如何赢得朋友并影响决策(Julie Zhuo)| Lenny & Friends Summit 2024
How To Win Friends & Influence Decisions (Julie Zhuo) | Lenny & Friends Summit 2024
Guest Introduction
Lenny Rachitsky: We’re seeing this kind of flattening of orgs. Everyone’s becoming an IC again.
Reunion and Memories
Julie Zhuo: It used to be, okay, I don’t have the skills to do 10 different jobs, but now with AI 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 for us to get to the world where that’s the title.
Lenny Rachitsky: I also just saw a stat Google let go of so many of their middle managers.
Revisiting The Making of a Manager
Julie Zhuo: 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. Used to be people, but now it’s basically models and different models have different strengths. You have to assemble the Avengers so that you can use the right tools for the right purposes.
Lenny Rachitsky: What do you feel is the biggest change in the role in life of a manager these days?
Everyone Becomes a Manager
Julie Zhuo: 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.
Key Skills for Agent Collaboration
Lenny Rachitsky: You have such an interesting trajectory from being head of design to now being obsessed with data and analytics.
Julie Zhuo: 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.
Flat Orgs and Universal Builders
Lenny Rachitsky: 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 best selling and very important book The Making of a Manager. And most recently she started her own company, Sundial, which is an AI parent 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, ChatPRD and Mobbin.
Julie Zhuo: 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.
Skill Combinations in Small Teams
Lenny Rachitsky: Can you believe that first episode, the very first episode of this podcast, was over three years ago at this point? Holy shit.
Julie Zhuo: I’m not sure you had that fire in the background back then.
Acceleration from AI Tools
Lenny Rachitsky: So funny enough, I don’t know how many people have noticed this Easter egg that I’ve stuck with, in that first studio, I was just watching the episode, I had this funny little mirror. I don’t know if I had in the first episode with a fireplace that was showing up in that mirror because 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 various places.
Julie Zhuo: I even remember we chatted. Video was kind of a newer thing. You’re like, “We’ll record it, but it’s really about the audio.” And now we moved into the video era.
Data Analysis at AI Companies
Lenny Rachitsky: So as you were saying that, I realized my fire was broken, so I just had to turn that on. So we just cut a little piece. Yeah, that fire was my little funny strike for myself and I don’t think anyone’s ever realized this.
Julie Zhuo: It’s very cozy. I love it.
New Challenges in Conversational Analysis
Lenny Rachitsky: That’s the idea. I was actually just looking at the stats. So since that first episode, this podcast has done over 20 million downloads. It’s approaching 30 million downloads.
Julie Zhuo: 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 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.
Designers and Data
Lenny Rachitsky: My pleasure. I really appreciate that. So the reason we are chatting again three years later is you’re re-releasing your incredible book, The Making of a Manager. I’ve got it right here. You’ve sold a bazillion copies. It’s been on every list that I’ve seen. You’re releasing the paperback version, you’re adding some chapters. I guess first of all, just how do you feel on reflecting back on the success of this book?
The False Precision of Data
Julie Zhuo: 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 because thinking about and writing something 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, high-scale Silicon Valley, it might resonate. I couldn’t have expected that it would have much wider reach than that and 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 it really is very gratifying to hear that from readers.
Lenny Rachitsky: I feel like it’s the modern-day high output management. That’s the book that’s been mentioned most on this podcast and it feels like this is just a modern version. I feel like that book is actually out of date in a lot of ways, so I can see why people are really drawn to it. And this is a great segue to the first area I want to 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 want to talk through a few trends that I want to get your take on that relate to this general theme. The first is it feels like just everyone is going to become a manager in the near future because of agents being so integrated into our workflows. There’s this agentic society that we’re coming to and it feels like the same skills of being a manager make you really good working with agents. Just thoughts on that and where you think that’s going to go.
Management Changes in the AI Era
Julie Zhuo: I 100% believe that and agree with that, which is that management is just about, in my mind, having an outcome. So you want to 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 you’ve got the 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? 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. You still need a goal. You need to be very clear about what the outcome is and you have to understand the strengths of, 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 have to get to know it, 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 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. And now I think with better and better models, perhaps the agents get smarter so they can deal with 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 the right high level instruction so that we get what we want.
So really, it’s the same principles and I absolutely agree with you that more and more of us are going to have to double down on these skills to be able to use these tools very effectively.
Timeless Management Topics
Lenny Rachitsky: 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, 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 progress in [inaudible 00:11:29]
Julie Zhuo: That’s true. That’s true, though some people do joke that if we don’t treat our agents nice, what’s going to happen when AGI comes? And maybe it still might benefit us to be kind.
The Duality of Strengths and Weaknesses
Lenny Rachitsky: I’m one of those people that says thank you to the Waymo when I leave and just thanks ChatGPT when I’m in voice mode. Just like, “Thank you. That was really helpful.” So along these lines, I know there’s 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 in AI systems? I think about things like clarity, communication. Just what comes to mind when you think about here’s the things you want to double down on as you’re learning to be manager that will also help you be really good at AI tooling and working with agents?
Julie Zhuo: The first is defining the goal and defining the outcome and being really, really crystal clear on what does success look like. If you ask a company to do this, we’ll know that this is challenging for humans. I think a lot of times when you talk about 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, Lenny, I want to build this product and it’s going to be amazing, or this podcast episode, which you asked me, want lots of people to hear it and take away things, that’s very general. How do we get even more specific so that we know without question whether we’ve hit it or not. And this is actually a really, really difficult problem.
It’s 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 the first thing. I think if you’re really unclear about what success looks like, the prompt, you’re probably not going to get the most amazing work. I think that’s true for managing teams and it’s very much true for managing AIs.
Actively Designing Your Career Path
Lenny Rachitsky: 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, managers being let go. Everyone’s becoming an IC again. I just had the CEO of Airtable on the podcast and his whole shtick was that CEOs have to become ICs again. 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 will play out?
Julie Zhuo: 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 allows me to do many of those jobs myself. Now, I’m not going to do them at what’s called the PhD or the highest 1%, 10% level, but if I was at the zero or 10th percentile, it can certainly get me even today very quickly up to the 60th, 70th in terms of what the state of the art is.
And I think that that unlocks so many doors. And so the main thing that 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 they could be any of these traditional disciplines, but 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 and I’d love for us to get to the world where that’s like the title.
The Power of Feedback
Lenny Rachitsky: That’s funny. That’s the term I’ve been actually using more and more. I used to orient this podcast as a newsletter around product managers and then I started using just product to be a little more broad. And now I’m actually using that term builder and I love that term because 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? What are you doing differently? What are you seeing on the ground within your company that maybe would be different from a few years ago?
Building Feedback Relationships
Julie Zhuo: So we have eliminated more roles. For example, we thought we would need a bunch of product managers. It’s turned out that actually if you don’t have a product manager, I know this might be going against a little bit of the ethos of where Lenny started, but I find that sometimes when you have a designer or a product manager, and let’s say I’m an engineer, then when I have a problem, like 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 going to delegate that to them. And I think that in doing so, again, we want to be polite, we want to respect everyone’s lanes. I think that’s a missed opportunity for that, if I’m the engineer, to be like, “Wait a second, I should probably focus a lot, too.”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 even in the past, pre-AI, just have fewer of these, it allowed everyone to be like, “Wait, we don’t have product manager on the team, 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 we can make teams smaller and we can eliminate these lines. Sure. Again, I’m not trying to say 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 of rules or policies or this is how it’s supposed to be, then you get better work. You get faster work and you get happier employees because people feel like they actually can have the power to create the thing that they want.
Feedback Timing and Frequency
Lenny Rachitsky: That’s really interesting, just that constraint of not having a PM makes the engineer realize they’re not going to wait for someone else to do it. They have to figure it out. The obvious trick there is they have to be good at this. It’s a very different job from engineering to be really good at articulating here’s the problem we’re going to solve, here’s why it’s important that we’re solving, here’s how we’re going to prioritize everything we’re thinking about, here’s how we get alignment. Is there something you do differently when you’re hiring these engineers, knowing you’re going to probably not hire PM? And just that feels really hard to hire for someone that’s really good at all these things.
Concrete Feedback Techniques
Julie Zhuo: 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 going to create a team and we’re going to have a couple engineers and none of them are very good 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. And that might be a designer, or that might be another engineer who’s really good at that, or that might be a traditional product manager, 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 going to produce the best outcome. But I like to think of it as what are the skills that are needed for this and can we now find a couple people?
But it doesn’t mean we just automatically go to that script of need a PM, need a designer, need three engineers, need that. Another example for us is even thinking about front end, back end engineering. And it used to be like some people are front engineers. 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 going to go. But if you say, look, you’re an engineer, you’re a builder, this has a little bit of front end, but you know what? You can probably figure that out. Use AI to help you figure it out. Get obviously someone who’s a specialist to review the code or to give you some high level guidance on things, but just do it. And ever since we started to implement that as well, we see again a little bit of you have to invest a little bit in the beginning. So people are not as comfortable.
They have to learn, so initially things take longer, takes a little bit of extra time, 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 this is super front and heavy. Sure, let’s still bring in somebody who is more specialized in that particular skill.
Lenny Rachitsky: 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 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 tools that have been most helpful to you? Just AI tools for folks who’d be like, “I should check it out.” I’m guessing Cursor, but curious if there’s anything else.
The Power of Vulnerability
Julie Zhuo: Yeah, certainly engineering is one that, 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. We have two designers, but we also see engineers. We have a team that’s called product science, which is this interesting blend of you can think about it as like a forward deployed person who has a lot of data analysis background and is kind of playing a customer success role and also kind of playing a product role. 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. The other thing that recently we’ve also been trying to do a lot more is just 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 traditionally we would say, “Well, I have to learn that from a human. I have to ask this person and now I’m going to take a bunch of their time because I want them to explain everything to me.” And in fact, I think these days ChatGPT or these other AI tools are better teachers. I find that we tend to maybe not use them quite as much just for the purposes of accelerating our education or even going through something. Sometimes what I’ll do is I’ll find a curriculum online. And if you take a course, it’ll be like this 12 week curriculum and I’ll just feed it into ChatGPT and I’ll say, “Help me customize a program for me using the ways that I like to learn.”
I am a person who really needs examples. I need a lot of explain like I’m five. Give me an analogy. And I know some other people on my team are like, “These examples don’t make any sense.” We’re different types of learners and so the idea of a tool that personalizes learning for each of us really helps us, I think, accelerate 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 forget. We don’t think that, 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.
Win-Win Thinking in Management
Lenny Rachitsky: That’s such an interesting point. There’s these tools that are in the just in time, helping you move faster, but you also need to learn how to do something, some foundational lessons. What’s an area that your team did that? What did they work on learning?
Julie Zhuo: 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 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. If there’s a type of question …
… To do is obviously understand the best practices. If there’s a type of question, “Hey, what features 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, “Julie, I feel like I really understand the how. I know the algorithms, I know we do root cause analysis, how we do that. But what I don’t really understand is why or when this would be most useful. In what context in a company would this company come up?” Because he’s an engineer, he hasn’t done that job of being a PM or an executive that asks these types of questions. And that was like the perfect thing where yeah, traditionally you might’ve asked someone, but this is more general purpose. 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, it’s probably going to give you a much better answer and allow you to go deeper.
And a secondary thing we’ve been learning too is this idea of, almost like as a… Using ChatGPT it’s for to 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…” I try to explain back what I heard. “So does this mean… Is that right way to think about it, that this is kind of like this analogy?” And ChatGPT will critique me. “Yes, that is right,” or “No, you didn’t quite get that right. In fact…” And it always tries to say it nicely. This is a funny part. It’ll be like, “That’s close, and then eventually it’s like, “You were completely wrong.” Just in the style. But it helps so much because it’s interactive and so we can really test whether we really understand the concept by trying to retell it back in our own way.
Finding True Win-Win Outcomes
Lenny Rachitsky: It’s incredible just how many ways all this AI breakthrough is helping us advance and do more and learn more and become better. I know there’s some downsides, but this is incredible. So many ways of getting better and faster. 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. From being head of design to now being obsessed with data and analytics. So let me spend a little time there. What do AI companies that have kind of figured out how to use AI for data analysis and data work, doing differently, what are people missing and sleeping on in terms of getting better at working with data? And let me just add this point. It feels like we’re almost working through , here’s all the blockers to a team moving forward. There’s like waiting for the PM to write the PRD and then there’s waiting for the data scientists to give you answers analysis. So this is another really cool unblock that every team member will have.
Julie Zhuo: 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 if you got to a hundred million users, your company has probably been around for a while, and if your company has 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 done a bunch of work to log an instrument and then transform the data. And we’ve talked about what is the observability for our business. And you just usually had years to build and develop that, because of the rate of growth.
And so today we see companies that are growing insane and there’s 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 have all of that infrastructure, that logging, to be able to truly do data analysis. So I would say that these companies are totally getting by on just good instincts and good vibes and we see that. You don’t really need data analysis to sometimes make something that works. But I think what data helps us do is in my mind it sort of is helping us reflect back what is really reality. And so of course if ARR growing, awesome, 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 stops, everyone has this question of, “What’s going on? Why did it happen?”.
And then you start to be able to see the power of, 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 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 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 a lot of these hot companies 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… 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, looking at sessions or sessions per day or time spent on mobile, or 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, I knew you were interested in shopping if you click 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.
If I worked on any of these LLM, I would say one of 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 or a machine learning model to bucket user intent. We probably have to ask questions like, is the flow going really well in conversations? Like, if I just ask one question and I don’t go back and forth, did the user get value? It’s always trying to get back to, we’re trying to figure out if this was a good experience, but now it’s like we need to actually invent new methodologies to help us analyze that.
Belief and Sense of Direction
Lenny Rachitsky: Yeah, I think the question is always like with conversation, do you want it to be a long conversation, do you want it to be a short conversation? What’s the right answer, what’s better?
Julie Zhuo: Yes.
Living with Decisions You Disagree With
Lenny Rachitsky: I had a ChatGPT on the podcast, Nick Turley, and turns out one of the ways they found the most common use cases early on was watching TikTok comments and things going viral on TikTok after they launched. How about that?
Julie Zhuo: Yep, yep
The AI Corner
Lenny Rachitsky: Okay, so I want to come back to this really interesting, unusual path that you took from being a head of design at Facebook, you’re an inspiration to so many designers, now you spend your time on a data startup obsessed with data. 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 know better than… We have a sense of what’s beautiful and great and intuition,” all these things, what do you think designers are missing when they feel that and say that when they’re afraid of writing experiments and data and kind of want to push that out?
The Contrarian Corner
Julie Zhuo: There’s one phrase that my co-founder and I would always discuss with amongst ourselves very early on in which we shared with 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 going to tell you what you should build or what the solution is or how we’re going to 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, data helps you figure out what’s actually happening, what do people like, what are they engaging with, what what not.
It just gives you a story that better reflects reality. Because again, we all have stories. We’re like, “Oh, my company’s amazing, people love us,” blah, blah. 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 it’s an AB test and it’s quantitative things we can measure. To me data is also, well, what did people put onto TikTok and which things went viral, and what are they saying in the Twitter verse or X verse I guess is what it’s called now.
And if you do a customer interview, that’s still all data, it’s just that that is a little harder to distill and quantify. Although now with AI, we have better tools for synthesizing. So that’s all data in my mind and it’s just all trying to help us understand what is really happening, 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. You can experiment, which allows you to try more things maybe and more rigorously understand what that does in the short term. It’s all very contextualized. A-B tests don’t tell you what will happen in the very long run, and again, it’s all still data, you still have to synthesize and figure out what to do.
So that’s the thing, I’ll say. Diagnose with data and treat with design. The second thing I will usually tell designers about, is I find that sometimes, and maybe it’s the, let’s call it the 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 art, not a science. It’s just that sometimes I think we can give ourselves this feeling, and I get it, 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 ABC, everything will be great, our career’s going to be awesome, our product’s going to rocket ship.
And I think designers are rightly often pushing back and saying, “No, the reality is this stuff is ambiguous and 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 you just actually can’t make a really great product by thinking you can A-B test your way into it. So I fundamentally believe that, but I don’t think we should throw the baby out with the bathwater. I think there’s actually… You know? 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 minds, that’s the thing we would all want as a designer is like, if I could just know what everyone is thinking, 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 going to tell you whatever we hope that it can in terms of the true certainty and precision, but it doesn’t mean we can’t use it to better our product development.
Lightning Q&A
Lenny Rachitsky: I was going to say exactly what you just said, which is every great designer that I’ve worked with was obsessed with data in the most leaning into the data, versus designers that are just like, “Nah, I think I’m good, I have a sense of what’s right, and 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. Let me take us back to the management chat and maybe just let me ask something broad. 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?
Julie Zhuo: I think that managing change. It’s always been 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 where is AI going to be in two years from now? I don’t know. Who really knows? And so are we going to 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. It’s like if my career has always been in design and now these tools are getting 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 these more powerful tools in their arsenal of trying to get things done. So that is very different, I think, than maybe 10, 20, 30 years ago. 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 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 very open to change?
If we go and stick to our old ways, we’re probably going to get left behind, our product’s going to get left behind, even our way of doing things is going to be left behind. So we need to change. 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. But at the same time it’s like, how do we do that in a way that doesn’t just freak everyone out? And it’s like, “Ah, it’s chaos. Everything’s changing.”.
So I think about this metaphor a lot, of the willow tree, which is the willow tree is a very sturdy tree. It can survive a lot of storms, disasters, et cetera, but it’s also very flexible. 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 be sturdy while being flexible, and that is a very hard thing to pull off, but I think that’s at least when I even go into… I’m like, “Be like the willow tree, Julie. Just imagine the willow tree and try and channel that as the kind of feeling of what it is that we’re trying to do together.”
Book Recommendations
Lenny Rachitsky: This reminds me of a couple things from other guests. I had Marc Benioff on the podcast and I asked him, “Just how do you deal with all this change? It’s like agents now, it was, I don’t know, there’s AGI coming as you said, just like, “How do you survive through this?” And his advice is just, he’s like, “I’m always just like, ‘Good. This is great. 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 with “This is good.” And just I’ll never forget the way he responded to that.
Julie Zhuo: 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 all things be equal, lean into it. 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 if managers who try to pretend like it isn’t there, 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 going to get upset. We’re going to have some chaos. This is going to happen, but we will work through it because we’re going 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.
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Lenny Rachitsky: There’s another quote that and 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. Like, it will only get weirder. And I think giving people that sense of like, okay, just enjoy this normal, because this is going to be only weirder, is we’ll at least give people an expectation, real expectations where things might be going.
Parenting Feedback from Limitless Pendant
Julie Zhuo: Yes, yes.
Life Motto
Lenny Rachitsky: What a time to be alive.
Julie Zhuo: What a time.
Advice for the Next Generation
Lenny Rachitsky: Okay, let me zoom out even further and chat about… I want to 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 most timeless, most important 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.
Julie Zhuo: The first thing that comes to mind is the importance of managing yourself and understanding yourself. This was 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 was like, “Well, maybe you should get into some of the tactical…” People don’t necessarily think managing other people or manage a team 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 going to somehow get every dimension to be 100%. In fact, I think one of the most interesting concepts or frameworks for myself, and also even, this is also kind of like a data framework concept, is this concept of dimensionality. So what dimensionality means is 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
Outro
Lenny Rachitsky: Pretty good.
Julie Zhuo: How good is Lenny at being a podcast moderator? Fantastic.
Lenny Rachitsky: So-so. Okay, thank you.
Julie Zhuo: How good is Lenny at doing a zero to one type of project in the AI space? Right? So again, just can think about these as infinite dimensions. And the reality is each of our profiles is very unique, it’s like a fingerprint. So for you it’s like these are all these areas that you’re really great at, much better, like in the top 1%. And then there’s some areas where in the top 10%, then there’s some areas where you’re kind of average, and then there’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 take that as the model, you realize that none of these dimensions are you entirely. So 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, my identity is at risk,” right? Because it’s just one dimension of who you are. 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, and clearly individuals 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 get worse at? And so I say all this because I think this framework for me at least, and 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, you can 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 representative of your true worth as an individual.
I’m a big believer that we are all beautiful and worthy, and sure we have all of these skills and we want to improve those skills, but it does not speak to whether we are worthy or not by saying whether 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 going to 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, I would get this in my performance reviews from managers in the past, like, “Hey Julie, you’re really thoughtful. So when you think about something, you have a way to think about it, you’ve clearly thought about it in depth and you’ve got these frameworks and all this. That’s a great thing.”. And then on the flip side, I’ll get feedback like, “Well, Julie, you don’t really say a lot in a dynamic discussion. You’re kind of quiet and you don’t really think that quickly on your feet.” And what you realize is these are kind of, again two… 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, or at least, okay, when I was younger, it’s very clear that that particular weakness also very much is 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. 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,’” if 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 decisive and we just do something. And even if it’s not perfect, we just kind of 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 that’s so what I want to get to is not like let’s reject this strength or this weakness, but just know that that’s where we come from, that 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’s on my mind right now?”
Lenny Rachitsky: I love this advice that things that we are incredible at and have a downside, and oftentimes the feedback we’re getting is something we’re not great at, there’s a good version of that that people appreciate. And I was going to ask you, and 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 contributing quickly enough,” it sounds like, so one option is just like, “Okay, cool, that’s me, that’s how I am, and I’m just going to solve the problem this other way and then just not going to change anything.” What I heard you say is, find opportunities where you want to actually change that behavior, even though it doesn’t come naturally in specific situations where things are moving fast. I guess just how far do you recommend people push themselves in things they’re not great at, versus leaning further into their strength, let’s say?
Julie Zhuo: Oo, I think that’s a really great question. So the way I think about it is it’s very dependent on what is your goal. So for example, let’s say that you are…
… on what is your goal? So for example, let’s say that you are… 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. You love this thing and you just want to get better and better and better at this very specific skill or this craft, right? So think about in our dimension, infinite… It’s like you pick a couple dimensions, “I just want these to be… I want to be the top 0.01%,” and that’s kind of the pathway of extending it as an IC. Now, if that’s your high level goal and you’re like, “I want to be able…” Let’s say your high level goal is, “I want to be able to do this 10 hours a day because I love it and I want to be able to support myself doing it, meaning I get paid and I have a great job, and I want to have a bunch of impact in the world by doing this thing.”
So again, you still have goals. Then you have to see, okay, “Does my strategy of just deepening these things, is there a pathway to reach my goals according to that?”
And if there is, awesome. Then if someone’s like, “Hey, do you want to 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 the skill you really want to perfect is not something that may be commercially viable in the world, that’s going to somehow allow you to buy the big mansion that you want to buy to support your family, then I think you have to ask yourself, “Okay, so if I just do this, it’s not going to 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 going to 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, what are your goals? And there are cases in which yes, it’ll 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 the giant mansion and all of that, but you’re like, “But I also just want to spend on my time perfecting my egg omelet.”
And then, you’re just in this tension place, and it’s very hard to feel satisfied and fulfilled because you’re a little bit like, “Oh, why doesn’t the world value my deep egg omelet skills?”
You can [inaudible 00:52:27] egg omelet, you should maybe not do this thing. Or if you want this thing, you may actually need to be better at just egg omelets. Perhaps you need to expand your repertoire of cuisines, and go and build a Michelin star restaurant or something.
Lenny Rachitsky: This is really good advice. It’s not just 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, [inaudible 00:52:52] become a VP, you probably need to be really good in big important meetings, and being on the spot, and just not waiting until everything’s over and then sharing an email of all your thoughts.
Julie Zhuo: That’s right.
Lenny Rachitsky: Yeah. For me, I actually went through a period where I was like, “I do not want to get promoted. I’m so happy in this very specific role, just leave me alone.” And that path is very different from the skills I need to build to be a manager. And then things changed and then, okay, now these are the things I need to work on.
Julie Zhuo: Yeah. I love that you knew that about yourself, because I think it’s so easy for a young person to go into their career and everyone is telling them, maybe their whole family has been telling them, “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. What are the trade-offs? And is that really what you want to do? Does that really align with your passions? And of course, sometimes we have to… Again, it’s a compromise for us, but we get to design. We get to design what are goals and what’s the right pathway. And I go back to, usually when people are unhappy, it’s because these things are a little bit out of sync. They want this big thing, but they’re not actually excited about what it takes to do that thing, and therefore it’s just going to be a mismatch.
Lenny Rachitsky: And along those lines 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.
Julie Zhuo: A hundred percent. I think it’s so important to be… We often also have this mental model like, “Oh, our managers are our judge, and they’re going to judge me on whether or not 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’s like, look, the manager has a job, and if you understand your manager’s job, which is how to get better outcomes from the 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 a very direct path to creating value for the team. And that also is a kind of project that suits my skills. It’s something I’m excited about.” 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 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 want to get better at this skill. I really want to get that VP promotion, but I don’t know what it entails. Can you tell me, 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 adversarial, like I’m trying to get you to give me a promotion, and you’re trying to get me to work harder. That is not a very good vibe.
Lenny Rachitsky: 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’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.
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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?
Julie Zhuo: 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 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 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, 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, 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 I’m smiling and I’m very engaging, and I’m telling great stories, but is that really true? I don’t know. The reality is that I’m often biased, and we know these psychological effects where sometimes the Dunning-Kruger effect, 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, “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. 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 truth. And the way I think about it is like, I’m going to ask you for feedback after this podcast episode and you’re going to tell me something. And what you’re going to do is you’re going to give me a gift. Because it’ll be a gift of reflecting something back of what you see that I can’t see. Just like if I have a leaf in the back of my head, I can’t see that. And so if you’re telling me, “Hey, Julie, you have a leaf.”
“Oh, wow, thank you.” Okay, maybe I can get rid of the leaf or whatnot. But that is what feedback is. It is essentially reflection back. It helps us calibrate to reality, and it allows me to get this information about whether or not I’m moving in the direction of my goals.
Lenny Rachitsky: 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?”
Could you give us maybe a tip or two for delivering feedback well and for receiving feedback well? And maybe even just seeking, how do you get more feedback? This all makes a lot of sense. Most of the time people don’t get any feedback.
Julie Zhuo: 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 going to 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 [inaudible 01:01:42] given feedback, because 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 good at this stuff? How about we just work together and we just help each other get better at these things? And the way we’re going to do that is, all feedback is open. I want you to tell me everything. Ideally, you’re going to then say, ‘Yeah, I want you to tell me everything.’” And we’ve already established that.
Lenny Rachitsky: And this is colleagues or manager or all colleagues?
Julie Zhuo: It’s like everyone. It’s like people you’re dating, it’s like your children. It can be with everyone, just establishing what kind of relationship do we want to have? I think most people want to 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… 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 this is the kind of relationship that we want to have.
Lenny Rachitsky: One trickle throughout that I’ve heard that worked really well along these same lines is asking people, “Do you prefer feedback in the moment or do you prefer it kind of every month or every week or something like that?”
And everyone’s like, “No, no in the moment and just tell me as soon as something happens.”
And then that gives you that freedom to just, ” Okay, yeah, let me give you feedback here.”
Julie Zhuo: 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.
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’ve moved from 60% to 80%, it’s going to go well.
But what can often happen is something happens. You do something, it triggers me, because I don’t know, I had a bad experience about that type of thing before. And so, I’m kind of feeling mad and I want to be right. If my real rationale for why I want to give you feedback is I want to validate myself, I want to be right, I want to tell you you’re wrong, I want to punish you, it’s not going to go well. It’s just already there. There’s no way you can deliver it, unless you’re a tremendous actor. It’s just not going to 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 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 want to offend you. I really value our relationship. How am I going to tell you. I don’t want you to get defensive?”
Then the third tactic is, just say that out loud. If I sit down with you and I say, “Lenny, I’m so nervous right now. I want to give you some feedback and I’m really worried that it’s going to impact our relationship, and I so value our relationship and I don’t want that to happen. But I also feel like it’s just going to help you to hear it if you can.”
That does so much of the work of… It’s humanizing. You’re going to realize that I’m going out on the 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 drop it, just lobby 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.
Lenny Rachitsky: This is amazing advice. Very tactical. Okay, 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 not fully grokking for being great managers?
Julie Zhuo: I think the idea of win-win, I think about that all the time in my mind. And I go back to it, because I think that often we have the 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 want to do. I’m going to try and get them to work harder or I’m going to somehow put more pressure on them. 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.”
And I think if you start 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 somebody over the long run 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 the solution that can be a 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 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 huge disservice to this person, and that’s the most awful thing.
But there’s another way to look at it, which is, hey, if there’s persons on the team, they probably want to be successful. They want to do great work, they want to be valued, they want to 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 going to help them be successful is just not the thing that they either want to do or can do at this point, it doesn’t do that person any good for me to somehow try to continue to make it. It’s actually going to be miserable. I’m going back to prolonging that misery state.
And so, sometimes a win-win thing is to just say, “Look, it’s not working, and 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 going to 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, “Oh, my firing them is just definitely going to be a horrible…”
I’m not trying to say it’s not going to be hard, obviously it’s hard, but it’s in the mentality and the mental model I think makes all the difference. Because it’s going to be different in the way that I convey it to them. It’s going to be different and why this actually in the grander scheme of things may be great, and it’s going to reduce this adversarial feeling where they’re now going to see me as an enemy or somebody with all this power who’s making choices that impact them and they feel powerless. It has to be a collaboration. And I think if it’s not win-win… 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.
Lenny Rachitsky: Yeah, I was just going to say, they have to believe this. You can’t just make it sound like this, “Here’s the win you’re getting let go. It’s a huge win for you.” But in reality, the way you phrased it, it is actually almost always true, “This is just not a place that you’ll be happy and succeed at, and it’s better you go do something else.”
Julie Zhuo: Yeah.
Lenny Rachitsky: Okay. I’m going to 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 they’re still not fully getting?
Julie Zhuo: I think being aware of your own energy and conviction is really, really important. So a lot of these themes, as you can see, go back to, you have to first understand this about yourself and 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… We talked a lot about the three pillars of what are the major tools of a manager. The first is people. And so, we talked a lot about 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 the founder of the CEO of the company, but you might be a middle manager. So in some ways, you didn’t 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. They feel like they might have to be 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 thinking through, “Wait, why are we doing this? 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 their manager or whoever else, just so they can get to alignment on, “I really believe in what I’m doing.”
Because if you don’t really believe in what you’re doing or you’re just 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 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 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 going to be very likely that the project’s going to 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’s no case where I can think of where the project somehow turned out to be wildly successful.
Lenny Rachitsky: This is such a classic challenge of managers, is getting things done that you don’t really agree with. And I can’t help but ask you for advice on someone that isn’t in that place of just, “Okay, we have this feature our CEO’s prioritizing. This is not a good idea, but I need to have a brave face and not make it sound like I’m just being told what to do and I’m just reporting orders. I don’t believe in this.” You don’t want to do that. You become a terrible unsuccessful manager and people lose trust in you. What’s your advice to folks that are in that place of just how to find that balance?
Julie Zhuo: So I think, first, if you feel that way, you got to actually find a way to get it out and engage in dialogue. So if you’re like, “My manager told me to do this, I think it’s a terrible idea,” you’ve got to talk to your manager about it or you’ve got to talk to the CEO or whoever and feel… Because once you engage in a dialogue, what will often happen is you’ll learn more, you’ll have new information, you’ll have new assumptions, and maybe you’ll have influenced a project in some manner. But often, the more you can learn about, “Okay, why did some other smart people feel like we should do this? And what parts of it do I believe and what parts am I more skeptical about?”
You can probably decompose it from a blanket it’s good or bad to like, “Okay, this is a hypothesis, this is a hypothesis, this is a hypothesis. I might kind of believe this one. The reason I don’t like the proposal, I don’t believe this particular hypothesis, but I believe these other ones.”
And so, when you can start to get one level deeper into breaking it down into a set of assumptions, that makes it much easier, because then likely find something that you do kind of resonate with. And you might be able to then steer things like, “Okay, if that hypothesis doesn’t… I believe in disagree and commit, but now we can be very specific. We can isolate the thing that…”
And what we can also often do is like, “Okay, the reason I didn’t like this proposal is because I believe that this assumption is wrong.”
I’m going to come up with a really stupid example. But your suggestion is, “I know we have a great idea. We’re going to go and put a lemonade stand on every block. And my core assumption is people do not like lemonade. That’s not the hot beverage right now. And so therefore, I think this is a stupid plan.”
But if I talk to you about it and you’re like, “No, no, this is the core assumption we disagree on.”
Likely what starts to unfold is like, “Well, can we get some data? Can we get some information? Is there a quicker way to validate whether people like lemonade? Perhaps we should just test it in one market before we go and open up the lemonade stands across the entire 50 states.”
And so what happens is we can likely get to the actual specific area and come up with something. And then, if I have to now share with my team, We’re going to try this hypothesis. I’m not sure how I feel about it, but I actually do think… I don’t know for sure and our CEO seems to think this is… But we’re just going to test it.”
For sure, and our CEO seems to think this is… But we’re just going to test it, and we’re going to do the test in a way where… That’s what we want to find out, is do 18 to 25-year-olds love lemonade if we put them on these neighborhood college campuses? It becomes very specific and everyone’s like, “Well, yeah, I don’t know for sure, but I’m happy to go in, and test that, and commit to it.”
Lenny Rachitsky: This is such a good advice, and there’s also, you could layer on, “Here’s the things I do agree with and believe. Here’s the ways that I see this as totally right. Here’s the piece that I’m not so sure about, but that’s why we’re going to run this test, and here’s why it’s the smallest version of this test and why it’s a great idea just to figure it out.” We’ll show them. You probably don’t want to say that. As you give this answer, it’s so interesting, I almost want to do a whole new episode with you later of just common conundrums managers have, challenges that every manager runs into that are really difficult to figure out on the spot. We could save that for the future. Okay, I’m going to take us to a couple of recurring themes on this podcast, occasional recurring that every episode corners that we take guests to.
The first is I want to take us to AI corner. What I like to do in AI corner is ask, what’s a way that you’ve figured out to use AI in your work or your life that’s just really interesting, really useful?
Julie Zhuo: Well, I already shared a lot about education and learning, but I’ll share maybe a more fun story. It’s my kid’s birthdays. One of them just passed. My middle son’s birthday is in two weeks and my daughter’s birthday is in a month.
Lenny Rachitsky: By the way, the birthday just passed. The kid didn’t pass.
Julie Zhuo: Okay. Yes, the birthday passed.
Lenny Rachitsky: [inaudible 01:16:35].
Julie Zhuo: That’s right, that’s right. The birthday passed, my kid’s birthday. One of my goals this year was to try and build them something, so give them a present that has me going back to being the IC and making something for them. AI makes this really fun, and so just from my youngest son who was six years old, this is an idea that I stole from Eric Antonow, if you know Eric. Have you had him on your podcast?
Lenny Rachitsky: I haven’t, I am trying to. He actually sent me the… What is it? The-
Julie Zhuo: Yes, yes.
Lenny Rachitsky: What is it called? The metha-
Julie Zhuo: Methaphone?
Lenny Rachitsky: Methaphone.
Julie Zhuo: Yes.
Lenny Rachitsky: Methaphone, check this out.
Julie Zhuo: Yeah, yes.
Lenny Rachitsky: It’s like instead of holding the phone in your pocket, you hold this thing, and then you walk around with it and everyone’s like, “What the hell is that?” Methaphone.
Julie Zhuo: Yeah. I, too, am the proud owner of a methaphone and the next version upgrades with the little stickers, but-
Lenny Rachitsky: No, I don’t have that one yet.
Julie Zhuo: … Eric is great. You should definitely have him on your… He’s such a creative character. One time, I saw him with a parrot on his shoulder, and I was like, “Why do you have a parrot on your shoulder?”
He’s like, “Well, you can talk to my parrot. It’s a talking parrot,” and then I spoke to the parrot and the parrot spoke back to me. What had happened is that he had hooked up a microphone, he surgically went into the parrot and added a microphone, a speaker, and connected it to voice mode on ChatGPT so that… It spoken I think like a pirate voice.
I was like, “This is the best idea.” My six-year-old son is really into raccoons. He has a huge amount of raccoon stuffies. I was like, “I want a raccoon that can talk to him,” so I made that using the Eric Antonow method, but it was great. It was a huge hit. Now, my middle son’s birthday’s coming up, and he is really into parody. He loves video games, so Minecraft, but what he often listens to on his Alexa are these parody songs. It’ll be like Justin Bieber’s hit or Gangnam Style, but they’ve changed the lyrics so it becomes a video game parody of some video game that he’s playing, and they’re horribly sung. They’re like off-tune, it’s just like some person who produced it. I was like, “Well, if he doesn’t seem to mind off-key singing, I’m going to create him an album of video game parody songs, and I’m going to create an…”
I created an app on Replit, and what it does is you just give it a song. This is Justin Bieber’s Baby and you link to a Spotify song, and I give him some context like, “Oh, Locke likes playing Kingdom Rush right now. We have an inside joke about the gargoyles being free money.” Whatever it is, I just give it a bunch of context. I’m like, “Write me a song that just personalizes it and it’s a parody of this particular video game.” It writes me the lyrics. It’s pretty good at doing this. It’s pretty high quality. Again, it does it according to the beats of the music, and then I just sing it and record it, and then I got myself a song, so I’m creating an album of this, which I’m going to give to him. He’s not going to hear this podcast, so no one spoil it to him. I think this is going to go publish after his birthday, but I’m very excited about this.
Lenny Rachitsky: Wait, so you’re going to be the one singing the song?
Julie Zhuo: Yes, yes.
Lenny Rachitsky: I thought you were going to use Suna or some AI thing to actually sing it.
Julie Zhuo: No, I think I’m going to sing it myself.
Lenny Rachitsky: Wow.
Julie Zhuo: All of this made it so easy. All I have to do is just record. Again, I’m not a very good singer, but it doesn’t turn him off to hear off-key singing.
Lenny Rachitsky: Yeah. Wow, that is so beautiful. This gave me so many ideas for gifts I can give to kids in my life, and I just love how AI is making it, I don’t know, easier to be a parent and, in some ways, more delightful. These are awesome examples. Okay, I’m going to take us to a different corner, contrarian corner. What’s something that you believe that most other people don’t, people would disagree with?
Julie Zhuo: I believe that there’s infinity in every direction. That makes me pretty contrarian on pretty much everything that anyone says. If someone says something like on Twitter, I sometimes play this game with myself, which is in what context would that actually not be true? I think the reality is that the world is so, or at least my reality and my understanding of the reality, is that the world is just infinitely complex. For example, if my kids say something like going outside is boring, or taking a walk is boring, or doing something is boring, my general response will be, “Well, it’s because you’re not seeing the infinity that’s in that direction.”
Even, for example, something really mundane like staring at a blank wall, I think that you can make that actually deeply, deeply interesting, because you can use that as an opportunity to go into your own mind and to figure out how you can make time pass, or you can meditate on the existence or meditate on your breath, or just be grateful for the purpose of being alive. Two people, one person you can say, “Sit in front of a wall for an hour,” and, like my kid, they will super complain and be like, “This is the worst thing ever,” but you can put somebody else like a monk and they’ll have a wonderful experience. It’s not really about the environment or the wall. It’s really about how we see it and whether we can find the thing that is deep, and rich, and infinite in that direction.
Lenny Rachitsky: Wow, these are some deep answers. This is very, I don’t know, Buddhist, very mindfulness-oriented. I did a retreat once and their advice was just anytime you’re bored, just notice all the things that are going on around you. What does your seat feel like right now? What does the air feel like? What are you hearing right now? It’s exactly what you’re saying, there’s infinite things to pay attention to and keep you interested. It’s hard.
Julie Zhuo: It’s hard.
Lenny Rachitsky: Hard to actually do that for a long time and practice. That’s why it’s a practice.
Julie Zhuo: That’s why it’s a practice. But I repeat that to myself, because oftentimes, if I have a bad experience feeling a certain way, it helps me to realize that it’s often probably in my head. It’s because I haven’t gained the skills to be able to see the richness and infinity in that… I can maybe work on that. That feels better than feeling like, “Oh, I’m a victim of my circumstances. This thing happened to me,” and that’s so awful but not powerless, I can’t do anything about it. That, to me, is a worse feeling than the alternative, which is I just don’t have the skill yet. I can recognize it for what it is. I don’t have the skill yet, but I can grow. I can maybe get better at it. There is a person out there who had the same situation as me and feels much more positively than I do, and don’t I want to be more like that person?
Lenny Rachitsky: It’s such a beautiful circle back to our very first episode, which a lot of it was on imposter syndrome and overcoming that and your story there, so I love that that’s maybe a way to close this conversation. But before we do that and before we get to our very exciting lightning ground, is there anything else that you wanted to mention, or share, or double down on that we’ve talked about?
Julie Zhuo: I just want to say thank you. Honestly, I’m so inspired by the work that you do. I know we’ve known each other for quite a while, and I just think from the very first idea that you had for this newsletter, for the podcast, has been incredible, and I think the world gets so much from it. I’m sure you hear that a lot, but I am very grateful.
Lenny Rachitsky: Well, I really appreciate that, and I say this every time we do a chat, is just this wouldn’t have been possible without you, Julie. I was inspired by your longtime newsletter, The Looking Glass. Essentially, my idea was what if I do this for product? I started on Medium just like you did, and then I moved to Substack, and then it’s like, “What if I charge for this?” That worked, and then I’m like, “What if I do a podcast?” and then that worked. But it all began with your concept, so thank you, Julie.
Julie Zhuo: Yeah. I think you do it with so much kindness and curiosity as you always have, so I love that.
Lenny Rachitsky: That’s just who I am. Well, with that, we have reached our very exciting lighting round. I’ve got five questions for you. Are you ready?
Julie Zhuo: I’m ready.
Lenny Rachitsky: What are two or three books that you find yourself recommending most to other people?
Julie Zhuo: The first is Zen and the Art of Motorcycle Maintenance. I absolutely love that book. It’s beautifully written. It’s so deep. My whole philosophy around quality is beautifully… A lot of it comes from that book, the idea and even all the stuff that we talked about change. What does it mean to be at that forefront of change and dynamic quality? I think he just talks about so beautifully and so masterfully in that book. Old classic, but I try to reread it every few years or so. Second is Conscious Business. It is my favorite management book. It’s a little bit of a sleeper head because I actually end up recommending this one far more than my own book.
Lenny Rachitsky: Oh, wow.
Julie Zhuo: I read this one after I wrote my book, and I always tell people that if I read it before, I’m not sure I would’ve written my book, because I would’ve been like, “Conscious Business is really the book that really, really so much resonates.” Many of the things I talked about, this idea of win-win, idea of being a player, not a victim, and how to think about work, not just it’s a job but how do you really think about aligning it with your own personal values and what you want to do in the world, I think that this book really speaks to that so beautifully. It is also very tactical. It’s got a lot of really wonderful examples. I will tell people, the cover isn’t very attractive, and I think that if you judge a book by its cover, this seems very corporate-y. The title also seems like, “What conscious business?” and the first chapter is a little bit more technical. But if you just get past it and get into chapter two and you start with examples of the soccer team, it’s just the best management book.
Lenny Rachitsky: That is good advice to get people over the hump when they look for it. They’re like, “Okay, okay, I’m going to stick with it.”
Julie Zhuo: Yes. Okay, third book. I love the book Good Inside by Dr. Becky. It’s a parenting book and it’s a very wildly popular parenting book, so I really recommend it to all parents, but I also think it’s just a wonderful book for thinking about relationships, because parenting is that. It’s like a very, very deep and intense relationship and interaction that you have with another human being, and there’s so many things that I read in parenting books, including Good Inside by Dr. Becky, that I think could just as well been a management or a team leadership book.
Lenny Rachitsky: I am thinking about trying to ask Dr. Becky to come on the podcast. I feel like there could be a lot of synergy exactly for that reason. She uses this term sturdy, which inspired maybe your bullet tree process.
Julie Zhuo: Oh, yeah, I probably got it… I think she talks a lot about sturdiness and that just incepted right in here.
Lenny Rachitsky: Yes. Yeah. Her whole thing is being a sturdy parent. Strong but flexible, I imagine. Yeah. I love her and I love her stuff. I watch all her videos on TikTok and Emily Oster. Okay, next question. Is there a movie or TV show you recently enjoyed?
Julie Zhuo: I have not watched anything. I have no good answer for you. I think the only thing I watched this year was a rewatch of La La Land, which I do truly love.
Lenny Rachitsky: So delightful. Okay. Is there a product you recently discovered that you really love?
Julie Zhuo: I don’t think there’s anything too new. I love Granola, I love Replit. I’ve used all of the different coding lamps. Cursor is big on me for now. I just got a Matic Robot. I think that’s been really delightful so far, at least the setup. I haven’t used it long, long term, but it’s the setup, the way that it worked. The fact that it had little stickers and you could make it into a dog or a cat was a wonderful experience.
Lenny Rachitsky: The Matic Robot, willing to it, I am also a huge fan. I’m not an investor that’s… Essentially, Waymo meets Roomba. For folks that don’t anything about it, it’s like a very sophisticated robot vacuum built by AI vision people.
Julie Zhuo: Oh, I just thought of one more as well, the Limitless Pendant. Disclaimer, I am a small investor in Limitless, but what I love about it is that… Okay. It’s a pendant, you wear it, and it just records everything that’s going on, and later it summarizes things and it gives you feedback. I don’t usually wear it out because I find that maybe other people feel awkward that I’m recording everything, I usually try and get people’s permission, but I do wear it at home when I’m with my kids, and one of the best things that the pendant does is it gives me feedback on parenting.
Lenny Rachitsky: What? Automatically or run into ChatGPT?
Julie Zhuo: No, automatically. There’s an app and it will sometimes notify me, or if I check it, it’ll… Or I can also engage with Ask It, but what it does is essentially… It’s like Granola, but for your life in terms of capturing everything, summarizing it, and then giving you tips and feedback. It’s said things like, “Hey, there was that time you were talking about the game and you cut your kid off a lot. Maybe next time, think about letting them speak fully and listening better.”
Lenny Rachitsky: The app itself natively does that?
Julie Zhuo: Yeah.
Lenny Rachitsky: I did not know that, because I have one. I haven’t used it much recently. That is incredible. I wonder if it gives you relationship advice too if you’re talking to your partner. I wonder how it even knows.
Julie Zhuo: Yeah. It did a pretty good job of inferring. I think I said person two, but it was kind of eye-opening for me.
Lenny Rachitsky: Incredible. There’s a recent episode of our How I AI podcast, our sister podcast, where somebody wears that in their meetings with their CEO and automatically turns what they’re asking for into a prototype from the meeting notes, and then sales teams can start showing it to people to see if they’re interested. How about that?
Julie Zhuo: That’s awesome. That is super cool.
Lenny Rachitsky: Holy moly. [inaudible 01:30:22], what is even happening? Okay, I’ll keep going. Do you have a favorite life motto that you find yourself repeating to yourself, sharing with others?
Julie Zhuo: I like make it happen. Just a reminder that, at the end of the day, we could have a lot of motion. Maybe this is another one that I really like. I think about this poster. It used to be a poster at Facebook that says “don’t mistake Motion for progress”. There’s this idea of be the change We want to be in the world, I guess is other ways of saying the same thing, which is I can do things. We can all do things. We have better and better tools to go out there and make things happen. Make it happen.
Lenny Rachitsky: The common meme on Twitter, you can just do things.
Julie Zhuo: Yes.
Lenny Rachitsky: Final question. I like to ask this question to folks that are really deep in AI, and been working with AI, and getting a sense of where things are going. Is there something that you teach your kids or teaching your kids, think about encouraging them to learn, knowing that AI is going to be a big part of their life?
Julie Zhuo: Emotional regulation is still really, really, really important. That’s probably the thing that I think about the most in terms of what I want my kids to learn. I want my kids to be able to introspect, to have a better understanding of where their state of mind is, because we’re still human. We still have the same hardware that humans have had for thousands of years, and that’s not changing even as the tools and the environment around us change, and so I feel that you have to really understand yourself and you have to understand what’s going on for you and where you are biased and where you’re not, because AI can make it… This is my great fear, is that it makes things so much more comfortable. I have this great fear that this has been the trajectory that we’ve been on with technology. This is, again, going back to every strength is a weakness.
Technology makes things a lot easier. That’s why we invent, that’s why we create. Human race has always been about trying to better our circumstances and, in some ways, control our destiny, control our future. But at the same time, all of that control gets to a point where we have so many shortcuts in our lives and you can shortcut a lot of things. You can shortcut relationships, you can shortcut hard feelings, because now you can just watch TikTok instead of actually dealing with a very difficult emotion or tension that you had with a colleague, or with your partner, or with your children. AI makes it even, I think, more attractive, because now there’s a person or there’s a thing that can be very, very personalized, and if you’re like, “Oh, I want a distraction, I want to do something,” you got that.
But how do we actually still learn to sit with what is our true biology that’s not changing, and how do we continue to be the kind of people that want to take on the freedom of doing challenging things? Because I find that if we don’t do challenging things, we suffer. We suffer in a different way, and so, to me, true freedom is you can pick the things that are hard and you can feel pride in becoming the thing that you want to be. It’s not forced upon you. It’s not for survival’s sake anymore, but you still have to pick. I want to figure out for my children the fact that it is really important to still find the challenge. Yes, you can use AI to do that, but really, don’t think about it as a shortcut tool, because if that’s the case, I don’t actually think that they’re going to be able to become the kind of people they want to be in the world.
Lenny Rachitsky: What a beautiful way to end this conversation. Julie, it feels like this is just some kind of huge milestone of this podcast. Just like having you back three years later, it’s like, I don’t know, a chapter in the journey. I appreciate you coming back. I appreciate you sharing all this wisdom with us. Two final questions. Where can folks find you online if they want to reach out and maybe chat about maybe Sundial, maybe whatever else you’re up to, and then how can listeners be useful to you?
Julie Zhuo: Well, I would love to work with people who are at companies building really cool things and want better answers to how we build better, and so if you think your company would be interested in working with us at Sundial and figuring out how do we make every single decision maker into their own expert analyst, please reach out. That’s one area, sundial@sundial.so. I am on X, so I’ve been tweeting a lot more, sharing thoughts. Going back to that skill of practicing, just share what’s on your mind.
But for the long form stuff, I have my blog, The Looking Glass. It’s on Substack. I share articles and thoughts about AI, product building, leadership periodically, and then, of course, I have my book, the revised edition with two additional chapters. One is around managing remotely and the other one is around managing in a downturn or managing in difficult change scenarios. That will be coming out in two weeks’ time. The new content will be in the paperback. That’s important. I’ll send you a version of this when I get a copy myself, Lenny-
Lenny Rachitsky: Sweet.
Julie Zhuo: … but the paperback has a gradient type of cover. The hardback will eventually get the new content, but it just takes a while to phase out from all of the different retailers, so if you buy one, I cannot guarantee that it’s going to have the new content. But certainly, the Kindle and the paperback will have all of the new content.
Lenny Rachitsky: Just for the publish day, because this might come out later, what’s the date that’s coming up just for folks?
Julie Zhuo: September 9th.
Lenny Rachitsky: Okay, amazing. I think it’ll be out by the time this is out, so go buy it. I imagine available on Amazon, all your local retailers.
Julie Zhuo: Yes, yes.
Lenny Rachitsky: Amazing. Julie, thank you so much for being here.
Julie Zhuo: Thank you so much, Lenny. This was so fun. I hope to be back in another three years or whatever the next chapter is.
Lenny Rachitsky: Hopefully sooner. Bye, everyone.
Julie Zhuo: Bye.
Lenny Rachitsky: Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at lennyspodcast.com. See you in the next episode.
Glossary
| English | 中文 |
|---|---|
| agent | 智能体 |
| agentic systems | 自主智能体系统 |
| alignment | 对齐 |
| builder | 构建者 |
| charter | 职责范围 |
| disagree and commit | 不同意但承诺执行(Amazon 著名管理原则) |
| evals | evals(评估基准) |
| heuristic | 经验法则 |
| IC (Individual Contributor) | 独立贡献者(已在术语表中) |
| imposter | 冒名顶替者 |
| KPI | KPI(关键绩效指标) |
| motion | motion(忙碌/动作,此处保留原文以呼应 poster 原文) |
| north star | 北极星 |
| PM | PM(产品经理) |
| process | 流程 |
| sleeper hit | 冷门佳作 |
| stuffies | 毛绒玩具 |
| sturdiness | 稳固 |
Reformatted by reformat_english.py
如何赢得朋友并影响决策(Julie Zhuo)| Lenny & Friends Summit 2024
文字记录
Lenny Rachitsky: 我们正在看到组织结构的扁平化趋势,每个人都在重新变成 IC(独立贡献者)。
Julie Zhuo: 过去是这样的:我没有能力做十种不同的工作,但现在 AI 让我自己就能胜任其中很多。我们需要打破这些传统角色的边界,统称自己为 builder(构建者)。我很希望我们能进入这样一个世界——builder 就是我们的头衔。
Lenny Rachitsky: 我还刚看到一个数据,Google 裁掉了大量中层管理者。
Julie Zhuo: 管理依然至关重要。你有一个北极星、一个愿景,你要做的就是想清楚如何利用手中的资源来实现它。过去资源是人,现在基本上是模型,而不同的模型各有所长。你得像组建复仇者联盟一样,把合适的工具用在合适的地方。
Lenny Rachitsky: 你觉得现在管理者的角色和生活最大的变化是什么?
Julie Zhuo: 管理变化一直是管理者的职责。我只是觉得变化的速率在加速。今天的管理真正需要的是”坚固而灵活”的理念。我经常想到柳树的隐喻——它能经受很多风暴和灾难,同时又非常柔软灵活。
Lenny Rachitsky: 你的职业轨迹很有意思,从设计主管到现在对数据和分析如此痴迷。
Julie Zhuo: 你要用数据做诊断,用设计做治疗。数据并不是一个能告诉你该构建什么的工具。我其实觉得很多快速增长的公司目前并没有很好地使用数据。传统上事物不会增长得那么快,这些公司完全靠好的直觉和好的氛围在支撑,但始终会发生的是——增长最终会停滞。
嘉宾介绍
Lenny Rachitsky: 今天的嘉宾是 Julie Zhuo。Julie 是我这个播客的第一位嘉宾,那期节目录制于三年多以前,所以这次对话非常特别。我也在很多其他场合说过,Julie 的 newsletter The Looking Glass 是我创办 newsletter 的灵感来源,基本上引领了我现在所做的一切。如果你还不了解 Julie,她曾长期担任 Facebook 应用的设计主管,该应用被超过三十亿人使用。她也是畅销且非常重要的著作《The Making of a Manager》的作者。最近她创办了自己的公司 Sundial,这是一款 AI parent analyst 产品,被 OpenAI、Gamma 和 Character.AI 等公司使用。Julie 是我见过的最有思想、最有洞察力的产品领导者之一,她对产品构建也有着最独特的视角之一。
曾在 Meta 这样的大型企业担任设计主管,如今又作为创始人经营一家以数据驱动决策为核心的小型创业公司,能拥有这样跨度经历的人实属罕见。在我们的对话中,我们谈到了如何将优秀管理能力直接转化为善用 AI 工具的能力,哪些具体技能在未来几年会变得更有价值,她对新任管理者最宝贵且历久弥新的建议,为什么她的创业公司不招产品经理,以及她判断何时该用数据、何时该凭直觉做决策的简单经验法则。这期节目对每个人都有收获。好了,下面有请 Julie Zhuo。
重逢与回忆
Julie Zhuo: 谢谢你,Lenny。我非常高兴来到这里,期待这一刻已经一整周了。我非常喜欢你的播客,也很喜欢从我们第一次对话至今你带它走到的方向,超级兴奋能有一次有趣而深入的交流。
Lenny Rachitsky: 你能相信第一期节目,就是这个播客的第一期节目,到现在已经三年多了吗?天哪。
Julie Zhuo: 我不确定你当时背景里有那团火。
Lenny Rachitsky: 有趣的是,我不知道有多少人注意到了我一直在保留的这个小彩蛋——在第一个工作室里,我正好在看那期节目,有一面有趣的小镜子。我不确定第一期里壁炉有没有出现在镜子里,因为镜子映出了什么无聊的东西。于是我就把这个壁炉保留了下来,搬到每一个工作室都带着。
Julie Zhuo: 我甚至还记得我们当时聊过,视频还算是比较新的事物。你说”我们会录视频,但主要还是音频”。现在我们已经进入视频时代了。
Lenny Rachitsky: 你这么一说的时候,我才意识到我的壁炉坏了,所以刚刚才把它打开。我们刚才剪掉了一小段。那个壁炉是我给自己留的一个小趣味,我觉得从来没有人发现过。
Julie Zhuo: 非常温馨,我很喜欢。
Lenny Rachitsky: 这正是我的初衷。我其实刚看了数据,从第一期节目到现在,这个播客已经获得了超过两千万次下载,正接近三千万次。
Julie Zhuo: 真的很了不起。我觉得这充分证明了你的好奇心,以及你对打造优秀产品这门手艺的热爱和与世人分享的热忱。我和我的团队都在听你的播客、读你的 newsletter,我们经常分享你邀请的那些精彩嘉宾带来的内容。所以谢谢你做这些。
Lenny Rachitsky: 荣幸之至,非常感谢。三年后我们再次对话的原因是,你的经典之作《The Making of a Manager》要重新发布了。我手里就有一本。这本书卖出了天文数字的册数,登上了我见过的所有榜单。这次你要出平装版,还会新增一些章节。首先想问问,回顾这本书的成功,你有什么感受?
《The Making of a Manager》再版回顾
Julie Zhuo: 说实话,它超出了我的预期,所以我非常满意。我写这本书的主要动机,很大程度上是因为我觉得如果把这些东西写下来,我自己很可能也会成为更好的管理者。这其实是很大的一个原因——我写博客已经写了很久了,我深知自己的一个习惯:当我真正坐下来,试着把所有的感受付诸笔端、给自己写信的时候,这对我帮助极大。所以这确实是一个巨大的驱动力。我当然希望它能面世、能卖出一些。我原本觉得,对于在像我所在的 Facebook 这样的高规模硅谷公司里成长起来的人来说,它可能会引起共鸣。但我没想到它能触及更广泛的读者群,这真的很棒。
有很多人告诉我:“我以为只有我一个人有这种感觉,但这本书让我意识到,原来这些感受再正常不过了。“我自己当年就是这样——一路跌跌撞撞,觉得自己像冒名顶替者(imposter)好多年。所以听到读者这样的反馈,真的非常欣慰。
Lenny Rachitsky: 我觉得它就像是现代版的《High Output Management》。那本书是我播客中被提及最多的,而你的这本书就像是它的现代版本。那本书实际上在很多方面已经过时了,所以我完全理解为什么人们会被你的书吸引。这恰好引出我想深入探讨的第一个话题:你在管理学中学到的很多技能,似乎可以迁移到善用 AI、高效使用 AI 工具上。我想和你聊聊几个相关的趋势,听听你的看法。
人人都会成为管理者
第一个趋势是,感觉在不久的将来,所有人都会成为管理者,因为智能体(agent)将深度融入我们的工作流程。我们正在进入一个智能体化的社会,而优秀管理者所需的技能,恰恰能让你在与智能体协作时游刃有余。对此你有什么想法?你认为这会如何发展?
Julie Zhuo: 我百分之百相信这一点,也完全同意。在我看来,管理就是围绕一个目标展开——你想把某件事做成,就这么简单。你有一个北极星,有一个愿景,然后你要想办法用手头的资源去实现它。通常我们谈管理,在传统语境下,资源指的是人——找到合适的人才,确保你能组建起”复仇者联盟”,拥有所需的技能组合。第二个杠杆是目标——每个人是否清楚自己应该用才华做什么?我们有共同的目标吗?有使命吗?第三个要素是流程(process),也就是所有这些不同的人和工具应该怎样协同运转。
这些仍然是与自主智能体系统(agentic systems)协作的基本法则。你仍然需要一个目标,必须非常清楚期望的成果是什么,而且你必须了解——过去是人的强项,现在基本上是模型的强项。不同的模型有不同的优势,就像它们有不同的性格一样。你得去了解它们,培养一种直觉,这样才能在合适的场景用合适的工具。我们谈到智能体,但也要考虑智能体可以调用哪些工具——你仍然需要在这方面做出决策。当然还有流程,也就是具体怎么做。我认为随着模型越来越强,智能体会越来越聪明,能够处理越来越高层级的任务规划,但我们仍然需要提供正确的上下文、给出正确的高层指令,才能得到想要的结果。
所以本质上,是同样的原则。我完全同意你的看法——我们中越来越多的人需要深耕这些技能,才能高效地使用这些工具。
Lenny Rachitsky: 顺着这个思路,我手边正好有你的书。你写道:管理者的工作是建立一个协作良好的团队,支持成员实现他们的职业目标,并创建流程以使工作顺畅高效地完成——这基本上就是你刚才说的。有趣的是,中间那一条——关心成员的职业发展——在面对智能体时就不需要操心了。你不用担心它们的职业发展和成长。
Julie Zhuo: 确实如此。不过确实有人开玩笑说,如果我们不好好对待智能体,等 AGI 来了会怎样?也许对它们友善一点还是对我们有利的。
Lenny Rachitsky: 我就是那种人——下 Waymo 的时候会对它说谢谢,用 ChatGPT 语音模式也会说谢谢,就像”谢谢你,真的很有帮助”。
与智能体协作的关键技能
Lenny Rachitsky: 顺着这条线,我知道可以展开很多方向,但就管理者所需的核心技能而言,你认为哪些在与智能体和 AI 系统协作时最有价值?我想到的是清晰度、沟通能力之类的。当你想到”学好管理的同时也能让你擅长使用 AI 工具和与智能体协作”,你会想到哪些需要加倍修炼的技能?
Julie Zhuo: 首先是定义目标和结果,对”成功是什么样的”有极其清晰的认知。如果你让一家公司来做这件事,会发现这对人类来说就已经很有挑战性了。很多时候,当我们讨论为什么大公司的对齐(alignment)那么困难,归根结底就是这个问题——不同人对成功的画面可能有截然不同的理解。哪怕我用人类的语言描述:“Lenny,我要做这样一个产品,它会非常棒”,或者”这期播客,你邀请我的时候说希望很多人听到、有所收获”——这些都非常笼统。我们怎么进一步具体化,才能毫无争议地判断是否达成了目标?这其实是一个非常、非常困难的问题。
这对我们来说是个难题,因为同样地,我们往往倾向于非常高层次地思考。所以弄清楚如何把它具体化,让智能体真正理解什么是成功、什么是失败,这本身就是很大一部分工作。我认为这也涉及到——比如,这就是为什么我们需要写 evals,为什么它们如此重要——因为它们帮助我们理解什么是客观标准。现在我做的是数据领域的工作,我的公司致力于自动化数据分析。而一个永恒的问题是:数据和指标以及 KPI 的全部意义,就在于我们试图建立一个更客观的衡量尺度,尽可能清晰地界定成功是什么样的。我认为这与其说是一门科学,不如说是一门艺术。但这是第一点——如果你对成功的样子不够清晰,那你的提示词恐怕也得不到最惊艳的结果。我认为这对管理团队如此,对管理 AI 更是如此。
组织扁平化与”人人都是构建者”
Lenny Rachitsky: 好,那我把这个话题翻过来,聊聊我们正在看到的另一个趋势——组织的扁平化,管理者被裁撤,所有人又重新变成了独立贡献者(IC)。我刚刚请了 Airtable 的 CEO 上播客,他的核心观点就是 CEO 必须重新成为独立贡献者(IC)。他现在写的代码比以往任何时候都多,他的看法是你必须亲自动手、沉浸其中,才能判断产品应该做成什么样。我还看到一条数据,谷歌裁掉了大量小团队的中层管理者。就是一个扁平化的趋势。所以一个问题是:未来我们还需要管理者吗?以及你对这件事会怎么演变有什么看法?
Julie Zhuo: 我认为 AI 在职场中展现出的真正前景和魔力在于,它让每个个体都获得了远超以往的能力。过去的情况是——我没有能力做十种不同的工作,所以我需要通过雇人来补充。我需要一个精通设计的人、一个精通编程的人、一个精通数据分析的人,然后我组建一个团队。但现在有了 AI 这个伙伴,就像,等等,AI 让我自己就能完成其中很多工作。当然,我不会做到所谓的博士水平或最高的 1%、10%,但如果我原本在第零或第 10 百分位,它确实可以在今天非常快地把我拉升到第 60、70 百分位的水平。
我认为这打开了许多扇门。而让我最兴奋的一点——也是我一直跟团队说的——就是我们需要打破这些传统角色的边界。过去,我们有一个传统团队结构:工程师、产品经理、设计师、研究员、数据科学家。而现在团队可以更像——只有两个人。他们可以来自任何传统职能,但关键在于,他们现在可以用 AI 来帮助自己完成以前需要其他人做的大量工作。所以在某种意义上,我们可以放下所有这些不同的角色区分,把我们自己称为构建者(builder)。我认为这是思考我们每个人都能成为什么的最通用方式。我们都可以是构建者(builder)。我很期待我们进入那样一个世界,“构建者”就是大家的头衔。
Lenny Rachitsky: 有意思。这恰好是我越来越常用的一个词。我以前把这个播客和通讯定位为面向产品经理的,后来我开始用”产品”这个词,范围稍微广一点。现在我真的在用”构建者”这个词,我喜欢这个词,原因正是你说的。这也越来越成为这些对话中反复出现的主题——界限正在模糊。我很好奇,在你的公司里,这具体是什么样的?你们的做法有什么不同?你在公司一线看到了什么可能与几年前不一样的变化?
Julie Zhuo: 我们确实裁减了一些角色。比如,我们原本以为需要一批产品经理。结果发现,如果没有产品经理——我知道这可能有点违背 Lenny 当初的初心——但我发现有时候,当你有一个设计师或产品经理,而我是工程师的时候,遇到问题比如需要确定产品定义,我的第一反应就是:我有这些人,这大概就是他们的职责范围,所以我就把这件事交给他们。我觉得这样做——当然我们想保持礼貌,想尊重每个人的领域——但其实是错过了一个机会。作为工程师,我应该想的是:“等等,我也应该投入很多精力去思考。我需要理解并有自己的判断——做什么、用户体验应该是怎样的。”
所以我们发现,如果我们把团队缩小,甚至在过去 AI 时代之前就减少这些角色,反而能让每个人都意识到:“我们没有产品经理,所以沟通是我的事。弄清楚如何为用户创造最大价值,现在就是我的职责范围。“这就是为什么我非常支持缩小团队规模、打破这些界限。当然,我不是说每个人都要做所有事情。我们仍然可以承认你在某个特定技能上可能比我强得多,但重点不再是角色,而是我们所处的具体情境。
我发现,每当你赋予团队更多自主权,让他们基于自己的具体情境做出更多决策,而不是依赖更高层级的规则、政策或”事情就该这样做”的条条框框,你就能得到更好的工作成果、更快的工作速度,以及更快乐的员工——因为人们觉得自己真正拥有了创造想要之物的权力。
小团队中的技能组合
Lenny Rachitsky: 这很有意思——没有产品经理这个约束,反而让工程师意识到不能等别人来做,必须自己去想。但显而易见的难点是,他们必须擅长这件事。从工程到真正善于表达”这是我们要解决的问题、为什么这个问题重要、我们如何排优先级、如何达成共识”——这是非常不同的能力。在招聘这些工程师的时候,知道可能不会配产品经理,你们有什么不同的做法吗?因为要找到一个所有这些都擅长的人,感觉真的很难招。
Julie Zhuo: 确实如此,我并不是说每个人都需要精通所有事情。我觉得那不太现实。比如,如果我们组建一个团队,有几个工程师,但他们都不太擅长思考产品需求或用户角度,那我们确实需要给团队补充一个有这方面能力的人。这个人可能是设计师,也可能是另一个擅长这方面的工程师,也可能是传统的产品经理,甚至有时是一个很擅长这方面的数据分析师。所以这项技能仍然很重要,团队仍然需要具备这项技能,否则可能产出不了最好的结果。但我更愿意这样思考:这个团队需要哪些技能?我们能不能找到几个人来覆盖这些技能?
但这并不意味着我们自动套用那个模板——需要一个 PM、一个设计师、三个工程师,之类的。另一个例子是我们对前端、后端工程的思考。以前的情况是,有些人就是前端工程师。所以如果你有一个项目,既涉及前端又涉及后端,最省事的做法就是”我需要一个前端、一个后端,就这样搞定”。但如果你说,你是一个工程师,你是一个构建者,这个项目有一点点前端的工作,但你知道吗?你大概率能搞定。用 AI 辅助你来搞定。显然可以找一位专家来帮你 review 代码,或者给你一些高层次的指导,但直接去做就好了。自从我们开始推行这种方式之后,我们发现同样需要在一开始投入一些成本。大家一开始没那么自在,他们需要学习,所以初期事情会花更长时间,比直接安排一个前端专家来做前端项目要慢一些。但从长远来看,这笔投资真的会有回报,因为现在有更多的人变得更全面一些,能够独立承担更多的模块。当然在特定场景下,如果某个项目前端极其密集,那当然可以引入在那个特定技能上更专业的人。
AI 工具带来的加速
Lenny Rachitsky: 我很喜欢你这样的经历——在 Meta 这样的大型公司工作过,现在又在打造自己的小型创业公司,而且正好处在这个趋势中:保持非常小的规模,保持非常精简,每个人都做更多的事情。你能亲身体验这些真的太棒了。我有几个问题想问——在所有这些 AI 工具中,你看到哪些职能被加速得最多?是工程?还是其他方面?另外,有没有哪些工具对你们帮助最大?就是那些让人觉得”我应该去试试”的 AI 工具。我猜是 Cursor,但好奇还有没有其他的。
Julie Zhuo: 嗯,工程肯定是其中之一。毕竟我们公司大部分都是工程师,所以这是我们重点投入的领域。我也确实看到更多的人开始做原型设计了。我们有两个设计师,但我们也会看到工程师自己动手。我们有一个团队叫 product science,是一个很有趣的混合体——你可以把它想象成一个前线部署的角色,拥有很强的数据分析背景,同时扮演着某种客户成功的角色,也扮演着某种产品的角色。你会看到他们也开始构建更多原型,或者参与到一些工程工作中。所以看到这种每个人都能做一点其他领域工作的融合真的很棒,而且我们都在互相鼓励。我们最近在努力推动的另一件事是,显然我们会说,“嘿,工程师,现在你也可以做分析了。”
他们的第一反应是,“哦,我不太懂分析。“这时候 ChatGPT 就派上用场了。按照传统,我们会说”我得跟一个真人学,我得去问某个人,然后占用他大量时间让他给我解释所有东西。“但事实上,我觉得现在 ChatGPT 或者其他 AI 工具是更好的老师。我发现我们可能还没有充分把它们用于加速学习或系统性地过一遍某个领域。有时候我会这样做——我在网上找一个课程大纲,如果是一门课的话,通常是一个 12 周的课程,我就把它喂给 ChatGPT,然后说,“帮我按照我喜欢的学习方式,为我定制一个学习计划。”
我是那种特别需要例子的人。我需要很多”当我五岁一样解释给我听”,给我一个类比。而我知道我团队里有些人会说,“这些例子根本说不通。“我们的学习方式不同,所以一个能为每个人个性化学习方式的工具,确实能帮助我们加速,比以前快得多地掌握这些技能。是的,工具很棒。我们用 Cursor,它能帮我们自动补全,写很多东西,但学习的加速我认为是我们所有工具库中另一个可能被低估的工具,因为我知道每次我跟别人聊起这个,大家都会忘。我们不会想到,对啊,我们其实可以这样做——坐下来,大概 30 分钟或一个小时,就能比以前快得多地学到很多东西。
Lenny Rachitsky: 这个观点很有意思。有些工具是即时帮助你提速的,但有时候你确实需要学习一项新技能,需要一些基础性的课程。你的团队在哪些领域做过这样的事情?他们学了什么?
Julie Zhuo: 我举个例子。我今天早上刚和一个工程师聊过,他写了很多算法。我们公司做的事情之一是尝试自动化数据分析,所以我们显然需要理解最佳实践。如果有一种类型的问题是——
Julie Zhuo: ——我们需要理解最佳实践。如果有一种类型的问题,“嘿,哪些功能才是人们真正愿意付费的?“我们需要搞清楚该做什么样的分析。那位工程师跟我说,“Julie,我觉得我真的理解了怎么做。我知道算法,我知道我们做根因分析,知道怎么做。但我不太理解的是为什么,或者什么时候这最有用。在公司的什么场景下会出现这种需求?“因为他是一个工程师,他没有做过 PM 或高管那种会问这类问题的工作。而这恰恰是那种完美的情况——按照传统你可能会去问某个人,但这个话题其实更通用,互联网上有大量相关资源。这是那种你只要跟 ChatGPT 聊,它大概率会给你一个更好的答案,而且能让你深入探讨的问题。
我们还在学的另一件事是——几乎像是把 ChatGPT 当作一个……用来测试你的学习成果。它解释完一堆东西之后,我经常喜欢这样做——“好,我读了这个,所以这意味着……”我尝试用自己的话把听到的复述回去。“所以这意味着……这个类比是这样理解的,对吗?“然后 ChatGPT 会纠正我。“是的,这个是对的”,或者”不对,你理解得不太对。事实上……”它总是很委婉地说。这其实挺逗的。它会先说”很接近了”,然后最终变成”你完全错了。“就那个风格。但这真的很有帮助,因为它是交互式的,所以我们可以通过尝试用自己的方式复述回去,来真正测试自己是否理解了这个概念。
AI 公司的数据分析实践
Lenny Rachitsky: 这一轮 AI 突破正在以如此多的方式帮助我们进步、学习更多、变得更好,真是令人惊叹。我知道有一些负面影响,但它确实了不起。有这么多方式让我们变得更好、更快。我想在数据分析这个话题上再多聊一会儿。你从大公司工作到创办自己的小公司,从设计负责人到如今痴迷于数据和分析,这段轨迹非常有趣。所以让我在这个方向上多聊聊。那些已经搞清楚如何用 AI 做数据分析和数据工作的 AI 公司,他们到底在做哪些与众不同的事?在这方面,人们在哪些地方还没跟上、还在错过什么?让我再补充一点——感觉我们几乎是在逐一攻克团队前进道路上的各种阻碍。比如等 PM 写 PRD,等数据科学家给你分析结果。这是又一个很酷的解锁,让每个团队成员都能突破瓶颈。
Julie Zhuo: 你的第一个问题是,许多 AI 公司在数据使用上有什么不同?有趣的回答是,我其实不认为目前很多高速增长的公司在很好地使用数据。主要原因在于,传统上事物并没有增长得那么快。所以如果你做到了一亿用户,你的公司可能已经存在了很长一段时间,而如果你的公司已经存在了很长时间,你就有时间去搭建日志系统,你已经在那个阶段招了增长团队、招了数据团队,他们做了大量的日志埋点和数据转换工作。我们也讨论过业务的可观测性应该是什么样子。你通常有数年时间来构建和发展这些能力,因为增长的速度就是那样的。
而今天我们看到一些公司增长极其疯狂,但团队可能仍然只有大约十个人或者两个人,不管多少人,但他们的 ARR 已经达到数亿美元,用户数达到数亿。而你知道吗?他们其实并没有所有那些基础设施、那些日志系统来真正做数据分析。所以我会说这些公司完全是靠好的直觉和好的氛围在维持,我们也确实看到了这一点。有时候你并不真的需要数据分析也能做出有效的东西。但我认为数据帮助我们做的事情是,在我的理解中,它帮助我们映照出真正的现实。当然,如果 ARR 在增长,太好了,继续做你正在做的事。但总会发生的是,增长最终会停下来。增长不会永远持续。通常当增长停滞时,每个人都会有这个问题:“怎么回事?为什么会出现这种情况?”
这时候你就能看到它强大的地方了——如果你把一切都做了很好的埋点,对业务有一个非常好的可观测性模型,切入根因就容易得多,甚至预测增长是否会在某个时刻放缓也更容易,更早捕捉到这些趋势也更容易。如果你对业务的运转方式和公司的关键杠杆没有良好的可观测性,那你就会手忙脚乱,而那通常就是人们开始大量投入数据的时候。所以我不认为很多当红公司已经到了那一步,但我认为另一个趋势是,每次出现新的技术变革,我们实际上都必须改变我们思考的方式——分析必须回答我们所面临的问题,如果技术变了或环境变了,我们就需要新的分析方法论。
对话式分析的新挑战
比如,当移动互联网走到前台时,查看会话数、每日会话数、移动端使用时长、会话长度等指标,就成了我们需要理解的重要维度,用来判断人们是否在这个新媒介中获得了价值。我认为今天的情况也是如此。对话式分析完全不同。过去在谷歌的世界里,我知道你对购物感兴趣是因为你点了购物标签,我知道你对地图感兴趣是因为你点了地图标签,我们可以衡量点击。今天这一切都是对话,所以实际上更难分辨用户的意图到底是什么。
如果我在任何一家做大模型的公司工作,我想最大的问题之一就是:哪些用例在增长,哪些用例在萎缩?今天这更难判断了,因为它不再是对标签或页面的点击。我们可能需要用一个大模型或机器学习模型来对用户意图做分类。我们可能需要问这样的问题:对话流程是否顺畅?比如如果我只问了一个问题,没有来回交流,用户是否获得了价值?我们一直在试图回到这个问题——我们想弄清楚这是否是一次好的体验,但现在我们需要真正发明新的方法论来帮助我们分析它。
Lenny Rachitsky: 对,我觉得问题总是在于,对于对话来说,你到底希望它是长对话还是短对话?什么是正确答案,什么更好?
Julie Zhuo: 是的。
Lenny Rachitsky: 我之前请过 ChatGPT 的 Nick Turley 上播客,结果发现他们早期找到最常见用例的方式之一,就是看 TikTok 上的评论和在 TikTok 上疯传的内容。你敢信?
Julie Zhuo: 是的是的。
设计师与数据的关系
Lenny Rachitsky: 好,我想回到你走过的这条非常有趣、不同寻常的路——从 Facebook 的设计负责人,到成为众多设计师的灵感来源,如今你把时间花在一对数据创业上,痴迷于数据。怎么说呢,传统上设计师并不是实验和数据以及基于数据做决策的最大拥趸。当你看到设计师们,听到他们那种抵触的声音——“不,我们不想被数据驱动,我们比数据更懂……我们有对美感和优秀产品的直觉”诸如此类——你觉得设计师们在感受到和说出这些话的时候,他们错过了什么?当他们害怕写实验、害怕面对数据、想要把这些推开的时候?
Julie Zhuo: 有一个说法是我和我联合创始人在很早期经常私下讨论的,也跟我们合作的很多公司分享过,那就是——你真正想要的是用数据诊断,用设计治疗。数据不是那种会告诉你应该做什么、解决方案是什么、或者我们该怎么解决留存率不好这个问题的工具。它不是。但它可以告诉你是否存在问题,以及那个问题或机会可能在哪里。你仍然需要回到一个非常有创造性的流程中去,找出解决问题的最佳方式。所以我想说的第一件事就是这个框架——数据帮助你弄清楚到底发生了什么,人们喜欢什么,他们在参与什么,什么没有效果。
它只是给你一个更贴近现实的故事。因为说到底,我们都有自己的叙事。我们会说,“哦,我的公司棒极了,人们都爱我们”,等等。那是我想相信的故事,但现实可能是另一幅图景。所以数据试图做的就是捕捉现实。顺便说一下,我不认为数据仅仅意味着 AB 测试和可以量化的指标。对我来说,数据也是——人们在 TikTok 上发了什么,哪些东西疯传了,他们在 Twitter 上或者说现在应该叫 X 上说了什么。
数据的虚假精确性
Julie Zhuo: 如果你做了一次用户访谈,那仍然是数据,只是那种数据更难提炼和量化。不过现在有了 AI,我们有更好的工具来做综合分析了。所以在我心目中这些都是数据,它们都在试图帮助我们理解到底发生了什么,现实中正在发生什么现象,以及我们如何理解它?你仍然需要去发明、去创造、去梦想,没有公式,也没有哪门科学能确切地告诉你怎样才能做出一个爆款。你可以做实验,这也许能让你尝试更多东西,更严谨地了解短期内会产生什么效果。但这一切都非常依赖具体情境。AB 测试无法告诉你长远来看会发生什么,而且话说回来,这些都还是数据,你仍然需要综合分析,判断该怎么做。
所以我想说的就是——用数据诊断,用设计治疗。我通常会跟设计师们说的第二件事是,我发现有时候——也许可以称之为数字带来的虚假精确性吧,我们很容易掉进这个陷阱里,对吧?因为感觉就像是,好吧,我们拿到了这些数字,数字涨了。但实际上,你仍然要选择看哪些指标,这本身就是一门艺术,不是科学。你对数字涨了 5% 的解读——这算好还是不好——同样是一种解读,同样是一门艺术,不是科学。只是有时候我觉得我们会给自己制造一种错觉,我理解这一点——有时候人会有一种想要控制一切的直觉,我们希望一切都整整齐齐,我们想知道只要做了 ABC,一切就会很好,我们的职业生涯会很棒,我们的产品会一飞冲天。
我觉得设计师们对此的抵触是有道理的,他们会说:“不,现实是这些东西本身就是模糊的,存在不确定性,我们永远无法确切知道。“我认为这些都说得非常对。所以我非常支持的另一个观点是,你确实不可能靠 AB 测试一路测出一个伟大的产品。这是我根深蒂固的信念,但我认为我们不应该因噎废食。我认为实际上……你懂吗?这不是非此即彼,不是数据或设计二选一。
它们只是我们可以使用的工具。而且我想说,我见过的每一位优秀设计师,都极度痴迷于试图更好地理解现实。他们想知道用户真正在想什么,他们真正在做什么。如果他们能读懂每个用户的心思——那正是我们所有做设计的人最渴望的事情——如果我能知道每个人在使用时在想什么、感受什么,我的工作会轻松很多,因为我就能构建出越来越好的东西。所以这就是数据试图帮我们做到的。它并不完美,没有任何一个指标能像我们期望的那样给出真正的确定性和精确度,但这并不意味着我们不能用它来改进我们的产品开发流程。
Lenny Rachitsky: 我正想说你刚才说的那些话——每一位与我合作过的优秀设计师都对数据非常痴迷,是那种主动拥抱数据的人;而那些说”不,我觉得我差不多行了,我对什么是对的有一种感觉,为什么要让数据来告诉我们该怎么做?“的设计师则不然。而且正如你所说,数据不会告诉你该做什么,它会告诉你机会在哪里。
AI 时代的管理变革
让我把话题拉回到管理这个话题上,我想问一个比较大的问题:随着 AI 的兴起,你觉得管理者的角色、日常工作和管理生活,发生的最大变化是什么?
Julie Zhuo: 我觉得是管理变化。管理变化一直都是管理者的工作,也总会伴随着各种混乱的状况。我只是觉得变化的节奏正在加速,过去几十年我们一直在见证这一点。所以我发现人们现在面临的不确定性要大得多,比如两年后 AI 会走到哪一步?我不知道。谁真的知道呢?我们五年内会实现 AGI 吗?这种事情会极大地改变整个格局。更不用说,我认为很多组织正在感受到相当大的恐惧。比如我一直在做设计,现在这些工具在我擅长的领域越来越厉害了,那我的职业生涯和未来怎么办?我需要转型吗?我需要学不同的东西吗?
所以这就是变化,就是这种不确定的感觉。而且我认为很多时候管理者必须应对这些,除了你之前说的那些——他们自己也必须学习这些新技能,也就是管理 AI,管理他们工具箱中这些更强大的工具来完成工作。所以我觉得这与十年、二十年、三十年前非常不同。因此我认为变得更重要的技能,显然是沟通、反馈、共情能力——就是能够与人协作,让他们理解:是的,我们正处于一个变化的状态。我认为现在每位领导者都必须这样做,我认识的每位创业创始人、每位 CEO 都在思考——你如何传达”情况正在变化,我们需要对变化非常开放”这个信息?
如果我们固守旧的方式,我们很可能会被抛在后面,我们的产品会被抛在后面,甚至我们做事的方式也会被抛在后面。所以我们需要改变。我们需要改变我们的产品,也需要改变我们工作的方式,就像我们之前讨论的那样——更小的团队,更敏捷,等等。但与此同时,我们如何做到这一点,而不让所有人都恐慌?不让人觉得”天哪,一片混乱,一切都在变”。
所以我经常想一个关于垂柳的比喻。垂柳是一种非常坚韧的树,它能经受很多风暴和灾害,但它同时也非常柔韧。它的枝条非常非常柔韧,在某种意义上正是这种柔韧让它能够如此坚韧。所以我认为今天的管理,核心就是”坚韧而柔韧”这个理念。这是一个非常难以做到的事情,但我觉得至少当我去面对的时候……我会跟自己说,“像垂柳一样,Julie。想象那棵垂柳,试着把那种感觉融入到我们共同做的事情中。”
Lenny Rachitsky: 这让我想起之前几位嘉宾说过的一些话。Marc Benioff 来上播客的时候,我问他,“你到底怎么应对所有这些变化?现在又是智能体,又是什么……正如你说的,AGI 也要来了,你靠什么撑过去?“他的建议就是——他说,“我总是告诉自己:‘很好。这太棒了。这就是我们想要的。这太令人兴奋了。我们有这么多机会,关键是绝对不会无聊。我们可以一直重塑自己。‘“他总是以一种”这是好事”的态度去拥抱变化。他回应那个问题的方式让我永远忘不了。
Julie Zhuo: 我觉得如果你不觉得这是好事,那这种活法会很痛苦。接下来的日子会非常非常艰难。所以我确实认为,在条件相当的情况下,不如拥抱它。如果你每天醒来都能把它看作机会和兴奋,而不是恐惧——当然,它们就像硬币的两面,一直都在——但我觉得如果我们能更多地拥抱”它可能变成什么”,同时承认另一面确实存在,它一直在那里。而且我觉得,如果一个管理者试图假装它不存在,一切都很好,没有人不高兴之类的,那也少了些什么。你需要能够直面现实,承认——是的,这很难。变化很难。我们可能会焦虑。我们会有一些混乱。这些都会发生,但我们会一起走过来的,因为我们会保持柔韧,我们会把目光放在大局上,看到那些令人兴奋的可能性。
Lenny Rachitsky: 你说到这里,我想起了另一句话。我忘了是谁说的了,可能是 Kevin Wheal,也可能是 Mike Krieger。他们说,现在将是最正常的时刻——以后只会越来越奇怪。我觉得给人们这样一种感觉,就是——好吧,享受当下的正常吧,因为接下来只会更奇怪——至少能给大家一个真实的预期,知道事情可能往哪个方向走。
Julie Zhuo: 是的,是的。
Lenny Rachitsky: 活在当下这个时代,真是不可思议。
Julie Zhuo: 真是不可思议的时代。
管理中永恒的课题
Lenny Rachitsky: 好,让我们再把视角拉远一些来聊聊——我想问的是,撇开 AI 不谈,管理在很多方面其实没有变。它仍然是很多相同的工作——管理人,帮助他们成功,产出优秀的成果。你觉得有哪些最经得起时间检验的、最重要的经验教训,是你认为管理者——尤其是新管理者——还没有完全理解、需要多听听的?先说说浮现在你脑海里的?然后我们再看看这个话题能走到哪里。
Julie Zhuo: 我首先想到的是管理自己、理解自己的重要性。这是我书的第五章,叫”管理自己”。事实上,写的时候我很想把它放在第一章,然后我的出版商说,“嗯,也许你应该先讲一些更实操性的内容……”人们不一定认为管理他人或管理团队要从自己开始,但我确实从根本上相信这一点,因为我认为我们每个人,和任何人一样,都有擅长的东西,也有不擅长的东西。而且我非常相信,每一个优势本身就是它自己的劣势,每一个劣势也是一个优势。
不存在什么”你能在每个维度上都达到百分之百”这种事。事实上,我觉得对我自己来说最有趣的概念或框架之一——这也是一种数据框架的概念——就是维度的概念。所谓维度,就是你是一个人,但我们可以从无限个维度来看你。比如说,Lenny 扔飞斧的水平如何?这就是一个维度。
Lenny Rachitsky: 还不错。
Julie Zhuo: Lenny 做播客主持的水平如何?非常出色。
Lenny Rachitsky: 还行吧。好,谢谢。
Julie Zhuo: Lenny 在 AI 领域做一个从零到一的项目的能力如何?对吧?所以你看,可以把它想象成无限个维度。而现实是,我们每个人的画像都非常独特,就像指纹一样。对你来说,有些领域你非常出色,远超常人,排在最顶尖的 1%。然后有些领域你在前 10%,有些领域你处于平均水平,还有一些维度你低于平均水平——和其他人相比。这对我们所有人来说都是如此。而我喜欢这个框架的原因是,如果你接受这个模型,你就会意识到,这些维度中没有哪一个就是你全部。所以我可以对你说,“Lenny,你扔飞斧真的需要提高一下。“理想情况下,你不会觉得”Julie 在说我是个糟糕的人,我的身份认同受到了威胁”,对吧?因为它只是你的一个维度而已。但有时候发生的情况是,我们会对某些维度非常执着,因为我们开始认为那就是我们本身。我觉得管理者会这样,他们团队里的个体显然也会这样。一旦出现这种情况,就很难进行更加客观的对话——好吧,你在哪些方面可以做得更好?哪些方面需要改进?所以我说这些,是因为我觉得这个框架——至少对我自己和我聊过的很多人来说——帮助大家意识到,别人可以给你反馈,或者你在某些维度上可能不那么出色,你有提升空间,但这并不代表你是谁,因为你是这无限个维度的总和,它们中没有哪一个能代表你作为个体的真正价值。
我深信我们每个人都是美好而有价值的,当然我们有这些技能,我们想要提升这些技能,但你在这些技能上是强还是弱,并不能说明你是否有价值。所以我觉得如果你能接受这一点,真正把它内化,那么作为管理者,你就能更客观地看待自己,你就会意识到有些领域你确实很强,有些领域你有偏见,而往往这两者是同一回事。举个例子。人们经常告诉我,我过去在绩效评估中也会从管理者那里收到这样的反馈——“Julie,你很有思想。当你思考一个问题的时候,你有自己的一套思考方式,显然你做了深入的思考,你有这些框架等等。这是很好的。“而另一方面,我也会收到这样的反馈——“Julie,你在动态讨论中说得不多。你比较安静,不太擅长即兴反应。“然后你就会意识到,这其实是同一枚硬币的两面。因为我不那样做,我不会随口就来,这才使得我往往能够非常有思想——或者至少,好吧,在我年轻的时候就很明显——那个特定的弱点其实也在说明一个特定的优势,就是我这种人不会总是有即兴的判断。我需要真正去思考它、内化它,有时候需要先弄清楚自己的感受,然后才能把它分享和呈现给世界。
所以,了解自己的这一点极其有帮助。当然,这不意味着我永远不能在这方面变得更好,但我经常思考的是,所谓精通,就是当我们意识到这两者我们都可以提升,而我们需要做的是根据具体情境判断怎样做是合理的。所以我收到这个反馈,我就想,“好的,我需要改进的一点是,想办法在当面交流中更开放一些,说得再清楚一点,也许可以说类似这样的话——‘我还不完全确定自己怎么想,但这是我目前的想法’“——如果有一些明确的具体方法能让我成为一个更有效的团队成员,在我的团队中把工作做得更好,那我应该去做。
Julie Zhuo: 所以我一直在努力培养这些技能,但更上层的元技能是能够退后一步说,好吧,在某些情境下,快速行动、果断决策、先做再说确实很重要。即使不完美,我们也必须去做。如果我在这一点上有困难,我应该意识到这是需要改进的地方。但在其他情境下,正确的做法恰恰是退后一步,深思熟虑,不急于做决定。
所以我想表达的不是说要否定这种优势或弱点,而是要知道这就是我们的出发点,我们天生可能就以某种方式运行。我们的成长往往表现为在做相反的事情上变得更好,但不是抛弃我们擅长的东西,而是随着时间的推移,达到一种平衡——我们能够读懂情境和场合,知道”这次我是不是该更多地深思熟虑,还是这是一个需要更果断一些、直接说出我此刻想法的时刻?“
优势与弱点的两面性
Lenny Rachitsky: 我很喜欢这个建议——我们极其擅长的东西也有其代价,而我们收到的反馈中那些我们不擅长的方面,往往也有一个被人们欣赏的正面版本。我本来想问你这个问题,我觉得你已经回答了大部分,但就是当你收到”Julie,你在这些会议上说得不够多,你的贡献不够及时”这样的反馈时,听起来,一种选择是”好吧,这就是我,我就是这样的,我换一种方式来解决问题,不去改变任何东西。“但我听到你说的是,找到你想要真正改变那种行为的机会,即使那不是你的本能,特别是在事情进展很快的场合。我想问的是,你建议人们在让自己不擅长的事情上推自己走多远,而不是更多地投入到自己的强项上?
Julie Zhuo: 哦,我觉得这是一个非常好的问题。我的思考方式是,这很大程度上取决于你的目标是什么。比如,假设你是……让我们拿独立贡献者(IC)和管理者来举例。我经常思考独立贡献者的成长路径,他们想要深耕一门手艺。你热爱这件事,就想在这个非常具体的技能或手艺上变得越来越厉害。在我们的维度模型里想——就像你选了几个维度,“我就想让这几个达到前 0.01%,“这基本上就是独立贡献者延伸自我的路径。现在,如果这就是你的高阶目标,你觉得”我想要能够……”假设你的高阶目标是”我希望能每天做这件事十个小时,因为我热爱它,我希望能靠它养活自己,也就是说我有报酬、有一份好工作,我希望能通过做这件事在世界上产生影响力。”
所以,你仍然有自己的目标。然后你就要看,好吧,“我仅仅深耕这些技能的策略,有没有一条路径能让我达成目标?”
如果有的话,太好了。那如果有人来问,“嘿,你想做管理者吗?”
你就可以说,“不想,因为这是我的目标,而这条路实际上能让我实现它们。”
但如果你在某个节点发现,你真正想精进的技能在商业世界中可能并不那么可行,没办法让你买下你想要的大豪宅来养活家人,那你就得问问自己,“好吧,如果我只做这件事,那是远远不够的。我可能实际上需要学一些其他技能,才能胜任一份足够有价值的工作,让人们愿意在高层次上付给我很多钱,这样我才能买得起我的豪宅。”
所以我认为一切都要回到你的目标是什么。在某些情况下,是的,这样做、深耕你的手艺是符合你的目标的。在另一些情况下则不然。我觉得这很重要,这对每个人来说都是一个非常个性化的问题。但我经常认为,所谓的痛苦,就是当这些东西不一致的时候。你想要的是大豪宅和所有那些东西,但你又说”可我只想把所有时间花在研究怎么做好蛋包饭上。”
然后你就处在这种紧张状态中,很难感到满足和充实,因为你有点像在说,“哎,为什么这个世界不看重我高超的蛋包饭技能呢?”
你可以选择不做这件事。或者如果你想要那个东西,你可能确实需要在蛋包饭上做得更好。也许你需要扩大你的烹饪技艺范围,去开一家米其林星级餐厅什么的。
Lenny Rachitsky: 这个建议真的很好。它不是说一定要总是补短板,也不是说不用管它们,而是说——如果你需要做这件事才能实现你的目标,那你得先搞清楚你的目标是什么。然后问自己,这件事是不是你需要去努力的?比如,你想当 VP,那你可能真的需要在重要的大型会议上表现出色,能够当场应对,而不是等到一切都结束了再发一封邮件分享你所有的想法。
Julie Zhuo: 没错。
主动设计自己的职业路径
Lenny Rachitsky: 是的。就我而言,我实际上经历过这样一个阶段——“我不想升职,我在这个非常具体的岗位上很开心,别来烦我。“而这条路和我需要成为管理者所需要培养的技能是非常不同的。后来情况变了,好,那这些就是我现在需要努力的方向。
Julie Zhuo: 是的,我很欣赏你对自己有这么清楚的认识,因为我觉得年轻人进入职场时太容易被这样推着走了——也许他们全家人一直在告诉他们,“你需要往上走,你需要赚更多钱。你需要拿到那个管理者的头衔。你需要当上 VP。”
到了某个节点,我觉得有时候人们在没有真正了解自己到底在签署什么的情况下就选择了这条路。权衡是什么?那真的是你想要的吗?那真的符合你的热情所在吗?当然,有时候我们不得不……说到底,这是一个妥协,但我们可以去设计。我们可以设计自己的目标是什么,正确的路径是什么。我经常说,当人们不开心的时候,通常是因为这些东西之间有些脱节。他们想要那个大目标,但并不真正对实现那个目标需要付出的代价感到兴奋,因此就会出现错配。
Lenny Rachitsky: 顺着这个思路,听起来好像,哦当然,我可以设计我的人生、设计我的角色。但我的发现是,如果你至少首先清楚自己热爱什么、理想情况下想做什么,然后至少把这件事告诉你的管理者,往往比你想象的要可行得多。
Julie Zhuo: 百分之百同意。我觉得主动沟通非常重要……我们往往还有一个心理模型,就是”哦,我们的管理者是我们的评判者,他们要评判我做得好不好,我是不是该升职,我是不是该被开除。”
所以人们有时会有这种恐惧,但我觉得在最好的上下级关系中,管理者更像是一位向导。要知道,管理者有自己的职责,如果你理解管理者的工作——也就是如何让团队产出更好的结果——同时你也清楚你的管理者认为什么才是团队的成功,那你就会更容易发现:“哦,如果我做这个项目,那就是一条非常直接的为团队创造价值的路径。而且这个项目也适合我的能力,我对它也很感兴趣。“你应该主动把这个建议提给你的管理者。
反过来也是一样的道理。如果你去问你的管理者:“你的工作是什么?你认为什么是成功?你最大的期望和目标是什么?“了解了这些信息,你也能更好地帮助自己的职业发展,因为你掌握了这些上下文。反过来,如果你说:“嘿,管理者,这些是我的期望和目标,我觉得这是我擅长的,我真的想在这项技能上有所提升。我非常想获得 VP 的晋升,但我不知道需要做到什么程度。你能告诉我需要具备什么条件吗?”
这也是一段非常好的对话,因为你会获得所有这些上下文,然后你才能真正决定自己是否想要去做。如果你想的话,就请管理者帮忙:“好的,如果你看到有能帮我成为更好的演讲者、提升沟通能力的机会,请告诉我。“更好的是,“如果你对我的沟通有任何反馈,我想听,因为那才是帮我在这项特定技能上成长的东西。”
这样一来,这就会变成一种协作关系,而不是那种几乎对抗性的——我试图让你给我升职,你试图让我更卖力工作。那种氛围是很糟糕的。
Lenny Rachitsky: 这让我想起 Ethan Evans 写的一篇客座文章,我会附上链接,里面有一个非常好的框架,正好讲的就是你说的这件事,叫做”魔法循环”(The Magic Loop)。它提供了一个框架,帮你搞清楚该做什么工作、如何让你的管理者看到你的能力,从而赢得信任。
反馈的力量
Lenny Rachitsky: 说到经典的、尤其是给新管理者的建议,你已经分享了很多。还有什么你觉得特别重要、特别有意思、特别有价值的吗?
Julie Zhuo: 反馈是另一个我非常非常热衷的话题。我对自己和我共事过的所有人的总体印象是,我们对反馈的重视程度远远不够,或者思考得远远不够。同样,公司有绩效周期,所以我们都说,好的,每六个月我们去做一次评审,那时候我会得到反馈。但在我看来,反馈理想情况下应该是一种日常实践。因为对团队来说,长远来看真正重要的是我们进步的速度有多快。一个每周进步 1% 的团队,哪怕起步的基准线低得多,也会在很短的时间内超越那个每月才进步 1% 的团队。
那么,让我们变得更好的最好工具是什么?就是反馈。我对反馈的理解,和我们之前谈到的数据指标非常相似——本质上就是把你的假设拿出来,与现实进行检验。举个例子,也许我现在觉得自己是一个积极且有感染力的演讲者。我感觉自己在微笑,很有感染力,讲的故事也很精彩——但真的是这样吗?我不知道。现实是,我经常是有偏见的,我们知道那些心理效应,比如达克效应(Dunning-Kruger effect),人们往往觉得自己在某个方面比实际水平专业得多。你问别人:“嘿,你的驾驶技术高于平均水平吗?“大概百分之七八十的人会说:“是的,我高于平均水平。”
这怎么可能呢?我们有认知偏差。而冒名顶替者综合征(imposter syndrome)则是反方向的偏差,就像我觉得,“哦,我太差了,我其实不配在这里。“这同样是一种偏差,可能并不是事实。事实上,我完全可能属于这里,其他人也认可我的贡献。
所以,很多时候我们对自己、对自己的优势劣势、对正在发生的事情的认知,与实际情况之间存在巨大的偏差。而我们真正理解并取得进步的方式,就是需要其他人把我们看不到的真实情况反映给我们。我的理解是这样的:我会在这次播客结束后请你给我反馈,你会告诉我一些东西。你所做的事情,就是送给我一份礼物——把你自己看到而我看不到的东西反映给我。就像如果我脑后沾了一片树叶,我自己是看不到的。所以如果你告诉我:“嘿,Julie,你脑后有片树叶。“我说:“哦,谢谢你。“也许我就可以把那片树叶弄掉。这就是反馈的本质——它是一种映射,帮助我们对准现实,让我获得关于自己是否在朝着目标方向前进的信息。
Lenny Rachitsky: 我非常喜欢这个比喻。完全同意。但你也知道,对大多数人来说,真正的挑战在于:给出反馈时,如何让对方愿意接受而不产生防御心理;接受反馈时,如何不让自己的想法变成”哦不,他们不懂,他们什么都不懂,他们怎么敢这么说我?”
你能不能给我们一两个建议,关于如何做好给出反馈,以及如何做好接受反馈?甚至如何主动寻求反馈?这些道理都很说得通,但大多数时候人们几乎得不到任何反馈。
如何建立反馈关系
Julie Zhuo: 最好的方法是……关于获取反馈或给出困难反馈的第一个建议是,首先要去真正建立这样的关系:我们重视彼此的贡献,我们想帮助彼此成长,因此我们会成为那种每周都愿意给对方反馈的人。所以当你刚开始和某人合作时,不要等到出了问题才去给反馈,因为那已经是一个有压力的情境了。一开始就可以说:“嘿,很高兴能和你一起工作。我觉得我们最好的合作方式是你帮我变得更好。我擅长这些东西,不太擅长那些东西。你呢?好,你觉得自己擅长这些?那我们就这样一起工作,互相帮助在这些方面进步,怎么样?我们的做法就是:所有反馈都公开。我希望你告诉我一切。理想情况下,你也会说:‘好,我也希望你告诉我一切。‘“这样我们就已经达成共识了。
Lenny Rachitsky: 这是对同事、对上级,还是对所有同事都适用?
Julie Zhuo: 对所有人都适用。就像你在约会的人,你的孩子。可以和任何人这样做,就是明确我们想要什么样的关系。我认为大多数人都愿意选择一种可以亲近、可以紧密的关系。你可以对彼此说出真实想法,不用隐藏在……我认为大多数人会选择加入,如果你选择了加入,后面的所有事情都会变得更顺利。所以第一步就是让每个人都选择加入,确立这就是我们想要拥有的那种关系。
反馈的时机与频率
Lenny Rachitsky: 我听说过一个在同一思路下效果很好的小技巧,就是去问别人:“你希望我即时给反馈,还是希望每个月或每周定期给?”
大家的反应都是:“不不,即时给,一有事就告诉我。”
这样就给了你那种自由,“好,那我就在这里给你反馈了。”
Julie Zhuo: 所以如果你让人们选择加入——“是的,我希望我们有一段好的关系。我希望我们互相帮助变得更好。我想要反馈。“这就解决了给出困难反馈时百分之六十的难题。
给反馈的具体方法
然后第二个技巧是,当你真正给反馈的时候,这会很有帮助。首先你要检查:“我给这个反馈,是真的出于帮助彼此的心意吗?“如果答案是肯定的,那我们就从百分之六十到了百分之八十,反馈会进行得很顺利。
但经常发生的情况是:某件事发生了。你做了某件事,触发了我的情绪,因为可能我之前对类似的事情有过不好的经历。于是我开始感到愤怒,想要证明自己是对的。如果我给你反馈的真正动机是想验证自己、想证明自己是对的、想告诉你你错了、想惩罚你,那就不会顺利。这个意图从一开始就在那里。除非你是极其出色的演员,否则无论怎么措辞都不可能顺利进行。所以你首先要检查自己的动机。
但如果你检查过了,你说:“不不不。我认真想过了。我现在冷静了。我不再怒火中烧了。我真的认为 Lenny 只是没有意识到,当他说这样的话时,会让我和其他人感到被排斥在外,“或者诸如此类的情况,对吧?那我就需要能够把这个反馈给你。
然后通常你会想:“好吧,现在我可能会紧张,因为我不想冒犯你。我非常珍视我们的关系。我要怎么告诉你呢?我不想让你产生防御心理?“
展露脆弱的力量
那么第三个技巧就是:把你的紧张说出来。如果我坐下来跟你说:“Lenny,我现在特别紧张。我想给你一些反馈,但我真的很担心这会影响我们的关系,我非常珍视我们的关系,不希望那种事发生。但我也觉得如果你能听到这个反馈,对你会有帮助。”
这句话能起到非常大的作用……它让你显得真实而有人情味。你会意识到我在冒险,我在展露自己的脆弱,而相比之下,如果我只是在某个时刻不经意地抛出来,或者因为太难开口而含糊带过,效果会差得多。你反而更可能听得进去。所以,直接承认这件事确实很难,把它暴露出来,因为这能建立很多人与人之间的连接。
管理中的双赢思维
Lenny Rachitsky: 这个建议太棒了。非常实用。好,还有什么吗?我们聊了很多关于管理的永恒智慧,那些人们尤其是新管理者需要听到的东西。你觉得还有什么非常重要、但大家还没有真正领会的东西,对于成为优秀管理者来说?
Julie Zhuo: 我觉得就是双赢的理念,我脑海中一直在想这个概念。我反复回到这个点,因为我觉得我们脑子里经常会有一种叙事,认为有些事情是对立对抗的。作为管理者,我试图让人们更高效,所以我试图让他们做他们可能不想做的事情。我打算让他们更努力地工作,或者我打算以某种方式给他们施加更大的压力。如果你开始这样想,那就不是双赢的思维方式,对吧?那等于你在说:“我要得到更好的结果,就必须以别人失去什么为代价。”
我觉得如果你开始这样想,就很难找到好的策略,也很难真正取得成功。但如果你说:“看,实际上,我的工作是想办法创造双赢。“所以我其实不希望一个人从长期来看觉得我所做的只是给他们制造了大量压力,然后他们很快就精疲力竭了,因为那对我们的团队不好,对我不好,对我们长期的关系也不好。我们怎么找到双赢的解决方案?我觉得如果你这样思考,很多事情会变得更简单。比如对新管理者来说,我觉得我也是这样,我第一次不得不告诉一个人他不应该继续留在这个团队时,内心极其煎熬。主要原因是我在设身处地为他想,想象这对那个人来说是多么糟糕的事,我做了多么大的亏欠,那是最可怕的事情。
但还有另一种看待方式,那就是:嘿,如果一个人在这个团队里,他大概是想成功的。他想做出出色的工作,想被认可,想发展自己的职业。如果这里不适合他,因为与他真正的兴趣不符,那些能帮他成功的事情不是他想要做的或者目前能做到的,那我继续勉强维持下去对他没有任何好处。实际上只会很痛苦。我又回到了延长痛苦状态的那个问题。
所以,有时候双赢的做法就是直接说:“看,这样行不通,而我非常尊重和重视你,我知道你想做一些让你感到自豪、能让你成长、能被认可的事情。而在这里,我们现有的,不是那个。”
这就是一种双赢的看待方式,而不是那种”哦,我让他们离开就一定是件糟糕的事……”的想法。
找到真正的共赢
我并不是说这不会很难,显然这很难,但我认为心态和心智模型的差异会产生截然不同的结果。因为我传达给他们的方式会不同,我解释为什么从更大的格局来看这其实是好事也会不同,这会消除那种对抗感——他们不再把我看作敌人,或者一个掌握所有权力、做出影响他们的决定而让他们感到无力的角色。这必须是一种协作。而我认为,如果这不是共赢的话……当然我也有可能判断错误。我会说我也不认为自己的判断就一定对。对方完全可以说:“不,你错了。“这其实是很好的信息,因为那也许我们可以回过头来,找到一种方式让它变成共赢。
Lenny Rachitsky: 对,我正想说,你必须真心相信这一点。你不能只是嘴上说成”被辞退对你来说也是个大赢”,但如果你的表达像你刚才说的那样,事实上这几乎总是成立的——“这里不是一个让你快乐和成功的地方,去做别的事情对你更好。”
Julie Zhuo: 对。
信念与方向感
Lenny Rachitsky: 好,我继续在这块内容里再看看还有什么值得聊的,等聊完了告诉我。还有什么你觉得大家应该知道、应该听到的,尤其是新管理者还没有完全领会到的东西?
Julie Zhuo: 我觉得觉察自己的能量和信念是非常非常重要的。你可以看到,我们谈到的很多主题都回到了同一个起点——你必须先了解自己,建立正确的心态,当你做到这一点之后,对他人产生影响就容易得多了。所以这又是同一个道理。我觉得管理者很难做到的一点是……我们之前谈了很多管理者的三大支柱。第一个是人。所以我们讨论了维度感、反馈、帮助人们反思和成长的重要性。
第二个支柱是关于方向感。方向感就是”我们在这里要做什么?我们的北极星是什么?”
我觉得如果你自己都没有信念,其实很难把这一点传达出去。所以关注自己的信念非常重要,尤其是因为很多管理者,你往往不是公司的创始人或 CEO,你可能是一个中层管理者。所以在某种意义上,愿景不是你创造的,但你却被期望去执行它,或者取其中一部分来完成。我发现新管理者经常忽略的一点是,自己真正的信念是什么。他们觉得自己可能需要当一个士兵,接到命令就去执行。但如果他们自己真正花功夫想清楚”等等,我们为什么要做这件事?我相信这个策略吗?它说得通吗?“——这真的会有很大的区别。
如果觉得说不通,就应该去找他们的经理或者相关的人进行对话,这样至少能达成对齐——“我真正相信我正在做的事情”。
因为如果你自己并不真正相信你在做的事情,或者只是在鹦鹉学舌地复述组织传下来的话,那你很难帮助别人看到其中的魔力,也很难作为一个能够承载愿景和方向感的人真正发挥作用。所以我觉得你必须认真审视自己的内心——“等等,我知道我们被告知要做这个、要做那个,但我内心到底怎么想?”
因为如果你自己对此感觉不好,那项目成功的可能性就很低了。我可以直接告诉你,在我管理过的每一个经理中,只要他说”我真的觉得这不是个好主意”,我想不到有任何一例这样的情况,项目最后竟然取得了巨大成功。
与自己不认同的决策共处
Lenny Rachitsky: 这真是管理者面临的经典难题——去执行自己并不真正认同的事情。我忍不住想问你,对于那些不是那种”好吧,CEO 要优先做这个功能,这主意不好,但我得装出一副有信心的样子,不能让人觉得我只是传话的、只是在执行命令。我并不相信这个”的人,你有什么建议?你不能这样做,那样你会变成一个糟糕的、不成功的管理者,人们也会对你失去信任。对于那些处在这种困境中、不知道如何找到平衡的人,你有什么建议?
Julie Zhuo: 我觉得,首先,如果你有这种感觉,你必须找到一种方式把它表达出来并展开对话。所以如果你觉得”我的经理让我做这件事,我觉得是个糟糕的主意”,你必须跟你的经理谈,或者跟 CEO 或相关人员谈。因为一旦你展开对话,通常会发生的是——你会获得更多信息、新的信息、新的假设,也许你还能在某种程度上影响这个项目。通常来说,你能更多地了解到”好吧,为什么其他一些聪明人认为我们应该做这件事?其中哪些部分我相信,哪些部分我更持怀疑态度?”
你大概可以把”好或不好”这样的一刀切判断分解为——“好,这是一个假设,这是一个假设,这又是一个假设。我可能比较相信这个。我不喜欢这个提案的原因,是我不相信这个特定的假设,但我相信其他那几个。”
所以,当你能深入一层,把它分解成一组假设时,事情就容易多了,因为你很可能会找到某个你能产生共鸣的部分。然后你也许能够引导方向——“好,如果那个假设不成立的话……我认同’不同意但承诺执行’的原则,但现在我们可以非常具体地定位到那个点……”
我们通常还可以这样做——“好,我不喜欢这个提案的原因是我认为这个假设是错误的。”
我来举一个特别蠢的例子。你的建议是”我有一个好主意,我们要在每个街区都开一个柠檬水摊。而我的核心假设是人们不喜欢柠檬水。那不是现在流行的饮品。因此我觉得这个计划很蠢。”
但如果我跟你谈了这件事,你说”不不,这才是我们真正分歧的核心假设。“那接下来很可能就会展开这样的讨论——“那我们能不能找些数据?找些信息?有没有更快的办法来验证人们是否喜欢柠檬水?也许我们应该先在一个市场测试,然后再去全美五十个州开柠檬水摊。”
这样一来,我们很可能就能聚焦到那个具体的分歧点,并提出一些方案。然后,如果我不得不跟团队说——“我们要验证这个假设。我不太确定自己怎么想,但我确实觉得……我不完全确定,我们的 CEO 似乎认为这是……但我们就是要测试一下,而且我们的测试方式会是……我们想搞清楚的就是,如果把柠檬水摊放在这些大学校园附近的社区,18 到 25 岁的年轻人会喜欢柠檬水吗?“这变得非常具体,每个人都会觉得——“好吧,我不确定答案,但我很愿意去做这个测试,并且全力投入。“
AI 角落
Lenny Rachitsky: 这个建议真的太好了,而且你还可以在此基础上叠加——“这些是我认同和相信的部分。这些是我觉得完全正确的地方。这个环节我不太确定,但正因如此我们才要做这个测试,而且这正是最小范围的测试版本,去做一下验证是个好主意。“这样大家就都能看明白了。你可能不想直接这么说。你给出这个回答的时候,我觉得特别有意思,我甚至想以后跟你专门做一期新节目,就聊管理者常见的困境——每个管理者都会遇到、但又很难当场想清楚的那些挑战。这个我们以后再聊。好,我要带大家进入这档播客的几个固定环节了——每期都会带嘉宾去的一些”角落”。
第一个是 AI 角落。在 AI 角落里,我想问的是:你在工作或生活中有没有发现一种使用 AI 的方式,特别有趣、特别实用?
Julie Zhuo: 关于教育和学习方面我已经分享了很多了,不过我可以讲一个更有趣的故事。最近是我孩子们的生日季。其中一个刚过完。我二儿子的生日在两周后,我女儿的生日在一个月后。
Lenny Rachitsky: 顺便说一下,是生日刚过完了,不是孩子过完了。
Julie Zhuo: 好的,对,是生日过完了。
Lenny Rachitsky: [听不清]。
Julie Zhuo: 没错没错,生日过完了,我孩子的生日。我今年的一个目标是亲手给他们做点东西——送他们一份礼物,让我重新回到独立贡献者的身份,为他们亲手制作点什么。AI 让这件事变得特别有趣。比如我小儿子,他六岁,这个主意是我从 Eric Antonow 那里偷来的——如果你认识 Eric 的话。你请他上过你的播客吗?
Lenny Rachitsky: 还没有,我正在努力邀请。他其实给我寄了那个……叫什么来着?那个——
Julie Zhuo: 对对。
Lenny Rachitsky: 叫什么?Metha——
Julie Zhuo: Methaphone?
Lenny Rachitsky: Methaphone。
Julie Zhuo: 对。
Lenny Rachitsky: Methaphone,你看看这个。
Julie Zhuo: 对,是的。
Lenny Rachitsky: 就是说不用把手机揣在口袋里,而是拿着这个东西,然后你带着它到处走,每个人都会问”这到底是什么玩意儿?“Methaphone。
Julie Zhuo: 对,我也是 Methaphone 的骄傲拥有者,下一版还升级了小贴纸。不过——
Lenny Rachitsky: 不,我还没有那个版本。
Julie Zhuo: ……Eric 特别棒。你一定要请他上你的……他真的是一个非常有创造力的人。有一次我看到他肩膀上站着一只鹦鹉,我就问”你肩膀上为什么有只鹦鹉?“他说”你可以跟我的鹦鹉说话,这是一只会说话的鹦鹉。“然后我就跟鹦鹉说话,鹦鹉也回答了我。事情是这样的——他在鹦鹉体内安装了一个麦克风,他”外科手术式”地拆开鹦鹉,加了麦克风和扬声器,然后连接到 ChatGPT 的语音模式。所以它说话的时候好像是海盗的口音。
我当时就觉得”这主意太棒了。“我六岁的小儿子特别喜欢浣熊,他有一大堆浣熊毛绒玩具。我就想”我要做一只会跟他说话的浣熊”,于是我用 Eric Antonow 的方法做了一个,效果特别好,大受欢迎。现在我二儿子的生日快到了,他特别喜欢恶搞歌曲。他喜欢电子游戏,比如 Minecraft,他在 Alexa 上经常听的就是那些恶搞歌曲。比如 Justin Bieber 的热门歌曲或者《江南 Style》,但歌词被改成了他在玩的某个电子游戏的恶搞版,唱得特别难听,完全走调,就是某个随便什么人制作的那种。我就想”既然他好像不在意跑调的歌声,那我就给他做一张电子游戏恶搞歌曲的专辑。“我要做一个……
我在 Replit 上做了一个应用。它的使用方式是——你给它一首歌,比如 Justin Bieber 的《Baby》,附上一个 Spotify 链接,然后我给它一些上下文信息,比如”Locke 现在喜欢玩 Kingdom Rush,我们有个内部笑话,说石像鬼就是白送的钱。“不管什么内容,我就给它一堆上下文,然后说”给我写一首歌,把它个性化,做成这个电子游戏的恶搞版。“它就会给我写出歌词,而且写得相当不错,质量挺高的。它还会按照音乐的节拍来写,然后我只需要唱出来录下来,一首歌就完成了。我正在做一整张这样的专辑,打算送给他。他不会听到这期播客,所以大家别给他剧透。我觉得这期播客会在他生日之后才发布,但我对此非常期待。
Lenny Rachitsky: 等等,所以歌是你自己唱的?
Julie Zhuo: 对,是的。
Lenny Rachitsky: 我还以为你会用 Suno 或者什么 AI 工具来唱呢。
Julie Zhuo: 不,我打算自己唱。
Lenny Rachitsky: 哇。
Julie Zhuo: AI 让这一切变得太简单了。我只需要录就行。再说一遍,我唱歌不太好听,但跑调的歌声并不影响他听的兴致。
Lenny Rachitsky: 确实。哇,这太美好了。这给了我好多灵感,可以给身边的孩子们送这样的礼物。我就是喜欢 AI 让做父母这件事变得更轻松了,而且在某种程度上也变得更有乐趣了。这些都是非常棒的例子。好,我要带大家进入另一个角落——反共识角落。你有什么信念是大多数人不认同、别人会反对的?
反共识角落
Julie Zhuo: 我相信每个方向上都存在无限。这让我在几乎所有事情上都跟别人唱反调。如果有人在 Twitter 上说了什么,我有时会跟自己玩一个游戏——在什么情境下这句话其实是不成立的?我认为现实是,世界——或者说至少我的现实,以及我对现实的理解——是无限复杂的。比如我孩子们说”出门好无聊”或者”散步好无聊”或者”做什么什么好无聊”,我通常的回答会是”那是因为你没有看到那个方向上的无限性。”
甚至比如盯着一面白墙这种极其无聊的事情,我觉得你也可以让它变得非常非常有趣,因为你可以利用这个机会走进自己的内心世界,想办法让时间流逝,或者冥想存在的意义,或者冥想自己的呼吸,或者单纯感恩活着这件事。同样两个人,你对一个人说”面对墙壁坐一个小时”,像我儿子那样的,他会超级抱怨,说”这是世界上最糟糕的事”。但你把同样的事交给一个僧人,他会有非常美好的体验。所以真正重要的不是环境或那面墙,而是我们如何看待它,以及我们能否在那个方向上找到那个深层的、丰富的、无限的东西。
Lenny Rachitsky: 哇,这些回答都很深刻。非常有——我不知道怎么说——非常有禅意,非常有正念的感觉。我曾经参加过一次禅修,他们的建议就是,任何时候你感到无聊,就去注意到你周围正在发生的一切。你现在坐着的感受是什么?空气的感觉是什么?你现在听到了什么?这跟你说的一模一样——有无限多可以关注的东西,让你保持兴趣。只是很难做到。
Julie Zhuo: 确实很难。
Lenny Rachitsky: 要长时间真正做到并付诸实践,确实很难。所以这才叫”修行”。
Julie Zhuo: 所以这才叫修行。但我时常把这句话重复给自己听,因为很多时候,如果我对某种感受有不好的体验,意识到这通常很可能是自己头脑中的问题,会对我很有帮助。是因为我还没有掌握那种能力,去看到当下丰富的无穷可能……我可以去练习这种能力。这比觉得自己是环境的受害者要好受得多——“这件事发生在我身上了,太糟糕了,但我无能为力”——对我来说,这种感受比另一种更差:另一种是,我只是还没有这项技能而已。我能认清它的本质——我还没掌握这项技能,但我可以成长,我可以慢慢变得更好。世界上一定有人和我处境相同,但比我积极乐观得多,我难道不想成为那样的人吗?
闪电问答环节
Lenny Rachitsky: 这真是太美了,完美地呼应了我们的第一期节目,那一期很大一部分聊的就是冒名顶替者综合征以及如何克服它,还有你的故事。我很高兴这或许可以作为我们这次对话的收尾。但在此之前,在我们进入非常精彩的闪电问答之前,你还有什么想补充的、想分享的、或者想在我们已经聊过的内容上再次强调的吗?
Julie Zhuo: 我只想说谢谢。说实话,你做的事情让我深受启发。我们认识已经很久了,从你最开始产生做 newsletter 和播客的念头,就一直非常出色,我认为这个世界从中受益良多。我确定你经常听到这样的话,但我还是非常感激。
Lenny Rachitsky: 非常感谢你这么说。而且每次我们聊天我都会说——如果没有你,这一切都不可能实现,Julie。我当初就是受到了你长期撰写的 newsletter The Looking Glass 的启发。本质上我的想法就是:如果我把这件事做到产品领域会怎样?我和你一样先从 Medium 开始,然后转到了 Substack,然后想”如果我收费呢?“——那成功了,然后我又想”如果我做一个播客呢?“——那也成功了。但这一切的起点都是你的构想,所以谢谢你,Julie。
Julie Zhuo: 是的。我觉得你始终带着极大的善意和好奇心在做这件事,一如既往,我很欣赏这一点。
Lenny Rachitsky: 这就是我这个人嘛。好了,话不多说,我们已经到了非常精彩的闪电问答环节。我准备了五个问题。准备好了吗?
Julie Zhuo: 准备好了。
书籍推荐
Lenny Rachitsky: 你最常向别人推荐的两三本书是什么?
Julie Zhuo: 第一本是《Zen and the Art of Motorcycle Maintenance》。我非常喜欢那本书。文笔优美,思想深刻。我关于质量的整个理念,很大程度上都源自那本书——包括我们今天聊到的关于变化的所有内容。站在变化的前沿、动态的质量意味着什么?我认为他在书中论述得极其精妙和娴熟。这是一本老经典了,但我大概每隔几年就会重读一遍。
第二本是《Conscious Business》。这是我最喜欢的管理书。它有点像冷门佳作,因为我实际上推荐这本书的频率远远超过我自己的书。
Lenny Rachitsky: 哇哦。
Julie Zhuo: 这本书是我写完自己的书之后才读到的,我总跟人说,如果我先读了它,我可能就不会写自己的书了,因为我会觉得”《Conscious Business》真的是那本深深共鸣的书”。我谈到的很多内容——双赢的理念、做一个参与者而不是受害者的理念,以及如何理解工作——不仅仅是把它当作一份差事,而是如何真正让它与你个人的价值观以及你想在这个世界上做的事情对齐——这本书对这些话题的阐述非常精彩。而且它也非常实操,有很多精彩的案例。我会告诉大家,这本书的封面不太好看,如果你以貌取书,它看起来非常”企业风”。书名也让人觉得:“什么,有意识的商业?“第一章也偏技术性一些。但只要你坚持过去,进入第二章,从那个足球队的案例开始,你会发现这是最好的管理书。
Lenny Rachitsky: 这个建议很好,能帮人跨过那个门槛。他们会说:“好吧好吧,我会坚持下去的。”
Julie Zhuo: 对。第三本书,我喜欢 Dr. Becky 的《Good Inside》。这是一本育儿书,非常畅销的育儿书,所以我向所有父母强烈推荐,但我同时也觉得这是一本关于关系的精彩之作,因为育儿本质上就是与另一个人之间非常深入、非常紧密的关系和互动。我在育儿书里读到的很多东西——包括《Good Inside》——我觉得完全可以写成一本管理书或团队领导力书。
Lenny Rachitsky: 我正想邀请 Dr. Becky 来上播客。我觉得会有很多协同效应,正是这个原因。她用一个词叫”sturdy”(稳固),可能启发了你的 bullet tree 流程。
Julie Zhuo: 哦,对,我可能就是从那里学来的……她经常谈到 sturdiness(稳固),就这么植入到我脑子里了。
Lenny Rachitsky: 是的,她的核心理念就是做一个稳固的父母。强大但灵活,我想是的。我很喜欢她,喜欢她的内容。我在 TikTok 上看她的所有视频,还有 Emily Oster 的。
最近喜欢的影视和产品
Lenny Rachitsky: 好的,下一个问题。最近有没有喜欢的电影或电视剧?
Julie Zhuo: 我什么都没看。我给不出什么好答案。我觉得我今年唯一看的就是重温了《爱乐之城》,我确实非常喜欢那部电影。
Lenny Rachitsky: 真的很好。好的。有没有最近发现并且非常喜欢的产品?
Julie Zhuo: 我觉得没有什么特别新的。我喜欢 Granola,喜欢 Replit。各种编程工具我都用过。Cursor 是我目前的主力。我刚入手了一个 Matic Robot。到目前为止体验很棒,至少设置过程是这样的。我还没有长期使用过,但它的设置方式、运作方式,还有它附赠了小贴纸,你可以把它装饰成一只狗或一只猫——这个体验非常棒。
Lenny Rachitsky: Matic Robot,说到它,我也是超级粉丝。我不是投资人,它基本上就是 Waymo 遇上了 Roomba。不了解的人可以把它想象成一个由 AI 视觉团队打造的非常精密的扫地机器人。
Julie Zhuo: 哦,我又想到一个——Limitless Pendant。先声明,我是 Limitless 的小股东,但我喜欢它的地方是……它是一个吊坠,你戴在身上,它会记录周围发生的一切,之后会给你总结并提供反馈。我一般不戴出门,因为我觉得别人可能会对我记录一切感到不太舒服,我通常会征求别人的同意。但我会在家和孩子在一起的时候戴它,这个吊坠最棒的一点是它会给我育儿方面的反馈。
Lenny Rachitsky: 什么?自动的还是丢到 ChatGPT 里跑的?
Limitless Pendant 的育儿反馈
Julie Zhuo: 是自动的。它有一个 app,有时候会主动给我推送通知,或者我自己打开查看也行。我也可以直接跟它的 Ask It 功能交互。它本质上做的事情就是……类似于 Granola,但面向你的日常生活——捕捉一切、做总结,然后给你建议和反馈。它说过类似的话:“那次你在聊游戏的时候,频繁打断了孩子。下次可以试试让他们把话说完,更好地倾听。”
Lenny Rachitsky: app 本身就能做到这些?
Julie Zhuo: 对。
Lenny Rachitsky: 我居然不知道,因为我也有一个,只是最近没怎么用。这太不可思议了。我好奇它能不能在你和伴侣聊天的时候也给出关系建议。我甚至不知道它是怎么判断出来的。
Julie Zhuo: 它的推断做得相当不错。我记得它显示的是”人物二”,但对我说来确实挺有启发性的。
Lenny Rachitsky: 太厉害了。我们 “How I AI” 播客——我们的姊妹播客——最近有一期节目,嘉宾戴着这个东西去跟 CEO 开会,然后自动把 CEO 要求的东西从会议记录变成原型,销售团队就可以直接拿去给客户看,试探兴趣。你说厉不厉害?
Julie Zhuo: 太棒了,真的很酷。
人生座右铭
Lenny Rachitsky: 天哪,这个世界到底怎么了。好,我继续。你有没有特别喜欢的人生座右铭,会不断对自己重复、也分享给别人的那种?
Julie Zhuo: 我喜欢”make it happen”。提醒自己,说到底,我们可能会有很多 motion(忙碌)。也许这是另一个我很喜欢的理念。我想起 Facebook 以前有一张海报,上面写着”don’t mistake motion for progress”(不要把忙碌误认为进步)。还有”be the change you want to be in the world”,说的其实是同一件事——我可以去做事情,我们每个人都可以做事情。而且我们有越来越好的工具去创造、去让事情发生。Make it happen。
Lenny Rachitsky: Twitter 上那个常见的说法——you can just do things(你真的可以直接去做)。
Julie Zhuo: 没错。
给下一代的建议
Lenny Rachitsky: 最后一个问题。我特别喜欢问那些深入 AI 领域、一直在和 AI 共事、对趋势有感觉的人:考虑到 AI 将成为他们生活中的重要组成部分,你有没有在教你的孩子、或者鼓励他们学些什么?
Julie Zhuo: 情绪调节仍然非常、非常、非常重要。这大概是我最常思考的问题——我希望我的孩子学到什么。我希望他们能够内省,更好地了解自己的心理状态,因为我们仍然是人。我们仍然拥有和几千年来人类一样的”硬件”,这一点不会因为周围的工具和环境在变化而改变。所以我觉得你必须真正理解自己,了解自己当下的状况,了解自己在哪里有偏见、哪里没有,因为 AI 会让一切变得……这是我最大的担忧——它让一切变得太舒适了。我一直有这样的担忧,认为这正是技术发展的轨迹。这又回到那个观点了——每个优势同时也是劣势。
技术让事情变得更简单。这是发明和创造的动力。人类一直在努力改善自身处境,在某种意义上掌控命运、掌控未来。但与此同时,所有这些掌控到了某个阶段,我们的生活中就充满了各种捷径。你可以走捷径——你可以对关系走捷径,你可以逃避困难的情绪,因为现在你完全可以刷 TikTok,而不是真正去处理与同事、伴侣或孩子之间那些困难的情感或紧张关系。我觉得 AI 让这一切变得更具吸引力了,因为现在有一个”人”或者说一个东西可以非常个性化地回应你。你想:“哦,我想要分散注意力,我想做点什么”,立刻就有了。
但我们如何才能真正学会面对我们不会改变的生物本性?我们如何继续保持那种愿意主动迎接挑战的人?因为我发现,如果我们不去挑战,我们会痛苦。一种不同方式的痛苦。所以对我来说,真正的自由是——你可以选择那些困难的事情,你可以为成为自己想成为的人而感到骄傲。它不是被强加的,不再是为了生存,但你仍然要主动去选择。我希望让我的孩子明白,找到挑战仍然是非常重要的。当然你可以用 AI 来做这些事,但真的,不要把它当作走捷径的工具。因为如果那样的话,我并不认为他们能够成为自己想成为的那种人。
尾声
Lenny Rachitsky: 多么美好的方式来结束这次对话。Julie,感觉这简直是这个播客的一个重要里程碑。三年后再次请到你,就像是这段旅程中的一个新的篇章。感谢你再次到来,感谢你与我们分享所有这些智慧。最后两个问题。大家如果想联系你,聊一聊 Sundial 或者你正在做的其他事情,可以在哪里找到你?另外,听众们怎样才能帮到你?
Julie Zhuo: 我很想和在很酷的公司里构建产品的人合作,帮助他们更好地回答”如何构建得更好”这个问题。如果你觉得你的公司有兴趣和我们在 Sundial 合作,一起来探索如何让每一个决策者都成为自己的专家分析师,请联系我们。这是一个方向,邮箱是 sundial@sundial.so。我也在 X 上,最近发推多了很多,分享各种想法。回到之前说的——练习的技能,就是分享你脑子里的东西。
长篇的内容的话,我有我的博客 The Looking Glass,在 Substack 上。我会定期分享关于 AI、产品构建、领导力的文章和思考。当然,还有我的书,修订版新增了两章。一章是关于远程管理,另一章是关于在下行周期中管理,或者在困难的变革场景中管理。两周后就会上市。新内容会出在平装版里,这很重要。Lenny,等我自己拿到样书后会寄一本给你。
Lenny Rachitsky: 太棒了。
Julie Zhuo: 平装版的封面是渐变色的。精装版最终也会上新内容,但从各个零售渠道把旧版替换掉需要一段时间,所以如果你买精装版,我不能保证一定有新内容。但 Kindle 版和平装版肯定包含全部新内容。
Lenny Rachitsky: 为了确认一下出版日期,因为这期节目可能会晚一些播出——新书是哪天出?
Julie Zhuo: 9月9号。
Lenny Rachitsky: 好,太好了。我想这期节目上线的时候书应该已经出了,所以大家去买吧。应该亚马逊和各大零售商都有。
Julie Zhuo: 对对。
Lenny Rachitsky: 太好了。Julie,非常感谢你来。
Julie Zhuo: 非常感谢你,Lenny。太开心了。希望三年后再来,或者下一个篇章是什么都行。
Lenny Rachitsky: 希望不用等那么久。大家再见。
Julie Zhuo: 再见。
Lenny Rachitsky: 非常感谢大家的收听。如果你觉得这期节目有价值,可以在 Apple Podcasts、Spotify 或你最喜欢的播客应用上订阅本节目。也请考虑给我们评分或留下评论,这真的能帮助更多听众发现这个播客。你可以在 lennyspodcast.com 找到所有往期节目或了解更多关于本节目的信息。我们下期再见。
术语表
| 原文 | 中文 |
|---|---|
| agent | 智能体 |
| agentic systems | 自主智能体系统 |
| alignment | 对齐 |
| builder | 构建者 |
| charter | 职责范围 |
| disagree and commit | 不同意但承诺执行(Amazon 著名管理原则) |
| evals | evals(评估基准) |
| heuristic | 经验法则 |
| IC (Individual Contributor) | 独立贡献者(已在术语表中) |
| imposter | 冒名顶替者 |
| KPI | KPI(关键绩效指标) |
| motion | motion(忙碌/动作,此处保留原文以呼应 poster 原文) |
| north star | 北极星 |
| PM | PM(产品经理) |
| process | 流程 |
| sleeper hit | 冷门佳作 |
| stuffies | 毛绒玩具 |
| sturdiness | 稳固 |
此文档由 AI 分片翻译(translate_long_document)