In this episode of The Main Scoop, Greg Lotko and Daniel Newman sit down with Barry Wordell, Head and Global GTM for Sales and Strategy at Microsoft, to discuss the importance of leveraging both cloud and mainframe strengths for an effective hybrid strategy.
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Transcript:
Greg Lotko: All right. Hey, folks. I’m Greg Lotko, and we’re here for the next episode of The Main Scoop. I’m joined by my esteemed colleague and cohost, Daniel Newman. We always have lively, vibrant conversations. How you doing today, Daniel?
Daniel Newman: Yeah. It’s good to be back, Greg. We’ve made it to 26 episodes. It’s taken us a minute, but this has been a lot of fun. The journey’s been continuous. Yeah, we do have a bit of a banter. But I think over time, if I’m being candid, it’s improved. I think we’ve found that right mix. We only pick a little bit. You look great today, Greg. All things considered, I’m doing really well. Excited to be on with you this morning, excited for the conversation we’re going to have.
Greg Lotko: Today, we’re here to talk about hybrid IT strategies. From data security, to AI, to transactional, and data, and beyond. Look, I think it’s a hybrid world. I know it’s a hybrid world. There’s all these different technologies out there. I’ve said it before, I don’t believe any one in isolation is the right answer for anything. I think many of the best solutions out there incorporate multiple technologies. They use them for their strengths, they time them into something else, and then the whole workload goes across the plane. Are we aligned with that, Daniel?
Daniel Newman: Yeah. Look, you and I are generally aligned on these things. Of course, we find those little bits of contention. I think that’s always fun. Hybrid IT and the way it’s described is fluid. We’ve seen an era where the recognition of hybrid cloud came, and then multi-cloud came. Of course, we’ve seen this while everybody’s going to move to technology A or B. And then, you see the graduated or gradual progress that we have with these things. I remember, what, it’s been almost 20 years, almost two decades of public cloud now.
Greg Lotko: Which is astounding because everybody’s still talking about it as, “Oh my God, this is new. It’s the leading edge.”
Daniel Newman: Yeah. It’s been a wild ride.
Greg Lotko: It’s maturing.
Daniel Newman: Yeah, but we’re still on the road. Of course, your business and the whole idea behind The Main Scoop is that there’s role to play for the mainframe. I think in the hybrid IT era, we’re seeing that different technology architectures, different parts of the stack, different security protocols, and different hardware implementations have remained important over many, many years. As hybrid IT really comes to fruition, it’s all about getting that data in order, getting all those different infrastructure deployments working together. It has moved fast, but it hasn’t moved all in one direction, why is why we’ve landed on this hybrid notion.
Greg Lotko: Right. 20 years ago, the discussion was that the cloud was the answer to everything. Then when hybrid came into the conversation, at first everybody said that meant different cloud technologies or different providers. Then they started using multi-cloud. But when you and I talk about hybrid, we talk about hybrid IT and technologies across platforms and across infrastructure. But let’s bring somebody in from part of the overall hybrid IT world. With us today is our guest, Barry Wordell. He’s head and global GTM for sales and strategy at Microsoft. Barry, welcome to the show. Can you tell us about your roles and responsibilities at Microsoft? Along with what you think are some of your key focus points around hybrid IT.
Barry Wordell: Sure. First, Greg, Daniel, thank you for having me on here today. It’s nice to spend this time with you. I’ve been looking forward to it. Appreciate the intro. As you said, I’m the global go-to-market leader at Microsoft for mainframe, mid-range, and Linux. It’s a privileged position I say, in the sense that I get to receive a ton of signals across the globe for all of our different business segments. And more importantly, all of our different industries. Those signals, as you know, at that scale are invaluable. What that does is it allows me and the people around me to learn, and to shape our strategy to support what we’re hearing from the field. If we have particular blockers, or there’s a thematic change in customer outcome expectations, et cetera, we’re shifting to support that. That is, again, a privileged position. On the topic of mainframe and the topic of hybrid, as you and Daniel opened with, I like to say mainframe and cloud. It’s the same thing as hybrid, but I think it’s a simple way to put it. And it resonates with many of our customers. I’ll share with you just my brief view of the history of the hyperscale, with respect to the mainframe.
Greg Lotko: Sure, sure. I’m curious, especially to hear you say that, when you talk about hybrid, to think about Microsoft and mainframe. I think for years, a lot of people outside the know, outside the people who are running the largest enterprises and their IT, thought it was either or, not and.
Barry Wordell: Yeah.
Greg Lotko: Even to the conversations that we’re getting into about data, it was about maybe moving it one place or the other. I’m curious to hear your thoughts, as you weave that in there, about what do you think about the role of data as it either moves across or is accessed between platforms?
Barry Wordell: Yeah. Well, one thing I want to just quickly touch on, in the whole cloud space. I think that what we’ve learned, with respect to mainframe, is that when the hyperscalers really started 10, 15 years ago, and we got underway, there was a massive amount of enthusiasm. We would have some really interesting, and frankly naïve conversations around mainframe. The cloud scalers, and I’m guilty of this as well, would come in, “Hey, we’re going to move all your workloads in the cloud. Easy-peasy, everything’s going to be great.” We’ve learned so much since then, and up until now, and every day that boy, did we lose credibility in those early conversations, and have we learned a lot, and have shifted that into a mainframe and cloud conversation. That’s really important.
The data front is probably one of the biggest values that we can get from or with the mainframe. You have the systems of record. You have the most important, sensitive, most valuable data in the world that is on and being transacted on these mainframes. On the other hand, you have all of the capabilities of the cloud that we know. Obviously, all of the data integrations, data security, data privacy, and the ability to then open up that data into all of the AI. We’re going through this massive gen AI moment. To not include the mainframe and the value of the data on the mainframe would be, frankly, silly. We would be missing a massive opportunity. Again, we believe really, really hard in that hybrid nature. It does start with the data, and integrating with and taking advantage of that data to provide those insights using the cloud AI platforms. That’s really what we’re trying to do.
Daniel Newman: Yeah. I’m glad you said that. I think, over the past four or five years, there was a bit of a sentiment shift among the largest public cloud providers. Where there was a bit of, like you said or suggested, Barry, just put everything in the public cloud. I think you started to see more of this modernization effort, different specialty business units, people like yourself, being put into these roles to make sure that these things worked together very fluidly. I think we’ve seen better results because of it. Another area, Barry, that I think has been in focus too, has been of course security.
Barry Wordell: Yeah.
Daniel Newman: Look, there’s been events every day. If you read deep enough into The Wall Street Journal, you’ll find an event that took place, ransomware attacks. You see different denial of service attacks. This is complicated, but it’s also been one of the specialties of mainframe for a long time, is keeping that vault. Keeping it locked up. Keeping transactions moving. Keeping the world moving. What are you seeing in terms of the challenges for enterprises to find that balance of that fluid, fast, agile cloud?
Barry Wordell: Yeah.
Daniel Newman: With the important, secure scale that exists inside the mainframe.
Barry Wordell: Yeah. To reiterate, security is top-of-mind. It is in everyone’s job description. It’s hyper-critical. We have to, of course, appreciate the incredible security technology product, know-how process that envelopes the mainframe. That’s a given. That’s on one side. Then on the other side, you have the cloud, the cloud scale, you have the cloud product. The whole security envelope that is there to support the cloud. Each in their own right are very powerful, very effective, very challenged, and being very much invested in. Very, very important. But you essentially have two different, if you will, groups. The important part, and frankly what becomes the challenge or the caution, is when they intersect. When we start opening up the mainframe, it’s data, it’s APIs, et cetera, that’s the place where we have to pay particularly close attention, and make sure that we’re not looking at this from a mainframe security perspective, a cloud security perspective, but a landscape perspective that’s protecting and supporting that integration. Think about the API calls, and think about all of the different data integration points. That’s where we need to bring our focus. It’s the power of two that supports that intersection point, and that’s where we have to be.
Greg Lotko: I totally agree. It drives me nuts when people are thinking they’re accessing data on the mainframe and they go, “Hey, we’re going to worry about the mainframe securing that.” When, even if you’re only going in and getting bits or elements of the data, you’re transporting it back and forth. You need to think about not necessarily just the platform it originated on or even the path, you need to think about the sensitivity of the data, and make sure that you’re protecting it all across its journey, wherever it’s going to be manifested. Hear, hear. Totally agree with you.
Barry Wordell: Yeah.
Daniel Newman: Yeah, it’s a substantial challenge. I think security’s always going to be cat-and-mouse. I think that part of the industry is going to be powered by the need for this ongoing security. Of course, it’s always going to be up to companies to figure out that workload distribution, what the best … But in the end, Greg, you and I have had this conversation 26 times in some different ways on this particular show, that there is a really important role for that secure transaction data.
I’m glad to see that companies, like Microsoft, have really bought into that partnership. Because I’m someone too, that always wants to be on the leading edge, Barry. We’re going to talk about AI here in a second. Look, I want to go fast, I want to go far. I want to do it at a break-neck pace. I wrote the book on fail forward, at least one of them. The point is, we do need to keep things going. I always tell my team, Barry, it’s all about doing two things at once. You got to be able to make the change you need to make, and keep things stable in the background. That’s a lot of what the mainframe’s role has been. But AI is going to change it again.
Greg Lotko: Before we go into AI, I don’t want anybody to miss that point about the cat-and-mouse. I immediately got the vision of Tom and Jerry. I know I’m dating myself, but people can go out there and Google.
Barry Wordell: My eight-year-old loves Looney Tunes.
Greg Lotko: But the thing was, Tom and Jerry, they never caught each other and they never did each other in. It was always oh my God, the next attack, attack surface area. There was always that next cartoon, or that next interaction, or their next venue. Really, across platforms, that’s how we have to be thinking about this. It’s not secure and done, or wait for a year from now and then bundle up the changes and everything. It is an ongoing chase. Not a reaction, but an offset, and a preparation, and an anticipation. It is ongoing. But go ahead, let’s get into AI. That’s your favorite topic.
Daniel Newman: It’s not my favorite, it’s just the only thing that anybody’s talking about anymore. No, it is pretty awesome.
Greg Lotko: Not us. We’ve talked about other things.
Daniel Newman: I’m back in New York today. But I was in New York several months ago, Barry, when you guys launched some of your new Copilot Plus features. I got to sit down with Satya and talk about it. The vision of what Microsoft has done, its early ambition, its partnership with OpenAI. Now it’s building a lot of things on its own, it’s implementing AI deeply into every part of its portfolio software. And of course, in the developer realm, inside of GitHub. We’ll talk about that in a minute. But just more broadly on the AI front, the interaction between Microsoft, the mainframe, and AI. What are you seeing?
Barry Wordell: Well, it’s an exciting area obviously. On one hand, I have this massive opportunity to expose the mainframe data, and take advantage of all of the AI process. I think that that’s fairly well established, in terms of how we do that and the value that it brings. We should all be pursuing that. Let me just take a second to say that in the years that I’ve been in the mainframe field, I have not seen so much interest and so many opportunities from customers and from partners as a result of the gen AI motion, within the realm of mainframe. There’s a certain population that sees gen AI as the silver bullet to solve any modernization or transformational challenges with the mainframe. Which is interesting, because it’s not a silver bullet. It’s an incredible augmentation in this very, very complex landscape.
But very specifically inside of the mainframe, gen AI is there to augment. We’re seeing it go from exploration to commercialization. It’s bringing value, it’s lowering cost, it’s lowering risk. But it’s not necessarily solving the entirety of the mainframe landscape complexity. When you think about the integrations, and the tooling, and security, all of those sorts of things. While there’s, again, an incredible and a growing opportunity to bring AI into the mainframe as a platform, there’s more to go there. Again, the value that we’re seeing today, right now in the mainframe world, is that data, it’s making use of the data. There’s different ways to look at gen AI and Copilot around the mainframe. Right now, that data extraction and the ability to bring AI to that is incredibly powerful.
Greg Lotko: We talked about AI there a little bit, and you started talking about Copilots relative to it. How do you see the role of the developer evolving across the hybrid IT nature? Is it, “I’m developing for the mainframe, I’m developing for the distributor or the cloud world?” How do you see that-
Daniel Newman: Is it developing for us?
Greg Lotko: Coming together or not?
Daniel Newman: Is it developing for us?
Barry Wordell: To me, it’s part of the hybrid conversation. The more that we offer a common user experience for legacy developers, and for developers in a more modern code base, the more that we can provide that common experience, the better off we are. Obviously, we have the tools and technology to do that. We can bring those tools to support that “legacy,” I’m using air quotes when I say legacy, and the more modern programmers.
But it’s really important. By providing that common toolset, not only are we supporting, say, the legacy programmers and the more modern programmers, but we’re also enabling, if you will, that bridge between the two. If you think about all of the organizations that are investing, incentivizing and investing in people to learn COBOL. Well, if you have that common toolset that people are accustomed to using, then that makes that conversation easier. Conversely, if you have let’s say a COBOL programmer who wants to reskill into a different, more modern language, then they can do so much more easily through a common toolset. By bringing these integrations together, we are effectively growing the hearts and minds of the developer community. If we don’t do that, then we lose innovation. Again, I view the, if you will, the legacy and that more modern developer whose thinking DevSecOps, and pipelines, et cetera, bringing that together, it’s going to drive innovation, and it’s going to win the hearts and minds of the developers.
Greg Lotko: I look at what we’re doing. It’s funny, you used all the words in there. I’m the worst at naming products or capabilities, but I feel like wow, we might have gotten this one right. Providing that common experience. Endeavor is the largest source code repository on mainframe. We now have, for a number of years, have Bridge for Git for Endeavor.
Barry Wordell: It’s incredibly popular. Incredibly popular. The whole ecosystem that supports Endeavor Bridge for Git is incredible. For a tactical example, if you’re using Endeavor Bridge for Git, and you’re using VS Code, you’re using Zowe plugins, you’re using various other plugins that are welcomed and have been used for decades by some developers, that is the commonality of the developer ecosystem that we’re trying to continue to support and evolve. That, again, is the hearts and minds.
Daniel Newman: Barry, if I’m hearing you right, when we talked about AI at the top here a few minutes back, you alluded to augment versus replace. I think that’s really an important call-out here, and what you guys are both saying, between the tools that you’re building is that you’re building an ecosystem where developers can thrive. They can move faster, they can take advantage of Copilots, they can take advantage of code repositories. But it also still requires the unique skill. I know both of your companies invest a lot in upskilling, and training, and creating capable and competent people. It sounds like you’ve found that right mix. Where Copilots can certainly accelerate, it can certainly add to some layers of automation. Of course, we’ve got generative code. But the whole, “Everything’s going to be coded in generative, and you’re never going to need to learn.” I think what I’m hearing here … Well, none of us can predict 20 years out. Over the next several years, skill meets tools is going to be exponential capability and accelerated innovation, but it still requires those skills.
Greg Lotko: We definitely see that all around us. Barry, I don’t know about you, but I know Daniel and I follow a bunch of auto racing, and we’re into cars. There’s been technologies that have been put in cars that, I don’t know that they make us a better driver, but they make us more effective on the street and the track. Whether it be faster around a track or safer on the street. But the reality is you put a professional or a skilled individual, two different individuals in the same car, and the person does make the difference. All this technology is augmenting. It’s not replacing. The differentiation is still those developers that are interacting with those tools and making the most of it, to deliver the capabilities for their companies.
Barry Wordell: Hence, the name Copilot.
Greg Lotko: Absolutely. Absolutely.
Barry Wordell: It’s augmentation. Yeah.
Daniel Newman: Yeah. It’s another area that Microsoft nailed, and a few others followed. I think the market and the world has definitely caught onto that trend line. Barry, as we wrap up, we have the data fabric of IT and hybrid architectures. You’ve certainly alluded to how much they’ve won out. AI is fast-approaching, and enabling developers. It sounds like it’s top of mind for both Broadcom Mainframe Software and Microsoft. Any other thoughts about how you see this space evolving? Is it going to keep moving quickly? It sounds to me like you buy in 100% that the mainframe has a long term role to play.
Barry Wordell: Oh, there’s no doubt. The degree of investment that is continuing in the mainframe landscape, particularly in the largest enterprises, is unquestionable. To go about our business, and not to support that integration, and not to support those customer outcomes would be short-sighted. There will definitely be a continued investment in that. And clearly, a massive investment that is going to continue in the AI space. How that continues to augment and support this journey that our mainframe customers are on is anyone’s guess. But we know it’s going to be a big part of it. We know we have to be there to continue to learn and understand how that augmentation is going to help with all of our mainframe customers.
Daniel Newman: Well, Barry, I want to thank you so much for joining Greg and I, and tying that together so nicely. We have a world where innovation is moving very, very quickly. It’s exciting. We need to be able to tie it together, those technologies that have driven enterprises for the past 30, 40, 50 years. Of course, we want to continue to add that special secret new sauce that’s creating all the enthusiasm and excitement in the marketplace. This conversation definitely intersected those two things. Barry, good luck with the continued growth of your business. Greg, always good to see you here on The Main Scoop. It’s episode 26. We’re not doing one every other week, but maybe we should because this is always fun. It’s great to see you, my friend.
Greg Lotko: Good seeing you, Daniel. Awesome having you on, Barry. Go ahead, Daniel. Take us home with your final thoughts.
Daniel Newman: Go ahead and hit that subscribe button. Join us, as part of our Main Scoop community. We appreciate everybody that joins us for each and every episode. Can’t wait to see you back here with us soon, but we got to go for now. See y’all later.
Author Information
Daniel is the CEO of The Futurum Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise.
From the leading edge of AI to global technology policy, Daniel makes the connections between business, people and tech that are required for companies to benefit most from their technology investments. Daniel is a top 5 globally ranked industry analyst and his ideas are regularly cited or shared in television appearances by CNBC, Bloomberg, Wall Street Journal and hundreds of other sites around the world.
A 7x Best-Selling Author including his most recent book “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor.
An MBA and Former Graduate Adjunct Faculty, Daniel is an Austin Texas transplant after 40 years in Chicago. His speaking takes him around the world each year as he shares his vision of the role technology will play in our future.
