my criteria, which is, you know, what things are important to me.

GEHRKE: Yup.

FORSGREN: You know, some of my big moves—what’s important to me in the city? And then for each of those criteria … or when I am considering a new job—what things are important, and then how important are they?

GEHRKE: And you put, like, a risk score behind it or, like, a score?

FORSGREN: Either a risk score or an importance score. And then I’ll just, kind of, multiply it out. And, now, then I will go back and I’ll like …

GEHRKE: That sounds so amazingly systematic.

FORSGREN: … and then I’ll nudge all the numbers, and then sometimes, I’ll still change my mind because there’s something about your gut that says, I don’t know. But by identifying all those things first, it helps me think through it. Now, the spreadsheet, like, I’ve shared with folks, and it’s really interesting because just the exercise of saying what things are important to me for this decision and how important are they sometimes … not even doing like the math, right. Because it’s not real math. Let’s be real. Or it’s, like, very simplified math. Just identifying those things, sometimes just that exercise, people are like, “Oh, I know what my decision is now.”

GEHRKE: I think often just even thinking about this with that clarity, right, creates the resulting clarity then and think about all the factors.

FORSGREN: Right. And there have been times where I’ve completely changed what I thought I would do and, like, I can give an example. After I left academia, I was at a startup, and then following that, I started, like, my cute little baby startup company. I thought for sure I was going to go to a large consulting firm. I mean, I had them ranked. I thought I knew my choices, and I was like, no, let’s, let me think. Let me identify what order I should go in. And, like, it didn’t matter how I, kind of, rearranged all the numbers, starting my own company was at the top.

GEHRKE: Well, let’s go to that in your career.

FORSGREN: Yeah, so let’s, let’s catch up.

GEHRKE: Exactly, so you decide to go do your PhD?

FORSGREN: So I finished the PhD. I stay in academia for a while because I really like the research that I’m doing. It’s really interesting. I think I’m, kind of, on to something, and academia is a good place to do this, right. So I was a professor at Pepperdine for a few years. I go to Utah State for a few years. Again, like, what’s this opportunity? Pepperdine was a lovely place. The faculty were incredible. Malibu is gorgeous. Utah State, my alma mater, comes along, and they’re like, we would like to hire you, and we’ll create an opportunity for a new position. So I took that pivot. And now it’s a joint appointment to create an analytics program in the MIS department. I was also an accounting professor, because I have a master’s in accounting, so it was, kind of, this, like, perfect situation. I was there for, you know, two, three years, et I’m doing really, really well. A really strong path to tenure. Letter from the provost saying that things are looking really well. And I’m like, this is good, but it’s not great.

GEHRKE: You had a spreadsheet that said that basically or [LAUGHS] …

FORSGREN: This was in my gut.

GEHRKE: This is just “I had a feeling.”

FORSGREN: In my gut, I’m like, I’m doing really well. My research is going really well. We just hit the Wall Street Journal because we find early signal that DevOps—like now it’s being called DevOps—shows organizational impact. And so a few folks in industry were coming to me and they said, you know, “This is super relevant. You’re really changing how we’re doing things.” This was still, kind of, earlyish in this research program, and they said, “What if we create an opportunity for you where you could spend half of your time doing research and half of your time helping our company improve our engineering practices,” and I was like, I think I might do this. You know, at that point, I just decided to go for it, and it was a little company here in Seattle called Chef Software.

GEHRKE: It was actually here in Seattle?

FORSGREN: I was here in Seattle.

GEHRKE: Chef Software?

FORSGREN: Yeah,they did configuration management software. And also, that was a really interesting tie because—or, kind of, like pull, tug and pull because I was doing this research with their competitor called Puppet, and I went to Chef, and so I’m, kind of, like, managing these relationships really well or as well as I could. But that was also one of my first exposures to managing conflict at work and in professional relationships because this report, it was a research report, but it was done, kind of, through industry. So the main sponsor was Puppet, but I was working at Chef. And so how do I manage that? So I was at Chef for a year and a half, and then at the end of that year and a half, we, kind of, looked at each other and we were like, I think we’ve reached the end of this road because I had done about as much as I could do for this little startup. They had about 200, 250 people. They really didn’t need a researcher. They were doing me a solid. And then at the same time, we had, kind of, spun out a separate entity called DORA—DevOps Research and Assessment—and we said, so what should happen here? We had been doing research, the State of DevOps Report, but then so many companies were coming to us and they were saying, what if I want to have our own customized assessment? How could we do this? And, you know, I looked at a couple of my co-founders, you know, Jez Humble and Gene Kim, and I said, I know how to do this. I know the algorithm I would use. I know how I would build this out. I think we could do it, a SaaS company. I have a very low risk tolerance. I have never wanted to start a company. And I think, you know, to your prior question, like, how have I thought about doing this before? I actually looked at them, and I said, you know, who wants to be CEO? And they said, we think you should. And I said, eh, I’ll give you one year, and then I want you to tell me if you want me to continue doing this. And so we started this company. I mean, our first prototype, I drew pen and paper in the back of a notebook, and I showed it to Capital One, and we said, would you buy it if it looked like this? And then we just, kind of, iteratively built out pieces and pieces. And I was like copy-pasting pieces of it into reports as we went. And then at our offsite after one year, we read our results. I shared ARR and sales projections, and I said, OK, well, you have a first right of refusal, and do you want to renew? And they looked at me like what? And I’m like, no, it’s been 12 months. Do you want me to return again? And we just, kind of, decided if we wanted to. After that, things were going really well, but we were also growing and scaling really, really rapidly. Too fast for us to keep up as a bootstrapped company. And so, you know, I needed to figure out how to gain and acquire infrastructure. And so that would either have been external funding and hiring really rapidly or getting acquired, and so we … I approached a handful of companies, and Google acquired us.

GEHRKE: Wow. It’s an amazing story and must have also been a time of craziness and also fear of uncertainty. How, you know, what were some of your emotions during that time?

FORSGREN: It was. It was a lot. It was really interesting because it was, kind of, balancing also a few things, right. Because I had … I think some of it is also balancing identity, right. Am I a researcher, and how do I think about maintaining that identity and that credibility that I care so much about when the research and “publication path”—you know, kind of, in finger quotes—that I care so much about has shifted, right. Because now I’m doing a lot of applied research, and how do I think about that? Some of it was, am I an entrepreneur, and what does that look like, and what does, what does that credibility look like? How do I put out a product fast enough? How do I manage and maintain this company? How do I manage and maintain relationships with my employees, with my partners, you know, with this partner ecosystem that we’ve developed? And then when we get acquired by Google, what does that look like? How do you manage that growth path?

GEHRKE: And these are all very, very different skills than you had as a software developer or even as a professor.

FORSGREN: Especially as a professor. Right. And it was also a really, really wonderful time, I think, to grow and learn and iterate. And I’m really grateful for the partners that I had along the way, right. There were times that were bumpy, right. But I appreciate that we were really honest with each other, right. There were times when we disagreed, and there were times when I also said, like, I know this is the right thing. Please, you have to let me do this. And there were times when, you know, they had their expertise.

GEHRKE: And then, you know, you were at the company. The company gets sold to Google.

FORSGREN: Yep, company gets sold to Google.

GEHRKE: Now you’re at MSR.

FORSGREN: And then I was at Google for a little bit. And then I had this amazing opportunity to join GitHub. And I was really excited about that because that framing in that invitation, we were talking about, you know, what could it look like? You know, what would a perfect world be where I could return to something that looked like research and strategy? Because I realized there were pieces about research that I really, really loved. And there were also pieces about, I don’t want to say products—it’s not quite product—but it’s about strategy. What is it that I love doing in terms of, kind of, execution and identifying holes, and how does that feed back into the research projects that I want to do? And so when Microsoft first approached me, they said, you know, what would your ideal job look like? And I, kind of, laid that out, and they said, you know, well, let’s think this through. And so we started with GitHub because, you know, if you want to study developers, that’s an amazing place to start. So we did a couple of iterations with the Octoverse report that were really rewarding and then we said, you know, another good place, you know, another wonderful opportunity would be to think about developers and a Developer Experience Lab. And if there’s a research lab, where does that live? And we talked about it some more. You and I did, too.

GEHRKE: That’s how we started talking … exactly.

FORSGREN: Yeah, and we thought, you know, MSR really is the perfect place for that to live.

GEHRKE: And you’ve been at MSR now for a few years, and now we’re going through yet another change. I mean, you’ve been through many of these changes before. We talk about this current change. It seems like, again, coming back to this, you’ve been amazing of, like, when the environment shifts, finding out where to go. You know, you have your spreadsheets, you know, as one mechanism. Now we’re at another sea change with AI, right. And AI is clearly changing the way we write code, which is, sort of, the innermost loop right now with GitHub, with Copilot, but it’s probably going to make it much more into the inner and outer loop and the whole way we write code and the way we develop with low code. So, I mean, first of all, how do you think about that sea change, and how do you deal with your research group and, you know, yourself as an identity, again, as the world around you is having this massive change towards AI?

FORSGREN: You know, sometimes, I just laugh that the world is a circle, right. I’m really excited because, you know, we’ve come back around to getting to rethink what it means to do what we love, right. So I’m personally getting an opportunity to come back to be a developer again, right. What does it mean to dive back in and learn brand-new things again? Because AI is new for almost all of us. Even people who have been studying AI for 10 years are saying, like, so much of this is new, so much of this is something that we couldn’t have predicted. I’m getting to, you know, dive back in and play with new tools and new technologies, and that I really love. I also love that you mentioned that, you know, there’s the inner loop and there’s the outer loop. And so in terms of my team, I’m really, really excited about the team that I get to work with because …

GEHRKE: Do you want to explain maybe a little bit, just for the audience, inner and outer loop?

FORSGREN: Yeah, so inner and outer loop. So inner loop is, you know, the coding that we do, kind of, locally, so it can be writing the actual code, you know, local build, if you do local build. It can be debugging; it can be everything that’s like just right there on your screen as you’re writing your code. Now outer loop is everything that you do to get that code running in production, right. So it can be additional tests. It can be integration build. It can be, you know, everything out through release and deployment until we’re operating that code and then, like, continuing to operate that on our systems at scale.

GEHRKE: I mean, the way I saw this was so impressive when I joined Microsoft, of course, right. What it means to actually … that first of all, software development is a team sport, right.

FORSGREN: Yes.

GEHRKE: And also it’s not a team of like 11 people like soccer, where I grew up with, but it’s a team sport of, you know, potentially thousands of people, right, and that there’s an, actually, there’s a lot engineering systems around it. And it’s called software engineering for a good reason.

FORSGREN: Yeah.

GEHRKE: Because there’s systems around it that help us to scale to that many people contributing to a single outcome. And so the inner loop is, basically, my notion is that when I do my own little exercises with the ball and then the outer loop is when I actually, you know, do strategy with the whole team and see that I integrate well. Is that a reasonable analogy?

FORSGREN: Exactly. And so sometimes the joke is, you know, well it worked on my machine, right. That’s kind of inner loop. Yeah. And then outer loop is all of the orchestration, right. All of the architecture. Everything else that we need to make things, especially really large things and complex distributed systems, work at scale. Yeah.

GEHRKE: And so if you think about … how do you think AI would influence both the inner and outer loop? I mean, we see what’s coming out in terms of, you know, GitHub Copilot and even more capabilities. I mean, in the “[Sparks of Artificial General Intelligence]” paper, we describe that GPT-4 can actually write an application with close to a thousand lines of code, right. So how do you think AI’s actually going to influence developer productivity and software engineering as a whole?

FORSGREN: I think there are so many exciting ways to think through this, right. I love your point that there’s inner and there’s outer loop, right. So, yes, we absolutely have opportunities to think about how it influences the way we write code, but I think it also has so many opportunities downstream, right. How can it, how could we use it to improve our code bases, right? Can it identify technical debt and clean up some of our technical debt for us? Can it help us think about downstream incident management? Can it help us manage our servers and our systems? Can we use it to take a look at our code for us? Can we ask it, can you please help me improve the security posture of my code? Can you help me improve the performance of my code? Can you help me improve anything else in my code, right? Even that explicitly: can you say, is there anything I haven’t thought of in my code, and what should I do? We can ask it, you know, to proactively watch and monitor our systems’ performance for us and then proactively manage that for us, you know. As we look, you know, even further into the future, there may be opportunities for brand-new abstraction layers. What happens if we let LLMs, or invite LLMs, to execute for us and then reason about that code for us so that all we need to do is guide and direct it?

GEHRKE: We’ve been talking a little bit about code, but maybe in the future, code would be, sort of, this low-level abstraction like what we have right now with assembly. There are very few people who still optimize, let’s say, locks and database systems with the assembly code, but most people write at a much higher level of abstraction. So what do you see as this next level of abstractions that are coming?

FORSGREN: You know, I think …

GEHRKE: Is it language, basically, language interaction?

FORSGREN: I do think some will be language. You know, I really like that idea for at least a few things, for a couple of things I just mentioned, right. Like asking it to do things like please check for security; please improve the performance. Can you help me generate workloads? Can you help me run these type of canary tests, right?

GEHRKE: Like semantic linters with a very bigger … with much bigger capabilities.

FORSGREN: Exactly. I also think there’s an opportunity for graphical interfaces, and by that, I mean what if we create a diagram or a UML and then ask it to implement that in the best way possible. Or reverse it, right? When I think about when I was working in code bases, the best way I could get a feel of the code base was to code it, and then I could create this mental model. If we’re doing less coding, how can we create that mental model? I think there could be wonderful opportunities to ask or invite these LLMs to diagram some of these code bases for us.

GEHRKE: So interesting …

FORSGREN: You know, don’t just ask it to create documentation or explain it to us, because language can be somewhat limited, but we know that diagrams and pictures can be incredibly powerful.

GEHRKE: I see. Create the actual architecture diagram for us.

FORSGREN: Create an architecture diagram—and create it in two or three different ways to help us understand how different components interact, which can also help us understand where there may be redundancies in code. There’s a huge amount of technical debt out there, right. So I think that, kind of, opens up some really interesting ideas for what could be there. You know, there are also some wonderful horizons that we’re already approaching in terms of testing and exploratory testing and what that can mean for really improving the way our code works.

GEHRKE: It’s super exciting. I mean, I would love to be able to talk more about that with you. But let me ask one last question. I mean, you’ve had this absolutely stunning career. I mean, if you think about where you started out, you know, then developer, you know, professor, startup founder, you know, working in a big company, being in a restructuring of the company, for someone who’s starting out, what’s the career advice that you give for anybody who’s right now starting and going into tech, people who are at university or just graduating?

FORSGREN: I think there would be two, and I think they’re related. One would be assume that something can be figured out and that it’s not hard. I think that would probably be one of my best tricks. I didn’t find out until the end of college that girls were bad at math, which I am not, or that computers were hard. It really helped that for most of my life, my dad just, sort of, helped me rethink through things or repivot or retry lots of things. And so if it’s hard, that’s OK. It just might mean that you should just spin it on its head and try to take another look. So that would be the first one. And I think the second one is consider new opportunities and go ahead and take them. And if after six or nine or 12 months, it’s not the right opportunity, go ahead and change your mind. I would not be where I am today if I hadn’t taken one or two really incredible opportunities that seemed a little bananas at the time, and it just worked out.

GEHRKE: That’s amazing advice, especially also in something that tells us to A/B test even our own life. The only problem is that we have only a limited number of tests that we can do, but I mean, it clearly is an amazing story. Thank you so much for the conversation.

FORSGREN: Yeah, thank you.

GEHRKE: Thank you.

To learn more about Nicole’s work or to see photos of Nicole as a child in Idaho, visit aka.ms/ResearcherStories (opens in new tab).