Behind The Tech with Kevin Scott - Sam Schillace: Deputy CTO, Microsoft

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SAM SCHILLACE: Find the thing you feel kinda guilty about being paid for and do the hell out of it. Like if you feel kind of guilty that you’re getting paid to do something it probably means you’re really good at it, and it’s fun for you, and if people are willing to pay for it, just go do the heck out of it.

KEVIN SCOTT: Hi, everyone. Welcome to Behind the Tech. I’m your host, Kevin Scott, Chief Technology Officer for Microsoft.

In this podcast, we’re going to get behind the tech. We’ll talk with some of the people who have made our modern tech world possible and understand what motivated them to create what they did. So, join me to maybe learn a little bit about the history of computing and get a few behind-the-scenes insights into what’s happening today. Stick around.


CHRISTINA WARREN: Hello, and welcome to Behind the Tech. I’m Christina Warren, Senior Developer Advocate at GitHub.

KEVIN SCOTT: And I’m Kevin Scott.

CHRISTINA WARREN: And today we have Sam Schillace with us, and he’s somebody who was a huge part of the creation of Google Docs. And now he’s working with you at Microsoft. Right, Kevin?

KEVIN SCOTT: Yes, Sam and I have known each other for a very long time. So Google, many, many, many years ago, bought the startup that Sam and his co-founders started that created the first interactive web word processor, like back at a point in time where people thought that doing that was impossible. Yeah. And that work became Google Docs. And Sam ran all of the Google Apps business at Googl, for a while he went on and ran engineering and operations at Box, another startup until he went public, and was back at Google. And now he works here for us. At Microsoft.

CHRISTINA WARREN: that’s awesome. And we’re really lucky to have him especially like all of his experience, and also like, thank you for bringing the word processor to the web browser. That’s amazing. All right. So let’s go ahead and let’s dive into your conversation with Sam.


KEVIN SCOTT: Sam Schillace works at Microsoft in the office of CTO as Deputy CTO and Corporate Vice President, focusing on consumer product culture and next generation productivity. Prior to Microsoft, Sam spent three tours at Google, Gdocs, Google Ventures, and then Maps and Search. Sam originally worked at Google as a founder of the Writely acquisition and led the teams that built Google Docs. He has a long history in consumer software as the focus area lead for consumer apps at Google and in multiple startups he’s founded. He also worked at Box as head of engineering for four years, where he and I met on the technical advisory board. He holds a BS and MS in Theoretical Mathematics from the University of Michigan where he focused on combinatorics and discrete mathematics. Sam, it’s great to have you on the show today.

SAM SCHILLACE: It’s nice to be here, looking forward to it.

KEVIN SCOTT: Yeah, so we always start these podcast conversations by going all the way back to people’s childhoods, and I’m just super interested in how you first got interested in science and math and programming, and like just what lit the spark.

SAM SCHILLACE: Yeah, it’s kind of like, I’m a little bit of a black sheep in my family, like my mom’s an artist and my dad’s a psychologist and a psych professor, and so like it’s a little – it’s always been a little bit of a mystery, like that was always the thing I’ve liked, as long as I can remember. I still have this old microscope my mother bought me as a – or my parents bought me as a birthday present, when I think I was like, eight, you know? It was like the coolest thing ever, that I had this like cool microscope, and like, I was super, super into it, like always, and like I wanted to be a doctor when I was younger. I did a lot of like biology and stuff like that in high school and things like that. But when I was about 12, for reasons that I don’t even really think I understood, even at the time, and certainly don’t remember, I really got into doing computing and the computer at the time was the TRS-80, you know, model one, the “Trash-80.” I convinced my dad to by me one, this used one from somebody. It was like 600 bucks, I remember, which – you know, it was like the equivalent of like three grand or something today, like a huge amount of money.

You know, I don’t know why he did it, really, but he did, and he bought it and like, I remember it being down in our basement, and I would like, you know, write BASIC on it, you know, out of the back of Dr. Dobbs, and you know, the pixels were 3x2. They weren’t even square pixels. They were this chunky, little thing that you could do like really basic stuff on, and if you felt like, you know, not retyping your program, you’d tape it out to a cassette tape, and you know, read it back in later, and all that crazy stuff.

And a friend of mine had an Apple 2 that we played on, you know, and wrote video games. I was really – I liked pixels a lot, like I liked making pixels on the screen, so that kind of drove a lot of it

KEVIN SCOTT: Did your high school have computers? I mean, like this is in the ‘80s, right?

SAM SCHILLACE: I graduated from high school in ‘84. My high school didn’t really have computers or really have a computer program. I didn’t really think of computers as anything other than a fun hobby, even most of the way through college. Like, it, college – the first exposure I really got to anything significant, other than just early things was like the nursing school, across the road from my dorm, had a basement full of Mac Classics that you could go write – you know, use, and I would go write my papers on them because they were awesome. Like I didn’t have to like – you know, I was a terrible typist, and I never learned to type-touch, so – you know, to actually type the right way, so like, that was great because I didn’t have to like white out and backspace and retype all my papers. I’d just go do them there.

And I even remember, even then, like all of my – like friends and roommates and stuff, classmates, thought it was a weird thing to do, like why would you go type on a computer, like we’ve got all these perfectly good typewriters, and I was like, no, this is way better. And that’s where I sort of started getting into them, and then like they – I did a lot of like goofy, weird little side programming projects in college, like making, like sort of pseudo 3 – 2-1/2-D landscapes that were randomly generated that I liked to look at, and crazy stuff like that.

And then, you know, I took one class in – one CS class in college. It was like the Knuth algorithm class, you know, the first book. It was cool, but at the time I was really into math and really into science, and I thought I was premed, and I was doing like graduate math classes, so that Intro to Algorithms class was just super easy. It was like the only thing I ever got an A+ in, ever in college, and my math profs really looked down on it, and sort of discouraged me from doing computers because it’s like – well, there’s like math, and then there’s applied math, and then there’s engineering, and then there’s whatever the hell those hairy computer guys are, you know, it’s like the bottom of the bucket.

So I didn’t really pursue it, like I didn’t get a CS degree. I kept doing my math degree, got to the end of college, and my college roommate, who was one of the cofounders of Writely, ultimately, had dropped out to go do a company that was also a word processing company, called Ann Arbor Software, they got bought by this company called Ashton Tate, before Oracle killed them, and got moved – he got moved out to the Valley, and I didn’t know what to do with this weird math degree, and I didn’t want to be a doctor anymore, and so I just moved out to the Valley and started writing code with him.

We wrote a video game and then ultimately wound up starting six companies together, and just worked together for about 25 years, just fell into it, I mean, just absolutely fell into it.

KEVIN SCOTT: Going back a little bit. I’m curious, like why math?

SAM SCHILLACE: I don’t know. Like, I liked math. I thought it was fun. I’ve always been kind of an abstract thinker. I like math. I like the – I don’t know, I like being able to kind of tinker and build stuff with your mind. I mean, that might be a – kind of a throughline of all of this, like software is always – you know, you and I are both makers, we really like to make stuff, and I always liked software because it was the most that you could – you know, the most direct connection between your mind and making something, right, like there’s as little mediating that as possible.

Math is kind of the same way, right, where like you can think really interesting crazy cool thoughts, but you can do it in this interesting structured way where you’re not just bullshitting, like you’re actually like – you know, like I did a bunch of stuff with like set theory and the completeness and correctness theorem and the omega number, and all this other, like – you know, the whole thing, probability, like – it’s just wild stuff. It’s like metaphysical and cosmological, but like it’s grounded in some real rigor, which is just a really interesting way to think about the world, right, like just trying to be this amazing toolset for understanding stuff.

KEVIN SCOTT: Yeah, it is, it is an interesting thing, it’s some mathematicians go off in a completely different direction, but like a lot of what you do in math—and I don’t think I really appreciated this enough when I was taking a lot of math in college—is that it is teaching you, in a sense, like how to do abstraction really well.

SAM SCHILLACE: Yeah, and decompose problems, and I – one of the I think there’s very little that’s sort of really directly valuable in the computer career from my math degree, although there are some – definitely some ways of kind of thinking about Venn problems and stuff, but the thing that’s super useful about it is, it taught me to be alone in a room with a – an unsolved, you know, seemingly unsolvable or extremely difficult problem, and just you know, not having any excuses, just like work through it, right? Like, you know, and like one of the – like this – I had this class, at one point – like there’s group theory which most people know, sort of like this abstract theory of algebra, and then there’s semi-group theory, and semi-group theory, you start to take away some of the axioms like you don’t have associativity or commutativity of the binary operator.

And man, is that stuff hard. You look at these things, these theorems that you have to prove, and you’re just like, that’s obviously true, and there’s like – but you’ve got to prove it, and there’s just like no place – you know, it’s like a seamless wall. There’s like no place to get any traction on it at all. And like, sitting in a room with those things, spending like eight, ten hours, on like – like a two-line proof, you know, is just like really good mental discipline of like, you know, well, there’s a solution, you’ve just got to dig away at it, and you’ve got to break it down into smaller problems, and you’ve got to, you know, figure out what you know is true, and like what you hope is true, and how you get to the things that – you know, like all that skill is super valuable, I think, in engineering.

KEVIN SCOTT: Yeah, I learned a similar set of lessons when I took Linear Algebra in college. So my Linear Algebra prof, it was a very theoretical course, and he – 100% of your grade were two exams, a midterm and a final, and on the two exams, they were 10 true-and-false questions, and they were take-home exams, and you could spend as much time as you wanted doing them, and it was brutal. Like you would take those home and get to, oh, I’m confident that this true or this is false was a massive amount of theorem proving.

SAM SCHILLACE: Yeah, I remember doing one of these midterms like this, I think, for one of – like one of my Group Theory classes, where it was 12 problems like that, and I took it home over spring break, and I got one problem done a day, you know, like I literally, like I could grind through one of them every morning, and then I would go out on the beach, or whatever, wherever we were. Yeah, it’s – I think that discipline is – you know, this is the nice thing about math, I think, is that it’s very easy to fool yourself. You look at something and think you understand it, or you look at something and you think you know how to do it, but like, doing it is the proof, right? And math really teaches you that

KEVIN SCOTT: Yeah, I also had a - when I took combinatorics in grad school, I had a professor who would occasionally slip an unsolved problem into an exam, and what that teaches you is what to do when you are faced with a problem that is literally too hard for you or anyone else to go solve. Like, can you get anything out of it, just the process of making the attempt? And you know, the answer to that question is like obviously yes.

SAM SCHILLACE: Well, yeah, I had one of those happen, by mistake once, in one of my advanced classes, where the prof would give one, two or three stars. One was like you really should be able to solve this, two is like advanced, three was unsolved. And he accidently mislabeled a three-star as a one star, and he had a very unhappy group of kids on Monday morning, who had spent the weekend banging their heads against this obvious problem that was unsolved, actually.

KEVIN SCOTT: So, so how did you go from being a theoretical mathematician to – I – I understand the impulse to go work on some of this software, but like why work on software in context of starting a bunch of companies?

SAM SCHILLACE: I – you know, it – again, it was a little bit of this like kind of falling into it, and a little bit of networking, right, which is also one of the reasons why I try to like network outside of my particular group because I think networking is why we don’t have good diversity in the tech industry. People network with people like them, and so you kind of have to force yourself to go, you know, break those networks, and I think it’s an important part of increasing diversity. But like, you know, we were at Ashton-Tate. Ashton-Tate was where I got – we got hired into the – that Mac division of Ashton-Tate and they were in the process of being strangled to death by Oracle, basically, right?

So they were a database company that Oracle was crushing, so that job only lasted about a year-and-a-half, and about six months into it, it became very apparent that it wasn’t going anywhere, and we were trying to figure out what to do next. And like, my friend and I, Steve Newman, we were just bored, and we wanted – like, we had – they had loaned us like a silicon graphics machine that we were playing around with the flight simulator on it, and so we were like bored dudes, and like we wanted to play games, and there weren’t any really good games.

Like Castle Wolfenstein was the game that was there at the time, and we just like, wanted a Twitch game, and so – like this is actually a pretty good, like set of learnings from this game. Like we built this thing called Spectre, and it was a very early multiplayer game. It wasn’t even ethernet, it was over AppleTalk, so you could play against other people in real time, you know, in your LAN, like within the office, just a straight-up, like first-person shooter. You’re driving around in a tank. It looks like this old game, Battlezone, and it like taught me a whole bunch of stuff.

It taught me about like really focusing on user need and user value. Like we knew what we wanted. We were the customer. We were iterating with ourselves. We wanted a Twitch game, we wanted it to feel really clean, we wanted it to be really straightforward, we wanted stuff to blow up a bunch. And so like we built that, which was really hard to do on the hardware of the time. It was super hard to do with the networking stuff we had to deal with, so like we learned a whole lot about like value in programming is in like confronting these like really annoying problems and getting them right, you know, because like – again, like we got a patent for how the rendering worked because the hardware was too slow to draw all the pixels, and so we had to like erase a bunch of them. There’s all this kind of stuff like that.

So that taught – that taught me a whole bunch of stuff, and then that like wound up paying for like four years of my life, like we sold it to this company – or we licensed it to this company that just like published it for us, and that was like, you know, good money for me at – you know, as a kid, like kind of to live on, and then – you know, as Ashton-Tate fell apart, the group that had been part of that company went on to do another startup, which didn’t really go anywhere, but Steve and I went with them and worked on that for that four-year period.

And when that failed, we sort of took the pieces of that and, you know, the dotcom movement was starting, and so we turned that – the pieces of that company, which was like a personal information manager, but we had built, like a – a good cross-platform Mac and Windows app framework out of it. We took that and quickly pivoted into building internet tools, one of which we sold to Claris. So that, right there, is like three startups in a row. It was like bing, bing, bing, you know, like kind of by accident, but like – you know, again, like – in that era, I spent a lot of time like feeling bad that I was doing something fun for a living. Like I kept feeling guilty that – I had dropped out of being premed to go do this thing, and I literally spent like the first 10 years I was in Silicon Valley, thinking like computers were a fad, I needed to go back to med school and get a real job, like this is just kind of a goofy, stupid thing to do, like – and eventually, after about 10 years and several successes, I was like, well, I guess this is my life now.

You know, I’ve got money in the bank, and this is kind of fun, and it seems to be continuing to develop, so I guess this is a career, let’s go do this. And there’s actually a lesson in there, that I tell people all the time, which is, I think we’re really confused, mostly. We have this kind of Calvinistic ideal – idea in our heads, that like work is equivalent to suffering, right? You’re not really working if you’re not – if you don’t hate it. And I don’t think that’s true. I actually think the place for people to be – this is the career advice I always give people is like, find the thing you feel kind of guilty about getting paid for and do the hell out of it, right?

Like if you feel kind of guilty that you’re getting paid to do something it probably means you’re really good at it, and it’s fun for you, and if people are willing to pay you for it, just go do the heck out of it. Like career growth usually comes from having impact, which usually comes from doing something you love with a lot of passion, like that’s – it’s not that much more complicated than that – so that’s how – I never started off with like I’m going to go do a bunch of startups. I just was like, what’s the next interesting thing I want to go work on? Let’s just go do that with all this energy.

I always liked working with my friend, so we just kept doing stuff, and we kept making money, and it kept being successful enough, so like why stop?

KEVIN SCOTT: Yeah, and I think you had another couple of pieces of interesting career advice in there as well, so I totally agree with what you just said. Like, I also agree that working with your friends, like whether they were your friends before you start something, or whether you like form bonds with folks, you know, when you join a company, and you start working with them, I think that’s pretty important. Because, on most days, like even when you’ve got a thing that, you know, you’re passionate about, and you nominally enjoy, like there’s just a bunch of hard stuff you’ve got to go do to make anything worthwhile. And so you do want to be doing it with people whose company you enjoy, or – and where you feel like some degree of camaraderie with them, otherwise it’s just – I mean, you and I do this now, right, like I don’t want to sell the image that Microsoft is, you know, somehow perfect.

Like we’ve got hard things we work on all the time, and then the two of us, like you know, because we’re friends, we will, you know, we will complain to one another, and you know, the thing that you try to do, I try to do, you know, I even do this in my – in my marriage – is like, you want to sort of be grumpy, out of phase with each other.

SAM SCHILLACE: Yeah, right, yeah, that’s right, you want to be complimented, all kinds of complementarity you want in these partnerships, right, that’s definitely one of them. Skillsets is another one, right? Like you want a linear thinker and a nonlinear thinker, and then you want them to be like, you know, in creative tension with each other, basically, in a constructive way, right?

KEVIN SCOTT: Yeah, I mean the other, like the most interesting, like complementarity advice that I ever got is, I had a mentor years ago who told me to imagine a histogram that has five buckets, and on the extreme left of the histogram, the bucket is labeled “idiot” and on the far right end of the histogram, the bucket is labeled “genius” and in the middle is “average” and you can take everything that you do, and every skill that you possess and put it into one of those buckets. So like that’s not the – you know, the breakthrough thing for me. Like the breakthrough thing was this mentor said, if you work really, really, really, really hard, you can move something over one or two positions on that histogram, which means that if you’ve got a thing that you are an idiot at, like you probably –

SAM SCHILLACE: You might get to average, if you’re lucky.

KEVIN SCOTT: Yeah, and every minute that you spend trying to get to average is a minute that you’re not spending doing the thing that you’re a genius at, and you know, like what you want to do with teams or partnerships or anything else, to your point, about – you know, nonlinear versus linear thinkers, is you want to – like, you try to do something together, you need a set of skills to go do the thing, so like how do you, like figure out this thing where everybody’s histogram adds up to like above average, where you can have everybody focus on what they’re really good at?

SAM SCHILLACE: Well, and the real challenge with this is that, you know, just to keep going with that example, like sometimes you know, if you’ve got two geniuses that are pulling in different directions, they neutralize, and then you don’t have either genius, and so like – and so, and like in fact, that often happens, right? Like this, I have this tension a lot with my cofounder, with Steve, like you know, when you have genuinely different perspectives on the world, and you are genuinely both good at them – those are often – you know, you’re kind of blind to the other perspective to some degree.

And so finding a way to like understand and respect the other perspective, even if you don’t really get it, like you just understand, like this person, I don’t get their domain, I don’t even maybe necessary fully value it, but I understand that it is valuable and they’re good at it, and so I’m like deliberately – like carving out some space. I always tell founding teams, like pick somebody you like arguing with, like that’s – you know, don’t pick somebody you like. Like it’s easy, you know, don’t just go found something with a friend. Pick somebody that you enjoy arguing with, where like you have genuinely different perspectives where you’re struggling to even find common vocabulary, but it’s okay, like you’re willing to have those arguments to kind of find that common ground in between your domain, because often there’s like super small overlap in the Venn diagram of even like the language that they use, right?

KEVIN SCOTT: Even going back to, you know, marriage, like my wife is smarter than I am, and like – a lot, and you know, there were a bunch of things when we first got together that both of us were – both of us were good at and both of us liked doing, and eventually we learned that, like we just sort of had to pick on bunch of these things, where I sort of had to say, like all right, this is going to be your thing, and like I’m not going to try to get up in your business on this, and vice versa.

SAM SCHILLACE: Yeah, everybody has comparative advantage and stuff, too. Like, one of the things that drove me nuts in my marriage for a long time is – I have opinions about stuff and my wife doesn’t, as much, right? Like I’ll know what I want for dinner, and she won’t, and whatever, and like we just sort of decide, like okay, like that’s fine, like you know, we kind of get comfortable with those different modes, and like you take that role

KEVIN SCOTT: I think the thing that we’re sort of getting at, the meta point, is like you just really have to be thoughtful about how you’re trying to do things together with other people. You have to pay attention to what the dynamics are and try to make things work for everyone.

SAM SCHILLACE: And, and you have to recognize that that’s not – like, if you’re struggling with a coworker, or a team member, or whatever, like that’s not an anomaly to be worked out. That is a fundamental requirement of high-functioning teams is that you’re going to have tension between different perspectives, and that’s like a fundamental critical value of being a mature team member and leader is that you’re actively aware of this and managing it. Like you’re never – there’s no easy, like you know, if you snap a bunch of people together that are all the same person, that team will fail, right? There’s always tension in these teams. There has to be if they’re going to be high functioning. That is the fundamental skill.

KEVIN SCOTT: Yeah, and I think the thing for managers as well is realizing that you can realize all of what we just said and still be a victim to some of the stuff yourself, and which is why it’s really important, if you are leading things to like have people in your network who can help you go deal through your own shortsightedness, where intellectually you should understand how to go deal with it, and yet, you just aren’t because you’re a human being.

SAM SCHILLACE: This is actually a really good illustration of one of my favorite things in tech, in general, is that favorite patterns that shows up in a bunch of different ways, which is this tension between long term and short term, right? The manifestation is, like, the tension between what I know I should do in the long term versus what I want to do right now. I always joke, it’s like, well, I want to be on a diet, but there’s a donut in front of me and I’m eating that thing, you know? Like, that kind of the easy way to think about it.

But, like, here, right, you know what you should do. You know you should build and manage this thing in the long term, but it’s, like, hard to do because what you want is a day-to-day life where you don’t have to deal with tension among your team members. And so, you’re kind of biased in this direction of picking the easy thing.

And the thing you mentioned of, like, you know, reaching out to outside groups and stuff like that is a common solution to that. You have an externality. You pick something that’s an external forcing function that makes the short-term kind of equivalently expensive in some way to the long term or reduces the cost of long term. So, you do the long-term thing.

But that – like, that pattern manifests in architecture. It manifests in development tooling. I mean, it manifests everywhere in the tech industry. I see it as, like, one of the fundamental challenges of doing what we do very well at scale.

KEVIN SCOTT: Yeah so going back to what, you know, we were talking about 10 minutes ago, just in terms of career advice, like, one of the other thing, nuggets that you had in there that is worth calling out is it is very important, I think, to choose to go work on things that are hard. Like, usually, the meaningful things, things that have impact, like, things that have lasting value were hard and, like, if they weren’t hard, somebody else would have done them and the problem would be solved. But, like, you know, the – we have this, you know, hypothetical frontier that we’re all, you know, as human beings trying to collectively push forward. And, like, getting the frontier pushed forward is just an inherently hard thing.

SAM SCHILLACE: Right. Yeah, absolutely.

KEVIN SCOTT: It pushes back against you. And so, the only way you make progress is just with the choices that you make. You have to choose to go work on hard things.

SAM SCHILLACE: You have to sit in discomfort all the time with this stuff.


SAM SCHILLACE: Which is hard for engineers, right? Like, engineer, the engineering mentality, we like neatness. You know, people like things to – our job is to solve problems. And so, we don’t like things to be unsolvable or to confront stuff where you don’t know the solution or whatever. Like, one of the common mistakes people make is waiting for that moment where the thing seems obvious to do because it’s, as you said, it’s too late.

Like, I always think the right time to work on a new problem is when you have this pit in your stomach where you just know that it’s going to happen. But it also, like, you just know it’s going to be hard and miserable to grind through it because it’s so early. Like, you know, we can talk about this in the context of G Docs.

Like, I always give this example in the early days of Writely, we’re like, you know, I had this – I didn’t really – I can’t claim I had the whole idea for G Docs early on. What I mostly had was just me messing around with JavaScript and content editable in the browser because it seemed like a fun thing to play with, which is a lot of what we would do. But, you know, we had this idea of doing this word processor, and we kind of stood it on its feet and we cleaned up some of the early collaboration stuff so we could kind of work together without stepping on each other.

And, you know, we had this sense – first of all, we had this sense that, like, this was cool, and it was going to be really hard to pull off. And you kind of had that sinking feeling in your pit of your stomach, like, oh man, is this going to hurt? But also, like, my two founders said, you know, “This is a dumb idea. We’re not going to be able to build a word processor in a browser that’s satisfying.”

And the funny thing is that they were right as well as being wrong, right? In the moment, they were right. The browser of the day, IE4 and early Firefox and all that stuff, like, there’s no way, man. Like, they were really not ready. The JavaScript environments weren’t ready. The DOMs were flaky. There were no standards. Like, in a zillion ways, we were not ready.

But the interesting thing was, like, if we solved enough of the problem, we confronted that hard stuff at that early stage and solved enough of it to demonstrate value to ourselves and to some other people. And that started a flywheel, right? And that flywheel between, like, the browser got better, the app got better, the users adopted it more, the browser got better. You know, we had these three pieces of this triangle started to spin and that dragged us forward to where we are now, where the browsers are super capable, the apps are super capable. Billions of people use these things.

Like, you know, that’s the – you know, 100% agree with you. Like, that is the thing you have to do is like you have to be able to see those vistas as they open up, and then you have to jump into them when they’re nasty and hard to deal with.

KEVIN SCOTT: Yeah. I think it’s a good thing to just sort of pause and think about. So, in 2022, as we have this conversation, people take for granted that, like, obviously, you’re going to be able to have an interactive word processor with collaboration. And you can comment, and you can share it with anybody in the world, and, like, you’ve got all of this stuff. When were you first doing this? It was 2002?

SAM SCHILLACE: Five, five, 2005.

KEVIN SCOTT: Two-thousand five. So, like, in ‘05, like, nothing like it existed.


KEVIN SCOTT: And so, everything today that’s in your life, whether it’s a PC or a laptop that you’re able to buy for not that much money, relatively speaking, that you’ve got an Internet that’s got all of this information on it. You’ve got a device in your pocket that connects you to all of that. You have things, like the… Everything that we take for granted now was impossible at some point in the not-too-distant past.

SAM SCHILLACE: Right. The iPhone didn’t exist when we started doing this. Like, we were right before it, right? Like, you know, I don’t know if AWS was a thing then, but I don’t think it really was. Like, I think, like, LoudCloud was a thing back then, right? Like, it was sort of like, yeah, like, all of it had to happen somewhere, right?

And I think Jobs had a quote about this, right? Like, he realized at some point, like, all the cool stuff in the world, like, somebody came up with it and that somebody could just be him. And so, that’s why he came up with a bunch of stuff. You know, like, you know, like, he’s Jobs, but, like, he’s right. Like, everything gets done by someone somewhere. So, you know, if you don’t confront these seemingly almost impossible things, then you don’t get to be one of those people. I guess it’s kind of the price of admission is you have to deal with it.


SAM SCHILLACE: I mean, the other lesson I take from that is, you know, and I tell people this all the time, like, I’m you know, I’m not that smart. Like, I didn’t, you know, foresee the cloud or anything like that. Like, we were we were messing around with stuff, and we were listening to signal from the market and from users, right?

And that’s really the important thing, is, you know, this stuff in retrospect, 16 years later, looks super obvious, like, oh yeah, of course, collaborative documents and mobile and all this other stuff is obvious. But, like, it wasn’t at the time. It was super controversial. And there are a bunch of reasons why stuff like that is controversial. You know, it’s not only that it’s just hard to implement, but there are also, like, kind of natural psychological reasons that people push back on stuff, right?

Like, you know, you also have to remember, like, in that era we were mostly on the desktop. The Internet was just kind of starting. And, you know, the idea was like, well, Microsoft has won this game. Like, Office is this giant thing with all these features, and they have this distribution channel, and software is just – software comes in boxes and that’s just how it is.

And so, like, this disruption of, like, we’re going to distribute differently, we’re going to focus on convenience instead of functionality, we’re going to kind of go down this different path, like, it was super controversial to – challenging to a lot of people’s worldview. And when you – when your worldview is challenged, you have this very stark binary choice that you have to make, which is I’m wrong or it’s wrong. Like, that’s, you know, something – either I was wrong about the world or, like, the world is right or, you know, this thing is wrong.

Like, and so, usually, people choose the thing, and humans are great at coming up with stories for why, whatever they want, right? Like, we all know this. So, like, if you want to think a thing is wrong, a new challenging thing that challenges your worldview, if you want to think something’s wrong, 100%, you will find a reason why that thing is wrong.

I told you that, like, my founder said, like, “The browser won’t support it.” That’s a good example of that kind of story. But almost every new technology gets dismissed as a toy or impractical, or there’s no use for it, or whatever. Like, and I always feel like, you know, the right place to put yourself is the what if, not the why not right? Like, you have to ask the question of what if. Like, when you confront this thing and you see a bunch of problems with it, you don’t – why not is like, well, here’s all the why not? Here’s why it’s not going to work, right? Here’s the problems, all the problems I can see, the stories I can tell.

But the real thing to say is like, what if it works? What if, like, we transform software into being this zero install, on demand global thing where we can collaborate with people? What does that world look like? And if that world’s compelling, then it’s worth doing the effort to break through all the problems. And that’s the much better mentality.

But you have to recognize that in the moment, you won’t see the vision. Like, you won’t see the prize even if you ask the what if questions. You’ll maybe see some of it, but you just kind of have to, like, grind through these things and make them happen.

KEVIN SCOTT: Yeah. Yeah, you know, and it’s sort of interesting. I mean, Bezos has said this a bunch of different times, and I suspect you and I have both experienced it over and over and over again, of people, other people telling you why it is the thing that you are – it isn’t going to work.

I mean, one of my favorite examples, and, you know, I won’t name names, is when I first joined LinkedIn, right before LinkedIn IPO’d, we had a whole bunch of work that we had to go do to make all of the company’s development infrastructure better. Like, we had just gotten ourselves into a state where it was getting progressively harder to, you know, do the sorts of rapid software development that a consumer Internet company needed to be able to do.

And I came in and, you know, there were a bunch of people inside of the company who knew what needed to be done before I got there, but there were also, like, a bunch of people who looked at what they were suggesting that we do. And they would be like, “Oh, this is impossible. Like, we’ll never be able to pull it off. These three people who tried to do this before failed, and it was a miserable, embarrassing failure.”

SAM SCHILLACE: Right. That’s my least favorite excuse. (Laughter.)

KEVIN SCOTT: Oh, God, it’s the worst.

SAM SCHILLACE: I’m just like, just because you couldn’t do it doesn’t mean I can’t do it, right?

KEVIN SCOTT: Yeah. And so, the interesting thing, we did a whole bunch of things that I think are innovative and, like, some of them are now, you know, multi-$10 billion public companies that spun out of even what LinkedIn was doing. But, like, you know, the core of what we were doing, like, wasn’t rocket science. Like, I had sort of done it a couple of other times in different contexts, and it was just a matter of will and determination, and, like, enough patience to get it all the way over the finish line.

And I remember going into a meeting with a bunch of people and told them what the plan is. And the plan was uncomfortable because it meant you had to – we literally burned – we went over this bridge from old build and deployment infrastructure to new and burned the bridge behind us. We literally tore the old system down where there was this three- or four-week period in December of 2011, right after we’d gone public, where we did not have the capability to deploy new software.

SAM SCHILLACE: (Laughter.) Yeah, that’s pretty terrifying.

KEVIN SCOTT: Yeah. And so like, you know, I was telling people, you know, what this plan was and, like, why it was important to go do it and what we would get on the other side. And I had, you know, like, a senior person look at me and it’s like, well, you better – you know, you better hope you’re right. Like, it was this personal thing that I was doing. I was like, “No, no, no, I’m not doing this for me. I’m doing this for all of us. Like, we all need to hope that this is right.” (Laughter.)

KEVIN SCOTT: Yeah. The proper response is, “You better, too, right?” (Laughter.) We all better hope we’re right. No, for sure.

KEVIN SCOTT: But yeah, it is my least favorite thing, is, like, somebody telling you that a thing is impossible.

SAM SCHILLACE: I mean, one of the lessons, the real lesson for me from the early days of Writely which was super valuable was this exact lesson of, like, don’t listen to the naysayers very much, right? Like, and you get this, like, particularly really disruptive things. You know, when you – when you have a product idea and you get it to people, mostly what you get is, like, a bell curve of interest, right? Like, some people are kind of interested. They’re sort of smeared along. It’s not – like, there’s not really high emotional valence anywhere.

The really interesting stuff I’ve found has high emotional valence. You either get a small number of people who are totally on your side because they see the vision, and the rest of them want you to stop doing what you’re doing immediately or have it die in a fire, or whatever. Like, they’re violently opposed and there’s very little in the middle.

And we had that with Writely for, like, years. Like, after Google bought us, we were at Google. I had executives at Google tell me it was a bad idea, and they didn’t want to fund it and that we should stop doing it. And I was like, “I’ve got millions of people already that think it’s a great thing, and the company is moving over to it and, like, what are you talking?”

So, like, fortunately, like, we had enough. Like, I was not – you know, I hadn’t learned the lesson, but I had, you know, a contract that I had to fulfill, and I had backing of Eric Schmidt. And we had, like, a bunch of reasons why, you know, we kind of believed in it and kept going. And I didn’t listen to the naysayers, but, like, that was a real privilege of, like, being given permission to not listen to the naysayers, and then realizing after the fact, like, holy crap. Like, I’m really glad I didn’t listen to them because that would have killed this thing. And it was critical to it coming into existence that I didn’t listen to the naysayers.

And that – like, that’s a really deep lesson for me of, like, I’m very comfortable being in conflict or, you know, in these kind of early, chaotic things, like, taking these controversial positions. If I have conviction, if I can see a path and I think the problems are solvable and I have a vision for where I think we might be going, like, it’s fine if people object. Like, it’s kind of a good signal. It actually is a good signal. Like, you want it. Like, you want controversy, you want it that energy.

KEVIN SCOTT: Yeah, and what’s the worst that can happen if you fail?

SAM SCHILLACE: Right, right. Well, even failing, like, you know, the worst thing that can happen if you fail is you don’t learn anything. Failing when you learn something is fun.

KEVIN SCOTT: Or that you learn not to try again.

SAM SCHILLACE: You learn not to try again, yeah. Like, you know, like, you know, I’ve you know, there’s all kinds of things where I’ve seen teams try stuff and they’ll say, look, well, that didn’t work and, you know, you can’t do it again. I’m like, no, actually you achieved part of it. You just didn’t get it quite right. You didn’t quite get the – you know, you didn’t quite understand the market. You didn’t quite understand the problem, but you made progress. Like, you got energy out of the system. Like, keep doing it; like, you know, you’ll get there.

KEVIN SCOTT: Yeah. I was having this conversation with someone yesterday who was… who had just joined the advisory board for an energy company. And the particular energy company is doing something that’s completely preposterous sounding, but it is a thing that if it’s successful, like, we would all want it to exist.

SAM SCHILLACE: Right, right.

KEVIN SCOTT: It would like, everybody would want it. And so, you know, the only question is like, is it a good use of time to go push this thing forward that everybody will want if someone can make it exist? And like, you know, this person I was chatting with is like, yeah, you know, it’s like, I don’t know for sure or whether this is going to work, but I know they’re going to make at least a little progress on it. And even if the person who solves it later, like, they’re going to refer back to this and sort of say, like, hey, this was, like, you know, an important thing that helped me solve the eventual problem.

SAM SCHILLACE: There’s a there’s a book that I like by this guy named Steven Johnson. It’s called Where Good Ideas Come From, I think is the title of it. And he talks about, like, the adjacent possible, right, and this principle that, like, it’s very difficult to see more than, like, one step past the edge of what’s known and possible currently. Like, not many people can see really two or three steps into the unknown. You kind of make these – these, you know, small – we move kind of in small incremental steps.

And, like, sometimes, you get, like, kind of concurrent inventions of things when, you know, a bunch of different fields advance to within, you know, one – each of them is one step away from coming together on some new thing, like microwaves, I think, was the example he gave of, like, there are three or four inventions that, like, all of a sudden if you were in, like, one of three positions, you were one step away from figuring – putting these pieces together.

So, I think, like, that’s – you know, it’s important to make those, like, those steps forward. And, you know, you just – it’s fine to not really quite know the solution to the problem, as long as you can have these kind of relatively short chains of problems that you think you can solve, or at least you know the vector that you need to solve along, right, because you’ll get there eventually. Someone will get there eventually. Even if all you do is move one step. If it was three steps were needed, well, then the next person only needs to do two, right? And like –

KEVIN SCOTT: Yeah. Another really good book along those lines is Arthur C. Clarke’s Profiles of the Future. And, like, this is the book where he articulated his three laws, like, one, everybody knows the third law, which is any sufficiently advanced technology is indistinguishable from magic.

But the point that he was making in that book is that it’s very hard with high precision for anybody, no matter how smart they are or how good they are as a futurist or a scientist or an engineer, to predict exactly what the future is going to be like in 20 or 30 years. And, you know, he had some practice with this because he was a science fiction writer in addition to being, like, a really quite a good engineer.


KEVIN SCOTT: His framework for looking at the future is, like, you know, don’t try to make very specific predictions about the future. Like, make predictions about what the shape of any possible future must be, like, where the progress trend’s going, like, what is going to have to be, like, a set of things that will be true in the future, and then sort of direct your effort, like, to your point, along those vectors.

Yeah, you could not have predicted when we were – you know, even when you and I were in college, that we were all going to be carrying a smartphone around in our pockets. Like, it’s… I think of smartphones, right, are even, like, a little bit crazier than the, like, Tricorders from Star Trek.

SAM SCHILLACE: Yeah, and, like, in that era, I remember the Cray-1 was, like, the hot computer. And I think that’s about as powerful as, like, an iPhone 4 or something like that, you know. So, you know, like, even if you knew Moore’s Law intimately and you like math and did the math, like, you still don’t have a visceral feel for how much that’s going to change the world, right?

KEVIN SCOTT: Yeah, but you just named the trend. So, the trend is, like, you have these exponential progress curves on the price of compute, the density and the density of compute, the, like, energy density of batteries, like, the transmission in receiving bandwidth of wireless communication. And so, like, all of these things are sort of inflecting up. And so, if you look at all of that, like, you may not predict Android or the iPhone, but something’s going to happen there.

SAM SCHILLACE: One of my favorite things right now is the learning rate thing, right? Like, we understand there’s about an 18% generational learning rate with solar panels and about a 6% generational learning rate with batteries. Every time you double the deployment, you get that percentage increase in efficiency. And, like, you know, it seems kind of funny, like, where did that come from? But if you look back, like, literally, like, 40 years, you can see it.

And I was just talking to my wife yesterday about EVs, and we’re looking at, like, buying an EV. And I remember when the Tesla came out, that was, like, six generations of batteries ago. Originally, like, the 300-mile range that everybody wants was really hard to achieve. And now, all of a sudden, like, every EV that’s out there has a 300-mile range. And you’re like, wow, like, did they all get smarter or whatever? Like, well, no, kind of they did. But, like, also, batteries just got way better because there’s a baked-in learning rate. And so, you know.

And you look at a lot of climate, like, alternative energy and climate change. Like, I still think people don’t fully factor this in, that, like, solar is going to just keep getting better. And, you know, all these – wind has another – wind I think is 12%. You know, you can see the learning rates in a bunch of these technologies.


SAM SCHILLACE: So, like, you just – that trend is durable for a while.

KEVIN SCOTT: Yeah, and you get to the point where, at a certain level of scale, you – you just get much broader participation in an ecosystem than in the beginning. So, it was sort of an elite thing, you know, like, elite – elite engineering schools and, like, just a very small handful of companies could have even conceived of building something like the Tesla Roadster when, you know – like, when – when Tesla really started getting going.

Today, like, you know, I was hanging out with someone the other day where, like, they’ve got two classic cars they’re converting into EVs right now. And like, you can buy all the components offline, the motors, the inverters, the power management systems, the – like, all the components in the car talk over this car area network that’s standardized. Yeah, like, not everything is great, but it’s almost like the early days of the PC ecosystem where you just sort of buy a bunch of stuff, build your own PC. Like, you can buy a bunch of stuff, build your own electric car.

SAM SCHILLACE: Yeah, you can totally see this coming. I also like to talk about one of our favorite subjects, too. I think this is going to happen right now with AI. I think this is, like – I have the same sense, you know, I’ll kind of pull all these threads together. Like, I have exactly the same sense of imminent disruption and that kind of uncomfortable pit in your stomach when you know something is going to happen and you have to do the heavy lifting engineering for it, about AI.


SAM SCHILLACE: And I think, you know, we’re – I think we’re at the cusp of a fourth transformation, right? So, like, PC, the Internet and mobile were these three transformations where a lot of activity became suddenly accessible to computer programming, right? And I think that accessibility or legibility, however you want to describe it, is, like, the core thing, right? Once, like, an area of human activity becomes accessible to software in some way, you get these explosions of businesses and value.

You know, we got all the stuff that the Internet gave us and then the mobile let us take it out into the real world. And, like, every stage, like, the businesses got bigger, the value got bigger, got more ubiquitous. And I think AI is going to take this into the cognitive realm now.

All this stuff that’s cognitive, like natural language, and object recognition, and video and just reasoning about the world is now becoming very accessible, not to programming in, like, the large scale, like, oh, we’ve got these large models to do that. So, but programming in the sense of, like, I can give it to, like, a guy who’s, like, the guy building or gal who’s building the car, you know, and, like, they can snap pieces together and build interesting things out of it. And that, like, accessibility to folks and of these cognitive – like, I think that’s going to be hugely transformative.

And I suspect people listening to this, half of them are rejecting that out of hand. Like, it’s – you know, here’s the why not. Like, it’s happened before. It’s really hard. I don’t like that. People, I don’t want people to be out of jobs, like, all those reasons.

KEVIN SCOTT: It’s too expensive. It’s dangerous in these ways.

SAM SCHILLACE: But like, we’ll solve them. Like, we’ll solve those, and the what-if is amazing.

KEVIN SCOTT: We will, yeah. And – and that is the thing. I – I wrote an essay in… like, I published in the March issue of Daedalus, which is the Journal of the American Academy of Arts and Sciences, where the framing that I was proposing for thinking about this stuff is just sort of cognitive work, and, like, thinking about AI as a set of tools that we’re developing that will help us with our cognitive work, like, the same way…

And, like, we had a whole – in the Industrial Revolution, like, you had this big set of changes that were happening with physical work. And so, the practice arrived a little bit before the theory, but the theory came that you had thermodynamics. Like, you have very precise definitions of what physical work was. Then you had whole engineering practices that developed around it, and, you know, it is just ubiquitous in the industrialized world. Like, I think that’s the kind of transformation that we’re about to go through.

SAM SCHILLACE: And I think, like, similarly to that, like, you have – there’s this process we need to start of, like, unlearning some stuff, right? Like, we had to unlearn what work meant and kind of relearn it for that process. And I think we’ve spent 40 years convincing ourselves as computer technologists that we have to do a bunch of work for the computers. Like, we have to build a schema, and we have to put things in a form, and we have to, like, structure data in certain ways.

And, like, it was true. We didn’t have the tools for that, but now we do. And now, we understand how to deal with messier stuff. And we don’t – like, we don’t have to have forms. We have classifiers instead and we have things that have judgment, and we have things that can synthesize, synthesize.

KEVIN SCOTT: Well and there are even some more subtle things. So you, as a trained mathematician, and, like, both of us, as practicing computer scientists and engineers for, you know, a handful of decades, part of our job is, like, we wield these, like, big stacks of abstractions to go solve problems.

And like, part of the reason that we need these stacks of abstractions is, like, you can only do so much with the brain that you’re born with.

SAM SCHILLACE: The brain yeah.

KEVIN SCOTT: And it’s almost, like, the abstractions are a compression algorithm to allow you to, like, go approach problems and, like, you know, just sort of fit all of these tools inside of your head.

So, a lot of people, I think… So, you know, a lot of people, I think, think that mathematics itself is sort of this, like, universal thing, that it’s like a necessity of the universe. And, you know, Ted Chiang, who wrote the short story that became the movie Arrival, I think, sort of pokes at this in a bunch of different ways.

Like, you know, mathematics may be more about humans than it is about the universe. And when you have a tool like AI, that’s a way to, a different way to do a whole bunch of cognitive abstraction, you can sort of get after a bunch of problems that we solved – used to solve with mathematics that you’re now going to be able to solve in a different way. And, like, that will be uncomfortable.

SAM SCHILLACE: Yeah, it’s really interesting. Like, one of the most fascinating things about AI is less that it thinks like us and more that it doesn’t, right?


SAM SCHILLACE: That’s the interesting – like, it thinks as well as we do, but in a different way. That’s fascinating, right? A lot of that, like, you know, the deep, deep dream stuff, you know that just, like, blows your mind with some of these weird ways they’ll produce images or just knowledge – it’s just really interesting, like, what comes out of these, right?

KEVIN SCOTT: Yeah, and even what you said. Like, we’ve got to get new vocabulary for talking about it because, like, in a sense, it doesn’t really think at all. Like, when you say “think,” you are thinking about what we’re doing right now. You have a – you have this cognition that’s running on your brain, and, like, it is a different qualitative thing than what a model does.

SAM SCHILLACE: Well, it’s interesting. This is going to get too abstract and too deep for us to dive into, but, like, to some degree, like, our brain is a bunch of these networks, right, that kind of are strung together in a certain way. And what we’re doing is making new ones external and also kind of folding them into the mix, right? So, it’s… just defining what ‘to think ‘means is challenging all by itself, right?


SAM SCHILLACE: Like, you know, we have this, to your point, very particular sense of what that combination of networks means, right?

KEVIN SCOTT: Yeah. And look, there’s just a bunch of things that you’re not going to be able to get a machine to do. I wrote about this in my book, and it started as a dinner conversation I was having with a – you know, with a bunch of people. Like, it’s one of those weird dinners, like, it was Yuval Noah Harari who wrote Sapiens was there and, like, bunch of other people. And we were you know, we were talking about some of this stuff.

And I made this assertion that I believed at the time that this group of people made me rethink, which is like, oh, I don’t think that a machine will ever be able to compose and perform music in a way that gives me the same emotional response that, like, Murray Perahia gives me when he is performing Chopin’s G minor ballad. And they were like, “Yeah, why do you believe?” And like, they just sort of pushed back hard on the assertion.

And, like, they probably were right. Like, you could build a system, I’m guessing, that would produce music in a feedback loop, like you could sort of put a bunch of EKG probes on you and, like, you could probably have the system in a closed feedback loop give you the same, like, autonomic response, like, the – you know, the shivers up your spine or goosebumps.

But, like, that, to me, still is qualitatively different than, like, what I get when I listen to this performance because it’s, like, this – this human composer from a different time who was, like, trying to communicate something to everyone else. And then this performer from another different generation and a set of experiences who takes this work and interprets it in a way that no other performer interprets it that produces this emotional response in me.

And, like, part of the beauty of that is that, you know, it’s this stacking of human connection that has nothing to do with –

SAM SCHILLACE: Oh, of course. Like, of course, like, the definition of that is I want to stack a bunch of human connections up. Then you can’t do that if there’s no humans in the stack, right? Like, of course not, by that definition.

One of the things I really like, though, is somebody – I forget who gave this example. Someone who was talking to a bunch of students, and they said, “Do you think it’s possible to build a computer that’s roughly the size and shape – roughly the size of a human brain with all the capabilities of the brain.” And the students, you know, mostly said, “No.” And then he said, “Well, what did you use to come up with that definition? You used a computer that’s roughly the size of the human brain with the capabilities of the human brain,” right? So, it’s like, there’s a little bit of tautology in there of, like…

To your point, though, it depends on, like, the definition. Like, I think you’re right, like, there’s… You can’t replace humans by something that’s not human definitionally, right, like, if part of the meaning and the emotion is about the human connection.

KEVIN SCOTT: Well, and look, I think the single most important thing for people to get through their heads is, like, it is not necessarily a goal of the AI work, certainly not the goal of the AI work that we’re doing or that I’m doing, is to replace humans. So, you even look at something, like, GitHub Copilot. The reason that you build an AI that helps people turn natural language expressions of a thing that they want code to do into actual code is to help you, you know, be able to get to the more important parts of your job more quickly.

SAM SCHILLACE: Right. We did get a very nasty letter early on in writing – doing Writely from the Medieval Scribes Guild, saying that we were replacing scribes by doing this word – newfangled word processor thing. I’m kidding, but like, you know, of course, like, nobody cared, right? (Laughter.) Like, we had long since replaced them and we understand that people need to write their own stuff, and it’s awesome, right? And it makes you better. Like, the tool makes you better as a person, makes lots more value in the world, which is what’s going to happen with these tools, too, right? It makes everybody better.

KEVIN SCOTT: It just unlocks creativity. It does a whole – it does the thing that all of these tools eventually do. And, like, the trick is just sort of managing the transition, I think.

SAM SCHILLACE: Right. Right, absolutely.

KEVIN SCOTT: So, we are at time. I could go on more.

SAM SCHILLACE: I knew we would not through any of our – all of our questions, man. Like, I knew it was going to be like this.

KEVIN SCOTT: I do have one last question. So, I ask everyone on the podcast at the end, outside of their work, and most of the people we talk to, their work is a thing that they find fun. But, like, outside of the things that you get paid to do, like, what do you enjoy doing in your free time?

SAM SCHILLACE: I do lots of different stuff. I like – I’m kind of a maker as, you know, as you are. I got really into fountain pens for a while and making fountain pens. I got really into old time music – I play mandolin, bluegrass mandolin and Celtic mandolin and old-time mandolin. So, I go hang out with people. That’s really been fun. I took a mandolin with me all over the world. It’s a little travel mandolin. So, I played bluegrass on a stage in Tokyo, and played bluegrass with some folks in Sydney and played actual Irish music in Dublin. So, that’s super fun. I mean, it’s just it’s all kind of connected to me. I like cooking, I like making stuff. I kind of like getting into the world and doing things.

I have too many hobbies, actually. Like, I could answer that. I could spend an hour on that question.

KEVIN SCOTT: Yeah, I reject that assertion. I don’t think that there’s anything – (laughter).

SAM SCHILLACE: (Laughter.) You and I have that in common.

KEVIN SCOTT: Yeah, there’s no such thing as too many hobbies.

SAM SCHILLACE: But that’s, yeah, you know, you got me going on leather working recently, so that’s kind of…I’ve got a pile that I look at guiltily every once in a while. I think I should do something with that.

KEVIN SCOTT: Oh, you should totally do something with that. (Laughter.) Cool.

Well, thank you so much for taking the time to chat with us today. This has been a great conversation, and I’m happy to have you on the show.

SAM SCHILLACE: A lot of fun, yeah. Yeah, super fun. I’ve been – had been looking forward to it. So, it’s great.


CHRISTINA WARREN: All right, that was a super fascinating conversation with Sam Schillace. So one of the really interesting things you were talking about, you know, you’re getting into AI, and one of the things that was said was like that, AI, what’s so interesting about it is that it’s not that it thinks like us, but that it doesn’t, could you expand a little bit more about that?

KEVIN SCOTT: Well, I mean, one of the things with AI, is, we’re just seeing it more and more over the last handful of years is being an assistive tool, like a thing that helps us with the things that we’re just not great at. And, you know, this has been sort of true with most of computing technology. You know, CPUs are better than human beings at arithmetic, like their computer algorithms are better at dealing with certain types of complexity than human brains are. And like, this is certainly true with AI. There are things about human creativity, and like intuition, and, you know, all of these things that we actually take for granted, that are very hard for AI systems to do. Whereas like, there are all of these things to do with complexity that AI is getting increasingly good at doing. And so the thing that I think we ought to be doing over the coming years is like just sort of leaning more and more into those differences than trying to, you know, build things that are exactly like a human brain, because like, basically, what we want to do is build these tools that can help us offload all of the repetitive, irritating cognitive things that we’re doing. So we can go spend more time on the things that are uniquely human and special and rewarding and fulfilling.

CHRISTINA WARREN: Yeah, no, and you kind of you, you’re mentioning, like you wrote a journal article, kind of to the same point, right?

KEVIN SCOTT: Yep. Yeah, I mean, so the journal article was, in the American Academy of Arts and Sciences did a special issue on AI and society. And my article was on a framework for thinking about AI as a tool for assisting us with cognitive work. You know, the same way that steam engines and you know, sort of mechanical devices in the 18th and 19th century were ways to, new ways to assist us with physical work for like, you know, picking heavy things up, for moving heavy things from one place to another for doing this sort of rigorous heavy mechanical work over and over and over and over again. It is, essentially AI is a new type of steam engine, and like we don’t quite understand everything that it’s doing yet the same way that we were inventing these machines before we had the physics of thermodynamics. Like we’re slowly figuring out exactly what the science of cognitive work is and like how you measure it and how you sort of see whether you’re making progress towards making it better and better and like you’re building the right machines to go do it. But you know that that is I think the right framing for thinking about it. It’s like, they’re just tools like GitHub copilot, for instance, it’s just, it’s just a tool, like you know, instead of having to go look up a whole bunch of stuff, like you just sort of tell the machine like what you’re trying to accomplish, right? Like it, it writes some code for you.

CHRISTINA WARREN: Right, right. It’s just a tool. I mean, that’s why it’s called the copilot. It’s not, you know, the pilot, it’s not doing it for you, it’s assisting, you know, you’re exactly right. One other one kind of final thing I wanted to touch on, you know, Sam kind of mentioned, like, he feels like we’re on like, the cusp of like, kind of like this, this big fourth, kind of, like wave of advancement. And, and he can be, like, you know, it’s sounds like he can just like taste like where we’re going to be. Are you on the same wavelength with that?

KEVIN SCOTT: oh yeah, very, very much. I am more excited about where we are, and where we’re likely to be over the next handful of years than at any point in my career as a programmer and computer scientist, and like, I’m 50 years old, I’ve been doing this for…I almost sound like my grandpa. Now, I’ve been doing this for almost 40 years. Now. Like I wrote my first program when I was 12. And, yeah, so like, I’ve lived the three big revolutions that we’ve had. So yeah, this transition from computers being scarce, right? Like how everybody has one. And I went from information being scarce, to you have the internet and information is no longer scarce. And, you know, you went from computing being, you know, sort of physically tethered to being like, physically ubiquitous, you know, your smartphone. And I think, you know, what we’re about to have happen now with AI is like another transformation where the thing that’s hard right now is technology is brittle. It is super challenging. To use still, like things crash, like user interfaces are complicated, like, you know why? You have to like, have five programs come together, or five apps to like, do the thing that you want to do. And I think very soon now we will have copilots for everything. Yeah, you will have AI that can just sort of listen to you and hear what it is that you’re trying to accomplish, and then can do all of that management of complexity for you to get your thing done.

CHRISTINA WARREN: No. Yeah, I mean, I think it’s exciting. And I mean, I think, you know, Sam had mentioned this to like when you think about just how, if you even think just just holistically like how quickly all of this has happened, and how much quickly you know, how much shorter distance there is kind of between these different waves? Like, I think that that’s really exciting, too. So I’m glad that we have like people like we have people like you and Sam, who are thinking about these things, and are leading teams, and doing research and all this stuff. Because that gets me excited. Right. And I’m sure that it gets a lot of members of our audience excited as well.

KEVIN SCOTT: Yeah, it’s a it’s a good time to be in tech.

CHRISTINA WARREN: All right. So that is all the time that we have for today. Huge thank you to Sam Schillaci, for being with us today. If you have anything that you’d like to share with us, please email us anytime at behind the tech at and and you can follow behind the tech on your favorite podcast platform, or you can check out our full video episodes over on YouTube. Thanks for tuning in.

KEVIN SCOTT: See you next time.