Surviving the New Economics of a Post-Agentic World

0:01Welcome to the Practical AI Podcast, where we break down the real-world applications of artificial intelligence and how it's shaping the way we live, work, and create. Our goal is to help make AI technology practical, productive, and accessible to everyone. Whether you're a developer, business leader, or just curious about the tech behind the buzz, you're in the right place.

0:24Daniel Whitenack:Be sure to connect with us on LinkedIn, X, or Blue Sky to stay up to date with episode drops, behind-the-scenes content, and AI insights. You can learn more at practicalai.fm. Now, on to the show.

0:41Daniel Whitenack:Welcome to another episode of the Practical AI Podcast. This is Daniel Whitenack. I am CEO at Prediction Guard, and I'm joined as always by my co-host, Chris Benson, who is a principal AI and autonomy research engineer. Welcome, Chris. It's one of these episodes where it's just the two of us and we get to talk about whatever's interesting for us. So I'm excited about this. I missed the interview with you last week. It was a great one, but yeah, excited to be back on. Absolutely. Welcome back. And I know we both had outages lately with some vacations and family and things like that that we've been doing.

1:19Good to be back together. And yeah, these fully connected episodes, as we call them, where you and I get to kind of go wherever we want to go, they're always fun for me. Yeah, for sure. For guests, it gives Dan and I kind of the chance to freelance and to kind of, instead of just focusing on a particular topic, to kind of go wherever we want to go. And so we have a good time with them. Yeah. So, yeah, a lot's happening right now.

1:46Daniel Whitenack:Lots happening. And yeah, just as a reminder also for our guests, a few things that we don't normally share on our shows when we have a guest because we like to get into that. But please do engage with us online. If you didn't know, we are posting videos now on YouTube. So if you haven't got a chance yet, at least go over there. Give us a subscribe on YouTube, The Practical AI Show. and of course you can still listen to us on all the other places as well. And then a reminder, just coming up in October, October 15th in Indianapolis, we're going to have another Midwest AI Summit, which was a great experience.

2:27Daniel Whitenack:Chris and I got to jam at a little bit last year and excited for some really cool speakers that we have on deck this year and lots of practicality with an AI engineering lounge where you can sit down and talk through architecture and design and agents and plans and security and whatever you want to talk about with practitioners. So check it out. Just search for Midwest AI Summit and make sure you get registered for that. But yeah, lots of things happening. Before you get away from that, I want to point out that that's a fun conference. You and I go to a lot of conferences and that one is a fun conference.

3:05It is. And everybody is accessible. If you want to talk to somebody, they're there. It's great. So I just wanted to point that out. I love that one. So, yeah, you want to start us off?

3:16Daniel Whitenack:Sure, sure. It's interesting today, this morning. I mean, I guess like most people now, we don't have regular TV, but sometimes my wife and I listen to some sort of like feed of like on Prime Video, they have CNN news highlights or whatever. So sometimes we'll listen to that in the morning while we're eating our cereal. This morning on those news highlights, it highlighted that IBM had a major hit in their stock. So 25 % stock plunge, which is kind of crazy. And it talked about, oh, IBM has this 25 % plunge in their stock. It has something to do with AI. And I was obviously paying attention. I don't know that based on how they were describing it, it immediately made sense to me.

4:06Daniel Whitenack:but I did a little bit of research and, you know, I am looking at this and also thinking about if it's a wider trend that is going to be happening across tech companies. So is this something you ran across or have been thinking about, Chris? So I wasn't at all surprised about this in that way. Like I didn't know that IBM would do this, but so it's something I've been thinking about quite a lot lately. And something that I know I've mentioned this to you, I'll mention it without any names. I'm in discussions about writing a book that's kind of hits this topic with the CEO of a publishing company.

4:46And I'll leave it at that. It may never happen. But they asked me to write some books that they were a book that they were interested. And I said, no, I'd rather write this book. And the notion of the book, if it ever comes to pass, is kind of a post-agentic world is kind of like if you look at what's happening right now in the marketplace and you take all your biases and all the things that you want or are scared of out of the equation where all your emotions are removed a little bit and you say well these are what's happening and you play the events out over months and years what what are the probabilities of various outcomes that are they're looking like based on today and I've been going through this exercise and spending quite a lot of time on it.

5:32And so that's why the IBM thing didn't surprise me. And I think, I think just to scare the heck out of people, I think that we're going to see a lot of that, a lot of that disruption happening in the months and years ahead, because you're really looking at a situation where you have technology that is replacing both existing technologies and existing human positions and processes that people are engaged in with these new technologies. And as we scale out that in an agentic world, that has quite an impact on the fundamental economics of how businesses are changing now. We've seen all the mass layoffs in the tech industry.

6:20and we're going through a moment where companies are really experimenting with hyperproductive alternatives to human labor. And so that doesn't remove all the humans from the equation, but what it does is it changes their roles and it changes the activities that the humans are engaged in. And that's evolving very, very rapidly. And so that, you know, as a start, you know, it leaves it as something, you know, I know it sounds very ominous, But I think the key point there, rather than just being frightened of it, is really that the rate of change is accelerating exponentially right now. And so the IBM thing is kind of that.

7:02I know the New York Times referred to it as potentially a canary in the coal mine, and that's one way of looking at it. But we're going through the beginnings of a period of rapid change and the fundamentals of business, not just technology. It's really important that people catch that, but business itself that's using that technology. So I'll stop there for the moment. How would you react to that?

7:27Daniel Whitenack:Yeah, I think there's a lot of things tied up into this discussion, some of which were cited in the IBM case, some of which maybe were not. There's, and maybe we can get into a few of these things. One of them would be like where where AI companies are trying to become more sticky and make sure that you stay with them so that they can recover some of these costs that they put in and just sort of hemorrhaged over time. There's also the kind of panic buying situation of people trying to make sure they aren't priced out of AI and they get actual hardware that will make them a little bit more resilient to that.

8:15Daniel Whitenack:But there's the, you know, I saw the, I think it was another article that you had posted to me about, or maybe it was something that I saw elsewhere. But Anthropic really doubling down on kind of implementation and services side, which we've also seen with OpenAI versus kind of the model side. So there's so much tied up into this. Just to give some stats on the IBM case, the kind of canary. 25 % single trading session collapse, which is about$70 billion in market value, marking it the worst single day drop in over 50 years, outpacing even its losses during the 1987 Black Monday market crash. And part of this where I was researching is like, well, what's going on?

9:07Daniel Whitenack:And what are the, at least the cited dynamics that they're talking about in relation to this from IBM and other analysts. And part of what they're talking about is that companies are diverting their IT budget or their technology budget away from enterprise software and services. So enterprise software and services to some of these other things like the like I was mentioning, the panic buying of maybe hardware or infrastructure such that they aren't priced out of maybe what they see as coming as a price hike in the usage of these AI models, the agentic future where you need much more context. You have long running processes, et cetera.

9:56Daniel Whitenack:And so there's been this shift, I guess, from the capital expenditures on enterprise software and services, at least to some of these hardware and infrastructure expenses as kind of, yeah, there's finite budget and there's this tug of war happening. So any thoughts on that piece of the puzzle? So all those things I think are contributing. And there's something else I don't know if you saw this in the news. It kind of skimmed by pretty quietly, I thought. And that was China is now recognizing the value it has in its open models, which are much cheaper to use than these expensive proprietary models in the U.S.

10:45And they're recognizing that while the U.S. has put export controls around that, that these open source models that we've assumed that the world will kind of fall back to because they're leading the way in that may now become restricted going forward. And so there's this political, like there is one set of capabilities that the U.S. is stronger in and is putting protections around. And now China has recognized that there is another set of capabilities that they are stronger in, you know, of economic value and that they're putting protections around that. So I think all of these things that we have talked about are kind of feeding in to how people are shaping their use of technology.

11:35And I think it's creating, to your point, a certain level of panic in executive level companies where they're trying to figure out how to mitigate the risk, both in terms of the proprietary U.S. models, the expense associated with that. But the fallback strategy of going to Chinese models, if you're in an industry that allows for that, is now closing off potentially as well. And so that is putting a lot of pressure from multiple sides on companies on what they're going to do. And so they are definitely funneling internal budget to try to mitigate that risk at the expense of a lot of other things that have historically been kind of keystone operations, you know, in their organizations.

12:24And I think, you know, whether we're talking about IBM's collapse and the shifts that they're making, you're seeing all these influences affect kind of emergency allocation of capital. And so and I don't I don't expect that process to stop. I don't think this is a blip. So I think those those things will continue to evolve, but those reactions will continue to happen.

12:47Daniel Whitenack:Chris, I was in a meeting with our engineering team this morning, and one of them mentioned the Chinese token black market. Have you heard of this? I have. Yeah. So I'm all the time learning new things. My engineers are on Reddit more than I am, so I hear about things through them. But yeah, so it's related to some of what you're talking about. There's this Chinese token black market, which is kind of a reference to this like underground gray market area where brokers are reselling discounted API access to Western artificial intelligence platforms, AI platforms like OpenAI or Anthropic because those services are blocked to mainland.

13:40Daniel Whitenack:you know, Chinese users. There's a lack of the ability to actually pay for that. And so there's this economy or ecosystem of resellers and proxies that's emerging to work around this kind of access piece. And those kind of things almost always happen when you put in kind of regulation for the purpose of artificial shaping, you know, for political ends and such. So you're going to have black markets that appear. So, you know, that I don't think that should surprise most people seeing that. So, you know, the question is then where is everything going, you know, with this? And what does it mean for listeners and viewers?

14:24Daniel Whitenack:If you're an enterprise software, well, I guess if you're an enterprise software consumer or you're an enterprise software vendor, right? What is the future, I guess. Yeah. That's so like if people are moving away from investment and enterprise software, where are we going? Yeah. I mean, one of the things that I think is, is interesting is that lately I'm hearing a lot more conversations about, um, uh, you know, uh, not only looking for other sources of open weight models that are out there, you know, that are not specifically Chinese or specifically from the U.S. Obviously, Europe is doing that.

15:04We've talked to some of the organizations there. But also, I'm starting to hear about the recognition that there may be a need, especially as models are now getting, you know, we're getting smaller models that are used for a lot of specific purposes and edge cases to actually go and do training of models or getting back to fine-tuning. I think a lot of organizations got away. Remember, we used to talk about fine-tuning, you know, once upon a time And then it seemed like the models got so good that a lot of organizations said, why would we bother with that? And they would just take a model and it was good enough without fine tuning, without the cost of that.

15:40And so I'm hearing a lot of like, what do we do as we get squeezed from both directions? And how do we approach that? And so some of these things that people had said, let's not, we don't need to do that. We don't need to engage in that are now coming, are now kind of coming back around. It seems like those are conversations that are starting to happen again. And so I found that very interesting.

16:03Daniel Whitenack:Yeah, I think that that also becomes, I mean, there's platforms like Unsloth and others that allow you to fine tune, you know, even on your MacBook and, you know, run things a lot more efficiently. So I think that also gets to some of what this was the episode that I recorded when you were out on vacation, I think, Chris, with the ZenML folks. But as we transition from agents being like my personal assistant on my laptop, which I interact with back and forth, which obviously limits the speed at which and the amount of context that agent can consume. and I move that into the cloud as a long living agent that just works for hours and days and weeks, maybe, right?

16:53Daniel Whitenack:Then all of a sudden the economics do change around like, hey, if I'm using a pay-as-I-go API endpoint, that's going to be a vastly different economics than a small self-hosted model, right? That's powering those agents. So I do think that that makes an impact. I do too. And I think, you know, but I think we're moving past that. You know, when we talk about having our agent that's long lived and stuff like that, and this also depends on industry and need and stuff like that requirements. But I'm looking at situations where loops are incorporating hundreds of thousands of agents or millions of agents that are that are all creating very complex contextual productivity, you know, or outcomes, I would say, you know, in terms of what you're trying to do.

17:49So if you are if you are just assigning agents a bunch of very discrete responsibilities and that there's kind of teams responsible for each of those and they're interacting a lot. But and I think that's the kind of thing as we're moving toward and that becomes more common across industries that you're you're looking at a set of capabilities that you know going back to the ibm thing right here where that level of agentic implementation um and and agents running agents uh which is happening more and more is really uh taking us into a new world like like it changes it completely changes the value proposition for a lot of enterprise software out there because you suddenly have a new capability that in many cases can do things that traditional enterprise software just can't touch.

18:39And I think that goes to the, when we talk about IBM stock today, I think that's the threat. But I mean, IBM is just one significant company in multiple industries with lots and lots of companies that are essentially taking that enterprise software approach. And they are all at risk to some degree. And I think that's gonna continue to play out in the marketplace. So it's, you know, the world is shifting. The paradigm of operation is shifting significantly right now. And the economics that that implies are going to play out. So I think, you know, I think that's why. And you're seeing some recognition, maybe not of the full picture at the executive level, but enough to where they're saying, ooh, we really need to spend money.

19:26You know, we need to move capital from here to there. And so that's impacting employees and such.

19:31Daniel Whitenack:Yeah. And as a founder of a software company, obviously, I believe there's a place for software in the future. But I do want to validate your point of like with our vision and what I'm trying to paint at Prediction Guard, we're working towards that future that you mentioned of the agentic workforce, the thousands, hundreds of thousands of agents that need to run, run securely, run, govern, run with identity. And just to validate your point, like even in the last couple of weeks, we've talked to one company that already has 70 ,000 agents running, one that has, I think it was like 6 ,000 or something.

20:13Daniel Whitenack:So this is not, yes, it is future, but it's not like five years future. This is very rapidly what companies are. are so I think there are many people out there that are maybe still on a one-to-one basis with their Claude code or with their Hermes agent or whatever it might be and so this picture of thousands of agents running in enterprise infrastructure might seem far-fetched but I think it is not it is very much we're getting there very rapidly and people will start really experiencing this, which I think stresses all of us to think of like, you know, in our, uh, in, in my world, it's very much like, Hey, as, as a software vendor, how do we prepare for that?

21:03Daniel Whitenack:What, what is your thought, Chris, in relation to, uh, I guess if you're, if you're, if you have enterprise software that people have been using for some time, let's say like IBM, or even a smaller midsize or a niche, you know, vertical software vendor. Because I've talked to a lot of those vertical SaaS software vendor, right? How do you, like, how do you lead your company ahead into this world? And what becomes important? What strategy is important as you move into this world? I've seen some take the approach of, hey, well, you know, like a NetSuite or something like that. They're saying to some degree saying, well, we're going to provide a connector into the AI world, right, which is often MCP, right?

21:54Daniel Whitenack:So their value is maybe they're assuming their value is in their data platform, how they organize data, the functionality that they provide, but surfacing that in an agentic way. So that's, you know, through the MCP side. So that's one take that you have. You have others than, you know, maybe more vertical software companies that are saying, no, we're not going to expose that, but we're going to create our own proprietary set of agents that are our agents and are going to run in, you know, what you need. and we're not going to tie into the more generic kind of agentic ecosystem. Do you have any thoughts on that kind of like or maybe there's like other options within those strategies, right?

22:38Daniel Whitenack:So I think so. Yes, I have some thoughts on that. I think the world. So the way interactions are going to occur or going forward is not going to be in traditional interfaces. You know, the GUIs and the web interfaces that people are used to, you know, and that's dominated all the way through kind of the early Internet era. And then as we got into the cloud era and then even the beginning of the AI era, as we've gone to, you know, app interfaces where we've interacted. But as we look at agents doing all these different things and collaborating, the way interactions will occur is agentically in a direct, you know, if you might think of it as B2B in a sense, but think of it as agent to agent.

23:23And the vast majority of interactions across different systems are going to occur agentically without a human directly involved in most of those processes. So with those processes being automated through Agentex, you have to be thinking that way. So if you're one of these companies, you know, I know you mentioned NetSuite and obviously there's the IBM concern and lots of others. You have to be thinking, how do I move from where I'm at right now into a world in which Agentex are incorporated from a business transaction consideration? You know, it's going to happen without anyone going into your GUI.

24:04And without that, you're going to set the permissions. You're going to set, you know, what they have access to and how the MCP servers are configured for the different parts. And that's quite complex. And I think there's a whole industry right there of how do you manage agentics at massive scale with resources and MCPs. And so like if you're an entrepreneur out there and you haven't, you know, that's an area that is wide open. And I know your company is already addressing a lot of those things. And so it's, you know, that's the kind of thinking. And I think going back to your point, this is happening really, really fast now.

24:43And so if you're thinking we're a few years out, then you're going to get overtaken quite quickly as IBM discovered this morning with their stock. So I'm not trying to create panic, but people in these organizations that are stepping into kind of AI and now agentics, they need to be thinking not where things like tomorrow, fairly big leaps are happening. And, you know, like right now, as we're talking, you know, loop engineering, you know, we were agentic engineering was, you know, kind of the buzzword a few months ago. And then lately it's loops because now your agents are tied up in loops. But tomorrow it's going to be past loops.

25:23Looper is a very transitory thing because this is evolving so quickly. um but before the year is out i'm pretty sure uh the notion of loop engineering uh is going to be kind of antiquated uh by what what follows and and the evolution of where things are going and so if you're a business owner get on top of what's here now and start thinking how am i going to get ready for those agentic interfaces of the future and that's that's how i would uh start addressing the problem from any given business perspective.

25:53Daniel Whitenack:Yeah. And just to make sure we're not painting or just taking one data point, this is much more widespread, as you mentioned, and is spreading quickly. I was just looking while you were talking and on the same day today as IBM crash, It looks like unless unless my agent is hallucinating, Workday, Workday slid down 10 percent, Salesforce 9 percent, ServiceNow 8 percent, Adobe 6 percent. All, you know, similar dynamics going on. What did gain was the, you know, NVIDIA Intel chip chip providers rising as people, again, you know, panic by some of these these hardware solutions. and there is a lot of I think distraction related to the cyber security side of this as well which is partially related to the hardware but more more related to maybe some of this distraction around mythos and cyber security and how agents violate you know cyber security and so there's there's a focus on that rather than kind of the generic SAS software and enterprise software as well.