Lenny's Podcast: Product | Career | Growth
00:48:17 · Noam Segal, Lenny Rachitsky
You don't apply your thinking to it and you slowly let your mind, your involvement in your work, your agency collapse into this rotting state, so to speak. [00:48:36] S1: Yeah, this is such an interesting takeaway. There's a positive note to this. As you said, I'm looking at the numbers here. 82% of people say AI is making them at least moderately better at their job and nearly 50% say very much or extremely better, which may correlate with that original, just this bifurcation. The people that feel like AI is making them better at their job, probably the people feel most energized. So whether it's true or not, so I think there's a couple happy points. That's one. People feel AI is making them better. They feel that. So that's real even if it may not be. And at the same time, I think they're self-aware the quality is an issue. And also, maybe I'm atrophying in my ability to say code or write strategy docs. So at least people are self-aware that this is happening, not just I'm killing it, all my stuff is higher quality and it's much better than ever.
00:49:28 · Noam Segal
[00:49:28] S0: They are self-aware, but among other things, I'm a certified coach and I would suggest that beyond being self-aware, we need to act on this. There are several explanations I could give to this phenomenon. One of them might be that the honeymoon period with AI is over. We thought it was perfect and the best thing that ever happened to us since sliced bread or whatever typical Americans say, but we've realized it's not quite there yet. And yes, the models are the worst they're ever going to be, they're only getting better, but there's still- And yes, the models are the worst they're ever going to be, they're only getting better. But there's still so much they need to get better before we can really say, "Yeah, my work is just so much better and I don't need to be as involved with it." You had Simon Willison on this show talking about how people are worried about skill atrophy. That they're not learning enough and that we need to be consciously resistant to this. And not let ourselves cognitively rot. And I think this data suggests that we're losing that fight a little bit. We need to put a little bit more energy into it, into fighting this cognitive rot that we're feeling. And to make sure that as the bar continues to rise and this technology continues to evolve, that we are meeting that with deliberate practice, deliberate thinking, deliberate judgment.
00:50:59 · Lenny Rachitsky, Noam Segal
[00:50:59] S1: People are just so bad at that. Just like if I have an easy button, I will press it. I know I shouldn't, but I'm just going to eat those Doritos. So that's the challenge I think for people. It's just like because you could do it the easy way, it's so hard to resist. And that connects again to this ladder that's being raised that people are just getting into this stuff. It's just they have to make themselves do it the hard way to learn how to do it for real. And I'm really curious how that plays out with junior folks in the market learning how to actually code, how to do peer writing, how to write a [inaudible 00:51:28] from scratch with your fingers versus talking to Claude about it. [00:51:31] S0: Yeah, there's so much to say here. I think people miss feeling smart sometimes. I think I thought once upon a time about myself that I'm smart. And then you encounter these models, most recently a Fable 5 that just came out for the second time and you don't feel that smart anymore and you sort of lose the sense of self-efficacy that you used to have. And the second thing to say about this is that every time you, you, not the AI, solve a problem and get over a barrier, it increases, it raises your baseline of self-efficacy, of self-confidence, of self-belief. And every time you offload that to your favorite AI model, you are lowering that baseline and your thinking and your judgment is watching. And that's a serious problem.
00:51:31 · Noam Segal, Lenny Rachitsky
[00:51:31] S0: Yeah, there's so much to say here. I think people miss feeling smart sometimes. I think I thought once upon a time about myself that I'm smart. And then you encounter these models, most recently a Fable 5 that just came out for the second time and you don't feel that smart anymore and you sort of lose the sense of self-efficacy that you used to have. And the second thing to say about this is that every time you, you, not the AI, solve a problem and get over a barrier, it increases, it raises your baseline of self-efficacy, of self-confidence, of self-belief. And every time you offload that to your favorite AI model, you are lowering that baseline and your thinking and your judgment is watching. And that's a serious problem. [00:52:26] S1: So maybe just wrap up this takeaway, the sentence used in this report I love, I'll just read. The productivity gains are real, but the quality of the work and the sharpness of the person producing it are taking a hit. [00:52:37] S0: Absolutely. And maybe we'll get to this in the end, but we should keep a close eye on this and really try to work on our own self-efficacy. [00:52:47] S1: We need evals for people. Are humans becoming- [00:52:49] S0: Evals for people. Let's do that. [00:52:52] S1: [inaudible 00:52:52] your smartness. Okay. Let's talk about takeaway number five, which I also though was extremely interesting, my God. So much interesting in this. Let's talk about the fifth takeaway.
00:53:03 · Noam Segal
[00:53:03] S0: Yeah. So I think the dominant narrative right now in our community is the fear of being replaced. And as we talked about, a lot of people in tech do fear and are worried that they're going to be replaced, that they're going to be laid off. And so it would make sense that if we had a question and one of the options to respond to that question were, I'm worried about losing my job to AI, that it would rank fairly high. But when we look at this slide and when we look at when people are asked, what are your concerns and what's bothering you right now? What are you afraid of in tech? Losing my job to AI is actually second to last on that list. And instead what we saw rise up to the top is the expectation to do more for the same pay. It's almost as if we're all feeling like we're being squeezed and squeezed and squeezed some more to accomplish more things in less time for the same pay. And so that fear of being overworked is by far the dominant fear. Alongside the second item in this list, which is that the pace is becoming unsustainable. And by pace, I mean both the pace of the work. And the expectation of work velocity, just how much you have to put out a day, every single day. And the pace of change of the technology. Which requires you to invest a significant amount of time in learning the new model, the new framework, the new way to use the technology. Which of course takes away from your core focused working time. So it's sort of an evil downward spiral that really prevents you from feeling like you're able to accomplish anything of meaning. You just feel very overworked, very tired.
00:55:10 · Lenny Rachitsky, Noam Segal
[00:55:10] S1: I'm confident everybody listening understands exactly what you're describing here. Obviously connects to that burnout point we made earlier. I'll close this takeaway with another quick read from your post. You're such an amazing writer, Noam. [00:55:25] S0: Thank you. [00:55:25] S1: I love reading your summaries of what you learned, so I'll just read this. The speed AI unlocked got plowed straight back into expectations. Every game becomes the new baseline and the people expected to hit it are running out of room to breathe. [00:55:40] S0: When are we going to get to the optimistic part of this episode? [00:55:46] S1: Maybe we'll find something. Okay, let's talk about takeaway six, which has a little bit of optimism. [00:55:51] S0: Oh, yeah. Okay. Okay. [00:55:52] S1: A lot of ambivalence is kind of the way to put it.