Lenny's Podcast: Product | Career | Growth
00:58:15 · Lenny Rachitsky
[00:58:15] S1: This is so interesting because I've worked with people that are good at these two skills and they were always called unicorns at the company. She can code and design, oh my god. And what I'm hearing here is this is what you need to become. You need to become really good at at least two things there. I think you used the term smoke stack or something where it's like PM over here, engineer design, and what I'm hearing here is you need to get good at at least two of these skills. The silos of these two roles are disappearing.
00:58:37 · Marc Andreessen
[00:58:37] S0: That's right. That's right. And again, I can't overstress the following, for anybody listening to this, the thing about AI that I think people are just not getting enough benefit out of yet is just it will teach you. This is amazing. There's never been a technology before where you could ask it, "Teach me how to do this thing." And so I always feel like it's like people spend too much... it's one of these things where it's like so much focus on figuring out how to use a large language model is like, "Okay, what am I going to try to get it to do for me?" which is of course very important. But the other side of it is, what can I get it to teach me how to do, and it's just as good at that. And so again, this is this level of latent superpower. People who really want to improve themselves and develop their career should be spending every spare hour in my view at this point talking on AI, being like, "All right, train me up. Super empower me. Train me, train me how to be... I'm a coder. Train me how to be a product manager." It will happily do that. It knows exactly how to do that. Run me, make me problems... yeah, make me assignments, then evaluate my results. It will do that just as happily as it will do work, quote unquote, for you.
00:59:44 · Lenny Rachitsky
[00:59:44] S1: Two tricks I've heard along those lines. One is to watch the output, what the agent is doing and thinking as it's doing the work. So if you're not an engineer, just sit there and watch it think and make decisions, and it's almost become this layer on top of learning to code is learning to see what the agent is doing and thinking because that teaches you about architecture. And the other is, a couple podcast guests have mentioned this, when you get stuck and then you figure out how to unstuck yourself, you ask it, "What could I have done differently? What could I have said that would've avoided this error in the first place?"
01:00:14 · Marc Andreessen
[01:00:14] S0: Yeah, that's right. That's right. Yeah, look, on that first one, and again, this is what I'm doing with my 10-year-old. Yeah, look, if you ask me, yeah, this is a really good point. So if you ask an AI, "Write me this code," and then it does it and it comes back and it doesn't work right, if all you know is single function, I asked it and it gave me back something that's not good, what do you even do with that? You don't understand why it gave you that result. Do you even understand what to tell it to try to get it to do something different? But to your point, if you actually watch what it's doing and then you have the grounding, kind of that leg of your E or your F, if you have that grounding, then you can be like, "Oh, I see what it's doing. I see where it made the mistake. I see where it went sideways." And then you're all of a sudden able to intervene and be able to say, "No, no, that's not what I meant. Do this other thing." And again, this is a big part of having the actual kind of synergistic relationship is that you understand. And by the way, look, I mean, like everything I'm saying is... everything that we're saying right now also is the same as if you're working with human beings. If you and I are colleagues and I would ask you to do something, you'd come back with something completely different, I do need to understand what was happening in your head in order to be able to give you feedback. If I just tell you, "Oh, that's wrong," nothing happens. I need to actually understand. I need to have theory of mind. I need to understand what you were thinking in order to really give you the right feedback. And again, the great thing with AI is AI will happily sit there and explain all day long why it's doing what it's doing. It'll happily critique itself. By the way, this is a very fun thing where you can have one AI critique the other AI which is another thing which is you have one AI write the code, you have another AI debunk the code. And so you can actually, you can play the AIs off against each other and get them to argue with each other. And yeah, these are all the kinds of skills that are going to become, I think, incredibly valuable.
01:02:01 · Lenny Rachitsky, Marc Andreessen
[01:02:01] S1: I think people call those LLM councils- [01:02:03] S0: Yes. [01:02:03] S1: ... where they're talking to each other. [01:02:05] S0: Yeah, that's right. That's right. [01:02:07] S1: I do feel like if I were... I have no design background. I've always wanted to design. I've always wanted to be a great designer. It feels like that's the hardest one to learn of all these three by just watching and talking because there's a lot of exposure hours as folks have used this term, just like how do you learn to be a great designer. That feels like that's going to be really hard and valuable. [01:02:25] S0: So my true confession is I've always kind of wanted to be a cartoonist, but I have no art skills. But as we're talking, I'm like, "Hmm, it might be time." [01:02:35] S1: The time has come, Marc. [01:02:37] S0: Yes. [01:02:38] S1: I want to pivot to founders, maybe your bread and butter. You spend a lot of time with the most cutting edge, AI-forward founders. I'm curious what you see them do, how you see them, some way they operate that's maybe blowing your mind about how the future of starting a company looks, how the future of AI-forward companies look.
01:02:57 · Marc Andreessen
[01:02:57] S0: Yeah. So this is a great and very topical topic that's all playing out in real time right now on the leading edge. So I think there's like three layers of it and see if this makes sense. I think there's like three layers of it. I think layer one is they're thinking, "All right, how does AI redefine the products themselves?" And this is kind of the time-honored kind of thing that happens with technology transitions, and this is kind of what a lot of venture capital is based on which is, okay, there's a new technology that comes out. Maybe it's the personal computer or the iPhone or the internet or now it's AI, and it's like, all right, is this a new capability that gets added to existing products. So all of a sudden you've got, I don't know, an existing software business and now you've got your PC version of it and now you got your iPhone version of it and you just keep on going and the new technology kind of gets added into the mix with another ingredient to an existing formula, and of course, a lot of new technologies are like that. I don't know when flash storage came out or something, it didn't really redefine the software industry because people just went from using hard disk using flash storage or something. But when the internet came out, like basically old school on-prem software for the most part, not entirely, but a lot of it died and it just got replaced by web software. And so sometimes you get the kind of, it's additive to an existing thing. Sometimes you get the actually it redefines an entire product category, redefines an industry. In many cases, the companies themselves turn over it. So there's sort of this question, and an example you just mentioned, Nano Banana. So a great example is there are these businesses, like just take Adobe. Photoshop is built a, whatever, 40-year franchise in image editing. Okay, is AI a sort of a feature now that gets added to Photoshop to be able to do AI-based image editing, or do you just stop editing images entirely because you're using Nano Banana and all images are just being generated and it's just easier to just have AI generate a new image than it is to try to edit an old one? And so I think there's many areas of tech in which that question is being asked and the answers I think will vary by domain.