Lenny's Podcast: Product | Career | Growth
00:10:57 · Lenny Rachitsky, Noam Segal
[00:10:57] S1: Super. So following that thread- [00:10:59] S0: Sorry for the bad news. [00:11:00] S1: Sorry for the bad news. There's some good news here. So following that thread, these buckets correlate super strongly with, basically every other measure of how people are doing. See this kind of regression on just every other core question you asked, and it's so interesting to see how connected these are.
00:11:20 · Noam Segal
[00:11:20] S0: Yeah. And just to put a couple of statistical terms on this to clarify how big the effect is. In tech, we are somewhat obsessed with the notion of statistical significance. But the thing about statistical significance is that, if you have a large enough sample, you can reach that type of significance, regardless of how much the effect matters practically. A better way to look at things is using an effect size measure, like Cohen's d in this case. And what effect size tells you is, practically, how much does this thing matter? So for example, last year, a couple of the largest effects we saw were number one, your manager. Who your mager is and how effective they are matches a ton, to how much you are enjoying your job and how optimistic you are and how burnt out you are or not. And we'll see some of that later on. And the second large effect we found was the founder happiness effect. Founders, these people who are currently founders and in their journey of running a startup, are incredibly happy, probably because they have lots of agency and autonomy, relatively to the typical employee. This finding, this insight around the impact of AI on your identity, and on every single other variable around your job, is about three times as large as those other effects. So this technology, this era that we're in, is having an outlier level, outsized impact on how people are feeling about work, more so than anything else we've seen.
00:13:02 · Lenny Rachitsky, Noam Segal
[00:13:02] S1: So let's actually look at that data of just how this sort of classification connects to just optimism, burnout, things like that. And we're going to come back to just what exactly is that divide, just the question to ask that tells you which side you're on, but let's look at this first. [00:13:16] S0: Yeah, so we'll dive into some of these things in a little more depth later on, but just to put it all together, what you're looking at here is the AI identity stance, and then a breakdown by your AI identity around career optimism, burnout, layoff worry. And, an interesting one for me, and we'll talk about this further, would you recommend your role to someone coming into the industry now? And what you can see is that as you move from the people who feel amplified to the people who feel diminished, career optimism goes down significantly. Burnout, or reports of burnout, go up significantly. Layoff worry also rises significantly. And perhaps the most significant finding of them all, is that people would not recommend junior people, early career people, entering into the tech workforce at this moment given what's happening with AI. And you are seeing these very linear, clear, and organized effects, which just demonstrates to you the impact that AI is having on all of these different variables. [00:14:38] S1: And what I love is you took all of all these data points, and you've created these four archetypes of people today. And I feel like everyone listening is going to be like, "Okay, that's me." So let's go through that.
00:14:50 · Noam Segal
[00:14:50] S0: Yeah. So we're seeing these four tech workers, and the way we got to this is later on in the survey, we asked people about how they're feeling, and to report specific emotions. And people could choose as many emotions as they wanted. And by the way, fun fact, on average, people selected five different emotions, and I think a couple of people selected 13 emotions that they're feeling, which is a lot. So, the first archetype we found is the energized tech worker, and that's 41% of our samples. These are the people who were saying that products has become fun again. "I'm exploring things. I feel like I'm in the tech amusement park, where everything is open to me, and I can experiment with new approaches. I'm a builder now. I have powers that I've never had before," et cetera. These people are very energized about the technology and about their careers. The second group we called the conflicted, the ambivalent middle. These are 35% of the sample. These are people who are having, on the one hand, the most fun they've ever had as builders, as PMs, as designers, as engineers, whatever their role is. And on the other hand, they're feeling the most uncertainty that they've ever felt in their careers. They just don't understand where this is going, and whether they're building the things that will ultimately lead to the end of their careers as they know it. The third archetype are the disoriented people, the people who feel like their role keeps shifting. There's a quote that we saw from one of the respondents, "We're like farmers on the cusp of the industrial revolution and we just don't see a clear path to what's happening." Very interesting comparison to that era. And these are people who are feeling very disoriented around what's going on in their career and where things are leading. And then finally, 12% of the sample we categorized as resentful. They're feeling pressured, they're feeling checked out. They are not enjoying their work right now. They're saying things like, "I've been forced to use AI or lose my job. And even when I use AI, I'm still seeing people lose their jobs. I just hate it. I hate having to leverage this technology, rather than do my own thing, and maybe ignore the technology," which obviously none of us can ignore at this point.
00:17:45 · Lenny Rachitsky
[00:17:45] S1: There's a lot of people clearly that are very unhappy, resentful, disoriented. I imagine that group can't imagine a lot of people are feeling extremely energized, and I think vice versa. So I think this is just really interesting to see that many people are very different from you. There are many people that are having a really good time, a lot of people that are having a really bad time, and it's just a good way to remember and basically have empathy for the other half, especially the folks not doing as well, because not everyone is as energized. And we'll talk about what that energized group looks like. But I think that's just an important point. A lot of people are having a really hard time.
00:18:28 · Noam Segal, Lenny Rachitsky
[00:18:28] S0: I really agree with you, Lenny. And I think that given the pace of change of the technology, I really do feel that too much of our focus is being spent on mastering the technology and trying to understand what the heck we should be doing with these new releases, new models, new capabilities, loop engineering, whatever the next thing will be next week. And we're not spending enough time and focus on our relationships at work, on seeing our colleagues, on supporting our peers in also being able to work with this technology, thrive with it, succeed with it, and get along and collaborate well with people who don't belong in the same bucket as us when it comes to how the technology's being perceived. So, I personally would love to see all of us, especially energized people, take some of that energy and spend it on the people around you rather than the all-in focus on whatever the next thing is with AI. [00:19:36] S1: Let's go to the next takeaway. Let's talk about burnout and optimism.