What Happens When Hype Hits Budgets

Cloud was supposed to simplify everything. Instead, a lot of CIOs are staring at bills that are far higher than anyone forecast, feeling locked into hyperscalers, and wondering where the business value went. I sit down with David Linthicum, former Deloitte chief cloud strategy officer turned tech influencer, to give an unvarnished reality check on cloud computing costs, cloud repatriation, and what “pragmatic architecture” looks like when budgets are real and timelines are slow.

We also get blunt about enterprise AI. David explains why so many AI-driven transformations stall out on two constraints: money and talent. We dig into why AI can cost 10 to 20 times more than traditional software, why “AI-first enterprise” messaging can be dangerous, and how leaders can pick high-impact use cases instead of trying to bolt generative AI onto everything. Along the way, we talk about how AI is reshaping SaaS economics as agents start using systems on behalf of humans, and what that means for vendors and buyers.

Then we tackle the loudest buzzword of the moment: agentic AI. Where does it shine as a productivity force multiplier, and where is it mostly hype when you try to deploy it at enterprise scale? We round out with underhyped edge computing opportunities and the growing backlash around data centers, power, and the grid. If you care about enterprise architecture, cloud strategy, generative AI, and what’s actually deployable right now, you’ll get a clear set of takeaways you can use this week. Subscribe, share this with a CIO or architect, and leave a review with the most overrated tech trend you want us to challenge next.

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Transcript

SPEAKER_00 0:06

Hey everybody, boy, do I have a treat for us today? The man, the legend, David Lindhacum. How are you?

SPEAKER_01 0:13

Legend in my own mind. Evan, how's it going, man?

SPEAKER_00 0:17

You and me both. Uh, great to speak with you. We've chatted many times in the past, particularly in your decade-long tenure at Deloitte, but you are a free range, uh, free bird now. And I have so many questions and topics to uh to discuss with you today. Before that, how do you describe yourself now and your work? Uh, now that you're out of the corporate rat race.

SPEAKER_01 0:40

Yeah, I guess I'm best described as a tech influencer focusing on cloud and AI. Obviously, spent um eight, nine years as Deloitte as the chief cloud strategy officer, worked on cloud strategy, worked with a lot of clients, had a lot of fun there. But now I'm, you know, looking at technology, trying to figure out where it's going to be applicable to businesses, how do they use it, you know, patterns of success, patterns of failure, and the ability to kind of look at this stuff through a pro uh through a uh you know, pragmatic eye, which I think is missing out there. So telling the truth, calling balls and strikes, you know, trying to not get down with the narrative as much as possible, and helping people get through AI, helping people get through cloud computing, and trying to figure out what this technology is going to fit and how to use it.

SPEAKER_00 1:21

Well, that's a lot to unpack, but we have some time and I appreciate you joining here today. Um, gosh, where do we even start? Let's start cloud. You mentioned cloud. Uh I've been following the cloud journey like yourself for for two decades. Are are we in the golden era of cloud now or or was uh in the cloud hangover uh era? What how would you describe the state of the union here?

SPEAKER_01 1:45

I think it's definitely the cloud hangover, and what we've done is kind of baked it into the cake. So, in other words, it's part of the infrastructure. We're not looking at it as new technology anymore. It's in its sixth or seventh generation. Now that AI is coming up fast and furious, people are looking at the cloud as a place to run it, but also reevaluating many of the migrations that they made over the last 15 years to the cloud, many of which I was involved in. And so, in other words, they've migrated 10,000 applications to the cloud. They got 50% of their infrastructure, which is outsourced to AWS, Microsoft, or Google, or perhaps even somebody else. And now they're trying to figure out how they're gonna make money at it. You know, as I wrote my insider's book, you know, people are realizing the price of cloud is about three to four times what they thought it was going to be. And I'm seeing that as a common pattern. And so they are looking at the value of this technology and then trying to figure out if they need to modernize it or normalize it in some way that's gonna bring more value back to the business. Because as you know, my CIO friends tell me, and those are the people actually the heroes of the world, trying to make this AI cloud stuff work, that it's they don't have an unlimited pile of money. And the reality is if the cloud is taking more than their share, then they're unable to put it in other places. It's naming AI, you know, edge computing, whatever they're they want to invest in. And they're trying to normalize that and trying to find value in these stacks. And so many of these enterprises are reevaluating the cloud, they're moving it off to co-location providers, managed service providers, or even modernizing their systems in place in the cloud. So the cloud is, you know, trying to find its legitimate place where it's going to do the least amount of damage and provide the most amount of value. And I think that is the big focus now. And so it is definitely in the hangover stage. I think uh uh most of the CIOs that I talk to, they feel like they're getting extorted by the cloud providers, not necessarily getting value from them. And they're locked into those infrastructures and uh they're trying to make sense of it. And that's really the name of the game right now. And now the AI is just putting urgency behind it.

SPEAKER_00 3:37

Wow, that was really well said in uh just under a minute. So the cloud bill hangover era, I think, is the way we uh describe it. Of course, it wouldn't be a tech chat if we didn't talk about AI. Isn't one of the challenges is AI is suddenly making this old enterprise software look even more ancient? I mean, isn't that one of the main challenges? We're forcing uh enterprise SaaS into modernization, whether they like it much or not.

SPEAKER_01 4:06

It is. And I think that's uh, you know, it's kind of a core challenge of the SaaS providers out there now. They have a couple of things. Number one, AI is showing them up in terms of their ability to provide value and certainly like things like Salesforce automation. I'm able to leverage chat GPTs in ways. I mean, it's like LLMs in ways, and I'm able to get value out of it more so than the SaaS uh SaaS systems out there, Salesforce and you know, the hundreds of others that are out there. And the other thing is they're going to end up losing revenue from the fact that people are multiplexing their SaaS connections. In other words, they're they're not necessarily using SaaS as a human, but they're using it or consuming it as an agent. And so, in other words, you can have one agent which is consuming a few less sessions of SaaS and therefore their revenue is gonna go down. So they're trying to figure that out. So everybody called for the demise, you know, a couple of months ago, and I got a few reporters who talked to me about that. I think that's overblown. I think at the end of the day, they're gonna have to get used to the new market. The reality is that they're selling software and they're selling business solutions. And if able people are able to consume those business solutions in other places, certainly an LLM or are basically some of the new startups that are leveraging LLMs, that's gonna be the new normal and they're gonna have to figure out how to make it work. And I think there's gonna maybe a uh less share of a pie out there ultimately, and then certainly the growth is gonna slow down a bit. So they're gonna have to figure out a new path through that.

SPEAKER_00 5:24

Well said. On a side note, you and I both have an uh affinity for nostalgia, tech nostalgia, retro tech, retrocomputing. I love your post, by the way.

SPEAKER_01 5:34

Your posts are amazing.

SPEAKER_00 5:35

Thank you. And I think it's because we're both old, or at least of that era, we begin to look back. Do you remember when software was sold in shrink rack boxes? You went into a store and you bought your software and you owned it. And um, is this truly nostalgia, or are we going to get back to that in some form or fashion one day, do you think? Maybe with AI and private AI and that kind of thing.

SPEAKER_01 5:57

I think those days are gone. I think going into a micro center, which was my favorite, you know, my my happy place back before the NAT, and we had to go to the, you know, tech, you know, to the tech newsstand and you know, buy all the different papers and things like that. And then also buying getting software and getting the CD or even getting the three by five-inch floppies or even the five and a half inch floppies.

SPEAKER_00 6:17

Or 20 of them, but yes.

SPEAKER_01 6:18

20 of them, yeah. That was awesome. Amazing. Try installing an operating system took all day. Um, the those days are long gone. Everything's gonna be connected, everything's gonna be automatically distributed, things like that. That's just the way it's going to be. And but I think at the end of the day, businesses are gonna be able to choose their own journey in terms of what kind of software is gonna be needed specifically for that. Now, if you talk to people who are consuming SAP and Salesforce and other, you know, canned business applications, they're gonna say, well, it really kind of meets about 90% of my needs. And the other 10% it doesn't. And I think where we're headed now, you're gonna be able to define what that 10% additional is, and you will build that on top of the SaaS systems, or even build build a complete SaaS system for yourselves. And I think that's gonna be the benefits of AI. Now it's a little dangerous to start generating code, it's basically gonna be something that's gonna work awesome until you try to maintain it and that's gonna fall apart. But we're gonna find some uh kind of combination, some kind of a gray space between what SaaS providers are able to provide and the ability to augment those sorts of things with AI. And I think the SaaS providers are trying to figure that out now. And they're doing a lot of missteps in the marketplace. I wish I was there as their CTO. I could guide them as to where they should be focused. But eventually they'll figure it out. And I think SaaS is gonna be a very different game in three or four years, probably even just you know, two years, uh, uh based on what it is today. And it's gonna be a very different market. People are gonna choose their own journey. They're not necessarily gonna choose the Salesforce journey or the Net Suite journey or the SAP journey. It's gonna be a little bit more customized for their exact needs.

SPEAKER_00 7:46

Yeah, and speaking of needs and journeys, you know, everyone's talking about AI-driven transformation, but so much of it is being blocked, uh blocked for many reasons, uh, cultural, financial, uh, bad data architectures. What's happening in actuality about these AI journeys, these transformations that's stopping them from really reaching the potential that's so talked about?

SPEAKER_01 8:10

Yeah, two words, money and talent. I mean, that's what I'm hearing all the time. And and so some of the tech providers or AI providers are coming to me and they say, we're not getting seeing the adoption that we thought they would see. You know, AI is gonna be the next revolution. You hear any keynote, you know, talking about the AI first enterprise and all this kind of dribble out there with that. And but the reality is that um um, sure, but you got to remember they don't have an unlimited piles of money. And you're really kind of talking about them about building solutions that are gonna cost 10 to 20 times that of using traditional software. People don't realize that. And, you know, those are the metrics. And you can go ahead and, you know, Google it or Chat GPT, and you're gonna find those metrics are gonna be sound. So without that big pile of money that the enterprises don't have, it's difficult for them to move into AI. That's the big thing. And I think that unless they are able to free up some resources or the AI industry, if you're listening to AI industry, get a clue here, are able to provide more pragmatic use of the technology is going to be optimized for how much money they're looking to pay, versus assuming that we're gonna throw GPUs at everything and DRAM at everything and all this expensive resources. Get into the little bit more of a pragmatic deployment. Also, the ability to kind of look at the use cases. AI is not meant for everything, it's probably meant for about 20 to 30, uh 20 to 40% of the applications at the bare minimum, at the best case scenario. So try to figure out how to pick your battles. And I think people are mispicking their battles right now. So spending too much money, mispicking their battles, and the other thing would be talent. In other words, we just don't have enough AI people around who understand AI. And we have a lot of people out there, they're doing real damage. When I hear, you know, I'm an AI strategy officer, and I kind of look at what they're doing, and I realize they're just kind of guessing their way through it and following the hype. And that's not the way to do it. They're gonna be spending lots of money fairly quickly, very much like we did with cloud 15 years ago, where not a lot of business value that's coming back. And so the reality of that, we're not producing enough AI people who have an understanding of AI specifically, how it's gonna be strategically used. People were able to look at it with a more pragmatic eye. They're just throwing money at it, and that's gonna just get them in trouble. So I see very many of the same patterns how we messed up cloud computing, you know, 10, 15 years ago, you know, occurring in the AI field right now. And so eventually there's gonna be a day of reckoning. We talk about the cloud hangover. There's gonna be a huge AI hangover. It's gonna feel worse than any other hangover we ever had.

SPEAKER_00 10:26

Well, get your hangover remedies ready. Uh, speaking of AI, agentic AI, of course, is all the rage. And I personally, professionally think for very good reason. I've I have two agents I'm keeping an eye on in the background here as we're talking. One from Mattis that's doing some posting for me, the other from uh Claude Cowork that's editing a video in a way that I could never do personally. So as a as a solo practitioner, small business, I guess you could call me, I'm super excited. I mean, this is this is a force multiplier. There uh co-work is a true digital worker, at least for me. But what's happening in the enterprise? Why, you know, isn't uh agentic AI really being deployed in the vision of digital workers in which it's being touted? Is it just the complexity and the rules and the and the security challenges? Is it really not ready for prime time yet?

SPEAKER_01 11:19

It is for edge cases. Now, everything you just described to me is an edge case. In other words, you're using it to uh enhance your productivity. In other words, instead of working on a terminal or working on your workstation, you have an agent that's basically taking that stuff over and is able to carry out aspects of it and the ability to automate tasks. Agentic AI, and we've known this since the 80s, and that's when I was building AI agents back there. We're gonna be really good at that. The ability to take proactive tasks, the ability to learn as it goes, the ability to, in essence, emulate kind of human intelligence and carry out certain very narrowly focused tasks, just like you just described. And I think we're gonna see some uplift there. But the reality is the real value that the businesses are gonna find from a gentic AI or AI in general is going to be with the core use cases. In other words, your ability to automate inventory control and sales, you know, sales automation, logistics processing, factory resource management, all these kind of core things that really allow them to make money versus the edge cases where it's just basically enhancing somebody's you know personal productivity, which is where people are using it now. So the big thing is number one, finding the use, the business cases for it. So agentic AI is gonna have very narrowly focused use cases. You just hit a couple that are gonna be that I'm seeing really kind of a strong use cases for agentic AI. It's not gonna have use cases for the larger enterprises for the most part. Um, if anything, it's gonna be core AI systems, generative AI or just basically machine learning or even deep learning-based systems, you know, old school stuff. And that's where I think people don't understand the match. In other words, the tech guys are coming to me and they're saying, hey, we're not seeing the adoption of agentic AI based on, you know, what you think we saw. And I say, But number one, you didn't hear it from me. Um and so, you know, go back to those influencers and yell at them. So number two is they don't have a lot of money to deploy at this stuff. And the big thing is it's gonna have very narrow use cases, which are going to be more edge cases. And so it's not gonna be core to your business. It's not gonna be, you know, replacing all of your humans with digital workers. I mean, that's stuff like McKenzie's saying and other folks are talking about we have, you know, 20,000 of our employees or agents, all that stuff's a pile of crap. And and at the end of the day, again, you get into the monetary resources, your use of the technology, your ability to have true architects who are able to look at how you're going to apply this stuff. It's one of these things where it's helpful, but it's not the revolution that people think it's going to be. And there's and the reality is we've been doing agentic AI since the 80s, since I got in this business. We're just really, really good at using it now. We get lots of very cool platforms. But the way in which it's architected and the way in which it's defined, you know, the proactive use of AI is going to be have very few use cases out there relative to all the business problems we're looking to solve.

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SPEAKER_00 13:56

Wow.

(Cont.) What Happens When Hype Hits Budgets

SPEAKER_00 13:57

Such a realistic take and great insights. You advise so many Fortune 2000 CIOs out there. What's one AI investment you'd suggest they avoid, at least right for now?

SPEAKER_01 14:12

I I think it would be um uh in the agentic AI space based on the amount of hype that's out there. And so that's the number one question that I get in there. I you know I have the best-selling uh agentic AI architecture course out on out on LinkedIn Learning, about you know we're pushing up to about 300,000 people who have taken the course and graduated from the course. So they come to me with where they're hoping to get cheerlead uh agentic AI cheerleader and trying to figure out you know what you're gonna use for this stuff. And they're gonna get basic a pragmatic understanding of what an architect should tell you. In other words, I'm here to represent the business. And that is so overblown right now based on what the uh leaders of these companies are saying. I mean, I had a you know, a video I said, you know, agentic everything, agentic people, agentic water, you know, and it's all part of the nomenclature now where it's almost silly and ridiculous. And I don't think the enterprises are gonna be able to follow that and really kind of make use of it, basically for the reasons that we're just talking about. So my advice would be it's always gonna be an architectural resource. You're able to leverage an architectural pattern that you're able to bring to some solutions, but it's not, it shouldn't be applied everywhere. Normally, best I can tell, it's gonna be 10%, 15% of the existing problem domains that are out there. Uh, and you're gonna have to figure out how to use it in very narrowly focused ways. Don't get involved in the hype, don't listen to you know, all the craziness is going on right now. Look at your own issues, figure out how the technology is going to back in and solve any number of those problems. And chances are it's not gonna be agentic. And uh, and chances are if you're gonna use AI, you're gonna have to use it sparingly just because of the cost. So that's the reality of it. You know, I hate to be the designated buzzkill, but there's so many people out there that are running around in circles, you know, with their hair on fire, you know, saying agentic AI, agentic AI, agentic AI. And it's gonna be replaced by some other buzzword in a couple of years, and we're gonna be on to something else, and it's gonna be just craziness. Now, hopefully, a lot, not a lot of people are gonna buy into uh, you know, into the uh the voodoo, you know, that's supposed to be agentic AI, and we're gonna learn from it and then move on. And I think we're gonna see, you know, this technology, don't get me wrong, technology is value. I mean, the use cases you just presented are an example of that. You know, I also have um open claw running on a Mac mini, and you know, I'm doing experimentations for my agentic AI class and all that kind of stuff. And we're doing, but the reality is I also see its viability and its use, and I think it's gonna be overly exposed right now. So that's my only bummer, you know, prediction is the agentic AI stuff is probably a fraction of what uh what the value that they're proposing.

SPEAKER_00 16:39

Well, it's great to see some balance. The sunshine pump is constantly pumping every day, including yours truly. I I love I had to get excited about emerging tech. But uh balance in all things. But speaking of balance, I mean, what does, in your view, a modern enterprise architecture stack look like in three years? What is your vision of you know, this architecture and apps and cloud and orchestration and how that comes together in a realistic but you know elegant way?

SPEAKER_01 17:10

Yeah, pretty much like it looks now. Yeah, uh Evan, you know, I would love to tell you that it's gonna be completely replaced by antic everything, and you know, there's gonna be no humans and all that kind of stuff. And the reality is that enterprises don't move that fast. So the revolution, and basically look at the past patterns, the revolution of cloud, you know, back in 2009 to 2013. I mean, Gartner was saying we're gonna be, you know, have 80% of our applications in the cloud in a year, and everybody gets excited about that. But if you go forward a year, basically their stacks looked exactly the same, maybe with a few cloud projects there. So the stack is going to be hopefully gonna be something with better data because everybody has has to get a hand on their data to get any kind of AI stuff working or any kind of business processes working, and hopefully they can do aspects of that in three years. But I don't think a lot of progress is gonna be made just because the amount of money that can be spent and how quickly they can they can use. Now, if it was 10 years, 15 years maybe a little different. There's gonna be some AI that's gonna be associated with a stack, but it's going to be, you know, maybe 20% of the existing systems and typically the edge cases, they're gonna be best automated by that. It's not gonna be many of the core systems that we talked about, um, you know, Salesforce automation and factory management and all the things that are really core to the business, just because the amount of cost it's gonna take to augment those systems and the risk it's gonna take to take them offline to get them changed. So you go forward three years, you're looking at you know, the stack of a hospital system or a factory or a manufacturer or a retailer, it's gonna look very much like it is today with probably a few pockets of AI, you know, that they're able to leverage, probably a lot of AI that's that's been snuck into the enterprise being by being bound to whatever application software they're using. Obviously, a everything in the world right now, if you're using any software, any automation, they're gonna have AI, which is gonna be an option of the system. They hook everything up to an LLM. But as far as real value, real use, real usage of the system, it's gonna be very much like you see today. And that's the bummer. But the reality is enterprises, and and this is my experience, been in here a long time, only move so fast. They only have so much money, they are willing to approve, but the improvement is gonna take five to 10 years. It's never gonna take two to three years, and it's definitely never gonna take a year. Anyone tells me that it's gonna be a year in production, we're gonna move to, you know, 50% of the uh human, I heard this a bunch of times, 50% of the humans are gonna be replaced by agents in just a year's time. You're full of crap. You're gonna be wrong. And so I hate to say it, I would love to have that happen. I love science fiction, but the reality is I have real clients that have real budgets and and real objectives, and I'm very quickly to tell them pragmatically what they're able to do.

SPEAKER_00 19:40

Oh, that's great advice. And if anything, the cost equation was for me even a surprise with my two agents hundreds and hundreds of dollars in token costs. This is at a high plan and with subsidized token costs from Claude and Madison and uh and others. So the the uh the bill for those tokens is only now kind of catching up for all of these use cases. Uh, probably some of these use cases will cost more than the human or humans that were doing the job. So there's like you said, uh so much hype needs to meet the reality uh out there. Um what's an enterprise tech or trend that you think is underhyped or underappreciated? Maybe something used personally. I'll give uh mine example. I I'm just so excited about the wireless technologies from Starlink, uh 5G Advanced, uh, which is sort of the bridge between 5 and 6G. You're seeing from some players, really exciting opportunities uh for video and other applications and Wi-Fi 7 outcoming Wi-Fi 8, really interesting opportunities for campus wireless. But what about yourself? What are you some of the technologies you're tracking that you think aren't getting a lot of attention?

SPEAKER_01 20:51

Actually, it's similar to yours, but not really communication, but dealing with the growth of the edge-based stuff. And so, in other words, the ability to use devices and automobiles and all these sorts of things, and even looking, you know, putting AI at the edge in many of these things, that's gonna be a huge growth opportunity right now because we have a lot of processing power that lives in these devices, my thermostats, you know, everything else is a pretty much a high-powered computer, as long as the memory doesn't get expensive. And the ability to really kind of push many of the processes out of these devices closer to where it's gonna be dealing with the data and where you do have additional bandwidth uh availability. You just mentioned two uh technologies are gonna be moving in the area, is really kind of underrated. And so, in other words, everybody's focused, everybody's talking about edge technology five years ago. Now everybody's focused back on putting things into some sort of a centralized processor and building data centers and you know, shoving everything into that. And the reality is we don't need to do that. We have all these underutilized devices, edge based computers. You know, our computers we're staring at right now, I guarantee you they're at 5% utilization. We're able to use them for other things. And the ability to use those in a more effective way and the ability to have common infrastructure to make that happen. So common security control planes. Common security, common operations control planes, governance control planes. All these sorts of things are going to be needed to make that happen. That's what's being undersold right now. And many enterprises who had very good edge computing strategies a few years ago have kind of abandoned that, chasing the AI, uh AI stuff. In the reality, they should be thinking of both. And I think that they're going to be missing out on a big opportunity to leverage technology in a way that is truly going to be a force multiplier.

SPEAKER_00 22:26

Love that. Good to know. You're in Virginia, Northern Virginia, uh epicenter of the data center world. How did you survive to this point in terms of water and power with all of those data centers in your backyard? Kind of a cheeky question. But what is the reality given this huge pushback against data centers, multiple states banning data center projects, grassroots uh uh folks out there protesting data center builds for, you know, maybe good reasons. Uh, what's your take on this whole really difficult question right now?

SPEAKER_01 23:03

Yeah, the the data center folks really kind of uh uh made a misstep and they didn't think in terms of what kind of repercussions were gonna come back. Uh and they just went ahead and decided that they work like they did for the last 20 years, but just accelerate 20 times, 30 times as much. And there's some real limitations there. Number one, uh the grid is not gonna be able to take it. Um we don't have enough power around here to run the data centers that they built. And so funny is when they announced that they're they're going to cancel or delay half of the data center projects for 2026. I mean, who didn't think that see that coming? Anybody who can do math in looking at the grid, the capacity, and what you're able to bring up. And also not an understanding in terms of how people think about that. Data centers are these big, I mean, uh are these big, ugly buildings. They're four stories high, they have no windows, they don't employ anybody. They may have six cars in front of them at every given time. Everything's automated. And the reality is it's not gonna do the community uh communities any particular good. Now, it isn't loud in county because guess what? They're paying a ton of taxes. In fact, half the tax revenue is coming in directly from the data center crew, and this is the richest county in the world, and it's gonna continue to be that because they're gonna allow the data centers in because of the power and the also we have a big bundle of fiber coming out of the ground here, and so it's it's it's cost effective to put them here, but eventually there's going to be some sort of limitation you're gonna reach. And I think the grid is gonna be a limitation here. By the way, we burned coal around here, it's not solar, you know, it's not nuclear power. And so, you know, yeah, and uh, everybody is funny, everybody was talking about green computing, you know, 10 years ago, and I was in the middle of that. You don't hear a lick of it now. So everybody's like they're putting their signs in the garbage.

SPEAKER_00 24:38

Well, nuclear is green, I guess.

SPEAKER_01 24:40

That yeah, nuclear is green, but you get pushback on that too. They were talking about that, and everybody, everybody lost their heads. And so, well, it's got to come from someplace, it's not gonna come from solar or steam or you know, anything like that. So it's either come from uh fossil fuel or it's gonna come from nuclear. So pick pick one or no data centers. And I think people are saying no data centers. And I think they didn't understand that kind of repercussion coming back. And the reality is people are a little sensitive when you go through that kind of a gross spurt. So, in other words, if the data center folks would have said, let's be a little bit more conservative in how we roll this stuff out, let's also put community education that's aligned with how we're gonna roll the data centers out, that would go go to an end degree. They didn't do that. They just went ahead and, you know, if they can, they should. And they went ahead and did it, and now everybody's losing their mind and they're getting a grassroots pushback, and they're out there with pitchforks and torches, and they're about to burn the places down. And it's their own fault. In other words, they should have understood that this was going to be the repercussions for them doing that. Most people aren't in IT. They don't, you know, they're not talking about AI and cloud computing like we are and care less about data centers, but they see these big ugly buildings are making their power bill go up and or uh, you know, making lots of weird noises. Sounds like an alien uh spacecraft. They're gonna they're gonna not like that. And so who would have thought that coming? I think anybody with a brain.

SPEAKER_00 25:57

Yes. Uh it's that not in my backyard. Uh, particularly, you know, you have some of the most beautiful countryside in the country.

SPEAKER_01 26:04

Well, it is in my backyard, but yeah, maybe not in your backyard. My backyard's already got a data center in it.

SPEAKER_00 26:10

Uh let's talk about you and your body of work. Uh you're you've become a social media superstar. Uh, you know, how how many YouTube followers, can uh subscribers do you have now?

SPEAKER_01 26:24

Uh I got about 320,000 on the Cloud Insider channel. That's the older of the channel. I started that the day I retired from Deloitte. Uh, and then Dave is not AI, which basically talks about many of the topics we just talked about, limitations of AI, pragmatic use of the technology, things like that, um, which is about a year old and it's about a hundred and hundred and twenty-five thousand, I think, followers, and then about two hundred thousand on uh on um on LinkedIn. And I I know uh you're doing a major, you're doing some major numbers there too, as well as Twitter. Oh, sorry, Twitter X. Um, so just getting back into the social media stuff, I definitely wasn't posting a lot when I was at Deloitte because I couldn't, because there was limitations of what I could say. Thing has things had to be approved, and I had some things I had to take down. Um, but getting back into it, you know, really kind of using social media as a way to get some of the ideas out there that I think are not necessarily contrarian, but I think are needed in the marketplace right now. In other words, the ability to take a pragmatic use of look at this stuff, what we can afford, how to use it, how to make it work, I think that's really kind of undervalued in the market right now. We have so many people out there just cheerleading, you know, getting in a big circle, going to the conferences, and you know, just getting and you know, starting to talk about the the joy of AI and all this sort of things. Well, there's a good and the bad aspect of anything. And your ability to kind of look at both sides, I think has been missing in the market. And that's that was something I think resonated with a lot of my followers. We're mostly IT leaders. They're mostly CIOs and you know, people who are working, you know, in the industry, and they were looking for an uh a voice where they're telling them a bit more of the truth and not necessarily everything on the positive side. And so I'm playing that role, and I'm gonna be playing that role probably to the end of my day. And fortunately enough, people like it, so they follow me.

SPEAKER_00 28:00

And they do, and obviously, brilliant insights and analysis and a unique point of view, and being uh occasional tranquarian is amazing. But also, there are best practices, any tips, tricks, uh, insights, uh tactics you'd recommend for folks, including myself, I I learn from you, but but others who are building a channel, building their social and digital footprint and presence, because it's not just what you say and your point of view. There's there's a lot behind the scenes that has to work. What's what's a couple of uh tactics on YouTube, for example, or LinkedIn that really worked for you?

SPEAKER_01 28:34

Yeah, what I do is I use uh LinkedIn and also my InfoWorld blog as a kind of a poor man's focus group. And so I'll come up with topics and I say, well, this is kind of a unique topic. No one's talking about it. And some things will resonate, some things won't. And I hit something that resonates, suddenly I'll focus on that on my other channel, certainly putting out more articles on LinkedIn and more YouTube videos as well, which are harder to produce than writing, you know, a blog for uh 10 minutes a week, which is what I do for InfoWorld. I've been doing that for the last 20 years. Um, and it's really looking at what the sensitive spots are in the marketplace and then focusing on that. With me, it was repatriation. In other words, when I started to talk about repatriation, those things were hit like a hundred times more than anything else. And I thought that was going to be something that no one wanted to hear about, because in essence, it's kind of a bummer. You know, it's a bummer. We have to basically move everything back to where we found it, which means you have to go to the board of directors and say, oopsie, we got to put everything back on the systems we had. Uh, it's not necessarily going like that. But the thing is, people, no one was talking about it. And that's because, you know, I think the larger narrative out there was moving everything to the cloud, and cloud's good and always going to be good and it's always gonna be cheaper, where that's not the case. And I found that out as a cloud architect for many years. And so that was one thing and the ability to move into some other stuff, some of the contrarian stuff in the agentix space, looking at the downsides of it, the use cases of many of the topics that we saw, those things are hit like crazy. Um, they love the fact that they're getting they're getting contradicting evidence, and some of them are being pushed out by the uh uh the narratives are being pushed out by the big tech marketers out there. And also the ability to kind of call it the silliness of the market. And I just recently called out in a YouTube video the silliness around the whole AI first enterprise that everybody keeps saying, big mantra. All the cloud, all the all the consulting companies, including Deloitte, are using that over and over again. I'm saying that's the most dangerous phrase I've ever heard in my life because we had the AI, we had the cloud first enterprise 15 years ago. How did that go for you? Huh? Okay, well, same thing's gonna happen here, but guess what? It's 10 to 20 times as much damage that's gonna be done. So stop saying that. It it doesn't help anybody and it makes you look silly. And actually, I did some polls out on LinkedIn, you may have saw it. Where the silliness is there, it's proven. I mean, 80% of the people just think it's marketing dribble. And I think that hopefully the tech providers are seeing that and becoming a little better at producing the message.

SPEAKER_00 30:53

I love that. Yeah, taking an edgy, controversial take uh on issues that are controversial and important can really get a lot of attention. I love the LinkedIn polls you do, a great way dynamic on LinkedIn that that's unique for audience engagement. And I I I follow all the channels. So where where can people meet you in person? I think you'll be at Dell uh Tech World. Uh, you're you're get you get around.

SPEAKER_01 31:18

Yeah, I get disinvited for more conferences than I get invited to. So that's an easy, easy, easy thing to do. Yeah, I'm at Dell Tech World. Everything they didn't cancel my invitation this week. At least I haven't looked seen in the mail. Uh, I should be at reInvent. Um, and uh and just some uh, you know, anytime they have an analyst participation thing, I'm always happy to show up and learn. Um, but I can be found. Follow me on LinkedIn. You'll see, you know, where I am every day. And I I put all my video content there and all my blogs and posts and the inforal content. That's all aggregated to that. And uh, you know, come see me. And so I always enjoy hearing about case studies and hearing about what people are doing, how they're using the technology. It's fascinating to me. I I just never get sick of hearing those stories.

SPEAKER_00 31:59

Love it. Well, I like you know what you do, and I love how accessible you are and open to doing shows like this. So thanks, thanks for joining, David.

SPEAKER_01 32:06

Thank you for the invite.

SPEAKER_00 32:08

And thanks everyone for listening, watching, sharing this episode. It's gonna be a quite a blockbuster, I think. And be sure to check out our TV show, techimpact.tv, now Bluebird Television and Fox Business Monthly. Thanks, everyone. Thanks, David. Thank you.