Lenny's Podcast: Product | Career | Growth
00:38:24 · Marc Andreessen, Lenny Rachitsky
How do I make sure I can also do AI-based design?" And the same thing for the designer, which is, "How do I use AI to also become a coder, and also become a product manager?" And then what you get is maybe, those individual roles change. Maybe, those are not any more sort of stovepipe roles the way that they have been for the last 30 years or whatever. But what happens is that the talented people in any of those roles become super powered, and they become good at doing all three of those things. And then, those people become incredibly valuable, because then those are people who can actually build and design new products from scratch, which is the most valuable thing. And so, I think that's the opportunity. [00:39:02] S1: I love this answer. So what I'm hearing is, essentially, if you're amazing at any of these three roles, you will do well.
00:39:08 · Marc Andreessen
[00:39:08] S0: Number one, if you're amazing at these roles, that's great. But also, part of being amazing in these roles is also being able to fully harness the new technology. So if you're a master coder today and you don't ever get to the point where you figure out how to use AI to leverage your coding skills and do more, at some point you are going to hit an issue. Here's another way economists talk about this, which is there's the concept of the job, but the job is not actually the atomic unit of what happens in the workplace. The atomic unit of what happens in the workplace is the task. And then the way the economists think about it is a job is a bundle of tasks. Everybody wants to talk about job loss, but really, what you want to look at is task loss, the tasks changing. The classic example of task changing. Classic example of task changing was once upon a time, executives never used typewriters or personal computers themselves. If you were a vice president of a company in 1970 or whatever, you did not have a typewriter or a computer on your desk typing things. You had a secretary who you dictated memos to. And then there was this change where emails started to show up. And what would happen was the job of the secretary, it went from... The job of the secretary changed from sending out letters with stamps on them to sending or receiving emails with the other admins. Then the secretary would print out the email and bring it into the executive's office. And the executive office would read the email and paper, scroll the reply and give that message back to the secretary, who would go back and type it into the computer on his or her desk, and send it as an email. Fast-forward to today, none of that happens. Now, executives just do all their own email. They still have secretaries or admins, but they're now doing different tasks. They're travel planning and orchestrating events, and doing all of these other things that the great admins do. And then the task set, ironically, of the executive, has expanded to do actually more of the clerical work themselves actually. Like, sit there and type their own memos. Which again, 50 years ago, they never would've done that. And so the executive job still exists, the secretary job still exists, but the tasks have changed. And I think that's a great example of what's going to happen.
00:41:12 · Marc Andreessen
In coding, the tasks are going to change. Product management, the tasks are going to change. Designer, tasks are going to change. And so, the job persists longer than the individual tasks. And then as the tasks change enough, then that's when the jobs change. And so at the level of individual, you want to think of like, "Okay. I have this job, the job is a bundle of tasks. I need to be really good at making sure that I can swap the tasks out. I can really adapt, use the new technology." Get really good at AI coding, for example. And then you want to add skills. "I can also get really good at design. I can also get really good at product management because I've got this new tool." So, you want to pick up more and more scope as you do that. And then 10 years from now, is your job title coder or coder/designer/product manager? Or is it just, "I build products"? Or is it just, "I tell the AI how to build products"? It's like whatever that job is called, who even knows what it's going to be, but it's going to be incredibly important because the people doing that job are going to be orchestrating the AI. And so that's the track that the best people are going to be on, and I think that's the thing to lean hard into.
00:42:17 · Lenny Rachitsky, Marc Andreessen
[00:42:17] S1: I think people aren't fully grasping just, specifically, software engineering and how much that is changing. It's pretty clear we're going to be in a world soon where engineers are not actually writing code, which I think, a year ago, we would not have thought. And now it's just, clearly, this is where it's heading. It's like there's going to be this artisanal experience of sitting there writing code, which is so crazy how much that job is going to change. [00:42:39] S0: Yeah. So again, here, I go back. And again, pardon maybe the history lesson, but I go back coding. So, the first... Do you know the original definition of the term calculator? Do you know what that referred to? [00:42:50] S1: No.
00:42:50 · Marc Andreessen
[00:42:50] S0: It referred to people. So back before there were like electronic calculators or computers or any of these things, the way that you would actually do computing, the way that you would do calculating... Like the way that an insurance company would calculate actuarial tables or the military would like calculate, I don't know, whatever troop logistics formulas or whatever it was. The way that you would do it is you would actually have a room full of people. And by the way, these are like big rooms. You could have hundreds or thousands or tens of thousands of people doing this. And you would actually figure out... Somebody at the head of the room was responsible for whatever the mathematical equation was. And then, they would parcel out the individual mathematical calculations to people sitting at desks, who were doing them all by hand. And that job title was those people were calculators. And so, we've gone from a world in which you literally have people doing mathematical equations by hands. Then, we got the first computers. The first computers, of course, didn't have programming languages. They only had machine code. So, the first computers were programmed with 1s and 0s. And so the task of the programmer became, "Do the 1s and 0s," and then that became punch cards. And you can still... There's still people, kicking today, whose job as a programmer was to build the punch cards. And then you got, actually, this big breakthrough, which was called assembly language, which was basically the way to do machine code but with some level of English added to it. And then the best programmers did assembly language. And then when I was coming up, it was higher level languages like C, that compiled into machine code, and that's what programmers did. And then I still remember when scripting languages... We developed JavaScript at Netscape, and then Python took off, and Perl, and these other scripting languages. When scripting language took off in the 2000s, there was this big fight in the technical community, which is, "Scripting, real programming or not?" because it's like it's kind of cheating. Because real programmers write code that compiles to machine code, and real programmers do memory management themselves, and they do all of this whole craft of writing a C code.
00:44:43 · Marc Andreessen
And these JavaScript or Python programmers are just doing this kind of lightweight things. Does it even really count as coding? And of course, the answer is yes, it very much counted. And now, most coding is done with the scripting languages, which have... You see my point. The scripting languages have abstracted away, like, five layers of detail underneath that, that people used to do by hand, and they don't anymore. And then to your point, AI coding is the next layer on that. AI coding actually abstracts the way the process of actually writing the scripting code. And so in one sense, this is a really big deal for all the obvious reasons. But on the other hand, it's like, "Okay, this is the next layer of the task redefinition under the job of programmer." Now, what's the job of the programmer? To your point, it's not necessarily to write the code by hand. But what it is now is, all right, if you talk to the world's best programmer of yesterday, what they'll tell you is, "Oh, my job is I'm sitting there and I'm orchestrating 10 code bots, coding bots that are running in parallel." And literally, they sit there and they shift from browser to browser, or terminal to terminal. Their day job now is arguing with the AI bots to try to get them to write the right code, and then debug it and fix the problems, and change this back, and do all of these things. And so now, the job of the programmer is to argue with the coding bots. But if you don't know how to write the code yourself, you don't know how to evaluate what the coding bots are giving you. And so, you asked about the 10... Our 10-year old is super into computers and super into programming. He's using Claude, and ChatGPT, Copilot, and all of these things. And what I'm telling him is like, "Look..." And by the way, he loves vibe coding. He's on Replit all of the time doing vibe coding, doing games. He's sitting there. It's hysterical because he's sitting there. It's a 10-year old basically, who spends two hours at dinner arguing with an AI for fun. But what I'm telling him is, "No, look, you need to still fully understand and learn how to write and understand code, because the coding bots are giving you code.