Jared Sleeper on Which Software Companies Will Survive the "SaaSpocalypse"

23:31And, you know, they signed up 10 ,000 dentist office and then they pay those offices, pay them$10 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.

24:11And the reason is if anyone's going to take advantage of this wave of technology to really 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, my dad runs our family's grocery store. He's been in the family for 100 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. Will your dad come on All Thoughts? Yeah. Yeah, sure thing. We love grocery episodes. Yeah, we'd love to do that episode. All about independent grocery.

24:43And 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 I think that's not something he's going to switch to anytime soon. He doesn't want to go through that pain for another few decades to come. And so it really is kind of company by company. 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.

25:18I'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 e-signature software. We've all experienced it. DocuSign has more employees today than OpenAI and Anthropic combined. Oh, my 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 a signature to be legally valid?

25:52Most of its signatures are done as an API, so folks are integrating it into their own applications. And there's a benefit to using DocuSign, 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 company by company. It's definitely a stock picker's market where there's some that are either relatively immune or have a chance to benefit, and there's others that could be in real trouble.

26:27So 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 like 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.

27:05Yeah. 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 bull 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's been a thousand engineers working on them for 10 years, and they've built not all but most of the things that you'd want to build with today's technology.

27:38But with agents, there's ways to automate a big chunk of the work. So one 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 Fin, which answers customer support queries on its own. And I think they've mentioned that it's almost 100 million of ARR now on a base that was like 300 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 kind of exists as a tool that humans use.

28:19And so, yeah, I think that's like the mega bull case, 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 incorporating e-commerce into its business. And then there's going to be some that are like Sears and go away. That's funny. Sears always reminds me, my dad loves Sears because he always said the parking lot was empty when he goes to the shopping mall.

28:55So he always went through Sears. Anyway, so I understand like the cost argument. It 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, 20, 30, 40,$50 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.

29:35So, you know, we will sell you customer support tickets getting closed out for 50 cents or a dollar per ticket. And you can do the 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 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. And this is a totally new pricing model for software. We actually just recorded another episode and the guest teased at that.

30:10But talk to us about, so it's like results-based pricing? Talk to us about that. 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, OpenAI, Anthropic, 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 who said they think 50 % gross margins on intelligence are about right.

30:45But we see a lot of variance in how startups are doing it today. Some are getting 80 % gross margins on top of the model vendors. Others are getting 20%. 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 of 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. A 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?

31:22You know, think about Salesforce, you know, at the elite tier, you know, 80, 90,$100 per user per month. So for round numbers, say$1 ,000 per user per year. For sales reps who could be making on average$250 ,000,$300 ,000 per year. If you have a technology that can come in and replace a sales rep, you can charge$50 ,000, still give the customer a 5X ROI, and then you've effectively 50X'd your take rate on that revenue. And so that's the exciting opportunity. That 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.

32:01And 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 at, say, an 80 % gross margin, And then for the model makers themselves, they're like, well, why do we just want to be, this is going to sound weird. Why do we want to be the dumb intelligence, right? And that's sort of like, we don't, they used to, we don't want to be the dumb pipe. And we saw that like in the cloud era, right? The Azures and the Google cloud and the Amazon one, they didn't want to just be commodity cloud. And they started building like medical features.

32:32They 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 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 going to have to make decisions, right? So when 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?

33:02And 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 OpenAI 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, you risk being an API that's commoditized. People switch back and forth between you and that kind of application vendor has that control.

34:07We'll be right back. On stage discussions to exclusive networking with global leaders. This is where ideas connect. Bloomberg House Miami. Learn more at BloombergLive.com slash Bloomberg House Miami. 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. Yeah. 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.

34:48Does 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 Clodbot and the kind of rise of this, you know, open source agents that people are deploying for themselves, giving them access to everything, their whole computer, etc. That's Joe. Yeah. No, I didn't install. I did install Clodbot. Oh, you didn't? No. I'm getting mine set up on a Mac Mini with a hammer next to it. Wait, I'm really curious.

35:19Why not? Because of this issue? Yeah, because of that. And it just seemed like a potential waste of tokens and stuff. Yeah, and then it turned out that for a while on Maltbook, which was the social media for all of the APIs were available in a public-facing database. Anyone could go read. And so it was like a completely open system that had to get fixed. And so enterprises really do worry about this stuff. And they worry about it for good reason. I'll give you 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.

35:55And 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 great point. And one of the things that makes me wonder is companies that are willing to skirt the rules or 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.

36:26And startups are able to just move faster given that. So every time software stocks sell off with this and people say, oh, they might go bargain hunting. And they say, what's cheap? And what baby is being thrown out with the bathwater? 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. It was a very interesting note from Barclays. I think it was. I think it was Barclays. This is very interesting. And it said, our European investors are always asking about SBC.

37:00Our American investors only ask when there's a crisis, which I think tells you something about the difference between Europeans and Americans. I thought that was a fascinating sociological observation. Tell us, 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 pare 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 80 % of Twitter X's headcount, we really haven't seen any companies take the pill and kind of realize the benefits of that.

37:36The SBC debate has been going on for a long time. I've had it ad nauseum over 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 it 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-GAAP, 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 that much about the financial side, you're a product person, you may think that you've been doing a good job of being a profitable company because your CFO is telling you, well, we're at a 25 % non-GAAP operating margin, that's pretty good.

38:18When the reality is you're running break-even, which is a very common state of affairs. We looked at the whole universe and the media and public software company has a 5 % non-GAAP net income or GAAP net income margin, which is not enough to value the companies on. And so it creates this dynamic where, yes, there's this terminal value concern, which by far the most important thing, but there's also no floor. I was looking at the earnings report from Freshworks, which is a mid-market seller of customer support and IT management software, it trades at one and a half times EV to sales. If it ran at even a 10 % gap margin, it'd be trading at 15 times earnings, which is a pretty attractive place to be.

38:58You 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 sense of trajectory towards that. And you see the share price down. It's down 16%. 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?

39:37And 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 2023 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 co-work, kind of changing the way that they work.

40:12And the 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 cost, 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.

40:45And 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, I was talking to a private company I invested in and they're losing employees left and right to these high growth AI companies who can afford to pay huge comp packages in both equity and stock. And you want to keep your good people. You don't want these AI companies to pluck away all the best people and leave you with the folks who are relative Luddites. 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.

41:22And 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?

42:02There'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, 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.

42:35It'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. In a lot of companies, it'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 three to five years.

43:08Beyond that, if things get weird, hard to tell. But then for people more broadly, I think 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 in 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 a company's doing. Not yet, at least. They have to make some friends first, right? They're talking about, they are talking to each other on Moldbook, right?

43:41They're talking to each other on Moldbook, yeah. So maybe if there's an AI agent from Sequoia and an AI agent from Andresa. I was intrigued by that for about five minutes. That's okay. It was pretty fake. It was very evocative, but pretty fake. Well, also there was that Wired article of the guy who like infiltrated as a bot and pretended to be a bot. It was pretty obvious. 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 yeah, I think the rough mental model is if there was any effort to outsource your job to India, that's risk.

44:07Because that tells you that a job can be done by 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. Yeah. It's going to be a 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 take two little observations from my time vibe coding in 2026 that are interesting?

44:48One 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, press enter 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.

45:22And I do that through the Cloud API, which actually runs up the bills a little bit. And one thing, this API run was going to cost like$100. And I stupidly asked Cloud, I was like, is this a good thing? It's like, well, when you're done with this API run, you're going to 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 itself to you, right? It was selling itself. It was like, oh, yeah, use the API, Joe. Run this. Like, annotate all these documents. It wasn't actually, like, a good use of my time. So you can't really always – they're just going to – they're going to just sell these things.

45:55So Tracy asked about data and stuff. There's one other sector that I'm interested in. You see these companies like Moody's or Fair Isaac or S &P Global that have an index. And they're selling off too. And it's not like this is another area where like it's, you know, people are fund managers for a long time. Unless things get really weird, they're super – they're going to be like benchmarking themselves off of like S &P 500 for a long time. Or lenders are going to be using the FICO for a very long time, et cetera. Intuitively, it would strike me as this would be a very hard thing for AI to replace.

46:30I share your intuition, right? I can't say I fully understand the sell-off in these companies. I wonder if there's not some parts of their businesses that are more services or consulting heavy that people are working. There's often combinations, right? Where I don't think anyone's suspecting that the S &P 500 is going to be displaced as an index. The Anthropic 500, yeah. 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, holding the bag here?

47:14And how much do you think that's contributing to some of these market moves? It's a great question. I won't speak to my fund because I think Kotu and Tiger Cubs like it are a fairly small share of the overall market in dollars, right? But if you look at trading volumes, the pod shops, Citadel, Ballyasney, Millennium are a very large share of the volumes. And yeah, those people can't afford drawdowns, 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.

47:52And you know, you're 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 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, shrinking their share count, issuing dividends. You know, I have a friend who works at a mutual fund where there's a lot of dividend funds that would love to buy dividend in companies growing 10 to 15 percent like a lot of software companies.

48:23But they're not right. And so you've kind of lost the ability to kind of put an actual floor in underneath the valuations as a result of that. Jared Sleeper, thank you so much for coming on OddLots and explaining how software works. My pleasure. Super fun. Thanks.

48:50Tracy, 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, they might go to zero. But also in the short term, they're not really doing fine because actually 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 Bullshit Jobs, 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.

49:30So, 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, what do I know? I have no, I was going to say something about how businesses were going to buy. What do I know? I have no idea how businesses are going to buy software in the future.

50:04I 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 thinking 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$250 ,000, what is$1 ,000 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.

50:39Getting from like here to there where, okay, AI really changes the nature of software buying does feel like you have to get it to, this is going to be weird towards here. But maybe things are going to, 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 leave it there. This has been another episode of the Odd Lots podcast. I'm Tracy Alloway. You can follow me at Tracy Alloway.

51:10And I'm Joe Weisenthal. You can follow me at The Stalwart. Follow our guest, Jared Sleeper. He's at Jared Sleeper. Follow our producers, Carmen Rodriguez at CarmenArmond, Dashiell Bennett at Dashbot, and Kale Brooks at Kale Brooks. For more Odd Lots content, go to Bloomberg.com slash Odd Lots for a daily newsletter on all of our episodes. And you can chat about all these topics 24-7 in our Discord, discord.gg slash oddlots. And if you enjoy Oddlots, if you like it when we talk about the casastrophe, casastrophe, then please leave a positive review on your favorite podcast platform. And remember, if you are a Bloomberg subscriber, you can listen to all of our episodes absolutely ad-free.

51:50All you need to do is find the Bloomberg channel on Apple Podcasts and follow the instructions there. Thanks for listening. Thank you.

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