Episode 18: Tim Beyers on the SaaS-pocolypse and AI Disruptions

Hey guys and welcome to episode 18 of "Shoot in the Bull Pod" with Drousy and Bear. Bear and I are so very lucky and so very pleased to have our guest on today. We've been listening to this person's help for almost a decade plus now in the tech space in particular. We think the world of him and we're so very lucky to have our guest on today is a senior analyst at the Mollie Fool Timbiers. He will kind of fill out the trifect of understanding the AI space and what it means for the SaaS world as we watch SaaS apocalypse 2026 happen. So Tim, thank you so much for being here. Yeah, thanks for having me. I'm really interested to have this conversation and it's a really interesting time to be having this conversation because as we're recording, there has been multiple days where the market has just decided that SaaS is terrible and the world is collapsing. Is that the case? I'm not so sure. That's the cliffhanger. There's the, yeah, you'll find out after this session. So Tim, I wanted to start the conversation sort of for kind of the casual listener and work our way up into the more intricate question. So to start, can you walk us through the history of SaaS? What is SaaS? And then tell me about the glory days, you know, several years back. Yeah. So as you mentioned, I'm a senior analyst at the Mollie Fool and I've been in and around not always as a senior analyst, but I've been in the tech markets for about 30 years now. I started in the PR and marketing side of things. My job used to be to translate really complex deep, deep tech products for things like marketing and PR campaigns. I used to write stuff. I had, I've had an eclectic number of jobs in the tech industry, but over the past 20 years, I've been on rule breakers and analyzing tech stocks. And SaaS is an invention. I mean, we're probably about 15 years in. That means software is a service. So the idea is, and it really did start. I mean, they weren't the first company to do this, but Salesforce.com. For those of us old enough to remember, I have the white air to do remember this. 1999 Salesforce had its own campaign. If you've got this button, congratulations as a correct collector's item, but it was these buttons they gave out. And for those who can't see us, I'm making a circle with my fingers, like a button that had no software. You know, they had software in the middle and it was crossed out. And the idea was that you could access Salesforce inside of a browser and that the browser would be the default place where you would access software and features from here on. Now, that is advanced significantly over the course of time that we do deliver software now via the cloud. It gets hosted elsewhere. It's not necessarily on our own machines. We don't have to do as many updates on our own machines as we used to, although some days probably doesn't feel like that. Probably doing way too many updates. But that's the basic idea. Now the principle of it and why it caught fire to answer your question is that it had two really important strategic advantages that made CFOs really happy. And if you want to find text docs that have distinct advantages, find the ones that make CFOs happy, sasted that in two ways. The first way was a salesperson would come in and say, I have something for you that's going to be really interesting. This is a software that you need to solve your problem. Let me tell you, you are not going to have to spend any catbacks from day one. You're going to be able to write it off to your operating expenses. You're going to get a tax break using my software. But wait, there's more. Yeah. And the CFO says, you had me, you had me a tax break, right? Like, that's the first thing. That was number one. Number two is you could go to the CTO and say, you know, all those engineers you have to pay overtime to on, you know, for midnight and weekend updates because you have to take down the server system and go into the closet, do a whole bunch of stuff and do an upload and make all of these changes and it has to be off hours. That's over. You never need to do that ever again. All of the updates are going to be pushed to you via the browser. The CTO has got interested. So there were two really interesting economic benefits to SaaS from day one. Now that is, that's part of the paradigm. That is absolutely part of the paradigm. What's changed in the year since is that we have that paradigm now is the SaaS software able to keep up with other things we can do via a SaaS model, which is where the AI part comes in. So if Baron and I were hosting the show a couple years ago, we would have been spending 20 minutes on data dog. We would have been spending 15 minutes on CrowdStrike where more like for me, like an hour and Baron would have spent a minute on it. We would have been talking Monday.com and Asana and Slack and all these other companies. This really was the bread and butter for investors. Not only did it make sense for CFOs of tax breaks and not having people come in late, but investors. This was good as gold. This was recurring model that was measurable. That was in the bank. You could see the backlog. This was the perfect model. So in 2022 to 2020 to 2022 or a little bit beyond, our portfolios were 90% SaaS. We were so inclined and so just oriented towards that market. And now the economics are shifting. Now the big question is, where are we? I would welcome your thoughts and kind of so we had this glory day and now we're kind of 2026 and sort of trying to figure out what's next. So can you help us with like economics argument? Can you help us? What is a CFO kind of thinking when they see that this SaaS gold model is kind of changing before their eyes? Just help us. Yeah, and just to put a finer point on the question, Jersey, are you saying, are you trying to lead into the what's changed for SaaS companies in the industry in the market or what's changed for investors? So why not? Think the former. Yeah, I do want to hit both and bear thanks for bringing that. Let's start what's changed for the company. Maybe we take them one by one because then we'll transition to kind of how investors should be interpreting this. So over to you. Yeah. Fair enough. And what's changed for the companies is that in those early days, you had real pricing power and it because you had real pricing power, it made a lot of sense to employ a lot of software developers to build up a very functional SaaS product and just be rolling out feature after feature after feature knowing that the way that SaaS was priced, which is basically seat based. For time, this is one of the dirty secrets of SaaS is that if you committed to this and didn't do a capital investment where you made all of that big investment up front and then you depreciated it over time until it got to zero. If you had done that by the time you got to like year five, year six, you know, you are now paying more for the SaaS product than you would have if you had the install and manage product and CFOs kind of wise up to that and you're like, you know what, this is not a cheap product. It's I mean, I know the benefits I'm getting, but this is not a cheap product. So then you start thinking about all right, how do I manage cost here because SaaS costs did start to get out of control, lots of seats, lots of premium pricing and suddenly it became something that was used to be like, wow, this is incredibly economically attractive to wow, this is an economic bowdanker. And that was a shift right around 22 to 2023 and it made some companies wake up and that's when we started to get to you guys may remember this. You may remember the shift where we started talking about, I wonder if we could have usage based models. Hey, what about usage based models? Those are kind of interesting. Maybe we don't have as many seats. Maybe I only pay for what I use and that started to come into Vogue and now that has become much more in Vogue more recently, but that was the shift here like the thing that changed is that the economics started to look a little bit more hairy and CFOs woke up to that and they started putting pressure on their SaaS companies and that changed things a bit and some companies did not deal with that very well. Others dealt with it fine. I'll give you an example. You mentioned DataDog, a company that did deal with this okay. There were some real horror stories of companies that spent way too much on DataDog because what they ended up doing, DataDog is an observability platform. You can ingest a whole bunch of data about what's going on in your network, in your infrastructure, and then you can run a lot of analysis and say like here are the things that are happening inside my network. Some things are going well, some things are not. Where companies ended up spending way too much money on DataDog is they just decided Let's just hook in everything. Let's hook in everything. We'll ingest all the data. And so you end up spending a boatload of money. And then the usage bill ran up real fast. Exactly. And there's $5 million, $10 million a year, some companies on data. And of course, you know how much they tout the net retention rate. So I was-- Absolutely. I remember at the time trying to do some math. Go ahead and wait a minute. They're actually growing more from their current customers existing more on usage than they are from actually signing new customers. And that did become a bit of a problem. And now of course, that was the 2021-2022 as revenue was getting up until like substantial levels per company and also a couple billion dollars a year for some of these SaaS companies. And now it's, I guess, the question is, is that revenue-- is there a threat to that revenue again from some exogenous thing like AI? There it is. So there is? Yeah, there is. What I would say, the way DataDog handled this is they introduced a tool that said, why don't we show you how to monitor the stuff that you are ingesting and eliminate the stuff where you're not getting any value? They kind of disrupted themselves. They did. There's a book from Clayton Christensen about-- and why am I forgetting the title here. The innovator is dilemma? Thank you. The innovator's dilemma about if you don't disrupt yourself, you will be disrupted. So DataDog disrupted themselves. And they started cutting out. They deliberately reduced some of these bills because they knew it would be better for them long term. But yes, like-- so this is the economic argument. The SaaS companies had to get smarter. The bills were too big. The economic boat anchor became a real issue. And because that economic boat anchor existed, and maybe we can pivot to AI at this point. But that-- I mean, Drowsy, that's what opened the door for AI and AI agents. So yes, let's pick on that right now. So you're-- you described sort of the gap from 2020 to 2023. Economics usage basis sounds like a snowflake model. Then we're moving into today. And you're kind of a CEO or CFO looking at your bills. And wondering, is it even worth this adjusted kind of SaaS purchase? They've kind of adjusted over the last few years, but is even worth it now that we have clawed or chat GPT. So from that mindset, what are-- Or are they thinking? Or are you? Yeah. Or is it not quite ready for prime time for my company yet? So Tim, you're the CFO of a Fortune 500 company. Congratulations. What are you kind of thinking as you see these advancements? But you've had data dog. You've had CrowdStrike protect your company forever. What are you thinking? Yeah. This is such an interesting question, because now that you have these economic issues. And the first thing that me as a CFO would be looking at is like, I get a bunch of seat-based licenses here. And if I start eliminating seats, I can eliminate cost really fast. And if an AI agent can do the work, let's just for argument's sake, we don't know that this could happen. But if you're a CFO, you would do this exercise. You would say, I could probably do the work with an automated AI agent. I'll make up a number here, 50 seats. If I could get rid of 50 seats, man, that would save me. Another make up another, now it would save me $2 million in licensing fees a year. I got to get interested in that. That's the kind of thinking that is going on here. Now there's a caveat to this. And it's a really big one. And I think it's the narrative that is not being properly appreciated in the market that is selling off all of these stocks. And it's the CTO perspective. The CTO comes into that conversation, and says, yeah, you could do that. You could do that if you want. How do you expect me to manage the risks that are introduced by these AI agents? We know nothing about them. We don't have any governance tied to them right now. We don't know, I mean, do we need to run identity against them? What's our audit trail on them? Part of the thing, this has been always been true about software. And I think this is a huge misnomer. You guys have probably heard me say this. Like the company that's the enterprise software company that's best positioned solves a migraine level problem for a company that is experiencing extraordinary pain. And they will pay up to solve it. Part of that is they provide a feature. But really what they're doing is they're solving pain. But what the company who's paying for it, what they're really buying, the feature is the small part of it. What they're really buying is, OK, you're going to solve this problem so I don't have to. You're going to be secure so I don't have to. You're going to be the one that's constantly looking for the improvements. So I don't have to do any of that. What the SaaS company is selling to a degree, it's the feature, but really what it is, it's the reassurance. I have somebody I can go to. I know they're going to be secure. I know they have professionals who are looking out about how to build this. They're going to have a road nap and they're going to build this over time. The second, this is the thing that the AI agent argument misses, even if you agree. And I do that AI agents are going to take some of the market at the larger scale, like eliminating all enterprise software. The reason I think that's nonsense is because once you decide to employ AI agents, guess who's on the hook? For all of those things, you outsourced to SaaS. That's you. Now you're on the hook. Are you ready for that? Do you have the people for it? Do your lawyers think you have the people for it? Does the SEC think you have the people for it? Like these are big questions that are not being considered, I think, in the broader market narrative. So within the realm that you're-- we'll say you're still CFO. Congratulations. Are you ready for to quote you? My question is, are there areas in the SaaS portfolio that you're looking at your company that you're probably more akin to try to cut back on versus other areas that you'd be hesitant to touch? That's the third rail. And then between you mentioned identity, you mentioned security, you mentioned Althrow out productivity or team building or kind of knowledge management. Yeah, what are the areas that you think are most at risk and least at risk as you oversee your Fortune 500 company? Yeah. I think the areas that you really don't want to monkey with unless you're really forced to. And I recognize this area of the market moves very fast. So there's probably going to be changed. But security is one. You'd like your security innovations and your security changes to be on the margins. You wouldn't really want to mess with the central. Your core security infrastructure, you probably would want to mess with that too much, which is why even though I think CrowdStrike is middling a little bit at the moment, I don't really like the cash flow directions I'm seeing from CrowdStrike. But having said that, they're in a wonderful position. They really are. They provide essential infrastructure that is unlikely to get disrupted. I also probably wouldn't mess too much with my core data systems, like the stuff that has all of the data that I rely on, like my customer data, my inventory data, like all the things that help me make big decisions about the future of the company. I'm probably not messing too much with that. So that's probably good news for like a snowflake. It's probably if Databricks ever goes public. It's probably good news for Databricks. Companies like that. Does that even apply to the fabled system of record? Like, I mean, would that kind of? Yeah, and in that case, you're-- Salesforce even? Yeah, you're talking about Salesforce. You're talking about SAP. In that case, you're talking about Oracle, like to a degree, yes, but at workday, there's another one that kind of fits in in that category to a degree, yes. But also, you do wonder, and here's the thing. Anywhere that AI agents can chip away at the margins, I think they probably will. So is there a workflow on the margin where they could do some work? So for example, let's take that-- so let's take that system of record example. Is there an argument that's a shipping and invoicing, which is typically handled in a system of record. Could that be automated? and hand it off through an AI agent. I mean, I think the answer to that is probably yes. So you could see that there's little ways that it chips away. >> You might be able to judge something a module or two, even if you have to keep the system itself. And then you still have the risk of, if you're reducing your staff head count, or if your customers are reducing their staff head count, well, that's few receipts for whatever system you're talking about. So I see where you started with Snowflake and Databricks, the data systems and then we're about like the middle two. >> Rubrics when I haven't spent a lot of time on it, but there's like the backup of data, they're not necessarily selling a process, they're allowing you to back it up like the data holders. >> Right. You would expect you're not gonna make too many changes there, but on the margins, I do think two things can be true here. We don't need to denigrate AI agents. They are coming and they will probably start by doing work on the margins. Just another wrapping in a bit of tech history here, just as a way to think about this. There's a great book from 1993. So again, I'm old. I remember the beginnings of Enterprise Software. This book's called, it's a great read. It's still very relevant today, called Crossing the Casm from Jeffrey Moore. And the way that Moore defines the Casm is, if you are building an innovative product, if you're building a tech product, let's say it's Enterprise Software, let's say it's an AI agent, in order to gain scale and go from the innovators to the early market all the way over to the early majority, to get from the early market, the early adopters over to the early majority, there's this thing called the Casm. And in order to cross the Casm, to go from, this is really super cool. And you have people that like to buy super cool stuff in the LevenRite big checks to do it. That exists, but in order to get to a mass market, you have to solve a problem. You have to solve a migraine level problem. And it's okay to solve a migraine level problem in a niche. So like in the case of Apple, in order for the Mac to cross the Casm, you need a desktop publishing. You needed a laser writer. And yet a whole product said like, this is an entire niche that is growing up around digital publishing, and the only company that has the whole product to do it happens to be Apple. And that crossed the Casm. And so in order for AI agents to do something very similar, you would expect that the way these things evolve, you're gonna have types of AI agents that will solve niche problems, probably in vertical markets, do it so well that they become the whole product. Now is that something to invest in right now? Probably not, but I will say this, and I think this is super important in what you wanted to know about the investing side of this. So the investing side of this, and the reason I'm not fearful of AI agents, can you imagine a better distribution mechanism for AI as a feature than enterprise software, particularly vertical enterprise software? Is that not the best distribution mechanism ever created for AI features? - The best feature for AI. - Yeah, 100%. - Ironically. - Ironically, right? So there will be some disruption, but there are some smart companies that have said, hey, let's see if we can make AI features as part of our particular offering and make that compelling inside. So you make it part of your go-to-market. So there are other companies like this that have done this pretty well. Salesforce is trying to do it by taking what were automations inside of Salesforce, and now terming those agents. And you have all of your Salesforce automations in our deployed as agents. So why would you want to take your data out of Salesforce when those automations you work so hard on, now can just like that be deployed as agents? Whether or not that works, it's still a little early. A better example of how this works in the niche area would be what Toast is doing with Toast IQ in order to come up with, you know, you have a bunch of data and then it will automate for you like, based on the data we have of all the things that are selling really well at your restaurant, here are some menu ideas for trying out the next time you are going to have specials. That's an interesting way to use some AI that functionally takes advantage of the existing features and the existing data in the system. - That's a really cool example. I hadn't, I mean, bear, I don't know about you, but I haven't looked much at Toast. So that's really interesting. You're building on top of your data. So you're essentially almost tactically retreating slightly for a long term strategic win. You're saying you're staying core data system staying with us and we'll add features on so you don't need to go elsewhere to try to add those features onto us. Tim, with the example again, so we talked about companies you feel that are probably least or most resistant to kind of AI overhaul, we talked about those on the margins, the sales force is not middle category. What is that end category of most at risk? The most at risk are the companies that depend completely and I would say to a large degree on the free tier and you've probably seen these try X and then once you scale from the free tier into the upgraded tier that really works, the free tier is going to be under some serious threat because the AI tools and the AI agents are free to build. They're expensive to run, by the way, let's not forget that. AI agents are expensive to run. So if you think that AI agents are going to immediately disrupt well established SaaS companies, you need to bear that in mind. Having said that, at the lowest level, small team, you're using a free tier and you use that free tier product and you push it all the way to the limit and you're not willing to pay for it yet 'cause you're a startup, that is likely to get disrupted by AI agents that are also free to build because you can do a lot with a little when it comes to these AI agents. So that's a problem. That is an issue for a company that I do like in Monday.com, you mentioned them earlier, but that is an issue for them. They do have a free tier. That free tier is going to get disrupted. I think the cost to acquire new users for Monday is going up. They are not going to be the only ones that face this. Asana is going to face this too. Atlassian is going to face this too. So any kind of company where you're really dependent on the free tier and you're going to market is going to have a very interesting time. Another one that's outside of the productivity world would be like Cloudflare, which has a massive free tier. So that's, we're going to have to watch those companies. There may be some disruption on the margins, but overall, I think the fallacy is that AI agents come in and just wholesale replace enterprise software. I don't believe that at all, but there's a very good chance that AI agents come in and take jobs on the margins where they can solve a niche migraine level problem, solve it economically and do it in a way that is fully automated without adding staff. CFOs are going to get real interested in that. I do think that is a genuine threat. - That's interesting. I was sort of when you were talking about the free tier, I was thinking maybe by proxy companies whose customers or small businesses, small and medium size are going to be more prone to things like that. And maybe even those customers are more likely to be trying new things and be a little bit more agile and not necessarily care quite as much about the system of record and all that because they have smaller teams and things. So definitely tying in a lot of things. I know we've got to wrap up in a second, but I thought that was a different way to read what you were saying. I'm not sure if you agree with that or not. - I do agree with that. And I would say like what you want is a company that provides something more than just a really interesting feature set. If the feature set by itself is the entirety of what the company offers, then that is probably under threat. But if it does something where it is addressing a well-known customer need, like the reason I don't think toast is under threat is because it does multiple things. Like there's no restaurant operator that wants to be in the business of being an IT manager. Now if you could deploy a bunch of agents and actually run front of house and the back of house, that would also be interesting, but it doesn't solve the payments problem for you. So like, if you have a whole product, that addresses exactly what the company's trying to do in order to solve customer pain. It's gonna be very difficult to disrupt that. But if it's something small, so like, for example, if you were just in the business of doing automated work to underwrite insurance policies and that's all that you did, and let's say you only did it for motorcycles, that is something I think could be, you know, even though that might be hard to price, could that not be replicated by AI agents? I think it probably could have, but anything that has multiple steps is much harder to disrupt. The genius of toast is when they laid on the payment area of it so that the restaurant could win toast could win and customers could win, all at the same time. So that's the kind of business model of I'm interested in, I was talking to you guys before we started recording. The go-to-market matters. Look at how you sell, what you're selling, how you're selling, and what the customer gets on the back end. You know, why are they buying? If they are buying for more than just price or a small set of features, that might be a stickier business. Another indicator that I like is cost to acquire. If cost to acquire goes down over time and the way you measure that is the aid, so let's say on a year over year basis, current year revenue, minus prior year revenue, so the new revenue accumulated during the year, and then sales and marketing expense, current year sales and marketing expense, prior year sales and marketing expense, and just compared the two, how much revenue do I get for each incremental investment in sales and marketing? If that number is going up, that's great news. That is a company that is scaling. Even if they are unprofitable at the moment, that company is scaling. They are likely to succeed over time. But yeah, it's a hard one. You want to watch, but I scaling unit economics are a decent sign for all of these companies. I think the perfect way to kind of wrap, and maybe end your short, but really amazing and stunning role as a CFO on our show, and the job is always going to be open for you for the record as well. And we have a policy here on shooting the bull. So final question would be within kind of the framework you just laid out, is there a name in particular that is on your radar that you think, whether maybe it's had a big drop, maybe it's introduced a new product, is there one that's really high on your potential to add and radar right now in the SaaS world? There's one that is, it is under threat, but I like the way it is operating. I really like the CEO and co-founder, and the unit economics I just mentioned are unbelievable for this business right now. That is Figma. So ticker, FIG, Figma did come public, and they had to make good on a lot of performance equity that they issued as a private company. So the initial year looks horribly unprofitable. There's a whole bunch of stock-based compensation, but that's one time. Over time they should scale to free cash flow margins, really generous free cash flow margins relatively quickly, presuming they don't get fundamentally disrupted. So that metric that I just talked to you about, like that measure, I did this for Figma, and the current year, their incremental revenue for every additional sales and marketing expense was $2.97. The prior year it was 90 cents. It is gone, it is more than tripled. It is outrageous what they have been able to do in a very short period of time. So they're a highly efficient business, but they are gonna be under threat by AI-powered alternatives, the biggest of which I believe it's called Stitch from Alphabet. That's gonna be an issue. Now in order to deal with that, they have embedded AI tools. They haven't built their own product called FIGMA-MAKE in order to deal with this, where you bring in models and you prompt to designs and you prompt to code. So they are competing, and it will be a bear knuckles competition, but I think it's a very fairly valued stock. I think it's a very well-run business. And bear in mind that one of the things that I really like, a leading indicator for a tech company is if they have either survived or led a paradigm shift previously, they are more likely to do it again. It's the venture capital principle. Why do VCs like backing entrepreneurs who've created a company and either sold it or scaled it previously? 'Cause I know how to do it. It's a better bet. Tested bet, yeah. A tested bet. FIGMA did unleash the collaborative design paradigm, making essentially the Google Docs of paradigm design, and that is now the paradigm. FIGMA created that. So now, are they going to be the ones that lead the prompt driven design and automated code generation that goes from design to prototype via AI? I don't know, but they have as good a shot as anybody. They have a lot of cash, good balance sheet, great leadership. I like FIGMA quite a bit. - That's definitely a name that Bear and I haven't talked much about. So thank you for teaching us about that. And really thank you for walking us through your kind of SaaS world. That you've lived, sleep, and breathe for so long. So I think this is kind of the perfect way to end our episode here. So thank you so much, Tim, for spending some time with us today. Truly, we appreciate it. We can't wait to have you back at CFO. Our finances are all out of order, all out of whack. We need you to come in and really clean house. So we can't wait to have you on an episode coming up soon. - I appreciate it. Now this was fun. Thanks a lot, guys. Thank you.