AI Product Leadership Masterclass with the author of The Making of a Manager

Aakash Gupta 0:00 Is the product designer role gonna exist in 10 years? Is the product manager role going to exist in 10 years? So what are the right steps people in those roles should be taking?

Julie Zhuo 0:09 First, let's not think of ourselves as these predefined roles. Let's just actually think of ourselves as builders. ChatGPT, obviously we all know that it's the fastest-growing consumer app to hit 100 million.

Aakash Gupta 0:20 Julie Zhuo spent 13 years as a designer at Facebook, where she started as an IC and rose to become a VP of product design. She also wrote the Wall Street Journal bestselling book, The Makings of a Manager, and now she is an AI product leader working as a founder at Sundial and building products for companies like OpenAI.

Julie Zhuo 0:42 In some ways, I feel like there's a contraction, because the whole promise of what AI enables is that each individual person can do more than they've ever been able to do before. You have to know-

Aakash Gupta 0:52 Yeah

Julie Zhuo 0:52 ... what the AI is doing and whether it's producing exceptional or average work.

Aakash Gupta 0:57 How are you day-to-day building your product sense or your product taste?

Julie Zhuo 1:00 Go and figure out who are the absolute best, and it's much easier these days. You can go on Twitter-

Aakash Gupta 1:05 Mm-hmm

Julie Zhuo 1:05 ... and you can probably figure out, like, who are the best designers on Twitter.

Aakash Gupta 1:08 As you're making that transition from IC to new manager, what are the biggest blind spots?

Julie Zhuo 1:13 I think the first one is that it's really hard sometimes for people to give up the IC work.

Aakash Gupta 1:20 Yeah. What makes a really great product leader in the age of AI? Really quickly, I think a crazy stat is that more than 50% of you listening are not subscribed. If you can subscribe on YouTube, follow on Apple or Spotify podcasts, my commitment to you is that we'll continue to make this content better and better. And now on to today's episode. So today, we are gonna break down everything you need to know to become an amazing AI product leader, and specifically how you can work with design, how you can input into design in a way that's really effective. Julie, thanks for being on the podcast.

Julie Zhuo 2:05 Thank you for having me, Aakash. I'm super h- happy to be here.

Aakash Gupta 2:08 Yes, in San Francisco, meeting in person. After reading your content... I think I've been subscribed to your newsletter for, like, three or four years now.

Julie Zhuo 2:15 Mm-hmm.

Aakash Gupta 2:15 It's like a dream come true.

Julie Zhuo 2:16 You gotta keep kicking me to write more stuff these days. [laughs]

Aakash Gupta 2:21 [laughs] Yeah.

Julie Zhuo 2:21 It's harder and harder to find the time.

Aakash Gupta 2:22 Yeah, right? The consistency part is always-

Julie Zhuo 2:25 Mm

Aakash Gupta 2:25 ... the, the challenge there, and that's The Looking Glass, if you guys haven't seen it. So

Aakash Gupta 2:31 you recently wrote in the newsletter-

Julie Zhuo 2:32 Mm

Aakash Gupta 2:32 ... about the death of product development as we know it.

Julie Zhuo 2:35 Mm.

Aakash Gupta 2:35 Can you break this down for us?

Julie Zhuo 2:37 Yeah. I was really struck by the fact that with all of the innovation that we're seeing in the AI space, that of course it's changing the way that we interact with products. You know, ChatGPT, obviously we all know that it's the fastest-growing consumer app to hit 100 million. And, you know, I, I lived through the time of Facebook back when that was really fast growth, and Instagram, WhatsApp, and now we're just sort of s- seeing an even steeper trajectory. Um, but yet I didn't feel there was enough people talking about what is changing, not just from the product lens for consumers, but how we work. Like, how we as product builders actually go about creating products. And a lot of what I would call the, the kind of current, uh, bar is this idea of these very well-defined roles. You know, there's product designer, there's engineer, there's product manager, there's researcher, there's data analyst. And essentially at these larger or more mature companies, the goal is to get all of these different... You know, you kind of think about it as like, my analogy in my head was, like, Captain Planet, [laughs] if you ever remember that from, like, the '80s.

Aakash Gupta 3:46 Oh, yes.

Julie Zhuo 3:46 Maybe shows my age.

Aakash Gupta 3:47 [laughs]

Julie Zhuo 3:47 But it's like, you know, you have a representative from each of these different disciplines come together to form a group or a pod, and then this pod goes and creates a product. And so, you know, we've, we've gone and we've invested over these last 20 years in building, you know, a very clear type of career ladder for each of these disciplines. Like, I think there's good standard industry-wide understanding of, like, what is a intro-level designer, what is, like, a senior designer, what is, like, a architect designer. Obviously even more true for engineering, which has been around for a long time. I think that's true for product management as well with even your newsletter or the content of people like you, Lenny, and so forth, right? Trying to spread the knowledge of what makes these disciplines what they are. And what I was observing is that that's actually totally changing because of AI. Um, in some ways, I feel like there's a contraction, because the whole promise of what AI enables is that each individual person can do more than they've ever been able to do before. You know, AI can take care of a lot of the lower-level manual work. It can help a lot with even higher-level ideation. Not to mention, it's getting smarter and smarter, so, you know, every year, every six months, we're seeing new models. And so if things continue at this rate, then it's very clear that we're not gonna have to have, like, all six or five or however many of these roles come together to make anything. It should be the case that one person or two per- two people, [laughs] uh, or three sometimes, can have everything that they need to kind of develop a, a entire end-to-end product.

Aakash Gupta 5:26 Yeah.

Julie Zhuo 5:27 And if that's the case, then we really need to redefine what it means to be each of these different functions.

Aakash Gupta 5:33 Yeah. I think that's kind of the existential question [laughs] out there for people in each of these roles. When I talk to them, they're kind of worried, like-

Julie Zhuo 5:41 Yeah

Aakash Gupta 5:41 ... is the product designer role gonna exist in 10 years?

Julie Zhuo 5:44 Mm-hmm.

Aakash Gupta 5:44 Is the product manager role going to exist in 10 years? So what are the right steps people in those roles should be taking to prepare themselves for whatever eventual merging that might happen?

Julie Zhuo 5:55 I think the first thing is to try and see if we can remove ourselves from the identity of whatever role title. Which is hard, because obviously when we start, you know, we wanna... glom onto something, right? And for me, I know there was, you know, I came in, I actually was trained as an engineer. I joined Facebook, I was on the front-end engineering team.

Aakash Gupta 6:15 Oh.

Julie Zhuo 6:15 Uh, but the front-end engineering, engineering team was kind of also the design team. And I remember, you know, some of my earliest questions are always like, "Well, what does it mean to be a designer? What does it mean to be a good designer? Who are the older designers or more experienced designers who can help me?" And, you know, we all wanna maybe learn a craft or a discipline and feel like we know what the lane is. And I think, though, that what this time calls for is for us to try and separate ourselves from those lanes. Like, I actually-

Aakash Gupta 6:43 Yeah

Julie Zhuo 6:43 ... think it's very, very healthy for us to no longer think of ourselves as, "I'm a product manager," "I'm a designer," "I'm an engineer," but actually to think about these as just different skills and experiences. I mean, we all, you know, even within the realm of product management or design, there's different archetypes. It's not like every single designer is the same. We talk about specific skills. This person is really, really strong at visual aesthetics and craft. This person is a great systems designer. This person is a, a wonderful zero to one type of visionary, right? But, you know, that's true in PM, I think it's true in engineering. I'd rather us talk about the specific skills that people have and also how we can use those skills and the fact that we're good at these particular things to then augment ourselves with tools, AI tools, to kind of help us figure out how we build either, you know, the one or two or three-person team that can come together to build something end to end. So first, let's not think of ourselves as these predefined roles. Let's just actually think of ourselves as builders or product builders.

Aakash Gupta 7:46 Yeah.

Julie Zhuo 7:47 I, I quite like that term 'cause I think it's, it's more general purpose. And at the end of the day, the reason we were in that role to begin with was to contribute some of our skills to the art of building, building something meaningful. So think of ourselves as a builder. Think, "Okay, what are the skills that I come in where I am much better than the average, maybe today much better than the AI?" I'm sure there are still things today that, um, all of us bring to the table where we can likely have better taste than AI, which you and I can talk about in, in just a little bit. Um, figure out how to, uh, you know, use that to direct the AI, but then figure out which skills are we lacking that we can then augment either with, um, another person who can complement us or, you know, by figuring out how to perhaps use the AI in a, in a more sophisticated manner. But that's the way to think about it, right? Not in terms of roles, but in terms of skills.

Aakash Gupta 8:42 Yeah. And I feel like one of the important things, if you are a designer or you are an engineer or a product manager, is start to learn the craft of those people in those other roles, right?

Julie Zhuo 8:54 Mm-hmm.

Aakash Gupta 8:54 Ask them questions about, "Well, how are you building this?" What I love to do is, like, shadow people on the job, really empathize-

Julie Zhuo 8:59 Mm

Aakash Gupta 8:59 ... with what they're doing so that you understand what they're specially bringing, right, that's way above average from the AI.

Julie Zhuo 9:06 Mm-hmm.

Aakash Gupta 9:06 I think that that helps the collaboration a lot.

Julie Zhuo 9:09 Absolutely. And I think you're hitting on a really important point, which is understanding what great looks like, what the difference between exceptional versus great versus average versus mediocre or le- less than average. The ability for the eye to discern all of these different sub levels is increasingly important. Because, again, if we have this very smart technology, AI, that can do a lot of things, the difference between the work you're gonna do that's great and the work that's gonna be average comes down to you have to know-

Aakash Gupta 9:45 Yeah

Julie Zhuo 9:45 ... what the AI is doing and whether it's producing exceptional or average work.

Aakash Gupta 9:50 Yep.

Julie Zhuo 9:51 And if you don't know because you've never been exposed to that skill or your eye isn't well trained, then we can only expect you to do the average of what the AI can do, which isn't going to stand out.

Aakash Gupta 10:03 So the critical skill then is product taste or product sense. I think those are the words that people put around it. If you are someone who wants to be that great product leader, how are you day-to-day building your product sense or your product taste?

Julie Zhuo 10:17 I think, um, it is a lot of what you mentioned, which is that you wanna first identify who are the best at this.

Aakash Gupta 10:23 Yeah.

Julie Zhuo 10:24 That's always how I start. If I'm trying to learn, you know, for example, when I started Sundial, and a lot of what we do is data analytics, I didn't, I'm not a data analyst by training, so I know that there's a lot I don't know. The first question is always, "What does amazing look like? Who are the people who do it the best?" And I was lucky to work with my co- co-founder, Chandra, who I think is truly, truly world-class. But one of the things that we spent a lot of time on is him actually try to break things down for me.

Aakash Gupta 10:50 Mm.

Julie Zhuo 10:50 Try to help me understand what is the art of the thing, right? Because every discipline or every, uh, creative skill, when you stretch it out to what the very best looks like, it always is much more like an art than it is a science.

Aakash Gupta 11:03 Yeah. [laughs]

Julie Zhuo 11:04 And so the people who are, like, the masters, quote, quote, or the people who are very, very good at that often, you know, learning from them is, is a lot of conversation. It's a lot of also seeing how they will tackle a problem and break it down and just understanding their thought pattern and, and tr- and from that trying to extract, like, okay, what are the principles? How can I build my own mental model and framework from what does, what great looks like?

Aakash Gupta 11:30 Mm-hmm.

Julie Zhuo 11:30 And so I would say, like, f- go and figure out who are the absolute best. And it's much easier these days. You can go on Twitter-

Aakash Gupta 11:36 Mm-hmm

Julie Zhuo 11:36 ... and you can probably figure out, like, who are the best designers on Twitter. And if not, you know, an easy, an easy tactical way is I go to just one person, like any designer, and I'm like, "Who are the 10 designers that you admire the most?" And they give me a list, and then I will go and, you know, recurse it, go to each of those designers, like, "Who are the 10 that you admire the most? Who are the 10 that you..." And eventually you'll see patterns 'cause people start to converge on, like, which people, um, are, is doing really good stuff. And-

Aakash Gupta 12:03 Yeah

Julie Zhuo 12:03 ... this has, you know, worked for me in engineering or even in a lot of other disciplines. But if you just ask people, eventually you do get a good s- list of like, "Oh, these people are really good." And then what I try to do is I try to look at all of their work.

Aakash Gupta 12:16 Mm.

Julie Zhuo 12:17 I try to read everything that they produced, if they blog, if they got, you know, um, I try to, um, get into their heads a little bit. And really what I'm trying to look for is, like, how do they see the world? How do they think? How do they understand the art of what they do?

Aakash Gupta 12:32 Yeah.

Julie Zhuo 12:33 And if I'm lucky enough, if I do work in that domain, then I wanna show it to those people for feedback.

Aakash Gupta 12:38 Okay. Yeah. Go a step further. Actually reach out to them, get feedback.

Julie Zhuo 12:42 Yes. That's right. Um, or if, if, if, you know, maybe, like, maybe they're like, "Okay, I won't give you feedback, but I'll go and do, like, an introductory meeting," what I try to do is just come prepared with, like, "Okay, help... This is my mental model of, like, what great looks like. Critique it for me. Like, is it right? Are there things that you think I'm not considering?" Um, often, you know, as an example, recently I'm trying to figure out, um, how to do a better job marketing my company-

Aakash Gupta 13:09 Mm-hmm

Julie Zhuo 13:09 ... Sundial, and I reached out to one of the people that I felt was, like, one of the absolute best, um, at marketing. And a lot of what I just sat down with was, like, "Here's my... Like, if I were to hire someone for this role, if I were to assess someone in this role of marketing, these are the specific skills I would look for, and this is how I'm seeing what great looks like. What do you think?"

Aakash Gupta 13:29 Mm.

Julie Zhuo 13:30 And then he totally critiqued [laughs] my mental model, and that was very, very helpful for me, and I felt like I walked away from that conversation with, like, a, a more refined mental model for what great marketing looks like.

Aakash Gupta 13:45 So what if Picasso could do two painting, right? Let's give Picasso something to actually look at one of your paintings.

Julie Zhuo 13:50 Mm-hmm.

Aakash Gupta 13:51 And so you're going to the best, you're showing them. That's awesome. So we've zoomed in, just to recap so far, right? We've zoomed in on the future of product development is changing. The roles are getting more blurred.

Julie Zhuo 14:03 Mm.

Aakash Gupta 14:03 It's becoming really, really important to develop your product sense and product taste, and you do that by talking to the best. Now I wanna zoom back out to just the, the fundamental concepts that you write about in your book, On the Making of a Manager, because there's, there's that temporal component of what's changing-

Julie Zhuo 14:20 Mm

Aakash Gupta 14:20 ... but then there's all this timeless stuff. And I think the timeless stuff, you say it so well. Like, other people, they may know these things, but I think they're gonna get a lot of unlocks hearing you describe them. So let's start with the first one. I put taboo cards-

Julie Zhuo 14:34 Mm

Aakash Gupta 14:34 ... in this book because I feel like some of the things you talk about, they're, like, kinda taboo topics.

Julie Zhuo 14:39 Mm.

Aakash Gupta 14:39 So I want you to break these down for us. So you talk about what is a manager's job, right? And so you talk about your initial v- d- definition of what a manager's job was, have meetings with reports to help them solve their problems, share feedback about what is or isn't going well, and figure out who should be promoted and who should be fired. But what's the real definition of what a manager's

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Julie Zhuo 17:00 To me, what a manager is really trying to do is get better outcomes-

Aakash Gupta 17:04 Mm

Julie Zhuo 17:04 ... from a group of people towards the goal of that group. And so it is very contextual because first of all, you have to understand what is the goal of that group. If this is a group of educators, I'm a superintendent for a school district, my job is to educate kids, like, have basically the highest quality education that I can for the school district and make sure that each child is prepared, right? That's the goal. And so the job of the manager is to figure out how to use the levers, and there's three of them, which we'll talk about, to essentially get this group of people. You know, it's everyone on the school staff. It's, uh, all of the teachers. It's everybody, you know, who is employed by the school district. How do you get them to work together so that you get that outcome, a better outcome-

Aakash Gupta 17:53 Mm

Julie Zhuo 17:53 ... than you would've gotten, let's say, if you weren't there or if, you know, there was another random person who was managing, right? So that's, that's really the, the end thing that we're trying to go after. There has to be something concrete about getting better outcomes from a group of people towards their objective.

Aakash Gupta 18:10 Mm.

Julie Zhuo 18:11 And so now we talk about levers. What are the levers of a manager? And it really comes down to three things. The first is people. Do you have the right people together? Do you have the right teachers? Are y- are you hiring great teachers? [laughs] Are you, uh, hiring the right people to hire those teachers or manage those teachers, or, um, are you hiring the right staff to support those teachers, right? So-People is probably the biggest lever, and the ability to hire people, to set expectations for them, to create role definitions, boundaries, and to be able to performance manage them, including fire them if it's not working, is, is one such lever.

Aakash Gupta 18:50 Yeah.

Julie Zhuo 18:50 So that's probably the most important. The second lever is process. So sure, I might have hired all these amazing people, but how do they work together? Let's say two amazing people disagree. What should happen? How do we make decisions? Are we just gonna argue it out? Are we gonna have three meetings and then make a call? You know, a lot of the, like, how people work together or what are the norms around how w- work happens is what I call process.

Aakash Gupta 19:20 Process.

Julie Zhuo 19:20 Yes. And then the third bucket is just purpose. It's, it's the idea of like, do you have a picture and a vision, and can you get everyone aligned on what we're really trying to do together? Because even if you had great people, and even if they had, you know, all the rules for it, if people are not on the same page about what really matters or what success looks like-

Aakash Gupta 19:42 Yeah

Julie Zhuo 19:42 ... then they're still going to be at odds. So all these three things are really important, and I would say are the levers of what a manager has to be able to get this group to reach their outcome.

Aakash Gupta 19:53 Hmm. So the original definition, the definition that most people walk in with, is like, I have these discrete tasks.

Julie Zhuo 20:00 Mm-hmm.

Aakash Gupta 20:01 I'm giving feedback to people, I'm meeting with them. But the revised definition is start with the outcome-

Julie Zhuo 20:06 Mm-hmm

Aakash Gupta 20:06 ... and then think about how you're gonna use the three Ps of people, process, and purpose to achieve that outcome.

Julie Zhuo 20:13 That's right. Yeah.

Aakash Gupta 20:14 Okay.

Julie Zhuo 20:14 And all of the tasks are in service to being able to drive those outcomes, right? Which is also why, you know, often it's very hard to just judge someone. Like if they seem busy and they're doing all the right things, I always go back to like, well, is the team better off? Are they producing better work, you know? And what, what does a good outcome look like? It, it really only boils down to two things. You're either doing things at higher quality or, or, you know, so quality meaning like, let's say, teachers, going back to our example, right? Quality of education is improved, so like all the students are better off. That's what I mean by, like, the work improves or the quality improves.

Aakash Gupta 20:49 Yeah.

Julie Zhuo 20:49 Or you're doing things faster at the same quality.

Aakash Gupta 20:52 Mm-hmm.

Julie Zhuo 20:53 So you're able to scale, right? So maybe in, you know, same quality, but now, you know, you can do things faster, so everything's more efficient. Um, or perhaps, you know, one teacher can now support 50 students instead of 25 at the same quality. Like that would be another way to think about, you know, we've, we've done better work.

Aakash Gupta 21:11 Hmm.

Aakash Gupta 21:13 And this is truly timeless. Is there anything about AI that's changing how you apply those three levers of people, pers- process, and purpose? Is like... Like, I'm just wondering like, you know, AI agents, how do those fit into all of this? Is that another P asset that you need to think about deploying?

Julie Zhuo 21:29 Well, it's funny because I've actually thought about agents almost like as another person-

Aakash Gupta 21:34 Yeah

Julie Zhuo 21:34 ... in the workforce, right? So you have to pick the right... You know, we talked about people as a lever, and maybe you can, if you add agents or this type of AI intelligence in there, you're like, "Okay-"

Aakash Gupta 21:43 Yeah

Julie Zhuo 21:43 "... well, do I have the right tools or do I have the, the, the, you know, model with the right skill set or whatever it is for my purpose?" Um, process is still really, really important. I mean, we, you know, prompt engineering and the way that we direct AI-

Aakash Gupta 21:56 Yeah

Julie Zhuo 21:56 ... and we help them understand what does the job look like and what does a good job look, you know, and, and all of the work that goes into trying to, in a highly structured way, help them do their best work.

Aakash Gupta 22:09 Yeah.

Julie Zhuo 22:09 It's not that different in my mind with actually managing humans. You know, for example, if you have somebody who is a very early career type of person on your team, you wanna direct them well, and oftentimes that means break things down for them in a way that they can actually be effective. And I find that that process of being able to break down a complex task into smaller and smaller tasks so that maybe this new grad on your team can do it, is not that different from doing that with, for example, an AI agent.

Aakash Gupta 22:39 Yeah. I think LLMs are brilliant interns.

Julie Zhuo 22:41 Mm-hmm. Yes.

Aakash Gupta 22:42 Right?

Julie Zhuo 22:42 Exactly. Yeah.

Aakash Gupta 22:43 Yeah.

Julie Zhuo 22:43 And, and it, it, it, you know, and they, they kind of struggle sometimes with, like, ambiguity or complexity the same way that you might imagine, you know, an intern or somebody who's just doesn't have a lot of experience yet might struggle.

Aakash Gupta 22:56 Hmm. So in the AI era, apply that same skill set. And I really like actually that you have purpose as its own, right? Because for the agent, you need to set the right purpose.

Julie Zhuo 23:05 That's true. Yeah.

Aakash Gupta 23:06 It usually needs to be kind of narrow. [laughs]

Julie Zhuo 23:08 Yeah.

Aakash Gupta 23:08 It needs to be well-defined.

Julie Zhuo 23:08 And it's like almost the first thing, right? You need to tell the, this is the outcome.

Aakash Gupta 23:12 Yeah.

Julie Zhuo 23:12 Like this is what you're trying to do, and by the way, this is... And then you start with usually the process, like this is all what you should do, like or this is how you should work.

Aakash Gupta 23:19 Yeah.

Julie Zhuo 23:20 Right. And then of course, you have to choose the right one. Like are you gonna use Claude for this one? Are you gonna use OpenAI? Like, you know, some are better than others at, at various tasks. Like which particular submodel? Like that to me is like maybe like the people element.

Aakash Gupta 23:33 People. Yeah. And some are like 100x more expensive than others too.

Julie Zhuo 23:36 Yes. That's right.

Aakash Gupta 23:36 So you have that same dynamic as we do with people.

Julie Zhuo 23:39 Yes. That's right.

Aakash Gupta 23:41 All right. So I think the first one, timeless lesson, clearly applies. The second one I have here, okay, so this is, this is a great one. You said, "Whenever a new manager joins my team, my favorite questions to ask in a few months are, 'What turned out to be more challenging than you expected, and what was easier than you expected?'" Talk to us about why those questions are so important.

Julie Zhuo 24:05 I'm a big believer that a lot of human dynamics comes down to what are people's expectations and are we aligned on them?

Aakash Gupta 24:15 Hmm.

Julie Zhuo 24:15 So if there was a way for you to map exactly what was in your brain into my brain, then honestly our jobs would be much easier as humans trying to connect and trying to do things together.

Aakash Gupta 24:27 Yeah.

Julie Zhuo 24:28 But unfortunately, we can't do that. We don't read minds. You have your own, you know, very, very, um, unique worldview, which comes from your own lived experience. I have mine. And oftentimesWe think we might know. Like, I project onto you maybe what I went through. So if I'm feeling a certain which way, I might assume that you do, too, because I assume the world does.

Aakash Gupta 24:50 Yeah.

Julie Zhuo 24:50 But the reality is we are very different. And so questions like what were your expectations, what was different than you expected, what was not, help, help us, I think, calibrate-

Aakash Gupta 25:01 Mm

Julie Zhuo 25:01 ... a little bit more. So try to bring, um, to the surface, like out explicitly on the table, where our mental models might differ.

Aakash Gupta 25:11 Yeah.

Julie Zhuo 25:11 And so for me, you know, my job often when I'm talking to a candidate is I wanna paint for them a picture of what it might look like if they come and work at my company, at Sundial, for example, and ideally I want it to be accurate. Because if it's not accurate, then what's gonna happen is they're gonna join and two or three months later they're gonna be really unhappy because they felt like I presented a false image and the job's actually totally different or, you know, I, I made it seem like it was gonna be amazing in these ways and that they were gonna do XYZ, and then they came and actually the job is ABC and, like, you know, we're- or it's like it sucks, right? Then they're gonna be really unhappy-

Aakash Gupta 25:50 Yeah

Julie Zhuo 25:50 ... and they're gonna lose, uh, or, or leave, and, like, I'm gonna lose them anyways. So it, it doesn't serve me. Um, so I'm constantly trying to test how good is my explanation or my mental model and how well does it match other people's. So if I do hire people and I give them the spiel and they turn and they, they, and they, they tell me, "Actually, you know, this was really much different than what you said," then it's new information for me because somehow my version of reality needs a, a little bit more of, like, a check, right?

Aakash Gupta 26:22 Yeah.

Julie Zhuo 26:22 Maybe it's not accurate. Maybe I'm missing something. Maybe they're seeing something that I'm not in terms of, um, how we might perceive the company. You know, from their vantage point they're seeing all these problems that I'm, like, thinking is, is amazing or awesome or-

Aakash Gupta 26:36 Mm-hmm

Julie Zhuo 26:36 ... you know. Like, so to me it really is always about, like, what are the opportunities that I have to try and calibrate our respective mental models so that we can do a better job of being aligned so that we can go back and, you know, do the thing we're here to do together.

Aakash Gupta 26:50 Mm. And if you're a new manager, what are the things you should be doing to make sure that you are meeting the company's correct definition of what good management is?

Julie Zhuo 27:02 I think a lot of, of, of what I just mentioned, which is bringing up proactive situations-

Aakash Gupta 27:08 Mm

Julie Zhuo 27:08 ... and saying, "Hey, this is what I think, but am I calibrated with you?"

Aakash Gupta 27:13 Yeah.

Julie Zhuo 27:14 Right? So for example, I might come into a company and maybe I see some, a project that I thought is going really, really well. So I might have this concern of like, oh, I think that project is, is totally killing it. That's so awesome. But does everyone else see it that way? Because if I think it's going well but everyone else thinks it's going poorly, then I'm gonna have more and more issues later on as I manage and as, like, you know, I use my opinion or judgment in things. And so a lot of it is about just, like, again, testing that judgment, right? It's almost like, you know, AB test- finding little p- ways of being like, "I thought that project is really..." Or, "I went to a meeting and I thought that that person led a wonderful meeting, so I wanna go and actually bring that up to my manager or bring that up to, um, you know, other people that I trust in the company and, like, I thought that was awesome. Did you guys agree?"

Aakash Gupta 28:01 Mm-hmm.

Julie Zhuo 28:02 And if they're like, "Yes," then I'm like, cool. That, that meant, like, yeah, I'm pretty well, you know, my, my-

Aakash Gupta 28:06 Calibrated

Julie Zhuo 28:07 ... yeah, my judgment was, was, um, in line with where the company is. And if they're like, "No, that was actually

Julie Zhuo 28:12 awful for th- these reasons," then it's a learning opportunity for me to try and understand what is normal or what is good or what is expected in this place.

Aakash Gupta 28:21 Mm. And then outside of aligning your expectations, as you're making that transition from IC to new manager, what are the biggest blind spots people have?

Julie Zhuo 28:33 IC to new manager. I think the first one is that it's really hard sometimes for people to give up the IC work.

Aakash Gupta 28:40 Yeah.

Julie Zhuo 28:41 Because it was a great point of pride. It's something that they love doing.

Aakash Gupta 28:46 Mm.

Julie Zhuo 28:46 And frankly, they're good at it, and maybe they had the best context about it. And so moving to this mindset where you're not just contributing because of your core skill in this area, but you're also being asked to scale, is challenging. Because what I notice is that, you know, as a new manager, and by the way, I don't think... I think this is a great, um... This is, this is actually a really good thing in certain contexts. But, you know, if you look around and you're like, "Oh my God, this particular piece of code is not as good as it could be or needs these changes," and you're a very good IC, you may have this instinct of, "Let me go in and let me fix it."

Aakash Gupta 29:26 Yep.

Julie Zhuo 29:28 But you can only do that so many times because you only have so many hours in the day. [laughs] Eventually what you really need is, like, hey, everyone's just writing kinda shitty code [laughs] and I'm the one going in trying to fix it. This is definitely not gonna scale. [laughs] And so what the, what the manager needs to elevate their mindset to is, like, these are system problems. You know, it's not just an individual example of bad code which I myself can go, "I need to fix the system problem. Why do we have so many instances of shoddy code-

Aakash Gupta 29:59 Mm-hmm

Julie Zhuo 29:59 ... in the team? How do I fix that?" And usually, again, your lever is, like, somebody else needs to play that role. You know, uh, maybe the reviewers aren't doing their thing and, and I need to hold them accountable. Um, maybe I just need to hire better engineers. [laughs] Or maybe I have a better process, right? We need, we're not doing code reviews and we do code reviews. You know, like, I mean, things like that are how you would want the person to start thinking, but it can be tough because some- it's, like, so... Feels, like, so tempting to just go in and just continue to do the IC thing, which will solve the p- the problem in its small, isolated form. But-May miss solving it in a broader and systematic

Julie Zhuo 30:40 scale.

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Julie Zhuo 32:56 I think the first thing that is really important is that you wanna be the kind of team where we can confront reality. And reality, when I say reality, I mean what's really happening on the ground, right?

Aakash Gupta 33:09 Mm-hmm.

Julie Zhuo 33:09 'Cause what might be really happening on the ground is, you know, you have a bunch of customers that don't really love what you're building, or they're, they're unhappy. Or you actually have a team that's not working very well together, and they're not gonna hit their, their, their, uh, deadlines that they set, you know? And so reality is just what it is. This is like what is truly happening on the ground. But what can be tough is that sometimes we don't wanna face reality because it's a problem.

Aakash Gupta 33:35 Yeah.

Julie Zhuo 33:35 You know, we'd rather, of course, all of us would rather be like, "The business is going great. Our customers love us."

Aakash Gupta 33:41 [laughs]

Julie Zhuo 33:42 "We're, we're always on target to hit our..." You know, and, and so I think that if you're the kind of person who maybe almost like holds on a little too tightly to like what is this ideal vision and is not as open to reality, it will be very hard for other people to feel like they can be honest with you.

Aakash Gupta 34:02 Mm-hmm.

Julie Zhuo 34:02 So I would say the first thing, which is how do you get people to trust you, is be the kind of person that can face reality.

Aakash Gupta 34:10 Yep.

Julie Zhuo 34:10 Be the kind of person where it's not, you're not expecting everything to be perfect all the time. You know, you may intend for it. You may wish for it. You may aspire for it, but you don't expect it. And you're the kind of person where given a problem, you're not gonna, you know... 'Cause sometimes, like I think if we get too attached to this vision, "Oh, it should be this way," and then some messenger comes and says something like, "Hey, Julie, we're not gonna go," and, "By the way, you know, this project is really not gonna hit its deadline," I might feel really upset about that because like I have to give away, like I was very happy in my vision that, you know, everything's going to be awesome, and now this is an issue which doesn't match my expect- it doesn't match, like it doesn't match my expectation. And what will happen is sometimes I'll take it out, you know, or it's natural for, for leaders to sometimes take it out on the messenger. [laughs]

Aakash Gupta 34:58 [laughs]

Julie Zhuo 34:58 It's like, "Why did you tell me this?" You know, "Go and fix it," blah, blah, blah, right? But the pro- problem isn't that. The problem is not the messenger. The problem is like this is actually happening, and you just need to be the kind of person that's okay with where reality is and not let it kill your motivation or make you angry, upset, but actually be sturdy. Just be like, "Okay, so that's happening. What do we need to do?" And turn towards action, bias towards action. And I think if you can be that person who, who's collected, who's calm, who even thanks the messenger, like, "I'm really happy that you brought to me an area where my understanding of, of, of how things were going was not calibrated," right?

Aakash Gupta 35:38 Yeah.

Julie Zhuo 35:38 "You helped me see reality. That's a wonderful thing, you know. I appreciate people like you. I hope you do that more often."

Aakash Gupta 35:45 Yeah.

Julie Zhuo 35:45 "Now help me figure out how we're gonna go and resolve this together."

Aakash Gupta 35:48 Yeah. I think you wrote about this link, recently on LinkedIn that like the people that managers value the most bring problems to them.

Julie Zhuo 35:57 Mm-hmm.

Aakash Gupta 35:57 And the hardest part is just creating this environment where you do it. So the tactics you outlined, right? Number one is like control yourself in that conversation [laughs] . Number two is like, as you control yourself, actually thank them for bringing the issue to you. And then number three is like deeply think about solving the system instead of that specific scenario. Did I get that right?

Julie Zhuo 36:18 That's right. That's right.

Aakash Gupta 36:19 Okay.

Julie Zhuo 36:19 Yeah. And also ask the person or the rest of the team for help because I go back to like it's not always your job. You know, ultimately, as a manager, as a leader, you own the outcome. But it doesn't mean you have to be the one to come up with every single solution and every single idea. And in fact, if you think that is you, that, that should have been another thing we talked about in terms of like what's another blind spot that ICs often have.

Aakash Gupta 36:45 Mm-hmm.

Julie Zhuo 36:45 You know, as an IC, you were asked to do this, and it is your job. And so if, if, you know, someone said, "Hey, you're, you're gonna do this project," like it's on you to come up with a solution to that project. But as a manager-There's no rule that says the only solutions are the ones that come from your head. It's very, very, um, common that great ideas are gonna be across the organization, and your job is more to curate and find. Like, you know, a lot of people have great ideas. How do you curate the ideas, and how do you invite everyone else to work with you to be the kind- be part of the solution, be members who can go and, and drive the action that solves the problem that an organization needs?

Aakash Gupta 37:28 Mm-hmm.

Julie Zhuo 37:28 So again, it doesn't all have to come from you. It's not like every single problem is ultimately you're the only person who can come up with, with a solve for it. [laughs]

Aakash Gupta 37:36 Yeah.

Julie Zhuo 37:36 Um, there are some problems that only you can solve, but the vast majority are the kinds of things that, that I think great managers, they- they're humble enough to realize that, like, they should ask for help from many other parts of the organization.

Aakash Gupta 37:48 Mm. And that's probably another blind spot that people have, is you have to be kind of prideful in your craft as an IC, but as you become a manager, you almost need to put the humble hat on, where you're looking for problems, looking for problems in your org instead of just, "We're the best. We're awesome. We're doing great."

Julie Zhuo 38:05 Yes. Yeah, it's a, it's a very delicate balance. I think you can go too far on either side. So on one extreme, to your point, if you're-- You wanna have enough conviction, right? Because it goes back to, like, one of the things is purpose, and a lot of times people are looking to you to at least, if not have all the answers, at least have some kind of conviction in the vision and what great looks like and what are we all here to do and why does it matter. And so I think you kind of have to have some amount of conviction. And a lot of the times the teams gain energy from the fact that there's a sturdy person who has some kind of conviction, if not necessarily, like, I know what the answer is, that I have conviction we will find the answer-

Aakash Gupta 38:45 Mm

Julie Zhuo 38:45 ... some way, somehow. So that is important. I think if you show up and you have no clue what to do and you just don't stand for anything, it's very hard to be effective in that role as, as a leader and as a manager. And so I think that conviction, and to your point, there's some amount of, like, belief, trust, um, you know, pride that comes from you having a good eye in things. That's gotta be there. But on the other hand, if, if it's too far that way, right, and you're like, "No, we're perfect. We're great. There's nothing wrong," then you're not even opening yourself up to reality, as we were talking about before, and that also creates issues because then people are afraid to break your bubble. Nobody wants to tell you what's really going on. And then your image of where the organization is starts to deviate more and more from the reality. And then if you don't have a good understanding of reality, all of your judgments and all of your, your guesses as to what to do will be off.

Aakash Gupta 39:42 Mm. So the north star here is having a really clear-eyed picture of the strengths and weaknesses-

Julie Zhuo 39:49 Mm

Aakash Gupta 39:49 ... of the org that you're managing.

Julie Zhuo 39:50 Yeah. And if-- And I also think that there's-- You know, I, I come from design and it's, uh, obviously a very, very ambiguous, right? Same with product management. These are ambiguous problems. It isn't usually the case that someone says, "Hey, we have this big problem to solve. We have to figure out how to make, you know, people not get confused." It's not usually the case that, like, "Oh yeah, I know what the solution is." But what I've learned through being a designer is that even if I don't have conviction in any solution, I can often have a lot of conviction in a process.

Aakash Gupta 40:22 Mm-hmm.

Julie Zhuo 40:23 You know? And the process is go and talk to customers, understand the problem. If we have a very, very deep understanding of a problem, I have very strong conviction that we'll come up with a great answer, right?

Aakash Gupta 40:34 Mm-hmm.

Julie Zhuo 40:35 Another thing that gives me a lot of conviction is this idea of iteration and moving quickly. I have a lot of conviction that, look, if we understand the problem, we'll try the thing. I may not have a lot of conviction that the thing itself is 100% going to work, but I know that if I get it out there and I get it in front of people, I get their feedback, that I will learn something, and the thing that I learn will help me make a better next version and a better next version. And so a lot of just everything I've learned about, you know, what it's like to operate in ambiguity comes from, I think, a much deeper trust of here's the process of what it is. And that gives me a lot of, I would say, optimism-

Aakash Gupta 41:11 Mm-hmm

Julie Zhuo 41:11 ... for things, that, um, as long as I don't just, you know, get lazy or give up or whatnot, that, like, eventually we'll find our way to something really, really great.

Aakash Gupta 41:19 Mm.

Aakash Gupta 41:21 Wanna move to this next lesson I have highlighted here, which I believe, yes, is feedback. And you talked a little bit about this, right? Managing, performance managing people. And how do you really deliver feedback that leads to positive action?

Julie Zhuo 41:39 So the most important thing is that how we have to talk about what is feedback and why does it matter. And what I think we do for each other when we give feedback is we're kind of holding up a mirror for the other person that reflects back something that we see with the hopes that the other person will then recognize something and it helps them become the kind of person that they're proud to be. So ev- again, go back to, like, feedback is just a, you know, a tactic. What's the end goal? The goal is to help the other person make a change to become a person that they wanna be, so when they look back they're really proud of it. So that's what I mean by, by, um... Well, that's what I think really, really good feedback is. And I, I think both of... You know, if I were to ask you, Aakash, like, what's some of the best feedback you have ever received, it probably has that quality where someone said something, they made you aware of something you weren't aware of, and in becoming aware you change your actions which allowed you to become, um, the person that, that you're happy with or, like, a, a quality that you're happy with, right?

Aakash Gupta 42:45 Mm-hmm.

Julie Zhuo 42:46 So that's what we're trying to do. And so if you think about it, feedback is really a gift. You know, we're trying to do something that helps the other person. So I think the most important thing that helps feedback land well is you genuin- genuinely have to care about the person-

Aakash Gupta 42:59 Mm-hmm

Julie Zhuo 42:59 ... and care about the fact that you're trying to help them.And this sounds really obvious, but I will tell you that even my own experience, there are times, you know, I, with my kids, with my husband, with people at work, where sometimes my motivation for giving feedback is I just wanna be right. [laughs]

Aakash Gupta 43:16 [laughs]

Julie Zhuo 43:17 You know, I just want-- like I, I'm, I feel a little bit peeved. Maybe I feel like there was an injustice, and I wanna tell them how they really pissed me off.

Aakash Gupta 43:26 Mm-hmm.

Julie Zhuo 43:26 In that moment, there's a difference in the feeling, right? The feeling is like I'm trying to get it off my chest 'cause I feel bad and I wanna feel better. I can tell you from a lot of experience that it's unlikely to land [laughs] in the way that I want.

Aakash Gupta 43:42 Yeah.

Julie Zhuo 43:42 But if I can really, you know, give myself a moment, calm down, and think about it, and, you know, maybe the f- the, the substance of the feedback is the same, but now my attitude is, you know, this person really needs to hear it because they may not be aware of the impact that these words have on me, and they'll probably keep saying it to other people, and, and other people will have that type of reaction, and it would help them to be aware of this so that they don't do it again. If that's the i- you, you see the difference is like, you know, the, the substance can be exactly the same, but my mentality makes all the difference.

Aakash Gupta 44:17 Yeah.

Julie Zhuo 44:17 And if I have the second mentality, then the way that I will deliver the feedback, the w- the, the style, the tone, the words I use, my facial expression, my body language is gonna be totally different. It's gonna connote care for the other person. It's gonna connote, or it's gonna, sorry, convey, um, a sense of respect, and it's going to make it far more likely that they're going to hear the message and it will truly change them.

Aakash Gupta 44:45 Mm-hmm. If you have that caring, that empathy, and you don't bring that emotional baggage of-

Julie Zhuo 44:51 Yeah

Aakash Gupta 44:51 ... just trying to do it for yourself, but you're doing it for them.

Julie Zhuo 44:53 Yes. That's the single most important thing, and everything else just naturally, I think, falls into line if that's the mentality that you carry.

Aakash Gupta 45:01 Mm. So it's less about the tactics of delivering sandwich feedback or those types of things, and it's more about the right mindset going in.

Julie Zhuo 45:08 That's the most important. I, I know, I think there are still tactic, tactics. I think a very important tactic is also, you know, I even have like a particular script that I sometimes give people if they're feeling very nervous about giving feedback, and the script goes something like, you know, you start with how I felt. Like, Aakash-- or you start with like a particular fact. When you failed to respond to me after I pinged you four times, I felt, how did I feel? Nervous. I felt, um, rejected maybe. I felt disappointed because it made me think that maybe I was doing something wrong, or maybe you didn't care about me, or whatever it is, right? That's just, that's a general script. So, so therefore, I wanted to bring this up so that I could really understand your perspective and how we can make our relationship work.

Aakash Gupta 46:03 Mm.

Julie Zhuo 46:04 So that is the general feeling of the script. Start with something factual, like this thing happened. How did it make me feel? 'Cause usually this feeling is some kind of negative. I felt worried. I felt rejected, again, disappointed, et cetera, et cetera. Why? Well, I felt that way because I assumed XYZ.

Aakash Gupta 46:21 Mm-hmm.

Julie Zhuo 46:21 And so now my goal is to bring this to the table and just try and see if, you know, my assumptions are right, or maybe they're not, or like, how, how can you help me, essentially? Like, and help and be a part of working this out with me because I really value our relationship, and I wanna make sure that we can grow in our trust of each other and the way that

Julie Zhuo 46:43 we can work together.

Aakash Gupta 46:44 So those are four of the timeless nuggets-

Julie Zhuo 46:46 Mm

Aakash Gupta 46:46 ... that I thought we had to cover here because we're trying to cover everything it is people need to know to be a good AI product or design leader. So bringing it back to that, how is AI changing product and design leadership?

Julie Zhuo 47:01 I think the first thing is that it is a time of great uncertainty. I think we have to acknowledge that. I think, you know, you started by saying a lot of people are really nervous. Will my role still be around in 10 years? What does it mean for me and my career? You know, we're, you know, you and I are talking about, uh, roles blending, and, like, it's, we're not gonna have these, like, very, very well-defined career ladders as we used to have in the past. Like, what does that mean? And so I think the first thing that leaders have to understand is that there's a lot of uncertainty, and people might rightly be nervous, and they don't know what to expect. And so I think sturdiness is really important.

Aakash Gupta 47:39 Mm.

Julie Zhuo 47:39 Sturdiness being the quality of like-- like I think a lot about like a willow tree, which is the type of tree that is very, very strong, but the limbs are quite flexible. Right? So it's a sturdy tree, but it isn't brittle.

Aakash Gupta 47:53 Mm.

Julie Zhuo 47:54 It's not like you snap it and it breaks. And I think that's kind of the feeling that we need to convey, that, yes, it's a time of change. We're not trying to deny it and that things will change, but, you know, let's go back to like what principles, what are the true principles, um, that keep us together? Uh, you know, and, and I think every company or every organization that's trying to do good work has those principles, which is what are we here to do? What's our outcome? What's the vision? And if we have all of these great tools and this better technology, then, like, might we see it as an exciting time rather than just a purely fearful/negative time? So I think a lot of it about it is like acknowledge where we are, but also use that as an opportunity to create a new narrative-

Aakash Gupta 48:39 Mm-hmm

Julie Zhuo 48:39 ... for like what, again, goes back to like what greatness looks like and how it can help, how all of this change can likely help us achieve or, or, or get to the outcome that we're all here to do. So, um, I think acknowledge the uncertainty, take the time to craft like a new narrative, help people understand like what really matters and what are the things that are timeless even despite this change. And I-- the third is be very experimental.You know, going back to our analogy of the willow tree, this is a time for experimentation. This is not a time when anyone, including me, can sit here and be like, "You know what you need to do? It's like A, B, C, D, that those are it. If you do it, you're gonna succeed." I think it's ... I think all of us have to take this mindset of like, yeah, we can all get great ideas from a lot of places, but we have to try them, and we have to see how it works, and we have to iterate our way. So, um, as an example, you know, we mentioned, uh, just to take this example of like maybe some teams today are constructed where you need one of each of these roles in order to be able to have a team that can go and, and, and operate. Well, is that really true? You know, could it be the case that we might just have two people work on something, and could they ship it end to end? I don't know. It's an experiment. Let's try it. Let's see what we learn. And from the learnings, you know, again, it's probably not binary. We'll learn something. We'll, we'll evolve it. Okay, so, um, how should we piece together the working groups or pods of the future? And I think framing everything as this is an experiment, and we're gonna try it, and we're gonna ... You know, this is how we're gonna set up the experiment, but then this is what we're going to n- notice, or this is how we're gonna debrief on it and take away the learnings. Like, I think that we, we have to kind of embrace experimentation and iteration in this, in this period, you know? And it's not following tried and true playbooks of the past. It's like all of us trying to adopt new things, try this thing, try that thing, and then figure out for ourselves what's gonna happen.

Aakash Gupta 50:37 Mm-hmm.

Julie Zhuo 50:37 And I always ... I felt like the best companies have always kind of carried a little bit of that, right? Not every, um, you know, e- every company who's kind of gone and, and innovated in the way that they work has, has, has kind of had that sense. I just think more companies have to be forced to do that now, um, because we're in a time of greater change.

Aakash Gupta 50:56 Yeah. Start from the first principles of the talents you have and the things you need to accomplish instead of, okay, these are the traditional titles that I would put against a problem to solve a problem. Be experimental with how you're building your teams.

Julie Zhuo 51:08 Mm-hmm. Yeah, and then also I think that leaders have to try and really pay attention to, like, what are the mental models that people are carrying, 'cause they may be older mental models.

Aakash Gupta 51:20 Yeah.

Julie Zhuo 51:20 Right? And if it's ... You know, it goes back to, like, if your mental model is very different from mine, then we're definitely going to, uh, be at odds, uh, on one decision or another somewhere down the line. And so I think we have to be very clear, like, what are people's mental models, and let's just make them explicit and be able to actually have, like, open discussion about, like, okay, no, that was the old mental model. Now we're gonna try a different way, and that does mean we're gonna have to, you know, do things differently. I think when people's expectations are set that like, yeah, okay, we are gonna do things differently or ... You know, um, and one example for me is, like, you know, we ran a hackathon recently for, um, for our team, and I was really blown away by all of the different ideas that came out of the hackathon. And they ... And, and people felt, like, far more empowered, or they were like, you know, one or two people were able to build so much more, especially using all of these AI tools. And it was interesting because it almost felt like people had permission to do a lot of things that maybe they, they didn't feel like they did, they had, um, when it wasn't hackathon time. And that was quite surprising to me because I didn't realize that, like, there's a different mental model. Um, 'cause for me I'm like, oh, aren't we the kind of company where everyone can just have an idea and do it and ... If they wanted to. But I think for everyone else, like, actually the mental model sometimes can very, can be very unconscious in terms of like, well, what does the day job look like versus, like, what does hackathon look like, right? And, um, and how do we, you know, bridge the gap, or how do we become explicit about the fact that that is actually what people think?

Aakash Gupta 52:48 Yeah. Very

Aakash Gupta 52:49 ... I think a lot of people feel that way coming out of hackathons. It's a really good tactic probably [laughs] for-

Julie Zhuo 52:54 Yeah

Aakash Gupta 52:54 ... creating a little bit more of that ownership mentality.

Julie Zhuo 52:57 Yeah.

Aakash Gupta 52:58 A little bit more of thinking of the ideas instead of just being handed them. So we talked about these ... Those elements that you just highlighted, I think that's gonna take you to modern product design leadership good stuff. What makes a really great product leader in the age of AI?

Julie Zhuo 53:18 I think a really great product leader is somebody who is pretty, you know, is, is very, very solid in, like, things like what is the problem that we're trying to solve, what's the mission, you know, what's ... What are we here for? So all of those principles, those core principles of, like, understanding the problem, the customers, the user, that continues to be true. That was true then. That's still true now. So I'm, you know, saying that-

Aakash Gupta 53:44 Yeah

Julie Zhuo 53:44 ... that still continues to be, um, somebody that or a person needs to kind of have that. I think the second is what I mentioned. Like, I think you have to be very much, um, a learner. So there's a lot changing about the world. I think you kinda have to be at that cutting edge. Like, if you don't understand where technology is today, it's very hard to say that you're a great product leader in the age of AI. You have to understand the tool, and that just means all of us, you know, who are trying to be good product leaders, like, we need to be building things with these tools. We need to be using the tools. We need to be the first people to have switched our habits-

Aakash Gupta 54:22 Mm-hmm

Julie Zhuo 54:22 ... um, over from what they used to be. We're the ones who need to throw away our old systems of working and use them as an opportunity to, like, test what this new generation of tools has to offer, right?

Aakash Gupta 54:36 Yeah.

Julie Zhuo 54:36 I even say that as somebody who, you know, have a very traditional way of, like, writing, 'cause I love writing. And I realize, no, but the world is changing. Like, I need to actively disrupt how I-go about writing or communicating, even though that's something that I felt like I honed and maybe I thought I was, like, getting reasonably good at. But all that is changing because, like, that's, like, people are gonna do it differently and if, like, I'm not there in the trenches, like, actively trying to figure out how these things are changing, like, why would I expect anybody else on my team to, to, to do that as well? So I think, like, leading by example and being, um, at the forefront of using things and disrupting our old habits and, and ways of doing things is also really, really important. Um, I think the third is, as we said, ex- you know, um, the kind of experimental, being able to direct and lead a team through this period of change and, and, and nimbleness, flexibility. I think that's really important. Um-

Aakash Gupta 55:33 Mm

Julie Zhuo 55:33 ... I, I think that all of us just going back to, like, we're all beginners here again, right? Going back to remove our identity from what it was that got us here. You know, like I'm sure many of our listeners are, are very esteemed and experienced product leaders, but even that idea of, like, we're good product leaders almost feel like let's throw that out, out the window.

Aakash Gupta 55:54 Mm.

Julie Zhuo 55:55 Are we actually really good product leaders in this new era? I don't know.

Aakash Gupta 55:58 Mm-hmm.

Julie Zhuo 55:58 I think we have to earn that. You know, we have to almost go back to, like, being a beginner, get back on, um, in the ring, build some things in this new way, and actually earn the stripes again to be considered somebody who is a great... I, I don't know if I'm a great product leader-

Aakash Gupta 56:14 Mm

Julie Zhuo 56:14 ... in the era of AI.

Aakash Gupta 56:15 [laughs]

Julie Zhuo 56:16 I hope I can be. I hope I, you know, I, I wanna go back and, and, and, um, like I, I every day try to show up and, and do these things, but I can't say that I am yet.

Aakash Gupta 56:25 Mm. With that in mind, staying humble, what are the right tools? Let's say I'm a product leader and I haven't really embraced those AI tools. If I wanted to catch up to the latest in August 2025, what are those AI tools I should be using in my work?

Julie Zhuo 56:41 Oh, I mean, [laughs] there's so much.

Aakash Gupta 56:43 [laughs]

Julie Zhuo 56:44 I mean, the default one that, um, I'm sure you know i- is, is already well-known is, like, all you do is just use ChatGPT-

Aakash Gupta 56:51 Mm-hmm

Julie Zhuo 56:51 ... and you just incorporate way more of that through your workflow. To me, it's, like, less about tooling and more about when we use it, right?

Aakash Gupta 56:59 Okay.

Julie Zhuo 56:59 I think there's a lot of things, and I have to catch myself daily, where I have this idea, my first instinct is to just do it the way I would've done it. Like, I'm gonna create a doc. I'm gonna go in and actually create, you know, the Slack post. And now even the idea of, like, wait, can I get feedback first from ChatGPT? [laughs] You know, can I run my high-level thinking and ask it to poke holes at my mental model or my assumptions? [laughs]

Aakash Gupta 57:24 Yeah.

Julie Zhuo 57:24 You know, can I ask it to, like, read anything that I write and, like, just tell me what it, it thinks, like, I'm, my blind spots are from, from, you know, reading this? Can I ask it to analyze, like, you know, a bunch of, um, uh, emails and, and tell me patterns in terms of, like, what am I not s- I mean, even just the idea of thinking about all of the ways in which we can get value, like, I'm sure that for me, I'm barely scratching the surface of-

Aakash Gupta 57:51 Mm

Julie Zhuo 57:52 ... conceptualizing the ways that I could use even that particular tool, right?

Aakash Gupta 57:55 Mm-hmm.

Julie Zhuo 57:56 So that's probably one of the first things is, is, um, even if that's just your tool and you're just like, "Okay, how can I use it to its maximum extent?" I, I think we're quite far from it-

Aakash Gupta 58:04 Yeah

Julie Zhuo 58:04 ... like, in, in most of our day-to-day lives. Um, I think, but you know, I think then there, there's building tools. Like, I use a variety. I use Cursor a lot for-

Aakash Gupta 58:14 Mm

Julie Zhuo 58:14 ... prototyping and building. I've also used Lovable. I've also used... Like, I've tried to actually use a lot of different tools 'cause I'm trying to understand, you know, going back to understanding people. Like, if you're gonna go and you have a role, you'd probably wanna interview multiple candidates for your role, for that role so you can kind of understand what are the strengths and weaknesses of different candidates. And I kind of have that approach with a lot of tools. So I try to use as many as possible for different things so that I can get a sense of, like, what is the strength and weaknesses of that tool? What is the, um, you know, what, what's the kind of personality? Or sometimes it's even stylistic. Which one just sort of resonates with me or fits the way that I wanna work a little bit more? Um-

Aakash Gupta 58:52 Yeah

Julie Zhuo 58:52 ... so, so I, I do try and, like, just even if I have, like, a new task and, like, yes, I could have done that in Cursor, sometimes I'll be like, "Well, let me use v0 for that. Let me just try this. Let me try this," and then, you know, build up a little bit more of my knowledge. Um, and so that's, that's... I use, um... What else do I use? I use, uh, yeah, like recently I started using, uh, Claude Code.

Aakash Gupta 59:14 Yeah.

Julie Zhuo 59:14 Um, I was just trying and experimenting with that. Um, I love Granola-

Aakash Gupta 59:18 Mm

Julie Zhuo 59:19 ... for meeting notes.

Aakash Gupta 59:20 Yeah.

Julie Zhuo 59:20 I do a lot of meetings, and so, um, I think that's a fabulous tool for, uh, helping me. It just takes away that whole, like, taking notes and summarizing and, and makes the workflow really, really easy. Um, obviously use my tool, Sundial, for data analysis, even, even in, in- including, you know, how we think about what's going on with customers or, like, our sales leads. Like, we use Sundial for, um, for internal analysis as well. Um, yeah, and I try, you know, I try to be, you know... Like, I'm, I'm just very curious about other things. Like, I got, um, the... Oh, I forgot the name. I'm really bad with names. Uh, there's, like a, like a cleaning robot-

Aakash Gupta 59:58 Hmm

Julie Zhuo 59:58 ... recently. Um, so little examples of, like, even hardware, other things. I just, I'm, I'm very curious to try this. Oh, another one is, like, a, a pendant. I don't have it with me today, but, like, Limitless Pendant.

Aakash Gupta 1:00:09 Hmm.

Julie Zhuo 1:00:10 Um, that one is really o- it- it's basically like a little clip, and it just hears all the audio that's going on. I really like to use it at home with my family and my kids because it gives me feedback on my parenting.

Aakash Gupta 1:00:22 Whoa. That's amazing.

Julie Zhuo 1:00:24 Yeah.

Aakash Gupta 1:00:24 I need that.

Julie Zhuo 1:00:25 Yeah. It's, it's pretty cool. So, so, um, and you know, a- and everything gives you a little sense, right? Like, even... Like, I wouldn't have expected it. I, like, got it. I was like, "Oh, this is kind of cool." I wasn't thinking that, like, oh, the use case is that it'll actually help me be a more aware parent.

Aakash Gupta 1:00:39 Mm-hmm.

Julie Zhuo 1:00:40 But sometimes it will say things like, "You know, maybe you should let your kids talk a little more because, like, you direct... You said this thing, and then, you know, they started talking and you kind of cut them off."And I was like, "Whoa." [laughs]

Aakash Gupta 1:00:53 [laughs]

Julie Zhuo 1:00:53 And, um, and that's really awesome.

Julie Zhuo 1:00:55 Yeah.

Aakash Gupta 1:00:55 Wow. Analyzing your own conversations.

Julie Zhuo 1:00:58 Yeah.

Aakash Gupta 1:00:58 How should product leaders be using AI data tools?

Julie Zhuo 1:01:01 How should... I, I think, so my answer to a lot of your questions have had this pattern of like, well, what first, what are some of the principles that are-

Aakash Gupta 1:01:08 Yeah

Julie Zhuo 1:01:08 ... like timeless, right? And then how do we think about the tooling layer on top of that? Um, I think a lot of what I'm seeing right now is that we see a lot of huge organic growth because there's so much market pull for the next generation. I mean, we see that with ChatGPT in terms of its growth. Obviously Cursor, Replit, like, there's these, you know, companies are scaling faster than ever because they've unlocked something really remarkable, which has made it so that, you know, it used to be only people who could code could code, but now lots of people can go and actually create an app. And it used to be, like, only certain people could answer medical questions or, you know, pay for a therapist, and now you've, like, got a tool that can kind of do that, right? And, um, and that's awesome because you, you know, you see, like, a lot of organic growth. But I think what's important with, with, um, any sort of analysis is, like, the whole point of data is to give you a better view of reality and what's going on. And so it's not always just like, oh, if things are going well, then you don't need to look at the data, right? I go back to, like, the best teams that I've ever seen use data are the ones in which people on the ground are, like, absolutely fanatical about trying to understand what is the real phenomenon that's happening, um, and, and in as much texture as possible.

Aakash Gupta 1:02:24 Mm-hmm.

Julie Zhuo 1:02:25 And so the texture can come, you know, from, like, talking to your customers. Like, if you talk to your customers all the time, you're gonna get a lot of texture about, like, what's working, what do they hate, what do they not. That's... I consider that data. But I also think that's true quantitatively as well, which is like, what are people doing? What are they clicking on? You know, how much time did they spend? What are the use cases are... Which use cases are growing for your tools, which aren't? And a lot of times, you know, you, like, I talk to a lot of these startup founders and, like, they don't actually know. They don't have... They know, like, they have maybe good texture if they talk to their customers, but they don't always know exactly, like, what's happening in the product because it isn't instrumented, and even if it is instrumented, it isn't, like, brought together in, um, in an operational model that's easy. Like, I als- I think about everything as like this is just observability. So good analytics is observability for your business, and the more refined your model, meaning the more things you log and track and you understand which metrics impact which things, the easier it is for then if, like, you know, something starts to go off, you catch it early, right? You don't wait until, like, oh my gosh, growth has stopped or stalled. You catch it when the trend is starting early. So that would be, you know, what I would say to everybody who, you know, even if you're growing like a rocket ship and things are going really well, you gotta ask yourself, how much do you really understand about how all of the different users are using the product? And the narrower you can go, where you're like, which kind of user? Which use cases are growing well? Which features are being used? Um, what's the, you know, trend or the impression? What's the conversation in the marketplace about, right? There's a lot of really great tools that can help you now get more and more of that color and that fidelity, but even the best tools won't matter if the person doesn't feel like they want to get exposed to that, those things, if they want to actively be looking for those things. And so it still goes back to, like, you have to be the kind of person who's absolutely curious and maybe fanatical about just understanding reality.

Aakash Gupta 1:04:24 Hmm. I like how it came full circle back there. So we talked about this a little bit. We talked about the importance of taste, and we talked about, and you previewed, what happens when AI has better taste than you.

Julie Zhuo 1:04:40 I think it's coming. [laughs]

Aakash Gupta 1:04:42 [laughs]

Julie Zhuo 1:04:42 So here's... Let's zoom back. This is what I think is the state of the world today, right? AI is, I would say, maybe in the s- 70th or 80th, um, of, of a lot of... So it's, like, probably better than average. It certainly is average in terms of the, the content that's online about a lot of stuff. It's probably a little bit biased towards, like, you know, um, more knowledge because, like, the kinds of people who write the stuff or, or, you know, write books about it is, like, maybe, um, uh, uh, ha-has structured it or kind of has, like, a little bit more, um, uh, depth of understanding. But it isn't usually great at, like, the cutting edge today, right? And that's true with, um, design. I think that's true with, like, uh, you know, the engineering. It's true with even writing. Like, it's not as good as a Hemingway or a C.S. Lewis or, or any of that. Um, and so it, you know, we can say that it's, like, slightly better than average on a lot of stuff. And so, um, so, so then if we look at, okay, like, well, let's say I'm an individual. There's certain things that I think I've, um, you know, invested a lot of my time and energy into, and so maybe I can do better than AI, but there's, like, a whole lot of stuff that I'm worse than where the bar is. And so if I'm worse where the bar is, then AI's actually doing better than me, and I should just kind of trust it more and use it more, right? So examples for me include things like, um, uh, anything that's related to go-to-market. Like, I'm kind of a noob there, and so all of its ideas that AI has for me is, like, clearly better than mine, so I should probably follow more of that [laughs] and not just rely on my own instincts.

Aakash Gupta 1:06:17 Hmm.

Julie Zhuo 1:06:18 Um, similarly, you know, maybe drawing or illustration. Like, I think I draw fine, but clearly, like, it's doing much better than me, um, already in terms of, like, what Midjourney and other things can create. So like, cool, I'm gonna use that, and I'm just gonna go with what its recommendations are, and maybe I can continue to develop my eye, but I know it can certainly, um... There are areas where, like, look, I can just kind of trust it a little bit more. Um, and if I don't trust it enough, I'll try and, like, go back to, like, find the expert who can, who's still a human, and, and have them help me out.

Aakash Gupta 1:06:48 Mm-hmm.

Julie Zhuo 1:06:49 Now, in areas where I think I'm still better than AI, I think a couple of things. The first is I should assume that with the rate of change, one day AI will have better taste than me. [laughs]

Aakash Gupta 1:06:59 Mm-hmm.

Julie Zhuo 1:06:59 Right? And so-What I can continue to try and do in all respects is continue to train my eye, 'cause the eye is easier to train usually than the hand. Um, so we, this also brings us back to what we were talking about in the initial parts of our conversation today, which is, like, how can I learn from the best so that I have, maybe for as long as possible, have an advantage in terms of at least knowing or recognizing what great is. And so then for, I will have more of an ability to direct the AI towards, um, um... So I can try and do that as long as possible, okay? But let's assume that one day AI gets better than me, then even at that, because we're getting just better and better intelligence. I think then, okay, what does that world look like? I don't know. I think there's, like, a lot of speculation. I think, like, lots of things will break or be better. Um, but I will say that one thing that I think AI can never really take away from us is the journey and the process, um, of learning and growing and doing things that we're proud of, right? And so for me, I look at this example of chess. So it's been a while now since computers have bested humans at the game of chess. But it isn't the case that somehow it, we, we all gave up and nobody plays chess anymore because what's the point, because AI is better than humans. I think actually chess has become way more popular since we've had AI come to the forefront and all those news articles about how it, you know, bested the best chess player. And I think a lot of the reason why is it's still an inherently human activity to wanna choose to do this thing, to compete against someone, to feel like you're getting better in this particular skill. Even if you're not gonna be the best in the world at it because AI is better than you, there is still something very human, very joyful about doing these things.

Aakash Gupta 1:08:47 Yeah.

Julie Zhuo 1:08:48 Right? And that is very human, you know? So even if AI can do all of the skills better than me, I don't think it should take away from the fact that if I derive joy, pleasure, and meaning from getting better at certain skills, let me continue to do that. Let everyone continue to do that. Let us all enjoy chess for the sheer joy of playing the game.

Aakash Gupta 1:09:08 Mm-hmm.

Julie Zhuo 1:09:09 You know? And that might, that might be a fine world for us to be in.

Aakash Gupta 1:09:16 Speaking of learning from the best, you get to work with some of the best product leaders in the world because you build data analytics products for the product leaders at OpenAI. What have you learned from them? What do they do differently?

Julie Zhuo 1:09:29 I think that they are, um... So sp- okay, so first, OpenAI, wonderful company, really amazing, super, super high talent density. Um, I will say is they work really hard. [laughs]

Aakash Gupta 1:09:41 [laughs]

Julie Zhuo 1:09:42 Um, and I think that that's probably already well known. Uh, but it's, it's such a competitive time right now, and it's-

Aakash Gupta 1:09:47 It's, like, seven days a week is what I hear

Julie Zhuo 1:09:48 ... Yeah, and, and, and so I can tell you, yeah, like, people are looking at data and dashboards and stuff, like, every day of the week. [laughs] So that's data point number one. Um, I think data point number two is what I was, uh, alludes to what I was, uh, speaking of earlier, which is that having a very, very, very detailed and refined understanding of what is happening on the ground. So, like, every single day, you know, I see analysts and data practitioners from OpenAI come in, and they are just, you know, they're, they're like, their usage is extremely deep. They spend a lot of time, and that's because anytime something changes, you know, this amount grew. Like, you know, this country grew by this amount, or this country sort of stalled. They want to understand why.

Aakash Gupta 1:10:36 Mm.

Julie Zhuo 1:10:36 Why did it happen? What does it tell us? You know, what, what can we learn? Is there a pattern? Is there something that we can do to change that trend if we don't like it? But even not, do we start to understand a little bit more about human nature and the nature of our customers, or what works for them, or what they want, or how they behave? So it's, I think, this extremely obsessive need to, like, get at the deeper explanation of understanding what is really going on. And I think the other thing is just, like, good hygiene, right? What I see, like, really top companies h- have is this hygiene of, like, we have a metrics review every week. Why? A lot of the purpose of a metrics review, okay, is, you know, metrics review is essentially like, you know, you get a group of leaders there, um, and everyone looks at the numbers, the KPIs, and the dashboards, and everyone talks about, like, how they're trending. And I think that that's really important because it does a couple things. So first is it creates alignment, right? E- everyone now understands, okay, we're on the same page about the story. You know, if we didn't do that, you may have a week where you think, "Oh, our company's doing really awesome. We had a great month." And I might think, "No, we did really poorly," and it's 'cause I have one anecdote about how, like, we lost two clients.

Aakash Gupta 1:11:46 Mm.

Julie Zhuo 1:11:46 But you're, like, looking at how many features we shipped. So it's like we have a different frame. You know, we have different, um, mental model of, like, what success looks like. I think when you go back and you have, like, a really great observability layer and you've kind of agreed that this is the right observability layer for, like, truly, you know, measuring reality, and therefore you also have a forum in which every week we can get out in there and we're like, "Well," you know, I can say something like, "Well, we had a great week." And you're like, "Wait, why do you s- why do you think that? We had a shitty week." Because, you know, then we're on the same page, right? That is a forum for us to be able to align as a leadership team or as a, as a, as a group on that. So that's, I think, the hygiene of something like our metrics review. I think the second one is just, you know, uh, like, if you're representing a particular country and that went down, it's an accountability where we're like, "Hey, Aakash, why did it go down?" And you should be expected to, like, know because you've done your research, 'cause you're curious, and if not, it sort of builds that discipline that, like, we should know. You know? It's your responsibility to go and figure it out. It's my responsibility for, like, the areas that I own. So I think the metric review provides that kind of rigor, um, so that we can be accountable to understanding what is actually happening and why, so that we can be more in control of it.

Aakash Gupta 1:12:57 Mm-hmm.

Julie Zhuo 1:12:58 I think the third thing that it does well is that it, uh, allows us to have, like, a, a shared common language which we can then take back to the rest of our teams.

Aakash Gupta 1:13:08 Yeah

Julie Zhuo 1:13:09 ... about what, what, uh, so I do see, like, some of the best companies have that kind of rigor when it comes to understanding their analytics, understanding, uh, which in my mind is just rigor about, like, understanding operationally how things work-

Aakash Gupta 1:13:24 Mm-hmm

Julie Zhuo 1:13:24 ... and what all the levers are.

Aakash Gupta 1:13:26 So today we covered, I think, all 360 degrees of being a great AI product leader. The reason you've become tech's favorite management guru is this book. So I'm curious, for people who are creators, who are, who wanna learn, like, how did you create a Wall Street Journal bestselling book on management?

Julie Zhuo 1:13:48 I, it's hard to answer that because for me, I've always, I liked writing, and writing works for me in, on honesty because I always felt like I was a better writer, I was a clearer communicator in writing than in person.

Aakash Gupta 1:14:03 Hmm.

Julie Zhuo 1:14:03 And it's taken me a lot of time to develop, but I used to get a lot of feedback that I rambled a lot.

Aakash Gupta 1:14:08 [laughs]

Julie Zhuo 1:14:09 I didn't r- quite get to the point very quickly. I, it was hard for me to think on my feet. And so writing for me is, like, a way of actually getting my thoughts more clearly articulated. And so I started the practice when I was at Facebook. It, you know, I would go into a meeting and everybody would be talking, and I would, like, struggle to figure out what to say. And my manager actually gave me a lot of feedback that, like, "Hey, you, you need to, like, speak up more."

Aakash Gupta 1:14:33 Yeah.

Julie Zhuo 1:14:33 "Like, we don't know what you're thinking." And so my first instinct is, okay, so maybe after the meeting I'll just write what I was thinking. That's how it started. And then I realized it was actually almost very therapeutic for me. [laughs] And I thought about my writing as letters to myself. And a lot of this book is essentially that. The, one of the primary reasons that I decided to even take on writing this book is I thought if I wrote a book about management, it's like writing this giant letter to myself [laughs] about what it is that I want to be, and how to, um, get the values that I have on paper in a way that will help me become a better manager. So I still am on that journey. I still am trying every day to be a better manager. I think there's so much for me to learn and grow. You know, I think as with a lot of things, sometimes the theory is easier to explain and the practice is still hard. [laughs]

Aakash Gupta 1:15:22 Yeah.

Julie Zhuo 1:15:22 So much of life is like that, right? Like, we might understand intellectually that this is what it is. You know, like even very basic stuff like talk to your customers, but the actual reality of doing it day in and day out is a practice. And I think about management or leadership or any of-

Aakash Gupta 1:15:37 Yeah

Julie Zhuo 1:15:37 ... the stuff that we do, design, like product, these are practices.

Aakash Gupta 1:15:40 Mm-hmm.

Julie Zhuo 1:15:40 And the only way... There's no perfection. The only thing we can do is just show up, do the practice, and through the art of doing the practice, hopefully derive a lot of joy and meaning, and watch ourselves become better day every day than where we were yesterday.

Aakash Gupta 1:15:55 Wow. What a way to end the podcast. After literally years of reading your content, this conversation over-delivered. Thank you so, so much.

Julie Zhuo 1:16:05 Thank you. This was really fun. And I mean, you, you do amazing work too, so I'm a big fan of your podcast and, um, your newsletter, and I love that you, you try so hard to, uh, to, to make this knowledge accessible and make all of us better.

Aakash Gupta 1:16:20 Appreciate that. All right, everybody, we'll see you later. I really hope you guys enjoyed that episode. It would mean a ton to me and the team if you could please subscribe on YouTube, follow on Apple and Spotify podcasts, and leave a rating and review. Those ratings and reviews really help grow the show and help other people discover the show, and they help fund the production so that we can do bigger and better productions. Can't wait to share the next episode with you. Until then, see you later.