Julie Zhuo: How AI is flattening orgs into broader builders

1. 0:00 – 5:18

   Welcome back, Julie!

   1. LRLenny Rachitsky0:00

      (tense music) We're seeing this kind of flattening of orgs. Everyone's becoming an IC again.

   2. JZJulie Zhuo0:04

      It used to be, okay, I don't have the skills to do 10 different jobs, but now with AI, it allows me to do many of those jobs myself. We need to dissolve the boundaries of these traditional roles and call ourselves builders. I'd love first to get to a world where that's the title.

   3. LRLenny Rachitsky0:19

      I also just saw a stat, Google let go of so many of their middle managers.

   4. JZJulie Zhuo0:22

      Management is still really critical. You have a North Star, you have a vision, and you're just trying to figure out how to use the resources that you have to get that thing done. It used to be people, but now it's basically models, and different models have different strengths. You kind of have to assemble the Avengers so that you can use the right tools for the right purposes.

   5. LRLenny Rachitsky0:39

      What do you feel is the biggest change in the role in life of a manager these days?

   6. JZJulie Zhuo0:43

      It's always been manager's job to manage change. I just think the rate of change is accelerating. Today, management is really about this idea of be sturdy while being flexible. So I think about this metaphor a lot of the willow tree. It can survive a lot of storms, disasters, et cetera, but it's also very flexible.

   7. LRLenny Rachitsky1:00

      You have such an interesting trajectory from being head of design to now being obsessed with data and analytics.

   8. JZJulie Zhuo1:05

      You want to diagnose with data and treat with design. Data is not a tool that's going to tell you what you should build. I don't actually think a lot of the fast-growing companies are using data well at this point. Traditionally, things just didn't grow that fast. These companies are totally getting by on just good instincts and good vibes, but what always happens is eventually, things stop growing.

   9. LRLenny Rachitsky1:25

      (instrumental music) Today, my guest is Julie Zhuo. Julie was my first ever guest on this podcast, which I recorded over three years ago, so this is a very special conversation. As I've shared many times before in other places, Julie's newsletter, The Looking Glass, was the inspiration for my newsletter, and basically led to everything that I do now. If you're not familiar with Julie, she was the longtime head of design for the Facebook app used by over three billion people. She's also the author of the bestselling and very important book, The Making of a Manager. And most recently, she started her own company, Sundial, which is an AI-powered analyst used by companies like OpenAI, Gamma, and Character.AI. Julie is one of the most thoughtful and insightful product leaders that I've ever come across, and she's also got one of the most interesting perspectives on product building. Having worked at a mega large corp like Meta as head of design and now as a founder at a tiny startup that's all about using data to help you make decisions, it's really rare for someone to have this spectrum of experiences. In our conversation, we talk about how learning to be a great manager directly translates to learning how to use AI tools extremely well, which specific skills will become more valuable in the next couple of years, her most valuable and timeless advice for new managers, why she's not hiring product managers at her startup, her simple heuristic for knowing when to use data and when to use intuition in making decisions. There's something in this episode for everyone. And if you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. It helps tremendously. And if you become an annual subscriber of my newsletter, you get 15 incredible products for free for an entire year, including Lovable, Replit, Bolt, N8n, Linear, Superhuman, Descript, WhisperFlow, Gamma, Perplexity, Warp, Granola, Magic Patterns, Raycast, ChatBRD, and Mobben. Head on over to lennysnewsletter.com and click Product Pass. With that, I bring you Julie Zhuo. This episode is brought to you by Mercury. I've been banking with Mercury for years, and honestly, I can't imagine banking any other way at this point. I switched from Chase and holy moly, what a difference. Sending wires, tracking spend, giving people on my team access to move money around, so freaking easy. Where most traditional banking websites and apps are clunky and hard to use, Mercury is meticulously designed to be an intuitive and simple experience. And Mercury brings all the ways that you use money into a single product, including credit cards, invoicing, bill pay, reimbursements for your teammates, and capital. Whether you're a funded tech startup looking for ways to pay contractors and earn yield on your idle cash or an agency that needs to invoice customers and keep them current or an e-commerce brand that needs to stay on top of cash flow and access capital, Mercury can be tailored to help your business perform at its highest level. See what over 200,000 entrepreneurs love about Mercury. Visit mercury.com to apply online in 10 minutes. Mercury is a fintech, not a bank. Banking services provided through Mercury's FDIC-insured partner banks. For more details, check out the show notes. Today's episode is brought to you by DX, the developer intelligence platform designed by leading researchers. To thrive in the AI era, organizations need to adapt quickly, but many organization leaders struggle to answer pressing questions like, which tools are working? How are they being used? What's actually driving value? DX provides the data and insights that leaders need to navigate this shift. With DX, companies like Dropbox, Booking.com, Adyen, and Intercom get a deep understanding of how AI is providing value to their developers and what impact AI is having on engineering productivity. To learn more, visit DX's website at getdx.com/lenny. That's getdx.com/lenny.

2. 5:18 – 8:41

   The success of The Making of a Manager

   1. LRLenny Rachitsky5:18

      (instrumental music) Julie, thank you so much for being here, and welcome back to the podcast.

   2. JZJulie Zhuo5:26

      Thank you, Lenny. I'm so excited to be here. I've been looking forward to this all week. I love your podcast. I love where you've taken it since our very first conversation, and I'm super excited to have a fun and engaging chat.

   3. LRLenny Rachitsky5:38

      Can you believe that first episode? The very first episode of this podcast was over three years ago at this point.

   4. JZJulie Zhuo5:45

      Mm-hmm.

   5. LRLenny Rachitsky5:45

      Holy shit.

   6. JZJulie Zhuo5:46

      I'm not sure you had that-

   7. LRLenny Rachitsky5:47

      Um...

   8. JZJulie Zhuo5:47

      ... fire in the background back then. (laughs)

   9. LRLenny Rachitsky5:49

      So funny enough, I don't know how many people have noticed this Easter egg that I've (laughs) stuck with. Uh, in that first studio, I was just watching the episode, I had, like, this funny little mirror, I don't know if I had it in the first episode, with a fire...... uh, place that was showing up in that mirror, 'cause the mirror was showing something stupid. And so I've just kind of kept this fireplace across every studio I've moved across in my, in my various places.

   10. JZJulie Zhuo6:12

       I even remember when we chatted, video was, like, kind of a newer thing. You were like, "We'll record it, but, like, it's really about the audio." And now we've moved into the video era.

   11. LRLenny Rachitsky6:21

       So as you were saying that, I realized my fire (laughs) was broken, so I just had to turn that on. So we just cut a little piece. Uh, yeah, that fire was my little fun Easter egg for myself, and I, I don't think anyone's ever realized this.

   12. JZJulie Zhuo6:32

       It's very cozy. I love it.

   13. LRLenny Rachitsky6:33

       (laughs) That's the idea. Uh, I was actually just looking at the stats of since that first episode. This ep- podcast has done over 20 million downloads. It's approaching 30 million downloads.

   14. JZJulie Zhuo6:43

       It's really incredible. I think it is a testament to just your curiosity and how much you really care about the craft of building great products and sharing that with the world. And I know I listen to your podcast and your- read your newsletter, my team does. We're constantly sharing things from all of the amazing speakers that you've had, so thank you for doing this.

   15. LRLenny Rachitsky7:00

       Uh, my pleasure. I really appreciate that. So the reason we are chatting again three years later is, uh, you're re-releasing your incredible book, The Making of a Manager. I've got it right here. Uh, you've sold a bazillion copies. It's been on every list that I've seen. Uh, you're releasing the paperback version. You're adding some chapters. I guess, first of all, just how do you feel on the- reflecting back on the, the success of this book?

   16. JZJulie Zhuo7:24

       It honestly went beyond my expectations, so I'm super happy with it. My big motivation to write it was, I think largely because I felt if I had to write this thing, I was likely going to become a better manager. And that was actually a huge part of it, um, because thinking about and writing something, you know, I've been blogging for a long time, and I know that part of my process is when I really sit down to try and put down everything I feel and write letters to myself, it really helps me. And so that was honestly a huge motivation. I hoped that it would go out there and it would sell some books. I was thinking about that maybe for people who grew up in companies like mine, like Facebook, you know, high-scale, Silicon Valley, it, it might resonate. I couldn't have expected that it would have much wider reach than that, and, um, and it, that's been really awesome. And just how many people will tell me things like, "I thought I was the only one who felt this way, but this book made me realize that, hey, these are very normal feelings." And that's certainly how I felt just stumbling through and feeling like an imposter for so many years. And so I'm, uh, it really is very gratifying to hear that from readers.

   17. LRLenny Rachitsky8:29

       I feel like it's the modern-day High Output Management. Uh, feels... That's the book that's been mentioned most on this podcast.

   18. JZJulie Zhuo8:34

       Mm-hmm.

   19. LRLenny Rachitsky8:35

       And it feels like this is just, like, a modern version. I feel like that date- book is actually out of date in a lot of ways, so I can see why people are really drawn

3. 8:41 – 11:38

   Why AI will make everyone a manager

   1. LRLenny Rachitsky8:41

      to it.

   2. JZJulie Zhuo8:41

      Mm-hmm.

   3. LRLenny Rachitsky8:42

      And this is a great segue to the first, uh, area I wanna spend some time on, which is, it feels like a lot of the skills you learn as a manager translate to being really good with AI and using AI tools really well. And I wanna talk through a few trends that, uh, I wanna get your take on that relate to this general theme. The first is, it feels like just everyone is gonna become a manager in the near future because of agents being so integrated into our workflows. There's this agentic society that we're, that we're coming to, and it feels like the same skills of being a manager make you really good working with agents. Uh, just thoughts on, on that and, and where you think that's gonna go.

   4. JZJulie Zhuo9:19

      I 100% believe that and agree with that, which is that management is just about, in my mind, having an outcome, so you wanna get something done, that's the thing. You have a North Star, you have a vision, and you're just trying to figure out how to use the resources that you have to get that thing done. And typically, when we talk about management in traditional settings, we talk about the resources being people and getting the right talent and making sure that they're, you know, you've got the, like, uh, assemble the avengers, so you've got the right mix of skills that you need. The second lever is around, okay, what's the purpose? Does everyone know what they're supposed to do with their talents? Like, do we have a goal? Do we have a purpose? And then the third thing is process, which is, how should all of these different people and tools come together? And these are still the fundamentals of working with agentic systems. Like, you still need a goal (laughs) , you need to be very clear about what the outcome is, and you have to understand the strengths of, of, you know, used to be people, but now it's basically models. And different models have different strengths, so it's like they have different personalities, and so you kind of have to get to know it, like, um, you know, develop an intuition for it so that you can use the right tools for the right purposes. And, I mean, we talk about agents, but we also talk about, like, what are the tools that agents have access to? So you still have to make decisions around that. And then there's of course process, which is how you do it. Now of- now I think with better and better models, perhaps the agents get smarter so they can deal with, um, higher and higher levels of figuring out how to do something, but I think it's still very important for us to be able to provide the right context, provide in- the right high-level instructions so that we get what we want. So really, it's the same principles, uh, and I absolutely agree with you that more and more of us are gonna have to double down on these skills to be able to use these tools very effectively.

   5. LRLenny Rachitsky11:09

      So along those lines, I have your book right here. You have this list of, "A manager's job is to build a team that works well together, support members in reaching their career goals, and create processes to get work done smoothly and efficiently," uh, which is basically exactly what you just said. Interestingly, that middle bullet is the part you don't have to worry about anymore with agents. You don't have to worry about their career development and (laughs) progress

   6. NANarrator11:28

      That's true.

   7. LRLenny Rachitsky11:29

      ... and rich success.

   8. NANarrator11:29

      That's true, uh, though some people do joke that if we don't treat our agents nice, what's gonna happen when AGI comes and, uh, you know, maybe it still, it still might benefit us

4. 11:38 – 14:00

   The future of management roles

   1. NANarrator11:38

      to be kind.

   2. LRLenny Rachitsky11:39

      I'm one of those people that says thank you to the Waymo when I leave and just, like, thanks, uh, ChatGPT when I'm in voice mode. Just like, "Thank you. That was really helpful." So along these lines, I know there's, uh, a lot of ways to go here, but just in terms of skills that are important to a manager, which do you think are most valuable to develop in working with agents and AI systems? I think about things like clarity communication. Just, like, what comes to mind when you think about, like...Here's the things you want to double down on as you're learning to be a manager that will also help you be really good at AI tooling and working with agents.

   3. JZJulie Zhuo12:16

      Like, the first is defining the goal (laughs) and defining the outcome and being really, really crystal clear on what does success look like. I mean, there's obviously lots and lots of... Like, if you ask a company to do this, we'll know that this is challenging for humans, right? I think a lot of times when you talk about, you know, why is alignment so difficult at a big company, it often comes down to this question, which is different people may have different pictures of what success looks like. And even if I describe in human words, "Oh, you know, Lenny, I want to build this product and it's gonna be amazing," or, you know, this podcast episode which you asked me, "Want lots of people to hear it and take away things," that's very general. Like, how do we get even more specific so that we know without question whether we've hit it or not? This is actually a really, really difficult problem. It's a different- a difficult question for us, because again, we tend to think very high level, so figuring out how to boil it down so that an agent can really understand what success and failure looks like is a lot of the game. And I think this also relates to things like, well, that's why we have to write evals, and that's why they're so important, because they're helping us understand what is the objective criteria. And these days, I work in data, and my company is all about trying to automate data analysis, and the forever question goes, the whole point of data and the whole point of metrics and KPIs is we're trying to put a little bit more of an objective measure, or get as crystal clear as possible about what success looks like. And I think it's really an art more than it is, like, a science, but that's, like, the first thing. I think if you're really unclear about what success looks like, the prompt, you're probably not gonna get the most amazing work. Um, I think that's true for managing teams, and it's very much true for managing

5. 14:00 – 21:30

   Empowering teams with AI

   1. JZJulie Zhuo14:00

      AIs.

   2. LRLenny Rachitsky14:01

      Okay. So let me actually flip this on you and talk about another trend that we're seeing, which is this kind of flattening of orgs, uh, managers being let go, everyone's becoming an IC again. I just had the CEO of Airtable on the podcast, and his, his whole shtick was that CEOs have to become ICs again, they- he's coding more than he's ever coded again, and his feeling is, you have to know what's possible by being in the weeds in order to figure out what your product should be. I also just saw a stat that Google let go of so many of their middle managers of smaller teams. It's just, like, this flattening trend. So do we even need managers, I guess is one question, in the future? And then just thoughts on how this, uh, will play out.

   3. JZJulie Zhuo14:42

      Yeah. So I think the real promise and magic of AI that we're seeing in the workplace is that it leads us to each individual is far more empowered. So it used to be, "Okay, I don't have the skills to do 10 different jobs, so I need to supplement by hiring people to do these jobs. I need someone who's really good at design, I need someone who's really good at coding, I need someone who's really good at data analysis, and then I'll assemble that team." But now with AI and my companion, it's like, wait a second, AI makes- allows me to do many of those jobs myself. Now, I'm not gonna do them at the, let's call it the PhD or the highest 1%, 10% level, but if I was, you know, at the zero or 10th percentile, it can certainly get me, even today, very quickly up to, like, the 60th, 70th in terms of, um, what the state of the art is. And I think that- that unlocks so many doors. And so the main thing that I- I felt so excited about, and this is something I tell my team all the time, is we need to dissolve the boundaries of these traditional roles. So in the past, again, we would have a traditional team, engineers, product manager, designer, researcher, data scientist, and I think now the teams can look more like, well, it's just two people. And again, they could be any of these traditional disciplines, but, uh, the- the key thing is they can now use AI to help themselves do a lot of the things that the other folks used to be able to do. So in some ways, we can drop all of these different role distinctions and call ourselves builders. I think that's sort of the most general-purpose way of thinking about what we can all be. We can all be builders. We can all be builders, (laughs) and I- I- I'd love for us to get to the world where that's just- that's, like, the title.

   4. LRLenny Rachitsky16:30

      Uh, that's funny. That's the term I've been actually using more and more. I used to orient this podcast as new- and newsletter on product managers, and then I started using just product to be a little more broad, and now I'm actually using that term builder. Uh, uh, so... And I- and I love that term, 'cause- 'cause it's exactly what you're saying. And this is very much a theme that comes up often in these conversations more and more, just the lines are blurring. I'm curious, at your company, how does that look? Like, what are you doing differently? What are you seeing in- on the ground within your company that maybe would be different from a few years ago?

   5. JZJulie Zhuo17:01

      So we have eliminated more roles. Um, for example, we thought tradit- we would need a bunch of product managers. It's turned out that actually, um, if you don't have a product manager, I know this might be, uh, going against a little bit of the ethos of- of where-

   6. LRLenny Rachitsky17:16

      Here we go. Here we go.

   7. JZJulie Zhuo17:17

      ... where Lenny started, but I find that sometimes when you have, like, a designer or product manager, and let's say I'm an engineer. Then when I have a problem, like, "Oh, I need to figure out the product definition," my default will be, "Well, I've got these people, and that's kind of their job description, so I'm just gonna delegate that to them." And I think that in- in doing so, you know, again, we're- we want to be polite, we want to respect everyone's lanes. I think that's a missed opportunity for that engi- you know, if I'm the engineer, to l- be like, "Wait a second. I should probably focus a lot too. Like, I need to understand and have an opinion about what to build or what the user experience is." And so we found that if we actually make teams smaller and we kind of even, like, in the past, you know, pre-AI, like, just have fewer of these, it allowed everyone to be like, "Oh, wait. We don't have a product manager on the team. Okay, so communication's up to me. Figuring out how we get..."... greatest value to users is something that is now strictly in my charter, and so that's why I'm such a big fan of, like, we can make teams smaller and we can eliminate these lines. Sure, again, there's still... I'm not trying to say, like, everyone has to do everything. We still can respect the fact that you might be much better at this particular skill than me. But it's less about the role and it's more about the specific context that we're in. And I find that whenever you have teams and you empower them to be able to take more action on their specific context rather than having these higher level rules or policies or, like, "This is how it's supposed to be," then you get better work, you get faster work, uh, and you get happier employees because, you know, people feel like they actually can s- you know, have the power to create the thing that they want.

   8. LRLenny Rachitsky18:57

      That's really interesting that just that constraint of not having a PM makes the engineer realize they're not gonna wait for someone else to do it, they have to figure it out. The obvious, kind of, trick there is they have to be good at, good at this.

   9. JZJulie Zhuo19:08

      Mm-hmm.

   10. LRLenny Rachitsky19:08

       It's a very different job from engineering to be really good at articulating, "Here's the problem we're gonna solve, here's why it's important that we're solving, here's how we're gonna prioritize everything we're thinking about, here's how do we get alignment." Is there something you do differently when you're hiring these engineers knowing you're gonna probably not hire a PM, and, and just that feels really hard to hire for someone that's really good at all these things.

   11. JZJulie Zhuo19:30

       It is true, and I'm not trying to say, again, that everyone needs to be good at everything. I don't think that's very realistic. I do think, for example, if we were gonna create a team and we're gonna have, uh, a couple of engineers and none of them are very good at, at thinking through product requirements or what the user angle is, we probably do need to supplement the team with somebody with that skill set, right? And that might be a designer or that might be another engineer who's really good at that, or that might be a, you know, a, a traditional product manager or some- or even sometimes a data analyst who's really good at it. So, that skill is still important and the team still needs to have that skill, otherwise it's probably not gonna produce the best outcome, but I like to think of it as, like, what are the skills that are needed for this and can we now find a couple of people? But it doesn't mean we just automatically go to that script of need a PM, need a designer, need three engineers, need, need that, you know? Um, another example for us is, like, even thinking about front end, back end engineering. It used to be like, "Oh, some people are front-end engineers, some are back." And so if you have a project and it's got some front end, some back end, the shortcut is like, "I need one of these and one of these," and that's how it's gonna go. But if you say, "Look, you're an engineer, you're a builder, you can... This has a little bit of front end, but you know what? You can probably figure that out." Like, use AI to help you figure it out. You know, get, obviously someone who's a specialist to review the code or to give you, um, some high level guidance on things, but just do it. And ever since we started to implement that as well, we see... Yeah. Again, a little bit of, um... You know, you have to kind of invest a little bit in the beginning so people are, are not as comfortable, they have to learn. So you... Initially, things take longer. It takes a little bit of extra time, right? Versus if you did slot in a front end specialist and this is a front end project, it probably would've gone a little bit shorter. But in the long run, that investment really pays off because now you have a lot more people who are, again, a little more well-rounded and can take on many more pieces just on their own. And then in specific scenarios, "Oh, this is super front end heavy," sure, let's still bring in somebody who is more specialized in that particular

6. 21:30 – 26:53

   Specific roles being accelerated by AI

   1. JZJulie Zhuo21:30

      skill.

   2. LRLenny Rachitsky21:31

      I love that you've had the experience of working at a mega large company, at Meta, and now you're building your own startup that's small and in the middle of this trend of just staying very small and, and staying really lean and just everyone doing more things. It's so cool that you're experiencing that. So, a couple of questions there. Just which functions are you seeing most accelerated with all these AI tools? Is it engineering? Is it something else? And then are there, are there tools that have been most helpful to you? Just AI tools for folks who would be like, "Oh, I should check it out." Like, I'm guessing Cursor, but, uh, curious if there's anything else.

   3. JZJulie Zhuo22:04

      Yeah. Certainly engineering. Engineering is one that we... I mean, most of our company is engineers, so that's the one that we focused on a bunch. I certainly do see more people also prototyping things, and so it's not just we have not... we have, like, two designers, but we also see engineers. Um, we have one... Uh, we have a team that's called Product Science, which is this interesting blend of c- It's... You can think about as, like, a forward deployed person who is... Uh, has a lot of data analysis background, um, and is kind of playing a customer success role and also kind of playing, like, a product role. Um, and you see them starting to take on building more prototypes or getting into some of the engineering. And so it's really lovely to see that blend of everyone can do a little bit of everything else and we're all encouraging each other. Um, the other thing that recently we've, we've also been trying to do a lot more is just, you know, obviously we say, "Hey, engineer, now you can do analysis." And their first thing is like, "Oh, I don't really know analysis." This is where ChatGPT comes in and it's like, well, you know, traditionally we would say, "Well, I have to learn that from a human. I have to ask this person and now I'm gonna take a bunch of their time because I want them to explain everything to me." And in fact, I think these days, you know, ChatGPT or these other AI tools are better teachers. Um, I find that we tend to maybe not use them quite as much, you know, just for the purposes of accelerating our education or, or even going through something. Like, sometimes what I'll do is I'll find a curriculum online and, uh, you know, if you, like, take a course, it'll be like this, whatever, 12-week curriculum and I'll just feed it into ChatGPT and I'll say, "Help me customize a program for me, you know, using the ways that I like to learn." Like, I am a person who really needs examples. I need a lot of, like, "Explain like I'm five. Give me an analogy." And I know some other people on my team, they're like, "I, I don't get..." Like, these examples don't make any sense. Like, we're, we're different types of learners and so the idea of like a, a, you know, a, a tool that personalizes learning for each of us really helps us, I think, accelerate and, and just learn these skills much faster than before. So yes, the tools are great. We can use Cursor. It helps us. It autocompletes, it writes a bunch of things. But the acceleration of learning, I think is another maybe underutilized tool in all of our arsenals just because I know whenever I talk to people, we just... we forget. Like, we don't re- we don't think that like, "Oh, wait. Yes, we could be doing that," and just sitting down and probably in-... 30 minutes or an hour, learn so much faster than what we used to be able to do before.

   4. LRLenny Rachitsky24:33

      That's such an interesting point. There's, like, these tools that are in the just-in-time, helping you move faster, and then there's ... But you also need to learn how to do something-

   5. JZJulie Zhuo24:41

      Yes.

   6. LRLenny Rachitsky24:41

      ... like, to some foundational lessons. Uh, what's an area that your team did that? Like, what did they f- w- work on learning?

   7. JZJulie Zhuo24:49

      So, I'll give you an example. I was just talking to an engineer this morning, and he's written a bunch of these algorithms. So, one of the things that our company does is we're trying to automate data analysis, so one of the things we have to do is obviously understand the best practices. Like, if there's a type of question, "Hey, what features are, are really the ones that people pay for?" We need to kind of figure out, what is the right analysis to do? And so, the engineer was saying to me, "You know, Julie, I feel like I really understand the how. Like, I know the algorithms. I know we do root cause analysis, like how we do that. But what I don't really understand is why or when this would be most useful. Like, in what context in a company would this company come up?" Because he's an engineer. He hasn't done that job of being, like, a PM or an executive that asks these types of questions. And that was, like, the perfect thing, where like, yeah, you know, traditionally, you might have asked someone, but this is more general purpose. Like, there's so much resources in the world on the internet about it. This is, like, the perfect type of question, where if you just talk to ChatGPT, you're, he's probably gonna give you a much better answer and allow you to go deeper. And a secondary thing we- we've been learning, too, is this idea of almost, like, as a, uh, using ChatGPT

   8. NANarrator26:01

      Yeah.

   9. JZJulie Zhuo26:01

      ... it's sort of like you test your learning. So, explains a bunch of things, and so what I often like to do is, like, "Okay, I read this, so this mean," and try to explain back what I heard, right? "So does this mean ... Is the right way to think about it that this is kinda like this analogy?" And ChatGPT will critique me, "Yes, that is right," or, "No, you didn't quite get that right." Like, in fact ... And it always tries to say it nicely. This is the funny part. It'll be like, "That's close," and then eventually it's like, "You were completely wrong." (laughs) Just in, in the, the style. But, like, it- it helps so much because it- it's in- interactive, and so we can really test whether we really understand the concept by trying to retell it back in our own way.

   10. LRLenny Rachitsky26:39

       It's incredible just how many ways all this AI breakthrough is helping us-

   11. JZJulie Zhuo26:45

       Yeah.

   12. LRLenny Rachitsky26:45

       ... in advance, and do more and learn more and become better. I know there's some downsides, but this is incredible and, uh, uh, so many pers- ways of getting better and faster.

7. 26:53 – 32:02

   Data analysis in AI companies

   1. LRLenny Rachitsky26:53

      I want to spend a little more time on this data analysis stuff. So again, you have such an interesting trajectory, from working at a big company to starting your own small company, uh, from being head of design to now being obsessed with data and analytics. So, let me spend a little time there. Um, what do AI companies that are, have kind of figured out how to use AI for data analysis and data work doing differently? What can people ... What are people missing and sleeping on in terms of getting better at working with data? And let me just ask, uh, at this point, it feels like we're almost working through here's all the blockers to a team moving forward. There's, like, a P- waiting for the PM to write the PRD, and then there's, like, waiting for the data scientist to give you answers, analysis.

   2. JZJulie Zhuo27:33

      Mm-hmm.

   3. LRLenny Rachitsky27:34

      So, this is, like, another really cool unblock that every team member will have.

   4. JZJulie Zhuo27:38

      So, your first question was, how are a bunch of AI companies using data? So, the funny thing, my funny answer to this is, I don't actually think a lot of the fast-growing companies are using data well at this point. And the main reason why is because traditionally, things just didn't grow that fast. And so, you know, if you got to 100 million users, your company's probably been around for a while, and if your company's been around for a while, you've had time to set up things like logging, and you've hired a growth team at that point, and you've hired a data team, and they've, like, done a bunch of work to log and instrument and then transform the data. And, like, we've talked about, like, what is the observability for our, our business? And you just usually had years to build and develop that because of the, the rate of growth. And so today, we see companies that are growing insane, and they're still about 10 people or two people or however many people, but they've got hundreds of millions in ARR and hundreds of millions of users, and you know what? They don't actually (laughs) have all of that infrastructure, that logging, and all, uh, to be able to truly do data analysis. So, it's, I would say that these t- these companies are, are totally getting by on just good instincts and good vibes, and we see that, right? Like, you don't really need, um, a data analysis to sometimes make something that works. But I think what data helps us do is it just ... It, it, in my mind, it's, it sort of is, like, helping us reflect back what is really reality. And so, of course, if AR is growing awesome. You know, great. Keep doing what you're doing. But what always happens is eventually things stop growing. Growth does not happen forever. And usually when growth stop, growth stops, everyone has this question of, like, "What's going on? Why did it happen?" And then you start to be able to see the power of if you've obs- if you've instrumented everything very well, and you have a very good observability model for your business, it's much easier to start to get into the root cause. It's d- easier to even predict whether growth will slow down at a certain point. It's easier to catch these trends earlier. If you don't have good observability over how your business runs and what the company's, um, key levers are, then you will be scrambling. And at that point, that's usually when people start investing a ton in data. So, I wouldn't say that we're ... Do a lot of these h- hot companies, like, you know, are, are, are quite there yet. But what I also think is a trend is that every time there's a new technological shift, we actually have to change the way that we think about ana- like, analysis has to answer the questions that we have. And if technology changes or context changes, we need new methodologies of analysis. So, for example, when mobile came to the forefront, right, looking at sessions or sessions per day or, or, um, time spent on mobile or, um, you know, kind of, uh, length of sessions became something that was important for us to understand. Are people getting value in this new medium? I think that's the same with what we have today. Conversational analytics is totally different. Used to be, let's say in the Google world, right, I knew you were interested in shopping if you clicked the shopping tab. I know you're interested in maps if you click the maps tab. We can measure clicks. Today, it's just all conversation, and so it's actually harder for us to tease apart what is the user intent.You know, if I worked on, um, any of these LLM, uh, I would say, like, one of the, probably the biggest questions is, "Hey, what use cases are growing or what use cases are shrinking?" And that's much harder to tell today because it's not just clicks on tabs or pages. It's like we have to probably use an LLM to... or a machine learning model to bucket user intent. We probably have to ask questions like, "Is the flow going really well in conversations?" You know, like a, like if I just ask one question and I don't go back and forth, like did the user get value, right? It's always trying to get back to, like, we're trying to figure out if this was a good experience, but now it's, it's like we need to actually invent new methodologies to-

   5. LRLenny Rachitsky31:37

      Mm-hmm.

   6. JZJulie Zhuo31:38

      ... help us analyze that.

   7. LRLenny Rachitsky31:40

      Yeah, I think there... The question is always, uh, like with conversation, do you want it to be a long conversation or do you want it to be a short conver-

   8. JZJulie Zhuo31:45

      Yes.

   9. LRLenny Rachitsky31:45

      ... like what's the right answer? What's better?

   10. JZJulie Zhuo31:48

       Yes.

   11. LRLenny Rachitsky31:48

       I had, uh, the head of ChatGPT on the podcast, Nick Turley, and turns out one of the, uh, ways they found the most common use cases early on was watching, uh, TikTok comments and things going viral on TikTok after they launched.

   12. JZJulie Zhuo32:00

       Yep.

   13. LRLenny Rachitsky32:00

       How about that?

   14. JZJulie Zhuo32:01

       Yep.

8. 32:02 – 37:21

   The role of data in design

   1. LRLenny Rachitsky32:02

      Okay, so I want to come back to this really interesting, uh, unusual p- path that you took from, uh, being a head of design at Facebook. Uh, you're an inspiration to so many designers. Now, you spend your time on, on a data startup, obsessed with data. Uh, I don't know, classically designers aren't the biggest fans of experiments and data and making decisions based on data. When you look at designers and you hear designers kind of push back on like, "No, we don't want to be super data-driven. We wanna, uh, we, we know better than... We have a sense of what's beautiful and great, and intuition." All these things. What, what do you think designers are, are missing when, when they feel that and say that, when they f- they're afraid of running experiments and data and kind of want to push that out?

   2. JZJulie Zhuo32:46

      There's one phrase that my co-founder and I would always discuss with us, uh, amongst ourselves very early on, and which we shared with like a lot of the companies that we work with, which is, what you really want is you want to diagnose with data and treat with design. So data is not a tool that's gonna tell you what you should build or what the solution is or how you're gonna, you know, cure the fact that you don't have really great retention. It's just not. But it can tell you if you have a problem and where that problem or opportunity might be. But you still need to go back and undergo a very creative process to figure out what's the best way to solve that. So that's the first thing I would say is this framework of, like, data helps you figure out what's actually happening, what do people like, what are they engaging with, whatnot, right? It's just, it gives you a story that r- better reflects re- reality. Um, because again, we all have stories, right? We're like, "Oh, my, my company is amazing. People love us," bla, bla. Like, that's the story I want to believe, but reality may be a different picture. And so what data is trying to do is capture reality. And by the way, I don't think of data just as like it's a A/B test and it's quantitative things we can measure. It's... To me, data is also, well, what did people put onto TikTok? And which things went viral? And what are they saying in the Twitterverse or X-verse, I guess is what it's called now.

   3. LRLenny Rachitsky34:04

      (laughs) That's right.

   4. JZJulie Zhuo34:05

      And, uh, um, and, and what are, you know, and if you do a customer interview, like what are... Like that's still all data. It's just that that is, you know, a little harder to distill and quantify. Although now with AI, you know, we have better, better tools for synthesizing. So that's, that's all data in my mind and it's just all trying to help us understand what is really happen- what is the phenomenon that's happening in reality and how do we understand it? You still have to go and invent and create and dream, and there's no formula and there's no science that will tell you exactly how you're going to make a hit. Um, you can experiment, which is, allows you to try more things maybe and, um, and more rigo- rigorously understand what that does in the short term. You're gonna have to... It's all very contextualized, right? 'Cause it... A/B tests don't tell you what will happen in the very long run. And that's still, a- again, that's all still data. You still have to synthesize and figure out what to do. So that's... This thing I'll say, diagnose with data and treat with design. I think the second thing I will usually t- tell designers about is, I find that sometimes, and maybe it's the, let's call it the, uh, false precision of numbers that we kind of fall into, right? Because it's like, okay, we got these numbers and the numbers go up. It's like, no, the fact that you still have to choose which things you look at is an art, not a science. And your interpretation of if the number went up 5%, is that good, is that not good is also an interpretation and is an, is an art, not a science. It's just that sometimes I think we can give ourselves this feeling, and I get it, like we... Sometimes there's this instinct to want to control things, and we want everything to be buttoned up, and we want to know that if we did A, B, C, everything will be great, our career is gonna be awesome, our product's gonna rocket ship. And I think designers are rightly often pushing back and saying, "No, the reality is, like, this stuff is ambiguous and it, there's uncertainty and we can never know for sure," and I think all that is quite true. So the other thing I would say that I really support is like you just actually can't make a really great product by thinking you can A/B test your way into it. So that's... I fundamentally believe that. But I don't think we should throw the baby out with the bath water. I think there's actually, you know, this... It's not either/or. It's not like data or design. It's like these are just tools for us to use. And I would say every amazing designer that I've ever met is absolutely obsessed with trying to get a better understanding of reality. They want to know what users really think. They want to know what they're really doing. If they could read every user's mind, that's like the, the thing we would all want, right, as a designer, is like if I could just know what everyone is thinking and feeling every time they used it, my life would be a lot easier because then I would be able to build better and better things. And so that's what it's trying to help us do. It isn't perfect. No metric is gonna tell you whatever we hope that it can in terms of the, the true certainty and precision, but it doesn't mean we can't use it to better our, our product development.

   5. LRLenny Rachitsky37:03

      I was going to say exactly what you just said, which is every great designer that I've worked with was obsessed with data, and the most leaning into the data versus designers that are just like, "Nah, I think I'm going to... I have a sense of what's right, and why, why would we let that tell us what to do?" And to your point, it's not going to tell you what to do. It'll tell you where opportunities arise.

9. 37:21 – 40:22

   The evolving role of managers in the AI era

   1. LRLenny Rachitsky37:21

      Let me take us back to the management chat, and maybe just let me ask something broad. What, what do you feel is the biggest change in the role and day-to-day work and life of a manager these days with the rise of AI?

   2. JZJulie Zhuo37:34

      I think that managing change. It's always been a manager's job to manage change, and there's always the chaos of what's going on. I just think the rate of change is accelerating, and we've seen that over the last couple of decades. And so I find that there's just a great deal more uncertainty that people have about things. Like, we all, you know, where is AI gonna be in two years from now? I don't know. Who kno- who really knows, right? And so, you know, are we gonna have AGI in five years? That kind of changes a lot about the landscape. Not to mention, I think there's quite a lot of fear that many organizations are feeling. You know, it's like if I... My career has always been in design, and now these tools are getting (laughs) better and better at what I'm doing, then holy shit, what happens to my career and my future, and do I need to pivot? Do I need to learn different things? And so it's this change, it's this feeling of uncertainty, and I think a lot of times managers have to deal with that, in addition to what you were saying before, which is they also have to learn these new skills, which is managing AI and managing kind of, like, these more powerful tools in their arsenal of trying to get things done. So that is very different, I think, than maybe, you know, 10, 20, 30 years ago. Um, and so I think that the skills that become more important are obviously communication, feedback, compassion, but just being able to work with humans and to have them understand that, like, yes, we are in a state of change. I think every leader has to do this now. Every startup founder that I know, every CEO is, how do you land this message that things are changing and we need to be ver- like, we need to be very open to change! If we go and stick to our old ways, we're probably gonna get left behind. Uh, our product's gonna get left behind. Even our way of doing things is going to be left behind. So we need to change, right? We ve- we need to change our product and we need to change the way that we work, as we all talked about in terms of smaller teams, more nimble, blah, blah, blah. Um, but at the same time, it's like, how, how do we do that in a way that doesn't just freak everyone out? (laughs) And it's like, "Ah, it's chaos. Everything's changing." Like, so, so I think about this metaphor a lot of, like, the willow tree, which is like, the, the willow tree is a very sturdy tree, you know? It's, um, it's, it, it, it can survive a lot of storms, disasters, et cetera, but it's also very flexible. Like, the branches are very, very flexible, and that's in some ways what allows it to be very sturdy. So I think today management is really about this idea of, like, be sturdy while being flexible. And that is a very hard thing to pull off, but I think that's, like, at least when I even go into b- I'm like, like, "Be like the willow tree, Julie. Just imagine the willow tree and, like, try and channel that as, as the, the kind of feeling of, of what it is that we're trying to do together."

10. 40:22 – 42:14

    Embracing change and uncertainty

    1. JZJulie Zhuo40:23

    2. LRLenny Rachitsky40:23

       This reminds me of a couple things from other guests. Uh, I had Marc Benioff on the podcast, and I asked him just, "How do you deal with all this change?" Things are, it's like agents now. It was, uh, I don't know, a- there's AGI coming, as you said. Just like, how do you survive? There's... And his advice is just, he's like, "I'm always just like, 'Good. This is great. I, I... This is what we want. This is exciting. We have so much opportunity. It's just not boring. We can always reinvent.'" And he's always embracing what... This is good.

    3. JZJulie Zhuo40:52

       Yes.

    4. LRLenny Rachitsky40:52

       And I just... I'll never forget the way he responded to that.

    5. JZJulie Zhuo40:55

       I think if you don't think it's good, it's kind of a painful way to live. It'll be very, very difficult over these next... So I do think that it, all things being equal, lean into it. Like, if you can wake up every day and see it as opportunity and excitement rather than fear. Again, they're all flip sides of the same coin, but I think if we can lean more into what could it be while recognizing that the other side does exist and it's still there, and I think of managers who try to pretend like it isn't there, like, "It's all good, no one's upset," et cetera, there's something also missing about just addressing and being able to be like, "Yeah, it's hard. Change is hard. We're probably gonna get upset. We're gonna have some chaos. Like, this is gonna happen, but we will work through it because we're going (laughs) to be flexible and we're going to be able to put our eyes on the big picture of what is possible, which is exciting."

    6. LRLenny Rachitsky41:45

       There's another quote that stu- that come, came up as you were talking. I forget who it was exactly. Maybe Kevin Wheal, maybe Mike Krieger. They said that this is the most normal things will be ever.

    7. JZJulie Zhuo41:56

       Mm-hmm.

    8. LRLenny Rachitsky41:57

       Like, it will only get weirder.

    9. JZJulie Zhuo41:59

       Yes. (laughs)

    10. LRLenny Rachitsky42:00

        And I think giving people that sense of like, "Okay, just enjoy this normal 'cause this is gonna be only weirder" is, well, at least give people an expectation, real expectations of where things might be going.

    11. JZJulie Zhuo42:10

        Yes, yes.

    12. LRLenny Rachitsky42:11

        What a time to be alive.

    13. JZJulie Zhuo42:12

        What a time.

    14. LRLenny Rachitsky42:13

        (laughs)

11. 42:14 – 49:03

    Timeless lessons for managers

    1. LRLenny Rachitsky42:14

       Okay. Let me, uh, zoom out even further and chat about... I wanna ask you, just outside of AI, management in many ways is unchanged. It's still a lot of the same work, managing people, helping them be successful, producing great work. What are just some of the, I'd say maybe most timeless, most important, uh, lessons that you think managers, especially new managers still don't totally understand, need to hear more? What are just some that come to mind? And then we'll see where this goes.

    2. JZJulie Zhuo42:43

       The first thing that comes to mind is the importance of managing yourself and understanding yourself. This is chapter five of my book. It's called Managing Yourself. In fact, when I wrote it, I kind of wanted it to be chapter one, and then my publisher's like, "Well, maybe you should get into some of the tactical..." Like, people don't necessarily think managing (laughs) other people or managing teams starts with them. But I really do fundamentally believe this, because I think all of us, of course, like any human being, we have things that we're strong at, we have things that we're weak at. And I am a very big believer that every strength is its own weakness, and every weakness is a strength. There's no such thing as you're gonna somehow, you know, get every dimension to be 100%. In fact, I think one of the most interesting concepts, uh...... that we can, like a, or frameworks for myself and also even, this is, is also kind of like a data framework concept is this c- concept of dimensionality. So what dimensionality means is like, you're a human being, but we can kind of look at you in infinite dimensions. There is, for example, how good is Lenny at throwing an ax? That's one dimension. There's-

    3. LRLenny Rachitsky43:49

       Pretty good.

    4. JZJulie Zhuo43:50

       (laughs) How good is Lenny at, uh, being a podcast g- uh, moderator? Fantastic.

    5. LRLenny Rachitsky43:56

       So, so. Okay, thank you.

    6. JZJulie Zhuo43:58

       How good is Lenny at doing a zero to one type of project in the AI space, right? So again, just you can think about these as infinite dimensions. And the reality is, each of our profiles is very unique. It's like a fingerprint. You know, so for you, it's like these are all these areas that you're really great at, you know, much better, like, in the top 1%. And then there's some areas where you're in the top 10%, then there's some areas where you're, like, kind of average, and then there's s- some dimensions in which you're worse than average compared to other people. And that's just true for all of us. And what I like about that is therefore, if you, if you take that as the model, right, things that then you, uh, you realize that none of these dimensions are you entirely. (laughs) So we can be, you know, I can make a comment like, "Lenny, your ax throwing really could use some improvement." And ideally, you're not like, "Julie is saying I'm a bad person. (laughs) I'm a, like my, my, my identity is at risk," right? Because it's just one dimension of who you are. Uh, but what happens sometimes is that we can get very attached to certain dimensions because we start to think that that's who we are, and I think managers can do that, um, and, uh, uh, clearly individuals, you know, on their teams. And when that happens, it starts to get very difficult to have, I think, more objective conversations about, "Okay, what can you get better at? What can you get worse at?" And so I say all this because I think this framework, for me at least and that many people that I've talked to, has helped them realize that somebody can give you feedback, or you can be maybe not great at certain dimensions. We could have room to improve, and that's not who you are, because you are all of these infinite dimensions in one. And none of them is, is, um, representative of, like, your true worth as an individual. I am a big believer that we are all beautiful and worthy. And sure, we have all of these skills, and yes, we wanna improve those skills, but it does not speak to, like, who we, whether we are worthy or not by saying whether, you know, we are strong or weak in these skills. And so I think if you can take that and really internalize that, then you can look at yourself a little bit more objectively as a manager, and you can realize that there are areas where you're gonna be really strong. There are areas where you have biases, and often, they are one and the same. So I'll give an example. People have often told me as, like, I would get this in my performance reviews from managers in the past, like, "Hey, Julie, you're really thoughtful. Uh, so, you know, when you think about something, you have, like, a, a th- a way to think about it. You've clearly thought about it in depth, and you've got, like, these frameworks and all this. That's a great thing." And then on the flip side, I'll get feedback like, "Well, Julie, you know, you're, you're, you don't really say a lot, um, in, in a dynamic discussion. Like, you're kinda quiet, and, uh, you know, you don't really think that quickly on your feet." And what you realize is, like, these are kind of, again, two s- like, because I don't do that, and I'm not just off the cuff, that's what allows me to oftentimes be very, very thoughtful, right? Or like that, uh, at least, again, when I was younger, like it, it sort of, it, it's very clear that that s- that particular weakness also very much speaking to a particular strength, which is, I am the kind of person that doesn't always have a snap judgment. I have to really think about it and internalize it and sometimes get to how I feel, and then I can share it and present it in the world. And so just knowing that about me is supremely helpful. Um, now, doesn't mean, of course, that I can never get better at this thing, but what I often think about is, mastery is where we realize that both of these we can get better at, and what we want to do is just figure out in the context what makes sense to be. So I got this feedback, and I'm like, "Cool. One of the things I need to work on is figuring out how to be more open in person, how to speak a little bit more clearly in person, maybe say things like, 'I don't know exactly how I feel about it yet, but this is what I'm thinking right now.'" Like, there's still clear tactics that will allow me to be a more effective team member and to do a better job in the context of what I'm trying to do with my team. So I've tried to build those skills, but the meta-skill is now being able to step back and say, "Okay, in certain context, it is really important that we move fast and we are, uh, decisive, and we just do something, and even if it's not perfect, we just kinda have to do it. And if I struggle with that, I should realize that that's an area to improve upon." But there are other contexts in which the right thing to do is actually to take a step back and be very thoughtful and to not rush into decisions. And so that's, like, so what I wanna get to is not, like, let's reject this strength or this weakness, but just know that that's, like, where we come from. That's naturally we might be wired in a particular way. Our growth often looks like getting better at doing the opposite, but not rejecting, again, the thing that we're good at, but rather, over time, getting to this balance where we can read the context and the situation and know, "Should I lean a little more thoughtful, or is this a time where I need to try and be a little more decisive and just share what I need to sh- what's on

12. 49:03 – 57:49

    Balancing strengths and weaknesses

    1. JZJulie Zhuo49:03

       my mind right now?"

    2. LRLenny Rachitsky49:04

       I love this advice that things that we are incredible at have a downside, and oftentimes, the feedback we're getting is, is something we're not great at. There's, like, a good version of that that people appreciate.

    3. JZJulie Zhuo49:15

       Mm-hmm.

    4. LRLenny Rachitsky49:15

       And I, I was gonna ask you, and I, I think you answered most of this, but just when you got this feedback of, "Hey, Julie, you're not speaking enough in these meetings. You're not, uh, contributing quickly enough," uh, it sounds like so one option is just like, "Uh, okay, cool. That's me."

    5. JZJulie Zhuo49:29

       Mm-hmm.

    6. LRLenny Rachitsky49:29

       "That's who I am, and I'm just gonna solve the problem this other way and then just not gonna change anything." What I heard you say is...... find opportunities where that's actually, mm, you want to actually change that behavior, even though it doesn't come naturally w- in specific situations where things are moving fast. Um, I guess just how far do you recommend people push themselves in things they're not great at, versus leaning further, further into their things, their, their strengths, let's say?

    7. JZJulie Zhuo49:54

       Ooh, I think that's a really great question. So, the way I think about it is, it is very dependent on what is your goal. So, for example, let's say that you are l- let's even take, for example, ICs versus managers. I think often about the pathway of an IC, an individual contributor, as wanting to deepen a craft. Like, you just, you love this thing and you just wanna get better and better and better at this very specific skill or this craft, right? So, think about in our dimension, infinite d- it's like, you pick a couple dimensions, like, "I just want these to be, I want to be like the top .01%." And that's, that's kind of the pathway of extending as an IC. Now, if that's your high-level g- goal, and you're like, "I wanna be able..." Let's say your high-level goal is, "I wanna be able to do this, you know, 10 or, uh, hours a day because I love it, and I wanna be able to support myself doing it, meaning I get paid and I have like a great job, and I want, you know, to, um, uh, have a bunch of impact in the world by doing this thing," right? So, again, you still have goals. Then you have to see, okay, does my strategy of just deepening these things, um, is that, is there a pathway to reach my goals according to that? And if there is, awesome. Then if someone's like, "Hey, do you wanna be a manager?" You're like, "Nope, don't need to because these are my goals, and this pathway actually allows me to do that." But if somehow you get to a point where, I don't know, the skill you really want to perfect is not something that may be commercially viable in the world, that's gonna somehow allow you to buy the, the big mansion that you wanna buy to support your family, then I think you have to ask yourself, "Okay, so if I just do this, it's not gonna cut it. I might actually need to learn some of these other skills in order to be able to fulfill the job that is going to be valuable enough that people are gonna pay me a bunch of money at this certain level so that I can afford my mansion." So, I just think it has to go back to like, what are your goals? And there are cases in which, yes, like, it supports, it will support your goal to do this and to deepen your craft, and there are cases in which it won't. And I think it's important. It's a very individual question for each person, but what I often think suffering is, is when these things are not aligned. So, what you want is like the giant mansion and all of that, and the, but you're like, "But I also just wanna spend all my time perfecting my egg omelet." And then you're just like in this tension place, and you, it's very hard to feel satisfied and fulfilled because you're a little bit like, "Oh, why doesn't the world value my, my deep egg omelet skills?" Um, like, okay, you can be an egg omelet, you just have to, you know, maybe not do this thing. Or if you want this thing, you may actually need to be better a- at just egg omelets. Like, perhaps you need to expand your repertoire of cuisines and like go and build a Michelin star restaurant or something. (laughs)

    8. LRLenny Rachitsky52:38

       This is really good advice. It's not just like, definitely always work on your weaknesses or don't worry about them. It's if you need to do this thing to achieve this goal that you have, make sure you understand what your goal is. And then, is this thing a thing you need to work on? For example, if you wanna become a VP, you probably need to be really good in big, important meetings and-

    9. JZJulie Zhuo52:56

       Mm-hmm.

    10. LRLenny Rachitsky52:56

        ... not being on the spot and just not, you know, waiting until everything's over and then sharing an email of your, all your thoughts.

    11. JZJulie Zhuo53:01

        That's right.

    12. LRLenny Rachitsky53:01

        Um, yeah. For me, I actually went through a period where I was like, "I do not wanna get promoted. I'm so happy in this very specific role. Just like, leave me alone." And, and, and that path is very different from the skills I need to build to be a manager. And then things change, and then okay, now these are the things that you need to work on.

    13. JZJulie Zhuo53:17

        Yeah. I love that you knew that about yourself, because I think it's so easy for, you know, a young person to go in their careers and everyone is telling them, maybe their whole family has been telling them, like, "You need to get l- You need to level up. You need to get paid more. You need to get that manager title. You need to get a VP." And at a certain point, I think sometimes people opt into this without knowing what they're actually signing up for. Like, what are the trade-offs, and is that really what you wanna do? Does that really align with your passions? And of course, you know, sometimes we have to, again, it's like, it's a compromise for us, right? But we get to design. Like, we get to design what our goals and what's the right pathway. Um, and I go back to usually when people are unhappy, it's because these things are a little bit out of sync. Like, they want this big thing but they don't actually, they're not actually excited about what it takes to do that thing, and therefore it's just going to be a mismatch.

    14. LRLenny Rachitsky54:09

        And along those lines, uh, it sounds like, "Oh, sure, I can design my life and design my role," but what I find is if you at least, first of all know what you'd love and ideally do, and then at least mention that to your manager, it often is a lot more possible than you think.

    15. JZJulie Zhuo54:26

        100%. I think it's so important to be ... Like, we often also have this mental model, like, "Oh, our managers are a judge, and they're gonna judge me on whether or not I got it, I did well, I should get a promotion, I should be fired." So, there's this sometimes fear that people have, but I think in the very best relationships, the manager is like a guide. It, it's like, look, the manager has a job, and if you understand your manager's job, which is how to get outcomes, f- better outcomes from a team, and also you understand what exactly would your manager consider success for the team, it also makes it easier for you to then be like, "Oh, well, if I do this project, then that clearly seems like it's very, you know, direct path to, you know, creating value for the team, and that also is a kind of project that, uh, uh, suits my skills, it's something I'm excited about," and like you should suggest that to your manager. But the other is true, right? So, you would know that if you actually asked your manager, "What is your job, and what do you consider success to be, and what is your greatest hopes and dreams?" And then you might be able to help your own career and yourself, um, because you would know that context. And conversely, if you say, "Hey, manager, these are my hopes and dreams. This is what I think I'm good at. I really wanna get better at this skill. You know, I really wanna..."... get that VP promotion, but I don't know what it entails. Can you tell me? Like, what does it take?" That's a really wonderful conversation as well, because then you'll get all of that context, and then you can actually decide whether you want to do it or not. And if you want to, then ask your manager for help, "Okay, if you see opportunities that are going to help me become a better presenter or increase my communication, please tell me. Even better, if you have feedback for me about communication, I want to hear it, because that's what's going to help me grow in this particular skill." And so it becomes this collaborative relationship much more so than this almost, like, adversarial, like, I'm trying to get you to give me a promotion, and you're trying to get me to, like, work harder. Like it's, yeah, like it, that is not a, a very good vibe.

    16. LRLenny Rachitsky56:27

        There's a, it reminds me of a guest post by Ethan Evans that I'll link to that has a really good framework for how to actually do exactly what you're talking about called the magic loop, where it, it's kind of a framework for figuring out what to work on and how to help your manager see you're capable of stuff and earn that trust. This episode is brought to you by Posthog, the product platform your engineers actually want to use. Posthog has all the tools that founders, developers, and product teams need, like product analytics, web analytics, session replays, heat maps, experimentation, surveys, LLM observability, error tracking, and more. Everything Posthog offers comes with a generous free tier that resets every month. More than 90% of customers use Posthog for free. You are going to love working with a team this transparent and technical. You'll see engineers landing pull requests for your issues, and their support team provides code level assistance when things get tricky. Posthog lets you have all your data in one place. Beyond analytics events, their data warehouse enables you to sync data from your PostgreSQL database, Stripe, HubSpot, S3, and many more sources. Finally, their new AI product, Analyst Max AI, helps you get further, faster. Get help building complex queries and setting up your account with an expert who's always standing by. Sign up today for free at posthog.com/lenny, and make sure to tell them Lenny sent you. That's posthog.com/lenny.

13. 57:49 – 1:05:33

    Building a feedback culture

    1. LRLenny Rachitsky57:49

       So along the lines of timeless manager, especially new manager advice, you've shared a bunch. Is there anything else that you think is really important, really interesting, valuable?

    2. JZJulie Zhuo57:58

       Feedback is one of the other topics that I am super duper passionate about, and my general impression for both myself, everyone I've worked with, is that we don't value feedback enough, or we don't kind of think about it enough. Again, companies have these performance cycles, and so we're all like, "Yes, every six months we're going to go and do these reviews. That's when I'll get feedback." But feedback really, in my mind, ideally should be like a daily practice, because the thing that matters for us in the long run as a team is, how quickly are we getting better? So a team that just gets 1% better every week compared to a team that gets 1% better a month is, even if they start off at a much lower baseline, is going to outperform in a very short amount of time the team that doesn't get better. And so what is the best tool for us to get better? It is feedback. And what I think about in feedback is, it, it's very similar to what we said earlier about data metrics. It's essentially trying to put your hypotheses and test them against reality. So as an example, maybe I have this perception right now that I am a positive and engaging speaker. So I have this sense that, like, I'm smiling and I'm very engaging and I'm telling great stories. But is that really true? I don't know. Like, the reality is that I'm often biased, and we all have, you know, we know these, like, psychological effects, right? Where like, sometimes the Dunning-Kruger effect, like people think they're way more expert at something than they actually are. You ask people, "Hey, are you a better than average driver?" And it's like 70 or 80% of people are like, "Yes, I'm better than average." How could that possibly be? We have biases. And imposter syndrome is a bias on the other side. It's like me feeling, "Oh, I suck. I don't actually belong here," whereas that also is a bias. Like, it may not actually be true. In fact, I might very well be here and other people value my contribution. So we are just wildly out of sync a lot of times in our perceptions of ourselves, our strengths, our weaknesses, what's going on. And the way that we're going to understand and truly get better is we need other people to reflect back what is actually their, their truth. And the way I think about it is like, I'm gonna ask you for feedback after this podcast episode, and you're gonna tell me something, and what you're gonna do is you're gonna give me a gift. 'Cause it'll be a gift of reflecting something back of what you see that I can't see, right? Just like if I have a leaf in the back of my head, I can't see that. And so if you tell me, "Hey, Julie, you have a leaf." "Oh, wow, thank you." Okay, maybe I can get rid of the leaf or, or whatnot. Um, but that is what feedback is. It is essentially reflection back. It helps us calibrate to rel- reality, and it allows me to get this information about whether or not, um, I'm moving in the direction of my goals.

    3. LRLenny Rachitsky1:00:50

       I, I love that. I completely agree. The challenge for most people, as you know, is giving feedback that people receive and don't feel defensive about, and then receiving feedback and not being like, "Oh no, they don't know. They don't know anything. How dare they say this about me."

    4. JZJulie Zhuo1:01:06

       Yes.

    5. LRLenny Rachitsky1:01:06

       Could you give us a, maybe a tip or two for delivering feedback well and for receiving feedback well, and maybe even just like seeking feed- how do you get more feedback? 'Cause this all makes a lot of sense. Most of the time people don't get any feedback.

    6. JZJulie Zhuo1:01:18

       The best way, the first tip on getting feedback or delivering hard feedback is first go and actually establish that our relationship is one in which we value each other's contribution, we want to help each other grow, and therefore we're gonna be the kind of people that want to give feedback to each other every week. So when you first start working with someone, don't wait until something bad has happened, now you have to give them feedback, 'cause that's already a pressurized situation. Start by saying, "Hey, really excited to work with you.I feel like our best collaboration is, I want you to help me get better. I think I'm good at this stuff, I'm not so good at this stuff. What about you? Okay, you think you're- you're good at this stuff right now. How about we just work together and we just help each other get better at these things? And the way we're gonna do that is all feedback is open, I want you to tell me everything. Ideally, you're gonna then be- say, "Yeah, I want you to tell me everything," and we've already established that.

    7. LRLenny Rachitsky1:02:10

       And this is colleagues or manager or a-

    8. JZJulie Zhuo1:02:12

       It's like-

    9. LRLenny Rachitsky1:02:13

       ... colleagues?

    10. JZJulie Zhuo1:02:13

        ... everyone. It's, like, people you're dating. It's, like, you know, your children. Like, it's, it can be with everyone, just establishing, what kind of relationship do we wanna have? I think most people wanna opt into a relationship where you can be close, you can be tight with one another, you can say things to one another and not have to hide behind ... Like, I think most people will opt into it. And if you opt into it, everything gets easier down the road. So the first thing is get everyone to opt in that, like, this is the kind of relationship that we wanna have.

    11. LRLenny Rachitsky1:02:40

        One trick I'll throw out that, uh, I've heard that worked really well along these same lines is asking people, "Would you prefer ... Do you prefer feedback in the moment or do you prefer it kind of, uh, every once, uh, and everyone, every month or s- or every week," or something like that. And everyone's like, "No, no, in the moment, and just, like, tell me as soon as something happens." And then that gives you that freedom to just, "Okay, yeah. Let me give you feedback here."

    12. JZJulie Zhuo1:03:00

        Yeah. So if you get people to opt in, yes, I want us to have a great relationship, I want us to help each other get better, I want feedback, that's 60% of the hard part of delivering difficult feedback later on. So then the second tactic I will say is that when you actually give the feedback, it helps a lot. First, you have to check, am I actually giving this feedback because it's in the spirit of trying to help one another? And if the answer is yes, then we're- we've, like, you know, moved from 60% to 80%, it's gonna go well, right? But what can often happen is I'm feeling ... Like, something happens, you do something, it triggers me because, I don't know, I had, like, a bad experience about that type of thing before, and so I'm kind of feeling mad and I want to be right. Like, if my, my real rationale for why I wanna give you feedback is I want to validate myself, I wanna be right, I want to tell you you're wrong, I wanna punish you, it's not gonna go well. It's just already there. It's, there's no way you can deliver it and somehow, unless you're a tremendous actor, um, it's just not gonna go well. So you have to first check your intention. But if you've done that, you're like, "No, no, no, I thought about it. I'm calm now. I'm not, like, see- seeing red. I really think that Lenny is just not aware that when he says this, it makes me and other people feel left out," or whatever it is, right? Then I need to be able to give it to you. And so usually then if you're like, "Okay, now I might be nervous because I don't wanna offend you. I really value our relationship. How am I gonna tell you?" Uh, you know, "I don't want you to get defensive." What then the third tactic I have is to say that out loud. Like, if I sit down with you and I say, "Lenny, I'm so nervous right now 'cause I wanna give you some feedback and I'm really worried that it's gonna impact our relationship, and I so value-"

    13. LRLenny Rachitsky1:04:58

        Mm-hmm.

    14. JZJulie Zhuo1:04:58

        "... our relationship and I don't want that to happen, but I also feel like it's just gonna help you to hear it if you can," that does so much of the work of, of ... It's- it's humanizing, right? It's like you're gonna be ... You're gonna realize that I'm going out on a limb, I'm being really vulnerable, and likely you're going to hear that so much more than if I just find a way to, like, drop it, like, and just, like, lob it over because it's so difficult. Just actually lean into the fact that it is difficult and expose that, because that builds a lot of human connection.

14. 1:05:33 – 1:09:27

    Creating win-win situations

    1. JZJulie Zhuo1:05:33

    2. LRLenny Rachitsky1:05:33

       This is amazing advice. Very tactical. Okay. Uh, is there anything else? So we've talked about a bunch of timeless pieces of manager wisdom, things that people need to hear, especially as new managers. Is there anything else that you think is really important that you think people are just n- not fully grokking for being great managers?

    3. JZJulie Zhuo1:05:53

       I think the idea of win-win. I think about that all the time in my mind, and I go back to ... Because I think that often we have this story in our heads that sometimes things are adversarial. As a manager, I'm trying to get people to be more productive, so I'm trying to get them to do a thing that maybe they don't wanna do. I wanna try and get them to work harder or I'm going to, um, somehow put more pressure on them. Like, if you start thinking like that, that's not a win-win way to be thinking, right? That's like you saying, "My getting better outcomes has to come at the expense of somebody else losing something." Um, and I think if you start w- thinking like that, it's very difficult to come up with a strategy or to truly be successful. But if you say, "Look, actually, my job is to figure out how to create win-wins," so I actually don't want, I don't want somebody over the long run, um, to feel like what I've done is just create a ton of pressure for them and now they're super burnt out real quick, because that's not good for our team, that's not good for me, that's not good for our long-term relationship. How do we find a s- Like, how do we find the solution that can be win-win? And I think if you think like that, a lot of things get easier. So for example, with new managers, I think this is true for me too, the first time I had to tell someone that they're not ... tha- they shouldn't be a part of this team was extremely fraught for me. And the main reason was because I'm putting myself in their shoes and I'm imagining that this is truly horrible and I've just done a, a huge disservice to this person and that's, like, the most awful thing. But there's another way to look at it, which is, hey, if this person's on the team, they probably wanna be successful. They wanna do great work, they wanna be valued, they wanna grow their career. If this is not the place for them because it doesn't align with their true interests and the things that are gonna help them be successful, it's just not the thing that they either want to do or can do, um, at this point, it doesn't do...... that person any good for me to, to somehow c- try to continue to make it. It's actually gonna be miserable. Like, I'm going back to, like, prolonging that misery state, and so sometimes a win-win thing is to just say, "Look, it's not working, and I know I've... I respect and value you so much that I know you want to do something that you can be proud of and you can grow in, and that's gonna be really valued, and right here, what we got, this isn't it." That's, like, a win-win way of looking at the situation, not a, like, you know, "Oh, my... Firing them is just definitely gonna be a horrible..." You know, it- I'm not trying to say it's not gonna be hard. Obviously, it's hard, but it's in the res- in the, the mentality and the, the, the mental model, I think, makes all the difference, 'cause it's gonna be different in the way that I convey it to them. It's gonna be different in why this actually, in the grander scheme of things, may be great, and it's gonna reduce this adversarial feeling where they're now gonna see me as, like, an enemy or somebody with all this power who's making, you know, uh, choices that impact them and they feel powerless. Like, it has to be a collaboration, and I think if it's not win-win, if- and I could be wrong. I would say, "I don't think it's right," the person could actually say, "No, you're wrong," and that would actually be great information, because then maybe we can go back and we can find a way to make it win-win.

    4. LRLenny Rachitsky1:09:12

       Yeah, I was just gonna say, they have to believe this.

    5. JZJulie Zhuo1:09:14

       Yes.

    6. LRLenny Rachitsky1:09:14

       You can't just sa- make it sound like this.

    7. JZJulie Zhuo1:09:16

       Yes.

    8. LRLenny Rachitsky1:09:16

       "Here's the win. You're getting let go. It's a huge win for you."

    9. JZJulie Zhuo1:09:18

       Yeah.

    10. LRLenny Rachitsky1:09:19

        Uh, but in reality, the... What we phrased it is actually almost always true.

    11. JZJulie Zhuo1:09:22

        Yes.

    12. LRLenny Rachitsky1:09:22

        Like, this is just not a place that you will be happy and succeed at.

    13. JZJulie Zhuo1:09:25

        Yeah.

    14. LRLenny Rachitsky1:09:25

        And it's better you go do something else.

    15. JZJulie Zhuo1:09:26

        Yeah.

15. 1:09:27 – 1:12:12

    Being aware of your own energy and conviction

    1. JZJulie Zhuo1:09:28

    2. LRLenny Rachitsky1:09:28

       Okay. I'm gonna keep fishing in this pool to see what else we got, but when we run out, let me know. Is there anything else that you think people should know, should hear, especially new managers that, um, they're still not fully getting?

    3. JZJulie Zhuo1:09:41

       I think being aware of peop- your own energy and conviction is really, really important. So, I go back... It's like a lot of these themes, as you can see, go back to, like, you have to first understand this about yourself and ha- have the right mindset, and when you do, it becomes much easier to be able to be impactful with other people. So, this is another one. I think it's very difficult for managers to be able... You know, we talked a lot about the three pillars of what are the, the major, um, uh, tools of a manager, right? The first is people, and so we talked a lot about, like, the importance of dimensionality and feedback and helping reflect and grow people. I think the second one is around purpose. Purpose is like, what are we here to do? What's our North Star? And I think it's very hard to actually convey that if you don't have conviction yourself. And so watching your conviction is really important, particularly since a lot of people who are managers, you often start out not as, like, the founder and the CEO of the company, but you're- you might be, like, a middle manager. So, in some ways, you don't- you didn't, like, create the vision, but you are in some ways expected to execute it or take a piece of it and do it. And I find that sometimes what new managers don't pay attention to enough is, what is their true belief? Like, they feel like they might have to be like a soldier, so they just get orders and they have to execute it, but it really makes a difference if they themselves have gone through the work of, of, of thinking through, wait, why are we doing this? Does- do I believe this strategy? Does it make sense or not? And if it doesn't make sense, to go and actually have the conversation with, you know, their manager or whoever else, just so they unders- they can get to alignment on like, "I really believe in what I'm doing." Because if you don't really believe in what you're doing and- or you're just kind of parroting the thing that got passed through the organization, it's very hard for you to then be able to help other people see what that magic is or to be actually really effective as, as a person who can hold that vision and that purpose. So, I just think you have to really check in with yourself on like, "Wait, I, I know we're told to do this, and this is what we have to do, but how do we really feel about it?" Because if you don't feel good about it, then it's not gonna be very likely that the project's gonna succeed. I can tell you right now. Every single manager I've ever managed where they're like, "I don't really think this is a good idea," there, there's no case where I can think of where the project somehow turned out to be, like, wildly successful.

16. 1:12:12 – 1:15:57

    Navigating disagreements with higher-ups

    1. JZJulie Zhuo1:12:13

Episode duration: 1:36:23