Skip to content
Lenny's PodcastLenny's Podcast

Robby Stein: Why AI is expansionary, not replacing search

How Stein imported the Stories, Reels, and Close Friends instinct into Google: AI Mode and AI Overviews multiply user questions, not cannibalize search.

Lenny RachitskyhostRobby Steinguest
Oct 10, 20251h 21mWatch on YouTube ↗

EVERY SPOKEN WORD

  1. 0:00 – 4:46

    Introduction to Robby Stein

    1. LR

      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.

    2. RS

      Google's mission around have any information be universally accessible, that'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.

    3. LR

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

    4. RS

      The core Google 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 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.

    5. LR

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

    6. RS

      You need to be the physical manifestation of two pieces of things. One is just 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.

    7. LR

      You built and launched Stories at Instagram. 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."

    8. RS

      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 just robbing your user base of the opportunity to have a better product.

    9. LR

      Today my guest is Robbie 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 grew 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, 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, ChatPRD, and Mobben. Head on over to LennysNewsletter.com and click Product Pass. With that, I bring you Robbie Stein. My podcast guests and I love talking about craft and taste and agency and product market fit. You know what we don't love talking about? SOC 2. That's where Vanta comes in. Vanta helps companies of all sizes get compliant fast and stay that way with industry leading AI, automation, and continuous monitoring. Whether you're a startup tackling your first SOC 2 or ISO 27001, or an enterprise managing vendor risk, Vanta's Trust Management Platform makes it quicker, easier and more scalable. Vanta also helps you complete security questionnaires up to five times faster so that you can win bigger deals sooner. The result? According to a recent IDC study, Vanta customers slashed over $500,000 a year and are three times more productive. 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, and helps you build a roadmap that drives alignment, not questions. 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/lenny. That's atlassian.com/lenny.

  2. 4:46 – 6:08

    Google’s recent success with AI

    1. LR

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

    2. RS

      Thanks so much for having me.

    3. LR

      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. Uh, 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 consumer-wise yet?

    4. NA

      (chuckles)

    5. LR

      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.

    6. RS

      Many, many more people, yes.

    7. LR

      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 Nano Banana the, the... a source of a lot of this recent growth? Or is there something else going on?

    8. RS

      I think people are really excited about-

    9. LR

      Okay.

    10. RS

      ... Nano Banana, to be clear.

    11. LR

      Yeah.

    12. RS

      Very much so. Um, but I think also people are recognizing that, you know, there's just so many cool things that you can do, um, across the Google set of products.

    13. LR

      Mm-hmm.

    14. RS

      And, and they become quite p- powerful. And so I, I'm always shocked even for, you know, things in Search. People... like we think they're very obvious 'cause 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-... um, right, how powerful these tools are now.

  3. 6:08 – 9:41

    The evolution of Google Search

    1. RS

    2. LR

      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 then it's just like, "Where has Google been? And actually w- 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 years that have led to this moment where Gemini is now the top app in the world?

    3. RS

      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, for 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. Um, I think the people who are... You know, we work very closely with our partners at DeepMind, you know, at- at Google DeepMind. We work very closely obviously across th- 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 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 any, like, one thing that has happened. I think that a lot of times people ascribe, you know, a lot of momentum to, to, 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 e- 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 I... 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, it just hit a moment where, you know, people are seeing the effects of that now.

    4. LR

      As ChatGPT emerged over the past couple 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 a- at 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 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?

    5. RS

      Yeah. Well, what's interesting is people come to search for just a ridiculously wide set of things, like all kinds of things. They want a specific phone number. They want a price for something. They wanna get directions. They want to find a, you know, payment web page for their taxes, like every possible thing you can imagine. I think the vastness of that is underappreciated by many people, and what we see is that, that doesn't... It's not changing. Like, AI hasn't really changed those, those foundational needs in many ways. I think 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, like, the core Google Search isn't really changing, in my opinion. We're not seeing that, but you're getting this expansion moment, 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%, um, 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 and say, "Where can I buy this?" or take a picture of your homework and say, "I am stuck on question two." And then just take a picture of your bookshelf and say, "What other books I should get based on these books?" And AI an- can help you with those things now. So it's just an example of, uh, I think why there's so much growth left, a- and, you know, why we're so excited.

  4. 9:41 – 15:30

    AI Mode and its impact

    1. RS

    2. LR

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

    3. RS

      No.

    4. LR

      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 at google.com/ai. Is that-

    5. RS

      Yep.

    6. LR

      ... is that the right URL?

    7. RS

      Yep.

    8. LR

      Okay, cool.

    9. RS

      Yep.

    10. LR

      So I've been playing with it, uh, as we were prepping for this conversation. It's really incredible. I asked it, uh, "What is the best newsletter on product and growth?" And, uh, it's very smart.

    11. RS

      (laughs)

    12. LR

      It said, "Lenny's newsletter." So an- that's my eval, how well this thing does. (laughs)

    13. RS

      Fantastic. Okay, one of one, perfect eval.

    14. LR

      (laughs) Perfect. Uh, 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, uh, 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.

    15. RS

      I can tell you, there's, 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. You know, one is obviously AI overviews, which are the, the quick and fast AI you get at the top of the page many people have seen, um, and that's obviously been a... something growing very, very quickly. This is when you ask a natural question, you just put it into Google, you get this AI now that's really helpful for people. The second is around multimodal, so 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, uh, search experience on state-of-the-art models to really truly let you ask anything of Google Search. Um, 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? 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 instance. They're updated two billion times an hour by merchants with live prices, right? You have 250 million places in Maps. You have all of the, you know, finance information. I mean, just the w... 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, um, into this brain, um, that is effectively this way to talk to Google and get at this knowledge, a- and that's really what, what you can do now. And so you can ask anything, um, on your mind, and it'll use all of this information to hopefully give you super high quality a- and informed information, um, as best as we can. And, 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.

    16. LR

      Mm-hmm.

    17. RS

      Same for the, uh, Lens stuff. You take a picture, it takes you to AI mode, so you can have this back. You can ask follow-up questions and go there too. Um, so it's increasingly i- integrated experience into the core part of the product.

    18. LR

      I imagine much of this is tr- 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 overviews at the top, and then this min- multimodal experience, or is there a vision of somehow pushing these together even more over time?

    19. RS

      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, I think of them as very complementary 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, um, 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. Um, and then it should trigger AI at the top, it's a preview, and then you can go deeper into AI mode and have this back and forth. So that's how these things connect. Same for your, your camera. So if you take a picture of something, say, "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. So you shouldn't have to, like, think about that. It should feel like a consistent, simple product experience ultimately. Um, 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, with s- with something like a direct, uh, entry point like google.com/ai.

    20. LR

      I recently had, uh, Brian Balfour on the podcast and he shared this quote that's really stuck with me that (laughs) I think about as you talk about all this. Uh, 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, ma- now here comes Google." I don't know if I have a question here, but it just feels like this is, uh... (laughs) there's been all this time for people to find distribution and now it's like, "Okay, now it- Google is coming."

    21. RS

      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. Um, and so now that you have this really sophisticated AI that's based on our frontier models, we can just handle increasingly l- more and more stuff for people. Um, and so hopefully that's, like, a more natural on-ramp here. And then we just need to make it easy enough for people to use 'cause these are new products and people are used to using Google in a specific way. They type in keywords, which is what we call it sometimes keywordese, but you can actually use natural language in Google. That's the biggest shift we're seeing, people asking real long, hard, complex questions 'cause you just don't think, "Oh, I can go to Google and type in, like, 'What's a great place for a date night? I've 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, and I think that's the kind of thing that we're excited to, to continue to, to make easy for people.

    22. LR

      It's interesting that we've come around to... back in the day, there was Ask Jeeves, which was this whole...

    23. RS

      (laughs)

    24. LR

      ... just ask a question as if you were asking a human-

    25. RS

      Yeah.

    26. LR

      ... 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.

    27. RS

      Yeah, Ask Jeeves was surprisingly prescient on that, huh?

    28. LR

      (laughs)

    29. RS

      It's like, they, like, had-

    30. LR

      Too early.

  5. 15:30 – 18:50

    The rise of AEO

    1. LR

      man. What's your take on, uh, this whole, uh, rise of AEO, GEO, which is kind of this evolution of SEO? I'm guessing your answer's gonna 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?

    2. RS

      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, um, it's actually trying to... it does something called query fan-out 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 a- and append all of these other queries, like, maybe dozens of queries and start, start searching basically in the background and, and it'll 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 web page is designed to be extremely helpful and y- you can look up, you know, Google's, um, human r- uh, rater guidelines and read, you know, it's a very long document that's r- been thoughtfully crafted for decades now around, you know, what makes great information. You know, this is something Google has studied more than anyone and it's like, do you satisfy the user intent on what they're trying to get? Do you have sources? Do you cite your information? Um, 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, uh, because it's gonna 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. I think the only other thing I would give advice to would be, you know, think about what people are using AI for. I mentioned this is 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 kinda content is someone using AI for and then how could my content be the best for that given set of needs now?" A- a- and I think that's a, that's g- a s- a really tangible way of thinking about it.

    3. LR

      It's interesting your point about how it goes and searches. When you use it, it's like searching a thousand pages or something like that. Uh, 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?

    4. RS

      Yeah, this is something that we've done uniquely for our AI.

    5. LR

      Mm-hmm.

    6. RS

      Um, it obviously has the ability to use parametric memory and, 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? It's what Google's all about. Um, 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 wanna...... probably use in a response, all the way to, "Wow, this is, like, the most authoritative, helpful piece of information. We're gonna link to it, and we're gonna explain, 'Hey, according to this website, you know, check out that information," and you're gonna go, you know, probably go see that yourself. So, that's how we've thought about designing

  6. 18:50 – 21:31

    Building successful AI products

    1. RS

      this.

    2. LR

      You've worked on a lot of AI products at this point. Uh, it wasn't, it's not just Google. 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?

    3. RS

      I think the, the most recent one, and this is true, like, 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 incantations, you had to prompt in a really specific way. Like, people would have all these hacks, like, "Hey, act like you're an, you know, you're a coach and you do these things," and you have to really push it. Or, to use a tool, um, 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. 'Cause it just, you'd, 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 da-" 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, 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, 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 wr- 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," or, "I'm gonna use tools or code to, code use, code execution, um, in order to connect to this API I'm, 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, to get the most sophisticated outcomes, increasingly, I don't think you need to do a lot of this heavy-duty fine-tuning.

    4. LR

      It makes me think about, I had this recent guest, Nesrine Chengel, on the podcast. She was a PM at Google. She worked on 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, 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.

    5. RS

      Exactly.

    6. LR

      Might be obvious, but (laughs) it's good to think about that.

  7. 21:31 – 30:10

    Embodying relentless improvement

    1. LR

    2. RS

      Yeah.

    3. LR

      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, I've shared in the intro at this point.

    4. RS

      Many, many n- Um, also on the other side of the spectrum. We got the whole portfolio.

    5. LR

      Okay, (laughs) 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 you used this phrase, "Embodying relentless improvement." Can you just talk about that? What does that mean? Why is this so important?

    6. RS

      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 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. And I think this actually came out of a story, a little bit of a funny story where, um, I was at Instagram at the time doing a big, um, you know, all-team meeting, one of my first, and they had this icebreaker. It was like, "What's one word to describe yourself?" And so, in the backstage area, I, like, texted my wife really quick. I was like, "Hey, just one word to describe me, first thing that comes to your mind." And she just wrote back, "Dissatisfied." And I was kinda chuckling in the, in the back room, 'cause I was first of all, like, kind of offended, 'cause I was like, "It's not, like, loving, caring, like, like something good." And then she, and then I saw, like, her little bubble thing. Like, 'cause 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, um, 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 wanna 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, now billions of people use them, where it felt like one of the big differences, um, 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 gonna 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 to this tipping point where it just kinda tips over into being net useful to people, 'cause of just that amount of compounding effort that you put into something. 'Cause 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, and there's this other, other incredible story that Tony Fedele told, um, at, at, on a TED Talk, like 10 years ago. Um, you can look it up. Um, I think it's something around Think Younger, uh, um, as a title, and he talks about what it means that, that as we grow up and age and become grown-ups, uh, I have two little kids, so it, 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 kinda sucks. Oh, well," and 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, like, like tolerating this, and how do I make it better?" And 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, and it's got that sticker. And w- who put that sticker there? And then how you, 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, and he goes into just incredible detail about how it punctures the flesh of the, of the fruit. It, 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, that's how they think, um, in my opinion.

    7. LR

      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, uh, in action, of this actually working really well and delivering something really huge?

    8. RS

      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.

    9. LR

      Mm-hmm.

    10. RS

      Or AI overviews just didn't show up. And so, you know, a bunch of us sat around and 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, 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 just be like, this is ridiculous. We need to build something, uh, here. And, um, that was a big motiv- that was one of the big motivations, was actually identifying that, like, user problem, being very disgruntled on behalf of the user. Like, I am, we're just failing the user every day. We are not helping them actually get their thing, uh, like, kind of better understood, and we're gonna go build a whole thing because of it. Um, 'cause 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.

    11. LR

      There's kind of two buckets of people, let's say, uh, 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 th- 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 combined?

    12. RS

      Yeah, I don't think of them as an or. Like, I think they have to be th- uh, like, intersected, because basically the way to think ab- the way I think about it is, you actually start with, you know, a problem or a b- the inverse of that, which is a vision. Um, 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 a, 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, so it comes out of this dissatisfaction and this, this sense of better, that you need to make things better, but then you're gonna 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. Do people like it? It's like... And then each product goes through its journey. So the way that you better understand if people like it is you, you scrutinize typically, um, you talk to people, um, but you also add some analytical tools there, and 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 30, day 90, and does it flatten or do people just drip out of there? Like, over time it's, it's just not insa- exciting people, and that would go to zero. If on a long enough timeline no one's gonna use it. You don't get past that, you're toast, right? Then okay, some people are doing it. Okay, great. Um, 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? 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 gotta go through that journey. No product has started big. Even ones that get big really quickly, even af- even, like, a week quickly, they had something and th- even internally, they started small. They started small with 100, 200 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, our core metric's down 5% this week. It's like, well, what's going on? Right? And so you, you need to be really close to root cause analysis there and say, "Well, actually it 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? Where does my problem lie? And then when you get to it, you understand the problem, and then you can... This improvement thing comes back where it's like, okay, I'm gonna make that, I'm gonna fix that thing. I'm gonna, what's the treatment for that, that disease? Um, and you get, and then you're back to growth again. And so you kinda need this and you always are looking at what's the s- what's the system that I'm working on and what, 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. Um, it can just show you a little bit of the way.

    13. LR

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

    14. RS

      (laughs)

    15. LR

      (laughs)

  8. 30:10 – 35:20

    Lessons from Instagram Stories

    1. LR

      I wanna go on a quick tangent. Speaking of products that have done really well and become really big, uh, Stories. You built and launched Stories at Instagram. It's, uh, quite an infamous product launch back in the day. It was quite controversial because, uh, 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 is so far in the past, uh, I'm so curious just to hear about that time, uh, 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.

    2. RS

      I think there's a couple of really important lessons from that launch. Um, and I mean, we went on afterwards to launch Reels, um, a bunch of updates to direct messaging. We had feed ranking. I mean, there was just a huge era there when I was there between, you know, 2016 and 2021 or so, where just so many new 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. 'Cause not every great thing is gonna be invented by you. But I think that a lot of these things are, you know, they're rela- 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 sharing your life and connecting with people, ultimately. And if there's a way to do that that, you know, lowers the pressure because it doesn't have likes, or it's this ephemeral format, and it's optimized well for, for mobile, because it's this full screen experience. Like, it's, it's a really great format, and kudos to Snapchat for inventing it. You know, we didn't think of that as a, a, like a deterrent, that we had to go make, like, you know, Instagram photo clock. That... 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. Uh, and so we knew we needed to do something, um, new. And then it, it was so clearly was critical to the core essence of what the product could do, it could fit in naturally. But the question was, how do we make it our own? And h- 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. Um, 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. 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 'cause they want to save it, and they want it to be in a very high quality, high resolution photo 'cause 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 cam- their photo? Like, w- like, why... Like, this is the dis- back to the dissatisfied point. Like, that's frustrating. You know, or there's another example where you couldn't pause, um, if you, like, were consuming a story. You couldn't pause it. It just would, like, go through and be done, 'cause it was like this ephemeral thing, and you wanted to create safety. It's like, why can't you just pa- 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 now. And so there were a whole set of those things that were shipped that made Stories feel Instagram. It wasn't like you just had some other thing. And then it turns out that worked incredibly well. And so, so much to the, to the fact that someone on the team mentioned that they always felt like, uh, 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 an, I think an important lesson.

    3. LR

      Instagram definitely got a lot of hate for that moment, esp- for a lot of, from a lot of founders, who were 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?

    4. RS

      I mean, I think it's more that we're focused on our, our peop- our users, and the, 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. You know, at the end of the day, that is a format that people adopt, in the same way that if you 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? I mean, there's a LinkedIn feed, and there's a, there's a feed for, um, DoorDash. (laughs)

    5. LR

      (laughs)

    6. RS

      You know, it's, it's not like... Like, it, 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 if you're not making the best possible product for your use cases. And for Instagram, it was used differently. Like, people use Instagram differently than they use other products. Um, 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, um, which is, which was fascinating.

  9. 35:20 – 40:08

    Driving growth in established products

    1. RS

    2. LR

      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, and improvement. Google, it's, it's happening. We're in the middle of the improvement and growth you're, you're driving. Uh, not a lot of people get to do this, where they go into an existing product and 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.

    3. RS

      There's a couple lessons here. And I, I think, by the way, the first lesson is to be humble, always, because it's extremely incredible to be able to work on products that have such impact on people. And I, I've, I view product like golf. Like, you're always one stroke away from shanking. (laughs)

    4. LR

      (laughs)

    5. RS

      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, 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, um, and where are the areas of growth? And so usually, even in a, in a big product or a mature and 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, that's declining or, or isn't growing as much. You know, uh, certainly in Instagram, there's been a big shift over the years of sharing into p- 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 c- 'cause the...... e- 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, I'm a big fan of. And, and, you know, Clayton Christensen's book on Competing Against Luck, um, 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, what are they doing with it, um, and what are they trying to get done with it? And that usually leads you to kind of bigger next stage ideas, and it, it, it obso- it, it removes this belief that you need to solve the problem with the current tools. So in the Instagram ex- uh, 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. Um, 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, if 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, could be a new for- i- in many ways, the AI version of Google and Stories and Reels, they, 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 complementary, having it be a core part of the experience, but clearly defined as a distinctive thing that has its own attributes associated with it, 'cause people think spatially. So if you have a feed and then 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 or you can't like it or ho- it operates differently than the other parts of your feed, it's gonna be super confusing for people. It sucks. Um, 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 wanna snap in something that's working. You have to make it work for your users, your expectations, and, um, what people are trying to do with your product. 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 or their, the consumer expectation of their product, it's th- totally different set of expectations. So you have to kind of respect that a- and say, "What can we learn from that and bring it here?" So that was, I guess, if you were to talk about the kind of the method that I've seen now twice, I guess, that's kind of how these, these products have developed.

  10. 40:08 – 43:39

    Balancing optimization and innovation

    1. RS

    2. LR

      I l- 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 s- 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 in how you structure teams and prioritize across, okay, we have all amazing Google Search experience today, what percentage of resources go into improving that versus trying something totally new?

    3. RS

      That's one where I actually do feel like the s- the more analytical, sys- like, systematic thinking helps a lot, because you kind of... You're trying to produce, um, value in the world. You're try... You wanna quantify it some way. And so if you're seeing this growth curve and you're trying to understand, well, people are using it more and more, they're liking 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 growing 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, and i- it's just not gonna 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? 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 principled 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 get th- 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 p- and to make it better for people, and you can see that in the data. And, and so it does become... Again, we talked about this instrumentation. It becomes your, but your guide for, 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 i- more quantitatively, it's really hard to know if the thing you're doing is, is mattering to anyone, 'cause you'll just... I made... think I made the product better, but, like, is anyone using it? Does anyone care or are we just congratulating ourselves? Like, ultimately you wanna have impact on people and that's what matters.

    4. LR

      So this is essentially tracking S-curves on every product and-

    5. RS

      Yeah.

    6. LR

      ... understanding if you're in a plateau and if it's time to invest heavily somewhere else.

    7. RS

      Yes.

    8. LR

      This episode is brought to you by Orkes, the company behind open source Conductor, the orchestration platform powering modern enterprise apps and agentic workflows. Legacy automation tools can't keep pace. Siloed low code platforms, outdated process management, and disconnected API tooling fall short in today's event-driven, AI-powered agentic landscape. Orkes changes this. With Orkes Conductor, you gain an agentic orchestration layer that seamlessly connects humans, AI agents, APIs, microservices and data pipelines in real time at enterprise scale. Visual and code-first development, built-in compliance, observability, and rock-solid reliability ensure workflows evolve dynamically with your needs. It's not just about automating tasks, it's orchestrating autonomous agents and complex workflows to deliver smarter outcomes faster. Whether modernizing legacy systems or scaling next-gen AI-driven apps, Orkes accelerates your journey from idea to production. Learn more and start building at orkes.io/lenny. That's O-R-K-E-S.I-O/Lenny.

  11. 43:39 – 48:05

    The journey of AI Mode: From launch to expansion

    1. LR

      Maybe it would be helpful to talk about the journey of AI mode, just like-

    2. RS

      Mm-hmm.

    3. LR

      ... 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?

    4. RS

      I mean, I think it, 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, 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 kinda 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. And so that led us to have, uh, form a small team, uh, of folks, a few people that were like technical leaders, um, a couple designers, very small, to just prove out, like what if there was on the m- almost like blank screen, like delete, uh, 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 for every one of it, you can tap right into the AI that, you know, was originally powering, powering, um, you know, this top of the experience in search, but we invested in making it, uh, much more, uh, more powerful in the ways I described before. It was in, it, 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. 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 5 to 10 people worth of people originally.

    5. LR

      And how long ago was this team formed?

    6. RS

      This was probably over the last, last year. Like last summer-

    7. LR

      Oh, wow.

    8. RS

      ... basically into the fall-

    9. LR

      Oh, wow, so about a year ago.

    10. RS

      ... into the fall. Yeah, maybe about a year ago was where maybe it's, it, it started. And, and we were really kind of plugging away on it, and then we, we kinda 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 kinda 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, like, 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 si- it had links to like go to the site and confirm a bunch of things. Um, it had Google Maps information that, like, for my daughter you could, you know, walk up. It had like, it was walkable. 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 sh- we should go and, 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 as like a little working team that, that initia- you gotta, you gotta 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, we basically built it out and, and built the first version that w- that launched in labs basically.

    11. LR

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

    12. RS

      Yes, it's, it's working. And then we did bring it before labs actually to a trusted tester group, there were maybe like 500 people externally that we added onto it, and we had pings with them. Some of them were fr- they actually had friends and family and we tried to treat it a little more like a startup, where, 'cause we want, we feel like you gotta have people test it that tell you the truth and tell you when it sucks, 'cause it probably does, and then they message you. So like I had a friend who was loving it, um, 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 kinda 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 more scale, and so that could tune it to make it better, and then we launched at I/O to everyone, um, or at least in the US, and then we've now been on this journey to expand it to all countries and languages and, um, have more people be able to access

  12. 48:05 – 49:51

    Organizational changes and urgency

    1. RS

      it.

    2. LR

      It's incredible that Google went roughly in a year from idea to, uh, 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. Uh, what, 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, is there something more?

    3. RS

      No, I mean, I think it's interesting how, how organizations change. I think, I think when you feel like there is an, 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. Um, and obviously, there's lots of people building lots of things, and, and the market's crazy, and there's lots of things shipping all the time. And so, there's a, 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, 'cause I think people believe, and I certainly believe, that the next year or so of product is gonna kind of establish how people use the next wave of products for, 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. So that's, that's, that's driving a lot of the, the excitement.

    4. LR

      Yeah. It's such a good point, that, uh, 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, uh, worried that, "Oh, shit, everyone's changing their habit from searching Google to searching ChatGPT," and the fact that now Gemini is number one.

  13. 49:51 – 51:35

    AI Mode vs. competitors

    1. LR

      I was actually looking at the list of top... So in the top 15 apps, Google is, I think, five of them. (laughs) A third. Uh, it's out of control. (laughs) Killing it. When people look at AI Mode versus a ChatGPT or Claude, or Per- 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?

    2. RS

      Yeah, I mean, AI Mode's a way to ask Search anything you want. It's for in- 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, um, a trip. You're trying to buy something. You're working through a question for, uh, your research project. Like, it needs information. And, and 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, um, core AI product. Like, you can ask it to rewrite something for you. It'll do that. But we are less focused on, you know, creativity, productivity, like upload a spreadsheet and, like, output graphs for me. Like, we're not focused on that. 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, um, and, and context and links to then also verify, dig in, and go to the, to the authoritative sources ultimately that people want and, 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. Maybe you would talk to it. Like, you maybe even have, like, a bit of, like a, "Hey, how are you doing today" with that chatbot. That, you know, we, 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, uh, and we, we've focused our product on that.

    3. LR

      Got it. Okay. AI Mode is not your therapist.

    4. RS

      (laughs)

  14. 51:35 – 57:07

    Core product principles

    1. RS

    2. LR

      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 s- helped you build such amazing and successful products, what would those be? What comes to mind?

    3. RS

      I mean, there's, there's typically three things I think about.

    4. LR

      Mm-hmm.

    5. RS

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

    6. LR

      I love that. I love the how short that would be. I think that's the ideal book.

    7. RS

      The, the first... I mean, I thought abou- I thou- I've thought about these three areas now for a while, and it's like-

    8. LR

      Mm-hmm.

    9. RS

      ... they're, 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, you know, Clayton Christensen's book I, which, which I loved, around competing against luck. It really helps you un- be a student of why someone ends up, uh, 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, 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 can build an amazing product. And also, by the way, how do you, um, when you go back, like, why is someone not using your product, right? Like, and so you, it, it focuses on these techniques to extract causation. So they'll... he actually talks a lot about, um, this interview, he calls it, like an interrogation, where you talk to a user like, "Hey, why'd you use my product? Where were you? 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, 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 first chapter, is like deeply understand people. Second's 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, um, you know, root cause analysis and understanding, okay, the metrics are dropping, like why? If 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 talk to, and then you understand, oh, it turns out that it was most... We actually learned about this in... There's this, there's a story in, in, uh, close friends at Instagram where it just totally failed at first on, on, uh, in, in 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 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, so the product was just broken. So it's like you got to 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 you and me 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 book. Don Norman's book, obviously. The Design of Everyday Things is a, is a big one. 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- on each side on a glass door, it like doesn't communicate in- 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 those dots in it that connects it to this other product," and you're like, "People, just, just... It's a camera. Just, 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. And if you do those three things, I think you typically can g- do well. And then, oh, sorry. The fourth one, which is gonna be more of the coda, is be humble. Like, constantly and always question yourself, listen to others, listen to users and be open to being wrong.

    10. LR

      I love these. Uh, uh, on that third point, (laughs) I feel like AI mode, as the name, is such a good example of clarity. What is this? This is AI mode. (laughs) So we talked about it.

    11. RS

      We talked about it internally. Like, 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.

    12. LR

      Yeah.

    13. RS

      Or we could call it something, like, random, but then what is that, you know? And, and now you're working against yourself.

    14. LR

      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. Uh, I love the, I love the... It's like lowercase j- jobs to be done. It's not like the-

    15. RS

      Okay.

    16. LR

      ... the rigorous whole thing that-

    17. RS

      Exactly. No.

    18. LR

      ... you know, everyone... Yeah.

    19. RS

      Lowercase for sure.

    20. LR

      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, uh, 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.

    21. RS

      Exactly, yes.

    22. LR

      Is there-

    23. RS

      And be humble.

    24. LR

      And be humble. Yes, okay. (laughs) Important.

  15. 57:07 – 1:03:01

    Instagram’s Close Friends feature

    1. LR

      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."

    2. RS

      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 d- it, it totally failed originally. This is the product that lets you add a, 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 and maybe-

    3. LR

      The green, green circle.

    4. RS

      Green circles, yes. Um, it's one of the most popular w- well, 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, we, we actually used a bunch of these, these techniques here. So one was, um, 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. Um, had a bunch of ru- it was just super confusing. Like, you would 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, uh, for the, the, you know, the reason people use feed. And then it was just confusing 'cause 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. If you opened the story, it had a green thing inside the story. And it... People were just so confused. And it had this other issue with the list where 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 enc- it 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 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 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. 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 something Clayton Christensen t- 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 'cause 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 was that it was working really well for people who added 20 to 30 people to their list '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 buil- 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 in- and then we updated the design to put the green ring on the outside of the story so that this was kind of the design for clarity. It was... We, 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 be 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.

    5. LR

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

    6. RS

      Yeah. It took a while. That was actually one of the longest projects we worked on. Um, but that actually came... The re- reason we did it was when we, we asked people, for people to understand people, um, like, "What... Why aren't you posting to your stories?" Like, "What's preventing you from doing it?" And it... Everyone had some version of, "Well, my ex is on it," "I have a teacher on it," um, "Oh, a friend that kind of is judge-y is on it." It was like this, this kind of like common- commonality. It was audience problems. Someone had an issue with people watching them. And so we... 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.

    7. LR

      Was this connected to the Finsta, Rinsta trend also?

    8. RS

      It was. Actually, I think that informed us. Like, everyone had a Finsta and there was a Binsta, right? It was like the best friend.

    9. LR

      What is a Binsta?

    10. RS

      Best friend.

    11. LR

      Best friend.

    12. RS

      Binsta. So like different... It's like this layering of, like, people have like 20 Finstas down to, like, your partner Pinsta. Um, and then-

    13. LR

      Oh, Pinsta. (laughs)

    14. RS

      ... it's basically like... I made that up. I don't know if that's true.

    15. LR

      I don't care. (laughs)

    16. RS

      But I'm sure there are Pinstas out there somewhere.

    17. LR

      Yeah.

    18. RS

      Um, and, and we were like, "Wow, people clearly are trying to hack Instagram, basically, to create these private smaller group settings, and so we should just make a product." Yeah.

    19. LR

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

    20. RS

      Yeah, we rolled it out-

    21. LR

      Just a couple

    22. RS

      ... in a few other countries. Exactly.

    23. LR

      Okay. Got it.

    24. RS

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

    25. LR

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

    26. RS

      I think that was one of the earlier ones, yeah.

    27. LR

      Okay.

    28. RS

      But it's, it's a always... Every time you ship something, there's a slightly different reason why. Um-

    29. LR

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

    30. RS

      No.

  16. 1:03:01 – 1:06:39

    The importance of resources in development

    1. LR

      Okay. Let me go in a different direction and talk about something that, uh, you have a hot take on. There's a lot of talk these days about lean teams, small teams, just creating s- uh, limited resources. Not hiring at all. Uh, 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.

    2. RS

      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, um, there's kind of this, uh, 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, a product that works for a lot of people that is based on a technol- 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, a single product that is a way to, I don't know, uh, 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. And you think about these large, um, 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. It... The product never gets good enough internally, and then it kinda 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 was, actually was a small team. One of the reasons it took us forever was it kept the team so small and scrappy, the, 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. 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 gonna be the two of us until this thing has escaped velocity and market fit," which it's not always true.

    3. LR

      This is definitely counter to the narrative (laughs) 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 gonna be this do 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?

    4. RS

      Yeah. I think that it's mostly when you have co- 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, you put 20 friends on it, and by the way, I've, I found out very quickly building startups that if you put 20 friends on something, they're not gonna do you that many favors. Like, they're not gonna use a product every single day 'cause 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 of 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. 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, uh, build the right product eventually is the mentality, and you can only really do that with the right, with the right group.

  17. 1:06:39 – 1:11:19

    AI corner

    1. RS

Episode duration: 1:21:37

Install uListen for AI-powered chat & search across the full episode — Get Full Transcript

Transcript of episode kOnsqqVbIeY

Get more out of YouTube videos.

High quality summaries for YouTube videos. Accurate transcripts to search & find moments. Powered by ChatGPT & Claude AI.

Add to Chrome