The rise of taste, human authenticity and judgment in an AI world | Adam Mosseri (Head of IG)

Adam Mosseri is the Head of Instagram, where he oversees an app used by over 3 billion people. He also leads the team building Threads. Adam has run Instagram for longer than its founders did, after taking over from Kevin Systrom and Mike Krieger in 2018. A designer by training, he spent over 15 years at Meta, starting as a designer on Facebook’s mobile app, rising to lead Facebook’s News Feed, and eventually chosen to lead Instagram. During his tenure, Instagram’s user base has more than tripled. *In our in-depth conversation, we discuss:* 1. How the canonical product team structure is changing in 2026, from baker’s-dozen specialist teams to lean pods of four to six generalists 2. The rise of the “product staff” role—a blending of PM, design, data science, and research into one generalist operator 3. Why Adam is bullish on designers even as functional boundaries dissolve, and which roles are most at risk 4. What the Instagram algorithm knows about you, and why it’s only now catching up to what people assumed it knew years ago 5. Why the rise of AI-generated content is a tailwind for Instagram, and how the company is thinking about creator identity in a synthetic-content world 6. The two biggest product failures of Adam’s career—Facebook Home and the first version of Reels *Brought to you by:* WorkOS—Make your app enterprise-ready, with SSO, SCIM, RBAC, and more: https://workos.com/lenny Mercury—Radically different banking, now with Command: https://mercury.com/ *Episode transcript:* https://www.lennysnewsletter.com/p/adam-mosseri-ai-is-a-tailwind-for *Archive of all Lenny's Podcast transcripts:* https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0 *Where to find Adam Mosseri:* • X: https://x.com/mosseri • LinkedIn: https://linkedin.com/in/mosseri • Instagram: https://www.instagram.com/mosseri • Threads: https://www.threads.com/@mosseri *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 Adam Mosseri (02:09) How product teams are changing inside Meta (05:48) Blurring roles and career anxiety (14:01) Hiring traits that matter now (16:48) How AI is resetting who succeeds at work (19:38) How Meta thinks about token spend and AI costs (23:23) Where human judgment still matters (25:56) Why AI is not automatically great at strategy (30:36) Why great product leaders are curators (34:23) What Instagram’s algorithm actually knows about you (38:08) Why chronological feeds often disappoint users (40:56) Why AI content may be a tailwind for Instagram (43:42) The future of AI and human content in the feed (48:00) What Adam admires about other social platforms (52:05) How he handles public criticism (56:31) Lessons from the Instagram feed redesign backlash (01:00:21) Adam’s biggest failure: Instagram on iPad (01:03:03) His approach to kids, screens, and social media (01:06:56) What Adam wants listeners to remember *Referenced:* • What happens after coding is solved? | Fiona Fung (Manager of the Claude Code and Cowork Teams): https://www.lennysnewsletter.com/p/building-the-most-ai-pilled-engineering • Claude Code: https://www.anthropic.com/product/claude-code • Claude Cowork: https://www.anthropic.com/product/claude-cowork • Head of Claude Code: What happens after coding is solved | Boris Cherny: https://www.lennysnewsletter.com/p/head-of-claude-code-what-happens • A rational conversation on where AI is actually going | Benedict Evans: https://www.lennysnewsletter.com/p/a-rational-conversation-on-where • OpenAI’s CPO on how AI changes must-have skills, moats, coding, startup playbooks, more | Kevin Weil (CPO at OpenAI, ex-Instagram, Twitter): https://www.lennysnewsletter.com/p/kevin-weil-open-ai • Mythos: https://www.anthropic.com/claude/mythos • Fable: https://www.anthropic.com/claude/fable • Pluralistic: The Reverse-Centaur’s Guide to Criticizing AI: https://pluralistic.net/2025/12/05/pop-that-bubble • Plastic Dream Sequence on Instagram: https://www.instagram.com/plasticdreamsequence • TikTok: https://www.tiktok.com • Facebook–Cambridge Analytica data scandal: https://en.wikipedia.org/wiki/Facebook%E2%80%93Cambridge_Analytica_data_scandal • Facebook Home: https://en.wikipedia.org/wiki/Facebook_Home _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.

• 0:00Speaker 00

  No, I think taste matters a ton. In a world where it's easier to build things, it's more important to make sure that your time is spent figuring out what you should be building in the first place. The people who I think are gonna make the most of it are the ones who are clear-eyed about what AI is good at and what it's not good at, and also have an instinct or a nose for what it will be good at and not good at.

• 0:23Lenny Rachitsky?

  What's something that the Instagram algorithm knows about human behavior that people may not realize?

• 0:30Speaker 00

  I think people assume that there's a much more detailed semantic understanding of everybody's interests and preferences and yada than there is.

• 0:38Lenny Rachitsky?

  Is the rise of AI content a headwind or a tailwind for Instagram versus other platforms?

• 0:44Speaker 00

  I think it's gonna be a tailwind, but I think it's gonna be a challenge. In a world where there's an abundance of synthetic content, I actually think people are gonna seek out creativity and authenticity and people. I don't think we should filter out AI content. I think we should let you know if content is AI content or not. That's hard, by the way.

• 1:04Lenny Rachitsky?

  Where do you think human brains will continue to be most valuable as AI continues to eat more and more of that product development lifecycle?

• 1:12Speaker 00

  That's a great question.

• 1:13Lenny Rachitsky?

  So.

• 1:16Lenny Rachitsky?

  Today, my guest is Adam Masary, head of Instagram. Over 3 billion people use Instagram monthly. That's one in every three people alive. It boggles the mind. Prior to Instagram, Adam designed and led the early Facebook newsfeed. He also ran the team that built the Facebook ranking algorithm. And eight years ago, he took over Instagram from its founders, Kevin Systrom and Mike Krieger. He's a designer-turned-product manager-turned-leader of Instagram. Adam is also famous for being the face of all of the controversy and changes that come with evolving Instagram as a product, which we talk about. Before we get into it, don't forget to check out lennysproductpass.com for a free year of the most interesting and well-crafted AI products in the world,

• 2:01Lenny Rachitsky?

  available exclusively to Lenny's newsletter subscribers. With that, I bring you Adam Masary.

• 2:09Lenny Rachitsky?

  Adam, thank you so much for being here. Welcome to the podcast.

• 2:13Speaker 00

  Thank you for having me. Excited to be here.

• 2:15Lenny Rachitsky?

  You've been doing product for a long time. You get to see how a lot of teams operate across Meta within Instagram. What does just kind of like the canonical product team look like in 2026? What's kind of most different today in how teams operate slash should operate versus, say, a couple of years ago?

• 2:33Speaker 00

  It's changed a lot this year. So for the longest time at a big company like ours, the canonical team was something like two or three Android engineers, two or three iOS engineers, two or three server engineers, maybe a generalist, a PM, a designer, a data scientist, a researcher if you were lucky.

• 2:52Speaker 00

  And maybe that's about it. So, you know, on the order of a baker's dozen. And that is a function of,

• 3:02Speaker 00

  you know, you wanna have, for anybody who's writing code, someone who can review their code and that's who's familiar with that codebase and having these different functions that are more specialized. You know, I think it's very different at a startup. But this year, it's changing. We've adopted what we call pods, which are just mini-teams, where it's, call it, four to six engineers who are a bit more generalists. One, we call product staff, which is sort of a devolution of the PM. So a PM who can do some of what a designer does and some of what a data scientist does and some of what a researcher does, leveraging the latest tools that we have for them. And then whatever specialist they need.

• 3:45Speaker 00

  If they're doing something that requires a pricing strategy, you need a senior data scientist. If you're doing something that is really novel from an experience standpoint, you need a very senior product designer. So we try to build a team based on the needs of the work a bit, but then end up with a much smaller core, which is more on the order of six or seven usually. And that is a very big shift that's just happening to us this year. But they, just by virtue of having less people to coordinate, they can often move faster and make better decisions, a little bit less designed by committee. So we talk a lot about, you know, AI adjusting and improving productivity, and that's part of it.

• 4:30Speaker 00

  But I think another part of it is just the small teams, I think, often are just more effective.

• 4:38Lenny Rachitsky?

  This episode is brought to you by our season's presenting sponsor, WorkOS. What do OpenAI, Anthropic, Cursor, Vercel, Replit, Sierra, Klei, and hundreds of other winning companies all have in common? They are all powered by WorkOS. If you're building a product for the enterprise, you've felt the pain of integrating single sign-on, SCIM, RBAC, audit logs, and other features required by large companies. WorkOS turns those deal blockers into drop-in APIs with a modern developer platform built specifically for B2B SaaS. Literally every startup that I'm an investor in that starts to expand up-market ends up working with WorkOS. And that's because they are the best. Whether you are a seed-stage startup trying to land your first enterprise customer or a unicorn expanding globally,

• 5:23Lenny Rachitsky?

  WorkOS is the fastest path to becoming enterprise-ready and unblocking growth. It's essentially Stripe for enterprise features. Visit workos.com to get started or just hit up their Slack, where they have actual engineers waiting to answer your questions. WorkOS allows you to build faster with delightful APIs, comprehensive docs, and a smooth developer experience. Go to workos.com to make your app enterprise-ready today. I love this. So on this team of six to seven, what's the makeup again? And which role are you finding you have less of if you're going from the kind of the, if you're going 50% size?

• 5:59Speaker 00

  You just have less specialists, right? So you might not have any. It might be four engineers and a product staff. And there's no data scientist, there's no designer, there's no researcher, there's no content designer. The product staff is the generalist that sort of supports all of those things. I mean, what's clearly happening is all of the functions are starting to bleed into each other and the whole industry is wrestling with what that means. You know, a lot of what a data scientist does at a big company, for instance, is relatively mechanical. And so, you know, there's stuff that they do that is really more like, you know, art and science and the stuff that's really more like just pulling data, data management. You know, so some of the tools that we're building internally to understand, for instance, a traditional data science question would be a waterfall.

• 6:44Speaker 00

  So if you wanted to look at people creating reels, you would look at all the steps and then how people fall off on each step and try to figure out whether there might be opportunities to improve things. That kind of basic waterfall analysis is like much easier now to use some of our internal tools to just pool automatically as opposed to having to have a data scientist do a bunch of bespoke work for that. So a product staff might be able to do that now, and they couldn't do that a year ago. So you just end up with this generalist, these people have more generalist shapes. And then, and then when you need it, when you really need it, you have a more senior ideally or just more creative specialist. So, you know, a phenomenal product designer

• 7:27Speaker 00

  or just a genius data scientist or researcher.

• 7:32Lenny Rachitsky?

  This is so interesting. It's exactly what I just heard. I had Fiona Fong, the head of engineering for Claude Code and Co work on the podcast. She's Force Journeys manager. And she described the people she hires now are, one, builders with great taste that can take an idea from end to end, and people with deep expertise in a very specific domain.

• 7:53Speaker 00

  The taste thing matters a lot. I really agree with that. Boris used to work at Instagram.

• 7:57Lenny Rachitsky?

  Oh, that's right.

• 7:59Speaker 00

  Yeah, he was a senior. I see it in Instagram for a while. I love seeing him. He's all over threads now. It's like he's sort of like the face of Claude Code.

• 8:05Lenny Rachitsky?

  He's killing it. He's a celebrity now.

• 8:08Speaker 00

  He really is. He's his own, yeah, for sure. In a world that is like on fire right now. No, I think taste matters a ton. So in a world where it's easier to build things, it's more important to make sure that your time is spent figuring out what you should be building in the first place. Actually, so a lot of designers right now are very anxious about their roles. You know, you've got these other generalists doing design. You've got engineers doing design, product staff doing design. But I'm actually pretty long on design or designers because they tend to have taste. And I think that is something that is much more difficult to imagine being automated away.

• 8:53Speaker 00

  And so there's other challenges with design sometimes, but I'm pretty long right now on designers.

• 8:59Lenny Rachitsky?

  I've always felt that too, as it is so easy to build and all the work that AI produces is so like, you can tell this was Claude design. I know what you did here. This is Codex.

• 9:10Speaker 00

  Well, they all have their vibe, right? Like your vibe code, your apps, we call it vibe code, and we're like, oh, that's a Codex app. Oh, that's a Claude app.

• 9:17Lenny Rachitsky?

  Right, and that's Replit. That's lovable. Like you can, you can predict these things. You, like, I've always thought that too, that design should be thriving already now. For some reason, it hasn't yet. If you look at jobs for designers, they're kind of flatlining. I feel like the missing pieces, like the PME piece of deeply understanding the business and what will grow it and what successfully, you know, like all that stuff, the business side of it versus the taste side of it.

• 9:40Speaker 00

  Yeah. I think you're gonna see, like, you know, we have a senior designer at Instagram called Nate who just transferred into product stuff. So I think, I think some of what you'll see is, you know, it will be harder to talk about design roles and who's a good designer because they're not gonna just stay in traditional design roles. You know, if you're an amazing designer, you might, you probably have strong opinions outside of just the interaction and visual design. You probably have strong opinions on product strategy, even on the business, on the go-to-market. And so I actually think some of our strongest product staff are gonna be converts from design and from data science who are just looking to expand their reach. And they were influential across functional boundaries before,

• 10:24Speaker 00

  but this world where those functional boundaries are just wildly blurred just allow them just to jump in. And so, sure, they'll be technically a generalist on paper, but they're clearly have a uniquely, you know, strong ability in one, one type of craft. But they've got the ability and strong opinions to make informed decisions across other parts or other crafts. And so. You know, I don't know that all the strongest designers I have will all be in design. They probably will be the majority, but I can imagine a bunch of really strong ones, you know, moving roles. But I mean, I should also check my own bias here, though, because I started as a designer at Facebook way back when and I switched roles.

• 11:05Lenny Rachitsky?

  No, designers are great. I'm a big fan. So this is really interesting. There's always been this like GM model where different types of functions can become GMs. It's like this product staff role feels like a similar situation where different functions can become product staff.

• 11:17Speaker 00

  Yeah, and that was true of PM before, but it's just so much more true now. And it'll, I mean, in some ways, it's probably the age of the generalist, but I still think there's going to be a real important role for these really amazing specialists who are just, they're all about going, I wish I was like that. I always had this like, I romanticized like phenomenal machine learning engineer or AI researcher or shoemaker. Like, I think that's the coolest thing in the world, but it's never been my shape. I've always been, I've never been great at anything. I've always just had range. That's always been my strength.

• 11:54Lenny Rachitsky?

  Same. Okay, so this idea of product staff. So the idea is on these new pods, so this is like a new thing you guys are doing. So there's these pod teams, product staff, engineers, and maybe one specialist that's going deep on, say, pricing algorithm or something like that. So what this tells me is there's these like adjacent roles that are maybe more in trouble over the years. Data science, for example, user research, for example. You talked about designers being anxious. Is there, is there anything there of just like, oh, these, maybe folks in these groups should think about shifting to other roles?

• 12:26Speaker 00

  I mean, there's anxiety everywhere. I mean, I, I've talked to a lot of people at a lot of other companies and it just seems like this is a lot of concern right now about competition, about job displacement, about unintended or unforeseen consequences of all this technology and all this moving so quickly. So that's definitely happening. I, I think that, I think that you will see the functional lines continue to blur, but I still think there will be room for functions. They'll just be shaped differently. They'll be more, they won't all be senior ICs necessarily, but they'll all be either senior or on their way to being senior. Like, you can't just have a bunch of super senior data scientists and like no new ones, because then who's going to be the new super senior data scientists in the future?

• 13:10Speaker 00

  So you need to basically hire and mentor and grow talent. You know, maybe the team is smaller overall and then that those who aren't on their way to being super senior move into more of a generalist role. I think that's like a reasonable soft landing. But I do think you're going to want to make sure you're investing not only in today's senior talent for each specific function, but in tomorrow's. Otherwise, I think you're going to regret it in a couple of years. My take. That said, who knows what the world looks like in a couple of years? So my big thing is generally like, don't over, don't be overly confident in whatever your predictions are, because there's just too much flux right now.

• 13:51Lenny Rachitsky?

  Benedict Evans was on, was on the podcast recently, said the same thing. We don't know anything about what's going on.

• 13:56Speaker 00

  Yeah, I like, I like, I like him a lot. I'll make sure I'll listen to the pod.

• 14:00Lenny Rachitsky?

  Yeah. So you talked about taste. This makes me think about, so you're interviewing a lot of people, hiring a lot of people. What are some traits that you're, that are like trending up in things that you look for more and more now in this world? And what are some traits that are trending down and maybe less important to you?

• 14:17Speaker 00

  I mean, there are some things that are the same, right? So for the longest time, almost no matter what the function, I always look for three things. Do you have sort of grit? Like, you know, you're kind of like, you're really gonna, you've got some drive, some fire in your belly? Are you a quick learner? And are you, you know, are you reasonably, ideally very self-aware? So that you can actually take feedback and know what you're good at and what you're not good at? Because if you're those three things, if you've got fire in your belly, you learn quickly and you're self-aware, you can kind of get good at anything eventually. And, but if any of those things are missing, it's usually an issue. So that's sort of like the baseline. Right now, for hiring, but just for, I think, people who are going to be more successful

• 15:00Speaker 00

  over these next five or 10 years as things change so significantly, I think two things that I'm continuing to encourage myself to do are to stay curious and to put yourself out there. I just think you've got to try things, right? This is like, you know, to that point before, then no one really knows what's going on. You just have to be willing to try things. It's almost, I don't know, do you speak another language?

• 15:25Lenny Rachitsky?

  Russian, yeah.

• 15:26Speaker 00

  Yeah, so when you learn another language, I think one of the most important things, one of the best predictors, this is my guess, I don't have any research on this, about, you know, are you going to get good at speaking? Is are you willing to sound like an idiot? Are you willing just to say it and be corrected and not be offended and then just get better and better? You have to put yourself out there. And with all of these new tools and models and technologies, I think you just have to be willing to try stuff. So if you're curious and you try stuff, I think that'll, you know, you'll learn, you'll adapt. But if you're not curious or you're not willing to make mistakes or try things, I think you're in a ton of trouble. Or at least I think it's going to be a really difficult time. So those, I think, are premiums, not just for hiring at a company like Meta or a team like Instagram, but I just think across the industry and multiple industries over the

• 16:11Speaker 00

  next 10 to 20 years. Is this something that maybe we're looking for less of? For some of these functions, I think that there's some that are still going to be very large teams, and so you need people who are really good at managing large organizations. Large organizational leadership is its own craft and skill. It's actually different than management. But I do think there'll be less of those roles. I think we'll have more smaller teams and there'll be less people who manage thousands of people. And so that's not that that job will go away, but there will be less of what I'm looking for in hires, because I'm going to have less roles like that.

• 16:48Lenny Rachitsky?

  Something I'm hearing from a few folks is AI is almost kind of resetting people's impact and success in terms of some people that were maybe low performers pre-AI can now do like things they were bad at, or AI now allows them to do. And now they're thriving, building all these things, helping other people. Do you see that at all? Just like AI is just like lifting other people up, maybe lowering some people down?

• 17:12Speaker 00

  Yeah, I mean, the job is just different. I mean, take, take us, take, um, take engineering. Engineering used to be, maybe not majority, but a large percentage, 40, 50, 60% writing code. You know, it's not now, especially if you talk to anybody at these labs, they're spending most of their time planning and reviewing code. That is a very different job. You might hate that and you might have loved just writing code, or you might have, you might love that and you might not have been that fast at writing code. So, you know, who, who succeeds is a function of whose strengths are aligned with the tools, needs and the business's needs. And so this is definitely happening.

• 17:54Speaker 00

  Another thing is you've had people who had good ideas about how to contribute it to other functions, but didn't have the mechanical or technical skills to do so. And AI reduces the boundary to do that. And then all of a sudden they can, like, you know, I, it's, for me, it's kind of funny because when I got hired at Facebook, we, all the designers had to be able to program. That was like our, I had, I went through a technical loop. We gave up on that because it was too hard to hire people. But I now get to program again for the first time in maybe 10 years. And, you know, I am not a good engineer. I'm a mediocre engineer on a good day. But now I can write code responsibly, which is just an amazing thing.

• 18:38Speaker 00

  You're seeing this across all sorts of levels and seniority and functions. You know, designers who are programming, engineers who are pulling data and doing strong analyses, data scientists who are putting together proposals for designs. You know, the tools aren't all great, by the way. I think too often we have this really polarized binary outlook on the state of AI. Like, are you AI pilled or are you anti-AI? It's like people aren't binary. I said that to the team yesterday. And the state of the tools isn't binary either. You know, they're amazing at some things and remarkably bad at others.

• 19:20Speaker 00

  And the people who I think are going to make the most of it are the ones who are clear-eyed about what AI is good at and what it's not good at, and also have an instinct or a nose for what it will be good at and not good at, you know, not, you know, next month or in a couple of months from now.

• 19:38Lenny Rachitsky?

  You mentioned that AI writes all our code now. Someone tweeted this, that's this idea that's stuck with me for like months now of just like, remember, we used to be able to just write code for free?

• 19:52Speaker 00

  I think it's not be able to write code for free, just be with a smaller model, but yes.

• 19:57Lenny Rachitsky?

  Like, I guess that's true. Like, there's a model that are close to free, but it's like, yeah, that's crazy. Now it's just like.

• 20:03Speaker 00

  But just think about, think about the cost. Think about what you pay for a model now and how and what the level of intelligence you're getting from that model is. And then at that same price point a year ago, what were you getting? At some point, they will just, the incremental value is, will be, won't matter. Like, you know, you know, we're getting there, I think, with small projects and programming. Like, I think the models will matter even beyond, you know, this week you've got Fable and obviously Mythos from Anthropic, but I spent a lot of time with that this week. I'm, it's for the first time, I'm like, oh, I'm just talking to a much more technical, much smarter engineer than I am.

• 20:45Speaker 00

  You know, the next version, you know, you know, a year out of that model, do I need to pay for frontier tokens, you know, for whatever, you know, Anthropic Model 6.0 is? Or is Fable just fine for all of my side projects? Probably just fine. Probably pretty, pretty cheap by then, too.

• 21:04Lenny Rachitsky?

  Yeah, when Kevin Wales on the podcast, when he was CPO at OpenAI, he's, he famously said, this is the worst the model will ever be.

• 21:12Speaker 00

  Yeah.

• 21:13Lenny Rachitsky?

  And it's still hard to comprehend that. Wow, that's, that's only gonna get better. So on this point of tokens, span, ROI and things like that.

• 21:22Lenny Rachitsky?

  Meadow was famous for this like leaderboard of token spend.

• 21:25Speaker 00

  It's a terrible idea. No leaderboards for token spend.

• 21:28Lenny Rachitsky?

  Okay. Talk about that and just how do you think about just like budgets for engineers and product teams at this point? Just like spend as much as you want? Is it like, there's a cap we have? Is there any sort of thing you've kind of figured out that works well?

• 21:38Speaker 00

  Right now, we've managed to get the costs reined in a little bit by like shutting down the silly things that we were doing. And so, you know, it's not that hard to build a token incinerator and that doesn't create a lot of value. And as soon as you actually look at the dollars in and value out, you might just be like, oh, that's just a bad idea. And so right now, we don't have token limits for, for, for our engineers. Actually, I think for anybody, really. I think that'll eventually have to happen, particularly if costs go up before they go down. I think they'll eventually go down because, for the reasons that we just talked about. But I think of it like as any other resource, right? Like, I have to decide how to deploy capacity to my different teams because I have a limited number of GPUs and CPUs and storage and RAM, et cetera.

• 22:22Speaker 00

  I have to decide how to deploy OpEx for labeling budgets across my teams. I have to decide how to deploy payroll for headcount across my teams. I think that you can imagine at least in a year or two coming that the, the burn rate of a strong engineer might be the same as their salary or their cost of employment. And if in that world, like, you're gonna probably need to put in some caps. The caps should probably be

• 22:55Speaker 00

  like a proportional to your sort of, you know, the company's sort of trust in your ability to use them in an ROI positive way. But I can imagine caps being healthy. Right now, we're not there. I think costs will go up because we'll just be using more tokens. Not because prices will necessarily go up, but then I think prices will come down because all of these frontier models are gonna be in a bit of a pricing war. So we'll see. I think it'll be a bit of a roller coaster.

• 23:23Lenny Rachitsky?

  So coming back to this idea that, as you said, we've evolved from, we used to write all our code to now we're approaching, all code will be written by AI. And it feels like now the transition is it's not just written by AI, but it's like one shotted by AI. Like coding now is steering AI. And it's like, how often you have to correct it is, is coding now. And then there's, so it's like the software development lifecycle slowly being eaten by AI. It'll start helping us come up with ideas, I imagine, more and more. The question I like to ask people is, where do you think human brains will continue to be most valuable? As AI continues to eat more and more of that product development lifecycle?

• 24:04Speaker 00

  Taste, like we talked about, judgment, particularly around strategy, right? Like, you're, you're not, you might get feedback from an AI on the strategy, but you're not asking AI to come up with a strategy anytime soon. Or if you are, then it's within the context of bounds you set. So here's my goal, here's my vision, here are my constraints, here's my job, here's my budget. I think that, you know, it looks more like management, right? Like, you are trying to define what success looks like. Decide how prescriptive you want to be about the path to success. And then giving feedback along the way. And that is its own craft, you know, and you, it'll be interesting to see how Matt, you know,

• 24:48Speaker 00

  you know, if some of the same dynamics come up. Like, I believe that if you are too prescriptive as a leader with a team, you end up stifling good ideas. But if you're too open-ended, sometimes teams just waste time going in the wrong direction. And so that level of autonomy you give a team, like maybe that applies to agents in the future. Particularly when we're talking now just about building something, but deciding what you build in the first place. But I think of, I think of vision as an articulation of the world or the, or the state of the product you want to get to. And I think of strategy as an opinionated path to achieve that vision.

• 25:30Speaker 00

  If strategy can't be like, be the best or be amazing. It has to be controversial that you have to be, or just a reasonable person should be able to disagree with it because otherwise you're probably just trying to compete on raw execution. And I think that both vision and strategy, I think, are gonna be where our brains are spending a lot of our, more and more of our cycles. And I think less on, on execution.

• 25:56Lenny Rachitsky?

  Something I have always thought is AI should be incredibly good at strategy. Because you would think, here's the market, here's all the information on the market, our competitors, our metrics, our numbers, our growth, all these things. Help me figure out how to win. You think AI, knowing all that, would be really good at this.

• 26:14Speaker 00

  I think it could be. I have found it's not unless you steer it pretty aggressively. And I don't mean towards an answer, I mean based on the constraints. It turns out when you're trying to come up with a strategy, there's a lot of things to consider, right? You need to consider the state of the technology, the personnel on the team and what's motivating them and what you can get. You know, sometimes coming up with an idea that is on the bubble, you know, it's gonna actually attract some of the best talent. And so that kind of like, that kind of the push then goes to the idea. Obviously, the competitive landscape, the regulatory landscape for companies as large as ours, and the compliance landscape, the identity and reason to exist for the brand. You know, you have to consider all of these things. I think if you

• 27:00Speaker 00

  ask an AI just for a strategy lazily, you're not gonna get something great. You're gonna get something pretty predictable that pop up at the competition would expect you to do. I think if you want a really more effective one, you need to think long and hard about what are all of the different inputs that need to be considered. Make sure you

• 27:19Speaker 00

  steer the AI in a way that it's considering those as well. And it needs to be a conversation and a back and forth. But I think if you're willing to put in the work and the time, it can definitely be helpful and definitely be clarifying. Particularly if you tell it to be critical.

• 27:35Speaker 00

  Different models have very different vibes, though, on how willing they are to be pushed back. So I, I recommend picking one that likes pushing back.

• 27:44Lenny Rachitsky?

  Yeah. Mythos has gotten really good at being like, I can't do this, let's, let's move on. Like, there's all these limitations.

• 27:49Speaker 00

  Claude has always been a little bit of a jerk in a way that I actually appreciate.

• 27:55Lenny Rachitsky?

  That's true.

• 27:55Speaker 00

  I appreciate it. I really do. Because I don't want one that's just like, oh, you're so right. I'm so sorry I said that. It's like, hold on, I want, I want, you know, I want the real, real sort of intelligence. I don't want a pleaser.

• 28:07Lenny Rachitsky?

  This point you made about people being excited about the strategy is such an interesting one. There's this idea that I read, I think Corey, Corey Doctorow wrote this. There's this kind of concept of a centaur, centaur and a reverse centaur. So centaur is a human body, horse, this is going somewhere, I promise. Human body, horse, sorry, human upper part, horse, lower part.

• 28:28Speaker 00

  Horse body, yeah, yeah, yeah.

• 28:29Lenny Rachitsky?

  Horse body, where the human is in charge. And that's kind of, we prefer that, we want to be in charge. Reverse and chart, which is what we want to avoid with AI, is where the AI is controlling us. And we're just doing its bidding.

• 28:40Speaker 00

  It's a horse head on a human body.

• 28:42Lenny Rachitsky?

  Yeah, exactly.

• 28:43Speaker 00

  It's terrifying.

• 28:44Lenny Rachitsky?

  Like, in a sense, like Uber drivers and DoorDash people, kind of, this is their life, which is not great. And this is the danger thing for a lot of people is like, like if it's giving us the strategy and telling us, here's where we're, but like, no one's gonna want to do that. So that's a really interesting counterpoint to, we don't want AI to be telling us the strategy almost.

• 29:02Speaker 00

  Yeah, no, I, I think there's a lot of things to be careful about right now. And I would certainly not just assume that because you might be able to outsource some workflow to AI that you should. There are certain ones where I think it's really just a win-win. There are certain ones where I think is the risk outweighs the benefits.

• 29:24Lenny Rachitsky?

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• 30:05Lenny Rachitsky?

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• 30:37Lenny Rachitsky?

  Okay, going back to product leadership, things you've learned along your journey. We were chatting ahead of this about just things you've learned. And one thing that you said about some of the product, the best product leaders you've worked with is that they're less visionary and more curators. I'd love to hear more along these lines.

• 30:54Speaker 00

  Yeah, I mean, you do sometimes find amazing product leaders who are, who are just like idea machines, just prolific idea machines. But I do think a lot of the best are, have, have taste, are.

• 31:10Speaker 00

  Have something about them that really makes wants makes really strong talent want to work with them. But end up sort of being curators, curators of people, curators of ideas, curators of technologies, curators of strategies. Cause I don't really care if I'm hiring a strong lead for an area. If the strategy comes from them or comes from somebody else. I just care that there is an amazing strategy and everyone is bought into it and that the and then we're executing against that strategy well. And so I think that some of the best product leaders, yes, have ideas. It's hard to be a great curator if you don't have some of your own ideas.

• 31:49Speaker 00

  But are the embrace the reality that they can't come up with everything themselves. And so they need to create an environment in which great ideas bubble up and are chosen or decided upon. And so, you know, I think it's not just about curating ideas, but it's sometimes about curating teams and people.

• 32:13Lenny Rachitsky?

  I love that. I so agree. I feel like everyone's always joining a team and they just want to do vision strategy, just like not actually hands on work. And now AI is coming in, here, let me do the strategy.

• 32:23Speaker 00

  Yeah, exactly.

• 32:26Lenny Rachitsky?

  And I love this point that there's so much power and value and people underestimate just the need for just like a really good curator of of the team's ideas.

• 32:35Speaker 00

  Yeah. Sometimes it's also, sometimes it's not just who's good or what idea is good. It's also what is going to work, given the broader context. So for instance, on team building, a huge thing that I'm always considering is not just like, is this person a really strong candidate for this role? It is how does this person fit into their leadership team, you know? So if I, you know, for an area like trust and safety, you know, I have an engineering lead, I have a product staff lead, I have a data science lead, I have a design lead, I have a research lead. I need to make sure that those five complement each other. I need to make, and that's, you know, about what skills each one has, what weaknesses each one might have.

• 33:16Speaker 00

  I also need to make sure that they, um, this is more art than science. Have a good vibe, right? You know, you need, you know, trust and rapport. A leadership team with strong trust and rapport can work through most anything. A leadership team without trust or rapport, like anything can become an issue. And so that that chemistry bit is, is, is like I said, much more art than science, but that also matters. And so I think some of the best leaders and product leaders specifically also either do that instinctively or consciously, but you know, they have a, they have a nose for, for building teams that are gonna have good energy and good collaboration.

• 33:59Lenny Rachitsky?

  Warm and fuzzy stuff.

• 34:01Speaker 00

  Yeah, yeah. Well, the flip side is also true, right? Like I've, I've had many times in my career, I've had two people who I think are amazing and I even adore them and love them. And they just can't get along. You're like, this isn't a competency issue. This is just a personality issue. And you just have to just sometimes call it and split them.

• 34:23Lenny Rachitsky?

  I want to transition to talk about Instagram, the product, the platform, things you guys have learned there. Let me start with this question. What's something that the Instagram algorithm knows about human behavior that people may not realize?

• 34:38Speaker 00

  One of the most common misconceptions is actually in the opposite direction. I think people assume that there's a much more detailed semantic understanding of everybody's interests and preferences in the algorithm than there is. Most of what's really driven the progress in the world of recommenders over the last five, 10 years have been, you know, these large embedding models and these other techniques that basically produce artifacts that cannot be read by people. They're not legible. They're like giant vectors. It's like, sure, I can show you the vector, but it's just going to be a bunch of numbers in like a seven dimensional space. It's like. And so when, when we talk about, does the algorithm know something? Usually we think in these more semantic terms, it knows I like surfing.

• 35:23Speaker 00

  And it's like, it doesn't, it just has this big ass number that happens to correlate with surfing. That said, I think that is starting to change, right? I think that what, one of the things that LLMs are enabling is they can describe in, you know, words, you know, English for, or whatever language you prefer. What some of those previously illegible artifacts are at least proximate to, if not mean directly, right? So this is like the thing I've been really, I posted about this this week, this thing called your algorithm. Basically, the idea is we take a look at all of the stuff that you've interacted with.

• 36:06Speaker 00

  And then, you know, we, all of that is in an embedding space. You can think of embedding space as a map. You can map a bunch of videos into the same map. And so videos that are close are similar. And now we can just have an LLM just be like, describe that part of the map. And it can be like, oh, that is like deep pour over coffee snobbery. And that's kind of amazing.

• 36:29Lenny Rachitsky?

  That is so cool. That like you can ask the LLM to look at these numbers and extrapolate here's like the topic that you're interested in.

• 36:36Speaker 00

  Yeah, or look at the videos. And so the way you're both, so you can also embed concepts into that same space. And so, I mean, embeddings are really the underlying technology underneath LLMs, right? That's how the whole thing works. And so, you know, so what, what we, what we, what we do now is we let you, you know, quote unquote, see your algorithm. You can see what topics we think you're interested in. And you can adjust it, you can add and remove things. But the idea here of giving people some agency back in a world where, you know, these social media apps are getting taken over by recommendations. But we can't do a lot of other things yet, which we will be able to do. You know, you could, there's things that aren't topical that you might ask for.

• 37:19Speaker 00

  I want more fun content. I want to see my friends more. I don't want to see my high school's kids, friends' kids' photos. You know, I don't know, we can come up with, I don't want to see seven photos in a row, but I'm happy to see six photos in a row, whatever your heart, you know, whatever your mind can come up with. So we have a lot of work to do and so I'm excited about that. But I think a misconception historically is until recently, we don't really know as much about you as you think. We're just like, oh, like you liked these photos. This, these people also like those same photos and they like these other photos, so you might like those other photos. Like that's kind of how, I'm oversimplifying, that's like, yeah, kind of how it worked.

• 38:01Speaker 00

  Now, only now are we actually getting as sophisticated as I think people have assumed we've been for many years.

• 38:06Lenny Rachitsky?

  That is really interesting. One that comes to mind is to kind of this transition everyone eventually goes through to this like algorithmic, broad, global feed. Everyone, it always feels like people think, I just want to see chronologically everyone I know and follow, and that's going to be my favorite feed. And it continues to be proven wrong. No, you actually engage a lot more, a lot more when it's this algorithmic feed of things we think you will love.

• 38:31Speaker 00

  Yeah, it's tough because, I mean, I get, I mean, I posted this week, this thing about agency and I just got destroyed in the comments, which is just part of the job. I get it, right? The, there's, but there are a couple of issues with the algorithm, with the chronological feed. So one is, and some of this is the tension between an individual's interests and what works when you scale it up, right? So if you do a pure chronological feed, the incentive for everybody is to just post as much as possible. Cause it will always be at the top of everyone who follows you's feed as soon as you post.

• 39:09Speaker 00

  So what ends up happening is that the feed gets overwhelmed with professional content, with usually large company content and publishers. Cause they, you know, the New York Times can pump out 50 things a day. Your, your best friend won't. You might get one thing a week from them. And so your feed just gets taken over. So part of it is the incentives that emerge, because when you, when you design these systems, it's almost like designing a city. You need to think about, okay, here's the, here are the, here's how the mechanics work. What are the incentives that arise? How are people going to act within those incentives? And then what happens? And the other thing is, sometimes the most interesting thing was just not the most recent thing. Recency is an important input into relevance, but it's not the only one.

• 39:53Speaker 00

  My sister got engaged last night and, you know, she's in Germany. No, she didn't. If she did, she's married. She got married last year. That's why it was top of mind. But if she got engaged, you know, and I missed it because she lives in Europe and, you know, with different time differences. Like, do I really want to see a picture of like my brother's po bo sandwich, you know, po boy sandwich? Or do I want to like see my sister's things first? So I, it's tough. It's tough. I'd love to figure out a way to find the right balance. I want to give people agency over the experience, but I think it needs to be in a way that creates a system that makes sense. Not just for us as a business, which matters, I'm not pretending that's not an issue, but also for the overall community. Cause we've done chronological by default and where you can make a default.

• 40:38Speaker 00

  And you see, not only does usage go down, overall sentiment goes down. The individual who made that choice might be happy at the moment, but when you just get pummeled with stuff you're less interested in over the course of months. We ask, we run surveys at massive scales. We just see people start to become less and less satisfied with Instagram.

• 40:57Lenny Rachitsky?

  Kind of along these lines, everybody asks you about this these days, AI and content and how that all impacts everything that's going on. I want to ask you something I haven't seen someone ask you. Is the rise of AI content a headwind or a tailwind for Instagram versus other platforms? Do you think this helps or hurts you guys?

• 41:17Speaker 00

  I think it's going to be a tailwind, but I think it's going to be a challenge. It's, and not just because it's more content. Obviously, we're an attention business, driven business. We're an advertising business. More content means potentially more attention. That's not for free, though. Like, I don't think we're very good at ranking AI content yet. There's great AI content, there's crap AI content. You should just see the stuff you're interested in and not any of the stuff you're not interested in. But I do think that in a world where, or for years now, and I've said this many times, power is shifting from institutions to individuals across industries. The easiest example is sports where players are more relevant than teams now, and that was not the case when I was a kid. In that world, you're gonna, I think it behooves us to invest in individuals and to invest in,

• 42:03Speaker 00

  specifically for Instagram and creators. And I mean creators broadly. I don't just mean influencers who are promoting branded content and making, you know, native only videos. I mean, anybody who's using platforms like Instagram to help do what they do, right? It could be, you could be a journalist, you could be an artist, you could be selling scarves, you so. But like you're out there as yourself for creating and sharing content that helps you achieve whatever it is you're trying to do. So we've been leaning in that direction for many years now. That's been our, you know, one of our two or three most important audiences for as long as I've been on Instagram. In a world where there's an abundance of synthetic content, I actually think people are going to seek out

• 42:45Speaker 00

  creativity and authenticity and people more, not less. And I think that that will help us. That doesn't mean that we won't have AI content on our platform. There's gonna be bad and good AI content and we're gonna try and handle that, you know, the way we normally handle content. So unsafe goes away. Interesting versus not interesting is based on ranking and personalization. But I think people are gonna really seek out other points of view. Cause Instagram was never just about the content. It was always about, to a certain degree, the person behind the content, the point of view, the reason they're sharing it, their perspective. And I think that's gonna become more important, not less. And I think, given that we are

• 43:27Speaker 00

  not the best at a lot of things, but we are the largest creator platform. You know, if you look at how we define creators and how many creators use us for still the platforms, I think it'll be a tailwind for us because I think people are gonna seek out people.

• 43:42Lenny Rachitsky?

  And this connects to your earlier point that companies like Sanier James can pump out a bunch of AI content versus a creator. And so you're saying you kind of want to protect against that too. Allow individuals to continue to perform well in spite of just all this AI content.

• 43:58Speaker 00

  If you just love AI content, great. Like you should be able to have a feed that's just like AI town. And if you don't, then you shouldn't have it in your feed. Like, you know, to me, it's like, I don't think we should, I mean, I understand why people are, right? There's a, I'm not oblivious to the overall paradigm shift and sort of revolution that we're sitting in. But I don't think we should judge content based on the tool that made it. I think we should judge it based on the content, the point of view, the person behind the content. Like, I don't, I don't think we should filter out AI content. I think we should let you know if content is AI content or not. I think we should let you know more about the person who posted anything so that you can make

• 44:41Speaker 00

  informed decisions about whether or not to believe or trust them based on, you know, knowing who they are, where they are, or how many times they've changed their profile, or, you know, you know, if their profile's three days old or three years old. But I don't think we should be making value judgments based on what tool you used.

• 44:59Lenny Rachitsky?

  Is there an AI content creator you love that you're just like, this is so good, I love watching these AI videos?

• 45:05Speaker 00

  Yeah. What is she called? Plastic, Plastic Dream Sequence? Is that what it is?

• 45:11Lenny Rachitsky?

  I'll check it out.

• 45:12Speaker 00

  Check it out, yeah. Plastic Dream, Plastic Dream Sequence. I have it on my phone. I'll do a check. It's these like, like sort of dolls, Barbies, but they're like singing songs and these little tiny silhouettes and snippets. And it's just, it's just amazing. It's like a little weird, but like also kind of amazing. And it's, it's very clearly AI. It's not pretending not to be. But it's, has a very clear creative and aesthetic point of view. And every time I come by one, I'm like, yep, we're doing this now. I'm gonna watch this for 30 seconds.

• 45:47Lenny Rachitsky?

  I have it pulled up here and I don't, I wanna watch it, but I'm not going to.

• 45:52Lenny Rachitsky?

  That's awesome.

• 45:53Speaker 00

  If only that AI, that's another one. He's out of, he's in France. I think he's in Paris. He uses multiple different tools and models, but he kind of tries to create these dreamscape's and animate them. So he creates, uses one model to create the image, another one to create the video, music, et cetera. He's like very clearly got his own aesthetic. And he's just like, you could, you could think of him as a painter, but like this is his tool.

• 46:18Lenny Rachitsky?

  Is there kind of a vision of AI versus human in the feed? Do you think it'll, like, you said you maybe wanna market, like, how do you think about people? Are they gonna be like AI account, non-AI account? How do you think about, or is that still kind of a work in progress?

• 46:30Speaker 00

  Maybe we'll end up in the same place, but there's a difference between marketing content and marketing accounts, and they're both useful and interesting. So if content was created with AI, I think you should be able to know that. That's hard, by the way, because we can detect that right now, but as these models get better, we might lose the ability to detect that. So we should also be very careful, to be honest with you, about how confident we are in our own sort of assessment. But I think you should be able to just ask, be like, hey, is this AI? And we should be able to tell you, we think it probably is, or we're not sure, or it's definitely not, or it definitely is. I actually think we might be, might be more practical to, to label

• 47:10Speaker 00

  camera captured content, like basically non-AI content as opposed to labeling AI content long term for a couple of reasons. But then at the account level, I think it also matters. There is definitely a new spam vector, which is these fake accounts. Which by the way, an AI creator, that's fine. There's nothing wrong with that necessarily. But there is, there are these spam vectors which are trying to abuse that. And, you know, they're selling like, you know, bogus supplements and it's like an AI monk and it doesn't present it and said, obviously it's an AI. And it's just trying to like take advantage of, you know, a certain aesthetic or a certain sort of stereotype. That we need to figure out how to crack down on that. And so I do think, I do think we should be making sure that

• 47:52Speaker 00

  you know, basically you just need to know, and then you can make your own informed decision. Is the account a real person or not? Is the content a real piece of content or not?

• 48:01Lenny Rachitsky?

  When you think about other platforms in the space, social, you know, content platforms, are there any features or just, or like ways of, of approaching stuff that they do well, that you're kind of jealous of? Or really impressed by?

• 48:15Speaker 00

  Yeah, there's a bunch. Everybody, so many people do so much good stuff. I mean, for me, like, one of the things that we are finally catching up with, but I've been always very impressed with is TikTok and their recommenders' ability to break small talent. In the world of ranking and recommenders and rank, you can talk about exploitation based ranking, that sounds terrible, but it just means like using the data you have. And then you can talk about exploration based ranking, going and trying to figure out, you know, what someone might be interested in that they might even not know they're interested in yet. And it is much easier to move engagement by showing people stuff that you know they'll probably like, because lots of people like it. It's much harder to go and figure out

• 49:00Speaker 00

  how to essentially test content so that we can see like, hey, maybe you, sure, you like Bieber, but you might also like Afro punk. And so we're just gonna like show you some Afro punk and see what happens. If you do the latter, this exploration based ranking, you can, I think it's really good for niche creators and small creators because you give them a chance to find an audience that either wasn't gonna see on them before, or didn't even know that they were interested before. So we've invested a lot over the last couple of years in ranking, not just increasing engagement, but increasing originality, increasing the number of pieces of content that break out, increasing recency to stay culturally relevant. And so a lot of that has been inspired by, by TikTok and ByteDance.

• 49:44Speaker 00

  I think we're catching up. There's actually a couple of those areas where we, I think, by, as we can tell, we're ahead of them. There's a couple where we're still behind, but for, we have line of sight to, I think, being the best in class at recommendations for the first time during my tenure. So that's, I think, and they get a lot of credit for inspiring a lot of that work.

• 50:05Lenny Rachitsky?

  Nice job.

• 50:07Speaker 00

  Well, we'll see. Not there yet. They call me disappointed dad. My team is always like, can you ease up on the disappointed dad? Vibe. So I'm trying to, I'm trying to be a little bit more generous about giving people their flowers.

• 50:22Lenny Rachitsky?

  Like you say that, but that's an interesting common thread across really successful leaders is just never being satisfied.

• 50:29Speaker 00

  Yeah, it's a blessing and a curse.

• 50:31Lenny Rachitsky?

  Here's all the problem. It is.

• 50:34Lenny Rachitsky?

  On this creator piece, I think that's also, you know, people complain about this global algorithm not showing them all their friends, but I feel like this is a benefit of what happens when you do this. Now that you can break new creators into a wide audience, if you have this kind of global algorithmic feed, which is really great for a lot of people.

• 50:55Speaker 00

  I mean, I'm out there talking about a lot of these contentious issues and I get beat up a lot in the comments, which is fine. My main thing here is just to try to communicate that there's almost always trade offs, right? There's, you know, you can't just have all of the things, unfortunately, you know. You wanna have, you know, you wanna never see something you're not interested in, then you're also just gonna see like the most basic, general, lowest common denominator stuff all the time. You know, you wanna discover new and interesting things, you're occasionally gonna see stuff that was just amiss. You know, you know, but this isn't just true about ranking. These, all, all these major debates have trade offs, right?

• 51:36Speaker 00

  You know, privacy and safety, those two things are intention, you know? Do you, do you want a company scanning your messages or not? There's some really significant trade offs on both sides of that debate. And so generally speaking, when I argue and engage in debate with people who feel really strongly about things, I'm not usually trying to convince them. They usually, their mind is usually made up. I'm just trying to enumerate all of the different puts and takes for the rest of the people watching the conversation.

• 52:05Lenny Rachitsky?

  Speaking of getting torn apart in the comments, like, you're so in the middle and thick of all of these really hairy situations, changing the feed, you're like in the Cambridge Analytica lawsuit, all this. You're just like, you're in the center of so much controversy and, is that something?

• 52:27Lenny Rachitsky?

  Oh, man.

• 52:27Speaker 00

  Hello.

• 52:28Lenny Rachitsky?

  Is that just like you, I will lead into this. This is the thing I need to do. Or was it like Zuck being like, Adam, you gotta be the front face of all the stuff and get in there? Like, where does that come from?

• 52:38Speaker 00

  It started on News Feed. So I used to run News Feed at Facebook. And I, my take was that the debate was gonna happen with or without us. So we might as well participate. And so I started being really active on Twitter specifically, because that's where journalists really lived at the time. And I thought it'd be, show some humility to show up on their turf, so to speak. My Twitter ended up being like the most, the darkest place in my life, because I just followed all of our biggest critics. It's not a dick on Twitter. That was just like what I did. And that's where it started. And it kind of slowly built from there.

• 53:15Speaker 00

  For better, for worse, we've become a really important part of daily life for a lot of people. We touch a lot of people. We have a lot of responsibility and there's a lot of change. And there's, with change means there's gonna be anxiety and stress and scrutiny. We've made great decisions. We've made mistakes. We've been criticized for things that I think, we've been criticized unfairly. We've been criticized fairly. And so we just need to accept that this debate is gonna happen broadly. So I just think it's better for us to talk about it and just be clear about what we're doing, why we're doing it. What the trade-offs are. If people disagree, that's okay. We're not necessarily, you know, winning over friends when we talk about what we do.

• 53:58Speaker 00

  But I think over the long run, people are fundamentally more afraid of things that they don't understand and about things where people are more secretive and less accessible. And so I've been tried, I've tried to show up in an accessible and authentic way. And I've made mistakes and I have enjoyed it at times and hated it at other times. But that's kind of how it started. There was also kind of a fun debate in Mark's sort of senior leadership team a long time ago, where we were just talking about how we're a social media company, where we had like a very sort of conventional approach to communication and like press releases. And so why don't we just use our platform? So I was not in that debate, but I stuck myself into that debate, tried to mediate it.

• 54:41Speaker 00

  And I think, but that was also a reason why I ended up getting sucked in. Because Mark was like, all right, well, let's see. Like, why don't you try and see how it goes?

• 54:48Lenny Rachitsky?

  What's something that helps you deal with the hate that flows at you every time you say something that people disagree with?

• 54:55Speaker 00

  You try to put it in perspective, right? You know, like, so it started with, I did a redesign of News Feed in 2009. We launched it, March of 2009 for Facebook. I was a designer. I was a front, like an IC designer, front, you know, entry level designer. And the first comment that came in was something pretty derogatory. It was like, it was like homophobic and antisemitic. It was just like, literally, we're all sitting there. We launched this thing and we're just looking at the stream of comments. And it's like the first one. And it was specifically about, they don't know me, but it was like, what expletive, expletive, censor, censor, designed this shit?

• 55:38Speaker 00

  And I was like, oh, it was me. And I was like devastated. I was like 25 year old kid. And I don't know, I thought about it and I came, I came to this idea that if you spend 30, 40, 50 minutes a day at your desk and you organize your photos there and you wrote letters to your friends there and you read there. And then I just came and I rearranged your desk and I didn't tell you. I didn't warn you. I didn't even explain why. Like, you would be pissed and that would be reasonable. And that was what was happening, just, you know, with millions of people. So I tried to put things in perspective.

• 56:19Speaker 00

  And then I tried to step away from it, get time with my kids, get time outside. There are months where it's really not hard at all. And there are months where it's really, really grinds on me.

• 56:31Lenny Rachitsky?

  Along those lines, there's a famous kind of reversal. When you redesign the feed into this kind of video scrolling experience, there's this whole protest. The world protested.

• 56:41Speaker 00

  Yeah, that was pretty rough.

• 56:44Lenny Rachitsky?

  What was kind of like, okay, wow, we're actually not right and we should go back. What was kind of, what helped you decide, okay, let's change course?

• 56:50Speaker 00

  So actually, that one got, that one, three or four things got conflated. We had a redesign of feed that went to the video viewer. That was a test to 4% of users on iOS. It was a not, it was not gonna roll out. It was just like an early test to get some sense and feedback on the idea. We were also leaning into reels a lot. We were also leaning into recommendations, so posts from accounts you don't follow a lot. And there were also creators who were upset about the fact that their reach was going down and they were blaming ranking changes on that. Those four things got all conflated. We had some pretty big name creators publicly like slap us.

• 57:30Speaker 00

  Then the press covered that creator sort of backlash, which then got more creators doing it. So we ended up with this little bit of like a multiplier effect or echo between the creator community and the press back and forth. But we were never gonna launch that. That was an early test. We were, we knew it was gonna need to work. We actually have continued to grow video and invest in creative tools and invest in ranking and invest in recommendations. And that's driven in the most of our growth in the years since.

• 58:03Lenny Rachitsky?

  Showed them.

• 58:03Speaker 00

  But I think we were pushing, well, I don't know. Does it feel, but like it, I think we were, I think my real takeaway wasn't that we should have not tested that design necessarily. I think we could have been, we could have been done a bunch of things better to explain and maybe move a little fast, move a little slower. I think we were just pushing things a little bit too fast. And when you are responsible for a platform like Instagram, you need to be reasonable and realistic about how much you can evolve it. Now, I would much rather have backlashes like that every couple of years or continue to evolve and continue to stay relevant than the alternative, which would have been like, we didn't have video, we didn't have DMs, we didn't have stories, we didn't have ranking,

• 58:44Speaker 00

  and we wouldn't be on having this podcast right now. But the cost of leaning in is that you're gonna occasionally like make a mistake and you're gonna definitely pay for it.

• 58:58Lenny Rachitsky?

  It's interesting how running experiments now is like very risky for companies at your scale. One person spots it and then I go, shit.

• 59:04Speaker 00

  You kind of need to have a press, you don't need to be proactive about communicating it, but you need to have a calm strategy. Like, we can't, for any, for any design change or any test that could be controversial, we, we talk about it beforehand and be like, okay, not if it leaks, when it leaks, what are we saying? You know, are we, you know, should we talk about proactively? Should we talk about reactively? Either way, what's the message? Because you can't, you can't, you can't launch something to 3 billion people and not test it first. But you can't test something at our scale and not expect people to cover it. And not, and so you have to be ready to talk about it before you even know you wanna launch it.

• 59:49Speaker 00

  So it's, it makes the development cycle more complicated than it used to be.

• 59:54Lenny Rachitsky?

  Yeah. Yeah. Head of growth at Anthropic launched an experiment with pricing and it just went crazy on Twitter. He's like, this will have to, 1% of people were just trying stuff. They're like, no. Anthropic.

• 1:00:04Speaker 00

  Pricing particularly. That one is a real, you gotta be real careful with that one. I've, I've, we've all learned these lessons. We should all share notes more. That's what I think.

• 1:00:12Lenny Rachitsky?

  There's one not to do. How to avoid the internet hating you for the day.

• 1:00:15Speaker 00

  Yeah, yeah. I'm happy to talk to that growth in Anthropic.

• 1:00:20Lenny Rachitsky?

  I think he's all right. He's all right. Okay, I'm gonna take us to two recurring corners on the podcast, fail corner and hot seat corner. Fail corner. What's, what's something that you worked on that was just a huge failure that helped you become better?

• 1:00:33Speaker 00

  Oh, a bunch.

• 1:00:35Lenny Rachitsky?

  So any.

• 1:00:36Speaker 00

  So I'll give you two maybe. So before Instagram, my first project as a PM was on a project called Facebook Home, which was a sort of fork of Android at the operating system level and a, and a piece of hardware with HTC. It was a spectacular failure. I learned way more in that year, year and a half. And I did it any year, I think, probably in my career. Because I was just a design manager before that. I declared myself a PM because the PM on the project quit and I just threw myself headfirst in understanding carriers and OEMs and certification, as well as Android and operating systems and just learned a ton.

• 1:01:17Speaker 00

  So, and I'm happy I brought that project to an end because it had been going on for a long time. And sometimes you, the best thing you can do is execute an idea that doesn't have market fit well and just to decide whether or not the idea was a good idea in the first place. Another big mistake I made during my Instagram tenure was the first version of reels was built on top of stories. Stories had a ton of momentum. This was, I think, 2019. And we were trying to build reels into stories because we were trying to build them the thing that was growing the fastest. But it was not a strong foundation. Most, you know, the read through rate on stories is relatively low. There's way more stories than most people have time to consume.

• 1:01:59Speaker 00

  So most of the reels were never seen and then they disappeared. And if we had the version of reels that we launched in like mid, maybe I think it's like the summer of 2020 and the summer of 2019, I think, I don't think TikTok is in.

• 1:02:17Speaker 00

  I think TikTok is still big and important, but I don't think it's as big as it is now. Because when they really took off was when the pandemic hit and a bunch of people had a lot of time at home and were looking for a little bit of joy and were totally fine with their phone having sound on. And so if you look at the numbers, the 2020 is when they exploded and we were out of position. And on one hand, you know, I'm a designer, I'm trying to not add new things to the product. I'm trying to extend existing primitives and that was the idea. On the other hand, I was wrong. And it's a pretty big fork in the road if you just look at the overall business over the last eight years.

• 1:02:55Lenny Rachitsky?

  We create a lot of economic opportunity in the world, allowing TikTok to grow.

• 1:03:00Speaker 00

  Yeah, it's good. I'm glad they exist.

• 1:03:03Lenny Rachitsky?

  Okay, final question. I'm curious just about your screen time policy with your kids. I know you have three kids. There's a lot of concern these days about Instagram not being great for people, not for kids. A lot of tech executives don't let their kids use devices while they're building the product. As head of Instagram, how do you think about screen time with your kids?

• 1:03:27Speaker 00

  The key thing for me is boundaries. It's also about education and having conversations with them. But my kids are too young to use social media. They're 10, eight and six. But they each have an iPad. They get, they have to earn their time. So they have different ways they earn that time. It's usually about like sitting down to do your homework three times for half an hour each gets you a total of 90 minutes on the weekend. And then they can use that time on the weekend. But you kind of have to set that boundary where it's like you can't just like, you know, it can't just be they ask for it and you give it to them. I think that matters a lot. And then I'm pretty opinionated about what they do on it. Like I approve what apps that they have. I think parents should be approving

• 1:04:09Speaker 00

  what apps to kids specifically are downloading onto their devices. We've been advocating for this at a policy level for a long time at Meta. I think those things help a lot. There are some exceptions. One is planes. It's just like about surviving. I don't know if you're, for those of you who are parents.

• 1:04:29Lenny Rachitsky?

  I'm going to be, yeah.

• 1:04:30Speaker 00

  Yeah, it's like you just like, that's just like, all right, you know, we're flying, you know, it's a 10 hour flight or eight hour flight. It's like, yeah, just, just, you just need to get through it. The other one that I'm starting to experiment with my 10 year old with is, so schools are interesting because I think I'm pretty supportive of a no phone in classrooms. That's happening more and more. I think that's just probably good for education. And I do also know in the world of AI that there's concern about kids using AI and not learning critical thinking skills. And I think that's a valid concern. But I also am worried about kids not learning how to leverage AI and then being sort of at a disadvantage. So that's a balance. I think you need both. So with,

• 1:05:14Speaker 00

  with my eldest, we started vibe coding recently together. He's just loves video games. So I was like, all right, let's make a video game. And so he's made this 19 level platformer game that kind of looks like an eight bit version of Super Mario from when I was a kid. But like each level has its own theme, its own types of monsters. There's a store where you can buy different skins or weapons. And there's like, like, it's unbelievable what a 10 year old who still types with three fingers can do with just, you know, a couple hours of sitting together. But that is more of like a, I want you to learn how

• 1:05:54Speaker 00

  to make things. I want you to be thinking, not just playing games. And I'm going to sit with you and do that. We're going to do this together. So to me, these are the things that matter. Boundaries, scoping it down to the activities you think are healthy for your kid. Every kid is different. But I do think you want your kids to be digitally literate, AI literate, because I think if they're not, they're going to be at a disadvantage. But you also don't want it to be a free for all.

• 1:06:22Lenny Rachitsky?

  This is selfishly useful for me as a, as a, I have a three year old and I'm trying to figure all this stuff out. So this is useful.

• 1:06:27Speaker 00

  Oh, yeah, no.

• 1:06:28Lenny Rachitsky?

  For me to figure out a strategy.

• 1:06:29Speaker 00

  It's amazing. It's a thing. And you're, you're, you're not that far off. You're really just not that far off. It's going to happen in a couple of years.

• 1:06:35Lenny Rachitsky?

  Vibe coding next year. Let's do it.

• 1:06:37Speaker 00

  I couldn't believe it. I tried to do it six months ago and it just totally didn't work. And then now with the newer models, it's been amazing.

• 1:06:44Lenny Rachitsky?

  What's their platform of choice? Are they cloud coding?

• 1:06:48Speaker 00

  Yeah, my 10 year old is using, is using cloud code right now.

• 1:06:51Lenny Rachitsky?

  Amazing.

• 1:06:53Speaker 00

  But we will see. We'll see how that goes.

• 1:06:56Lenny Rachitsky?

  Adam, I'm gonna let you go. Thank you so much for being here. This, you're just like such a gem of a person. It's just so obvious how clear.

• 1:07:04Speaker 00

  I appreciate that.

• 1:07:05Lenny Rachitsky?

  Like how authentic you are and just like how deeply you think about everything. So I really appreciate you being here.

• 1:07:10Speaker 00

  I appreciate you bringing me on. Been a fan for a long time. It's nice to finally get to have a conversation.

• 1:07:15Lenny Rachitsky?

  I really appreciate that. I really appreciate that. Let me just ask you this final question. Ask everyone, what's a way that listeners can be useful to you?

• 1:07:22Speaker 00

  I just think, you don't even have to tell this to other people, but just remember that

• 1:07:30Speaker 00

  this world and technology is complicated and there are almost always trade offs. And you can totally disagree with the decisions I or we make. But just remember that we are people here trying to make these decisions, just trying to do the best we can. And I actually do invite the criticism and the critique and the feedback. But, but know that none of these contentious debates are nearly as simple as most people pretend to make them out to be.

• 1:07:58Lenny Rachitsky?

  Wise words. Adam, thank you so much for being here.

• 1:08:02Speaker 00

  Pleasure. Thank you, Lenny.

• 1:08:04Lenny Rachitsky?

  Bye, everyone. 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.