# Surviving the New Economics of a Post-Agentic World - **Show:** Practical AI - **Published:** 23 Jul 2026 - **Source:** https://share.transistor.fm/s/8a2e4fc0 - **Transcript:** https://podcasts.opennash.com/shows/practical-ai/surviving-the-new-economics-of-a-post-agentic-world-249cd8/ - **Provider:** OpenNash Podcasts (machine-generated) ## In brief Chris Benson and Daniel Whitenack argue that AI agents, software that carries out tasks and works with other software, are already moving money, jobs and the value of software. They read IBM's sharp one-day stock drop as an early warning. Enterprise software built for humans clicking through screens is losing its edge as agents increasingly deal directly with other agents. The tension is between alarm and practicality. Budgets are being pulled toward hardware, while expensive US models and possibly restricted Chinese models squeeze companies from both sides. The hosts say humans and software vendors can still adapt, by exposing data to agents and dropping old roles. Much of the evidence is anecdotal and news-driven, and IBM's fall is only partly explained. ## Key insights 1. **IBM's plunge is read as an early warning** Daniel cited a roughly 25% single-day drop, about $70 billion of market value, and called it the worst day in over 50 years. Chris says he expects more such disruption because agents are replacing both older technology and human work. 2. **Tech budgets are shifting from software to hardware** Daniel said companies are diverting spending away from enterprise software and services toward hardware and infrastructure, partly out of fear of future AI price hikes. On the same day he saw Workday, Salesforce, ServiceNow and Adobe fall while Nvidia and Intel rose. 3. **Software will increasingly serve agents, not people** Chris argues most system-to-system interactions will be agent to agent, with no human in a vendor's interface. That makes permissions and the configuration of MCP servers (connectors that let agents use a system) a major new problem. 4. **Cost pressure is reviving interest in fine-tuning** Chris hears companies squeezed by pricey US models and possibly restricted Chinese open models returning to training and fine-tuning small models. Daniel adds that long-running cloud agents change the math compared with paying per use for an API. 5. **Companies already run tens of thousands of agents** Daniel said he recently spoke with one company running about 70,000 agents and another with roughly 60,000. He uses this to argue the agent-heavy future is not five years away. ## Questions this episode answers ### Why did IBM's stock fall so sharply? Daniel said it dropped about 25% in one day, roughly $70 billion of value. He cited analysts saying companies are moving tech budgets away from enterprise software and services toward AI hardware and infrastructure, though the hosts do not give IBM's own explanation. ### What does 'agents running agents' mean? An agent is AI software that carries out tasks on its own. Chris says agents now manage other agents inside loops, and he sees setups with hundreds of thousands or even millions of them. ### What is MCP, and why does it matter to software vendors? MCP is a way for AI agents to connect to a vendor's data and features. Daniel said some vendors, like NetSuite, expose their platform through it, while others build their own closed agents instead. ### Will AI agents take people's jobs? Chris says humans still have a place but their roles are changing quickly, and clinging to old roles is a poor strategy. He pointed to mass tech layoffs as companies experiment with agent-based alternatives. ### Why does China matter for the cost of AI? Chris said China's open models are much cheaper than US proprietary ones, but China may now restrict them, removing a fallback for companies. Daniel added that a gray market of resellers has emerged to sell Chinese users access to Western AI services. ## Facts - **Daniel Whitenack** [0:03:16]: "IBM had a major hit in their stock, so 25 stock plunge, which is is kind of crazy." - **Daniel Whitenack** [0:08:35]: "25 single trading session collapse, which is about 70 billion in market value." - **Daniel Whitenack** [0:08:35]: "Marking it the, uh, worst single day drop in over 50 years, um, outpacing even its losses during the 1987 Black Monday market crash." - **Daniel Whitenack** [0:09:18]: "companies are diverting their IT budget or their technology budget away from enterprise software and and services" - **Daniel Whitenack** [0:08:00]: "Anthropic really doubling down on kind of implementation and services side, which we've also seen with with Openai versus kind of the model side." - **Chris Benson** [0:10:17]: "China is now recognizing the value it has in its open models, which are much cheaper to use than the, you know, these expensive proprietary models, you know, in the US." - **Daniel Whitenack** [0:13:15]: "brokers are reselling discounted API access to Western artificial intelligence platforms. AI platforms like Openai or Anthropic" - **Daniel Whitenack** [0:16:02]: "there's platforms like Unsloth and others that allow you to fine tune, uh, you know, even on your MacBook" - **Chris Benson** [0:15:17]: "it seemed like the models got so good that a lot of organizations said, why would we bother with that?" - **Chris Benson** [0:17:14]: "looking at situations where, um, loops are incorporating, um, hundreds of thousands of agents, or millions of agents" - **Daniel Whitenack** [0:20:02]: "we've talked to one one company that already has 70 zero agents running, one that has, I think it was like six zero or something." - **Daniel Whitenack** [0:21:51]: "Which is often MCP, right? So their value is, maybe they're assuming their value is in their data platform, how they organize data" - **Chris Benson** [0:23:05]: "the way interactions will occur is agentially, in a direct, you know. If you might think of it as B2B in a sense, but think of it as agent to agent." - **Chris Benson** [0:25:04]: "loop engineering, you know, we were agentic. Engineering was, you know, kind of the buzzword. Uh, a few months ago, and then lately it's loops" - **Daniel Whitenack** [0:25:53]: "Workday Workday slid down ten, Salesforce nine, ServiceNow eight, Adobe six, um, all, you know, uh, s similar dynamics going on." - **Daniel Whitenack** [0:26:32]: "What did gain was, uh, uh, the, you know, Nvidia, Intel chip chip providers rising as people again, you know, panic, buy some of these, uh, these hardware solutions." - **Chris Benson** [0:28:19]: "I saw a quote earlier today from George Lucas saying, If you're not really on top of this with agentics, you're kind of holding on to the heart, the the heart, the, the, the cart, the cart and horse" - **Chris Benson** [0:28:45]: "we're looking at things like Mythos and fable from, you know, which are the latest generation able to really, um, to really, um, you know, do things that no human is able to do, you know, Mythos, especially in terms of cybersecurity." - **Daniel Whitenack** [0:29:34]: "Anthropic J did just release a paper. Um, I I forget which day re, uh, recently now, whenever it was, uh. Verbalizable representations from a global workspace and language models." - **Daniel Whitenack** [0:30:15]: "there is this functional capability of these models to an improving functional capability of these models. To route and report information." - **Chris Benson** [0:31:20]: "that models are creating what they're calling workspaces, where they're essentially the W. The. The notion of the workspace is fulfilling the same function as working memory in a human brain." ## Transcript **[0:00:02] Ad read:** Welcome 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. Be sure to connect with us on LinkedIn X or Bluesky to stay up to date with episode drops, behind the scenes content and AI insights. **[0:00:32] Ad read:** You can learn more at practicalai. fm. Now on to the show. **[0:00:41] Daniel 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, Good, uh, 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 I'm excited about this. I missed, uh, missed the interview with you last week. **[0:01:08] Daniel Whitenack:** It was a great one, but yeah, excited to be back on. **[0:01:10] Chris Benson:** absolutely good, welcome back. And, uh, I know we both had allergies lately, with summer vacations and family and things like that that we've been doing. Um, good to be back together. And, uh, and yeah, these fully connected episodes, as we call them, um, where, where you and I get to kinda go wherever we wanna go, uh, is are. They're always fun for me, um, yeah, for and it gives for for guests. It gives Dan and I kind of a chance to freelance and to kinda, instead of just focusing on a particular topic, to kinda go wherever we wanna go. **[0:01:40] Chris Benson:** And so we have a good time with them. Um, and so, uh, yeah, and a lot's happening right now. **[0:01:46] Daniel Whitenack:** a lot's happening. And yeah, just as a reminder, also for for our guests, uh, a few things that we we don't normally share on our shows when we have a guest, cause 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 on YouTube. Uh, the Practical AI Show, and of course, you can still listen to us on all the other, all the other places as well. **[0:02:17] Daniel Whitenack:** And then, uh, reminder, just um, coming up in October, October 15th in Indianapolis, we're gonna have another Midwest AI Summit, which was a great experience. Chris and I got to 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 within in AI engineering lounge, where you can sit down and talk through architecture and design, and, uh, agents and plans and security, and whatever you wanna talk about with practitioners. **[0:02:50] Daniel Whitenack:** So check it out, just search for Midwest AI Summit and make sure you get registered for that. But yeah, I'll, I'll just lots, lots of things point out happening. **[0:02:57] Chris Benson:** before you get away from that, I wanna point out that that's a fun conference. You and I go to a lot of conferences, and that one is a fun conference **[0:03:04] Daniel Whitenack:** it is. **[0:03:05] Chris Benson:** and everybody is accessible. If if you wanna talk to somebody, they're there, uh, it, it's great. So I just wanted to point that out. I l I, I love that one. So, uh, yeah, you wanna start us off? **[0:03:16] Daniel Whitenack:** sure, sure, it's, uh, it's interesting today this morning. Uh, 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, uh, like on Prime Video, they have, uh, CNN news highlights or whatever. So sometimes we'll listen to that in in the morning while we're eating our cereal. And this morning on those news highlights, it highlighted that IBM had a major hit in their stock, so 25 stock plunge, which is is kind of crazy. **[0:03:52] Daniel Whitenack:** And it talked about, Oh, IBM has this 25 plunge in their stock. It has something to do with AI. And I was o obviously paying attention. Uh, I don't know that I've, based on how they were describing it, it immediately made sense to me. But I, 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. **[0:04:17] Daniel Whitenack:** So is this something you you ran across or have been thinking about, Chris? **[0:04:21] Chris Benson:** So I wasn't at all surprised, uh, about this in that way, like I, I didn't know that IBM would do this. But so it's something I've been thinking about quite a lot lately, and, uh, it, uh, something that I know I've mentioned this to you. I'll mention it without any names. I'm I'm in discussions about writing a book that's kinda hits this topic, uh, with the CEO of, uh, of a publishing company, uh, and I'll leave it at that. **[0:04:47] Chris Benson:** 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 um, and and the the notion of the book, if it, 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 to where all your emotions are are removed a little bit. **[0:05:15] Chris Benson:** And you say, well, these are what's happening. And you play the events out over months and years, what I? What are the probabilities of various outcomes that that are that are looking like based on today? And I've been going through this exercise, uh, and spending quite a lot of time on it, and so th that's why the IBM thing didn't surprise me. And I think, I I think, uh, just to scare the the heck out of people. **[0:05:40] Chris Benson:** I think that we're gonna 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, um, replacing exist, both existing technologies and existing, uh, human positions and processes that that people are engaged in with these new technologies. And as we scale out that in an agentic world, um, that has quite an impact on the on the fundamental economics of of how businesses, uh, are, are changing. **[0:06:17] Chris Benson:** Now we've seen all the mass layoffs, uh, in the tech industry. And um, we're going through a moment where where companies are really experimenting with hyper productive alternatives to human. Um, and so that doesn't remove all the humans from the equation, but what it does, it ch is it changes their roles, and it changes, um, the activities that the humans are engaged in. And that's evolving, uh, very, very rapidly. And so, um, that, you know, as a start, you know it it leaves it as something, you know. **[0:06:48] Chris Benson:** I know it sounds very ominous, but I think the the key point there, rather than just being frightened of it, is really that the rate of change is accelerating, uh, exponentially right now. And so the IBM thing is kind of that. I know the The New York Times referred to it as potentially a canary in the coal mine, and that's one way of looking at it. Um, but we're going through the beginnings of a period of rapid change in in the fundamentals of business, not not just technology. **[0:07:17] Chris Benson:** It's really important that people catch that, but business itself that's using that technology. So I, I'll stop there for the moment. What? Uh, how? How would you react to that? **[0:07:27] Daniel Whitenack:** yeah, I 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 w were were not. There's, uh, 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've put in and just sort of hemorrhaged over time. **[0:08:00] Daniel Whitenack:** There's also the kind of panic buying uh 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. Um, there's the, you know, I I saw the I. I think it was another article that you had posted to me about, or maybe it was something that I I saw elsewhere. But Anthropic really doubling down on kind of implementation and services side, which we've also seen with with Openai versus kind of the model side. **[0:08:35] Daniel Whitenack:** So so there's so much tied up into this, just to give some stats on the IBM case, the kind of canary, uh, 25 single trading session collapse, which is about 70 billion in market value. Marking it the, uh, worst single day drop in over 50 years, um, outpacing even its losses during the 1987 Black Monday market crash. So a and and part of this, what I was researching is like, well, what's going on? What are the the the at least the cited dynamics that they're talking about in relation to this on, uh, from IBM and and other analysts? **[0:09:18] Daniel Whitenack:** 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 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 m much more context, you have long running processes, et cetera. **[0:09:56] Daniel Whitenack:** And so there's been the shift, uh, I guess, from the capital expenditures on enterprise software and services, at least to some of these hardware and infrastructure expenses. Uh, as kind of, uh, uh, yeah, there's finite bud budget, and there's this tug of war happening. So any thoughts on on that piece of the puzzle? **[0:10:17] Chris Benson:** I I I th so I all those things I think are contributing, and there's something else I I I don't know if, uh, if you, if you saw this in the news, uh, it kind of skimmed by, uh, pretty quietly, I thought, and that was, um. China is now recognizing the value it has in its open models, which are much cheaper to use than the, you know, these expensive proprietary models, you know, in the US. Um, and they're recognizing that while the US. **[0:10:49] Chris Benson:** has has put export controls around that, that, uh, 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, um, may may now become restricted, uh, going forward. And so there's there's this political like th. There is one set of, uh, of capabilities that the US. is stronger in and is putting protections around, and now China has recognized that. There is another set, uh, of capabilities that they are stronger in, um, uh, you know, of economic value, and that they're putting protections around that. **[0:11:25] Chris Benson:** So, um, I think all of these things that we have talked about are are kind of feeding in to, um, to how people are shaping their use of technology. And I think it's creating, to your point, a certain level of panic, uh, in in executive level companies where they're trying to figure out how to mitigate the risk. Both, uh, in terms of the proprietary US. models, the expense associated with that, um, but the fallback strategy of going to Chinese models, uh, if you're in an industry that allows for that, is now closing off potentially as well. **[0:12:00] Chris Benson:** And and so that is is putting a lot of pressure from multiple sides on companies on what they're gonna do. And so they are definitely funneling internal budget, uh, to, uh, to try to mitigate that risk. At the expense of a lot of other things that have historically, uh, been kind of key keystone operations, you know, in their organizations. And 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, um, kind of emergency allocation of capital, uh, and and so, and I don't. **[0:12:37] Chris Benson:** I don't expect that process to stop. I don't think this is a blip. So, um, I think those those things will continue to evolve, but those reactions will continue to. **[0:12:47] Daniel Whitenack:** Have have Chris? I? 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, I have Yeah, so I th this is actually so I'm. I'm all the time learning new things. I my engineers are on Reddit more than more than I am, so I I don't. I hear about things through them, but yeah, so the it's related s to some of what you're talking about. **[0:13:15] Daniel Whitenack:** There's this Chinese token black market, which is kind of a reference to this. Like underground gray market area where, uh, brokers are reselling discounted API access to Western artificial intelligence platforms. AI platforms like Openai or Anthropic, because those services are blocked to mainland, you know, Chinese, uh uh, users. There's a lack of the ability to actually pay for for that. And so there's this economy or ecosystem of resellers and proxies that's emerging to work around this, this kind of access piece. **[0:13:54] Chris Benson:** a. And those kind of things almost always happen when, when you, uh, when you put in kind of regulation for the purpose of artificial shaping, you know, you know, for political ends and such. So you're gonna have black markets, uh, that that appear. So I'm, you know, that that I don't think that should surprise most people seeing that. Uh, so, uh, you know, the question is then, where, where is everything going, you know, with Yeah, if this, and what does it mean for if you're an enterprise, listeners and viewers? **[0:14:23] Daniel Whitenack:** yeah, if you're an enterprise software, well, I guess if you're an enterprise software consumer, or you're an enterprise software s uh vendor, right? What, what? What is the future? I guess, yeah, that's so. Like, if people are moving away from investment in enterprise software, where, where are we going? **[0:14:41] Chris Benson:** 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 US. Obviously, Europe is doing that. We've talked to some of the organizations there, but but also I'm starting to hear about the recognition that there may be a need, uh, 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. **[0:15:17] Chris Benson:** To actually go and and and do training of models, uh, or getting back to fine tuning, I think a lot of organizations got away from. 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, um, and it was good enough without fine tuning, without the cost of that. **[0:15:40] Chris Benson:** And 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 these things that people had said, eh, let's not, we don't need to do that, we don't need to engage in. That are now coming, are are now kind of coming back around. It seems like those are conversations that are starting to happen again. Um, and so I found that that very interesting. **[0:16:02] Daniel Whitenack:** If, yeah, I I think that that also become, I I mean, there's platforms like Unsloth and others that allow you to fine tune, uh, 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 th. This was the episode that I recorded when you were out on vacation. I think Chris, with Zen, the ZenML, um, folks. But as we transition from agents, being like my personal assistant on my laptop, which I interact with back and forth. **[0:16:36] Daniel Whitenack:** Which obviously limits the speed at which, uh, and the amount of context that 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 then all of a sudden the economics do change around. Like, hey, if I'm using a pay pay as I go AI API endpoint, that's gonna be, um, a vastly different economics than a small self hosted M model, right? **[0:17:09] Daniel Whitenack:** That that's powering those agents. So I I do think that that makes a makes an impact. **[0:17:14] Chris Benson:** I, I do too, uh, and I think, you know, uh, but I think what I think we're moving past that. You, you know, when we talk about having our agent, that's long lived and stuff like that, um, and this also depends on industry and need and stuff like that and requirements. But I'm I'm looking at situations where, um, loops are incorporating, um, hundreds of thousands of agents, or millions of agents, um, uh, that are that are all do, uh, creating very complex contextual productivity. **[0:17:45] Chris Benson:** You know, you know, in or outcomes, I would say, you know, in terms of what you're trying to do. So if you are, if you are des uh, assigning agents a bunch of very discrete responsibilities, um, 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 sa set of capabilities that, you know, going back to the IBM thing right here. **[0:18:15] Chris Benson:** 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 can do things that traditional enterprise software just can't touch. And and I think I think that goes to the. You know, when we talk about IBM stock today, I think that's the threat. **[0:18:46] Chris Benson:** But I mean, IBM is is just one significant company in in a in multiple industries, with lots and lots of companies that are essentially taking that enterprise software approach. And they are all at risk, uh, to some degree. And I think the I think that's gonna continue to play out in the marketplace. So it's, you know, the world is shifting, I I the paradigm of operation is shifting significantly right now. Uh, and the economics are going, uh, the economics that that implies are going to to play out. **[0:19:14] Chris Benson:** So I think, 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, you know, we need to move capital from here to there. And and so, and that's impacting em, that's impacting employees and such. **[0:19:31] Daniel Whitenack:** yeah. And as a as a founder of a software company, obviously, I believe there's a place for software in in the future. But I do wanna validate your point of like, like with 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, uh, thousands, hundreds of thousands of agents that need to run, run securely, run, govern, run with identity. And just to validate your point. **[0:20:02] Daniel Whitenack:** Like, even in the last couple weeks, we've talked to one one company that already has 70 zero agents running, one that has, I think it was like six zero or something. So this is not, yes, it is future, but it's not like five years future. This is, this is very rapidly what we're, what, that's what companies are are. So, I 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. **[0:20:32] Daniel Whitenack:** And so this picture of thousands of agents running in enterprise infrastructure might seem far fetched, but I I think it is not it, it is very much. We're. We're getting there very rapidly and and people will start really experiencing this, which I think stresses all of us to think of. Like, you know, in our uh, I, in my world, it's very much like, Hey, as as a software vendor, how do we prepare for that? What? What is your thought, Chris, in relation to, uh, I guess if you're, if you're I, if you have enterprise software that people have been using for some time. **[0:21:16] Daniel Whitenack:** Let's say like IBM, um, or even a smaller midsize or a niche, you know, vertical software vendor, cause 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? What becomes important, what strategy is 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 gonna provide a connector into the AI world, right? **[0:21:51] Daniel Whitenack:** Which is often MCP, right? So their value is, maybe they're assuming their value is in their data platform, how they organize data, the the functionality that you're 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, uh, software companies that are saying no. We're not gonna expose that, but we're gonna create our own proprietary set of agents that are our agents and are gonna run in. **[0:22:25] Daniel Whitenack:** You know what you need, um, and we're not gonna tie into the more generic kind of agentic ecosystem. Do you have any thoughts on that kind of di like, or, or maybe there's like other options within those strategies, right? **[0:22:37] Chris Benson:** so, I think, uh, so, yes, I have some thoughts on that. I think the the world, the so. The way interactions are going to occur are going forward is not going to be in traditional interfaces. You know, the the GUIs and the the web interfaces that people are used to. Y, you know, and that's dominated all the way through, kind of the the early internet era, and then as we got into the cloud era, and then even the beginning of the AI era. **[0:23:05] Chris Benson:** As we've gone to, you know, app interfaces where we've interacted. But going a as we look at agents doing all these different things and collaborating, the way interactions will occur is agentially, in a direct, you know. If you might think of it as B2B in a sense, but think of it as agent to agent. And the vast majority of interactions across different systems will are going to occur agentially, without a human directly involved in most of those processes. **[0:23:32] Chris Benson:** So with those processes being automated, uh, through agentics, um, you have to be thinking that way. So if you're one of these companies, you know, yeah, 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? Uh, into a world in which agentics are incorporated? F from a, uh, a business, uh, a business transaction consideration, you know how that? **[0:24:01] Chris Benson:** It's going to happen without anyone going into your GUI and and without that. You're going to set the permissions, you're gonna set, you know what they have access to, um, and how the MCP servers are are are configured for for the different parts, and that's quite complex. And I think there's a whole industry, uh, right there, of how do you manage, uh, 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. **[0:24:29] Chris Benson:** 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 and I think, going back to your point, this is happening really, really fast now. Um, and so if you're, if you're thinking we're a few years out, then you're gonna get overtaken quite quickly. As IBM discovered this morning with their stock. So, um, not trying to create panic, but people, uh, in these organizations that are stepping into kind of AI and now agentics, they need to be thinking. **[0:25:04] Chris Benson:** Not where are things to 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. Uh, a few months ago, and then lately it's loops, because now your agents are tied up in loops, but tomorrow it's gonna be past. Loops. Looper is a very transitory thing because this is evolving so quickly. Um, by 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. **[0:25:39] Chris Benson:** 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. **[0:25:53] Daniel Whitenack:** yeah, and just, uh, to make sure we're not, uh, painting or or just taking one data point. Th th this is this is, uh, 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 as IBM crash, um, it looks like, uh, unless, unless my agent is hallucinating. Um, Workday Workday slid down ten, Salesforce nine, ServiceNow eight, Adobe six, um, all, you know, uh, s similar dynamics going on. **[0:26:32] Daniel Whitenack:** What did gain was, uh, uh, the, you know, Nvidia, Intel chip chip providers rising as people again, you know, panic, buy some of these, uh, these hardware solutions. Um, and there is a lot of, I think, distraction related to the cybersecurity side of this as well, which is partially related to the hardware, but more, uh, more related to maybe some of this distraction around. Mythos and cybersecurity and how agents violate, you know, cybersecurity. And so there's, um, there's a focus on that, rather than kind of the generic, uh, SaaS software and enterprise software as well. **[0:27:13] Daniel Whitenack:** So just wanted to bring in a couple of those points. Um, I was And and hoping, uh, I was hoping my additional agentic research would back up our points, and it seems like it does so. **[0:27:22] Chris Benson:** I I think so, and I think I think those are good call outs in terms of, you know, you're, you're looking at enterprise software companies struggling, uh, because people are starting to realize what's happening, uh, and not not going to happen happening. And and so I I think, to your point, there's also needs to be a rethink, uh, and I think this is really important. And and and I, I'm not claiming to have all the answers by by any stretch, but there needs to be a rethink about how humans are fitting into this equation. **[0:27:54] Chris Benson:** I, I do think that there is a place for them. I think it's very different going forward. Um, I think trying to hold on to old roles is, uh, is not the best strategy. I think being creative and, uh, you know, Re, I. I get into these conversations with people all the time where they're kind of they're kind of, um, holding on to what was. They don't wanna let it go. It's what they know, it's what they're comfortable with. **[0:28:19] Chris Benson:** Um, I saw a quote earlier today from George Lucas saying, If you're not really on top of this with agentics, you're kind of holding on to the heart, the the heart, the, the, the cart, the cart and horse in a day where the automobile is happening. And I think that still happens a lot. Cause I get into all these conversations, um, especially with with older, you know, people closer to my age, um, that are seeing the world change out from under them very quickly. **[0:28:45] Chris Benson:** I think the right strategy is to recognize what agentic's is really good at doing. And and also, you know, like, we're, we're looking at things like Mythos and fable from, you know, which are the latest generation able to really, um, to really, um, you know, do things that no human is able to do, you know, Mythos, especially in terms of cybersecurity. And I think you embrace that, I think you recognize that's not gonna change, um, and you embrace those, change and look for places where you can plug in on that. **[0:29:14] Chris Benson:** And so, and I'm gonna do a lot more, uh, exploration of these ideas in the days ahead, especially like I said, if I end up writing anything about it. But um, yeah, it's the world's changing really fa faster than it ever has. Right now, it's speeding up much faster than it was a year ago. Um, and so it's, uh, it's a good moment for people to self reflect a bit. **[0:29:34] Daniel Whitenack:** yeah, yeah, and that gets. This is maybe something for a complete other episode once we do the full research on it, Chris. But to your point, in terms of how things are advancing, Anthropic J did just release a paper. Um, I I forget which day re, uh, recently now, whenever it was, uh. Verbalizable representations from a global workspace and language models. This is basically th. It's a lot of words, but part of this is talking about, you know what, what forms of, uh, uh, consciousness, access, e emergent behavior, like w how, how understanding is represented in these models. **[0:30:15] Daniel Whitenack:** And, uh, there's some interesting things there, obviously. Th. There's always a wide range of opinions once you start thinking about, or once you start proposing. What is cognition, what is consciousness, what types of consciousness are there, what can be included in these models, what do they understand? Um, but anyway, the the there, there is continued thinking there. And I think one of the the, uh, points of the paper, if I'm understanding it right, whatever your take on sort of consciousness and cognition, is that there is this functional capability of these models to an improving functional capability of these models. **[0:30:58] Daniel Whitenack:** To route and report information. So this is not like they're feeling, or they like they have emotions necessarily, or or other types of consciousness. But certainly there is this capability of routing and reporting information, which is obviously key to the uh, k, key to the agentic transformation that we're seeing. So there may be more on that in the future. **[0:31:20] Chris Benson:** Yeah, I I think, you know, one of the things in the paper that you're referencing that was pointed out was that, um, Anthropic had noticed that, um, that models are creating what they're calling workspaces, where they're essentially the W. The. The notion of the workspace is fulfilling the same function as working memory in a human brain. And and that, you know, and so I think one of the big questions, and you have both sides of people on the consciousness side. **[0:31:49] Chris Benson:** Uh, some people are saying that's not what consciousness is, uh, and other people are saying, what if? What I would say is, um, sadly, there's never been a u a unified, uh, definition of what consciousness is that is widely accepted. So, uh, uh, that needs to be put out there, um. But I think that there's also the consideration of if. If you have a model, kind of achieving an outcome, an apparent outcome, based on what, based on what it's doing, um, but it achieves it in a way that's very different from what we traditionally would associate with. **[0:32:27] Chris Benson:** Um, and like, so, if you're really trying to model consciousness around what a mammal, a mammalian brain does, and how it achieves that, um, or are you willing to say there are alternative paths? That, if you get to the same kind of an outcome for a given task associated with that, is that legitimate? And I think that's kind of when I look at the argument, that's how I perceive. That is, there are people who are who, um, have a a very strict and narrow definition that are probably traditional neuroscientists, um, in terms of how they're doing it. **[0:32:58] Chris Benson:** And then I'm seeing other people that are kind of going going. But if it's getting to the same place in function, you know, not full consciousness, but some of the things that would contribute toward that, does that count? And so there's a little bit of a philosophical debate on on, um, what's legitimate at this point? Um, I think it's interesting, uh, I, I, and it wouldn't surprise me if, um, some of these things arise eventually, emergent qualities arise from vastly different ways from what we had anticipated. **[0:33:26] Chris Benson:** So, um, I'm pretty open minded in terms of how things can. Uh, can something that we never would've expected to happen contribute towards something that we were ultimately an outcome that we were looking for? So **[0:33:37] Daniel Whitenack:** yeah, yeah, I like, um, actually, it was a sugg suggestion from one of our customers. And and when we were discussing things, uh, they're, they're thinking about the rather, uh, you know, obviously there's an architecture associated with agents that y each company is trying to enable. But thinking about things at the level of outcome and how how do we achieve these outcomes? And what's the necessary human input? What is the possibilities with the agentic, uh, systems that we that we can deploy? **[0:34:08] Daniel Whitenack:** I I think it is very useful to think at that outcome level. And um, Chris, I'm, I'm pretty, uh, I'm pretty happy with the the outcome of some of this, this discussion. I think fun it was, I think it was **[0:34:21] Chris Benson:** conversations, I know. a good one. Um, Ha enjoy this. These for for folks that are watching or listening, these are completely unscripted. This is just us having fun. So, uh, yeah, that's, uh, a good one today, and, uh, gives, given me a lot of, uh, food for thought, uh, for going forward. Uh, we l. We hope folks will engage us on the social social media channels, uh, YouTube and the others that they find us on. Um, give us your feedback, let us know what you think. **[0:34:48] Chris Benson:** We'd love to, uh, we'd love to get your insights into these. **[0:34:52] Daniel Whitenack:** yes, for sure. Have a good day, Chris. We'll see you soon. **[0:34:54] Chris Benson:** Take care. **[0:35:00] Ad read:** All right, that's our show for this week. If you haven't checked out our website, head to practicalai fm and be sure to connect with us on LinkedIn X or Bluesky. You'll see us posting insights related to the latest AI developments, and we would love for you to join the conversation. Thanks to our partner Prediction Guard for providing operational support for the show. Check them out at predictionguard com. Also, thanks to Breakmaster Cylinder for the beats and to you for listening. **[0:35:27] Ad read:** That's all for now, but you'll hear from us again next week.