Lenny's Podcast: Product | Career | Growth
01:16:25 · Dan Shipper, Lenny Rachitsky
[01:16:25] S1: Yes. And I think that is actually super important. The only thing you need to do is ride the models and that means use them for whatever it is that you do. We've talked about how Codex and Cowork are becoming the sort of standard operating system for work. If you're just doing that and when new models come out, you're trying them and figuring out, okay, now there are new powers. How can I use them? Instead of just being like, "I'm going to try to ignore it because it makes me afraid." Which I think is honestly, it's rational. It's a reasonable response. And also if you ride on top of them, they extend your powers in a way that doesn't leave you behind. You're part of the future and part of the way work happens. And I think that we're going to need people doing that for a very, very long time. [01:17:16] S0: I like this term, ride the model. So what's like say a new model comes out, what do you think someone say working at, I don't know, Salesforce? Say a PM at Salesforce, what should they do to ride the model?
01:17:27 · Dan Shipper
[01:17:27] S1: Well, one of the things that's really interesting is a lot of companies handicap their employees from even doing this because I don't know if you can use the latest models at Salesforce. A lot of times you have to wait or it's whatever. So maybe you have to do it in your off time. But the thing that I really like to do with new models is play, and there are certain things where I know it can't quite do it yet, but when a new model comes out, I always turn the rock over again to be like, "Can I do it now?" So it could not do the senior engineer benchmark last time, and I turned the rock over again and now it's at a 60 out of 100, which is really good. So the way to ride the models is not one specific thing because they're always changing, but it is to be curious and playful to apply the model, the new model to whatever it is that you care about, whether that's your job or something outside of your job and to keep turning over rocks because it may not work now, but it may work eventually. It probably will work eventually and the way that you use it matters. So what's really cool is that I think people think of the edge of AI as being in San Francisco, and I actually don't think that that's where it is. I think the edge of AI is wherever AI meets a real human doing something because the people at San Francisco, they're making it, but they don't actually know a lot about how to use it. They don't know, or at least they don't know everything about how to use it. They need to see how other people use it. And so whenever a new model comes out, you get to be one of the first people in the world to discover what it might be useful for. And it's like a new discovery. And I think that's why, for example, we're in Brooklyn, but I really think of us, and I think we are quite far ahead of people in San Francisco because we just use them for everything. And if people do that consistently, I think it's going to be very hard to lose.
01:19:35 · Lenny Rachitsky, Dan Shipper
[01:19:35] S0: That is one of the most amazing things about AI right now is no matter how much money you have or a little money you have, you have access to the most advanced AI model. It's not free, so you need some money and you can get it immediately when it comes out. Maybe the only people that have an advantage are the people working at OpenAI or Anthropic, but otherwise it's just available. [01:19:59] S1: I know. I was at their event with you, their Code with Claude event with you last week or a couple weeks ago and they're all using mythos and I'm like, "God, damn it." It's so annoying, but I think that's totally true. If IBM had invented AI, you can bet it would not be like this, and it would be a bajillion dollars and only the top companies could use it and they would be using it in the weirdest, most uninteresting ways. It's really important that AI was built in America and in the Silicon Valley culture that's like, "We want to make intelligence too cheap to meter." That's not the default stance. And it means that everyone has this broadly accessible tool that they can use and I think that's amazing. [01:20:51] S0: That's such a good point. And interestingly, it's also created the most fastest growing companies in history, the biggest companies in history. [01:20:57] S1: That's true. Those Silicon Valley guys, they're smart.
01:20:57 · Dan Shipper, Lenny Rachitsky
[01:20:57] S1: That's true. Those Silicon Valley guys, they're smart. [01:21:02] S0: If I zoom out on the conversation, it's really interesting. There's kind of these two sides to the coin. One is not a lot is actually, so much is not changing. SaaS continues, jobs not disappearing. We're still emailing each other. We're still working on Slack. A lot of the work not changed. On the other hand, every role transformed, engineers don't write code, PMs don't write PRDs, design and design. It's so interesting how much has changed, how much has not changed. I don't know. It's interesting that people think it's going to be this whole new world, but in many ways it's, okay, it'll continue the way it is with a lot of stuff around the edges.
01:21:38 · Dan Shipper
[01:21:38] S1: That's how I feel. I'm simultaneously so excited and it feels like everything has changed, and I'm so bullish on it and the progress that we're making, all that kind of stuff. And, yeah, I feel like there are these things where they're going to be pretty similar to how they are and that's probably good. And I think generally our intuitions about the future, the model that I have of what our intuitions are about the future is the intuitions that people had in the Middle Ages about what happened at the end of the horizon. It's like, are there dragons? Does it drop off into nothingness or whatever? A lot of people have a lot of deep intuition that there's something terrible going to happen over the horizon and also that some people are like, "There's something incredible. It's going to change everything. We're all going to be happy. It's a utopia." And what happens is you get there and you're like, there's some really cool things, there's some not cool things and it's just another horizon. And I think that's the way to think about the future. And until you get to that place where you're starting to see it, and I think we get to see it because we get to see it internally all the time. It's important not to let your mind get away from you and being like, "This is going to happen and this is going to happen and whatever." Because you're going to tell a story that sounds so real in the moment, but later on you're like, "Actually it's much more complex than that." And somewhere it's sort of a both, everything's changed and nothing has. And once you get there, I think you're sort of starting to see like, "Oh, yeah, this is a real thing."
01:23:11 · Lenny Rachitsky, Dan Shipper
[01:23:11] S0: Part of it is the AI companies are very good at scaring us about what might happen in the future. And I think that's actually shifting. I think they've realized maybe we should not freak everybody out about the dangers. [01:23:21] S1: That PR strategy just does not make any sense to me. I do think that it's genuine, but it's so ineffective, and I think it's also wrong. [01:23:32] S0: How about we end with maybe just a few things listeners should do to be successful over the next year with the way the world is moving. [01:23:42] S1: Ride the models. I would try all of your workflows in Codex or Cowork and see how that works. And if your company doesn't let you do it on your own time, I would try out some of these agent products like OpenClaw or Hermes or for less technical people, there's like Victor, we have OnePlus ones. I would get comfortable with both of those ways of working and try to have fun. I think there's too much of I'm doing this because I have FOMO, I might lose my job or I might miss out on this big thing or whatever. And the best way to actually figure out interesting, useful things to do with AI is to do something enjoyable. [01:24:32] S0: Nikhil Singal was on the podcast and the way he described it is you got to find your moment of joy with AI once you find like, "Wow, I can't believe AI did this for me. This is awesome. We're going to keep building stuff." [01:24:42] S1: Yeah, I agree.