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Hello and welcome to another episode of the Odd Lots podcast.
I'm Joe Wasnal and I'm Tracy Alloway. Tracy.
We're recording this February eleventh, and IGV the software ETF down another three percent today.
It has been ugly in software. Everyone's throwing around the term SaaS apocalypse. I mean, the great thing about SaaS is there are a lot of things that like rhyme with it, a lot of hominems, so you can you can make all those puns. Yeah, exactly, SaaS is trash whatever. But I'm looking at the share price of Salesforce, oh yeah, in particular because I always think of Salesforce as sort
of like emblematic poster child. Yeah, post child of like a software company that I'm not really sure what they do, but yeah, it's it's just ugly.
It's basically been cut in half, hasn't it. Since it's peaked like an early twenty twenty five. Right now it's one eighty four eighty.
Four, and it's all your fault, shoe.
It's all my fault.
That's right, because earlier in the year, after we got back from Christmas, vacation or Christmas break, you know, around that I'd seen everyone playing around with claud code, and then I had to do it. We did an episode, and so people were like, oh, if Joe Wisittal can like figure out claud code, that there must not be any value to any of these companies at all.
There.
You know, you mentioned Salesforce. That's far from the ugliest one. I'm looking at Atlassian, which makes a lot of like workforce productivity companies, like some Slack competitors and stuff. That was a four hundred and fifty dollars stock back in twenty twenty one. That's an eighty six dollars stock. So like, yeah, it's ugly, and yeah, as you said, everyone is realizing that if any old fool can write software, maybe these companies, yeah, I don't have much value.
I mean, I will just say it's not just software right now. So we're seeing sort of rolling series of concerns where like every time AI does something or create some new product, it hits a particular industry. So on Monday it was the insurance industry, insurance brokers, and you know today Wednesday, February eleventh, I think it's some of the stockbroker firms.
And yeah, all you have to do is just say AI industry and there's a you know, it's really there's a lot of anxiety. But there's something that doesn't make any sense to me about this or the thing that I'm wrapping my head around.
It's like, sure, any of.
Us could easily like write some software, but like writing software is a cost center for these companies.
Right.
If you're salesforce and you can trivially reduce the cost of building software, that's also a benefit for you. And there's a lot more to a software company than just code generation, because there's all kinds of you know, network effects and links into this. It's like a software company is clearly more than just code, and so the fact that maybe code can be generated a lot cheaper does not screen to me, like, oh, these companies are worth lessing views.
Sure, but at the same time they've been pricing. Their pricing is based on that assumption, right, like that there is no competitor for what they're doing, and suddenly you might have an in house competitor.
Absolutely, But you know, it's like network effects and do companies want to start like building their own like payroll software Anyway, I have a lot of questions about this sell off, and to your point.
No, no, no, this is you doing like penance first, for causing causing the sell off.
All right, let's talk to someone who actually might be able to answer some of these questions for us. We're gonna be speaking to someone who's been in the software space, an investor in the software space for a long time, recently put out a great deck really diving into SaaS of the SaaS apocalypse and what kinds of companies are thriving and what kinds of companies were struggling even before everyone started talking about AI code generation and all that.
We're gonna be speaking with Jared Sleeper. He is a partner at Avenue, which does a growth investing private company.
So, Jared, thanks for coming on off.
Yeah, my pleasure. Excited to be here.
Why are we talking to you? Just you know, for our listeners. Apparently your first time on a podcast, which is crazy. But why are we talking you? Give us a little bit about.
Your background investing in software and understanding the space.
Yeah, my pleasure. So I think one thing that makes me a little bit different in the investor world is that I've spent time investing in early stage startups, public companies, and everything in between. So I spent a chunk of my career at an early stage venture fund in Boston called Matrix Partners, working with an og SaaS investor named David Scock, and then was also at ko TU where
I ran public software. And so I've kind of have this like experience across a spectrum from ground floor startups to looking at the big public companies, which I've done for the last ten years.
Perfect guest, Perfect guests.
So give us some color on the mood in software at the moment. Are people like I don't know, hunkering down in their bunkers. How bad is it?
Yeah?
I get texted constantly from folks on the byside, just you know, retrenching. I can't believe this is happening, can't go lower. I keep saying that it's one hundredth time I bought the DIP. You use the SaaS apocalypse like casastrophe is my science. It's definitely one of those moments. And we were talking about this a little bit earlier before starting, But one of the things about software that's really fascinating is there's very few folks, even on the
buy side who really understand how software works. It's one of those roar shot tests kind of sectors where no almost no one's logged into Salesforce and clicked around much less than a Salesforce admin and understood the full complexity. And so when there's panic, there's not a lot of support for the stocks, and people, you know, get scared very easily.
Well, explain what this means.
So, for example, in a lot of companies, it's like you're saying that the people who investor trade these stocks, they just know them as financial tables basically, and they have some idea of their financials and some idea of their customer base, et cetera. But they don't have like a great intuition for the product onlike say, you know people who use Instagram and therefore might have a feel about meta for example.
Yeah, if you're an investor in Lulu Lemon, you have a pretty solid conception of what that business is. You can go into the scioga pants exactly. You can buy the product to ship it to yourself. If you're an investor in Viva, which makes CRM software for pharmaceutical reps, I bet you there's almost no investors in Viva who have ever been inside the product even once, much less used it on a day to day basis and understood how it works.
So I'm going to go way back in time and start, I guess the very beginning, But why is it that software like this, you know, payment management systems, whatever, Why were they historically not developed in house?
Like?
How did we get this model where we have these huge software companies that are really you know, to date have been really integral to a lot of businesses.
Yeah, it's a great question. You know, back in the very early days of software, like back in the seventies or eighties, there was a lot done in house, and we've seen a very clear mixshift over time towards using third party software. And what it comes down to is the software was expensive to build and maintain, and there's this need for an ecosystem of integrations around it, which
are also expensive to build and maintain. And so if you look at a software company, it can afford to have one, two, three thousand engineers plus partnership teams, et cetera, all working to build the perfect piece of software for a given application, and then what's striking And this will come up a lot more in this conversation, is not selling it for that much money.
Right.
A lot of software companies report a stat which is the share of our customers that pay us more than one hundred thousand dollars a year, And one hundred thousand dollars a year is less than half of the fully
loaded cost of a software engineer, right. And so the software model was build a product that can be applied to thousands of customers and it's the same product for every customer, and then sell it to them for way cheaper than they could ever hope to build it themselves, even less in the cost of one employee.
Okay, I'd love to just talk long term software history even before you know, we think a lot about SaaS and these startups and stuff like that. But like a lot of the big companies that we think of in software, especially like pre Salesforce, whether it's like SAP Oracle Microsoft obviously, aren't there a bunch of third party companies whose job is to just like help install it for you, Ye, like an SAP installed, And that'll be a totally separate company.
Because it's so big and it's so unwieldy and complex that you actually you can't just like install it yourself, or it has to be customized or whatever.
And there's two parts to that which I think are important. One is the integrations into your existing systems. Right, a lot of big old companies have old databases, old applications, and it's important for everything to be stitched together. So you need software engineers and you know, consultants to go in and understand those existing systems and kind of get them linked up to the new systems. But the other one, which is probably bigger, is just people management and change management.
You know, any software system is the combination of the code and all of the individual users who have learned how to use it. If you're trying to change out your CRM at a company, that means training every single sales rep on how to use the new CRM and getting it right. And if they get it wrong, then you lose deals that quarter. And so, you know, one of the kind of tropes in investing is if you see a company that's doing an ERP transition. ERP stands
for Enterprise Resource planning. It's the kind of core software accounting you know, supply chain, et cetera. That company's probably going to miss its earnings over the next one or two quarters because those transitions are so painful and so yes, there's a big consulting complex around it that does its best to come in and parachute in the talent that's required to make those transitions smooth. And that tells you something about what makes software so sticky, or at least has historically.
It's third party agents all the way down, I feel. But actually, on this note, so we hear the integration point brought up a lot, and I think the very first episode we did on claud code we talked a little bit about it as well. But like, if you have something like claud code where you can just give it permissions to make changes to your computer, does some of that integration expertise actually start to go away, because
presumably we are going to get AI. I would assume at some point, given the rate that it's developed and improving, that we'll be able to do this like plug itself into various systems.
Yeah, one hundred percent. I think the challenge of writing the code for the integrations is going away. That's not the bulk of the challenge for a majority of integrations. It's about really deeply understanding the prior system and how it maps to the new system. And the reality is, within most organizations that's a human problem. It's hey, this column says status two thousand and four, what does that mean? Like? How does that map to the new system that we're building?
So you have to go talk to someone and understand it. And so there's certain types of integrations where I think they're effectively solved problems now because you can write a quick write into chat in to clog code and get a perfectly written piece of software to make it happen. And then there's others that are just fundamentally human problems because the data doesn't exist in digital space.
Let's talk more about that, because really it is pretty extraordinary the degree to which I don't know it's the working code. I don't know if it's high quality code, but certainly these models can generate working code, and it's
just it blows my mind whenever I use it. But talk to us a little bit more about from the perspective of various software vendors, and I'm sure there's a range about what they're selling and how much is it code versus how much is it other stuff, and which ones are more exposed to the pure like code generation ability.
Yeah, it's a great question, and you're one hundred percent right. It's producing working code, and frankly it has been for the last year or so. I built my first leveable app that was working in production about about a year ago, and it's even intensified in the last three months.
Right.
I think when people buy software, there's a set of things that they're buying. One thing that I think is important for everyone understand is that open source software has been a thing, and there have been free, open source versions of almost any software you could buy for all of recorded history. There's actually some companies that are public that built their businesses packaging that open source software and adding a few custom features and then support on top
of it. Because of the companies reliant on an open source database or a company like Elastic with its Elastic Search product, which is an infrastructure tool and it breaks, they need someone to call, both for COIA reasons and because it can be very complex and technical and they need to quickly understand it. And so that has been a big part of the story historically, is that need
to you know, have support. Another thing that you sell when you sell as a software vendor is what I call herd familiarity, which means everyone on Earth knows how to use your software, which just simplifies the training and onboarding workflow. I'll give a few examples because I'm sure it's a new term for listeners since I.
Made it up.
You know, Zoom is a great business. Microsoft has been giving away a free version of the product forever in teams. Why do people use Zoom Because in certain industries almost everyone knows how to use Zoom. They have their Zoom setup, they have their virtual background chosen. They're not going to fumble around for the first minute or two on the call, and that's well worth the twenty dollars a month to have a Zoom plan. But that applies to lots of
other areas as well. So think about Microsoft Excel for example. You might be able to use Google Sheets to do the same thing, but you really want to retrain every person who comes in on the Google Sheets shortcuts versus Excel shortcuts. It's not a good use of time, especially
when the software is already so cheap. And so that's another plank in what people are buying when they buy software is the standardization and the knowledge that they'll be able to hire employees who have that, and then there's things like brand again, the kind of ecosystem that comes around it, and so it really is more than just the raw code.
We've been joking about this, but the idea of software companies value lying in being a scapegoat essentially for when things go wrong is kind of funny and dystopian, I think in many ways.
Yeah, I mean, I think you know, it's a real fear, right And the way I think about it is, there are two arguments against software right now. One is the world is going to stay the same, but software just going to get a lot cheaper over time now that it's cheaper to build. And I think there's no one who would argue that it's not gotten dramatically cheaper to build for reasons that we laid out in our deck and we can talk through it more. We don't buy
that argument. I don't buy that argument. But the second is the world's about to get really weird and the way that knowledge work happens is going to change. And if we think out three, four or five years, who knows if there will even be customer support reps or sales reps or software engineers, and I think that's what's causing the kind of hit to the share prices lately, is this terminal value concern.
Yeah, it was interesting.
So one of the companies that's been associated with the uh, what did you say casastrophe?
One of those companies that's been.
Caught up with this blue owl, the private investing firm Private Credit. I read through their conference call and their CEO was like, not only do we not see red lights, not only do we not even see yellow lights, we actually see a lot of green lights, which I think is really interesting.
Because it can fit with this idea of.
This year could be fine, next year could be fine, year after that could be fine, and then the year after that could be zero or at least that's the anxiety that there's this terminal value talking.
That's like a cliff rest.
Yeah, there's this cliff Yeah. I think it's really helpful.
You know, this is our second iteration of the deck, and so we kind of force ourselves to recenter on what actually happened since the last deck, right, and there's a very clear pattern in software and what happened over the last five years, which is the pandemic. People freaked out at the beginning, but it was rapidly clear that it was an accelerant for SaaS as everyone tried to digitize their companies, and so you had a spike in
the growth rate and net retention of the businesses. It peaked at just over forty percent and twenty twenty one for the median software companies. That's really nice annualized growth. And then there was a hangover and that slowed down, and we wrote eighteen months ago that that reflected the sector sort of maturing. The adoption had just slowed down because most folks had adopted the software that they needed
under the pressure of the pandemic. And so for the last few years after that, we saw this degradation and growth rates across the sector. By the beginning of last year, the median company was growing eighteen percent instead of forty percent, so you saw a pretty significant draw down. What's fascinating is that if you look at the actual financial performance of the companies in the last year, it's been pretty good. That growth rate has held. It was eighteen percent again
in Q three. Net retention has also been consistent at about one hundred and ten percent. That's revenue from existing customers over the same revenue from those customers a prior year. So there's not a churn issue developing or a lack of expansion within the customer base, and a lot of the companies are actually accelerating growth or guiding to accelerating growth. We have a chart showing the number of those companies has increased each quarter of the last three successive quarters.
And so there's a lot going on right now with the terminal value. But it's very hard to argue that this is something that's happening today and showing up in the numbers. The thing is investors are sharp, right, and they're constantly looking at that booking.
Yeah.
I mean look at CHEG right, which went down very quickly in the aftermath of chat GPT coming out, and that was completely correct.
Right.
Investors were ahead of that, and of course for the first few quarters the management team of CHEG, you know, had their heads in the sand, but then it became clear that it really was existential to their business.
That's a fun chart.
I thought I was looking at a typo because I saw, wow, that was a near one hundred dollars stock in February twenty twenty one.
It is now a sixty one cent.
Stock and you have to give the markets credit. Like the second chat of T came out, people were like, this company's in big trouble. They didn't wait for it to hit the financial results, and so there is signal and what people think.
I have a bunch more questions, but just briefly, where does data actually fit into all of this? Because the other thing we hear about AI is maybe the models don't matter that much, but it's the actual data that you have access to. And I imagine the customers themselves of SaaS companies, they have their own data. Do the SaaS companies have their own data as well? Can they build off of that?
Yeah, it's a great question. And we're here at one of the world's biggest data companies, so very apt. Well, disclosure data is definitely something that gets more valuable in this world. If you think about a stylized AI model, it could have PhD level intelligence in a domain. But if you hired a PhD in your company and sat her down on her first day, she wouldn't be very useful, right. She would have to understand how the organization functions, where
things live. Do I trust this chart or that chart. I need access to the Google drive, I need access to Slack, I need to spend some time reading up and so we call this kind of context.
Right.
It's all the extra information that an AI needs to get something done, no matter how intelligent it is. And we wrote about this in the chart in the deck. But there's a real question of who becomes that system of context. And you're right, a lot of the software companies do sit on a pool of very important data. Let's talk about Salesforce for example.
Right. CRM is where.
You track the records of every customer. You have every prospect in your pipeline, all of your historic interactions with them, notes from sales reps on what's going on the status of their account, their customer support requests. It's an incredibly complex piece of software for a large enterprise, and obviously if you are an AI agent working within a company, you would need access to that in order to get almost anything done. Right, But you need more than is there.
You don't know what happened at the sales dinner last night unless the rep took really detailed notes. And I can tell you one comment learning and software is they do not take very detailed notes.
Especially have a sales party, right, yeah, exactly.
Can people assume that software management teams know exactly what's going on, but they're looking through really messy salesforce data and doing their very best.
Now I'm imagining a sales agent being like the Cabernet was exquisite at last night's party, just putting in all these irrelevant like diary entries, exactly.
But a lot of that context does live in human brains. You know, a sales rep meets a person at dinner, gets to know their kids, figures out what sports team they root for, and they're not automatically pumping all that into the CRM. And so there's this race to collect the information that an AI agent would need in order to actually take proactive action, and the software companies have
a position there. But there's also this set of AI native startups that are coming in building actual agents who are doing their own work to collect that context.
And that's one of the.
Battles that we saw, you know, kind of highlighted in our deck is whoever wins that has a chance to be a really valuable company.
You know what I think about and I think you talk about this in your deck, But when I think about software, I sort of have like if there's a spectrum, you know, I think about Salesforce dot com, which is a platform, and there's third party developers that build on top of Salesforce and they sort of offer any everything, And then I think about something niche like this is the company that makes point of sales software for dentist's office,
and they went around by giving them free payment terminals, and they joined y Combinator, and you know, they signed up ten thousand dentist office and then they pay those offices pay them ten dollars a month forever for access to that. You know what, I'm just making it up, but things like that. Is there a side of the spectrum that's more at risk here? Is that spectrum legitimate way to think about the industry or is there threats on sort of wherever you look?
Yeah, it's a great question. I mean, certainly in the world gets really weird scenario, it's not clear there's anywhere immune from threats, but it's important to think through what it looks like. I think what's most at threat is companies that serve enterprises with very customized software already or
software that takes a very heavy implementation. And the reason is if anyone's going to take advantage of this wave of technology to really you know, advance and replace a core system of software, it's going to be the enterprises that have the resources and the customization needs. If you
think about SMBs. You know, my dad runs our family's grocery store in the family for one hundred years, and he just changed his point of sale for the first time in a few decades, and it was a really messy process.
It took a long time. Your dad, come on all alls, Yeah, sure, we love, we love to.
All about independent grocery. And but you know he's certainly not going to sit down and vibe code himself a point of sale system and put the store on it. I can guarantee you that, nor will any dentist.
Right.
There's a chance that someone comes along with a cheaper version, but you know, I think that's not something he's going to switch to anytime soon. He's going to go through
that pain for another few decades to come right. And so it really is, you know, kind of company by company, Like I'm doing this exercise right now on X where every day I look at a different software company and just think hard about what will AI look like for this company, And it's really interesting when you press I'll give an example like DocuSign, which I think to most investors would seem like an incredibly simple, easy piece of software. Right,
it's an eating software. We've all experienced it. DocuSign has more employees today than open ai and andthrop it combined god, which is a crazy stat and probably reflects that labor is inefficiently allocated across the market. But when you actually double click into what DocuSign does, there are ways in which it's very complicated. Right understanding the signature regulations in every country around the world, what does it take for
signature to be legally valid. Most of its signatures are done as an API, so folks are integrating it into their own applications. And there's a benefit to using docu sign which is the brand people have been giving away
free e signature software for a very long time. But if you're a company of a certain esteem, you want to make sure your customers trust what they're signing, and if they're getting a contract from you, you'd much rather say DocuSign than xyz sign that someone vibe coded, right, And so I think it's really important to look a
company by company. It's definitely a stock pickers market where there's some that are either relatively immune or have a chance to benefit, and tho's others that could be in real trouble.
So is the argument the bold case for software, or at least the non sudden death case for software. This idea that like, Okay, if you have a software company that's producing I don't know, like DocuSign, you're able to sign documents digitally and track them and share them and all of that. You can build more quickly and more efficiently off of that base model and provide new versions, new customizations for customers. So I could do DocuSign for dentists,
just to stick with that example. I don't know what specific needs dentists would have. I don't know, maybe marking up like teeth or something. Yeah, and then I can do like DocuSign for doctors and DocuSign for sales agents or whatever and just keep going.
Yeah.
I think that's right. I actually kind of think of it as there's three cases. There's the software gets wiped out case, there's the not much happens to software case, and then there's the bual case where the software companies capture a lot of value. I think it's a little different than them adding a lot of features and functionality. Frankly, I think a lot of software products today are pretty mature.
There than thousand engineers working on them for ten years, and they've built not all, but most of the things that you'd want to build with today's technology. But with agents, there's ways to automate a big chunk of the work. So software company that's done this very well is Intercom. Intercom sells customer support software. It's those little widgets on the bottom right hand corner of websites. They were the
creators of that. They had a nice business, but then they got very aggressive about building out an AI product called Finn, which answers customer support queries on its own. And they've i think they've mentioned that it's almost one hundred million of ARR now on a base that was you know, like three hundred million of ARR or something
like that. And so they've really reaccelerated their business by building an AI native tool that actually solves the work, not just a tool that not just kind of exists as a tool that humans use. And so yeah, I think that's like the mega bowlcase, right. I think about it like almost a transition from brick and mortar retail to e commerce, where you have a brand new way of doing business and you have a bunch of legacy companies and some of them will probably just exist as
they always have. Others can benefit from the change and add new business lines. You look at Walmart's share price, it's done amazingly well at incorporateing e commerce into its business. And then there's going to be some that are like Seers and go away.
That's funny. Sears always reminds me of my dad loves Sears because he always said the parking lot was empty when he goes to the shopping mall, so he always went through Sears anyway. So I understand like the cost argument and brings down the cost of code. Maybe you have fewer employees or whatever, But where does growth actually come from in that world? How are you expanding your customer base?
Yeah, you're really going to them and saying we are replacing human labor. And there's a different pricing paradigm.
Now.
You used to think of us as something you paid, you know, twenty thirty forty fifty dollars per seat, per month for as a tool for your employees, almost as if you know your employees are artisans and they're getting a toolkit to work with. And now we're just selling
you an employee or the results of an employee. So you know, we will sell you customer support tickets getting closed out for fifty cents or a dollar per ticket, and you can do math of what it would cost you for the human to do that, or what it would cost you for AI to do that, and we'll be cheaper. But we're also dramatically increasing what you pay us because you know, we're cutting into a completely different stream.
And so that's what I think it looks like. We see a lot of exciting examples in the startup space of companies that are getting much much higher pricing.
This is a totally new pricing model for software. If you just recorded another episode and they guess teased that, but talk to us about like results based pricing, talk to us.
Yeah, it's results based pricing. There's a lot of questions on how it'll ultimately shake out. Fundamentally, what these companies are doing is they are reselling intelligence.
Right the core model.
Vendors Open Eye and Thropict, Google have created a way to get elastic intelligence. And if you have the right data and you can put the right harness around it, you can now sell that to your customers. What's an open question is how do you price that relative to the intelligence. So I was talking to someone this morning. You said, I think fifty percent growth smart on intelligence are about right. But we see a lot of variants
in how startups are doing it today. Some are getting eighty percent gross margins on top of the model vendors. Others are getting twenty percent. But what's absolutely true in any case is if you're able to do that, you get much much higher pricing in total dollars than you did before orders a magnitude in some cases.
But just to be clear, like the cost savings, it can't be priced so high that the company that's using the software to produce these outcomes like isn't saving money, right, that's the balancing act.
One hundred percent. But I think if you think about when we talk about this a little bit earlier, think about where software pricing was already right, you know, think about salesforce. You know, at the elite tier, you know,
eighty ninety one hundred dollars per user per month. So for round numbers, say one thousand dollars per user per year, for sales reps who could be making on average two hundred and fifty three hundred thousand dollars per year, if you have a technology that can come in and replace a sales rep, you can charge fifty thousand dollars still give the customer or a five x ROI, and then you have effectively fifty x your take rate on that revenue.
And so that's the exciting opportunity. That's that's what has people excited in startup land for sure. If you talk to folks from Silicon Valley, they are foaming at the mouth about the opportunity to really expand tech spend in this way. And that's also the opportunity for the software companies that get it right.
There must be another risk too, which is that if you can sort of resell intelligence it'd say an eighty percent gross margin, then for the model makers themselves, they're like, well, why do we just want to be this is gonna sound weird. Why do we want to be the dumb intelligence?
Right?
And that's sort of like we don't they use it. We don't want to be the dumb pipe. If we saw that like in the cloud era, right, the Asias and the Google Cloud and the Amazon One, they didn't want to just be commodity cloud and they started building like medical features. They wanted to differentiate themselves. So it must be a risk for the company's reselling intelligence that it's so lucrative. And then like, how are you thinking
about the core model makers themselves? Yeah, and how they're thinking about expanding into some of these fields rather than just piping in intelligence for them.
Well, look like in any situation, they're gonna have to make decisions, right, So in Amazon, you know, built aws, they had to decide where are we going to press and where are we not? Are we going to sell database software or are we going to let other vendors do that on top of us? And they kind of made those decisions as it went out. What's really interesting is if you look at the foundation model vendors, they
have been racing towards the application layer. Both cloud code and cowork and open ai codex are applications that people download and use right, And I think that reflects this understanding that there is value in getting the users used to using your application. Otherwise, as you know, you may you risk being an API that's commoditized. People switch back and forth between you and that kind of application vendor has that control.
So one of the advantages that software has is like this network effect comfort software as a security blanket for management. Right, But at the same time, people are getting really comfortable with AI, like telling them everything. And I keep thinking like if part of the sales pitch for software is like this sense of comfort, but then AI is rapidly becoming the thing that you talk to for everything. Does it eventually just become a portal for doing all these different things.
It's a really interesting question, and this is where there's probably the biggest disparity between how enterprise buyers think and how humans think. Right, I'm sure you guys have seen claude Bot and the kind of rise of these, you know, open source agents that people are deploying for themselves, giving it and access to everything their whole computer, et cetera.
That's Joe.
Yeah, no, I didn't install I didn't install Club.
Oh you didn't know.
I'm getting mindset up. I lacked many with a hammer next to it.
Well, I'm really curious why not?
Because of this issue?
Yeah, because of that and it just seemed like a potential waste of tokens and stuff.
And yeah, and then then it turned out that for a while on Moltbook, which was the social media for all of the all the APIs are available in a public facing database and one could go read and so it was like a completely open system.
That had to get fixed.
And so, you know, enterprises really do worry about this stuff, and they worry about it for a good reason. You have another really interesting example. So there's a bunch of startups that help you record zoom calls and transcribe them.
All of those zoom calls then become legally discoverable because they're transcribed somewhere, and so you have vcs in Silicon Valley who will refuse to use them, and you have other firms that are all in and recording everything that happens across the board so that they can upload that into AI as context. I think it's a really it's
a really great point, you know. And one of the things that makes me wonder is companies that are willing to skirt the rules or you know, play fast and loose, will be moving much faster over the next two or three years. And One of the reasons big incumbents struggle is because they actually do have to care about this stuff.
They have stuff to protect, they.
Don't want to be sued. They can't handle a major breach, and startups are able to just move faster given that.
So every time software stocks sell off with this and people say, oh, they micro bargain hunting, and they say what's cheap and what baby is being thrown out with the bath water?
Someone always a bunch.
Of people is like, yes, they look cheap, but have you considered a stock based compensation? And it turns out that these companies are not nearly as profitable once you factor this in. Its very interesting note from Barkleys I think it was I think it was Barkleys. This is very interesting, and it said our European investors are always asking about SBC. Our American investors only ask whether there's a crisis.
I think tells you something about.
The differentiat in Europeans and Americas. I thought that was a fascinating sociological observation. Tell us, like, how should we think about the cost, because again, if code generation is a cost base, presumably these software companies don't need as many employees either. And they could pair back on this, So talk to us about how we're thinking about the costs inside the software company.
Great question, and yeah, I mean certainly theoretically true, right, but aside from Elon cutting eighty percent of twitter X's headcount, we really haven't seen any companies take the pill and kind of realize the benefits of that. The SBC debate has been going on for a long time. I've had it at nausimo of the course of my career. It's a real expense. You're issuing your employees stock. They value it like cash. Many of them auto sell it the
day at vests for them. And I think what the problem that it creates for software companies is they the management teams are addicted to reporting non gap, which excludes
the impact of SBC. And so if you are an entrepreneur who founded the software business who's technical, hasn't really ever cared more that much about the financial side your product person, you may think that you've been doing a good job of being a profitable company because your CFO telling you, well, we're at a twenty five percent non gap operating margin. That's pretty good when the reality is you're running break even, which is a very common state
of affairs. You know, we looked at the whole universe and the media and public software company has a five percent non gap net income or gap net income margin, which is not enough to value the companies on. And so it creates this dynamic where you know, yes, there's a terminal value concern, which by far the most important thing, but there's also no floor.
Right.
I was looking at the earnings report from fresh Works, which is a mid market seller of customer support and IT management software. It trades at one and a half times EVY to sales. If it ran at even a ten percent gap margin, it'd be trading at fifteen times earnings. You know, that's which is a pretty attractive place to be. You could get some value investors, maybe some European investors interested in buying it there, but it doesn't have material
gap earnings. And on their earnings call, there was no real you know, sense of trajectory towards that, and you see the share price down sixteen p exactly, and like, the top line results were actually pretty good, and so there's a real issue here on the financial side as well. It's incredibly disappointing to me that management teams haven't embraced this as a way to cut costs themselves, and I expect they will.
Yeah, talk to us about this specifically. Are we going to see big layoffs across the SaaS space in the near term and what do you think is the timeframe for that great question?
I think we will. I think we've seen that management teams do respond to price signals. If you look at the history of the sector, it was in twenty twenty three when there was a round of layoffs and companies showed margin, and then they've kind of resisted it for the last two years. The thing about it is layoffs
can help you move faster, right. I think if you look within any company today, unfortunately, there is this spectrum of employees and how fast they've adopted AI, whether they're still doing things the old way or they're on cloud code, cloud cowork, kind of changing the way that they work. And employees who are on the lower end are actually slowing you down as a company. They're not even zero
marginal product, they're negative marginal product. There's just been such a change in how you work, especially in software development, and so I think management teams are going to realize that there's two benefits to actually doing layoffs in addition to the obvious pain of it and the kind of human costs which I never forget to discuss. But one is saving money and showing your shareholders you're financially disciplined and probably seeing your share price stabilize, especially if you're
trading at some very low multiple. And the second is moving faster and also almost as importantly, being able to pay your top performing employees. The war for talent in Silicon Valley has never been more intense right now. Is talking to a private company you invested in and they're losing employees left and right to these high growth AI companies who can afford to pay huge compackages in both equity and stock, and you want to keep your good people.
You don't want it.
You don't want these AI companies that pluck away all the best people and leave you with the folks who relative leddites. And so I do think we'll see this. It's very sad that that will have to happen, but it's the obvious path forward for the sector, and I think if done right, it accelerates innovation.
I have a tangential question on that note, which is whenever we talk about technological disruption, you know, people bring out examples of like remember when Excel was basically actual, people sat down with like papers in front of them doing the math. And those people didn't disappear when Excel got created, but they started doing new things. I imagine a lot of people are very interested right now in alternative careers for basic commoditized coders. What do those actually
look like? Yeah, I feel like you might have some insight here the alternative.
Well, so I think there's two ways to answer the question. Right, There's like what do you do if you want to stay a coder? And then there's what are the careers that are going to still exist over time?
Right?
I think if you think about what's happening to coding, it reminds me a lot of civil engineering, and so it's kind of a funky example, but you know, civil engineers used to work pen and paper doing calculus will this bridge hold up or not? That's been obsolete for a very long time. All those calculations are done by
a computer. They're kind of clicking and moving, and they go on site, they collect some data, they talk to stakeholders, and they're effectively project managing this computer that can do the physics part of their job. For them, it's important that they understand the physics in case something looks strange, but they're not doing much physics right. That's clearly where software engineering is heading in the near term, and a
lot of companies that's already there. And these companies are still hiring software engineers because that job is valuable, and in fact, each individual software engineer is way more productive
than they were before. And there's happily elastic demand for software, Like we still are undersupplied with software in the world, and so there's quite a bit of room to go to add those and so I'm not necessarily bearish on the demand for software engineers, at least for the next you know, three to five years beyond that if things
get weird hard to tell. But then for people more broadly, I think the the best advice is just adaptability, you know, constantly trying and testing these tools, making sure you're staying at the cutting edge of them, and then being aware of what's human right. I think in like in my work and venture investing, you know, there's a lot of data that comes out of human relationships that an AI wouldn't have access to you know, an AI can't call its friend at another fund and ask how company is doing.
Not yet, at least they have to make some friends first.
Right, they're talking about they are talking to each other on moultbook.
Right, they're talking about their Moult book. Yeah, so maybe if there's an AI agent from Sequi.
I was intrigued by that.
Yeah, it was very evocative, but pretty fake.
Well also there was that Wired article of the guy who like infiltrated as a bought and pretended to.
Be They're like, oh, why are we let's create a new language just for us, Like they're not making new.
Languages right, But I think I think the rough mental model is if there was any effort to outsource your job to India, that's risk because that tells you that job can be done by person, someone who's not physically present in a space. And you know, if you like working on problems in isolation, not socially with other people, you know, grinding out math problems or little coding assignments, that's probably also a pretty tough place to be. It's going to be more social world.
This is something we've touched on before, which makes me kind of sad, which is the edge in the AI world becomes like sociability right, And to some extent we talked about this in the context of look smack, I know you love it, Joe, I do not.
Can I say two little observations from my time vibe coding in twenty twenty six that are interesting. One is I have zero technical background. I've been surprised by the speed with which I can build intuitions about when it's going off the rails, like when it's doing something that doesn't seem right. Like I joke that vibe coding is just typing make it better presenter over and over again and then hitting yes. When it offers to do something.
You actually can start to build an intuition fairly quickly, like when this doesn't make sense, and then the other thing. And this relates to your question of like trusting the AI. So one of the things I'm doing is I'm having a lot of documents get annotated, and that I do that through the Claude API, which actually runs up the bills a little bit. And one thing this API run was gonna cost like one hundred dollars, and I stupidly asked Claude it is like, is this a good thing.
It's like, well, when you're done with this API API run, you're gonna have this annotated asset that no one else has done, and that'll be very.
It was sort of useless what I did, so you shouldn't.
It's selling it.
Selling itself is like, oh.
Yeah, use the API, Joe run this like annotated all these documents. It wasn't actually like a good use of my time. So you can't really always they're just gonna they're gonna just sell these things. So Tracy asked about data, and there's one other sectors that I'm interested in.
You see these companies like.
Moody's or fair Isaac.
Or sp Global they have an index, yeah, and they're getting they're selling off too. And it's not like this is another area where like it's you know, people were fund managers for a long time. Unless things get really weird, the super they are gonna be like benchmarking themselves off of like that S and P five hundred for a long time, or lenders are gonna be using the FICO for a very long time, et cetera. Intuitively, it would strike be is this would be a very hard thing for ad or replace.
I share your intuition, right, I can't say I fully understand the selloff and these companies, I wonder if there's not some parts of their businesses that are more services or consulting heads that people are there's often like combinations right where like I don't think anyone suspecting that, like, you know, the S and P five hundred is going
to be displaced as an index throughout Yeah. Maybe, but look, we're in a world where folks are very happy to shoot first and ask questions later once AI risk comes out.
Actually going back to your hedge fund time, like how much is it just the sort of the nature of hedge fund traders right now where there's very little stomach to take any downside risk and appear to look stupid for missing you know, yeah the bag here, and how much do you think that's contributing to some of these market money?
It's a great question.
I won't speak to my fund because I think CO two and Tiger cubs like it are a fairly small share of the overall market and dollars, right, but if you look at trading volumes, the pod shops, Citadel, Ballyas and the millennium are very large share of the volumes, and yeah, those people can't afford draughtouts, right. And the scary thing about this for them is because it's not fundamental.
Because the companies aren't struggling themselves, they have no idea when it will stop, right, And so you're left predicting this thing. And you're like, well, I bet my career that people are going to feel better about software companies in three to six months than they do right now. And you know, your one open AI model release or anthropic model release away from more fear. And so I do think there's a lot of short termism right now, and there's all but again I think we come back
to the SBC point. But there's also no valuation support, no real valuation support. You know, in normal times, if companies were like this, they'd be buying back a bunch of their stock, taking their share out, issuing dividends. You know, I have a friend who works at a mutual fund with is a lot of dividend funds that would love to buy dividending companies growing ten to fifteen percent, like
a lot of software companies. But they're not right, and so you've kind of lost the ability to kind of put an actual floor in underneath evaluations.
As a result of that, Jared Sleeper, thank you so much for coming on odd Laws and explaining how socrow works.
My pleasure is super fun.
Thanks Tracy.
I thought that was really interesting. I'm very fascinated with this idea that in the short term most of these businesses are doing fine. In the long term it might go to zero. But also with the short term they're not really doing fine because actually, you on a gap basis, they're not making much money. I guess that sort of makes sense that they're all selling off right now.
Yeah, I keep thinking this is probably a stretch, but I keep thinking back to that book Full Jobs. Yeah, remember, and like the argument there is a lot of jobs exist not because like people are doing anything specific, but because they're like providing some sort of social value in a way. So, for instance, like you have a person
who is essentially the designated scapegoat for senior management. And I keep thinking of you know, business is basically an ecosystem of different players, So it might be that in the new AI world the role of software companies just kind of changes, like their social role changes. And I don't know what the price or the valuation looks like on that it.
Still feels like to me, I have no I was going to say something about how businesses we're going to what do I know? I have no idea how businesses are going to buy software in the future. I did think that was really helpful, Like I really don't know anything about how the software business works generally, so I
find that very helpful. One other interesting thing though, and it may sort of speak to think about this risk, is just the idea that, like, even high end software is not that much money, right, So if you have a salesperson who's making two hundred and fifty thousand dollars, what is one thousand dollars a year from salesforce.
To do their job?
Particularly and then also given the fact that you know, free and open source software has existed for a long time, but still you know you want to pay an implementer for a company that like manages et cetera. Getting from like here to there where okay Ai really changes the nature of software buying does feel like you have to get.
Into this is going to be weird toward tear, but maybe.
Things are good.
I think things probably are going to get really weird.
Yeah, I think that's that's a pretty good bet. Right, Like, if you bet on weirdness, if there is a weirdness index.
Someone should build that weirdness index.
That would be a pretty good investment. Yeah, all right, shall we leave it there, Let's live it there. This has been another episode of the All Thoughts podcast. I'm Tracy Alloway. You can follow me at Tracy Alloway.
And I'm Joe Why Isn't Though? You can follow me at the Stalwart. Follow our guest Jared Sleeper He's at Jared's Sleeper. Follow our producers Carmen Rodriguez at Carmen armand dash Ol Bennett at dashbod and Kilbrooks at Kilbrooks. For more odd Laws content, go to Bloomberg dot com slash odd Lots or of a daily newsletter on all of our.
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