Hello, and welcome to another episode of the Odd Lots podcast. I'm Joe Wisenthal and I'm Tracy Alloway. Tracy, you know, we've had a number of episodes about tech and some of the excesses of the VC boom, et cetera, maybe the softening labor market. But it's one of these topics that we can't talk about enough because it's so critical I think, to the markets, to the economy, and so I think ambiguous about like where the industry is going next.
Absolutely, So there's two big things that seem to be going on right now. Are two big questions, and the first one has to be we've seen a lot of layoffs in the tech sector, and I guess the question is is that reflective of the broader economy or is that something tech specific as a more interest rate sensitive part of the economy. And then I guess the second thing is, you know, tech heck was one of the big winners of the pandemic era, and how much of
that is getting rolled back now? How much of you mentioned excesses, how much of the excesses are being taken out of the system.
Well, And then I would say the third thing, which is that and it just really leaped to the public consciousness in the last several months. Is people being very aware of AI and these questions about like, Okay, we had this sort of like era of what we thought of as like a software company over the last decade, the software is a service company's VC funded, et cetera.
So in addition to the macro questions about hiring and a different in addition to the question about financing, there's this question like, well, what's going to happen with like tech business models and how like upended will be and what that's going to mean for existing talent and where the money is going to flow from all that, And I think, like, you know, everyone has posted threads on that, but I've never like found something that's like, oh, that's that compelling.
No, You're right, there's a lot to talk about.
So I'm very excited because today we're going to be speaking with a guest that I would say has really been I was going to say like the four front of two sort of like major apocal tech trends, but I kind of actually think it's two and a half because so there was the web two point zero like sort of like social kind of like user generated Internet, and then there was the sort of like the SaaS boom,
software as a service, et cetera. And then in the last few years with work from home like tech that enabled work from home, which is almost like its own distinct kind of story in my view.
Yeah, someone who brings those mega trends together and maybe maybe might be on the verge of another mega trend that we should.
Ask, well, well, the perfect person to see if there's another mega trend. So we have the perfect guest. We're gonna be speaking with one and only Stuart Butterfield, the co founder of Flicker, the photo sharing site, the co founder of Slack, the workplace messaging app that everyone used that eventually sold the salesforce. Recently stepped down as the CEO of Slack. So Stewart, thank you so much for coming on.
So I gotta say I meant to say. What's also interesting here is both Flicker and Slack, as far as I understood, it originally started because you wanted to create an online game company, and both of them had to pivot into these like mego world changing hits. So I guess my first question is, are you working on a new online game?
I am not. I get asked that a lot, and maybe.
It is a cliche questions like a good warm up. Okay, but you're not right now, No.
I'm not okay.
So I mean, maybe we should start with the pandemic boom, because I mean, Slack really became the sort of poster child for the success of SAS.
In twenty twenty and twenty twenty one.
And you also had a kind of famous Twitter thread where you explained what it was like being on the front lines at that moment in time. But talk to us about how would you characterize that experience, because looking back on it now, there is a lot of talk about maybe there was over hiring, maybe there was access in various ways, but how did you experience it?
Yeah, that was a big moment, like the March of twenty twenty, but I feel like it really started twenty fifteen or something like that. I was looking back through some old interviews and I think it was twenty and fifteen. It might have the years a little bit off. Slack raised money in a two point eight billion dollar valuation
and people were like, well, that's crazy. And even back then it was a parent and we would say interviews, this is just zero interest rate, like this is what happens, and so I think that kind of boost that that I don't know to say rocket fuel, but rocket makes it sound like. I think this kind of like rocket fuel propelled us all the way through and even you know, before going back, I guess twenty fifteen, tenty sixteen, we
started to be launched. In twenty fourteen, we had a million dollars of ARR the you know, the following week. I think it took us about eighteen months to get to one hundred million dollars of ARR, and that growth was crazy through that whole period and then accelerated in March of twenty twenty. I think the excesses are maybe not a different story. But I guess there's there's two parallel tracks, and one is like the Google Facebook track, which is r they make a lot of money and
so there's no real constraint on hiring. And then there's the VC back company, which is they raised a lot of money and so there's no real constraint on hiring. But absent those constraints, you hire someone, and the first thing that person wants to do is hire other people, right because they it's a very obvious signal. And it's very true that the more people who report to you, the higher your prestige, the more your power.
In the organization than the hire bility.
Yeah, exactly, and even you know, even if it's like a two person empire, it's something like, you know, if you're a we become a manager, you want to become a senior manager. If you're a senior manager, you want to become a director. And there's a very powerful intentive. So if you hire a thousand people, you have you know, nine hundred and ninety six people or you know, roughly one hundred percent, we're like, I need to hire. So every every budgeting process is I really want to hire.
And that to me is the root of all the excess because if you don't have the constraint of we just don't have the money. You know, if you're manufacturing lighting or something like that, like yeah, you know, a seventy year old industry where there's a lot of competitors and all the margins been taken out of it, you can't do that. And if you have infinite money, either from being monopoly on search engines or having vcs give you lots of money, you can get rid of that constraint altogether.
You know. You mentioned like this sort of like this flood of VC money and maybe like the sort of zero interest rates or cheap money was like a sort of jet fuel or rocket fuel for it. But on the other hand, like there was something real going on because the entire like the entire way the world consumed software massively changed, probably between the Great Financial Crisis between
then and the pandemic. So like how would you wait those two different factors, Like, sure, there's the cheap money in the vcs, but also like there was this like real shift in corporate spend on technology.
Oh absolutely, yeah, Sorry, I don't mean that, no.
No, no, no, And I'm always like but I but I do think like I do think like you know, for listeners, like it's easy to characterize the last decade like sort of dismissively right as like well, cheap money VC, but like something real, like really did change about how we usually how the companies use it. For sure, technology.
Slack launched in the beginning of twenty fourteen, so not quite ten years ago. Still, you know, it's like nine and a half years in and it's at a two billion dollar revenue run rate. You know, and we went public five and a quarter of years after we launched, and you know, we're acquired by Salesforce a couple years after that. So that's that's very real, Like it's not not many companies in the world ever get to a billion dollars in revenue, and that's a real change in
people's behavior. That's you know, tens of millions of people who spend hours and hours a day in a fundamentally different way than they did before.
So Slack launched in twenty fourteen, as you just mentioned, and since then, I think there's been a lot of competition from the big incumbents. Microsoft would be the obvious one. But I feel like there's always sort of mixed feelings in Silicon Valley about startups versus incumbents, because on the one hand, you think of a startup, maybe they're more innovative, maybe they're more flexible in what they can do. You know,
they can zig when others are zagging. But then you do have these giants that just have lots of money, lots of capital, lots of talented engineers that they can throw at these problems and either acquire you or maybe do a similar thing with their own resources.
Yeah, it's funny. I used to go back to Wikipedia's kind of registry of what the components of the DOW were, and you can look, like one hundred years ago today it was American Leather Corporation and I don't know US Steel, maybe it wasn't quite But like the first tech companies were Westinghouse in General Electric and a couple of Yeah, and everything has a has a life cycle. Roughly, you know, there's a couple of companies that survive for one hundred
plus years. But all of the and I know we should all say the word H, E, G, E, M, O and Y at the same time so you can see what the real pronunciation is.
But one, okay, geminy.
We actually did a whole episode about the US dollar roll where we said this quite a lot.
That eventually disappears. And I don't know how real that AI threat to Google is, for example, but Google has seemed absolutely invincible for a decade plus. Like it's just it's inconceivable to me that anyone would compete with them on their ground. To build that technology and to build the infrastructure and to build the data centers and stuff like that seemed impossible. But you know, maybe there's a
way around. And obviously, if you're a venture capitalist, you know your job isn't to get a fifteen percent return by investing in a basket of public tech companies. So you're very much incentive to see the startups succeed, but they're also you look back over the last twenty years or even just make it from the Great Financial crist the last fifteen years, it's been a lot of value created.
I mean not just in in you know, funny money, but like a lot of revenue, a lot of shift in how business is done, and a lot of huge successes.
Well, you know, I'm sure we're going to talk more about like AI and how that's going to change the whole world. But it is interesting to me that like the one big publicly traded company that like a lot people are giving a lot of credit to for AI is Microsoft, which was like the dominant tech company thirty
years ago, thirty five years ago. Probably, like does that surprise you that like the biggest, like powerful juggernaut, And then of course obviously with the teams versus slack competition, just like that there's this in this industry that's supposedly so disruptive and like so competitive that there's like this company and a couple of companies that are just so like seem rock solid.
Yeah. I think that that one. It's interesting, very effectively done. But the AI tech is all open AI. Sure, it's a.
Part like ahead of it, and they're like god, you know they they did make that investment and people are excited, like oh, they're going to create a word and all that stuff. So it's like tech aside, Like people are giving the company a lot of credit for how they're positioned in this.
Yeah, it's using their enormous resources and a huge profitability as leverage to leapfrog into the next next thing. I think it is very impressive.
This was sort of why I asked that question about you know, Microsoft versus startups, but like what are the pros and cons of a smaller tech company versus a bigger tech company, And you know, you can shade it towards AI or talk about tech in general.
I mean, I think it's just classic innovator celebrity people become when you have nothing to lose, then you can do take any risks you want, and if you have a lot to lose, then become much much more conservative. And I think Google and AI is a great example because obviously, if you asked anyone two years ago who's the greatest company when it comes to AI, everyone would have said Google, you know right, zero percent of people would have picked Microsoft at that time. And why aren't
they in Microsoft's position today? I think a lot of it has to do with that conservatism, because you know, they see, we can release this thing and then it says dumb racist stuff, and then we get in trouble, or we release this thing and someone relies on it and then someone gets injured or killed in an accident. You can come up with a million yeires. Like you know, I was up talking to the CEO of another company once and we're just talking about you know, we're just complaining.
We're like, oh yeah, our life is hard. But he was saying, if they're at a board meeting and the board said, you really need to hire someone doing risk and compliance, and he's like, okay, So it hires that person, and then the first thing that person does, like it started earlier, was they need to hire two more people because they need you know, there's a lot of work too. We haven't you haven't had anyone at risk. We've got to catch up, we've got to make sure we have
the right policies and stuff like that. Fast forward eighteen months and they're doing the agenda for this board meeting and someone tells him that they're going to have eight people from the risk team show up, and he's like eight people? How many? How many people work in that group? Twenty three? So this is like, you know, over over the course of eighteen months, and every single one of
you know, it's just like the classic incentives. They get zero upside if they say yes to something, and they have this powerful incentive to say no.
Downside basically if they mess something up.
Well beyond just risk. However, like thinking about Google and AI, like it is like, you know, an AI inference, I guess is like costly, right in a way that a search is not, like people seem to like you kind of have to pay for it, chad GBT is a service that people pay for, like Google has been free, this,
you know, has always been free. Seems like some of the AI tools may not be as conducive to an AD sales model since the answer is right there rather than taking you somewhere else, and so I'm curious like this tension that exists in Google where that maybe like AI is like kind of like a I hate you at the word paradigm because because I don't know what it means. But a different business, like the business model of AI is different than say the business model of search.
All these companies, like well many companies, whether large or small, sort of find that in a more AI driven world, like there's a real business model shift even sitting aside, like some of like the risks associated with it right now.
One hundred percent. And I don't know that either. I'm smart enough where I've thought about it long enough to be able to predict all the way out obviously, but something like you know, image licensing for stock photos, that seems like a business that I wouldn't invest in today. When you can just go to mid journey or whatever, then they'll get better and better.
I think some big, some big stock photos. I just like had a biout side for a biotofer for a few billion. I don't know what's going anyway.
Oh yeah, yeah, there's a funny story said, if someone gives me four billion dollars, then I will buy Getty Images.
I will do that too, if someone gives me four billion.
Okay, but yeah, so there's there's like a pretty trivial example. But I think the longer term it's a little bit harder to know how the knock on effects because you think about previous ways of technological innovation. And I don't mean software computers. I mean like just you know, going
back to steam power and stuff like that. It would have been tough in eighteen forty to kind of predict the impact of railroads on the world and then the automobile, all those technologies, but they really become part of us because when you think about I used to use this example of slack all the time. If your job is to dig ditches, you can only dig so many ditches a day, and if you are given tobacco, you can dig one hundred times more, five hundred times more, whatever
the multiple is. But those technologies come with I think there's a better word than risks, but they come with additional risks. You can like accidentally knock down a building with tobacco, and you can't accidentally knock down to building with the shovel. We get to the point now where there's this incredible augmentation to our memory to our ability to think. You know, I remember going to the library when I was a kid and having to talk to someone.
Then they can maybe find the book, maybe they can't find the book. And now it's like anything like a little card. Yeah exactly, I can just like type it a couple of words. I don't even have to spell the words, right, Like, I just have to kind of gesture at the words that I want and Google return and everything I can want. What does that do to us?
Long run? And I think, you know, we're living with the effects now, and this is pretty well recognized of what social media does and the doom scrolling and the changes to our physical posture because we're looking down on
our phone all the time. And I would really compare this to give a couple hundred thousand years of evolutionary pressure to seek calories and then not today we live in a world of effectively infinite free calories for everyone, and so a lot of people get diabetes, and we have a couple hundred thousand years of evolutionary pressure towards acknowledgment and recognition and all these social signals that suddenly you can get a thousand x what you used to be able to get and you end up with the
kind of cognitive diabetes. So when I say the long term effects are hard to recognize, both in AI and just in what technology does to us as human beings in general, it can take a while for us to catch up. Like the Thames and the Charles River used to catch on fire routinely in the end of the nineteenth century, and we kind of figured out how to have benefits of the industrial evolution without those and content weathers.
I think we'll do that with all kinds of tech, but it might take a generation or two.
Just on the business model idea, can you talk to us about how tech companies actually make money off of AI? And and here is where I, you know, very embarrassingly confess that I still don't really understand what salesforce does and how they make.
We're gonna ask this is the big question. We're gonna have to let's segment this for like TikTok, because a bunch of people have this question, and ever no one has ever had the chance to get an answered. So we're gonna like have to do a little like online segment of Stewart's answer to that.
Okay, so I guess my question is one, what does Salesforce actually do?
How do they make money?
And then secondly, like you know, if a company like Salesforce were to build something like open ai, how would they actually derive money from that product.
Yeah, that's it's a good question. I think that Salesforce is actually really well positioned to take advantage because here's what it does. I mean, obviously, it makes money by selling software to people. And it was the first to say, rather than just pay us one hundred dollars and you can have the software and run it on your computer like we used to do with floppy disks and stuff, We're going to sell it to you for much cheaper, but you got to pay us every month or every year.
But what the software does, I think is interesting because the original Salesforce product was CRM, or Customer Relationship Management, and it's just it's a database, right. It has like here's all my customers, here's depending what's important to me their phone number or if I'm a dentist the last time they had to check up r or if I'm a retailer, of the total of all their purchases. And you can kind of extrapolate from there to more and
more sophisticated products. So being able to do marketing segmentation and send the right promotional email to just the right people, and that's incredibly valuable people. It's hard to build, it's expensive, and so Salesforce has a lot of customers that kind of rely on it for this core set of services that the branch onto a lot of things, but are
roughly around customer relationship management and marketing. So what do people do with that software, Well, they have you know, they sit in conference rooms and they show each other slide decks saying this would be a great promotional idea.
Which is very relatable.
That's the most Yeah if you who said this, But someone's description of like, here's what a lot of people's job are and this is this is actually a great opportunity for slack. Their job is to get some data, put it into Excel, make a chart, take a screenshot of the chart, past into a PowerPoint, and then email
the PowerPoint to people. And then it really is like that's that's what's seventy percent of people with desk jobs do is But so sorry, people are trying to decide how can we use this database of customer activity or marketing to be to make more money, to be more effective on our business. And that's almost certainly something that AI will do better or at least, you know, having an AI copilot alongside here.
So AI could, for instance, like look at your proprietary database. I mean the software itself is not proprietary, but the data within it is unique to your company and maybe spot like opportunities within it that you, as a human wouldn't have thought of.
Yeah, absolutely, I mean so both Like people who are professional investers, I love the stories of you know, they drive outside some parking lot in the mall and see who's right, which retailer has the most cars parked?
And this is my favorite genre of sell side research. It's when they send the analysts to like the shopping mall to look at foot traffic and stuff like that.
But people do that inside their company too, right. They're looking for opportunities. Should we sell more of access to sell more of? Why should we sell more online? Should we you know, open more smaller retail outlets so that customers can come in and see the product, or should we concentrate on whatever? I think most of that stuff is. You're going to do a better job with with some companion, let's say that finds those patterns more easily because they can just day the AI.
I have this image of Clippy coming back and being like, have you considered well, I.
Think you think about things much faster to you?
Well, the I mean the other area. And just as you said customer relationship management, it seems like a I would be really great at like remembering birthdays, and for a salesperson specifically, it's like, hey, how did you know, oh, your daughter turned sixteen and you know she need driver's
insurance or something like that. And then it's like, well, does the salesperson even need to like pay attention or can they just put in a rule that says, every time I have a client that you know, has someone in their family that has a major life event, and just send them a message and something that seems like it's coming from me, and so like, ay, like, well it be good enough so that like sales salespeople can like talk to one hundred clients in a day versus ten,
and not maybe like two out of those one hundred things times say something so embarrassing that it destroys their entire reputation.
Well, the I don't know if it's good news or whatever. The fact is that people who have done that for a while you don't even to kind of like automatically get a prompt you send at your desk and pops up and says you should email I got.
A happy birthday from the dentist, and it's like, yeah, I'm not. I don't. I'm not. I'm not under the illusion that the dentist is like paying attention to.
But also I get a lot of it. And like, the dumb version of this is SDR sales development representatives or like kind of people who are trying to drum up some business for a company send a lot of email. I think I probably get a disproportionate amount this because I've made a bunch of databases as a CEO of
a company who will buy software from you. So I just get all of these ridiculous pitches like Hello Stewart, I couldn't help but notice that you are the CEO of Slack Technologies in Corporated, and you're like, I mean them.
We get that people think that we can make purchasing decisions on behalf of Bloomberg all the time.
So I think better versions of that. But I think even more, remember Google demo that that voice assistant that would call and make an appointment at the hairdresser for you. It was like it even like it paused and said
and stuff like this very convincing. This image of like I'm a salesperson and you know you're a buyer at some company, and my AI automatically generates this long email to you, and then your AI reads the email and summarizes it and just says like Stewart has widgets sell And then you know, your generates this long response to me, and then my AI reads it. I can imagine a lot of activity just becoming like AI.
So this was going to lead into my next question, and I'm trying to think about how to phrase this, but you can imagine how AI would be very very relevant to an application like Slack. But I guess the question is how extreme do you think companies will go here? Because you know, there's a big difference between having a companion, as you put it, who is helpfully pointing stuff out and maybe you know, going over your data and spotting
things that you wouldn't have seen other wise. And then at the other end of the spectrum, you can also imagine where you have, you know, someone who actually uses AI basically to do their whole job. You know, you could just automate responses to Slack and retreat completely from that communications platform. So how far do you think companies will go with this tech?
Yeah, I think they'll go all the way and where well, I don't know what all the way is, by the way, but I see this example all the time. Ben Evans, who is a former vc I Guess Andres and Horowitz, wrote this great article called Office Messaging and Verbs, and in the beginning he takes these stills from the movie
The Apartment Jack Lemon and Shirlie McLain. It's nineteen sixty and Jack Lemon works at an insurance company and there's like all these you know, like early in the days of office buildings, all these shots of like long rows and columns of desks, and on his desk there's an
adding machine, there's a typewriter, there's a telephone. And then people come by with the push carts, you know, with paper on it, and they like they'll put some paper on his desk and then he'll perform some calculations and then type up the results, and they put the paper on the other side of his desk, at his outbox, and someone will come along with a trolley and take that. He's literally a sell on a spreadsheet. That is exactly what he's doing. It's like take input, you know, execute formula,
produce output. And that's what each Ben talked about. Each floor of this insurance company's office is like one worksheet in a big fact sheet. The same number of people work at insurance companies today. No one does that anymore. So when you say that people do their whole jobs with AI, that'll last for a little while. You know. Let's say if you're content marketer, and honestly you couldn't a I couldn't do worse than most of the garbage
content marketing. But eventually people say, look, that's not your job anymore. Like no one's job is to perform a rhythm.
And that's a good way of looking at it.
I just remember my first job at Bloomberg when I was an intern, was to monitor the fax machine and to actually like bring the important faxes to someone. And that has that job has thankfully gone away, and I don't feel that bad about it.
I think hundred years the pace at which jobs become obsolete has definitely increased.
I think this idea that you know, tech will not end employment as we know it. It'll likely change and certain specific careers or categories will go away and new things will created. But as someone obviously in your career who has hired many engineers and coders, and this is a whole other aspect of AIS, like people are kind of blown away frequently, like how do you see like that specific.
Changing or specifically are freaked out right?
And is there going to be an infinite demand for the skills that we call coding or engineering today, or will like what we think of as a coder sort of be a different skill set.
It's a little bit harder to extrapolate, but definitely it will become different. But even people kind of tending to these machines who are generating code for them, software is really hard to make and it's like surprisingly hard, and
that's why there's so much crappy software. I don't know exactly what their supervisory duties will be, but it is going to be just like any wave of technology, it's like this massive augmentation and that people end up moving higher up the value chain, just like you know, I sometimes think about banks in I don't know, nineteen tens or something like that. I have no idea how they knew how much money anyone had. I think this all the time, talk about.
Card cattle all the time, like how did stocks work?
You opened the vaults, and I know, I'm glad you said.
It makes no sense to me that we had any banking and finance before computers. I just cannot rep my head around.
Well, you also had a lot of bank failures, which suggests that they weren't.
Maybe actually very good in it.
But then imagine being like a stock trader in the nineteen sixties than in the eighties, and then in the two thousands, and now you know, like the thirteen milliseconds you get by moving your servers closer to wherever in New Jersey make a real difference. No one was doing that before. But there again, there's no there's not fewer jobs impact probably a lot more jobs that are trying to make money off trading than there were the sixties or the eighties. So I think the same thing is
true of coders, whatever that role evolves to be. You know, like no one in the sixties was hiring physics PhDs to be quants at some hedge fund. But now, look there's another pathway for people who do PhDs in physics, and so I think the same thing will be true of coding as well.
Since this is now firmly an AI conversation, can we ask, you know, is this something that you're interested in? And is this maybe what your next project could be?
Weirdly, not really, I mean so I'm sorry. I'm interested in it as like a human, as a citizen, I haven't come up with anything where I'm uniquely able to contribute. I don't think in AI. Maybe that'll change because you know, it'll become part of the background of everyone's roles and you come to rely on it more and more, just like you know, this is probably a crappy example, but we're processing or you know, I would never would have been someone who is doing letter press layouts and moving bits
of lead around and something like that. But it definitely changed the way we're prosably changed the way I wrote because it's not longhand and I can infinitely edit it, and I wrote a thesis for my grad school and all that stuff. But maybe a better idea are better comparison is EXCEL because I think about in my life, I might have done as much financial modeling as all of humanity did until nineteen sixty five something like that.
Because when you because you can just like make a spreadsheet and then be like, oh, change those changes, changes everything cascades through, whereas before that was you know a lot of people with ledgers and calculators and pencils and paper, and allows you to think at a much higher level. So I think about AI again and that augmentation capacity and what it will enable us to do.
Just actually going sort of back to the last decade or two decades, I mean, you know, Slack was sort of like the to my mind, one of like the prototypical like software as a service companies, but there were all these other ones, and many of which we've never heard of, that probably made a bunch of money by like we're going to improve you know, dentist billing or ticketing at sports events. There's all all kinds of like little like niche categories that someone found an opportunity for.
Is there still like I don't know if low hanging fruit is the right word, but moderate hanging fruit in that world that has not been exhausted of essentially still taking like tech one point zero and really legacy tech. We've talked about a little bit with like Patrick McKenzie and you know, some of the old whether it's government and just sort of like, is there still a lot of the economy that hasn't really even got to like twenty tens tech yet?
Yeah. I mean, I think anytime you see you're in a financial transaction with someone and there's pen and paper involved, that there's an opportunit there. And I think a lot of the blockers tend to be regulatory. So like when you go to the doctor and you know you're give them like seven pieces of paper and you have to write your name on five piece. Sometimes you have to write your name two times on the same sheet of paper and the date over and over again. That's a regulatory block It's.
Also my big gripe about fintech, right, which is you got a bunch of people going like, oh, it's ridiculous that we're still writing checks nowadays or doing this or doing that. But often the reason is a regulatory constraint versus a technological one.
Yeah, So I think where eventually those regulatory dams break because well maybe I've mentioned with such confidence, but I can't imagine that one hundred years from now we're still getting seven pieces of paper when you go to the doctor's office and have to write our name on five
of them. I think there's a lot of opportunities for real improvement, and the low hanging fruit maybe never ends because as soon as you automate some layer and people start operating at a higher level, the people who are doing financial modeling aren't doing arithmetic anymore. There thinking about the business. Then there's new opportunities for automation that comme
at higher and higher levels. And that's what we really thought about at slack, the ability to maybe a little bit abstract, we thought about Slack is like a messaging bus inside of a computer. It's the like interchange or the traffic controller for all the thoughts that people are having. And a lot of those are just like, yeah, want to get lunch or something like that, and some of them are here's my extensive proposal for next quarters blah
blah blah. When you're able to improve the efficacy of communication versus the all set of paper memo that can schedule a meeting and it's three weeks from now or something like that, it opens up new possibilities, and the same thing is true with every bit of automation that you can do. There's a huge amount of business processes that are essentially humans translating between one database and another
because the databases aren't connected effectively. And eventually those databases become connected effectively and people move up the chain again and get to work on harder stuff or I guess stuff that produces more value.
AI to standardize databases would be amazing. Just on the topic of constraints and going back to the first part of this conversation where you were talking about how you know a lot of the empire building or hiring boom that we've seen in tech companies was potentially driven by low interest rates and you know, you didn't have a financial constraint on the amount of resources you could accumulate.
It does feel like in twenty twenty three, Silicon Valley, the tech industry in general, is in a very different financial environment.
We have higher interest rates.
We just saw Silicon Value Bank fail and that seems to have taken a big chunk of potential liquidity out of the market. How do you expect that to impact the industry and what are you seeing now.
Well, obviously we've seen a lot of layoffs, and I think probably you know, I never want to suggest that being laid off is a good experience for anyone. For the companies, it's almost certainly a healthy thing because a lot of companies are you know, that have twenty thousand people could probably do what they're doing with twelve thousand people or something like that. The higher indust rates, I think, I don't know, I don't want to say that they're good.
But go back to two thousand and nine, which is when the company that ended up becoming Slack was founded. This is, you know, like March of two thousand and nine. So I said, we're still probably in the Great Financial Crisis or like you know, maybe just just getting out of it. And if you're a venture capitalist like Excel, you could buy twenty percent of what became Slack for five million dollars, you know, and then you end up
making four billion or something like that. So I think from a if you're a VC, it's it's probably not all bad. You know, like some of your existing investments I think lost a lot of value and maybe we're going to have to defer realizing a lot of gains that you might have realized much more quickly a couple of years ago. But over the long run, I don't think it's a net bad for them for the companies. It can be a debt bad can.
I as a sort of cultural slash economic question, which is like I was, I think slack is like an acronym for something, right, Yeah, it's kind.
Of It's unclear.
So we have a lot of the conversation you're the one who created.
Well, there's we have a transcript of a conversation we were having internally where I suggest it as searchable log of all communication and knowledge. But I'm not sure if I Yeah, I'm not sure if I if we came up with the name slack.
First, because I think slack is catch Here I got to say, but the reason.
I actually asked the question is because the last decade that edition everything else was characterized by labor market slack, and so I wish think it's sort of interesting that this big company slack was like came of the decade
of like loose labor markets. And it also seems like that your technology changed in many ways, the relationship between management and employees, and employees and places can unionize more easily because they have slack channels and they can communicate in ways that maybe the management doesn't love, or maybe managers at companies want all their work, want them back to the office, and it's like, well, yeah, but we
can communicate on slack et cetera. Can you, like, do you have any like like sort of like broader reflections on the way like, because this is not really like a software question, it's a very slack specific question of like how you saw firsthand your software like changing this sort of employee management or just this sort of corporate environment.
Yeah. I think, going back to that idea of the ditch digger given a back up, most technology kind of amplifies our ability to accomplish something or augment us and gives us extra power. So that's true everywhere. Obviously, where you intend it to be true, that's great, or you don't intend it to be true. Sometimes it's great, sometimes it's terrible, sometimes it's somewhere in between. But the superpower in people's ability to have conversations at work will include
conversations that sometimes managers where they didn't have. I do think that's something that works itself out relatively quickly. And I also think interestingly, internally we will call that slack divism, andably someone else came up with that outside. But I think that's probably moderated quite a bit over the last year, just because the environment has changed. Because the other, you know, fact that comes with the low interest rates is that
people pay a lot of money for engineers. The engineers can always change jobs and get paid more and more money, and that's less true today. People are more worried about job security, so there's less And I'm not saying this is a good thing necessarily, but there's certainly less like labor organizing happening on people's slack insance that there would have been two years ago.
This is a slightly weird question maybe, but I mean one of the debates about work from home is are people actually more productive in an office environment or at home?
Within slack?
Did you ever have conversations about maybe like measuring productivity in some way using the communications channel?
We did, and they were all they all seemed kind of doomed. You know that there's a had a I don't know if she's still the CIO, but a woman named Luri Beer was the CEO of JPY. Maybe still is if so Hi, Lori and we have the great conversation once they breakfast at a conference and we're talking about like the history of trying to measure the productivity of software engineers, which is like famously impossible. So you would say, well, how many lines of code do they produce?
And then people would just change their coding style to be you yeah, exactly. Or you would say how many bugs get closed? And then instead of just fixing something right away, people take the time to go file the bug and then fix it and then close the bug.
Insert a bunch of bugs. Then you're the solution to your own problems.
Like as soon as you start to measure something then yeah, yeah.
Yeah, and so you kind of I don't know what we came up with, the way the conversation kind of ended was looking at employee engagement surveys. If engineers are happy, it doesn't necessarily mean that they're productive. But if they're unhappy, I think, do I have the backwards If.
They're unhappy, it probably means they're unproductive.
Yeah, because no engineers are not productive and and happy like they just it's it's frustrating to feel like you come into work and you put all this effort in and nothing happens, you know, like no one wants to work on debt end projects that get canceled and all
of that. So the same thing I think is true, Like if you think it's hard to measure the productivity have a software engineer, like marketing, it's impossible to measure, Like people just have no idea whether their marketing department needs to be five times bigger or five times smaller, or do they need one at all. I'm not sure what you do about that, like the measurement, because there's a lot of just kind of hand feel and in management.
It would be great if you could in some sense, but I think you also run the risk of limiting all the opportunities for serendipity and accidental discoveries and cool innovation.
I have I have one last question, and Tracy's gonna hate me for asking it. I already asked the cliche question. I already asked the cliche question about whether you're going to start another games company. Do you still support minting the coin to avoid a debt sealing disaster.
It's unavoidable.
We can anot have a single con we can talking about.
The coin, but when there's a when there's a prominent, famous person who on Twitter has expressed support.
Yeah, I feel like that's that's you and me. We bonded over over the coin, so yes, I think you definitely could. I think it's really funny. The debate about modern monetary theory seems to have come down to should we spend lots of money? And if you think yes, then MMT and if you think no, then you're against empty which doesn't seem to capture it at all to me.
Like the the idea that the deficit is a myth seems just obvious, and that the government's role in the amount of money is like the adjudicator of a basketball game deciding how many points you can have. Too many points, I mean, you can mess up the game of basketball, so it's not fun for anyone, Like you can cause a lot of inflation. But that idea that you need to have the money in order to be able to spend it is obviously not true if you're the government.
For what it's worth.
I'm not a big fan of MMT, but I do think the government should spend money.
So the Stuart Butterfield, this is such a treat to have you on kind of funny that our first guest in our new like physical video studio is the founder of Slack, which, more than anyone else, contributed to the ability to work on and operate and communicate remotely. But such a treat to have you in and thank you so much for joining me.
Thank you.
Next interview we can do via Slack. Just to just to even.
It out, Tracy, I thought that was a lot of fun. That was a real treat. That was just very I don't know in my head, in my mind, I had that hyped up and I felt like my mind it lived up to my own hype.
It was.
It was a wide ranging conversation, and I love that we went from like how did banks used to do business in the early nineteen.
Hundreds to like the future of AI market.
We were going to have to do an episode on just like how a bank work one hundred years ago, because in my mind, I do not understand how they kept track of anyone's how much money anyone had before digital technology, Like they really just what had a piece of paper for everyone?
They just opened the vault and see what's in there. No, we're all good today.
We're all good.
No, there is a lot to pick through that conversation. I mean, I do think like the idea of finances being a constraint on resources in the workforce, I mean it is kind of obvious, but also we are seeing it play out in real time right now.
So it was good to hit that.
No.
And just like this idea is like there's it does feel like there's multiple turning points at once, and I don't feel like anyone knows it's like pretty clear right like they're like, oh, well, this is who's this is who's going to win, this is who's going to make money,
this is going to be the business model. Like it does feel like even if we didn't have this sort of like macro change, there would be a tremendous amount of ambiguity about like how value is going to accrue and how companies are going to work and all of that.
Well, also the conversation about Microsoft and how you know, two years ago, no one would have expected Microsoft to be the sort of front runner in the AI game and yet here we are today.
That was really interesting.
Do you have any bets on what Stuart's next project is actually.
Going to be?
Even though he said no, I bet it, I still feels like he's probably gonna do a game.
Can I resist the lure? If you really try twice, it's like what times.
And then it'll pivot that something can be another world changing thing. That's my guest.
Shall we leave it there?
Let's leave it there?
All right?
This has been another episode of the Odd Loots podcast. I'm Tracy Alloway. You can follow me on Twitter at Tracy Alloway, and.
I'm Joe Wisenthal. You can follow me on Twitter at the Stalwart. Follow our guest Stuart Butterfield under the handle at Stewart, Follow our producers Carmen Rodriguez at Carmen Arman and dash Oll Bennett at dashbod, and check out all of the podcasts at Bloomberg under the handle at podcasts, and for more odd Logs content, go to Bloomberg dot
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