AI: A Generational Perspective

Eric Müller of Work & Co meets with “TBR Talks” host Patrick Heffernan to discuss security in the AI age, the importance of curiosity and creativity, and advice for the upcoming generation of talent from his perspective as a seasoned industry professional.

Eric Müller is an Associate Director of Product Engineering at Work & Co, part of Accenture Song. With over 20 years of experience spanning banking, social media, B2B, retail, fashion, and online gaming, he brings deep expertise in both engineering and digital security. Before joining Work & Co, Eric served as VP of Engineering and CISO at Presence, and held key roles at Wells Fargo, Charles Schwab, Razorfish, and Mekanism. He has led award-winning digital initiatives for major brands including Microsoft, Samsung, eBay, and DKNY. Eric is known for his empathetic leadership style and transparent communication, which foster resilient, high-performing teams that deliver without burnout. He also champions strong agency–client collaboration, involving partners early and often to build trust and create better outcomes. Outside of work, Eric is an amateur photographer, baking enthusiast, and passionate advocate for digital security. 

Episode highlights:

• The slow ROI of AI

• Compliance and security in the age of AI

• AI impact on developers

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Edited by Haley Demers

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Art by Amanda Hamilton Sy

AI: A Generational Perspective

TBR Talks Host Patrick Heffernan: Welcome to TBR Talks: Decoding Strategies and Ecosystems of the Globe’s Top Tech Firms, where we talk business model disruption in the broad technology ecosystem from management consultancies to systems integrators, hyperscalers to independent software vendors, telecom operators to network and infrastructure vendors, and chip manufacturers to value-added resellers. We’ll be answering some of the key intelligence questions we’ve heard from executives and business unit leaders among the leading professional IT services and telecom vendors. 

I’m Patrick Heffernan, Principal Analyst, and today we’ll be talking about AI and generational trends in technology with Eric Müller, Product Engineering Associate Director at Work & Co, part of Accenture Song. 

Photography and architecture to technology

All right, we’ll jump in. So, Eric, thank you very much for joining TBR Talks. Really appreciate it, and looking forward to this chat so much. Why don’t you just give us a sense, not only what you’re doing now, but your background. What brought you to the point that you are right now in your career?

Eric Müller, Product Engineering Associate Director at Work & Co: Yeah, absolutely. Thank you for having me, by the way. I’ve been doing this for a while, and my background actually was not in computers. I started off, well let me take a step back, you know, I did get involved with computers as a kid, as a teenager. My dad had built a computer that my mom was basically using as an overpowered word processor for her doctoral dissertation. And of course, I started playing with it and I guess we’re lucky I didn’t destroy her dissertation. And, you know, when I got to college, this was in the 80s. I wasn’t really sure what I wanted to do, I studied photography for a little bit, I studied architecture for a little bit. I ended up working at Wells Fargo Bank, but I fell back into technology, the love was there, I missed it. And the timing was, you know, I was very lucky. It was the late 80s, and the internet was sort of like this nascent thing. And by the early 1990s, of course, the web was blowing up. 

And so, while I was at Wells Fargo, I became a developer there, started doing some web work, started contracting and bouncing around between agencies. So, I was a consultant, I worked for companies like, you know, Charles Schwab, Wells Fargo, did a brief stint at Netscape. And, you know, along the way, I just kind of kept building up these development skills and really kind of fell in love with the agency space. I think the fact that I enjoyed photography and architecture earlier in my life, and I still do photography as my primary hobby, really kind of informed where I wanted to move with technology. So, I ended up at Razorfish for a while, Edelman for a little bit, and about 13 years ago landed at a company called Presence. So, I ended up being the Head of Technology and our CISO. What we did is we partnered with design companies to build out, you know, what they had been working on, their designs. I always like to say that we realize people’s dreams as a technologist. And so along the way, Presence was acquired by Work & Co, a great design firm, strategy, technology, product development, who was also ultimately acquired by Accenture, although we are still an independent brand. And that’s how I got to where I am today.

Being curious and continuing to take on new challenges

Patrick: It’s fascinating. So, you’ve had the opportunity to work in so many different organizations, different structures within the technology space. So, I think of an agency, I think of an Accenture, I think of a bank as being just organizationally, functionally so different. Was there a certain appeal to someplace like Razorfish where it was an agency?

Eric: Yeah, you know, it’s interesting. When I look back, there are two things. One is obviously the ability to be creative. And so, I’m building stuff out, but while I’m doing that, or my team is building this stuff out, we’re also working with the creative team, and so there’s a lot of back and forth, and we bring our understanding of user experience and design as technologists and as end users to those conversations, and I’ve always worked in places that appreciated that kind of feedback. And the other thing that I really like about agencies, and I do include a company like Accenture in that, is that we are exposed to different things all the time, right? So, I have an opportunity to work with, you know, over my career, I’ve worked with small startups, I’ve worked with Fortune 100 companies. I’ve worked on hardware, software, mobile experiences, and, you know, I might work on a project for a year or two and it’s wonderful because I’m learning about new technology. I’m learning about a new business. And I dive in very deep into that space. And so, it’s just this constant, it’s like I have a new job every couple of years, but I’m not changing my employer, right? And so, working in places that appreciate that and give me that space, it’s been just incredibly fulfilling.

Patrick: And I would say in all of our research, I think a lot of the folks I speak with who enjoy what they do and they’re still with the same company are often the ones that describe exactly what- have the same experience you had, which is every couple of years they bounce around to something new, something challenging. It’s like- it’s maybe the best way to keep the best talent is to continually give them something new to do and make them challenge themselves to do it well.

Eric: Yeah, and you know, all of the companies I’ve worked at, and I think, you know, I think about Presence and Work & Co in particular, my last, you know, two companies, they really encourage learning, right? I think companies that are successful recognize that no matter how experienced a person is, that there’s always something new to learn, and they encourage that exploration. I didn’t start off in security, as an example, but when I got the Presence, you know, I realized that we had a need with our clients to really understand the security space. And so, although I’d done a little bit of work with that when I was at Charles Schwab and at Razorfish, I really dove in deep at presence, became our CISO, we got our SOC 2 compliance, and then I started consulting with our clients to help them get their SOC 2s or their ISO 27001s. And then that’s been very helpful when AI became the thing, right? And I’m talking not, you know, not just classic machine learning or data analytics but, you know, LLMs that people are talking about now. There’s a lot to learn there, and being able to go into a new field or a new technology and have that curiosity, I think, has really benefited me.

Patrick: Yeah. And you bring not only the curiosity, but also the experience. I mean, you mentioned Netscape earlier, not a whole lot of people that are, you know, that are mid-career right now would remember that, ’cause, you know, I’ll confess, Eric, you and I are both older here, but I think that experience too is important to have grown up at the early ages of technology in this sense.

Eric: Yeah, absolutely, and I find it fascinating that people talk about, I’ll lean into the age thing. You know, people talk about digital natives, and I think people miss the fact that a lot of folks our age, we actually grew up, like we were the first generation to have video games. We were the first generations to start using computers at work and we had to dive in and understand it. It wasn’t like an iPhone or an iPad, we had to really understand the operating systems.

Patrick: Right, and had to understand the change that came with being able to adopt a technology. 

The slow ROI of AI

And actually, that’s a good segue into AI. I wanted to talk about AI a little bit, in part because sort of everybody talks about AI all the time now. It’s the biggest topic. But there’s a couple questions that sort of- that kind of come to mind, particularly knowing your background, knowing what you’re doing now, and especially your background on the agency and the consulting side. There has been a ton of investment in AI, and there’s lots of really cool stories about enterprises adopting this or that, you know, particular piece of AI, particular solution. And there’s a lot of revenue for consultancies, but there hasn’t been that much ROI for the enterprises. In your opinion, and again, this gets back to your experience, your long experience in technology. Is it surprising that there hasn’t been that return on investment right away with AI? Should we have expected it to be slow? Should we have expected faster adoption? I’m just curious, like you’re thinking around all the money that’s being poured in, not a lot of ROI coming out. Does that make sense? Or did we sort of, was the expectation that adoption would be faster and ROI would be quicker, was that just a missed expectation?

Eric: You know, it’s interesting because I, yeah, I’m not that surprised. I think that with any new technology, people need to figure out how to use it. And then- so that can take a little bit of time. I think it’s unfortunate that we are spending so much money on it. I don’t think we need all these companies dumping that much money into this space. And I think there’s some missed opportunities because of that. And I think that there are some really strong use cases that I’ve seen. I mean, full disclosure, I will use an LLM when I’m writing some scripts, right? I’m not a full-time programmer anymore, but I still want to automate some stuff. So, I’ll go ahead and I’ll open up an LLM, and I’ll use it to crank out some Python scripts. And I know some great developers who are using it as a very powerful tool that accelerates their process. I know some folks who use it, I think it can be a very powerful tool if you’re, I don’t know, having to do a little bit of writing. It can be a tool to kind of support that effort. I think the problem is, is that people, for some folks, they think of it as not a tool, but as a replacement, and I don’t think that will be successful in the long run. 

I think that, you know, creativity is a human endeavor, right? An LLM is not creative. It is derivative. It generates the synthetic content. I think that’s all powerful, I think that’s a useful tool, but true creativity, true intuition, that’s a human endeavor, and I don’t think that’s ever going to be replicated by a machine. And I think the idea that we can remove humans from this process is bound to fail. And so, I’m really bothered in this space because I feel like there’s some folks who feel like, you know, they’re on the hype train and they think these AI tools are gonna come along and if we’re not careful, we’re gonna get Skynet, we’re all gonna die, right? That’s not gonna happen. I don’t buy that for a second. I also, I’m really bummed out by people who sit down and say, these tools are worthless and you know, why are we bothering with them? I don’t think that’s true either. I think the middle ground is true, that they’re very powerful tools if they’re used properly and that’s all they are, they’re support. And we shouldn’t think of them as anything more than that.

Compliance and security in the age of AI

Patrick: Yeah, I love how you brought up creativity, because I think the two things that we look at when we say, okay, there will always need to be a human in the loop, to use a very overused phrase, but still it’s the two C’s: creativity and compliance. And I’m really interested in your thoughts on the compliance part of it, because when we think about how much AI can take over running a system, and now I’m thinking more agentic AI, but running within an enterprise and be able to remain compliant and be able to meet all the regulations. That’s all well and good, but at the end of the day, when something goes wrong and something always eventually does, you’re not going to sue the robot. You need to sue a human. You need to, you know, the legal action that comes in goes after a human being. So, with your experience in security, do you think that compliance is sort of always going to be certainly accelerated by and certainly assisted by agentic AI and AI broadly, but always going to have to have that human in the loop?

Eric: Yeah, absolutely. And it’s interesting, so my first pitch here is everyone should go and read the OWASP top 10 on AI. You know, that’s the Open Web Application Security Project, and they’ve always had this top 10, a list of security vulnerabilities for general web application development. And now they have one very focused on agentic AI, and so, I think it’s a wonderful place for people to look at. So, I think that AI tools, having said that, is both the cause and the cure for a lot of security problems. So, starting with secure space, I love, you know, the fact that we can use these tools and going beyond LLMs, right? Going back into classic machine learning, data analytics, sentiment analysis, all those kinds of things, right? They’re very, very powerful tools when you are, if you’re running a SOC as an example, right? And you have to deal with, you know, hundreds or thousands or tens of thousands or millions of potential alerts, right? Having an AI tool there looking for those patterns, those potential attacks against your space, it’s just amazing, right? It takes over or enhances human experience, right? So, it looks for these patterns, it looks for potential attacks, as an example, that can then be analyzed by a human, right? So, I think that’s an excellent example of how AI tools can be incredibly powerful support tools for us in the security space. 

On the other hand, I think that these AI tools, particularly the LLMs, have a lot of security vulnerabilities. So that’s the OWASP top 10. And like any other tool, we need to make sure they are secured. And I think, unfortunately, not enough companies, not enough people are thinking about the risks of, you know, as an example, giving an agent complete control over your local computer, right? 

Patrick: Right.

Eric: There is a massive risk there. What kind of data do you have on your computer? And do you know what that agent is truly doing? Is it exfiltrating data right now? You know, is it reading your emails? Is it pulling up your bank statements? And so, I think people need to be as skeptical of AI agents as they would be of a human, right? Would you ask a random person that you really haven’t vetted into your space and give them complete control over your GitHub, over your databases, the ability to deploy whatever they want into your AWS account? You wouldn’t do that with a human. Why would you do that with an agent? 

Patrick: Right, right. And that’s, I mean, that’s the whole, the trust factor that is just- every single time the hype cycle gears up into a new higher speed around AI, the trust factor goes in the other direction. People are just uncomfortable with exactly the way you just described it. Why would you hand over the keys to your IT environment, to an agent that you haven’t actually trusted, vetted, and ensure that it’s not going to do something harmful?

Eric: Yeah, absolutely. And again, it’s not like the tools should be ignored and they shouldn’t be used, far from it. It’s just we need to be very thoughtful about the way they’re being used.

Patrick: Yeah, yeah, totally agree. 

AI isn’t going to get rid of developers

I want to sort of take a step back and like you, again, I keep referring to how long you’ve been in the business, but I think it’s important because you’ve got that longevity, that longitudinal perspective. And I’m wondering if there’s been a change, a development in the technology space that you kind of expected that didn’t happen. I mean, flying cars is the one that everybody, you know, always taps into or mentions, but forget about flying cars for a minute, something more grounded, something that’s more like, maybe even just in the last year, things that haven’t developed the way you thought would happen, or maybe the opposite, like something like, okay, we’re a lot further along with this technology development than I thought we’d be in 2025.

Eric: That’s an interesting question. You know, a long time ago, I stopped making predictions. *laughs*

Patrick: *laughs*

Eric: That’s part of the problem. I, you know, I- gosh, I really don’t know. I mean, there’s so many of these, so many trends that have come and gone, right? I’m thinking about as long as I have been in this industry, there has always been this idea that we can get rid of developers, right? So, I’m thinking all the way back, remember when 4GL languages were kind of the thing that, you know, you could drag and drop components around and your application would work. And now “what do we need these developers for,” right? 

Patrick: Right.

Eric: It’s interesting. That is a trend that I have always been skeptical about. Maybe that’s the better way to describe it, I’ve always been skeptical of this idea that we can get rid of developers, that everything can be done through drag and drop or, you know, talking to an LLM, like vibe coding or whatever. 

Patrick: Right.

Eric: And so, I’m not surprised that people have not been able to eliminate the developers. I know I’m not answering your question, but that is one trend that I have been seeing for the last 30 years, is how do we get rid of technologists and it still hasn’t happened and I’m really skeptical that it’s ever going to happen.

Getting to the higher value tasks

Patrick: So, I think it’s really important the way you frame that because it’s easier to look at the things that didn’t happen that you thought they would or things that happened quicker than you thought they would. It’s a lot harder to think about all the different expectations and predictions that sort of have flatlined or have sort of not panned out despite all of the investment and effort that people have put into it. And, you know, I think about like, when we look at companies and they tell us that through automation, RPA, artificial intelligence, agentic AI, whatever, they’re going to have such productivity gains that their people are going to be able to do higher value tasks. I always ask the same thing, which is like, why aren’t those people doing those higher value tasks now? What is stopping you? Why are you not? And that has been a drumbeat for, I don’t know, a couple decades now, where the expectation is that the technology will allow for people to do higher value tasks. And yet, those higher value tasks remain elusive. And that’s not a, I mean, that’s not a trend so much as it’s just a constant that, curiously enough, has not been resolved. Maybe it will be. Maybe we’re on the cusp of that with agentic AI and all. We’ll see. We’ll see.

Eric: Well, I do think we are seeing a little bit of that. And in some ways, I think, you know, I’m being biased here from a technology standpoint, I think we have seen that over the years. In that, as we develop more higher-level languages, that it becomes easier in some ways for folks to kind of get their job done. They’re not worried about like memory management as the classic example, right? And so that allows them to focus more on functionality, and I think, what’s interesting to me with a lot of the agentic tools, particularly in the development space, is that you can offload a lot of the basic stuff, you know, setting frameworks, you know, maybe unit tests, you know, boilerplate code. You can offload that to these tools and then your developers can focus on the core of your business. Right. 

Patrick: Right.

Eric: So, I think that in a lot of ways, that’s kind of leaning into that where your developers- you’re getting more value out of your developers, not because they’re necessarily cranking more code. And I’m always bummed out when people sit down and say, you know, I forget who said this recently, but they’re like, I’m doing 10,000 lines of code a day, you know, using agentic AI. I’m like, whatever, who cares? What problems are you solving? What is your business doing? How is it growing? I don’t care about number of lines of code. I’m concerned about functionality. I’m concerned about user interfaces. I’m concerned about your core business. And if you’re offloading a ton of that boilerplate to the AI, now your developers are working on that higher level stuff. They’re focused on the core of your business, and they’re delivering that higher level value.

Patrick: And that gets exactly back to what you said at the very beginning, that you sort of were, I’m going to paraphrase this because I can’t remember exactly the way you said it, but something to the effect of you help people realize their technology dreams. And that’s- if you’re thinking about lines of code, you’re not thinking about dreams. If you’re not thinking- but if you are thinking about why is this good for the business, what’s the business value in bringing, then you’re actually beginning to realize what you’re trying to go after, right?

Eric: Right, right. I mean, it’s the classic line that developers use, which is the best line of code is the one you don’t write. And so, you know, focus- I’m going to repeat myself, but again, it’s like, offload the boilerplate, offload the drudge work, focus on the core business value, and you’re going to have a lot of, you’ll have a successful company, and you’re going to have a lot of happy technologists as well. They’re doing work that’s meaningful.

Patrick: Right, yeah, and that’s what we all want. 

Finding a passion outside of the workplace

A couple more questions, Eric, this has been really fantastic. I’ve enjoyed this conversation immensely. I do- I’m curious because you mentioned at the beginning that you studied architecture and photography and you still bring those perspectives with you to everything you’ve done in your career. Does that make you, have you ever thought sort of, all right, what would I be advising people in their, you know, early 20s or even late teens heading into college, what should they be studying if they want to have a career that’s similar to the one you’ve had? Or what should people study if they want to go into technology other than, of course, technology?

Eric: I’ve always felt, so obviously technology, but I’ve always felt that it’s important to have a passion outside of technology. You know, I’ve always hated the phrase, if you do something you love, you’ll never work a day in your life. And it’s like, no, that’s BS. The moment that you’re sitting down and your passion becomes the thing that you need to do to put food on the table and a roof over your head, you have a different relationship with it. Because you, you know, with a passion project, you can put it down for three months, who cares, right? You can’t do that with work. And so, I think it’s important to have something outside of your career that can re-energize you. Now, it can be related to technology, if you’re a technologist and you want to have a side project, do that. Absolutely do that. But you need to carve out the space for that. But it doesn’t have to be a side project in technology. You can be into photography. I’ve had friends who play an instrument. I know technologists who love to cook. And, you know, the interesting thing about all these things, particularly with cooking and baking is there’s still this geeky kind of component with it, right? 

Patrick: True. 

Eric: You know, guitar playing can have that, photography can have that. You can kind of see how these side creative passions still lean into, you know, mathematics or, you know, formulas or, you know, kind of doing things step by step. They’re very related and for me, photography, to make it very personal, that recharges my energy over the weekend. I go out, I take some pictures. I’m not writing code. I’m not thinking about technology per se, but I’m leaning into the stuff that made me fall in love with technology in the first place. So, I come back Monday morning, I’ve got the energy back. And so, I think for a junior developer, having that kind of weekend recharge tool or passion, I think is really, really important.

Patrick: Yeah, absolutely. I agree 100%. I’ve always believed you have to have a going to work life and a non-work life. You have to have those things that you love that are not what you’re doing every day at work. 

Change management for developers around agentic AI

I want to ask to bring it back to what you’re working on, speaking of work, what you’re working on right now. I’m just curious, to sort of frame up like what are, what’s something that you’re working on now with the company you’re with that sort of has, this might be a strange question, but kind of has you puzzled? And I mean that in a good way. Like it’s a thorny thing that you’re trying to figure out now. And I’ll give you an example. We’re looking at how AI is changing the labor pyramid within IT services companies and consultancies. So, like, how is AI going to change those 800,000 people and that pyramid? And we’re trying to figure out when AI changes the size of the average consulting team, maybe it just expands their capabilities and adds digital full-time employees, whatever. We thought we would see this change by now. We would see more obelisks and fewer pyramids, but we’re seeing the opposite. Companies are actually hiring. So, we’re sort of puzzled about why that’s happening. And I’m not asking you about that. I’m just saying, is there something you’re working on sort of day-to-day that has you kind of asking, why is this happening right now? What’s going on?

Eric: So, I can’t answer that. *laughs* This is probably one we’re gonna cut out, because for NDA reasons and all that, I just really don’t speak about what I’m doing right now.

Patrick: Oh yeah, all right, I understand. Yeah, that’s fine.

Eric: Yeah, looking at it, I can look at it from- I can speak philosophically around that. I think that it’s interesting to me from talking with folks in other companies, with some of my colleagues, that there’s this idea within technology that when we have a new technology that comes along in theory, people are going to lose their jobs, right? And we’ve seen that forever. You know, the classic is the, you know, the buggy whip manufacturer, right? 

Patrick: Yep.

Eric: And I think that in this space right now, from talking with other folks and from what I’ve read, you know, we’re learning that, you know, the dream was that, and I don’t think this is a good dream. Unfortunately, a lot of companies kind of felt like- here’s a great example. I had a friend who said that when all the agentic AI stuff came out, he’s talking to his board of directors and the board said, great, when can we fire all of our developers? Right. Like, there’s this idea that we can fire everyone and our profitability will go up and look at how smart we are. And a lot of companies did that. And then they learned, hey, hallucinations are never going to go away. Like, that’s how LLMs work. You need hallucinations, right? And LLMs can’t create something from scratch, right? They’re always derivative. And so, they kind of made those choices, they realized they made mistakes, and now they’re bringing people back. They need those senior folks back who understand their core business, who understand how to make these tools work. And that’s, I think, the adjustment that we’re seeing right now.

There’s also the cost, right? You know, the AI companies need to turn a profit, and they’re starting to change their price pressure. And so, companies are starting to sit down and look at it and go, you know, for the quality of the work that we’re getting, you know, do we keep dumping money into it? In some instances, absolutely, it makes sense. It’s a great tool that’s supporting them. In other instances, I think companies are kind of rethinking it. And I think we’re still in this space where folks are trying to figure out, one, for the AI companies, how do they turn a profit? And then I think, you know, how do they turn a profit and how do they price this at a level that is profitable? And then for the companies that are using those tools, it’s like, what is the proper use case for it? And what is the team that we need to surround to make it successful?

Patrick: Right, and that is the, well that’s the sweet spot for consultancies to talk about change management. But that is the biggest challenge, I think, going forward for enterprises is it’s not necessarily the adoption of the technology, it’s the adoption within the enterprise, within the organization, what it’s actually going to mean to the structure of the organization and achieving those actual business outcomes from AI, not just the promise, the actual outcome.

Eric: Yeah.

Skills to pursue 

Patrick: Yeah. All right, so I lied. I have one last- I’ll call it a last, last question, but it really, it’s just because I’m really, given your background in photography and architecture and that you still do photography, I have to ask this. So, and we were talking about, you just mentioned, like, when can we get rid of all the developers? We talk about AI replacing people in jobs, that running fear. But we also talk about sort of the importance of skills, of mastering something so good that AI could never replace you, right? So, and just thinking like about skills like that, is there any skill, if you could say, all right, I’m taking three months off of work, I’m just going to perfect this particular skill, like playing, you know, you mentioned your friends have played guitar or maybe speak 4 languages or even turn yourself invisible. What’s a skill that you would say, okay, I’m going to spend 3 months and I’m going to master this?

Eric: Well, it depends, right? So, are we talking about reality of AI?

Patrick: No, there’s no reason to stay within the realm of reality. We can be creative here.

Eric: Well, I ask that because, I mean, if the dream is that AI can do everyone’s job. And if that is true, then there’s no skill you can pick up. If AI can replace us, if it truly is capable of replacing us, then there’s no skill you can pick up that’s going to make you valuable in the future. They’re just isn’t. But I don’t think that’s reality. I think that the cost alone, you know, the energy cost, the compute cost, all of that would be just too high to replace everyone’s job. And so, I think it’s going to be a little rough while people are trying to figure out how we use these tools, how we incorporate them, like I said, how the companies become profitable. And so, I would say, continue to follow your passion. right? If you love technology, continue to do technology. If you love medicine, keep doing medicine. If you want to do the trades, right? If you want to be an electrician or a plumber, continue to do that. And I think this will all shake out. It is going to, unfortunately, it’s going to be kind of difficult. And we’re kind of seeing that some jobs are harder to fill right now because the perception is that AI is taking it over.

Patrick: Right.

Eric: But I just don’t think that’s sustainable. I just don’t think in the long term the costs are going to justify basically replacing every human being in every company. It’s just not going to happen.

Final thoughts

Patrick: Yeah. So, listen, we’ve touched on so much stuff here. I know you said you don’t make predictions anymore, but I would like to predict that we can get together in six months and have a second round of this discussion, and we could probably expand on a lot of the different topics that you brought up and the different trends that we’re seeing, and we just- you just mentioned energy that’s definitely something I think is going to be a constraint as we go forward around AI. So, I think that would be, I’d love to have this conversation again sometime in the spring, Eric, and talk about what we see that’s different now, six months from now.

Eric: Yeah, absolutely. I’d love to see how absolutely wrong I was. *laughs*

Patrick: *laughs* I’ve been wrong so many times and it doesn’t bother me at all anymore. So, Eric, thank you so much for coming on. This has been really fantastic. I appreciate your time. Appreciate your insights.

Eric: My pleasure. Thank you very much.

Patrick: Next week I’ll be speaking with Dan Demers about managing strategic alliances and ecosystem partnerships. Don’t forget to send us your key intelligence questions on business strategy, ecosystems, and management consulting through the form in the show notes below. Visit tbri.com to learn how we help tech companies, large and small, answer these questions with the research, data, and analysis my guests bring to this conversation every week. 

Once again, I’m your host, Patrick Heffernan, Principal Analyst at TBR. Thanks for joining us and see you next week.

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