The Pragmatic Engineer - The revised rules of engineering management with Will Larson

Episode Date: October 21, 2026

Brought to You By:• turbopuffer – a vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable.• Entire – Git hosting, rebuilt for the agentic era. Every agent session, prompt and tool calls: stored in your repo.• Antithesis – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages.—What’s changed in “the unwritten rules” of engineering management since the 2010s, what drove the shift to today, and what has it done to the engineer-to-CTO career path? Today’s guest is one of the best people I know who can tackle these questions.Will Larson is CTO of Imprint, was an engineering executive for 10+ years, and is the author of several popular books on engineering leadership, including ‘The Engineering Executive's Primer,’ ‘Staff Engineer, An Elegant Puzzle,’ and ‘Crafting Engineering Strategy.’ Previously, he was also CTO at Carta and Calm, and an engineering leader at Stripe and Uber.In this episode, we explore how engineering leadership has evolved from management practices shaped in the long post-financial-crisis ZIRP era to the altered expectations of engineers and managers today.Is middle management an increasingly precarious career path, and might managers need to reskill and return to hands-on technical work – or even consider retirement? Will makes the case, and we hear why the traditional path to engineering executive roles is changing, as well as why taking one step backward might sometimes be the best way forward.We discuss Will's early career, and get his first-hand account of Digg's disastrous relaunch, his own path to CTO, and he tells us why career ladders still matter. We also explore how AI is changing engineering roles and bringing technical decision-making back to leadership.Timestamps00:00 Intro08:20 Stories from Yahoo!12:47 Digg’s v4 rewrite: the insider story26:02 Will’s path to eng leadership30:03 Uber, Stripe, Carta, and Calm35:11 What does a CTO do?38:09 Will’s role at Imprint42:48 How engineering management has evolved51:08 ZIRP’s impact on tech57:21 Career ladders1:01:03 Eng 1 vs Eng 21:06:58 How software engineering roles are changing1:16:25 Revised rules of engineering leadership1:21:57 The risks of becoming a bureaucrat as an EM1:25:57 How to become a CTO?1:31:33 Middle management vs. line management1:41:36 Will’s writing1:52:13 Book recommendations—The Pragmatic Engineer deepdives relevant for this episode:• The end of ZIRP and what it means for startups and the tech industry• Getting an Engineering Executive Job – an excerpt from Will’s book, The Engineering Executive's Primer• What is a Staff+ Engineer?• Inside Stripe’s engineering culture • Engineering career paths at Big Tech and startups • Staying technical as an engineering manager• Performance calibrations at tech companies• Scaling Uber with Thuan Pham (Uber’s first CTO)• Hypergrowth startups: Uber and CloudKitchens—Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [e-mail]. Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe

How has engineering management changed in the last few years? Will Larson is one of the best people to talk about this. He's been an engineering executive for the last 10 years at four different companies, wrote some of the most widely-ledered books on engineering leadership and saffplus levels, and I really appreciate how deep and thoughtful of a thinker he is. Today we cover how zero interest rates heavily influence a decade of management habits in the 2010s, many of these habits are no longer helpful. How the role of engineers is changing and why solving problems that the business cares about

is becoming much more important to thrive inside of companies. The path to becoming a CTO today and why line managers often make better engineering executives than minimal managers do, and many more. If you're an engineer or engineering manager and are wondering what your query path could look like with AI changing the industry and how the path to CTO looks like today, this episode is for you. This episode is presented by Turbo Buffer, a ridiculously scalable, fast and cheap hybrid search engine built on top of object storage by an engineering team that I've really grown to like after spending time with them. The turbopuffer engineering team is doing something really cool.

They are completely redesigned their storage architecture from purse principles to make sure it's faster, cheaper, and more reliable at scale. The new system, called turbopfer V3, is not yet in prod, but it already passes CI. Still, it's not nearly as performance as the current production version, V2, and so the T-Buff team is now perf-maxing query plans until they are as fast or faster than V2. They are doing all of this in public documenting how they increase performance all the way up to the V3 production launch. And it's so cool to follow along and see the different performance wins

and how they did it. For example, we see how Fultex search, the red line, started out as 129 times slower than the current system. But now it's only four times slower. And in the development log, we can also see that the team use things like batch scoring or batch reads to increase performance. A lot of these wins are basic foundational work right now,

but the team will be sharing some very cool systems work over the next few weeks. But hang on, why is the team doing a floor rewrite? It's because search is changing and so is TurboPuffer. TPUFs start as a vector database, but it's no longer VTB. It has evolved into a high-performance database for search. The V3 discards the vector primary index, and all indexes will share the same columnar source system. Every query will run on vectorized query engines, which is something you don't usually see in search databases,

but which will result in both very fast search and just generally a very fast database. The TurboPuffer team is keeping a work log of their journey, and you can follow along at turbopuffer.com slash v3. It's a blast to see how it's being built. Will, welcome to the podcast. Thank you for having me. Excited to be here. Finally chat in person.

Finally in person, because we know they should have for so long. Both started writing. We will talk about that writing as well. And also just hung out before, but this is nice. I wanted to jump into the beginning. How did you get interested in computers?

Were you interested in computers to start with? From the time, I was five. We had like a Mac 2C or something like that. This was like a not, not black and white, not the very earliest one, but it was pretty basic. And I think it had like one thing that I understood how to use as a four and a half or five-year-old, which was like kid picks, which you've maybe, I don't, did you ever use to see kid picks? I didn't, I know of it, but I never used it. It wasn't like a super sophisticated thing.

I don't even know if you could save files, but it was basically like a graphical program for children. And you could make squares and circles and little like graphics. But that was kind of the introduction to me. And I remember using that computer a lot. And like that this is an era. One's really no internet to speak of, really no way to figure out how to do anything other than just banging on it, which is sort of the fundamental of writing software in some ways. It's just banging until you figure out how to make it work. I think that was a great introduction.

But to be honest, I wasn't doing a whole lot in like software other than, you know, multi-user dungeons. Did you ever like play a mud growing up? Multi-user dungeon. No, what's a mud? It's a text-based game. And so basically the idea is that World Warcraft is actually a graphical text-based game. We basically derive from these ideas of muds or multi-user dungeons. But when I was a kid in high school, that's when I started doing more software.

So a little bit, you start with IRC, Internet Relay Chat, and Merck, which I don't even know what the M stood for it. To be totally honest, I suppose a client, you could do a little bit of scripting with Reg X's, but then a lot of the mud clients as a kid could do a ton of triggers, reg X's and that's where I got it a little bit further into it. Learn my rexx is there, but really I didn't start writing software at all until I got to college. And then at college, what did you start writing? How did you get into a more serious level? So came into college not really knowing what I wanted to study and I thought it might do physics or English or, you know, economics. My father was professor of economics. So there's some family, you know, lineage to try to love up to. But ultimately, I kind of fell in the computer science at my school, which was a small

kind of private school in Kentucky. There were, I think, 13 people in the computer science program the year that I graduated. So, and that was like the entire program. So I think there were four graduates my year. And then like the juniors and sophomores in total were like 13. And so it's quite small. So I think there were four that graduated my year. But yeah, but really that was when I got into it and why I just enjoyed how to intro course that we're required to take. And it's kind of funny with a lot of American colleges, especially smaller private ones. They have random kind of requirements. So I was required to take an introduction to Christianity course, like at the history of Christianity, but also required to take like an introduction to computer science or some of their course. I forget

what the other alternative was. So I really enjoyed the computer science one. Did you decide that you're probably going to be a professional software, developer, engineer, programmer, whatever we call it back then. So I think one of the interesting things when you talked a lot about careers is like a lot of folks go to like elite school. So you talk to someone from Waterloo and they go, how did you get your job? They're like, well, literally everyone at Waterloo is coached on how to go do software. They're literally trading the answers to interviews with each other. So they know the interviews and drill on the interviews before they go in. They also like amazing program. They've been doing co-ops for years. They're great. They're great candidates. They tend to do really well. But go to Waterloo,

to MIT, you go to Stanford, you really, there's like this path, and you just kind of put your foot on it, and you do well, and it carries you there. And these are amazing students. It's like an escalator almost. But it is an escalator. If they're good enough to stay in the program, they tend to kind of get there. Going to a small school with, again, like four-ish folks that graduated my year in computer science, there really was no path. I remember one of the, one of the folks that graduated the year before that was working in software, he went to go work on a horse racing bedding software company in Lexington, Kentucky, which I don't think there were more than like five engineers there. And this was like a really talented, really capable person. And this is kind of what they knew

how to find. And so for me, it actually was interesting. I wasn't quite sure what I was going to do. I actually ended up teaching English in Japan on the Jet Program, the Japanese Exchange teaching program. So I was in the middle of nowhere in Japan in the Gifu Prefecture for a year. But that's when I really started writing a lot. So I was like, hey, I'm definitely not going to be. an English teacher for more than one year to one year contract. I did that one year. I had no thoughts about doing a second year. And I came back and started trying to figure out how to actually break into Silicon Valley from there. And you have the goal breaking Silicon Valley already. Why Silicon Valley? Can you take us back to what Silicon Valley was like back then?

First of the time, I didn't know what Silicon Valley was, right? I just wanted a job that that paid well. And I think, you know, this was, so I graduated in 2007, and then the next year I was teaching English. And then I actually started working for Yahoo in, I guess, maybe early 2009, something like that. Really interesting time, though. So initially, I was working for Yahoo from the East Coast as a remote contractor. It was an interesting moment. So I started working with Yahoo! Because I wrote a series of blog posts on something called Yahoo Boss,

just build your own search service. And this was a product that they had launched on this one team. I think it wasn't getting a lot of kind of traction in the industry. But when it launched, I was writing a lot. So I did three or four tutorials on building boss things in Python, boss things with Django, kind of made a Django. Forget the name. It might have been Django Springsteen.

It was like the name of the search library to use Yahoo boss with Django. And so I think they got excited because someone was writing about it, which also got me excited. And that ended up ultimately in this contract job. And then ultimately they had the policy where you had to move after a year. as a contractor and go full time. And the reason I was hired as a contractor, though, is they had a hiring freeze for basically that entire year. Because this was right after a financial crisis. And so they're just going through layoff after layoff. And so they could hire a couple contractors. Couldn't

hire anyone full time. And then at 12 months, they are like, hey, now you have to go full time or you're not employed because there's kind of the compliance obligations to avoid. And so they're like, hey, and if you go full time, you got to move. And so basically I had a job at Yahoo. If I moved, or I didn't have a job at all. And so I moved from the East Coast out to California. Pretty easy at the time. Didn't have a lot of obligations other than employment. Yeah, and back then Yahoo, I guess, their star was kind of fading with Google,

but they were still pretty good company, right? Good engineering talent. Like WhatsApp founders famously came from Yahoo. I think Yahoo, honestly, is a really interesting company, right? And so I think one of the challenges for Yahoo is if you came into tech in 2007, 2008, a lot of open source sort of made things easy. Yahoo, though, is a company that predated all these open source libraries. And so how do you run a server at Yahoo 2007, 2008?

You run Y Apache. So they had their own fork of Apache with a Y in front of it. What programming do language do you run on Y Apache? Well, of course, you would run YP, which was their fork of PhP. And what UI library would you use? You might know this one, but it's YUI. And then how do you install things? So if you think about like, you know, a month

you'd have kind of like APT or whatnot, well, you'd use Yinst, which was this pearl script that would navigate kind of the dependencies for installation. And so there's like really, really fascinating place to come up. But every single thing there they made from scratch. Even they had like a precursor to Kafka, which I think was called YREPL, which basically would do like a read log to do replication

kind of outside of a database. And that was like a core tool, for managing state, just like a fascinating place. And I think if I just had one quick Yahoo story that I loved, so David Philo kind of famously approved every server that was allocated in the company. And so one of the founders, like, would review. And so the theory was this would drive accountability, right?

You had to prove you needed more servers. What it actually did is it created like the black market of servers. And so on my team, there was like one engineer that had 30 servers from a prior canceled project. He never gave back. And so he would basically sell them to you effectively, right? And so if you couldn't get approval. For like favors and IOU and that kind of stuff.

And so it actually meant they had massive numbers of outdated servers that were like using like inefficient like power wattage because people would never give servers back. And so you had to find like someone who liked you with servers to loan for your projects to launch. Like fascinating how these incentives drive just like wild, wild situations. I guess that's one thing. you remembered for when you later became an engineering leader. Yeah, it was very instructive, right? And I'm sure, I'm curious, like, did David Philo know that people literally had a black market of servers?

Like, I assume he probably did know, but didn't change the kind of the top-down mandate. After Yahoo, is that when you ended up at Dig? Yeah. At the time, very famous company for a very amusing story. Can you tell us about, like, how we decided to switch? Because it was a startup, right? dig was a startup back then. So depending who you talk to, there were going to be different narratives, but I think the dig narrative is basically, it was like the before Reddit, it was the big

community site, but it was centrally curated. And so Reddit had these sub-communities, where the communities kind of voted with the algorithm on what they wanted, the Reddit algorithm. Dig was actually centrally curated on what went on to the front page. And so I had like a very different experience. But it also meant that the quality was consistent. And, you had less of kind of the bias and subreddit problem. Instead, you had a bias in central moderation problem. And there were, you know, communities, there are IRC channels where people would basically trade favors trying to get things on to the dig front page. And in fact, for Dig before, we changed the algorithm. And I had people saying they had come murder me for stealing their livelihood,

because their entire, you know, livelihood was selling access to the front page. The new algorithm didn't support that, and they were literally threatening our lives. And so it was a fascinating place. But Dig was a really important website. And, you know, when I joined Yahoo, this wasn't true, but a little bit before I joined Yahoo, literally the front page of Yahoo was a static file on a net scaler, which was basically like a filer, which is like a way to store files. And Yahoo Sports was just like a static page, right?

And so Dig in that era, like early on, was like a very important static page. But then it became not a static page, like a dynamic of sorts community. I think really was extremely important to folks at the time, though it's faded into slightly less relevancy over time. And it's been restarted a couple of times since, but never really picking up the traction once did. I think it was a top 10 website at one point. Yeah, it was top. And that's why the story that I remember is they did a big rewrite. I think it might have been a V4 one, right?

And from the outside, what I remember is, well, Dick was doing good. It was popular. There were complaints, a bit like with Stack Overflow, maybe a few years ago. And then Dig did this massively right and disaster followed. And it was like a very juicy story.

Everyone was talking about it. Can you tell us like what actually happened and what did it look at from the inside? Because you were building this thing. Yeah. So I was there. I was there for that launch. And I was there after that launch. And so I joined Dig about three to six months before that launch went out.

And it was a fascinating time. So I joined. And then the Friday, before I started, the CEO got removed. And then Kevin Rose came back in as CEO. He was a founder, right? Kevin Rose was the founding CEO. He was there for a while. And then he kind of stepped back.

And then he came back in. But he came back in and we had this, you know, very hard deadline to launch DigB4, which was a rewrite. And so Dig V3.5 was the prior version before Dig4. basically entirely a PhDB software running on distributed MySQL. And this was like a different era, right? So Dig was running on hardware that we owned in like a Kolo. And so it wasn't like just spin up some capacity or whatnot.

But Dig V4 was trying to solve a bunch of problems. But first and foremost, the internet was changing at that time. So this dig at one point a top 10 website was starting to lose traction to Facebook. and it was starting to lose search traffic as well. And so there were a series of large Google changes, and I think we don't hear about Google search algorithm changes that much these days. But back then, there was like the Google Panda algorithm change, and there were a handful of others.

And they were starting to really reshape how traffic flowed through. So for a company like dig, a substantial amount of the traffic, I want to say like 60 to 70 percent, the traffic is actually coming in via search into something called the permalink. And so the permalink pages would be, like, say you'd write a great blog post, that would then get posted to dig, and then we'd have the reference to the permalink and also like a small link to your site, of course, and comments about it. But we would take a ton of traffic through these permalant pages that would be higher page rank than the original source themselves. And you can argue, like, now, like, maybe we shouldn't have then. Probably not. I think that would be kind of the perspective today. But from the perspective of that moment, like, we were actually creating the discoverability and the conversation around it.

This was before Twitter. This was before Facebook got, like, substantial distribution. This was really early moment. And so for us, like, that was the core of where people came into. Also, it was really where we sold the most ads. And so losing that traffic was basically tanking the company's, like, financial kind of prospects. And so dig before, from the outside, dig was working pretty well. It was, you know, seemed like maybe it was growing.

But really, like, what we knew is, like, dig was shrinking. We had one beautiful month of profitability, and then an algorithm change hit. And we started shrinking. And we knew that this is existential for us. We were going to simply not exist, not that far down the path. And we were, when I joined, I want to say, 110, 120 people, something like this. But this was in 2010 when funding rounds were a million dollars or three million dollars or something. It's not like today when people are raising, you know, $500 million and you can have a team of however many.

It was a very different moment. So even with 110 people, that was pretty substantial when we were running down, you know, the remaining coffers pretty fast. The launch, in turn, did it go poorly? Did it go well? Because from the outside, again, there was a perception that it went terribly. And people, there was a bit, I think a lot of it was the community was upset. And then there was a bit of celebration as well. like, well, they messed it up, like, they kind of deserve that.

You know, the mob, the people, especially who were very involved, they didn't like change. First, there's like a really fascinating set of cartoons someone made was just like Dig versus Reddit and like Dig is like blue and then like Reddit's red and there's this like giant war that someone did like a four or five part. It's like this very intricate comics someone wrote around this time. And it is kind of interesting to see how much energy people put into it. But yeah, there was a lot of passion and I think it's one of the challenges of like a really passionate community. is like when you foster a passionate community, then you change what you are. Community doesn't like that.

Because, I mean, there are literally these folks, like Mr. Baby Man was like a really big one, like one of the top. Did kind of curators, unsolicited curators of content getting to the front page. And he and many others were, they lost kind of their business, right? But the launch went pretty poorly.

And why did they go poorly? They went poorly for a lot of reasons. So first, the launch technically wasn't really ready. And so we made a lot of really aggressive technology decisions. And again, I came in about three months before this went live. So I don't personally take a ton of responsibility. I also again, thinking about where I was in my career. I was basically was my second job. I'd been at Yahoo for two years. So I won't own this one. Later my career will own anything that happened. But this one wasn't really by fault. But basically, we made the decision to launch on Cassandra. And there's like a joke at the time, which is that Cassandra, was a Trojan horse basically ruined competition in the industry. Because anyone who launched on Cassandra was basically screwed afterwards, which I think certainly was true for Digg. And so running Cassandra to replace the Sharded MySQL system.

The sharded my SQL system was pretty complicated, but it definitely worked. And to Sandra, I would argue, like, basically didn't work. But I remember there was a team response for load testing Cassandra before a launch. and two days before the launch, this other guy, Rich, who was fantastic, he and I were pulled aside and were like, hey, well, they never did the load testing. The two of you to do the load testing before, you know, in the next two days. And so Rich was just like a software engineer like me. And so we're like, well, I guess we'll like install J meter and try to figure out how J meter works to do some load testing. And we had this like really interesting conversation with Chris, who's kind of the head

of the Cassandra initiative. It's like, hey, like, I can't do the reeds on. on Cassandra. He's like, that's not true. I was like, well, I can't do the rights. He's like, that's also not true. I'm like, okay, Chris, if I'm writing to Cassandra, I can't read from Cassandra. If I'm reading from Cassandra, I can't write to Cassandra. He's like, that is true. It's like, we're supposed to launch in two days. And then we launched and we didn't fix it. We just launched. And so I think the company thought that we were literally dying. And the company was, the company literally was done. It was running out of money. But it was, like the most interesting day I've ever had professionally. Can't remember when I got to the office,

probably around 8 a.m. Wouldn't you say interesting, even stressful? You can judge. Let me like paint the scene a little bit. So it was a launch, but they also decided to have a launch party. So the entire day, there were caterers kind of in tuxedoes with like sushi trays, champagne. Oh, wow. And so like the entire office was there to have this like kind of like celebration.

And then in the center of the room, there was this like table. It might have been like a boardroom table or something that been pulled out, this giant table, maybe three or four times the size of this. where the engineers were sitting. And we didn't have enough hardware to run the new system and the old system concurrently. And again, this was hardware we owned. So they were literally wiping the old servers

and installing the new software. So we couldn't roll back. We didn't have the money to, or the, and again, we were running out of money, but enough budget for the party, but like not enough budget for the servers, right? So we were wiping server by server, spinning it up.

And ultimately, like, the damn thing didn't turn on. It was functionally, what happened, right? And so we had this, you know, like down for maintenance page up for, I think, roughly 24 hours. And then we're able to scrap it while the champagne and the tuxedos are coming around. Surreal. And there were people upstairs getting massages. There were, you know, I remember certain groups who won't be named playing ping pong while we're trying to get this up. And it was, it was just like, it was sort of like a magical realism. I see what you mean by interesting. This is not how

I imagined a launch like this. You could never imagine a launch like this. It was just, it was so, it was so surreal. True like a magical realism moment where there's kind of all this normalcy happening while this like site's literally imploding. And it was just, it was unlike anything I've seen, but it's also like a moment I take a lot of pride in. And so I'd been there three months. I think interesting thing is we did get the site kind of working, but there were a lot of issues. And so people just gave up and like day by day, like people just stopped showing up. And like a small group was really the only group left of maybe like six people trying to keep it working. And we did. And so we, in the first two days, like the same guy, Rich and I wrote like a caching system from scratch on top of Redis, which helped the site stay on for hours.

Yeah. But we still had huge memory leaks. And so we're actually like restarting every process every, you know, like hour or two. And the only way to keep it up was rolling restarts of every, every process. And so it took us, it took us like a full month. debug, and I have like a blog post I wrote a long time ago about it, but basically the core bug was we created an API service that could be used for like third parties, and it was in Python. The people writing it didn't know Python very well, and this was Python then calling like another

Python gRPC that was hitting Cassandra. And basically, in Python, when you instantiate a default parameter, if it's mutable, I don't know if this is still true, by the way. I hope it's not so true, but at the time it was true, where if you basically put a list as a default parameter, and then you mutated it, like appended IDs into it, it would persist in memory. And so each time that function was called would have the same dictionary, or the same list. And so the memory of the user IDs, basically every time they call this API to lookup user IDs, they get the user objects back, all the users that were ever passed into it would still be there.

And so it just cascaded over and over and over until we restarted. And we installed Memcash, kind of in between these, and the Memcash would start falling over, and then it would, you know, destroy Cassandra. So really finding that bug, it took me, I think, four weeks to actually find it once you found it trivial to fix, but we got it up. And then our new CEO started, I think, that basically the same day that I fixed that, and then we, you know, basically the entire company got laid off over the next year. So, yeah, pure a victory in the sense that we did solve it.

It was working, but I think you can't really have the central site be hard to use or down for a month. But like if you go to the counterfactual, what would the company have done differently? If they had simply kept up the old site, they also would have died. Right. And so I don't know that they made the wrong choice, but at the time, I certainly was pretty, pretty salty about it. Yeah. How did you eventually get into enduring leadership? I know you and me overlapped a little bit at Uber.

Actually, we both worked there, but we never worked together. So the kind of the end of the dig story was we got acquired. And so they sold the patents for, Dig did a lot of like innovation. So like in ad, or in stream ad units, basically like you see it on X now where they'll have like an ad that kind of looks like the stories from people that are posting. They dig owned the patent to that. They were the first company to do it. They own like a variety of other patents.

And so the patent portfolio got acquired by one company, dig.com, like the actual like brand and the website got acquired acquired by, I think BetoWorks. that in New York at the time. I think they've sold it subsequently a few years ago. And then the team got acquired by Social Code, which is like a third company, a subsidiary of the Washington Post Company from the time when that was a holding company

that owned the Post Kaplan and this company's Social Code, which basically did advertising on Facebook. And so the team went there, and I was there for a couple of years. But when I left, I was thinking about, okay, I want to be kind of an engineering leadership, but I can't get hired into a really large role because at that time I was managing maybe a team of 12 engineers or something like that. So I can't get hired in this big role because I haven't done the big role.

Like, how do we get hired into this big role? And so if you're out of a small startup, like you just, the scale is not there. Even if you go be ahead of engineering of this 15% startup, there's just five engineers there. And so you can never get into this scale. They're looking for it for these large roles. And so what I was looking about at the time and my thoughts in this topic changed a lot since then. But it's just like honestly where I was. It's like, well, if I want to manage a large team, I got to join a company that's growing really quickly.

And I kind of looked around and like, where is growing really quickly. And like Uber was growing really, really quickly. Is it 15, 16? I think this is 2014. This is early 2014. This is one growth just started to kick off. And this was very early. This is pretty early.

You have to be in San Francisco to know that Uber was doing really well. Like outside of itself, I think, I think news started to spread in 2015. And then by 2016, it was a global news. That sounds right. But the way I knew is that one of the engineers, Jeremy Grosser from Dig, who was on infrastructure there left and joined Uber. And actually, there's like an interesting technology adoption curve because Dig made all these technologies. One of them is called Clusto, which I think Dig, Uber, and then like a second life, that company, I forget their actual name, but whatever it is. Maybe the only three companies in the world that ever adopted this tool, Clusto.

but it managed basically a key value store to manage kind of state for infrastructure a little bit like a console from a Hashi Corp is very, very similar. Just years before console was out. Yeah, it was probably made originally in like 2008, 2009, something like that. And so he had actually brought

like a ton of the dig stack over into Uber. He was one of the first infrastructure engineers there. And so, you know, his team was hiring. And I really was like a generalist engineer. Like I got who was actually hired to do front end engineering, which I don't know if I was super qualified for. And then at, at dig, I was doing, you know, front end, Cassandra, were back in just like everything. And then they hired me to kind of run this SRE team. But it wasn't really an SRE team. It was just like an infrastructure team that

they called SRE. You know, I read like an SRE book like the week before trying to figure out what the job was. You probably read the SREE book that existed, which is the Google SREA book, right? I don't think that book existed then. It might have. What book did you? have access to. I think there was a DevOps book might have been what I was doing on. And it might have been like the Phoenix project might have been out around then. I'm forgetting it's at the exact timeline. But there was something like the Phoenix project. Maybe there was one other. And I just showed up. And then of course, like classic interview. I remember doing the traveling salesman's problem on a whiteboard and Python, stuff like that, which didn't really evaluate my

DevOps acumen very well. But somehow I think the company was a little bit desperate on hiring at that point, but I did get the job and started. And then you were leading a team. Already you were growing a team. So the team when I joined, I probably was managing like six people, but it was managing an incredibly broad range of responsibilities. So Uber when I joined was 2,000 people, it was 200 engineers, and this team of about six was managing our databases, our Kafka, like our actual servers. Not, well, the management of the servers, there was a tech ops team, that managed literally racking them and installing them,

that once they were racked, we managed that. Our service provisioning, like, we owned basically everything other than there was like a two-person developer experience team. There is this tech ops team that actually racked and installed the servers, but we owned all the other infrastructure and it was, um, it was quite an experience. And then in terms of just focusing on your, your leadership journey or your management journey, so at Uber, you started at this team, how far did it go and then what were the next steps between Stripe, Carta.

Yeah, absolutely. So when I joined that team was, I think, roughly five or six folks. When I left two years later, that team was 70, and that was all external hiring. And I think that that was like the most kind of amazing thing about Uber at that point is like Uber doubled an inch head count every six months. And so you can't just like steal people from other teams because those teams are hiring a ton too and also really underwater.

And so I really learned how to hire at Uber. I had no idea how to hire before I'd. joined Uber, but they were just hiring so many folks. I think one of my favorite stories, was this guy out of the Vemprite that I managed for a year and a half that would give him an offer at like 4.30 p.m. on a Friday, and he started Monday at 8. But I have so many like Uber hiring stories. Like some of them like funnier than others. I remember someone who interviewed with Uber four times and I saw him interviewing a fifth time. They got rejected four times. And a team interviewed him a fifth time. I was like, we cannot hire this guy. We've already interviewed him like four

times, like stop wasting his time, but he got an offer for that team. And he joined, and then he quit within six hours and took a different offer that because he got an offer from Twitter, which was right down, right, a block away or somebody was also a boat. He spent, he spent more time interviewing for Uber than working there despite accepting the job. And there just like so many, so many wild stories from the Uber experience there. But that team, six to 70, over two years, and our scope increased a lot in that time. But it was just like a really wild time. And it's hard, you know, some of the companies today, I think, remind me a lot of that Uber experience. But Uber, when I joined basically every Friday, we were literally manually

reallocating software between servers, trying to keep the servers up, because typically Friday rush hour was our peak time of the week. Though a Saturday, you might have more volume, but that would be like spread over more hours because people weren't all leaving work at the exact same time. So many kind of wild stories of just like what a manic place that that was to work at. But I was there for a couple of years. Then I went to Stripe. I was at Stripe for about four years in 2016 through early 2020. Then I was actually at Calm for your CSO right. Three and a half three years. CTO, that was my first CTO job. It was really kind of deliberate at that point. I think I was really worried. So I'd been at Striper four years. You know, Stripe had done really well. I think I joined

at five and a half billion and I think it was at 96 billion. four years later. Company valuation. It really came together. But also, I think the quality of the work we were doing was going really well. And I want to say I was roughly someone that joined the day I joined at Stripe was employee 500. I don't know if that was me or someone else in the batch. But I think by the time I left, it was 1.5 to 2000 folks, something of the company.

So Stripe grew about 70% year over year of the period that I was there, which is a lot less than Uber, which doubled every six months. And obviously, like Uber subsequently contracted much more. aggressively than Stripe ever did, which is the natural consequence of doubling every six months. Yep. But at that point, I was just worried that, like, my entire kind of, like, savings were all in one company that was never going to go public, which I think has been true. And so it was, like, a bit of a diversification play, but also the desire to, what does it actually feel like to fully lead?

And so for my entire time at Stripe, I was basically, you know, one step away from the CEO's reporting into Jeff Winter for my first year, then into David Singleton, who was my manager for the rest of the time. Oh, Stripe's CTO later or maybe at that time as well. He was high. He joined as the CTO. Oh, no, that's not true. He joined as the head of engineering.

Yeah. And then he became a CTO maybe a year or two later, something like that. But I was reporting to him from when he joined through through the time I depart in early 2020. So I was only one step away. I was like, what if I could get into that seat? Could I do things better? And that seemed like the right thing to try for anyway.

and has been educational ever since. And then you have had several CTO gigs. And so it was calm, three and a half year CTO, then you were at Cato? So I was at Calm for, I think, three and a half years. Then I was at Cato for two years. And then I joined Imprint a year, year and a half ago, something like that, which is where I am today. Okay. So now I three times CTO.

I need to ask you, what does a CTO do? As an engineer. Like, let's like, if you put yourself back as being an engineer, of course, I think, I myself had aspirations when I was an engineer like, oh, it could be nice to want to be a CTO because in your mind it's like, well, it has some management, but it's also a lot of CTO you see are technical and close to the thing. How do you find the CTO? I know you have a book on this as well on engineering executive careers and there's a lot of answers. But what is your mental model? How was it and how is it now especially? Because now with AI, I think your role has changed. I think one of the worst parts of being an engineering manager in the 2010, ends is I think like when you joined the ranks of engineering management, like one of the first lessons you'd get is like, hey, you need to never make a technical decision again. That's what it used to be right. I remember. That is, that's like literally, you know, what I was told. And I think you'd see people like the most important thing is to let go about technology decisions.

And this was the ethos then. And that's definitely not the ethos today. But I think the thing that I kind of aspiration really loved is the CTO was like the only place for this like engineering kind of career, this technical-arranged one, and this managerial one converged. And so one of the things I've believed strongly in and continue to do today is having both engineering managers, but also like individual contributor engineers report directly into me in the CTO roles. And so today I have 14 direct reports right now, and I think four or five of them are ICs, and then the rest are our managers. But having that balance is like really for many roles in management, you're just not allowed to be a technical leader or you weren't for a long time. And so to me, actually getting to the level

where they converged again and you were allowed to be a leader on the technology and the management side was like one of the big appeals. But also, there's so many like bad CTO decisions out there. And I don't, I don't mean this to reflect on any of the individuals I've talked about. I think David in particular was like really excellent. And the decisions at Strype were generally decision quality at Stripe was pretty high. And so sometimes you could be like, I disagree, but you couldn't be like, this makes literally no sense. But often, like, you know, especially outside of the Stripe experience, there are just decisions that, like, just didn't make sense.

And I thought, like, maybe I could do it better. But I think the thing that I've really loved in the most recent kind of era is, like, you're really, like, not just allowed to be in the details again. Like, you're really sort of required to be. And that, to me, has been, like, the very most fun part of being back in software in this era is I think I, you know, I've done over 500 pull requests in a year and a half at imprint, going all the way to production, which is substantially more than I did in my prior career combined. And that's pretty cool.

And then you didn't imprint at CTO, or are you more than CTO at imprint? So I joined as the CTO, and right now I'm also kind of leading the product design teams. So product design and engineering all reporting into one person. Yeah, it's like a unified EPD structure. Is this a new trend, one person, because CTPO I started to hear about two years ago, Chief Technology and Product Officer two or three years ago, and now I'm starting to hear design also going into one person a little bit. I don't know if it's a trend or not. I do think that for one challenge I've been seen with like the agents kind of getting more mainstream is you actually have to be able to make decisions and make them quickly. And how do we do things? How do we not do things? How does agent adoption work for product? How does it work for design?

Hey, design, if they aren't using the new tools like Cloud Design or the Figma MCP or whatnot, then they're really the bottleneck. How do you kind of split the responsibility there on who owns design now? And so Imprint, for example, has been experimenting with this developer-led design model for kind of second-tier features, and it's created a ton of friction. Like, it's solved this bottleneck. It's also created a lot of, like, who's responsible for these design gaps that show up when engineers do lead design and sometimes like don't follow the design system properly.

And so having a unified kind of point that can actually make these tradeoffs, I think this moment of like immense change, I think is pretty powerful. I do think just in my core, I believe the industry is changing more in terms of how we create software than it ever has in my career. And, you know, I started in, you know, late 2008. I've never seen a change like this. A lot of the changes I've seen were more subtle or more kind of cultural or social, just to How I create software is really different than it was even a year ago. And having a centralized kind of mechanism during this moment of immense change, I think it's been really helpful for us.

But I don't personally think it's like a long-term friend, but I don't know, I'm trying to avoid predictions about too deep in the future at this point. Everything's changing a lot. Will just said how he's never seen the way we've built software changed this much in his whole career. One thing that is changing is a stack that we used for Git hosting, which brings us nicely to our season's sponsor and Tire. Git hosting has a problem that starts with AI and ends with agents. Engineers like you or me are creating more code with agents,

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Oh, and did I mention it works with any agent and it's open source. Oh, and one more thing. Something tells me they're releasing a full Gitchforses soon, from a CI to a placement for the pull request and code hosting natively on Entire. Get in early on what could turn out to be the next GitHub for the agent era. I also want to mention our season sponsor, Anticis. Agents are writing more and more of the code that we ship to production, we know that. So how can we trust that our system works correctly and without bugs?

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So let's talk about the Silicon Valley companies. We know they're a bubble, but they're useful bubble to talk about. How did building software change? Leading teams change over, you know, like starting from, like what, like 2007 all the way to today. I don't know what your first experience was like kind of as an engineer. But when I was first an engineer, first I was a contractor. I was like 22 for Yahoo working remotely.

No one else in the team was remote. And then when I went full time, I had the same manager. So I had the same manager for two years. I had two one on ones with that manager over two years. Yep. I had no one on ones or like once a year or for performance, not even performance, for pay conversations. And then they would say, yeah, good job.

Here's your raise. Or like, oh, and then promotions used to be like, congratulations, you're now promoted. And it was more about like, yeah, you're making more money. Cool. And I didn't have any expectation that I'd have more than two. And the first one was basically he wanted to talk about another employee's performance trying to get like some signal about whether they were doing poorly.

So it wasn't like feedback for me or something. And the second one was like, oh, you like gave notice. You're leaving. Like, what's going on? Right. And so that was just kind of normal. And so his job, the way he saw it, and I think he was like really good at it, was his job was to go find an opportunity in the company for the team to have impact. So he was going around the company, searching for something we could do that was really valuable.

And he kind of like brought that back. And then our job was to implement it and make it work. And that was just like how the work was done. And there was no idea that he was like helping me have a rewarding career or something like that. That like I think was irrelevant to know. We're talking pre-2010 pretty much. Yep. And then when I, you know, got to dig, I think all the managers basically got fired.

I actually became a manager at dig because I was the only one dumb enough not to say no when they asked me. But, but, you know, I had like two and a half, three years of experience tops at that point. And I knew nothing about management, right? And again, I never interacted with my manager at my prior job. I interacted with a tech lead to kind of set technical direction and then got upset if I screwed something up, but that was kind of the entirety of like the leadership model there, right? So I came in and I was a manager, but there was really no management at a dig other than, you know, me for the last year and I didn't know what I was doing whatsoever. So really, I learned a lot at Uber, but again,

at Uber, everyone was so busy. There was no management there either. It was really a sink or swim and either you figured it out and your team really struggled because if you didn't get the decisions right, the scale of the growth around that you would just crush your team. And so again, like really, really no support. It was interesting because by 2017, when I became manager, Uber put together as first apprentice manager program, which actually talking with people. So when I became a manager there, I had like a few days of getting together, mentors assigned all that. Most engineering managers never ever had that. And Uber, it was brand new at Uber. They made it more formal. So they actually did some internal DIY training, honestly.

Yes, before that, nothing. Oh, and they did it because I think they realized that bad managers were coming a really big problem. Yeah, which makes sense. I think people were just figuring it out. And I think the Uber I worked in was extremely kind of myopic. So one of the kind of values I might get it wrong was basically solve it yourself. That's like not literally on the stated values, but people didn't go get blocked in other teams.

They just did it themselves. And maybe let Builders build might have been like a variant of this. There was the lead builders build, be an owner or not a renter. And when you combine the two, there was something of a principled thing. But it was like just roam your way and don't ask for forgive. I just get it done. And there was sort of like a no dependencies culture, which I found really empowering. Whereas like, oh, I'm blocked.

It's like, you're not blocked. You need to go figure it out. And that was really painful sometimes. But it really meant you could always take responsibility and just figure it out yourself. Sometimes, you know, I remember signing like purchase orders for Uber China where we couldn't get anyone to sign it. And I ended up signing like a multi-10 million dollar purchase order. And I was, I was probably like 27 or just there was no one to approve it. And we had to get done.

And so, you know, Amir, the head of tuckups and I were just staring at each other. And I guess we'll just sign it. And like the thing that I loved about Uber of that era is like no one ever talked to me about it. Like there was never, there was never like a follow up. Probably not good either in a certain in a corporate governance perspective. That's like maybe a little bit like ad hoc. But we really didn't get each other's way and we're able to do like amazing things. Also extremely challenging place to work in its own right. Yeah, but people left and burned out for a reason, a lot of them. A hundred percent. But really, so I all the way through then, I finally get to

Stripe around 2016. And Stripe sort of famously didn't have a management culture either. So when I joined, there were I think three managers, one of them who I really loved working with. with Raylene, I think, had somewhere between 40 and 50 direct reports on because Stripe had read the, like the paper from Google when they used to have basically no managers for some period of time. And how it didn't work? Initially managed, no, they initially followed the model where there were no managers for a long time.

And so I kind of joined in that the wave of managerization as like one of the early managers in that wave. But I think there were three or four managers, Raylene, Jorge, and they're like one or two. others. Jorge was managing a team of, I think, 30 was maybe no one manager underneath him. For those 30 folks, Raylene, I think, and no managers. It was just like a very, it was a very chaotic time as well, but again, kind of coming out of the Uber experience, I was very, very familiar with chaos at that point. But there also the business was growing really, really fast. And so I think really that period at Uber, though, is one of the cultural change around

what is the role of manager, I think, started to like cement itself a little bit and kind of this role of manager, not as a kind of a core dewer or a decision maker, but as a facilitator really started to take hold. And that was like pretty, pretty fascinating to watch. And one of the reasons why I wrote staff engineer, which I think came out in 2021, was actually like collecting feedback for some of the staff engineers I'd worked with. Because one of the, one of the ideas that I was really frustrated with at the time was this idea that staff engineers principally got to work on interesting fun problems that they found personally rewarding, which wasn't what I needed for my staff engineers at all. Like, I needed them to go work on the business problems and the scalability

problems that I, as like a leader. And when I left Stripe, I want to say my team was like 250, 260, something like that. I had all these problems. And so some of my very best engineers were like, I want like a more interesting problem. And it's like I only have suffering to offer, but this suffering will make is what's going to make the business succeed. And so how do I refocus them? And I think many of them at the time felt like that was a violation of the management contract. Like my goal and my obligation was to give them interesting work they wanted.

Oh, interesting. When we look back just how it changed from like 10 years before. Totally. Right. And so I think that that was like a fascinating time to. it to be in. But I don't think that perspective was ever really right. If you look, the people who are really senior at Strite, but also everywhere I've worked, those folks were doing the really valuable work that the company needed. You never saw that perspective, like, really take hold

in the executive ranks. But a lot of the folks coming in really had that belief. And I'd say, like, without naming names, certain companies that they came from had very strong versions of that where kind of the obligation of the manager for senior hires was to give them fun work. And I think the industry is really reverted on that one for sure. Was this something to do with zero interest rates? We often come back to this, which is so curious. I wrote about this as well how an interest rate, which feels so abstract and we sometimes hear about it, how it probably impacted funding in tech for a very long time, probably hiring

startups, startups that were funded, that maybe didn't have a business model, but they were still funded. And ultimately, software-enduring archetypes manager, types management decisions. And then the music stopped sometime around 2022, where efficiency became more important. And now we're kind of seeing this. And now I think a lot of us are asking, and I'm also asking myself the question, like, everything that we did during that time, was it right at the time? Did you ever read, I'm going to get his name wrong. I think it was like Ron John Roy's like Zerp explains everything.

Blog posts from the margins. Yes, the margin. We'll also link that. I love his writing, yes. One of my colleagues at Dig, who then I hired at Uber, was John Durek, who is the other writer on the margins along with, I think it's Ron John Roy. But so I read that piece, and it really resonated, right? I do think that ZERP has explained the entire like 2010s in terms of how management styles changed.

Salaries went up. Then competition for hiring became your ability to hire and close and retain became the differentiator between these, like, successful companies, the less successful because he simply couldn't retain great people. And that, like, pulled kind of leverage back into the engineer's hands and created, like, a very different environment. And so part of the way companies were pitching themselves was, like, more relaxed, more focused on you, more career development. And I think in ways that I think we're often, like, kind of self-defeating. So I think there's this kind of, like, broad judgment of, like, the Google perk culture. And I don't think any company that did incredibly

well other than maybe Google and meta had that level of perk orientation. But I do think ignoring the perks, there are many other ways that companies try to focus on rewarding work, interesting work, you know, companies like, oh, engineers maybe shouldn't be on call. That's right. The second tier is to be on call, which was interesting because that was actually a place where every single person I've worked with knows engineers being on call for the work makes the software better. And yet companies were still kind of like, oh, maybe for the enjoyment of it, we should let folks not be on call for the work they're doing and instead page other people that aren't involved in the creation of the software. And that orientation really reveals, I think, that the shift and priorities

in those companies. Well, I also wonder if that was a time where managers were rewarded for having low attritionity, meaning few people left, being able to hire on the team to fill headcount, because often there was a time this might sound crazy, but filling headcount was difficult. You were given, let's say you had a team of 30 as a director or senior injury manager. You had 10 headcount this year. And if you couldn't fill that,

meaning you couldn't hire the right people, and this was like, let's say, senior and above. So it was like you couldn't just get new grass because that would be too easy. Then it kind of counted a little against you. Or someone else would get that head count, which might help their promotion because it was kind of obviously if you have 40 plus people,

you're now, you might be senior manager that's your director title. And so managers who did well in this environment became a bit of people pleasers. And also they started to shield their engineers from the business, for example. And I wonder if this shielding from the business has bitten back a lot of people

because now as engineers, you're increasingly expected to be saviy about the business, understand a business. That's when you're going to be in demand. That's when in a startup or other places you get to hit the ground running. And I still hear stories from people who worked at this big company,

the, let's say a big observability company, any of them. And they want to start up, seven person startup. And they say, it's terrible. Like, they're not letting me do things. And I'm like, hang on, you're a seven person company. Like, how is it and you're an experienced person? How is it that you're not asking, what does a business need to do? Let's do it.

Boom. And they've been socialized in a different place for a while. Yeah. I think that is like a huge part of it in terms of the incentives. I do think the orientation around the head count filling team. kind of management, like the employee kind of survey results. These are really valuable tools. I get, like, a lot out of them. But I remember spending a lot of time at these faster-growing companies, like analyzing the quality of manager based on the survey results. But survey results are, like,

you have to really interpret them. Like, high scores or low scores don't mean good or bad manager. There's, like, context that ask other questions about, like, hey, why is your team all upset about this? That doesn't mean you're a good manager or not, right? And I think these became a little bit a goal of their own rather than an interpretation mechanism, which, you know, in a lot of ways, is just like lazy kind of middle management in terms of how these are deployed. But I definitely, definitely saw that. And I think in general, I think I hate headcount conversations. Right. I think they're almost never the most interesting conversation.

But I think in a world where managers are not allowed to make technology decisions, the only lever they have to actually execute faster is headcount for prioritization. are you saying that at that time during ZERF where managers were the conventional wisdom was do not make technical decisions, this forced Savy and Smart managers to put way more focus on the non-technical side, potentially underinvesting in the technical things, maybe just not making decisions that should have been done, and overindexing on the soft side or maybe shielding their team from the business for all these things because they put their energy there? Oh, 100%. I think that's very true. Like for most, What I tell my teams that I work with now is like the hiring is the least interesting way to solve every problem. Like we almost always should never talk about hiring.

But the corollary to that is like if you have open headcount and ask for more headcount, we shouldn't talk about headcount either. Because like what matters then is like the hiring throughput and you actually like can't use more headcount anyway. But yeah, I think we basically told managers they couldn't think about technology solutions. And then what do they have? They have like process solutions. They have scheduling or they have people. And so I do think this was the natural consequence of the bifurcation of these two roles, which isn't to say we shouldn't bifurcate at all.

But I do think we need effective leadership to have both, or they over-anchor on kind of hiring, and that drives a lot of the bloated orgs we saw in the past. Let's talk about careers, career development. Let's start with individual contributors. How do you think career opportunities have changed for software engineers working at startups, mid-sized companies that you see? because we used to have a pretty clear career ladder, Eng 1, Eng 2, Senior Eng, Staff, Eng,

it was clear on how you get promoted. To start with, you know, AI tools are out. You know, they're writing the code, which used to be like Eng 1 and inch 2. They're now getting better at like architecture. We're talking about loops. Do we have a career ladder? Should we have a career ladder?

If you are a manager at a company, should you be worried about putting together a career ladder right now? It's a good question, right? And I do think the expectation is certainly from the teams that we should have career ladders, right? And that is, so the belief, which I think is backed up in research is that, like, having rubrics drives more fairer decisions than not having rubrics. And so I think this anchoring on career ladders is, like, something that's here to stay. And I do think if you don't have that, then you do undervalue certain things, right?

And so maintenance work, blue work, gel work, whatever you want to call it, I think gets like under-emphasized and flashy things that actually work and get overemphasized. I think that's definitely true. So I'm still a believer in career laddering, right? I think it's still valuable. But what you'd be there, I think, is complicated. And I think it's much less clear about what should be it. I think I don't know which consultancy has been selling some of these career ladders. We kind of small company by a small company, you see the exact same career ladder from some like kind of like, I don't know, like packet you can buy somewhere.

And so I think all of those are just really outdated, but we don't have like the next version of it. That said, when I think about folks getting to like staff, or principal these days, like, what I really care about is I've been thinking by doing like an add-on to staff engineer. I'll get to it in like, I don't know, the next decade sometime. But it's really about decision-making and complicated situations. And so first, this idea of navigating ambiguity. And so at Stripe, I remember working on this project where we wanted to go multi-region. And I kept getting from the engineers trying to lead it. Like, we need product to decide how on cross-region replication works or what, like,

What's the product behavior that we support if there is like only the consistency and availability but no partitionability? They wanted the product team to make these like cap theorem tradeoffs, which the product team can't possibly make cap their own tradeoffs, right? And what they were doing is they were finding a way to get stuck. Instead, like what you need like someone at staff or principal level to do is to navigate an ambiguity by making some tradeoffs, build the conviction, figuring out how to like make a prototype that like tests, like whether the prediction, the assumptions that made are valuable and

workable or not. And so I think these ambiguous problems are still a really challenging one. And to me, like a strong marker even today, even with agents, you still have these complicated tradeoffs that you have to make. And some of the tradeoffs, to your point, about kind of understanding the business earlier do come from not just understanding, like, how the technology works, but the product implications. And to understand product implications, you have to understand what your users are actually trying to do. You have to understand and the unit economics of like the product that you're offering and the cost to the service it and to actually what you're charging. And so increasingly, I think you have to be quite broad

to actually work these ambiguous problems. But I do think decision making has always been where staff and principal engineers have to make the impact. And that hasn't changed at all. I don't actually think agents are exceptionally good at making these tradeoffs. I think the agents often don't even recognize the tradeoffs because they're not in the context window, kind of subtle, implicit things that live kind of outside of the software. What about Eng 1, Eng 2 careers? I just had a senior engineer asked me saying, so, you know, like, AI clearly has gotten as good as an Eng 1,

N2 writing code because that's what we expected a lot of times from them. And then this person was saying that, well, somewhere that'll come to senior, but it's not there right now. But I still remember this one because obviously there's truth to it, but in your org, how do you think of NG1, NG2, New Grad, or people who are under the senior, they don't yet have the battle scars or the expertise or the judgment

that you can fully trust them, both in terms of hiring, but also developing them. So one of the things I try to stay away from is I call like artificial like specificity. And so like what's the difference in an inch one or inch two? And you know,

I think that's like actually pretty hard to be like super concrete about it. I think a lot of companies successfully say the difference is like three years of work experience. And they could say is that equitable? And like I don't know if there's any like super equitable. of a way to evaluate NG 1s versus NG 2. And again, a really bad NG 1, you can identify.

But the difference in like a really good NG 1 and NG2 often is time and roll in terms of just like building more kind of context over time. But it's not like super like they can do this or can't do this, especially with, you know, the coding harnesses. Like they can do anything but actually deciding whether they should be doing it increasingly, increasingly tricky. And in the wrong situation, we're getting a lot of direction. you can't even perceive their judgment in a lot of cases, right?

So I actually care less and less about some of these things, where I think just general things like time and level, stuff like that is probably good enough for a lot of these. I do worry that getting incredibly detailed on these criteria is like a bit of a, like a fake victory, where it's like, oh, it's made it really precise. But often, you've been in like calibration meetings where there are people who played to the rubric.

I remember at one company I worked at we had to get to like staff. There was like a mentoring requirement. And so we'd have people that literally went out and like would talk to someone and then be like report them as like a mentee. And they were like collecting mentees. And then you talk to that person like I didn't know why I was talking to them. They just talked to me once. And so like this is where if you actually create like the, you know, like you get what you measure. So I really think for promotions there's always been a lot of judgment whenever you try to remove the

judgment, I actually don't think you get good outcomes there either. And so having the rubric to help guide people, I think that's useful. But ultimately, it's like pretty subjective. And for a lot of these things, I think it actually having kind of constraints is more interesting than having really comprehensive rubrics that are used to make judgment. So here's an example. So something you did at Carter. Well, is that card. There's a lot of cost pressure. Cost pressure meaning that like to reduce costs of the, let's say, or info or whatever. To reduce their managed costs. Yes. Exactly. And so I actually had like a ratio. We can't have more than this number of staff engineers relative to the number.

And they're just, you was not possible to exceed that ratio. That was very annoying to a lot of folks, right? But I think it actually is more honest where the industry was like 15 years ago. 15 years ago, I think there wasn't a role past senior in most companies. Like senior really was the ultimate role for almost every company. And so, you know, as people have gotten like further along of their careers, and we have more people with like 20, 30, 40 years of software experience, you have opened up more of these levels.

But like a lot of these levels are like ultimately more like time and roll kind of titles rather than like really like a definitive like obvious like change in the capabilities the individuals that are that are doing it. I try not to worry quite as much about like the details. And I do think having like a hard block of like one, or one to eight or whatever it is, is really helpful if like what you're trying to do is manage costs. Because when you're managing costs, what you have to be honest about is that you're managing costs. And so at Carter, that was kind of a situation we're in.

Now at imprint, like we're not trying to manage costs. We're trying to manage velocity and quality level. And so we haven't thought about that at all. But this is where I think part of leadership is knowing what you're doing, explaining how you're doing it, and then letting people like accept the consequences of that. And so because of CARTA, we were going to have like a fixed ratio that meant we had to start shifting hiring to be less senior. So we could actually have more of a pipeline of folks coming in and filling those levels.

From that fix, a lot of things came from it, which worked really well. But it wasn't if we had just tried to fix it without figuring out the other parts of the hiring earlier in the funnel, wouldn't have worked. But I don't know, I'm less of a believer and kind of like a perfect description of things that are true than I was earlier in my career, just so many exceptions to everything. The thing with the rubrics and expectations, like it used to me, you know,

when both of us worked at Uber, you later worked at Stripe, it was pretty well understood what was expected of the role. And you know, with the levels like, yes, I agree that I inch one inch to senior, these can be murky, but there was a pretty clear expectation at some point. For example, a senior, you could trust them.

Typically, I think the industry started to understand at some point for like closer to a decade. A senior could trust them. with a project. If they had junior engineers, they would mentor them. A staff, you could trust them to set the direction

of a unit or multiple projects and so on. And the engine one and inch two is they could execute well coding without too many issues, took feedback. They were kind of like almost like they were like apprentice levels. Like I think engine one's inch two. It wasn't a serious promotion in terms of it. It was just,

it wasn't a destination. It was just they're growing. Some companies even had the expectation of Uber that you need to grow to a certain level. But they were like almost like apprentice honestly. They were just kind of getting, getting to have good judgment and all these things. Now that we're all using AI harnesses a lot more, including for reviews, code reviews are slowly going away as well. We're doing less of the what we used to do, which is coding and the very visible feedback between each other.

How would you define what the role of a software engineer is? And is it different from before? Is it more ambitious? Is it, how do you think about it? Because it is changing. Like I feel it's getting more ambitious somehow, but I'm not sure I'm able to put my finger on exactly how, especially from a CTO perspective.

And is this like the general role or is this like the level three? No, this is the general software engineering rule. How, because I think, I feel each role has changed a lot. Maybe the staff role, the staff engineers never did too much writing code at like midsides and above companies because they were busy making sure we're building a right thing. So maybe it's hard to separate. Because now no one is writing too much code.

And even the smallest rules, they will have, they will need to decide are we doing the right thing. Am I doing it, right? First, I think we're still like early days in terms of where we're going. And there's certainly people you're going to talk to. They're like, hey, like the software teams of the future are five people for any size company. And maybe that's true. Maybe we'll get there at some point. But we're definitely not there right now.

And I don't know if we're going to get there soon. But there certainly are companies that are, you know, have a small number of engineers spending, which is a staggering number of tokens in productive ways. And that's like a pretty, a pretty cool thing to see where is the role of software going? I think we're going to find out. And this is actually why it's such a fun time to be in the industry right now, right? The most fun thing is like, I think our profession is changing in a much more extreme way than anything I've seen since I entered the industry. And for me, like someone who's always been very oriented around the outcomes of the work I'm doing. It's just been like the most fun time I've, I've had. But I've also spoken to folks who got

basically joy from, you know, being in the zone, being in that flow state. And they like, have fallen out of love with software. So what they loved was like the actual art of doing it. And for them, like, you know, a few folks, like one person I've spoken with recently, he actually, he's retiring. It's like, I just don't enjoy writing software anymore. And he's lost this flow state. He's like, more productive, but like, they just don't enjoy it. And so I think the role is shifting, but I think it's shifting in a really interesting way. And I, to me, I have this kind of idea of software where the time to actually implement is approaching zero. These systems are still very slow in terms of like, you know, okay, let's say you can instantly implement stuff.

You still have to make all these decisions. It still doesn't work in all these ways. It still is going to scale poorly in all these ways. It's still going to break the user expectation. and still going to have like the wrong unit economics to actually be like a profitable business. And so I do think even if software were like literally free to write, it's still really, really, really hard. And so like today, you'll see this like if software's free, then all the sudden engineers are running ahead of the PRDs from product and running ahead from the high fidelity mocks from design. And that's creating a ton of issues for design teams trying to work with this engineering led model and something we're still trying to figure out at it. print totally honestly, right? That also could create the opportunities where like, well, if an engineer also puts on

design hat or a business domain hat and now, and now like runs an experiment full on. And obviously now you get to like, there's only so many experiments you can run without confusing you customers, which now it goes back to a strategy, someone having to just saying no. And also, like, who are you building with? Like if it's for people, like, they will have any number of attention. like Netflix has, I don't know how many new movies they bring out, but I know that when I open Netflix, they don't overload me.

I mean, they do. But they have, they have, they don't show me all 8,000 movies. They, they figure out. And so I wonder if, if software becoming faster, like as engineers,

we will need to discover the constraints of the other parts of the business, the domain, the customers, the, the reality, like you say unit economics, how money can be made. I think something I thought of,

about a lot working at Carter. So Carter is a low-scale business, by which I mean, there's not like hundreds of thousands of requests per second coming in. There's no like massive infrastructure problems there, but it's incredibly detailed business. How cap tables work is really, really, really specific. And it's very complicated. And there are tons of exceptions. And then doing it's important, right? It's a little thing, but you need to get that right. And accuracy is really important from like an audibility perspective. You're also working with law firms that have like a real strong point of view about how everything should be done very particularly as well. And you could be in a legal battle between two founders who are arguing about how much equity was actually vested or something

like that. Similarly, the other businesses Carter went into like the fund administration also incredibly detail-oriented. And so there are a lot of businesses out there where the domain context has always been the hard thing. And it's not super clear to me if businesses, where the domain context is really the hard part have benefited that much yet from kind of all the AI tools. It's still incredibly hard to do cap table management because of the details, the laws, the relationships, the law firms in terms of training like the paralegals there. There's like all these little pieces that I think domain, like complex domain businesses still have like a lot of defensibility in this day and age. And I don't know if that's how that's going to change.

I think it will change. Every two to three years, there's this kind of like, the product engineers are the new king. Product engineers are the new superhero, kind of like meme that comes around. Now is the AI engineer. Now it's the AI engineer who really are like product engineers that use like AI techniques, right? So the question is. Which is pretty much every product engineer these days. A hundred percent, right?

So it's like it's unclear. I mean, I've never really quite understood an AI engineer means. I think it means someone who uses harnesses and wants to get paid a lot of compensation, as I think what it means. But it probably means something else. too that I've just sort of missed the nuances on. But like, can you actually get individuals to hold all this context in their head? So even today, you know, people used to talk about like the front engineer who's actually a good designer or the designer who could actually write production

and running code, that person's always been rare. And now a designer with like a little bit of taste can write production code, right? And vice versa. Forn engineer with like good design taste can do design. Why aren't we seeing more of that yet? And so I think that's like a social constraint. Well, it's a really good question because I was asking this same thing. I saw some data from linear showing that PRs for designers and product managers are up. And I was like, oh, actually someone messaged this to me, a fellow engineering manager, said, like, hang on, I've been asking around. Like, we should be seeing more designers push to production, right?

Or product managers. Ask around 10 companies. I asked around another 10, including the likes of linear, ramp, open AI. I have yet to hear, except for like some exotic edge cases or like just one example of designers pushing production code. They will find bugs. They will identify them. But they will still get an engineer involved who confirms this approach works in the codebase, especially when we're talking about outside of prototyping.

They do prototype more. But even if we're not there. I wonder if it's an accountability thing. It's a, you know, like when even though like I can change a light bulb. I will still call the electrician when I need to do something a bit more on my house because it's electricity, right? And I can read the book. I wonder if it's this or specialization. I don't know.

You know, one of the things that I think a lot about is like there's one worldview right now, which is like if you have a great design system and you've actually used that design system, you don't need product designers anymore. That's like a viewpoint that a few people have. I haven't found that to be true, though. Even with a good design system, understanding how all these different components fit together, understanding the missing components in your design system, figuring out when you have like tradeoffs across different screens, how you manage those tradeoffs while presenting like the unified experience for the user. These are still really hard things to do. And so, you know, I know attention is all you need is actually not about human attention at all. But do you think there's some dimension where

people are still constrained on attention and great designers and great product designers and great design system designers as well are all so constrained on like the detail. of what they're doing to do it well, that they just don't have a ton of time to also be branching out. Does that inherently have to be true? I don't think it's inherently has to be true. And I do think, in theory, if you have a great design system, you have a ton of consistency and a ton of linters in terms of like it has to be used this way, all of a sudden, your design system folks, your product designers can be just looking at the exceptions much more aggressively. That is where we're trying to get to at imprint for what it's worth, where the basic case is just done by engineering using the stock design system and product design is more working

on the really complicated kind of versions of it along with extending the design system of the design system folks it's not working that way yet though like it's still it's still a little bit tricky but you know as as like the folks deep in AI say like I kind of do assume this is like a quote unquote skill issue and that we will like get to the other side of it but it's still a skill issue for us we're still figuring that out one thing related to this is you you wrote a Rules of Engineering Management. A really nice article will link it in show notes below. And one of the rules that I want to highlight, you say we wrote durable high ownership team, I'm quoting you, durable high ownership teams with domain context are even more important.

One of my biggest lessons at Uber was that persistent durable teams work magic by accumulating domain context, building a sense of camaraderie and feeling increasingly strong sense of ownership over an area as they continue to work on it. Now this was from Uber like what, like 2014, 15, so like more than 10 years ago. And you're saying that you feel this is very relevant, right? I think this is the only way to build skill of organizations. And it's interesting, though. I think this seems kind of like obvious,

but it's actually a bit of like a non-consensus take, if you will. And so a lot of times you're at a company, say there is 50 engineers and you have a really important project for a partner that project's late. There's still the Mythical Man Month thing. They're like, hey, we're moving 15 more people to work on this key project. And, you know, the Mythical Man Month, I want to say was written in like 80, 84. 75, 75.

And the second version 95. And that's a while ago. And so... More than 50 years. We know this doesn't work. And so, like, first, like, when people do things like this, a lot of it's like optics and creating the perception of doing everything possible. Yes.

So that when you miss, it's not, it's not your fault. But actually, not only does it not work, it also destroys the thing that does work, which is creating little pods that are able to own areas. And so when I joined. stripe, I had, you know, I took over kind of the team Jorge was leading up the time and he moved on to a different part of the company, I think to lead connect. And so I had 30 people and one manager was managing like four or five of them. And then I was directly managing, say, like, 23, 24 people. The first thing I did was like, all right, what are some pods and figure out like some areas I

could put together who could own areas. And then once I saw some progress, I just stopped thinking about them entirely until something went really wrong. So I could focus on. on the bigger priorities for me, which is like the problems you couldn't solve. This works so well. And so at Uber did the same thing. When I came into imprint, did the same thing as well, same at Com. Cardo was like a really well kind of scaled organization by the time I joined it. So I didn't need to do the same thing there. I think this just works incredibly well. I think if you do this well that people actually do better work than you will from top down dictation simply because they understand it really well, and it gives you the ability to actually put your attention on the

highest leverage or most painful parts of the company. And so, yeah, I think this is a strange non-consensus take, but it just works incredibly well, but optically, it almost always looks wrong. And that's like one of the reasons it's hard to do, where you have like a partner launch and you're like, hey, I'm not going to, I'm not going to move these folks. I'm going to let them say on what they're doing. It's really important. Instead, the team that's on the critical path, we're going to work hard as hell together. But like, we're going to burn to get through it. We're not going to pull everyone over because if you don't do that.

Or what you might have done in the past is especially in SERP, where it was, you had meetings, recruitment, all that. You would say, like, for this team on a critical path, we removed them from all of the BS. Totally. The recruitment, the university trip, you don't need to attend all hands and all these things so you can be heads. Which actually, by the way, works so much better than adding people.

And also sometimes telling people like, look, this will be a two-week push. Anyone who can commit to it, please do so, including putting extra hours. And in return, you can take time off afterwards or, or, you know, like, you create incentives and you just treat them as adults. And you're saying, like, can you, and oftentimes people will, like, I know in my life outside of work, sometimes you are okay taking a thing for this one thing,

especially when you know that I will repay you in kind somehow. Yep. And if you don't do that, the thing that happens is actually, at a real growing company, there's a crisis every day. And that means if you rotate people to crises, there's a crisis for everyone every day. And it creates the sense of devastation. And so I remember talking with someone at Stripe one or two years in.

We were talking about this. And he's like the way Stripe had run up to that point, his metaphor was like people on a wall trying to defend a castle. And they were always running to the place where they're about to get like overwhelmed. But they just couldn't be everywhere because they were getting faster and faster. are running, but they still were not everywhere all at once. And what we were trying to do was switch to this metaphor was like we had many people in many places. And so the people working in one spot had to solve that spot, but it meant they didn't have to be everywhere. Those are

kind of the two tradeoffs. But to be a successfully scaling company that's growing quickly, you do have to get to a mode where it's not the same people running everywhere at once because those people just completely burn out over time. And there's a certain point where they just can't manage the coverage anymore, no matter how amazing they are. Although I think the question with AI is, is that point much further than it was before? But I'm not sure if it is. I still think their attention runs out before their ability to write code does. Also, recently, something that I was thinking about this with the durable high ownership teams is just an example with Slack on how we have Google, Google chat, you have Mattermost, you have Microsoft

teams and Slack. Let's say these are four big competitors for the chat mark. And it's pretty well understood was there. And oh, and you have AI, your startup, you could also instruct an AI to like copy Slack. And here's the interesting thing. If you do it, the AI will copy Slack's UI and or find open source things. First of all, there's a lot of decisions that have never been documented that are behind the scenes that people at Slack will know and they take it takes years. Which if you build it, you'll figure it out. If you're big enough from the concurrency, deliverability, platforms, yada, yada, yeah.

But taking that aside, Slack launched Slack agents, which was a super sweet integration with coding agents that do the work inside of Slack. It just works beautifully. It's been well thought out, clearly. Like, this is a team that has a domain context, and they've clearly been working behind the scenes with teams' partners. I'm kind of like, hang on,

why has none of the other competitors launched it? Why has Google chat who have amazing people as well? These are all people that have the domain, and I think this is where I'm starting to, this one example just started to realize, like, there is probably value in, like, Slack having all, these people who are working, I'm sure there's, we would be horrified of how many people work there. I know it's from Uber like, why does Uber have this many people? But they're

working on this, but they're not only able to operate what they have, but they are, they keep reinventing what customers will want as the world changes. You know, the other companies seem to have not been responded, even though agents have been here for a while, they just haven't responded. Slack has not only responded, they did something that is objectively good. And now it's copyable, but how did you get there, right? There's some paper about the size of the bureaucracy of managing the British kind of empire and the size of bureaucracy, the number of bureaucrats kept growing even as the territory getting managed kept shrinking.

And there's sort of this inherent kind of thing where companies do just expands and create like bureaucracy and create like more kind of overhead. So there's something there where like sometimes companies have just kind of like lost the plot on their ability to actually move. But like my assumption, I think this is true for the muse word. work on for meta. My impression is that when really interesting good products come out, there is one or two highly empowered people that are connected to the founder, the CEO, the executive team that are pushing it through and that are able to make painful tradeoffs that are not well liked. And those can be

like legal versus like company tradeoffs. Those can be product tradeoffs. Those can be there are, you know, the sacred kind of elements of how things have to be done, not doing it that way. And so like, My guess is like for Slack, there was some sponsor. And look, people hate over-emphasizing executives. But I do think executive sponsorship to actually empower folks to do something difficult. Imprint moved over to linear, you know, like three or four months ago from Jira. We did it in like less than four weeks. And there were basically zero people that thought it was a good idea when I decided to do it.

We still did in less than four weeks. And now people are really glad we did. It solved a lot of problems you had about having centralized issues. management so the agents could actually know where tasks were, pull them down, work them, actually do kind of task unification, et cetera. We're having a really hard time managing workloads of tasks without that. But there were like maybe three people out of like 230 that thought it was a good idea before I did it. And that one, I just, you know, push through. And I think now people like, oh, that was a good idea. But they just didn't think it was. And sometimes you do have to

have someone who's willing to take the risk. And then, you know, the flip side is who then, need to judge execs and other senior leaders on are the risks they made us take good. And so I think three months into the linear migration, I think, you know, no one talks about your anymore, but certainly no one's upset about the change. People are really glad with it. But conversely, if people had hated it, like they should be like, you know, rallying to get me fired, right? But I think a lot of times people don't get held account to this. And so that's the flip side of that highly empowered executive sponsor. That does make these great products. Sometimes we let's them do incredibly boneheaded things and don't hold them to account.

Which is great segue to talk about executives. You've been a CTO, which is a former executive. Can you tell me what in your interpretation of executive is and how, what is the career path today to get to that level from an engineer like, okay, like I like the executive. I like that to be able to make decisions, including unpopular ones, helping people, helping companies. What was the old path and what's the new path? if there's any. So I think the old path, your software engineer for some number of years,

could be pretty short. Then you get into management and then you climb through middle management, and then you get to the CTO role. Middle management, end manager, senior end director. Exactly. And so I think there are a lot of problems with that. First, it means that often the people that were selected for management initially weren't like the most focused on the technical pieces of the work because they're trying to get promoted into management. And then the selection bias is really towards people that are able to operate well, which doesn't necessarily. have a whole lot in common with the technology side. Often they happen to be really good technology, but there wasn't like a strong kind of selection bias for it. But you really do have

to be a good bureaucrat to be an executive. And this is like one of the interesting challenges where a lot of my work is incentive management. It's knowing, hey, if we roll out this sort of performance review, here's how it's going to fail. And so we just shouldn't do that. We should do this other thing instead. And so if you haven't done the reps of being like a bureaucrat, you actually like can't run a function because a lot of running a function is in fact being a bureaucrac. How do you learn to be a good bureaucrat? I was a bureaucrat, right? And so, I mean, out of necessity, so at Uber, there weren't really like rubrics.

There wasn't like an interview. We didn't have any structure of how we interviewed when I was there. So you had to make it all up yourself for your function. And again, we were doing tons of interviews. And each time we didn't give an offer out, I was like so pained because I was doing so many interviews. So I had to figure that out. And then at Stripe, Stripe was like a much more structurally cohesive company.

And so we did have like a lot of structured process. And then I got to work on a lot of that and learned a lot there. You got pulled into it. You picked the other pace. 100%. And a lot of the structure I thought wasn't working well at the point that I joined to kind of like work to try to iterate and approve little pieces of it because we were growing, going pretty quickly.

And so really, you know, working these middle management jobs, I think, did educate me on how to be a good bureaucrat, which is part of being an effective executive because you can just allocate processes that work and avoid processes that don't work. Think about incentives that work and don't work. Structure that does work and doesn't work. You know, the Jeffer Reid seeing like a state, like you're not allowed to be in Silicon Valley if you haven't read seeing as like a state. But it's basically a book about how states see citizens and accomplishments and how that shapes how policy works. And it's the same thing.

Like if you've never been a bureaucrat, you don't know how to see things as a bureaucrat. But also, like, if you can only be a bureaucrat, you don't know how anything actually works. You don't know how software actually gets made. And so it's like very damaging to you. Am I getting this right that you're saying to be a good engineering executive? So VP engineering or CTO, you want to be excellent technology, knowing how it works, being hands-on if you need to be or just be hands-on, and also be a good bureaucrat where you can manage it. And you want both.

And you're saying that if you go out the middle-man-manage route, oftentimes it might happen that you either never were a good technologist or you stopped becoming that by the time you get up there. So you're a great bureaucrat, but not technology. but if you just go from like an engineer, your great technology is straight up here, let's say like your startup to mark and grass your de SETO, you will not be a good bureaucrat. I think that's exactly right.

And it's interesting where oftentimes I think line managers are better kind of instinctual executives than kind of middle managers because they're used to working the detail. So they can make better calls for the team or the company? Their judgments just better on all these like non-bureaucratic dimensions of the job, but then their judgments terrible on kind of the bureaucratic dimensions of the job.

And so this is why I think being an executive is hard and why it's a hard career path, is that it was, you know, in the 2010s in particular, you had to climb these, like, layers of middle management to learn this kind of bureaucratic component of it. And that was the only way to get scale to actually understand that. Now those layers are kind of gone. But the interesting thing is, like, the other half of the job

is now really emphasized in terms of better decision-making, understanding the actual product, understanding the actual business, understanding how software is shipped, in a way where we kind of de-emphasize, is that. So I think, you know, people are like, is it easier? Is it harder? I don't think it's like any easier or any, any harder. It was, it's all harder to become like a bureaucrat now, which again, like negative connotations, right? But this is like learning how to actually operate a function is

really difficult work. And as like a C level, like you'll often end up running three or four functions. Often one, you don't know much about yourself. So for example, at imprint, I was running the customer operations team for, you know, much of the last year, which is not something I am incredibly detailed on. I have like some exposure to and had like an amazing leader in place. But I've had to learn how to do that and I've had to do that, you know, a number of times at Stripe, I was managing support engineering, which is not something I've done personally myself. I was running data engineering, it's not something I've personally done myself. And so, you know, you learn how to run that way when you have to. It's really hard to get the jobs to learn how to

operate a function that way where you don't actually know the details of the work. But you get to be a much better, more detailed-oriented leader for longer. And that's really where I think the best future executives are, are line managers, because middle management has historically selected for totally different set of skills. How do you get both? It's incredibly hard now, and it was always hard in different ways. And what's your take on middle management? Slowly dying? Do you agree? It's definitely a hard time to be a middle manager right now, especially if you came up in the 2010s, You were kind of selected and trained in this more of this empowerment model, more of this like functional like bureaucracy model. And now people are like, we don't want it and we don't need it.

And so you've kind of risen to this pinnacle, but you can't get to the next step because of these other skills that are more kind of in the details execution really de-emphasized. And kind of people have changed the rubric on you, which is like super, super frustrating for folks who kind of get trapped by that. That's definitely the challenge that folks are in now. And I don't know how this wave of execs are going to happen. But it's always, it's always been a hard role to get. Well, and I do want to ask you, two people ask me for advice, and I'll share both of their stories, and you can decide if they're similar or different.

One is the head of engineering who has about seven people reporting to them at a company and was thinking, I wonder about my future because I'm seeing about this middle management. The other one was a story from another head of engineering who has, three EMs reporting to them and three ICs reporting to the VP of engineering. They've been shifting to AI transformation and the department also doing some other things. The VP of engineering is satisfied with their work, but they're under the VPI engineering. And this person also wondering, like, hmm, both people are wondering, am I in a bit of a career trap? And they ask me to ask you, well, you have a lot of experience.

what a tactics would you be able to suggest to them to figure out what career path could be for them to figure out what they might want, what is possible. And again, I think the tricky thing in both cases, both people have spent a bunch of time in middle management. It's not that they're not technical, but, you know, they had this path and it was pretty clear where they would go. Next would be VP of engineering for both of them. But in their current company, clearly will not happen or unlikely. So it's a hard time in middle management, right? There's a lot more competition for these roles. And so I think what I found personally very rewarding is kind of getting back into the details of writing software. And so when I left Carter, my team was 250, maybe something like that. When I joined imprint, the team I was leading was, I think 25. And so for me, this is kind of like a unique moment to actually re-skill. Well, if you're in management, I think right now, either you have to like get back into the details or the world is changing so radically. that like you, the profession you know will not be valued in three years. And I think you sort of have to decide like, am I retiring now or am I reskilling? And I thought about that too. Like I, you know,

a card I was like, I could just, I could just be done, right? Is this is what I want? But it's not what I want, right? I really want to still be participating. And I really genuinely believe the way that we work has radically changed in the last year. It hasn't changed everywhere. There's like a long tail that's going to take a long time to catch up. But in the places I work, it's changed a tremendous amount. And for me, personally, it's a lot more fun. So first, I think there has to be some, like, openness to, like, taking a backward step or a lateral step.

Just what people want is very different, and you have to be open to, like, getting a different, like, look at it. And so I think going back into, like, a line management position, for example, is actually much more educational than a middle management. The tools for line management, and writing software are so good. The tools for headcount planning or doing performance reviews are basically terrible, right? Like all LLM applications for these things are not good.

So I do think you're missing a lot in middle management right now. I would try to find my way out of it, but thinking a little bit about some folks that I hired at imprint. One of them that comes to mind is Jasmine, who I worked with at Carter, came over, and she was hired as a VP, but she was a VP that was hiring or managing. a team directly. So she was a line manager? She was a line manager. A really experienced line manager was running engineering at a Mux some time ago. And she came in to line manage. And she's doing just a tremendous amount of software, which she would have never done at Karta because she could

have never gotten time to do it. And at Mux, she was also like way too busy like running the function to actually be in the details of writing. Those people that are willing to actually go back and get their hands on to it are so valuable. And if that is who you are, you have to let people know, because otherwise people would think you would never take that opportunity, but I would hire more people like this all day long. You know what we're talking about in the 2010s on the reserve, how engineers got a little bit too used to like, oh yeah, my company and manager is here to do what I would like to do. I would like to do platform. No, no products are. Even if the business needs it, just not for me. You know, I'd rather quit. And sometimes they quit. Like it's it. I wonder

if there's a little bit of this with management. We're like, look, again, I don't mean to imply too many things for these folks, but generally similar. I have this path. I thought I would be VP of engineering soon, and I want to get there. But is that what the industry wants? Is that what the other companies? Well, no, right now they want really good, let's say line managers.

And either similar to those engineers, the best engineers I know, they kind of put their ego on the back and when the business said, like, look, we need product to build. They're like, look, I'm great at platform. You know what? let me be the best product engineer I can be. I felt with you as well that you, you know, you had 250 people, I assume, you know, compensation, equity, status. And you went down to lesser known startup with not as a well-known brand yet or at the time,

taking a lot smaller team, smaller responsibility. You let the ego at the door if you know what I mean. And then you learned so much more. Yeah, I think in a lot of ways it was just like a much better situation for me. And so, like, there are a lot of pieces that weren't, like, kind of, oh, like, this is a hit. That's not really how I thought about it. It was the perfect situation for me, because what I knew what I wanted was getting back into the details. Relearning how to do software in the current age, that's what I believe is going to be the unlock to kind of the longevity of my career.

Also, though, it's just, like, much more fun. And so, like, to me, it's just, like, much more energizing. And I've always been someone who kind of got tricked into management, going back to the big story, where they just needed. a manager and so I said yes. You've been tricked ever since. And then they made a director so it looked like they had a director in the acquisition conversations. So they, that was more palatable. But I didn't know how to align me and it to let her own direct. I just, they kind of needed one on paper. So, you know, very kind of them. So for me, this has been kind of what I wanted. And this has been like a unique opportunity. But I think for a lot of folks, there is this sense the industry has

betrayed them and that they're owed something that they've worked for. And the thing is, like, they're right. Like, they have worked incredibly hard, but the rules have changed. And so I think that at certain moments, the world looks very stable. And our industry looks very stable. And I think in the 2010s, we forgot that our industry is actually very volatile. Our industry has changed just a staggering amount in the last every decade. Things are just radically different than they were in the decade before. And we've sort of like lost sight of that. And I think that people that kind of came up in the era of a lot of stability don't remember that sometimes. And so I do think we have to be willing to kind of take lateral moves. We have to be willing to be a little bit humble. But if,

if doing the actual work, that's like the thing that matters to the company is humility, then we've sort of like lost track of what we're doing here because we really do just get paid to do things that are valuable to the companies, right? Like they don't, there's no like entertainment orientation into why these companies employ us. Yeah. What about the TLM role, tech lead manager? This was a role that we declared dead. You and me both declared dead as a dead end.

It is there, but this was back in, you know, like the tech leads who were given a very small team to manage as well. And we were clear, like in ZERP that it's just a career rut. And if your experience is great, I think you also made it clear that it's a trap. I think you have that article. What do you think about this role now? It's funny. It's still a trap, but it's a highly demanded trap. And so, and I think in many cases, there's no way to actually, there's no alternative. So kind of, it's less a trap than simply what's there. And so I think in a lot of companies, management is getting flattened. So we're starting to see like a director, let's say, have a bunch of like tech leads and like a org of like, you know, 30 people and a couple of tech leads here and there. Yep. And I think you're either seeing kind of two models. You're seeing that there are engine managers, but they're managing much larger scopes. And so they're actually.

like less kind of hands-on the individuals than they were before because they're managing, say, like 12, 13, 14 people before instead of like, you know, like four to, four to eight. And then we're also seeing kind of directors but then managing tech lead managers instead of managing kind of these line managers and different companies are trying different things. But I think this is where I see the industry kind of asking for folks right now. And I do say like some of the best folks we've hired at imprint have been folks that were in like more pure management roles that came in, but really wanted to be writing software. And I've just been doing an amazing job of kind of like doing a blend of both.

It is hard to find those folks where it's almost like interview them to be a great EM. And then like do you just get frustrated? You're not writing more software. It's really that person is kind of what you want. But it's hard, you know, not how we've been interviewing them so far. I think we've just found a few great folks. But that that is the role that we really want.

And again, it kind of goes back to this thing where you want people who have the capability to do the bureaucratic folks. parts, but don't want to. Like the capability, but not the desire, because those are really the folks that I see super effective these days. They can use that when they need to, but they default to actually your writing

software, which is really where most of the value is. As a closing topic, I wanted to ask you about how you write. You've been such a prolific writer. Still, I really enjoy your blog whenever there's a new article. I check it out. There's also you can subscribe. There's an email that I

subscribe to and I actually get it in my inbox. how you approach writing and what do you think about AI? And also, what is your take on? There's a lot of AI writing going on, not just for social media on LinkedIn. We know that, but also for some authors who, before AI, they didn't write with AI, but now they're starting to a little bit.

So I've been writing for about 20 years online in my blog, and I founded Irrational Exuberance in 2007. And then, you know, in next year, I actually might have done like May or June or something when I started writing it. So I'm getting close to this 20-year kind of anniversary. And when I first started writing, I was simply trying to figure out how to, like, network my way into a job, basically. But I did a ton of tutorials, just like, here's how I did this.

And this was a different era. Now the sort of thing that you just ask, you know, an AI, like, how do I do X? And it would write a great tutorial just for you or maybe just do it for you directly, right? Then as I started working at Uber, I started writing a little bit more of, like, the things I've been learning in hyperscale. and then really took off when I was writing at Stripe, because I think Stripe was a place that both had a lot to learn, but a real love of writing, and that to me really energized my work.

And then wrote my first book, kind of the culmination of the things I had written at Stripe and Elegant Puzzle, and then got a lot of momentum. I think a total of four books, probably not writing another book for at least a decade, maybe not ever. But I think it's just been, it's been so transformational for me.

I think so much of like when people know me, which is not that very often, really. But like when people know me, it's exclusively from the books that I've written or or the blog. And I really do believe writing is like unique way that we as individuals can actually change the shape of the industry. And I think when you've done that, there's like little things that kind of pop up. So for you like the the primodal kind of salary piece, right? And that is first like a memorable name that helps.

But also like I think it was like a really. important observation that a lot of people didn't understand. I think you've, you've changed a lot of people in how they approach compensation. And then Patrick McKenzie has his work on negotiations. So impactful. Probably created so much wealth for people in the world. I think he might try to track how much he's created on it. But I'm not, I'm not sure if that's still true. But for my books, I really think I've changed the industry with them. I think staff engineer, I think, notably, I think like the staff plus kind of concept, that that book created staff plus as like a concept, right? And there's other things that I think are like less like quotable, but have been

mattered. And there's just like, there's nothing I could have done in my work in any company that could have impacted the industry in this way. This many people and so so positively. I remember that both the elegant puzzle and Sapinger, I read it and I took, I took a lot of guidance from it. And that's just so powerful. And then I think about writing with AI. And I, I've spent tens of thousands of hours over 20 years creating this, writing this stuff. I'm not like super craft-oriented in my writing, which I mean I'm really trying to get ideas out more than I'm trying to write like the best blog post that I've never been craft-oriented in terms of writing great blog posts.

And we're just trying to get the ideas out written somewhere. I think what I like about your writing is there are very punchy ideas. It's not about the writing per se. Like you're, I would say you're a decent writer. or it's enjoyable, but it's not, it's not like, I don't like it because it's enjoyable to read. The idea comes and is there, and it makes me thinking.

And I'm not thinking because of how you presented it. And again, the presentation is fine, but the idea is what brings me home. Yeah, it's pretty minimal writing. And some of your articles are short. It's not even about the length. I'm way more wordy in my writing than then you are, which you will know, but it's just my natural side.

But in yours, it doesn't have to be. Like, what I like about yours, you don't waste a breath in your writing when there's not much. And that's complete. And then I think about that. All the stuff I put together, all of the things I've tried to change people's minds on. And to me, like, writing with AI would just be like throwing that away. And so I think, you know, like, I've never done a newsletter trying to collect like a huge number of folks.

It's more if you want to read what I'm writing, this is what it is. It's not like my business like it is for you. But still, like, you know, I've gathered. there are like some number of folks and like they I think they read what I write and that's really powerful and I know I know if I write something like often there'll be hundreds of companies talking about the idea there and the next week and that's just such like a privileged thought to be in if I just wrote swap I would just throw it away and it it's I can never get it back like I'll never I'll never spend another 20 years doing this right and so when I think about the advantages I have that I've kind

carefully built over like two decades, why would I throw that away? And so if I don't have something to say, I just don't say something. I'm not trying to manufacture content or something like that. I think it would be such like a devastating moment to me to throw that all away for nothing. Like if I was throwing it away for something, I could maybe get there. But I think it would just be like an uncompensated loss if I were to write AI slap articles. Like I don't think anyone would read them. And then I would throw away this, this thing that I've spent so long putting together. And And I assume that you feel the same way as that true. Yeah.

Well, I feel that to me, writing is how I think. And when I write the drafts, I often, like a lot of my social media activity, actually, and I never talked about this before. But sometimes people ask me, what is your social media strategy? I have a large number of followers, which is just a byproduct of doing things consistently. And in my case, honestly, it's researching and thinking about, like, I almost do full-time or close to full-time thinking about stuff that's happening in the industry and that I'm talking with engineers. Usually what happens, I started writing a draft about something. And I have this idea.

I put it in a tweet, just like in another window, and I keep writing it. And I later look back, it's now got traction because I guess it was an interesting idea. Sometimes it's controversial. Sometimes I actually test them up. I'm not quite sure. I'll just put it out there. I call these a little bit like brainfarts, which is not entirely true because I am thinking about things, but I don't really care about them. And I've actually more interested in the conversation. Sometimes it then distracts me when I go back, but it then makes my ideas form and a lot of my ideas are about observations. As is happening, are you seeing this, which just generates conversation? And to me, that is the writing.

And what I found with AI, there was a time where it was popular to feed all your writing and have a bot that you can talk to. And some people wrote a pragmatic injury and bot, which I didn't like the idea to use. But anyway, I still tried it out. And it was almost hilarious because, for example, it would. My opinions change all the time. My views change. And it was kind of spit back something that I said, you know, like years back. And I know that we talk about TLM. If you had a Will Larson bought, it would say TLM is a trap. And now we're talking about like, well, actually there's way more to it. I tell people like, don't put your thinking. Whenever I see someone write on

LinkedIn, especially a fellow professional or they message me, they often comment with their real voice. And I'm like, well, I'm just right that imperfect. That's you. I like, I like, the you. And I don't like the sterile thing. And I also don't like how with AI, it's got the same voice for millions of people using it, whereas millions of people talking have millions of different voices. So this connects to something I think is really related to this, which I think is a lot of people believe to be successful, they need to be writing content. But they don't really want to be writing content. And so they're like, I really hate writing content. But to get my promoted, to get my next job, I need to be writing content.

Like, how do I do that? And it's like, obviously AI, right? And I think something I've been trying to push back on folks on for a while. I wrote a piece of the exact name, but how to be like a tech influencer or something like that. We're going to link that. That post, it's such a, like, not catchy, but almost a click baiting name. It is the single best post about how to be influential in tech. And I will link it.

It's one of my favorite articles. I forward to so many people. So, by the way, thank you for. writing that. Of course. And the reason I wrote it was like, these people were like, oh, I need to write 200 things, 300 things, I need to write every week, I need to do this. And it's like, well, if your goal is to be visible, what you need to do is write one thing that gets traction. Spend a lot of time on it, test it. Like figure that out. You don't actually need to write a ton of stuff. There's almost no value in writing a ton of stuff unless you are, you know, running a

business that is based on a subscription. If you're just trying to get your ideas out, if you're just trying to be a little bit more visible, if you're trying to show, proof of your ability to write cogently, you can write like two things. You can write three things. You can write one thing every two years. And you don't have to write a lot. I think about Tanya O'Reilly, who has not written a lot on her blog, but when she writes something, it says something really interesting, right? And so she's not like a volume writer, but she's been able to have really impactful pieces. I think no glue is like the most obvious one. That had really been transformative. And so I think even for people that do write a lot, people don't remember the vast

majority of the thing, right? There's like a few pieces that stick out. So I really think that if people reoriented around the real goal, which is maybe to have some visibility, one or two good things matters so much more than volume. And so I wish people would stop creating volume if they don't actually, I think it doesn't serve their goals. And in fact, like I've seen some candidates that have interviewed, you know, over the last year where they have just like AI slop content and like a huge volume of it. And I don't know. I'm pretty conflicted on those candidates because it's like, hey, people aren't reading it. You keep doing it. And it's sort of like, why are you continuing to do something that doesn't serve any purpose? Because no one's responding to it. So it just feels

like people who are like running like a recipe but aren't tasting the product and aren't, it's cargo culting, right? They don't actually know why they're doing it. And so to me, it actually, it actually implies like poor judgment, rather than showing like a sign of like, oh, this is an ambitious person trying hard. Yeah. And that's closing. What's a book that you would recommend or books that you enjoyed reading? Certainly I think I would recommend kind of my books to anyone who enjoys spending money on

things. Your books are all excellent, really. Thank you. And certainly I think crafting engineering strategy came out last year. And I think it's, you know, the newest one. But I think there's like a lot of interesting ideas in there for, for, for, for, you know, for sure. I think, you know, thinking in systems of primer by Donnell Meadows is like one that I think about a lot. I read it based on your recommendation. I think it's, it's honestly the book

that kind of formed my view about management and kind of operating in companies. I think that is not really about operating companies, but it's like a mental model. You can use that book. I think is incredibly, incredibly helpful. But really like any book that forces you to have like a different perspective on something. And so I spent, you know, a decent enough time thinking about typing a couple years ago, like not typing like on a keyboard, but how to have like better type systems, which is not that relevant to my work on a day-to-day basis. And then there's another great book whose name I'm losing on TLA Plus and using that. Is that Hillel-Wain? Yeah, exactly. Yeah, he was on the podcast. Yeah, he has the famous TLA Plus. Fantastic book. And look,

like, I'm not using a lot of TLA plus on a day-to-day basis, but I think just the ideas there are incredibly powerful in terms of using languages to increase the verification or verifiability of your software, which is one of the biggest challenges of our time, right? If all of our software is getting written by someone else, which is an agent, making verification cheap is really critical. And even if TLA Plus is not the tool for that in many cases, thinking about that problem, and this is the same reason why typing is really interesting, really, really valuable. And so I think right now those are some useful ones. Thank you. Well, it was awesome to have you and finally have this super nice conversation.

Likewise, thank you for having it. I've known Will for so many years, and it was great to sit down in person. And we did it at a time when there's a lot of change happening with traditional best practices when it comes both to engineering management as well as engineering career progression. One really interesting topic was how far managers used to bend backwards to find interesting projects for their engineers. Will recalled how it striped some of his best engineers asked him for more interesting problems. Back then, he already pushed back saying that the only thing he has

is suffering to offer, meaning not particularly glamorous problems, but that suffering is what's going to make the business succeed. But back in the 2010s and the early 2020s, lots of engineers saw this approach as not particularly great management behavior. And yet today, it's kind of a default. For career stability and promotions, as an engineer, especially at the senior plus levels, you will want to help the business solve their most pressing problems, and this includes having empathy for those problems. I also found that eye-opening how Will thinks about what it takes, to be great CTO. He thinks of it as you need to be two things. One, a great standout technologist who knows what to build and how to build, as well as a bureaucrat who can run a whole function,

including a function you might not be an expert on like product or design. In the 2010s, lots of managers learn mostly about the bureaucracy part, and by the time they became CTOs, they lost the technology side. Today with smaller teams and less mental management, many CTOs will be technologists first, which will think it might be better overall, and I have to agree with it. Finally, I appreciated Will's advice to middle managers, middle managers being engineering managers who have teams that other managers report to them. Will did not beat around the bush.

Yes, today, it's a hard time to be in middle management. The two paths to seize looking forward are either you go back to being closer to where software is being built, work on a smaller team, or as a line manager role, or just accept that your expertise of mostly being a barracat, but not a technologist, could not be valued that much in a few years' time. Will himself took it backwards when he left the 250-person engineering team at Carter to help a 25-person team at Imprint. But he did it consciously to learn how to build with AI changing the engineering profession. I do find an inspiring that Will not only talks about the importance of learning the new rules of software engineering, but also walks to walk.

Do check out the show notes on Related the Pragmatic In your Deep Dives on Zero Interest Rates and Engineering and EM careers. If you enjoy the podcast, do subscribe in your favorite podcast player and a special thank you if you also leave a rating on the show. and I'll see you in the next one.