# Engineering Leadership in the AI Era

**Podcast:** The Pragmatic Engineer Podcast
**Published:** 2026-10-21

## Transcript

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 read books on engineering leadership and SAP plus levels, and I really appreciate how deep and thoughtful of a thinker he is.
Today we cover how zero interest rates heavily influenced a decade of management habits in the 2010s, many of these habits 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 middle managers do, and many more.
If you're an engineer or engineering manager and are wondering what your career 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 TurboBuffer, 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 redesigning their storage architecture from first principles to make sure it's faster, cheaper, and more reliable at scale.
The new system, called TurboPuffer V3, is not yet in prod, but it already passes CI.
Still, it's not nearly as performant as the current production version, V2, and so the TPUF team is now...
perf maxing query plans until they are as fast or faster than v2.
They're doing all of this in public documenting how they increased 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 full text 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 used 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.
TPuff started as a vector database, but it's no longer VectorDB.
It has evolved into high performance database for search.
The V3 discards the vector primary index, and all indexes will share the same column or storage 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.
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 each other 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 want 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 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 is like KidPix, which you've maybe, I don't, did you ever use to see KidPix?
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 this is an era when there was 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 software other than multi-user dungeons.
Did you ever play a MUD growing up?
Multi-user dungeon?
No, what's a mod?
It's a text-based game.
And so basically the idea is that World of Warcraft is actually a graphical text-based game.
We basically derive from these ideas of mods 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, IRC, Internet Relay Chat, and Merck, which I don't even know what the M stood for, to be totally honest.
It was a client.
You could do a little bit of scripting with regexes, but then a lot of the MUD clients as a kid could do a ton of triggers, regexes, and that's where I got a little bit further into it.
Learned my regexes 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 I came into college not really knowing what I wanted to study, and I thought I might do physics or English or, you know.
economics.
My father was professor of economics.
So there's some family lineage to try to live up to.
But ultimately, I kind of fell into 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 really, that was when I got into it.
And why?
I just enjoyed it.
We had an intro course that we were 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 a introduction to Christianity course, like at the history of Christianity, but also required to take like an introduction to computer science or some other course.
I forget what the other alternative was.
Really enjoyed the computer science one.
Did you decide that you were 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 talk a lot about careers is like a lot of folks go to like elite schools.
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.
Like they're great.
They're great candidates.
They tend to do really well.
But go to Waterloo, you go 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.
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 folks that graduated the year before that was working in software, he went to go work on a horse racing betting 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 CHET 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.
It's a 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 had the goal, break into 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 paid well.
And I think, you know, this was, so I graduated in 07, and then the next year I was teaching English.
And then I actually started working for Yahoo in, I guess, maybe early 09, 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, which is 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 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, you know, employment.
Yeah.
And back then Yahoo, I guess their star was kind of fading with Google, but they're still a pretty good company, right?
Good engineering challenge.
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 in 2007, 2008?
You run Y Apache.
So they had their own fork of Apache with a Y in front of it.
What programming language do you run on Y Apache?
Well, of course, you'd run Y PHP, 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, Ubuntu, you'd have kind of like APT or whatnot.
Well, you'd use Yinst, which was this Perl script that would navigate kind of the dependencies for installation.
And so just like a 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 be 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 like one quick Yahoo story that I loved.
So David Filo 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 Filo 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 Digg?
Yeah.
At the time, very famous company for a very amusing story.
Can you tell us about how you decided to switch?
Because it was a startup, right?
Dig was a startup back then.
So depending who you talk to, there are going to be different narratives.
But I think the Dig narrative is basically it was like 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...
but went on to the front page.
And so I had 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 and central moderation problem.
And there were, you know, communities, there are IRC channels where people would basically trade favors trying to get things onto 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.
a Netscaler, 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 it, I think it was a top 10.
website at one point.
Yeah, it was top-set.
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, Dig 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 massive rewrite 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 like 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 on the Friday before I started, the CEO got removed.
And then Kevin Rose came back in as CEO.
He was the 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 Dig before, which was a rewrite.
And so Dig V3.5 was the prior version before Dig 4, basically entirely a PHP 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 colo.
And so it wasn't like just spin up some capacity or whatnot.
But Dig V4 was trying to solve a bunch of problems.
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 was actually coming in via search.
Oh.
Into something called the permalink.
And so the permalink pages would be like, say you 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 permalink pages that would be higher page rank than the original source themselves.
And you can argue now, maybe we shouldn't have been.
Probably not.
I think that would be kind of the perspective today.
But from the perspective of that moment, we were actually creating the discoverability and the conversation around it.
This was before Twitter.
This was before Facebook got substantial distribution.
This was really early moment.
And so for us, 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 like 110, 120 people, something like this.
But this was in, you know, 2010 when funding rounds were a million dollars or $3 million or something.
It's not like today when people are raising, you know.
$500 million and you can have a team of however many or it was a very different moment.
So even with 110 people, that was pretty substantial.
And we were we were running down the remaining coffers pretty, pretty fast.
The launch internally, 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, Dig, 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, which is 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 around this time.
And it's 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, they 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 dig kind of curators, unsolicited curators of content getting to the front page.
And he You know, he and many others were they lost kind of their their business.
Right.
But the launch went pretty poorly.
And why did it go poorly?
It 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 went live.
So I I don't personally take a ton of responsibility.
I also, again, think about where I was in my career.
I was basically.
It was my second job.
I'd been at Yahoo for two years.
So I won't own this one.
Later in my career, I'll 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 that had launched to basically ruin 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 MySQL system was pretty complicated, but it definitely worked.
And Cassandra, I would argue, like basically didn't work.
But I remember there was a team response for load testing Cassandra before our launch.
And two days before the launch, this other guy, Rich, who was fantastic, he and I were pulled aside and we're like, hey, well, they never did the load testing.
We need the two of you to do the load testing, 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 install JMeter and try to figure out how JMeter 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.
He's like, hey, like I can't do the reads on Cassandra.
He's like, that's not true.
I was like, well, I can't do the writes.
He's like, that's also not true.
I'm like, OK, 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, well, 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 dying.
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.
When 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 tuxedos.
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've been like a boardroom table or something that had 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 because 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 were 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 out.
And 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.
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 process.
And so it took us like a full month to 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, it would have the same list.
And so the memory of the user IDs, basically every time they call this API to look up user IDs to 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 memcache kind of in between these.
And the memcache would start falling over and then it would 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 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 engineering 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 on x now where they'll have like an ad that kind of looks like the the stories from people that are posting they dig owned the patent for that they were the 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 hired acquired by i think betaworks at 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, 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 in 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.
I can't get hired in this big role because I haven't done the big role.
Like, how do we get hired in this big role?
And so if you're at a small startup, like you just there's the scale is not there.
Even if you go be a head of engineering at this 15 percent startup, there's just five engineers there.
And so you can never get at this scale they're looking for for these large roles.
And so my what I was looking about at the time and my thoughts on this topic changed a lot since then.
But it's just like honestly where I was.
It's like, well, 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, Uber was growing really, really, really quickly.
15, 16?
I think this is 2014.
This is early 2014.
This is when 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 SF, 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 Digg, who was on infrastructure there, left and joined Uber.
And actually, there's like an interesting technology adoption curve because Digg made all these technologies.
One of them is called Clusto, which I think Dig, Uber, and then like 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 HashiCorp 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, he was actually hired to do front-end engineering, which I don't know if I super qualified for.
And then at DIG, I was doing, you know, front-end, Cassandra work, back-end, 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 SRE book that existed, which is the Google SRE 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 reading on.
And it might have been like the Phoenix Project might have been out around then.
I'm forgetting if that 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 a classic interview.
I remember doing the traveling salesman's problem on a whiteboard in 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 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.
But 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 was this tech ops team that actually racked and installed the servers.
But we owned all the other infrastructure and it was quite an experience.
And then...
In terms of just focusing on 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 the edge headcount 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 joined Uber.
They were just hiring so many folks.
I think one of my favorite stories was there's this guy out of a 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 Uber hiring stories, some of them 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 the 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.
A block away or somebody was also about.
He spent more time interviewing for Uber than working there despite accepting the job.
And there are 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 aren't all leaving work at the exact same time.
So many kind of wild stories of just like what a manic place that I 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 from 2016 through early 2020.
Then I was actually at Calm for 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 Stripe for four years.
You know, Stripe had done really well.
I think I joined at.
$5.5 billion, and I think it was at $96 billion four years later.
Company valuation, yeah.
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 an employee of 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 2,000 folks, something of the company.
So Stripe grew about 70% year over year 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.
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, 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 joined as the CTO.
Awesome.
No, that's not true.
He joined as the head of engineering, 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 the time I departed in early 2020.
So I was only one step away, but I was like, what if I could get into that seat?
Could I do things some better?
And that seemed like the...
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 Carta.
So I was at Calm for, I think, three and a half years.
Then I was at Carta 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 CTOs 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 2010s 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 aspirationally really loved is the CTO was like the only place where this like engineering kind of career, this technical oriented 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 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 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 Stripe 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 were 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'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 did an 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 seeing 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 products?
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 trade-offs, 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 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 has been really helpful for us.
But I don't personally think it's like a long-term trend, but I don't know.
I'm trying to avoid predictions about too deep in the future at this point.
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And with this, let's get back to Will and what changes he's observed across the industry.
But why don't you go back to like from when you started in the industry?
Can we talk about the changes you've seen in software engineering?
And let's just focus on your experience.
So let's talk about the Silicon Valley companies.
We know they're a bubble, but they're useful of a 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 as a contractor, I was like 22 for Yahoo working remotely.
No one else on 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.
I had no one-on-ones or like once a year or for performance, not even performance, but 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 from you or something.
And the second one was like, oh, you like gave notice, you're leaving.
Like, what's going on?
Right.
And so and that was just kind of normal.
And so his job, the way he saw it, and I think he was 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.
We're talking pre-2010.
Pretty much.
Yep.
And then when I, you know, got to Digg, I think all the managers basically got fired.
I actually became a manager at Digg because I was the only one dumb enough not to say no when they asked me.
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 like 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 Digg 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, scale of the growth around 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 his 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.
But 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 let builders build, be an owner, not a renter.
And when you combine the two, there was something about principled.
But it was like, just roam your way and don't ask for forgiveness.
Just get it done.
And there was sort of like a no dependencies culture, which I found really empowering, where it's 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 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 tuck ups and I was kind of staring at each other and was like, 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's never like a follow up.
Probably not good either.
In a corporate governance perspective, that's like maybe a little bit like ad hoc.
But we really didn't get in each other's way and were 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.
100%.
But really, so 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, Raylene, I think, had somewhere between 40 and 50 direct reports because Stripe had read 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 the model where they there were no managers for for a long time and so there 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 there were like one or two others jorge was managing a team of i think 30 with maybe no one one manager underneath him out of 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 also the business was growing really, really fast.
And so I think really that period at Uber, though, is when 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 doer 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've worked with.
Because 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 was like a fascinating time to be in.
But I don't think that perspective was ever really right.
If you look at the people who are really senior at Stripe, 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's 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 engineering, 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, but I think it was like Ron John Roy's, like, Zerp Explains Everything blog post from The Margins.
Yes, The Margins.
We'll also link that.
I love his writing, yes.
One of my colleagues at Digg, who then I hired at Uber, was John Durek, who's 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 you simply couldn't retain great people.
And that like pulled kind of leverage back into the engineers 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 were 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 like the second tier SREs 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 this software.
And that orientation really reveals, I think, that the shift in priorities in those companies.
I also wonder if that was a time where managers were rewarded for having low attrition on the team, 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 engineering 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 can just get new grass because that would be too easy.
Then it kind of counted a little against you.
Or if someone else would get that headcount, which might help their promotion, because it was kind of obvious 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 savvy 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.
They're not letting me do things.
And I'm like, hang on, you're a seven-person company.
How is it, and you're an experienced person, how is it that you're not asking, what does the 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 a huge part of it in terms of the incentives.
I do think the orientation around headcount 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 to 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.
Oh, so are you saying that at that time and during Zurb where managers were, the conventional wisdom was do not make technical decisions, this forced savvy and smart managers to put way more focus on the non-technical side, potentially under-investing in the technical things, maybe just not making decisions that should have been done and over-indexing on the soft side or maybe shielding their team from the business or all these things because they put their energy there.
Oh, 100%.
I think that's very true.
Like for most, like 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, Eng1, Eng2, 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 Eng1 and Eng2.
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 like backed up in research, is that like having rubrics drives more fair 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 over-emphasized.
I think that's definitely true.
So I'm still a believer in career laddering, right?
I think it's still valuable.
But what should be there, I think is like complicated.
And I think it's like 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 small company, you see the exact same career ladder from some like kind of like, I don't know, like a 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 about 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 a product to decide how cross-region replication works or what's the product behavior that we support if there is only the consistency and availability, but no partitionability.
They wanted the product team to make these cap theorem trade-offs, which the product team...
can't possibly make cap their own trade-offs, right?
And what they were doing is they were finding a way to get stuck.
When instead, like what you need, like someone at the staff or principal level to do is to navigate an ambiguity by making some trade-offs, building conviction, figuring out how to like make a prototype that like tests, like whether the assumptions they 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 trade-offs that you have to make.
And some of the trade-offs, to your point about kind of understanding the business earlier, do come from not just understanding 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 the unit economics of the product that you're offering and the cost to 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 trade-offs.
I think the agents often don't even recognize the trade-offs because they're not in the context window.
Kind of subtle, implicit things that live kind of outside of the software.
What about Eng1, Eng2 careers?
I just had a senior engineer ask me saying, so, you know, like...
AI clearly has gotten as good as an NG1, NG2 writing code, because that's what we expected a lot of times from them.
And then this person was saying that, well, somebody will 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 a 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 between an NG1 and an NG2?
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 say, is that equitable?
And like, I don't know if there's any like super equitable way to evaluate NG1s versus NG2.
And again, a really bad NG1 you can identify.
But the difference between a really good NG1 and NG2 often is time and role in terms of just building more context over time.
But it's not super, they can do this or can't do this, especially with the coding harnesses.
They can do anything, but actually deciding whether they should be doing it, 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 like hear 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 the calibration meetings.
where there are people who play 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 that 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 Carta.
Well, at Carta, there's a lot of cost pressure.
cost pressure, meaning that like to reduce costs of the, let's say, org or info or whatever.
To reduce or manage 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 there 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 are 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 in their careers and we have more people with like 20, 30, 40 years of software experience, they have opened up more of these levels.
But like a lot of these levels are like ultimately more like time and role kind of titles rather than like really like a definitive, like obvious, like change in the capabilities of the individuals 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 Carta, that was kind of the situation we were 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 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 in 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 like the rubrics and expectations, like it used to be, 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 want 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 on the engine, 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 was engine two.
It wasn't a serious.
promotion in terms of it was just it wasn't a destination it was just they're growing some companies even had the expectation as uber that you need to grow to a certain level but but they were like almost like apprentice honestly like they were just kind of getting getting to that that 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 a 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 role.
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 midsize and above companies because they were busy making sure we're building the right thing.
So maybe it's hard to separate because now no one is writing too much code and even the smallest roles, 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, 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 just a staggering number of tokens in productive WIS.
And that's like 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 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.
It's like I'm more productive, but like I 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've had this kind of idea of software that 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's still going to scale poorly in all these ways.
It's still going to break the user expectation.
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 literally free to write, it's still really, really, really hard.
And so like today, you'll see this, like if software is free, then all of a 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.
something we're still trying to figure out at imprint totally honestly right that also could create opportunities where like well if if an engineer also puts on a design hat or of or a business domain hat and now and now like runs an experiment full on to 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 strategy someone having to say no and and also like who are you building with like if it's for people like they will have the need 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 don't show me all 8,000 movies.
They figure it out.
And so I wonder if software is becoming faster, like as engineers, we will need to discover the constraints of the other parts of the business, the domain, the customers, the reality, like you say, unit economics, how money can be made.
I think something I thought about a lot working at Carta.
So Carta 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 accounting.
And it's important, right?
It's a little thing, but you need to get that right.
And the 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 with 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 it's the AI engineer.
Now it's the AI engineer who really are like product engineers that use like AI techniques, right?
And so the question is- Which is pretty much every product engineer in these days.
A hundred percent, right?
So it's like, it's unclear.
I mean, I've never really quite understood what AI engineer means.
I think it means- Someone who uses harnesses and wants to get paid a lot of compensation is 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-end engineer who's actually a good designer or the designer who could actually write production 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, for an engineer with a 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 the 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.
Asked 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 code base, 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.
Even though 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.
One of the things I think a lot about is there's one worldview right now, which is 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 trade-offs across different screens, how you manage those trade-offs 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 I do 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 details 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 and 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 base 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 a little bit tricky.
But, you know, 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 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 wrote revised rules of engineering management.
A really nice article.
We'll link it in the show notes below.
And one of the rules that I want to highlight, you say we wrote durable high ownership teams.
I'm quoting you.
Durable high ownership teams with domain context are even more important.
One of my biggest lessons that we wrote 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 skilled organizations.
And it's interesting, though.
I think this is 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.
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.
1975.
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 your fault.
But actually, not only does...
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 at 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 who 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 figuring 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 the bigger priorities for me, which is like the problems you couldn't solve.
This works so well.
And so at Uber, I did the same thing.
When I came into Imprint, I 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.
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 gonna move these folks.
I'm gonna let them stay on what they're doing.
It's really important.
Instead, the team that's on the critical path, we're gonna work hard as hell together.
But like, we're gonna burn to get through it.
We're not gonna pull everyone over because if you don't do that.
Or what you might've done in the past is especially in Zerp 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, 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 OK taking a thing for this one thing, especially when you know that I will repay you in kind somehow.
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 this sense of like 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, it 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 at 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 trade-offs.
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 you have Google, Google Chat, you have Mattermost, you have Microsoft Teams and Slack.
Let's say these are four big competitors for the chat market.
And it's pretty well understood what's there.
And oh, and you have AI.
your startup, you could also instruct an AI to 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 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, yada.
But taking that aside, Slack launched Slack Agents, which was a super sweet integration with coding agents and 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 there is probably value in Slack having all these people who are working.
I'm sure we would be horrified of how many people work there.
I know it's from Uber.
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 keep reinventing what customers will want as the world changes.
Data companies seem to have not 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 like 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.
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 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 trade-offs.
Those can be product trade-offs.
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 overemphasizing 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 it in less than four weeks.
And now people are really glad we did.
It solved a lot of problems you had about having centralized issue 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, pushed through.
And I think now people are 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 we 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 you 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 accountable to this.
And so that's the flip side of that highly empowered executive sponsor that does make these great products.
Sometimes we let them do incredibly boneheaded things and don't hold them to account.
Which is a great segue to talking about executives.
You've been a CTO, which is a former executive.
Can you tell me what in your interpretation 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 have, 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, you're a 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 to 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 bureaucrat.
You learned 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 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 kind of got pulled into it.
You picked up the pace.
A hundred percent.
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 improve little pieces of it because we were growing 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 Jepper Reed scene 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.
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 at 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 the middleman of this 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, great technologist straight up here, let's say like you're a startup tomorrow, congrats, you're the CTO, 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 in the detail.
So they can make better calls for the team or the company.
Their judgment's just better on all these like non-bureaucratic dimensions of the job, but then their judgment's 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 shipped in a way where we kind of de-emphasize 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 harder.
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, which is 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 like 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 detail-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 a 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 to 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 been a hard role to get.
Well, and I do want to ask you, two people asked 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 end department also doing some other things.
The VP of engineering is satisfied with their work, but they're under the VP of engineering.
And this person also wondering like, Both people are wondering, am I in a bit of a career trap?
And they asked me to ask you, Will, you have a lot of experience.
What 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...
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.
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 Carta, 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 reskill.
Well, if you're in management, I think right now, either you have to get back into the details or the world is changing so radically that 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, you know, I could just I could just be done.
Right.
Is this 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, 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 Carta, 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 Unlux 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 Carta 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 onto 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 were 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.
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, 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 want?
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 teams, smaller responsibility.
You let the ego at the door, if you know what I mean.
And then you learn so much more.
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 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 and acquisition conversations.
So they there was more palatable.
But I didn't know how to line manage letter and 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.
since 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 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 to 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 flattens.
So we're starting to see like a director, let's say, have a bunch of like tech tech leads and like a org of like 30 people and a couple of tech leads here and there.
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 individuals than they were before because they're managing, say, like 12, 13, 14 people before instead of like, you know, like four to eight.
And then we're also seeing kind of directors who 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 have 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 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 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 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 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 and 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 been like May or June or something when I started writing it.
So I'm getting close to this 20 year 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 it 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, like 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 like 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 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 trimodal kind of salary piece, right?
And that is first like a memorable name that helps.
But also like I think was like a really important observation that a lot of people didn't understand.
I think 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 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 book created staff plus as like a concept, right?
And there's other things that I think are like less like, quotable, but have it 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 positively, or I remember both the Elegant Puzzle and Sapinger, I read it and I took a lot of guidance from it.
And that's just so powerful.
And then I think about writing with AI, and 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, by which I mean, I'm really trying to get ideas out more than I'm trying to write like the best blog posts.
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 I like 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.
It's enjoyable, but it's not like, I don't like it because it's enjoyable to read.
The idea comes and it's 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 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 like it is for you.
But still, like, you know, I've gathered 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 in the next week.
And that's just such like a privileged thought to be in.
If I just wrote slop, I would just throw it away and 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 of 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 thing that I've spent so long putting together.
And I assume that you feel the same way.
Is 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 industry and that i'm talking with engineers usually what happens i start writing a draft about something and i have this idea i put it in a in a tweet just like in another window and i keep writing it and i later look back it's now got it's gotten 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 brain farts, which is not entirely true because I am thinking about things, but I don't really care about them.
And I'm actually more interested in the conversation.
So sometimes it then distracts me when I go back.
But it then makes my ideas form.
And a lot of my ideas are about observation.
Is this 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 engine 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, my opinions change all the time.
My views change.
And it was kind of spit back something that I said years back.
And I know that we talked about TLM.
If you had a Will Larson bot, it would say TLM is a trap.
And now we're talking about like, well, actually there's way more to it i i i tell people like don't but you're 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 why don't you just write that imperfect that's you i 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 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, I forget the exact name, but how to be like a tech influencer or something like that.
That, we're going to link that, that post, it's such a, like, not catchy, but almost a clickbaiting 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 has really been transformative.
And so I think even for people that do write a lot, people don't remember the vast majority of the 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 matter 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, I don't know, I'm pretty conflicted on those candidates because it's like, hey, people weren'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 implies like poor judgment rather than showing like a sign of like, oh, this is an ambitious person trying hard.
Yeah.
And as a 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 is the newest one, but I think there's a lot of interesting ideas in there for sure.
I think Thinking in Systems of Primer by Don Elamedos is one that I think about a lot.
I read it based on your recommendation.
I think it's honestly the book that kind of formed my view about management and kind of...
operating in companies.
I think that it's not really about operating companies, but it's like a mental model.
You can use that book.
I think it's incredibly, incredibly helpful.
But really, like any book that forces you to have 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 Wayne?
Yeah, exactly.
Yeah, he was on the podcast.
Yeah, he has the famous TLA Plus.
Fantastic book.
And look, 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.
Will, it was awesome to have you and finally have this super nice conversation.
Likewise.
Thank you for having me.
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 farm managers used to bend backwards to find interesting projects for their engineers.
We'll recall how at Stripe, 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 it eye-opening how Will thinks about what it takes to be a 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 learned mostly about the bureaucracy part.
And by the time they became CTOs, they lost the technology side.
Today, with smaller teams and less middle management, many CTOs will be technologists first, which Will thinks 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 barackhard 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 Carta to have 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 it inspiring that Will not only talks about the importance of learning the new rules of software engineering, but also walks the walk.
Do check out the show notes on related to pragmatic in your deep dives on zero interest rates and engineering and EM careers.
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