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DJ Patil | An Update From the Front Lines of AI - A Perspective From Spock on the Bridge
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Podcast Host/Announcer
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.
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DJ Patel
The podcast that takes you inside the drama, decisions and choices that go with being the head of marketing. Hosted by five time CMO Mike Linton.
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Mike Linton
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 CMO of Best Buy, ebay, Farmers Insurance and Ancestry.com here today with my guest, DJ Patel. Today's topic, an update from the front lines of AI A perspective from Spock on the bridge. Now, D.J. held leadership positions at eBay and LinkedIn and served as the chief Data scientist for the United States of America. He's a senior fellow at Berkeley and also an advisor and investor. Full disclosure, we worked together at eBay where DJ was, and I really mean this in Star Trekking terms, the Spock on the bridge for the company. This is his third time on the show and today we are going to dive into AI from that perspective and he's going to do his best Star Trek impersonation. Welcome back, dj.
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DJ Patel
Hey, thanks for having me back. I feel like now do I get to call a regular? Is that, like, how it works?
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Mike Linton
You can. I think you can if you want. Yeah, that's totally good. All right, first question, dj, where are we really in the AI adoption curve?
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DJ Patel
Yeah. So I think the best way to call it is you ever, like, make a cake or do anything and it's got crazy lumps and you're just like. Like that. Like we're lumpy. It's like lumpy in. In a ridiculous way. There's certain areas where AI is, you know, it's knocking it out of the park. And there's other areas where you're like kind of there. The teams that are adopting it look very different. There's different areas. There's all sorts of things. Like, you know, maybe here's the best way to think about it. So the first time you use one of these AI systems, you're like, wow. Oh my gosh, this is amazing. Look at this. This. Like you're. And then like the third, fourth time, fifth time, you're doing the same exact thing. You're like, could it be a little bit better? Could it, could it, could it, like, could it just actually be a little more helpful? You want this, this thing to actually work for you. That's kind of where we are on this. But then you flip it around and you kind of look at self driving cars and automation on that side and you go, wow, Waymo keeps expanding its footprint. You're seeing lots of great stuff happening there. You're seeing the, the, the kind of big warehousing, like Amazon style warehousing, take advantage of robotics and AI and that's working wonders too. And then in national security, you're seeing it really work well in battlefield conditions like in Ukraine.
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Mike Linton
Well, I want to go back to the Ukraine thing in a minute, but you know, you, you describe this as, you know, cake in its batter form where you've poured it into the. Correct me if I'm wrong in this. You poured it into the, you know, your baking dish and you're not sure what kind of cake it is yet. Is that a fair way to look at it?
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DJ Patel
Yeah, I think that is, you know, the way one of the things that I think is really essential is, and here's the framing that I use right now, is we're in this kind of very early phase of the technology and the applications where the people who are what we might call native, the AI native people, they haven't actually graduated yet. They're like sophomores in college. And the way to think about this is, you know, Mike, you and I are not AI or we're not going to be AI native because not that age. We weren't even mobile native. We weren't cloud native.
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Mike Linton
Killing me here, D.J.
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DJ Patel
But we weren't, we weren't even desktop native, right? Like, you know, like we went to labs and those things. But the, the thing that I think is essential for people to know out there is that you have to go, you. We had to be fluent, we had to learn how to be compute fluent, we had to learn how to be mobile fluent, cloud fluent. And right now what you're seeing is you have a lot of teams that are working to be AI fluent. And then there's going to be a wave as those people come in and those, that new guard that's coming in, those are going to be the AI native people in many of the ways, same ways, you know, like kind of kids people have kids. Like, they, like, you know, my kids, at least they, they, they Take my phone. And they're like, you're too slow at this. And I'm like, hey, did you know I, I actually built that, I made that. They're like, shows what you know, like you can make the technology, but doesn't mean you know how to use the technology is what they constantly remind me. And it's a good lesson because I think what we're, what we see right now in this lumpiness is people who are adverse to even becoming AI fluent. And we were talking about this a little bit before the show. You see this in the classroom. Some professors are like, no AI allowed at all. And others are like, use it like you are, Mike. Like, as you're teaching. They're like, use it all you want.
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Mike Linton
YOLO can't help. It's not going to help you get the answer. But it can help you think and create the platform.
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DJ Patel
Exactly, exactly.
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Mike Linton
I think this thing. I have to go back because I can't let how AI is affecting the battlefield between Ukraine and Russia. Just as a sidebar, tell us what's going on over there.
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DJ Patel
Yeah, so you take a look at the autonomous weapon systems. Think of these as drones, and these are what are referred to as kinetic strike capabilities, where you have a drone, drone, it kind of flies out, maybe goes and hits something, maybe it tries to deploy a payload, shoot something, drop something, those type of things. Recently you've heard about it, maybe you heard about it in the news around the Russian fleet, the tankers, the Ghost fleet, kind of that's been moving oil secretly. Those have been being taken out by sea drones. Well, when you kind of launch these things, you know, some of them may have some human assisted type technology, but they're more and more say, oh, that's the target. Let me figure out how to, how to do it. Because if, if you're a, if you're connected to it as a human from somewhere, somebody can intercept that feed, hijack it, and, you know, change everything up to, you know, counter. It's a counter attack. And so you're here. What you want to say is like, look, that's the target. You've got it.
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Mike Linton
Go do your Terminator thing.
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DJ Patel
Exactly. And so you're seeing. And it's less about tech innovation, it's about forced necessity of survival. And this technology as it's kind of moved along and we've seen this over time, is like, you can use these huge models like the OpenAI, the anthropics, the Googles, et cetera, or you can use a lot of times these small Models, these miniature models, many of which are referred to is open source models. These are the things that you hear out of China, Deepseek or Llama, which is, has been Facebook's version.
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Mike Linton
So I want to flip this over now to all the circular investing going on. You know, you got the chip makers, you got the models, you got.
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DJ Patel
I feel like you need a backdrop with a flowchart.
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Mike Linton
You know, if I could, I would maybe next show and maybe when you come in, you know, later this year, how do, how art do you think about that? You got all this energy needs, you got stuff. I think you got at least seven big players in this. What, how are you thinking about this and how is everyone going to eventually make this payout or won't they all do it?
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DJ Patel
I mean one thing is just to recap what a crazy, I don't know, six months it's been in terms of flip flopping of whose model is the best between OpenAI anthropic and even Google's Gemini. You know, in the last three months, you know, we had the Math Olympiad that this famous exam that high school students take last year, the year before this, this last, this, this last Olympiad, only four out of the six problems had been solved by AI systems and it took them a long time computationally. Do four, five out of the six this year were solved. So that qualifies you as a gold medal. So these models effectively got a gold medal. A number of students did get six out of six. We're expecting all six out of six to be solved next year. But what's happened in this small short time period is one of the hardest math proofs that's out there. The Erdos problem, one of his famous conjectures, was just solved by one of the models out there. And so it's introduced a whole new way of thinking about solving some of the hardest math problems have ever been created. And then you kind of go okay, that's this high level, big stuff, right? And then you kind of go okay, well we've got vibe coding that's happened. We now have all these other kind of like ways that people are starting to figure this out. And so I might separate. I think everyone is really focused on the big giant players and that there's right to do so because of the volume of, of, of, of the amount of dollars that are going into these things. And you're right, there's like, you can't keep track. It looks like those that remember reading Oliver Twist, you're like, wait, who's related to who? And what's happening kind of feels like that, like, and you're just like, wait, are they investors? Are they not? Are they frenemies now?
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Mike Linton
Like what exactly.
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DJ Patel
It's like Game of Thrones at very, very esque. And then like the talent, it keeps moving. You're like, wait, that person, like Alex was over at scale, now he's at meta. And you're like, like everyone's kind of moving around. Apple's making moves, everyone's making moves. So a lot's taking there. What I find more interesting is the applications that people are starting to really leverage for these technologies. So specifically, like, we're starting to see where people are able to say, hey, this is actually adding lots of value on the legal front inside the corporation. We're actually able to use a product. Might be Harvey, might be one of the many others that are out there, we're actually able to do this. You take a look at Figma, which is on the design side, something that, you know, I've been really fortunate to be involved in for a long time. You take a look at Figma and now you can do a lot of the design components by, you know, just talking to the system and saying what you want. Are you going to get something perfect? No. But boy, remember the days when it took you like weeks and weeks to talk to the designer.
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Mike Linton
So dj, there's this. The question beneath all that is we can talk about Amare's Law, but also the, there's all this thing like, will this pay out or not? One day Wall Street's up, the next day Wall Street's in this flop sweat panic that we've over invested. How, you know, and Amare's Law says you underestimate it now and, or you overestimate the short term and underestimate the long term. How should people think about this in terms of ROI and these investments paying off and you're an investor, how should they be thinking about it?
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DJ Patel
So I think that public markets are a super confusing way to look at the world and the valuation of these things. And what is the actual, like the, the actual ROI on this? I think there's absolutely going to be a small set of massive big companies that, that are able to take advantage of AI and disproportionately leverage them. I think that's going to be the case. You know, if you look at Google and the infrastructure, they have all those things, Nvidia, the chip designs, all this stuff, Amazon, they're sitting not just on data you can think of, there's Like a Maslow's hierarchy. It's like in life you have food, clean water, shelter and up. The same way exists for AI power. You need power, you need data, you need water to basically build data centers.
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Mike Linton
You need all that. The data center is cool.
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DJ Patel
Yeah, right. But then you.
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Mike Linton
Data centers don't drink, but they do stay cool.
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DJ Patel
They just stay cool. And then you kind of go up the stack and one of the things that people don't realize is like, you need the model, you need lots more data that start to come in and you need user feedback loops. You need user feedback loops to keep iterating this, creating different data interaction points. All of those things that's the one to watch is, is like where are the, the feedback loops? So, so, so, but, but here's the way I would encourage everyone out there to think about this. How are like at the balance sheet level, at the board level, are we spending pennies, nickels, dimes or dollars? And when do we start seeing the savings? So right now on the balance sheet for a corporation, you're spending pennies and you'll be spending pennies relatively through 2026. You'll start making. And my, my very dangerous things to do, make forecasts. But here we are kicking off 2026. You know, the beginning is, I think we start to make pennies towards the end of 2026, maybe into 2027.
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Mike Linton
And then you're talking like the average.
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DJ Patel
Corporate user, the big corporate like so, so you're still only like on your, on your revenue lines. You're not seeing big dollars through 2026. You're seeing pennies. You're still seeing like, hey look, I saved, you know, if you're UnitedHealthcare, you're like, look, I saved billions of dollars. But you're like, what's billions on this? On this?
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Podcast Host/Announcer
Or something.
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DJ Patel
Yeah, yeah. You're like, maybe we, maybe we'll call that a dime. You start to really start seeing and your spend moves from pennies to maybe a nickel in there towards the end of 2026. You really start to see the impacts in 2027. Why does it take so long? It's not just only about the technology getting there. The cultural component of this is one of the big.
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Mike Linton
We did a whole show on this that said that is the biggest blocker. Yeah. With the CEO of Typeface saying it's culture. And it's also, and I want to flip over, there's all the hype around it. And also you have a lot of boards probably going, oh my God, what are we doing in AI? What are we doing in AI? And a lot of our user, a lot of people that have come on our show have said, look, the board shouldn't be doing that. It should be sorting out use cases and getting traction here. It shouldn't. And it, and also leaders can't delegate this. Tell us what you think about that and, and then weave the culture story into it.
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DJ Patel
Yeah. So for, so let me give you first a framework why I think this is what, what's, what's. Why this is that it, it sort of epitomizes how bad things are going to be. So I think of these things in timescales. So you know, you think about product releases. A major company has one big product launch every year. Like you get your new iPhone every year, you hear about the launch and you're like, wow, okay, this is what I get 1 1x kind of for a major company. The lesser companies, it's like 02x maybe every or 0.5x every other year. So startups typically release three times a year, so they're 3x. So 1x versus 3x put you on exponential. AI companies are launching 7 to 10x 7 to 10x major releases a year. So that puts them on this crazy scale. Culture changes roughly once every 10 years for a company, if you're lucky, if you're able to transform it. So that's 0.1x policy changes every 20 to 30 years. So that's a 0.02x. So you got a point.02x versus a 10x in technology change. So out of that there's three things that can happen. You can have a hard landing, you can have a bumpy landing, soft landing, or you can leverage it on opportunities. And so to your point, Mike, I think what we see is executives think of this like traditional software. Let's make a big investment, let's go do this stuff. It should be lots of experimentation, lots of play to allow your teams to learn and codify with this technology, allow them to become AI fluent, to leverage it, figure out what are those things work and then go. The infrastructure for these bets, the infrastructure, the raw infrastructure for to allow all this stuff to work is super in the infancy and it's likely to only get hardened and codified over a year. So, so if you better be repair like and Mike, you and I live this like we were trying to do all this stuff with data and you're like, well that data is, you know that data warehouse style technology doesn't work. Got to rip it out, put in a new one and you do it again and again to stay competitive. These companies are not ready for that level.
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Mike Linton
But this says you have to really have a board. In particular a board and, and, and the C suite that is cognizant of everything you just said. Or they will either pass this down to someone to do it or demand someone do it that isn't them.
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DJ Patel
If your executive team doesn't have carved out time to be doing the AI, playing with the AI themselves and they are just delegating it, they're going to mess up. This is that Facebook moment where they, you know, Mark, we know we did this at LinkedIn too, is like, if you tell the exec team, you're like, you can't use, like you can't use the product on the laptop. You have to be only mobile. If you don't do that, you're out. Like, we can't have you on this team. The board has to be this way too. A lot of the board things that people, groups that I interact with and I see the same thing we saw during the data science era, the same thing we saw during the web era, 10 to 2.0. If they're not using the tech, they don't get it.
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Mike Linton
And they don't get it, but they're getting all their information out of either business posts that are reading or talking to their friends, which is not going to be enough. You know, the. All the consulting companies are saying they can help you with this.
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DJ Patel
How do you feel about myself in trouble?
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Mike Linton
Well, we love that on the show. You know, be tasteful. But, you know, because what you just said kind of goes counter to saying, I'm going to have a consultant come in and tell me how to do this, because if I don't know how to do it myself, I'm not going to be able actually to lead it.
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DJ Patel
Yeah.
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Mike Linton
So tell me about the consulting companies and then, you know, how you feel about it and then we can talk about if you still have to hire one, what do you look for?
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DJ Patel
So here's what at least I'm seeing out there is you see a lot of people who are trying to do the traditional handed to a bunch of consultants, management consultants, who historically have been really effective and really helpful to the companies. And doing this, they're not here because the stuff has to be integrated. It's like, it's like changing your DNA. You can't change your DNA as a company by, you know, we saw this with mobile, where suddenly they're like, oh, we should have a mobile team. And you're like, no, everyone has to have mobile DNA. You don't. There's not like a team that you hand it over to. The same thing as like on marketing teams. Like if you have this separate, well, let's call in the social media team, you're like, well, this is probably going to go bad real fast. So we see that. The other thing is because the tech is so changing so quickly, what does it mean to be a consultant who understands and utilizes technology? The shift that we're seeing is more what people refer to as a forward deployed engineer or somebody from the vendor. So for example, you work with Palantir, you work with OpenAI, you work with Anthropic. Fill in your name of sort of cutting edge technology shop. You know, you spend so much, they're going to give you the team, they are going to give you their team of super, you know, talented, young spirited people that before you were like, oh right, you would be, you'd be at like one of these, these big five shops kind of thing. They look the same, they act the same, but they are way more savvy on the technology. And because they are from the DNA of the company, they're not like a system integrator. They have a direct line, they're directly connected and they're like, hey, here's how you use our technology. We see this all the time in healthcare right now where you work with these players and then you get. The management consultant comes in and they just don't. They're learning too, they're figuring it out. Also, the tech is so early.
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Mike Linton
Well, and also if it's evolving, they're not going to leave anything behind when they finally go, so tell us about, you know, there's all the job cuts, Amazon, Meta, Goldman Sachs, there's so many job cuts. How should people feel about that? And is this just the beginning of the job cuts?
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DJ Patel
All right, I'm going to get myself in trouble again. But hot takes, so we'll see, see how much what people come at me with. So my take is the following at the junior levels, the pullback on hiring that we're hearing about like everyone, like kids aren't getting internships, new job hiring is not there. All of those type things. There's been a lot of talk of, oh, this is AI. It is AI for like the Amazons and other places that have invested in this for decades already. Like, you know, they're year 15 plus on this journey. Those ones you are seeing some of the advantages for everybody else it's just economic pullback. It's a bigger sign of economic weakness. And everyone's like, hey, we're not, it's not in our hiring plan. Talk to lots of companies out there and they're just saying, hey, we're not going to get take interns this year because we're not planning to hire. We're going to stay flat or go slightly down next year because we just overhied our efficiencies for the later stage employees call it 10 years out or something like that to more. That's just streamlining with the hope that AI is going to take those efficiencies out there. The place where we see AI having big impacts right now is more on just straight up automation and a lot of things. A place that is counter to this is health care. So in health care, and this has been driven by the last few quarters of job growth. The job growth in the United States is driven by health care. That's back office work. Yeah, that is like that. And, but I would argue that is not good jobs. And those jobs are likely to disappear because that's the stuff that you hear about that costs a lot like claim denials.
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Mike Linton
Oh yeah.
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DJ Patel
Passing paperwork all the.
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Mike Linton
And that nobody likes to do.
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DJ Patel
Nobody likes to do those jobs like.
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Mike Linton
Well if they do, they're going to get hired by like Scrooge and Marley's.
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DJ Patel
Yeah, exactly.
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Mike Linton
Yeah.
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DJ Patel
And these are the jobs that I would call stupid boring problems. And they're ready. Those tech problems are more likely to get, get evaporated. And that's the form that you're already starting to see disappear elsewhere. And we are seeing these things like on the call centers and other type areas that the tech is getting decent enough to deploy to deploy there. You know some of the metrics that are there. Brett Taylor, Sierra Company already announced that they've surpassed in Q4 of 2025, they surpassed 100 million in ARR. For a company that's been around in short term, short term, while, but people actually like talking to it, people like working with it.
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Mike Linton
So dj, if I read between the lines there, what I hear you saying is AI may take a lot of jobs in the long run, but a lot of the stuff you're reading about now, it hasn't even started working yet.
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DJ Patel
It hasn't. We're not seeing the real impact yet. The way I would think about a lot of these AI systems say in the corporate world, they're 80% ish solutions, they're good ish, but they're not like, they're not ready to kind of really be prime time. Sure. Can I solve this ridiculous math problem? Can they do all this amazing stuff? Yes. Can they do real work?
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Mike Linton
Yeah. So they're like autopilot, but they can't fly the plane yet.
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DJ Patel
Exactly. But it is getting there. Right? And it's. But, like, the same way, like, you saw this with Waymo, you saw this with other autonomous driving vehicles kind of technologies. It's about a decade for that stuff to really get hardened.
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Mike Linton
So. All right, let's flip this over to investing, because we had the. The two. Two gentlemen that wrote AI first on the show, and they said, look, AI is the biggest prize in the history of capitalism. How are you investing in the biggest prize in the history of capitalism?
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DJ Patel
So I think that a lot of the big bets are already taken for the big. You know, you kind of think about this as, like, boulders, and then you've got to put in the smaller rocks and you put in the pebbles, you put in the sand. The big boulders have largely been put in for the big foundation models. I still think there's plenty to be done on more tailored or what we might call small models, where they're actually very specific to an application area. And then I think there's a ton that can be done in verticalized solutions. The place where I am really focused on a lot of these things is kind of 2ish, 3ish fold. One is the analogy I would use, and I know I'm mixing metaphors here, is like, you know, we got this giant muscle that's the big LLM, but you don't have the ligaments in tendon, and you can't run without ligaments and tendons.
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Mike Linton
You have been an analogy machine. We started with cake, and now we are to tendons. And in the introduction, we were on the bridge of the enterprise. So no, I used no AI. So we're working on tendons and ligaments now.
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DJ Patel
Exactly. But like. Like, the way I think about it a lot of times is like, people are like, look at my super cool AI. And I'm like, well, like, you know, and like, here's a concrete version. So you're like, hey, we're gonna have, you know, maybe 20 agents, you know, AI agents doing stuff this this year. And I'm like, great, Once you unleash that, then are you gonna have fifty, a thousand, two thousand, five thousand? Who's gonna manage that? What happens when the model changes? How do you do evaluation? How do you think about all these other things where Your checkpoints and like all those little things that are required. That's a lot of stuff. That's a.
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Mike Linton
Like, you know, you got to hold the body together, focus.
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DJ Patel
Exactly. And.
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Mike Linton
And you said there were three things. Are there too much?
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DJ Patel
Okay, so that's, that's like the, that's like the, like the, the small muscles, ligaments, tendons.
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Mike Linton
Yeah.
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DJ Patel
Then I think there's a lot of space in the application area specifically to something like health tech and healthcare. What is the AI? What could AI do? Right now everyone's focused on how does the AI help the doctor. Could we have scribe or all these other things? I think that's nice. But there's a ton more where AI can just be extraordinarily additive, net positive. We have areas of the country where there are no care. Like, there's no physicians, there's no access to care. So what could we do with AI assisted technologies to help get you faster care? Look over things. And this is the sad thing is, you know, in the era of big data and data science, we have really only done one thing for healthcare, is make more money for hospital systems and payers, the insurance companies. We have not delivered the care to people.
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Mike Linton
So we have tendons and now we have what I'm going to call it a vertical.
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DJ Patel
Yeah.
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Mike Linton
And there's a third thing and then.
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DJ Patel
The other vertical sort of area, which I would say is like, you're going to have things like in government that makes a lot of sense, whether it's audits. It could be national security.
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Mike Linton
The IRS could audit absolutely everybody if it wanted to.
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DJ Patel
Well, I'm like, why can't I have. Like, why can't I have A.I. do my taxes?
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Podcast Host/Announcer
I.
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Mike Linton
That would be fantastic.
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DJ Patel
Would that be like, how much time do you spend on this? Like, why can't it just do it for me? That seems like a stupid, boring problem. Like, those are the things.
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Mike Linton
Okay, so we've gone from cake to tendons. I wanted, I want to write, just before we get to our traditional last question, write marketers into this story now.
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DJ Patel
Yeah.
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Mike Linton
What should marketers be doing or people that want a career in marketing be thinking, given everything you've just said on the show?
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DJ Patel
So, number one, the superpower of marketers, in my experience, they have one power above all else. They come from the liberal arts and everybody else around AI and all the technology comes from the hard sciences, and they have not done a good job of exposing themselves to the liberal arts. That means we've lost human connectivity, we've lost touch, we've Lost the ability to inspire. The place where marketers, I think have the greatest challenge is they've always kind of said, oh, I don't do math, I don't do tech. Like you hand it off.
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Mike Linton
Not all marketers, but yeah, not all marketers, right.
- [31:49]
DJ Patel
But Mike, you're very far from it. You should have been a data scientist or if you were, you really were. And I've been always a data scientist, so, so. But like, you know, like what does it mean to really to, to, to use this technology as an asset, as a superpower? So some of the things I would do if I was a marketer, I'd be absolutely making sure I use this technology any chance I could get, even if it makes me 20% slower. Because like you don't become fluent in a language by just sort of being like, I'm going to be fast at sucks. It's a grind. You have to immerse yourself in it, number one. Number two is it allows you access to technology and coding in a way that we'd never seen. There's this kind of concept called vibe coding where you tell the answer, yeah, lovable, bold, all these things. Every marketer should be doing this. They should be creating their things. And then marketers have to also flex into the design space. They should be using Figma, which I'm biased to, or Canvas, you know, Canva or anything else where you're actually, you're like, you know, we have this notion of full stack developer where you're like, hey, you go from ideation all the way to deployment, you build everything. You single superpower person. Same way you, you have to be that as a marketer. You have to be the, you have to be the CMO all the way to the person writing copy. I think that you're not going to get budget, you will not get budget. The new marketing teams are going to look like two to three person shops. They're not, you're not going to have an army and you're not going to be have the budget to go get a massive team of consultants. The best people are going to be doing themselves and you got to, you got to be social media savvy to all the way, all the way through. And at the same time, the parts I think that a lot of marketers that I see now is they haven't taken the lessons, Mike, that people like you have learned from the school of hard knocks and the traditional way of doing things. And if you skip over that stuff, you're just going to repeat history. You're just leaving a ton on the floor.
- [34:13]
Mike Linton
So I hear you saying marketers, get deep, get involved, do it fast. You heard it here first. This brings us to our traditional last question. Funniest story you can tell on the air and or practical advice we haven't talked about yet. You can pick one or both, but you must pick at least one.
- [34:32]
DJ Patel
Oh, yeah, well, I'll tell one that's AI related. That just kind of shows the awesomeness and the sort of goofiness simultaneously. So Waymo just opened up in our neighborhood and so I was like, oh, we're going on date night. We're going to take a Waymo instead of. Because. Because you're not going that far, but you're going to get a drink. So you always feel bad with the Uber driver. You're like, I kind of made you.
- [34:56]
Mike Linton
Nothing says romance like a Waymo.
- [34:59]
DJ Patel
Exactly. So we're like, so we take the Waymo there. And then I'm like, but it dropped us off 18 minutes from where we should have been dropped off. Or an 18 minute walk because it didn't understand which side of the train tracks were on. But the saving thing is if you put kind of the customer service, it sends you back to the. It takes you back to the right. The right place.
- [35:22]
Mike Linton
All right, well, just as a service to our listeners, that is not dating advice from dj. That's just a story. So thank you, dj, and thanks to everyone for listening to CMO Confidential. If you like our content, please like share and subscribe. New shows are released every Tuesday and you can find everything on Apple, YouTube and Spotify, which include Colonel Mustard in the study with the job spec. What your CFO wants to tell you, but won't the AI application layer the Good, the Bad and the ugly? And of course, DJs earlier shows, one of which is titled is a high like taking the red pill or the blue pill. Hey, all you marketers, stay safe out there. This is Mike Linton signing off for CMO Confidential.