Bret Taylor: belief

Transcript context

…I love that you're like, I don't know if I have a great answer then you just give us an incredible answer to this question. I want to go in a different direction. You mentioned that you describe yourself as an engineer. I know I heard you code to relax still. Let me just ask you this question, something a lot of people in college are thinking about. Do you think it still makes sense to learn to code? Do you think this will significantly change in the next few years? I do still think studying computer science is a different answer than learning to code, but I would say I still think it's extremely valuable to study computer science. I say that because I think computer science is more than coding. If you understand things like Big O notation or complexity theory or study algorithms and why a randomized algorithm works and why two algorithms with the same Big O complexity, one can then practice perform better than others and why a cache miss matters and just all these little... There's a lot more to coding than writing the code. The reason I think that is I do think the act of creating software is going to transform from typing into a terminal or typing into Visual Studio code to operating a code-generating machine. I think that is the future of creating software. But I think operating a code-generating machine requires systems thinking and I think that computer science, there are other disciplines as well, but computer science is a wonderful major to learn systems thinking and at the end of the day, AI will facilitate creating this software. We may do a lot more in the next few years we can't even imagine, but your job as the operator of that code-generating machine is to make a product or to solve a problem and you really need to have great systems thinking and you're going to be managing this machine that's doing a lot of the tedious work of making the button or connecting to the network. But as you're thinking of the intersection of a technology and a business problem, you're trying to affect a system that will solve that problem at scale for your customers and that systems thinking is always the hardest part of creating products. I'll just give you, it's this cheesy simple example, but I think it's representative. At Facebook, we spent a lot of time designing the newsfeed and if you ever had a really, really good designer and they showed you at the time, a Photoshop mock-up of the newsfeed, it was just all as beautiful. The photos, the family was happy and the photo was a perfect photo and the posts were all perfectly grammatically correct and of a completely normal length and the comments and there was the like... Everything was just perfect. And then you'd implement that design and you'd look at your own newsfeed and it looked like shit because it turns out not everyone's photos were made by a professional photographer. The posts were all these different lengths. The comments were like, you suck and... All that stuff. And then all of a sudden you realize that designing a newsfeed, Photoshop is the easy part. You need to actually design a system that produces both in content and visual design, like a delightful experience given input you don't control. that designing a newsfeed, Photoshop is the easy part. You need to actually design a system that produces both in content and visual design, like a delightful experience given input you don't control. And that's a system, it's sort of a design and it's just, what we did practically, I am sure it's changed a lot since I left in 2012, but we made a system so designers had to show their newsfeed designs with real newsfeed data that was messy rather than anything artificial because I think it forced the process to be more realistic. But I say that because I think that whether AI is writing code or doing the design or doing all these other things, you need to learn how to have a system in your head. You need to understand the basics of what's hard and what's easy and what's possible and what's impossible. And AI can help you do that too, by the way. But I do think that's a really useful skill. I think in general, with the advent of AI agents and AI approaching super intelligence in certain domains, I think the tools with which we do our job will change a lot. I think it's very important to have a very loose attachment to the way we do our jobs and that story that we won't talk about when I rewrote Google Maps, everyone talks about that story and I think it's because of Paul [inaudible 00:35:57] who told it on some podcasts and that's where it made the rounds. I think that's going to end up this vestige of the past, almost like the human calculators at NASA before the computers were invented, like wow, a person was a calculator? Whoa, that's fun. Tell me that story. I think just what I was good at will no longer be useful in the future or certainly not valuable in the future and that's okay. So I think we need to have a really loose view of it, but the idea that you shouldn't study these disciplines, it's like people say, I don't want to study math because I'm not going to use it in my career for X. Well, studying maths is quite important. It teaches you how to think. It teaches you how the world works, physics, math, and I think computer science especially, at least the foundations of it, will continue to be the foundations of how we build software and understanding that when you're interacting particularly with something that's smarter than you, producing code you might not completely understand how you constrain it and how you get it to produce these outcomes. I think it will require a lot of sophistication actually.…

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