Lenny's Podcast: Product | Career | Growth
01:13:21 · Fiona Fung, Lenny Rachitsky
[01:13:21] S1: Actually, I'll share some vulnerability here. Speaking of big open questions, I really do think how we grow the next generation just because how you and me got to our engineering path is just so different. It's almost like okay, now when you graduate from school, it's like, "How do you fast-forward?" But the important thing to me, but still understand that double click I talked about to the layer of a need, but that is a big question I have, and I wish I have the answers, but I wonder if it's for software engineering, it's almost like you go more towards a fellowship or apprenticeship program. I know it's odd because technically we have internships that would, but those were kind of like three months and little projects, but I do wonder, and I wish I have a crystal ball here, but it's like how do you almost cram, and maybe it won't matter, but some of the life experiences that we all got, how do you actually enable us to teach that to the next generation of builders? [01:14:28] S0: Right, if you don't have to ever look at code, what's the incentive for a new software engineer to truly understand how infrastructure works and memory allocation, all these things that are kind of foundational? [01:14:42] S1: And it's interesting, maybe the models will get good enough that it doesn't matter. [01:14:46] S0: You don't have to worry about it.
01:14:46 · Lenny Rachitsky, Fiona Fung
[01:14:46] S0: You don't have to worry about it. [01:14:48] S1: But I do think there's something about that double click because I think that's where there might be an opportunity to improve the product or the system, but figuring out how to learn that not necessarily by years of- [01:15:01] S0: Of typing code. [01:15:03] S1: Yeah. Like years of- [01:15:01] S0: Of typing code. [01:15:03] S1: Yeah. [01:15:04] S0: Yeah. Somebody's got to have to understand code at some level. It's like some COBOL engineer they have to pull out of that retirement one day. Do you remember how to write Python? [01:15:13] S1: You know actually what's really fun, one of my previous managers, he started software engineer when it was punch cards and it's so fabulous. He's been messaging me everything he's been building with Claude Code and I'm like, wow, what a career that you go from. He's really seeing this whole change. So maybe I think for us to think about is when I think about his career, how he got started with punch cards was also totally, totally different than now. I think it'll be interesting for us to see what remains important and then what changes in terms of importance and then it's like how do you gain... I have a theory, maybe that's what is important will shift over time. And then how do you build the proficiency in doing that?
01:15:13 · Fiona Fung, Lenny Rachitsky
[01:15:13] S1: You know actually what's really fun, one of my previous managers, he started software engineer when it was punch cards and it's so fabulous. He's been messaging me everything he's been building with Claude Code and I'm like, wow, what a career that you go from. He's really seeing this whole change. So maybe I think for us to think about is when I think about his career, how he got started with punch cards was also totally, totally different than now. I think it'll be interesting for us to see what remains important and then what changes in terms of importance and then it's like how do you gain... I have a theory, maybe that's what is important will shift over time. And then how do you build the proficiency in doing that? [01:16:03] S0: Yeah, just learn the things that really matter. The argument that I constantly hear is just like it's a new level of abstraction, just like assembly and binary. It just keeps going up and up. And now, okay, we don't need to actually look at the code. It's like a new layer of traction, prompts and Claude's thinking messages. [01:16:20] S1: Yeah. And it's maybe like, okay, what is an interesting problem and what's the prioritization for experience to build? It's interesting. Yeah. And then when you build things, how do you know it's actually resonating and it's doing what you intended?
01:16:20 · Fiona Fung, Lenny Rachitsky
[01:16:20] S1: Yeah. And it's maybe like, okay, what is an interesting problem and what's the prioritization for experience to build? It's interesting. Yeah. And then when you build things, how do you know it's actually resonating and it's doing what you intended? [01:16:34] S0: And it's good. Yeah. Are we just building a bunch of slop here or is this actually this architecture that will work? I think the advantage though for young people is it's so much easier to just lean in and work in this new way versus being stuck in the way that things used to be. It's rare. It's amazing how many longtime engineers like yourself have adapted and embraced this. It's like so hard to just change everything. Okay, let's do it. Everything.
01:16:34 · Lenny Rachitsky, Fiona Fung
[01:16:34] S0: And it's good. Yeah. Are we just building a bunch of slop here or is this actually this architecture that will work? I think the advantage though for young people is it's so much easier to just lean in and work in this new way versus being stuck in the way that things used to be. It's rare. It's amazing how many longtime engineers like yourself have adapted and embraced this. It's like so hard to just change everything. Okay, let's do it. Everything. [01:17:06] S1: Well, because the rate of change is also so fast. Actually, that was the one thing of, I remember the first time it was probably Sonnet 35 or 36 and I remembered it was still making some mistakes when I was doing things on the side. I'm like, "What are you doing?" And then what I noticed was some of the engineers that were resisting AI tooling, they're like, "Ah, but see, look at all of these." But then I think it was hard to understand of how the exponential rate of improvements. And maybe that's another interesting thing that I, myself, I'm learning too. There might've been something I tried to automate that Claude wasn't quite good enough. And then actually in the next model, oh, well, now it is good enough. So it's always also thinking about what may have not worked. It might be worth the time to revisit because that now might be a new capability.
01:17:06 · Fiona Fung, Lenny Rachitsky
[01:17:06] S1: Well, because the rate of change is also so fast. Actually, that was the one thing of, I remember the first time it was probably Sonnet 35 or 36 and I remembered it was still making some mistakes when I was doing things on the side. I'm like, "What are you doing?" And then what I noticed was some of the engineers that were resisting AI tooling, they're like, "Ah, but see, look at all of these." But then I think it was hard to understand of how the exponential rate of improvements. And maybe that's another interesting thing that I, myself, I'm learning too. There might've been something I tried to automate that Claude wasn't quite good enough. And then actually in the next model, oh, well, now it is good enough. So it's always also thinking about what may have not worked. It might be worth the time to revisit because that now might be a new capability. [01:17:50] S0: Yeah. That comes up a lot on this podcast. Just build something that is almost working that is at the edge because once the model gets there, you'll be so far ahead of everybody else. Okay. Final question. You may have already answered this with what you just said, but what keeps you up at night?