Thompson: Yeah. That’s all this place does. It’s very hard to read. So you go off and you start reading the binding code. And then this code. And then the general IPC. That gets you a handle into where you can actually start reading stuff and understanding stuff. Before that, you can’t understand a thing.

Seibel: When you work on a team, what’s the structure that you like?

Thompson: Just working with good, compatible people.

Seibel: When you’re working with compatible people, do you favor strong code ownership: “I wrote this piece of code; it is mine and I’m responsible for it,” or more shared ownership: “We all own this code together and anyone can do what they see fit.”?

Thompson: I’ve always worked halfway in between. There’s somebody who owns it and if you have a problem with it, you mail them or tell them and their job is to fix it. And then at some point they disappear, they don’t want it, they don’t fix it, they’re not responsive—then you fix it. The catchphrase is, “You touched it last.” You own it. So it’s halfway between. You don’t have a bunch of people going in and modifying the code willy-nilly. It’s all filtered through an owner. But that owner can change pretty easily.

Seibel: These days there are folks who advocate pair programming, meaning two people working at one keyboard. Have you ever worked that way?

Thompson: Something small can be done like that. Very often I’ll be typing and somebody else, who will obviously be faster at it than I, will sit down and they’ll type and I’ll talk. I’ve done that on orders of minutes to hours, very few hours, to get one thing done that both of us could have done separately.

Seibel: And did you find that the result was better or it got done faster?

Thompson: The result isn’t better. Probably debugging is faster—as you’re typing, someone can catch a bug over your shoulder. So I think it will generate fewer bugs as you go. But I didn’t find it as a philosophy as a way to go—it just happens.

Seibel: Do you still enjoy programming?

Thompson: Yes. I like small programs. Small, meaning you can do it in a month. If you’re trying to do some monster task that takes a year, I can’t keep in it that long.

Seibel: Was that always the case, or have you lost the energy for longer projects?

Thompson: I don’t know. It depends on the actual thing. Something big that takes years, like an operating system, you subdivide that and there are lots of fun pieces, so that counts as multiple small things as opposed to one big thing. But there are lots of things that are just one big thing, and those I think I’ve always found difficult. I need gratification, feedback. And if you have to sit there and work and work and work for days, months and see nothing except a pile of code, then I have trouble doing that.

Seibel: You’ve mostly worked in research and it seems you’ve had a lot of latitude to work on what you like, but did it change when it become a job? Did it take any of the fun out of it?

Thompson: No. It’s always been fun, and mostly because I just selected what I wanted to do. And even when it was a job, back in college, there were tons and tons of jobs available. It seemed to me that there were tons of people who were doing something, whatever it is, and they needed some little programming task done on the side to aid them. So they were perfect for me. They were little tiny jobs that I could get into, get in and out in days and pick and choose which one I wanted to take.

I think my first one was a humanities professor cataloging Homer’s work. And he had The Iliad and The Odyssey on cards. He wanted word frequencies and counts—essentially statistical analysis of these two works. And that was fun. It was text processing, which just wasn’t done by computers in those days. So that was my first odd job.

Seibel: In a 1999 interview you talked about how you had told your son he should go into biology instead of computers because you thought computers were played out. That was almost ten years ago. How do you feel about that now?

Thompson: I feel the same. Nothing much new has happened in computers that you couldn’t have predicted. The last significant thing, I think, was the Internet, and that was certainly in place in ’99. Everything has expanded—the speed of individual computers is still expanding exponentially, but what’s different?

Seibel: Reading the history of Unix, it seems like you guys basically invented an operating system because you wanted a way to play with this computer. So in order to do what today might be a very basic thing, such as write a game or something on a computer, well, you had to write a whole operating system. You needed to write compilers and build a lot of infrastructure to be able to do anything. I’m sure all of that was fun for its own sake. But I wonder if maybe the complexity of modern programming that we talked about before, with all these layers that fit together, is that just the modern equivalent of, “Well, first step is you have to build your own operating system”? At least you don’t have to do that anymore.

Thompson: But it’s worse than that. The operating system is not only given; it’s mandatory. If you interview somebody coming out of computer science right now, they don’t understand the underlying computing at all. It’s really, really scary how abstract they are from what a computer is or even the theory of computing. They just don’t understand it.

Seibel: I was thinking about your advice to your son to go into biology instead of computing. Isn’t there something about programming—the intellectual fun of defining a process that can be enacted for you by these magical machines—that’s the same whether you’re operating very close to the hardware at a very abstract level?

Thompson: It’s addictive. But you wouldn’t want to tell your kid to go into crack. And I think it’s changed. It might just be my aging, but it seems like when you’re just building another layer on top of another layer on top of another layer, you don’t really get the benefit of writing, say, a DFA. I think by necessity algorithms—new algorithms are just getting more complex over time. A new algorithm to do something is based on 50 other little algorithms. Back when I was a kid you were doing these little algorithms and they were fun. You could understand them without it being an accounting job where you divide it up into cases and this case is solved by this algorithm that you read about but you don’t really know and on and on. So it’s different. I really believe it’s different and most of it is because the whole thing is layered over time and we’re dealing with layers. It might be that I’m too much of a curmudgeon to understand layers.