In short
```markdown
Lenny's Podcast
Product | Growth | Career
Episode Title
The Engineering Mindset | Will Larson (Carta, Stripe, Uber, Calm, Digg)
Introduction Guest: Will Larson, CTO at Carta Background: Former CTO at Calm, Engineering leadership at Stripe, Uber, Digg Publications: Author of *An Elegant Puzzle*, *Staff Engineer*, and upcoming *The Engineering Executive’s Primer*
In this episode, Lenny and Will discuss various aspects of engineering leadership and strategy, including systems thinking, fostering productive relationships between product managers and engineers, and writing's impact on his career.
---
Key Topics Discussed
- Systems Thinking
- Definition: Understanding systems through stocks (accumulating entities) and flows (movement between stocks).
- Application Example: Hiring pipelines and incident management at Stripe.
- Takeaway: Systems thinking can identify gaps between models and reality, but requires action to implement changes.
- Engineering Strategy
- Importance: Often overlooked compared to other functions.
- Key Components: Diagnosis, guiding policies, actions.
- Examples:
- Uber's use of data centers.
- Stripe's Ruby monolith strategy.
- Advice: Document strategies to improve clarity and focus.
- Writing and Career Impact
- Approach: Write about topics that energize you; avoid writing on a set schedule.
- Benefit: Writing helps refine thinking, which can improve professional performance.
- Publishing Strategy: Focus on creating a few high-quality artifacts rather than continuous output if career advancement is the goal.
- Building Relationships with Product Managers
- Challenges: Misaligned incentives and lack of understanding.
- Advice: Understand each other's needs before attempting to resolve conflicts.
- Cultural Change: Suggests aligning EM and PM performance ratings to encourage collaboration.
- Measuring Developer Productivity
- Challenges: Balancing meaningful metrics with business goals.
- Strategies:
- Align evaluation with product and business objectives.
- Use metrics as diagnostic tools rather than absolute measures of productivity.
- Developing Company Values
- Essential Criteria:
- Honesty: Reflect actual practices.
- Applicability: Guide decision-making.
- Reversibility: Values should offer a choice, not be universally applicable.
- Failure Corner: The Digg V4 Rewrite
- Background: High-pressure rewrite to introduce social functionality.
- Outcome: Ultimately unsuccessful, but provided invaluable learning and career growth.
---
Resources and References
- Books Recommended:
- *Thinking in Systems* by Donella Meadows
- *Good Strategy/Bad Strategy* by Richard Rumelt
- *The Crux* by Richard Rumelt
- *How Big Things Get Done* by Bent Flyvbjerg and Dan Gardner
- Other References:
- The Phoenix Project
- Accelerate by Nicole Forsgren et al.
- The Value Flywheel Effect
- Technology Strategy Patterns
---
Where to Find More
Will Larson:
- [Twitter](https://twitter.com/Lethain)
- [LinkedIn](https://www.linkedin.com/in/will-larson-a44b543/)
- [Website](https://lethain.com/)
Lenny:
- [Newsletter](https://www.lennysnewsletter.com)
- [Twitter](https://twitter.com/lennysan)
- [LinkedIn](https://www.linkedin.com/in/lennyrachitsky/)
---
Sponsors
- DX - Platform for improving developer productivity.
- OneSchema - Embeddable CSV importer for SaaS.
- Vanta - Streamline security compliance for businesses.
---
Episode Conclusion Will Larson shares insights from his extensive career in engineering leadership, focusing on practical advice and strategies for current and aspiring tech leaders.
```
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Transcript
Automatic transcript. May contain errors.0:00I 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 I go, 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 this moment where we can actually treat engineers like our peers and put them in their really senior leadership roles and not have this kind of baseline assumption of the go. But we have to cuddle them or hide them from the real problems.
0:30And this is how they're going to get the opportunity to grow as well. Today, my guest is Will Larson, one of the most requested guests I've had on this podcast. Will is currently CTO at Carter. 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 lathein .com, which is a must read for every engineer and age leader. Inner conversation will share his advice on developing your engineering strategy and strategy in general.
1:11How to improve the relationship between an engineer manager and a PM. How he finds time to write while also working in 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 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. 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.
1:50If 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 Proctoring Gamble. To learn more about DX and get a demo of their product, visit their website at getdx .com slash Lenny. That's getdx .com slash Lenny.
2:28Today's episode is brought to you by one schema, the embeddable CSV importer for SaaS. Customers always seem to want to give you their data in the messiest possible CSV file. And building a spreadsheet importer becomes a never -ending sink for your engineering and support resources. You keep adding features to your spreadsheet importer, the customers keep running in CSUs. Six months later, you're fixing yet another date conversion edge case bug. Most tools aren't built for handling messy data, but one schema is. Companies like Scale AI and Pave are using one schema to make it fast and easy to launch delightful spreadsheet import experiences.
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3:36Will, thank you so much for being here and welcome to the podcast. Thank you so much. Super, super excited to be here. 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. No, thanks. I'm hope to be a good early engineering guest before you pivot entirely to engineering at some point in the future. Wow, I love that. How cool would that be? I wasn't an engineer actually when I started my career. How interesting would that be if we come full circle?
4:11Anyway, 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 for 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 engine leaders about how to handle all this change? I think it's a pretty strange time in the market. So I think the, I started working right before the 2008 crash. So the first few years there were not so good. When I joined Yahoo, there was a layoff basically every four months.
4:48There 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. A revenue went up. Headcount went up. 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 even remember who you're talking to because you talk to so many people one after another after another. You just have to not scrap it. Scramble notes. You're trying to decode afterwards.
5:20Pretty 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 200 views a month or less, maybe zero interviews. There's a real shift in just the amount of time people are putting into hiring. Instead, all these different competencies that kind of become more critical were a really great engineering director might have 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 what they're great at. And 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 details.
5:58And also sometimes getting into the figure out, what is the right allocation? What are the right sizing of engineering teams? This is stuff that we weren't talking about much. Or maybe if you really pissed off this CEO, maybe in 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 kind of avoided for that syrup era. Now we come like a core part of a lot of the job. It feels like also engineers of, they used to have a lot of leverage over companies, inside companies.
6:34Imagine that's also changing in a big way. I think that's true. I think this actually has been bad for engineers in some way. Like one of my like 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 I go, 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 this moment where we can actually treat engineers like our peers and put them in their really senior leadership roles and not have this kind of baseline assumption of the go.
7:09We have to cuddle 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 shift recently. 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 well. 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 and the middle management.
7:43Losing team members was huge, huge issue, right? And so you started to cuddle a little bit, which is actually bad. Again, bad for engineers, bad for the teams, bad for kind of everyone, bad for efficiency of the organization. But now like, there's something that I love. As we get to like give engineers real hard problems and 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 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, because we just want to retain all the engineers, we can't put them in senior roles.
8:21And so I think we're actually seeing a bit of the 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. 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 your 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.
8:46It'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? 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.
9:26And so what's a concrete example? At Stripe, we work 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 collect money successfully for the service that are selling. Stripe is 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.
10:01And it took us a while to figure that out because we were so stuck in the systems to key model. And it's not like, oh, the team was wrong. 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. You know, there's like measured twice, cut once, like, sure, but you don't measure infinite times and never 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. And I think a lot of people who get too far in the systems thinking make the same mistake where they think reality is wrong.
10:38And reality is never wrong. Reality is always right. Your model is always wrong if it's in conflict with reality. But the 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 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. Then you can go educate yourself and improve the model and just keep doing that.
11:12And at some point, like the model is close enough and you can stop doing that and go like, actually do the work. So 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. 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 do what you're talking about. This is probably a better place to start, right? Versus a rambling anecdote about using it. We can go and backwards. It'll be great. System thinking is basically, you try to think about stocks and flows.
11:45So 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 a lake. And so a flow between those two could be the number of fish in a lake will decrease that summary 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. We'll go down slower. But also then there's these flows, which kind of dictate that, where if you know, we got much more efficient, fishermen, the flow of fish out might go down.
12:23But 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, I 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 carcinogens or something low in the ecosystem or the food chain rather as they get consumed by predators further and further up, get concentrated.
13:00And 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 as they go up to the food chain, they start to concentrate it and an unexpected change can happen. So then going back to your example of the hiring pipeline, let's come back to that to connect this definition, which I've never heard, which is awesome. Very clear to how you actually implemented, say, and hiring. 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.
13:33And this could be kind of basically infinite. And then you have a couple of inflows. So you could have like source, 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 a number of sources you have dedicated to a role. So you have another stock of like how many of your 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 like conversion rate for people who pass the first recruiter screen.
14:06And that would move into step two of your process. 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 wanderin around LinkedIn posting about their deep thoughts, kind of convert, 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 candidate, there are a lot of pipelines. The biggest issue is hiring managers don't want to extend any any offers because the hiring managers can't get to confidence on any candidate.
14:40And you'll see in this pipeline, you'll see a ton of candidates getting to offer stage, but almost none of them converting from the potential offerer to actually offer. And then you can say, hey, hey, here's the problem. 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.
15:12You're actually doing a great job of making decisions, great job of closing candidates. They're just not enough candidates coming in. So by looking at this and you can build this model, then you can go to your your applicant tracking system, a greenhouse or whatever and pull the 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. 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. Because like, oh, it feels like we're not not hard enough on how we evaluate candidates or something.
15:49You go change a bunch of stuff. But often the real problem might be that the hiring managers are making offerer extensions to people who never pass the loop anyway. It's just that 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 happened a lot. And this just helps you take a complex kind of abstract problem and turn it into something that can actually work in a systematic way. I feel like product managers will naturally do it things this way already because a lot of them think and funnels.
16:23And 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. First, I start to question whether any function has a strategy in most companies. My general experience is that there's very rarely a written strategy for any company.
17:02Sometimes it's like a value statement. 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. I don't know what that means. And hearing often has this problem where I think people will make comments like in their culture amp or their quarterly surveys or whatever is like, hey, the strategy is not clear or where is 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 business has no strategy.
17:37And the reality is like product, 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, zilled in. Doesn't mean you don't have a strategy. You do have a strategy. It's maybe like a little bit harder to like articulate. And maybe it's like applied inconsistently across different like layers of the product like reporting chain because it's not written down. But like it's never true that there's like no product strategy.
18:10There'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. It's just sometimes it's bad. And the first rule of strategy is that if you write it down, then you can like, improve it. If it's not written down, it's hard to say like if this PM is just like not a good PM or if they're trying to apply the strategy that they misunderstood, or if they actually are correctly applying the strategy from the header product, that's just not appropriate. The problems are 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.
18:48It's a K the header product should improve the clarity of this document. Hey, this PM 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 kind of the first thing I think about. But the second kind of big theme on strategy I think about is that often good strategy is so boring. It's a hard hard to talk about. And so 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 you know, a lot of times you 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.
19:39And that Karta went 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, 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 the lines you with what the company actually cares about are really good for you even if they're a little bit annoying at a time.
20:16And I can extend on this idea a lot, but I won't ramble and definitely on it. 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. So first, what is the definition of strategy? And the best one I've ever seen is from Richard Romalt. He wrote good strategy, bad strategy. He's coming down the podcast. Amazing. He also wrote the crux. I think came out this year or some time, which which I also read. And I think both both great. And just like a phenomenal thinker who has so much depth.
20:52I 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 that thing that's impressive about Richard Romalt is you seeing so many different scenarios that he's able to really operate from both like 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 authors, but really amazing data set of how mega projects kind of succeed and fail. But anyway, Richard Romalt definition of strategy is basically three components. There's a diagnosis like what is the current status quo?
21:28Like what are the things that are real today? And there are guiding policies, which are basically based on the diagnosis, like how do you want to address them? And there's actions and actions are how are we going to implement this guiding policies? And he talks a lot about actions because he's concerned about this idea of like inner 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. 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.
22:00Yeah, I think strategy is more interesting on engineering in terms of kind 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 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. They're also meant that we're able to spin up in China in like literally three months. And some like surreal stories from that. We couldn't fit our racks into the data centers.
22:38They had like take the roof off the data center and like lift like that 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. But they left with like a nice and nice take a D .D. quality and not not not not a bad outcome overall. But I think that strategy, we run everything in data centers. We don't use the cloud. Met we were able to move in and out of different geopolitical constraints and companies that relied on cloud presence simply can't.
23:15They're Google cloud or Azure have built out. So that's one good example. Another good example at strike 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'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 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 in the stripe policy around, you know, Ruby monoliths, a lot of engineers hated these.
Read the full transcript
24:02But the goal of good strategy is not too long. A piece 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 towards that end. The 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. In solving the constraints, to me, I think the most interesting thing that that strategy really does. And I think when we talk about bad strategy, usually it's because the diagnosis is bad.
24:38And it's usually because people are sort of 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 that your guiding policies are going to go here and to be in with. Awesome. I'm excited for that episode of the 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?
25:24Is it read these books? Is there anything else? If people want to get good at strategy, there's a lot of different types of strategy, right? But here are some things that really recommend. First, I think the Richard Rumeil book, I think good strategy, bad strategy is probably the right starting point. I think the crocs 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. The big part of strategy is being able to model the reality so you can improve your diagnosis.
25:56And so I think that 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 McCahn and O 'Reilly. The Phoenix project by Kimber, Stafford, which is kind of a modern rewrite of the goal by Goldrat. 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. I also took a stab at it and Staff Engineer, my previous book.
26:36But I still think there's a missing book here. So I sort of see if that actually comes together. Well, I actually follow that thread of writing. Something I was definitely hoping to chat about. You write a lot. You've written two, three, four, four, four, four, four, how many books you've published? Two books and there's a third one coming out. So I have two books for the first one. The first one was Stripe Press. The second one self -published and the third one with O 'Reilly coming out in like two months effectively. Okay. And then also many, many blog posts for many, many years. And I asked a few people what to ask you.
27:15And this came up a lot. Gergay Oros and Alex Zhu from Bite Bite Go both asked just this question. Just how do you make time to write as much as you do? And then I also, I'll ask this too and just answered either first or second. It's just what impact does writing had in your career? Why has it been? Why do you keep doing it? 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 that I don't write for financial gain and I don't write. I don't write very much on like my 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.
27:59If the topic starts like missing, like you're 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, 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. We're conversely like when I own this schedule, when I get to like write about, hey, like I'm writing about something. So I started writing this infrastructure engineering book a couple 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.
28:30Maybe 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 like 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 the publisher. And if you are, I think, diligent and good at anticipating what their concerns are going to be, you can most do 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 like a really technical introduction to like my sequel or something.
29:12You can't just like, re -sequence 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, 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 and I don't write what I'm not thinking about and I don't write for any audience. Just write what is interesting to me and you know that that means some people don't like it and that's great.
29:48Like that's that's totally fine. 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 right. This episode is brought to you by Vanta helping you streamline your security compliance to accelerate your growth. Thousands of fast growing companies like gusto, calm, kora and modern treasury trust vanta to help build, scale manage and demonstrate their security and compliance programs and get ready for audits in weeks, not months. By offering the most in -demand security and privacy frameworks such as SOC 2 ISO 27001 GDPR, HIPAA and many more, Vanta helps companies obtain the reports they need to accelerate growth, build a fishing compliance processes, mitigate risks to their businesses and build trust with external stakeholders.
30:34Over 5 ,000 fast growing companies use Vanta to automate up to 90 % of the work involved with SOC 2 and these other frameworks. For a limited time, Lenny's podcast listeners get $1 ,000 off Vanta. Go to vanta .com slash Lenny. That's vatnta .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? I would guess about a thousand like that. That would roughly be my assumption. I think there are a few years where I wrote, you know, hundreds of posts and so if you do that like three years, it's not that hard to be to a thousand from there.
31:16That'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 cosine 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, crater life and they're like, what do people want? What do people want me to write about? What's popular? What's getting inspired? Go viral.
31:47And that's easy to do like a couple of times, but then you end up creating this job for yourself that you don't want. Don't be spending all your days writing about AI if you're not that excited by AI or whatever's hot these days. 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, it's going to do really well. Because otherwise you just burn out. You created a job for yourself that you don't want. Why would you do that?
32:13Yeah, I just 100 % agree with that. 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. 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 say something about it. It's almost certainly not what you're that knowledgeable about. Word, 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.
32:50The biggest risk is not that you grow too slow initially. There's always a sense that like you've missed the wave. It's too late to join substack.
33:03There'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's just like 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 can actually keep doing for the next decade. That's way harder than doing it for one year. We have the same exact advice on this. This is exactly the advice I tell everyone. When I joined substack, I thought it was too late. It was like, man, it's over. And when I started this podcast, like, oh, man, there's a billion podcasts.
33:36That was there 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 an easy letter. 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 not six from failure is just people that can keep at it. There's not like an end game to this. It's an infinite game. And it's about being able to sustain that over long term. And you're not competing with other other content creators. If you think of it as an infinite game, right, like you're all working together, you can all help each other grow.
34:13There's no maximum number of product writers or thinkers who can be doing something. You're not less successful. Because Shreya exists or something like that. There's no competition there. It's like a false, false dichotomy. Yeah. I totally agree with that. Unless there's so many. And then I'll send 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 got to get right is just the bar.
34:48You 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 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 new that no one's heard before or share new information. They haven't seen it anywhere else. I totally agree. I just I could keep ranting about this for for the entire I don't want to derail about this.
35:22But I totally agree. Well, 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? I used to do things differently before I had a kid. So I have a three and a half year old 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.
35:59So I think it's it's incredibly hard to find time to write about stuff that's nothing to do with your work. It's just this tracksuit from really 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 it urgent DM 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 or you do one either right or you do your job well.
36:36I think you can find a way to like align. And so a lot of podcasts 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 a 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 an alignment. So that's like one piece. But yeah, I've played around with my schedule a lot before I before I had a kid, often like Saturdays would be like the writing day. And so like you know morning and early afternoon would just be like writing. I can't I can't do that anymore.
37:08So so now I I'm mostly right 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. If you're not excited about it and it's 9 p .m. you're just going to 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 energy management like they 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 just doesn't make sense.
37:41Just to close out this thread for someone that wants to do more writing, those that it's going to be valuable, but just hasn't any one tip that you would leave them with to get on the string. It depends why people want to write. I tell people if you just want to like write something that is going to 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 a long -running blog or you publish every week.
38:12There's really no need to do that. If your goal is just to create some artifacts that show you're a deep thinker that kind of like help position you in the industry, don't start a newsletter. You just want to 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 goal is to write like a lot consistently over time, my biggest advice would be just just publish. There's a lot of people out there with like stuff that hundreds of drafts, they've not published anything. And my thing is like I publish almost everything I write.
38:48If there's something that I'm not going to publish, I don't start writing it because I just have like a quick check in my head. Is this something I can write and publish? If my answer is like no, I just don't even start. And my accuracy has gotten higher, go over time as they person more. But I publish pretty much everything I write. That's why some of it's not that good. And that's okay. I'm like 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 these different roles and different companies. I'm not writing, trying to create a polished, perfect thing.
39:22And also I'm not writing to maximize their readers' experience of reading it. And some people don't like that. And I think that's 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 for my books. The books are taking like a collection of thoughts over like a couple of years, cleaning them up a little bit, packaging them.
39:53They're way higher quality than my typical writing. But yeah, I've just published, published 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. 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. Just kind of like thank you. Move on to the next. Don't even don't even spend time worrying about it. And like that's 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, yeah, and like that's the worst case scenario.
40:29Basically, it's just like, I don't care about this. Not like, oh, will is such a fool. What a dumb thing to say. No one's, I'm going to start for that. And if they do like that, that's like that's a them problem, right? Like it's like there are the interests of big places 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.
40:58Like you don't have to take that on. That's like, that's not your situation. Like it's okay. 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 shut. Just do stuff. Like it only gets more stressful as you build audience over time. Yeah. Absolutely. Absolutely true. Okay. Shifting topics. There's a lot of product managers to 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 or productive, happy relationships with their engineers and engineers managers?
41:37So the core problem and most of the EM PM pairs 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 the 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 engineers 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 it's really important for me getting promoted or something like that.
42:18And is it ever this simple? It's really never that simple. 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 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 a business succeed.
42:49That doesn't work either. 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 before understanding. And so my biggest advice to both the EMs and the PMs, it's 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 being made in kind of the field.
43:25But my experience is that if you really deeply understand what everyone wants, there's usually like a compromised 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 the true needs for each party. Which is often like not what they're saying, by the way, which is part of the confusion. 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. There's uptime. Do you just work to change those latter definitions?
44:02Do you actually can help that situation? My biggest thing has been trying to force this idea that like EMPM pairs are pairs and they generally have the same performance rating. There's exceptions here. It could be the EM is clearly not performing. Then it's not the PM's fault if the EM is like, can't show up to work.
44:30Sometimes there's clear and non -performance. Hard situations are not situations when persons are 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 the overall execution is not working out, I think this idea that same per rating for both drives a level of one pain, but the right sort of perspective. Also something that I think Karta has experimented a little bit with OverTime. Henry RRCO has a blog post about trifecta's 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.
45:20Wow, 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 to be rating. And so they're discussed in the same. Yeah, the head of the Archief Product Officer, Bruce Schall, I like spend a fair amount of time like calibrating together and making sure, again, there's cases where there's an exception, because there's like 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's pretty powerful.
45:55That is so interesting. I've never heard of that approach that is definitely solving that problem of the MPM or 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. That is really interesting. And imagine some companies might even want to include design managers in that take it another step. You know, the role in the primacy of different functions in different companies, like various so much that it's hard to have a one size.
46:29You could also imagine where you want like a staff engineer and that or not. And so I think very companies specific. But yeah, I think design could absolutely be involved, particularly for like a design like company, like an Airbnb or something like that. Wow. So interesting. Maybe just as a final thought there, if 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, I never thought about that. I think one of the biggest challenges I've historically seen pretty in the last like decade is that idea that engineering managers have the job of getting their team interesting work.
47:10And I think that that can put, you know, you obviously, this is like growth teams where the growth teams like, hey, we just need to do like a ton of experiments. And then engineers like, I want to build something brand new. And the the engine managers in between those try to figure out like need to shift 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'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.
47:46And it makes the EM seem like totally on 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 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 this constraints versus just like, man, you won't believe what my EM partnered in today. Like this, this, those O did like, blah, blah, and having like sort of this like victim, villain kind of mindset about your peers.
48:24And a Jason topic that I want 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 NG 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 NG leaders for? And NG teams just for how to measure productivity well? This is a question that's coming up even more, right? In a moment when we're kind of reducing a lot of the slides of teams, one of the industry, one of the venture capitalists that are on the board for these like venture bath companies are pushing on the efficiency of engineering.
48:58Engineers 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? In math, 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 sending an R &D?
49:30How much should we be sending on? You know, infrastructure engineering in R &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. If you will 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 career ever. But you know, this idea that if you just have the right benchmarks, like DCs won't judge you for stendty 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.
50:07Which 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 on your organization effectively. So then there's like the much harder immediate problem with how do you actually know if your R &D team for engineering team is like effective. And what I find is a couple of things. First, if you're a good leader and you talk engineers, they will tell you like, engineers, no, 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 a crumb you can start like picking up and you can trace trace the crumbs to figure out what's wrong.
50:49They 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 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 your board. Oh, like it's fine. I talked to the teams that they're good. My intuitions spot on because how do they know if your intuitions good or not, right? They're dealing with like a huge portfolio and some of their leaders are talking to you are good and some of them have terrible intuition.
51:22How 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, um, well, we did a good job products like screwing up over there. Obviously a lot of companies find comfort doing that. But like really we're here to support the product to support our customers in doing like something interesting, but we're not here to like build novel systems unless it supports the customer and the end of product. And so first try to align heavily there.
52:02Second, I think just like showing the roadmap of the valuable things we've done in the last six months is really powerful. Because I think sometimes people 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, neither, meeting things that have 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 should be, they should be concerned about that.
52:36Is 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's always just like, give us this number, we're tracking, give us this dashboard, see what engineers doing. So one of the most influential books in the last decade in kind of software engineering leadership and kind of infrastructure is accelerated by Nicole Horzgren, 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 like four metrics. It comes up with like lead time, comes up with like incident remediation time, comes up with failure rate, and the fourth one of some sort.
53:18And there's like at least 50 different startups out there that are selling you dashboards that kind of instrument these pieces of data. And they want you to just evaluate your team on them. The challenges, 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. Just tells you where you should focus on improving. It doesn't actually change how how how you are. And similarly, if your lead time is quick or slow, tell us you where you should invest or doesn't actually tell you if you should like fire your engineers or something like that.
53:57That's like way more detailed specific. So people do like to see these metrics, just like they see a time metrics. A lot of engineers report on like sprint points or stuff like that to their board, which is like totally, totally fake thing to be like 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. You can tell you why every measure is wrong or inaccurate. And they rule everything out.
54:32So they measure nothing and they go to someone who's not an expert and they're like, well, actually, there's no accurate method to give. The not an expert is like, you're you don't know what you're really. 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 an opportunity to educate people on like 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.
55:04They're not about this perfect data set that shows everything. Starting with something mediocre and the door of 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 to 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 that can possibly measure.
55:36Awesome. 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. They 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 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.
56:07What do you share? What do you recommend to people that are trying to figure out what values they should define for their organ their company? 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.
56:39But I think those values did work well for Facebook and those values were meaningful for Facebook. And so it's first that you can't do is just like steal values. I value cargo, culting. Man, users first, great Amazon value, right? 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 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?
57:15Like 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 like applicability. Like you have to have values that you can actually figure out how to apply to your work. And so one of the stripes of 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 or interesting value.
57:51Sometimes you want to do something and you're like, hey, I want to introduce a new programming language because that's better for my team. We're like for the organization overall, this is actually much worse for 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 that opposite values, but they're both very applicable. It's like how should we navigate decision? Should I optimize for my team or for the organization?
58:21And then so those 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 move so fast because they just didn't worry. Wasn't there a value of toe stepping, encouraging toe stepping, something like that? 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.
58:59So there's some values that aren't actually usable. And so here's a good example on 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 we solve customer problems that matter. Like good, what, who would ever say they're like, what what company doesn't think they're self and customer problems that matter? And so there's certain 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.
59:38Like, great. But like, who would say they don't care about like, they're just like, there's certain values that I think of it just like identity values. And they're not like, they're not wrong to have identity values. You 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 type debating, like, what are these identity values? It's like 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.
1:00:10That 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 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, is probably actually not helping the team make decisions? 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 in these buckets is you need to be clear who doesn't.
1:00:40Like, 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, 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 to be safe? It's kind of like a cult a little bit. Like, who's not a narcotic? Who doesn't belong to it? But I agree. Like, if if it doesn't apply to anyone, then like, why bother saying it? It's like, it doesn't, it doesn't mean anything. And you could say it's actually a hiring filter where there are people who you've explicitly chosen not to hire, because this wouldn't apply to them.
1:01:13Then 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 just sort of like isn't worth having because you already have too many values. You are sure already trying to get rid of values who you have like 17 and you need to get down to like four where people kind of remember them. So if it doesn't apply to anyone, like why bother having it at all? Yeah. Like integrity is a common one. Integrity, like, everyone has nobody wouldn't want integrity. Like, what is unique? Yeah. We're the non -integrity company.
1:01:40Like, we were the company that like thinks integrity is bad. Like, that's like not a real thing. The other one I'll add to is honest. So there being B, 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 an 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.
1:02:12I wanted to visit a failure corner, something that I've added recently to this podcast or 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. Can you just tell that story and what happened and how much of a mess it ended up being? Yeah. Big P4 is, I mean, still, still something I have a lot of like 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, the middle of this giant office. And they're like serving like sushi.
1:02:50We had like waiters, caterers come in that day. They're serving like sushi. They have like plates with like champagne flutes on it. There was a bar. They were all around this table because the site's not up. And so dig before essentially what Kevin Rose or the board or some combination they realized is that dig was losing was losing to the sofa networks and that this idea of kind of aggregated news was going to be out competed by the the Twitterers, the Facebooks, etc. If we didn't find a way to move to have a social component for it, even out competed by Reddit long term was kind of the fear, although at the time that that was far from from obvious.
1:03:31And 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 in this the shift 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's more experienced I could have predicted this wasn't going to work out. But I was earlier in my career, my my PM counterpart at Yahoo .gov .noss. He went to Yahoo and he's like come to dig. Worst case you'll make a couple hundred thousand in a year.
1:04:13Worst 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 that 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. And so we we pushed really hard. This is before the cloud for the most part. So we wiped all of our pre -match 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.
1:04:55And so that day sitting around that table with like 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 like 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 really terrible way to do software on a side note. Like I'm not recommending this to anyone.
1:05:32This 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 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 to be 12 hours. And it was this incredibly simple issue that just in a hard to debug basically related to the way that Python initiates variables used as default parameters. And it's sort of something like super super silly. And we just had someone who hadn't written Python before who was working on the API code.
1:06:13So it 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. 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 you know what? The company still went to zero. And so we had this that 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 around the layoffs. This is back, I think like 2012.
1:06:50The team nine months after I started was down to like 30 people from about a hundred. And they just went, it went downhill from there from a from a business perspective. But we launched a lot of functionality. It's really one just a tremendous amount. And they 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 the engineering work.
1:07:32It 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. And I learned so much. And I really like that that's like the the kernel that like turned into like my entire career was that opportunity. Even though at the time it was that it was pretty pretty grim. 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. And of being the most interesting and looking back into being the most biggest teaching experiences. The ones you like bond over with people you work with.
1:08:04Like Apple always comes to mind where it's just like Steve Jobs's Joe people like crazy. And then they look back. And that was the best moment of my career. 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 I over China was similar or like if someone had been like hey do you want to go work on this over China vibration. I would have been like absolutely not.
1:08:33But like no one asked they're just like get this done. And so we did. And I think these things are like pretty remarkable. And just to be clear. So Dick was down for a month basically during this period. Is that so it basically didn't work properly for for much of the month. It was like read only was back up in like about three days. But the vast majority of the actual like user functionality just wasn't working properly for pretty much an entire month. And it was not not that good. I mean like not not great. But you know that wasn't the biggest problem with Dick had at that point. But it was one of the biggest problems that had at that point.
1:09:12And it wasn't it wasn't a real sign of 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 in the team like got it working got it got it running. Even if like ultimately like we still went to zero and like ran out of money and kind of sold the sole for parts. Do you think Dick could have made it? There was a world where Dick would have been a hugely successful business. Or do you think it was just way too late and it was the product? The thing that really killed Dick is the the change it was an SEO driven like so monetization was from ads.
1:09:46Dick was the well many companies including Dick claimed that it was the first in kind of stream in fee like advertising company like where Twitter has like ads within like the tweet surface but does that but Dick did that before they took or Twitter really innovated can the ad format. But the vast majority of our monetization was on because like we called them permalink 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 the thing that started creating the urgency for us to launch this migration.
1:10:20SEO 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 Dick 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 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 then successful as businesses.
1:10:55And I do think there's a gap there still but there's a lot of people trying on successfully to fill it and and there must be a reason why people struggle to fill it. Despite somebody will try it. Awesome. Will is there anything else you want to share or leave people with before we get to our very fast lighting round because I know you have to run in about five minutes. I think we've covered a lot of it. New book coming out, new book coming out in February uh engineering executives primer O 'Reilly but that's probably it. Awesome. Where do people find that? I know it's on O 'Reilly. You can look at a preview of it even today, right?
1:11:29Yeah. O 'Reilly can see that the early copy you can order it on Amazon as well but it won't be shipping until on February. Okay and then just to be clear who's this for it for engineering executives by the sound of it. It's for engineering executives but but more so like anyone who wants to be one, anyone who's trying to figure out how to work with the 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 ahead of product and you can't get CTO to stop complaining about the engineers need more interesting projects to work on.
1:12:03That this might be useful for you too. Amazing. Okay. Ready for the lighting round? Let's let's do it. What are two or three books you recommended most to other people? 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 Lekoff. It's a really interesting book about framing things and conversations that has really changed how I communicate. Amazing. Favorite recent movie or TV show you really enjoyed? I don't watch much TV or many movies anymore but something I do still watch is Top Chef with my wife.
1:12:34She's a Top Chef super fan and there's something just like very relaxing from like this formulaic structured shows where you kind of know what's going to happen. There's no real consequences that matter too much and just kind of escaping from real life. These like formulas can be pretty pretty useful. Everyone'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? A lot of my interviews now are trying to help people decide if they actually want to join a company and so my favorite my favorite question I ask now is like hey we've really loved you.
1:13:09You'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 like pitch them on what matters versus pitching on things that don't love that. Do you have a favorite life motto that you often come back to share with friends find useful either in worker and life?
1:13:39No, no, no, motto is that I can think of like two two things I thought about a lot. At Uber or something I talked to people a lot because it was a challenging time for much of 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 like gut through it and we're going to get the other side and then 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? 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.
1:14:11So I'm like well anyone cares in six months what we did here and the answer is no like just do something reasonable and like let's move on the next more important thing. I love that you've done a lot of writing. Is there a piece that you've written that you feel like is under appreciated that no one really totally got and hasn't spread and you're like I'm so proud of that one. Maybe the piece I'm most proud of from 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 their view it 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 it was holding people accountable.
1:14:55People 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 never you like talk about like honest value is 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 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 there's 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 I think this is one that I you know hope to more people would hope more people will read over times because they're really important lesson for me in there.
1:15:41Well we will link to it in the show notes and help more people discover it. Two last questions we're gonna focus finding online if they want to reach out and maybe follow up on questions and how can listeners be useful to you. So find me online on lathan .com lehtan .com all my writing my books everything links linked there and the biggest thing that I think about right now is just strategy. So really curious for folks who are thinking about strategy you think they've done product business or engineering strategy well we'd love to hear from folks what they're thinking about what's actually works and maybe what are the lies that have not turned out to work that they thought might work earlier in their journey.
1:16:19Amazing. Well thank you so much for being here. Thank you so much this is this is really fantastic. 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 lenniespodcast .com. See you in the next episode.
From the publisher
Will Larson is 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. 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
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Find the full transcript at: https://www.lennysnewsletter.com/p/the-engineering-mindset-will-larson
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Where to find Will Larson:
• X: https://twitter.com/Lethain
• LinkedIn: https://www.linkedin.com/in/will-larson-a44b543/
• Website: https://lethain.com/
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Where to find Lenny:
• Newsletter: https://www.lennysnewsletter.com
• X: https://twitter.com/lennysan
• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/
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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
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Referenced:
• The end of the “free money” era: https://www.theguardian.com/technology/2023/apr/11/techscape-zirp-tech-boom
• Work on what matters: https://lethain.com/work-on-what-matters/
• Sheryl Sandberg to Harvard Biz Grads: “Find a Rocket Ship”: https://www.forbes.com/sites/kashmirhill/2012/05/24/sheryl-sandberg-to-harvard-biz-grads-find-a-rocket-ship/?sh=708c9a93b37a
• What Is Systems Thinking?: https://www.snhu.edu/about-us/newsroom/business/what-is-systems-thinking
• Introduction to systems thinking: https://lethain.com/systems-thinking/
• Thinking in Systems: https://www.amazon.com/Thinking-Systems-Donella-H-Meadows/dp/1603580557
• Silent Spring: https://www.amazon.com/Silent-Spring-Rachel-Carson/dp/0618249060
• Writing an engineering strategy: https://lethain.com/eng-strategies/
• Carta: https://carta.com/
• Eric Vogl on LinkedIn: https://www.linkedin.com/in/ericvogl/
• Good Strategy/Bad Strategy: The difference and why it matters: https://www.amazon.com/Good-Strategy-Bad-difference-matters/dp/1781256179
• The Crux: How Leaders Become Strategists: https://www.amazon.com/Crux-How-Leaders-Become-Strategists/dp/1541701240/
• How Big Things Get Done: The Surprising Factors That Determine the Fate of Every Project, from Home Renovations to Space Exploration and Everything in Between: https://www.amazon.com/How-Big-Things-Get-Done/dp/0593239512/
• Technology Strategy Patterns: Architecture as Strategy: https://www.amazon.com/Technology-Strategy-Patterns-Architecture/dp/1492040878/
• The Value Flywheel Effect: Power the Future and Accelerate Your Organization to the Modern Cloud: https://www.amazon.com/Value-Flywheel-Effect-Accelerate-Organization/dp/1950508579
• The Phoenix Project: A Novel about IT, DevOps, and Helping Your Business Win: https://www.amazon.com/Phoenix-Project-DevOps-Helping-Business/dp/1942788290
• The Engineering Executive’s Primer: Impactful Technical Leadership: https://www.amazon.com/Engineering-Executives-Primer-Impactful-Leadership/dp/1098149483
• An Elegant Puzzle: Systems of Engineering Management: https://press.stripe.com/an-elegant-puzzle
• Staff Engineer: Leadership beyond the management track: https://www.amazon.com/Staff-Engineer-Leadership-beyond-management-ebook/dp/B08RMSHYGG
• Gergely Orosz’s newsletter: https://blog.pragmaticengineer.com/author/gergely/
• Leaving big tech to build the #1 technology newsletter | Gergely Orosz (The Pragmatic Engineer): https://www.lennyspodcast.com/videos/leaving-big-tech-to-build-the-1-technology-newsletter-gergely-orosz-the-pragmatic-engineer/
• The art of product management | Shreyas Doshi (Stripe, Twitter, Google, Yahoo): https://www.lennyspodcast.com/videos/the-art-of-product-management-shreyas-doshi-stripe-twitter-google-yahoo/
• Henry Ward on LinkedIn: https://www.linkedin.com/in/heward/
• Vrushali Paunikar on LinkedIn: https://www.linkedin.com/in/vrushali-paunikar/
• Accelerate: The Science of Lean Software and DevOps: Building and Scaling High Performing Technology Organizations: https://www.amazon.com/Accelerate-Software-Performing-Technology-Organizations/dp/1942788339
• How to measure and improve developer productivity | Nicole Forsgren (Microsoft Research, GitHub, Google): https://www.lennyspodcast.com/how-to-measure-and-improve-developer-productivity-nicole-forsgren-microsoft-research-github-goo/
• DORA: https://dora.dev/
• Setting engineering org values: https://lethain.com/setting-engineering-org-values/
• Digg: https://digg.com/
• Kevin Rose on LinkedIn: https://www.linkedin.com/in/kevinrose/
• Digg’s v4 launch: an optimism born of necessity: https://lethain.com/digg-v4/
• Dash Gopinath on LinkedIn: https://www.linkedin.com/in/dashgopinath/
• Rich Schumacher on LinkedIn: https://www.linkedin.com/in/richschumacher/
• The ALL NEW Don’t Think of an Elephant!: Know Your Values and Frame the Debate: https://www.amazon.com/ALL-NEW-Dont-Think-Elephant-ebook/dp/B00NP9LHFA
• Top Chef on Peacock: https://www.peacocktv.com/watch-online/tv/top-chef/5172289448907967112
• Hard to work with: https://lethain.com/hard-to-work-with/
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