The Bull Case for Software in the AI Era

You can see how much revenue they are going to get in the next 12 months and that's this number and it it grew again 20% and the guidance just stay something around those levels. So revenue and this backlog should keep growing at 20%. And I think those numbers are are just great. >> What's up everybody? It's LG Ducet here and welcome to Milk AI the daily AI show that dumps the stock even when the earnings are very positive. Today is July 23rd 2026. One of the big themes this year has been the death of software. And my god, is it ever unsexy to talk about software stocks compared to all this awesome AI stuff being built, but that may just be the opportunity. Today, we sit down with our lead researcher, Martin, to dive into two software stocks that have been absolutely nuked in the market, yet have both built powerful AI products that will not only help them retain customers, but has also been a blessing to their balance sheets. And of course, we raised the question, is the market wrong about these stocks? and how big of an opportunity is this really? A reminder before we roll that if you want to see all of Martin's trades, including his solid calls recently on Hyperlquid and Robin Hood and a basket of other mispriced opportunities, you can try out Milkroad Pro for just a dollar at the link below. And again, a different reminder that our podcast is free today and it wouldn't be possible without our partners at Securitize, the regulated rails for tokenization, and BitGet stocks 2.0 with real liquidity and real dividends. Keep an ear out later in the show for a message from each of them. Uh Martin, it's earning season. We're recording this on Thursday the 23rd and earnings have started. You have been on the SAS apocalypse rebound trail for a very long time. You've written about this in Milkroad Pro. What are you seeing today? Well, I see that one of my favorite SAS companies that were supposed to be dead just shared their Q2 earnings and they smashed all the estimates and the company's service. Now, all the estimates were just um beat out. So, I think what this company is actually doing is just proving my thesis that SAS might not be dead. It's quite the opposite because you know in this show you you talk with Melvin, Winston, Kyle and the the common narrative is that intelligence is getting cheaper and better which means that I'm able to do more work for less money using AI. And I think that's that's that's the core of my thesis. And once you agree with this take, you are going to the market and you are going to start thinking about how you can express that thesis in the market and who is in the best position to really benefit from this trend. And I think Service Now is probably in the best position in in uh all the SAS businesses because they are integrated pretty much in every uh Fortune 500 company. And so it's pretty easy for them to just upsell another service and just provide you know more efficiencies in their in their business flows because they have already access to their databases. they know all all the details, all the workflows, all all the governance, all the rights, all the approvals, all the chains that those companies use. And so it's just so easy for them to, you know, upsell AI. And I think on on the earnings call yesterday, the CEO said that it's already starting to sort of replace um humans or labor. So it's really becoming an arbitrage. So you know you can have I don't know 50 people doing um uh customer relations or you can have um service now who is going to provide you some of those services as well but it's going to cost you a fraction of like what you would have to pay to humans. So I think that's pretty interesting and it's still something that it's not showing on profit statements yet like at scale but the comments that I see from uh those people and you know the analysts that are asking uh on the earnings calls the whole narrative is like about this it's not about you know selling the old business that that that's how they grew but it's more about like okay where this is heading And quite frankly this is a transitioning phase for like all the companies. I think all companies in the world needs to find their AI strategies and the AR approach and most of them will find that to implement AI successfully in the companies is not a trivial task and so most likely a lot of them are going to outsource that to some you know companies that are able to do it. And again it's pretty easy to just you know okay we work with service now today they have access to like everything we do they provide back end for most of our stuff anyway so let's just ask them for like more services from there and like really make those productivity gains leveraging AI because that's what investors want and when I was thinking about my portfolio and my like all my companies I said like when I am listening the earnings call and they are not talking about AI at all I am starting to be like very bearish because I think we have hit the point where I think you need to have your AI strategy and it's okay that we are still not seeing productivity gains on your earnings but at least I want to see why and how are you trying to fix that in the future and so um yeah that's that's sort of the the whole angle that this you know Q2 earning season is like that's how I'm going to like listen all the earnings call and through this lens as that's what I want to hear from like all the CEOs and CFOs when they are talking through these earnings calls. >> Just going to pause there for a second to point out that the market [clears throat] is showing signs of something kind of different happening and our analysts at Milkro Pro are all over it. They spent the last couple weeks making a lot of trades, getting out of some positions and getting into a lot of new ones, getting ready for the next wave of robotics space or even kind of picking some different AI winners. If you want to see what they have in their portfolios, what positions they're opening, it's just a dollar in Milkroad Pro at the link below. >> Right. So, basically your your thesis is that on the software side, right? And we've this has been the story and it's been a marketing story as well for the LLMs right for Anthropic and everybody that it's like listen we're putting out you know all this stuff back in February every week there's a new plugin that is like replaces an entire sector of software there's been the whole SAS apocalypse software stocks have gotten destroyed and your theory or your thesis is that basically the only ones that will survive and rebound are probably some of the larger ones who are who have started to adjust and have started to create products using AI that are AIcentric to basically retain their customers and continue to grow, right? And Service Now is is is a really good example of that. What ex people don't know this, what exactly does Service Now do because it is it's a massive company. They have a lot of different partners, but like what what do they do? It's just like AI workflows for enterprises basically. >> Yeah. Well, they do a lot of stuff and they started as a they call it IT um management services which was you know if you file a request that you have something broken or you are a new employee and you want to request a new laptop or stuff like that. That's how they started and so eventually they added more services on top of that and now they run pretty much like a lot of backend stuff for the company. So um like you know it's not just like you just file a request they are also now doing like customer service tickets and but that's a that's actually a difference because when you look at some other SAS companies like Salesforce let's say they are a um CRM company CRM is uh customer relationship management and so like you know when you have troubles with your op mobile operator or service you are going to issue a ticket and then some person needs to like you know um get it sold for you. So and that's that's sales now um the sorry that's Salesforce >> they are only providing that sort of interface but they are not solving the issue per se and that's difference because um service now is going at one uh layer deeper and okay you can issue a ticket using Salesforce or service now that's the same for both but they are also giving you an agent that's going to fix it for you because they have got access to the client. So they know that the client, you know, has that plan and they have already called before about some other incident and so they can connect like everything together because it's not it's never just a ticket and you need all that context and so like it's really hard for people to really understand Service Now business and it's it's really it's really a lot of stuff. So if you buy a new laptop it's everything is stored in their database all the clients data as I said all all the chains that like if I need for vacation I need to send an approval I need to uh send a request somewhere you know so it needs to land and ask my manager can I you know have take a time off and so he needs to approve it so it's like chain of chain of processes or like what needs to be h happening here who needs to approve roof. And so there are a lot of stuff behind running a corporate of like you know tens of thousands of people and so they are providing all that infrastructure and all that back end that might sometimes be invisible or sometimes it just like one chat or one button but that's what service now is providing. I know it's not like super sexy like you know if you talk about Tesla or something that people can get very familiar pretty quickly about what they are doing what the products are but sometimes like the things that are not seeing could be really valuable and here actually someone asked me today on our discord what's the motive service now what are they doing better than open AI or Microsoft and that's that integration part and so as I said in the beginning if you are already have relationship and they already do a lot of stuff for you you are not going to like you know um just cancel your contracts and go to another person or another company because you already have the relationship they already know a lot of stuff so the the switching cost would be very high and assuming you have a good relationship and the quality of their products or services were really good that's why you keep like having them then like it's it's an easy upsell and that's what they are doing actually >> right and B and and I think the other thing too is that it's not just the cost of switching it's also that the the narrative has been that these companies like service now um that their clients would suddenly build their own in-house solutions be using claude right and that that basically what you're saying is that it's a little more complicated than that when you are when it's like a huge part of your entire workflow that would take even with claude like yes maybe you could do it quickly but that would create such a headache to do and it's already so inter interwoven that it makes a lot more sense for these companies to for themselves to create more better better AI workflows to offer better products within that integration rather for their clients to go and figure it out themselves even though there are better tools for them to figure it out themselves right like that's that's basically the theory here for something like this >> the difference is like you know it's different like when you are milk road like we have I don't know 15 people maybe but when you have you have they just announced a partnership with some um airline company I don't remember the name but anyways the point is that when you are company with you know 10,000 employees it's a very different beast and you are not going to ask your engineers hey build us the whole system that we are all going to use and you know issue our tickets then it's going to resolve that ticket for the user And like it's not a trivial thing for companies like this. So it's a scale issue as well. >> That's right. Yeah. And service now and you had you had pointed this out in a report recently uh or just a few months back is that service now actually has been build has had their own um they've been building their own like kind of AI assistant which I think is called like now assist or something like that. and that and this is back in June that you wrote this or maybe there's an update in the earnings but um this had already generated a billion dollars in revenue for them as like a new product as well uh and it's some it's somewhere in this pro report so if anybody it's on our website uh in the pro section if anybody wants to check it out but basically they've already started to adjust so this is a good example of a company well Martin I want to ask you in this in this sector though um what is kind of the TAM because you had this you had this uh this chart in that report from a month ago that's basically about service now being part of this kind of addressable market of like AI oversight software. I don't even know what you call that now. And you're point and you're telling me that it's like it's it's it's an area that's growing massively and has and is going to continue to grow. >> Yeah. Um this is by the way from their um Q1 earnings presentation where they were talking about this whole growing addressable market for their business. And I think, you know, my edge in AI as an investor is not just that I'm trying to understand the the numbers behind the business, but also I'm using AI daily and I try to build stuff. Um, and so the things I'm struggling with is probably showing me what a lot of other people or other companies are going to struggle at some point because like I am very early adopter and I'm sure that like service now is still not where I am today. So they cannot just experiment with everything that's going on. But I have realized pretty soon that the biggest sort of challenge for AI implementation is not you don't care about the model that you are going to use like I I don't I don't care if I'm using you know oppus like cloud or open AI. I don't care about that. I think that this part is going to be abstracted away and we will use aggregators in the same way that we use aggregators for like Netflix or YouTube or Amazon. They are all aggregators. I think we will we are just going to send you know a request to the model aggregator and they are going to just route that question to the best model to serve that particular question. So that's one piece. But the other thing I want to talk about is the crucial thing is to orchestrate everything. So when you know when I'm talking to my agent, we have a whole discussion about some company and then what happens with that conversation? How is it going to get you know locked into my system and then how is it going to update my whole thesis and when? Who is going to do it? Like do I have rights to change my thesis? Does my agent has access and rights to do those changes? And so like it it's it's also pretty hard to describe it, but think about that whole orchestration layer. And so it's like okay, here are the data, here's the context, here are the rights, here is the aggregator like like you need to connect all these pieces together and I think that's what they are trying to do here. They call it AR AI control tower because once you have access to all the data, all the context, all the relationships, the time is like it's it's even higher than this because at at that point you are becoming a yeah as they said a control tower of everything. And so you know earlier this month um even in Milk Road we were talking about everything the people do today is you know like my my processes and my daily routines that I do should be embedded into a code or a skill and then that skill should be implemented on a company level and at that point like Milk Road will have a huge system that is just you know compounded of like consisted of multiple skills of different people of everything we do and Milkroy will just govern that the whole system you know at this point you should use this skill and once this is done then we should follow here and then the person should share his view so that's the whole idea and why this market is so huge and it might still sound a bit complex but think about it like as I said at the beginning they were also talking about replacing um the the human labor by just okay you they are actually trying to do this already. They call it AI specialist layer um level one which is still um not a scale product of this but they said that in in service now they use 20 of those um agents that sort of replace humans. And so once you use them more and more they can be trained and then at that point because they can run 24/7 you don't need you know 50 people doing the same task but you will have one agent who is doing all that work for you. So I think I am even more bullish not necessarily in the next like three years that their you know addressable market is going to be at trillions but like at some point when you have access to all the data and you understand all these processes inside you can really build like everything and it's it's a threat to I don't to humanity but I think that the success of service now will inversely correlate with the with the job market and so right now it doesn't look like you know people are going to get lost going to um be without jobs anytime soon right >> but at some point I think it's going to happen and it's going to happen because service now is going to replace you with the agents that they are building and providing to the companies >> real world assets like funds treasuries and private credit are still running on rails built decades ago gated paperwork heavy slow to settle everyone's talking about tokenizing them but far fewer can actually do it and do it without cutting regulatory corners. Securitize can. It's the SEC regulated infrastructure bringing real world assets onchain. 9 years in native tokenization not wrapped, backed by Black Rockck, Morgan Stanley, and Kathy Woods Arc Invest and chosen by the New York Stock Exchange, Van BNY, and Apollo to do it at scale. It's the regulated bridge between traditional finance and crypto. Tokenize the world at milkroad.com/securitize. Everyone's tokenizing stocks these days, but almost nobody's doing it right. Thin liquidity, prices that drift from the real thing, dividends that just vanish. Bit stocks 2.0 is different. Real NASDAQ and New York Stock Exchange depth through licensed brokers. Prices mapped one to one. Dividends paid to your account in real time. Plus, you get the lowest fees in the market at just 0.04%. And you can trade them like any other crypto as margin in earn in grid trading. Tokenized stocks finally done right. Head to milcrow.com/bitgget to get started. To summarize all that, companies like Service Now and they're incredibly well positioned. We'll look at their chart in a minute too because I I also want to I want to talk more uh positioning as well. U but basically they have so much data and they're so deeply integrated into the business that they're in a better position to basically build these like company brains for all their clients that will then be kind of operated by agents. they're in a good position to basically replace to kind of push this more jobs apocalypse that's supposed to happen at a lot of companies. It is going to be a company like Service Now who profits from that because they're building they're going to be in position to build these brains with all these agents that can that can kind of coordinate all these company resources and like you're saying create create skills out of what people do and then use those to kind of keep the company running and integrate them and and basically replace people uh or or give or or give people something else to do and they can go create a new skill and learn new stuff. So Martin, I want to look at the chart really quick because you said today in Milk Road Pro that you were adding after the the earnings, but also interestingly uh post earnings the chart is down today, right? Um so what's up with that? Because you're saying that earnings smashed but the but the chart is kind of uh or at least the market is kind of disagreeing so far. >> Yeah. Um I I don't understand to be honest. I think it's it's a nonsense. I think it's a great opportunity to add more because if you have some thesis and just after the earnings your thesis where like my thesis at least was you know uh validated and become even stronger and so now I'm getting like very good price. I think I would expect the market to really react positively and I think it was actually in the pre-market I think now was up like six or seven% and now when the market's open it's it's down. Um I don't really understand the reaction here. Um yeah, I think maybe let's revisit the the chart in like a couple days when all the people will you know listen the earnings call and just look at the numbers and because the reaction should like I don't see a reaction that is not you know service now should be at least 100 bucks today because it's just after the results it's it just changed the game changed the game. Would you would you say that this is this is also not uncommon that this happens because we've also seen this year like Nvidia earnings come in, they're enormous and the next day the stock is down. So is there this kind of natural like sell the news even if the news is good effect maybe happening with Service Now? >> Um maybe I don't know but those are well today I'm looking at NASDAQ it's down 2%. So you know maybe it's it's more that the whole market is not doing that well today and so um you know when everything is just going down pretty bad then it's [clears throat] really hard to see green numbers even for service now >> I mean the fundamentals are there the sentiment might not be because it's red day today but like I would be very surprised if it we not see a a green week for service now >> and you're adding to your position today you've already added uh which you can see here in Milk Road Pro. You've already you added quite a bit to your position. I think a 16 oh 16% position increase. So a decent little little ad. >> Yeah, I [snorts] think because um I said that before the earnings I want to see that their revenue backlog keeps increasing. They service now reports something which is called CRPO which is contracted revenue performance obligations which is like okay how much contracted revenue there is for the next 12 months because a lot of the services are already contracted so you can see how much revenue they are going to get in the next 12 months and that's this number and it it grew again 20% and the guidance just stay something around those levels. So revenue and this backlog should keep growing at 20%. And I think those numbers are are just great. >> Martin, are there any other companies out there that fit this thesis for you? >> Yes. Um it's not it's not exactly the same thesis. Um it's more on a general level than when intelligence is getting cheaper, what it means and who is going to benefit from it. Um and my other position that is uh trying to express this uh bullishness is oh yeah this is the chart where you can see that price of intelligence is just going down over time which is pretty great and again because I'm using it every day I can see what you know cost me 10 bucks before is now costing me not even a dollar because I can use all these aggregators and so I don't really need to bother about like and one more thing is that today I'm not just asking a question to get an an answer instead I'm trying to sort of create a a loop or something where I just define what I want to get as a final output and I just let my agents to do it and because he's using those aggregators it cost me um less money than before and so here you can just see that the intelligence is getting cheaper um and that's that's awesome for like you know end users like me or you or anyone who is really using AI but also like for companies who are really able to take advantage of this. And another expression of my bullishness on on this theme is um applovin which is exchange that is selling ads in the in the in the games on on phones and why it makes them so interesting is that um they own the exchange. So um think of it as a marketplace. There are like you know um companies who want who are looking for um advertisement advertising and then there are uh companies or like games that are providing the the slots in their games for advertisers and so um AppLav has that exchange and so they see the data for you know the people who are um asking or like looking for advertisers and then who are supplying uh that those slots and because they see the data, they can improve their model over time and they can deliver better results to the to the advertisers. So I think that's that's pretty pretty unique and also they can they they are building this exchange and at the same time they are uh sort of participating on on this exchange as a you know if someone wants to um advertise something they can go to Axon and anyone can connect to the marketplace but if you want um some ad you can go to Axon uh to applovin directly and they will try to win your spot because they have access to all these data. they can trade their models and they can become better and so your returns on ad spend is getting higher and which drives the flywheel that then more people are coming to your platform and that's what's happening with app because when you are thinking about it yes here this chart it it shows it so nicely we have 85% margins like I don't think there are many companies in the world actually that have 85% margins. Yes, maybe Micron, maybe Skylonics, but there are just a a few of them. Okay. And Epin is just keep growing their business like crazy while still keeping margins at such a high level that is, you know, un it's just extraordinary. go. I really love this business and now they are expanding their business because they were just trying to um attract gamers but now they are trying to tap into e-commerce and insurance and fintex and like everyone else um yet we are need to see that it's working for them as well and also because AI is getting better they are now providing hey you want ad on our platform sure no problem, but you might not have, you know, um, a visual team or like content creation team who would be able to create you that ad. And guess what? You can just like describe what you want to have in your ad and like they have a a tool that is going to help you to build that ad for you. So you are going to save so much money. So that addressable market for who who can actually advertise on applovin is increasing because now you know I am individual and now I can just go there and just I can create my ad using using their tool and I can just advert make advertise there. Joe, it's it's the question of how AI is getting uh their business and like how they are adopting this new into this new world where AI is getting you know cheaper and more powerful and like here for AppLin they are making it more accessible to more people because you can just you know create your ad in their platform and they are making their models much much smarter. harder because they see all the data and once you have better intelligence, you can build better models which are going to results in better returns on your ad spend which again is going to attract more people to your platform and the flywheel continues. You see more data, you train your models again, you have better models again and and so that's the flywheel I really like here, >> right? So these guys, so AppLoving Services has a marketplace that services like a it's something like 140,000 mobile games that basically use them as they're like Google Adwords basically. And not exactly, but like in some version of that. And then now what you're saying with their new AI engine is that those advertisers can can even have to do the creative for their ads. They can just come straight to that marketplace and it'll make an ad for them. um which then massively increases uh apploven's uh revenue and and also keeps their margins pretty high because it's all just an AI that's doing it for them, right? So they don't even have to increase spend other than um subsidizing the token use for for the for the advertiser. So that's another way that this just like mobile gaming is also a thing that's not going to go away [laughter] that's going to keep growing. Um so they are well positioned. You know what's interesting, Martin, is that, you know, these are two companies that have boring names. Uh, and as a result, are not like these high mind share software companies, right? I think when people talk about software, the SAS apocalypse, they're thinking Microsoft and Salesforce, right? And and other a lot of other software that that maybe is a bit more familiar. Uh, but these are definitely like more back-end companies that you don't know exists, but that you probably even as a retail user, you probably interact with some with a company that's using them every day, right? Um, and I like these plays. This is kind of like more the the you know I don't want to say the plumbing because it's a that's a cheesy word but it's it's definitely um a huge part of software that we don't see right and that is down is down massively. So let's go let's talk about the apples stock to to kind of wrap this up. Um you' said in your recent pro report that you would start buying below 500 and now we're at 400. So this is like a huge discount going on here. >> Yeah I think my I'm going to add more. I I I see that there is some um support levels around 380. So if we go there, I'm definitely going to add more. And as you said, Algie, I think what people needs to realize is that do I only want to hold, you know, the very sexy AI names that everyone is talking about that do, you know, 15% up one day, minus 7% the other day, and like that are super volatile. Um or you can you know uh look at less sexy place that is not as known as recognized by most market participants and just do your homework. Try to understand their business. See if you think that they are going to benefit from AI and if so is the price right and if that's the case you should buy. And and so again, I think for most people it's like I want to buy something and I want my stock to go up 20% tomorrow and you know do a 3x in the next 6 months and if not then it's fail. But it can work for some time but if you play all your bets on one thing then there might be an issue if you know your thesis is incorrect. But here I'm just trying to diversify. So I'm looking at less known bets but I am making my my thesis and my base case based on what is going on. How is their business doing today? Is it a good timing to enter this business? Is the price okay? And if so then I'll just enter my position and then I just keep learning and just monitoring my positions in my companies. if something goes wrong or if you know if maybe there are some good announcements I might be adding more and so um yes because quite frankly you asked a very good question that those are not as known and recognized and sexy I get that but do you want to hold something that's sexy and like what's your edge if everyone knows about that company like you are just you know riding wave with with everyone else And then at some point you might that might be a troublesome at least for some people. Um so >> absolutely you're listening to to to to the the narrative to to the more of the mind share versus something this makes a lot more sense where there's fundamentals and these these are both hundred billion dollar companies. That's the thing is like these are not obscure companies that don't have a lot of customers man like this is service now is a hundred billion market cap. Appleven is what 136 uh billion dollar company. So these are not, you know, they're they're small maybe compared to the, you know, $5 trillion NVIDIA, but these are not small businesses by any means and they, like you're saying, they they are companies with competitive modes with a lot of revenue, with growing revenue. And back to your thesis from the start, they are leveraging AI. They do not want to lose their customers. They want to increase their customers and increase their revenue per customer and and they're doing a good job of it so far. So they're definitely good companies to track. Um, Martin, I feel like you're going to keep bringing us a lot of these plays. Um, and it's been great to have you on the podcast again. So, uh, thank you. And if you guys want to follow Martin and especially what his moves are and see the rest of his portfolio, it's on Milk Road Pro for a dollar. You can check it out at the link below. Uh, and even just get a quick glimpse of his portfolio, see how much he holds both of these companies and also what else he has. Otherwise, Martin, thank you for your time, man. [music] Want to stay ahead of the biggest technological shift in history? Subscribe now to get insight [music] straight from the sharpest minds in tech and finance. Quickly, you'll note this show is for educational purposes only. Nothing here is financial advice. Investing always carries risk. Never invest more than you can afford [music] to lose. Thanks for tuning in.