Lenny's Podcast: Product | Career | Growth
00:22:56 · Tara Seshan, Lenny Rachitsky
And to me, the best way of trying to do that is Patrick Collison has on his website, patrickcallison.com/fast, I think, which is all of these projects that were unreasonably ambitious that were executed in a really, really short time period. And what, for me, is now remarkable about that list of projects is that they all existed before these tools made it possible for you to learn how to build something almost instantly, or ask it with one question, "Hey, can you summarize this very complicated text or this very complicated book for me immediately?" Or can I try to do all of these things that were previously impossible to me, but now I'm able to do? "Can you make for me a CAD model of this idea that I might have?" Really, capabilities that were truly beyond my reach are now in my reach. And so if those fast projects were possible before with the capabilities we used to have, shouldn't we just see an exponential increase of the number of those types of unreasonably quickly and effectively executed things with what AI has given us? [00:23:57] S1: To your point, the hardest part is just remembering to even to try just to be like, "Oh yeah, well let me see if Codex can do this for me." It's just a new habit, a new thing we have to build in our brain.
00:23:57 · Lenny Rachitsky, Tara Seshan
[00:23:57] S1: To your point, the hardest part is just remembering to even to try just to be like, "Oh yeah, well let me see if Codex can do this for me." It's just a new habit, a new thing we have to build in our brain. [00:24:08] S0: Tyler Cowen has this statement on his site, which is that most people underrate the impact of going to someone else and saying, "Hey, what is the more ambitious version of what you're doing?? Or, "Couldn't you try this faster?" Or, "Couldn't you try this at a 10X bigger scale?" And in some ways, again, when I think of, what do PMs do that is incredibly effective now or what can they do that is incredibly effective now? I think elevating others' ambitions or reminding them of what's possible here is a huge part of the product management role. When folks say, "Hey, I think we can get this done in this way," or, "We can get this done by this timeline," or, "Maybe this is the first version of it," part of your job now is to elevate everyone's ambitions and say, "Actually, isn't the possibility ceiling meaningfully higher? Shouldn't we be more ambitious about what we're attempting here? Or couldn't we try this faster?" And I think it's a great place to be. It's a great place to be in terms of what you can build, what's possible, and in terms of how exciting the job becomes. [00:25:08] S1: That is so interesting. I remember Nick Turley was on the podcast who maybe had the role before you. I think he's working at Enterprise Stuff now. He had this meme internally. "Is this maximally accelerated?" [00:25:20] S0: Yes.
00:25:20 · Tara Seshan, Lenny Rachitsky
[00:25:20] S0: Yes. [00:25:21] S1: There's like an emoji, I think, inside the Slack, "Is this maximally accelerated?" [00:25:24] S0: "Is this maximally accelerated," is totally a OpenAI meme. The other OpenAI meme that Andrew Ambrosino and I love to ask the team is, "Are you mainlining it yet?" Which is, are you using this product all day every day to get your thing done? And I think that in combination with, are we being as ambitious as possible, which is about the scope and the scale of what you're trying to do, is this maximally accelerated? Are we moving as fast as possible on it? And then are you mainlining it yet? Are you using it? And are you bringing all your taste to bear on whether this thing works and is something that people really want and tightening that feedback loop as much as possible? Those to me are the three memes of product development that we just have to spread as much as possible now. [00:26:08] S1: I love that. It's like the new dogfooding instead of dogfooding, you got to mainline it. [00:26:14] S0: Yeah, exactly. [00:26:15] S1: And that shows so deeply in the tweets. This is mostly how I see your team communicate of just how obsessed they are with the product and are just constantly asking, "What can we do better?" "What's bugging you now?" "Here's the thing we're building." It's very clear how, to your point earlier, that everyone is just the founder of their product and it's very clear how they act as an external observer. Are there any other memes internally? Those are so interesting. Any other, I don't know, cultural-
00:26:44 · Tara Seshan
[00:26:44] S0: Yeah, I'm trying to think if there's other good cultural memes. Certainly a really important one is feeling the AGI or just being conscious of AGI coming. There are so many outcomes for what it could look like or how one thinks about it, but a huge part of what puts most people at this company is believing in that mission of AGI being beneficial and trying to do whatever it takes to make that possible, both realization of AGI and ensuring that it is beneficial for humanity. And in building products, another just constant refrain I have to keep in the back of my mind is, are we building for where the models are going to be in two to three months? You fail if you build for where the models are now, you fail if you build for where you think the models will be in a year. Both outcomes are equally wrong, and I'm sure many people have talked about this, but both outcomes are really equally wrong. If you're too early, you're wrong. If you build something that was overly focused on a past model's capabilities, you're entirely wrong. The only way to build is two to three months. And having this meme of models are going to get way better. I need to think about the model capability as the center of this product. I need to get out of the way of the model in terms of the product constructs that I create. How do I ensure that this is right for the model in two to three months' time?
00:28:05 · Lenny Rachitsky, Tara Seshan
[00:28:05] S1: How do you know what two or three months is like? It's a challenging understanding, especially while we're on this exponential. Is it just a gut feeling? Is there anything the researchers give you a sense? How does that work? [00:28:17] S0: Yeah, certainly communicating really tightly with research on where they think things are going is incredibly important. These things aren't entirely a black box in that you know, "Hey, we're focused on these particular things. We would like models to be better at coding in these specific ways," or, "better at writing in these specific ways." So we certainly have focused efforts on making the model better at specific capabilities. And so knowing where that is and ensuring that product development is as tied as possible to what research has as its agenda and its roadmap is really important. [00:28:54] S1: A quote that I'll never forget is when Kevin Weil was on the podcast, he was chief product officer at that time. He said that this is the worst the models will ever be. And it sounds so simple, but it's hard to just wrap your head around that, that this is the worst there will ever be. It's such a cliche almost now to say that, but it's true. It's absurd. This is- [00:29:16] S0: Yeah, it's absurd. It's truly absurd. [00:29:21] S1: Oh man. Okay. I want to talk about ChatGPT, the app, briefly. Okay, so I have it open right now. [00:29:28] S0: Yes.
00:29:28 · Tara Seshan, Lenny Rachitsky
[00:29:28] S0: Yes. [00:29:30] S1: Okay. So here's what I see in it. ChatGPT, and then there's a dropdown and there's ChatGPT and Codex, and then there's this toggle, Chat and Work. Tara, what is going on? What are all these things? Help us understand what each of these things are for. And where do you think this goes? Is it going to stay like this? Is there a next step that you're imagining already? [00:29:50] S0: Our north star here is that users do not need to make decisions between picking between all these different options. Ideally, there is no toggle here. That you go to the box, you type in your task, like, I would like to build a really awesome app that, I don't know, helps my podcast guests do research before episodes or something like that. [00:29:50] S1: Yes. Do that.