From ChatGPT to Instagram to Uber: The quiet architect behind the world’s most popular products

You built and led Facebook newsfeeds. You've shipped the messenger app as its own app. You launched ChatGPT Enterprise. What's an important lesson you've learned about what it takes to succeed? Building something from idea to one to billions.

You have to plan your chess moves out in advance. You have to really think before you act and build systems that are going to let you go sustainably faster.

What's the most counterintuitive lesson you've learned?

Sometimes your product actually doesn't matter at Uber. I learned this because really the price and the ETA at Uber was the product. Looking at it from a holistic perspective, we humans consume the entirety of the product. It's not to say that you shouldn't fix the bug, but it doesn't have as much of an impact as something that is more important to people.

What's one specific thing you think will change in a big way with AI that people don't think enough about Education.

Is going to change. My son, he was 9 at the time, built a custom GPT that you can type in any topic and it would give you a sentence that had every letter of the English Alphabet. Isn't that mind blowing? I can already see his brain rewiring.

What's one thing you look for in people you hire in six months?

If I'm telling you what to do, I've hired the wrong person. It helps me and the person operate on a different level where the goal is not did you hit this okr? The meta goal becomes are we calibrating enough? Are we actually getting to a spot where in six months you're the one telling me what needs to be done?

What's something you've learned about what it takes to be a great product person?

I think there are five different types of product managers.

Number one is today my guest is Peter Dang. Peter is maybe the most under the radar, impactful product leader that you have never heard of. I often say that the best product people are not the people on Twitter and LinkedIn sharing advice, but the people who don't have time to do that because they are too busy doing the work. Peter is the epitome of this. He was VP of Product at OpenAI where he oversaw product design and engineering for ChatGPT and helped ship ChatGPT Enterprise voice memory, desktop, custom GPTs and more. He also oversaw and built their first growth team. He was the first head of product at Instagram where he worked closely with Mike and Kevin and oversaw all product development including on content sharing, ads, growth, even helped build out their design and user research functions. He was also head of the Ryder product team at Uber where he oversaw everything in the Rider app, including big improvements to pickups and drop offs in Uber pool and airports. He also helped the team launch new products including Uber Reserve, which is now approaching a $5 billion a year business. He also spent nearly 10 years at Facebook as their fourth ever product manager where he built and led the team behind the current Newsfeed product, the standalone messenger app, also photos and groups and homepage and profiles. And he was also Chief Product Officer at Airtable, where he helped the company systemize how they built products and transition to enterprise. He also led product management at Oculus. These days he is General Partner at Felicis where he's able to bring everything he's learned to more founders. As an investor, he has never done a podcast before or shared any of these lessons or stories publicly, so you are in for a real treat. A huge thank you to Eric Antonow, Nick Turley, Lauren Motometti, Joanne Jiang and Sandeep Jain for contributing questions and topics to this conversation. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. Also, if you become an annual subscriber of my newsletter, you get a year free of a bunch of amazing products including Bolt, Linear, Superhuman, Notion, Perplexity and Granola.

Check it out.

Lennysnewsletter.com and click bundle. With that I bring you Peter Deng. Many of you are building AI products, which is why I'm very excited to chat with Brandon Fu, Founder and CEO of Paragon. Hey Brandon.

Hey Lenny, thanks for having me.

So integrations have become a big deal for AI products.

Why is that?

Integrations are mission critical for AI for two reasons. First, AI products need context from their customers business data such as Google Drive files, Slack messages or CRM records. Second, for AI products to automate work on behalf of users, AI agents need to be able to take action across these different third party tools.

So where does Paragon fit into all this?

Well, these integrations are a pain to build, and that's why Paragon provides an embedded platform that enables engineers to ship these product integrations in just days instead of months across every use case from rag data ingestion to agentic actions.

And I know from firsthand experience that maintenance is even harder than just building.

It for the first time.

Exactly. We believe product teams should focus engineering efforts and competitive advantages, not integrations. That's why companies like U.com, aI21 and hundreds of others use Paragon to accelerate their integration strategy.

If you want to avoid wasting months of engineering on integrations that your customers need, check out paragon@use and paragon.com Lenny this episode is brought to you by Pragmatic Institute, the trusted leader in product expertise. Pragmatic Institute helps product professionals turn ideas into impact through proven courses, workshops and certifications designed for real world success. For over 30 years, they've trained more than 250,000 product leaders at companies like Google, Microsoft and Salesforce, equipping them with practical strategies to build and scale market winning products. Pragmatic's full time instructors each bring over 25 years of hands on leadership experience, teaching strategies proven to deliver real world results. And it's not just about what you learn, it's also about who you learn it with. Completing a course connects you to an active community of over 40,000 product professionals. You'll engage in meaningful conversations, collaborate with peers and mentors and gain direct instructor access to refine your strategies and stay ahead of trends. Get 20% off with code Lenny20@pragmaticinstitute.com Lenny.

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

Thank you. I'm so thrilled to be here. Really honored. Looking forward to having a great time here.

As we were preparing for this conversation, we were jamming on what we should focus on. There's so much that we're going to talk about, but something that you said was really interesting and I'm really excited to start with this, which is that you've always felt that you haven't been able to say all the things you really think and feel because you've been within corporations, PR people, keeping on message and this is the first time that you feel free to share.

First time.

Okay, so first of all, just how does that feel?

Second of all, tell us something that you've been wanting to share that you can finally talk about.

Well, it feels really good. So let me ask I love it that you're starting with a spicy question here and let me share some more context behind it. I'm here to speak more freely, but it's not really what you think. I'm not here to divulge any secrets from the companies, but naturally I'm a storyteller. I'm an introvert. So this podcast, I feel like I have the ability to go deeper with you on any topic and add the context because I think without some of the context, some of my spicy takes or whatnot might be taken out of context. And just not having the time pressure, not feeling like there's some, you know, PR message I have to hit is just really freeing. So it feels awesome, really. Anything that is on your mind that you would find interesting to your listeners, I'm here for it. And, yeah. Excited.

Something I always tell guests, and I don't want people to take this out of context also, but I always describe myself as a reverse journalist, where I want the guests to be the best version of themselves. I never want to catch people off guard or just say something they never meant to say.

So that's great.

A safe space. Okay. But still, is there anything that you want to share or that might be interesting to share that you've been wanting to share, that you haven't been able to? Is there anything along those lines?

I mean, I always get this question around sort of, you know, AGI, is it coming? Is it going to solve everything? What have you seen? I mean, it's so interesting because, you know, when I was at OpenAI, it was around the time that people were really scared of AI. And, you know, oh, it's going to, you know, get rid of humans, or it's going to, you know, do all these things. But with every technology, I think everyone's been just kind of taking some time to acclimate to it. And I think with AGI, it's a similar thing, which is it's so far out that everyone's like, well, is it? Is it What? What's our world gonna be like? And the real answer is, like, none of us really know. But in terms of solving problems, I think some people believe AGI is gonna solve everything, but I don't think so. AGI is just necessary, but not sufficient. A lot of the value is still going to require a bunch of hustle from a lot of builders to really turn that new source of energy and channel it into something that we humans want to use that solves some of our problems. And that hustle is going to be required, that elbow grease is going to be required to really make AGI something useful.

Your point is that people think AGI hits. All of a sudden, all jobs are gone. AGI is doing everything, because I think this is a optimistic message that things will be okay if AGI, basically, AGI being. And I'm curious if you have a clear definition, but AGI being, AI being just basically as smart as humans.

Look, I won't claim to be an expert on this at all, but I just. I think that with every technology that's come out, we've been able to harness it, and it takes a lot of harnessing. I think I'm going to use that word very deliberately, right? I'll. I'll use something really basic. What seems obvious today is that, you know, there was a time when databases were all the rage. It's like, oh my goodness, you can store a bunch of data and you can query it really quickly and like, imagine all the possibilities. And I think that a lot of amazing entrepreneurs and builders, you know, built some really great products on top of databases. Right? In fact, that's kind of the basis of all the stuff that we're seeing today. And it seems so obvious today, but I don't know, maybe in 10 years, 15 years when we look back, it's like, of course it made sense that we have this super intelligent thinking machine, but it requires product builders to be able to go in there and say, how do we channel this energy to make it something that we as humans love to use and want to use?

I love the optimism around this. It's just like things will not go crazy once computers are as generally intelligent as humans.

I think that's exactly what I'm trying to say. And I think that again, every technology people have this fear, right? And I remember reading or I started watching a documentary once and they were talking about how when the bicycle came out, people were like, oh my goodness, this is going to be the end of all things. And again, it sounds silly today, right, because you're like bicycles really. But then if you put yourself in the context, in the mindset of a previous generation, which, you know, the next generation will be looking back at this podcast in that previous generation, I think that, you know, again, I think optimistically, things are going to be okay, we're going to adapt. And this was actually one of the things that I talked about with my fresh friend Josh Constein at South by Southwest is this idea that humans will always co evolve with technology. And I think that that co evolution is already happening. If you take a look at sort of, there was a lot of a fear of AI just when ChatGPT came out, but when you start to get familiar with it, that kind of things change. And then you are able to evolve from being fearful to familiar and going all the way to having this mastery of this thing of like, oh my goodness, look at all the startups that are happening now, all the things that we can build, right? And just over 18 months, I would say we look back and there's been an attitude shift, right? And so I guess part of My optimism comes from, if you look back 18 months and you look forward 18 months, like, might it be the same thing for something that we're chasing now?

Let me follow this AI thread a little bit more and then we can.

Move on to other things.

I feel like every conversation there's like a time to AI conversation and it's like, okay, there's other things that also matter. So let me ask you this. The question, what's one specific thing you think will change in a big way with AI that people don't think enough about?

I think education is going to change in a big way and I think a lot about this because I'm involved in my kids school quite a bit. And that's something I've done after I left OpenAI. And what's fascinating to me is that watching my son who got to dog food a bunch of the OpenAI stuff before it was public, I think that was, I think I can safely say that that seems okay. And when he was, was playing with like, you know, ChatGPT and some of the latest models and he's, he's, he was nine at the time. I can already see his brain rewiring, right? He was starting to ask questions and he never heard the word prompt before. But his, like, just this is how awesome the human mind is because he was exposed to this technology at an early age. Some things just are unlocked and I think that you're able to think differently. And I'll give you a specific example of what I mean here. You know, he, you know, he goes to Python class, right? And he's, he's coding now. I don't actually think he's going to have to code when he grows up. I think that's going to be a solved problem. But it's a very, very valuable skill because I think learning to program is learning how to think structure in a structured way, right? And very semantic way, a systematic way. And you know, he was, he, he was prompting ChatGPT with some really crazy things that I never even thought of. And one of the things was, hey, ChatGPT, can you give me a sentence that has every letter in the Alphabet along the theme of oceans or along the theme of space? And the reason this kind of blew my mind is because in traditional programming you couldn't write that program. You can't say to, you know, in, in Python like, oh, write a function that goes and, and formulate. I mean it's a really difficult function to write. But for, you know, him to be able to think of that Prompt, which is really cool because he built a custom GPT that you can type in any topic and it would give you a sentence that had every letter of the English Alphabet. Kind of like the, the quick brown fox jumped over the lazy dog. Right. Like, isn't that mind blowing? It's like that, that he can now at age nine, he could think about that. Whereas being at age nine, I was playing with Legos and like maybe Q Basic. Right. And so this idea of how young humans brains will evolve because of this new tool we have is going to change the way I think we're going to do education. Right. And I'll be very honest, I'm not an expert in education, but I just thought a lot about it and you know, one, one thing I want to be, I think it's going to be really important in the future is being able to figure out how to ask the right questions. You know, we humans are inherently inquisitive, but you know, being inquisitive and turning that into the right questions to, you know, prompt or ask AI, which is going to be again, something that everyone's going to have access to, is going to be a differentiator for sort of what kind of work can be done. Right. And the analogy I'll draw is when the calculator was invented, people didn't stop doing math, they just did higher level math. And it frees the mind up to do other things and think more at a higher level of abstraction. And I think we gotta prepare our kids on thinking about, well, how do you think at a higher level of distraction? And this has happened before, right. I think Google has made memory kind of obsolete. Like you don't have to memorize facts anymore, you can just Google it. Right? And the next phase will be something around, well, code will just appear if you summon it. So what are the things that, you know, people will think about and the skills that develop that are at the next level of abstraction. Right. That tap into our creativity, that tap into our curiosity. That's going to be really interesting. So I think education is going to change dramatically. Just like how progressive education in the past switched from memorization of like multiplication tables into something that's a little bit more kind of higher level, higher level thinking. And I think that's going to be one of those big areas.

This makes me think about an NPR story I was just listening to where they were following professors using ChatGPT to create their curriculum. There's a lot of talk of students using ChatGPT cheating, you know, having ChatGPT write their essays, but teachers are using ChatGPT in a big way. And, and then students are rating professors badly because they notice they're using ChatGPT for their curriculum. So it's kind of this, like, arms race.

Well, well, but it's also interesting because then that's, that goes further that like, you know, the whole system has to change. Right. Because again, I still believe that human brains are inherently inquisitive and that we still need development in some way. But how that's going to develop, I'm fascinated to watch how that plays out.

I want to get back to product. But first of all, I know something that you think a lot about along these lines. This came up in many conversations I had with folks that you worked with is your emphasis on the power and importance of language. Being really good at thinking about the words you use, both in writing and speaking. Just talk about how you think about that. Just the importance and power of language as a leader.

I remember taking this class that really stuck with me in college. It was called Language and Thought, and it was taught by Herbert Clark. And he had this thesis that kind of blew my mind, which is that, you know, language actually affects the way you think. That's one of the parts of the thesis. And I once I heard that and read that in his book and listened to the lecture, I couldn't stop thinking about that because it just rang so true. Right. I grew up speaking Chinese, and I think that there's a lot of things of just the Chinese language that, you know, I feel like I noticed I thought differently when I learned English. Right. And there were some studies around this too. I think that there's a, I think in. I'm not sure exactly if this trap to go check up on this, but I think in Russian there's, there are two different words for like a blue. There's like a greenish blue and a bright blue or something.

Russian and I, but it's like I was, I, I moved to the US When I was six, and so my Russian's not great.

So I'm trying to think of this.

As you say it, but keep, keep going.

Well, I mean, I, so, so then this is great. So I, I, I need to get a way to, to, to, to validate this. But you know, from what I remember, because there were these two different words for this, different shades of blue. Russian speakers who then learned time distinguishing between these two shades of blue than, and a faster time doing so than people who had just grown up speaking English. So I read some studies on that. And also there's some other languages that don't actually have a word for blue, I think. And I think that's actually really hard for them to distinguish over time. So that really stuck with me, and I think that it kind of rings true. So when I. You know, how I put it in practice is that when I make slide decks. I gave a presentation to a class a couple weeks ago, and there were probably a total of 20 words on the entire slide deck. And I spent hours obsessing over them because I really wanted to make sure I captured the right essence of what I was trying to say. And I think that crafting is really important when you're working in product, because if you're sitting down and you're writing a vision doc or you're writing a prd, and if you don't pay attention to the words you use and you're not intentional about it, those have downstream effects, like people might misinterpret things. The connotations may not actually come through. And so I really am very careful about it because I think that there's a multiplicative effect and a downstream effect for using the wrong word. And I really believe in that kind of language affecting thought thesis, which is why I've just really, really paid attention to that. Yeah.

And I feel like AI can help you with that too.

Actually, speaking of AI, actually, that's a really interesting point. I think it's really interesting and kind of poetic and fitting that the breakthrough in artificial intelligence came from large language models. Right. Like, that's. It's interesting to me because, you know, there's. With every word and every sentence, so much of the knowledge is encapsulated and shaped. And when ChatGPT does something really interesting, I tell people it's oftentimes just writing Python code and interpreting it. And Python is a language yet again. Right. So I think that there's something really interesting where, like, the condensation of human thought in language has. Is related to the LLMs and the advancements in area that we have today.

I think it was Ilya on a Dwarkesh's podcast where he was talking about how you may think LLMs are just like, oh, it's just predicting the next word. What's the big deal? But in order to do that, it has to understand the universe and everything in the world that has ever happened and existed and everything anyone's ever written to predict the next word.

Yeah. Love it. Yeah.

Okay, so let me. Let me zoom out a little bit and shift a Little bit to just product in general. Sure, you've worked at and built some of the most iconic products in history. You worked at OpenAI, Facebook, Uber head of Product, and Instagram. So let me just ask you this question and see where this goes. What's the most counterintuitive lesson you've learned about building products or leading teams that goes against common wisdom?

I think one thing that it's a really hard lesson that I learned at Uber, which is sometimes your product actually doesn't matter. And by product I mean kind of the pixels you put on the screen or things that you build in your, in your, in your mobile app. And at Uber. I learned this because it pains me to say this, but really the price and the ETA at Uber was the product. And I think a lot of times people at tech companies think of the product as just this digital manifestation. But looking at it from a holistic perspective, we humans consume the entirety of the product. And I think that's. That was one of the things that I learned. The lessons that I learned that was like really kind of hard hitting, right? That sometimes the pixels don't matter as much as you think. Right. And you fix a certain bug, it's not to say that you shouldn't fix the bug, but it doesn't have as much of an impact as something that is more important to people like a price or NTA. And this happens a lot in, you know, B2B products where it's not just about, you know, how it's great that your product is well loved by its end users but, you know, doesn't make good business sense. Is one of those hard lessons I learned as a very bright eyed, bushy tailed, sort of design based product manager going into Uber. I think the other insight that I had, or rather other thought I had the other day was just the idea that like so many of the tech companies today, this is kind of counterintuitive. So many of the tech companies that are most valuable today didn't really start with any technological breakthrough. They were built on some kind of technological breakthrough and they ended up building a lot more technology. But really a lot of these companies, like Facebook for example, just put in the hard work, right? The elbow grease, especially in the early stages, to take essentially a database of human connections and build something valuable on top of it and keep on polishing and iterating that product and, and coming up with new ones like newsfeed and photo tagging were just, you know, kind of came out of just really paying attention to what people wanted and some of the ideas are super simple and it's not something that came out of the lab. Right. So Uber, for example, took the fact that everyone had these GPS devices in their pockets and they didn't invent the GPS device, but they were able to take that. And the fact that people had cars and people wanted to kind of, you know, get around and there was a human need and they just put the. Connected the dots and put everything together and eventually built a ton of tech to predict the right marketplace and pricing, etc. But largely, like, that's a very valuable tech company, but it's largely an operations company. And I want to give a huge shout out to my colleagues there who run, you know, kind of Uber Eats and Uber Rides from, from a operations perspective. Because truly, like, that was one of the biggest kind of business model hacks that I've seen. Right. And so I think that's, you know, Silicon Valley. It gets lost a lot. It's like, oh, this is a new tech company. Oftentimes some of the most valuable ones are just the ones that are just building what people need on top of existing tech.

This is such. There's so much to say here. I love it. And this is coming from someone that led the Uber Rider product team and worked at Facebook and head of product Instagram. You know, it's like, it means a lot coming from someone like you, not someone, you know, that's like, not in product especially.

Yeah, I mean, I'm just. To go further on the Instagram part. Like, it's. The idea was super simple. It was. It was showing photos and visual sharing, but the craft that Mike and Kevin had in putting in the hard work to get the product just right, that's what made it really take off. Right. That's a great example. I'd forgotten about Instagram, but how could I? But, you know, it wasn't anything that any other company couldn't have done, but it was that product taste that Kevin and Mike had and conviction that there's a certain sort of vibe, if you will, that people wanted and building that and iterating. I mean, and look at it now. It's. It's a, it's a core part of our lives. Visual sharing, they really solved it. Yeah.

I just had Mike Krieger on the podcast, so it's interesting. There's two tensions here. One is just like the product doesn't matter. In a lot of really successful companies, it's secondary to the cars, the drivers, the GPS and the phone. And then on the other hand technology. There doesn't need to be a technological breakthrough for to build a huge business, is there? It's almost like if the, if there's no technological breakthrough, then the product matters. Like Facebook is an example. Basically, it's like a database of connections. But what allowed an Instagram would allow them to be breakthrough. And there was, you know, classically competitors at the time was the experience was a lot better. And then maybe on the flip side, if the, if the.