工程师思维 | Will Larson (Carta, Stripe, Uber, Calm, Digg)
The engineering mindset | Will Larson (Carta, Stripe, Uber, Calm, Digg)
Will Larson: I think that we often treat engineers a little bit like children instead of giving them the responsibilities and ability to actually thrive as adults. And so like, “Oh, the engineers won’t want to do that work.” Well, that’s actually not good for the engineers to be sheltered from what is important. And so actually one of the, I think, highlights is that I think we’re coming back this moment where we can actually treat engineers like our peers and put them into really senior leadership roles and not have this kind of baseline assumption of like, “Oh, we have to coddle them or hide them from the real problems.” And this is how they’re going to get the opportunity to grow as well.
Guest Introduction and Opening
Lenny: Today, my guest is Will Larson, one of the most requested guests I’ve had on this podcast. Will is currently CTO at Carta. He’s been a software engineering leader at Stripe, Uber, and Calm. He’s the author of two essential books for all engineers, An Elegant Puzzle and Staff Engineer, and he’s releasing his newest book The Engineering Executive’s Primer in February of next year. He also publishes regularly on his blog at lethain.com, which is a must read for every engineer and eng leader.
In our conversation, Will shares advice on developing your engineering strategy and strategy in general, how to improve the relationship between an eng manager and a PM, how he finds time to write, while also working an intense full-time job, how he recommends approaching measuring engineering productivity, how to develop your company values, an amazing story about his time at Digg and so much more. Will is such a gem of a human and leader and I’m excited to bring you this episode. With that, I bring you Will Larson after a short word from our sponsor.
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Will, thank you so much for being here and welcome to the podcast.
Recent Changes in Engineering
Will Larson: Thank you so much. Super, super excited to be here.
Pitfalls and Essence of Systems Thinking
Lenny: So many people have suggested that I bring you on this podcast. You have a lot of fans out there and I am excited to be digging into engineering topics, which we don’t do enough of on this podcast. So thank you for making time for this.
Will Larson: No, thanks. I hope to be a good early engineering guest before you pivot entirely to engineering at some point in the future.
Stocks and Flows
Lenny: Wow, I love that. How cool would that be? I was an engineer actually when I started my career. How interesting would that be if we come full circle? Anyway, I thought it’d be fun to start with just what is changing in engineering? It feels like there’s been a lot that has changed over the past few years, especially from kind of the ZIRP zero interest rate era to today’s market, which is very different. What have you seen most change from an engineer’s perspective and then just also what are you telling eng leaders about how to handle all this change?
Will Larson: I think it’s a pretty strange time in the market. So I think that I started working and right before the 2008 kind of crash. And so the first two years there were not so good. When I joined Yahoo, there was a layoff basically every four months. There was a layoff of some sort. It’s pretty chaotic. But then we got into the last decade and it was just smooth. So numbers went up, revenue went up, headcount went up and people started learning how to build really large teams.
People started learning how to hire a lot. When I was at Uber, some days I would do six interviews back to back. I would just be in a conference room and at some point you can’t even remember who you’re talking to because you talk to so many people, one after another after another. You just have some scrambled notes you’re trying to decode afterwards.
Pretty different now. A lot of engineering managers are spending half their time or more hiring 18 months ago and now they’re doing two interviews a month or less. Maybe zero interviews a month. So there’s a real shift in just the amount of time people are putting into hiring. Instead, all these different competencies that have become more critical or a really great engineering director might’ve just been spending their time hiring really well and that could be a top performer and now that person can’t actually demonstrate what they’re great at.
So that person might be perceived as a low performer if they’re not also figuring out how to lead the team, getting deeper into the details and also sometimes getting into the figuring out what is the right allocation, what is the right sizing of the engineering teams, this is stuff that we weren’t talking about much or maybe if you really pissed off the CEO, maybe an infrastructure you just grew a little bit slower next year, but different ballgame at this point where teams are actually disappearing, teams are getting cut down, teams are getting consolidated. And that’s just something that we’ve avoided for that ZIRP era that now we become a core part of a lot of the job.
Building an Engineering Strategy
Lenny: It feels like also engineers… They used to have a lot of leverage over companies, inside companies. I imagine that’s also changing in a big way.
Definition and Core of Strategy
Will Larson: I think that’s true. I think this actually has been bad for engineers in some way. One of my hobby horses is that I think that we often treat engineers a little bit like children instead of giving them the responsibilities and ability to actually thrive as adults. And so like, “Oh, the engineers won’t want to do that work.”
Well, that’s actually not good for the engineers to be sheltered from what is important. Actually one of the, I think ,highlights is that I think we’re coming back this moment where we can actually treat engineers like our peers and put them into really senior leadership roles and not have this baseline assumption of like, “Oh, we have to coddle them or hide them from the real problems.” And this is how they’re going to get the opportunity to grow as well. That’s a highlight for me and the shift recently.
How to Improve Strategic Skills
Lenny: I have definitely worked with that and experienced that where you don’t want to piss off engineers. And so are you saying that because that’s changing, leaders maybe don’t have to worry as much about upsetting engineers plus you just generally think we shouldn’t treat engineers that way?
Will Larson: Yeah, I think a little bit of both, but I think there’s been, in this previous era, where hiring and retention were one of the biggest ways you evaluated middle management. Losing team members was huge, huge issue. And so you started to coddle a little bit, which is actually bad, again, bad for the engineers, bad for the teams, bad for everyone, bad for efficiency of the organization. But now something that I love is we get to give engineers real hard problems and we get to actually hold them accountable. And that means we can put them in senior roles.
One of the things that I’ve been pushing on, I wrote my last book, Staff Engineer about what is the career path for senior engineers. One of the challenges is if we aren’t comfortable holding engineers accountable because we just want to retain all the engineers, then we can’t put them in senior roles. And so I think we’re actually seeing a bit of a shift where we can actually hold them accountable, which means we can put them in senior roles, which means the engineers can actually get what they’ve been trying to get the entire time, but we haven’t been able to because we’ve been coddling them a little bit too much.
Persistence in Writing
Lenny: Okay. So there’s a few directions I want to go and I’m just going to poke around and see where we go. The first is you’re a big advocate of systems thinking. We were chatting about this before. I think a lot of people have heard this term systems thinking and there’s books about it. It’s sounds great. I want to be a systems thinker. What does that actually mean? How do you find you apply it in your work? How do people get better at this way of thinking?
Will Larson: A lot of the least successful but smartest people I’ve worked with were really strong systems thinking advocates. And so I do want to say every kind of framework has a lot of downsides. There’s no framework that people can apply consistently, universally, and get good results. And so briefly on this one, what I see is often people will find a spot where their system and reality are in conflict and they’ll be like, “Reality is wrong.” And so what’s a concrete example?
At Stripe, we worked on incident management. And so Stripe pretty important company where our API is available. If the API is down, you lose money and if you lose a lot of money, you leave Stripe because you’re pretty upset about that. The number one thing businesses need to do is to collect money successfully for the service that they’re selling, right? Stripe is super important.
And so we did a lot of analysis on incidents trying to understand why things weren’t working, what we could do better, but we got so caught up in the analysis that we lost track of whether we’re actually improving things. And it took us a while to figure that out because we were so stuck in the systems thinking model and it’s not like, “Oh, the team was wrong.” It’s like, “I was wrong.” I was caught up in that model myself, to realize like, “Hey, we weren’t actually prioritizing improvements, we were just prioritizing measurement.” And you can’t keep measuring. There’s measure twice, cut once. Sure, but you don’t measure infinite times and never get to cut.
And you do have to cut at some point to actually make impact. But we just got caught a little bit there. I think a lot of people who get too far in systems thinking make the same mistake where they think reality is wrong and reality is never wrong. Reality is always right. Your model is always wrong if it’s in conflict with reality. But that conflict, that gap is really interesting and that’s where you can learn.
And so I had this model. It’s really clean. It represents your hiring pipeline that moving through different steps. It represents your incidents and how you remediate incidents. It can model almost anything pretty quickly when you get good at it. And then understanding how reality is in conflict with that, you start to understand where your mental model is wrong and then you can go educate yourself and improve the model and just keep doing that.
At some point the model is close enough and you can stop doing that and go actually do the work. So that the biggest thing I tell people is this is a great way to learn, but you also have to do things. You can’t just learn. That’s not our entire job.
16 Years of Writing Experience
Lenny: To make it a little more concrete, how would you best describe this idea of systems thinking? What’s a good way to just like, “Okay. I get what you’re talking about?”
The Biggest Risk Is Quitting
Will Larson: This is probably a better place to start versus a rambling anecdote about using it.
Content Creation as an Infinite Game
Lenny: We can go backwards. It’ll be great.
Will Larson: Systems thinking is basically you try to think about stocks and flows. So stocks are things that accumulate and flows are kind of the movement from a stock to another thing. So what’s a simple example of a stock? A stock could be the number of fish in a lake. A stock could be the number of people fishing in a lake. And so a flow between those two could be the number of fish in a lake will decrease at some rate based on the number of people fishing in that lake.
So if there’s a ton of fishers, the stock of fish will go down faster. There’s only a couple of fish, IT will go down slower. But also then there’s these flows which kind of dictate that where if we’ve got much more efficient fishermen, the flow of fish out might go down, but also the fish do reproduce. So then there’s another flow going back. So based on the current number of fish and the reproduction rate, the current number of fishers and their fishing rate, you start to see how these can evolve over time. And a lot of this.
So first always recommend Thinking In Systems by Donella Meadows. Really phenomenal book. And a lot of her work is also kind of referencing the work in Silent Spring by Rachel Carson, which talks about how small amount of carcinogens or something low in the ecosystem or the food chain rather as they get consumed by predators further and further up get concentrated. And that’s a kind of a classic systems thinking problem to think about where you wouldn’t think a small amount of carcinogens and a small fish actually matter. But as they go up the food chain, they start to concentrate it and an unexpected change can happen.
Writing Goals and Handling Feedback
Lenny: So then going back to your example of the hiring pipeline, let’s come back to that to help connect this definition, which I’ve never heard, which is awesome, very clear to how you actually implemented say in hiring.
Will Larson: The first thing to do is to get a model out there of any sort. And so you think about your stocks. And so in a hiring pipeline you might have potential candidates and this could be basically infinite, and then you have a couple of inflows. So you could have sourced, you could have outreach, you could have referrals, and then you have the candidates and those… How many people get sourced. There’s probably a function of number of sources you have dedicated to a role. So you’d have another stock of how many sources you have and then that would impact the rate going from potential candidates to actual candidates you’ve sourced.
And then from candidates that you have in that box, you’d have a conversion rate for people who pass the first recruiter screen and that would move into step two of your process. And then from step two you have maybe a hiring manager screen and that would be another conversion rate. So you can see over time how the candidates of the infinite potential candidates like wandering around LinkedIn, posting about their deep thoughts, convert into actual people, your first, your second, your third.
But then as you get deeper into it, you start to actually see interesting things. And so for a lot of candidate or a lot of pipelines, the biggest issue is hiring managers don’t want to extend any offers because the hiring managers can’t get to confidence on any candidate. And you’ll see in this pipeline, you’ll see a ton of candidates getting to offer stage, but almost none of them converting from a potential offer to actually offer. And then you can say, “Hey, here’s the problem. You need to go work with the recruiter and the hiring managers on getting conviction about who they should hire.
Classic problem with early managers, right? Here’s a second problem. Manager wants to extend a ton of offers. They do extend them and none of them actually accept. And so that focuses you on the second problem. But there’s a third potential world where actually you’re just not getting enough candidates in. You’re actually doing a great job of making decisions, great job of closing candidates. There’s just not enough candidates coming in. And so by looking at this and you can build this model, then you can go to your applicant tracking system, a greenhouse or whatever and pull the historicals and you can just see how the historicals work versus how you’d expect it to work.
You can see the drop-offs and this helps you figure out where should you go try to fix things first. I think we’ve all worked in companies where you roll out big changes with no data behind them because like, “Oh, it feels like we’re not hard enough in how we evaluate candidates or something.” You go change a bunch of stuff. But often the real problem might be that the hiring managers making offer extensions to people who never passed the loop anyway. It’s just the managers are issuing too many offers because they’re panicking. And man, less true now, but a decade… Or not a decade, two years ago, hiring managers panicking to get offers out, that was a real thing that happened a lot. And this just helps you take a complex kind of abstract problem and turn it into something you can actually work in a systematic way.
PM and Engineering Collaboration
Lenny: I feel like product managers will either naturally do it things this way already because a lot of them think in funnels. And it’s interesting to hear this version of it of this idea of just following the stock through the flow of the different steps. Awesome. Another thing that I know that you are very passionate about and spend a lot of time thinking about is engineering strategy. I think you have this kind of feeling like engineers don’t think enough about the end strategy. Every other function has a strategy and engineers often don’t. Talk about what you find there and what your advice is around that.
Will Larson: First, I start to question whether any function has a strategy at most companies. My general experience is that there’s very rarely a written strategy for any company. Sometimes it’s a value statement. It’s like we build the highest quality products and you’re like, “Good. Okay. What do I do with that?” You’re like, “Build a high quality product.” You’re like, “Okay. I don’t don’t know what that means.”
Engineering often has this problem where I think people will make comments in their culture amp or their quarterly surveys or whatever. It’s like, “Hey, the strategy is not clear or where’s the engineering strategy?” And the biggest thing I tell people when they complain and then engineers complain about the product strategy. The PMs don’t have any strategy or the business has no strategy. And the reality is product eng and business always have a strategy. It’s just often not written down.
And so the first thing I want to do is I push people not to get caught up on the fact that there’s no template out there, which is product strategy that someone has forked and filled in. It doesn’t mean you don’t have a strategy. You do have a strategy. It’s maybe a little bit hard to articulate and maybe it’s applied inconsistently across different layers of the product reporting chain because it’s not written down. But it’s never true that there’s no product strategy. There’s always a product strategy. Sometimes it’s bad, but there’s always one. And true for engineering as well. There’s always an engineering strategy. Just sometimes it’s bad.
The first rule of strategy is that if you write it down, then you can improve it. If it’s not written down, it’s hard to say if this PM is just not a good PM or if they’re trying to apply the strategy that they’ve misunderstood or if they actually are correctly applying the strategy from the head of product that’s just not appropriate to the problems they’re working on, how do you debug any of that?
If you have a written document, even if it’s not a super compelling strategy, at least you can start debugging. It’s like, “Hey, the head of product should improve the clarity of this document. Hey, this DM actually isn’t applying it correctly. Hey, the strategy actually isn’t appropriate for this one business unit where it makes sense for the others.”
So that’s the first thing I think about. But the second big theme on strategy I think about is that often good strategy is so boring. It’s hard to talk about. For example, on the engineering side of thing, a common strategy that’s really good but very boring is we only use the tools we have today. So a lot of times you’ll get engineers that want to introduce new programming languages, new databases, new cloud providers. And a really good strategy for almost all companies is like we just use the standard kit we already have today.
And at Carta, when I joined one of the engineers, Eric Vogel wrote the standard kit and that is our strategy of the tools we use. And you know what? Some people are really frustrated by that and I feel for them. It feels like they’re losing control, but the power of these boring strategies is that it focuses people’s energy on the problems that we value as a company. And so it is painful coming into alignment if you’re kind of slightly misaligned over time, but boring strategies that tell you what actually matters and aligns you with what the company actually caress about are really good for you even if they’re a little bit annoying at a time. And I can expand on this idea a lot, but I won’t ramble indefinitely on it.
Measuring Engineering Speed and Productivity
Lenny: Well, maybe what might be helpful is what are some other examples of engineering strategies that you’ve seen just to give people even more just like, “Oh yeah, maybe this should be part of our strategy.”
Will Larson: So first, what is a definition of strategy? And the best one I’ve ever seen is from Richard Rumelt. He wrote Good Strategy, Bad Strategy.
Using Metrics and Tools
Lenny: He’s coming on the podcast.
Will Larson: Amazing. He also wrote, The Crux I think came out this year sometime, which I also read. I think both great and just a phenomenal thinker who has so much depth. I think one of the challenges of writing about strategy is you’re like, I’ve seen two things and I write the book, but I think the thing that’s impressive about Richard Rumelt is he’s seen so many different scenarios that he’s able to really operate from both the particular but also the general and dataset in a really interesting way. Another book with similar characteristics is How Big Things Get Done by… I forget the authors, but really amazing dataset of how mega projects kind of succeed and fail.
But anyway, Richard Rumelt, definition of strategy is basically three components. There’s a diagnosis. What is the current status quo? What are the things that are real today? There are guiding policies which are basically based on the diagnoses, how do you want to address them? And there’s actions. And actions are how are we going to implement these guiding policies. He talks a lot about actions because concerned about this idea of inert strategy where you have like, “We’re going to deprecate our old product features we don’t use, but no one deprecates any of them.”
So he’s really concerned about this non implementation kind of useless strategy that doesn’t do anything. On engineering, I’m a little bit less worried about that. I think strategy is more interesting on engineering in terms of clarifying how we make future decisions. And so what are a few examples of that? At Uber, we only used our own data centers. We didn’t use the cloud. And this has changed since the era I was there, but in the 2014 era, no cloud, and we had a strict no cloud policy. And this was annoying because we had to indent everything ourselves or run copies of everything ourselves.
But it also meant that we were able to spin up in China in literally three months and some surreal stories from that. We couldn’t fit our racks into the data centers, so they had to take the roof off the data center and lift the racks in with the crane.
Establishing Company Values
Lenny: Holy shit.
Testing the Validity of Values
Will Larson: Just tons of stories and all this had done in three months and truly phenomenal. And Uber wasn’t in China for very long, so in some ways you’re like, we did all that just a leave? But they left with a nice stake of Didi Kuaidi and not a bad outcome overall. But I think that strategy, we run everything in data centers. We don’t use the cloud, meant we were able to move in and out of different geopolitical constraints and companies that relied on cloud presence simply can’t. There are fully constrained by where AWS or Google Cloud or Azure have built out. So that’s one good example.
Another good example at Stripe was this idea of we run a Ruby monolith and that’s what we did and that’s evolved a bit since then. There’s more Java and the Stripe of 2023 than there was in the stripe of 2016 or the 2012 or whatnot. But that policy really focused the engineers on building innovative features for our users rather than building different tooling to support different programming languages. And so in both cases, both the Uber policy around running our own data centers and the Stripe policy around Ruby monoliths, a lot of engineers hated these.
But the goal of good strategy is not to appease everyone. The goal of good strategy is to dictate how we invest the limited capacities we have or the limited capabilities we have into the problems we care about. And I think both of them were really effective towards that end.
Failure at Digg: The Rewrite Disaster
Lenny: A common theme across all these examples is essentially constraint, deciding we will constrain our options to move faster and focus on the things that really matter.
Will Larson: In solving the constraints is to me, I think the most interesting thing that strategy really does, and I think when we talk about bad strategy usually is because the diagnosis is bad and it’s usually because people are exerting what they want to be true on constraints where it’s like, “Hey, we can do all of these projects at once.” And often that’s just not true, but it’s hard to convince people that when they’re the CEO or they are really committed to believing it, but almost all bad strategies basically come down from a willful disbelief of what an accurate diagnosis is, which means then your guiding policies are kind of incoherent to begin with.
Growing From the Disaster
Lenny: Awesome. I’m excited for that episode of Richard where we’re going to go real deep into strategy, but maybe just as a lasting topic around there, if someone listening wanted to get better at say end strategy specifically or a strategy in general, is there anything you recommend they do? Is it read these books? Is there anything else?
Will Larson: If people want to get good at strategy, there’s a lot of different types of strategy, but here are some things I’d really recommend. First, I think the Richard Rumelt book, I think Good Strategy, Bad Strategy is probably the right starting point. I think The Crux also quite good, but maybe I would read that one second. Great overview of how to think about strategy. Also Thinking in Systems, I mentioned that before related to systems thinking, a big part of strategy is being able to model the reality so we can improve your diagnosis.
So I think that one is really quite good as well. If you get into the engineering side of things, there’s a lot of interesting books here. There’s Technology Strategy Patterns by Evan Hewitt. There’s The Value Flywheel effect by Anderson, McCann and O’Reilly. The Phoenix Project by Kim, Behr, Spafford, which is a modern rewrite of The Goal by Goldratt. But I think there’s still the missing canonical book is kind of missing on this one. So I took a stab at strategy and my upcoming book, which is coming out the Engineering Executives Primer coming out early next year.
Also, took a stab at it. In staff engineer my previous book, but I still think there’s a missing book here. So I am dreaming of writing an engineering strategy book for my next project, although we’ll see if that actually comes together.
Root Causes of Digg’s Failure
Lenny: Well, let’s actually follow that thread of writing something I was definitely hoping to chat about. You write a lot. You’ve written two, three, four-ish. You’re writing a new book. How many books you’ve published? Two books and there’s a third one coming up.
Will Larson: So I have two books. First one with Stripe Press, the second one, self-published and the third one with the Riley coming out in two months effectively.
New Book Spotlight
Lenny: Okay. And then also many, many blog posts for many, many years. I asked a few people what to ask you, and this came up a lot, Gergely Orosz and Alex Xu from ByteByteGo both asked just this question of just, “How do you make time to write as much as you do?” And then I also, I’ll ask this too and just answer it either first or second, just what impact has writing had on your career? Why do you keep doing it?
Lightning Round Q&A
Will Larson: I feel really strongly that you can write a lot more if you write what you want to write. And so this is one of the reasons I don’t write for financial gain and I don’t write very much on a schedule, so I’ve done a few pieces for magazines, et cetera, but I find that actually really draining to be you have a topic, you have to agree on the topic. If a topic starts missing what you want to write about, you can’t fix it a lot of the time and you’re also on this deadline. You’re like, “Ah, I’m screwing up. I need to ship this. It needs to be done tomorrow.”
I just find that really draining. Conversely, when I own the schedule, when I get to write about, “Hey, I’m writing out something.” So I started writing this infrastructure engineering book a couple of years ago. It just wasn’t there. I just couldn’t get it to come together and so I just stopped. I’m not writing it anymore. Maybe I’ll come back to it at some point, but probably not.
To me, the biggest strength of writing what you want is you get to write where there’s energy and you don’t have to write where there’s no energy, which takes you really, really negative. And this also ties into how I write books, which is that I basically write the entire thing before I start working with a publisher. And if you are, I think diligent and good at anticipating what their concerns are going to be, you can mostly reuse the content that you’re trying to write. This is also easier in the sorts of books I write.
I think harder to do in a really technical introduction to MySQL or something, you can’t just resequence those chapters and pretend it’s going to work. Those chapters build in a different way than the sort of business book that I write does. Writing the stuff that’s energizing and just giving up on the stuff that’s not energizing, that’s how I write a lot and how I’ve been writing for 16 some years. And the way I keep doing it is just by writing what’s energizing and what I’m thinking about now.
I don’t write what I’m not thinking about and I don’t write for any audience, I just write what is interesting to me. And that means some people don’t like it and that’s great. That’s totally fine. It’s not really for them, it’s for people who want to follow the ride and that’s where I focus.
Lenny:
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Okay. There’s a lot more I want to dig into here. How many posts have you written do you think over the 16 years?
Most Underrated Articles
Will Larson: I would guess about a thousand. That would roughly be my assumption. I think there are a few years where I wrote hundreds of posts, and so if you do that like three years, it’s not that hard to get to a thousand from there.
Lenny: That’s incredible, especially because you’ve had intense jobs for all of those years or most of those years. Very high pressure, fast growing hypergrowth companies. Somehow you find time to work. So first, let me just double click slash co-sign your advice here around paying attention to what gives you energy and working on things that you’re actually curious about. This is exactly the advice I give to people. A lot of people start this full-time writer, creator life, and they’re like, “What do people want? What do people want me to write about? What’s popular? What’s going to inspire go viral?”
And that’s easy to do a couple times, but then you end up creating this job for yourself that you don’t want. You don’t want to be spending all your days writing about AI if you’re not that excited by AI or whatever’s hot these days. What I find is important is almost like 80, 90% of what you write has to be stuff you’re excited about. And then maybe there’s a bit of, “Here’s what I know people really want. Here’s what I know is going to do really well.” Because otherwise you just burn out. You create a job for yourself that you don’t want. Why would you do that?
Will Larson: Yeah. I just a hundred percent agree with that. I think the other thing is that everyone converges on the same thing that they think people want. So it’s crypto two years ago. It’s like AI right now or it’s counter AI. AI is going to ruin the world. It’s hard to say something very novel because, one, everyone is trying to say something about it. Two, it’s almost certainly not what you’re that knowledgeable about where if you just stick in your lane, I think the biggest risk to writers is quitting.
A little bit like the 40-year career idea. The biggest risk to content creation of any sort is quitting soon because you get burned out. The biggest risk is not that you grow too slow initially. There’s always this sense that you’ve missed the wave. It’s too late to join Substack. The top writers are already there. You’ll never be a top writer. It’s too late to podcast. There’s too many podcasts. You’ll never make it. It’s too late to join Medium. You’ll never make it. There’s too many Medium writers.
But it is just not true. If you just keep writing good stuff, you’ll build an audience over time and you can take that audience from platform to platform. What really matters is finding something you can actually keep doing for the next decade. That’s way harder than doing it for one year.
Lenny: We have the same exact advice on this. This is exactly the things I tell everyone. When I joined Substack, I thought it was too late. I was like, “Man, it’s over.” And when I started this podcast like, “Oh man, there’s a billion podcasts. How is it ever going to work?” So I so agree, and I also so agree on the fact that this whole thing is such a… It’s a long game. There’s a lot of people. I always say it’s easy to start a newsletter, hard to keep it up. Nobody actually keeps it up because people are going to come and go. The thing that really separates success from failure is just people that can keep at it. There’s not an end game to this. It’s an infinite game and it’s about being able to sustain that over the long term.
Will Larson: You’re not competing with other content creators. If you think of it as an infinite game, you’re all working together. You can all help each other grow. There’s no maximum number of product writers or thinkers who can be doing something. You’re not less successful because [inaudible 00:34:22] exists or something like that. There’s no competition there. It’s like a false, false dichotomy.
Lenny: Yeah. I totally agree with that. Unless there’s so many and then all of a sudden what happens is the bar just gets higher, which is good because then people get better stuff and that’s fine. That’s happening anyway. Just the bar continues to increase because there’s more and more content out there. And to me that’s the ultimate thing you got to get right is just the bar. You just got to be at a high bar for anyone to care about anything you’re writing about. And to your point, to do that well, you have to actually be excited about writing about it and have background and have something to contribute.
I’m just ranting here, but the way I think about this is you need to add something new to the conversation for anyone to pay attention because there’s so much fluffy, superficial stuff. And to get anyone to care is you need to say something new that no one’s heard before or share new information they haven’t seen anywhere else.
Will Larson: I totally agree. I could keep ranting about this for the entire time. I don’t want to derail on this, but I totally agree.
Lenny: We’ll control ourselves. So then getting very tactical, I think this is what a lot of people are always wondering, how do you make time? What’s your workflow? How do you make time for writing so that you keep at it with knowing you have an intense full-time job?
Will Larson: I used to do things differently before I had a kid, so I have a three and a half year old and just timing your life just really shifts a lot once you have kids. But the biggest thing that I found is finding things to write about that also directly relate to what I’m working on. And this is where I can do something that helps me at work and helps me write at the same time because I think it’s incredibly hard to find time to write about stuff that has nothing to do with your work.
And this distracts you from your work because these… Particularly if you’re in a senior role, these can be pretty demanding jobs, but they’re not demanding because you’re responding to an urgent DM on Slack every five or six minutes. They’re demanding because you need to make some really difficult decisions really well. And I think writing about related topics is a great way to refine your thinking and improve your performance. It’s not like a conflict or you do one.
You either write or you do your job well. I think you can find a way to align. And so a lot of podcast folks do interviews with folks who are related to what they’re thinking about at work, and that’s a great way for them to learn, build their network, to refine their thinking, to test their thinking against experts in the field. It’s not like in conflict with the work, it’s in alignment. So that’s one piece. But yeah, I’ve played around with my schedule a lot.
Before I had a kid, often Saturdays would be the writing day and so morning and early afternoon would just be writing. I can’t do that anymore, so now I mostly write at night, which is tricky from an energy management perspective. But the biggest thing I would say is just if you’re actually excited about something, you will find time and energy for it. If you’re not excited about it and it’s 9:00 PM, you’re just going to get asleep. And so I really think that this is where you have to schedule a little bit deliberately, but the first thing we talked about around energy management, they really come together. When your schedule gets tight, if you’re not energized, you just won’t get it done. And why would you? It just doesn’t make sense.
Lenny: Just to close out this thread for someone that wants to do more writing knows that it’s going to be valuable, but just hasn’t any one tip that you would leave them with to get on this train?
Will Larson: It depends why people want to write. I tell people, if you just want to write something that is going to help advance your career, you should really focus on writing two or three really good things and spend a ton of time drafting, revising, getting feedback. You just focus on making one great artifact or two or three great artifacts. You don’t need to create a long-running blog where you publish every week. There’s really no need to do that if your goal is just to create some artifacts that show you’re a deep thinker, that help position you in the industry.
Don’t start a newsletter if you just want to advance yourself in the industry a little bit. Just write two or three really good things. So that’s the first thing I’d say. But if your goal is to write a lot consistently over time, my biggest advice would be just publish. And so there’s a lot of people out there with stuff that hundreds of drafts and they’ve not published anything. And my thing is I publish almost everything I write. If there’s something that I’m not going to publish, I don’t start writing it because I have a quick check in my head like is this something I can write and publish?
And if my answer was like, “No, I just don’t even start.” And my accuracy has gotten higher over time as I’ve written more, but I published pretty much everything I write. That’s why some of it is not that good. And that’s okay. Again, I want to write. I want to get these ideas out. I want to show what I’m focused on and my evolution as a thinker trying to learn how to operate in these different roles in these different companies. I’m not writing trying to create a polished perfect thing, and also I’m not writing to maximize a reader’s experience of reading it.
Some people don’t like that, and I think that’s a totally reasonable thing not to, but I think what I can bring you is my experience as an operator who’s actively learning and thinking through. I think that’s really valuable to other operators in the industry. In terms of giving you the perfect writing, I try to do that, closer to that. I don’t know if I ever hit perfect writing, but that’s where my books are. The books are taking a collection of thoughts over a couple of years, cleaning them up a little bit, packaging them. They’re way higher quality than my typical writing.
But yeah, I would just publish a lot. Don’t worry about the quality. Sometimes people will send you silly feedback and I just don’t respond to that stuff anymore. You never know why people send you something like that. I think trying to debug people you don’t know is a bad use of time. It’s just kind of like, “Thank you. Move on to the next. Don’t even spend time worrying about it.”
Lenny: I like that term debug people. I think people way overestimate how much anyone cares about what you put out. Most people are going to look at it for three seconds and be like, “Eh.” That’s the worst case scenario basically is just like, “I don’t care about this.” Not like, “Oh, Will is such a fool.” What a dumb thing to say. Right? No one has time for that.
Will Larson: And if they do, that’s a them problem, right? The internet is a big place with a lot of people and there are people who are going to be having a really bad day when they encounter something you do and they’re going to channel that anger at you or that frustration at you, but that’s not about you. That’s just like you happen to be there when they engage with it. You don’t have to take that on. That’s not your situation. It’s okay.
Lenny: Also, when you’re just starting out, that’s going to be the least stressful time to write because nobody knows it or sees it, so that’s when it’s like “Take all the crazy… Just do stuff.” It only gets more stressful as you build an audience over time.
Will Larson: Yeah, absolutely. Absolutely true.
Lenny: Okay. Shifting topics. There’s a lot of product managers that listen to this. Something PMs often wonder is how to have better relationships with their engineers, their eng managers. What advice could you give to product managers to build more productive happy relationships with their engineers and eng managers?
Will Larson: So the core problem, and most of the EM PM peers that I’ve worked on… There’s two core problems. So one, sometimes the incentives are misaligned and that’s hard to navigate, but if you can just be honest with each other and understand the incentives, sometimes you can find a compromise, but sometimes the EMs and PMs will be misaligned because just their incentives are so far apart that there’s no way to get to the bottom of it. And so this might be timeline related or saying yes to sales related. Or the engineer is like, “Hey, we definitely can’t say yes to that.” And the PMs are like, “Actually, we’re going to say yes to it because really important for me getting promoted,” or something like that.
Is it ever this simple? It’s really never that simple. People create simplistic narratives to find villains that they work with. There are no villains in the workplace. They’re just people with complex incentives that are doing complex things. But sometimes I talk to EMs who think, “Oh, the product manager is just saying yes because they want to get promoted because the salesperson will review their promotion or something.”
The reality is never as simple. The reality is the business needs to sell stuff to remain functioning. You can’t just say no and have the business succeed. That doesn’t work either. So one, understanding the incentives. The other piece though, and I think this is the more common case or just that the EM or the PM just don’t understand the other person’s needs and they start arguing before understanding. So my biggest advice to both the EMs and the PMs, is before you try to solve the conflict, it’s like pushing to ship this feature, pushing to change the approach. Just make sure you actually understand what they care about.
There is this idea that you have to make trade-offs and that there are tons of hard trade-offs to be made in the field, but my experience is if you really deeply understand what everyone wants, there’s usually a compromised solution that gives everyone exactly what they want. That doesn’t take more time. You just have to be willing to dig deeper into it and understand the true needs for each party, which is often not what they’re saying by the way, which is part of the confusion.
Lenny: On the incentives piece, is there anything you’ve seen work to fix that problem? Because if PM performance reviews are based on impact engineering, performance reviews are based on interesting projects or uptime, do you just work to change those ladder definitions? What actually can help that situation?
Will Larson: So my biggest thing has been trying to force this idea that EM/PM pairs are peers and they generally have the same performance rating. And there’s exceptions here. It could be the EM is clearly not performing and then it’s not the PM’s fault if the EM is can’t show up to work. The team doesn’t respect them. Sometimes there’s clear non-performance, but generally hard situations are not situations where one person is obviously terrible. Those are easy to diagnose, those are the easy ones. But in cases where there’s two folks who seem to be pretty good, but just the overall execution is not working out, I think this idea that same perf rating for both drives a level of one pain, but the right perspective.
Also, something that I think Carta has experimented a little bit with over time. Henry, our CEO has a blog post about trifectas in doing that, but not just for EM and for PM, but also for that business leadership as well where you all get graded the same score based on your ability to evaluate and solve for the entire set of constraints, not just your functional constraints.
Lenny: Wow. That’s so interesting. So your recommendation, something you’re doing, it sounds like is the engineer manager and the PM get the same performance review rating? And so they’re discussed in the same meeting.
Will Larson: Our chief product officer, Vrushali and I spend a fair amount of time calibrating together and making sure… Again, there’s cases where there’s an exception because there’s clear issues happening for someone. But on average that is what’s happening. And I think people know that’s what’s happening because we told them that. And I think that’s pretty powerful.
Lenny: That is so interesting. I’ve never heard of that approach. That is definitely solving that problem of EM/PM or…
Will Larson: Yeah, the incentives are shared now, which isn’t perfect. It’s still hard to balance them. They can still make the wrong trade-offs, but at least they understand the incentives are shared, which I think is a pretty powerful idea.
Lenny: That is really interesting. I imagine some companies might even want to include design managers in that, take another step.
Will Larson: The role and the primacy of different functions in different companies varies so much that it’s hard to have a one size. You could also imagine where you want a staff engineer in that or not. And so I think very company specific. But yeah, I think design could absolutely be involved particularly for a design led company like an Airbnb or something like that.
Lenny: Wow. So interesting. Maybe just as a final thought there, if a PM is having challenges with their EM, what do you think PMs maybe don’t realize their engineering managers are finding important or maybe are stressed about that they’re just like, “Oh wow, I never thought about that.”
Will Larson: I think one of the biggest challenges I’ve historically seen, particularly in the last decade is this idea that engineering managers have the job of giving their team interesting work. I think that that can put… You often see this in growth teams where the growth team is like, “Hey, we just need to do a ton of experiments.” An engineer is like, “I want to build something brand new.” And the eng managers in between those try to figure out, “Need to ship 50 experiments that are pretty boring and they want to do something brand new. I don’t know how to do solve this.”
So it’s a tricky moment. And good EMs find the way to balance, but that’s the biggest source of ongoing friction where the EMs have been told by their teams they need to do something that the PMs just have no visibility into. And it makes the EM seem totally unreliable partners because they’re trying to solve these little bit of these invisible constraints. And that’s where I think pushing further to understand, “Hey, you keep prioritizing this rewrite into a new programming language.”
To me that seems like completely idiotic thing to be doing. What’s going on? And then once you understand, you might not agree with them, but at least you can have an honest conversation about how to navigate those constraints versus just like, “Man, you won’t believe what my EM partner did today. This bozo did blah, blah, blah.” And having this victim villain mindset about your peers.
Lenny: An adjacent topic that I wanted to spend some time on is measuring engineering velocity productivity. I think it’s probably one of the most common and also maybe the most annoying questions eng leaders get is just how do I know if my engineers are moving as quickly as they can? How do we help them move faster? What advice do you give to eng leaders for eng teams just for how to measure productivity well?
Will Larson: This is a question that’s coming up even more in a moment when we’re reducing a lot of the size of teams from the industry when the venture capitalists that are on the board for these venture-backed companies are pushing on the efficiency of engineering. Engineers are trying to figure out how do we represent this? How do we prove that we’re appropriately productive for the amount of headcount and funding that we have as an organization?
And man, that’s hard. So the first way that people focus on trying to answer these questions is just benchmarking by the amount of funding that you have. And that’s pretty straightforward to do is a mechanical exercise. You get a data set from your venture capital funds or whatnot, and you figure out, “Okay. How much should we be spending in R&D? How much should we be spending in engineering? How much should we be sending on infrastructure engineering in R&D?” And you can benchmark this all out and figure out what the correct numbers are there.
The problem is this is a very mechanical and not very insightful, driven way. It’ll get you a defensible answer. It’s like the old, no one gets fired for buying IBM, which definitely hasn’t been true in my career ever. But this idea that if you just have the right benchmarks, DCs won’t judge you for spending too much in engineering, but this doesn’t actually help you get to the right place. It just helps you get your board to be less angry at you, which is useful because it’s hard to do good work when your board is angry at you.
But it’s not useful in the sense that it doesn’t actually help you run your organization effectively. So then there’s the much harder mediator problem of how do you actually know if your R&D team or engineering team is effective? What I find is a couple of things. First, if you’re a good leader and you talk to engineers, they will tell you… The engineers know if their teams are effective or not. And if they’re not, they’ll also tell you why not. And their diagnosis can be wrong, but there’s a crumb you can start picking up and you can trace the crumbs to figure out what’s wrong.
Often you’ll have more experience to analyze the complaints to figure out what kind of the contributing causes are to them. But yeah, if you just go talk to the team on an ongoing basis, you’ll know if they’re effective or not and you can go work to solve those specific problems. But again, you can’t tell your board, “Oh, it’s fine. I talked to the teams that they’re good.” My intuition’s spot on because how do they know if your intuition is good or not?
They’re dealing with a huge portfolio and some of their leaders are talking to are good, and some of them have terrible intuition. How do they actually assess? I think it’s tricky. What I’ve tried to do is basically two things. One, aligning engineering evaluation to the business and product goals. So I want us to be wholly accountable with the product goals. Well, we did a good job products like screwing up over there. Obviously, a lot of companies find comfort in doing that, but really we’re here to support the product, to support our customers in doing something interesting. We’re not here to build novel systems unless it supports the customer and the product.
So first try to align heavily there. Second, I think just showing the roadmap of the valuable things we’ve done in the last six months is really powerful. I think sometimes people are like, “I don’t have anything to put there.” And you’re like, “Yeah, that’s a real issue.” Or if you have the ton of stuff to put there, that’s great. I really find that if you just commit, show the number of meaningful, meaty things that have impact that you’re doing and you can explain the impact, people will step back and give you space. If you can’t populate that list, people will have concerns and rightly so, they should be concerned about that.
Lenny: Is there any metrics or tools or anything like that that you find useful too? Because these are all awesome piece of advice, but I imagine everyone is always just like, “Give us this number we’re tracking, give us this dashboard, see what engineers doing.”
Will Larson: So one of the most influential books in the last decade in software engineering leadership and infrastructure is Accelerate by Nicole Forsgren, Gene Kim, and I believe there’s a third author on that one, but I’m forgetting right now. Really phenomenal book and it comes up with these four metrics. It comes up with lead time. It comes up with incident remediation time. It comes up with failure rate. And the fourth one of some sort. There’s at least 50 different startups out there that are selling you dashboards that instrument these pieces of data and they want you to just evaluate your team on them.
The challenge is these are really good diagnosis metrics. And so hey, our deployments are slow. Why is that? How do we speed them up? But your deployments being slow doesn’t make you a good company or a bad company, it just tells you where you should focus on improving. It doesn’t actually change how you are. And similarly, if your lead time is quick or slow, it tells you where you should invest or it doesn’t actually tell you if you should fire your engineers or something like that. That’s way, way more details specific.
So people do like to see these metrics just like they see uptime metrics. A lot of engineers report on sprint points or stuff like that to their board, which are just totally, totally fake thing to be reporting on. But people get some comfort on it. So my biggest thing here is when people measure things, this isn’t an engineering only problem, but when people measure, they take on the perspective of an expert and they can tell you why not to measure everything. They can tell you why every measure is wrong or inaccurate and they rule everything out and so they measure nothing and they go to someone who’s not an expert and well actually there’s no accurate measure to give.
They’re not an expert is like you don’t know what you’re doing. And so you just have to get comfortable measuring something that’s not perfect, but you can actually measure and reporting on it and then the measure that’s imperfect as people ask questions, that’s an opportunity to educate people on why the measure is imperfect. What are some things that misses or kind of the lies from the conversation.
Metrics are about educating the people consuming the metrics about the reality of the rich data underneath. They’re not about this perfect data set that shows everything starting with something mediocre and the Dora metrics are really helpful for diagnosis, but if you have to, they can also be a good enough starting place to start reporting to your board or your CEO or to the other executives and then you’re like, “Oh, there’s all these problems with them.”
Yes. There are all those problems with them, but that’s this place you start and you educate people up from there to help them understand the nuances and that’s how they become more sophisticated, understanding engineering, not by refusing to give them anything they can possibly measure.
Lenny: Awesome. I’m glad that was your answer because we had Nicole on the podcast and she talked through Dora and all the frameworks that she recommends. And she even actually shared some benchmarks that she points people to that give you some sense of just like, “Are you in a good place roughly or not?” So we’ll point people to that episode to dig deeper. Awesome. I’m glad that you’re a fan.
Okay. Just a couple more questions before we get to our very exciting lightning round. One is around values, company values, org values. Do you have some really good advice for people for how to think about coming up with values? What do you share? What do you recommend to people that are trying to figure out what values they should define for their org and their company?
Will Larson: I mean, values are really interesting, right? And different companies talk about values in different ways. I once worked at a company where the execs went to visit the Facebook campus. They saw the values written up on the wall and they took the Facebook values and wrote them up in our walls and that didn’t do a whole lot. It maybe undermined people’s confidence in the critical thinking of the executive team that just took these written up on Facebook walls and replicated it.
But I think those values did work well for Facebook and those values were meaningful for Facebook. And so first you can’t do is just steal values. Value cargo culting. Users first. Great Amazon value. A lot of companies aren’t users first and that’s okay, but what’s not okay is when you put, “Hey, we’re users first,” and then you actually show the decisions you’re making and you clearly aren’t users first.
So one of the things I think about is just honesty. And so good values have to be honest and so any value can be honest or there’s no universally honest values. You can say something like, “We’re thrifty.” Or we can say something like we spend as much as we need to get the best value. Those are totally different and good companies are run both ways. So the first rule I think about a lot is honesty. You actually do what you claim you do and the value. The second one is applicability. You have to have value that you can actually figure out how to apply to your work.
And so one of Stripe’s values was no longer a value I believe, but it’s optimized globally. And so optimized globally is a really interesting problem because sometimes you’ll have something you wanted for interesting value. Sometimes you want to do something and you’re like, “Hey, I want to introduce a new programming language that’s better for my team.” For the organization overall, this is actually much worse for the organization so I’m not going to do it.
Uber didn’t have this as a written value, but implicitly Uber’s value was do what’s good for your team and ignore everyone else because that will slow us down. So the two different companies had opposite values, but they’re both very applicable. It’s like how should we navigate decisions? Should I optimize for my team or for the organization? So those are applicable to real problems and they were honest where Uber was just like, “Don’t worry about other people.” Make it work for your team. And that’s how they moved so fast because they just didn’t worry.
Lenny: Wasn’t their value of toe-stepping, encouraging toe-stepping, something like that?
Will Larson: Let builders build toe stepping. There were a number of values that could be interpreted in different ways and sometimes they got weaponized in various ways as all values do. But these are both interesting in different ways. And so number one is honest and two is applicable. Three is I think the last thing for a good value is this idea of reversibility. So there’s some values that aren’t actually usable. And so here’s a good example. We build good software. Okay. But why would you ever not build good software? That doesn’t make sense or we solve customer problems that matter. Good.
What company doesn’t think they’re solving customer problems that matter? And so there’s certain values that just you can’t apply. And so I think of these as identity values. These are really just you describing who you want to be or we care about our customers. Great. But who would say they don’t care about that? There’s certain values that I think of as just identity values and they’re not wrong to have identity values, they just aren’t very useful.
You can’t actually use them for anything. And so I just always push people not to spend too much time on these because they feel good when you’re an executive team debating what are these identity values? It’s like we’re kind to other people or sure that sounds good. We’re a family. Sure, that sounds good. That one I guess is a little bit reversible. There’s Netflix, which is like, “We’re a team like a sports team. We’re not a family.” And so a little bit reversible, but not perfectly.
But yeah, these are the three that I found really useful for any value. Is it honest? Is it applicable? And can you reverse it? And if not, it’s probably actually not helping the team make decisions.
Lenny: These are great. It reminds me a lot of… I was there during Airbnb’s period of coming up with values. Something that I would maybe add and maybe fits into one of these buckets is it needs to be clear who doesn’t? There needs to be a group that doesn’t quite fit because if everyone fits, you’re not doing anything useful. What’s the point? Which feels weird to say, why would not everyone fit in our big group of awesome company? But it’s clear who is not a good fit, who doesn’t belong basically. It’s kind of like a cult a little bit like, “Who’s not in our cult? Who doesn’t belong?”
Will Larson: But I agree. If it doesn’t apply to anyone, then why bother saying it? It doesn’t mean anything. And you could say it’s actually the hiring filter where there are people who you’ve explicitly chosen not to hire because this wouldn’t apply to them. Then I think it’s useful because it helps you actually figure out who to bring in. But if it doesn’t apply to anyone you’re hiring or anyone that you have in the company, then it’s just isn’t worth having because you already have too many values. You are already trying to get rid of values because you have 17 and you need to get down to four where people can remember them. So if it doesn’t apply to anyone, why bother having it at all?
Lenny: Yeah. Integrity is a common one. Integrity. Everyone has that. Nobody wouldn’t want integrity. What is unique?
Will Larson: We’re a non-integrity company. We’re the company that thinks integrity is bad. That’s not a real thing.
Lenny: The other one I’ll add to is honest. So Airbnb, we had six values initially. One of them was simplify and a year or two later everyone just realized we’re not actually good at this. We want to simplify, but we’re not great at this skill and values should describe who you are not who you want to be and aspire to be. So they cut two values including that one, and they’re just like, “Let’s just do these four because this is actually who we are. Let’s be honest with ourselves.”
Okay, final question. I wanted to visit Failure Corner, something that I’ve added recently to this podcast where people share a story of failure. And you have this amazing post about your experience with Digg and the rewrite that you all went through. I think it was the version four of Digg. Can you just tell that story and what happened? How much of a mess it ended up being?
Will Larson: Yeah, Dig V4 is… I mean, it’s still something I have a lot of fond memories for. There’s one picture that I’ve kept and there’s a picture of a lot of the engineers around this table in the middle of this giant office and they’re serving sushi. We had waiters, caterers come in that day. They’re serving sushi. They have plates with champagne flutes on it. There was a full bar and we’re all around this table because the site is not up.
And so Digg before essentially what Kevin Rose or the board or some combination there realized is that Digg was losing to the social networks and that this idea of aggregated news was going to be outcompeted by the Twitters, the Facebooks, et cetera, if we didn’t find a way to move to have a social component for it. It even outcompeted by Reddit longterm was kind of the fear. Although at the time that that was far from obvious. And so we needed to move to support social functionality and the previous version we simply couldn’t get it to work.
So the decision that was done, I think two and a half years before I joined, and the shift about six months after I joined was they needed to do a complete rewrite in order to get there. This is a decision that never works out for anyone. So I think as someone with more experience, I could have predicted this wasn’t going to work out. But I was earlier in my career. My PM counterpart at Yahoo, Das Kofinovsky. He went to Yahoo and he’s like, “Come to Digg.”
Worst case you’ll make a couple hundred thousand in a year. Worst case. Probably really great outcome. Anyway, that’s not what happened. The worst case was a little bit optimistic. So we go and the CEO got fired two days before I joined. So the current CEO left and then Kevin Rose came back for about six months, something like that. And we’re just on the death march trying to get this thing out.
So we pushed really hard. This was before the cloud for the most part. So we wiped pretty much all of our existing servers to re-image them to the new software. We try to bring the site up and just keeps crashing. And so it basically takes us a month to get it fully functional again. And so that day sitting around that table with champagne and sushi, that’s just like day one. And by 30 days in, most people aren’t even trying to get the site back up anymore.
There’s maybe five of us who are still trying. And we did. I think that was a really powerful moment for me. I think in the first two days myself and Rich Schumacher, one of the other engineers, we had to write a caching system from scratch, which got us half the way up. Really a terrible way to do software on a side note. I’m not recommending this to anyone. This was a series of anti-patterns kludged into a launch. But we got it partially up, but we had to restart it every 12 months.
Every 12 hours, every server had to be restarted even with the caching mechanism. And then about three weeks after that, I finally figured out what the core bug was, that was bringing us down every 12 hours. It was this incredibly simple issue that had just been hard to debug, basically related to the way that Python initiates variables used as default parameters. It’s something super silly and we just had someone who hadn’t written Python before who was working on the API code, so they didn’t realize it’s gotcha.
Then no one else caught it when it was reviewed and it just took a long time to debug. It was such a non-obvious. It didn’t break anything, it was just doing a lot of extra load on the servers. We finally figured it out and it was just really remarkable experience pulling through. And you know what? The company still went to zero. So we had this at launch. I think we did this heroic, heroic stretch to get it working.
A couple weeks after that, a new CEO came in, did a round of layoffs. This is back I think 2012. The team nine months after I started was down to 30 people from about a hundred and it went downhill from there, from a business perspective. But we launched a lot of functionality, has really learned just a tremendous amount. And it kind of shaped what I think about in terms of early in your career, getting learning and going into a company that is maybe having a rough time.
I became a manager two and a half years into my career. Basically running the entire engineering team there because everyone who had a lick of sense quit or got laid off, and it was just complete idiot me trying to be the manager for the engineering org, wasn’t qualified and no one would’ve given me that job, but I was the only one dumb enough to take it at that point. I learned so much and I really the kernel that turned into my entire career where it was that opportunity, even though at the time it was pretty grim.
Lenny: That’s an amazing story. I feel like a lot of these experiences were in the moment, it’s just like, “What is going on? This is so bad and hard,” end up being the most interesting and looking back end up being the most biggest teaching experiences. The ones you like bond over with people you work with like Apple. It always comes to mind where it’s just like Steve Jobs’s joke, people like crazy and then they look back and that was the best moment in my career.
Will Larson: You would never voluntarily take on a lot of these really challenging things, but sometimes when they show up, you’re with a group of people you really respect, you love working with and you want to overcome together. And that’s really powerful experience. Even if Uber China was similar where if someone had been like, “Hey, do you want to go work on this Uber China migration?” I would’ve been like, “Absolutely not.” But no one asked. They’re just like, “Get this done,” and so we did. I think these things are pretty remarkable.
Lenny: And just to be clear, so Digg was down for a month basically during this period? Is that…
Will Larson: So it basically didn’t work properly for much of the month. It was like read only was back up in about three days, but the vast majority of the actual user functionality just wasn’t working properly for pretty much an entire month and it was not that good. I mean not great, but that wasn’t the biggest problem Digg had at that point. But it was one of the biggest problems that had at that point and it wasn’t a real sign of things likely to go well for us. But like I said, you learn from those and I’m really proud that we and the team got it working, got it running even if ultimately we still went to zero and ran out of money and kind of sold for parts.
Lenny: Do you think Digg could have made it? There was a world where Digg would’ve been a hugely successful business or do you think it was just way too late and it’s the wrong product?
Will Larson: The thing that really killed Digg is the change. It wasn’t SEO driven. So monetization was from ads. Well, many companies including Digg claimed that it was the first in kind of stream, in feed like advertising company where Twitter has ads within the tweets or Facebook does. But Digg did that before Facebook or Twitter really innovated the ad format. But the vast majority of monetization was on these… We call them permalink pages, which is page 40. Then article we crawled and the vast majority of traffic for that was driven by Google search. And so there was an SEO change, which really is the thing that started creating the urgency for us to launch this migration.
SEO changed, traffic started going down, monetization was driven by that. And so we were already on fire by the time we tried to launch this. But I do think that I still want something like what Digg was trying to become today. Social news based on like what my friends are actually reading and liking merged with a global index of similar users who are interested in similar topics. It’s still a product that I think Google Reader has some kind of similar components to it.
These are both interesting products solving interesting problems that have not for whatever reason been successful as businesses. And I do think there’s a gap there still, but there’s a lot of people trying unsuccessfully to fill it and there must be a reason why people struggle to fill it despite so many people trying.
Lenny: Awesome. Will, is there anything else you want to share or leave people with before we get to our very fast lightning round because I know you have to run in about five minutes?
Will Larson: I think we’ve covered a lot of it. New book coming out. New book coming out in February, Engineering Executive’s Primer, O’Reilly. But that’s probably it.
Lenny: Awesome. Where do people find that? I know it’s on O’Reilly. You can look at a preview of it even today, right?
Will Larson: Yeah. O’Reilly, you can see the early copy. You can order it on Amazon as well, but it won’t be shipping until February.
Lenny: Okay. And then just to be clear, who’s this for? It’s for engineering executives by the sound of it.
Will Larson: It’s for engineering executives, but more so like anyone who wants to be one, anyone who’s trying to figure out how to work with an engineering executive. So I think if you are struggling to understand why your CTO keeps doing boneheaded things, or if you want to side manage them, you’re the head of product and you can’t get the CTO to stop complaining about the engineers need more interesting projects to work on, this might be useful for you too.
Lenny: Amazing. Okay. Ready for the lightning round?
Will Larson: Let’s do it.
Lenny: What are two or three books you’ve recommended most to other people?
Will Larson: So I talked about Thinking in Systems and Primer. I talked about Good Strategy, Bad Strategy, but I’ll give you a third one, which is Don’t Think of an Elephant by George Lakoff. It’s a really interesting book about framing things in conversations that has really changed how I communicate.
Lenny: Amazing. Favorite recent movie or TV show you’ve really enjoyed?
Will Larson: I don’t watch much TV or many movies anymore, but something I do still watch is Top Chef with my wife. She’s a Top Chef, super fan. And there’s something just very relaxing from these formulaic structured shows where you kind of know what’s going to happen. There’s no real consequences that matter too much and just escaping from real life to these formulas can be pretty peaceful.
Lenny: No one has ever mentioned Top Chef before, so that’s fun. Do you have a favorite interview question that you like to ask candidates that you’re interviewing for a job?
Will Larson: A lot of my interviews now are trying to help people decide if they actually want to join a company. And so my favorite question I ask now is like, “Hey, we’ve really loved you. You’re going to come through. I think you’re going to get a lot of offers from other companies too. I bet you’ll have three or four really compelling offers because you’re a fantastic candidate. How are you going to figure out really specifically which of those options are right for you?”
I think it forces people to tell you what they want and then you tell them why you have that more than anyone else, and then you can actually pitch them on what matters versus pitching on things that don’t.
Lenny: Love that. Do you have a favorite life motto that you often come back to share with friends, find useful either in work or in life?
Will Larson: No mottos, but I can think of two things I thought about a lot. At Uber is something I talk to people a lot because it was a challenging time for much of it. It was there’s no way around, just through.And that was like, “Hey, we’re not going to dodge around this. We’re going to gut through it and we’re going to get to the other side and then we’re going to be there.” What I think about a lot more now is, will anyone remember what we decided in six months? Because I think people stress out about a lot of decisions, but I increasingly believe most decisions people stress out about just aren’t that important.
So I’m like, “Will anyone care in six months what we did here?” And the answer is no. Just do something reasonable and let’s move on to the next more important thing.
Lenny: I love that. You’ve done a lot of writing. Is there a piece that you’ve written that you feel like is underappreciated that no one really totally got and hasn’t spread and you’re like, “Ah, I’m so proud of that one”?
Will Larson: Maybe the piece I’m most proud of from last year was Hard To Work With. So Hard To Work With is basically I see a lot of people who are incredibly talented, but they try to hold their peers to a high standard and then they’re viewed as combative or difficult to work with. And this one comes from a core struggle of my early career where I kept trying. I thought I was holding people accountable and people were just like, “You suck to work with.”
And I was like, “But I’m just trying to have a high standard. Isn’t that what we want?” And talk about honest values. Every company is like, “We have high standards,” and you’re like, “Well, let’s do it.” And then they’re like, “We don’t have high standards here. You suck.” So that one is one that really is so transformational to me, and I think it really hits some people hard because I think a lot of people really go their entire career without figuring this one out.
And they’re some of the most talented, hardest working people you’ll ever work with and can’t quite land this one idea that’s holding them back. And they care so much and they are often despised because they care so much. I think this is one that I hope more people will read over times and there’s a really important lesson for me in there.
Lenny: Well, we will link to it in the show notes and help more people discover it. Two last questions. Where can folks find you online if they want to reach out and maybe follow up on questions? And how can listeners be useful to you?
Will Larson: So find me online, lethain.com, lethain.com. All my writing, my books, everything links linked there. And the biggest thing that I’m thinking about right now is just strategy. So really curious for folks who are thinking about strategy, who think they’ve done product, business, or engineering strategy well. Would love to hear from folks what they’re thinking about, what’s actually worked and maybe what are the lies that have not turned out to work that they thought might work earlier in their journey.
Lenny: Amazing. Will, thank you so much for being here.
Will Larson: Thank you so much. This is really fantastic.
Lenny: Same for me. Bye, everyone. 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 |
|---|---|
| An Elegant Puzzle | An Elegant Puzzle |
| CTO | CTO |
| Das Kofinovsky | Das Kofinovsky |
| Digg | Digg |
| Don’t Think of an Elephant | Don’t Think of an Elephant |
| Eric Vogel | Eric Vogel |
| flows | 流量(flows) |
| Gene Kim | Gene Kim |
| Good Strategy, Bad Strategy | Good Strategy, Bad Strategy |
| Hard To Work With | Hard To Work With |
| Henry | Henry |
| Kevin Rose | Kevin Rose |
| Nicole Forsgren | Nicole Forsgren |
| PM | PM |
| Rich Schumacher | Rich Schumacher |
| Staff Engineer | Staff Engineer |
| Steve Jobs | 史蒂夫·乔布斯 |
| stocks | 存量(stocks) |
| systems thinking | 系统思维(systems thinking) |
| The Engineering Executive’s Primer | The Engineering Executive’s Primer |
| Thinking in Systems | Thinking in Systems |
| Top Chef | Top Chef |
| Uber | Uber |
| Vrushali | Vrushali |
| Will Larson | Will Larson |
| Yahoo | Yahoo |
| ZIRP | ZIRP(零利率) |
Reformatted by reformat_english.py
随着科技行业告别零利率时代的野蛮生长,工程管理的核心正经历深刻重构。在这篇对谈中,资深工程领导者Will Larson分享了他对“工程师思维”的独到见解。他指出,行业过去常陷入一种误区:将工程师当作需要溺爱的“孩子”,刻意将他们与棘手的商业问题隔离。然而,当扩张红利褪去,这恰恰是重塑工程师角色的契机。Larson认为,真正的成长源于赋予责任——唯有打破保护伞,把工程师当作同侪,交予真正困难的命题,才能打通他们通往高级领导岗位的路径。本文提供了一种沉稳务实的视角,值得管理者与工程师共同反思。
工程师思维 | Will Larson (Carta, Stripe, Uber, Calm, Digg)
**Will Larson:**我认为我们经常把工程师当成小孩子来对待,而不是赋予他们责任和能力,让他们真正像成年人一样发展。于是就会出现,“哦,工程师不会想做那份工作的”这种说法。但把工程师与重要的事情隔离开来,实际上对他们是不好的。所以我认为,其中一个亮点在于,我们正回到这样一个时刻:我们可以真正把工程师当作同辈看待,把他们放入真正高级的领导岗位,而不是抱有这种基本假设:“哦,我们必须溺爱他们,或者把他们与真正的问题隔离开来。”这也是他们能获得成长机会的方式。
**Lenny:**今天我的嘉宾是 Will Larson,他是这档播客中观众点播次数最多的嘉宾之一。Will 目前是 Carta 的 CTO。他曾在 Stripe、Uber 和 Calm 担任软件工程负责人。他撰写了两本所有工程师必读的书:《An Elegant Puzzle》和《Staff Engineer》,并且他将在明年二月出版最新著作《The Engineering Executive’s Primer》。他还在 lethain.com 上定期发表文章,这是每位工程师和工程领导者的必读内容。在我们的对话中,Will 分享了关于制定工程战略以及总体战略的建议,如何改善工程经理与产品经理(PM)之间的关系,如何在从事高强度的全职工作的同时挤出时间写作,他建议如何衡量工程生产力,如何制定公司价值观,他在 Digg 期间的一个精彩故事等等。Will 是一个极其宝贵的人和领导者,我很高兴能为大家带来这期节目。言归正传,在简短的赞助商广告后,有请 Will Larson。
嘉宾介绍与开场
**Lenny:**Will,非常感谢你能来到这里,欢迎来到播客。
**Will Larson:**非常感谢。非常非常激动能来到这里。
**Lenny:**很多人建议我邀请你上这档播客。你在外面有很多粉丝,我很高兴能深入探讨工程话题,我们在播客里聊这个聊得不够多。所以感谢你抽出时间。
**Will Larson:**别客气,谢谢。我希望在你未来某个时刻完全转向工程领域之前,能做一个不错的早期工程类嘉宾。
**Lenny:**哇,我喜欢这个想法。那会有多酷?我刚开始职业生涯时其实是个工程师。如果我们兜兜转转回到原点,那该多有趣?总之,我觉得从“工程领域正在发生什么变化”开始聊会很有趣。感觉过去几年发生了很多变化,尤其是从 ZIRP(零利率)时代到今天截然不同的市场。从工程师的角度来看,你看到的最大变化是什么?另外,你又是如何建议工程领导者去应对所有这些变化的?
工程领域的近期变化
**Will Larson:**我认为现在是一个相当奇怪的市场时期。我大概是在 2008 年次贷危机爆发前夕开始工作的。所以最初两年情况并不好。当我加入 Yahoo 时,基本上每四个月就会有一次裁员。总会有某种形式的裁员,相当混乱。但随后我们进入了过去这十年,一切都很平稳。所以数字在上升,收入在上升,人数在上升,人们开始学习如何构建真正庞大的团队。人们开始学习如何大量招聘。当我在 Uber 的时候,有些日子我会连续做六场面试。我就会待在一个会议室里,到了某个时刻你甚至记不清你在和谁说话,因为你一个接一个地和太多人交谈了。你只剩下一些潦草的笔记,事后试图去辨认。
现在完全不同了。很多工程经理在 18 个月前可能把一半甚至更多的时间花在招聘上,而现在他们一个月只做两次或更少的面试。甚至可能一个月零次面试。所以人们在招聘上投入的时间确实发生了转变。取而代之的是,许多不同的能力变得更加关键,或者一个非常优秀的工程总监可能之前一直把时间花在出色的招聘上,这能让他成为高绩效者,但现在这个人实际上无法展示他擅长什么了。如果这个人没有弄清楚如何领导团队,没有更深入细节,有时候也没有弄清楚什么是正确的资源分配,什么是工程团队的正确规模,那么他可能会被认为是一个低绩效者。这些东西我们以前讨论得不多,或者可能如果你真的惹怒了 CEO,也许某个基础设施团队明年增长得慢一点,但到了现在这就是完全不同的游戏了,团队实际上正在消失,团队正在被裁减,团队正在被合并。这只是在 ZIRP 时代我们一直回避的事情,而现在它已经成为许多工作的核心部分。
**Lenny:**感觉工程师们……他们过去在公司内部、对公司有很大的杠杆作用。我想这也正在发生巨大的变化。
**Will Larson:**我认为确实如此。我认为这在某种程度上其实对工程师是不利的。我反复强调的一个观点是,我认为我们经常把工程师当成小孩子来对待,而不是赋予他们责任和能力,让他们真正像成年人一样发展。于是就会出现,“哦,工程师不会想做那份工作的”这种说法。
实际上,把工程师保护起来不让他们接触重要的事情,对他们并不好。实际上我认为亮点之一是,我觉得我们正回到这样一个时刻,我们可以真正把工程师当作同侪对待,把他们放到真正高级的领导角色中,而不再有这种基本的假设,比如,“哦,我们必须娇惯他们,或者把他们从真正的问题中隐藏起来。”这也是他们能获得成长机会的方式。对我来说这是最近转变中的一个亮点。
**Lenny:**我确实经历过这种情况,也体会过那种你不想得罪工程师的时候。所以你的意思是,正因为这种情况在改变,领导者可能不再需要那么担心惹恼工程师了,加上你通常也认为我们本来就不该那样对待工程师?
**Will Larson:**是的,我想两者都有点,但我认为在之前的那个时代,招聘和留存是评估中层管理者的最大标准之一。失去团队成员是一个巨大的、巨大的问题。于是你开始有一点娇惯,这实际上是很糟糕的,同样,对工程师糟糕,对团队糟糕,对所有人糟糕,对组织的效率糟糕。但现在我喜欢的一点是,我们可以给工程师真正困难的问题,我们可以真正让他们承担责任。这意味着我们可以把他们放在高级职位上。
我一直在推动的事情之一是,我写了上一本书《Staff Engineer》,关于高级工程师的职业路径是什么。挑战之一是,如果我们因为只想留住所有工程师而不习惯让他们承担责任,那么我们就不能把他们放在高级职位上。所以我认为我们确实看到了一点转变,我们可以真正让他们承担责任,这意味着我们可以把他们放在高级职位上,这意味着工程师实际上可以得到他们一直试图得到的东西,但由于我们把他们娇惯得有点过头了,之前我们一直没能做到。
系统思维的陷阱与本质
**Lenny:**好的。所以我有几个方向想去探讨,我就随便摸索一下看我们能聊到哪。首先,你是系统思维(systems thinking)的大力倡导者。我们之前聊过这个。我想很多人听过系统思维这个术语,也有关于它的书。听起来很棒。我想成为一个系统思考者。但这到底意味着什么?你发现你在工作中是如何应用它的?人们如何在这种思维方式上变得更好?
**Will Larson:**我共事过的许多最不成功但最聪明的人,都是非常有实力的系统思维倡导者。所以我想说的是,每种框架都有很多缺点。没有哪种框架是人们可以持续、普遍地应用并获得好结果的。所以简短地说一下这个,我看到的情况是,人们经常会发现他们的系统和现实发生冲突的某个点,然后他们会说,“现实错了。”那么一个具体的例子是什么呢?
在 Stripe,我们负责事件管理。Stripe 是一家相当重要的公司,我们的 API 是公开可用的。如果 API 宕机了,你就会亏钱,如果你亏了很多钱,你就会离开 Stripe,因为你会对此非常不满。企业需要做的第一件事就是成功地为他们出售的服务收款,对吧?Stripe 是超级重要的。
因此我们对事件做了大量分析,试图了解为什么事情不顺利,我们可以在哪些方面做得更好,但我们过于陷入分析之中,以至于失去了对是否真正在改善事物的关注。我们花了一段时间才弄清楚这一点,因为我们太深陷于系统思维模型中,而且这不是说,“哦,团队错了。”而是,“我错了。”我自己陷入了那个模型中,才意识到,“嘿,我们实际上并没有在优先考虑改进,我们只是在优先考虑测量。”你不能一直测量。俗话说“量两次,切一次”。当然,但你不能量无限次却永远不去切。
而且你确实必须在某个时候去切,才能真正产生影响。但我们就是有点陷入在那里了。我认为很多在系统思维上走得太远的人都会犯同样的错误,他们认为现实错了,而现实永远不会错。现实永远是对的。如果你的模型与现实冲突,那么你的模型永远是错的。但这种冲突,这个差距是非常有趣的,那才是你可以学习的地方。
所以我有了这个模型。它非常干净。它代表了你的招聘管道在不同步骤中的流转。它代表了你的事件以及你如何修复事件。当你熟练掌握它时,它几乎可以非常快地对任何事物进行建模。然后通过理解现实是如何与它冲突的,你开始理解你的心智模型在哪里出了错,然后你可以去自我教育并改进模型,就这样不断进行。
在某个时刻,模型已经足够接近了,你可以停止这么做,然后去实际做工作。所以我告诉人们的最重要的一点是,这是一种很好的学习方式,但你也必须去做事情。你不能只是学习。那不是我们的全部工作。
存量与流量
**Lenny:**为了让它更具体一点,你会如何最好地描述系统思维这个概念?有什么好方法能让人感觉,“好的。我明白你在说什么了?”
**Will Larson:**这可能是比讲述一个关于使用它的漫无边际的轶事更好的起点。
**Lenny:**我们可以倒回去讲。那会很棒。
**Will Larson:**系统思维基本上就是尝试思考存量(stocks)和流量(flows)。所以存量是积累的东西,而流量本质上是从一个存量到另一个东西的运动。那么存量的一个简单例子是什么?存量可以是湖里鱼的数量。存量可以是在湖里钓鱼的人数。因此这两者之间的一个流量可以是,湖里鱼的数量会以某种速率减少,这取决于在那个湖里钓鱼的人数。
所以如果有很多渔民,鱼的存量会下降得更快。如果只有几条鱼,它下降得会较慢。但随后也有这些流量在起决定作用,如果我们有更高效的渔民,流出的鱼的流量可能会下降,但鱼也会繁殖。所以就会有另一个流回来的流量。因此,基于当前鱼的数量和繁殖率,当前渔民的数量和他们的钓鱼速率,你开始看到这些如何随时间演变。诸如此类的很多情况。
所以首先总是推荐德内拉·梅多斯的《系统之美》(Thinking In Systems)。一本真正非凡的书。她的很多工作也参考了蕾切尔·卡逊在《寂静的春天》(Silent Spring)中的工作,该书探讨了少量致癌物或在生态系统或食物链中位置较低的东西,是如何随着被越来越上层的捕食者吃掉而富集的。这是一个经典的系统思维问题,去思考你可能不会认为小鱼体内少量的致癌物实际上会有什么影响。但随着它们沿着食物链向上走,它们开始富集,意想不到的变化就可能发生。
**Lenny:**那么回到你关于招聘管道的例子,让我们回到那个例子,帮助把这是我从未听过的定义连接起来,这非常棒,非常清晰,来对应你实际上在招聘中是如何实施的。
**Will Larson:**首先要做的是建立任何形式的模型。因此你要考虑你的存量(stocks)。所以在招聘管道中,你可能有潜在候选人,这基本上可以是无限的,然后你有几个流入量。所以你可以有主动寻访、外联、推荐,然后你有候选人,那些……有多少人被寻访到。这可能是分配给某个岗位的寻访者数量的函数。所以你会有另一个关于你有多少寻访者的存量,然后这会影响从潜在候选人转化为你实际寻访到的候选人的速率。然后从你在这个漏斗中的候选人开始,你会得到通过初轮招聘人员筛选的人员的转化率,这会进入你流程的第二步。然后从第二步开始,你可能会有招聘经理的筛选,那将是另一个转化率。所以你可以看到,随着时间的推移,那些在领英上漫步、发布深刻思考的无限潜在候选人,是如何转化为实际的人,你的第一轮、第二轮、第三轮候选人的。
但随着你深入其中,你开始真正看到有趣的事情。因此对于很多候选人或很多管道来说,最大的问题是招聘经理不想发出任何录用通知,因为招聘经理无法对任何候选人建立信心。在这个管道中你会看到,大量候选人进入了录用阶段,但几乎没有人从潜在录用转化为实际录用。然后你就可以说,“嘿,问题就在这里。你需要去和招聘人员以及招聘经理合作,让他们对应该雇佣谁建立信念。”这是早期经理的经典问题,对吧?这是第二个问题。经理想发出大量录用通知。他们确实发出了,但实际上没有人接受。因此这让你将注意力集中在第二个问题上。但可能存在第三个情况,实际上你只是没有获得足够的候选人。你实际上在做决策方面做得很棒,在促成候选人入职方面做得很棒。只是没有足够的候选人进来。因此通过观察这些,你可以建立这个模型,然后你可以去你的申请人追踪系统,比如 greenhouse 或其他什么,拉取历史数据,你就可以看到历史数据是如何运作的,与你预期的运作方式相比如何。你可以看到流失情况,这有助于你弄清楚你应该首先去哪里尝试解决问题。我想我们都在这样的公司工作过:你在没有任何数据支持的情况下推出重大改变,因为就像,“哦,感觉我们在评估候选人方面不够严格之类的。”然后你去改变一堆东西。但通常真正的问题可能是招聘经理向那些根本没有通过面试流程的人发出了录用通知。只是经理们因为恐慌而发出了太多录用通知。天哪,现在这种情况少一些了,但在十年……或者不是十年,两年前,招聘经理恐慌着把录用通知发出去,这是真实发生了很多次的事情。而这只是帮助你把一个复杂且有点抽象的问题,变成你可以用系统化方式去处理的东西。
工程策略
**Lenny:**我觉得产品经理可能已经很自然地会用这种方式做事了,因为他们中很多人是用漏斗思维的。听到这个版本,这种只追踪存量(stocks)在不同步骤的流量(flows)中的想法,很有意思。太棒了。我知道你非常热衷并花很多时间思考的另一件事是工程策略。我觉得你有这样一种感觉,就是工程师对最终策略的思考不够。其他每个职能都有策略,而工程师通常没有。谈谈你在那方面发现了什么,以及你对此的建议。
**Will Larson:**首先,我开始质疑在大多数公司中是否任何职能都有策略。我的普遍经验是,很少有公司有书面策略。有时它是一个价值观声明。就像“我们构建最高质量的产品”,然后你会想,“很好。好的。我拿这个干什么?”你会想,“构建一个高质量产品。”你会想,“好的。我不知道那是什么意思。”工程团队经常有这个问题,我觉得人们会在他们的文化调查或季度调查之类的东西中发表评论。就像,“嘿,策略不清晰,或者工程策略在哪里?”当人们抱怨时,我告诉他们的最重要的事情,然后工程师抱怨产品策略。PM没有任何策略,或者业务没有策略。而现实是,产品、工程和业务总是有策略的。只是通常没有写下来。所以我想做的第一件事是,我推动人们不要陷入这样一个事实:外面没有模板,也就是没有人复制并填写的那个产品策略。这并不意味着你没有策略。你确实有策略。它可能有点难以表达,也可能因为没写下来而在产品汇报链的不同层级上应用不一致。但说没有产品策略永远不是真的。总是有产品策略的。有时它很糟糕,但总是有一个。对于工程也是如此。总是有工程策略的。只是有时它很糟糕。
策略的第一条法则是,如果你把它写下来,你就可以改进它。如果没有写下来,就很难说这个PM是不是只是一个不好的PM,或者他们是否在尝试应用他们误解了的策略,又或者他们是否实际上正确应用了产品负责人的策略,只是那个策略不适用于他们正在处理的问题,你要如何去调试这些呢?如果你有一份书面文档,即使它不是一个非常有说服力的策略,至少你可以开始调试。就像,“嘿,产品负责人应该提高这份文档的清晰度。嘿,这个DM实际上并没有正确应用它。嘿,这个策略实际上不适用于这个业务部门,尽管它对其他部门是有意义的。”所以这是我认为的第一件事。但我认为关于策略的第二个大主题是,通常好的策略是如此无聊。很难谈论它。例如,在工程方面,一个常见但非常好却非常无聊的策略是,我们只使用我们今天拥有的工具。所以很多时候你会遇到想引入新编程语言、新数据库、新云提供商的工程师。而对于几乎所有公司来说,一个真正好的策略就像,我们就只使用我们今天已经有的标准套件。
在 Carta,当我加入时,一位工程师 Eric Vogel 写了标准套件,那就是我们关于使用工具的策略。你知道吗?有些人对此感到非常沮丧,我很同情他们。感觉他们失去了控制权,但这些无聊策略的力量在于,它将人们的精力集中在我们作为一家公司所重视的问题上。所以如果你随着时间推移有轻微的不一致,那么达成一致是痛苦的,但是那些告诉你什么才是真正重要的、并将你与公司真正关心的事情保持一致的无聊策略,即使它们有时有点烦人,对你来说也是真正有益的。我可以对这个想法展开很多,但我不会无休止地漫谈下去。
**Lenny:**嗯,可能有帮助的是,你见过的工程策略还有哪些其他例子,只是为了让人们更有感觉,“哦,是啊,也许这应该成为我们策略的一部分。”
策略的定义与核心
**Will Larson:**所以首先,策略的定义是什么?我见过最好的定义来自 Richard Rumelt。他写了 Good Strategy, Bad Strategy。
**Lenny:**他会来上这个播客。
**Will Larson:**太棒了。他还写了 The Crux,我想大概是今年某个时候出版的,我也读了。我觉得这两本书都很棒,他是一位极其出色的思考者,思想非常有深度。我认为撰写关于策略的著作面临的挑战之一是,你会觉得,我只见过两件事就写了这本书。但我认为 Richard Rumelt 令人印象深刻的地方在于,他见过太多不同的场景,因此他能够真正在具体案例和整体数据集之间游刃有余地进行运作,方式非常有趣。另一本具有相似特点的书是 How Big Things Get Done,作者……我忘了作者名字了,但里面关于大型项目如何成功或失败的数据集真的很惊人。
但无论如何,Richard Rumelt 对策略的定义基本上包含三个组成部分。首先是诊断。当前现状是什么?今天真实存在的事物有哪些?然后是指导原则,这基本上是基于诊断,你打算如何应对这些问题?最后是行动。行动是指我们将如何实施这些指导原则。他花了很多笔墨谈论行动,因为他很担忧那种惰性策略的想法,比如你会遇到这种情况,“我们打算弃用我们不用的旧产品功能,但没有人去弃用任何一个。”
所以他真的很担忧这种没有实施、毫无用处、什么都不做的策略。在工程方面,我对此的担忧稍微少一些。我认为工程领域的策略在阐明我们如何做出未来决策方面更有趣。那么这有几个例子呢?在 Uber,我们只使用自己的数据中心。我们不使用云。自从我在那里的时代之后,这种情况已经发生了变化,但在 2014 年那个时代,没有云,我们有一项严格的不使用云的政策。这很烦人,因为我们必须自己采购所有设备,或者自己运行所有东西的副本。
但这也意味着我们真的能在三个月内在中国启动业务,并且由此产生了一些超现实的故事。我们的机架放不进数据中心,所以他们不得不掀掉数据中心的屋顶,用起重机把机架吊进去。
**Lenny:**我的天。
**Will Larson:**只是有太多的故事了,所有这些都是在这三个月内完成的,真的非常不可思议。而且 Uber 在中国待的时间并不长,所以在某种程度上你会觉得,我们做了这一切就为了离开?但他们离开时持有滴滴快的不错的股份,总体的结果并不差。但我认为那个策略,即我们在数据中心运行所有东西,不使用云,意味着我们能够进出不同的地缘政治限制,而依赖云存在的公司根本做不到。它们完全受限于 AWS、Google Cloud 或 Azure 已经部署的地方。所以这是一个很好的例子。
在 Stripe 的另一个好例子是这样一个理念,我们运行一个 Ruby 单体应用,我们就是这么做的,尽管从那以后有所演变。与 2016 年或 2012 年等的 Stripe 相比,2023 年的 Stripe 有了更多的 Java。但那项政策真正让工程师们专注于为我们的用户构建创新功能,而不是构建不同的工具来支持不同的编程语言。因此在两种情况下,无论是 Uber 关于运行自己数据中心的政策,还是 Stripe 关于 Ruby 单体应用的政策,都有很多工程师讨厌这些政策。
但是好策略的目标不是取悦所有人。好策略的目标是决定我们如何将有限的容量或有限的能力投入到我们关心的问题上。我认为两者在实现这一目标方面都非常有效。
**Lenny:**所有这些例子中的一个共同主题本质上是约束,决定我们将限制自己的选项,以便更快地行动,并专注于真正重要的事情。
**Will Larson:**在我看来,解决这些约束是策略真正发挥作用的、最有趣的地方。我认为当我们谈论坏策略时,通常是因为诊断很糟糕,而这通常是因为人们将他们希望成真的事情强加于约束之上,比如“嘿,我们可以同时做所有这些项目”。通常这不是真的,但当他们是 CEO 或者他们非常执着于相信这一点时,很难说服他们。但几乎所有的坏策略基本上都归结于执意无视准确的诊断,这意味着你的指导原则从一开始就缺乏连贯性。
提升策略能力的方法
**Lenny:**太棒了。我很期待 Richard 的那一期,我们将在那里深入探讨策略,但也许作为围绕这个话题的持久探讨,如果听众想要在制定具体策略或一般策略方面变得更好,你有什么建议吗?是读这些书吗?还有其他什么吗?
**Will Larson:**如果人们想在策略方面变得擅长,策略有很多不同的类型,但这里有一些我真正推荐的。首先,我认为 Richard Rumelt 的书,我认为 Good Strategy, Bad Strategy 可能是正确的起点。我认为 The Crux 也相当不错,但我可能会把它作为第二本读。它对如何思考策略做了一个很好的概述。还有 Thinking in Systems,我之前提到过它与系统思维(systems thinking)相关,策略的一个很大部分是能够对现实进行建模,以便我们能够改进你的诊断。
所以我认为那本书也非常好。如果你深入到工程方面,这里有很多有趣的书。有 Evan Hewitt 写的 Technology Strategy Patterns。有 Anderson、McCann 和 O’Reilly 写的 The Value Flywheel effect。还有 Kim、Behr 和 Spafford 写的 The Phoenix Project,这是 Goldratt 的 The Goal 的现代重写版。但我认为仍然缺少一本经典的书籍。所以我在我即将出版的书里尝试了对策略的探讨,也就是明年初出版的 The Engineering Executive’s Primer。
在我之前的书 Staff Engineer 里也进行了尝试,但我仍然认为这里缺少一本书。所以我梦想在我的下一个项目中写一本关于工程策略的书,尽管我们还得看这是否能真正实现。
关于写作的坚持
**Lenny:**好吧,让我们实际上顺着写作这个话题聊下去,我绝对希望能聊聊这个。你写了很多东西。你写了大概两本、三本、四本左右。你正在写一本新书。你出版了多少本书?两本书,还有第三本即将出版。
**Will Larson:**所以我有两本书。第一本是与 Stripe Press 合作的,第二本是自出版的,第三本是与 Riley 合作的,实际上两个月后就会出版。
**Lenny:**好的。然后在很多很多年里,你还写了很多很多的博客文章。我问了几个人该问你什么,这个问题被提了很多次,Gergely Orosz 和来自 ByteByteGo 的 Alex Xu 都问了这个问题,“你是怎么抽出时间写这么多的?”然后我自己也想问这个问题,你可以先回答这个或者后回答这个,就是写作对你的职业生涯有什么影响?你为什么一直写下去?
**Will Larson:**我深信,如果你写你想写的东西,你可以写得更多。所以这也是我不为经济利益而写作的原因之一,我也很少按计划表写作,所以我为杂志等写过几篇文章,但我发现这实际上真的很消耗精力,因为你有一个主题,你必须对这个主题达成一致。如果一个主题开始偏离你想写的内容,很多时候你无法修正它,而且你还要面对最后期限。你会觉得,“啊,我搞砸了。我需要把这个交出去。它明天必须完成。”
**Will Larson:**我只觉得这真的很消耗精力。相反,当我自己掌握时间表,当我想写“嘿,我正在写点东西”的时候。所以几年前我开始写一本基础设施工程的书,但就是找不到感觉。我就是没法把它整合起来,所以我就停了。我不再写它了,也许我会在某个时候重新拾起它,但大概率不会。对我来说,写你想写的东西最大的优势在于,你可以在有动力的地方写,而不必在没有动力的地方写,后者会把你拉得非常、非常负面。这也和我写书的方式有关,基本上我在和出版商合作之前就会把整本书写完。而且如果你——我认为——足够勤奋,并且善于预判他们会关注什么,你基本上可以复用你试图写的那些内容。在我写的这类书里,这也更容易做到。我觉得如果是一本非常技术性的 MySQL 入门之类的书,就很难这么做,你不能只是重新排列这些章节然后假装它能行。那些章节的构建方式和我写的这类商业书是不同的。写那些让你有动力的事情,直接放弃那些让你没有动力的事情,这就是我写了这么多、也是我写了大约16年的方式。而我能一直坚持下来的方法,就是写让我有动力、写我现在正在思考的东西。我不写我没有在思考的东西,我也不为任何特定的受众而写,我只写我觉得有趣的东西。这意味着有些人不会喜欢它,但这很棒,这完全没关系。这本来就不是给他们的,而是给那些愿意跟着这趟旅程走的人的,这也是我专注的地方。
16年来的写作积累
**Lenny:**好的。这里还有更多我想深入挖掘的内容。你猜你这16年来大概写了多少篇文章?
**Will Larson:**我猜大概一千篇左右。这大概就是我的估计。我想有几年我写了几百篇文章,所以如果你像那样写上三年,从那里达到一千篇并不难。
**Lenny:**这太不可思议了,特别是因为在这些年里——或者说大部分时间里——你都在做高强度的全职工作。在非常高压力、快速增长的 hypergrowth 公司里,你竟然还能找到时间来写作。所以首先,我想对你的建议——关于关注什么能给你动力,以及去做你真正好奇的事情——深入探讨并强烈赞同。这正是我给人们的建议,很多人开始了全职写手、创作者的生活,然后他们会想,“人们想要什么?人们想让我写什么?什么流行?什么能引发病毒式传播?”这样搞几次很容易,但最终你会给自己创造出一份你并不想要的工作。如果你对 AI 没有那么兴奋,或者对现在不管什么热门的东西不兴奋,你不会想把所有时间都花在写 AI 上。我发现重要的是,你写的 80%、90% 的内容必须是你感到兴奋的东西。然后也许可以有一点,“这是我知道人们真正想要的。这是我知道会表现很好的内容。”因为否则你只会精疲力尽,你给自己创造了一份你不想做的工作。你为什么要那样做呢?
写作的最大风险是放弃
**Will Larson:**是的。我百分之百同意。我认为另一件事是,大家都会趋同于他们认为人们想要的东西。所以两年前是加密货币,现在就像是 AI,或者是反 AI,AI 将要毁灭世界。很难说出非常新颖的东西,因为,第一,每个人都在试图谈论它。第二,这几乎肯定不是你真正了解的领域,如果你只是坚持在自己的赛道上,我认为写作者最大的风险是放弃。有点像 40 年职业生涯的理念,任何形式的内容创作,最大的风险都是因为精疲力尽而很快放弃。最大的风险不是你最初增长得太慢,总会有一种感觉,就是你错过了浪潮。现在加入 Substack 太晚了,顶级写手已经在那里了,你永远成不了顶级写手。现在开始播客太晚了,播客太多了,你永远做不起来。加入 Medium 太晚了,你永远做不起来,Medium 写手太多了。但这根本不是真的。如果你只是坚持写好东西,随着时间推移你会建立起受众,而且你可以把这些受众从一个平台带到另一个平台。真正重要的是找到一件你在接下来的十年里能够坚持做下去的事情。这比做一年要难得多。
内容创作是一场无限游戏
**Lenny:**我们在这方面的建议完全一样。这正是我告诉每个人的话。当我加入 Substack 时,我以为太晚了,我当时想,“天哪,结束了。”当我开始做这个播客时就像,“天哪,有十亿个播客。这怎么能行得通呢?”所以我非常同意,我也非常同意这样一个事实,即这整个事情是一场长线游戏。有很多人,我总是说,开始写时事通讯很容易,坚持下去很难。没有人能真正坚持下去,因为人们总是来来去去。真正区分成功与失败的,就是那些能够坚持下去的人。这没有终局,这是一场无限游戏,关键在于能够在长期内维持下去。
**Will Larson:**你并不是在和其他内容创作者竞争。如果你把它看作一场无限游戏,你们都是在一起工作。你们都可以互相帮助成长。做事情的产品写手或思想者并没有最大数量限制。你不会因为 [听不清] 的存在就不那么成功之类的。那里没有竞争,这就像一种虚假的、虚假的二分法。
**Lenny:**是的。我完全同意。除非数量太多了,然后突然发生的事情是门槛变高了,这是好事,因为人们能得到更好的东西,这很好。反正这也是正在发生的事情,只是门槛在不断提高,因为外面的内容越来越多了。对我来说,你必须做对的最核心的事情就是门槛。你必须达到很高的门槛,别人才会关心你写的任何东西。而且正如你所说的,为了做好这一点,你实际上必须对写它感到兴奋,有背景知识,并且有东西可以贡献。我在这里只是随口说说,但我对这个问题的思考是,你需要为对话增加一些新的东西,别人才会关注,因为有太多空洞、肤浅的东西了。而要让任何人关心,你需要说出一些以前没人听过的新东西,或者分享他们在其他地方没见过的新信息。
**Will Larson:**我完全同意。我本来可以就这个话题一直说下去的。我不想在这个问题上跑题,但我完全同意。
**Lenny:**我们先收一收。那么来聊点非常战术层面的问题,我想这也是很多人一直好奇的,你是怎么挤出时间的?你的工作流是怎样的?你如何为写作腾出时间,从而在明知自己有一份高强度全职工作的情况下还能坚持下去?
**Will Larson:**在有孩子之前我的做法不太一样,所以我有一个三岁半的孩子,一旦你有了孩子,你生活的节奏真的会发生很大变化。但我发现最重要的一点是,找到那些与你正在做的工作直接相关的写作主题。这样一来,我就可以做一些既能帮助我的工作又能帮助我写作的事情,因为我觉得要想挤出时间去写那些与工作毫无关系的东西是极其困难的。而且这会分散你工作的精力,因为……特别是如果你处于高级职位,这些工作可能会非常耗费精力,但这种耗费不是因为你每五六分钟就要回复一条 Slack 上的紧急消息。它们耗费精力是因为你需要把一些非常艰难的决定做得非常好。我认为撰写相关主题是完善你的思考和提高你表现的一个好方法。这并不冲突,也不是你只能做其中之一。好像你要么写作,要么把工作做好,我认为你可以找到一种方法让它们保持一致。所以很多做播客的人会采访那些与他们工作中思考的问题相关的人,这对他们来说是一个很好的学习方式,可以建立他们的人脉网络,完善他们的思考,并在该领域的专家那里检验他们的想法。这与工作并不冲突,而是相辅相成的。这是其中一点。但是的,我也尝试过很多不同的时间安排。在有孩子之前,星期六通常是写作日,所以整个上午和下午早些时候我都会用来写作。我现在做不到了,所以现在我主要在晚上写作,从精力管理的角度来看这有点棘手。但我最想说的是,如果你真的对某件事感到兴奋,你就会为它找到时间和精力。如果你对它不感兴趣,而且时间到了晚上九点,你只会直接睡着。所以我真的认为,这时候你必须稍微刻意地去安排时间,但我们一开始谈到的关于精力管理的问题,在这里就真正结合起来了。当你的日程变得紧张时,如果你没有精力,你就是完不成。你又何必呢?这根本说不通。
给不同写作目标的建议与应对反馈
**Lenny:**为了结束这个话题,对于那些想要写更多东西、知道这会很有价值但就是还没开始的人,你会给他们留下什么建议来让他们搭上这趟车?
**Will Larson:**这取决于人们为什么想写作。我告诉别人,如果你只是想写点东西来帮助推进你的职业发展,你真的应该专注于写出两三篇真正好的东西,并花大量时间起草、修改、获取反馈。你只需专注于打造一个出色的作品,或者两三个出色的作品。你不需要建立一个每周都发布的长期博客。如果你的目标只是创造一些作品来展示你是一个有深度思考的人,帮助你在行业中定位,那真的没必要那么做。如果你只是想在行业中稍微提升一下自己,不要去搞订阅通讯。只要写出两三篇真正好的东西就行了。这是我想说的第一点。但如果你的目标是随着时间的推移持续大量地写作,我最大的建议就是直接发布。外面有很多人手里有成百上千篇草稿,但他们什么也没发出来。而我的做法是,我几乎会发布我写的所有东西。如果有什么东西我不打算发布,我就根本不会开始写,因为我在脑子里会快速做一个判断:这是我能写出来并且发布的东西吗?如果我的答案是“不”,我就干脆不开始。随着我写得越来越多,我判断的准确率也提高了,但我基本上发布了我写的所有东西。这就是为什么其中一些写得并不是很好。但这没关系。再说一遍,我想写作。我想把这些想法表达出来。我想展示我专注的东西,以及我作为一个思考者在尝试学习如何在这些不同公司的不同角色中运作时的演变。我写作不是为了创造一个经过打磨的完美事物,我也不是为了最大化读者的阅读体验而写作。有些人不喜欢这样,我觉得这完全可以理解,但我认为我能带给你的是作为一个正在积极学习和思考的从业者的经验。我认为这对行业里的其他从业者来说真的很有价值。至于给你完美的文章,我尽量那样做,努力接近那个标准。我不知道我是否曾达到过完美的写作,但我的书就是奔着那个去的。这些书是收集了我几年来的想法,稍微清理了一下,打包而成。它们的质量比我平时的写作要高得多。但是的,我就是会大量发布。不用担心质量。有时人们会给你发一些愚蠢的反馈,我现在根本不回应那些东西了。你永远不知道人们为什么会发给你那样的东西。我认为试图去 debug 你不认识的人是在浪费时间。这就像,“谢谢。继续看下一个。甚至不要花时间去担心它。”
**Lenny:**我很喜欢去 debug 人这个词。我觉得人们大大高估了别人有多在乎你发布的东西。大多数人会看它三秒钟然后说,“呃。”基本上最坏的情况也就是,“我不在乎这个。”而不是说,“哦,Will 真是个傻瓜。”说得多蠢啊。对吧?没人有时间搞那个。
**Will Larson:**如果他们真这么干了,那是他们的问题,对吧?互联网是个很大的地方,有很多人,当有些人遇到你做的东西时,他们可能正经历非常糟糕的一天,然后他们就会把那种愤怒或沮丧发泄在你身上,但这与你无关。这就像是在他们接触到它的时候,你刚好在那里而已。你不需要把那个揽在自己身上。那不是你的处境。没关系的。
**Lenny:**而且,当你刚刚开始的时候,那将是写作压力最小的时候,因为没人知道也没人看到,所以那个时候就像是“承受所有疯狂……尽管去做吧”。只有随着时间推移你建立了受众,压力才会变得越来越大。
**Will Larson:**是的,绝对的。完全正确。
PM 与工程师/工程经理的协作关系
**Lenny:**好的,换个话题。有很多 PM 在听这个节目。PM 经常想知道的一个问题是,如何与他们手下的工程师、工程经理建立更好的关系。你能给 PM 什么建议,来与他们手下的工程师和工程经理建立更高效、更愉快的关系吗?
**Will Larson:**所以核心问题,以及我合作过的大多数 EM 和 PM 同事……有两个核心问题。一个是,有时激励是不一致的,这很难处理,但如果你们能对彼此坦诚并理解这些激励因素,有时你们可以找到一个折中方案,但有时 EM 和 PM 会出现不一致,仅仅是因为他们的激励因素相差太远,根本无法触及问题的底部。所以这可能跟时间线有关,或者跟对销售说“是”有关。或者工程师会说,“嘿,我们绝对不能答应那个。”然后 PM 会说,“实际上,我们打算答应,因为这对我升职真的很重要,”之类的。
事情有这么简单吗?其实从来都没这么简单。人们总是编造简单化的叙事,给共事的同事扣上反派的帽子。职场中是没有反派的,他们只是带着复杂的激励因素在做复杂的事情的人。但有时我会和一些工程经理聊天,他们会想:“哦,产品经理只是想升职才说好的,因为销售人员会参与评估他们的晋升之类的。”现实从来没那么简单。现实是企业需要卖东西才能维持运转,你不能一味拒绝还指望企业能取得成功,那样也是行不通的。所以一是理解激励因素。但另一部分,我认为这是更常见的情况,或者是工程经理和产品经理根本不了解对方的需求,然后在理解之前就开始争论。所以我对工程经理和产品经理最大的建议是,在你们试图解决冲突之前,比如急于推进发布某个功能,或者急于改变方案时,先确保你真正理解了对方关心什么。
有一种观点认为你必须做出权衡,而且在这个领域有大量艰难的权衡要做,但我的经验是,如果你真正深入理解了每个人想要什么,通常能找到一个折中方案,让每个人都得到他们想要的。这不会花更多时间,你只需要愿意更深入地挖掘,理解各方的真实需求,顺便说一句,这往往不是他们嘴上说的那些,这也是造成困惑的部分原因。
**Lenny:**关于激励因素的部分,你有没有见过什么有效的方法来解决这个问题?因为如果产品经理的绩效评估是基于影响力,而工程师的绩效评估是基于有趣的项目或系统正常运行时间,你是去努力改变那些职级定义吗?到底什么能帮到这种情况?
**Will Larson:**所以我一直在努力推行一个理念,即工程经理和产品经理组合是平级关系,他们通常获得相同的绩效评级。这里也有例外,可能是工程经理明显表现不佳,如果工程经理连班都上不了,那就不是产品经理的错。团队不尊重他们,有时确实存在明显的不合格情况。但一般来说,困难的情况都不是那种某个人明显很糟的情况,那些很容易诊断,是容易处理的。但在两个人看起来都相当不错,只是整体执行不顺利的情况下,我认为双方获得相同绩效评级这个理念,虽然会带来一些痛苦,但能带来正确的视角。
另外,我认为 Carta 随着时间的推移也进行了一些这方面的尝试。我们的 CEO Henry 有一篇关于“三重奏”的博客文章讲了这个做法,但这不仅适用于工程经理和产品经理,也适用于业务领导层,大家根据评估和解决整套约束条件(而不仅仅是你们职能范围内的约束条件)的能力,获得相同的评分。
**Lenny:**哇,这太有意思了。所以你的建议,或者说你们正在做的事情,听起来就是工程经理和产品经理获得相同的绩效评估评级?因此他们会在同一个会议上被讨论。
**Will Larson:**我们的首席产品官 Vrushali 和我会花大量时间一起进行校准,并确保……再说一次,也有例外情况,因为某人出现了明显的问题。但平均而言,我们就是这样做的。而且我认为人们知道我们在这样做,因为我们告诉过他们。我认为这相当有效。
**Lenny:**这太有趣了。我从没听说过这种方法。这绝对解决了工程经理和产品经理之间或者……
**Will Larson:**是的,现在激励是共享的了,虽然这并不完美。平衡这些激励仍然很困难,他们仍然可能做出错误的权衡,但至少他们明白激励是共享的,我认为这是一个相当强大的理念。
**Lenny:**这真的很有趣。我想有些公司可能甚至想把设计经理也纳入其中,再往前迈一步。
**Will Larson:**不同公司中不同职能的角色和首要地位差异很大,很难有一刀切的做法。你也可以想象在某些情况下你是否想把 Staff Engineer 也加进去。所以我认为这非常取决于具体公司。但是的,我认为设计绝对可以参与进来,特别是对于像 Airbnb 这样设计主导的公司。
**Lenny:**哇,太有意思了。也许作为最后的总结,如果一个产品经理和他们的工程经理遇到了挑战,你认为产品经理可能没有意识到他们的工程经理觉得什么重要,或者可能正为什么感到压力,以至于他们会感叹:“哦,哇,我从没想过那个。”
**Will Larson:**我认为我从历史上看到的最大挑战之一,特别是在过去十年里,就是这种观念:工程经理的工作是给团队分配有趣的工作。我认为这会造成……你经常在增长团队中看到这种情况,增长团队会说:“嘿,我们只需要做大量的实验。”而工程师会说:“我想构建全新的东西。”夹在中间的工程经理试图弄清楚:“需要发布 50 个相当无聊的实验,而他们想做全新的东西。我不知道该怎么解决这个问题。”所以这是一个棘手的时刻。优秀的工程经理能找到平衡的方法,但这是持续摩擦的最大来源,即工程经理被他们的团队告知需要做某事,而产品经理对此却一无所知。这使得工程经理看起来像是完全不可靠的合作伙伴,因为他们正试图解决这些一点点的隐形约束。这就是为什么我认为需要进一步推进去理解:“嘿,你一直在优先考虑把这个项目用新的编程语言重写。”对我来说,这看起来像是在做一件完全愚蠢的事情。到底是怎么回事?然后一旦你理解了,你可能不同意他们的做法,但至少你可以就如何应对这些约束进行一次诚实的对话,而不是像这样:“天哪,你都不敢相信我的工程经理搭档今天做了什么。这个蠢货做了这这那那。”以一种受害者与反派的心态来看待你的平级同事。
衡量工程速度与生产力
**Lenny:**我想花点时间讨论的一个相关话题是衡量工程速度和生产力。我认为这可能是工程领导者被问及的最常见、也可能是最令人烦恼的问题之一,即我如何知道我的工程师是否在以他们所能达到的最快速度前进?我们如何帮助他们走得更快?关于工程团队如何良好地衡量生产力,你会给工程领导者什么建议?
**Will Larson:**在当前整个行业都在大幅缩减团队规模的时刻,这个问题被提及得更多了,当这些风险投资支持的公司董事会上的风险投资人们都在施压要求提高工程效率时。工程师们正试图弄清楚,我们该如何展现这一点?我们如何证明相对于我们作为组织所拥有的员工人数和资金,我们的生产力是合适的?天哪,这很难。所以人们专注于试图回答这些问题的第一种方法,就是根据你拥有的资金量进行基准比较。这是一个很直接的机械性工作,你从你的风险投资基金或其他地方获取一个数据集,然后你弄清楚,“好的。我们在研发上应该花多少钱?在工程上应该花多少钱?在研发的基础设施工程上应该花多少钱?”你可以把这一切都进行基准比较,并弄清楚那里正确的数字是什么。
**Will Larson:**问题在于,这是一种非常机械且缺乏洞察力的驱动方式。它能给你一个站得住脚的答案。就像那句老话,买IBM的产品没人会被解雇,但这在我的职业生涯中绝对从未成真过。但是这种认为只要你有了正确的基准,董事会就不会因你在工程上花太多钱而评判你的想法,实际上并不能帮你走向正确的方向。它只是帮你让董事会少生你的气,这很有用,因为当董事会对着你生气时,很难做出出色的工作。
但从它实际上并不能帮你有效管理组织的意义上来说,它是没有用的。因此,就有一个困难得多的中介问题,即你实际上如何知道你的研发团队或工程团队是否有效?我发现了几件事。首先,如果你是一个好的领导者,你去和工程师交谈,他们会告诉你……工程师知道他们的团队是否有效。如果无效,他们也会告诉你为什么无效。他们的诊断可能是错的,但那里会有你可以开始拾取的线索,你可以顺藤摸瓜弄清楚哪里出了问题。
通常你会凭借更多经验来分析这些抱怨,弄清楚导致这些抱怨的促成原因是什么。但是是的,如果你只是持续地去和团队交谈,你就会知道他们是否有效,然后你可以去努力解决那些具体问题。但同样,你不能告诉你的董事会,“哦,没事。我和团队谈过了,他们很好。”“我的直觉非常准”,因为他们怎么知道你的直觉是好是坏呢?
他们在管理庞大的投资组合,他们与之交谈的一些领导者很优秀,而其中一些人的直觉糟透了。他们实际上如何评估?我认为这很棘手。我尝试做的基本上有两件事。第一,将工程评估与业务和产品目标对齐。所以我希望我们能对产品目标负全责。“好吧,我们做得很好,产品就像在那里搞砸了一样。”显然,许多公司在这样做中找到了安慰,但我们真正的目的是支持产品,支持我们的客户去做一些有趣的事情。我们不是为了构建新颖的系统而在这里,除非它支持客户和产品。
所以首先要努力在那方面重度对齐。第二,我认为仅仅展示我们在过去六个月里所做的有价值的事情的路线图就非常有力。我认为有时人们会想,“我没有什么可以放在那里的。”而你会说,“是的,那是个真正的问题。”或者如果你有大量的东西可以放在那里,那就太好了。我真的发现,如果你只是致力于展示你正在做的、有影响力的、有意义的、实质性的工作的数量,并且你能解释这种影响,人们就会退后一步给你空间。如果你无法填充那个列表,人们就会有担忧,理应如此,他们应该对此感到担忧。
指标与工具的使用
**Lenny:**有没有你发现也很有用的指标或工具之类的东西?因为这些都非常棒,但我可以想象每个人总是会说,“给我们这个我们正在追踪的数字,给我们这个仪表盘,看看工程师在做什么。”
**Will Larson:**在过去十年的软件工程领导和基础设施领域,最具影响力的书之一是 Nicole Forsgren、Gene Kim 合著的《Accelerate》,我相信那本书还有第三位作者,但我现在想不起来了。真是一本非凡的书,它提出了这四个指标。它提出了前置时间。它提出了事件修复时间。它提出了失败率。以及第四个某种指标。市面上至少有 50 家不同的初创公司在向你出售对这些数据进行仪表盘化的工具,他们希望你直接用它们来评估你的团队。
挑战在于,这些都是非常好的诊断指标。所以嘿,我们的部署很慢。为什么会这样?我们如何加快它们?但是你的部署缓慢并不能使你成为一家好公司或坏公司,它只是告诉你你应该把重点放在改进哪里。它实际上并没有改变你是什么样的。同样,如果你的前置时间很快或很慢,它告诉了你应该在哪里投资,或者它实际上并没有告诉你是否应该解雇你的工程师之类的事情。那要具体详细得多。
所以人们确实喜欢看到这些指标,就像他们看到正常运行时间指标一样。许多工程师向他们的董事会汇报冲刺点数之类的东西,这完全是、完全是在汇报虚假的东西。但人们从中得到了一些安慰。所以我在这里最重要的一点是,当人们进行测量时,这不是一个仅限于工程领域的问题,但当人们测量时,他们会采取专家的视角,他们可以告诉你为什么不能测量一切。他们可以告诉你为什么每个测量都是错误或不准确的,然后他们把一切都排除掉,所以他们什么也不测量,然后他们去找一个不是专家的人,然后实际上没有准确的测量可以给出。
对于那个不是专家的人来说,这就好像你不知道自己在做什么。所以你只需要习惯于测量一些不完美、但你实际上可以测量并报告的东西,然后当人们问问题时,这个不完美的测量就是一个机会,去教育人们为什么这个测量是不完美的。它遗漏了什么,或者对话中存在哪些谎言。
指标是为了教育消费这些指标的人,让他们了解底下丰富数据的现实。它们不在于这个显示一切的完美数据集,而是从平庸的东西开始。Dora 指标对诊断非常有帮助,但如果必须的话,它们也可以作为一个足够好的起点,开始向你的董事会、你的 CEO 或其他高管汇报,然后你会说,“哦,它们有所有这些问题。”
是的。它们确实有所有这些问题,但那就是你开始的地方,你从那里开始向上教育人们,帮助他们理解细微差别,这就是他们变得更成熟、更理解工程的方式,而不是通过拒绝给他们任何他们可能测量的东西。
公司价值观的制定
**Lenny:**太棒了。我很高兴那是你的答案,因为我们曾邀请 Nicole 上播客,她详细讲解了 Dora 以及她推荐的所有框架。她甚至实际上分享了一些她指引人们去的基准,这些基准让你有一种感觉,就像,“你大致上是否处于一个好的位置?”所以我们会指引人们去那一集深入了解。太棒了。我很高兴你是它的粉丝。好的。在我们进入非常激动人心的闪电轮之前,还有几个问题。一个是关于价值观,公司价值观,组织价值观。关于如何思考提出价值观,你有什么非常好的建议给人们吗?你分享什么?你向那些试图弄清楚应该为其组织和公司定义什么价值观的人推荐什么?
**Will Larson:**我的意思是,价值观真的很有趣,对吧?不同的公司以不同的方式谈论价值观。我曾在一家公司工作,那里的高管去参观了 Facebook 园区。他们看到墙上写着的价值观,然后他们把 Facebook 的价值观拿过来写在了我们的墙上,但这并没有起多大作用。它可能反而削弱了人们对高管团队批判性思维的信心,他们只是把写在 Facebook 墙上的东西照搬过来。
价值观的有效性检验
**Will Larson:**但我认为那些价值观确实对 Facebook 很有效,而且对 Facebook 来说很有意义。所以首先你不能做的就是直接照搬价值观。价值观货拜。用户第一,很棒的 Amazon 价值观。很多公司并不是用户第一,这没关系,但不可接受的是你写下“嘿,我们是用户第一”,然后展示你实际做出的决策时,你显然并不是用户第一。因此我思考的一点就是诚实。好的价值观必须是诚实的,任何价值观都可以是诚实的,或者说没有普遍诚实的价值观。你可以说类似“我们很节俭”这样的话。或者你可以说类似“我们会花尽可能多的钱来获得最佳价值”这样的话。这完全不同,而且好公司这两种做法都有。所以我经常思考的第一条规则就是诚实。你实际上做到了你所声称的价值观。第二条是适用性。你必须拥有真正能弄清楚如何应用到工作中的价值观。
Stripe 的其中一个价值观——我相信现在已不再是了——是全局优化。全局优化是一个非常有趣的问题,因为有时你会为了某些有趣的价值观想要做些事。有时你想做点什么,你会想:“嘿,我想引入一种对我的团队更好的新编程语言。”但对整个组织来说,这实际上对组织更糟,所以我不会这么做。Uber 并没有将此作为明文规定的价值观,但 Uber 隐含的价值观是做对你团队有利的事,忽略其他人,因为其他人会拖慢我们的速度。所以这两家不同的公司有着截然相反的价值观,但它们都非常适用。这就好比我们该如何做决策?我应该为我的团队优化,还是为组织优化?所以这些价值观适用于真实的问题,而且它们很诚实,Uber 就像是说,“别担心其他人。”让它对你的团队起作用。这就是他们行动如此迅速的原因,因为他们就是不去担心。
**Lenny:**他们的价值观不是踩脚趾,鼓励踩脚趾之类的吗?
**Will Larson:**让构建者构建,踩脚趾。有很多价值观可以用不同方式解读,有时它们会像所有价值观一样被以各种方式武器化。但它们都在不同方面很有趣。所以第一是诚实,第二是适用。第三,我认为好的价值观的最后一个要素是可逆性的概念。有些价值观实际上是不可用的。这里有个好例子:我们构建优秀的软件。好吧。但你什么时候会不去构建优秀的软件呢?这说不通,或者说我们解决重要的客户问题。很好。有哪家公司会认为自己没有解决重要的客户问题呢?所以有些价值观是你根本无法应用的。我把这些看作身份价值观。这些真的只是你在描述你想成为什么样的人,或者说我们关心我们的客户。很好。但有谁会说他们不关心这个呢?有些价值观我认为就是身份价值观,拥有身份价值观并没有错,只是它们不是很有用。
你实际上无法用它们做任何事。所以我总是督促人们不要在这些上面花太多时间,因为当你作为一个高管团队在辩论这些身份价值观时,感觉很好。比如我们对他人友善,或者当然,听起来不错。我们是一个大家庭。当然,听起来不错。我想这个有一点点可逆性。比如 Netflix 就说,“我们是一个像运动队一样的团队。我们不是一个家庭。”所以有一点可逆性,但并不完美。是的,我发现这三个标准对任何价值观都非常有用。它诚实吗?它适用吗?你能反转它吗?如果不能,它实际上可能并没有帮助团队做决策。
**Lenny:**这些太棒了。这让我非常想起……在 Airbnb 制定价值观的时期我在那里。我可能会补充的一点,也许可以归入这些类别中的是,必须明确谁不符合?必须有一个不太契合的群体,因为如果每个人都契合,你并没有在做任何有用的事。有什么意义呢?这听起来有些奇怪,为什么不是每个人都适合我们这个伟大的公司群体?但很清楚谁不合适,基本上就是谁不属于这里。这有点像邪教,就像“谁不在我们的邪教里?谁不属于这里?”
**Will Larson:**但我同意。如果它不适用于任何人,那为什么要费心说出来?它没有任何意义。你可以说它实际上是一个招聘过滤器,有些你明确选择不雇佣的人就是因为这不适用于他们。那么我认为它很有用,因为它确实帮你弄清了该引入谁。但如果它不适用于你雇佣的任何人或你公司里的任何人,那它就不值得拥有,因为你已经有过多的价值观了。你已经试图摆脱一些价值观了,因为你有 17 个,而你需要精简到 4 个以便人们能记住它们。所以如果它不适用于任何人,到底为什么要保留它呢?
**Lenny:**是的。正直是一个常见的例子。正直。每个人都有这个。没人会不想要正直。有什么独特性呢?
**Will Larson:**我们是一家不正直的公司。我们是认为正直很坏的公司。这不是真实存在的事。
**Lenny:**关于诚实我要补充的另一件事是。在 Airbnb,我们最初有六个价值观。其中一个是化繁为简,一两年后大家只是意识到我们其实并不擅长这个。我们想要化繁为简,但我们不精通这项技能,而且价值观应该描述你现在的样子,而不是你想要成为和渴望成为的样子。所以他们砍掉了包括那个在内的两个价值观,他们就像是,“我们就只保留这四个吧,因为这实际上就是我们的样子。让我们对自己诚实一点。”
失败角落:Digg 的重写灾难
**Lenny:**好的,最后一个问题。我想去一下失败角落,这是我最近在播客中增加的一个环节,让人们分享失败的故事。你有一篇很棒的文章讲述了你在 Digg 的经历以及你们经历的重写。我想那是 Digg 的第四版。你能讲讲那个故事以及发生了什么吗?最后到底有多混乱?
**Will Larson:**是的,Digg V4 是……我的意思是,它仍然是我有很多美好回忆的事情。我保留了一张照片,照片里很多工程师围着这个巨大办公室中央的一张桌子,他们在供应寿司。那天我们请了服务员和餐饮服务商过来。他们在端寿司。盘子上有香槟杯。有一个完整的吧台,我们所有人都围着这张桌子,因为网站挂了。在那之前,基本上 Kevin Rose 或董事会或是他们的某种组合意识到,Digg 正在输给社交网络,如果我们找不到方法为其增加社交组件,这种聚合新闻的想法将会被 Twitter、Facebook 等击败。甚至长期来看被 Reddit 击败也是一种担忧。尽管在当时这还远未明朗。所以我们需要转向支持社交功能,而在之前的版本上我们根本无法让它运转起来。所以做出的决定是,我想是在我加入的两年半前,而在我加入大约六个月后发生转变,他们需要进行一次彻底的重写才能达到目标。这是一个从未对任何人奏效过的决定。所以我认为作为一个有更多经验的人,我本可以预见到这不会成功。但我当时处于职业生涯早期。我在 Yahoo 的 PM 同事 Das Kofinovsky。他去了 Yahoo 并跟我说,“来 Digg 吧。”
最坏的情况你一年也能挣个几十万。最坏的情况。可能结果还会非常好。总之,事情并没有这样发展。这个最坏的情况还是有点太乐观了。所以我去了,在我入职前两天 CEO 被解雇了。当时的 CEO 离开了,然后 Kevin Rose 回来掌舵了大概六个月左右。我们就只是在经历死亡行军,拼命想把这东西搞出来。
所以我们非常拼命。这主要是在云计算普及之前。所以我们基本上清空了所有现有的服务器,将它们重新镜像为新的软件。我们试图把网站拉起来,但它一直崩溃。所以基本上花了一个月的时间才让它完全恢复正常。所以那天大家围着桌子坐着,喝着香槟吃着寿司,那其实只是第一天。到了第 30 天,大多数人甚至都不再尝试把网站恢复上线了。
大概还有我们五个人在继续尝试。我们做到了。我觉得那对我来说是一个非常有力量的时刻。我想在最初两天,我和另一个工程师 Rich Schumacher 不得不从头开始写一个缓存系统,这让我们恢复了一半的功能。顺便提一句,这真的是一种极其糟糕的软件构建方式。我不向任何人推荐这种做法。这是一系列拼凑在一起用于上线的反模式。但我们让它部分上线了,尽管我们每 12 个月必须重启它一次。每 12 小时,即使有缓存机制,每台服务器也必须重启。然后在大概三周后,我终于找出了导致我们每 12 小时宕机的核心 bug。这是一个极其简单的问题,只是很难调试,基本上与 Python 初始化用作默认参数的变量的方式有关。这事情超级愚蠢,我们只是找了个人来写 API 代码,而他之前没写过 Python,所以他没有意识到这是个陷阱。
然后在代码审查时没有其他人发现它,只是花了很长时间来调试。它是如此的不明显。它没有弄坏任何东西,只是给服务器增加了大量额外的负载。我们终于弄清楚了,这真是一次非常了不起的挺过难关的经历。但你猜怎么着?公司最终还是归零了。所以我们在发布时经历了这些。我认为我们做出了英雄般的、极其艰辛的努力才让它运转起来。几周后,来了一位新 CEO,进行了一轮裁员。这应该是在 2012 年。在我入职九个月后,团队从大约一百人缩减到了三十人,从商业角度来看,从那以后情况就每况愈下了。但是我们上线了很多功能,真的学到了极其多的东西。这某种程度上塑造了我对于职业生涯早期如何获取学习经验,以及加入一家可能正处于困境的公司的看法。
在职业生涯两年半的时候,我成为了一名经理。基本上是在管理那里的整个工程团队,因为所有有点头脑的人都辞职或被裁了,而就只有完全是个白痴的我在试图充当工程组织的经理,我不够资格,也没人会给我这份工作,但当时我是唯一一个蠢到愿意接手的人。我学到了很多东西,这真的是我整个职业生涯的内核所在,那就是那个机会,尽管在当时情况相当黯淡。
灾难中的成长
**Lenny:**这是个令人惊叹的故事。我觉得很多这样的经历,在发生的那一刻,你只会觉得,“这到底是怎么回事?这也太糟太难了”,但最终它们会变得最有趣,回想起来也会成为最大的教学经验。就是那些你会和共事的人建立羁绊的经历,比如在 Apple。我总是想到史蒂夫·乔布斯的开玩笑,人们当时觉得疯了,但后来回头看,那是他们职业生涯中最好的时刻。
**Will Larson:**你永远不会自愿去承担许多这样极具挑战性的事情,但有时候当它们出现时,你是和一群你非常尊敬、你热爱与之共事并且想要一起克服困难的人在一起。那真的是非常有力量的一段经历。即使是 Uber 中国也类似,如果当时有人问,“嘿,你想去参与这个 Uber 中国的迁移项目吗?”我会说,“绝对不想。”但没人问。他们只是说,“把这东西搞定”,然后我们就搞定了。我认为这些事情是相当了不起的。
**Lenny:**为了确认一下,所以 Digg 在这期间基本上宕机了一个月?是这样吗……
**Will Larson:**所以基本上在一个月的大部分时间里它都没有正常工作。大概三天后只读模式恢复了,但绝大多数实际的用户功能在几乎整整一个月的时间里都没有正常工作,而且体验很糟。我的意思是,不算好,但这并不是 Digg 当时面临的最大的问题。但它是当时面临的最大问题之一,而且这并不是一个预示我们事情会顺利的好兆头。但就像我说的,你会从中学到东西,我真的为我们和团队把它弄好、让它运转起来感到自豪,即使最终我们还是归零了、资金耗尽了,而且可以说是被拆分出售了。
Digg 的失败根源
**Lenny:**你认为 Digg 本来能挺过去吗?有没有一种可能是 Digg 本可以成为一家非常成功的企业,还是说你觉得那已经太晚了,而且产品方向错了?
**Will Larson:**真正杀死 Digg 的是那次变更。它不是由 SEO 驱动的。所以变现来源是广告。嗯,包括 Digg 在内的许多公司声称它是同类中首家做信息流、嵌入式广告的公司,就像 Twitter 在推文中插入广告,或者 Facebook 那样。但 Digg 是在 Facebook 或 Twitter 真正创新广告形式之前就这么做了。但绝大多数的变现都落在这些……我们称之为永久链接页面,也就是第 40 页。然后是我们爬取的文章,而这绝大部分的流量是由 Google 搜索驱动的。所以发生了一次 SEO 变更,这真的是促使我们紧迫上线这次迁移的原因。SEO 变了,流量开始下降,变现也随之受挫。所以当我们试图上线这个新版本时,我们已经处于水深火热之中了。但我确实认为,今天我仍然想要一个类似 Digg 试图成为的那种产品。基于我的朋友们实际在阅读和喜欢的内容的社交新闻,与对相似主题感兴趣的相似用户的全局索引相融合。我认为 Google Reader 仍然具有某种与其相似的组件。这些都是有趣的产品,在解决有趣的问题,但无论出于什么原因,它们都没有作为商业项目取得成功。我确实认为那里仍然存在一个空白,但有很多试图填补这个空白的人都失败了,尽管有这么多人尝试,人们仍然难以填补它,这背后一定有原因。
新书速递
**Lenny:**太棒了。Will,在我们进入非常快速的闪电问答之前,你还有什么想分享或者想留给观众的吗,因为我知道你大概五分钟后就得走了?
**Will Larson:**我觉得我们已经涵盖了很多内容。有新书要出了。二月会出新书,The Engineering Executive’s Primer,O’Reilly 出版的。但大概就这些了。
**Lenny:**太棒了。人们在哪里能找到它?我知道在 O’Reilly 上有。今天甚至就可以看到预览版,对吧?
**Will Larson:**是的。在 O’Reilly 上可以看到早期版本。你也可以在 Amazon 上订购,但直到二月份才会发货。
**Lenny:**好的。然后确认一下,这是写给谁看的?听口气是写给工程高管看的。
**Will Larson:**这是写给工程高管看的,但同样适合任何想成为高管的人,以及任何试图弄清楚如何与工程高管共事的人。所以我想,如果你正苦恼于不明白为什么你的 CTO 总是做些蠢事,或者你想侧面管理他们,比如你是产品负责人,却无法让 CTO 停止抱怨工程师需要更有趣的项目来做,这本书可能对你也会有用。
**Lenny:**太棒了。好的,准备好进入闪电问答了吗?
闪电问答
**Will Larson:**开始吧。
**Lenny:**你最常向别人推荐的两三本书是什么?
**Will Larson:**我刚才提到了《Thinking in Systems》和《Primer》。我也提到了《Good Strategy, Bad Strategy》,但我再给你第三本,是 George Lakoff 的《Don’t Think of an Elephant》。这是一本非常有趣的书,关于如何在对话中构建框架,它真的改变了我沟通的方式。
**Lenny:**太棒了。最近最喜欢的一部电影或电视节目是什么?
**Will Larson:**我现在不怎么看电视或电影了,但我还是会和妻子一起看《Top Chef》。她是《Top Chef》的超级粉丝。从这些程式化的结构化节目中,你能大致知道接下来会发生什么,这让人感到非常放松。没有太多真正重要的后果,仅仅是逃离现实生活进入这些程式之中,就相当宁静。
**Lenny:**以前从没人提过《Top Chef》,挺有趣的。你有没有一个最喜欢的面试问题,是你面试求职者时喜欢问的?
**Will Larson:**我现在进行的很多面试,都是试图帮助人们决定他们是否真的想加入一家公司。所以我现在最喜欢问的问题是:“嘿,我们非常喜欢你。你会通过的。我认为你也会收到很多其他公司的录用通知。我打赌你会拿到三四个非常有吸引力的录用通知,因为你是一个非常出色的候选人。你将如何非常具体地弄清楚这些选项中哪一个适合你?”我认为这迫使人们告诉你他们想要什么,然后你告诉他们为什么你比其他人更能提供这些,接着你就可以真正在重要的事情上向他们推销,而不是在无关的事情上推销。
**Lenny:**很喜欢这个问题。你有没有一句最喜欢的人生座右铭,是你经常跟朋友分享,或者发现在工作或生活中很有用的?
**Will Larson:**没有座右铭,但我能想到两件我经常思考的事。在 Uber 时有一句话我经常跟人说,因为那段时间大部分时候都充满挑战。那就是“没有捷径,只能硬扛”。就像:“嘿,我们不会绕开这个问题。我们要咬牙挺过去,我们要到达彼岸,然后我们就会在那里。”我现在思考多得多的另一件事是,六个月后还会有人记得我们的决定吗?因为我认为人们为很多决定感到压力,但我越来越相信,人们为之压力巨大的大多数决定根本没有那么重要。所以我就会想:“六个月后还会有人在乎我们在这里做了什么吗?”答案是不会。只要做些合理的事,然后让我们继续做下一个更重要的事情。
**Lenny:**我太喜欢这个了。你写过很多文章。有没有哪篇你觉得被低估了,没有多少人真正完全理解,也没有传播开来,你会想:“啊,我真的很为那篇感到骄傲”?
被低估的文章
**Will Larson:**也许去年我最骄傲的一篇文章是《Hard To Work With》。《Hard To Work With》基本上是关于我看到很多人极其有才华,但他们试图让同僚保持高标准,然后他们就被视为好斗或难以共事。这篇文章源于我职业生涯早期的一个核心挣扎,那时我不断尝试。我以为我是在让大家负责,但人们只是觉得:“跟你共事太糟糕了。”我就会想:“但我只是想保持高标准。这不正是我们想要的吗?”说到真实的价值观。每家公司都说:“我们有很高的标准,”然后你就会想:“那好吧,我们来做。”接着他们却说:“我们这里没有高标准。你太差劲了。”所以那一篇对我来说真的具有变革性,我认为它深深触动了某些人,因为我认为很多人真的在整个职业生涯中都没有弄明白这件事。他们是你见过的最有才华、最努力工作的人,却无法真正掌握这个阻碍他们发展的理念。他们非常在乎,却往往因为太在乎而被鄙视。我认为这篇是我希望随着时间推移会有更多人去读的文章,里面对我来说有一个非常重要的教训。
**Lenny:**好的,我们会在节目笔记中附上链接,帮助更多人发现它。最后两个问题。如果人们想联系你或者跟进一些问题,在网上哪里可以找到你?听众怎样才能帮到你?
**Will Larson:**在网上找我,去 lethain.com,lethain.com。我所有的文章、我的书,所有链接都在那里。我现在思考得最多的一件事就是战略。所以我非常好奇那些正在思考战略的人,那些认为自己把产品、业务或工程战略做得很好的人。我很想听听大家在想什么,什么真正奏效了,也许还有哪些谎言最终被证明是无效的,而他们在这条旅程的早期曾以为会有效。
**Lenny:**太棒了。Will,非常感谢你能来这里。
**Will Larson:**非常感谢。这真是太棒了。
**Lenny:**我也觉得。大家再见。非常感谢大家的收听。如果你觉得这很有价值,可以在 Apple Podcasts、Spotify 或你最喜欢的播客应用上订阅本节目。另外,请考虑给我们打分或留下评论,因为这真的能帮助其他听众找到这个播客。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。下期再见。
术语表
| 原文 | 中文 |
|---|---|
| An Elegant Puzzle | An Elegant Puzzle |
| CTO | CTO |
| Das Kofinovsky | Das Kofinovsky |
| Digg | Digg |
| Don’t Think of an Elephant | Don’t Think of an Elephant |
| Eric Vogel | Eric Vogel |
| flows | 流量(flows) |
| Gene Kim | Gene Kim |
| Good Strategy, Bad Strategy | Good Strategy, Bad Strategy |
| Hard To Work With | Hard To Work With |
| Henry | Henry |
| Kevin Rose | Kevin Rose |
| Nicole Forsgren | Nicole Forsgren |
| PM | PM |
| Rich Schumacher | Rich Schumacher |
| Staff Engineer | Staff Engineer |
| Steve Jobs | 史蒂夫·乔布斯 |
| stocks | 存量(stocks) |
| systems thinking | 系统思维(systems thinking) |
| The Engineering Executive’s Primer | The Engineering Executive’s Primer |
| Thinking in Systems | Thinking in Systems |
| Top Chef | Top Chef |
| Uber | Uber |
| Vrushali | Vrushali |
| Will Larson | Will Larson |
| Yahoo | Yahoo |
| ZIRP | ZIRP(零利率) |
此文档由 AI 分片翻译(translate_long_document)