Lenny's Podcast: Product | Career | Growth
00:29:21 · Lenny Rachitsky, Josh Woodward
[00:29:21] S0: Yeah. And it's also along those lines, it's also hard to know what is better. How do you know what's going on? You have this new model, it's the best model ever. In practice, it's not that much different than the previous model that also everyone though was the best model ever. We have AGI. Every time there's a model launch, we have AGI now. And so the benchmarks are trying to show you here's where it's better, but if you didn't, you're just sitting there, "Okay, this is better. I like what it's doing here." [00:29:48] S1: Yeah. I think this is also though where I feel like a lot of folks that follow you and listen to you is like, please, please, please think of amazing products because ultimately all these model capabilities and benchmarks and all the intelligence gets translated into just can you build something people want? And so to me it's like what a time to be alive as a product person because you have this huge menu of things that were almost possible that are now possible more and more with each passing week. [00:30:17] S0: The first point you made there was something that came up recently in a conversation with Tara from OpenAI about how now that we could just build everything and AI has so many opinions about where to go, what you said is exactly right, which is what do we want the world to look like? What is the vision of the future we want? Not, okay, we can do all these things. That's great. Maybe we don't need to do all these things. [00:30:42] S1: Right. [00:30:43] S0: So I think that's a really important point there.
00:30:43 · Lenny Rachitsky, Josh Woodward
[00:30:43] S0: So I think that's a really important point there. [00:30:44] S1: Yeah, definitely. Definitely. [00:30:47] S0: This season's supporting sponsor is DX. Now that everybody at your company is finally using AI, the question that engineering leaders face is no longer are we using AI, but is it paying off? With DX, you can measure and benchmark the impact of AI adoption across your full product life cycle. DX shows you where AI is helping developers and where it's creating new bottlenecks. You can also use it to evaluate AI vendors, monitor costs and licenses and see exactly what's limiting your agents. That's why hundreds of enterprises, including Snowflake, Sony and BNY use the DX platform to measure AI's impact on developer productivity. Visit getdx.com/lenny to get a demo of DX. That's getdx.com/lenny. What skills are you finding are trending up in value in the people that you're working with and what do you feel are trending down when you look at people that are doing really well now? What are the attributes and skills of those people versus things that are maybe less important now?
00:31:53 · Josh Woodward
[00:31:53] S1: Yeah, I feel like there's a whole lot out there on taste and judgment and vibe coding and all of that. I guess the things I'm looking for, I'm always trying to find what are the misprice signals? And so, one I think is we'll hear sometimes people talk about what's someone's learning rate. Do they have a growth mindset? What's their learning rate? I'm actually looking a lot right now for people, what's their unlearning rate? How fast can they learn something and then walk away from it? Based on maybe what they're seeing when they test their product or something. So unlearning rate is one. Another one I'm interested in, I read a book a year or so ago about Roger Federer, the amazing tennis player. And there was this phrase in there about Federer had explosive endurance. It's just this beautiful turn of phrase and with the alliteration and everything, but it's like there's something around how are people taking care of themselves and the people around them where they can go really hard and that's the explosive part, but they can do it over a while and they find ways to pace themselves. In Labs, we have seasons of Labs where we talk about this. So I think that explosive endurance, this unlearning rate. And then maybe another one I would say is as much as coding and other things are becoming maybe trending towards you being able to direct lots of agents and not having to work with as many people, I still feel like collaboration and how you work with people matters even more now. And one of the things we look a lot for is can someone blend and bridge these worlds where they're incredible collaborator with an agent or a swarm of agents, but also with people? And I guess what we believe on the Labs team and on the Gemini team is that there's still just so much joy in working with people. But it's like how do you find the right chemistry? And so maybe one thing I'd say there is people that can build trust, that can scale trust, that underpins any kind of great collaboration. And so that's another maybe signal I'm always looking for is how fast can this person build trust with people and create that kind of environment, if that makes sense.
00:34:18 · Lenny Rachitsky, Josh Woodward
[00:34:18] S0: Yeah, these are so interesting. On that last one, is that kind of a growing, emerging, even more important skill you're finding with the rise of AI? And I'm curious why. [00:34:28] S1: I think so for a couple of reasons. I would say one maybe is uniquely Google. It's a larger organization, so you've got to be able to do that. But the ones that don't feel uniquely Google, one, it feels like as the execution costs of making products goes down, we'll be able to make more products, which you may make the same products with the same people, but I think there's a lot more, you probably see this too, is just people will team up with different people to make stuff. And so it's very interesting when we're thinking about almost like fielding a new team for a Labs project where you used to say it's about five to seven people. Now it's about two to three people, maybe four. But it's kind of like those people just almost... You can almost imagine super talented musicians who team up with different people and then they play different songs together, the songs are the products. But it's like those are the MVPs in Labs where you can be like, "Hey, drop this sort of PM," but that can also code and design because all the roles are blurring with other people and see how they jam on stuff together. So I think that's where my prediction is that skill will almost increase in importance because there will be more products and because there'll be more of this free agents kind of jamming on stuff together.
00:35:46 · Lenny Rachitsky
[00:35:46] S0: Along those lines, I imagine you have been pulling designers, engineers, NPMs into Labs and they all work together and sometimes different functions take leads. Has there been a shift in who you find is most impactful and successful in leading product ideas, Labs, teams in terms of the ratio of PM versus design versus eng? For example, are PMs becoming more valuable or eng becoming more valuable, something like that?
00:36:14 · Josh Woodward
[00:36:14] S1: Yeah, it's interesting. We've been studying this a lot and actually testing a lot of this too. I would say in general, PM happens to be the function maybe by nature because it's a bit more horizontal, that feels like it's maybe being able to adapt to some of the other functions faster. And we see this when we'll run little builder pilots across the company that comes back as like, oh yeah, that's maybe, I don't want to say it's easier, but maybe it's PMs are more accustomed to like, all right, I'm in this meeting, I got to simulate something as a lawyer or as a BD person or as a sales... Do you know what I mean? So I think in some way maybe there's some inherentness in who selects into that. So that definitely is true. But I would say our best people can come from any function. And I would also even widen it, Lenny, we're seeing strategy and ops people and PD people and marketing people be builders in Labs and they are really good. And I think maybe this is another overhyped, underhyped thing. I think right now people are maybe overhyping like everybody's a builder and it's just this new job function and everything's kind of the same. I actually feel like at least what we're seeing is that people still have their specialty. It's like their major or minor in college or something. And I feel like there's a risk if everybody becomes a builder that you lose a lot of respect and appreciation and obviously the expertise that comes from those specialties. And so I think when we set up teams, even though we may be like, this is more of a builder crew, we're still thinking about where are the specialties? And that ends up being super important as well.