Lenny's Podcast: Product | Career | Growth
00:09:04 · Andrew Ambrosino
[00:09:04] S0: Yeah. I think too, there's this part of the previous world was that the medium implied it had baked in a lot of signal around where in the process something was. So if you're seeing something that feels like the app in production, that means that it's late in the process. That assumptions have been de-risked, that design has looked at this, that this is a good business goal. And now those things are sort of divorced. And the reason it was that way is because it was hard to get resources to build the thing until it was properly de-risked. And now that's just out the window. And so I think it's really important to start saying, "Look, we can have prototypes. We can have documents. Are we clear around what this is doing?" Because to your point, you do not want to over anchor on this thing that was meant to be an exploration, but now it looks so production ready that, oh, visually it's ready for prod. But it's not actually the right model of where the research is going or what users are asking for or what's right for the business. Not to overdo the taste thing, but it's once again, it's like the taste to know what to work on, how to present that information, how to achieve the goals, what medium to use is emerging as the most important thing to do. And that's in every field.
00:10:26 · S1
[00:10:26] S1: What is taste when you talk about good taste? Is it what you described deciding here's the thing we're going to invest in? Is it also once you have a thing, is this right? Is this the thing to shift? Talk about when you think about what is good taste, good judgment, what is that concretely? Because people hear this word, they're like, "Oh, I have good taste. I know it." What does it look like in practice?
00:10:46 · Andrew Ambrosino, S1
[00:10:46] S0: Yeah. It's funny. There was a tweet, I'm too online. There was a tweet, I think it was yesterday from the head of product at Linear, I might be getting that wrong, sorry to anybody, who said, "People overemphasize the aesthetic part of what taste means." And they used, Paul Graham's great, but they used him as an example. Saying, "Paul Graham clearly has great taste and wears cargo shorts." We got to tease out what taste means a little bit and there's a lot of nuance here. I think it's all of the above to what you mentioned. There is an aesthetic part to it, but there's also a systems thinking part of it, like how does this fit in the system? There's a where are we going and what theme is this part of? There's how to present this. A lot of it is wider context. And obviously there are parts of taste that are like, "Hey, this interaction animation doesn't fit in the semantic meaning it's supposed to." It's too snappy for what it's actually trying to convey. And that's incredibly important and I focus probably too much on that. But there's the like, "What should this be?" If we can build anything, what's the goal here and how do we get there? That I think is actually the real taste question here. [00:12:06] S1: When I hear things like this, I always wonder where will human brains continue to be valuable as AI becomes stronger and better and doing more of the work? And it feels like taste is a part of it. Something I think about along these lines is just AI is still very bad at actual design. The output of AI is not great. [00:12:24] S0: Yeah.
00:12:24 · Andrew Ambrosino, S1
[00:12:24] S0: Yeah. [00:12:24] S1: Rarely is it like, "This is it, they nailed it." And it's always like, "Oh, this is Claude Design, this is Codex Design." Why do you think AI and the top frontier models are just not good at design today? And do you think they'll get there? Do you think we'll get to a place of like, "Holy moly, we're done."
00:12:40 · Andrew Ambrosino
[00:12:40] S0: Yeah. I tend to think that there are some practical reasons why it's lagged and also some harder problems to crack. I'm not in our research org, I'm sure I'll get yelled at for saying us. I think design's a little bit harder to grade than software. And that creating a loop where you can train the model and what's good design and what's bad design is just a little bit more tedious and onerous than does the code compile, does it do what it's supposed to? Because the human aspect of taste is part of the feedback mechanism you need. I also think that the labs historically invest in making their models good at things that accelerate AI research. And that in the early era of coding models, it was very clear that the model being able to write correct code would accelerate research. In a way that you can't really make the same case for design. Not that getting good at design isn't important, it's that it's not directly in that flywheel. Those are practical reasons and those will go away. These models will get pretty good at design. There are some kind of murkier things that is going to be really tough. I have kind of a short list of them. One is there is an aspect of culture to what is considered good design. In that you remember it was probably what last year where every new website that came out was just a copy of Linear's website. Linear's website, great design, great taste. If a model did that, I'd be like, "Wow, this is incredible leaps here." If I have a model that outputs Linear's website every time, that's not the challenge here. There's an amount of novelty that is more important in design than it actually is in software engineering. Software engineering, you must want it to over-index unknown patterns. Whereas design, it's like, "No, there's an element of randomness here and novelty." To me, I spent a lot of time writing code or supervising code on the early Codex app. And even as the models get good at design, there's sort of an abstraction layer that is an interplay between the software design and the code that's being written. This thing over here in this corner should share X, Y, and Z in the code base with this thing down here. And that's a little bit different than saying the model needs to be a better designer. Especially that is visual design, but it is significantly deeper.
00:15:24 · Andrew Ambrosino, S1
It's about the abstractions in that like, "Oh, if tomorrow our company did a rebrand, the shallow version of this is that we have to update 263 components one by one." The deep version is the semantics between these two things that look different. They're both in list that have this style, that convey this interaction pattern to the user. And I think that is still feeling a little bit out of reach with the current technology, that abstraction layer. So I think as we've gone through this process of, we started the Codex app in November. And we weren't using it full-time, now we use it for everything. That's been a journey. But now it's like the things that we actually do while using it are different things. So what was the question? [00:16:17] S1: I know, that was an amazing answer. Speaking of design and being creative, the Codex app when it came out, it's like such a new thing that nobody had seen before. It's not a terminal thing, it's not an ID thing. It's like this chat thing that codes and you could see code. To your point, it feels like it'd be hard for AI to be like, "Here's a whole new paradigm for how to code." And that feels like where human brains continue to be valuable for now is creativity almost in coming up with something new versus patterns of things that have been done before. [00:16:47] S0: Yeah, I mean, I totally hear you. Let's give it up for the human brain.