Code Complete with Steve McConnell

I thought this book would already have been written by someone and I wanted to see this book so that I could use it as material for an article. In my mind, I was going to write a 250 page book. So, for the first time, I thought since I'd never published anything, I should probably make it look like I knew what I was doing. And so, I created a detailed plan for the book and estimated the page count of the book and it came out to be 900 pages. >> Code Complete is a single bus book on code construction which includes coding, debugging, detailed design, testing, and many more topics. It's also the most detailed one with an impressive 900 pages. The second edition of the book was published in 2004 and 20 years later the book remains a bestseller in software engineering. I sat down with the author of the book, Steve McConnell in Seattle. In this episode, we get into the history of writing code complete and how the publisher did not expect the book to sell well. The difference between software construction and coding. Steve's mental model of career development for software engineers and why he considers the concept of lily pad hopping harmful. The impact of AI on software engineering topics that Steve left out of code complete but now talks about in-depth and many more. Steve rarely gives interviews so I hope you enjoy this special one. This podcast episode is presented by Statsig, the unified platform for flags, analytics, experiments, and more. Check out the show notes to learn more about them and our other season sponsor. If you enjoy the show, please do subscribe to the podcast on any podcast platform and on YouTube. Steve, welcome to the podcast. It's so good to meet you in person. >> Yeah, thanks for having me. >> So, you wrote this book, Code Completed, and I'm going to show it here. I was amazed when I first got my hands on the physical version on how long it is, how extensive it is and and how thorough it is. And the other big surprise I had, I assume that whoever wrote this must have been a really seasoned tech professional, you know, working 10, 20, probably 30 or 40 years, but I learned that you wrote this somewhat early career. How did you write it? And why did you even come up with the idea of writing such a massive and extensive book? >> So I didn't start out to write a book. I started out to write an article and I'd never published anything. And so I thought uh I I'd wanted to I'd wanted to write and I thought about writing all different kinds of things and I was active as a programmer so I thought write about what you know and uh so I started doing research. I'm a good researcher which is funny in today's context but back then that involved going to a research library and looking through a card catalog and requesting materials through inter library loan. I mean it's quite a different process and uh and so there was actually some skill involved in that. So basically I thought I thought this book would already have been written by someone and I wanted to see this book so that I could use it as material for an article and uh so I I basically just started doing research and after reading about I think I read about 80 articles and a handful of books I convinced myself that this book didn't exist and this was just baffling to me because there were books on requirements design testing project management But there wasn't a book on the main thing that programmers do, which is software construction. And so I just kind of shifted gears and I I didn't set out to write a 900page book, which was the first edition. I I I thought, you know, it's funny because in my mind, I was going to write a 250 page book because all the other books I'd read in that space had been 250 to 350 pages. And so I did background research. I wrote a couple sample chapters. I got ready to submit my proposal to the publisher. And at this point, I only had two chapters written. And so the f for the first time, I thought since I'd never published anything, I should probably make it look like I knew what I was doing. And so I created a detailed plan for the book and for the first time uh estimated the page count of the book. And it came out to be 900 pages. And I thought that can't possibly be right. I'm not writing a 900page book. I'm writing a 250 page book. And so I estimated it a different way and I came up with something like 875 pages. So I thought, okay, I think I'm writing a 900page book. I think the thing about that is that if I had thought a year earlier that it was going to be 900 pages, it never would have occurred to me to even try and uh but by that time I was too far into it. I was mentally and emotionally committed and so I decided to just go ahead and do it. and just help us imagine what stage of your career were you, you know, like in terms of work experience, college, those kind of things. >> So, I was about 5 years out uh 5 years out uh of college at that point. Uh I'd been programming professionally for you could call it six years I guess because I took some time off in the middle of college. I actually think that was the perfect time to write the book because I think it's really important in writing a book to have a really clear sense of the target audience. And for me, my target audience was me 5 years earlier. And it was recent enough that I could still remember where I was 5 years earlier and what I didn't know 5 years earlier. I think for somebody who was 20 or 30 years into their career, it'd be really hard to know. Plus, you'd just be out of date in terms of what you needed to know. after the book came out, what was the impact of it? Do you remember like initially and then a couple years later? >> Yeah. The um so the book came out and it started to get really good reviews and at that time the reviews of course were in magazines which people got in the mail on paper. >> This is pre Amazon. they trickled in way pre- Amazon and uh and so the reviews were great and I attended a book signing here in Belleview and one of the people from Microsoft Press came in and said uh said, "Oh, this is our sleeper uh book." And uh I learned that they never expected it to actually sell very well. That they decided to publish it because they thought it would be good for the catalog to have a more scholarly uh in-depth book, but they they assumed it wouldn't really sell very well. So uh the sales have been a nice surprise for everybody. >> You you must have learned about a really interesting inspiration the book had on the block called Coding Horror. >> Huh. I don't remember exactly when it was. It was I don't remember 2005 somewhere in >> there. Something like that by by Jeff Affwood. He he he started the blog or he re renamed it. I'm not sure. >> I think he conceived it from the beginning as coding horror. And he reached out to me and said, "Hey, I'm writing this blog. I want to call it coding horror. Can I have permission to use the coding horror icon from your book?" And I was like, "Yeah, sure." And I think he sent me a t-shirt or something with the coding horror uh image on it. And of course his blog did did really really well and uh you know led led to a lot of good things for him and I think had a positive impact on the world too. I >> I think at some point it might have been the most popular developer blog. He published about something like 100,000 requests per day. >> Wow. I >> I was reading it. So what when I was early career I read coding horror almost like every day or like you know every other day he published an article and then of course that led to stack overflow or or that helped him meet people Joel and and others and that led to Stack Overflow. So it's just kind of incredible how indirectly obviously but you know your book inspired someone else to to start a blog which inspired or or helped create this very special size Stack Overflow which Stack Overflow obviously now has has helped train some of the AI agents. So like it's just all trickling all down. >> Yeah. Well, I think uh you know, I don't know that I believe in karma literally, but I definitely believe in the general idea that if you put out good things into the world that there are positive ripple effects and you never know what exactly is going to happen, but probably more good things than bad will happen. And so it sounds like that's part of what happened with that. And so the book is on the concept called software construction. And and you know, you kind of start the book, I'll I'll quote a little bit from it. You you say at at one time software development and coding were thought to be one and the same but as distinct activities in the software development life cycle have been identified some of the best spines in the field has spent time analyzing and debating methods of project management requirement design and testing they rush to study these identified but it left code construction as the ignorant cousin of software development. I wanted to ask what is code construction? And I mean the book is about code construction but I think it helps us uh recap of and and how it's different to let's say software development or how it's similar to it. >> Yeah, I was pretty deliberate in the book in trying to capture the space of software construction and and a space that's distinct from writing code uh or not distinct from but is not the same as as writing code. Uh I think that the idea of just jumping in and coding is something that maybe you do when you're first learning how to program. Uh but as you get a little bit more advanced, I think there's a level of intermediate thought that includes thinking about how you're going to test what you're writing, thinking about how you're going to design in the details what you're writing, actually doing the coding and then the full set the universe of topics that come to bear on the actual code itself, the readability and the uh all aspects of readability. I think that that uh much of the literature before I wrote code complete there there were a couple things out there that were decent things on coding style uh but that was kind of it. It was coding style. It wasn't really about you know we had we had books on software design but the software design really stopped short of the level of design thinking that you would get into at uh what would have been at one time the the routine level and then later was really the class level. And it just seemed to me like there was just a lot of thought that wasn't necessarily guided or or necessarily taking place in terms of thinking about the uh activities that are adjacent to coding but not quite big enough to qualify for a book or a name of their own. And then just to be clear like like these thoughts are so clear like obviously we write the code but it's everything that encapsulates until I get something that is ready to to ship that is ready you know like clearly we have the planning or requirements or business requirements and then it starts from like me thinking about like how I'm going to structure my code as I build it. I iterate I I debug I check that it's it's it's running. I think about longerterm maintainment. These are all part of code construction. I I'm just like uh double-checking that I'm I'm understanding cuz I feel that code construction in in the book you you definitely cover it. But but since then I don't think we talk about code construction that much. >> I would probably make it a little narrower than what you just described. Uh I think that some of what you just described I would probably characterize as a higher level design. uh and uh but on any given project depending on how the project evolves or how it emerges the design level of thing it could happen at the beginning or it could happen incrementally as you go it could happen by somebody who is good at that kind of thinking or it could happen by the people who are actually doing the implementation I think one of my learnings over the years and I didn't really understand this when I wrote the first edition of code complete is really that different people's brain brains work differently and some people really are capable of thinking about design abstractly and then implementing the design and some people are really good at just writing the code and learning the lessons in the small and then building up from that and some people are good at both but I don't think a lot of people are actually good at both I think much more commonly you find people who are good at one or the other and then I think there's often a disconnect between the people who have ability in one area and not the other. And I've seen cases where people think that it's just not possible to work the other way because they're not able to do it and they just can't imagine that somebody else could be able to work that way and yet we've got all kinds of instance proofs of people working in both ways and having it work out fine. >> And then the two ways are like so just I understand is is one of like could you just spell out again the the two different ways of of working? >> You could think of it generally as top down versus bottom up. Mhm. >> Uh so you could think of it at word inductive versus deductive. Um I believe that most most programmers meaning the majority not like 99% but you know 51% or maybe 70%. I believe most programmers are pretty detail- oriented. And so I made a conscious design decision as I was writing code complete that I would write the book inductively. I wouldn't start out making a bunch of general statements and then demonstrate the specifics. I would start out talking about a lot of specifics and then build up to the general statements at the end. I just felt like more programmers than not were more oriented that direction. But what I didn't appreciate at the time I was writing that was how big the disconnect was and the idea that I think a lot of people just aren't capable of operating the other direction, whichever the other direction is. >> Steve was just talking about how there are different ways to get to a good design of a software system. Some developers do it top down, others do it bottoms up. But how do you know if a well-designed system works as expected in the real world? This is where analytics and experimentation are so important. And it's why companies like Meta, Uber, and others build complex experimentation systems themselves. These are far more advanced of what engineers at most companies could have access to until recently. That is when Static became available. 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Yeah, this is really interesting because you know for example these days at a lot of scaleups tech companies it's becoming increasingly expected of of engineers to start with a design document which is a software design document and when I work for example at Uber like we kind of operate like this but a lot of times it just feels like a nag like I know what I want to write which it kind of re makes me realize I think your point on some people up very differently they're always the same developers or engineers who wrote the code, did the thing, and they're like, "Okay, I'll I'll write a design document just to like check the box." But the code was already written and and at the time I tried to explain to these people, especially eventually I became a manager to some of these people like you need to start, you know, highlight your your your highle thing and I didn't appreciate at the time. I was like what? Because I guess maybe I I I am fine operating like this. I'm probably in this this first group. I didn't appreciate this until until now. Yeah, there's a great paper, really old paper by Dave Parnes called the irrational design process, how and why to fake it. And the the gist of the p so this paper is from I think the mid70s. I don't remember exactly. It was a really old paper, but the gist of the paper is that design is a sloppy process and nobody gets it right. It's not linear. You don't start out and march your way in a straight line toward getting a good design. And so number one, the paper sort of gave permission to experiment, try stuff, make mistakes, learn from the mistakes, iterate. But then then the paper also says the how the how and why to fake it part was at the end of that you describe what you did. And the description is not necessarily going to show you all of the mistakes and dead ends and so on. So it's going to look like it was a more rational process than it was. But um so I think both halves of that paper are are worth keeping in mind and it sounds like your experience would kind of bear that out that it's not even really possible to get it right the first time in most cases. >> Yeah. And I I I do sense that in the industry these days we've kind of forgotten a little bit about the the design or or or the iteration or even things like uh I I have to remember who who's who who said this. I think it was John Alistster Sterhout who in in his book on software design a Philadelphia software design his suggestion was design it twice because the second time you'll get a better design than the first time. These are just things that some people might still do but >> I would say three times but yeah >> and I'm serious about that. So when I was at Microsoft there was a programmer inside Microsoft who was famous at the time who was well known for rewriting everything three times. And the basic gist of it was if he had two weeks to do an assignment, >> he would spend the first six days coding and making all kinds of mistakes and not doing it very well. And then he just throw it out and spend the next three days rewriting it. And by that time, he would be applying all the lessons he's learned. Then he'd spend the last day or day and a half writing a third version and it would be perfect. And you know, if you think about your own experience, if you've ever, you know, this should never happen in theory, but it still happens where you've done a bunch of work and somehow you lose it. It gets deleted. You have a backup, whatever, right? Should never happen, but sometimes it does. >> And you think, "Oh, this is awful. I just spent a whole day working on this. It's going to take me forever." And then you rewrite it in 45 minutes. And as you go, you remember all the lessons that you learned and all the stuff you wish you'd done the first time. It actually turns out probably better than if you'd never lost it in the first place and had to keep what you wrote initially. >> Well, these days I think it happens a bit less thanks to get being everywhere committing. But I've had this earlier in my career and as you said, first of all, you blow up. You're like so mad like it it it I think it was a file loss or or deleted or or something like this. And as as you said, you're thinking, "Oh, it's going to be so much work. I don't even want to do it." But when I now remember the the same lesson >> I spent some time on the school board here in Belleview, and one of the surprising learnings I got from the school board was that one of the the best ways to build reading proficiency is to have kids read things they already have read. This repetitive reading uh builds confidence and and builds skill. And so I think you kind of apply the same idea to rewriting the same code you've already written that maybe there's a lost opportunity there because we're always trying to do something new and we don't often get the chance to go back and just redo the thing we just did. >> Yeah. And I I think this is one of the things where I wonder if we're talking a lot less about software design in the industry because we just ship once. We we don't even go back to rewrite the the whole thing especially with with web based software you know mobile is becoming that as a you can ship it you can change it anytime you know there there's a startups lean startups from from 2010 gave this concept of MVP minimum viable product you know it doesn't need to be good it just needs to be good enough >> and I guess the most mature companies which which hit so-called product market fit of product that works over time they will do a rewrite or maybe a second rewrite through a series of migration technology choices so they will get actually a better. But but that's kind of it. So I think this is a lesson we can probably all just consider. It's not a bad thing to rewrite. So your your career path uh we know that you wrote this book early career. What what was your professional development story up to the book and then after the book? What what happened after? >> Basically up to the book I had worked for a small insurance consulting company. I'd worked for a large briefly for a large insurance company. I had worked at Boeing on a defense project. I'd worked at a startup mode uh for company that was kind of doing a just a startup uh shrink wrap product. And then I was about to start working on the book full-time and I got an offer to go to Microsoft just initially for a summer and I thought h at the time Microsoft was the hot tech company and so I thought yeah if I get a chance to see what's going on inside Microsoft I should do that it'll make my book better. So I ended up being at Microsoft for a year. That was essentially my background. I'd also done I always had some kind of startup project of my own going throughout that that period. uh and you know I put a put a lot of time into those as well. I had started out being kind of interested in programming but not super interested in it uh notwithstanding the fact that I seem to spend a lot of my essentially hobby time on it anyway. Uh and so I started out just kind of thinking I wasn't really sure if I wanted to do this as a job. And then I thought well but I had a little bit of an entrepreneurial streak so I kept doing startup stuff in that mode. Uh, and I at some point in there I kind of switched over from thinking I don't know if I really want to do this as a job to thinking if I'm going to do this as a job I probably ought to figure out what I'm doing. And I I think at the time for the first couple years I had a little bit of imposttor syndrome because I didn't have a degree in computer science. I didn't know at the time that >> Oh, really? Oh, well, of course this was What was your degree in >> in philosophy? Yeah, I had minors in math and computer science, but >> uh but at the time less than half the people working in the field had degrees >> in computer science. That didn't change >> uh for a long time. >> Uh so I but I didn't realize that I that that was common. I thought that was unusual. So I I started trying to develop or acquire some skills so that I could basically be more more professional. Uh so I started going to user group meetings. cuz I had one friend who was as interested in the programming stuff as I was. So, we go to these things together and talk about them and and uh and then when I got the chance to be I I'd worked at Boeing and I was like, okay, I'm not seeing a whole lot here that really looks like qualitatively different professional programming to me. And then I got inside Microsoft and I thought, okay, I'm finally going to see what real professional programming looks like, >> the best of the industry, right? Like Microsoft back then was a bit like what Open AI is now or Google in like 200 I don't know four. >> It it was just the 800 lb gorilla and there was nothing else even close >> at the time and uh I don't know what percentage of all software share of the all market software share they had but it had to be a pretty high percentage. This was around the peak right around the wi windows and doss and and that era, right? >> It Windows was not really popular yet although that's what I worked on. Uh but uh it was sort of the it was sort of the the last phase of the DOSs era >> which was dominated beginning phase of Windows. Yeah. Yeah. >> And they weren't super dominant in applications the way they are the way they they are now. So I got inside Microsoft and what I discovered was number one the people were really really smart. So that was a factor. Uh and number two, you had like one person working on the printer device driver for one specific printer. And so the difference between that and my experience was my experience up to that point had been you're working for a company and you've got responsibility for figuring out how to get things to print, figuring out how to load and save files, figuring out how to display stuff on the screen. And it's like, oh, I've got like a whole person, not just on printing, but on printing to one device. So, I mean, that was a lot of it. It's just the the projects were broken down into much much smaller pieces and so people could put a lot more time into it. And then, yeah, they were really really bright. But qualitatively in terms of programming practices, you know, there wasn't really anything different than what I'd already seen. >> So, you you got into Microsoft, you you write the book. At this point, how did you think about your career? I think you you you you had a talk earlier uh which is not recorded, but about the the mental model on how you you viewed your career at the time and then figured out what next. >> At the time I wrote code complete, I was still trying to decide if I really wanted to be a programmer at all. And uh if you can believe that and uh and so I'd spent I spent a year full-time writing code complete but I'd spent two years doing background research before I spent the year full-time. >> So So you did research on like you had a full-time job and on the side you were doing and then you like took off time. >> I did. I took a year a year off. >> Wow. That did that not not look scary? Yeah. I mean, suddenly you were there with with with with, you know, like no job, just writing this book. >> Yeah, I really wanted to write the book. That was uh that was the main thing I wanted to do by then. >> And uh and I knew it was a big project because by then I'd figured out it was 900 pages. And uh with the 250 page that I've been carrying around in my mind, that could have been maybe a part-time, but 900 pages, I knew I needed to to take some dedicated time to do it. And I wanted to do it. I'd saved money and I could, you know, I could afford to take some time off. I had basically I was living a very low overhead life at the time. I didn't own a house. I wasn't married. I didn't have a dog, you know, uh so I could live really cheaply if I needed to, which I did. And uh so I spent about a year writing full-time. And at the end of that, uh number one, it was a terrific experience. At the time, I thought I felt like I'd gotten three years of experience in one year by writing the book. I I would I would say I learned so much more about what I was doing just through the process of the the the writing is only not not the main part of it. The thinking about what I wanted to write was the main part of it. But then I went back into hands-on programming role and I felt like, oh, this is great. you know, I like the writing, but I'm so glad I'm doing hands-on programming again because I was kind of sick of the writing at that point. By the time I published Code Complete, I was convinced I was never going to write another book. And uh because the end phase of that was just painful and uh so then I worked for a couple years and the memory of the pain faded and uh I was kind of getting an itch to write something again. And so then I wrote my second book, Rapid Development. And I kept thinking, I was going back and forth. I kept thinking, do I like writing better? Do I like programming better? I kind of liked whatever I was doing at the time better. It took me a while. Eventually, I realized I liked the back and forth. I like the variety. >> Um, but not the variety on a day-to-day, week to week, month-to-month basis. I liked having big blocks of time to concentrate, dive in, go really deep. So before I wrote rapid development at that point I was starting to think all right yeah I think this programming thing might be a good direction for me and maybe I am a little committed to the career and so I I started to think about where do I think my career should go and what do I want to do and so I have no idea how I came up with the idea but I created what I thought of as the career pyramid >> and I just I kind of organized the the software for universe into the base of the pyramid was all programmers like 100% of the programmers and my focus was on us and then the second level up was programmers who had maybe actually gotten a degree in programming which I had not and then the next level up was maybe advanced degree in programming or maybe written some magazine articles or were in a lead or manager position and so anyway the pyramid kind of went up to where there were just a very small number of people at the top who had a essentially a lif lifetime of significant contributions to the field. And so I thought, okay, just in terms of setting a direction, I'll just aim for the top of the pyramid. And it wasn't so much because I thought I wanted to get to the top of the pyramid. It was just more to have a point on the horizon that I could I could move toward. And uh and so I used that partly to guide what I did on the second book because I had a variety of books I I was interested in writing. And uh the the book that would have made the most sense after code complete would have been design complete. Uh I could have written it at the time but I felt like I would get pigeonholed as just pure tech guy if I did that. The other book I really wanted to write was performance optimization in Windows. Uh, which was a fun topic, but again it was a little bit too, you know, a little bit too uh, bits and bites. And so I decided to hop over and write something that was a little bit more management oriented. And uh, because I wanted to kind of triangulate on the top of the pyramid >> and then and by the way, this pyramid you shared with me so we'll also share. So, so people see I I I thought it was it's a it's such a good or interesting mental model that I haven't seen many people think and I really appreciated that you kind of zoomed out and looked like all right where am I where would I like to go how do I go there now as as as part of this you you mentioned again in this talk you mentioned the concept of lily pad hopping. >> Yeah. >> What is that and and how did you apply it to your career? Well, I think that the pyramid was in essence uh the antidote to lily pad hopping. And what I had noticed, I noticed it a lot more later, but even at the time, I'd realized that programming didn't really feel like a career. It felt like a job. And the reason it felt like a job rather than a career was I didn't get the sense that it was going anywhere. I saw people who'd work on one project and they'd work on the next project, then they'd work on the next project. That's the lily pad hopping part. But it didn't add up to anything. It was just different. It was kind of like difference for the sake of difference. And you know, they're probably learning things. They're learning a new business area. They're learning new technology. Uh, and you know, maybe that's interesting and stimulating. And there's some definitely some personal growth that goes on there. But I always felt like if I'm going to put the effort into learning something and growing, I'd like it to add up. I'd like it to accumulate. I don't want it to just be a bunch of different things that are all the same in a way. I really want it to be essentially more than the sum of the parts. And uh so part of the reason for me coming up with the pyramid in the first place was really just trying to think about okay, how do I get past this idea of I've worked on this project, I've worked on that project, I know a lot more stuff now than I used to, but I'm no more marketable. I'm really no more valuable. I don't have the ability to really contribute on any individual project or organization more than I used to have. So, how do I essentially build my skills in such a way that I become increasingly valuable as time goes by? You know, you're going to put in the same effort either either way. And so, it's almost back to the design question where it's like, if I'm going to put in this much effort, I can either have it add up to this or I can have it add up to that where that is a lot more than this. if I put some thought into it. So >> I really like this thing especially because as developers I think we forget or or software engineers that we have a lot of freedom on the job for example when I was a a manager to engineers if an engineer came to me and said on my team and said like hey I'm really interested in this area first of all if they said that I would be thinking how can I help them with that but even more so but sometimes that would be tricky to do or you know not as simple to say like hey I'm interested in this this this other project. I I'd love to work on it because I think it would help my skill set. So, if they kind of did the work to just look around, understand, you know, the limitations of the team, whatnot. Like my answer was like amazing. And I also thought, wow, this is a person who's really taking initiative. Let me help them because because as as their manager, I think, you know, I'm not sure if people still have the notion of like, you know, the like the boss who's uh who's something negative. Like, as a manager, you really want everyone to thrive. You want people to grow professionally cuz guess what? They'll have better output, more motivation. It makes your team better and as a manager that that's your goal. So I think the more people realize that you can think about where you want to go even at the workplace you can almost always make some of it happen if not all of it. >> I think that's right. I think uh you know there's the there's saying that most people live in a box that they build for themselves. And uh and then Larry Constantine, who's one of the founders of structure design, if that term even means anything, had a saying that I like, which he says, "Nobody needs to give you permission to do your job well." And and the correlary to that is your managers already think that you're going to do whatever needs to be done to do your job well. They they assume that you believe that you have permission to do it. Meanwhile, on the ground, a lot of people live in that box they built for themselves and they think, "Oh, I got to do this the same way that they did it last time." There's no reason they think that. It's just I guess it's human nature for people to just kind of constrain themselves that way. So I think you're absolutely right that in the vast majority of software jobs that I've ever been aware of, people can design a lot of their own job or their own day-to-day work in such a way that they can learn a lot and grow a lot in a in a more strategic way. >> And I think this is just becoming it's starting to become more of a baseline expectation. Just the one thing I noticed is when we were hiring people at Uber. At Uber, we had the we had a culture that was very startupy, experimental. We we had a saying, be an owner, not a renter, you know, do what needs to be done. >> And I have people who joined from like consultancies, uh, places where it was common for the client or someone to sign tickets to them, for example, Jira tickets, you know, and they would work on they it got used to they they weren't really allowed to go and ask questions. It was kind of like don't question it. And so when some of those people came over, they found it really hard to adjust because they were like, "Oh, you know, what tickets should I sell?" And I was like, "Well, like, don't tell me you you you tell me." But it's it's interesting how how there that's the first time I saw that there was a divide where people at some point in their career, they got told, you know, like this is the box, stay inside the box. >> And then they found it really hard to, oh, I I can actually Oh, there there's nothing here. I can I can actually go outside. my first summer job that I got paid for programming as an internship and uh I basically finished all the work they had for me halfway through the summer. So, they had to make up stuff for me to do. And my boss gave me the assignment. He just handed me a box of floppy discets. You have to put up a picture so people know what those are. Oh. >> And and he said, "I want you to do something useful with this box of discets." And my response was, "Well, what do you want me to do?" and he said, "I don't know what I want you to do. Part of your job is to figure out what I should want you to do. So, you take this away and, you know, do something useful with it." And at the time, I was incredibly frustrated. I felt like the boss wasn't delegating anything to me. He wasn't giving me clear direction. I really felt like he'd sort of abdicated his responsibilities as a boss. But as the years went by and certainly by the time I started my own company, that was basically the model for 99% of my day, which is nobody nobody when you're the owner of your company tells you what the next most useful thing to do is. You got to figure that out. In fact, it's really mainly your job to be the one who's looking at the whole landscape and saying, "What do I do next? What's the next most useful thing to do?" So, yeah, I I completely uh agree with that and identify with it. And it's funny how as a junior person, you can feel like the ambiguity in that assignment is a real liability, but really that's incredibly valuable training for what you deal with as you get into higher positions of responsibility. And when I say responsibility, I'm not just talking about for people. I'm talking about product direction, health of the organization, uh, all kinds of stuff ju just to to see how it how baseline is. you know, like at I didn't know if we were exceptional or not, but just a few weeks ago, I talked with someone at OpenAI about, in fact, I talked with the head of engineering at OpenAI, and you know, they're now one of the hottest companies right now, a bit like how Microsoft was in in the the '90s or Google later or maybe Uber Uber even at some point. And I asked the the head of engineer like how are you structuring, you know, like your team's engineers, etc. And he told me something interesting how like they don't really have roles anymore because they actually have some of the designers write code obviously with the help of of of AI some of the engineers like do the product requirements or even do design and it's all all becoming really fluid and he said that the model they follow is you know everyone should pick up both what they think is the most important thing to do and so suddenly what used to be a pretty like well- definfined role of software engineer product manager designer. They're all kind of murky. I mean, people still have their expertise and this is one of the most innovative companies right now. I'm seeing Sar do more and more of this. They're now calling it actually a product engineer, which means you are a software engineer. But your job is not just to write code. Your job is to understand what we do and then, you know, build solutions for the most pressing problems. And now it it is spreading across more and more startups are like only hiring for these folks. And if you're used to, you know, being told what to do or you're looking for it, they'll be like, "Yeah, sorry. We're we're we're not looking for these types of folks. >> Yeah, we just talked about how OpenAI works differently than many companies even in the roles they have. One other thing they're different is in the tools engineers at the company used to get things done. They use linear who are the season sponsor of this podcast and a big reason for their choice was the need to harmonize all the different ways their product team was working. Picture this. You're an engineer working on a critical project. You need to coordinate with another engineering team on a shared dependency. But here's the problem. Your team tracks work in Jira. They use GitHub issues and the product team writes specs in Google Docs. Every handoff requires you to translate not just the work but the entire way of thinking about the work. This slows you down massively. One OpenAI engine described as an archipelago where each team is on their own island using their own language which sounds funny but from my experience at Uber it's super accurate. So their switch to linear was driven by the need to establish a shared vocabulary between teams. Every project now follows the same life cycle, uses the same labels, moves through the same states. When an engineer from one team needs to understand what another team is working on, they don't have to learn a new system or decode different workflows. Their usage of linear in this way is how they can move so fast despite being quite a large company. And to close, Linear is just so simple to use. Their team needed no formal training. Try it for yourself by heading to linear.app/pragmatic. Well, what comes to my mind when you say that is I think companies go through uh maturing process. When I say maturing in this case, I'm not even saying more mature is better than less mature. Sometimes less mature is better, but you have certain personalities that work well in startup mode and you have other personalities that work better as you get into slow growth or sustaining mode. And so what you described I think is just is great when you've got most of the staff that's self-motivated, self-driven, and they're part of something exciting and it's growing and they're probably young and they're probably hired directly out of school or a couple years out of school. There's a lot you can do in that mode. As the company gets bigger, as it gets installed client-based, as companies start to other companies start to do things that rely heavily on the reliability, not just the innovation, but they they need different things. They don't they no longer need what's latest and greatest and coolest. They need the thing to work the same way it did yesterday because they've made assumptions that depend on it. Then you get essentially you're calling for a different kind of staff to work on that. So, as time goes by, some of the staff that were the biggest contributors early on get bored and frustrated with all the restrictions and they leave and then all that uh ambiguity or flexibility in the roles and stuff. Uh that's no longer a positive. And so my prediction with the scenario you described is that 10 years from now that organization will need what my company called a roles and responsibilities workshop because it's just so common that you start out in a way that that works. But you get to a point where as things scale up and as the character characteristics of the staff change, it just doesn't work anymore. And uh and so you just need to be a little bit more explicit about about it. And I think these, you know, these are all just natural pendulum swings that happen as time goes by. And it's not that one is better or worse than the other. It's really fit for purpose which in startup mode you know having a lot of bureaucracy in startup mode is a great recipe for never getting started. Uh but adding the right kind of bureaucracy at some point becomes necessary to sustain a an organization of of a larger size. I think I think you're very much right especially because it is popular now obviously I also talk with a lot of basically startups sometimes their scaleups are larger but they're still very young growing especially on AI it's it's a it's a new new topic and if you look at companies there's this joke that goes in the tech industry that eventually every company becomes IBM and now like when you look at Google in some ways well they're behaving awfully a lot like IBM used to but if you look at Google is now 30 or well it's going to turn 30 years old. It's a massive business. It has 100 200,000 people etc. Like as you said, the things don't work. And one model I've heard which I I don't know who to attribute it to, but there's the pioneer settler and citybuilder. Yeah. >> Which which also is one variation of what you said. >> And then I'd add age on top of that. When I was at Microsoft in the early 90s, the campus age was aging8 years per calendar year. And so when I was at Microsoft, I was 27. Average age on campus was 27 point something or 26 point something. I was about half a year off the average age on campus. And and that's average. That's not median. That's average. And so if we got one guy who's 60, you need a lot of guys who are like 22 to get the average down to 27. And uh so the average average, you know, misrepresented how old the campus was really. It was probably younger than younger than >> the media must have been younger. >> Yeah. So, and there were when I was there there were about 15,000 people total and the dev staff was about 2,000. So, but aging 08 demographic years per calendar year. Fast forward 15 years, now the campus is 40, not 27. And now people have got houses and they've got kids and they've got spouses and you know it's just all this other stuff that's more on the kind of technical technology code base customer base. There's all the business stuff but I think the demographics of the staff matter and and the reality is the people in the company age as the company ages and and that has some pretty big uh pretty big impacts. >> Yeah. And some of the companies that have been the hottest and fastest growing startups of all time. I'm thinking of Amazon, of Google, of Meta, you know, like their their CEOs and their staff is now, you know, they used to be 20 when they started or even I think Facebook 19 something like that. Now they're, you know, 40 45 50 as as as you say, it's it's all it's all growing with it. >> Yeah. >> It's good to keep in mind. Now also in this uh kind of career advice uh talk that that you did you you outlined three areas that you've noticed that software developers should become proficient in technology knowledge business domain knowledge and software best practices knowledge in your experience like how important are these and how how can you get good at them and and if if you had to you know take a stab at which ones are becoming more important as a developer is getting more experience which in your experience which one was, you know, like one more important either for you or the people you work with. >> They all matter to some degree at all times. Uh if you're a junior developer, you're not very good at all of them or any of them, but you're probably the strongest in the technology area. uh if you're a little bit less junior developer, you know, you maybe you've worked for the same company for uh five years, then you could be pretty strong in the software best practices or pretty strong in the business in addition to being pretty strong on the technology side. I mean, five years is a long time in the software world. At some point, the vast majority of software professionals I've ever met, they end up concentrating in in one area or another. And so I think the most careerlimiting unless you're in just a super techy organization is to just go all in on the technology side. There are some places where that's going to work, but it's that's the exception. Uh going all in on the business side is a really good background for moving into more of a like company level architect role. You understand how the different pieces fit together for both the technology and the business. you're able to make technical decisions on a business basis and not very many people are good at that and so I think that can be that can be super valuable useful career path. The best practices path which is my path is actually probably a little bit more limited in the vast majority of companies. It's less limited if you're a consultant or a trainer, but uh inside a company, you know, you can still be valuable, but you're probably going to move into more of a coach role or possibly move move into more of a manager role. Anyway, I think either of those either of those second focus areas can be uh viable and valuable uh paths to focus on. Um, and I think one thing I mentioned in that talk was uh that it's just it's very useful to think through which one do you want to be? And I I don't know that a lot of people actually think about it that much. They kind of they get an opportunity to be a manager. And so they're like, okay, that seems like a step up. And they don't necessarily realize, oh yeah, if I take the manager path, part of what goes with that is I need to get better at the people side of it, and then I also need to get better at the business side of it. If I go high enough on the manager path, at some point the business needs come into conflict with the technology needs and my role is going to require me to favor the be the needs of the business. And a lot of technical people can't make that transition because they're too wedded to the technology and they just can't conceive of the idea that the business would take precedence over the best, you know, that's in quotes, the best technical decision. >> Yeah. And it's interesting with with the manager path. Uh I think we've had about 10 years where looking back we had zero interest rates and companies were growing really fast. investing investment in technology was huge thanks to the mobile revolution, smartphone revolution, thanks to cloud, thanks to startup returns and IPOs just being big and going with the manager path used to be it seen as a very lowrisk one as one where you could go in you could manage people maybe make a bit more money open your options because now you could uh you could go to found a startup say I have management experience you could go back to being an engineer later as well but what what happened Now, well, some a some of those people like who thought, "Oh, I'll just go into management for a little bit uh and see how it is and I'll go back." They ended up, you know, going higher and higher again with with this high growth area, earnings potential was higher. But now the reality is hitting where where teams are not growing as fast. In fact, there are some companies are scaling back. So, managers are finding themselves formerly technical people in this really awkward position where they're not that technical anymore. their past few years of experience is scaling fast growing teams which is no longer needed. >> Yeah. >> So I've I've had some friends who saw this coming a little bit earlier head of engineering or or director of engineering and some of them went back to individual contributor roles or to tech lead roles where technically they you know they took a step down but and some of them are actually happier for it. Yeah. >> And it just gives a lot more stability. You know, there's there's still a lot of engineers who need to be hired, but just fewer managers and especially fewer managers without a warm referral. >> Yeah, I don't have enough knowledge of sales staff or general business staff to know how it looks on that side of the fence. But from the reading I've done, I feel like technical staff have a couple of interesting attributes as they move into management that I don't read about in general management literature. One is that I think a pretty common pattern for technical staff is going into management for a year or two, deciding they don't like it, going back into a technical contributor role, enjoying it, but going back to thinking about, huh, here I could have done the management thing this way, I could have done it that way, and then they make a second attempt at manager, and then they actually really like it and they do well. I've seen that pattern many times. Uh, and so just the idea of kind of bouncing up against the ceiling, coming back, regrouping, and then taking a second run at it a few years later. And some of those people end up being really, really effective managers. Another attribute that I find to be really uncommon is that most technical managers at any level don't have any aspiration to general management positions. If you're at a VP of technology role, VP of software role, it's unlikely that you aspire to be the CEO or the COO. What's likely, if you aspire to anything, is you aspire to having the VP technology role at a cooler company. Uh, and that's it. And so, it's funny because I think for uh general business people, this doesn't really compute. You know, they like, hey, if I'm a VP, I want to be the CEO. I want to move into the sea level. But for whatever reason, I don't think technical people think that way. I don't read about it outside technology. >> Yeah. And you know, there are some really interesting stories as as well. the the founder and and for a long time CEO of Hashi Corp, uh, Michael Hashimoto. He was a CEO for of the company for a while, I think, because he needed to I think he took over from his co-founder and then he went back to being an individual contributor at the same company, which is uncommon, but it comes to show now he's actually he's he he went back to writing, you know, he he founded Hashi Corp by writing software, I think Terraform or or some of the others, and now he's back to writing software. just shows that he just loves building. >> Yeah. You know, there's a great uh leadership book uh called What Got You Here Won't Get You There. And the the gist of it's really aimed at organizational leaders. And the the gist of the book is here are all the things you did to kind of get to where you are and they were all great for that role, but you're not in that role anymore. And so to be successful in your new role, you have to operate differently. And and some people don't want to operate differently. So the ones that actually have some self-awareness do what you described. They they go back into a different role. I think I think the specific scenario you described of the founder of the company going back into a contributor role organizationally we've seen that is super messy just because it's hard to disagree with the the governor and all that stuff and and it can be incredibly incredibly uh randomizing for the organization. But if that same person instead goes off and starts the next new thing, that can be great. You know, they can take advantage of everything they learned the first time. >> I do think that a lot of tech founders don't really think or or even talk or consume literature learnings from other companies. You know, there's a lot of like first- timers. Why not? So, so there there are some drama and and conflicts and and learning. Sometimes it works out, sometimes it doesn't. >> Yeah. But I I I wonder if this is engineering specific or and and any company has this tendency of like look I know what I'm good at which is engineering and you assume that you're going to be good at other stuff as well which you know >> sometimes you are you know >> sometimes you are sometimes you're not. Yeah. >> Yeah. Well, I think you know a topic that I I don't think I've ever written about uh but that I think is worth just throwing on the table is that and it is that focused application of personal energy makes up for a lot of other deficiencies and and in startup mode when you're talking about not having well- definfined roles and so on. If everybody's actually working in a focused way and they care about getting work done and they're applying a lot of energy, you know, mistakes aren't a big deal. You just go in and you fix it because you've got the energy to do it. If you're working in a super processoriented way and people are kind of thinking half about their home life and they're checked out because now they're 45 instead of 27. Not that that's a universal pattern or anything, but um >> but you know, if you don't have the the same level of personal energy to correct mistakes, >> the mistakes linger, they affect more people, uh affect more downstream products, work products and and it just becomes a much bigger deal. And you know, when I was at Microsoft, the core Windows team was under 15 people. And of course this was you know much earlier version of Windows but uh at the time there was a project going on at at IBM. Well Microsoft and IBM were jointly developing operating system called OS2 and IBM had something like 10 times the staff maybe more than that and Microsoft was really frustrated at how slow IBM was on their side. And the the reality is you can get a lot of stuff done with the right 10 people who are all super focused. And when you even if you just start thinking about it in terms of number of communication paths, how many people do I have to interact with on a day-to-day hour-to- basis of I've got nine or 10 people, how many does it take to make a decision that sticks? How many does it take to fully consider an issue? uh you know I hear if I have a decision where on a 10 person team I need four people to weigh in I've now heard everything with four people if I've got 100 people on the team I've got you know 30 that need to weigh in that's an entirely different proposition and uh so yeah you can get an awful lot done with the right with a high level of energy and I don't think in the technical space I haven't read much at all on people talking about the role that energy plays it's all about process and uh training your training your different people in technology and so on. And if I just think back of you know the past like just 20 30 years the ones that I've that I've seen repeatedly regardless of technology regardless of you know right now we have AI earlier we have like code generators in terms of tools or or in or intellisense that just autocompletes your thing you know we all these tools that make teams productive but whatever tools we have if I think back from the '9s all the way to like today we always see these things where there's a 5 10 person team comes out of nowhere builds this thing and and so you know we think in the gaming there's the the the team that built it software uh you know they built Doom with I think like three core people nine people and it was a huge hit then in social media with Instagram which was 10 people Facebook acquired them because they were growing so fast they would have been bigger in the face of WhatsApp again it was a small team but I think there were 50 people by the end when when they got bought right now we have a social media platform called blue sky which again uh they're with 12 engineers they're they're growing really fast open AI when they are small and so on and it's it feels that it doesn't really matter what the tech stages like what connects them is well energy focus yeah and I I've not read anything about this you know there's always the they interview people and like how did you do it and they tell you some kind of story and when you ask people about like so right now I have been talking with like some people for example to open AI cuz right now they're the hottest one I asked like what is it special? How how do you ship so fast like Alona is still out shipping some smaller startups as a larger organization? And the answer I get sounds cliche but their tongue is true. They say well it's the people and and how everyone's so focused and motivated. They don't say energy but yeah that as well. >> Yeah. And so during the era I was at Microsoft I think uh the culture at Microsoft when I was there was if you were awake you were working. And the thing that it looks from the outside like it's a sweat shop, but from the inside it's just they were doing an incredible job at that time of hiring people who really didn't want to do anything other than work on the next generation of software. And it was a great time to be there because you felt like you were at least a year ahead of the rest of the world because number one, you were developing it at Microsoft. Number two, everybody else who was doing anything interesting wanted to come to Microsoft to show it to you. And so you were constantly in one mode at work where you were seeing the future and then when you went home or talked to somebody from a different company, they were a year or two behind where you were. So it's incredibly exciting, stimulating place to be. And of course, you just naturally wanted to spend all your time working. But you can't replicate that through good management. Yeah. >> Uh where you're just trying to somehow motivate people to want to work 100% of their waking hours. You really have to just put the pieces in place so that people want to do it. And if you're if you're a a super high marquee company like Microsoft I was at that time, then you know it happens kind of automatically. Really the manager's job is not to mess it up. But if you're a regular just business or a sustaining mode company, I don't think it's possible to replicate in those companies. Every once in a while, you'll see some individual project where somebody does a halfway decent job of replicating it for a short time, but uh yeah, so all the examples that you gave resonate with me because they're all kind of in this same mold of super exciting time to be there uh part of something. you know, you're creating the state-of-the-art, advancing the state of the universe. Uh, unfortunately, it doesn't last forever. And so, yeah, you know, it's cool to be a part of it while while it lasts. >> Yeah. And I think, you know, those of us, for example, I've had opportunities to be part of a team where at the time, I mean, we weren't changing a universe, but we were doing something really exciting and felt we're up against the world. It felt a bit impossible as well. Those are relationships where I still keep in touch with some of the people, you know, like it's like friendships are are made through these crazy times. And it's it's weird because I want it is crunch time, but a little bit of self-inflicted sometimes external pressure, but you I would never advocate for that, but I'm also very glad that I did it that I had like I do want some times in my life like that, you know, like not all the time cuz that's burnout, but also like if you have none of it, like it's it's just a 9 to5 then. Like I don't want that. >> 100%. Yeah. And it was funny because we saw the agile movement go through the same kind of maturing of its view of sustainable pace that my company had gone through. We originally as a company really before agile existed uh had started out thinking 40hour work week. But the first guy that I hired uh who uh ended up being the CTO for 20 years, um eventually he and I realized neither of us had ever worked in a 40-hour work week. We both naturally worked in burst mode and we both did our best work in burst mode. And so it's not about having a steady state. It's about having a sustainable pattern. Uh and you know what you described I resonates with me 100% in that you don't want it all the time but yeah if you had to go through your whole career and never experience that I would really feel like I had missed out on something if I I couldn't have been in that mode at least some. I I came up with this analogy which is imperfect but I I I used to do sports at um like a competitive level and this involves swimming and and and running and especially especially with running because it it is a something where you can be injured you know when you're training like you you you have when you're actually sprinting or or you're doing the competition but even in train during training you're doing you're doing that part you're also doing the kind of endurance part where you're you're not giving all that and then you're also like resting and a a coach you know will will will instruct an athlete to go like okay go all out give me 70% give me 50% rest for for this much and if I think about our our professional career if I had a coach who who who was looking to maximize my impact on the long term right I mean for athletes it's only 10 years for us we have 40 years they would actually tell me the same and yet when when we're in a job we feel that I mean either we feel bad about kind of coasting a little bit after you know a hard project but we probably should be doing this. I mean, maybe, you know, don't advertise it cuz there's a bad stigma these days when you say like, "Oh, I'm doing but like after you do something like really tough, etc." I mean, yeah, like it's kind of okay to Yeah. As as long as that's not you're you're not get you're not getting stuck in that, right? >> Yeah. You know, I didn't really spend that long at Microsoft, but for some reason, this keeps coming back to that topic. And I think the being part of that is exciting for a while, but as you say, uh, when it becomes a marathon and not or becomes multiple marathons back to back, it doesn't really work as well. And and you know, Microsoft in that era had a lot of stuff going on that wasn't really that exciting. And so there's this background culture that people have participated in where they're working themselves to death. And after a couple years, they're like, I don't really want to do this anymore. And so you know there were cases where as the years went by uh there sort of developed an expectation that that was going to be the work mode. We're now in a completely different space when there's an expectation that it's going to occur rather than just the individuals doing it because that's what they want to do. And uh Microsoft because they were so successful got into a mode where they basically had to go to people on key products and say you know we need you for one more release because we've identified that we need to carry forward at least two of the key people from the last release to be successful on the next release. And they were basically saying look we'll give you enough stock to make you rich but we need you one more release on this. and uh and so now that's just a completely different vibe on the project than than the one before. >> So you mentioned that one topic you you didn't write about but maybe it could could have been a good idea in hindsight is rule of energy. I wanted to ask you since you know the the since the second edition has been published and that must have been 20some years as well. Uh what are what is are one or two other topics that you know if you wrote this book today you might have added into it? Yeah. So I think that that really gets into the limitation of where I am professionally now and and I really have not been active in software at the code complete level um for several years now. I mean the irony of it is I've spent more time actually doing hands-on programming just for my personal use the last five years than I did for probably 15 years before that. But it's really just one person project me personally doing it. Um I think uh you know we've talked quite a bit in this conversation about design three times and I think one one thing that has worked out really well for code complete second edition is really that it is the second edition and then I I published it 11 years after the first edition and so I think that was that was really kind of an ideal amount of time between the two editions because I had learned a lot in the intervening 10 years. the industry I think had matured quite a lot and when I went back and started working on the second edition I had a great vantage point for looking at okay what has changed since the first edition and really thinking through well what insights does that give me about the kinds of things that are shorterd and the whole point of the book was to try to capture the longer lived best practices that would span te uh generations of technology and span programming languages and so on. So the 10 years between those two, there was some stuff in the first edition, it's like, yeah, okay, this really wasn't lasting. This needs to go. There was other stuff it's like, wow, you know, it's been 10 years. This really hasn't changed much at all. And uh I think when the second edition came out in in uh 2004, agile was really it was beyond infancy. It was kind of at the toddler stage at that point, maybe a little beyond that, but we were still mostly focused on XP. scrum really hadn't hadn't uh emerged as the the dominant practice at that point. And so I think one of the challenges for me in in the second edition was trying to figure out okay well how much do I really want to talk about agile and how much do I really want to talk about XP in particular. I decided really I only used XP in one example in the book. So I'm pretty happy with how that worked out. But in in the first edition, that consideration had really been about object-oriented because when I was writing the first edition, object-oriented was well established in academic circles, but not well established in practice. And so I made a decision to really not do very much with it. And in the intervening 10 years, it became so well established that it wasn't really a separate topic. I originally thought I'd have some separate treatment of it, but really it just ended up weaving its way in really throughout the book and it it didn't make sense to try to to treat it as a separate topic. So I feel like the first edition had aged more in 10 years than the second edition has aged in 20 years. >> Yeah. And I actually like I I I just collected a few topics we don't need to go through but the things that I I thought did not age or actually aged well. So it's very applicable. the parts of managing complexity. You go through how you can use things like abstraction, clear conventions to reduce cognitive load. >> Our brains have not gotten bigger in the last 20 years. >> No. Cohesion and coupling h how how cohesion within modules but also loose coupling between the modules help for more maintainable software also has has not changed. I wanted to ask you like in the book goes into the value of iteration and continuous improvement. Was this cuz I feel this is like dah like like this is this is how we work but at the time when you wrote it was this uh a bit less accepted still or or a bit more novel of idea cuz it's interesting to see things that were like today like obviously but these are not how ideas start right >> yeah no it's a really interesting question uh and it does take me back to kind of the state of the world in 2004 in 2004 the reason we were talking about incrementalism and iteration had nothing to do with product delivery. It had to do it really had to do with uh efficient technical practices and a and a a virtuous learning cycle. Um but kind of around 2004 we started to go from internet brochure wear to actual meaning uh meaningful uh more rich functionality websites. So the idea of CI/CD wasn't really an is a concept in 2004. Not yet. uh but we had done work for Amazon in about that same time frame and at the time AWS didn't exist at least not by name but what what we'd observed in the work for Amazon was I thought they were okay at the technical programming level but I thought they were probably the best in the world at operations as we called it at the time and their concept of just if it doesn't work we'll roll it back there just weren't a lot of organizations back then that could do that And so yeah, in the last 20 years with uh mobile well internet at first and then mobile and just functionality getting rolled out continuously uh these two uh the what's good for the the learning cycle and for containing errors at the development level has merged very nicely with how you deliver functionality. Yeah. The product. >> Yeah. And so you know today like when I was writing my book the software engineers guide book that was published uh two years ago one topic I was really unsure of should I include it or not a little bit to your agile thing was genai because chat GPT had come out about a year before like before when I when I finished my manuscript like 6 months before and you could already see that it was big. It was great for learning. It was good at generating code. So I figured should I add this or not because and I in the end I added it because it felt to me already all developers I I knew were already using it even if just to explain things and since then one of the biggest changes how how Genai is becoming I'm not going to talk about the the generic stuff but but for coding it turns out it is very good at generating code and for example in the book uh one tech one technique that you encourage and what I've used before is the the pseudo code programming process where you come up with pseudo code and for example But when you do that, you could it it's great at giving it the the more detailed pursuit code, the better. And you can tell generate Java, Cotlin, Rust, whatever. It does a great job of of doing so. So I I just want to get get your thoughts in first principles now that I I know you've not been as embedded in in software in the past few years, but knowing that there's this tool which is very good at generating code. It's, you know, it's not it's it's a weird intelligence. It's not intelligent per se. It's it's, you know, it generates the next token, but it does it really well. >> Uh, and what we're seeing is >> it spits out code really really quickly. Often times good, sometimes not. I think some uh people like I I compared when I talking with John Auster with the tactical the tactical tornado of of of doing so. And there is some scare with with with some developers of like, wow, it's actually coding better than that than than I do. If you were, you know, like an early career professional in in in this industry, seeing that there's this tool that is actually good at spitting out code, not perfectly, but pretty good code, how would you think of making the most uh out of it for for your career for to to understand how how to tame this and and how how this might even change software development if it if it will. Maybe it won't. >> Yeah. Well, I think it's pretty clear it will. Uh I think it's totally unclear how how it will. In my mind, we're still in the pretty early stages of of how we would use any kind of AI for help with software development or really for help with anything. I think, you know, at this point in time, the lessons I feel like I've learned are the more guard rails you put in place, the better result you're going to get. There was a funny LinkedIn post yesterday from somebody who said the learnings about using uh AI and software are you've got to be really clear about your requirements. You've got to really define your test cases well. you've got to define uh uh all the exception cases really well and the gist of it was huh this just sounds like good software development fundamentals and uh only we are now you know AI is the thing that's finally after 75 years forcing us to do this and uh maybe it hasn't been 75 years that it's been >> it has been 60 plus >> yeah so um so I mean I think that that's funny but it's also true you know one of the things that um uh I think is true of software developers is developers are so techoriented. If you give them a tool to do something that works a lot better than giving them some rules or guidelines and so if AI is a tool and now to get the tool to work you've got to go through these software fundamentals. Yeah, maybe that is the thing that finally uh uh finally makes that happen. My other feeling about it, and I would, you know, love it if you correct me if you feel like I'm off base on this. Um, my other feeling is that I think writing the gold path or the happy path through the code has always been the easy part of coding. And you know, understanding which which exception cases did I forget about or was I unaware of or did the requirements never capture in the first place. uh you know Fred Brooks published a paper called no silver bullets and he talks about the difference between accidental complexity and essential complexity and a lot of the essential complexity comes from the real world because the real world is messy and to the degree that uh AI isn't 100% lined up with the the messiness of the real world then the programmer job of being the party that fully vets all of the exception cases and the corner cases and the off by ones and so on. That's the other thing that's concerning is I still think AI can't count and so off by one errors seem like they're just probably >> So I I have to agree because I think we should not forget like obviously the interesting thing with AI I talk with a with a really experienced engineer Simon Willis. He created the Jungle framework. He is a very productive engineer for about 20 or 25 years just like codes a lot and and writes really good code and he's been using chat GPC and all the other tools since they've come out. So coming up 3 years now >> and he he told me because I asked like hey Simon is it worth like understanding a theory because I I I took time to understand how this thing works. It's just matrixes everywhere which is why GPUs work so well with them because turns out you know 3D operations are also just matrix >> uh multiplications. So it's a huge matrixes that are hard for us to to understand and they predict the next token. And he said actually it's it might be a little bit harmful in his experience because you need to get a feel for how this works cuz now it it does work. And he says that it just takes a lot of time to to figure out where it works and where it doesn't. Now in his case and I think for a lot of us more experienced engineers it can be super helpful cuz as it works like I will call BS. I'll be like this is bad and it often gets things really bad. So as as long as I just use it as like this people think about it. I think Ken Beck said he he thinks of it as his genie where you ask you it it grants your wish but sometimes in really funny ways >> like >> in really unex for example you tell like oh make this work and it does or make it work and the test should not fail >> and sometimes it will just go and delete the test when it it cannot. When I early early in my career on the when I was at Boeing, we had a CDC cyber supercomputer >> and the way the cyber supercomputer was explained to me is it's very powerful, very literal giant that will do exactly what you tell it to do and but it's so literal that it has no ability to do anything other than exactly its interpretation of what you tell it to do. And I kind of feel like AI is in that same space is incredibly powerful. Uh and you know your comment about uh sometimes it's glaringly off. I don't worry about that case. I worry about it being subtly off. >> Yes. And it is off subtly a lot. So there are some already some small stories that are going viral which are it could have happened to human but a good example is startup. You know they use one of these one of the many agent which which does stuff. It created a PR. It looked good and you know it's after a while when it generates good stuff you're like looks good to me. You commit it. So, it just made a small change that added up observability logging to one of their things that was unnecessary. And this agent cost $500 a month and in a month it generated an extra $800 for nothing. And the guy was like, "Oh, okay." And I think we're going to see a lot of these things. I think we'll have to ask ourselves again like what is software engineering because now what I'm I'm hearing for teams that are using more of those AI is reviewing code is super important. Yeah. Yeah. >> But of course it is hard to like I I remember when when I again I I worked at Uber is like the more you got to know an engineer sometimes you realize they're really reliable. So eventually in code review we needed two two thumbs up or two two people to accept and when that person came and wrote their stuff and it was a long poll request you tended to say LGTM looks good to me without reading it. And of course the shorter it is we also started to have the shu I don't have long poll requests because like for a 500 line change you most people were like looks good to me because I just don't have the mental capacity for five lines you get like 50 comments saying hey what about this what about that etc. So it feels like we I don't know when but I think we're going to come back to some of the earlier learnings on software engineer because this thing will not change whether it's a machine doing it or whether it's a human doing it or whether a machine that is acting up able to take on some things that a human can do won't go anywhere. >> Yeah. So uh sometimes programmers have difficulty just getting started. You mentioned the pseudo code programming process. I think that's something where AI can be pretty helpful. your hey look what are the steps I should what are the different uh topics I should consider when I'm designing this okay what sequence would make sense you you can basically dialogue and say you know give me a a breakdown of this space and show me what the class design would look like okay I don't like that give me a different breakdown show me what that would look like the ability to iterate super quickly and and insert your own brain into those iterations I think is incredibly valuable and for that matter It's incredibly stimulating to be the human in that in that loop. And then of course you can also say what test cases should I consider you know you can kind of pit it against itself and and I think at least my own experience with that is you know I haven't tried it on anything super complicated but I think the general concept seems to work. >> Yeah these are definitely also one one other thing that seems to be very useful is explaining things. uh may that be a a language a framework technology obviously you always need to double check but some of them are already giving you references so like like it it can speed you up a lot and and help you and you know one thing I I'm seeing it seems to be happening across the industry is engineers are going to be more full stack in the sense of you might remember the time where there was like Java engineer and net engineer and they didn't mix and then later at my time when I when I started to work we now had backend engineers work across languages you could do multiple and that was kind of expected >> but still backend and front end mobile were separate and now with the help of these things you know like a backend engineering can generate a mobile poll request and so on. Yeah, and you know, one of your questions or one of the threads has been kind of what's changed over the years. I think what you just described is a huge change where first edition of code complete, a lot of readers would have learned one programming language when they read the book. By the second edition, maybe, you know, maybe it was more common or more universal for people to have learned two or three. But the idea that it's just assumed that you're going to learn a few because you need to be using a few on a day-to-day basis in your job as a full stack engineer, that's just a complete change. And I think the mental development that goes along with that of understanding what's common and what's different across languages, I mean, that's just really valuable. >> Yeah. And I also wonder if uh if if it will be really valuable now because I feel, you know, the breath keeps increasing. But don't forget, you know, back in 30 or 40 years ago, the the people who learned one language, they were just as smart as the people now, I guess the difference is so they and they probably stored equal knowledge, they needed to know way more details. There were a lot more this and that. So I wonder if it'll be more really valuable. We now have a lot more breath for sure, >> but you cannot have as much depth. So the people who are able to balance this and even though you have access to this you know genie that can explain everything actually taking the time to understand and have that mental model you'll probably go further. Yeah, I think you know in thinking about the Fred Brooks no silver bullets paper which is pretty interesting to think about in terms of AI because the whole premise the whole concept of a silver bullet is any single innovation technology development uh method that by itself is capable of producing an order of magnitude improvement over a 10-year period. You know AI might very well be the thing that that uh is the exception to the rule in in that paper. But you know the the basic argument is that the real world messiness and other sources of essential complexity aren't going away and unless you find a tool that can deal effectively a and utterly reliably with all those details the corner cases the off by one cases all that stuff you know programming we don't get to be approximately right we have to be exactly right and so you know that's really I think the to me the gist of it if AI can get to the point where it's exactly Right? Then you know maybe we really do start to replace programming jobs with AI. But the whole history of programming as languages have gotten more powerful and more expressive uh tools have gotten more powerful and more expressive. I think that the defining characteristic of a programmer is being the person whose job it is to figure out what what is exactly right. And if AI just basically changes the playing field. So now you're trying to identify what's exactly right with AI generated output. To me, it's almost the same job it always was. >> Yeah. And don't forget that AI generates code and that code at some point needs to be understood especially because they can get into loops, you know, again they can they can get confused because again just just how it works once we understand that. Uh so there is value both both in that but also I feel like there's this thinking as well. uh I'm not sure I describe full but how you know we used to have assembly as the programming language machine code then there was C or C++ then we had compiled languages we had we have some visual languages or visual basic and this can be seen as like yet another layer uh where English translates to this except it's not a one-on-one mapping like all the other ones so it's a lot more >> st we we'll see where it goes it's it's it's changing things but I think the history of programming has been layers upon layers you add an abstraction more people can uh get started. I mean you know cobalt apparently was was invented to make it a lot easier for for developers to get started. >> Everything was invented to eliminate programming. All the programming was invented to eliminate programming and yet including forran. Yeah. So I I would take what you say and I would look at it from a slightly different angle which is I think the history of programming is a history of increasing levels of aggregation. So you started out with assembly or machine language and then you had aggregation into assembly and that was one level of aggregation. Then you had aggregation into macro assembly. So as a second level of aggregation then you had this amazing invention called the subruine which was an aggregation of callable functionality and then you had an aggregation into classes where you had a combination of data and functionality and then I don't know it kind of you know at least that's kind of where my knowledge of it my direct involvement of it kind of stopped >> and that now I think you you have a combination of like these reusable functionality or or like things that uh you know like some some of the the AI can definitely spit out things that had seen a lot. Yeah. >> And and actually we even had like you know some some temp but still so you know we'll see how it goes but I I like this idea. But I think it makes sense >> you know and maybe it is truly that above and you know there were lots of attempts to have the next level of aggregation way back when ADA had notion of packages and uh C had notion name spaces and you know there have been other attempts and maybe there's an environment out there that I don't know about which is entirely possible that has done a great job of aggregating packages with their own interface and their own behavioral rules and and so on. Um but you know if if AI ends up being the way to to achieve the next level of aggregation that would kind of make sense. >> Well maybe but you know don't forget one thing that I think we just didn't neither of us mentioned a huge difference with AI and everything else that came before it is it's non-deterministic. >> Yeah. >> And in programming we have been used to and I think we've gotten really good at making the most of deterministic. And nondeterminism always has its its dangers it its flaws. it's uh it's it's harder to work with and often especially when you have a non-deterministic system and you want a deterministic outcome, you you need to do a bunch of work around that. So So maybe that'll keep us busy for a while and sometimes it's not possible. By the way, as as as closing, uh you've had a long and successful career. You've written a book that actually kickstarted a lot of people's careers. I I had one of my uh colleagues from from one of my like companies tell me that in their first first few years as a a developer actually served as a military and they read the book and it really helped them. What suggestions would you have for an engineer to have a durable career principles that that worked for you probably independent of of technology? When I was writing the first edition of the book, um, one of the things I tried to keep firmly in mind was that the guiding principle for writing the book and the principle that answered every question was, does this make the book more valuable for the reader? And so there were some things that I kind of liked but maybe were idiosyncratic to me. I ultimately decided that doesn't make it more valuable for the reader. So I I left them out. um design elements of the book, content of the book, everything was about what makes this more valuable for the reader. And as I iterated on that over the course of writing the book, I think that iteration with that in mind, just add it up to something. And uh I think the same thing would my career advice would be exactly the same. What makes you more valuable to your organization or to the world at large? And you know, it's not like anybody I would think someone's a bad person if they don't think that way. But if everything you're doing is just to scratch some personal itch, it's idiosyncratic. You're interested in it, but it doesn't add up to something. Just be aware that that's, you know, that's a a lost opportunity. And if on the other hand, every time you think about, well, what project should I do next? What do I want to do next in the organization? Sometimes you don't get a choice. Sometimes you do get a choice between option A and option B. Does option B open up more doors possibly than option A? Well, maybe you should choose option B for that reason. Does one of them make you more valuable? Uh, you know, choose it for that reason. And I don't think this is just about personal development or personal success. I think it's about making the world better. If you're making yourself more valuable, you're increasing your ability to contribute to the world. And uh and I think that's a virtuous thing. >> Yeah. And you close the book with with the how you emphasize how craftsmanship is important for professional growth and you you you write how curiosity, continuous learning are essential trait of great software engineers and to me that it feels this is just as relevant as ever. I just think it's it's part of the human experience. And I think that programmers probably more than average are curious people who like to learn, who are attracted to novelty, who want to learn what's new and what's cool, and who want to explore what's possible with what's new and cool. A lot of our conversation today about AI has been all about exploring what's possible with what's new and cool. I think this is just the way programmers are and and I wouldn't change that. Steve, it's it's been both a really good conversation and a privilege. Thank you so much. >> Thanks so much for having me. >> It was such a blast to interview Steve. After the interview, we grabbed dinner at one of his favorite local restaurants, and he told me more about why he decided to make a shift and leave the software industry after a successful 30 plus year career to try something different. Steve's energy levels, positivity, and thoughtfulness run deep. And I hope this came across through the podcast as well. For more observations on how the software engineering industry has changed the last few decades, check out related deep dives into pragmatic engineer which are linked in the show notes below. If you enjoy this podcast, please do subscribe on your favorite podcast player and on YouTube. This helps more people discover the podcast and a special thank you if you leave a rating. 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