Lenny's Podcast: Product | Career | Growth
00:25:19 · Josh Woodward
[00:25:19] S1: Yeah. Yeah, yeah. So there's parts of it out there today. If you're in Gemini, in Gemini Spark, you can actually connect all that stuff and it's quite powerful. I think where we're iterating on that though is we've been in a world where even if you look at some of the other competitors, they're different modes almost that you go into. And I think the lesson even from the last couple of weeks is forget the modes and toggles, just like one prompt box, tell it what you want and it just does stuff for you. So that's definitely not only where we're headed, where others are or headed. I think that's kind of a broader, almost like UX simplification happening across the industry. On the data bits there, it's interesting because actually one of the main things people will ping me about or others is like, "Oh man, Google, I've got all my stuff with you. Just make the thing work." And there's a lot of reluctance actually to be connecting it to a lot of other sort of competitor products. So watch this space. We hear you loud and clear. There's a lot of work if you go online and just look under personal intelligence is sort of the way we think about this stuff is you want a Gemini that is personal, proactive, powerful, that sort of works for you. And so that's been the vision for the last kind of year or so that we're headed towards. And there's a lot of stuff we're playing with right now that will be out soon.
00:26:51 · Lenny Rachitsky, Josh Woodward
[00:26:51] S0: All right. I'm excited. It just feels like, yeah, I have so many little schedules and things running within my email. I'm just like, "Man, why isn't Google just doing this?" It does feel that the event you all have is distribution. So once something happens, similar to Muse recently, it's going to be very easy to grow it and convince people to use it similar to within AI mode. So anyway, okay, I'm excited. Things are happening. [00:27:16] S1: Things are definitely happening. [00:27:19] S0: So going a different direction, what do you think is under-hyped in AI right now? And what do you think is over-hyped, if anything is over-hyped?
00:27:27 · Josh Woodward
[00:27:27] S1: Oh, yeah. Yeah. Under-hyped, I was thinking a lot about this over the summer. I ended up writing a doc internally just around Labs principles of how and almost like why are we building what we build? And so maybe the under-hype thing is more of a discussion around principles, values. I believe very strongly, whether you're at Google or a startup founder or anywhere in between, you speak through your products and your products actually represent and almost encode those principles. And so I wish there was a lot more discussion in the industry happening around that and what kinds of things do we want to build? What kind of future do we want? So anyway, that would be my under-hyped one because I think there could be more of that. I think the over-hyped one, I think I've been saying this maybe for a year now, but I still think it's over-hyped, model benchmarks. And I still, a lot of friends at a lot of Labs and everyone's still looking at the same set of benchmarks for the most part. But I think where I grew up and where I'm from, and I guess how I think about product development is most people in the world are never, ever, ever going to care about an Elo rating. They may not even know how to pronounce Elo. It just doesn't matter. And so that's where I get back to a lot of, I feel like the talk in AI right now is about speeds and feeds and benchmarks. And these are proxies obviously for where things are and capabilities. But I still feel like sometimes as an industry, it can over rotate to that and lose sight of why is this useful to someone and what's the product or the feature that's going to deliver real value to help people? So anyway, those would be my over-unders.
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.