Uber Just Exposed AI’s Biggest Cost Problem

Eric and Neil break down why Uber’s AI spend is skyrocketing, what it means when tools like Claude Code become too useful to cut back, and why token costs may become the next big enterprise bottleneck. They also get into why AI may create more jobs than people expect, how smart teams should think about ROI on token spend, and why the companies that learn to scale AI efficiently will have a major edge. Need marketing help? Visit: https://www.singlegrain.com/ and https://npdigital.com/ Want to recruit great marketers? Find them here: https://marketingschool.io/hire Key takeaways ◾ AI gets expensive fast when teams find real workflow value. ◾ Token costs are becoming a serious budgeting problem for enterprise teams. ◾ More AI usage only matters if it drives real ROI, not just more output. ◾ The biggest advantage may go to companies that optimize token spend first. ◾ History suggests new technology creates new categories of work, not just displacement. Chapters 00:00 Uber burns through its AI budget 02:52 How teams are cutting AI costs 06:16 Why AI may create more jobs 12:28 How to measure real AI ROI 16:47 A business idea: return on token spend 18:09 What history says about AI and jobs 𝗔𝗕𝗢𝗨𝗧 𝗧𝗛𝗘 𝗖𝗛𝗔𝗡𝗡𝗘𝗟 Welcome to Marketing School, one of the top business podcasts with over 61 million downloads. Each episode delivers actionable marketing tips and strategies from two entrepreneurs who actually test what they teach. The show is hosted by Eric Siu, founder of Leveling Up and Single Grain, and Neil Patel, co-founder of NP Digital and one of the most recognized marketers in the world. 🎙️ Learn More About the Hosts Eric Siu – Leveling Up: / @levelingupofficial Neil Patel: / @neilpatel 📩 Free Resources Ubersuggest: https://www.ubersuggest.com/ Answer The Public: https://www.answerthepublic.com/ ✅ Subscribe for Daily Marketing Insights!

• 0:00Speaker 00

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• 0:46Speaker 00

  So the adoption curve tells you everything about what happened. In December 2024, 32% of Uber's engineers were using Claude code. By February 2026, that number was 63%. That seems a little slow to me, but anyway, that's not a gradual rollout. That's a product so useful that engineers pulled it into their workflow faster than finance could model the spend. Okay, that's a lot of employees, though. Uber has about 34,000 employees, and you're just roughly 15% of that. Okay, so all this to say, Neil, is this CTO, if I go back over here, so look, AI-related costs at Uber are up 6X since 2024. This is what we're talking about, and we're seeing this in our organization, yours too. CTO Praveen Naga's quote was, "I'm back to the drawing board." That's the CTO of a $144 billion company admitting that the tools work so well

• 1:29Speaker 00

  that his team can't afford to keep using them at this rate. So here's the thing, so he has to go back to his CFO and ask for a larger budget now. But to Neil's point, if this is working for you so well, you should be spending more. And here's the other thing, you might be thinking, oh, I can put this all on, you know, open source tokens. But if you're actively building things and shipping code, you can't put in an open source tokens, because you might need to rework it a couple of times, and the time you spent there is not worth it. You, like, chances are, if you're shipping a lot of this stuff, a lot of it's gonna have to be on frontier models, so.

• 1:59Speaker 01

  And there's an important thing here. They rolled this out in December, and by February, they had good adoption. By April, they went through all their tokens. I bet you there's a lot of terrible usage of Claude code within this organization. I don't mean in a bad way, it's actually in almost all organizations, where they're doing a lot of things inefficiently, and they're not optimizing for cost savings. That'll start coming out soon. Start thinking about it and then his budget from April will last the whole year and he won't need to go back to the CFO.

• 2:29Speaker 00

  We'll see. I mean, so it says the CFO problem here is now the bottleneck of AI adoption at enterprise level. The technology works, productivity gains are real. Uber's own data says seventy-five percent of code review comments are marked helpful by engineers. Okay, there's your thing, Neil. Seventy-five percent are helpful. The constraint is that the traditional annual budgeting was designed for tools with predictable perceived costs. And AI coding agents have usage curves that look like cloud compute bills from 2015, exponential until someone notices. Every enterprise CTO is about to have the same meeting. The tools are too good to pull back, the costs are too unpredictable to ignore. And the companies that figure out token cost optimization first will have a structural advantage over every competitor. Still running annual budget cycles. I'll tell you something, Neil. We've been playing around with token optimization this week, just on my own stuff.

• 3:14Speaker 00

  I'm trying all the models, Gemma four, Quinn, which is from Alibaba. I'm trying all these other ones. It's like they're decent, but they're still nothing close to what you get with Claude.

• 3:23Speaker 01

  Well, on our end, we're, so let's look at it from a business standpoint. We tend to create a lot of tools for marketing related purposes, all right? For ourselves, our clients, or, you know, just putting out there because tools get you more brand mentions, build more links. So we use Claude quite a bit. What we've found is our outputs are similar. And I don't know exactly what my team is using, but I saw a report on this. We're down in twenty-one percent end costs because we've been optimizing for efficiencies. So twenty-one percent savings over the last thirty days is huge. And I bet you as time goes forward, not only will the models get cheaper, but people will come out with solutions for optimization because this is a big problem.

• 4:05Speaker 01

  And I bet you our bill a year from now will be maybe like twenty-five percent of what it is today on a monthly basis.

• 4:12Speaker 00

  So I'll give you guys some practical things you can do and I'll give you my thoughts on this, Neil. So you guys can all use Open Router. So Open Router will help you route to the right models and they'll save, it'll help you save a lot of money. They take five percent of the, the, basically the spend. Because you're routing everything through them, right? That's one thing you can do. You can buy a local infrastructure. So the reason why I buy- Bought these DGX sparks is to see kind of how local inference will work and then we're gonna consider buying more and more. The thing is Neil, I think we're gonna token optimize, I think I mentioned it last time, maybe seventy-five, eighty percent goes through it, maybe, maybe for, for open models and then fifteen, twenty percent on frontier. Which is like, when I say frontier, I mean, you know, you're using Claude, Opus, like the latest version, right? Or using Mythos when it comes out.

• 4:54Speaker 00

  I think Neil, the costs are gonna come down, but what's gonna happen is usage is gonna skyrocket even more. And so what ends up happening is costs still keep going up because the usage is still unpredictable and because I see my team using it now. The ones that are getting pilled by it, they're like, we need more, we need more, because they see how I'm using it and they start use it that way. They're like, oh my god, right? And I'm like, oh my god, if they even start using it even like twenty-five percent in, in, in the way I use it right now, my costs still go up exponentially.

• 5:20Speaker 01

  Yeah, but I don't look at costs going up exponentially because at the same time, even though the models are becoming cheaper and cheaper. You're gonna have it to a certain point where some of the older models are good enough for a lot of tasks and you won't be using as many frontier models. So that I think will save a lot. B, and this is the big one. No business really cares about the cost if the work is actually producing a direct ROI. So if they're able to, if they grow their cost by ten X, but their revenue for that department. But their profitability and their revenue grows in total, a business is happy.

• 5:57Speaker 01

  Look, if you're publicly traded and you spent too much on AI credit, but you can show, hey, we're predicting twenty percent growth in revenue and we actually hit twenty-eight percent. And I know our profit for the quarter was supposed to be a billion dollars, but we had the same amount of people, yes, we use AI more and due to the revenue increase. Our profitability was actually one point two billion dollars. The market will reward you and your stock goes up. No one really cares if you're spending more if you can produce more.

• 6:23Speaker 00

  I, I just think this, and this actually, I have a thing that ties in with this. I just think we're all gonna be producing a lot more, just looking at how I work. You might say you don't work that hard. I still think you work really hard right now. But I think the way we, I think we're just gonna end up doing more. So let me, let me share this with you real quick. Cause I, I've kind of said this before, Neil, on this podcast. I think there's gonna be net new, there's gonna be more entrepreneurs in the world because you can do so much now. So this guy from Deal, remember Deal, the, the one that did the, the spy with Rippling?

• 6:54Speaker 01

  Oh yeah, the, the company that you can use to, I think it's like pay employees internationally or something?

• 6:59Speaker 00

  Yeah. Um, I think, I think they're a good company, but I, they did that whole spy thing. So he said P. Marker. So P. Marker is Marc Andreessen. Oh, look, hey, look, I'm cool with these guys. I'm, I'm homies. Uh, so look at this. So when a company becomes more productive, this is from Alex Boaz, I don't know how to pronounce it. So when a company becomes more productive, it doesn't sit still. It goes after more customers, enters new markets, builds new products. Productivity gives you leverage and leverage makes you want to do more, not less. Exactly what I just said. So no CEO in history has looked at a more productive team and said, great, let's shrink. They hire more. That's what we're seeing in our data. So we also tend to forget that new tech creates new jobs and industries. A job title that didn't exist now demands 70K people, 283% year on year.

• 7:43Speaker 00

  For jobs that directly experience the productivity gains, demand should surge as CEOs watch how productive these people are and how much they, more they could be doing. So if you see this over here, Neil, you want to read it?

• 7:55Speaker 00

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• 8:30Speaker 01

  So AI trainers outpacing every job in 2025 at 283% growth. I can't, I can read 2025.

• 8:38Speaker 00

  I'll call out the rest, Neil. So, um, thank you for reading that part. So 2025 starts, you have 18,000 AI trainers employed globally. Now that's 70,000, but I, Neil, I never even thought about this. Like, you're gonna need more AI trainers, obviously, right? AI engineers and PM roles are actually up 400%. So you have 15,000 open AI engineering jobs, not the company, just open AI jobs on an 1,135 open AI product manager job. So it's going up, right? So I think, Neil, we're gonna see more entrepreneurs and then I think people are going to, people are gonna realize that creation gives them a sense of meaning and purpose and they're gonna wanna do more of it. And I think we're just gonna want more, more, more, Neil. That being said, I, I don't disagree with you that for more basic tasks like doing one plus one, maybe it's, it's, you know, that's gonna be free or close to free.

• 9:23Speaker 00

  But I think we're always like, maybe 10 to 20% of the time, you're still always trying to build new stuff and that still eats up a lot of budget because you still want the smartest models.

• 9:31Speaker 01

  Yeah, so I'm in Brazil right now as we're recording this. And yesterday I was at a really large publicly traded company's office in Brazil. They're global. To give you perspective, they own three floors of an office space. They're not the biggest floors, they're normal size, like, you know, just good sized buildings, but they have three floors or that's what they take up. I don't know how much they spent on their new office. If I had a guess, 50-ish million dollars, okay? Which is really, that's a lot of money for like decorations and technology and all that kinda stuff, right? And I'm in Brazil, so if you take the currency exchanger, that's roughly like 250 million USD equivalent. That's a lot of money. Because remember, people get paid less in Brazil as well.

• 10:15Speaker 01

  So for a company to spend around 250 million in their currency and employees get paid, you know, proportionally, like US employee getting 100 grand, they get 100 reais, so that would be like 20,000 US dollars.

• 10:28Speaker 01

  And I was talking to the whole marketing team and we were talking about strategy for Brazil as well as global strategy. And the one thing that's consistent with them and almost every other company I talked to, no one's thinking about shrinking or laying off employees in marketing or anywhere else. Everyone's talking about, hey, everyone's using AI, it's causing companies to move faster, we need to move faster. How do we adopt these tools in the correct way to be more effective? How do we focus on the right KPIs so that way we actually see revenue growth? And not just increased costs in AI and no change in the top line. But everyone has this mentality that we've been seeing recently. Because if you go back a year, Eric, I think you'll agree with this.

• 11:10Speaker 01

  Everyone's like, oh my God, doom and gloom, everyone's gonna start getting laid off, tons of jobs are gonna be displaced. At least in the corporate world, we're not talking about flipping burgers or stuff like that. Even in the corporate world, people were afraid of that. But we're seeing the opposite, we're not seeing sales reps get canceled, marketing employees get canceled. We're seeing them stay roughly the same, sometimes even increase. But everyone's like, how do you get 2X the output and productive output? Productive output doesn't mean, oh, they did 2X more work. It's more so, they did 2X more stuff that actually moves the bottom line or the top line. And that's what we're seeing, and if you don't keep up with the competitors, you're gonna lose. So you can't actually cut, you just gotta figure out how to move faster with what you have.

• 11:52Speaker 00

  You're not using your microphone.

• 11:54Speaker 01

  I'm not.

• 11:55Speaker 00

  That's right, okay, anyway. Neil's gonna get cut, so, okay, so.

• 12:00Speaker 01

  You wanna know what happened?

• 12:01Speaker 00

  What?

• 12:03Speaker 01

  So I had a, on my last trip, come back from Toronto, I keep it in my bag. So I have protein powder in my bag, okay? Like, literally, I, you know, travel with protein powder.

• 12:13Speaker 00

  Yeah.

• 12:14Speaker 01

  Vegan protein.

• 12:14Speaker 00

  Show the brand, that's Legion, right?

• 12:16Speaker 01

  Yeah, it's Legion.

• 12:16Speaker 00

  We should, we should give a shout out to Legion, there you go.

• 12:19Speaker 01

  Great product, okay? So I didn't know that they had to check it, like, they checked to see if there's.

• 12:24Speaker 00

  Powder, yeah, yeah, yeah, yeah.

• 12:26Speaker 01

  I had my mic on top, the rep pulled it out. And then boom, it hit the ground and it got messed up. So I ordered a new one from Amazon, but I was pissed. But what can I do? You know, so you can't be like, hey, TSA rep, you owe me.

• 12:41Speaker 00

  You know, you know what's funny? Sometimes I would get pulled aside from TSA and they'd, they'd take the mic out. I get stopped for the mic because they think it's a grenade. Yeah.

• 12:49Speaker 01

  I don't get the grenade. They would tell me, because you know, when they say, take all electronic devices out, I would say maybe like thirty, forty percent of the time, they stop my bag and they're like, you didn't take out your technology. And I'm like, it's a microphone. You just said laptops. But electric toothbrush? They never make me take out. But for some reason, the mic, it gets flagged.

• 13:09Speaker 00

  Yeah, the mic gets flagged quite often. Anyway, real quick, if you want to acquire customers faster and more efficiently this year with the latest strategies and tactics, then check out singlegrain.com. That is my ad agency. Again, www dot singlegrain.com. Check it out. And if it seems like a fit, we'll get in touch and help you with a free marketing plan. So Neil, I, I think I have, I'm one, one point to, to bring up, but it'll, it'll come back to me. So I, I want to bring up these charts over here. So these charts are from code two. We've, we've kind of covered them before, but I think it's worth bringing it up because the, the key thing here is will AI lead to mass unemployment? Oh, I remember what I was gonna say. So the way I think we might measure, this is going to be an experiment for, for, for us, Neil. So the way we're going to measure AI adoption

• 13:52Speaker 00

  is we have Claude teams right now. We can see usage in Claude code. We can see usage in Claude cowork. So we want to see, one, we want to see usage, but we also want to see the, the pull request coming from GitHub. Now, those two things can be gained. If you're just shipping a bunch of pull requests and you're just spending a lot, you could, it could be stupid spend, right? To Neil's point. So the thing that you saw earlier from Uber, where they're, they're saying seventy-five percent of engineers said the code was helpful code. We might have something like that where the engineers, or maybe the people, the managers are checking and saying, hey, like you did all this, you're engaged, but what have you actually built? Can you screen share with us? Right? So my point of saying this is that you can have these metrics that are maybe easy to record, but they might be easy to game. You need to have a pairing metric next to it to make sure that what you're

• 14:35Speaker 00

  doing is actually quality and it's not just a bunch of slop, which is what my homepage got called, even though it converts. So. Yeah.

• 14:41Speaker 01

  Eric's homepage was not slop. That's just what, again, what someone else thinks. I'm neutral. His homepage was crap. I would tell him. Yes, it's perfect from a design perspective. No, but get it out there. Find out if the model works, if the marketing message, you know, converts. And then go and adjust it and fine tune it later on. Once you've figured out how to really make the funnel.

• 15:01Speaker 00

  You know what I've learned from this, this Neil, uh, right now is, is when the, like you and I, we grew up during the internet, uh, era. But we weren't exactly working at the time just yet. And what I've learned is when the demand is there, it doesn't matter. Like you're gonna get pulled. The demand is gonna pull you and like, who cares? Right? So, um, okay, check this out. So this is, uh, done from code two. So literally they had a post about a month ago saying, will AI lead to mass unemployment? Okay. And so I just want to call out here, the, the ROI that we want to look at, instead of return on investment, we want to look at return on displacement. ROP, R O P. Okay. So when you look at agriculture in 1912 million agriculture workers, 41% of workforce. You go all the way to 1970, it's 2% of workforce, 3.5 million workers.

• 15:46Speaker 00

  But net, net, what happened was agriculture lost eight million jobs from 1910 to 1970. And then new industries gained 46 million jobs. Okay. So 46 divided by, by, by, by 12 over there, five X, right? So there you have it.

• 16:01Speaker 01

  I see the same thing with engineering. A lot of like, if you go back to the Uber example.

• 16:05Speaker 00

  46 divided by eight. Yeah, go ahead.

• 16:07Speaker 01

  Still, it's amazing, right? But if, if you look at like the Uber example and how they're talking about 75% efficiencies, the, the, or 75% approval, like they found it being helpful. The first thing that comes to my mind is outside of cost. When you're using it, yes, you're releasing more, but is that releasing more improving, uh, LTV customer, you know, repeat visits or repeat usage? Uh, you know, conversion rates, new potential onboarding or revenue, like all those kinds of things. And what you'll, what I believe is you'll end up seeing is you'll see some displacement because people are like, you're using all this A stuff. Do we actually need all these people?

• 16:47Speaker 01

  And B, I think you'll also see in addition to cost going down, people being like, you're using A for all this stuff and this is great. And you did. You know, fifty things this month versus the normal ten. But out of the fifty things you did, only six of them actually helped drive a return. While normally, when you do ten, four of them drive a return. So you did fifty percent more things on that end, but you did five times, five X the amount of output. So then they start fine tuning what is, things are being used for. And you're gonna start seeing, uh, not as much usage in certain areas, more usage in others. Employees getting displaced because they realize they don't need them all. And then some of those employees go on to other sectors, other fields, uh, other jobs. And it's the same thing in marketing.

• 17:32Speaker 01

  Dude, the amount of customers that are asking us to build them agents right now is ridiculous. And it just goes to show, people are like, oh, you're gonna have to get rid of people. Well, we're, at the same time, we're getting new requests that are requiring us to hire people or re-shift, we're replacing different people.

• 17:47Speaker 00

  So he- here- here's what I'll call it. I actually went and saw, guys, here's a, here's a free idea for you guys. So when what Neil and I just said, this is a problem. We're all gonna be spending more on tokens. We would like to track our return on token spend, our, our rots, return on token spend, okay? So if you can figure out, and I just went, I would just went to my agent. I asked, hey, can you build something that tracks return on token spend? Because like, that is something we'd all spend on, like, so we can optimize our costs, right? That's a smart idea. Someone take that idea, Neil will invest, I will co-invest with Neil. Uh, I'm speaking for Neil here. So anyway.

• 18:20Speaker 01

  I know, it's brilliant model.

• 18:22Speaker 00

  You look at this, okay. By the way, Neil, remember, I think it was ninety-eight percent of people used to be farmers. And then you go all the way to two percent. But this displacement took a long time, nineteen hundred and nineteen seventy or so, okay? I'm not even done here. There's a, there's another one over here. Spreadsheets, for example, okay? The return on displacement with spreadsheets. So people are like, oh, my God. Uh, so bookkeepers, like, you see this in, in the blue over here, it's going up and up. So bookkeepers, and then visit count comes out, Lotus one, two, three, remember that one? Uh, Excel, and then it's the bookkeepers start going down. But what happens? Accountants and auditors starts going up, and then financial analysts starts going up. So four hundred K bookkeepers disappeared at the advent of the spreadsheet era. But one point three million accountants and financial analysts were added. So we're gonna be doing different things. And again, we've said this before, don't hire humans to do robot things.

• 19:08Speaker 00

  And more human thing, tasks that we're used to are being taken over by robots. That's okay, because nobody wanted to do those things in, in the beginning, anyway.

• 19:16Speaker 00

  I have one more Neil.

• 19:17Speaker 01

  Go for it, share the next one.

• 19:18Speaker 00

  Here's one more. So, oh by the way, look, uh, New York Times in 1973 predicted ATMs would cut bank teller jobs by 75%. Instead, teller employment grew by 81% from 1970 to 1988. Um, that's because way more banks open. Here's the other thing, radiologists, oh my God, 10 years ago, I think one of these AI, uh, like, um, you know, speakers was like, you know, radiologists, that job's gonna go away. What happened? There's more demand than ever for radiologists. So I think, yes, I think short term, there's gonna be job displacement for the people that don't pick it up. Those are the people that I'm sensationalist, that I'm talking about, that like, I am genuinely concerned for those people, right? Because there's gonna be some short-term displacement. Long-term, that's why I keep saying Neil's been saying this too.

• 20:01Speaker 00

  Everything's gonna be okay because you see, you can see that history rhymes. It doesn't repeat, but it rhymes.

• 20:07Speaker 01

  Speaking of ATMs, it was funny on, I, I, I saw a lot of the original ATM ad campaigns from back in the day, but, um, you know, if you haven't Google them, you'll see them, they're kind of entertaining. Do you even use ATMs yourself? Like, I never use them.

• 20:21Speaker 00

  Only when I go to Vegas, when I lose money.

• 20:23Speaker 01

  The fees are so high.

• 20:25Speaker 00

  Yeah, but it's okay. I pay it anyway because I'm at Vegas.

• 20:29Speaker 01

  I don't even have an ATM card because I'm worried about fraud.

• 20:33Speaker 00

  You don't use an ATM, you just use your regular card.

• 20:37Speaker 01

  What do you mean?

• 20:38Speaker 00

  So, okay, this is when you're being degenerate like me. Guys, don't be like me. Okay. So let's say you're, you're gambling, for example, your ATM card has a limit on it. So you don't use a debit card because there's a limit on it, right? And then you can call them to try to break your limit, but that's annoying. So what you do sometimes, if you get desperate, is you just do a cash advance with the card and you end up paying even a bigger fee.

• 20:56Speaker 01

  So I have a credit card, I have Amex. You're saying with American Express, I can go to ATM and put it in and get money out?

• 21:02Speaker 00

  So I know what, here, let me speak on the debit card. The debit card piece first, I know you can get a cash advance. I think you could do the same thing with a credit card too, but I, if memory serves me right, I haven't done this for a while. This is only during my degenerate times when I gambled a lot, so.

• 21:14Speaker 01

  But and Eric's talking crap about himself. He's actually a very good gambler and overall has made money. He typically pays poker and he usually comes out winning.

• 21:23Speaker 00

  No, but when I play stupid table games, I lose a lot. And this is in our twenties or so, like you're you're like you're actually partying and drinking and stuff and being stupid. So like, you know, we don't do any of that anymore. So.

• 21:33Speaker 01

  Yeah, Eric came and visited me in Vegas one time and we all did dinner with his friends in Aria. And I remember Eric was gambling because we were waiting on some of his friends and we were there early. And one of his friends comes to me, he's like, well, Eric just lost five grand at a table playing blackjack, right? And even though it sounds bad and a lot of people were shocked, his poker winnings more than make up for all his table game losses. He's actually very good at poker.

• 22:01Speaker 00

  Poker, by the way, poker is great for poker is great for business. All you you learn a lot from it. You know, you know, remember your your brother in law, Heaton? So I was just talking about how poker has been so good for me and I tweeted it. And he's like, while you're playing poker, I'm playing business. So Heaton tweeted that at me, right? I was like, oh, motherfucker, right? So that's part of my language. And so you know what I did? I was like, well, Chamath doesn't think that Chamath thinks it's good for business and da, da, da. And then Chamath responds. Chamath's like, hundred percent, you know, poker has been great for business. It helped me with everything. It helped me with my my return on investment. I was like, that's right, Heaton. That's right. You take that. So anyway, that's just a fun story. So.

• 22:34Speaker 01

  Uh, wait, to go back on it, um, on the poker thing, it's not even just great for like strategy or whatnot. If you ever want to get into poker, I'm not big on poker. It is amazing networking. Like just from that aspect, the people you meet at like home games, you'll find that you can end up doing business with a lot of people if you are playing in the right games.

• 22:56Speaker 00

  Yeah.

• 22:56Speaker 01

  So I just want to put that out there for anyone who's thinking about gambling.

• 23:00Speaker 00

  I I can speak on that, Neil, because I actually do go to these home games. So one of the home games has like, uh, there's a few entrepreneurs there. Actually, everyone's an entrepreneur, entrepreneur there. There's some bestselling authors there as well. You would know the names. Um, and so we play like once a month or so. And then we're even talking about going to the World Series of Poker in July to play. Um, but it's good because we we end up talking about business. We talk about AI. We talk about, um, and and we just, we have a lot of fun and we we. I will say this too Neil, it's good for networking, that's number one. You just gotta make sure you're hanging out with the right crew. Don't, don't hang out at those like underground poker games in LA. Probably don't want to do that. But the other thing is you learn how to manage your bankroll. You learn how to manage your emotions a lot better too. And you learn when to bet hard and press your chips versus when not to. So Neil, I gotta give Neil a lot of credit. Neil knows when to press hard.

• 23:44Speaker 00

  When he sees an advantage, he presses really hard. I'm not gonna give examples here, but very hard. More like harder than you would ever imagine, right? I'll just leave it at that. Even when it comes to SEO. So all that to say is poker is good for you for, you need all these things. You need to learn bankroll management. You need to know who's, who's the fish at the table. You need to know when to press hard. You need to know what your odds are at every stage of, of the game. So, and then to your point Neil, it's great for networking too.

• 24:12Speaker 01

  Yeah, when you said you, you play with a bestselling author. Is this bestselling author a Stanford graduate?

• 24:18Speaker 00

  Uh, no.

• 24:19Speaker 01

  Okay, so it's not the one, not the one that posts a lot of political stuff on X.

• 24:24Speaker 00

  I don't even know who you're talking about.

• 24:26Speaker 01

  You do.

• 24:27Speaker 00

  Who? You can write it in chat, you can write it in chat.

• 24:31Speaker 01

  Oh yeah, let's, where's the chat button?

• 24:33Speaker 00

  You can write in chat, okay. So while, while Neil sends me.

• 24:36Speaker 01

  I can chat with you.

• 24:37Speaker 00

  You can? Okay, whatever.

• 24:39Speaker 01

  Oh yeah, now I can. All right, check this out. Yeah, it's not that person, but that's what I assumed when you said bestselling.

• 24:44Speaker 00

  Oh, no, no, no, no, absolutely not. No, no, no, definitely no. So anyway, that's a good place to end it. We will see you all tomorrow. Don't forget to rate, review, subscribe.