Adam Mosseri: AI is a tailwind for authenticity

- 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 has been 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. - What's something that the Instagram algorithm knows about human behavior that people may not realize? - I think people assume that there's a much more detailed semantic understanding of everybody's interests and preferences in the algorithm there is. - Is the rise of AI content a headwind or a tailwind for Instagram versus other platforms? - 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 of content as AI content or not. That's hard, by the way. - Where do you think human brains will continue to be most valuable? Has AI continues to eat more and more of that product development lifecycle? - That's a great question. - So. - Today, my guest is Adam Miserie, head of Instagram. Over three 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 news feed. He also ran the team that built a Facebook ranking algorithm and eight years ago, he took over Instagram from its founders Kevin Sistrim and Mike Krieger. He's a designer, turn 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 Lenny's product pass.com for a free year of the most interesting or well crafted AI products in the world available exclusively to Lenny's newsletter subscribers. With that, I bring you Adam Miserie. Adam, thank you so much for being here. Welcome to the podcast. - Thank you for having me excited to be here. - 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 operates, less should operate versus say a couple of years ago? - 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, or a researcher if you're lucky. And maybe that's about it. So on the order of what Bakers doesn't. And that is a function of, you want to have for anybody who's running code, someone who can review their code and who's familiar with that code base and having these different functions that are more specialized. I think it's very different to start up. But this year it's changing. We've adopted what we call pods, which are just many teams where it's called four to six engineers who are a bit more generalists. One, we call product staff, which is sort of a revolution 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 research does, leveraging the latest tools that we have for them. And then whatever specialist they need, 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 experienced 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 AI adjusting and improving productivity, and that's part of it. But I think another part of it is just this small teams, I think often are just more effective. This episode is brought to you by our season's presenting sponsor, Work OS. What to open AI and theropic cursor, Versel, Repplet, Sierra, Clay, and hundreds of other winning companies all have in common, they are all powered by Work OS. If you're building a product for the enterprise, you felt the pain of integrating single sign on, skim, R-back, audit logs, and other features required by large companies. 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And which role are you finding up less of if you're going from the kind of that, if you're going to do percent size? You just have less specialists, right? So you might not have any. You 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 the functions are starting to bleed into each other and the whole industry is wrestling with what that means. A lot of what a data scientist does at a big company, for instance, is relatively mechanical. And so there's stuff that you do that is really more like art and science and the stuff that's really more like just pulling data, data management. So some of the tools that we're building internally to understand, for instance, a traditional data science question would be a waterfall. So if you wanted to look at it, people creating reels, you would look at all the steps and then how people fall off on each step and try to figure whether it 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 pull automatically as opposed to having to have a data scientist too much of a book 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 general, these people have more generalist shapes. And then when you need it, when you really need it, you have a more senior idea or just more creative specialist. So a phenomenal product designer or just a genius data scientist or researcher. - This is so interesting. It's exactly what I just heard. I had a Fiona Fung that had of engineering for Cloud Code and Co-Work on the podcast. She's a force journey's manager and she described the people she liars now are one, builders with great taste that can take an idea from end to end and people deep expertise in a very specific domain. - The tasting matters a lot. I really agree with that. For us, he's the work of Instagram. - Oh, that's great. - Yeah, he was a senior, I see it in screen for a while. I love seeing him, he's all over threads now. It's like he's sort of like the face of a cloud code. - He's killing it. - He's a celebrity now. - He really is. He's his own little thing, 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 has been 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, I've got this other generalists doing design of it, engineers doing design, products after a design. But I'm actually pretty long on design, our designers, because they tend to have taste. And I think that is something that is much more difficult to imagine being automated away. And so there's other challenges with design sometimes, but I'm pretty long right now on designers. - 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 cloud design. I know what you did here, this is codex. - Well, they all have their vibe, right? - You have your vibe code your apps, if you call it vibe, when you're level, like, oh, that's a codex app, or oh, that's a cloud app. - Right, and that's repolate, that's levelable. You can predict these things. Like, I've always thought that too, that design should be thriving, or you know, for some reason it hasn't yet. If you like at jobs for designers, they're kind of flat lining. I feel like the missing pieces, like the PME piece of deeply understanding the business and what will grow it, and what success will, like all that stuff, the business side of it versus the taste side of it. - Yeah, I think you're gonna see, like, you know, we've seen your designer, I did 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 going to just stay in traditionally. of design roles. You know, if you're an amazing designer, you might 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 good and market. And so I actually think some of our strongest product staff are going to be converts from design and from data science who are just looking to expand their reach. And they were influential across functional batteries before, but this world where those functional batteries 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 strong ability in 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 for this 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 I switched roles. 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 GM's. It's like this product staff role feels like a similar situation where different functions can become product staff. Yeah, and that was true of PM before, which is 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 the like a 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. 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 pot teams, product staff, engineers, and maybe one specialist that's going deep on site 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, use a research, for example. You talked about designers being anxious. Is there anything there of just like these, maybe folks in these groups should think about shifting to other roles? I mean, there's anxiety everywhere. I mean, 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 enforcing consequences of all this technology and all this moving so quickly. So that's definitely happening. 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, I see necessarily, but they'll all be either senior or on their way to being senior. 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-seater data scientists in the future. So you need to basically hire and mentor and grow talent. Maybe the team is smaller overall and then 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. It might take. That's it. Who knows what the world looks like in a couple of years. But 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. The Benedict evidence was on the podcast recently said the same thing. We don't know anything about what's going on. Yeah, I like him. I'll make sure I'll consider the pilot. Yeah. So you talked about taste. This makes me think about so you're interviewing a lot of people hiring a lot of people. There are some traits that you're letting 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? 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? You're kind of like you really going to you've got some drives and 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. No, you're not good because if you're those three things, if you got fire in your belly, you learn quickly in your self aware, you can kind of get good at anything eventually. And but if any of those things are missing, those usually an issue. So that's like the baseline. Right now for hiring, but just for I think people who are going to be more successful 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 got to try things, right? This is like, you know, to that point before, that no one really knows what's going on. You just have to be willing to try things. It's almost, I don't know if you speak another language. Russian, yeah. Yeah. So when you learn another language, I think one of the most important things, one of the best predictors is this is my guess. I don't know how many 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 to just say it and be corrected and not be offended and then just get better and better? You just 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 you'll learn, you'll adapt. But if you're not curious, are you not willing to make mistakes or try things? I think you're at a ton of trouble or these things can 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 like this thing across the industry and multiple industries over the next 10 to 20 years. Is there 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 organization 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 that will be less of what I'm looking for and hired because I'm going to have less roles like that. 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 out do like things they were bad at or AI now allows them to do. And now they're thriving. The link, all these things, helping other people. Do you see that all? Just like AI is just like lifting other people out, maybe lowering some people down. Yeah, I mean, the job is just different. I mean, take a take a take engineering. Something used to be, maybe not majority, but a large percentage, 40, 50, 60 percent 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 succeeds is a function of whose strengths are aligned with the tools, needs and the businesses needs. And so, this is definitely happening. 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. You know, it's for me it's kind of funny because when I get hired at Facebook, we all the designers had to be able to program. That was like, I had to, 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. You know, I am not a good engineer. I am a mediocre engineer on a good day. But now I can write code responsibly, which is just an amazing thing. We've seen this across all sorts of levels of seniority and functions. You know, designers who are programming engineers who are pulling data, 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. And the people who I think are going to make the most of it are the ones who are clear at 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, next month or in a couple of months from now. You mentioned that AI writes all our code. Now someone tweeted this, this idea that stuck with me for like months now. I've just like, remember we used to be able to just write code for free. I think just to be able to write code for free, just do with a smaller model. But yes. I guess that's true. That's true. There's a lot of those that are close. to free, but it's like, yeah, that's crazy. Now it's just like, 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 will be one matter. Like, you know, we're getting there, I think, with small projects and programming, 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 that I am. 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 six that always was fable just fine for all of my side projects, probably just fine, probably pretty pretty cheap by then too. Yeah, when Tim and Wells on the podcast, when he was CPU to open the eye, he's, he famously said, this is the worst the model will ever be. Yeah. Yeah, it's still hard to comprehend that. Wow, that's, that's only going to get better. So on this point of token spend, RY and things like that, meta was famous for this like leaderboard of token spend. It's a terrible idea. No leaderboards for token. 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? Right now, we've managed to get the costs rained 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 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. 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 burn rate of a strong engineer might be the same as their salary or the cost of employment. And if in that world, like you're going to probably need to put in some caps, the caps should probably be like a proportional to your sort of, you know, the company's sort of trust in your ability to use them in an RWA 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 going to be in a bit of a pricing war. So we'll see. I think it'll be a bit of a rollercoaster. 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-shoted by AI. Like coding now is steering AI and it's like how often you have to correct it is coding now. And then there's so it's like the software development lifecycle slowly be 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? Taste like we talked about judgment, particularly around strategy, right? Like you're not you might get feedback from an AI on the strategy but you're not asking an 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 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 much script of you want to be about the path to success and then giving feedback along the way. And that is that's own craft. You know when you it'll be interesting to see I've met you know you know 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 and going in the wrong direction. And so that level of autonomy you give a team like maybe that applies to me agents in the future. Particularly when we're talking not 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. Strategy can't be like be the best or be amazing. It has to be controversial that you have to be a reason of a person should be able to disagree with it. So otherwise you're probably just trying to compete on raw execution. And I think that our both vision and strategy I think are going to be where our brains are spending a lot of more and more of our cycles. And I think less on execution. 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. 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. You need to consider the state of the technology. The personnel on the team and what's motivating them and what you can get. Sometimes coming up with an idea that is on the bubble you know it's going to 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 ask an AI just for a strategy lazily you're not going to get something right you're going to get something pretty predictable that pop up with the competition we're expecting 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 steer the AI in a way that it's considering those as well. And it needs to be a conversation in the 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. Different models have very different vibes though on how willing they are to push back. I recommend picking one that likes pushing back. Yeah, mythos has gotten really good at being like I can't tell you this let's move on like there's always been a little bit of a jerk in a way that I actually appreciate. 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. I want I want you know I want the real real sort of intelligence I don't want them to be easier. This point you made about people being excited about the strategy such an interesting one. There's this idea that I read I think Corey Dr. Arothis there's this kind of concept of a centaur and a reverse centaur. So centaur is a human body horse this is going somewhere from us. Human body horse sorry human upper part horse lower part horse body yeah yeah horse body where the human is in charge and that's kind of we prefer that we want to be charged reverse centaur which is what we want to avoid with AI is where the AI is controlling us and we're just doing its bidding. It's a horse head on a human body. Yeah exactly. It's terrifying. Like in a sense like Uber drivers and door dash people kind of this is their life which is not great and this is the danger I think for a lot of people is like like if it's giving us the strategy and telling us here's where we're like no one's and want to do that so that's a really interesting counterpoint to we don't want AI to be telling us the strategy almost. Yeah no 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. This episode is brought to you by Mercury. Radically different banking loved by over 300,000 entrepreneurs and now with command. 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Mercury is a Fintech company, not an FDIC insured bank, banking services provided through choice financial group and column NA members FDIC. 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. One thing that you said about some of the best product leaders you've worked with is that they're less visionary and more curators. I love to hear more along these lines. Yeah, I mean you do sometimes find amazing product leaders who are just like idea machines, just prolific idea machines. But I do think a lot of the best have have taste or have something about them that really makes once makes really strong town when I work with them, but end up sort of being curators. Curators of people, curators of ideas, curators of technologies, curators of strategies. Because 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 get that there is an amazing strategy and everyone is bought into it and that 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. 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 I think it's not just about curating ideas, but it's a sometimes about curating teams and people. I love that. I so agree. I feel like everyone's always joining a team and they just want to do vision strategy. Like not actually hands on work. And no way, I just kept it in here. Let me do the strategy. Yeah, exactly. 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. Yeah. Sometimes it's also sometimes it's not just who's good or what ideas 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? So if I first 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. You know, I need to make sure that those five compliment each other. I need to make and that's, you know, about what skills each one has, what weaknesses one might have. I also need to make sure that they, 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 with out trust or rapport, like anything could become an issue. And so that chemistry bit 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 going to have good energy and good collaboration. Warm and fuzzy stuff. Yeah. Yeah. Well, the flip that is also true, right? Like 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. I want to transition talk 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? 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 and like a seven dimensional space. It's like, and so when we talk about does the algorithm know something, usually we think in these more semantic terms, it knows I like surfing. 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 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. The idea is we take a look at all of the stuff that you've interacted with. And then, you know, we, all of that is in a numbedding space. You can think of a numbedding 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 I can be like, oh, that is like deep, pour over coffee snobbery. And that's kind of amazing. That is so cool. But like you can ask the LLM to look at these numbers and extrapolate here's like the topic that you're interested in. Yeah, or like 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 LLM, right? That's how all the whole thing works. And so, you know, so 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 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. But we will be able to do, you know, you could, there's things that aren't topical that you might ask for. I want more fun content. I want to see my friends more. I don't want to see my high schools, 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 you've heard, you know, whatever your mind can come up with. So we have a lot of work to do. And so we're 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. These people also like these 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 kind of how it worked. Now only now are we actually getting as sophisticated as I think people have assumed we've been for many years. 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 every one 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. 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? There's, but there are a couple of issues with the algorithm with the chronological feed. 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 because it will always be at the top of everyone who follows you's feed as soon as you post. So what ends up happening is that the feed gets overwhelmed with professional content, with usually large company content and publishers because they get, you know, the New York Times can pump out 50 things a day. 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 design these systems, it's almost like designing a city. You need to think about, okay, here's the, here's how the mechanics work. What are the incentives that arise? How are people going to act within this incentives and then what happens? And the other thing is sometimes the most interesting thing was just not the most recent thing. Recent season, important input into relevance, but it's not the only one. My sister got engaged last night and, you know, she's in the generations. But she didn't, if she did, she's married. She got married last year, that's why it was tough for me. But if she got engaged, and I missed it because she lives in Europe and different time differences, do I really want to see a picture of my brother's pobo sandwich? Pobo sandwich? Or do I want to see my sister's things first? So it's tough. I'd love to figure it 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, not pretending that's not an issue, but also for the overall community. Because we've done chronological by default and where you can make a default. And you see, not only does usage go down, overall, sent in that 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 and massive scales. We just see people start to become less and less satisfied with Instagram. Kind of along these lines, everybody asks you about 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? I think it's going to be a tailwind, but I think it's going to be a challenge. It's 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. I don't think we're very good at ranking AI content yet this great AI content, this crappy 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 of sports where players are more relevant than teams now, and that was not the case when I was a kid. In that world, I think it behooves us to invest in individuals and to invest in specifically for Instagram and creators. And I mean, creators broadly. I don't just mean influencers who are promoting brand of content and making native only videos. I mean, anybody who's using platforms like Instagram to help do what they do. It could be a journalist, you could be an artist, you could be selling scarves, you saw. But like you're out there as yourself 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 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 creativity and authenticity and people more, not less. And I think that will help us. That doesn't mean that we won't have AI content on our platform. This is going to be bad and good AI content. And we're going to try and handle that, 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 going to really seek out other points of view. Because 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 their perspectives. And I think that's going to become more important, not less. And I think given that we are 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 going to seek out people. And this connects your earlier point that companies, like St. New York Times 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 those AI content. 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. There's a lot of 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 think we should filter out AI content. I think we should let you know more about the person who posted anything so that you can make informed decisions about whether or not to believe or trust them based on knowing who they are, where they are, or how many times they've changed their profile or, you know, if they're profiles three days old or three years old. But I don't think we should be making value judgments based on what tool you used. Is there an AI content creator you love that you're just like this so good of watching these AI videos? Yeah. What is she called? Plastic, plastic dream sequence? Is that what it is? I think we should-- Check it out. Check it out. Plastic dream sequence. I had it on my phone. I'll do a check. It's these like sort of dolls barbies, but they're like singing songs and these little tiny sounds. Yeah. So though I've seen snippets. And it's just amazing. It's like a little weird, but also kind of amazing. And it's very clearly AI. It's not pretending not to be. But it has a very clear creative and aesthetic point of view. And every time I come by, when I'm like, "Yep, we're doing this now. How am I going to watch this for 30 seconds?" I have it pulled up here and I want to watch it, but I'm not going to. That's awesome. If only that AI. That's another one. 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 dream skates and animate them. So he uses one model to create the image, another one to create the video, music, et cetera. He's very clearly got his own aesthetic. And he's just like, you could think of him as a painter. But this is his tool. Is there a vision of AI versus human in the feed? Do you think it'll-- like you said, you maybe want to market. How do you think about people? Are they going to be AI count, non-AI count? How do you think about it? Or is that still working progress? 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 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. Are we not sure? Or is definitely not? Are definitely is. I actually think we might be more practical to label camera-captured content, like basically non-AI content, as opposed to labeling AI content long-term, for a couple reasons. But then at the count level, I think it also matters. There is definitely a new spam vector, which is these fake accounts-- which, by the way, in AI creator, that's fine. There's nothing wrong with that, necessarily. But there are these spam vectors which are trying to abuse that. And they're selling bogus supplements. And it's like an AI monk and it doesn't present it. And it's not obvious that it's an AI. And it's just trying to take advantage of a certain aesthetic or a certain stereotype that we need to figure out how to crack down on that. And so I do think we should be making sure that you know. Basically, you just need to know. And then you can make your own informed decision. Is the account real person or not is the content or real piece of content or not? When you think about other platforms in the space, social content platforms, are there any features or ways of approaching stuff that they do well, that you're kind of jealous of or really impressed by? Yeah, there's a bunch. Everybody's so many people do so much. Because for me, 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, you can talk about exploitation-based ranking. That sounds terrible, but it just means using the data you have. And then you can talk about exploration-based ranking, going and trying to figure out what someone might be interested in. The thing 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 how to essentially test content so that we can see like, hey, maybe you sure you like Bieber, but you might also like AfroPock. And so we're just going to like show you some AfroPunk 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 going to see 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 the recency to stay culturally relevant. And so a lot of that has been inspired by TikTok and by dance. I think we're catching up. There's actually a couple of those areas where we think, but as we can tell, we're ahead of them. There's a couple where we're still behind, but for we have line of side to eye, I think being the best in class at recommendations for the first time during my time. 10 year. So that's the I think and they get a lot of credit for inspiring a lot of that work. Nice job. Well 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. Like you say that, but that's an interesting common thread across really successful leaders is just never being satisfied. Yeah, it's a blessing in a curse. Here's all the problem. It is. On this crater piece, I think that's also, you know, people complain about this global algorithm not showing them all the friends, but I feel like this is a benefit of what happens when you do this. Now that you can break new craters into a white audience if you have this kind of global algorithmic feed, which is really great for a lot of people. 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 that, you know, you can't just have all of the things unfortunately. You want to have, you know, you want to never see something you're not interested in, then you're also just going to see like the most basic general lowest common denominator stuff all the time. You know, you want to discover new and interesting things. You're occasionally going to see stuff that was just a miss. You know, you know, but this isn't just true about ranking. These all, all these major debates have trade offs, right? You know, privacy and safety. Those two things are intention. You know, you, 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 are engaged in debate with people who feel really strongly about things, I'm not usually trying to convince them. They usually, they're minus 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. Speaking of getting to an effort in the comments, like you're so in the middle and think of all of these really hairy situations, changing the feed. You're like in the Cambridge Analytica lawsuit, all this. Just so you're in the center of so much controversy. Is that something? Oh man. Is that just like you? I will lean into this. This is the thing I need to do. Was it like, suck being like Adam, you got to be the front face of all the stuff you get in there. Like, where does that come from? It started on new speed. So used to run new speed at Facebook. And my take was that the debate was going to happen with or without us, so it 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 would be just a 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. That's not a dig on Twitter. That was just what I did. And that's where it started. And it kind of slowly built from there. For better, for worse, we've become a really important part of daily life for a lot of people. Let me touch a lot of people. We have a lot of responsibility. And there's a lot of change. And there's with change means it's going to 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 debate is going to 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 of sorrow of people disagree. That's okay. We're not necessarily winning over friends when we talk about what we do. 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 tried to show up in a accessible and authentic way. And I've made mistakes. And I have enjoyed it at times and hated it at other times. That's kind of how it started. There was also kind of a fund debate on Marx 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 a very sort of conventional approach to communication and press releases. And it's like 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. And I think that was also a reason why I ended up getting sucked in because Marx was like, all right, well, let's see. Why don't you try it? See how it goes. What's something that helps you deal with the hate that flows at you every time you say something that people disagree with? You try to put it in perspective, right? You know, like so it started with I did a redesign of newsfeed 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 anti-semitic. 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 sensor sensor designed this shit. 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 spent 30, 40, 50 minutes a day at your desk and you organized your photos there and you brought 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. It didn't even explain why. Like you would be pissed and that would be reasonable. And that was, what was happening just with millions of people. So I try to put things in perspective. And then I try to step away from it. Good 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 grads on me. Along those lines, there's a famous kind of reversal when you redesigned the feed into this kind of video scrolling experience. There's a whole protest. The world protested. Yeah, that was pretty rough. What was kind of like, okay, wow, we actually not right. And we should go back. What was kind of what helped you decide, okay, let's change course. So actually that one got that one of 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 in iOS. It was a not, it was not going to roll out. It was just like an early test to get some sense and feedback on the idea. We were also leaning into reals 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. 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 going to launch that. That was an early test. We were all, we knew it was going to be a 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 and met most of our growth in the years since. So that we were pushed. Well, I don't know, just feel like, 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 done a bunch of things better to explain and maybe the 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 backlash just like that every couple of years, but continue to evolve and continue to stay relevant. Then 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. And we wouldn't be on having this podcast right now. But the cost of leaning in is that you're going to occasionally like make a mistake and you're going to definitely pay for it. If interesting, I already experienced now is like very risky for companies at your scale, one person spots it, I go shit. 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 design change or any test that could be controversial, 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 proactive, should we talk about reactivity? 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 in our scale and not expect people to cover it and be, and so you have to be ready to talk about it before you even know you want to launch it. So it's, it makes the development cycle more complicated than it used to be. Yeah, the head of growth that anthropic launch and experiment pricing and it just went crazy on Twitter, he's like, oh yeah. about 1% of people were just trans stuff. Hell, no. - No. - The topic fit. - Pricing particularly. That one is a real, you gotta be real careful with that one. We've all learned these lessons. We should all share notes more. That's right. - Here's someone not to avoid the internet hating you for the day. - Yeah, I'm happy to talk to that a little bit and then drop it. - You 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 something that you worked on? I was just a huge failure that helped you become better. - Oh, bunch. - So any. - 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 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. 'Cause it was just a design manager before that. I declared myself a PM 'cause the PM on the project quit and I just threw myself head first in understanding carriers and OEMs and certification as well as Android and operating systems and just lend a ton. So, and I'm happy I brought that project to an end because it had been going on for a long time and sometimes the best thing you can do is execute an idea that doesn't have market fit well just to decide whether or not the idea was a good idea in the first place. Another big mistake I made under my Instagram 10 year 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 on the thing that was growing the fastest. But it was not a strong foundation. Most, you know, the read through read on stories is relatively low. There's way more stories than most people have time to consume. 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, just maybe we think it's like the summer of 2020 and the summer of 2019, I think I don't think TikTok is in, 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 we're looking for a little bit of joy and we're totally fine with our 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. - We create a lot of economic opportunity in the world allowing TikTok to grow. - Yeah, it's good. I'm glad that exists. - 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 or 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? - The key thing for me is boundaries. It's also about education and being and having conversations with them. But my kids are too young to use social media. They're 10, 8 and 6. But they each have an iPad. They get, they have to earn their time so they have different ways there. And that time it's usually about like sitting down and doing your homework three times for half an hour each, gets you a total of many minutes in 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 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. I have proved what apps that they have. I think parents should be approving what apps to kids specifically are downloading onto their devices. We've been to advocating for this at a policy level for a long time, I met. I think those things have a lot. There are some exceptions. One is planes. It's just like about surviving. I don't know if you've ever, for those of your parents going to be. I'm going to be, yeah. Yeah, it's like you just like that. It's just like, all right. You know, it's a 10 hour flight or eight hour flight. It's like, yeah, 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 classroom 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 about concern. But I also'm 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 my oldest, we started Bob 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 8-bit version of Super Mario from when I was a kid. By 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, well, it's unbelievable what a 10-year-old who still types with three fingers can do with just a couple hours of sitting together. But that is more of like a, I want you to learn how to make things. I want you to be thinking not just playing games and I'm gonna sit with you and 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 gonna be in a disadvantage. But you also don't want it to be a free for all. - So stealthishly useful for me as a, as a three-year-old and I'm trying to figure all this stuff out. So this is useful. - Oh yeah, no, I mean, it's a strategy. - It's a thing and you're not that far off. You're really just not that far off. It's gonna happen in a couple years. - Five-goating next year. Let's do it. - I couldn't believe it. I tried to do it six months ago and it just totally didn't work. And then now with newer models, it's been amazing. - What's their platform of choice? Are they a cloud code? - Person. - Yeah, my 10-year-old is using cloud code right now. - Amazing. - But we will see. We'll see how that goes. - Adam, I'm gonna let you go. Thank you so much for being here. This year, just like such a gem of a person. It's just obvious how clear. - I appreciate that. - It's like how authentic you are and just like how deep you think about everything. So I really appreciate you being here. I appreciate you bringing me on. Been a fan for a long time. It's nice to finally get to have a real position. - I appreciate that. I really appreciate that. Let me just ask you this final question. I ask everyone, what's the way that listeners can be useful to you? - I just think you even have to tell this to other people, but just remember that this world and technology is complicated and there are almost always trade-offs and you can totally disagree with the decisions I are 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 know that none of these contentious debates are nearly as simple as most people pretend to make them out to be. - Why is words? - The pleasure. Thank you, Dany. - Hi, 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 a leaving review as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at Lenny'sPotcast.com. See you in the next episode.