WEBVTT Kind: captions Language: en 1 00:00:11.934 --> 00:00:23.834 I'd like to thank Augment Code for sponsoring this first season of Still Burning. I can remember my excitement when I saw my first IDE. You could find anything, you could 2 00:00:23.834 --> 00:00:28.834 change any code, and I was just so excited. But the era 3 00:00:28.834 --> 00:00:37.767 of making changes to code like a watchmaker is gone. Most of the changes now are going to be made by the Genie, and Augment 4 00:00:37.767 --> 00:00:45.534 Code is helping go beyond the IDE with their new intent product. Programmers stay oriented, they 5 00:00:45.534 --> 00:00:54.033 keep learning, they see what's happened, they make strategic decisions, and meanwhile, agents go and do the detailed work. 6 00:00:54.033 --> 00:01:03.467 The gap between an idea and a running system has never been narrower, and that's exciting. The gap between a running system 7 00:01:04.567 --> 00:01:05.667 and a mature, 8 00:01:05.667 --> 00:01:10.200 fully running system is the same as it ever was. 9 00:01:10.200 --> 00:01:19.033 And the difference is not feature set, the difference is trust. Security, auditability, identity, the list of items a CISO 10 00:01:19.033 --> 00:01:35.167 hands you before your system will run in their system. Teams try to tackle this themselves. How hard could it be? It turns out that this is both a very important problem and a very complex problem. 11 00:01:35.167 --> 00:01:40.767 That's where WorkOS comes in. Single sign-on, identity providers, 12 00:01:40.767 --> 00:01:50.200 role-based access management. WorkOS gives you the infrastructure to trust the systems that you're excited to have built. 13 00:01:50.200 --> 00:02:19.467 Welcome to a very special edition of Still Burning, where we talk to geeks who still care and are still doing something about it. And I have a very special geek to share with you. My oldest, Bethany Andrews Beck, who's running for Congress in the 6th Congressional District of Massachusetts, and is also a high-level geek. Beth, welcome so much to Still Burning. 14 00:02:19.467 --> 00:02:21.334 Thank you so much for having me. 15 00:02:21.334 --> 00:02:23.601 Yeah, I've known you for a while. 16 00:02:23.601 --> 00:02:24.534 Couple years. 17 00:02:24.534 --> 00:02:33.167 Couple years. And so let me start with the question I always ask, which is, when did you first know that you were a geek? 18 00:02:33.167 --> 00:02:42.968 So the first pun I ever made was cheese-related. Okay. And we'd gone to the refrigerator. 19 00:02:42.968 --> 00:02:44.301 Forgive me for not remembering. 20 00:02:44.301 --> 00:02:46.701 I mean, why would you? 21 00:02:46.701 --> 00:02:47.267 (Laughs) 22 00:02:47.267 --> 00:03:01.267 And I said, but that one's cheddar. And I was so proud that you laughed. And that's it. That was the start of all of this. 23 00:03:01.267 --> 00:03:01.901 (Laughs) 24 00:03:01.901 --> 00:03:06.334 Okay. So that's a word geekdom. Right. 25 00:03:07.868 --> 00:03:09.901 How about computer geekdom? 26 00:03:11.334 --> 00:03:12.035 Ooh. 27 00:03:13.100 --> 00:03:24.601 Ooh. I really enjoyed a game called Widget Workshop. Yes. Where you built circuits and programs out of 28 00:03:25.801 --> 00:03:35.167 sort of anthropomorphized, like a switch was a rail switch, and a timer was dropping an elephant on Mars or something. 29 00:03:36.267 --> 00:03:36.667 And 30 00:03:37.501 --> 00:03:46.100 piecing together programs out of fun components. And making it do the thing that you wanted it to do. 31 00:03:47.834 --> 00:03:48.334 And 32 00:03:49.901 --> 00:03:54.035 at what point did you know that not everybody shared these interests? 33 00:03:56.501 --> 00:04:05.801 This is a sad moment of separation in the life of every geek. You think, oh, the world's this amazing place full of puzzles. And then you realize, oh, I'm kind of alone. 34 00:04:05.801 --> 00:04:10.701 Well, I think for me, it was actually interesting. I met, 35 00:04:12.067 --> 00:04:24.035 one of our friends' kids had some learning disabilities. And I was trying to teach him something and it wasn't working. And his brother explained, well, he always teaches, 36 00:04:25.301 --> 00:04:27.801 thinks different. And 37 00:04:29.267 --> 00:04:43.334 I realized that there were ways that other people interacted that were different than me. And to play, to like interact with them, you have to figure out the puzzle of 38 00:04:44.768 --> 00:04:47.200 what is it that they enjoy? 39 00:04:48.334 --> 00:04:51.868 What engages them? Because everybody is interesting in some way. 40 00:04:52.935 --> 00:04:58.868 Now that's a level of empathy that a lot of geeks struggle to achieve. Sounds like you had that early. 41 00:04:58.868 --> 00:05:01.001 People are fascinating. 42 00:05:01.001 --> 00:05:08.067 Oh, God. And I think that helps. People are annoying. And I wish they'd all just... Really? Go away, yes. 43 00:05:08.067 --> 00:05:08.801 Oh. 44 00:05:08.801 --> 00:05:10.200 I mean, not you personally. 45 00:05:10.200 --> 00:05:12.935 I appreciate that. But no, no, I 46 00:05:13.935 --> 00:05:25.701 think of it as the thing that's least, or that's most human. Like the thing that makes us people is the ways in which we're different. And we all bring 47 00:05:26.834 --> 00:05:39.634 something different to whatever collective endeavor we're doing. And there's always something we can't do. Like nobody can fly, right, without help. Yes. And 48 00:05:40.834 --> 00:05:51.501 if you want to achieve things that you can achieve by yourself, then like my capabilities matter. But if I want to achieve something that I can't achieve alone, 49 00:05:52.501 --> 00:05:58.200 then the question is what is the group of people who care about this thing? How do we 50 00:05:59.601 --> 00:06:04.200 collaborate? What makes it enjoyable? What makes it rewarding? 51 00:06:05.267 --> 00:06:06.067 And 52 00:06:07.134 --> 00:06:14.501 it lets us do things that I would get bored if I could only accomplish the things that I can accomplish by myself. 53 00:06:14.501 --> 00:06:16.200 Yeah, okay. 54 00:06:17.434 --> 00:06:21.200 I think I backed into that reluctantly. 55 00:06:23.067 --> 00:06:32.001 Which is probably why I write books and speak and so on, to accomplish more than I can accomplish myself. 56 00:06:33.100 --> 00:06:38.801 So tell me about some of your other geek-toms. You're a multifaceted geek. 57 00:06:38.801 --> 00:06:40.067 I am. 58 00:06:41.100 --> 00:06:51.467 I have started, my degree is in theater. Which is very much the study of people and how do we come together and build stories and 59 00:06:52.734 --> 00:06:54.501 talk about being people. 60 00:06:56.434 --> 00:07:01.401 And all of the context that we bring with that. So I got to study 61 00:07:03.167 --> 00:07:13.200 ancient history to modern day. What are the technologies of clothing? How does that influence what people wear and what that says about them? 62 00:07:16.434 --> 00:07:17.234 It turns out there, 63 00:07:18.334 --> 00:07:21.234 what shirt do I put on in the morning is a fascinating question. 64 00:07:21.234 --> 00:07:25.167 Okay. If you go deep enough. It's not just whatever's on top. 65 00:07:25.167 --> 00:07:27.801 Right. It doesn't have to be. It can be. It can be. 66 00:07:27.801 --> 00:07:28.401 Yeah. 67 00:07:28.401 --> 00:07:28.801 Yeah. 68 00:07:28.801 --> 00:07:32.567 Well, I tend to go beyond the what's on top. 69 00:07:32.567 --> 00:07:33.868 Yeah, yeah. 70 00:07:34.935 --> 00:07:37.301 So I remember the chicken phase. 71 00:07:37.301 --> 00:07:45.001 There was the chickens, yes. Actually, I was telling you with some of my references, like what made why chickens? 72 00:07:45.001 --> 00:07:46.601 That's a great question. 73 00:07:46.601 --> 00:07:51.234 Right. They do fit on not very much land, which helped. Yeah. 74 00:07:52.301 --> 00:07:52.367 And 75 00:07:54.200 --> 00:07:56.134 the roosters really were out to get me. 76 00:07:56.134 --> 00:07:57.067 Yes. 77 00:07:57.067 --> 00:08:01.701 Oh yeah. And so it was exciting in 78 00:08:02.968 --> 00:08:11.234 like slightly terrifying. Stimulating. Like they were quite large compared to small children. Yeah. And then they were delicious. 79 00:08:12.334 --> 00:08:18.801 Yes, we went through that part of the, we completed the cycle of life. Yes, yeah. All the way to dinner. 80 00:08:18.801 --> 00:08:21.701 Yeah, and as a kid, there's 81 00:08:23.067 --> 00:08:32.734 something really real about, like oftentimes you're watching shows about things, or you're reading books about things, or someone's telling you about things. 82 00:08:33.768 --> 00:08:38.534 And the chickens are really there, and those spurs are really sharp. 83 00:08:39.734 --> 00:08:46.334 So you're forced to be present in a way that you aren't if you're just viewing something on a screen. Right. 84 00:08:46.334 --> 00:08:51.634 And then I met other adults who knew lots of things about chickens. 85 00:08:51.634 --> 00:09:01.200 And we're delighted to share them with somebody who looked interested. Right. Because the average person is not gonna get lit up about 86 00:09:03.200 --> 00:09:03.834 chickens. 87 00:09:05.100 --> 00:09:05.734 But I 88 00:09:07.234 --> 00:09:15.467 think one of the things that I bring is that I get really interested in a lot of things. You know, at a facet, one of my friends 89 00:09:16.567 --> 00:09:18.768 leads road repair projects. 90 00:09:18.768 --> 00:09:19.634 Okay. 91 00:09:19.634 --> 00:09:43.001 One time we had a fascinating conversation about the way that they grind down roads before they repave them. Okay. Because he thinks a lot about how do you grind down a road before you repair them. I'm glad somebody does. Right, and I think following your interest is one of the joys of being a geek, is following your curiosity and finding that joy. 92 00:09:44.200 --> 00:09:46.968 What is it that people care about? Because there's always a reason. 93 00:09:48.901 --> 00:09:56.035 Like the through line of all my different interests is that there's always a reason, people do things for reasons. 94 00:09:57.467 --> 00:10:03.935 And there may not be reasons I agree with, there may not be reasons we think of as noble, 95 00:10:05.167 --> 00:10:17.768 there may not be reasons that anyone has thought through, but there's always something that influences you, nudges you, maybe the button's orange instead of blue, and you're more likely to click it by like 20 plus percent. 96 00:10:19.301 --> 00:10:28.167 And when you think about that, then you can go about solving problems like no one's writing tests 97 00:10:29.601 --> 00:10:37.701 in ways that you don't get to if you're starting, if you're not curious about why people aren't writing tests. 98 00:10:37.701 --> 00:10:40.567 Okay, so we've dived right to programming. 99 00:10:41.768 --> 00:10:47.434 What reasons have you found for people not writing tests? I 100 00:10:49.100 --> 00:10:53.968 taught you, your first lessons in programming were to remind me to write tests, 101 00:10:55.001 --> 00:11:14.868 and then you were supposed to remind me if I didn't write the tests. And then I don't know if this actually happened, but I remember it. Clearly being very, you said, do you have a test for that? And I said, oh, honey, we don't need a test for this. And then it broke later and I realized, oh, gah. 102 00:11:14.868 --> 00:11:30.935 It was date printing. Okay. It was printing a date, and it turned out the format that Smalltalk had in its date printer was wrong, which is also, which I remember, because that was like the idea that somewhere down there, there's something that tells it how to print. 103 00:11:31.935 --> 00:11:38.501 I also asked you what a hash function was in that, and you declined to explain hash functions to a nine-year-old. 104 00:11:40.001 --> 00:11:43.601 That shows a lack of imagination on my part for sure. 105 00:11:43.601 --> 00:11:47.901 I mean, you've learned some things, a couple years, I'm like, how would I? 106 00:11:49.601 --> 00:11:50.001 (Laughing) 107 00:11:50.001 --> 00:11:53.100 Yeah, that one still may be beyond my powers. 108 00:11:53.100 --> 00:12:09.501 But that was, yeah, it was, and then I went and got a degree in theater, worked in a hospital, checking people in for a couple of years, waited tables for a bit, and then got my first programming job, and then I didn't write tests for the next seven years. 109 00:12:09.501 --> 00:12:16.001 Okay, so why weren't you writing tests? This is not in a finger-wagging way. 110 00:12:16.001 --> 00:12:18.668 No, no, genuinely, it 111 00:12:20.367 --> 00:12:27.935 was an interesting question because I sort of knew that you were supposed to, right? And then I'm writing-- I did my best. Here I'm writing C++. 112 00:12:29.634 --> 00:12:40.401 There is no testing tool, the off-the-shelf, ready to go, and the IDE that I was using at the time, which was like the free version of 113 00:12:41.935 --> 00:12:43.601 Visual Studio, straight? 114 00:12:44.901 --> 00:13:13.935 So very bare bones, and I didn't have any examples. This was before we had all of the stack overflow on the internet, so this is far enough ago that I was reading things from paper books. Like, later I was working in Java, and I picked up Spring from a book in Japanese, which I do not speak in any way, but all the example code is in English, so I had no context except the code snippets in this paper book to figure out how to make the thing work, right? So in ye dark ages, 115 00:13:14.935 --> 00:13:21.367 how do you figure out what to test, what the format of a test is? 116 00:13:23.134 --> 00:13:43.067 And it wasn't something that I had examples for. And even when I went onto my next job, which was much stronger software development practices, we have 20-year-old code base that's remarkably clean, extremely stable, 1% test coverage. 117 00:13:44.701 --> 00:14:04.634 We had incredibly clean design that let you reason about the code in ways that tended to prevent the worst errors, but we just didn't have those kinds of tests. And what it turned out, part of what it was for me was learning how to write testable code first. Yes. So I learned to write testable code. And then 118 00:14:05.834 --> 00:14:21.467 I, and actually remember someone coming to me and being like, "Oh, I found this feature you wrote "all while ago, and I wanted to tell you "it's beautifully laid out." It was so easy to pick up, understand. It's just, you didn't have any tests for it, but they were really easy to add. 119 00:14:23.534 --> 00:14:29.167 And so I went and I looked at what Tessie wrote. And now I've got examples. And then I 120 00:14:30.301 --> 00:15:00.167 was doing my very first management role ever. And I decided I was just going to like brute force this a little bit. And I started just spending time figuring out how to test this old untest like legacy code that's not written with any idea of Tess in mind. And I just started writing down all of the things I did for that. And I started doing presentations. And every time I'd say, "Well, I'm on the mobile team "and we write Tess." 121 00:15:01.401 --> 00:15:01.935 And we... 122 00:15:01.935 --> 00:15:07.167 It's a remarkably powerful leadership technique. It's to just pretend. 123 00:15:08.567 --> 00:15:17.100 Well, it's a, like, maybe we aren't doing it right now, but we do-ish. So we hope to. 124 00:15:17.100 --> 00:15:23.467 Doing that phrasing of it, if you didn't write Tess, you would feel not part of the mobile team. 125 00:15:23.467 --> 00:15:42.534 Exactly. And so when you don't write a Tess, you think, "Why am I not doing it?" And then, and what happened is I would go into code reviews and instead of pointing out bugs, I would point out the Tess that was missing. So every time someone wrote a Tess, it caught a bug. And that dopamine loop is just so powerful. 126 00:15:42.534 --> 00:15:51.734 Oh yeah, when you write the Tess and you predict red and it comes up red, and it's exactly the exception you predict that it would be. 127 00:15:53.467 --> 00:15:54.935 And for a bunch of the 128 00:15:56.134 --> 00:16:07.267 people I was working with were straight out of school. Yes. So they'd write the Tess not knowing it was gonna be, they didn't realize there was a bug there yet. And so they discover, each Tess is a discovery. 129 00:16:07.267 --> 00:16:07.935 Right. 130 00:16:09.935 --> 00:16:15.567 Is that a bigger rush than having the Tess pass when you think it's gonna pass? 131 00:16:15.567 --> 00:16:28.067 Oh yeah. Like, oh, it worked great. That's nothing like, I think what's really exciting is when you discover something that you didn't expect to see. 132 00:16:29.134 --> 00:16:30.134 Yes. 133 00:16:31.401 --> 00:16:41.501 Yeah, yeah, especially if you can then look at it and go, "I'm so glad that didn't make it into production." Right, 134 00:16:42.968 --> 00:16:50.834 yeah. So now how can we get the genie to get excited about writing Tess predicting red? 135 00:16:51.968 --> 00:16:55.668 It's actually red, woo, it packs itself on the back. 136 00:16:55.668 --> 00:16:58.234 So first it needs an endocrine system. 137 00:16:59.567 --> 00:17:18.734 So genies don't have enthusiasm, excitement. Like those things are things that we give to, like I think right now, or I think of the collaboration, the thing that exists is us plus the genie. Yeah. It's not, the computer is just a lump that sits there. 138 00:17:19.801 --> 00:17:41.834 And like a human brain is never gonna just sit there because we're constantly seeing things and hearing things and experience and having feeling hungry, maintaining our blood pressure, you know, avoiding passing out all of these things that our bodies do all the time. And the computer doesn't have any of that to do. 139 00:17:44.267 --> 00:17:49.301 And so we are the thing that makes it excited about writing Tess. 140 00:17:49.301 --> 00:17:54.701 So why is it that there's such a temptation to 141 00:17:55.935 --> 00:17:57.668 make like 142 00:17:59.935 --> 00:18:23.701 agents, it was gonna be this independent thing that was gonna do a bunch of work. And then we realized, oh no, it's actually in a feedback loop. And now the next version of that is looping. We just say, well, just keep doing this until you're successful. We keep trying to write ourselves or draw ourselves out of the picture. Where does that, 143 00:18:24.734 --> 00:18:26.734 where's the motivation for that come from? 144 00:18:26.734 --> 00:18:31.834 It's an interesting question. One thing I keep talking about is, 145 00:18:33.100 --> 00:18:46.001 because one thing that comes up is like, oh, we can have medications prescribed by agents. Well, no, you can have, what you're saying is patients will prescribe their own medications as long as they use this program to do it. 146 00:18:47.601 --> 00:18:48.301 And 147 00:18:49.401 --> 00:18:57.134 if you skip that part, you miss that the company writing the agent isn't taking any responsibility. 148 00:18:57.134 --> 00:18:58.301 Right. 149 00:18:58.301 --> 00:18:58.634 Right. 150 00:18:59.768 --> 00:19:15.935 They aren't saying, oh, I, like if you go to the doctor, you may not even have been complaining about blood pressure. And if your blood pressure is high, they will say you need to take this thing, right? And it's a different, 151 00:19:17.868 --> 00:19:30.035 when I think there's the 10, there's a nervousness about humans. Like there's a nervousness about including humans just in things in general. We like to talk about 152 00:19:34.868 --> 00:19:44.634 automated scientific things as not involving people. Objective performance reviews. Yes. Are one of my bugaboos. Because if you 153 00:19:46.067 --> 00:19:49.701 don't have a subject, there is nothing judging anyone. 154 00:19:49.701 --> 00:19:50.334 Right. 155 00:19:50.334 --> 00:19:53.734 Right. And you can't-- 156 00:19:53.734 --> 00:19:56.367 Just say nothing that they're incredibly easy to gain. 157 00:19:56.367 --> 00:20:40.100 Oh, right. Like also the, it's a, well, as soon as you tell people that something's objective, you can get away with making it incredibly biased and they will completely look over that because, oh, clearly it's objective. And so you get more biased systems by pretending that they are objective than admitting where subjectivity matters. And actually we don't care whether someone is objectively good at their job because we don't have a platonic ideal of a job for them to do. We have this particular job for them to do. And if they are bad at that job, it doesn't matter how good they are at some perfect job out in thought space, right? We actually have to be good at the thing that we're trying to accomplish. 158 00:20:41.167 --> 00:20:45.134 And that's not an objective goal. It's the thing that's a subjective goal. 159 00:20:46.768 --> 00:20:55.501 Plus the system is so complicated. There's all these feedback loops and there's lots of other people involved and there's long-term versus short-term. 160 00:20:55.501 --> 00:20:57.601 And this is how you get, 161 00:20:59.801 --> 00:21:04.334 you get systems that reward behaviors that you don't actually want out of all of it. 162 00:21:05.401 --> 00:21:09.768 But I think that there's a tendency to avoid responsibility. 163 00:21:10.801 --> 00:21:18.367 We don't wanna feel responsible for the things that are happening, especially if they're not our, we don't feel like they're our faults. 164 00:21:18.367 --> 00:21:28.035 Yeah, well that hurts to be, to have consequences flow to you for something you didn't do. Right. That just triggers all of the, this is unfair. 165 00:21:28.035 --> 00:21:46.200 Which is the job of management. Yeah. And it's why the transition from writing code to management is so hard for so many people is because you go, now you are responsible for things you have no control over. And the more control you try to have over them, the worse the outcomes are going to be. 166 00:21:46.200 --> 00:22:19.167 Yes, which makes the, this shift to, let's just have the managers and we'll eliminate the individual contributors. That responsibility comes crashing back a hundred percent. Yeah. This reminds me of a story I read the other day where a autonomous vehicle whipped an illegal U-term right in front of a police car. And the police car pulled it over and it pulled over and they went to give the ticket and there's nobody in the car. Yeah. It's like, 167 00:22:21.067 --> 00:22:30.968 somebody, it was illegal, it was unsafe. There needs to be consequences for somebody and there's just nobody to have consequences for. 168 00:22:30.968 --> 00:22:31.567 Yeah. 169 00:22:32.601 --> 00:22:46.301 Yeah, and if you, when we've written a set of rules for a world where only people take action and you can't erase yourself, because someone made that decision but it wasn't there and it wasn't then. 170 00:22:46.301 --> 00:22:46.701 Yeah. 171 00:22:46.701 --> 00:22:52.401 Sometime in the past, some programmer, let that be a constraint that could be relaxed. 172 00:22:54.401 --> 00:23:29.701 And sometimes you want those, but I wrote, I was writing, when I was first writing self-driving car software back in 2008, we were doing the DARPA Grand Challenge and they would take the cars and they'd run them through an urban environment. And we had programmed ours, if you get stuck, if you can't move, relax constraints until you, you figure out how to get yourself out of it. And they had a place where they had blocked off a road with like a temporary roadblock. So our car sits there and thinks for a little while. And then the constraint it relaxed was the one that says, don't drive on sidewalks. So it just drove up on the sidewalk and drove around. 173 00:23:30.801 --> 00:23:31.668 How creative. 174 00:23:31.668 --> 00:23:32.434 Right. 175 00:23:32.434 --> 00:23:33.401 (Both Laughing) 176 00:23:33.401 --> 00:23:35.301 You could be so proud at that moment. 177 00:23:35.301 --> 00:23:45.668 Right, and you're like, I understand what my software just did. And also that was not what I would have liked my software to do in that moment, right? So it 178 00:23:46.768 --> 00:23:50.534 helps to have interacted with systems like 179 00:23:51.534 --> 00:24:04.200 this in some ways for a very long time. Because if you just encounter it for the first time, it feels like magic. Yeah. It feels like something that usually you only get when there's a mind behind it. 180 00:24:06.035 --> 00:24:17.968 And so the simplest explanation is, oh, look, I'm talking to a person. Or, oh, look, the computer is driving the car. Well, no, the software some programmer wrote at some point is driving this car. 181 00:24:17.968 --> 00:24:22.968 And the software some programmer wrote under some set of incentives 182 00:24:24.534 --> 00:24:25.868 created by 183 00:24:26.935 --> 00:24:39.734 the organization they were in, and also the influence of what they ate that morning and whether they had a fight with their spouse. Like there's a lot that goes into it. 184 00:24:39.734 --> 00:24:41.167 And venture capital. 185 00:24:41.167 --> 00:24:48.067 Right, what financial arrangements where that creates incentives also. 186 00:24:48.067 --> 00:24:58.334 Which other companies the board is invested in. What laws, tax, what tax laws? Like we saw when Trump cut 187 00:24:59.534 --> 00:25:05.968 the amount of research and development deductions in year one that 188 00:25:07.001 --> 00:25:10.834 it changed how companies were structuring their engineering departments. 189 00:25:12.868 --> 00:25:16.567 And that's gonna flow through to all the downstream decisions. 190 00:25:16.567 --> 00:25:19.301 And so I think in some ways, 191 00:25:20.701 --> 00:25:48.401 one of my favorite shows is "The Good Place." And the conclusion of the show along the way is, the world is so complicated that we can no longer tell what the outcome of any of our decisions are. So how could you possibly know whether it's a good decision or a bad decision? And I think that that's overstating it because usually we can figure out why. It's very easy to feel like these are things we can't change. 192 00:25:49.534 --> 00:26:07.901 Oh, I get to tax like, oh well. I think this is where being a geek helps because you can get around a lot of these with creativity. Whether it's cultivating a sense of resentment. Oh, they told you to do your job badly. 193 00:26:09.234 --> 00:26:17.768 I think almost everybody's been asked at some point, well, how long would it take you to write if you didn't write the test? Yeah, that's, yeah. Even if the answer is 194 00:26:19.601 --> 00:26:24.834 one and a half times as long as it's gonna take me when I don't have to debug all of those bugs. 195 00:26:25.935 --> 00:26:31.434 But just channeling that into like doing the thing more 196 00:26:32.668 --> 00:26:39.301 is a useful instinct to help people. Oh, instead of getting mad about it, 197 00:26:40.567 --> 00:26:46.267 just realize it's your fingers on the keyboard and write more tests out of defiance. 198 00:26:48.267 --> 00:26:54.968 I remember one of the favorite moments you told me there's a kind of 199 00:26:56.601 --> 00:27:57.134 a workers strike called work to rule. Whereas if you have all these rules about exactly how you're supposed to do everything in a factory and the strike is the workers do exactly what it says in the book and nothing else. And your proposal was that we would have programmers perform one of these work to rule strikes and they had to refactor and they had to write tests and they had to integrate frequently and they had to collaborate. And the, but the problem with that as a strike technique is that you'd be so much more productive as a consequence. Right, yeah. Oh, yeah. We do know how to write good software, which is the title of a talk that we gave together. One of my highlights of my career was doing a keynote with you. And you had come up with this metaphor of the forest and the desert as a way to explain the difference. 200 00:27:58.534 --> 00:28:10.534 Some people think that they're, you can write some tests, you can not write some tests and doesn't really change anything. Like it's a smooth transition and maybe it's a little worse or a little bit better. 201 00:28:11.801 --> 00:28:12.334 And I think 202 00:28:14.634 --> 00:28:18.668 we share an optimism that no, things really could be much better. 203 00:28:22.834 --> 00:28:28.167 And we're baffled sometimes that people choose not to make, they choose worse. 204 00:28:29.801 --> 00:28:31.467 Everybody can be better off. 205 00:28:31.467 --> 00:28:36.001 Well, depending on what we think better is. 206 00:28:36.001 --> 00:28:36.567 Yes. 207 00:28:36.567 --> 00:28:41.001 And this is where having that instinct of asking why, 208 00:28:42.834 --> 00:29:10.501 like what is different about this? Is there is a useful mental loop to have of, oh, the people do things that don't seem to make any sense. Okay, what's the reason? And that's how we came to the forest and desert was asking why, so you came up with this way of writing software. Yeah, and then people proceeded to not do it. Yeah. 209 00:29:12.501 --> 00:29:17.301 And in fact, teams would do it. Be successful at building software and get fired. 210 00:29:17.301 --> 00:29:18.935 Yep, over and over. 211 00:29:18.935 --> 00:29:27.768 Over and over. Because it didn't take into account what it was that management actually wanted, which wasn't working software. 212 00:29:29.100 --> 00:29:38.935 Yeah, yeah, yeah, productivity was not the point. Reliability was not the point. You can deliver those, more of those things and less of other stuff 213 00:29:40.434 --> 00:29:41.367 and then you get fired. 214 00:29:41.367 --> 00:29:41.868 Right. 215 00:29:43.567 --> 00:29:46.601 Which is part of why I'm less 216 00:29:47.668 --> 00:29:55.401 worried about our jobs than some people. I think the thing the AI agents do give managers is a sense of control. 217 00:29:56.501 --> 00:29:59.001 They do exactly what they're told, ish. 218 00:29:59.001 --> 00:29:59.868 Yes. 219 00:29:59.868 --> 00:30:02.467 Not aspiring to mediocrity. 220 00:30:02.467 --> 00:30:03.035 Yes. 221 00:30:04.567 --> 00:30:06.634 They hope to rise to the level of mediocre. 222 00:30:06.634 --> 00:30:09.534 Yeah, they're trying to get to average. 223 00:30:10.534 --> 00:30:13.167 But they will do what you tell them to. 224 00:30:14.467 --> 00:30:24.167 And you get to feel like you're in control of this set of things. But that also means that it's your fault when it doesn't work. 225 00:30:24.167 --> 00:30:24.534 Yeah. 226 00:30:25.534 --> 00:30:32.534 And it means that if it's not working, you don't have 227 00:30:36.200 --> 00:30:46.768 collaborative levers to pull. Right. Right, one of the things I do as a developer is talk to executives and say, "Ah, if you would like more of this thing, 228 00:30:48.634 --> 00:30:56.167 you're telling the developers this and so they are never going to give it to you." If you stop saying this, you can get the thing you want. 229 00:30:58.768 --> 00:31:05.768 So what awakened the geek in you around politics? 230 00:31:07.901 --> 00:31:23.567 A little bit, Howard Dean's campaign was the first one that spoke to the issues I was seeing. And he told the story of here is why things are the way they are and here's how they could be different. 231 00:31:24.601 --> 00:31:35.467 And was talking about problems that I saw and then other people didn't seem to think were problems. And I think that's a very powerful moment. 232 00:31:35.467 --> 00:31:36.267 Do you have an example? 233 00:31:36.267 --> 00:31:50.367 Like student debt. Okay, this was-- Housing prices back before that was a thing. Like we were talking about it now, right? Many, many years later. 234 00:31:51.768 --> 00:31:56.601 And it was partially that he was ahead of his time. So he did not have, he was telling 235 00:31:57.668 --> 00:32:00.701 a story that resonated with the people who had already noticed. 236 00:32:02.267 --> 00:32:05.901 But he was, if you're the first person telling a story, 237 00:32:07.768 --> 00:32:10.001 your audience is gonna be a lot more limited. 238 00:32:11.401 --> 00:32:12.134 And-- 239 00:32:12.134 --> 00:32:13.901 Well, you just sound like a whack job. 240 00:32:13.901 --> 00:32:18.868 Or you just sound like a whack job, which is why you go yee-haw and then everyone makes fun of you for a while. 241 00:32:20.035 --> 00:32:21.234 But the, 242 00:32:24.067 --> 00:32:43.834 so that started it. And then it was really the Occupy movement because we had this very concrete problem of a lot of people were out of work. So 18% of millennials did not have jobs. And I started talking about cutting unemployment benefits after they had bailed out the banks. 243 00:32:45.501 --> 00:32:51.035 And it started very simply. Someone was just like, "Hey, show up at Boston Commons tomorrow, we're all mad." 244 00:32:53.467 --> 00:33:18.634 And so he showed up and there were a lot of people there. And there were some people who had some techniques or how do you get a huge group of random strangers to make a decision? And so we decided where we were gonna go. And then we started taking, we were feeding people. We passed health inspections, right? Figuring out the basic logistics of having a lot of people in one place. 245 00:33:19.834 --> 00:33:38.901 Gives people something concrete to do together. Well, you're also talking about your political, like why would you spend your time being out here in the cold, in Boston? Like what brought you here? Because nobody was there because they were happy with how things were going. 246 00:33:38.901 --> 00:33:42.567 Right, it was not a rave. Right, right. 247 00:33:43.734 --> 00:33:49.567 And realizing that lots of people independently have similar problems. 248 00:33:51.234 --> 00:33:52.200 And 249 00:33:53.868 --> 00:33:58.534 then I took those same technique and there are people who have tools we can use to solve them. 250 00:33:58.534 --> 00:34:00.301 So do you have examples? 251 00:34:02.834 --> 00:34:21.634 Yeah, so one technique I use, I used a lot at work is the, I call it the Guild of Guilds. Because there's the idea that in tech companies you get together a bunch of people who work on similar kinds of things. Maybe they all write front end code, maybe they all interact with a particular 252 00:34:22.734 --> 00:34:37.567 analytic system or work on a particular code base. And those people get together, even if they're on different teams doing different things, you get together every other week, maybe once a month, and talk about what it's like to work on this thing and are there things we could be doing better. 253 00:34:38.935 --> 00:34:49.935 And the trick is to have one extra guild that is the leaders of each of those other guilds. And so then you get them together and they can talk about 254 00:34:51.167 --> 00:35:22.501 what it's like leading one of these. Are you getting a lot of enthusiasm? Are you running into people just yelling at each other? Are you seeing that there's two parts of the company and they're fighting in lots of different guilds? Oh, maybe our incentives are off across the company and we would have never figured that out if it wasn't this group, if we didn't have this group. And then the magic is you make that group open and at each of your other meetings, you say, "Hey, if you're interested in how this meeting runs, 255 00:35:23.668 --> 00:35:36.734 come to the Guild of Guilds because we're gonna talk about it." And whoever shows up is gonna end up leading one of these groups. Like if you are curious about how these groups work, 256 00:35:39.134 --> 00:35:40.801 you will end up in charge of one. 257 00:35:40.801 --> 00:35:42.567 Another form of geekdom. 258 00:35:42.567 --> 00:35:53.367 Right, right. And so it's basically a way of finding the kinds of geeks who are interested in how groups of people do things together. And it creates a 259 00:35:54.401 --> 00:36:06.200 way to get somebody new in so that you're never, someone doesn't quit and then the group falls apart. You always have new people who are interested and enthused and have things they wanna accomplish, 260 00:36:07.467 --> 00:36:17.901 things that they're frustrated by that are motivating them to get involved. And all of that becomes the, makes it into a system that can keep going even after you leave the company. 261 00:36:19.367 --> 00:36:38.567 That's something that I learned because I showed up on the first day and they said, "Hey, anyone who's interested in how this meeting just ran, the facilitation group is meeting over here." And that was a trap. And you do end up immediately with responsibility if you show up to one of the, but it was fun and it was interesting and it's a way to 262 00:36:40.100 --> 00:36:44.035 build teams that can build software together really well. 263 00:36:46.234 --> 00:36:54.234 Yeah, I went through a phase where I was really interested in that kind of group facilitation and I've really gotten away from it and now I'm wishing 264 00:36:55.401 --> 00:37:00.935 that I had a good excuse to get back into it. Tell me this story about your friend, the preschool teacher. 265 00:37:02.401 --> 00:37:23.968 My friend, the preschool teacher. So my friend was telling me about her class and she was teaching a group of kindergartner and one of them figured out how to count beyond the numbers that they had figured, learned how to count. They had learned to count to 30 and they were all counting to 30 together and they finished counting to 30 and he said, "31." 266 00:37:25.868 --> 00:37:30.901 And another little kid looked over and said, "How do you know that?" 267 00:37:32.868 --> 00:37:56.534 And my friend said, "You know, the first kid is smart, "but the second kid is going to go so much further, "so much faster because she wasn't just figuring "the thing out, she was asking, "how do you figure that out?" And so if anyone in the group is smart enough to figure something out, she can take it and figure out what they did and then adopt it herself. 268 00:37:56.534 --> 00:37:57.901 So this is the meta geek. 269 00:37:57.901 --> 00:37:58.834 Yes. 270 00:37:59.935 --> 00:38:01.801 And it is in fact called meta intelligence 271 00:38:02.834 --> 00:38:22.935 and is a thing that you can learn and teach and is an incredibly useful skill to pick up and is something that some kindergartners come with pre-installed and a lot of us have to practice and it means that you can go into any situation 272 00:38:24.035 --> 00:38:34.001 and look at who's being successful and think about why are they being successful? What need are they addressing? Why were they able to 273 00:38:35.234 --> 00:38:46.067 overcome the coefficient of friction wherever they are and start making change? Because the thing that stops us from doing better the most is just we don't think we can. 274 00:38:47.200 --> 00:38:56.067 Right, people don't have that vision. Right. They don't imagine that they can. Right. And then sure enough, you can't. 275 00:38:56.067 --> 00:38:59.935 Right. And sometimes there's a good reason. 276 00:39:01.035 --> 00:39:05.334 Sometimes the reason quit four years ago and nobody has tried since. 277 00:39:06.634 --> 00:39:11.534 And so the way that I tend to find out what stops something from happening is I try it. 278 00:39:12.701 --> 00:39:23.267 And it means that you can't treat, I don't treat failure as a failure. Failure is just me figuring out what was gonna stop me. And then sometimes nothing does and that's boring. But-- 279 00:39:24.334 --> 00:39:24.367 (Laughing) 280 00:39:24.367 --> 00:39:33.467 You fail to fail. Yeah. And then you succeed. Yeah, right. Got it. Okay, last question. What is it that keeps you up at night? 281 00:39:35.401 --> 00:39:39.367 Oh. Yeah, this is a nasty question to finish on, but. 282 00:39:40.801 --> 00:39:44.200 I just got started asking it and then I can't stop. 283 00:39:45.768 --> 00:39:53.634 I think the thing that's so, there's a lot of possible worst case scenarios. 284 00:39:54.701 --> 00:39:58.834 And I'm pretty good at thinking up worst case scenarios. 285 00:39:58.834 --> 00:39:59.768 (Laughing) 286 00:39:59.768 --> 00:40:03.567 And then sometimes they come true and it's, 287 00:40:05.668 --> 00:40:27.868 yeah, I was certainly unfortunate. But it also means that I'm less overwhelmed than other people by what's happening. And so the case I'm most concerned about is not the robots do whatever they want. It's they do exactly what some people told them to do. 288 00:40:29.401 --> 00:40:35.434 Because we know that there are people out there who don't care about the vast majority of humanity. 289 00:40:36.768 --> 00:40:54.768 We know there are people who care about their own power over other people. And we are building technologies that could be a personal army, where you no longer need to collaborate with other people to commit mass atrocities. You just need enough money to do it yourself. 290 00:40:58.334 --> 00:41:03.035 So bring thoughts. Thank you best so much. I appreciate it. 291 00:41:04.267 --> 00:41:05.334 (Laughing) 292 00:41:05.334 --> 00:41:07.901 And that's it. Thank you so much for listening. 293 00:41:09.234 --> 00:41:09.501 Thank you.