Odd Lots - Slack Founder Stewart Butterfield on AI, Software, and the End of the Tech Boom

Episode Date: May 25, 2023

Stewart Butterfield has been at the forefront of two epochal turning points for tech. First, he was the co-founder of the photo sharing site Flickr, that was one of the defining brands of the so-called Web 2.0 and the world of user-generated content. Several years after that, he co-founded Slack, one of the big winners of the software-as-a-service wars, changing how people work and how companies operate. Now we're at another turning point for the tech industry. Layoffs have occurred across the space and AI is putting traditional business models into doubt. On this episode, we speak with Butterfield about his experiences and what he sees coming next for tech.See omnystudio.com/listener for privacy information.

Today's show is brought to you by Vanguard. To all the financial advisors listening, let's talk bonds for a minute. Capturing value and fixed income is not easy. Bond markets are massive, murky, and let's be real. Lots of firms throw a couple flashy funds your way and call it a day. But not Vanguard. At Vanguard, institutional quality isn't a tagline. It's a commitment to your clients. We're talking top-grade products across the board of over 80 bond funds, actively managed by a 200-person global squad of sector specialists, analysts and traders. These folks live and breathe fixed income. So if you're looking to give your clients consistent results year in and year out, go see the record for yourself at vanguard.com slash audio. That's vanguard.com slash audio. All investing is subject to risk vanguard marketing

corporation distributor. Thanks for listening to Odd Lots, follow the show on Amazon Music for more future episodes or just ask Alexa play the Odd Lots podcast on Amazon Music. Oh, and welcome to another episode of the Oddlots podcast. I'm Joe Wisenthall. And I'm Tracy Al-Away. Tracy, you know, we've had a number of episodes about tech and some of the excesses of the VC boom, etc. The maybe the softening labor market. But it's one of these topics that like 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. No, 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 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's just really leap 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. These software is a service company, VC funded, etc.

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 posts some 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 at the forefront of two sort of like major apoccal tech trends, but I kind of actually think it's two and a half because so there was the web two

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 etc 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 megatrends together and maybe maybe might be on the verge of another mega trend we should ask the perfect person to see if there's another megatrend so we have the perfect guest we're going to be speaking with one and only Stuart Butterfield, the co-founder of Flickr, the photo sharing site, the co-founder of Slack, the workplace messaging app that everyone used that eventually sold to Salesforce recently stepped down as the CEO of Slack. So Stewart, thank you so much for coming on.

So I got to say, I meant to say what's also interesting here is both Flickr 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 mega 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's like a good warm up.

Okay, but you're not right now. No, I'm not right now. Okay. So, I mean, maybe we should start with the pandemic boom because, I mean, Slack really became this sort of poster child for the success of SaaS in 2020 and 2021. 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 overhiring, maybe there was access in various ways. But how did you experience it? Yeah, that was a big moment, like the March of 2020. But I feel like it really started 2015 or something like that. was looking back through some old interviews. And I think it was 2015. I might have the years a little bit off. Slack raised money in a $2.8 billion valuation.

And people were like, well, that's crazy. And even back then it was apparent. And we would say in interviews, this is just zero interest rate. Like, this is what happens. And so I think that kind of boost 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 before going back, I guess, 2015, 2016, we started to be launched in 2014.

We had a million dollars of ARR the following week. I think it took us about 18 months to get to $100 million of ARR. And that growth was crazy through that whole period. And then accelerated in March of 2020. I think the excesses are maybe not a different story, but I guess there's two parallel tracks. And one is like the Google Facebook track, which is they may be. 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 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. Empire building. Yeah, exactly. And even, you know, even if it's like a two-person empire, it's something. Like, you know, if you're, you 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, it's a very powerful incentive. So if you hire a thousand people, you have, you know, 996 people or, you know, roughly 100%.

We're like, I need to hire. So 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, licing or something like that. Like a 70-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 a 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 and the VCs, but also, like, there was this like real shift in corporate spend on technology. Oh, absolutely. Yeah. Sorry, I didn't mean to. No, no, no, no. And I'm always like, 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, as like, well, the cheap money VC's, but like something real, like really did change about how we use the, how the companies used to the technology. technology. Slack launched in the beginning of 2014, so not quite 10 years ago still. It's like nine and a half years in. And it's at a $2 billion revenue run rate. And we went public five and a

quarter years after we launched and, you know, we're acquired by Salesforce a couple years after that. So that's very real. Like it's 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 2014, 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 100 years ago today, it was American Leather Corporation. and, I don't know, U.S. steel, maybe it wasn't quite, but like the first tech companies were Westinghouse and General Electric and a couple of... Amalgamated jute. Yeah.

And everything has a life cycle roughly. You know, there's a couple of companies that survived for 100 plus years. But all of the... And I was... No, we should all say the word H-E-G-E-M-O-N-Y at the same time. So we can see what the real pronunciation is. One, two, three. Hedemone.

Okay, good. What two of them? We actually did a whole episode about the U.S. dollar recently where we said this quite a lot. Yeah. That eventually disappears. And I don't know how real the AI threat to Google is, for example, but Google has seemed absolutely invincible for a decade plus. Like it's inconceivable to me that anyone would compete with them on their ground. Yeah.

to build that technology and to build the infrastructure and to build the data centers and stuff like that seemed impossible. But maybe there's a way around. And obviously, if you're a venture capitalist, your job isn't to get a 15% return by investing in a basket of public tech companies to you're very much incentive to see the startups succeed. But they're also, you look back over the last 20 years or even just make it from the great financial crisis. The last 15 years, it's been a lot of value created. I mean, not just in 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 30 years ago, 35 years ago, probably. Like, is 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 one, it's interesting. Very effectively done. But the AI tech is all open AI. Sure. It's like it's a partnership. They were like ahead of it and they like got, you know, they did make that investment and people are excited like, oh, they're going to integrate it with 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, you know, huge profitability as leverage to leapfrog into the 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 things? 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's dilemma. People have 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. I mean, 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.

Right, 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 release this thing and someone relies on it and then someone gets injured or killed and an accident. You can come up with a million reasons.

Like, you know, I was not talking to the CEO of another. company once, and we're just talking about, you know, we're just complaining. We're like, oh, our life is so hard. But he was saying, 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 I started earlier was they need to hire two more people because they need, you know, there's a lot of work to do.

You haven't had anyone in risk. We've got to catch up. We've got to make sure we have the right policies and stuff like that. Fast forward 18 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 people work in that group?

23. So this is like over the course of 18 months. And every single one of the, 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 to everything. Infinite downside, basically, if they mess something up. Yeah, exactly. Well, beyond just risk, however, like thinking about Google and AI, like it is like, you 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 GPT 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 may be, like, AI is like a, I hate to use the word paradigm because I don't know what it means,

but a different, like the business model of AI is different than say the business model of search. All these companies like, will 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? A hundred percent. And I don't know that either I'm smart enough or 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-jurney or whatever. Then they'll get better and better. I think some big stock photos site just like had a buyout offer for a few billion. I don't know what's going. Anyway. Oh, yeah, yeah.

There's a funny story of a guy that said, if someone gives me $4 billion, then I will buy getting images. I will do that too if someone gives me $4 billion. Okay. But yeah, so there's like a pretty trivial example, but I think the longer term, it's a little bit harder to know how, like, the knock on effects. Because you think about previous ways of technological innovation, and I don't mean software or computers. I mean like just, you know, going back to steam power and stuff like that. It would have been tough in 1840 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 a back-oh, you can dig, I don't know, 100 times more, 500 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't accidentally knock down a building with a back-o, and you can't accidentally knock down a building with the shovel. we get to the point now where there's this incredible augmentation to our memory, to our ability to think. 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 I want to know. With a little card catalogs. Yeah, exactly. I can just like type in a couple of words. I don't even have to spell the words right. Like I just have to like kind of gesture at the words that I want and Google will return everything I could 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 dooms growing and the changes to our physical posture because we're looking down at 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 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 acknowledgement 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 a 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 19th century. And we kind of figured out how to have benefits of the Industrial Revolution without those negative consequences. I think we'll do that with all kinds of tech, but it might take a generation or two. Today's show is brought to you by Vanguard. To all the financial advisors listening, let's talk bonds for a minute. Capturing value and fixed income is not easy. Bond markets are massive, murky, and let's be real.

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That's 11 meals, free shipping and free sides for life, but only with the code fit at factoramills.ca. Factor, Canada's number one ready-to-eat meal delivery service. Just on the business model idea, can you talk to us about how tech companies actually make money off of AI. And here is where I, you know, very embarrassingly confess that I still don't really understand what Salesforce does. And how they make money. This is the big question. We're going to 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 going to like have to do a little like online segment of Stewart's answer to this. 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 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 $100 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

you for much cheaper, but you've 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 a checkup, or if I'm a retailer, the total of all their purchases. 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 to 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, they branch out to 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.

This is very relatable for me, by the way. Yeah. That's what most... I can't remember who said this, but someone's description of, like, here's what a lot of people's job are. And 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, paste into a PowerPoint, and then email the PowerPoint to people. And that it really is, like, that's what 70% 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 about our business. And that's almost certainly something that AI will do better, or at least having an AI co-pilot alongside you. So AI could, for instance, 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 opportunities within it that you as a human wouldn't have thought of. Yeah, absolutely. I mean, so both like people who are professional investors, I love the stories of, you know, they drive outside some parking lot in the mall and see who's, you know, which retailer has the most cars parked.

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 X? Should we sell more of Y? 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 you're going to do a better job with some companion, let's say, that finds those patterns more easily because they can just, they, the AI. I have this image of Clippy coming back and being like, have you considered? Think about things much faster to you.

Well, I mean, the other area, and just as you said, customer relationship management, it seems like AI 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 16, 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, A, like, will it be good enough so that like salesperson? salespeople can like talk to 100 clients in a day versus 10 and not maybe like two out of those 100 things time say something so embarrassing that it destroys their entire reputation. I don't know if it's good news or whatever. The fact is that people have done that for a while. You don't even need AI to kind of like automatically get a prompt.

You're sitting 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 under the illusion to the dentist personally. that the dentist is like paying attention. But I also, I get a lot of, 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 of 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, Stuart. I couldn't help but notice that you are the CEO of Slack Technologies Incorporated. And, you know, like something that a human would never, right? 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 demoed that voice

assistant that would call and make an appointment at the hairdresser for you? And it was like, it even like, it paused and said, um and stuff like, it was 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 in summarizes it and just says like Stuart has widgets to sell. And then, you know, your AI 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 otherwise. 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. I don't know what all the way is, by the way, but I see this as an example all the time. Ben Evans, who is a former VC, I guess,

Andrewston 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 Shirley McLean. It's 1960. Jack Lemon works at an insurance company, and there's like all these, you know, so 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 and his outbox and someone will come along with a trolley and take that. He's literally a sell in a spreadsheet. That is exactly. what he's doing. It's like take input, you know, execute formula, produce output. And that's what Ben talked about, each floor of this insurance company's office is like one worksheet in a big spreadsheet. The same number of people work in 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. Let's say if you're, you know, content marketer. And honestly, you couldn't, AI couldn't do worse than

most of the garbage content market. Fact. But eventually people say, well, that's not your job anymore. No one's job is to perform arithmetic. And that's a good way of looking at it. I just remembered my first job at Bloomberg when I was an intern was to monitor the fax machine and to actually bring the important faxes to someone. And that has that job has thankfully gone away. And I don't feel that bad about it. Over the last, I think, 100 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 in certain specific careers or categories will

go away and new things will create. But as someone obviously in your career who has hired many engineers and coders, and this is a whole other aspect of AI as like people are kind of blown away frequently. Like how do you see like that specific, uh, changing or will the really change? Yeah, because coders specifically are freaked out, right? And is, is there going to be an infinite demand for the skills that we call coding or engineering today, whether or will, like, what we think of as a code or sort of be a different skill set? It's a little bit harder to extrapolate, but it definitely 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 the people end up moving higher up the value chain. Just like, you know, I sometimes think about banks in, I don't know, 1910s or something like that.

I have no idea how they knew how much money anyone had. I think about this all the time. Talk about card catalogs. No, I think about this all the time. Like, how did stocks work before digital? You open the vaults and you take it. I know. I'm glad you said this.

It makes no sense to me that we had any banking and finance before computers. I just cannot wrap my head around. Well, you also had a lot of bank failures, which suggests that they weren't. weren't actually very good in it. But then imagine being like a stock trader in 1960s than in the 80s and then in the 2000s. And now, you know, like

the 13 milliseconds you get by moving your servers closer to wherever in New Jersey make a real difference. No one was doing that before. But again, there's not fewer jobs. In fact, there's probably a lot more jobs that are trying to make money off trading than there were the 60s or the 80s. So I think the same thing

is true of coders. Whatever that role evolves to be, you know, like no one in the 60 years 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 it'll become part of the background of everyone's roles and will come to rely on it more and more. Just like, you know, this is probably a crappy example, but word 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 WordPress and changed the way I wrote because it's not longhand and I can infinitely edit in and I wrote a thesis for like grad school and all that stuff. But maybe a better idea or a 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 1965 or something like that. Because you can just like make a spreadsheet and then be like, oh, change this, change this, change this, everything cascades through.

whereas before, that was 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, in that augmentation capacity and what it will enable us to do. Eating well shouldn't be complicated, but somehow it turns into recipes, prep, cleanup, and half your Sunday gone. Factors solves all that. These are fresh, ready-to-eat meals designed by dieticians, delivered to your door and ready in just minutes. No prep, no cleanup, no excuses. And it's not just about convenience.

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Now. 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, of love. 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 1.0 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 2010's 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, there's an opportunity there. I think a lot of the blockers tend to be regulatory.

It's like, when you go to the doctor and you're given like seven pieces of paper and you have to write your name on five of the pieces of paper. 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 book. This is also my big gripe about fintech, right, which is you get 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, like maybe a mission with such confidence. We hope. Yeah. But I can't imagine that 100 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.

But 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, they're thinking about the business, then there's new opportunities for automation that come at higher and higher levels. And that's what we really thought about at Slack.

The ability to, this is maybe a little bit abstract, we thought about Slack as like a messaging bus inside of a computer. It's the 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 you know stuff that produces more value. AI to standardized 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 2023, Silicon Valley, the tech industry in general, is in a very different financial environment. We have higher interest rates. We just saw Silicon Valley 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 that have 20,000 people could probably do what they're doing with 12,000 people or something like that. The higher interest rates, I think, I don't know, I don't want to say that they're good, but go back to 2009, which is when the company that ended up becoming Slack was founded. This is, you know, like March of 2009. So, I just said we're still probably in the financial crisis or like maybe just getting out of it. And if you're a venture capitalist like Excel, you could buy 20% of what became slack for

$5 million, you know, and then you end up making $4 billion or something like that. So I think if you're a VC, it's probably not all bad. You know, like some of your existing investments, I think, lost a lot of value. And maybe you'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 net bad. Can I ask like a sort of cultural slash economic question, which is like, I was thought, I think Slack is like an acronym for something, right? Yeah. It's unclear. So we have a

lawyer. You're the one who created it. 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. I think I'm much sure if I, yeah, I'm not sure if I. Yeah. I'm sure if I, if we came up with the name Slack first. I think Slack is catchier, I got to say. But the reason I actually asked the question is because the last decade in addition to everything else was characterized by labor market slack. And so I was like, 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 in 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 and companies want all of their workers we 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 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 abacco, most technology

kind of amplifies our ability to accomplish something or augments 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 superpowering people's ability to have conversations at work will include conversations that sometimes managers wish that 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 slackivism. And probably 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 fact that comes with the low interest rates is that people pay a lot of money for engineers and engineers can always change jobs and get paid more. 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 Slack and since 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, there's a head, I don't know if she's still the CIO, but a woman named Lori was the CIO of JP.

Worry, maybe still is, if so, hi, Lori. And we had this great conversation once, I had breakfast at a conference. And we were 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 right yeah exactly um 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 and then you're the

solution to your own problem exactly good heart's law right 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 or the where 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? No, no, that's all right. If they're unhappy, it probably means they're unproductive. Yeah, because no engineers are not productive and happy.

Like, they just, it's frustrating to feel like you come into work and you put all this efforted and nothing happens. You know, like no one wants to work on dead-in 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 of you 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 in management.

It will be great if you could in some sense. But I think you also run the risk of eliminating all the opportunities for serendipity and accidental discoveries and cool innovation. I have one last question, and Tracy's going to hate me for asking it. I already asked the cliche question. I know what it is. 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 selling disaster?

It's unavoidable. We cannot have a single conversation without talking about the coin. But when there's a prominent famous person who on Twitter has expressed support. Yeah, I feel like that's you and me. We bonded over. Over the coin. Okay. So yes, I think you definitely could.

I think, you know, 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 MMT, which doesn't seem to capture it at all to me. Like 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 or a basketball game deciding how many points. You can't have too many points.

I mean, you can mess up the game of basketball so it's not fair. 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 there we go. There we go. 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 and operate and communicate. remotely, but such a treat to have you in. And thank you so much for joining. Thank you.

Next interview, we can do via Slack. 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 mind, I had that hyped up and I felt like in my mind it lived up to my own hype. It was a wide-ranging conversation. And I love that we went from like, how did banks used to do business in the early 1900s to like the future of AI and the labor market? We were going to have to do an episode on just like how a bank worked 100 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 open the vault and see what's in there.

No, there's like, no, we're all good. We're all good today. We're all good. No, there was 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. So we are seeing it play out in real time right now. So it was good to hit that.

No. And just like this idea, 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 there's like, oh, well, 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 stuff. Well, also, the conversation about Microsoft and how, you know, two years ago, no one would have expected Microsoft to be the sort of frontrunner in the AI game. And yet here we are today. That was really interesting. Do you have any bets on what Stewart's next project is actually going to be? Even though he said, no, I bet it's still feel it's like, well, he's probably going to do a game.

Cannot resist the lure of video games. I just feel it's like if you're like tried twice. It's like, what? Well, no, third times a charm. Yeah, that's my bet. And then it'll pivot. they can be another world-changing thing. That's my guess.

Shall we leave it there? Let's leave it there. All right. This has been another episode of the Oddlots podcast. I'm Tracy Alloway. You can follow me on Twitter at Tracy Alloway. And I'm Joe Wisenthall. 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 Armin and Dashel Bennett at Dashbot. And check out all of the podcasts at Bloomberg under the handle at podcasts. And for more OddLod's content, go to Bloomberg, dot com slash oddlots where we post transcripts. We have a blog. Tracy and I have a weekly newsletter. And check out our Discord. Discord.g.g. slash oddlots where we chat 24-7. And stream Bloomberg originals on Apple TV, Roku, Samsung TV, and more. Tune in at 10 p.m. Easter time. The news doesn't stop on the weekends. Context changes constantly. And now Bloomberg is the

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