Transcript: What Happens to the Laid Off Tech Workers?

For years, tech companies were growing and hiring much faster than the rest of the economy. But over the last year things have gone in reverse. Tech stocks fell much harder than their peers. And while total layoffs in the US remain extremely low, tech companies large and small have been cutting back. So why the cuts? And who is getting cut? And do these cuts tell us anything about the long-term trajectory of tech employment? On this episode of the podcast, we speak with Patrick McKenzie, who recently left Stripe after 6 years, and is the author of the Bits About Money newsletter. This transcript has been lightly edited for clarity.

Key insights from the pod

Why did tech companies hire so much during the pandemic? —  5:37

How do tech companies get bloated? — 12:45

How overstaffed is the tech industry? — 17:13

Do tech companies hoard workers? — 28:50

Will laid off workers find new jobs? — 34:43

What impact will AI have on tech hiring? — 43:55

Joe Weisenthal: (00:10)

Hello, and welcome to another episode of the Odd Lots podcast. I'm Joe Weisenthal.

Tracy Alloway: (00:15)

And I'm Tracy Alloway.

Joe: (00:16)

Tracy, have I ever told you my idea for a two-part podcast, or like a series of two-part podcasts?

Tracy: (00:24)

A series of two-parters? Is it the debate one?

Joe: (00:27)

No, it's different. Okay. So I don't know about you but most of the time after we do these interviews, I usually have questions that I sort of kick myself for not having asked. 

Tracy: (00:40)

Yes, yes. So this often happens on the podcast because we often touch on kind of wide, varying topics. And we're not experts in a lot of the things that we talk about. And often the first episode is sort of, you get to know your subject matter. And then you leave it with even more questions.

Joe: (00:58)

Yeah. So I often kick myself like, ‘Oh I should have asked that, obviously.’ And then the other thing that happens is then the episode comes out, and then people on Twitter and elsewhere...

Tracy: (01:09)

They talk about it...

Joe: (01:09)

They talk about it.  And they're like, ‘What I'm curious about is X.’ You're like,’ oh, that's really good question too. I should have thought of that.’ So I've thought [that] a thing that we should do maybe one day is schedule, have all episodes be two-parters where we do an interview with a guest, take a week, sort of marinate on it, think about it, what are some questions we wish we'd ask? And then have the second episode scheduled.

Tracy: (01:32)

Oh, I really like that idea. It's sort of, it's almost the octopus model of podcast episodes where like one episode just springs forth a dozen new arms and legs that you can talk about forever.

Joe: (01:46)

So today we're kind of going to be doing that. I'm not sure what the record is, but this might be close to the soonest we've ever had a guest on so soon after they first appeared on the show.

Tracy: (02:00)

This is a pilot for podcast two parters.

Joe: (02:03)

The only other time I can think of is we talked to Claudia Sahm twice before the pandemic and once, because it was sort of her general views on how to forecast recessions. And then two weeks later the pandemic was in view and it was like, ‘oh shoot, this might be really bad.’ So we had her on really fast, but this is going to be close to that record, I think.

Tracy: (02:22)

Yeah. Sounds good. All right. Let's do it. 

Joe: (02:24)

recently talked to Patrick Mackenzie. He is a technology infrastructure, financial infrastructure specialist. He worked for Stripe for six years. He's currently an advisor there. He's the author of the Bits about Money newsletter. We talked to him about corporate IT, why it is the way it is, why does it seem to be years and years behind what we think of the cutting edge of software.

Why is it often clunky? Why does it often have these big technical issues that could take a while to fix? That was a great conversation. The public loved it. But there's a lot going on in software these days. And the other sort of big trend that we haven't really talked about is that for the first time in, I don't know, maybe like 15 years, we've been seeing all these tech layoffs.

Tracy: (03:08)

Right. And I think there was a little bit of tension in that episode in that we were talking about why corporate software is so bad. So it's almost like, well, obviously there's a need for better software. And yet all these big tech companies that ostensibly provide these services are laying people off.

But also in the broader macro picture, since we recorded that episode, we had a payrolls report that came out much stronger than anyone expected. And yet we've seen these big tech companies lay off people. And so the question obviously becomes, is this something specifically about tech or are these layoffs sort of the first sign of something broader to come in the economy?

Joe: (03:50)

Right. And the other thing that everyone points to when you see these announcements from Meta and Alphabet and various startups and Microsoft and Amazon, they've all done it, is they added so many jobs over the last two years that these layoffs are fairly small in the grand scheme of things, even for these companies, based on the amount of hiring that they've done.

Tracy: (04:11)

Yeah. I saw a figure from Goldman Sachs, I think it was Jan Hatzius, and he was talking about in the tech sector, most of the companies that have been laying people off grew their headcount by over 40% since the pandemic, basically, because they thought all the pandemic trends were going to keep going. Maybe there's a little bit of labor hoarding, but it's a big figure.

Joe: (04:30)

Absolutely. You know, people in our industry — journalism — when journalists lose their jobs, there's always trolls on Twitter saying, ‘Oh, learn to code.’ You know, that's a thing. I think at one point, even Twitter started banning people for saying that. But I guess the question is right now when you see these layoffs, should we learn to code or is that not the career safety net that it used to be? So all kinds of questions about what is going on in the market for tech talent.

Tracy: (04:56)

I'm sure someone's going to tell us to learn to code, probably. For the record, I can code just in very non-useful languages.

Joe: (05:02)

I have no code skills... well I coded in Basic.

Tracy: (05:05)

Yeah, exactly. Like C++ and like some really basic HTML

Joe: (05:10)

All right, let's talk to someone who knows more about this question than we do. We’re bringing back Patrick. Thank you so much for coming back on the podcast.

Patrick McKenzie: (05:17)

Thanks very much for having me.

Joe: (05:19)

So I guess the question is, before we even start talking about the recent layoff announcements, why don't we start with the hiring boom that we really saw over the last two years, just a massive amount of headcount added and all these companies — we know who they are — what drove that?

Patrick: (05:37)

So how about we roll back history to 2019? And if you're looking at recent history as of 2019, tech has been sort of an uninterrupted series of a bunch of very good years, broad-based expansion across the entire industry, basically riding, continuing to ride the wave that had happened since the late aughts, is that how we say it in English? With the consolidation of mobile gains, etc., etc.

Then the pandemic happened, and there was a brief pause of, okay, is this going to be an absolutely catastrophic event for the entire world economy? Many bad things happened during the pandemic. The way it played out for tech was probably not how anyone would've expected. 

For one thing, there was sort of a one-two punch of a combined fiscal response from governments both in the United States and worldwide to stave off a huge economic disaster, which had the effect of both putting money into consumers’ pockets and also using the markets for assets, for example, tech stocks, which we’ll come back to the importance of that in a moment.

Two, a lot of the customers were, due to various non-pharmaceutical interventions, sitting at home with very little to do other than use the internet. And so a lot of commerce that had been possible on the internet before, the share of it that was soaked up by the internet in both sort of like semi-discretionary places like food delivery, but also much less discretionary places like core supermarkets suddenly shifted online in a very, very fast way.

And so this combination of there's more money slashing around and more of it is falling into the online bucket led to absolutely blockbuster years for tech companies. And it was a like trying to keep your fingers onto the rocket internally at the companies like the amount of new users that was onboarding, the rate of growth of the business, the raw volumes of stuff that was going through the pipes made it like difficult to keep everything up and running.

And in a good news front the businesses largely successfully did keep up and running during a time where society very much needed them to. They also started to readjust their projections of what the future would look like. And for a while it was looking like the phrase that was going around was ‘Decades of growth were happening every couple of weeks’ in terms of our anticipated long-term shift of the offline economy into the online economy.

And it was a big question of how long does that continue for? And is that pulling forth growth that is happening in the future? Is it a one-time spike? Due to various structural and competitive dynamics, a lot of firms bet simultaneously, this is a pretty durable change. We find ourselves crushed by the amount of demand we're seeing right now. We are going to need to hire and hire aggressively to deal with this and to position ourselves for what we see as the, you know, eventual coming out of the pandemic future.

And as a result of this, companies were — mature companies, the Googles, Amazon's, Facebooks of the world — were hiring on the order of like 20% year-over-year growth across large portions of their business business, somewhat earlier stage companies, companies that might look like a Stripe, even though Stripe is somewhat larger these days or early stage startups were onboarding multiples of their pre-pandemic headcount as over the course of the pandemic. So huge expansion during the interval. And then as we came out of the pandemic companies assessed a number of things.

One, the growth rates tended to go back to its historical norms rather than this shot in the arm that the pandemic was offering. Importantly, and, you know, tech is a wide sector. It touches every part of the economy these days. So it's difficult to say with huge generalizations, but as a top line level, things did not decline back to 2019. And again, 2019 was not a bad year for tech. It was a pretty good year after a number of pretty good years. So we haven't gone back to the pre-pandemic baseline. We haven't even stopped growing in a number of cases. The growth curve has just bent downwards.

And so the sustained 20%++ headcount growth over time didn't look like it could be sustained. And then companies started to look at things that they had allowed to happen over the course of the pandemic. To characterize these broadly, one of the things that happened during the pandemic was due to the lockdowns and inadvisability of having large numbers of people congregate in small pockets of air, a bunch of companies went to both remote work and remote hiring where they might not have had a huge amount of institutional experience with that model of working before.

And after two to three years of working with these newer cohorts of people, they've found that there are some practices that they want to continue from this remote work world into the future. And there's some amount of internal impetus to return to office and have sort of a cultural reset around the office or headquarters, as the beating center of these firms.

I've worked remote for most of my career myself. I'm broadly a fan of the model. Let's say that there was some cultural tension in companies on like where the locus of activity is going to be, whether it's going to be in this online, in Zoom meetings and Slack all the time, or in the office, high bandwidth communication directly with trusted peers. And a lot of companies wanted to have a bit of a pullback towards the office, and then they're looking more granularly at the classes of people that hired over the last couple of years, and found that in comparison to prior classes, there was a bit of cultural drift relative to where the companies want their baselines to be.

And also in some cases, a bit of a measured productivity difference versus where they wanted their baselines to be. That's sort of expected because when you're pulling out all the steps to hire, you, like necessarily you have to be a little less choosy than you normally are. You know, to the extent that you ascribe any value at all to the in-person interview loop, which I ascribe relatively little value to, but hopefully it's like slightly greater than zero, you lose that amount of signal and they're sort of hiring in a slightly more challenged fashion than usual. And so the thing that companies will be pretty quiet about saying, but will say to themselves, is ‘we probably have a few more regrets in like the 2021 and 2022 hiring classes than we did in like the 2017 and 2018 hiring classes as a percentage.’

Tracy: (12:25)

Patrick, this actually leads to something that I want to ask you, but what does bloat actually look like in the tech sector? And, you know, is it something that only emerges as business activity actually slows down? Or even in 2020 and 2021, would you have characterized tech as bloated?

Patrick: (12:45)

So it's difficult as tech sort of subsumes more and more of the economy into its ever increasing embrace to make like broad brush assertions across all of it. But let's see where to start here.

So one, the number of things that are done in these large companies are extremely varied. People might have an image that like most people who work at Google are engineers. That's actually not the case depending on the company we're talking about. Between 20 and 40% of the people who work at the company are technologists broadly. They are software engineers, they're system administrators, they're designers at some companies, report into the same division, and then the rest are every sort of worker that you would have in any company in the economy — lawyers, regulatory people, customer support agents, etc. Management, layers upon layers of management.

So what does company growth look like? In one case, it is staffing up more teams to work on products that already exist. Sometimes staffing teams that sort of like grow with the the usage of your products. So like customer service teams typically grow relatively linearly with the usage of your service. Sometimes it's teams that grow relatively linearly with the size of your organization. So as companies were having these sort of like unprecedented amounts of employees getting onboarded every year, they needed larger recruiting divisions to staff up their other employees. And it's just based on like the productivity math of a recruiter. And you can like finger to the wind that if you hire a recruiter, that recruiter will be able to hire 25 people in a year. And so if you need to hire 4,000 people, then work the math backwards then you require 160 recruiters that you didn't have previously, that will tend to cause your recruiting division to get larger as you are doing rapid expansion, and then it will contract faster than the rest of your company will when you decide to take your foot off the gas pedal.

So those things that are sort of less inside of your control. You just need to keep doing them to run the business. And then you're making some, more speculative investments on like, what is our new product lineup going to look like? What features are we going to add? And so the basic unit of organization within an engineering organization these days is, is single engineering team. They'll typically be like five to eight people. And that team has mental bandwidth to deal with three relatively narrowly scoped problems.

And so the more that you want your software services suite, etc., to do the more like narrowly scoped problems that come into its domain, the more like five to eight people engineering teams you need. And so you might find yourself in a position where you've hired like five to eight people to work on three relatively narrowly scoped problems somewhat opportunistically.

And then when you come to 2023 and are thinking very rigorously around like, okay, we think we're a little bigger than we were when we were efficient back a couple of years ago, we think the economic environment might not be as strong in 2023 as we were modeling, which of all the problems in our company are the ones that we definitely need to keep focusing on, and which can we defer into later or just aren't core to our business right now? Then perhaps like some of these narrowly scoped problems are not at the top of our list. And then if you consider, you know, like this product that we thought we would bring to market in 2023 maybe will not be brought to market till 2024, then there might be like 10 teams implicated by that, that you do not have prompt need for.

Joe: (16:27)

I have a lot of questions. You know, when Elon bought Twitter and he went much more aggressive with the layoffs than anything else that we've seen. There were all these VCs and stuff who commented like ‘The dirty secret is that all these companies could do that. They have 50% of their employees not really working on anything and not really contributing anything. And so, thank you Elon, for showing that this could be done and Twitter still is operating.’ Although I don't know how the business is or whether he cut too deep to the bone or whatever, but like when you hear that, is that the case that just over the years, setting aside the unrealistic expectations of 2021 and maybe 2022, was there just wide scale over hiring relative to the needs of the business?

Patrick: (17:13)

So tech has been in sort of a land grab mode for essentially all of my adult life. We certainly haven't hit the asymptote of how many things in the economy can be orchestrated by software. We certainly haven't hit the asymptote of how many human interactions will be intermediated by a technical system happening over a smartphone, etc.

In that sort of land grab mode, you aren't simply like trying to answer what is the minimal set of things we can do with the minimal number of people, but are sort of opportunistically looking at what are the next 10 things that we can try as such that one of them becomes a company defining product feature, etc., etc. I have a little bit of re reflexive contrarianism when people say all tech companies are overstaffed by 80%, could you cut 80% of people who work at tech companies and still have something functional?

At the end of the day, probably true, that would be extremely painful. But if you went into a very different mode of operation and just wanted them to continue the products and services they had three years ago, possibly that could be done, probably wouldn't be optimal for any of them. That's one major reason why nobody does it. There's also some knock on cultural effects that make it virtually unthinkable.

If you were an executive at a tech company and you were sufficiently in your cups and had a heart to heart with someone and said, what's the true number of, like, ‘If I could wave a magic wand in note consequences, where would our staffing be?’ It would probably be like, eh, 85 to 90% of what it is currently.

I think, I think most people would say there's a bit of —  I hate the word fat —  uh, in this context, but a bit of fluff around the edges, but we're not in systemically a terrible place. And I think, you know, you, you would get different numbers from different people in different parts of the organization, but that feels like plus or minus right, to me should be noted that I was a peer worker b rather than the sort of executive that would be tasked with making that kind of decision.

Tracy: (19:33)

Patrick, you mentioned the sort of impetus towards creating company defining features. And this is also something I've always wondered, is there a bias in tech towards creating new products? And are employees and engineers, you know, rewarded for doing new things rather than maybe maintaining the old ones and perfecting those?

Patrick: (19:57)

Oh, this is an extremely important thing to understand the behavior of the large tech companies from outside of them. They all have what's called a ‘perf’ process in the industry. It's called perf. Outside it’s a performance review. And the performance reviews are largely how a company takes creative work that is done over this time scale of like quarters and years, and is often sort of indefatigable and very airy and reduces it to a number such that the company can dole out things of value like promotions and bonuses and career paths, etc., etc. And perf happens on a semi-annual or annual basis. And the way perf works at most large tech companies is it heavily biases in the direction of getting your name attached to new things that shipped in the world versus, you know, I was was assigned to this legacy product, the product did not go down for six months.

You should definitely give me a bonus on that basis. Oddly enough, this is not straightforwardly in the company's interests because all of the money is made by existing, well, not all of the money but the super majority of money in the tech company is made by satisfying customers you already have rather than getting new customers. And the super majority of money is made on your oldest and trues products rather than the new stuff.

But institutionally, tech companies biased towards, ‘We want our best people to be on the new things all of the time.’ And if your individual best people want to be, you know, doing the hard yards that keeps the old stuff running, they will quickly be dissuaded by their mentors and managers, etc., and ‘Say, no, no, no, that is not the way to exceed expectations. If you only do great maintenance work for the next couple of years, you will be severely career limited here. So figure out something new to do and make sure your name is attached to it in a way that is legible to your manager and your manager's manager and this performance review process.’

Joe: (21:56)

So let's talk about the layoffs that we've seen because you said something interesting in your first answer, which is that hiring discipline, hiring quality during those crazy years of 2021, part of 2022 may have been loose. The standards were a little lower or maybe people just didn't fit or something like that.

Companies these days are now or recently making the decisions about who they're going to let go. How skewed is it towards that recent cohort? Because the other thing I could see is that look at many companies, you probably have people who've been there forever who are getting paid extremely high salaries or very good salaries just based on the fact that they got some bump every single year. Maybe they're not pulling their weight to some perceived degree as much as they used to be. So how much of it is executives look and say, okay, we're gonna make cuts. How much was it skewed towards the new cohort versus seeing as an opportunity to get rid of some highly paid employees that maybe don't add as much value as they want.

Patrick: (23:02)

So a disclaimer off the top. Layoffs are understandably traumatic for the people who go through them. I don't wanna minimize that. At the same time, I think we often, particularly as workers in this industry, sort of like abdicate responsibility for understanding the structures that cause these things to happen in ways that are not in our interests.

So broadly it's good to have like open conversations about how these sort of decisions are made. I think it is different on a firm to firm basis, but broadly speaking, you would not want your simply to like roll back the last six months of your hiring. There's a couple of different reasons for that. One is that when you're dealing with these complex ecosystems that a sufficiently large companies an ecosystem to itself, there's all sorts of levers that you are like managing in parallel.

And one of those levers is that you are attempting to balance the seniority ranges in various parts of your organization, such that you always have a mix within some error bars of how many people that you have that are acclimating to the company versus how many who ha have acclimated and could do productive work versus how many are in that senior mode where they can light parachute in to consult on things and do the hard architecture stuff that your more intermediate employees might not be able to do yet. 

If you sort of create a bubble in the pipeline by concentrating your cuts in the people that were only hired in the last six months to two years, then you are setting yourself up for a bubble a couple of years from now where you have far too few people at a portion of the experience curve to do work that you urgently need to do work on a week by week, quarter by quarter basis.

And so if you come to the conclusion that, ‘Oh, we've hired a few too many people over the last couple  the last couple of months, what are we going to do about that?’ You have to distribute your cuts over a larger number of cohorts than the most recent cohorts, or you will set yourself up for some pain.

There's also some compliance and legal issues to come up with is employees seniority protected class in particular jurisdictions, which also plays into it into a little bit, but the biggest reason is to avoid causing the operational issues for your company layoffs is performance management. That is a thing that exists in the world. If you were hearing skeptical theses on Twitter that they would say about large software companies is not merely that they were a little bit flabby, but that they were a little bit self-assured of their position in the world.

It had too many good years in a row, and if you got attached to them, you could  get a job in a corner office and not do all that much and still be fine. I think that is a little exaggerated, but let's say there's certainly cases of it and there's certainly some people like mature into a career where they continue being impactful over years and decades, and some people end up in sort of a tenured professor mode where they've become critical to the organization because they know a couple of things that the organization needs to know, but they don't bring the same intensity that they used to in their career. And then there are some people who have like successfully created a niche for themselves inside the company that the company might not desire to exist.

And nobody wakes up in the morning and and says, ‘Oh, today I wanna do layoffs.’ But given a circumstance where everyone in the industry is doing layoffs, some executives might say, ‘Okay, it is a good time to reevaluate and like turn up the heat a little bit on our performance management and say, okay, is there anyone who has been coasting a little too long? Is there anyone who has you know, created a secured little nest for themselves in a way that that nest does not add a lot of value to the company given that we we need to?’ Usher some people onto new positions, let's like start with that first and then move to the cuts that are going to take more mental energy to do.

Tracy: (26:55)

You know, we're talking broadly about hiring discipline and the idea of bloat, and this is a slightly loaded question, but to what degree, if any, do you think the sort of maybe monopolistic moat that some big tech companies have built around their businesses has contributed to some complacency on the hiring front?

Patrick: (27:20)

I’m a little adverse to the word monopolistic, but I think I get what you're getting at is there is certainly a lot of rent created in the technology industry where  these are some of the most effective businesses ever created in any industry. Google AdWords will print a ginormous amount of money next year, and almost no amount of action taken by any set of adverse actors, internal or external will cause Google AdWords to not be worth many, many, many billions of dollars.

And so the, the margins on it are very high as well in comparison to you know, we were talking last time about the airline industry where the airline industry has struggled mightily to maintain like single digit percentage positive margins over a multi-decade timeframe. Tech doesn't have that problem. The nature of these very sticky products, the shearer sky size of them, and the margins do tend to create a little more room for flabbiness than  in exists in many industries that have more of a cutthroat reputation.

Tracy: (28:28)

This is sort of the polar opposite question, but nowadays we hear a lot about the possibility of companies hoarding labor when it comes to tech. How much of that do you think has actually gone on, in the sense that do you see tech companies opportunistically hiring people just so their competitors can't get their hands on them?

Patrick: (28:50)

I have heard this theory advanced many times, and honestly I don't think it is very explanatory and sometimes it's phrased, you know, Google would rather hire a particular talented engineer so that they don't create a startup and then eventually become competition to one of Google's products.

If hypothetically that were something that actually motivated executives at tech companies, there would be a number of things that would be easier to do than quote unquote labor hoarding that we don't do institutionally. So in finance there's this institution of gardening leave tech doesn't institutionalize gardening leave at any level, almost anywhere in the industry. And if you were thinking about let's prevent highly talented people from doing interesting things for our competitors or for new startups that they could create, the people in the industry that you have the, like tightest speed on their productivity level are your existing employees.

And so you would think like the natural place to start is like, start with people who already work here and say, ‘If you leave, we would like to buy 12 months of your time site unseen.’ And no one does that. And there's other things that you can do broadly. There's always a bit of push and pull between the needs of a company and the needs of employees, but broadly, tech is strikingly pro worker relative to many industries in the United States.

These things that are done that would be consistent with the labor hoarding hypothesis just are not done. You know, you can talk to the people that are involved in the decisions that are read on the outside as labor hoarding and they never advance that reason to, you know, buy up a new company that has four engineers attached to it.

It is typically phrased as something more similar to, ‘Well this is a team that seems already gelled. They're clearly highly, highly productive individual contributors, and we could have a bunch of engineering recruiters work for months to find four similarly talented individuals or team can like tick one box off in Q1 and get them all in in the door for the price of one low check.’ The notion of like, ‘Let's take this team off the table so they don't have a market success in three years and create something competitive with us,’ never comes up.

Joe: (31:12)

Okay. You, we've sort of talked about why the hiring boom happened in the first place. We've talked about maybe some of the decisions on who is getting cut. Let's talk about the, uh, sort of prospects for the people that have lost their jobs and or the people that are thinking about going into a career in tech. So how quickly do you perceive that the people losing their jobs over the last several months are finding new offers? Like, let's start really simple.

Tracy: (31:36)

Can I tack something onto that? Which is how fungible are these types of jobs in reality?

Patrick: (31:44)

A long time ago in a place far, far away during the.com crash, I was graduating from university and the Wall Street Journal was, which I read the Wall Street Journal every day with my father growing up, it was how I learned to read. The Wall Street Journal could do no wrong in my eyes, uh, as an undergrad and engineer. And the Wall Street Journal was pretty decided that, yep, engineering as a field is done in the United States of America, henceforth all engineering will happen in Asia. And I said, oh shucks, I really wanted to get an engineering job. I guess I have to move to Asia. And so I did...

Joe: (32:19)

Oh, the, the backstory, now we know...

Tracy: (32:21)

The origin story...

Patrick: (32:22)

This is the backstory of how I ended up spending my entire adult life in Japan. Now that ended up being a good life decision for me for entirely unrelated reasons, but it turns out there were in fact, engineers hired between 2004 and 2023 in the United States. And so reports of the field's demise were heavily exaggerated.

If you are considering a career in engineering, every reason you had to consider a career in engineering in 2022 is like still a reason to do it. So this like minor wobble that will be forgotten in a matter of months, please don't allow it to like, cause you to make major drastic life decisions. Although advice, you know, life is what happens when you're busy dealing with these little wobbles.

So that out of the way, how fungible are people? Broadly speaking, in the early levels of career, tech tends to cast a very wide net and hire people for what's often called horsepower with the expectation that they will be able to specialize over time.

There is some degree of worry that if you spend 10 years or 15 years in a particular industry doing the same year 10 years in a row, then you will end up over specialized and only be available for doing that sort of thing in the future. Depending on the thing you are doing, there might be a sharply limited set of firms for which that is relevant, but broadly speaking, the engineers that were hired to do anything in the first five, seven-ish years of their career are broadly expected to be able to do not quite anything, but like a large subset of all the things that a tech employer could want an engineer to do. And so the liquidity in the tech market within like a broad class like recruiters or engineers, etc., liquidity between job titles, exact roles, exact companies business model of the company is very high. And I'm forgetting what Joe's original question was.

Joe: (34:23)

Right, so are people finding new jobs the short term? Like you must hear from people, you must talk to people that just got cut. Are recruiters already reaching out to them from different companies

Patrick: (34:35)

Structurally tech companies… well, this would be a bad pull quote... Structurally, tech companies are like sharks.

Joe: (34:41)

Okay, we're gonna pull, we're gonna pull that quote now.

Patrick: (34:43)

Just like sharks, the way that their gills work, they have to keep swimming or they, they stop getting oxygen. And that's an unfortunate thing for most creatures. The tech companies, because of their staffing models, and that thing we talked about earlier where they are constantly mixing the, number of people at each level of seniority within the company. They have to keep hiring.

And so even if an individual company decides like, okay, we're going to like push pause for six weeks and do hiring freeze the amount of time that they can actually do that and not severely damage, the business is limited. So a pause is always temporary unless the the company is going down the tubes and like the large tech companies certainly are not going down the tubes. Some startups might get shaken out at the margin and due to  funding constraints, etc.

But like the overall business of the internet continues to grow a pace. So policies are temporary in nature and they exist, you know, like many different companies inside the, the broader ambit of tech, some of them might be paused at any given moment. Some of them are, you know, still attempting to make new investments for 2023. And some of them, while they're not in rapid growth mode for 2023 are doing things like, you know, we have to backfill for people who are leaving the company.

And in a typical year at a typical tech company that might be like 10% of our engineering staff. So if we've got 2000 engineers, we have 200 engineers that we are slated to hire in 2023. Interestingly, one of the things that caused a bit of the over-hiring was companies have this model for what percentage of people will leave in a year, and therefore how many you need to hire just to stay at the current level of employment that you have.

And when the economy started wobbling in 2022, what happened was the rates of voluntary attrition at companies, meaning that people who resigned out of their own volition went to lower than the model predicted. And because you need to set in place a process that takes months to hire people, but the process of deciding not to quit is not visible for those months, that resulted in sort of hiring overhang.

And so companies overshot their targets for how many people would be in the company which doesn't sound like an easy thing to do, but is a very easy thing to do if there is a sort of like sharp change in employee behavior with regards to things that they have total control over and don't have to announce to you like deciding to leave or not leave in a statistical fashion.

Tracy: (37:11)

Are there signs that tech workers should look out for that they're about to be laid off? Like do you stop being assigned new projects? Do your access codes get cut off? Does someone come take your stapler off your desk? What exactly are the warning signs that you might be in the danger zone?

Patrick: (37:30)

Many, many tech people have a large degree of stress with regards to ‘Whether I'm doing well, am I on the list,?’ etc., etc. And I don't want to add to that stress broadly. You should have an understanding of how performance is calculated at your company and consider that official view of your performance to be perhaps more important than you would naively believe it to. Because the official view where your, the entirety of your performance is reduced down to like one number, I'm a four for this six months. That is the only view that is going to be available to someone who might be 2, 3, 4, steps above you on the ladder when they're going to make hard decisions in a hypothetical future where they're making hard decisions.

So the things that cause formal visibility to the company are anomalously important, uh, and the career oriented people around you who are very good at, um, working those systems to their advantages, we'll find advantages based on that. But I wouldn't, you know, over-rotate on purpose. The only thing we're thinking about seems simple, but just do great work and then make sure people are aware of the fact that you did the great work and then things will tend to work out in a career fashion overly long period of time, knock on wood.

Joe: (38:45)

So I have a question that bridges this conversation with the conversation we had last week about it, and I realize I should have asked it last time.

Tracy: (38:54)

This whole episode has been because Joe wanted to ask this one question...

Joe: (38:56)

I actually only just had one question from last time. So I had to come up with a whole excuse for why we needed to have you back out just so I could ask this.

But it occurred to me, you know in the business press we're always reporting on CEOs getting fired or let go and hired. Sometimes CFOs, I don't see much coverage of like CTOs or CIOs like the people who run the internal tech systems being let go for poor performance. I actually think the only time I could ever remember hearing any sort of CTO or something losing their job for poor performance was probably like 15 years ago when Twitter was always having the Fail Whales and like they weren't scaling very well during the boom years.

And other than that, I can't actually recall a time in which I read a story about a CTO  being laid off for bad performance. How often does that happen? And you know, in the context of whether we're talking about tech companies or others — I think we were talking about Southwest and others last time —  like how often do the head of do those positions lose their job because they say the operations are not good.

Patrick: (40:01)

So it's a complicated subject for a number of reasons. One is that the degree of saliency of CTO most companies to the media is relatively low. The degree of saliency of many things that are very important to the tech industry, to the media is lower than many people in the tech industry would like. Uh, and that is, uh, one cause of the frequent conflict between the media and tech, but be the two people get laid off for per for performance. Yes.

One relatively frequent thing that happens relative to the incidence of senior executives departing is the sort of like fall on your sword motion if there's a significant outage is a thing that frequently happens or frequently relative to all causes for departure. I'm hesitant to give you the example because Tokyo is a small town, but there are a number of banks both in Japan and outside of Japan that have had disabling computer outages for like days to weeks at a time where that is an extremely, extremely thing to be avoided for a bank and rules up fairly directly to the  the head of it or the CEO.

And there are cases where either the head of it or the CEO have left as a result of doing that. There is one thing that I do like about the culture that is Japanese management where in, uh, the sort speech that an executive gives they will often say please don't blame the people that had their hands on the keyboards during this. The fact that this was allowed to happen was a result of management's missed decisions or have taken over the course of years. I presided over them and as a result, this, this outage, even if, you know, it was one person individually fat fingering, something that took us down for a week, this belongs at my door and I am resigning to take responsibility for it.’

There are many things I don't love about Japanese management culture, but that bid I do like. 

Another thing is there are reasons for companies to be other than maximally public about the fact that we are removing a senior executive for cause. If you remember that over the course of the last couple of years, the IT sector has been in sort of like massive boom mode, companies are extremely protective of their brand with respect to engineering candidates. Nobody wants to join a organization that exists under a cloud whose CTO just got fired for being an idiot.

So the thing that might happen is like well, the previous VP of engineering wasn't quite up to snuff. Maybe they can be shuffled onto a different project and we're going to hire a CTO above them. If you've already hired a CTO, that's a bit more difficult thing. But like shuffles with regards to what are the most important people in the engineering organization and is there a separate product organization, do they report to the same people, etc., etc., are sometimes caused by like, ‘X isn't getting it done’ or ‘We want to like shuffle in Y but we don't want that to be seen as a repudiation effects, not because we care about X's opinions so much, but we care about how this will be read by internal engineers who we want to keep attached to the company and external candidates.’

Joe: (43:03)

All right. One last small question. This is probably a question that we could talk about for a long time, but just real quickly. So one area within tech that seems like almost certainly going to be hiring like crazy for years at this point is anything to do with AI.

We all see going on there. How much are the skills that some of these like sort of cutting edge AI companies in need of how much are these skills that sort of legacy or existing tech workers might have, or how much are the skills that they need? Something that like you really need years of like focus training in the specific area to satisfy what these companies need?

Tracy: (43:41)

Can I add another thing? How many coding jobs will something like ChatGPT destroy? Should people stop learning to code? 

Joe: (43:52)

Talk about ChatGPT

Patrick: (43:55)

So I have a glib but true answer with respect to our advanced AI techniques going to destroy programming jobs. The first program or class of programs that we had where an advanced computer was obviating, the need for human programmers was called the compiler. Where instead of doing, you know, complex low level instructions directly in assembly and speaking sort of natively the language of the computer, you'd use what were called high level programming languages like C back in the day. And then the compiler would, you know, use its magic AI powers to turn that C into assembly language so that you didn't have to laboriously do the assembly language itself. So every technology that gives programmers more power, more capability to do things that are valuable for human society probably increases the aggregate demand for programmers is sort of like my high level view on the world.

And I've yet to see a contrary example to that. So an interesting question with regards to AI is what series of steps is going to be necessary to take it to market in a way that it actually creates the value for individual people and for society, and that it seems to have latent within it.

And if you look at like ChatGPT, if you view view it as an iceberg, there's the above-the-waterline part and below-the-waterline part. And the below the waterline part has some, let's say deep magic there, bracketing out that magic for at the moment. It seems like the above the waterline part was very important in why everyone has heard or ChatGPT and probably used it if you're listening to this podcast, but hasn't heard of like efforts at Google, etc.

The reason is that there was a, you know, a product focus team that made a relatively pedestrian piece of software, like a chat interface, but made it really, really good and worked on that to the point where people's interactions with the underlying large language model would be like sufficiently effervescent that you would screenshot that interaction and share it over to Twitter.

And so everything above the waterline part is amenable to the technologies and tactics that, existing engineers have with no modification whatsoever. You're talking to a backend, the backend is implemented in a different kind of magic than your backends usually are, but the backend has always been magic to you. That is like part of the answer. There's an interesting question on like how much of the work is going to be that above the waterline part, the productization of these, you know, creating new forms of user interfaces, new models for interactions with users, new metaphors that we have to teach to people. There might be an entire field in like education on how to do, I don't know, prompt engineering; how do you type in the right series of incantations to the machine so that the spirit up out from the aether does the right thing for you.

So like what percentage of the work will happen there versus what percentage of the work will happen on these like core under the hood model things? A sub sub-question to that is like, okay, so for the work happening at that model layer, is that work going to happen at every company that consumes models or is it going to happen primarily at OpenAI and Google and Microsoft?

And we can count the number of firms that like need these engineers on a single hand. In a world where we count the number of firms that need like dedicated hard AI researchers on a single hand that probably implies like lower total employment of them than in a world where every firm that touches AI has its own AI practice on staff, but it's at least as of like the current state of play, deeply uncertain where that will shake out.

And so these are some of the questions that get debated upon people at both the AI firms and also like, if you are a VC that's adventuring, that's investing in the space, you are probably having like a number of interesting dinner conversations on, ‘Okay, where does the value accrue in this chain? Where does most of the work get done? What do these products expose themselves to in the life of a user? Is it something deeply under the hood or is it integrated into their daily operations? Do they know they're using an ai? Do they know they're using software? Is it something that they're like directly typing in or is it something that they're interfacing with someone who's doing the typing on their behalf, etc., etc.’

Joe: (48:20)

Well, Patrick, this was absolutely great talking to you. We could talk for a long time, but instead we'll just talk to you in a few weeks again when we have, uh, a million more questions. No, I'm big facetious, but I learned a lot and really appreciate you coming back on the show.

Patrick: (48:35)

Thanks very much for having me and always happy to come back.

Tracy: (48:37)

Thanks Patrick. That was fun.

Joe: (48:52)

So Tracy, there were so many interesting elements of that conversation. I'm really glad we had Patrick back. I'm not even sure where to begin, but to start, you know, his point about the hiring boom during the pandemic, I thought was interesting. Not just that maybe these companies had a sort of unrealistic expectation about how long this growth boom would last, but that when you're hiring that fast and under sort of extremely unusual situations, you have that drift where maybe there's a little bit of ‘we're not that happy with the class,’ and then also to that point, you also can't just fire everyone who came in recently, for reasons of like seasoning and skill level growth. 

Tracy: (49:29)

Well, to me it kind of, I guess hammers home the point that three years on from the start of the Covid pandemic, we are still experiencing these abnormal developments. And it kind of gets to the macro versus micro point about some of the recent payrolls figures, you know, all the tech layoffs that have been announced. Are they saying something about the wider economy or is this really a tech-specific problem? And I think, I mean, I can kind of argue it either way. But I think I come away from that conversation thinking, well, you know, 2020 and 2021 were really unusual periods in terms of hiring for the big tech companies. And to some extent it seems reasonable that that starts to get rolled back a little bit.

Joe: (50:14)

But you know also, I take his point, and I suspect it's probably true, which is that if a year ago you were thinking you wanted to go into engineering or coding or something like that, very little about what we've seen so far in 2023 should make you change your mind. I thought that was really interesting too about sort of the questions about AI and how, as he pointed out, there are other places working on very similar, if not equal technology, what sort of made things breakthrough recently was the consumerization of some of the chat interface or some of these AI imaging things. So how much of the go-to market for this stuff ultimately is in sort of familiar experiences that people already have?

Tracy: (50:59)

It reminds me a lot, and I don't mean this necessarily in a negative way, but it reminds me a lot of crypto in the sense that yes, there is a lot of hype around AI, but also in the sense that this is a new technology that people can actually participate in. And so the use of the AI image generators, ChatGPT it kind of brings it to people in the same way that they were able to experiment with, you know, blockchain and different types of money using crypto. And so it suddenly becomes a lot more salient for people in that way.

Joe: (51:33)

Yeah. You know, that’s a good example because like with crypto, if you're interacting with like core protocols or developing on Ethereum, like that's going to be a limited number of people [who] know how to do that. But if you're building like an exchange, right? 

Tracy: (51:47)

I mean everyone can have a wallet, right?

Joe: (51:49)

Yeah. Or marketing or stuff like that. There are still all of these roles within crypto that have consumer-facing analogs to any other industry.

Tracy: (51:58)

Yeah. I need to look up the compiler. That sounds interesting. I'm going to go off and google deep learning compiler.

Joe: (52:05)

I guess, so for job security we still need to learn to code, huh?

Tracy: (52:09)

I think we need to learn AI? I don't know. I don’t know. But you know, C++, which is what I learned, and a little bit of Java…

Joe: (52: 20)

Can you teach me some?

Tracy: (52:22)

No, because it's obsolete. I don't think anyone uses C++  and they certainly don't use it for AI and machine learning stuff.

Joe: (52:28)

I should have asked Patrick what language I should learn.

Tracy: (52:30)

What coding language we should learn. Python maybe. Our next episode with Patrick will be about which coding language we should all be learning in the future. Yeah. Shall we leave it there?

Joe: (52:40)

Let's leave it there.

You can follow Patrick on Twitter at @patio11