Is AI the Future of Social Media Marketing? A Conversation with Cortex’s CEO, Brennan White

Yes, sir. Grew up in the Boston area as well, so haven’t moved too far. The town I grew up in is called Western Massachusetts. It’s like 15 miles directly west of Boston. A little sleepy town. Most people haven’t heard of it, but you might have driven through it on your way to Boston.

Yeah, huge sports fan. I mean, a Giants fan, but all the other teams as well. And my family is actually from New Orleans, so my kind of second-tier teams that I root for are like the Saints and things. So this season has actually been a phenomenal season for my family. The Pats are almost undefeated. The Saints are nine and two or ten and two. I forgot the outcome of the game yesterday, but yeah, they were both doing very well.

I have one sister. She’s seven and a half years older than me. She actually went to a completely different school—she almost graduated from high school in a different town, like basically the end of my elementary school. She goes off to college. We moved to Weston, so actually, we went to a different town. It’s almost like I was an only child in that town, at least. My Western friends don’t really know my sister too well.
Interestingly enough, but yeah, just two parents, one sister. Very small family, and that even includes my extended family. I’ve got one cousin, a couple aunts and uncles—not too much in terms of numbers in the family, but very, very cool family, mostly based in New Orleans, like I mentioned a moment ago.

Yeah, we got one actually coming up right at the end of this year, and they’re usually in New Orleans, which is nice. So we get away from the cold, we get some delicious food. We’re, you know, Cajun background, so that food is very delicious to us, and it’s all looking for an opportunity. You know, Boston’s not really known for the spicy food, so it’s a nice break.

You are welcome, sir. Let me know—that’s either we go in or Boston happy.

Yeah, I have, like, an incongruous background. I was a music major in college. A lot of my professional contacts don’t know I have that background. That’s usually surprising. I also played rugby for eight seasons, and was captain of a rugby team and played in England and Australia. So there’s a few of those. But nothing too crazy. Nothing like super wild.

Rugby’s violent, right?

It’s great. It’s funny. It kind of works, like golf—I guess golf also works. I don’t play golf, but you know, I was talking about how people bond over golf, and they have this, like, secret business network.
In my experience, there’s, like, a secret business rugby network that works really well, where you meet someone who played rugby. You know, maybe they’ve got a trophy in the corner of their office, or they’re, like, a ball leaning against the wall or something, and you connect over that. You end up being really good—yeah, really good—real relationship.

Because A, you know, you’ve got the connection, and B, I think rugby itself actually lends itself to good leadership if you played a leadership role in the team, because it’s like football and you’ve got plays and you’ve got to get 15 guys all doing the same thing, but it’s live. You know, it never stops—or almost never stops.
And so you don’t get— you know, you don’t have the benefit of football where it’s kind of from the same exact position. You’re gonna have to talk and communicate on the fly. And so I think it actually leads— breeds—good leadership and the ability to think on your feet and make stuff happen.

So I think there’s a lot of rugby players in positions that, you know, cool, cool roles throughout the business world that we kind of end up sniffing each other out one way or another.

Yeah, one of my best teammates over the years was a Jesuit guy in high school and played rugby there, and went on to actually be in the Super League, which was kind of, at the time, the best league the US has. Now we’ve got a major league, professional rugby league, that just started a couple years ago. But prior to that, he won the Super League as a super young guy and was a Jesuit guy. So I’m even familiar with that team.

You should have played in a club later.

I went to Vassar College, which is about an hour and a half north of New York City. So it’s in the Hudson Valley, just to the west of— matches, so not too far. Like three and a half, four hours from Boston.

Yeah, it’s— you know, you can just hop on the train as a college kid and be in the city in, like, an hour, hour and a half.
It’s pretty convenient for partying and, you know, seeing the museums and going out with your friends and all that good stuff.

But yeah, I actually played a ton of rugby there too, and so I spent, you know, almost every weekend on campus just training and playing games. So I didn’t really go to the city as much as the average kid there.
But yeah, yeah, it’s a really good school for a lot of things, as I mentioned earlier—music major. So they had a really great music department when I was there.

Well, yeah, people are always kind of thrown off by it, and in hindsight, it seems like an odd choice—even to me, ironically enough, being the guy who made the call.
But yeah, I mean, up in Weston, as I mentioned, they had one of the best public schools in the state, but it didn’t have a real music department. There were no music theory classes. You couldn’t really learn about music other than being in choir or band or something like that.

When I got to Vassar, one of my passions was music, but I was fully planning to be a biology major. I’d done really well on the AP Bio test and all that, and biology just came naturally to me.
But when I got to Vassar, I took some intro music theory courses and just thought, “Oh my gosh, there’s this whole language behind this thing that I really like.”

It appealed to both sides of me—I’ve got a creative side and a kind of mathy, nerdy side—and music is the meeting point of those two. It’s absolutely an art, but it’s also heavily rooted in numbers.
So to me, it just felt really right. I said, “You know what? I’m going to go from zero to sixty. I’m going to go from literally no experience to making this my major.”

The only thought I gave to a career afterwards was that I really wanted to compose for film. But by the time I was done with Vassar, I was already thinking about starting a business and that kind of stuff, and I never really looked back.

I’ve done a few little projects—I worked at an ad agency for a while—and occasionally there’d be a situation where we needed thirty seconds of music for the background of a video or something. So I got to flex my muscles once or twice, but not very…

Yeah, so I always wanted to be an entrepreneur because my dad had actually started an architecture firm, and it just kind of, like always, got preached to me that you don’t want to be trading time for dollars—you want to be doing your own thing.
And I was young and impressionable, so I took that to heart.

But right out of college, I didn’t have any money to start a company and, of course, no connections or anything like that. So I took on three jobs right out of school and just lived at home and saved money.
The main job was being a software sales guy for a tech company in Boston, and that was kind of my first exposure to tech.

And it actually was a Fast Company, so it was really early in the SaaS world, which was pretty good. Got some experience selling there. Turns out I was pretty good at it, so I made a decent amount of money.
But at night, I would bartend. On weekends, I was selling real estate. I was just trying to save as much money as I could so I could eventually hang my own shingle and do my own thing once I had the right opportunity.

Yeah, it’s funny because there was like an eight-year gap or so between those jobs and Cortex, where I founded a digital marketing agency. The sales there were actually quite different, but the sales skills I learned were probably some of the most valuable skills I have.

And then, of course, it helps with the first business, but that’s a very large sales cycle, high-relationship type business—whereas the SaaS business, Cortex even, is very analogous to what we did back then. Lots of people coming inbound, trying to get as much information as possible to make their decision as quickly and confidently as possible.

So a lot of the stuff we learned—like, I learned 12, 15 years ago—is now super relevant. Stuff you don’t really know at the time is going to end up being that relevant actually ends up being quite relevant. So it’s pretty cool how it all works out.

Yeah, especially on the sales front. Of course, I can’t speak to other jobs right out of college, but I can say that I think every job—almost every role, especially in corporate America—even if you’re not technically in sales, a sales role, especially an entry-level one, is super helpful for exactly what you were talking about.

Just getting used to talking to tons of people, quickly assessing their personality type, figuring out whether they want direct info or just to chat, and learning how to communicate with all kinds of people.
I think that’s a benefit, no matter where you are—even if you’re in ID or something else. Communication skills are huge.

And yeah, at the time, I had the same feeling as you. I was like, “This really sucks. I don’t want to do this very long.”
In fact, the impetus to start my agency—my first company—was the guy in the cubicle next to me. I was 23, he was 43, divorced, had alimony, the whole deal. Exact job.
And I said, “You know what? Twenty years from now, I could be this guy.”
And yeah, he did well, no knock on that. But I just knew I didn’t want that.
I was like, “I can’t do this for 20 more years—or even two more years—so I’ve got to figure this out.”

Then it would actually be Bob.

I can confirm—I don’t think anybody, even my co-founders, knows that guy’s name. So there’s no source. That was just pure clairvoyance, right there.

Yeah, the step between it—exactly. So the whole Bob thing was the push to start something, but the first real opportunity actually ended up being a digital marketing agency. It was called Pandemic Labs—still exists, and it’s actually crushing it right now. My co-founder was one of my best friends from middle school, back in Weston. We reconnected, and it turned out he’d had some experiences that really echoed mine. We were both class of ’05 in college, which, if you do the math, means we were part of that first wave of students on Facebook. He was at a different school than I was, but both of us were at schools that were part of that initial list—those 20 or so colleges that had access before the public. So we’d already had this experience of using social as users, and then as a couple of 23-, 24-year-olds, we started saying, “Hey, businesses are going to want to use this stuff.”

At the time, you were seeing people take early stabs at YouTube or Facebook—this was even before there were brand pages—or right around when Twitter launched. And companies were struggling to figure it all out. That’s when we realized, “They’re going to need someone young who actually understands this space to help them translate it.” That’s where the idea for the agency came from. Pandemic Labs was built to help businesses understand and use social. And as far as we can tell, we were the first social media marketing agency in the U.S. We were definitely early—started in 2007—and honestly, the market didn’t really take off until 2009. But by then, we already had deals in place with brands like Puma and Dunkin’ Donuts, so we were kind of the only game in town when the demand really hit. That turned into a pretty booming business—creating content, running social ad campaigns, all of that.

And that’s actually what led to Cortex. Working with all these Fortune 500 brands, globally, we kept seeing the same exact problem pop up. No matter if it was TV ads, online video, social content—if visuals were involved, everything was guesswork. Someone would make a piece of content they thought was cool, the CMO would sign off on it, and everyone would just hope the audience liked it. From the agency side, we were the ones on the hook if it didn’t perform. And even though Pandemic Labs was successful, it was really hard to guarantee results without knowing what would work. So the core idea for Cortex came out of that exact challenge.

We realized there was plenty of ad tech focused on the bottom of the funnel, but no one was helping at the top—where the content is created. Our question was, how do you predict the performance of a visual before you launch it? If you can do that, you can invest with confidence. You know how much budget to put behind something, what kind of photo shoot to plan, what visuals will actually land with your audience. Those were the questions we were asking over and over. And when things didn’t work, that’s usually where the failure came from. After you’ve had that happen 50 times, you finally go, “Okay, this is a pattern—can we actually solve this?”

Luckily, being in Boston, basically next door to MIT, we had access to a lot of really smart people. So we started asking around: does anyone know how to solve this problem? What tech should we be using? My co-founder and I weren’t technical—we were both business guys—but we quickly connected with a few machine learning folks who looked at what we were doing and said, “Yeah, this is exactly the kind of problem machine learning can solve.” And once we had that team, we were off to the races. That was about four, four and a half years ago.

I was gonna say—that’s the quote everyone uses, and you’re exactly right. But I think the conclusion people usually draw from it has traditionally been the wrong one. And that’s actually why we created Cortex.

The usual takeaway is, “Well, we’ve got to track things better,” which is true. We absolutely do need better tracking. But honestly, as an industry, we’re still embarrassingly bad at tracking certain aspects of marketing. Some of it has improved a lot, sure, but there’s still a long way to go.

The real insight from that quote should be this: if marketing is such a massive question mark from an investment standpoint—because that’s really what CMOs are dealing with, right? They’ve got $100 million to spend next year, and very little confidence in where to actually put it—the question we should be asking is: why is that the case?

And to us, the answer was clear. It’s because there’s this huge, undefined, opinion-driven, BS part in the middle of the process—creating the content.

If you really stop and look at it, marketing and advertising across every industry has this giant question mark right at the center. And our thinking was: if we can solve that piece—if we can remove the guesswork from content—then suddenly you’re operating with way more confidence across any channel. Because now you’re not guessing what a piece of content will do; you know.

So that’s what we did—we took a step back, looked at the problem that all these different companies and industries were facing, and realized, “This can’t just be us.” And that became the risk we decided to take.

You’re right—we’re kind of two for two on being too early. If I ever start something again, I’ll probably just wait a few years. Because being early is hard. But that said, both ventures have done pretty well, so I can’t complain too much.

Yeah, and especially because I think a lot of people are high-level thinkers—which I actually think is a good thing. They tend to believe humans are inherently creative, and since they haven’t seen a computer or software be creative, they assume creativity is something only we can do. And if that’s the case, then of course, there’s no way to measure or track it, right?

That kind of abstract thinking is useful, and I think in general, it’s a great way to approach the world. But in this case, with the way AI is evolving—not just in marketing, but in everything—it’s worth rethinking that a bit.

People hear “AI” and they immediately think of something like C-3PO or Data from Star Trek—something human-like, with a broad range of capabilities. Data can move, see, hear, talk, process huge amounts of information—he’s fully formed.

But in reality, the AI that’s impacting our lives today isn’t general intelligence like that. It’s narrow AI—systems that are really good at one specific task.

So yes, right now, it’s totally reasonable to say creativity is still a human-only skill. Even a couple years from now, I think it’ll still be reasonable to say the full picture of creativity belongs to humans.

But what’s happening, and what we’re seeing already, is that little pieces of what we used to think of as “creative work” are now being done by software.

In our case, we’re using machine vision to analyze millions of images. The software understands what colors are being used, what objects are in the image, whether there are people in it, their age, gender, positioning—all of it. Then it uses machine learning to find patterns in that data.

Now, sure, a human could kind of do that unofficially—hire a team, try to spot the trends manually—but software is just way better and more consistent at that kind of pattern recognition. That’s one small slice of creativity that machines now handle better.

And if we look ahead, five years from now, everyone will probably be using tools like ours to do that kind of analysis. At that point, no one will even think of that part as “creative” anymore. It’ll just be, “Oh yeah, that’s what the software does. We do the rest.”

And that’s how it evolves. One narrow piece at a time, AI chips away at tasks that used to be considered purely creative. Eventually, maybe half of what we once called creativity will be handled by machines, and the other half will stay with humans.

But that doesn’t make humans less creative—in fact, it makes us more powerful. Because now, when someone sits down to create an ad campaign, they already know the best colors to use, what their audience wants to see, the right kind of people to feature, where the scene should be set… all of that.

It’s still a creative process, but now it’s supercharged with the right inputs.

So yeah, you’re totally right—people think, “Well, this is human stuff. How can you automate human stuff?” And on a big-picture level, they’re right. Creativity isn’t going away. Creative jobs aren’t going away.

But all these little components that make up the creative process? Those are being done—and already are being done—by AI. And I think it’s exciting.

It kind of sneaks up on you, but it completely changes how we approach the day-to-day work of creativity.

Yeah, exactly. Let me give you a real-world example. One of our customers—a major consumer products company in hair care and skin care—did an initial analysis using Cortex.

One of the gateway products we offer is something called a Visual Vocabulary Report. It’s made specifically for people who aren’t quite ready to dive all the way in. Maybe they’re hesitant about using AI, like you mentioned earlier—they’re not ready to “invite the robot to the party” just yet. This report is a simple PDF. Super non-threatening. You can read it, ignore it, share it—it’s easy.

But what it does offer is a deep dive into hundreds of creative trends and choices, along with predictions on how those choices are likely to impact performance.

So in this company’s case, one of the things that stood out was a trend around color—specifically pink. The report highlighted a very specific shade of light pink and even provided the exact hex code for it. Because we’re talking about software, it’s super precise. No guesswork.

It said that using this particular shade of pink could boost performance by 19%. And then, later in the same report, it flagged a slightly darker shade of pink—again, with a specific hex code—and showed that it would actually hurt performance by about 17 or 18%.

So naturally, the team asked, “Wait a second—if we just change our images from this darker pink to the lighter pink, we could see a 35% swing in performance?” And the answer was yes. That one change alone had the potential to make a huge impact.

What made it even cooler was that they told us they had actually tried to run a color analysis before, using their internal team. But humans can’t really analyze colors at the pixel level. They can’t reliably distinguish between shades like that—or know where to draw the line.

So their analysis boiled down to something like the 12 colors from a crayon box. They had “one pink,” “one red,” and so on. And based on that analysis, they concluded pink was basically a neutral color—it didn’t move the needle either way. So they moved on.

But what Cortex revealed was that there are two stories within the color pink—and they never would’ve known that without software.

And here’s the key point: now that their team knows this, are they less valuable to the company? Not at all. They’re more valuable. Because now they can share this insight with designers, photographers, and campaign leads—across the board. They can apply it everywhere and significantly improve performance.

And that’s just one insight out of thousands Cortex surfaces. And it communicates them clearly, quickly, and in a way that’s actually usable.

So back to what you were saying earlier—that’s really the heart of it. In almost every case throughout history, when automation shows up, it actually makes the worker more valuable, not less.

Think about the Model T assembly line. Back then, you needed one person per screw. Now you’ve got five highly skilled people building the whole car, thanks to automation. But each of those five people contributes way more value than the hundred before them.

It’s the same with AI. When a marketer becomes more accurate, more strategic—when they start delivering better results—they’re not at risk. If anything, they get more budget.

So no—we’re not seeing people lose jobs to AI. We’re seeing marketers become more powerful because of it.

Yeah, actually, that’s exactly what’s been happening. The first, let’s say, three years were definitely tough. We were still learning, and it was a lot of what you’d call missionary selling—going out there and saying, “Hey, this exists, you should try it.”

But that’s changed a lot in the last year. Now, most major brands are actively looking for something like this and coming directly to us. Honestly, at this point, probably 95% of our revenue—maybe more—is inbound. We’re not cold calling anymore like I used to. It’s all coming to us, which is obviously a much better place to be.

Now, to answer your earlier question, there are basically three stages of maturity we see with companies, and we’ve built products to match each stage.

So if someone comes to us and says, “Hey, I’ve heard of this, but I’m not really sure what it is or how it works,” we start them off with that Visual Vocabulary report I mentioned earlier. It’s basically a sample—a non-threatening entry point. You’re not committing to anything. It’s a one-off PDF you can share around, use to look smart internally, and shop it to decision-makers. No strings attached.

That usually leads to the second stage. At that point, they’ve got all this data they’ve tested and circulated internally. They’ve seen the new trends. And now they’re ready to actually commit to using that data more regularly. That’s where our second-tier product comes in—it provides much more data, more often, and in a format that’s easier to integrate into their workflow.

Then there’s the third stage. This is where companies have seen the value, they’ve built their creative process around the data, and now they want to optimize. They want the data to be everywhere it needs to be and to extract the maximum value from it.

For that, we have our full SaaS platform. Not only does it give you the data, but it starts automating a lot of the creative decision-making.

Think about it—Cortex knows what colors your audience responds to. It knows what types of images work best, what objects should be in those images, what time of day to post, and how all of that changes depending on platform. It’s constantly clustering and comparing inputs to uncover patterns.

So let’s say, next Friday, Cortex sees that your audience is most likely to engage with a photo of your alcoholic beverage on a beach, with a specific set of colors. It doesn’t just tell you that. If you’ve connected it to your digital asset manager—or to Getty Images through our partnership—it can actually go find that image and prep it for publishing.

So now, it’s not just about insight—it’s about execution. Our top-tier platform handles everything from strategy to scheduling, all based on the data.

So yeah, you nailed it. Companies are at different stages of sophistication, but we’ve solved that by giving them the right tool at each stage—something useful no matter where they are in their journey.

Yeah, it’s really exciting. A lot of the innovation has been driven by us—by things we learned from the last company, or requests we’ve been hearing from customers, stuff we wanted to be able to do. So we’d go to the tech team and say, “Hey, here’s the mission. Let’s build this.”

But now, we’ve checked off most of those foundational boxes—the stuff we knew we needed from the start. And what’s happening more and more is, the tech team is coming to us saying, “Hey, did you know we can actually predict this now?” And I’m like, “Wait—what? That’s insanely valuable. Can we put that into the product tomorrow?”

It’s wild. And you’re exactly right—it’s exciting.

Part of it is that these guys have PhDs and have gone deep into machine learning in ways we haven’t. But part of it is also just the pace at which all this technology is evolving.

For example, let’s say Google releases some crazy new image-processing capability tomorrow—like, hypothetically, being able to analyze the angle of sunlight in an image to determine the exact time it was taken. I’m just making that up, but you get the idea.

We’d be able to take something like that and immediately plug it into our system to enrich our dataset. And that, in turn, would make our predictions better. So every time something new like that drops, we’re like, “Great—bolt that on, make the system smarter, give our clients even more accuracy.”

That’s essentially what’s happening now on a regular basis. The tech is moving fast, and the team is always experimenting—partly because it’s their job, but also because they love this stuff. They’re constantly nerding out, testing new tools, and saying, “Hey, what if we ran this? What if we tried that?” And sometimes it unlocks a whole new layer of predictive power—like a few extra percentage points of performance our clients wouldn’t have had otherwise.

So yeah, we’ve definitely entered that phase now where it’s just super fun and exciting—kind of exactly like what you were describing.

Well, thanks. Yeah—next time you’re in Boston, come on down. We’ll host a meeting just for you.

Yeah, of course. So to take one step back first—if you think about everything we’ve been talking about, we’ve mostly framed it from the brand or marketer’s perspective. But if you flip it around and look at it from the consumer’s side, what we’re really talking about is making better content for the consumer.

This technology helps you understand what your audience actually wants—what they like—so you can create content that aligns with that. And if you choose to follow that data and build content the consumer actually values, you’re already way ahead of the game.

Now, in terms of companies doing this well, there’s definitely a spectrum. But far and away, the most committed to that vision is Red Bull. Everyone knows them as a drink company, but they’ve essentially built a self-sustaining media division. They run wild, high-energy events their audience loves to watch—and that division is profitable on its own.

They put a guy into space just so he could skydive back to Earth. They run events like soapbox races with weird vehicles flying off platforms into water. All of it is designed around creating cool content that their audience genuinely wants to see.

And they’ve gone all-in. They literally split the company into two parts: the drink business and the content/media business. And that content arm exists solely to serve the consumer—to create value through content people actually care about.

Because of that, Red Bull is never short on things to talk about. They’re always in the conversation, constantly in the media. And of course, the drink side of the business does just fine too.

So yeah, I think they’re probably the best example out there because they fully committed to that idea—even before there was a way to track whether it worked.

Today, I imagine they’ve gotten a lot more sophisticated with it. I don’t know if they’re using AI like we are, but if not—they should definitely give us a call.

But seriously, they jumped in with both feet, and it shows.

Yeah, exactly. That’s the funny thing—whether brands realize it or not, almost every consumer brand has to think this way now.

There’s just so much content out there. The average brand is producing around 15,000 pieces of content per year—just to stay competitive. That’s across social, digital, and all the other channels.

And if you rewind 25 years—back to, say, the late ’80s or early ’90s, before the internet—it was maybe a few dozen commercials a year, a few print ads, a few magazine spots. Maybe 100 pieces of content total in a year.

So when you look at it over the last 30-plus years, you’re talking about brands going from 100 pieces of content a year to 15,000. That’s massive. Brands are media companies now, whether they think of themselves that way or not.

And getting smart about it—like Red Bull did—is what makes the difference. Red Bull didn’t just wait around; they got ahead of the curve and led the way.

Now, even companies like Tesla—while they haven’t jumped in the way Red Bull has, they still understand that the best thing they can do is give their audience content about new, futuristic stuff. Even though Tesla is very product-focused and doesn’t have a full content division like Red Bull, they’re still philosophically similar.

They barely spend on marketing, but they lead with their story. They lead with a vision—“We’re building the future.” Then they show you glimpses of it: these new products, this cool innovation, the futuristic vibe.

So even though they spend very little compared to Red Bull, they’re still in that same mindset. I’d say Tesla is actually in the same category as Red Bull—just on the opposite end of the spend spectrum. But they totally get it.

Yeah, we haven’t done any specific analysis on Tesla cars or anything like that, but I’d absolutely predict that the recent Cybertruck will do exceedingly well—just based on the design stance alone.

Almost every other car brand tries to blend into the middle. They play it safe and end up looking just like every other vehicle on the road. But if you watched the Tesla presentation, you saw they took the logos off of all the top-selling pickup trucks, and once you strip those away, they’re almost indistinguishable—functionally and visually.

Tesla made a bold choice. It’s not designed to appeal to everyone, but it doesn’t have to. It just needs to speak to the right people. And it clearly does—those trucks are among the top-selling of the year. They’ve already sold 100,000, maybe even 200,000. They’re off to the races.

Now, I don’t know what kind of research went into it—if they used AI or if it’s just Elon Musk going with his gut—but they made a bold decision. They said, “This is what we think our audience wants,” and they went all in.

And most companies don’t have the guts to do that—to say, “This is the direction,” and just commit. That’s why it works.

I don’t believe we’ve spoken there yet, but we’re scheduled to speak next year.

Yeah, honestly, it almost feels like cheating from a keynote speaker standpoint—because we don’t really have to talk about ourselves at all.

We go into every presentation having already processed a bunch of data—either about companies we know will be in the audience or focused on a specific industry that’s relevant to the event.

For example, I was speaking at a conference in Belgium last Thursday, and since Belgium’s known for beer—and people there are very passionate about it—we processed the entire beer industry ahead of time.

So when I got on stage, I just jumped right in. I didn’t bother with a long intro about us. I said, “Let’s get into the data,” and showed them what AI is doing in marketing. I walked through trends, insights, predictions—things they could actually use.

Like, “You guys in the beer industry? You should be using these colors, this kind of messaging, make these changes,” and so on. It’s immediate, actionable stuff.

Then we zoomed in on a niche market—small furniture stores in Belgium, Denmark, and the Netherlands—because a lot of attendees were from those areas. We even pulled data for a specific company, Deloitte, and showed them what their Belgian office could be doing differently from a marketing standpoint.

All of that turned into the presentation. It was super visual, easy to understand, and totally personalized. It gives the audience real takeaways they can act on right away.

And the best part is, we can do all of that with the push of a button. It’s so fast. We just ask the event organizer two days before, “Hey, who’s going to be in the room?” and then we tailor everything to those companies or industries.

So yeah—I love it. Because the audience gets real value, and it doesn’t feel like a sales pitch. It’s all about showing them what’s possible.

I’ll commit to it—on recording. If you’ve got an event you’re really excited about and want some trends, just give us a week’s notice. We’ll get you a bunch of insights, and you’ll look great on stage.

Thanksgiving.

Oh, that’s a good one. Okay, so let’s put aside any deceased family members, because I think that would be everyone’s first choice.

I’ll also skip over the dozens of jazz musicians I’d love to talk with—like Thelonious Monk, who’s amazing—but for this purpose, I want to keep it relevant to where I am in life and the responsibilities I have, especially with Cortex.

So for that reason, I’d say Elon Musk. And not to sound like a total fanboy, but I think he makes sense. If my goal is to level up my own software company, having dinner with someone like him would be incredibly valuable.

I’m not trying to compare myself to him, obviously—but I love how he tackles problems from the ground up. Like, he doesn’t just ask, “How do we make rockets better?” He asks, “Why are rockets so expensive in the first place? What if we built cheaper ones from scratch?”

That kind of thinking is really inspiring. He’s solving for the root of the problem, and that’s something I think everyone can learn from.

My second choice would be Eisenhower. I’ve read a few biographies on him, and he strikes me as someone with a lot of wisdom—especially when it comes to leadership and decision-making under pressure.

If Musk represents that raw, visionary brainpower, Eisenhower represents calm, steady judgment. He seemed to consistently make the right calls—even in incredibly difficult situations like World War II.

And I’d love to learn more about that process: how to manage urgency, make tough calls, weigh long-term impact vs. short-term needs, and lead effectively through chaos.

Have you heard of his “smoking stories” concept? Familiar with that?

Oh, yeah—so he used to be a smoker, like a lot of people from that generation. Pretty much everyone smoked back then, especially if they’d been in the war.

But after he got sick—I think it was a heart attack, I can’t remember exactly—he came back and decided to stop smoking. And instead of doing what most people would do, like tossing their cigarettes and being done with it, he did something different.

He kept a pack of cigarettes in his breast pocket for the rest of his life. Never touched them again—except to offer one to someone else if they asked.

And when people asked him why he kept them, he said it was because every time he didn’t reach for one, it reminded him of the victory. It was a symbol of self-control.

To me, that’s just incredibly badass. That kind of mindset—learning from that—is huge.

Now for my third dinner guest, I’d want to go in a more specific direction, someone who created something that didn’t exist before. I’d choose Marc Benioff from Salesforce.

He helped create—really define—the category of cloud software, CRM, and SaaS. Sure, he didn’t do it all himself, but he absolutely led the charge. He helped people understand those categories, and defined a space that hadn’t existed before.

And in a way, Cortex is trying to do something similar. We could call ourselves a marketing software company, but we’re really more focused on creativity and visuals.

The reality is, there isn’t really a defined category yet for what we’re doing—software that helps with creativity and visual intelligence in marketing.

Like we’ve talked about, people weren’t even looking for this five years ago. It just wasn’t on their radar. So part of what we’re doing is trying to create that category.

And that’s why I’d want to talk to Benioff—because he did exactly that. He built something new from the ground up, and made people see the value in it. He created the category. For sure.

Oh man, I’m very boring in this category. I’m struggling to think of something more exciting to say, but the real answer? I’d invest it very conservatively.

I’d factor in inflation and reinvest every year so the value doesn’t go down over time. Then I’d use whatever comes after—whatever gains I get—to help my niece and nephew go to college, and tell my family, “Hey, I’ve got it.”

Like I said before, really small family—so I think this is actually doable. There’s only about 10 or 11 of us total. So realistically, I think I could take care of everyone if I played it smart.

But… I am a big fan of boats and helicopters, so if you want a more exciting answer, you can pretend I said that.

Absolutely. So Cortex can be found at meetcortex.com—super easy. We’re very active and quick to respond.

People can also find me on LinkedIn. It’s just linkedin.com/in/brennanwhite—couldn’t be simpler. I’m super active there, usually respond within a day or two, sometimes faster.

And I’m also on Twitter, though I mostly just share stuff and don’t post too often. I go by the handle “@economics,” which I know sounds bold, but yep, that’s me. So yeah—those are the best ways to reach out.

Thanks for having me. Really great talking to you today.