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 is 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 or 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.
Hello and welcome to another episode of the Odd Lots podcast. I'm Joe Weisenthal and I'm Tracy Alloway. Tracy, we're recording this February 11th and IGV, the software ETF, down another 3% today. It has been ugly in software. Everyone's throwing around the term SaaSpocalypse.
I mean, the great thing about SaaS is there are a lot of things that rhyme with it, a lot of homonyms. So you can make all those puns. SaaS Crash.
Yeah, exactly. SaaS is trash. Whatever. But I'm looking at the share price of Salesforce.
In particular because I always think of Salesforce as sort of like emblematic, the poster child.
Poster child of like a software company that I'm not really sure what they do.
But yeah, it's just ugly. It's basically been cut in half, hasn't it, since its peak, like in early 2025. Right now it's 184, 84.
And it's all your fault, Joe.
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 seen everyone playing around with cloud code, and I had to do it. We did an episode, and so people are like, oh, if Joe Weisenthal can, like, figure out cloud code, then there must not be any value to any of these companies at all there. You know, you mentioned Salesforce. That's far from the ugly one. I'm looking at Atlassian, which makes a lot of like workforce productivity.
Yeah, like some Slack competitors and stuff.
That was a $450 stock back in 2021. That's an $86 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, they don't have much value. I mean, I will just say it's not just software right now. So we're seeing this sort of rolling series of concerns where, like, every time AI does something or creates some new product, it hits a particular industry. So on Monday, it was the insurance industry, insurance brokers. And, you know, today, Wednesday, February 11th, I think at some of the broker, stock broker firms. And, you know, 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 like 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 software, writing software is a cost center for these companies, right? Like if you're Salesforce and you can trivially reduce the cost of building software, that should also benefit you. And there's a lot more to a software company than just code generation, because there's all kinds of like, 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 scream to me like, oh, these companies are worth less than they used to.
Sure. But at the same time, 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 editor.
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 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 going to 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, sort of really diving into SaaS of the SaaSpocalypse, 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 going to be speaking with Jared Sleeper. He is a partner at Avenir, which does growth investing in private companies. So, Jared, thanks for coming on.
Yeah, my pleasure. Excited to be here.
Why are we talking to you? Just, you know, for our listeners, apparently this is your first time on a podcast, which is crazy, but what 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 Scott. And then I was also at Coatue, where I ran public software. And so I've kind of have this like experience across the spectrum, from ground floor startups to looking at the big public companies, which I've done for the last ten years.
Perfect guest. Perfect guest. So give us a sense of like, 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 buy side, just, you know, retrenching. I can't believe this is happening. Can it go lower? I keep saying that it's the 100th time I bought the dip. You know, you use the SaaSpocalypse, like SaaS atrophy is my guys. This is, 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 Rorschach test kind of sectors where no one's logged into Salesforce and clicked around, much less been 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.
We explain what this means. So for example, in a lot of companies, it's like you're saying that the people who invest or 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, etc., but they don't have like a great intuition for the product, unlike say, you know, people who use Instagram and therefore might have a feel about Meta, for example.
Yeah, if you're an investor in Lululemon, you have a pretty solid conception of what that business is. You can go into the store.
You can buy the product, try it on yourself. If you're an investor in Veeva, which makes CRM software for pharmaceutical reps, I bet you there's almost no investors in Veeva who have ever been inside the product even once, much less used it on a day-to-day basis and understood how it works.
Got it. So I'm going to go way back in time and start, I guess, at 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, today 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 70s or 80s, there was a lot done in-house. And we've seen a very clear shift 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, you can afford to have one, two, 3,000 engineers plus partnership teams, etc., 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 $100,000 a year, and $100,000 a year is less than half of the fully loaded cost of a software engineer.
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 than the cost of one employee.
We could. I'd love to just sort of like talk long-term software history even before, you know, we think a lot about SaaS and the 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 don't they have like a, aren't there a bunch of third-party companies whose job is to just like help install it for you, SAP install. 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.
100%. 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 a 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 that kind of core software accounting, you know, supply chain, etc. That company is 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 Cloud Code, we talked a little bit about it as well. But like if you have something like Cloud 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 developing and improving, that will be able to do this, like plug itself into various systems.
Yeah, 100%. I think the challenge of writing the code for the integrations is going away. That's not the bulk of the challenge for the 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 2004. What does that mean? Like, how does that map to the new system that we're building? So I 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, you know, write in the chat in the cloud 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 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 sort of more exposed to the pure like code generation ability?
Yeah, it's a great question, I think. And you're 100% right. It's producing working code. And frankly, it has been for the last year or so. I built my first Lovable app that was working in production 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 to 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 when a company's reliant on an open source database or a company like Elastic with its Elasticsearch product, which is an infrastructure tool, and it breaks, they need someone to call, both for SLA reasons and because it can be very complex and technical, and they need to quickly understand it. And so, you know, 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 set up, 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 $20 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 the Excel shortcuts. It's not a good use of time, especially when the software is already so cheap. And so that's another kind of 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 is 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 or 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 sort of been associated with the, would you say catastrophe, one of the companies that's sort of 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 light. Yeah, I mean, do we not even see yellow light? We actually see a lot of green lights, which I think is really interesting because it sort of can fit with this idea of this year could be fine, next year could be fine. Do you have to, that could be fine. And then the year after that could be zero. Or at least that's the anxiety that there is this terminal value.
Right. There's like a cliff for us.
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 there 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 40% in 2021 for the median software companies. That's really nice annualized growth. And then there was a hangover. And that slowed down. And we wrote 18 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 in growth rates across the sector. By the beginning of last year, the median company was growing 18% instead of 40%. So you saw a pretty significant drawdown. 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 18% again in Q3. Net retention has also been consistent at about 110%. So that's revenue from existing customers over the same revenue from those customers the prior year. So there's not a churn issue developing or a lack of expansion within the customer base. And a lot of companies are actually accelerating growth or guiding to accelerating growth. We have a chart showing the number of those companies has increased each quarter over 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.
Yeah. I mean, look, look, look at Chegg. Right. Which went down very quickly in the aftermath of ChatGPT 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 Chegg, 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 it. That was a Chegg was 100, nearly 100. It was a near $100 stock in February 2021. It is now a $0.60 stock.
That's right. And you have to give the markets credit. Like the second ChatGPT 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 in what people think.
Can you talk to us? 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 like, 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.
Full 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 into 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 what 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 in software is they do not take very detailed notes.
So you had a salesperson, right?
Yeah, exactly. 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.
And 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 of 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 on the one, like if there's a spectrum, you know, I think about Salesforce.com, which is a platform and there's third-party developers that build on top of Salesforce, and they sort of offer and everything. And then I think about something niche like, this is the company that makes point-of-sale software for dentist's office. And they went around by giving them free, free payment terminals. And they joined Y Combinator. And you know, they signed up 10,000 dentist's office and then they pay those offices, pay them $0 a month, forever for access to that, you know. Well, no, I'm just making it up, but things like that, like, is there a side of the spectrum that's more at risk here? Is that spectrum a legitimate way to think about the industry, or is there a thread, some sort of wherever you look?
Yeah, it's a great question. I mean, certainly in the world gets really weird scenario. Yeah. 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 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. Took a long time.
Your dad. Come on. Apple.
