As AI is reshaping how marketers create and deliver digital experiences, how do brands ensure that automation doesn’t strip away authenticity? Marketers are relying more on AI-powered tools, but can AI truly be brand-savvy and understand the nuances of a company’s voice and identity?
Joining us today is Dave O’Flanagan, CEO of Sitecore, a global leader in digital experience software that powers the websites and digital experiences of some of the world’s biggest brands.
And it’s always exciting when a platform we rely on unveils a few new and helpful features. Well, on Wednesday Sitecore announced over 250 new innovations for its platform, including AI-driven tools that help brands create, manage, and optimize their digital experiences. Today, we’re going to explore how AI is changing the game for marketers, content creators, and digital teams.
About Dave O’Flanagan
Dave O’Flanagan is CEO at Sitecore. He is a successful product leader and entrepreneur with 20 years’ experience building enterprise products in multiple industries including financial services, telecom and travel. Most recently he was CEO and Co-Founder of Boxever, before it was acquired by Sitecore, where he created a market-leading CDP and personalization platform that enabled global brands to transform their customer engagement using data and AI. Prior to founding Boxever, he led R&D at an airline e-commerce company delivering retail and merchandising solutions to some of the world’s leading airlines. Dave holds a BA in Mathematics and MSc in Computer Science from Trinity College Dublin, Ireland and is passionate about building high-performing teams that create products that delight customers.
Resources
Press release: Sitecore Supercharges Intelligent Digital Experience Platform and Content Management System for Marketers
Sitecore: https://www.sitecore.com
Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstrom
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Transcript
Note: This was AI-generated and only lightly edited
Greg Kihlstrom:
As AI is reshaping how marketers create and deliver digital experiences, how do brands ensure that automation doesn’t strip away authenticity and the nuances of a company’s voice and identity? Also, it’s always exciting when a platform we rely on unveils even a few new and helpful features. Well, on Wednesday, Sitecore announced over 250 new innovations for its platform, including AI-driven tools that help brands create, manage, and optimize their digital experiences. Joining us today is Dave O’Flanagan, CEO of Sitecore, a global leader in digital experience software that powers the websites and digital experiences of some of the world’s biggest brands. Today, we’re going to explore how AI is changing the game for marketers, content creators, and digital teams. Dave, welcome to the show. Thanks for having me, Greg. Really, really great to be here. Before we dive in, why don’t you start by telling us a little bit about your background and your journey to becoming CEO of Sitecore? Yeah, great.
Dave O’Flanagan: Well, so my name is Dave O’Flanagan. I’m the CEO of Sitecore. I’m coming up on my one year anniversary in a few weeks time. I’m a math stats guy. That’s where I came from. I spent the early part of my career coding. I was part of a startup in the telco space that I did in 2007. I started building my own company, again, another startup in 2011, a company called Boxhour. We provided enterprise CDP and personalization capabilities to large organizations globally. And Sitecore acquired my business in 2021, where we became, well, I joined as chief product officer for three years before taking this role as CEO. And during that, during that period, I was working on the integration of a couple of key acquisitions to accelerate Psycore’s path to the cloud and creating what we now know as our Intelligent DXP, which is our composable cloud native solution anchored on our next-gen CMS, but with world-class capabilities like personalization, CDP, search, and digital asset management, all fully in a fully integrated suite that allows customers to really deliver a world class digital experience to their end consumers.
Greg Kihlstrom: Great, great, love it. Well, yeah, let’s dive in here and we’re going to talk about a few things here. I wanted to start with this idea of the brand savvy AI. And so AI becoming more and more embedded in marketing workflows, but There’s always some concerns about how closely is it gonna adhere to brand guidelines and just voice and tone and all that stuff. How do you define brand savvy AI and why is it such a critical evolution for marketers?
Dave O’Flanagan: I think marketers and enterprises more generally are looking to vendors like psych or to be able to safely use AI. Why safely use AI? There’s a number of things that come into play. One is, is the AI going to have the guardrails so that it doesn’t hallucinate the content or outputs or results that it generates? of sufficient quality for the organization so that they can trust them and put them into production, so into a marketing context onto a website or into an email, and be confident doing that. And that’s one part of it. The second part of it is trust in terms of, is my data safe? As I, as an enterprise, start to leverage this capability, can I use my data safely and pass it to whatever system is using the AI so that I’ll know that my data isn’t being used to train the AI and my data isn’t being shared in some other pool of data for other purposes. And I think for Sitecore, when we’ve spent the last 18 months thinking deeply about how do we rethink market or workflows from an AI first perspective, obviously with the advent of chat GPT and all of this, it came came pretty quickly, but when we really sat down to think about it, we engaged a couple of key customers to help us understand how do they use technology like this? What do they need from technology like this? How do we go about building it? So when we talk about brand aware AI or brand savvy AI, it’s about, it’s been AI capability. Think of it as your brain at the center of your marketing stack that really understands your brand deeply. your tone of voice your content your copy your imagery how you want to present your your brand to the world but in addition it has all of the enterprise guardrails that a cio needs in terms of security data safety integrity around the day at how it’s being processed. so that an enterprise can safely use our technology in a way that they feel comfortable doing so. So we think about brand-aware AI, it’s the safe and secure brain at the heart of the MarTech stack that we’ve spent a number of years building that now powers all of these other new AI innovations that we’re bringing to market.
Greg Kihlstrom: And to that point, we’ve been talking, I feel like we’ve been talking about personalization for decades now and lots of focus on that, but to what you’re saying, the advent of generative AI and generative AI at scale with things like chat GPT, I think really opened people up to that possibility of personalization at scale, right? So can you talk a little bit about how does Sitecore approach that and, you know, you talked about the on-brand component of it, but the other part is, you know, we’ve got Omnichannel, we’ve got multiple audience segments, all that stuff. So, you know, how, how do you, how does Sitecore help those marketers reach their audiences at scale using AI?
Dave O’Flanagan: Yeah, I think, yeah, we have been talking about personalization at scale for decades, and I’ve been doing it for decades, I’m ashamed to admit, but I do think that, here’s the thing, there’s always been AI in personalization, right? So the AI we talk about today is all LLM-based and generative AI, but we’ve been, Boxever, my company that’s now Sitecore Personalize, we had multi-armed bandit and a whole range of different AI capabilities that allowed you to auto-optimize your personalization strategy many, many years ago. These are established techniques and algorithms that can be embedded in the organization in a safe and predictable way. And they’re just part of the feature set that we’ve had in our technology stack for many years. The thing that has changed and the thing that I saw firsthand working with large organizations like Emirates Airlines or Qatar Airways or big, big organizations globally is one of the limiting factors in terms of being able to deliver a personalization at scale is being able to create the sheer number of variants and quantity of personalized experiences. It requires content. It requires a whole bunch of analytics. It requires people to be able to manage all of that. And that was always a fundamental limiting factor. And the expense of creating more content when you needed to work with an agency to create the content or manage many, many parallel personalizations or A-B tests together in one go required sophisticated analytics and insights. All of these things required a lot more people and a lot more investment to be able to do it at scale. I would argue that the technology has been in place to do one-to-one personalization or hyper-personalization at scale for quite a while, but the limiting factors have been organizational, limiting factors have been cost, limiting factors have been operationalizing that in a way that makes sense for an organization. I think with what we’re seeing now with the advent of generative AI, I can create infinite variants of my personalized experience. I can create different copy. I can create different localized copy. I can create specific copy for specific market segments and not just broad segments like silver haired surfers, people over 50 or 60, but actually very targeted micro segments because with generative AI, I can start to generate content that will resonate and connect with them. I feel we’re now entering the golden age of personalization where the promise of being truly able to deliver a personalized experience is no longer limited by the organizational’s ability to deliver generative AI can absolutely cover the gaps and fill in the gaps so that we can deliver on that promise. And so that’s been something I’ve been very passionate about here in Sidecore as we start to embed this new generative AI capabilities deeply within our organization.
Greg Kihlstrom: Yeah, yeah. I’m glad you brought that. That’s what I’ve been most excited about, too, with generative AI, just because, again, to your point, we’ve had the technology to do it. But yeah, what I run into, I work a lot on the operations side of in large organizations. And yeah, they hit a wall. They hit a wall when their team just can’t churn out enough content. So yeah, generative AI really, really helps that. The other part of this is we want brand consistency and we want it at scale, but we also want to learn from what works and what doesn’t. And so it’s not necessarily contrary to to consistency, but, you know, how do you balance that? And, you know, how should marketers think about AI that learns over time and yet remains brand consistent and all that stuff? You know, how, how does Sitecore approach that?
Dave O’Flanagan: There was an interesting thing with an aha moment I had early on in kind of, it was in GPT-2 and I was starting to see some of these new, these new innovations emerge. And, you know, we were getting really excited about it in Sitecore. It was clear to me that that search or personalization was going to become far more compelling because. Historically, the way I would do a personalized recommendation would be, I would gather a first party data on the website. I would gain some intent or trying to mine some intent about what a consumer or user was there to, to, to find or what they were looking for. And then I would leverage that data to be able to, you know, recommend products or services or content, depending on. the purpose of the site. Sometimes I would be able to pull in some third-party data from a DMP, but that world, we’ve kind of moved past that pretty quickly. But now it’s really interesting because as I come to the website, I’m going to a site that sells sneakers, You know, I can say I’m a, I’m a, I’m a dad of a certain, of a certain vintage that has certain interests. And because the LLM has so much intrinsic knowledge about the internet, it can start to make really, really precise recommendations about what I’m interested in and then match that to the intent and then match that to the product catalog. So it really enriches the ability. for a brand to offer far more contextualized, personalized recommendations. If you think about, I’m interested in… I run 5K three, four times a week. I need a new pair of runners. I might go talk to Chachi, BT, or Claude about that and get some recommendations about it. It doesn’t need to know much more about me than what I’ve shared explicitly. So I’ve actively given the data in a value exchange with the LLM. But if you take that information and then apply that to what I’ve been browsing on an e-commerce site and align that or filter that based on what’s available on the e-commerce site, then you get to this really, really powerful recommendation. that’s aware of the inventory, that’s aware of my behavior, but it’s also aware of people like me that exist on the broader internet that is encoded deeply in the LLM. And so when I think about the opportunities to do personalization, I think having this, you know, a distillation of the internet available as the first step to work out what I might want is a really, really compelling new innovation in this space.
Greg Kihlstrom: And speaking of some of the newer things, certainly AI has been talked about quite a bit over the last couple of years, but agentic AI is being talked about quite a bit over the last few months. Can you talk a little bit about some of the agentic workflows in Sitecore’s AI enhancements? And maybe for those a little less familiar, break down a little bit what it means and how it’s going to help marketers.
Dave O’Flanagan: Yeah, it’s a, it’s a, it’s a good question. Here, here’s the thing, right? I believe that work is going to be radically different. It’s going to look radically different in, in two years, three or five years time. I think that the work we do today, some of the busy work, much of the busy work we do today will be, will be easily automated and taken off our hands and we will be doing different work. in the future. I can’t say for certain what we’re going to do, but I can say that our work, our day-to-day work is going to look different. Whether that’s how we write code, whether that’s how we do marketing, whether it’s how we do sales, whether it’s how we do finance and legal, everything is going to be dramatically impacted and enhanced by the introduction of these new capabilities. And so we think about agentic workflows in Sitecore. I talked at the start about, we spent a lot of time a couple of years ago, really rethinking marketing workflows from an AI first perspective. So what is the work that marketers need to do? How do they need to do it? It’s not that a marketer needs to go into the CMS and edit a page and save a page. That’s not really what happens. In the real world, a marketer works with a team. They need to find content for that page. They might have a brief that they want to do around launching a new page. They might have some copy and creative that would be briefed to the agency. All of that goes through an approval process. And that approval process then ultimately results in it getting published on the website or potentially in other channels. So there’s a Firstly, marketing is a team sport. And secondly, there’s a whole bunch of things that need to happen in advance of what seems like quite a simple task, which is I need to update my webpage or launch a new, I need to launch a new webpage. And so when we think about the workflow that sits on top of that, that coordination layer is typically manual today. So as I’ve outlined, the marketer needs to, is being tasked with launching. We’ve got a new campaign we need to launch urgently tomorrow. So the marketer is being tasked with going to brief the agency quickly to get content and copy and put it through the approval chains and ultimately get that through. But there’s many, many people involved in that. It could be the agency. It could be some internal development. It could be some localization resources because we need to publish it for different geos or countries. We need to push it through some accessibility validation. There’s a whole bunch of things that need to happen before an enterprise can confidently publish a webpage. Today, that’s largely, we’re coordinating things between people and stakeholders to make that happen. So we introduced this workflow layer to allow us to coordinate that work. And we want marketers to start their day in Sitecore, like a salesperson would start their day in Salesforce or a developer. in JIRA. And I think that going there with their lists of tasks and things that other people are waiting for, and things they have to do immediately to kind of move things forward so that we as a team can achieve the goals we want to achieve, I think is an important new innovation we’ve introduced, the Sitecore DXP. But to kind of answer your question about what does that mean in an AI world, some of those tasks today could already be automated. So for example, if I talk, if I think about localization, I want to launch a landing page. I’ve got my creative, I’ve got my copy. I need it to localize it. I need to localize it for French and German before I launch in addition to my English speaking countries. In that workflow, as things move through, there’s a point in that workflow where historically I might’ve emailed that to a localization agency. They’d come back with my localized content and I’d add that to the system and it would continue. With Sitecore, we can introduce agents in the workflow that allow us to do that localization automatically. So it just passes through the workflow, the agent picks it up, it localizes it. and passes it on. I think it’s a really important step towards the future in that I believe we need humans in the loop at the moment to make sure that the outputs of the agents in the agentic workflow are of sufficient quality that a brand feels comfortable that they can use them and leverage them and deliver them to their end consumers. And so we think about the workflow that we created, we can coordinate and orchestrate work for across marketing teams and people today. We have introduced the ability to orchestrate work between people and agents. I would call that hybrid agentic workflow, but it’s very important to have humans in the loop, given we know that AI still has propensity to hallucinate. Some of the outputs aren’t quite at the quality they need to be, albeit they’re very, very good today. But very, very soon, I think as we become more confident and the tools become more capable, we’re going to see more and more of those tasks in that workflow become automated. And ultimately, I think that many of these workflows can become fully agentic and fully automated over time. And so, Sycore’s view, kind of going back to right to the start that I I shared with you is that we want enterprises to be able to safely access this technology and introduce it into their organization in a staged and safe way. And so we think about our agentic workflow capability. This is key to that promise, which is you’ll be able to introduce steps in your process that can be fulfilled and automated. And over time, as you become more comfortable with the quality of those outputs, you can start to dial up or dial down how much of a human in the loop you need so that you can get more efficient with those processes.
Greg Kihlstrom: Yeah, yeah. Well, and to your first point, the role of the marketer, to me, that type of workflow and that type of automation still lets marketers be marketers. It’s just some of the details of what they do are going to evolve over time. I mean, I use my own personal example of, you know, when I graduate to date myself a little bit, I guess, but like when I graduated college, I got a job as a webmaster, which was a job that didn’t exist when I started college. And now I don’t think it exists anymore. So, you know, it’s there, there will be new and, and hopefully more valuable work for marketers to be focused on and stuff like that over time. But yeah, I see a lot of potential there. And I think that kind of is to the point of this other concept from psych or which is the marketer first. CMS, right? So it’s whatever, I’m defining it myself, I guess, but I’d love your thoughts on whether this is true is it, you know, the marketers kind of at the center of this and, you know, their day to day tasks may evolve over time, but it’s less about maybe relying on on other teams as much or like, what is it? What does that mean to you?
Dave O’Flanagan: I think, yes, we talk about marketer for CMS. I think it’s really, I’ve shared with you that we’ve rethought the marketing workflows from an AI first perspective, but we’ve really rethought how marketers work with our technology from a marketer first perspective. And that means that you’ve got the tools and capabilities that they need to be fully autonomous. Typically, in a large, complex CMS or DXP deployment, there are points in the process that require intervention or assistance with IT resources or some technical resources in order to launch the campaign or get the page live. And this is typical in all of MarTech. We’ve certainly seen now that with the advent of these new AI capabilities, many of those technical tasks can be given over to the marketer to do themselves. I’ll give you the most obvious example, is being able to manipulate creative in the process so that they can launch a new webpage. If you think about, say 10 years ago, if you wanted to resize an image, uh, you’d have to download the image onto your local, onto your local desktop. And you’d find some, you’d find some desktop software to manipulate the image and then you’d take it and you push it back up. Like think about how much we can do with our thumb on the phone today, right? I can, I can erase backgrounds. I can take people out. I can resize, I can do, I can do so much with these new really, really powerful video editing capabilities that exist in my phone, right? And so when you think about a world where a marketer is trying to do more with the platform that they’re working in day to day, why do they have to? If they need to do the significant image manipulation, for example, why should they have to go to a designer who needs Adobe Photoshop to do some work and then bring it all the way back in to do that? That world is going away. I think, you know, designers are going to deliver different value. They’re not going to be doing this rudimentary busy work. And that’s just one example, or if a marketer needs to launch a new webpage with a fundamentally different structure and some complex animations and dynamics. Why can’t the marketer today will be able to just prompt for that? This is the type of page I need. Using our brand-aware AI, we’ll make sure that the page adheres to all of the brand guidelines and copy guidelines and everything else. And they’ll be able to create this new complex page without any IT or development assistance. That wasn’t possible, you know, two, three, four years ago. It is possible now with Sitecore’s Intelligent DXP.
Greg Kihlstrom: And so we’ve talked about personalization at scale. I also want to talk about testing at scale. I mean, sometimes that goes part and parcel with personalization. But can you talk a little bit about the ABN testing capabilities and how this helps marketers experiment faster and improve things more easily?
Dave O’Flanagan: I see testing and personalization as two sides of the same coin, right? Like all of us would have great ideas about what personalization, what personalized experience might resonate or might convert better. But in reality, until you put that test into production on live traffic with real people, you can’t, you can’t say for certain that anything will work. And so how we think about personalized, about testing is that they’re like your, your initial, there’s conversion rate optimization. So I’m trying to improve the conversion on your website, or I’m trying to validate that a personalized experience is actually resonating or converting with the customer. And so we think about doing that. experimentation. It’s about being able to create variance, for a marketer to be able to create variance in a very easy to use tool, drag, drop, point, click, launch the variance. And for the system to do the work, to analyze the data so that they can confidently believe that the output, is one statistical significant, but two meaningful for the business. So that as they put more tests into production, they can feel confident that the system is working on their behalf. Traditionally, A-B testing required, despite what many A-B testing vendors would say, required a significant amount of technical resources and quite a lot of organizational maturity to do it. So if you wanted to launch, you know, hundreds, if not thousands of concurrent A-B tests on a website, You’ve got to know that you have the traffic on the website. You got to know that you can be, you can, you can run these tests concurrently side by side on different pages and all of the, the more tests you run concurrently, the more complex and sophisticated the analytics required to be able to do that. And so all of these things, it was probably the unsaid thing about testing and that, you know, there’s lots of freemium tools out there where I can run an A-B test on my website. But in reality, you know, as you move from a simple test to something more multivariate test or something more complex, you know, you actually need quite a lot of technical capabilities in the organization to do it. And I’ve seen this time and time and time again, where customers procure A-B test tools, thinking they can just. at a marketer and allow them to set up tons and tons of A-B tests. That’s not the way the world works. But however, with generative AI, I think you can solve this problem because it allows the marketer to lean on an LLM that is grounded and customized, specifically to be able to identify tests that need to be able to run. identify segments of customers that you should target, identify business problems that you can optimize and deliver variance to you in a way that takes a lot of the load off the marketer. I think now, again, similar to what I was saying about personalization, there are now opportunities to be able to, for organizations to be able to safely launch A-B tests that they can believe in. It is interesting because I think when I talk about personalization and A-B testing, they both have historically suffered from the same challenge, which is, it’s kind of hard to do. Beyond the very basic A-B test or personalized to a geo or a very broad market segment, it kind of gets hard pretty quickly. For us, the focus of Sitecore’s generative AI investments in that area is really how do we take the load off the marketer and start proactively suggesting, you know what, we’ve seen a decline in conversion for this segment from these campaigns for this product. We think you should run an A-B test and see if you can validate and optimize the funnel. Here are your variants, click go, and we’ll start working on that together.” And that comes back to my human in the loop example, Greg. I think in the current scenario, we can introduce generative AI to really take the load off the marketer, but the marketer is still in the loop. I think as we become more confident and the technology becomes more credible, many of these things become much more automated. Yeah, yeah.
Greg Kihlstrom: So last topic I want to talk about is digital asset management. You know, another another key component, you touched a little bit on it with the image resizing example, but wanted to look at, you know, how is AI transforming digital asset management and what are some of the challenges that AI can help them solve?
Dave O’Flanagan: I think there’s two parts to digital asset management. One negative thing or concern I have about the internet more broadly is now with the ability to generate images of all sizes and all types with all people, your ability to trust imagery and content is becoming increasingly challenged. And so for a brand that wants to maintain a certain brand equity in the market and make sure their brand is represented effectively, specifically around assets and imagery, I think a digital asset management solution is becoming absolutely critical in an AI-first world. The way I see the dam in this world, if you think about a CDP or a customer database as being your single source of truth for the customer, I think the dam is the single source of truth for your assets and your imagery. And as you think about how are you going to leverage that capability to create derivatives of those assets or create new assets, you got to keep going back to your brand signed off assets that can be used then to as seeds for creation of new digital asset capability. So as we think about the dam in the future, I think it’s absolutely critical that brands maintain all of their assets in a unified place so that they can feed AI capabilities in a structured and safe way. In general, as I think about features that we’ve been adding to our DAM over the last while, visual search is a big one. Just search based on the contents of the video. Find similar images is a big one. We have grounded image tagging, which means that I want AI to tag all of my images based on what it understands the image is. I also have a very complex and sophisticated taxonomy that I’ve implemented enterprise-wide in terms of how I manage my images. I want the AI to be aware of that taxonomy so that it can tag them effectively. It’s not just sticking a couple of tags on it. It’s actually working through a hierarchy of data. and updating those tags and attributes so that all of the information is stored and cataloged correctly. And that’s going to be important as you think about accelerating AI capabilities, using generative AI to kind of use that information that’s stored in the DAM to be able to do more with it over time. So we’re hugely bullish on our DAM capabilities. Our DAM is Unilever. P&G, Chanel, Richemont, some of the largest global CPGs in the world are powered by Sitecore. And you may have seen, Greg, that we co-innovated to build Sitecore Stream, our AI capabilities with Nestle, actually. It was Nestle that came to us and said, We need to rethink how we do marketing operations in our organization. We believe there’s a huge opportunity with generative AI. We don’t quite know what it is. And so we spent a year and a half co-innovating with Nestle, building the first iteration of Sitecore Stream with them. And it was hugely beneficial to us. And obviously Nestle got a huge amount of value out of it as well, but they were great partners in that process. And that was mainly focused on the dam where I guess the initial use cases for generative AI, given it’s so content and image heavy, are immediately obvious.
Greg Kihlstrom: Yeah, yeah, no, definitely. The taxonomy thing alone, I wish I had that a few years ago myself on some of these very large projects, right? But no, that’s great. I know we didn’t have a chance to talk about everything, all the things unveiled, but if there’s one thing that we missed that you’d like to highlight here, we’d love to hear. What didn’t we touch on that listeners should check out?
Dave O’Flanagan: I think just in general, you know, we’ve introduced 250 new innovations across our intelligent DXP. We talked a little bit about Sitecore Stream, which we, which we released a number of months ago. We’ve continued to enhance and we’re releasing a whole bunch of new improvements on the 19th. But I think you should take away from this discussion that Sycore is innovating at pace. We are committed to delivering the best products in market. Our vision is pretty simple. We want to be recognized as the number one DXP in the market. We’re building some of the most innovative software in the market, and we’re leading the pack with applying AI in this specific space. So we’re certainly excited about the future. We’re excited to see what our customers do with this new release, and we’re busy planning for the next one.
Greg Kihlstrom: Love it. Love it. Well, Dave, thanks so much for joining today. One last question before we wrap up here. I like to ask everybody, what do you do to stay agile in your role and how do you find a way to do it consistently?
Dave O’Flanagan: So I’m a techie, and so one of the things I’m really passionate about is staying up to speed with current trends. We’ve talked a lot about AI, but I’ve got way too many subscriptions to all of the AI tools. And I spent my Christmas getting up to speed with Cursor, Windsurf, and Repl.it and some of the other tools. And so I think I drive some of my team crazy, my CTO, my CPO crazy, but I know that I’m really, really passionate. about staying current in this new world where things are moving so quickly. And so I see enormous opportunity. I love talking to CMOs and CDOs that they’re looking to us to see what we can do. And by staying a little bit closer to the technology, sometimes hands on keyboards and developing applications, I feel that I can be more credible in those conversations as I understand the technology at a much more fundamental level. My wife doesn’t appreciate the fact that I’m, I like it. I see it as fun. My wife sees it as work. So I’m always trying to balance my home life with that. But you know, I’m really, really passionate about technology. I’m really passionate about the impact technology can have on our customers and their customers’ lives. And it’s a real privilege to be here in Sycorps making that happen at the scale, at the global scale that we have.
