Inside Google's AI turnaround: AI Mode, AI Overviews, and vision for AI-powered search | Robby Stein

Robby Stein is VP of Product at Google, where he oversees the core products of Google Search—including the new AI Overviews, AI Mode, search ranking, Google Lens, and more. Previously, he led consumer products at Instagram, where he and his teams built Stories, Reels, Close Friends, and other key features now used by billions. *What you’ll learn:* 1. Why Google’s AI products are suddenly taking off after years of perceived stagnation 2. How AI is expanding Search rather than replacing it, contrary to what many predicted 3. The three core product principles that have helped Robby build multiple billion-user products 4. Inside Instagram’s decision to build its own version of Snapchat Stories 5. His mantra of “relentless improvement” 6. How Google developed AI Mode from concept to launch in just one year 7. Why most teams give up too early on potentially transformative products *Brought to you by:* • Vanta—Automate compliance. Simplify security: https://vanta.com/lenny • Jira Product Discovery—Confidence to build the right thing: https://atlassian.com/lenny/?utm_source=lennypodcast&utm_medium=paid-audio&utm_campaign=fy24q1-jpd-imc • Orkes—The enterprise platform for reliable applications and agentic workflows: https://www.orkes.io/ *Transcript:* https://www.lennysnewsletter.com/p/how-google-built-ai-mode-in-under-a-year *My biggest takeaways (for paid newsletter subscribers):* https://www.lennysnewsletter.com/i/175041217/my-biggest-takeaways-from-this-conversation *Where to find Robby Stein:* • X: https://x.com/rmstein • LinkedIn: https://www.linkedin.com/in/robbystein/ *Where to find Lenny:* • Newsletter: https://www.lennysnewsletter.com • X: https://twitter.com/lennysan • LinkedIn: https://www.linkedin.com/in/lennyrachitsky/ *In this episode, we cover:* (00:00) Introduction to Robby Stein (04:46) Google’s recent success with AI (06:08) The evolution of Google Search (09:41) AI Mode and its impact (15:30) The rise of AEO (18:50) Building successful AI products (21:31)   Embodying relentless improvement (30:10) Lessons from Instagram Stories (35:20) Driving growth in established products (40:08) Balancing optimization and innovation (43:39) The journey of AI Mode: From launch to expansion (48:05) Organizational changes and urgency (49:51) AI Mode vs. competitors (51:35) Core product principles (57:07) Instagram’s Close Friends feature (01:03:01) The importance of resources in development (01:06:39) AI corner (01:11:19) Curiosity and learning (01:15:01) Lightning round and final thoughts *Referenced:* • Google Gemini: https://gemini.google.com/app • Nano Banana: https://aistudio.google.com/models/gemini-2-5-flash-image • Chat GPT: https://chatgpt.com/ • Perplexity: https://www.perplexity.ai/ • Google Lens: https://lens.google/ • AI Google search: https://www.google.com/ai • Why ChatGPT will be the next big growth channel (and how to capitalize on it) | Brian Balfour (Reforge): https://www.lennysnewsletter.com/p/why-chatgpt-will-be-the-next-big-growth-channel-brian-balfour • Alex Rampell on X: https://x.com/arampell • A 4-step framework for building delightful products | Nesrine Changuel (Spotify, Google, Skype): https://www.lennysnewsletter.com/p/a-4-step-framework-for-building-delightful-products • Look broader, look closer, think younger: Tony Fadell speaks at TED2015: https://blog.ted.com/look-broader-look-closer-think-younger-tony-fadell-speaks-at-ted2015/ • Jobs to Be Done: https://www.christenseninstitute.org/theory/jobs-to-be-done/ • The ultimate guide to JTBD | Bob Moesta (co-creator of the framework): https://www.lennysnewsletter.com/p/the-ultimate-guide-to-jtbd-bob-moesta • Rinstagram or Finstagram? The curious duality of the modern Instagram user: https://www.theguardian.com/technology/2016/sep/26/rinstagram-finstagram-instagram-accounts • V03: https://v03ai.com/ • Pirate GPT: https://www.kickstarter.com/projects/silentmeditation/pirate-gpt/ • The Bear on Hulu: https://www.hulu.com/series/the-bear-05eb6a8e-90ed-4947-8c0b-e6536cbddd5f • Dune on HBO Max: https://www.hbomax.com/movies/dune/e7dc7b3a-a494-4ef1-8107-f4308aa6bbf7 • Top Gun: Maverick: https://www.imdb.com/title/tt1745960/ • Purple pillows: https://purple.com/pillows • Avocado pillow: https://www.avocadogreenmattress.com/products/green-pillow *Recommended books:* • Competing Against Luck: The Story of Innovation and Customer Choice: https://www.amazon.com/Competing-Against-Luck-Innovation-Customer/dp/0062435612 • The Design of Everyday Things: https://www.amazon.com/Design-Everyday-Things-Revised-Expanded/dp/0465050654 • Aurora: https://www.amazon.com/Aurora-High-Stakes-Survival-Navigate-Darkness/dp/0062916475 • Project Hail Mary: https://www.amazon.com/Project-Hail-Mary-Andy-Weir/dp/0593135202 _Production and marketing by https://penname.co/._ _For inquiries about sponsoring the podcast, email [email protected]._ Lenny may be an investor in the companies discussed.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Lenny Rachitsky?

  It feels like something has changed internally at Google. Just last week, Google Gemini hit the number one app in the App Store. I feel like nobody saw this coming.

• 0:08Speaker 01

  Google's mission around have any information be universally accessible. It's a very enduring, very motivating thing. And it feels like with the AI moment, we can actually achieve that more than ever before. What I'm feeling now is just an incredible sense of focus and urgency. Things have hit a tipping point where these models are now truly able to deliver for consumers.

• 0:26Lenny Rachitsky?

  As ChatGPT emerged over the past couple of years, as perplexity emerged, a lot of people were just like, Google is dead. Nobody wants to sit through search results and click links.

• 0:35Speaker 01

  The core of Google's search isn't really changing, in my opinion. We're not seeing that. People come to search for just ridiculously wide set of things. They want a specific phone number. They want a price for something. They want to get directions. I think the vastness of that is underappreciated by many people. AI is expansionary. There's actually just more and more questions being asked and curiosity that can be fulfilled now with AI.

• 0:54Lenny Rachitsky?

  You've built a lot of very successful products. You use this phrase, embodying relentless improvement.

• 0:59Speaker 01

  You need to be the physical manifestation of two pieces of things. One is this relentlessness, like just complete effort that is always exerted in a direction of positive productivity. And then the second is make things better. You have to always make things better. You're never content.

• 1:12Lenny Rachitsky?

  You built and launched stories at Instagram back in the day is quite controversial because it basically took what Snapchat was doing really well. And then like, hey, let's bring it to Instagram.

• 1:21Speaker 01

  Not every great thing is going to be invented by you. Facebook probably created the modern feed, but there's a feed for every single product. At the end of the day, you're kind of robbing your user base of an opportunity to have a better product.

• 1:33Lenny Rachitsky?

  Today, my guest is Robby Stein. Robbie is VP of Product for Google Search and is responsible for essentially the entire Google Search experience, including the new AI overviews, AI mode, multimodal AI experiences like Google Lens, the ranking algorithm, and a lot more. He's at the forefront of one of the biggest shifts in Google's history and has already made a massive dent in Google's trajectory. He's also made a massive dent in the trajectory of Instagram, where he was head of product and led the launch of Instagram Stories and Reels and Close Friends, and through that, Groot Instagram, to half a billion daily active users. He's also on the founding team of Artifact with Mike Krieger. And Kevin Systrom started two companies of his own. Very few people have had this level of impact on two global consumer products at this scale.

• 2:19Lenny Rachitsky?

  And Robbie shares all of the biggest lessons that he's learned about building great and successful consumer products, along with a bunch of insights into where Google is headed in the world of AI. A huge thank you to Bart Stein for suggesting topics for this conversation. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. It helps tremendously. And if you become an annual subscriber of my newsletter, you get a year free of 15 incredible products, including lovable, replit, bolt, innate and linear, superhuman, descript, whisperflow, gamma perplexity, warp, granola, magic patterns, raycast, chat, PRD, and mobbin. Head on over to lennysnewsletter.com and click Product Pass. With that, I bring you Robby Stein.

• 3:00Lenny Rachitsky?

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• 3:45Lenny Rachitsky?

  Establishing trust isn't optional. Vanta makes it automatic. Get $1,000 off at vanta.com/lenny. This episode is brought to you by Jira Product Discovery. The hardest part of building products isn't actually building products. It's everything else. It's proving that the work matters, managing stakeholders, trying to plan ahead. Most teams spend more time reacting than learning, chasing updates, justifying roadmaps, and constantly unblocking work to keep things moving. Jira Product Discovery puts you back in control. With Jira Product Discovery, you can capture Insights and prioritize high impact ideas. It's flexible, so it adapts to the way your team works. It helps you build a roadmap that drives alignment, not questions.

• 4:29Lenny Rachitsky?

  And because it's built on Jira, you can track ideas from strategy to delivery, all in one place. Less chasing, more time to think, learn, and build the right thing. Get Jira product discovery for free at atlassian.com/leni. That's atlassian.com/leni.

• 4:49Lenny Rachitsky?

  Robbie, thank you so much for being here and welcome to the podcast.

• 4:53Speaker 01

  Thanks so much for having me.

• 4:54Lenny Rachitsky?

  This is such a cool week to be recording this podcast. So just last week, Gemini, Google Gemini, hit the number one app in the App Store. I have it right here. It's still number one in the App Store. It's above ChatGPT. I feel like nobody saw this coming. I feel like everyone's always like, Google, what have you guys been doing? You guys build all this amazing tech and where does, why isn't, why didn't you have anything working in consumer? Why is ChatGPT winning? Why are all these amazing companies doing better than Google? So first of all, let me just say, congrats, congrats on, I know this isn't all you. I imagine you had some part in this, so just congrats.

• 5:26Speaker 01

  Many, many more people, yes.

• 5:28Lenny Rachitsky?

  It feels like something has changed internally at Google. It feels like things are starting to really work, especially on the AI consumer side. So in terms of the growth, is Banana Banana the source of a lot of this recent growth? Or is there something else?

• 5:39Speaker 01

  People are really excited about Banana Banana, to be clear, very much so. But I think also people are recognizing that there's just so many cool things that you can do across the Google Center of Products and they've become quite powerful. And so I'm always shocked, even for, you know, things in search, people, like we think they're very obvious because they sit right in the core search experience. And then on, on X, I'll go look and like, oh, I just found out about this AI thing. And it seems very obvious, but I think a lot of people are just discovering quite how powerful these tools are now.

• 6:08Lenny Rachitsky?

  Yeah. So to go one level deeper, to your point, there's been all this incredible tech. You guys wrote the original Transformers paper that have powered so much of the innovation. And it's just like, where's Google been? And actually, why aren't they building the thing that's winning? What has changed? Is it just like, okay, we need a, has there been like major reorgs? Has there been new leaders put in place? Is there just like a new philosophy in the past couple of years that have led to this moment where Gemini is now the top app in the world?

• 6:31Speaker 01

  Yeah, I mean, look, I've been at Google now. This is, you know, my second time at Google. So I started at Google in 2007, done a bunch of things in between, and I've been back at Google now. So I can't speak to that whole period, you know, from many, many years back to today. But what I can tell you about how I'm, what I'm feeling now is just an incredible sense of focus and urgency to deliver great products quickly. And I think that that is in part leadership for sure. I think the people who are, we work very closely with our partners at DeepMind, you know, the Google DeepMind, we work very closely, obviously, across the organization. And it's just an incredible group of people and also an incredible group of, you know, researchers and technical thinkers who've been thinking about this for a while. And so when you have that energy, and I think the product teams and the tech, the research

• 7:14Speaker 01

  groups are working really closely together, we're able to move and we're getting a lot done. And so I don't think there's anything like one thing that has happened. I think that a lot of times people ascribe, you know, a lot of momentum to a one-time change or a single person. But I find a lot of this is actually this compounding effect. When you think about just every month, like ruthlessly improving the product or the models and just in every day getting better. And then it kind of just hits this tipping point where people just like it, they use it more, they enjoy it. And that's more of the feeling that I've had is just, you know, we've had kind of, I think, the right investment and focus. And then it just hit a moment where, you know, people are seeing the effects of that now.

• 7:52Lenny Rachitsky?

  As ChatGPT emerged over the past couple of years, as perplexity emerged and all these other chatbots, a lot of people were just like, Google is dead. Nobody wants to sit through search results and click links. Why not just get your answer right there? And it feels like that's not all happening. It feels like you guys are doing just fine. What can you share about just the, I don't know, the state of Google's search specifically? And then we'll talk about AI mode. Just like, how is traffic going? How is search going considering all these things are out there? And just what are you seeing in the data since the launch of, say, ChatGPT?

• 8:24Speaker 01

  Yeah, well, what's interesting is people come to search for just ridiculously wide set of things, like all kinds of things. They want specific phone number, they want a price for something, they want to get directions, they want to find a, you know, Payment webpage for their taxes, like every possible thing you can imagine. I think the vastness of that is underappreciated by many people. What we see is that that doesn't, it's not changing. Like AI hasn't really changed those foundational needs in many ways. And what we're finding is that AI is expansionary. And so there's actually just more and more questions being asked and curiosity that can be fulfilled now with AI. And so that's, that's where you get the growth. And so all like the core Google search isn't really changing, in my opinion, we're not seeing that. But you're getting this expansion moment.

• 9:06Speaker 01

  And so what we're seeing is a few examples is you can now take a picture of something and ask about anything you see. And Google Lens, one of the fastest growing products out there, it's growing 70% year-over-year increase in visual searches, which is already at like a massive scale. It's like billions and billions and billions of, of searching in that way. But you can, you can take a picture of your shoes, say, where can I buy this? Or take a picture of your homework, say, I am stuck on question two. And then just take a picture of your bookshelf and say, what are the books I should get based on these books? And AI can help you with those things now. So just an example of, I think, why there's so much growth left and, you know, why we're so excited.

• 9:41Lenny Rachitsky?

  Okay, so you're seeing, you're not seeing the death of search.

• 9:44Speaker 01

  No.

• 9:45Lenny Rachitsky?

  And along the same lines, you guys recently launched AI mode, which I don't think enough people are talking about. I think you get there, google.com slash AI. Is that, is that the right URL?

• 9:53Speaker 01

  Yep.

• 9:53Lenny Rachitsky?

  Okay, cool.

• 9:53Speaker 01

  Yep.

• 9:53Lenny Rachitsky?

  So I've been playing with it as we were prepping for this conversation. It's really incredible. I asked it, what is the best newsletter on product and growth? And it's very smart. It's a Lenny's newsletter, so that's my eval.

• 10:07Speaker 01

  Fantastic, okay, one of one, perfect eval.

• 10:09Lenny Rachitsky?

  It's perfect. Also, just if you go to it, you just, there's these recommendations for things to ask it that are just like, wait, how did you know I care about this stuff? So it's like, help me switch to product management, just like on the front page. I'm like, how, how did you know? And it tells you that it's based on your Google activity. Talk about just what people should know about AI mode, maybe what they don't really understand about the power of this thing.

• 10:31Speaker 01

  I can tell you, there's kind of three big components to what, how we can think about AI search and kind of the next generation of search experiences. One is obviously AI overviews, which are the, the quick and fast AI you get at the top of page that many people have seen. And that's obviously been something growing very, very quickly. It's just when you ask a natural question, you just put it into Google, you get this AI now, it's really helpful for people. The second is around multimodal, this is visual search and lens. That's the other big piece. You go to the camera in the Google app and that's seeing a bunch of growth. And then really with AI mode, it really brings it all together. It creates an end-to-end frontier search experience on state-of-the-art models to really truly let you ask anything of Google search. You can go back and forth, you can have a conversation and it taps into and is specially designed for search. So, so what does that mean?

• 11:16Speaker 01

  And one of the cool things that I think it does is it's able to understand all of this incredibly rich information that's within Google. So there's 50 billion products in the Google Shopping Graph, for example. And they're updated 2 billion times an hour by merchants with live prices. You have 250 million places in Maps. You have all of the, you know, finance information. I mean, just the, and then not, not to mention, you have the entire context of the web and how to connect to it so that you can get context, but then go deeper. And you kind of like put all of that into this, into this brain that is effectively this way to talk to Google and get at this knowledge. And that's really what, what you can do now. And so you can ask anything on your mind and it'll use all of this information to hopefully give you super high quality and informed information as best as we can.

• 12:01Speaker 01

  And, and, and you can use it directly at this google.com/ai, but it's also been integrated into our core experiences too. So, you know, we announced you can get to it really easily. You know, if you actually, you can ask follow-up questions of AI overviews right into AI mode now. Same for the lens stuff, take a picture, takes you to AI mode, so you can have this back. You can ask follow-up questions and go there too. So it's increasingly an integrated experience into the core part of the product.

• 12:23Lenny Rachitsky?

  I imagine much of this is wait and see how people use it, but what's the vision of how all these things connect? Is the idea continue having this AI mode on the side, AI overview at the top, and then this multimodal experience? Or is there a vision of somehow pushing these together even more over time?

• 12:40Speaker 01

  I think there's an opportunity for these to come closer together. I think that's what AI mode represents, at least for the core AI experiences. But I think of them as very complimentary to the core search product. And so you should be able to not have to think about where you're asking a question. Ultimately, you should just go to Google. And today, if you put in whatever you want, we're actually starting to use much of the power behind AI mode right in AI overviews. So you can just ask really hard. You could put a five sentence question right into Google search. You can try it. And then it should trigger AI at the top. It's a preview and you can go deeper into AI mode and have this back and forth. So that's how these things connect. Same for your camera. So if you take a picture of something, then what's this plant? Or how do I buy these shoes? It should take you to an AI little preview. And then if you go deeper, again, it's powered by AI mode. You can have that back and forth.

• 13:25Speaker 01

  So you shouldn't have to like, think about that. It should feel like a consistent, simple product experience ultimately. But obviously, this is a new thing for us. And so we wanted to start it in a way that people could use and give us feedback. You know, it's with something like a direct entry point like google.com/ai.

• 13:41Lenny Rachitsky?

  I recently had Brian Balfour on the podcast and he showed this quote that's really stuck with me that I think about as you talk about all this. It was by Alex Rampell. This idea that startups is a game of getting distribution before incumbents can innovate fast enough. And it feels like you guys are finally there where it's like, oh man, now here comes Google. I don't know if I have a question here, but it just feels like this is, there's been all this time for people to find distribution and now it's like, okay, now Google is coming.

• 14:07Speaker 01

  What we found is that people are asking these questions in Google, like they're trying to get this out of Google. And so if you can just have an AI that's powerful enough to answer a really hard calculation someone's trying to figure out, or like take a picture of like multiple choice homework question for a chemistry question, people are doing this. And so now that you have this really sophisticated AI that's based on our frontier models, we can just handle increasingly more and more stuff for people. And so hopefully that's like the more natural on-ramp here. And then we just need to make it easy enough for people to use because these are new products and people are used to using Google in a specific way. They type in keywords. We call it sometimes keyword ease. But you can actually use natural language in Google. That's the biggest shift we're seeing. People asking real, long, hard, complex questions. Because you just don't think, I can go to Google and type in like,

• 14:51Speaker 01

  what's a great place for a date night? I already went to these four restaurants. I'm looking for outdoor dining and my friend has this allergy. You could put that into Google. And I think that's the kind of thing that we're excited to continue to make easy for people.

• 15:03Lenny Rachitsky?

  It's interesting. And we've come around to back in the day, there was Ask Jeeves, which was this whole just ask a question as if you're asking a human and then it'll give you a really good answer. And then we moved into Google, just no, no, just type the thing you want and figure out how Google likes it. And now we're back to, okay, just ask your question and it'll give you a really good answer.

• 15:20Speaker 01

  Yeah. Ask Jeeves was surprisingly prescient on that, huh? It's like they like had, they had something like way before its time that I think it's rallied around now.

• 15:29Lenny Rachitsky?

  Oh, man. What's your take on this whole rise of AEO, GEO, which is this kind of this evolution of SEO? I'm guessing your answer is going to be just create awesome stuff and don't worry about it. But you know, there's a whole skill of getting to show up in these answers. Thoughts on what people should be thinking about here?

• 15:47Speaker 01

  Sure. I mean, I can give you a little bit of under the hood, like how this stuff works. Cause I do think that helps people understand what to do. But you know, when our AI constructs a response, it's actually trying to does something called query fanout, where the model uses Google search as a tool to find, to do other querying. So maybe you're asking about specific shoes, it'll add and append all of these other queries, like maybe dozens of queries and start, start searching basically in the background and, and analysts make requests to our data kind of backend. So if it needs real time information, it'll go do that. And so at the end of the day, actually something's searching. It's, it's not a person, but there's searches happening and then each search is paired with, with content. And so if for a given search, your webpage is designed to be extremely helpful.

• 16:29Speaker 01

  And then you can look up, you know, Google's human radar guidelines and read, you know, it's a very long document. That's been thoughtfully crafted for decades now around, you know, what makes great information? This is something Google has studied more than anyone. And it's like, do you satisfy the user intent of what they're trying to get? Do you have sources? Do you cite your information? Like, is it original or is it repeating things that have been repeated 500 times? And there's these best practices that I think still do largely apply. Because it's going to ultimately come down to an AI is doing research and finding information. And a lot of the core signals, is this a good piece of information for the question? They're still valid. They're still extremely valid and extremely useful. And that will produce a response where you're more likely to show up in those experiences now.

• 17:14Speaker 01

  I think the only thing I would give advice to would be, you know, think about what people are using AI for. I mentioned this as an expansionary moment, right? Like, seems to be that people are asking a lot more questions now, particularly around things like advice, or how to, or more complex needs versus maybe, you know, more simple things. And so if I were a creator, I would be thinking, what kind of content is someone using AI for? And then how could my content be the best for that given set of needs now? And I think that's a really tangible way of thinking about it.

• 17:45Lenny Rachitsky?

  It's interesting, your point about how it goes in searches. When you use it, it's like searching a thousand pages or something like that. Is that just a different core mechanic to how other popular chatbots work? Because the others don't go search a bunch of websites as you're asking.

• 18:00Speaker 01

  Yeah, this is something that we've done uniquely for our AI. It obviously has the ability to use parametric memory and, you know, thinking and reasoning and all the things a model does. But one of the things that makes it unique for, you know, designing it specifically for informational tasks, like we want it to be the best at informational needs, right? So Google's all about. And so how does it find information? How does it know if information is right? How does it check its work? These are all things that we built into the model. And so there is a unique access to Google. Google's, obviously, it's part of Google Search. So it's Google Search Signals, everything from spam, like what's content that could be spam? And we don't want to probably use in a response, all the way to, wow, this is like the most authoritative, helpful piece of information, we're going to link to it. And we're going to explain, hey, according to this website, you know, check out that information.

• 18:45Speaker 01

  And you're going to go, you know, probably go see that yourself. So that's how we've thought about designing this.

• 18:50Lenny Rachitsky?

  You've worked on a lot of AI products at this point. And it wasn't, it's not just Google or Artifact and Instagram. You did a lot of AI stuff. What's something you've learned about building AI products that you find maybe people don't truly understand? Maybe something that surprised you about building successful AI products?

• 19:07Speaker 01

  I think the most recent one, and this is true, something even within the last week or two, is that like, It's so obvious how human-like the interface is becoming with how you can communicate and steer AI. I think it used to be even just months back that you had to do a lot of work to like, get the AI to do the thing you're trying to get it to do, right? You had to do these incantations, you had to prompt in a really specific way. Like people have all these hacks like, hey, act like you're in, you know, you're a coach and you do these things and you have to really push it. Or to use a tool, you know, more on the technical side, you had to do post-training. Like you had to take this foundational model and you had to show it data. You had to train it and actually update its weights to do more sophisticated things.

• 19:50Speaker 01

  Cause it just, you'd tell it, hey, here's like documentation for an API. If you ever have a problem, you know, ping this API, here's the data. Like as if it's like an engineer that you had that you could talk to. And it would have no idea what to do with that, or it would have some idea and really wouldn't really do it. But increasingly you can just use language to like, almost if you were to write up an order, you know, you could be like, wow, like I, here's a, I'm a new startup. Here's my data internally, here are the APIs to it. Here's the schema and the URL, here's when to use it. By the way, make sure that if you get this kind of a question, you really make sure to get it right. And like, that'll end up doing a lot in the model. Like the model's been now encoded to, to be able to say, okay, I'm gonna like, use more reasoning or thinking budget for that kind of a question.

• 20:35Speaker 01

  Or I'm going to use tools or code, code use, code execution, in order to connect to this API I'm told about. And that's a relatively new thing. So I think it's gonna open up a lot of this democratization of accessing these models and building incredible things. Cause you don't even need to do a lot to get the most sophisticated outcomes increasingly. I don't think you need to do a lot of this heavy-duty fine-tuning.

• 20:58Lenny Rachitsky?

  Makes me think about, I had this recent guest, Nasreen Shingal on the podcast. She was a PM at Google, she worked in Google Meet. She was a delight PM, working on and making products more delightful. And she talked about the reason Google Meet did so well and is now feels like it's killing Zoom. Is they compared the experience of Google Meet to a human meeting versus making it the best possible video conference. It's, let's make this as good as a human experience. And that's interesting what you're talking about, how that's almost the goal here with AI is just make it feel like you're just talking to a person.

• 21:27Speaker 01

  Exactly.

• 21:28Lenny Rachitsky?

  Might be obvious, but it's, think about that. Okay, let me, uh, let me zoom out and talk about just, and let's talk about just broader lessons you've learned over the course of your career. You've built a lot of very successful products, which I've shared in the intro at this point.

• 21:44Speaker 01

  Many, many not, also on the other side of the spectrum, we got the whole portfolio.

• 21:47Lenny Rachitsky?

  Okay, perfect. Well, we'll talk about some of that. So I asked you as we were getting ready for this conversation, what's one thing you wanted to get across in this conversation? What's something you think would be really helpful for product builders to hear to help them build more successful products? And he used this phrase embodying relentless improvement. Can you just talk about that? What does that mean? Why is this so important?

• 22:07Speaker 01

  Of course. I mean, I think that you need to be the physical manifestation of two pieces of things. One is just relentlessness, like just complete effort, but is always exerted in a direction of positive productivity. And then the second is make things better. You have to always make things better. You're never content. And I think this actually came out of a story, a little bit of a funny story where I was at Instagram at the time, doing a big, you know, all team meeting on my first. And they had this icebreaker. It's like, what's one word to describe yourself? And so in the backstage area, I texted my wife really quick, like, hey, just one word to describe me, first thing that comes to your mind. And she just wrote back dissatisfied.

• 22:45Speaker 01

  And I was kind of chuckling in the, in the back room because I was first of all, like kind of offended because I was like, it's not like loving, caring, like, like something good. And then she, and I saw like her little bubble thing, like, and she's like, okay, there's more. And then she wrote me this like really thoughtful thing that was like, you know, it's not that you're just unhappy. It's like you're, you want the world to be better. You're driven out of a deep desire. It's, it's that you feel this sense of dissatisfaction with what the world gives you. You want to make it better. And you're pushed and motivated to do that. And I thought about that after, and it wasn't until we built a bunch of, you know, products, you know, some that didn't do well, some that have had a lot of really large success.

• 23:23Speaker 01

  Now billions of people use them, where it felt like one of the big differences, obviously a lot of it is just the conditions of the product and the, you know, a little bit of luck here and there too. But for the things that went well, there was always this spirit of just, we're going to get it eventually. If we just make two more moves to make it, to make it better. And then eventually, as I talked about before, earlier in our conversation, you get this tipping point. Where it just kind of tips over into being net useful to people because of just that amount of compounding effort that you put into something because you're just always so you're the harshest critic and the most dissatisfied person in the room about your own work, basically. And I think that's really meaningful. And there's this other incredible story that Tony Fadell told on a TED Talk like 10 years ago. You can look it up.

• 24:07Speaker 01

  I think it's something around Think Younger as a title. And he talks about what it means that as we grow up and age and become grownups. I have two little kids, so that's something I think about a lot. We habituate to everything, like we accept and we tolerate what the world gives us everywhere. And we just go, oh, that kind of sucks. Oh, well, we shrug our shoulders and we move on. But if you don't do that and you ask, why? Like, this sucks. Like, why am I tolerating this? And how do I make it better? He has this incredible story about going grocery shopping. And he goes on for like 10 minutes about this story almost, it felt like, where he talks about getting a piece of fruit, like a plum or a peach, and how it has that sticker on it. You know, it's got that sticker. And who put that sticker there?

• 24:51Speaker 01

  And then when you get home, you take your fruit out of your bag. You're ready to eat it. You're all excited. You stick your thumb under the sticker. It punctures the flesh. He goes into just incredible detail about how it punctures the flesh of the fruit. The sticker comes off. Now the fruit's bleeding. Then you like flick the sticker. The sticker like misses the garbage. You like bend over and pick it up. You like put the sticker back in. And I was like, wow, like that is embodying this mentality, right? Of like, just why is this here? How can this be better? And I think the best product people, the best thinkers in the space, that's how they think, in my opinion.

• 25:32Lenny Rachitsky?

  I imagine there are many examples of you doing this in the many products you've worked on. Is there one that comes to mind as a good example of this inaction, of this actually working really well and delivering something really huge?

• 25:44Speaker 01

  I mean, honestly, like a big thing is working on AI mode. Like, I think a lot of it was, you know, we um, we saw in um, AI overviews that people were trying to ask harder questions, and we weren't able to answer a bunch of them, or AI overviews just didn't show up. And so, you know, a bunch of us sat around, we're like, why can't you just do this for everything? Like, like, why can't we use, you know, instead of saying, oh, we don't need to to to solve for that? Or, you know, um, that's not something that's like in the most addressable next thing. It's like, we actually saw people in the query stream, putting the words AI at the end of their queries, because they're trying to like, get the AI to like, do the thing. And so, we would look at that, and it's like, this is ridiculous. We need to build something uh, here.

• 26:27Speaker 01

  And um, that was a big motive, that was one of the big motivations, was actually identifying that like, user problem, being very disgruntled on behalf of the user. Like, I'm, we're just failing the user. Every day, we are not helping them actually get their thing, and like, kind of better understood. And we're gonna go build a whole thing because of it. Um, because that's hard to do, by the way, to build all of that. Um, but it just was so obvious that that's what we needed to do.

• 26:52Lenny Rachitsky?

  There's kind of two buckets of people, let's say, hypothetically. One bucket is, just make things better, make amazing experiences, you're gonna do great. There's another bucket that's like, drive metrics, drive goals, hit our KPIs. I know what you're, you're not saying is just work, like, work on things, making the, just make things better, relentlessly make things better. How do you just think about, I guess, that overlap of, okay, makes things better, but also, here's what we really, here's the strategy, here's the vision? How do you think about those?

• 27:17Speaker 01

  Yeah, I don't think of them as an or, like, I think they have to be like, intersected. Because basically, the way to think, the way I think about it is, you actually start with, you know, a problem, or the inverse of that, which is a vision. Uh, but they're connected. It's like, people, most great companies, most great products come out of a problem. But out of the problem becomes like, here's a better way. What if you, instead of this crappy thing, or way of living, or thing that we all tolerate and accept? You know, some entrepreneur comes up and says, What if we did this other thing? And then it's what comes out of this dissatisfaction and this this sense of better that you need to make things better. But then you're going to build. And at the end of the day, you need your instrumentation to know if you're on the right track. And that's where you bring tools like, okay, you build your first version of the product.

• 28:02Speaker 01

  Do people like it? It's like, and then each product goes through its journey. So the way you understand people like it is you you scrutinize typically. You talk to people, but you also add some analytical tools there. You might look at something like a J curve. So this is the retention, the percentage of people still using the product. Day seven, day thirty, day ninety. And does it flatten? Or do people just drip out of there? Like over time, it's just not exciting people. And that would go to zero if on a long enough timeline, no one's going to use it. You don't get past that, you're toast, right? Then, okay, some people are doing it. Okay, great. We need more people to do it. And it needs to be good enough that people talk about it and then it grows. And so that's another gate. And then there's another one, which is like, well, how big can this get? Actually, is it a small thing?

• 28:47Speaker 01

  Is it a medium thing? And I think most companies like you have like an aspiration of being big, but you can't start big. Everyone's got to go through that journey. No product has started big, even ones that get big really quickly, even after even like a week quickly. They had something and that even internally, they started small. They start small with a hundred, two hundred, hundred people. And so you have to be metrics focused, I think, in order to know if you're doing the right thing. And then the other thing is on the other side of the spectrum, you're running a big thing. And there you need metrics to be your guide. Like if your product, let's say, okay, let's say our core metrics down five percent this week. It's like, well, what's going on? Right? And so you need to be really close to root cause analysis there and say, well, actually turns out that it's an issue. Is it in a region? Is it on a device? Is it in a demographic? Is it in a use case?

• 29:31Speaker 01

  Where is my problem lie? And then when you get to it, you understand the problem. And then you can, this improvement thing comes back or it's like, okay, I'm going to make that. I'm going to fix that thing. I'm going to, what's the treatment for that? That disease? And you get, and then you're back to growth again. And so you kind of need this and you always are looking at what's the, what's the system that I'm working on? And what are my instruments? I'm a pilot to know if this thing is going and flying correctly. But then it doesn't tell you exactly what to do. You have to think for yourself how to make it better. I make it just show you a little bit of the way.

• 30:05Lenny Rachitsky?

  I love that you just gave a masterclass on just how to prioritize and pick what to work on.

• 30:10Lenny Rachitsky?

  I want to go on a quick tangent. Speaking of products that have done really well and become really big, Stories, you build and launch Stories at Instagram. It's quite an infamous product launch back in the day. It was quite controversial because it basically took what Snapchat was doing really well. And then like, hey, let's bring it to Instagram. And it was not great for Snapchat. Now that it was so long ago and just it's so far in the past, I'm so curious just to hear about that time reflecting on just that decision, what you guys talked about, how you decided to go ahead with that. And anything, just, I don't know, you think about looking back at that?

• 30:47Speaker 01

  I think there's a couple of really important lessons from that launch. And I mean, we went on afterwards to launch reels, a bunch of updates to direct messaging. We had feed ranking. I mean, there was a huge era there when I was there between 2016 and 2021 or so, where just so many products got built. And I think an interesting lesson in all of those, and particularly in Stories, was you have to really understand why someone uses your product and know when something is actually an existential question. Because there's just a better format or a different way of doing something that has worked and works, and you need to figure out what that might mean for you. Because not every great thing is going to be invented by you.

• 31:28Speaker 01

  But I think that a lot of these things are, you know, they can become formats that you can make your own. And you need to learn from the world and what's happening out there in order for your product to always give the best thing to its users. And so for Stories, you know, we looked at Instagram like, what's the point of Instagram? It is sharing your life and connecting with people ultimately. And if there's a way to do that, that lowers the pressure because it doesn't have likes or it's just a ephemeral format. And it's optimized well for mobile because it's this full screen experience. Like, it's a really great format and kudos to Snapchat for inventing it. You know, we didn't think of that as like a deterrent, that we had to go make like, you know, Instagram.

• 32:12Speaker 01

  Photo clock. And actually, there were early versions of this idea where you try to take the core Instagram feed and make it ephemeral. And whenever you try to mix a core product that's very cemented in someone's mind and physically looks a specific way, and you're trying to make contort it to do something new, it's usually a bad recipe. And so we knew we needed to do something new. And then it was so clearly was critical to the core essence of what the product could do, could fit in naturally. But the question was, how do we make it our own? And how do we how do we build on this? And so if you think there were a bunch of things that we did that made it Instagram. And so, for example, it had different creative tools, and it had things like neon drawing and these like really sophisticated filters that people loved. You know, we also looked at this talk about being dissatisfied.

• 32:56Speaker 01

  Like, people took a lot of times, they would they want their main camera to take a picture of something. And then they want to upload it to Instagram because they want to save it. And they want to be in a very high quality, high resolution photo because it's a memory. And Snapchat at the time didn't allow you to upload photos. It was like you have to use a snap camera. And so we made a bunch of decisions like that, where why don't you just let people upload their can their photo? Like, what like, why? Like, this is the back to the dissatisfied point. Like, that's frustrating. You know, or there's another example where you couldn't pause. If you like, were consuming a story, you couldn't pause it. It just would like, go through and be done because it was like this ephemeral thing. And you wanted to create safety. Like, why can't you just like, it's it goes by too fast. So we added this pause. It's such a small thing, but you put your finger down to pause the story

• 33:39Speaker 01

  now. And so there were a whole set of those things that were shipped that made stories feel Instagram wasn't like you just had some other thing. And then it turns out that worked incredibly well. And so so much to the fact that someone on the team mentioned that they always felt like, at the time, they didn't realize it, but it was almost like it was missing the story sized holes at the top of the page. And it like completed the product in some weird way for them. And so that was, I think, an important lesson.

• 34:05Lenny Rachitsky?

  Instagram definitely got a lot of hate for that moment from a lot of founders. It was just like, hey, you guys just stole this idea and that sucks. How did you guys just deal with that internally? It was just, this is, you know, we gotta do this. We gotta focus on our shareholders and grow this thing. And that's how it goes sometimes.

• 34:19Speaker 01

  I mean, I think it's more that we're focused on our people, our users and the people who are loving Instagram. And it's denying them the opportunity to have an easy way to just share a photo and like have the thing go away. You know, I mean, that's ultimately what we were trying to add. At the end of the day, that is a format that people adopt in the same way that think about feeds. You know, I think we talked about this at the time too, when we shipped it, like, you know, Facebook probably created the modern feed. But there's a feed for every single product, right? And there's a LinkedIn feed and there's a, there's a feed for DoorDash. You know, it's not like, like these things become core primitives quickly and formats. And then at the end of the day, you're kind of just robbing your user base of the opportunity to have a better product.

• 35:03Speaker 01

  If you're not making the best possible product for your use cases and for Instagram is used differently. Like people use Instagram differently than they use other products. And it turns out that there were these experiences in WhatsApp and in Messenger and in many other social products over time. And they all were used differently, actually, which is, which is fascinating.

• 35:20Lenny Rachitsky?

  So something else I want to talk about is you, you came into two products that were already doing really well. Instagram and Google. And on the Instagram side, a transformative growth and improvement. Google is, it's happening. We're in the middle of the improvement and growth you're, you're driving. Not a lot of people get to do this where they go into an existing product, make it grow significantly. A lot of people want to do this. They have a product that's been around for a long time. Hey, how do we make this grow and be more successful? Is there anything specifically that you've learned about just coming into an existing product? Figuring out where the big opportunities are and then just like hockey sticking growth? Because this is what everyone wants to do.

• 35:57Speaker 01

  There's a couple of lessons here. And I think, by the way, the first lesson is to be humble always because it's extremely incredible. We gotta work on products that have such impact on people. And I view product like golf, like you're always one stroke away from shanking. And like, as soon as you think you're good, you're not like you don't know anything like the world changes quickly. You have to always be a servant to your user base and the people that are out there and and learn from them. And so the first thing I always do and think about is you get in touch in terms of like, why are people using this product? And where are the areas of growth? And so usually even in a in a big product or a mature in a complex system, there's an there's a part of it that's growing, there's a part of it that's mature. There could be a part of it that's that's declining or isn't growing as much. You know,

• 36:41Speaker 01

  I certainly in Instagram, there's been a big shift over the years of sharing into public, very large broadcast posts and feed into these more lightweight formats like Stories and DM, actually, private sharing as well. And so you have to observe that. And because the every every month, every year, the world changes, people's needs change. And so first thing you do is you you kind of get a sense of what do people want out of this product? What's its true essence? You know, I think a lot about this jobs to be done framework, which is one of the things that, you know, I'm a big fan of. And, you know, Clayton Christensen's book on competing against luck is one of my favorite books on this topic, where you have to really be a student of causation. Why is someone using this product? Like, what are they doing with it? And what are they trying to get done with it? And that

• 37:26Speaker 01

  usually leads you to kind of bigger next stage ideas. And it it it removes this belief that you need to solve the problem with the current tools. So in the Instagram version, it was like, you have to make a square photo, do more for people, right? Like, that would be like how you increment the product. Or in Google's example, there's like something very specific with the core search experience that needs to change. It's like a subtle tweak. You know, you have to kind of think, well, what's the big thing someone's trying like someone's trying to ask a really hard question out of Google? Like, what's the best way to do that for them? And so it makes you think more first principled. And that's the first basis of this. And then once from first principles, you're like, oh, this newer thing, and it could be a shift, it could be a new form. In many ways, the AI version

• 38:10Speaker 01

  of Google and Stories and Reels, they're all kind of similar in that they're new formats in the world that people are expecting and wanting more of. And by adding them, it becomes complementary, not replacement. And in both cases, like Stories didn't replace Instagram. It became it expanded in the same way we're seeing for AI. And so what's interesting is then you think, well, how do I bring that into my world? Right. You have this big mature product. And the best way I've seen is by making it complimentary, having it be a core part of the experience, but clearly defined as a distinctive thing that has its own attributes associated with it. People think spatially. So if you have a feed and you have holes with pictures, they expect those holes to do things. And so if you make one of those holes with a little clock and that one goes away the next day,

• 38:53Speaker 01

  or you can't like it, or it operates differently than the other parts of your feed, it's gonna be super confusing for people. It sucks. And so you have to add product carefully, but it needs to feel coherent, but different. So stories, you know, it has similar aesthetic. It obviously uses your camera roll in the same way. It works, you can share it in DM, it works in the system. But it has a different primitive in the same way. Google AI, you know, it's a full page experience that you can pop out now. You can have follow up conversation with it, right? People have a set of expectations you need to snap to for those use cases. And then you are constantly learning how to best make these new products work within your world. And you never just want to snap in something that's working. You have to make it work for your users, your expectations, and what people are trying to do with your product.

• 39:38Speaker 01

  It's actually one of the things I see people fail on the most is they assume something working for one system will work in your world. But someone else's system is on totally like the types of users they have, where the consumer expectation of that product is totally different set of expectations. So you have to kind of respect that and say, well, can we learn from that and bring it here? So that was, I guess, you were to talk about the kind of the method that I've seen now twice, I guess. It's kind of how these products have developed.

• 40:08Lenny Rachitsky?

  I love this topic. It makes me think about just this balance people always try to find between optimizing something they've already got versus trying to take a big bet on something. And you've done, you've had so many examples where you've taken a big bet on something totally new and it's worked out incredibly well. Do you have kind of just a heuristic and how you structure teams and prioritize across, okay, we have amazing Googles or experience today. What percentage of resources go into improving that versus trying something totally new?

• 40:35Speaker 01

  That's one where I actually do feel like the more analytical, like systematic thinking helps a lot. Because you kind of, you're trying to produce value in the world. You want to quantify it some way. And so if you're seeing this growth curve and you're trying to understand, wow, people are using it more and more to like this product. And when products are young, they grow. And then eventually, things mature. And you can break out product suites and different features of products all along the same way. Certain features that are going fast, other features that are not. And you get to these points of just diminishing marginal return in every system, where it feels like you could put 50 people on this project. Like, it's just not going to dramatically move the needle. And so, part of it is this bottoms up thing with your own team, being really thoughtful about what is the expected value of that investment?

• 41:19Speaker 01

  And knowing when it's starting to approach zero, like diminishing marginal return. And then, when that happens, these are these moments that usually coincide with something fundamental changing. Either people's expectations externally, market saturation, there's something happening where you need to adjust. And you then find your next growth driver or set of drivers. And that's where you need to go more first principles and try these new things more. And then, when you land a new thing, that creates this new little growth engine. And then, you put people on it and you optimize it because you're getting big. Like, each change is like 10% win, 20% win, 4% win. And it's clearly, like, still has so much value and headroom and to make it better for people. And you can see that in the data.

• 42:04Speaker 01

  And so, that's becoming, I talk about this instrumentation. It becomes your guide for knowing if you're making good calls. Otherwise, if you don't know where you're headed and you don't have a goal of what you're trying to do more quantitatively, it's really hard to know if the thing you're doing is mattering to anyone. Because you'll just, I think I made the product better, but like, does anyone use it? Does anyone care? Or are we just congratulating ourselves? Like, ultimately, you want to have impact on people and that's what matters.

• 42:29Lenny Rachitsky?

  So it's essentially tracking S-curves on every product and understanding if you're in the plateau and if it's time to invest heavily somewhere else.

• 42:36Speaker 01

  Yes.

• 42:37Lenny Rachitsky?

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• 43:19Lenny Rachitsky?

  It's orchestrating autonomous agents and complex workflows to deliver smarter outcomes faster. Whether modernizing legacy systems or scaling next-gen AI-driven apps, Orkis accelerates your journey from idea to production. Learn more and start building at orkes.io/leni. That's O-R-K-E-S dot I O slash leni. Maybe it would be helpful to talk about the journey of AI mode, just like how it emerged and the steps that you took to now it's just such a big part of the Google search experience. When did this start? How did you decide this is worth betting on? And then what were kind of the steps to get it further and further rolled out?

• 43:55Speaker 01

  I mean, I think it probably started earlier on with AI overviews, actually, which was the first way we brought kind of generative AI to search. And in that world, we noticed that people were asking these questions. And many people were actually trying to put natural language questions into search. And so how can you provide helpful context, links to go deeper, and make an AI that made sense for Google? And so that was our first version of these models that could do this for people. And then by building into that and seeing kind of this observation around people wanting more of it, direct access to it, and then being able to ask follow-up questions, like you kind of need a new modality. Like, it's not, it's gonna be really hard to build all of that within the construct of the core search experience.

• 44:36Speaker 01

  And so that led us to have a, form a small team of folks, a few people that were like technical leaders, a couple designers, very small, to just prove out, like, what if there was on almost like blank screen, like delete, like, like, make a little, like, like a fresh doc with a blinker? Like, what if there's a new, a new page? And you can ask the question, you can ask every one of it. You can tap right into the AI that was originally powering powering this top of the experience in search, but we invested in making it much more powerful in the ways I described before. It was in it could it could search for you. It had reasoning as a part of its model capability. It had multi-turn context. So if you had a conversation with it, it could keep track of that context.

• 45:21Speaker 01

  So it had some unique pieces to it. And what would happen if we tried that quickly? And we basically got, I mean, this was probably like five to 10 people worth of people originally.

• 45:29Lenny Rachitsky?

  And how long ago was this team formed?

• 45:31Speaker 01

  This was probably over the last last year, like last summer.

• 45:35Lenny Rachitsky?

  Oh, wow.

• 45:35Speaker 01

  Basically.

• 45:36Lenny Rachitsky?

  So about a year ago.

• 45:37Speaker 01

  Yeah, maybe about a year ago. It was where maybe it started. And and we were really kind of plugging away on it. And then we kind of saw this little version of it emerge that wasn't very good, but it had this moments of brilliance. And it's actually, again, it's kind of like golf where like you hit the perfect shot. And you're like, oh, my God, like you get that feeling where it's just everything worked. And I asked it a question about, I forget, I was like, I was doing something with my daughter and I was planning an experience. And it found all this like incredibly useful information about park information. It had it had links to like, go to the site and confirm a bunch of things. It had Google Maps information that like for my daughter, you could, you know, walk up. It had like, it was walkable.

• 46:19Speaker 01

  Like there was early examples like this where it was just, it blew me away what it could do, what it could find and how helpful it was. And so it gave us conviction that we should go and and go go further. And obviously, there's lots of people involved in this type of a decision, tons of support from leaders across the organization. But it just was like a little working team that that initially you kind of, you got to build something. And then you have to feel it yourself. And it's very entrepreneurial in that way. And then when you see it tangibly, you're like, we need like, what's what's a version of that? That's good and that could work. And that gave you gave you hope. And so then we basically built it out and built the first version that that launched in labs, basically.

• 47:01Lenny Rachitsky?

  So the the first big milestone was this is working. It was just a qualitative experience of like, oh, wow, this has really, this there's magic here.

• 47:09Speaker 01

  Yes, it's working. And then we did bring it before labs, actually, to trusted tester group. There may be like 500 people externally that we added on to it and we had pings with them. Some of them were friends. They actually had friends and family. We tried to treat it a little more like a startup where we want, we feel like you got to have people test it to tell you the truth and tell you when it sucks because it probably does. And then they message you. So I had a friend who was loving it, but also hating it for lots of good reasons and would just be messaging me all the time, screenshots, this broke, this broke, this makes no sense. And so we kind of had that for a while. And then we got to a point where it was feeling good. You know, the trusted testers were liking it, reporting good stuff. And then we brought it to this labs moment where anyone could turn it on. And then we used that to make it better with real query data. Like we could actually see what people were using it for at

• 47:53Speaker 01

  more scale. And so that could tune it to make it better. And then we launched it out to everyone, or at least in the US. And then we've now been on this journey to expand it to all countries and languages and have more people be able to access it.

• 48:05Lenny Rachitsky?

  It's incredible that Google went roughly in a year from idea to a significant change to the search experience that's AI powered. I think this is not what people imagine Google is like, and it feels like things are different and things have changed in how you guys operate. What has allowed this to happen so quickly? What's changed? Is it just like top-down leadership? We need to get you done? Or is there something more?

• 48:30Speaker 01

  No, I mean, I think it's interesting how organizations change. I think, I think when you feel like there is a moment in time that is clearly critical to deliver for people. Like, people are trying to get information from Google. We are not able to answer certain things or help people in certain ways. And there's this technology that can do it. That creates urgency. And obviously, there's lots of people building lots of things and the market's crazy and there's lots of things shipping all the time. And so there's a really exciting and healthy moment for us to build and build quickly. And I think it's just exciting to be able to capture that opportunity. Because I think people believe, and I certainly believe, that the next year or so of

• 49:09Speaker 01

  product is going to kind of establish how people use the next wave of products for many years. And so at least, I mean, I can only speak for myself, like I feel this obligation to our users to give them the best version of Google that's powered by AI and that gives them the full knowledge of everything Google knows about the world and information to people and accessible with AI.

• 49:31Speaker 01

  So that's that's that's driving a lot of the the excitement.

• 49:34Lenny Rachitsky?

  Yeah, it's such a good point that people are building their new habits. Like, it's wild how many people just now rely on ChatGPT and how quickly that happened. And I could see Google being worried that, oh, shit, everyone's changing their habit from searching Google to searching ChatGPT. And the fact that now Gemini is number one. I was actually looking at the list of top. So in the top fifteen apps, Google is, I think, five of them. A third. That's out of control. Killing it. When people look at AI mode versus ChatGPT or Claude or, let's even say, perplexity, what's the way you think about the positioning of AI mode versus these other tools? Is it like trying to be a direct competitor? Or is it just like, no, it's actually pretty different and here's what it's for?

• 50:14Speaker 01

  Yeah, I mean, AI mode is a way to ask search anything you want. It's for it's designed and specially created for information. And so really, it's it's it should give incredible, helpful responses for the things that people come to Google for. So think about, you know, you're planning a trip, you're trying to buy something, you're working through a question for a research project. Like, it needs information. And then that's really it's it's less focused on things like creativity. Although there's things it can do that are nice there, it can help you with just like any any kind of core AI product. Like, you can ask it to rewrite something for you, it'll do that. But we are less focused on creativity, productivity, like upload a spreadsheet and like output graphs for me. Like, we're not focused on that.

• 50:57Speaker 01

  Like, we're really focused on what people use Google for and making an AI for that so that you can come to Google, ask whatever you want and get effortless information about that and in context and links to then also verify, dig in and go to the to the authoritative sources ultimately that people want and we hear from people. So those are ends up becoming the distinct qualities of this product versus, you know, more of like a chatbot, or maybe you would talk to it, like, you maybe even have like a bit of like, hey, how are you doing today with that chatbot? That, you know, we have some of that, we see that a little bit, but people are usually coming for information, they're trying to learn something. And we've focused our product on that.

• 51:30Lenny Rachitsky?

  Got it. Okay, AI mode is not your therapist.

• 51:35Lenny Rachitsky?

  Maybe zooming out again a little bit and reflecting on all the amazing products you've worked on, all the places you've worked, if you had to pick two or three just core product principles or philosophies that have helped you build such amazing and successful products, what would those be? What comes to mind?

• 51:52Speaker 01

  I mean, there's typically three things I think about. Like, if I were to write a book about like, how to build great products, there'd be like, three chapters. I mean, probably more than that, but three chapters.

• 52:04Lenny Rachitsky?

  I love that. I love the shirt that would be. That's the ideal book.

• 52:06Speaker 01

  The first, I mean, I thought about these three areas now for a while. And it's like, they're always consistently the three things. The first is deeply understand people. And I think we talked about this a little bit with the jobs to be done point and Clayton Christensen's book, which I loved around competing against luck. It really helps you be a student of why someone ends up, in his words, hiring a product. Like, don't think of users as using your product. Think of users as hiring you to do something for them. You know, there's this famous quote, I think it's Theodore Levitt had, you know, people don't want a quarter, people don't want a quarter inch drill, they want a quarter inch hole. So what is someone trying to do? You have to understand that deeply. And then you

• 52:50Speaker 01

  can build an amazing product. And also, by the way, how do you, when you go back, like, why someone not using your product, right? Like, and so it focuses on these techniques to extract causation. So he actually talks a lot about this interview, he calls it like an interrogation, where you talk to a user, like, hey, why did you use my product? Where were you? Were you in bed? Were you like, at work? What were you doing? Oh, I was talking to my, you know, wife in the morning. Okay, well, what brought it up? Well, I guess I was reading the newspaper. Okay, well, why? And then you have this like, aha moment, like that, when they first decide to use your product, he calls it the big hire. That is information that you obtain ends up becoming the most critical, because that is what caused someone to use your product. And if you can study that and understand it, you will be much more on your way than just building things that sound cool. And so that's the

• 53:35Speaker 01

  first chapter is like, deeply understand people. Second is really around analytical rigor and understanding your problems. You have to understand your problems. And this got, this is a little bit of what we were talking about, about root cause analysis and understanding, okay, the metrics are dropping, like, why? Someone's not using your product, why? And really being able to dissect that to get to true root causes. It's like, well, they went all the way to the end and then bailed. And you talked to, and then you understand, it turns out that it was most, we actually learned about this and There's a story in Close Friends on Instagram where it just totally failed at first on a, in a bunch of, just when we shipped it. And it turned out that we looked at the data and people were only adding one close friend to their list

• 54:17Speaker 01

  because it was mistranslated as best friend in many markets. So people just put one person and then the probability that person saw it and wrote back to you was like zero. It's a product that's just broken. So it's like, you gotta understand your problems. And then the third one's around really designing for clarity instead of cleverness. Like a lot of people are like, oh, we're gonna differentiate the design. And we talked about this a little bit with stories. Like, we're gonna make a new version of something. But if something's a standard and people understand it, if you lean into it, you're gonna get so much leverage than if you reinvent it. And you have to be really thoughtful around when you reinvent and where you don't. And I think on this one, there's this great, Don Norman's book, obviously, Design of Everyday Things is a big one.

• 55:00Speaker 01

  But he has this incredible chapter in there about doors. And how, why is it that after all of these years, you walk up to a door? And based on how they're designed at times, people still don't know if you should pull or push that door. Because if you try to build the most beautiful symmetric two handles on each side on a glass door, it like doesn't communicate any information to you. And there's lots of, I've seen all the time we've designed new icons when we could have used global icons. Like, oh, wouldn't it be so cool if we used, you know, like a camera? That's like kind of a camera, but is mostly an AI looking thing. And then is most, but then has the dots in it that connects it to this other product. And you're like, people just, just, it's a camera, just put the camera in. Maybe you could add like a little thing to it. And that's how you get people to use your products.

• 55:45Speaker 01

  And if you do those three things, I think you typically can do well. And then, I'm sorry, the fourth one was more of the code is be humble, like constantly and always. Question yourself, listen to others, listen to users and be open to being wrong.

• 55:59Lenny Rachitsky?

  I love these. On that third point, I feel like AI mode as the name is such a good example of clarity. What is this? This is AI mode.

• 56:07Speaker 01

  We talked about it internally. It's like, if you look at it in the tab, it's like everyone knows, it's like you see it and you'll know what it is. Or we could call it something like random, but then what is that? You know, and now you're working against yourself.

• 56:20Lenny Rachitsky?

  So if I were to reflect back these three pieces of, basically this is the, this is the book you would write to help people build more successful products. It's understand the problem you're solving for people deeply. What's the job they're hiring you to do? I love the, I love the, it's like lowercase jobs to be done. It's not like the, the rigorous whole thing.

• 56:39Speaker 01

  Exactly. No, lowercase for sure.

• 56:41Lenny Rachitsky?

  Okay. This is just like, why are people hiring your product to solve a problem for them? What problem are they solving? So it's like, basically figure out why they, what, what problem they're having, then very, uh, through data, understand the problem and whether you are solving it. And then it's just keep it really simple, like clarity over cleverness, essentially.

• 57:02Speaker 01

  Exactly. Yes.

• 57:03Lenny Rachitsky?

  Is there? And be humble. Yeah. It's okay. Important. Is there an example that we haven't talked about that shows this in action of just like, cool, here's the problem we found. Here's how we figured out this is the solution. And if we're succeeding, and then here's a very simple way of solving it.

• 57:19Speaker 01

  I mean, honestly, the, this close friends example, I can give you more from Instagram days was really wild. It took two or three years to get close friends to work. And I think people, it totally failed originally. This is the product that lets you add a private list of people and then you can post to your story and then only those people see it. It's like this very exclusive private space. So you can feel really comfortable sharing.

• 57:39Lenny Rachitsky?

  Green, green circle.

• 57:40Speaker 01

  Green circles. Yes. Um, it's one of the most popular, at least when I was there, it was one of the most popular features of stories and did really well. But it totally failed. And I think, you know, what we, what we found out was that, um, you know, you actually used a bunch of these, these techniques here. So one was, um,

• 57:59Speaker 01

  We first thought about it as an overall system problem. And you could add a close friends post for anything. So you could do a feed post or a stories post. And you also had a close friends profile. So you could see like, like if Lenny went to Robbie's page, we were close friends. You would just be like, oh, you get to see extra stuff from me on my profile, too. So we shipped it. We thought it'd be great. This is the be humble part. Wasn't great. Had a bunch of, it was just super confusing. Like you'd see this really beautiful photo. And then in the feed, right after it, this blurry, very vulnerable moment, someone's trying to share with their friends. Just felt so out of place and weird for the, you know, the reason people use feed. And then it was just confusing because you didn't, it had like an extra little green thing on it. But it was like, that got a green thing and the stories one didn't.

• 58:43Speaker 01

  If you open the story, it had a green thing inside the story. And people were just so confused. And they had this other issue with the list where you're like, okay, the list doesn't work because it's mistranslated. And people don't get it. Cause I think it was actually called originally favorites. I want to say. And that encouraged people to just do like two people on it. But then the way that it worked was, so this gets to the framework, I guess. So I deeply understand people, like what are people trying to do with this? What they're trying to do is share a vulnerable thing and be like, hey, I'm lonely. Hey, what's going on? Like, are people up? And it feels very much, it's like a friend group thing. And if you only have two people on it, the job that we're doing is actually connecting you to your friends. And if you don't get a DM back, it's broken.

• 59:26Speaker 01

  And so really what we're doing is getting you a DM. And we're getting you connection. We're getting you a sense of being connected to your close friends. That is the job. It's actually, the other thing Clayton Christian talked about in the book is there are utility jobs and there are emotional jobs. People usually discount the emotional ones a lot. This was really an emotional thing as much as it was utility one. And so product's broken, right? And people don't even know that you can, it's a close friends story. They just see the little head because you have to click on it to see the thing. And so it just, people stopped using it. So we went through and we did these revs where we would like simplify it and we would update it. And we would go through this change list. Okay, take this out, take this out, change the name here. And then we saw it was that it was working really well for people who added 20 to 30 people to their list.

• 1:00:09Speaker 01

  Cause what would happen is you put 30 people on your list and then two of them would write back to you on DM. And now you have closed the loop and you feel connected to those people. It's a winning thing. And so we designed the whole system around that and also only worked in stories. So we were looking at the data. We were trying to understand where it was working and where it was failing. And then we we we updated the name to close friends. So it didn't feel like favorites. So it wasn't like three people. It's like 20. In the list, we made but we built this list builder where we recommended a set of people based on some data, some some cool algo that was created by an engineer. And then we and then we updated the design to put the green ring on the outside of the story. So that this was the kind of the design for clarity.

• 1:00:49Speaker 01

  It wasn't we were being cute like, oh, if you we thought, I think at the time it was like, oh, it's like a secret story or something. And if you open it, you see it. It just was not clear to people. And so we put the green ring on the outside so that users would see it in the tray and they're like, ooh, what's that little green guy? And then they'd click on it and be like, oh, this is like a private story for me. That system worked and did incredibly well. And and that was the process we followed from like a total flop to something that was very successful.

• 1:01:16Lenny Rachitsky?

  That is an awesome example. And this took two or three years, you said.

• 1:01:18Speaker 01

  Yeah, it took a while. That was actually one of the longest projects we worked on. But that actually came. The reason we did it was when we asked people to do to understand people. Like what? Why aren't you posting to your stories? Like, what's preventing you from doing it? And everyone had some version of, well, my ex is on it. I have a teacher on it. Oh, a friend that kind of is judgy is on it. It was like this this kind of like common commonality was audience problems. Someone had an issue with people watching them. And so that gave us conviction to go this hard at it for so long because we knew that that was a core problem with the product.

• 1:01:51Lenny Rachitsky?

  Was this connected to the Finsta Rinsta trend also?

• 1:01:55Speaker 01

  It was. Actually, I think that informed us. Like, everyone had a Finsta and there was a Binsta.

• 1:01:59Lenny Rachitsky?

  What is a Binsta?

• 1:02:00Speaker 01

  Best friend Binsta. So like different, it's like this layering of like people of like 20 Finsters down to like your partner. Pinsta. And then it's basically like, I made that up. I don't know if it's true, but I'm sure there's Pinsters out there somewhere. And and we were like, well, people clearly trying to hack Instagram, basically, to create these private, smaller group settings. And so we should just make a product.

• 1:02:23Lenny Rachitsky?

  How did you actually do this testing? Was it rolled out to some percentage? Was it rolled out like in New Zealand or whatever?

• 1:02:27Speaker 01

  Yeah, we rolled it out in a few other countries. Exactly.

• 1:02:29Lenny Rachitsky?

  Okay.

• 1:02:30Speaker 01

  We had like a basket of countries that we tried it in. And then we would do research. I think it was Australia was one of the first ones for that one.

• 1:02:36Lenny Rachitsky?

  Okay, I was gonna ask if you can share the countries. So Australia.

• 1:02:40Speaker 01

  I think that was one of the earlier ones. Yeah. But it's always, every time you ship something is a slightly different reason why.

• 1:02:46Lenny Rachitsky?

  Oh, interesting. So it's not always Australia gets all the new stuff?

• 1:02:49Speaker 01

  No. Although it sometimes is, Australia and Canada get a lot of stuff. Just because it's easier for the teams to like see feedback from them and.

• 1:02:58Lenny Rachitsky?

  Speak English.

• 1:02:59Speaker 01

  Yeah, exactly.

• 1:03:00Lenny Rachitsky?

  Awesome. Okay, let me go in a different direction and talk about something that you have a hot take on. There's a lot of talk these days about lean teams, small teams, just creating limited resources, not hiring at all. You kind of have an opposite perspective of you actually need a lot of resources to build really big breakthroughs. Talk about your experience there.

• 1:03:19Speaker 01

  Yeah, I mean, I think there's obviously, depends on what you're trying to build. And there's been famously small teams building big impact products. But I think there's kind of this

• 1:03:29Speaker 01

  cult of lean, scrappy, fast, throw away your product quickly, keep moving. And I think at some level, it's true for internal conviction. But to build a product that works for a lot of people that is based on a technological breakthrough. A lot of times I see teams just give up too early or under invest in the product. And obviously the space matters. And if you're building, you know, like a single product that is a way to, I don't know, do something with a digital app that's fairly straightforward, that's gonna be different than building a robotics company. Right? So what you're building does, does change. But even for software, I mean, I think for really hard technical problems, think about the amount of time and effort it took for teams to build a foundational model. And how many years and hundreds and hundreds of people that were needed for that to happen?

• 1:04:15Speaker 01

  And you think about these large.

• 1:04:19Speaker 01

  Companies that have had huge impacts on people. And I think particularly for bigger companies internally, something I've seen is it's almost like too scrappy because it never gets enough momentum. If the product never gets good enough internally. And then it kind of just dies on the vine. Whereas if you put more people on it, you have to be careful not to put too many too soon. But I see the opposite more true where people hold on to small teams too long. And then you kind of like, either it takes forever to get to the thing you're looking for, like this close friends example I mentioned. This actually was a small team. One of the reasons it took us forever was it kept the team so small and scrappy that like loop cycle was so short. And by a startup age, you'd be dead probably. So you can maybe do that in a bigger company, but as a startup, I don't know if you have that, you know, that leisure.

• 1:05:01Speaker 01

  And so I think you need to actually think, what is the group I need to build a version that's great? And from first principles, really think about it. Instead of just embracing blindly, okay, we're going to be the two of us until this thing has escape velocity and market fit, which it's not always true.

• 1:05:19Lenny Rachitsky?

  There's definitely counter to the narrative we see on Twitter. Anything you can share about just like the heuristic you use to decide here's when how long to keep it small. I know it's, you know, there's not going to be this step one, two, three, but just like, what I'm hearing is start small to prove out the concept designer, PM engineer, maybe. When do you find that makes sense to go big?

• 1:05:40Speaker 01

  Yeah, I think that it's mostly when you have, you've hit the conviction moment. Like, I think there's two, there's two big milestones. There's like internal conviction, like for yourself, do you believe in it? And you believe in it because there's some external validation, like your friends, you know, you put 20 friends on it. And by the way, I found out very quickly building startups that if you put 20 friends on something, they're not going to do you that many favors. Like they're not going to use a product every single day because they're your friend. Like 30 days in, 60 days in, 90 days in, they're not using your product unless you're doing something that's useful to them. And so you get like all this feedback and you're seeing people really enjoy it. You get to that moment. And then I think that's not a product that would win externally because if you were to ship it, it's like broken, doesn't work great.

• 1:06:22Speaker 01

  And then you need to, I think, invest enough to make the best version of it or as good a version as you can. To get it out the door and to ship it. And I think that that it's kind of like you want to build the right product eventually is the mentality. And you can only really do that with the right with the right group.

• 1:06:39Lenny Rachitsky?

  I'm going to take us to a recurring segment on the podcast that I call AI Corner.

• 1:06:43Speaker 01

  Okay.

• 1:06:44Lenny Rachitsky?

  What's some way that you've found a use for AI in your work, in your life? That is really interesting, really helpful, and maybe other people can be inspired by it.

• 1:06:53Speaker 01

  I think one of the coolest trends ever is how AI is affecting multimodal visual and inspirational needs for people. And it's we're early in this, and I think this is something that I'm actually working on as a project as well. But right now, if you think about what AI has done, you know, in large part, it was born and grew up in this text modality as chat. And so, you know, for a long time, if you were to ask it to help you, you know, what's what are what's a cool way to redecorate your bookshelf behind you? It's going to describe that to you in text because that's what it knows. But increasingly, AI is going to be liberated to help in every possible modality. And you know, this is something that we've seen a lot with this explosive use of Google Lens and our image search and image features. And with this deep understanding.

• 1:07:37Speaker 01

  And what I'm actually starting to use internally and some things that we're excited about more coming up that we actually announced at I O that we're going to be we're going to be building more of was how AI can help with inspiration, how AI can help with shopping and helping you really get things done that are more in the like inspiring bucket of needs versus these like core utilities like code, math, homework kind of side of things. And I'm really excited for, you know, things that are coming where you can ask it for inspirational tasks. And it's starting to do really fascinating things in terms of what I'm seeing. And hopefully we'll share more on that soon.

• 1:08:18Speaker 01

  But I think the one thing I can share is, you know, there's, there's a visual version of AI mode that basically we talked about for.

• 1:08:28Speaker 01

  At I O and so you can you can reference some of those those keynotes, but that that's in the process of being rolled out. And so you're going to be able to now ask like, you know, what's a what's a mid century, modern, beautiful office design with dark themes? It'll be able to produce this image board that's inspirational and you can do multi turn with it. And so you'll be able to go and say, actually, I want more of like a light theme, more creamy, more California, more coastal vibe. And it'll do that and it'll understand that and it'll actually see the images and be able to turn with you in the way that text works, which is going to be really cool. So I think that's going to be one of the more exciting things that that will be new to AI soon.

• 1:09:10Lenny Rachitsky?

  What I'm hearing is Nano Banana integrated into AI mode. Recipe for success.

• 1:09:14Speaker 01

  It's a little different than Nano Banana because Nano Banana is like an image editor. This is more like helping you find images on the web. So it's a little bit more like AI inspiration, AI image search, and allowing you to then talk with two effectively like visual responses with natural language. So that's going to, I think, be a little bit different than, you know, edit this photo so that it it changes it. Although potentially an interesting idea, too, to have an ability to like take a picture of your living room. And I think AI will help with that, too, ultimately.

• 1:09:48Lenny Rachitsky?

  Pinterest is in trouble. It feels like this is what people use Pinterest for. Here's all the inspiration. Now it's just AI doing it all. By the way, Nano Banana, where where does this name come from?

• 1:09:58Speaker 01

  I don't actually, I I forget that there's a story somewhere. I forget it now, honestly. But the team, I think, came from a scrappy, fun group of people building this and yeah, they they wanted to go for for something fun for folks.

• 1:10:13Lenny Rachitsky?

  Yeah, it feels like that's a part of the reason things have started to work. There's just like more fun and delight and random crazy stuff coming out, just like.

• 1:10:19Speaker 01

  It does feel like it feels a little more like when I was at Google the first time through right now, where you kind of just have so much stuff and then this kind of like fun curiosity happening where people want to try things and ship things. And yeah, hopefully that continues.

• 1:10:31Lenny Rachitsky?

  Yeah, feels like VO3 would be even more successful if it had a wacky name.

• 1:10:37Lenny Rachitsky?

  And I like that this is the opposite of your advice of clarity. Like, I don't know what Nano Banana is, but it worked.

• 1:10:42Speaker 01

  Yeah, that's the other thing. No, no advice is right universally, right? It's like, but yeah, Nano Banana.

• 1:10:49Lenny Rachitsky?

  Robbie, is there anything else that you wanted to share? Anything else you want to leave listeners with as a final nugget of wisdom before we get to a very exciting lightning round?

• 1:10:57Speaker 01

  This concept, be curious. Like, I think, I think of embodying everything as like, it's really about curiosity. It's about wanting to know why everything is the way it is. Why is someone doing something? Why does someone have a different opinion than I do? Why might this not be working? And the people who really have that level of intense curiosity and they chase things down until they know, I think you're well served by that. Those would be my only parting thought.

• 1:11:20Lenny Rachitsky?

  Let me follow that thread, actually, because it's maybe the most trending term on the podcast over the past few months is curiosity. It comes up a lot when I ask people, what are you teaching your kids? And then embracing with the rise of AI and curiosity comes up all the time. Is there anything that helps you? Is it just like, I am good at this and I'm curious innately and I'm just, and this is valuable? Is there anything you can share that helps you or others around you embody that and actually be curious?

• 1:11:48Speaker 01

  Well, I mean, AI is obviously like the ultimate curiosity engine. And that's what's so cool is you can now ask anything and just get information. And so I find that people just underappreciate just how much they can learn about whatever they want. But also I think that a lot of this also comes down to studying what you want to know about and knowing where the branches of knowledge live there. Like, a lot of times I'll read like old papers and PDFs that are free online on like a statistics thing if I want to learn about that. And I think people underappreciate those as like analog, old school, great learning. And AI can help you discover them. I'm using AI, I'm strictly at Google to help discover all these cool links and things to read.

• 1:12:27Speaker 01

  But I find that that is an interesting hybrid where it's not just AI, but really going to original sources more. And I find that like these books I mentioned on the chat here. I find that you need a blend of all of those things to ultimately really get to the bottom of things ultimately.

• 1:12:45Lenny Rachitsky?

  Like actually reading the thing, not just reading the summary of the thing.

• 1:12:48Speaker 01

  Yes, yes.

• 1:12:49Lenny Rachitsky?

  Let me actually ask you this question. I've been asking all these people that are at the cutting edge of AI. You have kids. Is there anything you're thinking about and leaning into helping them learn, develop as AI emerges and becomes a big part of the world?

• 1:13:04Speaker 01

  The biggest thing I'm doing, I have younger kids. So the biggest thing I'm doing is they're using live versions of AI that they just talk to now much more. And so, you know, funny enough, we actually just launched Search Live actually out of labs this week. And so you can talk to search in a live AI setting with its conversational voice, voice on. When you're driving, you can just talk all the knowledge I talked about, what you can do with Google. You can talk to it in a normal conversation with your voice. And I found that to be incredibly accessible for kids. And I hear all my kids come home and like, can I talk to Google about something? Like, what do you need? What do you need to say? And then they go to my app, they hit the live button and they just start talking to it. They want to know about animals. They want to know about, you know, certain history things.

• 1:13:46Speaker 01

  They learn about something in school and it's so natural to learn in that way. That I think that that's helping them become much more AI native than any other thing I'm doing.

• 1:13:56Lenny Rachitsky?

  Life as a parent is going to be way too easy now. Whenever kids have questions, just go talk to the AI. But I don't think that's bad. So this is within the Google search app. There's a live. How do you access this?

• 1:14:07Speaker 01

  Yeah, that's exactly right. You go to Google app. So there's one of the apps in the app store you mentioned. You open Google and there's a button now that's live on it, right on the home screen. And if you tap on it, it's a live version of AI mode that you can just talk to. It's a full screen experience and we'll say like, start talking.

• 1:14:22Lenny Rachitsky?

  In the show notes, I'm going to link to this project that somebody built, Eric Antinow, which I love. It's, it basically shows you how to put a little speaker into a little stuffed animal. And you connect the speaker to, it could be Google Live or it could be ChatGPT, whatever you like in voice mode. And you put it on your shoulder, you get a little magnet that attaches. And your kids could talk to this parrot, for example, and you could tell it talking a pirate voice. And so they're talking.

• 1:14:49Speaker 01

  Oh, that's really funny. Okay, that's really cute.

• 1:14:51Lenny Rachitsky?

  It takes like 15 minutes. You could like get an exacto knife and sew it and stuff. And it's kind of fun. I made one for my nephew. And he was looking for treasure with this parrot.

• 1:14:59Speaker 01

  That's really adorable. I'm definitely going to look into that.

• 1:15:01Lenny Rachitsky?

  Robbie, with that, we've reached our very exciting, lightning round. I've got five questions for you. Are you ready?

• 1:15:06Speaker 01

  All right, I'm ready.

• 1:15:08Lenny Rachitsky?

  What are two or three books that you find yourself recommending most to other people?

• 1:15:11Speaker 01

  I mean, definitely the two I mentioned, you know, here, Clayton Christensen, Competing Against Luck, Don Norman, Design of Everyday Things. But I also really love this for fiction, Aurora, which is this book David Koch wrote. It's about, it's like electromagnetic pulse in the sun that like knocks out. It's like fiction for just fun. And it was like a really fun beach read. And apparently it was going to be made into a Netflix show. It didn't work out. I don't know. I was sad to see that fall apart. But it's a really fun book.

• 1:15:39Lenny Rachitsky?

  There's a book along those lines that I love. They're making a movie of it right now called Hail Mary?

• 1:15:43Speaker 01

  Oh, I'm in the middle of reading that right now.

• 1:15:44Lenny Rachitsky?

  Okay.

• 1:15:45Speaker 01

  Yes.

• 1:15:46Lenny Rachitsky?

  The same mind. Yeah, they're making a movie of it. How about that?

• 1:15:50Speaker 01

  In the middle of reading it. It's getting wacky where I am right now, but I'm excited to see where it goes.

• 1:15:54Lenny Rachitsky?

  It gets wackier. The ending is extra wacky.

• 1:15:55Speaker 01

  Oh, really?

• 1:15:56Lenny Rachitsky?

  Okay. Prepare yourself.

• 1:15:57Speaker 01

  Okay.

• 1:15:59Lenny Rachitsky?

  What is a recent movie or TV show you've really enjoyed?

• 1:16:02Speaker 01

  I love The Bear. I think that's just absolutely awesome show. Dune, of course. And I thought the new Top Gun is a little old now, but I think the new Top Gun was so fun and awesome.

• 1:16:13Lenny Rachitsky?

  Is there a product you've recently discovered that you really love? It cannot be AI mode?

• 1:16:17Speaker 01

  I'm gonna use a non-digital product.

• 1:16:19Lenny Rachitsky?

  Perfect.

• 1:16:20Speaker 01

  I'm super into this new pillow that I got called Purple Pillow. And I've been recommending it to everyone, like at work, we're on like a pillow chat now. It's like a thing. It's like, you talk about like what pillows we're getting. But it's this really cool thing where it's got this like new technology of like this honeycomb polymer that's inside. And so it like supports you and it has these little micro holes so it doesn't get hot. It's really cool. Big fan. Strongly recommend Purple Pillow.

• 1:16:50Lenny Rachitsky?

  I've never heard of this thing. I am excited. I recently got an avocado pillow focusing on low toxins. So.

• 1:16:57Speaker 01

  Oh, those are good. I've heard good things about those, too.

• 1:16:59Lenny Rachitsky?

  Yeah, okay. I gotta drain this pillow. Pillow Talk is a great name for it, by the way.

• 1:17:03Speaker 01

  I didn't know you're into pillows, too. That's great. I love bedding. Yeah, great.

• 1:17:08Lenny Rachitsky?

  But I did upgrade my pillow. It's this is not Mr. Pillow, or whatever that guy is, right? The uh, is that guy that like, is there's like a

• 1:17:15Speaker 01

  No, no.

• 1:17:16Lenny Rachitsky?

  pillow guy, okay.

• 1:17:17Speaker 01

  No.

• 1:17:17Lenny Rachitsky?

  Okay, purple pillow, I'm gonna ask you eye mode.

• 1:17:19Speaker 01

  Yeah, you should.

• 1:17:22Lenny Rachitsky?

  Next question. Do you have a favorite life motto that you find yourself coming back to in work or in life?

• 1:17:28Speaker 01

  I guess it's be curious. I think I almost named a company Curious. I just think it's a really awesome.

• 1:17:34Speaker 01

  There's one thing in life, it's that in terms of getting things done, in terms of understanding the world, people, your kids, your family. Like, you always just wanna know more and question things outside yourself, not feel like you have all the answers. I think it's really important.

• 1:17:49Lenny Rachitsky?

  I love that. Final question, okay. So, speaking of startups, you started a company called Stamp, Stamped back in the day. It got acquired by Yahoo. Uh, I hear there's a story where you got Justin Bieber on your app and that was a big deal and a big inflection in in the success of the app. Can you just tell that story?

• 1:18:06Speaker 01

  Yeah, it's kind of a wild story. So I was just a like scene set a little bit. I was 25, right after Google, being an ICPM in New York with some Google friends building this company. So, um, very early on and maybe in a good way, had no idea what I was doing. But, um, basically, we decided that the the concept of stamp was to put your stamp on your favorite things, get recommendations from friends and from people that you trust. And so you think of like a Twitter feed, but it's all stuff that people think is cool. It's like books, restaurants, food, products.

• 1:18:36Lenny Rachitsky?

  Pillows, possibly.

• 1:18:37Speaker 01

  Pillows could be on there. I would totally stamp this pillow and then you could discover it. And, you know, one of the cold start problems was obviously like you want a group of people that are on it, that are already using it, that could have some like tastemaker type folks. And so we had a bunch of people that were like chefs and we had, you know, people who were like kind of literary folks. And then we wanted to get a couple of people that were more musicians, artists and these kind of influential folks. And so my co-founder and I just basically got the contact of, um, Scooter Braun, who's Justin's manager. And we just sent him an email and we're like, hey, we're gonna, we were in New York, like, we're gonna be in LA tomorrow. I think we said something, I don't remember the all the details, but it was something like tomorrow.

• 1:19:14Lenny Rachitsky?

  And you were not gonna be in LA tomorrow?

• 1:19:16Speaker 01

  No, no.

• 1:19:16Lenny Rachitsky?

  Okay.

• 1:19:17Speaker 01

  Do you happen to be there? And he he just like wrote back some one line thing, like, meet me at this hotel, like, for breakfast at something. And we're like. Okay, so we literally went immediately to the airport. I just remember like just basically going straight to the airport, flying to LA, meeting with him. We gave him the whole pitch. We showed him the product and then he was like, okay, I think this would be super cool. We can help be involved and maybe you can help be an advisor. And we ended up going back and meeting with Justin and showing him the product and even filming some little clips with him. It was actually really funny and it was a really fun moment. And he obviously like he would, he was using it to stamp his favorite stuff. And so people were like, oh, Justin's

• 1:19:59Speaker 01

  into this song or he's into this stuff and would post that. And it was one of the ways that we got lots of people to try out and see what we were doing. So that's a little extra scrappy moment in time, but I think it embodies a good lesson, just like do it now, be scrappy, be immediate, like intense urgency usually wins over thinking about it for a long time. And that certainly proved to be true on that one.

• 1:20:20Lenny Rachitsky?

  Incredible story. Thank you for sharing that. So many lessons to take away. Two final questions. Where can folks find you online if they want to reach out, maybe learn more about what you're doing? And how can listeners be useful to you?

• 1:20:31Speaker 01

  Yeah, I think on X at RM Stein is probably the best single place. And then to be helpful, send me feedback, DM me, just mention me, ping me, let me know problems with Google products, with AI in general, but also just anything. As I said before, you have to always listen to people, understand their experiences. So ping me ideas and feedback. That's the best way to be helpful.

• 1:20:52Lenny Rachitsky?

  Wow. What an onslaught you're about to receive of feedback on the search experience.

• 1:20:57Speaker 01

  Yes, please do.

• 1:20:58Lenny Rachitsky?

  Robbie, Robbie, why is this link second? Why is my site not at the top? I can only imagine the kind of stuff people complain about. Robbie, thank you so much for being here.

• 1:21:08Speaker 01

  Thank you. It was great.

• 1:21:09Lenny Rachitsky?

  It was great. Bye, everyone.

• 1:21:11Speaker 01

  Take care.

• 1:21:12Lenny Rachitsky?

  Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at lennyspodcast.com. See you in the next episode.