The engineering mindset | Will Larson (Carta, Stripe, Uber, Calm, Digg)

Will Larson is the chief technology officer at Carta. Prior to joining Carta, he was the CTO at Calm and held engineering leadership roles at Stripe, Uber, and Digg. He is the author of two foundational engineering career books, An Elegant Puzzle and Staff Engineer, and The Engineering Executive’s Primer, which will be released in February of next year. In our conversation, we discuss: • Systems thinking: what it is and how to apply it • Advice for product managers on fostering productive relationships with engineering managers • Why companies should treat engineers like adults • How to best measure developer productivity • Writing and its impact on his career • How to balance writing with a demanding job • How to develop your company values — Brought to you by DX—A platform for measuring and improving developer productivity: https://getdx.com/lenny | OneSchema—Import CSV data 10x faster: https://oneschema.co/lenny | Vanta—Automate compliance. Simplify security: https://vanta.com/lenny Find the transcript and references at: https://www.lennysnewsletter.com/p/the-engineering-mindset-will-larson Where to find Will Larson: • X: https://twitter.com/Lethain • LinkedIn: https://www.linkedin.com/in/will-larson-a44b543/ • Website: https://lethain.com/ Where to find Lenny: • Newsletter: https://www.lennysnewsletter.com • X: https://twitter.com/lennysan • LinkedIn: https://www.linkedin.com/in/lennyrachitsky/ In this episode, we cover: (00:00) Will’s background (04:12) Changes in the field of engineering (06:27) We need to stop treating engineers like children (08:32) Systems thinking (13:23) Implementing systems thinking in hiring (16:32) Engineering strategy (20:21) Examples of engineering strategies (25:08) How to get good at strategy (26:48) The importance of writing about things that excite you (32:40) The biggest risk to content creation is quitting too soon (35:24) How to make time for writing (37:41) Tips for aspiring writers (41:18) Building productive relationships between product managers and engineers (43:45) Giving the same performance rating to EMs and PMs (48:24) Measuring engineering productivity (55:53) Defining company values (01:02:10) Failure corner: the Digg rewrite (01:11:05) Will’s upcoming book, The Engineering Executive’s Primer (01:12:04) Lightning round Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected]. Lenny may be an investor in the companies discussed.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  I think that we often treat engineers a little bit like children instead of giving them like 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 kind of be sheltered from what is important. And so I actually, one of the I think highlights is that I think we're coming back to this moment where we can actually treat engineers like our peers and put them in the 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.

• 0:35Lenny Rachitsky?

  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 Com. 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 lithane.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,

• 1:20Lenny Rachitsky?

  measuring engineering productivity, how to develop your company values, an amazing story about his time at DIG, 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.

• 1:39Lenny Rachitsky?

  Today's episode is brought to you by DX, a platform for measuring and improving developer productivity. DX is designed by the researchers behind frameworks such as DORA, SPACE and DevX. If you've tried measuring developer productivity, you know that there are a lot of basic metrics out there and a lot of ways to do this wrong. And getting that full view of productivity is still really hard. DX tackles this problem by combining qualitative and quantitative insights, giving you full clarity into how your developers are doing. DX is used by both startups and Fortune 500 companies, including companies like Twilio, Amplitude, eBay, Brex, Toast, Pfizer and Procter and Gamble. To learn more about DX and get a demo of their product, visit their website at getdx.com/lenny. That's getdx.com/lenny.

• 2:28Lenny Rachitsky?

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• 3:11Lenny Rachitsky?

  Customers get frustrated by useless messages like "Error online 53" and never end up getting started with your product. OneSchema intelligently corrects messy data so that your customers don't have to spend hours in Excel just to get started with your product. For listeners of this podcast, OneSchema is offering a $1,000 discount. Learn more at oneschema.co/letty.

• 3:36Lenny Rachitsky?

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

• 3:39Speaker 00

  Thank you so much. Super, super excited to be here.

• 3:42Lenny Rachitsky?

  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.

• 3:54Speaker 00

  No, thanks. I hope to be a good early engineering guest before you pivot entirely to engineering at some point in the future.

• 4:03Lenny Rachitsky?

  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 ZERP, 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 engineer leaders about how to handle all this change?

• 4:32Speaker 00

  I think it's a pretty strange time in the market. So I think that, you know, I started working and, you know, 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 like four months. There was a layoff of some sort. Pretty chaotic, but then we got into the last decade and it was just smooth. Right. And so, you know, 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 like six like 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. Cause you talked to so many people, one after another, after another. You just have to scramble scrambled notes.

• 5:17Speaker 00

  You're trying to like decode afterwards. Pretty, pretty different now, like a lot of engineering managers are spending half their time or more hiring like 18 months ago. And now they're doing like two interviews a month or, or, 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, like all these different competencies that have kind of become more critical. Or a really great engineering director might've just been spending their time hiring, hiring really well. And that could be like a top performer. And now that person can't actually demonstrate like what they're great at. And so that person might be perceived as a low performer if they're not also like figuring out how to like lead the team. Getting deeper into details and also like, you know, sometimes getting into the figuring out like, what, what is the right allocation?

• 6:02Speaker 00

  Like, what are the right sizing of engineering teams, right? Like this is stuff that we weren't talking about much. Or maybe if you, uh, if you really pissed off the CEO, maybe in infrastructure, you just grew a little bit slower next year. But, but you know, different, different ballgame at this point where teams are actually disappearing. Teams are getting cut down, teams are getting consolidated. And that, that's just something that we've kind of avoided for that surf era. Now we um, become like a core part of a lot of the job.

• 6:27Lenny Rachitsky?

  It feels like also engineers of, they're, they used to have a lot of leverage over companies, inside companies. I imagine that's also changing in a big way.

• 6:37Speaker 00

  I think that's true. I think this actually has been bad for engineers in some way. Like one of my hobby horses is that I think that we often treat engineers a little bit like children instead of giving them like 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 kind of be sheltered from what is important. And so I actually, one of the, I think, highlights is that I think we're coming back to 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. That's like a highlight for me and kind of the ship recently.

• 7:18Lenny Rachitsky?

  I've 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?

• 7:32Speaker 00

  Well, yeah, I think a little bit of both. But I think there's been, you know, in this previous era where hiring and retention were kind of like one of the biggest ways you evaluated kind of middle management. Losing team members was a huge, huge issue, right? And so you started to coddle a little bit, which is actually bad. Again, bad for the engineers, bad for the teams, bad for kind of everyone, bad for efficiency of the organization. But now, like, something that I love is we get to like give engineers real hard problems and we get to, we get to actually hold them accountable. And that means we can put them in senior roles. So one of the things that I've been pushing on, I wrote my, my last book, Staff Engineer, about like, what is the career path for senior engineers? One of the challenges is like, if we aren't comfortable holding engineers accountable

• 8:17Speaker 00

  because we just want to retain all the engineers, that 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 you 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.

• 8:32Lenny Rachitsky?

  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 like, "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?

• 8:57Speaker 00

  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 like, every kind of like framework has like 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 like 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, a 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.

• 9:42Speaker 00

  The number one thing businesses need to do is like to collect money successfully for the service that they're selling, right? Stripe's super important. And so we did a lot of analysis on incidents, trying to understand why things weren't working, you know, what we can do better. But we got like so caught up in the analysis that we sort of lost track of whether we're actually improving things. 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." Like, 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. You know, there's like, "Measure twice, cut once." Like, sure, but you don't measure infinite times and never get to cutting.

• 10:25Speaker 00

  You do have to cut at some point to actually make impact. But we just got caught a little bit there. And 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, you know, your hiring pipeline, that moving through different steps. It represents your incidents and how you remediate incidents. It can model on almost anything pretty quickly when you get good at it. And then understanding how reality is in conflict with that, you start to understand

• 11:06Speaker 00

  where your mental model is wrong. Then you can go educate yourself and improve the model and just keep doing that. And at some point, like the model is close enough and you can stop doing that and go like 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.

• 11:25Lenny Rachitsky?

  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, I get what you're talking about?

• 11:32Speaker 00

  This is probably a better place to start, right? Versus a rambling anecdote about using it.

• 11:37Lenny Rachitsky?

  We can, we can go backwards. It'll be great.

• 11:41Speaker 00

  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. And 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, 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. If there's only a couple of fish, it'll go down slower. But also then there's these flows which kind of dictate that where if, if you know we've got much more efficient fishermen, the flow of a fish out might go down. But

• 12:23Speaker 00

  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 Donatella 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 kind 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, that's like a kind of a classic systems thinking problem to think about where you wouldn't think a small amount of carcinogens in like a small fish actually matter. But

• 13:08Speaker 00

  as they go up to the food chain, they start to concentrate it and an unexpected change can happen.

• 13:13Lenny Rachitsky?

  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.

• 13:23Speaker 00

  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 kind of basically infinite. And then you have a couple of inflows. You could have like sourced, you could have like outreach, you could have referrals, and then you have like the candidates. And those, you know, how many people get sourced is probably a function of number of sources you have dedicated to a role. So you have another stock of like how many sources you have. And then that would impact the rate going from potential candidates to actual candidates you sourced. And then from candidates that you have in that box, you'd have like a conversion rate for people who pass the first recruiter screen. And that would move into step two of your process.

• 14:08Speaker 00

  And then from step two, you have maybe like a hiring manager screen, and that would be another conversion rate. So you can see like over time, how the candidates of the infinite potential candidates like wandering around LinkedIn, posting about their deep thoughts, kind of convert into actual people, your first, your second, your third. And but then, as you get deeper into it, you start to actually see interesting things. And so for a lot of candidates, 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.

• 14:51Speaker 00

  You need to go work with the recruiter and the hiring managers on like getting conviction about who they should hire. Classic problem with early, 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 like not getting enough candidates in. You're actually doing a great job of making decisions, great job of closing candidates. There are 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, like Greenhouse or whatever, and pull the historicals. And you can just see how the historicals work versus how you'd expect it to work, and you can see the drop offs.

• 15:33Speaker 00

  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 kind of like big changes with no data behind them. It's like, oh, it feels like we're not. 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 manager is 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, like two years ago, like hiring managers panicking to get offers out. That was a real thing that 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.

• 16:17Lenny Rachitsky?

  I feel like product managers will not 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 like 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.

• 16:52Speaker 00

  First, I started to question whether any any function has a strategy at most companies. I my general experience is that there's very rarely like a written strategy for any company. Sometimes it's like a value statement. It's like, we build the highest quality products. You're like, good. Okay. Like, what is, what, what do I do with that? You're like, build a high quality product. You're like, okay, I don't know what that means. Engineering often has this problem where I think people will make comments like in their kind of their 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. Like the PMs don't have any strategy or the the business has no strategy.

• 17:37Speaker 00

  And the the reality is like product, eng and business always have a strategy. It's just often not written down. And so I really like, the first thing I want to do is like, I push people like not to get caught up on like the fact that there's no template out there, which is like product strategy that someone's like forked and like filled in. Doesn't mean you don't have a strategy. You do have a strategy. It's maybe like a little bit hard to like articulate. And maybe it's like implied inconsistently across different like layers of the the product like reporting chain because it's not written down. But like, it's never true that there's like no product strategy. There's always a product strategy. Sometimes it's bad, but there's always one. And and true, true for engineering as as well. There's always an engineering strategy. It's just sometimes it's bad.

• 18:20Speaker 00

  And the the first rule of strategy is that if you write it down, then you can like improve it, right? If it's not written down, it it's hard to say like if if this PM is just like 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 the header 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 like not a super compelling strategy, at least you can start debugging. It's okay. The the header product should improve the clarity of this document. Hey, this PM actually isn't applying it correctly. Hey, um, the strategy actually isn't appropriate for this one business unit where it makes sense for for for the others. Um, so so that that's like kind of the the first thing I think about.

• 19:05Speaker 00

  But the the second kind of big theme on strategy I think about is that often good strategy is so boring. It's a car hard to talk about. And so for for example, on the engineering side of thing, a a common strategy that's really good, but very boring is we only use the tools we have today. So you know, a lot of times you get engineers um that want to introduce new programming languages, new databases, new 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 when I joined, one one of the engineers, Eric Vogel, wrote the standard kit. And that is our strategy of the tools we use. And you know what?

• 19:49Speaker 00

  Some people are really frustrated by that and I feel for them like it feels like they're losing, 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 like slightly misaligned over time. But boring strategies that tell you what actually matters and aligns you with what the company actually cares about are really good for you, even if, even if they're a little bit annoying at a time. And I can expand on this idea a lot, but I won't, I won't ramble indefinitely on it.

• 20:21Lenny Rachitsky?

  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?

• 20:30Speaker 00

  So first, what is a definition of, of strategy? And the, the best one I've ever seen is from Richard Remol. He, he wrote Good Strategy, Bad Strategy.

• 20:40Lenny Rachitsky?

  He's coming on the podcast.

• 20:42Speaker 00

  Amazing. He also wrote The Crux, I think came out like this year sometime, which, which I also read, and I think both, both great. And just like a phenomenal thinker who has so much depth. I think one of the challenges of, of writing about strategy is you're like, I've seen two things and I, I write the book, but I think the thing that's impressive about Richard Remol is he's seen so many different scenarios that he's able to really operate from both like the, the particular, but also like the general and data set in a really interesting way. Another book with similar characteristics is How Big Things Get Done. I forget the, the authors, but, but really amazing data set of how mega projects kind of succeed and fail. But anyway, Richard Remol, definition of strategy is basically three components.

• 21:25Speaker 00

  There's a diagnosis, like what is the current status quo? Like what are the things that are real today? There are guiding policies, which are basically based on the diagnoses, like how do you want to address them? And there's actions and actions are, how are we going to implement those guiding policies? And he talks a lot about actions because he's concerned about this idea of like inert strategy where you have like. 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 like non-implementation, kind of like useless strategy that doesn't do anything. On engineering, I'm a little bit less worried about that. Yeah, I think strategy is more, more interesting on engineering in terms of kind of clarifying how we make future decisions. And so what are a few examples of that?

• 22:09Speaker 00

  At Uber, we only used our own data centers. We didn't use the cloud. And this has changed since, since the era I was there. But in the like 2014 era, every 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 like literally three months. And some like surreal stories from that. We, we couldn't fit our racks into the data centers. So they had to like take the roof off the data center and like lift like the racks in with the crane. There's just like tons of stories. And like all this we had done in three months. And truly, truly phenomenal. And Uber wasn't in China for very long. So in some ways you're like, we did all that just to leave.

• 22:54Speaker 00

  But, but they left with like a nice, a nice take of D V quality and not, not, not a, 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. They're, they're fully constrained by where AWS or Google Cloud or Azure have built out. So that, that's one good example. Another good example at Stripe was this idea of we run a Ruby monolith and that's like, that's what we did. And that's evolved a bit since then. There, there's more, there's more Java in the Stripe of 2023 than there was in the Stripe of 2016 or the 2012 or whatnot.

• 23:39Speaker 00

  But that, that policy really focused the engineers on building innovative features for our users rather than building kind of different tooling to support different programming languages. And so in both cases, both the Uber policy around like running our own data centers and the Stripe policy around, you know, 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.

• 24:17Lenny Rachitsky?

  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.

• 24:27Speaker 00

  And solving the constraints is, to me, I think, the most interesting thing that that strategy really does. And I think when we talk about bad strategy, it 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 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 are accurate diagnosis views, which means then your guiding policies are kind of incoherent to begin with.

• 25:08Lenny Rachitsky?

  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?

• 25:26Speaker 00

  If people want to get good at strategy, there's a lot of different types of strategy, right? 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. I also think Thinking in Systems, I mentioned that before, related to systems thinking. A big part of strategy is being able to model the realities so you can improve your diagnosis. And so I think that one's 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 Huitt. There's The Value Flywheel Effect by Anderson McConaughey and O'Reilly.

• 26:12Speaker 00

  The Phoenix Project by Kim Burge of Stafford, which is kind of a modern rewrite of The Goal by Goldratt. But I think there's like, 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, Engineering Executives Primer, coming out early next year. I'll take a stab at it and Staff Engineer, my previous book. But I still think there's like a missing book here. So I sort of am like dreaming of writing like a engineering strategy book for my next project, although we'll see if that actually comes together.

• 26:48Lenny Rachitsky?

  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, fourish. You're writing a new book. How many books? You've published two books and there's a third one coming out.

• 27:00Speaker 00

  So I have two books. The first one, first one was Stripe Press, the second one self-published, and the third one with O'Reilly coming out in like two months effectively.

• 27:08Lenny Rachitsky?

  Okay. And then also many, many blog posts for many, many years. And I asked a few people what to ask you, and this came up a lot. Gergé Oroz and Alex Zhu from Bite by Go 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. It's just what impact does writing have on your career? Why has it been, why do you keep doing it?

• 27:36Speaker 00

  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, I don't write for financial gain. And I don't write, I don't write very much on like on a schedule. So I've done like 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 the topic starts like missing, like what you want to write about, you can't fix it a lot of the time. And you're also like on this deadline. You're like, oh, I'm like, I'm screwing up. I need to ship this. It needs to be done tomorrow. And I just find that really draining. Where conversely, like when I, when I own the schedule, when I get to like write about, hey, like I'm writing on something.

• 28:20Speaker 00

  So I started writing this infrastructure engineering book a couple of years ago. And I just like, it just wasn't there. I just couldn't get it to come together. And so I just stopped and I'm not writing it anymore. Maybe I'll come back to it at some point, but probably not. To me, the biggest, 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 like really, really negative. And this, this also ties into how I write books, which is that I, I basically write the entire thing before I start working with the publisher. And if you are, I think diligent and good at anticipating what their concerns are going to be, you can, you can mostly reuse the content that you're trying to write. This is also easier in the sorts of books I write.

• 29:05Speaker 00

  I think harder to do in like a really technical introduction to like MySQL or something. You can't just like resequence those chapters and pretend it's going to work. Those chapters like build in like a different way than the sort of like business book that I write does. But yeah, that writing the stuff that's energizing and just giving up on the stuff that's not energizing. That, that's how I write a lot and how I've been, you know, I've been writing for 16 some years. And, and the way I keep doing it is just by writing what's energizing and what I'm thinking about now. And I don't write what I'm not thinking about and I don't write for any audience. Just write, write what is interesting to me and you know, that, that means some people don't like it. And, and that's great. Like that's, that's totally fine.

• 29:50Speaker 00

  It's, it's not, it's not really for them. It's um, for, for people who want to follow the ride and that, that's where I focus.

• 29:57Lenny Rachitsky?

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• 30:41Lenny Rachitsky?

  For a limited time, Lenny's podcast listeners get $1,000 off Vanta. Go to vanta.com/Lenny. That's V A N T A dot com slash Lenny to learn more and to claim your discounts. Get started today. 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?

• 31:00Speaker 00

  I would guess about 1,000 like that. That would roughly be my, my assumption. I think there are a few years where I wrote, you know,

• 31:10Speaker 00

  hundreds of posts. And so if you do that like three years, it's not that hard to get to 1,000 from there.

• 31:16Lenny Rachitsky?

  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, hyper-growth 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 like 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 go viral? And it's easy to do like a couple of 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.

• 31:59Lenny Rachitsky?

  And I find that what I find is important is almost like 80, 90% of what you have to, 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. Cause otherwise you just burn out. You create a job for yourself that you don't want. Why would you do that?

• 32:13Speaker 00

  Yeah, I just 100% agree with that. And I think the other thing is that like everyone converges on the same thing that they think people want. So it's like, it's crypto two years ago. It's like AI right now, or it's like counter AI, like AI is going to like ruin the world. It's just like, it's hard to say something very novel because one, like everyone's trying to like say something about it. Two, like 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 forty 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 this, there's always a sense that like you've missed the wave.

• 32:58Speaker 00

  Like it's too late to join Substack. There's already, 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. Like you'll never make it. There's too many Medium writers, but it's just like not true. If you just like 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.

• 33:25Lenny Rachitsky?

  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 there ever gonna 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 it, easy to let it, hard to keep it up. Nobody actually keeps it up because people are gonna come and go. The thing that really separates success from not success, from failure is just people that can keep at it. And there's not like an end game to this, right? It's an infinite game and it's about being able to sustain that over the long term.

• 34:04Speaker 00

  And you're not competing with other, other content creators. If you think of it as an infinite game, right? Like you're all, you're all working together. You can all like help each other grow. There's no like maximum number of product writers or thinkers who can like be doing something. Like you're not less successful because Shreya's exists or something like that. Like there's no, there's no competition there. It's like a false, false dichotomy.

• 34:27Lenny Rachitsky?

  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. And that's happening anyway, just the bar continues to increase because there's more and more content out there. And to me, that's like the ultimate thing you've got to get right is just the bar. You've 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 the way 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

• 35:11Lenny Rachitsky?

  new that no one's heard before, or share new information they haven't seen anywhere else.

• 35:15Speaker 00

  I totally agree. I just, I could keep ranting about this for, for the entire time. I don't want to derail a lot of this, but I totally agree.

• 35:23Lenny Rachitsky?

  We'll control ourselves. So then getting very tactical, I think this is what a lot of people are always wondering, how do you, 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?

• 35:33Speaker 00

  I used to do things differently before, before I had kids. I have a three and a half year old and, and just your, your timing, your, your life just like really shifts a lot once, 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. Because it's all, and this distracts you from, from your work. Because these, you know, particularly if you're like a senior role, like these can be like pretty demanding jobs. But they're not demanding because you're responding to an urgent DM

• 36:18Speaker 00

  on Slack, like every, every five or six minutes. They're demanding because you need to make some really difficult decisions really well. And I think writing about like related topics is a great way to refine your thinking and improve your performance. It's not like a, not like a conflict and, or you do one, you either write or you do your job. Well, I think you can find a way to like 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 like learn, to 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, it's, it's in alignment. So that's like one piece. But yeah, I've played around with my schedule a lot. Before I had a kid, often like Saturdays would be like the writing day.

• 37:02Speaker 00

  And so like, you know, morning and early afternoon would just be like writing. I can't, I can't do that anymore. So now I mostly write at night, which is tricky from an energy, 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.

• 37:23Speaker 00

  If you're not excited about it and it's 9pm, you're just gonna get a sleep. And so like, I really think that this is where you have to schedule a little bit deliberately. But the first thing we talked about, our own energy management, like 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? Like, this doesn't make sense.

• 37:41Lenny Rachitsky?

  Just to close out this thread, for someone that wants to do more writing, knows that it's gonna be valuable, but just hasn't any one tip that you would leave them with to get on this train?

• 37:51Speaker 00

  It depends why people wanna write. I tell people, if you just wanna like write something that is gonna help advance your career, you should really focus on writing like two or three really good things and spend a ton of time drafting, revising, getting feedback. You just focus on making like one great artifact or two or three great artifacts. You don't need to create like a long running blog where you publish every week. Like, there's really no need to like do that. If your goal is just to like create some artifacts that show you're like a deep thinker, that kind of like help position you in the industry. Don't start a newsletter if you just wanna like advance yourself in the industry a little bit. Just write like two or three really good things. So that's the first thing I'd say. But if your, if your goal is to write like a lot consistently over time,

• 38:34Speaker 00

  my biggest advice would be just like, just publish. And so there's a lot of people out there with like stuff that, you know, hundreds of drafts, and they've not published anything. And my thing is like, I publish almost everything I write. If there's something that I'm not gonna publish, I like, don't start writing it. Cause I just have like a, you know, a quick check in my head. Like, is this something I can write and publish? And if my answer is like, no, I just don't even start. And my accuracy has gotten higher like over over time as I've written more. But I publish pretty much everything I write. That's why like some of it's like not that good and like, and that's okay. Like I, I'm like, again, like, I want to write, I want to get these ideas out. I want to show like what I'm focused on and my evolution as like a thinker. I'm trying to learn how to like operating these different roles and these different companies.

• 39:19Speaker 00

  I'm not writing, trying to create like a polished, perfect thing. And also like, I'm not writing to maximize a reader's experience of reading it. And some people don't like that. And I think that's like a totally reasonable thing not to like. But I think what I can bring you is like my experience as an operator who's like actively learning and thinking through. I think that's really valuable to other operators in the industry. In terms of like giving you the perfect writing, like 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. Like the books are taking like a collection of thoughts over like a couple of years. Cleaning them up a little bit, packaging them. They're, they're way higher quality than my typical writing. But yeah, I would just publish, publish a lot. Don't worry about the quality. Sometimes people will send you like silly feedback and like, I just don't respond to that stuff anymore.

• 40:05Speaker 00

  And, and like, you know, you never know why people send you something like that. I think trying to debug people you don't know is like a bad use of time. It's just kind of like, thank you, move on to the next. Like, don't even, don't even spend time worrying about it.

• 40:18Lenny Rachitsky?

  I like that term debug people. Uh, 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. Like, that's the worst case scenario, basically. It's 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's, no one has time for that.

• 40:37Speaker 00

  And if they do like, that's like, that's a them problem, right? Like, it's like, there are, the internet's a big place with a lot of people. And there are people who are going to be having like a really bad day when they encounter something you do. And they're going to be, they're going to channel that anger at you or that frustration at you. But that's like, that's not about you. That's just like, you happen to be there when they engage with it. Like, you don't have to take that on. That's like, that's not your situation. Like, it's okay.

• 41:03Lenny Rachitsky?

  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 shit, just do stuff. Like, it only gets more stressful as you build the audience over time.

• 41:15Speaker 00

  Yeah, absolutely, absolutely true.

• 41:18Lenny Rachitsky?

  Okay, shifting topics. There's a lot of product managers that listen to this. Something PMs often wonders how to have better relationships with their engineers, their engineers. What advice could you give to product managers to build more productive, happy relationships with their engineers and engineers?

• 41:37Speaker 00

  So, the core problem in 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, that's hard to navigate. But if you can just be like 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 like timeline related or saying yes to sales related, where the engineer's like, hey, we definitely can't say yes to that. And the PMs are like, actually, like, we're going to say yes to it because it's really important for me getting promoted or something like that. And is it ever this simple? It's really never that simple.

• 42:21Speaker 00

  People create like simplistic narratives to like find villains that they work with. There are no villains in the workplace. They're just people with like complex incentives that are doing complex things. But sometimes like I talk to EMs who think like, 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 like, the business needs to sell stuff to remain functioning. You can't just like say no and like have the business succeed. That doesn't work either. So, so one, understanding the incentives. The other piece, though, and I think this is the more common case, or just the EM or the PM just don't understand the other person's needs. And they start arguing

• 43:02Speaker 00

  before understanding. And 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 like idea that you have to make trade offs and that there are tons of hard trade offs to be made in in kind of the field. But my experience is if you really deeply understand what everyone wants, there's usually like a A compromise solution that gives everyone exactly what they want that doesn't take more time, just have to be willing to dig deeper into it and understand like the true needs for each party, which is often like not what they're saying, by the way, which is part of the confusion.

• 43:45Lenny Rachitsky?

  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 latter definitions? What actually can help that situation?

• 44:05Speaker 00

  So my biggest thing has been trying to force this idea that like EMPM pairs are pairs and they generally have the same performance rating. And there's exceptions here, right? Like it could be the EM is clearly not performing and then it's not, it's not the PM's fault. The EM is like, you know, can't show up to work, like the team like doesn't respect them. You know, sometimes there's a clear non-performance, but generally like hard situations are not situations where one person's like obviously terrible. Those are easy to diagnose. Those are the easy ones. But in cases where there's two folks who seem to be like pretty good, but just like the overall execution is not working out.

• 44:47Speaker 00

  I think this idea that like same perforating for both drives like a level of one pain, but the right sort of perspective. And also, you know, something that I think Carter 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 the 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.

• 45:20Lenny Rachitsky?

  Wow, that's so interesting. So your recommendation, something you were 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, in the same meeting.

• 45:31Speaker 00

  So yeah, the head of the, our chief product officer, Bruce Shali and I like spend a fair amount of time like calibrating together and making sure, like again, there's cases where there's like an exception, right? Because there's like clear, 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've told them that. And I think that that's pretty powerful.

• 45:55Lenny Rachitsky?

  That is so interesting. I've never heard of that approach. That is definitely solving that problem of EMPM.

• 46:01Speaker 00

  Yeah, the incentives, the incentives are shared now, which doesn't, which isn't perfect. It's still hard to balance them. They can still like make the wrong trade offs, but at least they understand the incentives are shared, which I think is a pretty powerful idea.

• 46:15Lenny Rachitsky?

  That is really interesting. And I imagine some companies might even want to include design managers in that, take it another step.

• 46:22Speaker 00

  You know, the role and the primacy of different functions in different companies like varies so much that it's hard to have like a one size. Like you could also imagine where you want like a staff engineer in that or not. And so I think very company specific, but, but yeah, I think design could absolutely be involved, particularly for like a design like company like an Airbnb or something like that.

• 46:42Lenny Rachitsky?

  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 think, 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.

• 47:00Speaker 00

  I think one of the biggest challenges I've historically seen, particularly in the last like decade, is this idea that engineering managers have the job of giving their team interesting work. And I think that that can put, you know, you often see this like growth teams where the growth teams like, hey, we just need to do like a ton of experiments. And then here is like, I want to build something brand new. And the, the engine managers in between those try to figure out like, need to ship 50 experiments that are pretty boring. And they want to do something brand new, like, I don't know how to do solve this. And so that it's a tricky, a tricky moment. And good, good EMs kind of like find the way to balance. But that, that's like the biggest source of kind 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.

• 47:45Speaker 00

  And it makes the EM seem like totally unreliable partners because they're trying to solve these, a little bit of these invisible constraints. And that's where I think pushing further to understand like, hey, like you keep prioritizing this, like rewrite into a new programming language. To me, that seems like completely idiotic thing to be doing, like 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, like this, this bozo did like blah, blah, blah. And having like sort of this like victim villain kind of mindset about your peers.

• 48:24Lenny Rachitsky?

  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 engineers 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 engineers for and engineers just for how to measure productivity well?

• 48:44Speaker 00

  This is a question that's coming up even more, right? In a moment when we're kind of reducing a lot of the size of teams, when the industry, when the venture capitalists that are on the board for these like venture-backed companies are pushing on the efficiency of engineering, engineers are trying to figure out like, how do we like, 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. And so the first way that people kind of focus on trying to answer these questions is just like benchmarking by like the amount of funding that you have. And that's pretty straightforward to do. It's a mechanical exercise. You look at like, you get a data set from your venture capital funds or whatnot. And you figure out like, okay, how much should we be spending in R

• 49:29Speaker 00

  and D? How much should we be spending on engineering? How much should we be sending on, you know, infrastructure engineering in R and D? And you can like benchmark this all out and figure out what the correct numbers are there. The problem is this is like a very mechanical and not very like insightful driven way. Maybe it'll get you a defensible answer. It's like the old like, no one gets fired for buying IBM, which definitely hasn't been true in my, my career ever. But you know, this idea that if you just have the right benchmarks, like 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. That's which is useful because it's hard to do good work

• 50:11Speaker 00

  when your board is angry at you. But it's not useful in the sense that it doesn't actually help you run your, your, your organization effectively. So then there's like the, the much harder, immediate problem of how do you actually know if your R and D team or engineering team is like effective? And what I find is a couple of things. First, if you're a good leader and you talk to engineers, They will tell you, like 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 like a crumb you can start like picking up and you can trace, trace the crumbs to figure out what's wrong. Like often you'll have more experience to analyze the complaints to figure out what kind of the contributing causes are to them.

• 50:57Speaker 00

  But, but yeah, if you just go talk to the team on an ongoing basis, you will know if they're effective or not, and you can go work to solve those specific problems. But again, you can't tell like you're bored, oh, like it's fine. I talked to the teams that they're good. My intuition is spot on. Cause how do they know if your intuition is good or not, right? They're, they're dealing with like a huge portfolio and some of their leaders they're talking to are good. And some of them have terrible intuition. How do they actually assess? I think it's tricky and what I've, 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, not a, well, we did a good job products, like screwing up over there.

• 51:42Speaker 00

  Obviously a lot of companies find comfort doing that, but like really we're here to support the products, to support our customers and doing like something interesting. We're not here to like build novel systems unless it supports the customer and, and the product. And so first try to align heavily there. Second, I think just showing the roadmap of the valuable things you've done in the last six months is really powerful. Cause I think sometimes people are like, I don't have anything to put there. And you're like, yeah, that's, that's a real issue. Or if you have the kind of stuff to put there, that's great. And I really find that if you just commit, show the number of meaningful, meaty, meaty things that have

• 52:23Speaker 00

  impact that you're doing, and you can explain the impact, people will kind of step back and give you space. If you can't populate that list, people will have concerns and like rightly so. Like they, they should be, they should be concerned about that.

• 52:36Lenny Rachitsky?

  Is there any metrics or tools or anything like that that you find useful too? Cause these are all awesome piece of advice, but I imagine everyone's always just like, give us this number we're tracking, give us this dashboard, see what engineers doing.

• 52:49Speaker 00

  So one of the most influential books in the last decade in kind of software engineering, leadership and kind of infrastructure is Accelerate by Nicole Horstgren, Gene Kim, and I believe there's a third author on that one, but I'm forgetting right now. Really, really phenomenal book, and it kind of comes up with these like four, four metrics. It comes up with like lead time, it comes up with like incident remediation time, it comes up with failure rate, and the fourth one of some sort. And there's like at least 50 different startups out there that are selling you dashboards that can 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.

• 53:33Speaker 00

  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, but it doesn't actually tell you if you should like fire your engineers or something like that. That's like way, way more detail specific. So people do like to see these metrics, just like they see uptime metrics. A lot of engineers report on like sprint points or stuff like that to their board, which are just like totally, totally fake thing to be like reporting on. But, but people get some comfort on it.

• 54:15Speaker 00

  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 like, well, actually, there's no accurate measure to give. They're not an expert is like you're, 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 like an opportunity to educate people on like, why the measure is imperfect? What are some things it misses or kind of the lies from the conversation?

• 54:58Speaker 00

  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.

• 55:36Lenny Rachitsky?

  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.

• 55:55Lenny Rachitsky?

  Okay, just a couple of more questions before we get to our very exciting lightning round. One is around values, company values, org values. 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?

• 56:14Speaker 00

  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 on 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 it's first you can't do is just like steal values. Value cargo call thing. Man, users first. Great Amazon value, right? A lot of companies aren't users

• 56:55Speaker 00

  first. And that's okay. But what's not okay is when you put, hey, we're users first, and then you actually show like the decisions you're making, and you clearly aren't users first. And so one of the things I think about is just like honesty. And so good values have to be honest. And so any value can be honest, or there's no universally honest values, right? Like, 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 in the value. The second one is like applicability. Like, you have to have values that you can actually figure out how to apply to your

• 57:38Speaker 00

  work. And so one of Stripe's values was no longer a value, I believe, but it's like optimized globally. And so optimized globally is a really interesting problem, because sometimes you'll have something you want to do, or interesting value. Sometimes you want to do something, you're like, hey, I want to introduce a new programming language, because that's better for my team. But like, 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 Uber's value was, do what's good for your team and ignore everyone else, because that will slow us down. And 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? And then, so those

• 58:22Speaker 00

  are applicable to real problems, and they were honest. Where Uber was just like, don't worry about other people, like, make it work for your team. And that's how they moved so fast, because they just didn't worry.

• 58:32Lenny Rachitsky?

  Wasn't there a value of toe stepping, encouraging toe stepping, something like that?

• 58:36Speaker 00

  Let builders build, toe stepping. There were a number of values that could be interpreted in different ways. And, and sometimes they got weaponized in various ways, as all values do. But, but these, 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. Like, okay, but like, why would you ever not build good software? Like, that doesn't, that doesn't make sense. Or, um,

• 59:16Speaker 00

  we solve customer problems that matter. Like, good. What, who would ever say their, like, what, what company doesn't think they're solving customer problems that, that matter? And so there are certain, like, values that just you can't apply. And so like, I think of these as like, identity values. Like, these are really just you describing, like, who you want to be. Like, we care about our customers. Like, great, but like, who would say they don't care about that? They're just like, there are certain values that I think of it just like, identity values. And they're not like, 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, they feel good.

• 59:59Speaker 00

  When, when you're an executive team, kind of debating, like, what are these identity values? It's like, we're, we're kind to other people, or like, you know, sure, that, that sounds good. Like, we're a family. Like, sure, that, that sounds good. Um, that one, I guess, is a little bit reversible. Because, you know, there's Netflix, which is like, we're a team, like a sports team, we're, we're not a family. And so a little bit reversible. But, but not perfectly. But yeah, but these are the three that I found really useful for any value. Like, is it honest? Is it applicable? And can you reverse it? And if not, it's probably actually not helping the team make decisions.

• 1:00:30Lenny Rachitsky?

  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. Like, there needs to be a group that doesn't quite fit. Because if everyone fits, then you're not doing anything useful. What's the point? Which feels weird to say, like, right? Why would not, not everyone fit in our big group of awesome company? But it's clear, like, 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?

• 1:00:59Speaker 00

  But I agree, like if it doesn't apply to anyone, then like, why bother saying it? It's like, it doesn't, 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 like figure out who to, who to like bring in. But if it doesn't apply to anyone you're hiring or anyone that you have in the company, then it just sort of like, isn't worth having because you already have too many values. You are already trying to get rid of values because you have like 17 and you need to get down to like four where people can remember them. So if it doesn't apply to anyone, like why, why bother having it at all?

• 1:01:31Lenny Rachitsky?

  Yeah, like integrity is a common one, integrity, like everyone has it. Nobody wouldn't want integrity, like what is unique?

• 1:01:38Speaker 00

  We're the non-integrity company, like we were the company that like thinks integrity is bad. Like that, that's like not a real thing.

• 1:01:44Lenny Rachitsky?

  The other one else I'll add to is honest. So at 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 value should describe who you are, not who you want to be and aspire to be. So they cut two values, including that one. And there's 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 DIG and the rewrite that you all went through. I think it was the version four of DIG.

• 1:02:28Lenny Rachitsky?

  Can you just tell that story and what happened and how much of a mess it ended up being?

• 1:02:33Speaker 00

  Yeah, DIG V4 is, is a, I mean, still, still something I have a lot of like fond memories for. There, there's one picture that I, that I've kept. And it's a picture of a lot of the engineers around this table, the middle of this giant office. And they're like serving like sushi. We had like waiters, caterers come in that day. They're serving like sushi. They're, we have like, you know, plates with like champagne flutes on it. There was a full bar and we're all around this table because the site's not up. And so, Dig before, essentially, what Kevin Rose, or the board, or some combination there, realized is that Dig was losing, was losing to social networks, and that this idea of aggregated

• 1:03:16Speaker 00

  news was going to be outcompeted by the Twitters, the Facebooks, etc., if we didn't find a way to move to have a social component for it. Even outcompeted by Reddit, long term, was kind of the fear, although at the time, that was far from obvious. And so, we needed to move to support kind of social functionality. And the previous version, we simply couldn't get it to work. And so, the decision that was done, like, two and a half years before I joined, and this shipped about six months after I joined, was they need to do a complete rewrite in order to get there. This is a decision that never works out for anyone. And so, I think, like, as someone more experienced, I could have predicted this wasn't going to work out. But

• 1:04:01Speaker 00

  I was early in my career, my PM counterpart at Yahoo, Dash Gopanath, he went to Yahoo, and he's like, "Come to Dig. 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. But, so we go, and, you know, 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 this death march, trying to get this thing out. And so, we pushed really hard. This is before the cloud, for the most part. So, we wiped all of

• 1:04:43Speaker 00

  our, pretty much all of our existing servers, to reimagine them to the new software. We tried to bring the site up, and it 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, you know, 30 days in, most people aren't even trying to get the site back up anymore. There's maybe like five of us who are still trying. And, you know, we did. And I think that was like a really powerful moment for me. And I think, in the first two days, like, myself and Rich Schumacher, like, one of the other engineers, we had to write like a caching system from scratch, which got us like half the way up.

• 1:05:28Speaker 00

  Really a terrible way to do software on a side note. Like, I'm not recommending this to anyone. This was like a series of anti-patterns cludged into like a launch. But we got it perfectly up, but we had to restart it every 12 months. Basically, every server, sorry, every 12, 12 hours, every server had to be restarted even with the caching mechanism. And then, you know, about three weeks after that, like, I finally figured out what the core bug was that was bringing us down every 12 hours. And 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. And it's something like super, super silly. And we just had someone who hadn't written Python before, who was working on the API code.

• 1:06:13Speaker 00

  So they didn't realize this gotcha, then no one else caught it when it was reviewed. And it just took a long time to debug because it was like such a non-obvious. It didn't break anything. It was just doing a lot of extra, extra load on the servers. And we finally, we finally figured it out and it was just really remarkable experience pulling through. And, and you know what? The company still, still went to zero. And so we had this bad launch. I think we did this heroic, heroic stretch to get it working. A couple of weeks after that, like a new CEO came in, did a round of layoffs. This is back, I think, like 2020, 12. The team, nine months after I started, was down to like 30 people from about 100.

• 1:06:57Speaker 00

  And it just went, it went downhill from there, from a, from a business perspective. But we launched a lot of functionality. I've really learned just a tremendous amount and it kind of shaped like 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. Like I became a manager, like two and a half years into my career. Three, basically running the entire engineering team there because everyone who had a lick of sense quit or got laid off. And it was just like complete idiot me, like trying to like be the manager for, for the engineering org. Wasn't qualified and no one would have given me that job. But I was the only one dumb enough to take it at that point.

• 1:07:38Speaker 00

  And, and I learned so much and I really like that, that's like the kernel that like turned into like my entire career was that opportunity, even though at the time it was, it was pretty, pretty grim.

• 1:07:49Lenny Rachitsky?

  That's an amazing story. I feel like a lot of these experiences where in the moment, it's just like, what is going on? This is so bad and hard. End up being the most interesting in looking back, end up being the most biggest teaching experiences, the ones you like bond over with people you work with, like Apple always comes to mind where it's just like Steve Jobs just drove people like crazy. And then they look back and that was the best moment in my career.

• 1:08:12Speaker 00

  You would never like voluntarily take on a lot of these really challenging things, but sometimes like when they show up, like you're with a group of people you really respect, you love working with, and you like want to overcome together. And that's like, that's really powerful experience, even if Uber China was similar, where like if someone had been like, hey, do you want to go work on this Uber China migration? I would have been like, absolutely not. But like, no one asked. They're just like, get this done. And so we did. And I think these things are like pretty remarkable.

• 1:08:39Lenny Rachitsky?

  And just to be clear, so DIG was down for a month, basically during this period?

• 1:08:42Speaker 00

  Is that? So it basically didn't work properly for much of the month. It was, it was like, read only was back up in like 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, like, not great. But, you know, that wasn't the biggest problem DIG had at that point. But it was one of the biggest problems that had at that point. And it wasn't, it wasn't a real sign of things likely to go well for us. But, you know, like I said, you learn from those. And I'm really proud that like we and the team like got it working, got it, got it

• 1:09:25Speaker 00

  running, even if like ultimately like we still went to zero and like ran out of money and kind of sold silver parts.

• 1:09:32Lenny Rachitsky?

  Do you think DIG could have made it? There was a world where DIG would have been a hugely successful business? Or do you think it was just way too late and it was the wrong product?

• 1:09:39Speaker 00

  The thing that really killed DIG is the change. It was an SEO driven, like, so monetization was from ads. DIG was the, well, many companies, including DIG, claimed that it was the first in kind of stream in feed like advertising company, like where Twitter has like ads within like the tweets or Facebook does. But DIG did that before Facebook or Twitter really innovated kind of ad format. But the vast majority of our monetization was on these like, we call them criminal pages, which is the page where you then like 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 like the thing that started creating the urgency for us to launch this migration.

• 1:10:20Speaker 00

  SEO change, 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 Dig was trying to become today. Social news based on like what my friends are actually reading and liking, merged with like a global index of kind of similar users who are interested in similar topics. It's just still a product that I think Google Reader had 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.

• 1:11:05Lenny Rachitsky?

  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.

• 1:11:16Speaker 00

  I think we've covered a lot of it. New book coming out, new book coming out in February, Engineering Executives Primer, O'Reilly, but that's probably it.

• 1:11:25Lenny Rachitsky?

  Awesome. Where do people find that? I know it's on O'Reilly. You can look at a preview of it even today, right?

• 1:11:29Speaker 00

  Yeah, O'Reilly, you can see that the early copy, you can order it on Amazon as well, but it won't be shipping until February.

• 1:11:37Lenny Rachitsky?

  Okay. And then just to be clear, who's this for? It's for engineering executives, by the sound of it.

• 1:11:42Speaker 00

  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.

• 1:12:04Lenny Rachitsky?

  Amazing. Okay. Ready for the lightning round?

• 1:12:07Speaker 00

  Let's do it.

• 1:12:08Lenny Rachitsky?

  What are two or three books you've recommended most to other people?

• 1:12:11Speaker 00

  So I talked about Thinking Systems of 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 and conversations that has really changed how I communicate.

• 1:12:24Lenny Rachitsky?

  Amazing. Favorite recent movie or TV show you've really enjoyed?

• 1:12:28Speaker 00

  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 like very relaxing from like these formulaic structured shows. We kind of know what's going to happen. There's no real consequences that that matter too much and just kind of escaping from real life to these like formulas can be pretty, pretty futile.

• 1:12:50Lenny Rachitsky?

  No one's 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?

• 1:12:58Speaker 00

  A lot of my interviews now are trying to help people decide if they actually want to join a company. And so my, my favorite, 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? And 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 like pitch them on what matters versus pitching on things that don't.

• 1:13:31Lenny Rachitsky?

  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?

• 1:13:39Speaker 00

  No, no mottos. But I can think of like two, two, two things I thought about a lot. Yeah, at Uber, something I talked to people a lot because it was a challenging time for, for much of it was there's no way around just through. And that was like, hey, we're not going to, not going to dodge around this. We're going to like gut through it and we're going to get to the other side and then we're, we're going to be there. What I think about a lot more now is, um, well, anyone remember what we decided in six months? So I think people stress out about a lot of decisions, but I increasingly believe like most decisions people stress out about just like aren't that important. So I'm like, well, anyone care in six months what we did here? And the answer is no, like just do something reasonable and like, let's move on to the next more important thing.

• 1:14:17Lenny Rachitsky?

  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, oh, I'm so proud of that one?

• 1:14:30Speaker 00

  Maybe the piece I'm most proud of from last year was like 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 like combative or difficult to work with. And this one, this one comes from, you know, a core struggle of my early career where I kept trying, I thought I was holding people accountable. 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, isn't that what we want? And every like, talk about like 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. Like you suck. So that one, that one's one that I really is so transformational to me.

• 1:15:13Speaker 00

  And I think it really hits some people hard. Cause 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, this one idea that's holding them back. And they care so much and they are often despised because they care so much. And, and I think this is one that I, you know, hoped more people would, well, hope more people will read over time. And there's a really important lesson for me in there.

• 1:15:41Lenny Rachitsky?

  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?

• 1:15:51Speaker 00

  So find me online, lethain.com, L E T H A I N dot com. All my writing, my books, everything linked, 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, 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, that have not turned out to work that they thought might work earlier in their journey?

• 1:16:19Lenny Rachitsky?

  Amazing. Will, thank you so much for being here.

• 1:16:23Speaker 00

  Thank you so much. This is, this is really fantastic.

• 1:16:25Lenny Rachitsky?

  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.