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- [00:00]
Mike Linton
The CMO Confidential Podcast is a proud member of the I Hear Everything Podcast network. Looking to launch or scale your podcast, I Hear Everything delivers podcast production, growth and monetization solutions that transform your words into profit. Ready to give your brand a voice? Then visit iheareverything.com welcome to CMO Confidential,
- [00:25]
Podcast Announcer
the podcast that takes you inside the drama, decisions and choices that go with being the head of marketing. Hosted by 5 time CMO Mike Linton
- [00:36]
Mike Linton
typeface has completely changed the process of large campaign executions. Everyone knows AI can help with images and headlines, but the real impact is making the leap from a creative brief to a live, multichannel large campaign at speed. Typeface just announced its marketing orchestration engine, the first platform built to automate campaign workflows. You can roll out campaigns that used to take months in just a few hours. TypeFace uses Agentic AI to orchestrate the entire process, taking one campaign and instantly orchestrating it into thousands of personalized experiences across ads, email and video. Major brands like Asics and Post holdings are already transforming their marketing with Typeface. See how to move from brief to personalized campaigns in hours, not months at typeface, AI/cmo welcome marketers, advertisers and those who love them to Chief Marketing Officer Confidential. CMO Confidential is a program that takes you inside the drama, the decisions and the politics that go with being the head of marketing at any company in what is one of the most scrutinized jobs in the executive suite. I'm Mike Linton, the former Chief Marketing Officer of Best Buy, eBay, Farmers Insurance and Ancestry.com here today with my guest, Gene English. Today's topic, the AI Marketing Battle. A view from the front lines Now. Jean is currently the CMO of CoreWeave, a company that provides specialized AI cloud infrastructure, which we will talk about in a little bit. Previously, she served as the CMO of Jupyter Networks, Armis, Palo Alto Networks and NetApp, and also spent over 10 years in marketing at IBM, including Asia and the cloud business. She's also been at companies that have been acquired and ones that have done the acquiring. In short, if you are looking for directions at the intersection of B2B, AI and infrastructure, Jean is your person. This is her second time on the show. Welcome back, Jean.
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Gene English
Thank you, Mike. Glad to be here.
- [02:52]
Mike Linton
All right, let's start. Let's ground everybody in what Core Weave actually does because let's bring everybody up to speed.
- [03:02]
Gene English
Yeah, so Core Weave is a cloud built just for AI. So AI workloads, it's very different from a general Purpose cloud, which was mainly built for doing web applications many years ago. And so we built this cloud and it's based on how you think about a full stack of infrastructure tools to be able to build models, applications, and even more so now, different types of use cases, such as robotics, and different types of physical AI.
- [03:28]
Mike Linton
Hey, can you help me and our listeners the difference between what was a normal workload and an AI workload? What does that mean to someone that's not in the center of it?
- [03:41]
Gene English
Sure. So if you think of AI as needing to be trained. So models that are being built, and we call our customers the pioneers, but they're the model makers, these are labs that are creating models that everyone uses today, whether that's OpenAI and using ChatGPT. I'm assuming you have used ChatGPT, Mike? Yeah.
- [04:02]
Mike Linton
Oh, I'm a heavy user. I teach college. I'm using it like crazy.
- [04:08]
Gene English
If you're using it, most likely it's being run on Core Weave and most of you don't know that. But then there's also AI, which is called inference, which is really more about agentic AI. So how people use it, AI and applications and how they use it in different types of use cases and all types of enterprises around the world.
- [04:26]
Mike Linton
Okay, that was super helpful. Now, now that we've kind of grounded everybody and where you are in this game, give us your. You are in, in my mind, the catbird seat, because you can see just about everything going on and you have the background to actually understand all of it. Tell our listeners in your mind what's happening on the AI front writ large. You know, we have, we got frontier models, we got circular investing, the SaaS apocalypse, we got super bowl companies fighting on the super bowl ads. What's your take on, on AI and where is it? Give us, give us your view.
- [05:03]
Gene English
Well, AI is real. It is in the beginning. There's definitely, I think, debates in the market and the industry and the world. Is AI real? AI is real. People are seeing return. It is not a bubble. But the reality is that there are so many industries and companies that are using AI and they're using it to see impact that goes across the board. We work with so many companies today and so many different use cases of what we're seeing AI to be used for. And yes, there are a lot of frontier models that are massive and there's so much infrastructure that is needed to train these models. It's really something that most people have not seen before, but just the massive amount of, of needs of infrastructure of compute to have these models actually work. And they need it really fast. And so they need, like the pace of companies that are going to move as the fastest to get things built out and the infrastructure built out. They need the performance. And so especially with, like, GPUs, they're sensitive. And so you don't want to have a lot of, like, layers of abstraction between the model and the compute. And so you have to really simplify how you build up this infrastructure, which is what an AI cloud really does. And the ability for companies to now shift from just training to inference was really the big highlight of the show we just were at last week, which is Nvidia's GTC conference.
- [06:28]
Mike Linton
Yeah. So when, when you look at this, and I think everyone agrees it's going to be. This is what did. One of our guests called this the biggest prize in the history of capitalism. And, and everyone, like one of you know this, that AI will be like electricity in a couple of years, but how should. And we also had a venture capitalist on who agreed with all that, but also said there's so much change that's going to happen, a huge shakeout and there's probably a bubble in here and here's how it might pop, but it will recover. And then you see brands already fighting on the super bowl for consumer attention. Tell us, write the consumer and the B2B players into the story. People are fighting for consumers and they're fighting for B2B. Why they're spending all this money at the same time. Can you give us your perspective on all of that?
- [07:27]
Gene English
Well, I think creating a category is hard and a lot of time, it's defining first principles. And the categories that you're playing in right now in the AI space is ones that haven't been done before. And so, yeah, there's a lot of attention for people using models, models for using applications, and whether that's, you know, the labs themselves and what they're producing. And yes, there was a lot of attention in the super bowl and there was a lot of areas where, you know, there was some picking, happening, going, wait a minute, some things are changing. And we're going to highlight it here and we're going to make sure people know about it, which was fascinating. But I do think that creating a category is, is, you know, right now we are creating categories, we are making, we are making markets. Um, it is not something that has been before. And every time that you think about a model being refreshed, it getting to the next version, it's getting new Features and functionality. It is leapfrogging what you think is best now. And next thing you know, it's not like a year from now that something is better. It's like months, days, weeks. But yeah, it is changing the way people are perceiving what the applications are using today and how AI is going to shift that.
- [08:34]
Mike Linton
And then the consumer in this story, because there's all the B2B and then there's the actual who has the power and who has the product. But then there's almost like a little food fight that starts at the super bowl between, you know, anthropic and chat. How are the consumers playing in this story? And in a category where there's almost no switching costs for consumers, why are they so important? Or are they really.
- [09:02]
Gene English
They are important. I mean, we created an ad and we actually aired it during the Olympics. We debated Super Bowl Olympics, which one? And we said, I think we wanted to do something more pervasive at the Olympics than to do something just for the super bowl itself. But we made the ad more consumer facing. Right now. This. Where is AI going? Is it prototypes? Is it into production? Are you seeing the return? What are the use cases? And so we wanted to create an ad that actually that most people could understand. They could talk about all the ways in which you can use AI. And we said, you know, ready for anything, ready for AI. And so that was the premise of the ad. But, yeah, I think the consumer. Everyone's a consumer, whether you're a B2B or not. Everyone's.
- [09:49]
Mike Linton
Yes. I want to tear apart that B2B to B2C thing and talk about how much brands matter now and how that plays out depending on how the products come, like, and. And how you make the choices you make to say, all right, we're going to do a consumer ad on the Olympics versus, you know, and you may be doing all of this powering up, you know, 100 B2B conventions as well. Like, how do you decide where to go build the brand in a category like this?
- [10:21]
Gene English
We're very targeted. We're very precise. I mean, we are. I was asked this question before about, you know, why broadcast, you know, why do something during the Olympics? And we wanted to have a cultural moment. We wanted to get the attention we knew we wanted to bring through, but we did it based on markets. And we looked at, like, where our customers are, you know, who cares? Who will need us the most? Where should we show these ads? We are super targeted by city. When we look at a full surround of what that means we went heavy in airport advertising in San Francisco. Why? Because 25% of our base is in San Francisco in the Bay Area. So we said, let's go big there. We are targeted how we think about spending marketing dollars and we're seeing the return on investment based on that. And so we are continuing to refine and refine. But we do want to have bir of cultural moments where we get the attention of people because there's so many different people who are making decisions in this AI space because the buying power is so big, but the type of compute needs are so large that it can go all the way up to a boardroom conversation, a CEO conversation. Of course the CFO cares. And you start talking large deals and massive sizes of compute needed. You've got the CIO who cares about where's the data going, how expensive is it to move. You know, the CISO cares because is the cloud secure? So there's just a broad range. And then you've got the developers and the researchers and the platform engineers. So there's so many people now that are starting to think about AI and are looking at how they're going to use it inside their company and use it in their products.
- [11:50]
Mike Linton
And if I am an unknown brand in this space, especially now that it's been a couple years under our marketing belts, does that really hurt me now or because there's so much brand things. And then I want to talk about how you measure marketing progress. So take that as like three questions I rolled into two not very well phrased sentences.
- [12:15]
Gene English
They're great. I think now I've been so focused on with so much demand in the market, the clarity when I first got to Core weave was who we are and what we do. So are we clear about who we are? And we're an AI cloud. We're the number one AI cloud and that's been proven out. But different types of analysts who've gone through and done tests, the only platinum rating twice from semi analysis. When they go through and do a full benchmarking against all the clouds of AI and AI workloads, we are number one. So it was amazing to be able to declare that right out the gate. I was here for a month. I was like, amazing, this is good.
- [12:49]
Mike Linton
Wow, look what you did in a month. I have.
- [12:51]
Gene English
I didn't do it.
- [12:52]
Mike Linton
Oh, I'm giving you all the credit, Gene. And now I have a question though. Like, how do they measure, like, I'm number one in the cloud. By. By what are the variables? They Actually measure.
- [13:03]
Gene English
Oh, gosh, there's so many variables there. It's a very, very technical analysis, which I really love. It's not a surface level analysis. It goes deep into like workloads, into processing power and to performance, the performance of models. It's performance of systems, performance of compute. It's every layer that's inside of a cloud. And they went through and did all that analysis. They look at, they look at the actual security dimensions of it. They're looking at what is the compute as well as the powering process behind that. It is a very deep, deep, deep analysis. I love great products. I love the more technical the product and the more technical the analysis, the more I feel like it proves out
- [13:46]
Mike Linton
what you're telling me, and that makes a lot of sense, is the cloud is actually a measured thing based on performance. And as the performance gets better, the measures of what the cloud has to do also have to get better. Is that a fair way to think about it?
- [14:02]
Gene English
Absolutely. It has to have an outcome in terms of what it means for model performance, application performance. But that goes back to if you want to make sure that your infrastructure is working and if something happens during like a run of like a model and you're doing a training run and you don't and something stops, like, you don't want to have to go redo the run. So you want to know if something's happening, especially if it's in the infrastructure layer. And like, that's one of the things that core Weave does so well is like, give you really full visibility of exactly what's happening in the infrastructure so you can fix it really, really fast. So. So I always like to work for companies that have great technology. I'm like, that's my sweet spot. That's why I say the steak and the sizzle and I love doing the big sizzle and how we actually bring companies to life and become more human. But it has to have really good stuff Stake which is the great technology.
- [14:49]
Podcast Announcer
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- [15:57]
Mike Linton
I get if I'm a CIO or a CIO or on the board, how the cloud measures matter. If I'm a consumer, how do I evaluate the brand? Because my guess is most people listening to the show have not looked at a cloud. They look at number one cloud ranking, but they haven't looked at the variables. I mean, I surely haven't. How do consumers look at it and how is that different versus the B2B players?
- [16:25]
Gene English
Yeah, well, I would say, again, I think every B2B player is a consumer. Everyone is a consumer inside of a company that they're making massive decisions. Consumers tend to make those decisions in smaller groups, their families, but in B2B are making decisions in groups that are binary groups. And so everyone has to have some type of an appeal to the company. I think their brand is one of the most important things right now. I think building out a brand and being known in the market, I think having positive sentiment and having a share of voice in this market is critical. I think if you're not known and you're not being talked about, well, then the relevancy is going to be really small. But again, I don't think it can only be the brand by itself. I think this, like who we are, we defined ourselves as this essential cloud for AI. And at the same time, I want people to see the technology, the innovation that we're driving. Not every consumer will care about that. They won't necessarily care. But I do want people to say, oh, I've heard of core weave. And really, I think core weave right now is known for being an interesting stock or core weave. Like, I want to get a job early.
- [17:32]
Mike Linton
That.
- [17:33]
Gene English
So when we look at our search results, core weave stock, core weave jobs tend to like, top the charts. It really was when we put this brand campaign into market that we started to see core weave and core weave cloud start to take more dominance in our search results and become the top search results for us.
- [17:49]
Mike Linton
Hey, now, you guys have been in the news a huge amount.
- [17:53]
Gene English
Yes.
- [17:54]
Mike Linton
As has the whole category. You know, you went public, what was it, one year ago? And then there's the Nvidia collaboration. There has been some stock movements. There's a lot of stuff going on. How do you manage the brand through all that and manage the business through all that? And what are some lessons you can share with others? Because it's a roller coaster of excitement.
- [18:19]
Gene English
It is. And It's. So what's fascinating is that my one year anniversary was last week. I started, my first day was at the Nvidia GTC conference, which there couldn't have been a better way to start. Like, I met everybody, I got to meet Jensen, I got to meet our whole team, customers, partners. It was fascinating. And then two weeks after that we IPO'd. And so when I think about like a year from now, I actually was
- [18:47]
Mike Linton
probably one of the most interesting marketing starts in the history of marketing.
- [18:52]
Gene English
It was so fun. I met with the founder like three weeks before I joined. He goes, look, we got a 28 day challenge, we're going to IPO. And I was like, on it. Sounds good, let's do this. And so, challenge accepted. And so we needed to put a campaign into market. We needed to be clear and succinct in our roadshow. We wanted to make sure that we could make a big splash coming out. Because after you ipo, you know, you can't really have a lot of promotion in the market. And so you go through a quiet period. And so, yeah, so we went through and started analyzing, you know, what were the key messages? How are we iterating those through the IPO roadshow itself. There were, there wasn't really any content. And so we said, oh, what is this IPO road show? Let's break it into five pieces of content. One of those pieces happened to be Sam Altman from OpenAI that was speaking about the, what the work he's been doing with coreweave and the value and benefit he's been working with us as a company. I was like, great, it's our first customer reference. So here we go.
- [19:45]
Mike Linton
Good one to start with.
- [19:46]
Gene English
It's a great one to start with. I thought if you had to have one, this is the one. So it was good. And then we went big at the conference with Nvidia. Then we, yes, we IPO two weeks later and it has been a whirlwind ever since. And I think in this industry we made an acquisition of weights and biases, which is really around how do you build models and applications and make AI iterate faster and faster. And so that was a big opportunity for us to build out a full tool and tech stack around the cloud for that. Then we started doing other company acquisitions, whether it was for physical AI or if it was for notebook LLMs or if it was for reinforcement learning. So how do you continue to fill out capabilities in the cloud? But that was, you know, it's been a year of Just amazing speed and everything. It's like my, my focus has been like accomplish something every week and like how do we make accomplishments every step of the way?
- [20:43]
Mike Linton
So you look at the super bowl and you look at all this, all this stuff that you just talked about and tech does not always have or has not always had the greatest reputation for marketing. Is marketing becoming a much bigger thing now and is AI helping drive that marketing thing?
- [21:01]
Gene English
Well, you know, I think AI, I think marketing is a great function and use case for AI. You know, if you look at, and when I started at core, we had a team of 12 people. You know, usually my teams are hundreds and hundreds of people and like you know, going to a team of 12, the only way for us to scale was to use AI. You know, as companies start to think about how they're going to infuse AI into their own workflows and practices, there really is no way to do that other than to think about, you know, the uses of AI on the teams. You know, when I look at, you know, what is happening to change either the reputation of marketing or what can marketing do. I think that marketing can always, has to be one step, step ahead and to always be thinking about what's happening in the market with our clients. You know, what are we hearing in terms of trends and the ability for us to be a bigger impact on the business is for us to always stay with that type of speed.
- [21:56]
Mike Linton
Can you give us a really good example of one of the first use cases you applied when you came in to the company?
- [22:04]
Gene English
Yeah. So we did not have Personas. And so we looked at what are all the interactions we had with all of our prospects and customers. We had tens of thousands of records and we popped them into ChatGPT, did deep reasoning, started to understand like who were our buyers in different segments, whether they were labs or enterprises, you know, were they, you know, certain types of industries? Had we won the deal, have we lost the deal? And then we did all that synthesis of all that data, came out with five Personas. And I happened to be on a panel after someone at an ANA conference and he was from Evidence, which is a synthetic AI research company. And I said I want to partner. So like how do we partner? I have these five Personas, I don't know enough about them. We want to build them out with the team. And so we started to work with them to build out full fledged, full Personas. We ended up having 10 Personas in totality across the full AI cloud business we have. And we used synthetic AI to help us to accomplish that. And, you know, when I went back into our product management teams, into our sales teams, I was like, it's 80% right. I was like, there's 20% not right. 80% is a lot better than zero. And how did we get started? And everyone just was so embracing of, like, being able to take something that could get us 80% there and then to work through the rest of the 20 at the speed of which our business moves was incredible. So that was like, the. One of the very first things we did with.
- [23:33]
Mike Linton
Thank you. Hey, we just, we just. You are also. You're fabulous at your talking points. I just must say that we just aired a show with Richard Sanderson of Spencer Stewart where he was sharing a lot of their research on CMOs and AI. And one of the things he said is in the. In the big Fortune 500 companies, the belief is that AI has to show real traction by the end of 2026. And he also said the respondents called progress messy. Like, they were having, like, some of us going, well, some of us going or lumpy. When you look across your client base and their application of this, what's your take on that? And, you know, we also had the venture capitalists say, yeah, and people are going to start wanting ROI eventually here. And so how do you look at the balance of 20, 26 and parse those statements from your seat?
- [24:42]
Gene English
Yeah, well, I mean, AI infrastructure has been such a critical part of how many of these companies have been able to build scale at AI at the speed of where they want to be. And the competition is fierce. You said before, like, you know, people fighting and going back and forth in the super bowl is how you see it come to life. But, you know, the real battle of, like, who's got, like, the best AI for different applications and special use cases and even in broad use are the ones that are seeing it actually, like, come to life. And if you're looking at infrastructure as a strategic priority and how people are actually when they're doing fundraising or they're prioritizing capital investment, they know they have to have the access to infrastructure and the access to these GPUs in order for AI to go up speed of where they want to be. And so it is such a. It's such a tremendous opportunity to see companies who do prioritize and make it as part of a strategic investment as the ones who are getting ahead. And we see this, you know, time after time, the ones who think about it as like, oh, we may just, you Know, we don't want to spend like, you know, the money or, oh, we're worried about like, you know, what's going to be. They're not focused on more of like the TCO of what they need, then those are the ones that end up coming back to us and saying, hey, we went somewhere else. You know, we didn't get the performance we needed. And we're back because that performance is key. I mean, we just see it time and time again.
- [26:03]
Mike Linton
And so what you're saying, a tco, I think, is total cost of ownership.
- [26:06]
Gene English
Yes.
- [26:07]
Mike Linton
And I think what they're. They're pro. What you're probably saying is if you're not investing now, you might regret it later. But given the scale of the investment and the absence of a really great roadmap for what I should be doing, how do I know when I'm investing enough versus too much?
- [26:27]
Gene English
Well, there's different ways to get started. I mean, we just introduced some new consumption models for people that want to start to do things more on demand. And some companies, they just need. They know right now that they need a certain amount of compute. And what's fascinating is especially me being here, I haven't seen this before. Another company is the amount of companies that come back just months later to say they did not buy enough. And so the redoing of deals and the expansion of deals and the opportunity to go bigger with more computing power, I've never seen just the amount of companies coming back and needing more and more and more.
- [27:04]
Mike Linton
Gene, how do I know how much compute I need? Like, I know that IT folks will tell me if I ask, but if I say I have this much compute today and two years from now, I think I'm going to need to need this much compute. How do I wrap my mind around it if I'm not really close to the business? Like, how do we even think about how much compute I should have?
- [27:29]
Gene English
I don't know that anyone has a pure forecast. I mean, I do know that the companies who are buying and, you know, in large investments today have done it based on their models and applications. And they're looking at, like, what features and functions they need to build out. They look at the number of users, they're looking at the number of models that need to get trained. So they're all thinking through the aspects of, you know, where do they see the demand now and where do they see that their business is going in the future. But like I said, I think they estimated upfront, not of them get it right and they come back and they say, we thought it was going to be this amount, but nope, we need more. And so it's just, it's been like this, more, more, more. Which is really, for me, the first time that demand has not been an issue. You know, demand for a CMO is always a part of the job.
- [28:14]
Mike Linton
I mean, exactly.
- [28:16]
Gene English
You've got communications, you've got product, you got to make sure you've got the demand lined up to like, business needs to go. But yeah, the first time I've been so focused in this role on who we are and what we do, who we are as a company and what we do to build out the innovation and technology innovations that we're driving. So those product launches, it's like a drum beat. Every two weeks we have a product launch. And like, getting that out into market, making sure people know about it has been key. But yeah, demand has been insatiable.
- [28:42]
Mike Linton
I have a whole skit in my head if I asked my LLM if it needs more money and it said yes, that's good. The so what should our listeners be doing for the balance of this year and setting up for 2027 if they want to stay at the front of the marketing pack?
- [29:04]
Gene English
Yeah, I don't think that AI is just driven from the top down. AI is something that has to be driven from the bottom up. And we're seeing now that AI, yes, can be at the center of companies, but so much now is happening at the edges. Our company this week has actually launched a hackathon of which they have encouraged every single member of our company to be a part of. I'm proud to say that the marketing team has 32 projects in the hackathon and we only have less than 80 people. So we've got.
- [29:31]
Mike Linton
Give me a good example of a hackathon project.
- [29:34]
Gene English
Oh, I have some teams that are testing out how to build agents to do explainer videos. We have some teams that are building out how do you do better multi touch analysis for attribution to campaign results. We have some teams that are figuring out how do you write a solution brief, how do we build a knowledge base, how do we get solution briefs out faster? So those are just some examples. So sometimes it's content building, some it's analytics, some it's on, you know, what do you do for video production? And those are just a handful. But yeah, we've got 32 projects I'm excited to see. I'm a judge in the hackathon, so I'm looking forward to reviewing all the projects coming up.
- [30:10]
Mike Linton
Okay, excellent. Anything else? If you are looking in your crystal ball out into 2027 and you were telling anybody they should do this now because in 2027 if they don't do it now, they could be behind. Is there anything you would tell anybody they should absolutely be thinking about?
- [30:30]
Gene English
Well, I think a few years ago I said that to be employable you have to use AI. And I don't think that statement could be far less than true than what it is today. I think every single person must use and that goes from jobs and yes, development. If I think about marketing, just specifically, it's every function in marketing and I do think it's beyond just using ChatGPT. My focus over this year has been hiring the A team. So getting the very best talent. I actually interview every single person that joins our team and what I want to do is to take the A team and scale it. And the only way to scale it is to use AI. So I think for every CMO embracing the, the, the challenges and changes that come with AI, you know, is a lot of it is not the actual like building out of agents or the usage of AI tools. It's really the culture and mindset and I always want people.
- [31:27]
Mike Linton
Sanderson on the show, the one of the Spencer shows said one of the questions they are asking is how are you using AI in your personal life? Because that is allowing them to understand how much the person is actually thinking about it.
- [31:41]
Gene English
It. Yeah, I mean I use it every day. I feel like I asked AI how to like respond to my children. They asked me something to how to think about recipes. I mean every use case. I mean it's, it's a total usage. I even was using it back when Open AI first launched Chat GPT when I was doing some volunteer work for a nonprofit and they needed a fundraising campaign and so I was like, oh, I can help you. So you know, how do I start to put in the mission and the vision and like the outcomes we want and what is the theme? It's. And you know, and that was years ago and I just, I think that every CMO has to fully embrace it themselves in order to have their team embrace it. But it is a cultural and a mindset change as well.
- [32:21]
Mike Linton
So you heard it here first. Jean English says use AI to help manage your children.
- [32:29]
Gene English
Well, they're grown now. They're like 20 and 22. But I still.
- [32:34]
Mike Linton
Anyways. Which brings us to our traditional last question. Funniest story you can tell on the air and or practical Advice we haven't discussed yet. You can take one or both, but you must take at least one.
- [32:47]
Gene English
Okay, well, I'll, I'll always go with my mantra. Be bold, be kind. You know, I, I live by that every day. My teams know if I'm not pulling them back, they're not going far enough. And so we live boldly. We make, we make decisions, we make them fast, we make high quality, you know, conversations matter. But I always believe in being kind. I always think there's so many way to get to an answer and no one, there's not just one way to do it. So I think that's something I've embraced personally, something professionally. It's a mantra that I live by every day. So it's my piece of advice or something that I would pass on. Funny story. I used to DJ for fun, so that was always entertaining. I love hip hop music. I love to dance. Funny story. My friends and I were out and we went into a club and the DJ was up there. My friends were like, go up there. So I jumped up and he let me take over and start to mix some, some tunes. So it was great. Lots of fun.
- [33:42]
Mike Linton
Wow. All right, well, I think that's a great way to end the show. Thank you for joining us again, Gene. And thanks to everyone for listening to CMO Confidential. If you're enjoying the show, please like share and subscribe. New shows drop every Tuesday and you can find all of our more than 165 shows on Spotify, Apple and YouTube, which include Agency Economics in the Age of AI what your CIO wants to tell you but won't. Marketing at Meta the view from the eye of the storm. And a marketer turned technology exec talks about big data, mainframes and AI. And of course, you should also listen to Gene's first show. Hey, all you marketers, stay safe out there. This is Mike Linton signing off for CMO Confidential. Typeface is changing the way to think about brand marketing at scale. Their marketing orchestration engine is the first of its kind and built specifically for the enterprise. The orchestration engine uses shared brand intelligence designed to turn brand guidelines into personalized voice visuals and messaging delivered in a way that fits the context of your audience. It's how brands like Asics and Post holdings scale what works without sacrificing quality. Start orchestrating your brand at Typeface. AICMO.