The Pragmatic Engineer
00:49:35 · Titus Winters, Gergely Orosz
[00:49:35] S1: And you will not know because things just happen. Right. Like, you said the important keyword. Right? Trust. Right? Like, a substantial part of this is the psychological safety aspect of it. The other thing, which I think is natural for the AI labs but hasn't been nearly as dominant for the rest of the industry yet, is you're learning as you go. And if you look at all of the research, you know, like DORA research on stuff or any research on productivity or team efficacy or any of those things, like, at root, it always boils down to culture, psychological safety, and the the permission to learn. Right? It's the permission to admit that I don't know something. It is the incentive to learn from each other. It is the incentive to share your mistakes so that the team only has to do that once. Your lint rules or SRE postmortem culture. Every effective structure and organization in tech is actually about information flow and learning. And I think a really great perspective on that. I love Kat Hicks, the psychology researcher for tech. Like, her book, The Psychology of Software Teams, is beautiful. And, like, she talks about, you know, these these things a lot. Right? Similarly, there's a platform engineering at Google book that some of my friends are putting out. There's early release chapters on O'Reilly. I might have written the chapter on education for that. [00:51:03] S0: So so very surprisingly slash not surprisingly.
00:51:03 · Gergely Orosz, Titus Winters
[00:51:03] S0: So so very surprisingly slash not surprisingly. [00:51:06] S1: Right? But, yeah, like, education is the powerful route for, like, let's make this mistake a minimum number of times. Let's codify what we've done. Let's give people permission to admit they don't know and to grow because it's not a one off game. It's an iterated game, and you'll do better over time if your team is better next time. [00:51:30] S0: I want to go back to psychological safety because back about five, ten years ago, we kind of would talk so much about it in engineering leadership side side circles. This was pretty well understood that, you know, a good team feels a safe team. If you, for example, make a mistake, you cause an outage as an engineer, like literally, you push a code and that code causes outage. We should have a blameless postmortem where we don't say that, hey, Gergely pushed this code and he caused the outage because that's now, I mean, I feel terrible and... But let's talk about, like, for example, how could have we avoided this at a system Why did a test not fire? Why was it rolled out immediately when he was a new joiner on the team or she was a new joiner to him? Like, maybe some onboarding could have helped yada yada yada. What... How how do you define psychological safety and why is it important? Especially just playing devil's advocate, like, when we're talking about smart engineers who know stuff, like, is it all that important to us? Because we we should know our thing. Right? I'm just like, I'm kinda removing my emotional Yeah.
00:52:26 · Titus Winters, Gergely Orosz
[00:52:26] S1: Yeah. Hat here. Yeah. We should know our thing. Sure. So I would say... And it's been a little hard to, like, root this stat, but from talking with people in DORA, the the research... The one thing that I love was we can explain 30% of the variance in whether or not you... Your team will hit its goals based on how you score on psych culture questions. Right? Like, we could give you a 15 question true false or maybe Likert scale, like, but like a 15 question assessment for the team and predict 30% of whether or not you will hit whatever your goals are. That's insanity. Right? That is more powerful than any other signal. Like, okay. So you think that we're all engineers, and this is all just computers and tech and emotions have nothing to do with it. Find me anything that's even remotely that powerful predictor of success. It's a people problem. Like, period. Right? And going back to... Right? It's it's not a single shot game. It's an iterated game. I regularly cite Fred Brooks in the Mythical Man Month essays. Right? And in the surgical team... Like, the surgical team is my least favorite chapter in that book because it's structured as if we're only ever gonna do one project. Get the best person to do this. Get... Have everyone else build the tools and do the documentation. Under them. It's very [00:53:53] S0: hierarchical.
00:53:53 · Gergely Orosz, Titus Winters
[00:53:53] S0: hierarchical. [00:53:54] S1: Right. And it's very, like, power dynamics mad. Yeah. Right? But it might make sense if you're only ever going to do one task. Instead, we're playing, like, in a game theory sense. It's not prisoner's dilemma. It's iterated prisoner's dilemma. There's a different strategy. And the strategy is find the most junior person that can do it with supervision so that they learn and grow, and you still get a decent outcome. And that next, the higher level people can solve something that they don't know how to do yet or that no one else can tackle. Right? This is the only way to structure it so that growth happens. But in order for that growth to happen, people have to be willing to admit that they don't know a thing. And that brings you straight back to psychological safety and learning culture. Right? If it is a culture that highlights information sharing, learning, and growth, you will succeed. [00:54:52] S0: And and you mentioned that the AI labs probably take this for granted, and I'm gonna Because [00:54:56] S1: they don't know what they're like.
00:54:57 · Gergely Orosz
[00:54:57] S0: Well, I'm gonna paraphrase it. Like, with the AI Labs, a few things going. First of all, business is booming. They are growing. Revenue goes up. Customers goes up. Funding goes up. Headcount goes up. Their teams are only ever expanding. They're on hypergrowth. Like, we... We've seen companies like Netflix and Uber in hyper growth. This is even faster. Your equity also goes up. So you you don't need to worry about things like performance reviews because performance reviews are typically important where, like, how much bonus I'm gonna get, how much. But when you're at a place that goes like this and your equity goes up, your your financial part is taken care of just by focusing on helping the company succeed regardless of your titles. Second of all, because they're building new technology and they know no one knows, so they just tell, okay, I don't know. I'm learning from you. Here's what I learned. So it's just all natural. Whereas compared to a company that might not grow like this, they might still be using, let's say, AI, but now there's less of an incentive to say, I don't know because there's a performance review coming up. You wanna look like the smartest. You don't want people to say like, well, this person says I don't know a lot. Your bonus will be lower. You might be put on a performance improvement plan because you're now at a company that every year lets go of 6% of people. Right. And your goal is suddenly going from like, I just don't wanna be there. I wanna hang on to this job, but it's now hanging on. It's now... Uh-huh. And you also... You're now very of maybe your teammates because now there's an internal competition. You wanna hog that project. Yep. And so this is a huge difference.
00:56:25 · Titus Winters, Gergely Orosz
[00:56:25] S1: Yeah. It's huge. Like, if you get into the mode of believing that the team outcomes are what matter for your own success, then it is much easier for you to realize, like, okay, I don't have to have this one shiny task. Like, the team will be successful by virtue of someone doing this, and it might be my turn next. If when it breaks down into that individualism and, like, I don't trust the guy across the way from me or right shoulder to shoulder to me, even though we're on the same team, we're scraping by and fighting for attention and success, And that's not a recipe for innovation and growth. Like, that is a recipe for stagnation and and just bad. One of the obvious things that I assume, you [00:57:14] S0: know, is is is is... Does not do good for psychological growth or it's terrible for it is layoffs. Can you tell me based on your observation? And and we've seen. Right? Like, you... We've all been part of it. And in 2022, 2023, there has been a series of layoffs. Right right now, companies are doing it again. Back then, it was to do with honest interest rates and and over hiring during zero interest rates and and growth kind of going down. Now some companies are are actually openly saying that it's AI, some are not as openly, but we find out that Meta, for example, wanted to reduce scene sizes because they thought that I will be there. From your observations, at a company where a layoff happens, how does it change how software engineers show up, work, think, speaking both about your experience, the people you talk with?