我们如何为人工智能世界打造Instagram Adam Mosseri Instagram负责人

00:00:00 No,I think taste matters a ton.In a world where it's easier to build things,it's more importantto make sure that your time is spent figuring out what you should be building in the firstplace.The people who I think are going to make the most of it are the ones who are cleareyed about what AI is good at,and what it's not good at,and also have an instinct or a nosefor what it will be good at and not good at.What's something that the Instagram algorithmknows about human behavior that people may not realize?I think people assume thatthere's a much more detailed semantic understanding of everybody's interests andpreferences,and there is is the rise of AI content a headwind or a tailwind for Instagramversus other platforms?I think it's going to be a tailwind,but I think it's going to be achallenge in a world where there's an abundance of synthetic content. 00:00:51 I actually think people are going to seek out creativity and authenticity and people I don'tthink we should filter out. 00:01:00 AI content. I think we should let you know if content is AI content or not and that's hard. Bythe way, where do you think human brains will continue to be most valuable as AI continuesto eat more and more of that product development life cycle? That's a great question. Sotoday my guest is Adam aserri, head of Instagram. Over 3 billion people use Instagrammonthly. That's1 in every three people alive. It boggles the mind. Prior to Instagram, Adamdesigned and lead the early Facebook newsfeed. He also ran the team that built theFacebook 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 ofInstagram. Adam is also famous for being the face of all of the controversy and changes thatcome with evolving Instagram as a product which we talk about. Before we get into it, don'tforget to check out Lenny's product pass dot com for a free year of the most interesting andwell crafted AI products. 00:02:00 In the world available exclusively to Lenny's newsletter subscribers. With that I bring youAdam aseri. Adam, thank you so much for being here and welcome to the podcast. Thankyou for having me excited to be here. You've been doing product for a long time. You get tosee how a lot of teams operate across meta within Instagram. 00:02:21 What is just kind of like the canonical product team look like in 2026? What's kind of mostdifferent today in how teams operate, slash should operate versus say a couple years ago?It's changed a lot this year, so for the longest time at a big company like ours, the canonicalteam was something like two or three android engineers, two or three ios engineers, two orthree server engineers. 00:02:46 Maybe a generalist,APM,a designer,a data scientist.A researcher,if you're lucky.And maybethat's about it,so,you know,on the order of a baker's dozen and that is a function of.Youknow,you want to have for anybody who's writing code,someone who can review their codeand that's who's familiar with that code bases and having these different functions that aremore specialized.You know,I think it's very different at a startup,but this year it'schanging.We've adopted what we call pods,which are just mini teams where it's.Call it fourto six engineers who are a bit more generalists,uh,one. 00:03:30 We call product staff, which is sort of an evolution of the PM, SOA PM who can do some ofwhat a designer does and some of what a data scientist does and some of what a researchdoes, leveraging. 00:03:40 And the latest tools that we have for them and then whatever specialists they need, if they ifthey're doing something that requires a pricing strategy, you need a senior data scientist. Ifyou're doing something that is really novel from an experience standpoint, you need a verysenior product designer. So we try to. 00:03:58 Build a team based on the needs of the work a bit, but then end up with a much smaller corewhich is more on the order of six or seven usually, and that is a very big shift that's justhappening to us this year but they. 00:04:13 Just by virtue of having less people to coordinate, they can often move faster and make uhm. 00:04:20Better decisions uh a little bit less designed by committee, so we talk a lot about you knowAI adjusting and improving productivity and that's part of it but I think another part of it isjust.The small teams I think often are just. 00:04:36 More effective this episode is brought to you by our season's presenting sponsor work OS.What do OpenAI, anthropic, Cursor, vercel, replit, Sierra, clay, and hundreds of other winning companies all have in common? They are all powered by work OS. If you'rebuilding a product for the enterprise, you've felt the pain of integrating single sign on, skimr, backac, audit logs and other features required by large companies. Work OS turns thosedeal blockers into drop in apis with a modern developer platform built specifically