We tried autonomous AI agent swarms — total disaster - We Programmers by Robert C. Martin

[00:00:00]So, we had the idea. We're like, maybe if we write really well scoped tickets, like let's just try it and then let's farm it out to all of our individual agents, you know, like and do kind of completely autonomous programming, see how it goes. Disaster. Like, it just it didn't work at all.

[00:00:16][music] Hey there. Welcome to Book Overflows, the podcast for software engineers by software engineers, where every week we read one of the best angle books in the world in an effort to improve our craft.

[00:00:27]I am Carter Morgan and I'm joined here as always by my co-host Nathan Tops. How are you doing Nathan?

[00:00:32]>> Doing great. Hey everybody.

[00:00:33]>> Well, make sure to like, comment, subscribe, uh share the podcast with your friends and co-workers, share it on LinkedIn, share it, uh you can join our Discord, all sorts of things to help the podcast grow. Didn't you say the Discord's at 500 Farified members now, Nathan?

[00:00:46]>> We we just got we just passed the 520 mark or something like that. Pretty cool.

[00:00:52]>> Nice. I think before we begin today and talk about the book we're reading, Nathan, you have an announcement you must make to the audience.

[00:00:59]>> Well, I realize that I have a behoove problem. Um, [laughter] first of all, great comment uh talking about how I love to use the word behoo and then someone else called out the fact that I might be using it the opposite of what it actually means. And to my horror, they are correct. I've been I think this whole time my mother would use it in a very sarcastic tone. Um, I'm [laughter] blaming it. I'm blaming this on her because I'm just like, how how did I come to this conclusion? And so, I don't know, maybe you've had this experience in your life where you thought a word meant something and it actually meant something else.

[00:01:32]>> And so, yeah, I um I'm I'm doing a lot of introspection right now on my use of abuse of the word behoove. So, >> we uh there's a story my friend and I always tell when because when I was in high school, I played in I was in the marching band, but I played like percussion like up front, like not marching with the drums, but like keyboard and all that xylophone. And there's this thing called the rack, which is like a a contraption of a bunch of other drums. And one of our friends, Hector Lopez, quite the guy, uh our percussion instructor, said, "Would you be adverse to playing in the rack?" He said, "Yeah, man. Totally." And so we [laughter] we uh um we'll occasionally ask each other if you would be adverse to doing something to respond. Yeah, man.

[00:02:16]Totally. Um no, that's uh we're you know, like I said, this this week uh this podcast we we read a book every week to improve our technical craft and perhaps we also read a book every week to improve our vocabulary. I in my personal time, I'm reading a biography of Ulysus Srant and I'm learning all sorts of new words from that biography.

[00:02:36]Um all right. Well, we're excited about the book this week. Uh, this is another one by Uncle Bob. This is We Programmers. Um, I guess I'll introduce Uncle Bob, but most people here know him. Robert C. Martin, universally known as Uncle Bob, has been programming since 1970 and is one of the most influential voices in software craftsmanship. Best known as the author of Clean Code, The Clean Coder, and Clean Architecture, who was a co-author of the Agile Manifesto in 2001. served as the first chairman of the Agile Alliance and coined the solid principles that shaped a generation of object-oriented design. In his book, We Programmers, software legend Robert C.

[00:03:11]Martin dives deep into the world of programming, exploring the lives of the groundbreaking pioneers who built the foundation of modern computing. From Charles Babage and Ada Loveace to Alan Turing, Grace Hopper, and Dennis Richie, Martin shines a light on the figures whose brilliance and perseverance changed the world.

[00:03:27]Uh like we said we never promise any interviews but we have had Uncle Bob on the podcast twice. Once reading his book Clean Coder and second uh as a joint appearance with John Oster after we had connected them and they had a bit of a debate about uh clean code versus the uh philosophy of software design. Um and we are we're friendly with Uncle Bob. I I was actually texting him yesterday and just telling him hey we're reading we programmers. We love the book.

[00:03:54]>> Humble brag. humble bragging right here.

[00:03:56]I was just I was texting [laughter] off the bottom >> and he responded and said that he uh he was glad to hear we loved it and that he is happy to come on the podcast anytime.

[00:04:03]So again, no promises, but uh I I anticipate we'll get Uncle Bob back on, which will make him our second third timer along with Neil Ford. So exciting stuff. Uh and yeah, this has been I guess I can give my general thoughts first up. Uh I'm really really liking this book. um sometimes it's it's a great audio book which Uncle Bob himself narrates actually why I reached out to him like the the audio narration is really good. Is that you or a convincing sound alike but it is him. Um it's very clearly a passion project. Sometimes when people will ask me like about the people we've interviewed like what surprised you the most or who's been the most interesting I always say Uncle Bob is by far the most charismatic. um you can see why he's had a very successful career as a consultant because he's just he kind of like just oozes life and energy and so that charisma really shines through in what is very clearly a passion project for him here and I'll say that as an audio book it's great because I can listen to it on my commute home but you know I spend all day software engineering and sometimes I'm like oh gosh like do I really want to fire up another technical book on the drive home or or the bike ride home like I got to decompress press. Uh, this book is not that. This book is just a delight to listen to. It's a history lesson, but a history lesson targeted specifically towards us as programmers. Um, it's just been a super super fun lesson. Really excited for the episodes we're going to devote to this. Uh, Nathan, how about you?

[00:05:28]>> Yeah, same general thoughts. You know, I think it helps that we have some more context of, you know, having interactions with with Robert Martin.

[00:05:38]The book starts off great. you can see his like charismatic style and again having an author >> read well is so nice because it's like he doesn't you know >> sometimes you don't know how to interpret the intent of a writer and technical books especially it can be kind of dry I can't imagine being a professional um you know doing professional audio recordings and like reading fundamentals of software architecture or something like that but Robert M Martin reading his own writing was is super cool and um I will say I love the narrative There's a puzzling omission though, and I'm going to bring this up. [laughter] It's going to come up several times. I think it even goes through all the way to my hot take. We we've read through chapter 3. Uh it gets us right before the Grace Grace Hopper chapter. So, we get through the early 20th century, you know, and talk about folks like Vonman and Alan Turing. And there's not a single mention of Claude Shannon. And Claude Shannon is like, "That's my boy.

[00:06:37]I uh he's the one who invented the term the bit and there's no mention of it. I think it's and I'm I'm absolutely gonna talk ask Uncle Bob about this if uh yes.

[00:06:48]So >> well yeah it is interesting too like talking about Alan Turring like because the most the thing I know the most about Alan Turing is that he was supposedly well one I know that he he cracked the enigma code. I know he was uh there strong I don't remember if it's strong rumors or easily confirmed. But I think it is confirmed that he was gay.

[00:07:08]>> Um.

[00:07:08]>> Oh, absolutely. Yeah. No, it was a huge thing. And Yeah. Yeah.

[00:07:12]>> And then he and then he died under mysterious circumstances and and Uncle Bob's a little bit like much has been said about Alan Turing being gay and his his death by mysterious circumstances. I will not talk about that. I was like, "Oh, that was the part I was most interested in." But I can see why. Like, >> yeah, that was a very very Uncle Bob glazing over of that detail. There there is a lot written about it. And I I will say it's it's really good to to read about those histories. I think actually, and I'll talk about this later, >> this book is a really good catalyst for me being like, I need to learn more about this person. Like I I I've taken several times where I'm like, I'd like to read an a biography of of of this person. So >> yeah. Well, you know, we can just get right into it. Um although I will point out to any uh viewers of the podcast, you can often see me drinking a diet Mountain Dew Baja Blast. And you guys might think like, what do you guys record this podcast like right after lunch? No, we record this podcast at 7 in the morning. And I sometimes I my uh we're doing the new baby thing and my kids aren't sleeping great and so uh if I lose my train of thought throughout this podcast episode, that's >> You're also not a hot drink person, right? I >> I am not. No, no, >> I'm I'm three Americanos deep before this podcast.

[00:08:21]>> [laughter] >> So, >> it's funny uh in Utah cuz Latterday Saints don't drink coffee and so it it's interesting to see kind of like it more and more restaurants outside of Utah doing the whole dirty soda trend with like mixed sodas. But >> I've heard about this.

[00:08:37]>> Yes. But that is is such a Utah thing and we have chain we have multiple different chain restaurants that serve dirty sodas and like it um so you know when you you don't get your caffeine from coffee. Uh, some people, me included, get it from >> I'm a simp I'm a simple man and um I'm very fortunate that I live in Costa Rica and there's a farmers market that I go to once a week and the guy who grows the coffee also roast his coffee.

[00:09:04]>> I was going to say Costa Rica's probably have pretty good coffee, right?

[00:09:06]>> Oh, they buy excellent coffee especially and and again I love that I can, you know, kind of source it straight from the the folks who grow it themselves which is cool. It's a nice flex. I will say one of the um creature comforts. So like you know we have a lot of stuff in storage in the US. We haven't like brought all our stuff down.

[00:09:22]>> Right. Right.

[00:09:23]>> But one thing I absolutely did bring down was we have an espresso machine.

[00:09:27]And I I was like the second time like I went back to the US in January of this year and that was like one of the dedicated um like bags that I had was to bring back my my espresso machine. And so my my wife was very happy. I'm happy cuz we, you know, you can French press, pour over, there's all kinds of wonderful ways to have coffee if you're into coffee, >> but I there's something about espresso that makes me happy. So, it's there come >> tech startups in Utah are funny like that just because like about I think about 70 to 80% of our employees at my startup are Latterday Saints just because like that's just the demographics of Utah. So, we have like one neglected little coffee machine and we had like an intern who was visiting from San Francisco and he was like and I was in the kitchen with him. He's like, "Do you know how to use the coffee machine?" I'm like, "No, I I don't think so." Like, I don't think anyone here really uses it. And he he looked at me like I was insane. Like, what do you mean no one here uses the coffee machine? Um >> I feel like looking at you like you're insane visiting Utah, I'm like, you know, win in Rome. I I understand that [laughter] >> I guess that's fair, right? Yeah.

[00:10:32]>> Well, let's talk a bit about Uncle Bob here. Um, I actually uh I guess this book I I loved the starting chapter the second chapter one. So I guess uh >> let's let's just talk up front about the historical figures we'll be discussing today.

[00:10:47]>> Yeah.

[00:10:47]>> Um >> and I will say that the structure of this book's important to tap into. You know the first half of the book I think is is historical context and the second half is more of a memoir so of of of Uncle Bob's life himself. So, we won't be getting into any of the memoir stuff uh in this episode. We're really kind of getting deep into I guess the beginnings of the 20th century up to the middle of the 20th century. Um and and kind of it's I think he he narrates this really nice throughine. Um >> yeah. Well, I'm I'm trying to find the chapters and I'm looking at the chapters. I'm like chapter 27, Volcanic Passion. Chapter 28, Trading Places, Spoils of War, We Are All Americans, Sin Against Humanity. I'm like, "What?

[00:11:30]What?" Like, this book takes a turn. I'm like, "Oh, wait. This is the Grant biography, so let me find >> Let me find." Yeah.

[00:11:37]>> Yeah. I know. I'm like, "Do Uncle Bob has a taste for the theatrical." But >> um >> Yeah. I So, I guess it's it's a Charles Babage and Aydah Love Lace. And then it's Alan Turing, Von Noman, and uh who's the who's the other one?

[00:11:52]>> Uh is it Hilbert? Is that the >> I think so. I I can't tell.

[00:11:56]>> Hilbert. Hilbert who I didn't actually know anything about um but that David Hilbert who is again an interesting >> yes >> person as well of like how do we even abstract away the machine and the runtime for for how code runs um >> but before we even get into it yeah there's the the who are we you know >> who are we yeah >> yeah who what is a programmer what are we doing we've been doing this for two years we should figure this out yeah this is interesting because one thing I like about this book is that It is written like all books have a AI is moving so fast that like all books are kind of lagging indicators but this book is written with AI in mind and I do know that Uncle Bob you know on his Twitter feed is frequently talking about how he's using coding agents and that you know Uncle Bob is Mr. clean code, right?

[00:12:46]Uh and so the the fact that he's using coding agents, I think, is great to see because he's not someone who's just like a lite like he's trying to figure this out like the rest of us. And so he's talking about AI here, too. But he basically says that, you know, the whole uh prelude to the book is this idea that like as the machines have gained power, the people who program the machines have gained power and prestige with them. and that um and and he plants his flag early in the book and says that like AI will not eliminate this. AI will only make the machines more complex and as the machines have become more complex, it has required more skill to operate them.

[00:13:25]Um but my favorite thing about this first chapter he does is basically say like so why what makes us different as programmers? Because anyone can learn how to program. Like programmers we we like to fancy ourselves like way smarter than other people. And I do think this discipline requires a good amount of mental horsepower, but a lot of other smart people who go on to become product managers or business unit owners or whatever could could become programmers.

[00:13:51]So what is it that makes us different?

[00:13:53]And he he does this great little exercise of like let's say that someone has this idea and they think if they could draw a red line on a screen that they could make a billion dollars. And so he's like they could learn how to draw a red line. They would have to figure out if they looked at their phone. This is a funny example. If you sneeze on your phone and there's water on the phone, you might be able to notice that those dots in the screen are composed of red, green, and blue dots.

[00:14:16]And so there must be a way to make it so that only the red shines and the blue and green don't. And there must be a way to coordinate those dots and and and plant them one right after another. And then you might need the dots to be thicker to make the line thicker. So you must so you'll need to have multiple dots in a row. And then he kind of gets into like the algebra of it all like you know rise over run and how you know how how you could make a formula that could uh plot these dots in sequence. And he he does this whole bit for a while but then basically says like but here's the thing like at this point the guy wants to draw the red line. He doesn't want to think about any of this. What he wants to think about is how he sells his red line. He's like that's why you hire a programmer because a lot of people don't want to think about the details. What separates programmers out from the rest of any profession is that we like to think about the details. We're obsessed with the details. We find the details of how a system works fascinating. Yeah.

[00:15:11]>> Um and that's really what gives programmers their power in any organization.

[00:15:17]>> Yeah. And I love to and if you have this framing, he he makes a really good point and he says um indeed programmers have specialized are specialized like doctors nowadays. You have to hire the right kind of programmer, right? And he goes on to say and now they think the solutions will be AI but trust me the outcome will be the same with greater power the need for and stature of programmers can only increase and you know it it's these kind of little nuggets that kind of you have to kind of sit on that paragraph before you go off to the next one >> right >> and I I think this is correct like we are the best programmers that I know are pedantic about where which details are important strategically ally and at what time, right? I think we you kind of get a a feel for the aesthetics of >> last responsible moment. We've talked about this before. When when can I know that I can actually put off a decision to the future because I'll just be overwhelmed. And then where is it? Do we really need to stop and be like, "No, >> this really matters right now." like we absolutely have to nail the schema >> because if we don't, >> you know, or I'm I'm actually doing a personal project right now and I'm like >> this is a weird a weird thing of mine. I hate floating point numbers. I this is going to be [laughter] something I I I I love them and I hate them. I've been burned by them so many times that if I can represent data in some sort of integer format, high precision integer format, I will. Um, and then I'll put off floating point stuff to some presentation layer where I kind of just need, you know, the math part doesn't matter. It's like some render level thing. But if I'm doing something where I'm holding a what I would call like a high fidelity number for some period of time and I really need precision to be accurate, I'll try to find ways to do some high precision integer.

[00:17:07]>> Right. Right. That is a a level of detail that most people are like their eyes are glazing over and they're like why are you such a freak?

[00:17:14]>> Um but I think anyone who's done conversions across types of number sets have run into this before and if I have full control of the pipeline and I want to work this way and this helps me write a bunch of tests for it. This is the kind of like reveling in the details that no one should ever care, right? If I have something in kilograms or I have something in pounds, >> um, you're gonna be like, "Cool." You know, I'm I'm working on this like weightlifting app thing right now.

[00:17:39]>> Yeah.

[00:17:39]>> But I'm keeping this in I'm not joking.

[00:17:42]I'm keeping this in grams. Like I'm actually using grams as like [laughter] my universal >> integer value that I can convert and I've built all these converters and stuff.

[00:17:51]>> But this is the thing that like I love this. If someone ever wants to have a conversation with like why did I get to this decision or why is this going to be good? um we can get into this and and again I I was in an email chain recently uh where a few of us were talking between some security stuff and some architecture and some road mapping and there was another person on there that was like I trust that you're making having a wonderful conversation right now but I I think you I could be talking to Martians right like [laughter] they just had no clue about what we were talking about and it was funny because I didn't realize that if if I had realized the audience was broader, I probably would have used less domain specific language.

[00:18:33]>> But in you know, you kind of get in the flow of stuff and yeah, like we we come up with and and this is one of the things I love about this too and we'll get into this is that symbolic reasoning is the other sort of abstraction that comes up time and time again and all the way and he makes this this excellent point and I think this is a good segue >> into the history of Babage. Um >> well I just wanted to say about details really quickly. We saw this at at work.

[00:18:59]I I mentioned last week on the podcast that we have this kind of vision for redesigning our our inbox uh you know which is used for messaging uh at uh the company I work at and we had this I so we we had a the nice thing about redesigning something is that it's easy to know the requirements up front right you basically have to look at the current thing and say okay we're going to we we just need to replicate all of these features right so we had the idea we're like maybe if we write really well scope tickets like let's just try it and then let's farm it out to all of our individual agents you know like and do kind completely autonomous programming, see how it goes. Disaster. Like it just it didn't work at all. Like every PR that came in had a million merge conflicts, completely wrong patterns.

[00:19:40]And so I kind of hit the, you know, like pulling the end in cord, right, in uh with Toyota manufacturing. And and I kind of pulled my junior engineer aside and was like, "Okay, we got to we got to stop this. Like this is not working." I said, "Let's really lock in on the patterns." I say like I think we've got the workings of some really good front-end patterns and the workings of a really good backend pattern. So let's really define the actions that one can take on the back end because I said we're kind of using this event sourcing model for our messaging. So let's try that. And then on the front end he kind of defined like this schema registry pattern so that like any action you can take on the front end will automatically show like how it renders in the action menu and how and the sender and receiver previews. Um and I said like basically if we write this in such a way it should be harder to write wrong code because the path of least resistance should just be the exact pattern and framework that we've set up. And so we took took some time to really lock in on that and then we kind of handp prompted one using claude and really guided it through this process and then once we had it through this process we we had it summarize everything it learned into a skill and then after that I mean adding the rest of the features it was like butter uh with claude but only because we are so obsessed with that foundation and that pattern and then it was great adding the rest of these actions we wanted to because like every single one of them even reviewing the PRs was pretty easy even though they were like 25 file PRs.

[00:21:07]It was just like, yep, this is the exact same shape as everything else we've added here. Um although I will say that Claude is obsessed with generating integration tests and we have sharted our integration tests into four separate runners. We did that when they got to when it took 15 minutes to run the integration tests and now it's still taking 15 minutes because each runner takes 15 minutes. I'm like, okay, it's time to clean up all these integration tests because like I'm sure that about 80% of these are not even helpful. Um, but anyhow, that that just gets back to that idea of like we love the details and like product owners and and business folk do not want to sit and obsess about what is our front-end framework, what is our pattern here, what is the pattern on the back end. Um, they just want the result. And I just think like actually, you know, I told my co-orker uh uh Nathan um I said what you've told me which is slow is smooth, smooth is fast.

[00:22:01]Oh, nice. Yeah, >> I love it. Yeah, you're either going to get a positive response or like a well >> slow you don't you don't need to go slow and you're like [laughter] >> like watch us.

[00:22:15]>> Yeah.

[00:22:15]>> Um Yeah. Anyhow, and so that gets a perhaps Charles Babage could have learned the idea of slow is smooth, smooth is fast because >> Yeah.

[00:22:22]>> Char Charles Babage Yes. that he u what we learn about him is this idea of his adding machine. Do you want to maybe summarize for our our listeners a bit about Charles Babage?

[00:22:35]>> There's a couple of things that I love about Charles Babage. Number one, um, obviously a super genius and I think that he I I knew a bit about Babage, but I actually didn't know as much about him as until the depth of what Uncle Bob has in here.

[00:22:51]Charles Babage was simultaneously a genius and so scatterbrained and like unfocused that he [laughter] actually never became wealthy from any of his inventions. Even though >> he truly was the first programmer, >> right? Right. And [laughter] and and the thing is the reason he was able to get away with this is because apparently he had had inherited some estate that allowed him to have a lot of free time. Um, you know, I think this is very sort of like what you'd think of as the Victorian era of, you know, this sort of people who can pontificate and think about things and he was a tinkerer, right?

[00:23:24]>> The other thing was I loved about this is that he built so at the time and I think again he's he I knew about these tables that they they bring up in here.

[00:23:33]But so there's these truth tables, right? these tables, not just truth tables, sorry, but tables of like logarithmic calculations or high precision calculations where you you'd literally at the time buy books and flip through them and figure out that it was like a shortcut of doing math to like six significant digits or whatever. Um and I remember I knew about this because I think it was Oiler, you know, Oiler who you prolific mathematician um who would actually flip through these things and was looking at the numbers on these I think these logarithmic tables and realizing that there's a pattern here and he's like the one who figured out the relationship between I you know imaginary numbers natural log and um and pi and um seeing that these these these these large books of tables of things were there, uh people use these for random number generators, all kinds of crazy stuff. Well, apparently Babage was having to hand calculate or at least check the work of these hand calculations on these on these calculation tables and it drove him nuts. He was like, why are we having to do this? And it's like the most uh what's that quote? It's like uh I didn't do this because it was easy. I did it because I thought it would be easy. It was like one of those where his strategic laziness was a human shouldn't have to make these calculations, right?

[00:24:57]This is a beneath me. And so he spends decades coming up with a machine um and a symbolic system to like generalize how do we do these calculations? How do we make it so the human doesn't have to be a computer, you know?

[00:25:13]Um, and what's crazy is like it was so advanced that he could talk about it abstractly, but they actually didn't have the money to build it. Like I I didn't realize like what what an insane thing he was doing. He'd like speak at conferences and like talk to people and be like, "Oh, yes."

[00:25:29]>> Like they would all like be in awe of the beauty of this idea, but actually building the physical machine was like next to impossible.

[00:25:36]>> Well, and and this is the thing I love about it is so he does get the money to build the machine, right? And they build like they they build like a a prototype basically like the very first proof of concept like it works like it you know like and then you have to build the real thing and that's what like uh I think Uncle Bob said like yeah that last 20% is 80% of the work. I think this is also very analogous to like vibe coding right which is like you can build something that's like 80% of the way there really really easily these days but and so you can kind of say like oh my gosh like look it works. Um, but of course with anything that 20% is always most of the work. Um, and I guess there was I some I think it what do you like the London Museum of Computing? I don't remember but they actually did in the '9s they they built the adding machine. They built >> the second version. Yeah. There's there's like a second version of it where the symbolic system was a little more abstract and he had a better way of dealing with carrying numbers and some other interesting things. But even then I think >> they said it was a nightmare, right?

[00:26:40]They said debugging it was so complicated, right?

[00:26:44]>> Which which I think is, you know, if you really look at the improvements in our tooling, we've come so far in the ability to debug. Just look at early 20th century compiled languages, right?

[00:26:55]Mid I should say, it's not early, mid 20th century compiled languages. um so much of the innovations and he even called it out in mythical man month was hey there's this whole world of bespoke internal tooling that you know a lot of work needs to be done and that's where like if you look at any off-the-shelf modern language we now look if you look at TypeScript rust zig go I'm just I'm trying to think like it's table stakes now >> that you have to have good linting and testing and all of these other >> things on top of it to do the work. Um, and >> and not even just like the tooling on top of it, but like how [snorts] are you architecting your system? Because this adding machine they built, they talk about like if there was a bug in it, they had to like you have to take the whole machine apart. You have to like break it and other parts to see if you know if you can kind of like isolate the failure to a specific part. Um, because it's mechanical.

[00:27:52]>> Exactly. there's this very clean separation between the data that went through the system and then the the code. There was no code, right? It was a machine >> implementation. And so there's this and it and it makes sense because I think humans up to this point, why would the thing I'm computing have an interconnected relationship with the actual machine? Um, and so it what I love and we'll get into this later is this fuzzy line where we get into things like the touring machine where >> right >> the machine can program itself to calculate things which can then feed back into the calculations themselves.

[00:28:30]And that abstraction doesn't happen until the 20th century. But here we still see something interesting. I I also I I love these little facts that came up where um all the reasons that Babage would distract himself. One of them is he had these deep social contracts and so he'd have these like I guess dinner parties and and stuff when here's the some of his guest list.

[00:28:50]Charles Dickens, Charles Darwin. Yeah.

[00:28:52]Charles Lyle, uh Charles Wheatstone. Um who else? There's just like a bunch of people who were like, "Oh, Michael Faraday, >> John Hershel. There's just all these people." And you're like, "Yeah, well I mean if you're a socialite and of course obviously his intellect was high enough that in he could entertain and impress these folks. He he becomes like a fellow at the Royal Society in 1816.

[00:29:15]Um which again is you know Isaac Newton and other folks are like part of this like heritage uh that he's in.

[00:29:25]>> And so he's just having fun like working on pontificating about strange >> oh [laughter] you know in the f and he does he actually like calls this out.

[00:29:34]He's like oh in the future we're going to compute all of this stuff like we'll have machines that do all these things.

[00:29:39]And of course he was off by a while. Um but he's also absolutely correct and inspired.

[00:29:45]>> I mean so many people cite Babage and his his um his thought experiments is you know deep inspiration.

[00:29:52]>> Yeah. I had um one reading this kind of made me think because this is I I don't remember the exact dates this like late 18th century through early 17th cent or 19th century. Um, and it made me just realize like because now it's like the the epicenter of the tech world is it's in Silicon Valley like it's very clear that the United States of America is the leader globally in technology services, right? Um, but like back very different like all of all these famous people he's associating with like the the best and brightest minds are all in uh England, right? And uh and I was thinking like man like America must have been back then just been like this backwater country bumpkin uh sort of uh country.

[00:30:38]And so I I thought that was interesting that like yes now I mean all basically every figure from here on out in the book is is an American or or lived in America. Um >> right or or is or is incentivized to come to America. I think there's some geopolitics uh you know around World War II that really >> changes the course of history. Um >> um the other thing is yeah just talking about kind of like this idea of debugging like and this idea of details um and the final 20% being 80% of the work like I I've been using Fable um I probably shouldn't be using Fable as much because it's really expensive but work's paying for it but I had Fable just like straight up hallucinate the other day. This is Fable right which is like the the state-of-the-art frontier model although I've heard good things about chat GBT 5.6. Um and yeah I was I was trying to do like a scheduling flow and my understand and this is another thing where like domain knowledge really matters because my understanding of our scheduling flow is that basically whoever proposes the session uh cannot confirm it right >> and then if you propose a new time then it kind of kicks the ball back to the other party and so only the the the most whoever has not proposed the most recently can actually confirm the session and Fable just straight up hallucinated. I told it like I that's what I think it is and it it researched the code base and it was like nope that's not what it is. It's uh you know it and said it's only that the coach can ever confirm the session and so it wrote all this code based on that and I had to prompt it again. I'm like I'm I'm pretty sure that's not it. And and then it it searched again and was like oh you're you're totally right. You know again classic you're absolutely right. Um [snorts] but uh yeah just like I and our code base at this point is pretty well architected. like it's it's very easy to kind of trace an action through and figure out what's happening. We've isolated all the side effects to these downstream consumers in an event- driven way. Like it's very very easy to read and I'm I'm constantly harping on that with like AI assist development. Like what's good for AI is good for humans.

[00:32:38]Um and just good clean code bases to reason about and why I'm so obsessed with like making sure that our agents are operating in a good clean way because I'm like they will just bolt on if statements everywhere, right? Right?

[00:32:50]You'll tell it please do this thing.

[00:32:52]They will never think >> by you asking me to do this thing. We actually need to rethink our system.

[00:32:57]They'll just bolt on if statements. And I think even our code base is pretty clean and Fable hallucinated yesterday.

[00:33:03]I'm like I'm sure if we don't let it if we don't keep track of it. I mean that that rate of hallucination is just going to increase and our agents are going to become less valuable. I was even talking about this from a cost perspective because you might say, "Well, no, no, we have all these integration tests and they and so our agents can just run, you know, in in verification loops over and over again." I'm like, "Yeah, well, if if your agent needs to run 19 times to make a simple change and mine only needs to run once because my codebase is clean and well architected, then even from a cost-saving perspective, >> that's really valuable." Um, >> right.

[00:33:36]>> So, >> and even if you're have a really capable plate spinner, right? So, a lot of times I think about cognitive load, but how many plates am I expected to spin?

[00:33:45]>> And the the risk being that if you get off on any of them, the plates start to fall and they can kind of cascade.

[00:33:50]>> Even if these AI agents are quite capable at spinning lots more plates than maybe you can, it's going to make a mistake. And I, it's funny that you bring this up because I've been in this case. I've been using uh Matt PCO's styles a lot and I have some of my own skills that I've been developing where I'm actually full circle getting back to breaking problems up in really small incremental changes and stacking them.

[00:34:13]um mostly because that's how we did it before AI tooling and it I'm I do believe I think Will Larson actually had like a really good blog post recently about um there was already a problem in the software industry of being accountable for what you're shipping meaning that that like can you actually you say that this is the way that the system works or should work and not holding yourself into account or the code reviewer kind of just agreeing to it. Oh, you know, Sally's pretty smart.

[00:34:42]it kind of makes sense to me. I haven't fully groed it, but you know, I trust their work and I'm gonna approve it.

[00:34:49]That those add up. Those technical errors add up over time where you >> six months later you go, "Oh man, that's not what I wanted >> at all. Like, how did we get here?" And it's like, there was no egregious thing.

[00:34:58]It was like this one little problem. And the AI exacerbates this, right? AI, you you get in there and you're like, "Do I really want to read this verbose markdown file that's explaining everything?" Like, I'll kind of >> cruise over it. And um and so yeah, I think you're you're absolutely right like paying up this tech debt. First of all, make are we doing foundational principles? Do we really understand the domain that we're in? Um I've never regretted spending that extra time doing that, I guess.

[00:35:27]>> Yeah.

[00:35:27]>> You know, >> well, and um that's why I I I didn't get enough sleep last night and my I'm losing my train of thought. Um, but I just like some people are are all in on this idea of like we're just kind of like these agent swarms are gonna operate autonomously and and there's some things I really like about that in the sense that like on our checkout page for so long we have not displayed like like it's like hey you bought 10 hours of coaching right and for some reason we did not display the coach's actual name and their image. It was just like 10 hours of NBA coaching super impersonal.

[00:36:01]We hate it. And so we just like in Slack pinged our our agents, we call them the ponies and said like, "Hey, like can you fix it?" And it's great. It generated like a little fourfile PR, right? And then we and you can look at it and grock it pretty easily of like, "Yeah, this is what this is doing, right?" And very very small change and like done. And like that's something that's bothered us for years. We just haven't gotten to it.

[00:36:21]And so to be able to to fire that off in a slack command is great. But in general, I am not a huge fan of this idea of like like I said, we tried to kick off a swarm to do this net new feature development. and it was a disaster. Even when I'm coding, like some people are like, you should be working on five separate things at a time. Like generally, I'll have like maybe two agents going in separate workspaces if the features are very easily parallelizable, right? Just kind of separate domains. But in general, if I have downtime when my agents are going, I much prefer spending that downtime like, and this is different because I'm a principal engineer and so I have more like leadership responsibilities. Like I'll review the product road map. I will be in our analytics tool post talk and like be researching like how are our customers using the product. Sometimes I'm just clicking around the website myself and and trying to get ideas for like how could we be improving this? And so I think in an AI world like where we're supposed to become more product minded as engineers like this idea that you should just have like 10 agents going and switching back and forth between all of them like I find that context switching that plate spinning way too overwhelming and I think the time is better spent like doing something completely different related to the domain that can improve you know your your product but not necessarily how much code can I possibly generate at the same you know at a time. No, I I'm I'm in the same boot. I think my sort of like terminal agent usage is depends on the type of work, but it's if I get much more than three, >> right, >> start feeling the stress. I've definitely I will definitely have like and so it's funny. I've actually gotten I will use uh VS Code some I I have I'll have VS Code just so it's an easier way to file browse. Um, but most of my stuff is entirely terminal based now and I'm using T-Max and I have work trees and I have like I have these like clean separations and workflows that have kind of come up. I also um I work with multiple clients and I have strict separation across virtual machines. So I >> Oh, nice.

[00:38:23]>> the hygiene mostly being me being paranoid being like hey what happens if an agent breaks out or something crazy?

[00:38:32]I would like to I'd like it to be you know blast radius of a single you know client or whatever. Um, but this has forced me to do things like get my dot files working better, how make it as low cost as possible to spin up virtual machines for sandboxes. And all of those things have actually been useful and actually have gone back to to clients that I work with because these are the same problems they're trying to solve.

[00:38:53]Like how can I, >> you know, allow an agent to be autonomous within a set of constraints in a sandbox that keeps things safe but also allows it so I don't have to like hit yes every time.

[00:39:06]>> Have you ever used You're talking about dot files. You ever used envx?

[00:39:10]>> No, never. Never used that.

[00:39:11]>> It's super awesome. I I I'm familiar with this concept with EJSON, but it's this idea that um it's av file, but it's encrypted. And so um you just need one key to decrypt it, but what's fantastic about it is you can commit thev files to source control. And so as long as you only have the uh the key, you know, in bit warden or keeper or whatever, >> um you can commit all your MV files to source control. And so it's really helpful for like just like a a staging like like for example, you're running uh local development, but you want kind of all the staging secrets so that you know you're interacting with staging locally.

[00:39:51]>> Um >> it's uh yeah, it's awesome.

[00:39:54]>> This is interesting. I actually I think this would be good to go off on a on a a little tangent for a second. How let's say you So then is there a common secret that you have to share amongst your group?

[00:40:04]>> Yeah. Yeah. So there's a common just like a common one key. It's like just the decryption key. M so >> my my my tin foil hat Spidey sense goes off because I say okay well what happens when we need to key rotate uh because any so now we have an in like in number of engineers problem which is if anyone leaves for any reason we now have a key rotation event that has >> that's fair that's fair right but is that any different from just your your classic secret like >> ah so so here's a good well yes any secret inside of the envelope obviously if they have access to those secrets, you have to rotate all of them if they're not ephemeral, right? Which again, >> in a perfect world, we would live in a world where all secrets are short-lived.

[00:40:47]They're ephemeral. We ask some service for them.

[00:40:50]>> Um, so there's a couple ways I' I've seen in I'm not I'm not like dumping on uh NVX because I think that these are great solutions for lots of reasons. Um there's tools like um age or a I don't know how to pronounce it. Please roast me. But um age it's aging.

[00:41:08]>> Behoove you to roast Nathan.

[00:41:09]>> I know it'd behoove me to do my research before >> um so the uh in this one you it's a aggregate of all of your private keys.

[00:41:21]So basically if I add it reenrypts the envelope encryption.

[00:41:25]>> That's cool.

[00:41:26]>> But then I'm never we're never sharing a secret. It's just >> nice. We'll have to look into that. Also um one password has an amazing command line tool now and so that's actually yeah so I we are now using this at a couple different places and for me personally it's called op like one password >> and so OP um you can give it read access to stuff and then I use it to kind of bootstrap things um and then of course you get to like lean on all the cool things that one password does um and then the the the awesome one if you want to go vendor neutral role is um is a tool called Vault by Hashi Corp. And again, it takes a little bit more to get it set up, >> but that's like the best environments I've ever been in that needed to be cloud agnostic. Um then you can do cool stuff like software engineers never see production secrets ever. Only a role on an EC2 instance ever sees it. But when I'm doing local dev, my GitHub credentials can give me access to decrypt a secret. And so like our dev environment, anybody who's in certain GitHub groups can access it. Everything feels the same. But then if it happens to be in the prod environment, it uses a different, you know, sort of um sample handshake or you know, whatever single sign on stuff that you're you're handoff that you're doing.

[00:42:46]>> You say one password, it has a good CLI tool. How how recently did they develop this CLI? Do you know?

[00:42:52]>> I don't know. We've started using it in a way that's been pretty cool because again I still use it to kind of bootstrap. Um we're big on like injecting secrets it to just to the the smallest surface possible.

[00:43:04]>> Right. Right.

[00:43:05]>> But one password is great because any field in your one password can be a key value store.

[00:43:11]>> So you can use it for sensitive stuff. I actually have one I have one that I have for my private vault >> and one password called home lab. And it's literally just like a catch-all for certain my tail scale ephemeral API tokens or some other you know things like this that I kind of want to inject into something that I'm doing. Um it's made things nice for for personal projects.

[00:43:31]>> I I just wonder because with you saying it was developed recently that that's one thing because I've just noticed with like large language models that like it's just enabling us to take on new surface area we wouldn't have in the past. But I'm also big telling the team like look there's kind of two ways you can develop with large language models if you just have more bandwidth which is you can either just develop a ton more features or you can develop a little more features but just make them good right and just make like the quality of the website and I keep telling the team like the bar for user experience for the history of this company has been functional if it's functional it works the new bar is delightful right and so kind of with the new stuff we're building I'm I'm trying to like focus on like is this a delightful full experience and and just clicking around the site sometimes I'm like yep like this is this doesn't work and so I'm trying that that's my big hunt right now is to try to find those things and and fix them. Um but we we talked a lot about that we we should mention this this chapter with Charles Babage Love Lace is the companion figure in this chapter who was she was Babage's protege so to speak. Um yeah, she is called she's often called the first programmer because uh she recognized with Charles Babage's adding machine that it could inter that there was a a future where it could interpret symbols. Um and basically that idea that um understanding that a machine could work with symbols makes her in some sense the first programmer. Uncle Bob disputes the idea that she's the first programmer. He says there's evidence that Charles Babage understood that the machine could use uh could could interpret symbols one day too. Uh but he he gives her the title at least with Babage of they are the first pair programmers that they have lots of correspondence between each other discussing the potential of the machine and how the machine currently works. Um and and he has this really interesting point. She dies at 36 unfortunately of of cervical cancer. Um but basically like can you imagine living in this world I mean this is the early 19th century understanding this vision of what could be and just limited by the technology of your time. Um and and he also has this kind of like what if of like what if Charles Babage had been kind of more of a completer instead of a starter and what if he had actually just followed this passion through to the very end. Is there a world where the computing revolution takes off faster >> than it did? Right. You know, >> absolutely. And and I do I think it seems like, you know, and I don't know if it gets enough credit in the book itself, but I feel like with some of my own independent research, Ada Love Lace and Babage seem to be a feedback loop where they they were really pair programmers in the sense that I think they both fed off each other of like the potential. And I think it it's hard when you're the inventor of something to even know what its applications could be because you really are thinking of a world that doesn't exist yet. And you're also having to constantly validate and saying, "Am I crazy or is this are we really on to something? Am I tapped into some deeper truth that we haven't figured out up to this point?" And of course, most of the time is you're delusional, right? Most people think that they've come up with something amazing and it really isn't that amazing. And every once in a while, somebody comes up with something amazing and it really is so crazy that people don't even know how to [laughter] like >> wrap their heads around it. Right.

[00:47:00]Right. I bring up Oiler again because Oiler the mathematical equation. He was just doing it to like goof around and it was like weird weird abstract ideas and it's like the foundations of modern cryptography sitting there latent for like 200 years, right?

[00:47:17]um or hundred and [clears throat] some odd years. And um and so I I think that Babage was in in Ada were in the same spot where they they had the mathematical prowess. They had the understanding of how physical machines could function and they knew that we were just tapping into a potential >> and again you have to remember this was actually before the idea of like binary um binary operations. So they're still doing this on top of some base 10 type abstractions uh just because that's how numbers function. So you know these mechanical wheels and they would periodic and they flip over and but the fact that they could like turn things from a set of numbers I'm doing something that turns into a set of numbers and then those set of numbers go through a machine and then come out with a new set of numbers at the other side.

[00:48:09]uh and that those things can represent something abstract is a sort of um beauty and madness. I I would argue that anyone who does advanced mathematics are like high functioning crazy people. Um, and I mean that with the most loving way possible because I think if any of us who've ever had a conversation with somebody who's like super excited about, you know, uh, Ein Einstein's mechanics or something about quantum that's some real observation, you start being like, are what planet are you on? Right. Um, [laughter] >> I don't know. It's I it's it's it's interesting. And I so I I had a feeling that Babage probably at these dinner parties would go on about the future of this thing, >> right?

[00:48:54]>> Skeptical minds probably came through and were like, "This dude's nuts, right?" Like, "This guy's completely out of his mind."

[00:49:00]>> I know I' I've had as I've gotten older like and reading this book you you have to I think you have to recognize where your strengths are because I admire people like Babage who have that kind of like mad scientist mind and like sometimes I get frustrated that I'm not more like the bleeding edge of things but I think sometimes our greatest strengths are also our greatest weaknesses and that that groundedness that I think I have also makes me I think a more effective product thinker because when I think about building something it's very clear in my mind like who are we building this for? What do we want it to look like? What is a good user experience? And I think kind of the people who are a little more like nutty professor struggle with that which isn't to say one is even better than the other. I think um it's uh but yeah just you know different strokes for different folks. Uh maybe this is a good time to talk about the next chapter because this the book jumps time quite a bit basically from early I mean you know like American Revolution and pre-Ivil War era although obviously in England to World War II and uh Uncle Bob mentions this that basically necessity is a mother of invention and we reach the age where our machines are getting more powerful war breaks out and now there are uh government needs for computing to become more powerful. Um, and this introduces us to David Hellbert, Alan Turing, and Vonoyman. What is Vonoyman's first name?

[00:50:24]>> I don't I don't even John Vanoyman. Yes.

[00:50:26]>> Um, uh, yeah. All All interesting characters in their own right. Um, I guess. Yeah.

[00:50:34]>> And if your ears perk up because you recently saw the movie Oppenheimer and you knew that John Vonoyman was in that movie, >> he was a prolific polymath of polymaths.

[00:50:45]Yes, >> the guy is literally involved in everything uh in the 1940s um and and beyond. And um it's absolutely fascinating to see where his influence was, whether it was in um obviously the vonoman machine, which we'll get into um which is the foundations of how modern computing is abstracted across CPU and memory and everything else. Um he was deeply involved in quantum uh you know quantum physics. He was deeply involved in the Manhattan project. He was also very interested in the beginnings of AI and really was just a deep thinker in a lot of ways that it just again I'm going to I'm going to I'm going to talk about something really quickly which is Claude Shannon is absent from this section and I think it's to the detriment of this because Vonoman and Alan Turing had interactions with Claude Shannon. van was the reason that uh Claude Shannon named entropy entropy.

[00:51:50]So Claude Shannon was trying to say like hey there's this certain a maximum amount of information that can be extracted from any set of bits and um this the amount of surprise that comes from this or the distribution of what's the possible set is is the entropy. So like the the a high entropy system is one that has is very unguessable and a low entropy system is one that you can really guess. Turns out this is the ba the basis of how next token guessing functions as well. Um but vonoman's like hey in physics there's this word no one understands it's called entropy. Uh you should use this word right this is a kind of like running joke. And so the reason that there's this thing called Shannon entropy is because of conversations he had with with vonoman Alan Turing >> and Claude Shannon also worked on cryptographic systems during World War II and they were not allowed to talk about it but they did there was a period of time where Alan Turing was in the US I think it was the US but they were in the same spot and they would have tea like every day talking about the future of computing and so like again it it it just feels absent that the person who coins the term the bit like the foundations of how uh binary operations work in systems is not there. So anyway, that was my little my little scree. Um this section is great. It's just >> Claude the AI is not named after Claude Shannon, right? Is Claude Coats is that or is it >> No, it's named after Claude Shannon.

[00:53:13]>> Who's Claude Coats? Is that Is that something?

[00:53:16]>> I think I just think of it because of uh >> an American artist. Yes. Of course >> it's named after Shannon for sure. I just think of Claude codes because of Claude Code.

[00:53:26]>> Well, and that's the funny thing and again there may be people I I should say this. There are probably people on this listening to this podcast right now who don't know who Claude Shannon is. Um I'm really sad about it. He's probably the most important person in the 20th century that no one knows about.

[00:53:40][laughter] He's the father of information theory and he um he actually like as an undergraduate wrote a paper on how you could use boolean logic to to prove the correctness of circuits. And so there's this really interesting gap where being um an engineer was considered more of an art and he brought it into a a rigorous discipline that was backed by mathematics and there's this transition period happening in the beginning of the 20th century that happened with this um Bell Labs took his undergraduate paper and started using this so they could prove the correctness of their circuits that they would deploy out into their tele uh their uh telephon systems. And of course he individually ends up getting a job at Bell Labs. And so the reason I'm like this huge uh Claude fanboy is because like he absolutely is we programmers, right? Like it's just nuts to me and again I can't wait to ask Uncle Bob about this because um and it could be that the book would be going on for infinity if he didn't cut some people out.

[00:54:44]>> Uncle Bob will answer for his crimes.

[00:54:46]>> I know you crossed the one line that [laughter] this co-host can't stand. I've been I've been watching clips of Batman for some reason and so I'm thinking of Batman quotes. Like I have one rule, Nathan.

[00:54:58]You have one rule and it's you must not forget Claude Shannon. This reminds me of when I was in elementary school and we were like watching like this like History Channel thing of like the hundred most important inventions in human history and like and their inventors. Naturally, as a as a child, I knew exactly uh which invention should be on there. And the inventor is Nolan Bushnell, the creator of Atari and Chuck-E-Cheese, some sometimes known as the father of the modern video game. So, I'm just waiting throughout the series for of course Nolan Bushnell is going to get show up. We get to like number one and our teacher pauses it and it's just like, okay, what do you think is the number one most important invention? As again, I'm like, well, I don't know if I would put Nolan Bushnell number one, but he hasn't shown up here yet. So, I I'm sure he's going to come know who's Johan Gutenberg in the printing press.

[00:55:44]>> Hilarious. As a kid, I was like, "What?"

[00:55:46]Like, "When's the last time I've used a printing press?" Um, this is you and Claude Shannon.

[00:55:51]>> This is your arguments are are better founded than mine were.

[00:55:55]>> That's I love that though. I really [laughter] do. I really do.

[00:55:58]>> Little 10-year-old Carter. Um, yeah.

[00:56:01]Yeah, I I think this is an interesting I think there's also an interesting Uncle Bob doesn't get into this, but the parallel between John von Noman and Alan Turring, which is John Vonoman is a Jew and was persecuted and and uh and uh and I believe communist Russia at the time.

[00:56:16]And so he flees and then finds safe harbor in America. Uh basically, you know, one nation because of their prejudice changed out a brilliant thinker and and it was our gain as Americans. Um but then there's this interesting asymmetry with uh Alan Turing who is persecuted by his country for being gay and someone who could have been a brilliant mind was a brilliant mind obviously but his influence could have been tenfold if he didn't have this this prejudice against him right um >> and so it's fascinating none of these people fit into any clean path right all of these folks were such I mean it's so cliche to say out of the box thinker but really there. You know, one of the things I loved about Turing is obviously Turing was a genius and I think that that was witnessed early on, but he wasn't a great student in the way that some of the schools that he was in expected him to be. He would he got very bored with certain expectations of of how he was supposed to go through the education process, but also became fixated on certain types of problems.

[00:57:20]And unfortunately, I think systems chew up curious minds like this all the time, right? I I wonder how many Alan Turings through situation and circumstance the world never knew because they were born on the wrong side of the street or they weren't encouraged by a certain family member or a teacher. Um, and probably were exceptionally intelligent and yet, you know, never got to find a way to express that. And I I I think that these stories of these truly exceptional people, right? Like >> Alan Turing, John Bonoyman, um David Hilbert, these are, you know, not these are the exceptions of the exceptions.

[00:58:04]But I do think that like what we see here is that we really do need to have a way of cultivating wild new ideas and letting people go down certain paths so that they can find um you know blind spots in society. Right. Right. And uh >> well and it's fascinating. We we had this talk with Brian Kernneahan. I'll point out one looking at the chapters of like who's to come. I'm like, how neat is it that like he lists uh yeah, he chapter 10 is Thompson, Richie, and Kernahan, right? I'm >> like, how crazy that we've interviewed Brian Kernahan twice. What a nice guy.

[00:58:39]Um, but we asked Brian Kernahan in when we were interviewing him about Unix history in a memoir. Like, do you think this could happen again? Do you think a couple people with an idea can change the world? And he pointed out the uh the very first paper, attention is all you need, which is the foundation of LLMs.

[00:58:57]He's like that paper only had a couple writers on it. Right. And that's an idea that has >> word for a couple.

[00:59:02]>> Exactly. Right.

[00:59:04]>> And that is an idea that has I mean at this point it's undeniable is change the world.

[00:59:09]>> Um and so I I think yeah it's an interesting thing to think about which is like how many people out there are having ideas like that that could change the world and aren't being properly nurtured or encouraged or systems are not feeding through through the right pipelines.

[00:59:24]>> Exactly. And again, I know that we things will get controversial uh depending, you know, for all of his flaws.

[00:59:32]Uh you know, um Elon Musk is an exeutor, right? So, like there's lots of things that I I I'm not the biggest fan of, >> but I will say like, you know, when people write him off as like, oh, he really actually hasn't innovated or done anything. I'm like, well, >> I I understand from like cope I I would love for that to be true, but that's not true at all.

[00:59:53]>> Right. Right. He >> even if Elon Musk's only thing is that he finds interesting ideas and funds them, that's still a lot more than a lot of other people, >> right? And and and again, he did things that were considered impossible. People laughed at him. This idea that you could have a reusable rocket, that you could actually make a profitable business model off of um space internet. You know, I again I think I'm in the same um I'm in the same boat as Charles Mer, which is that like I don't most of the time I don't quite understand what Elon Musk's like really his point is of what he's doing, but I won't bet against him.

[01:00:26]Like it's just >> betting against him is is obviously not worked out well.

[01:00:31]>> Yeah.

[01:00:31]>> For folks. And so, you know, obviously he's he's talking about full self-driving. Oh, it's six months away for the past 10 years or whatever. But again, you look at this what he's built >> or at least what he has.

[01:00:43]>> He's a con man in a lot of ways, right?

[01:00:45]Like he's definitely hyped himself up and done things. But despite all of that, he's shipped some things that I think have changed the tra even if he disappeared tomorrow and all of his companies disappeared.

[01:00:54]>> We now know that you can reuse rockets uh and operate them at a fraction. And we know that there's viable business models with doing certain things in space. And so like I I think he's the antithesis to Babbage in some ways of like how many folks have had the crazy I would say like pthead ideas of like hey man it would be so cool if and then just kind of like sat on the couch and never finished doing that.

[01:01:18]>> Um and so I think what's unique about this aspect of the 20th century is that no one would have built Turring's machine unless World War II was happening, >> right? No one would have uh tried to split the atoms and you know cause the most devastating war weapon ever created unless we thought it was going to end war or you know give us sort of dominance in certain ways and um I'm not necessarily saying that all of those innovations are good and I think even I I loved that vonoman talked about this that he's like you know I wish I had the quote maybe I can find it in a second where he's like we're going to be misunderstood stood and hated. And at the same time, it's inevitable that these things are going to be developed, right? Like I think he kind of had this understanding that like if we don't do it, other folks are going to do it. And it's also like terrifying what that means, what's going to come out of the other side.

[01:02:14]>> Well, and it's um Yeah. And there's also this idea that like being early is just as uh bad as being wrong, right? And like I I follow this Twitter account that just like it's summarizing events from 25 years ago. Um and and just recently it says web van a grocery delivery startup goes out of business, right? This back in the com boom and and now we know that grocery delivery is a hugely profitable and popular business, but you were just too early. I think VR is one of those things like I'm just such a believer in the idea of the glasses. like the ability to put on glasses and my brother who lives 1,000 miles away now appears to be sitting in the room with me and we can have a conversation like that is a hugely valuable product. Um I owned an Apple Vision Pro briefly. I I had it for about two weeks before I returned it. Very very interesting product just way too heavy. Um, right.

[01:03:04]>> But one of the most magical things about it, and again, too heavy, too expensive for just this use case, was I took the spatial video of my children playing in in our loft. And the ability to sit back on that couch even for those two weeks in that same spot and to turn it on and it was like my children were playing in front of me was magical. And I do think there will be a future where we look back on like um like I mean, you know, right? Like how many videos do are there of you as a baby? Probably very little, if any. I don't know how good your parents are.

[01:03:37]>> I don't think my parents didn't have like an 8 mm or like or like a little mini uh >> it wasn't until probably I was like 10 or 11 that we probably had like some sort of camcorder type device. And I'm 10 years younger than you and so there's more of me, but we have my brother actually got them all and and published them as a private video on YouTube that the family has access to. And there's about I think 90 minutes of footage of us as as small children compared to my kids where there's just tons and tons of video. Right.

[01:04:07]>> Exactly. And so Right.

[01:04:09]>> Right. But I think our children might look at that one day if they if they do get the glasses kind of down and that will be kind of like we have this grainy footage of me and there's just a little bit of it. But they will take 3D spatial videos of their children to be able to put the glasses on and relive it. Um I think that's a really really interesting idea. I think it there will be a lot of demand for a product like that but it's just so early and I think there are people who have invested a lot of time and energy and effort into VR that just like that the consumer demand is not there yet. And so, you know, it'll be I I you wonder about how many people with those kind of crazy ideas right now are just they're not wrong, they're maybe just early.

[01:04:47]>> Um, >> yeah, it it it's it's fascinating and I would imagine it's probably a a cruel joke on one level >> to see a glimpse of the future that you know is going to exist capable, right? Yeah.

[01:05:01]>> Being capable of living in that world.

[01:05:03]And um I I'm sure there's folks like this that live amongst us now, right?

[01:05:08]That's >> absolutely >> something that I can't even wrap my head around because it just sounds completely nuts.

[01:05:15]>> Um well, we as far as hot takes go. You already shared yours. Claude Shannon.

[01:05:19]>> Yeah, right.

[01:05:20]>> Claude Shannon. Also, I'll give an honorable mention. Uh Alonzo Church is also not mentioned.

[01:05:26]>> Okay. He's like the uh he was the the first to do lambda calculus and is like the reason that like lisp and hasll and all these like programming. So >> little shout out.

[01:05:37]>> Uh mine mine's not a hot take so much as a disclaimer which is this book is very like Uncle Bob. It's a passion project by Uncle Bob. There will be some things you might hear in it and roll your eyes a bit and be like Uncle Bob's political opinions. He he likes to display on Twitter. Um, however you think of it, I do think there is something to be said for whether or not you agree with him or not. There's a bit of like separate the art from the artist. Um, but uh I I I enjoy Uncle Bob. I think there's something about someone who's just very opinionated. And even if you think those opinions are wrong, I can appreciate having those opinions. But if you're someone who just has this need for your opinions to kind of be constantly confirmed to you, like, yeah, don't read Uncle Bob's stuff. Um, but if you're someone who can instead hear an opinion and just kind of go, "Oh, that's just Bob being Bob, right?" Uh, then um then you know, I I like his work. I think it's it's always at least interesting.

[01:06:31]Um, what are we going to do differently in our career or or No, no. What? Unless you have a followup.

[01:06:35]>> Um, no, no, no. I uh I I definitely want to read um I want to read a biography on John Vanoyman. I think that was the thing. I He's such a fascinating person.

[01:06:46]Like I've I've seen him touch certain areas. Also, quick quick note, I was wrong. He did mention Alonzo Church briefly. So, okay. I think he was a student of Hilbert, but um there was no section on him. So, and again, you have to edit somehow.

[01:07:00]>> But, uh >> um for me, I want to not be Charles Babage in that I want to finish what I start. And especially at a startup, it's so tempting to just do that 80% and say it works. And the project I'm working on in particular, like I think we finally just hit like that finally. We've been working on this for a week. I think we've hit like that 80% of like, okay, this is like we could ship this theoretically, but there's so much beyond that with like reliability and monitoring and just kind of general UX polish that I really want to be good about, um, before rolling it out to customers. So, um, love you, Babage.

[01:07:36]>> I'm going to I'm going to take a contrarian take here, which is I want to be Babage. I would love to have a legacy of like this man worked on the most useless things or what felt like the most useless [laughter] things and then 200 years in the future they're like that guy he saw a vision of the future and it like and I'm just like unburdened by the practicality of actually making it something viable. I that sounds awesome. I would love to be remembered [laughter] in the history books for just like that dude had a lot of fun. He was so distracted and like touched way too many things uh but he had an influence on others. Like I that seems like a dream to me.

[01:08:12]>> You're you're like my older brother. Um he's always up to he's always up to some scheme. Um very very smart guy. But like uh Fourth of July fireworks were banned in Utah this year which is lame because it's 250th anniversary just because it's been so dry and you know I support it.

[01:08:25]Like let's not light our state on fire.

[01:08:27]But so people at work were asking like what did you do instead of fireworks?

[01:08:29]I'm like well luckily in my spare time my brother built a trebuche and so we launched like water balloon.

[01:08:36]I know right. like he's he's he's doing stuff like that all the time.

[01:08:39]>> I had a good friend in in high school and he was like yeah he would build guitars from scratch. He would he built a trebushe and I mean it became this multi-year thing where his trebushe just kept getting more and more advanced >> because you have to learn you know because you have to learn how >> of course >> you have to teach you're like how far could I launch this and like can I tune the release so that it's actually at the optimal angle.

[01:08:59]>> Fun. I love that stuff. Um, also I was half expecting you to be like he got into um, you know, uh, drone. Uh, >> yeah, I thought >> he probably will.

[01:09:11]>> Yeah, [laughter] he he makes drone matrix uh, art in the sky.

[01:09:18]>> Um, as far as book recommendations, I'd recommend this to anyone. This is a the audio book is great. Uncle Bob does a great job narrating it. Um it it's a fun little history lesson and just uh you can read about all of these people but it and other methods but it's so cool reading about this where like the audience is programmers right and and it's written by Uncle Bob who say what you will about Uncle Bob he loves programming it is so clear how much he loves the act of programming and so someone who loves it so much uh writing about all the people that have inspired him um is really really fascinating. I remember he he mentioned this book I think when we first interviewed him that he was working on it. I was like, "Huh, like interesting." I that's not the book I would write necessarily. Um but I think that's what makes it so great.

[01:10:04]It's a passion project for him and that passion shines through in every sentence. So yeah, anyone pick it up.

[01:10:10]It's a fantastic book.

[01:10:11]>> Yeah, it's I'd say it's in the same category as Unix, a history and a memoir that Knean wrote. Uh, it's just we need I think somebody in the comments last week who talked about this because we mentioned this and I I thought it was important that we know our history.

[01:10:25]>> This is a a great example of a very approachable way to kind of peique your interest and let you dive deeper. You know, there's a lot of inspirational, >> beautiful stories of like how did we get here? And I think that he does a a masterful job of making this approachable.

[01:10:43]>> Yeah, it's a great book. Uh, we're excited to cover it. uh throughout the weeks. Um but in the meantime, yeah, you can uh check us out on our website at bookoverflow.io. You can contact us at contactbook overflow.io. We're on Twitter at bookoverflop pod. I'm on Twitter, Carter Morgan. Nathan has worked for his consulting agency, Rojo.com with his newsletter atnewsletter. Uh thanks so much for uh sticking with us, folks. We're excited. We'll be back next week with more from Uncle Bob and we programmers. See you around. See you.

[01:11:19]>> [music]