← My First Million
My First Million
No Small Boy Stuff, Investing Wisdom from Nassim Taleb, plus ChatGPT Prompts We're Using
01:10:22
Loading summary
Transcript171 lines
- [00:00]
A
What's up, Sam? Hey, you like the. You like the fit?
- [00:03]
B
Where did you get that?
- [00:04]
A
Our boys at Jambi sent it over the no small boy stuff Christmas edition. I feel like I could rule the world. I know I could be what I want to.
- [00:15]
B
I put my all in it.
- [00:16]
A
Like days off on a road. Let's try.
- [00:19]
B
You know, it's pretty funny. I actually use the phrase no small boy stuff, like, kind of a lot.
- [00:23]
A
Yeah, I remember the guy who tweeted it. I think his name was Bengali87. And this was back in 2022. He said, best business slash entrepreneurship podcast out there. Big money. That is no small boy stuff. I love that.
- [00:37]
B
And that's basically the phrase that we use for this podcast a lot. No small boy stuff. But frankly, I kind of use it a lot in my life. Like, I don't know, man, that small boy kind of stuff, like, it's sort of like in succession where they say you're not a very serious person. It's kind of like that.
- [00:52]
A
I also use the phrase, but I never say it because saying it to me feels so cringe. But I think it like a thousand times for every one time that I say it. And every one time I say it, it feels so awkward to me. It's like saying. It's like saying, just do it in the Nike slogan way or something. You don't really want to say that. Hey, guys. Yeah, this in the fourth quarter, we just, Nike, baby, just do it. And then they'll be like, what? Why are you saying slogans at us? But I do think it a lot. It's actually, I think it a lot meaningfully affected the trajectory of my life is to use. Use this phrase. And because there's so many situations where there's like a little small boy response, oh, I'll. I'll behave like a little small boy in this situation.
- [01:31]
B
Or yeah, that phrase. And what Amjad said recently about what will make the better story that has had a fairly meaningful change just in, you know, it's only been a few weeks, but like, I, I think about that actually a lot.
- [01:44]
A
He also said something else where he was talking about he was basically so comfortable with this like 10 year plus odyssey that he's been on building this. And we're like, wow, you've been doing this for so long and wow, you did this for years before you had really any recognition or any funding. And he just kept going. And he was just like, yeah, I persist. He was just like, yeah, he's like, I think that's What I do. He's like, I. I didn't really think about it that consciously, but, like, I'm pretty comfortable pushing the boulder for a long time up the mountain. And I goes. I realized, like, I guess that's my, like, competitive advantage. Like, I'm in it for the long haul, and I'll just persist. It's like. And we were both, like, small. Like. Yeah. A quick intake of breath.
- [02:28]
B
What do you want to start with today?
- [02:30]
A
All right, I got a good story for you. So there's this great Naseem Taleb quote or tweet where he. Taleb, who wrote Black Swan and Antifragile, he's kind of this, like, contrarian thinker.
- [02:41]
B
Was he, like, a successful hedge fund investor? But he was successful because he had an interesting life philosophy, and then he became like, a thinker. Is that his.
- [02:50]
A
I believe so. I believe so. I believe he's, like a successful trader. And part of his success, unless I'm mixing him up with somebody else, part of his success was that he. He noticed that humans are. We would rather win frequently in small amounts and then lose a bunch when we're wrong. It's like gambling. It's like playing craps, right? You know, one roll of dice, you win a little money. Two rolls of dice, you win a little bit of money, but eventually you roll a seven, and it wipes out the entire board. All of the chips go away. But he's like, humans are more comfortable with that, versus, he was willing to bleed a little every day and look stupid every day for years. But then when his big. You know, sort of like the big short, when his big bet pays off and this contrarian bet pays off, he makes back all the money in one day.
- [03:35]
B
Got it.
- [03:35]
A
And I think that's his story. If it's not his story, his book is talking about the guy who does that. So I can't recall if it's him or if he's the author or he's the author and the hero of the story. Okay, so he. Taleb tweeted this thing. He goes, I conjecture that if you gave an investor the next day's news 24 hours in advance, he would go bust in less than a year. And this is basically the Back to the future premise, Right? So I don't remember the movie Back to the Future, but what's his name? Biff.
- [04:07]
B
Or whatever Biff he finds. Like the sports betting book that tells all the winners for the next decade of games.
- [04:13]
A
Exactly. He goes back in time, and then he just becomes a gazillionaire because he knows the scores. Okay, so, like, let's take. Yes, if you knew the exact score, you'd have to be pretty dumb to not win. What these guys did and what Naseem Taleb was saying is, I could give you the news, so not the price change, but I could give you the news. And I bet you would trade incorrectly, dude.
- [04:34]
B
I think about this all the time, by the way. All the time. I think if I know what I know today, But I was 10 or 50 years ago, how would I capitalize on that? I think about that all the time.
- [04:45]
A
Right. And usually the easy answers for that are, I just buy Bitcoin. I just buy Google. Yeah, it actually wouldn't be that hard if you could convince yourself, hey, do this one thing and just shut up and trust me. Don't touch it. For 15 years. Now, what these guys did was a little bit of a different experiment. So what they did was they took 118, as they call them, adults trained in finance, and they did the crystal ball test. And the crystal ball test was as follows. They said, we're gonna give you money. So they gave him $50 each. So I said, you have 50 bucks and you get to place trades and you're gonna trade. But we're gonna. Before you make a trade, we're gonna show you the front page of the Wall Street Journal, the actual front page of the Wall street journal from 15 random days in the last, like, I think, 20 years or something like that. Okay? So 15 random days, we're gonna show you the front page of the Wall Street Journal, and that's a Wednesday edition, and you're gonna place the trade that would execute on the Tuesday. So the day before that, news. So you had the news at 24 hours in advance. They blacked out the stock prices so they wouldn't just show you, oh, Johnson, Johnson's up 20%. Right. But they would say, like, there would be the headline about Johnson and Johnson. They would just redact the actual stock price.
- [05:53]
B
Johnson and Johnson beats earnings.
- [05:55]
A
Beats earnings, Exactly. Record job, record unemployment. Record jobs, posting, Fed indicates, blah, blah, blah. Right. Things like that. And by the way, anybody can go play this game online. There's like a link to it. We'll put it in the show notes, but you can go actually do it yourself. I did it, too. There's a couple other caveats to this when you go do it, which is it's not just a buy and hold, because what I was going to do, I went and did the thing. I was like, oh cool. This is news from 15 years ago. I'll just put all my money in buy and I won't trade. I won't do anything else for the next 15 years. I know there is a bull market so I don't need to be smart. But the way that this test was designed was the trade executes and you either go up or down that day. So it's kind of like the trade closes that day, you know what I mean? Like you get one day gain based on the one day news. Okay? They do it and the results are not good, as you might expect. Otherwise I wouldn't really talk about this. So the results are not good. Half the players lost money even having been given the news. One out of every six players lost everything. And the way they lost everything was they let you trade on leverage. So you can trade up to like 20x leverage if you want to in this thing. Like an options trader could. Or you could just trade or you could skip. You don't even have to trade any given day. You could just say pass. I don't, I don't feel confident.
- [07:10]
B
Sample headline would be like an example trade would be, they would see something that says like Fed is going to cut rate today. I guess you would assume that the index is going to go up like a couple of percent. So you would bet on the index.
- [07:21]
A
Or bet on what is basically the s and P500 or it's the, the 30 year treasury. So you could best, best you bet on one of those two things. You bet you buy the SP index for that day. Or you could short a bond. You go long or short, or you can go long or short the bond, right? So that's, let me just show you an example. So like this is the Wall Street Journal that they, the article that they show you. So it's Obama does something. And then you see this business and finance section and talks about Rupert Murdoch. Chesapeake Energy says that their CEOs gonna step down, auto sales are up. Homeland Security says blah blah, blah, right? So there's all this, there's all this news. And so you then go here and you place a trade. So you say, all right, I'm going to go in this, in this little game here. You can see my screen where it gave me a million dollars. So I'm going to trade and it says today's movement. I, you know, I bet a million dollars. So I use my full stack with no leverage. And the day was up 0.62%. So I got an extra $600, right? Then it gives me the next one and it says, oh, there's a, there's a deadly plane crash. Iran is doing some shit. Okay, cool. Blah, blah, blah. Kraft is in talks to acquire this Brazilian company and they're just blacking out any of the stock price news.
- [08:35]
B
Right?
- [08:36]
A
So you read this and you can decide what you want to do. And you do that over and over and over again. So 15, 15 days in history. And they tried to do it as 15. Like they did. A third of the days were like Fed quarterly meeting days, a third was jobs reports and a third was complete randomness. And they didn't. They're like, we're not trying to trick you. There's no, we're not like cherry picking like misleading days. These are just actually like random front from pages.
- [08:59]
B
Okay, this is an awesome experiment.
- [09:02]
A
And so, okay, so back to the results now. So like I said, half the people lose the money. One out of six lose everything. Because they got over leveraged. The average person was only able to gain 3.2%. So even being given the news during.
- [09:17]
B
That era, the market was up on average, I think 15% a year over the last 15 years. I don't know when this was done.
- [09:22]
A
Correct, correct. But again, these are like one day trades, right? So you know, you're not just like.
- [09:26]
B
Buying and holding for, oh, it was for 15 days. The experiment was a 15 day experiment.
- [09:30]
A
Exactly.
- [09:31]
B
Got it. Okay.
- [09:32]
A
And the. And so, okay, now why. Right. There's two ways you can lose in, in investing. One is you bet wrong, meaning you pick the wrong direction, you think it's going up, it actually goes down. So basically, even given the news, they were basically only able to bet the direction correctly 51% of the time. So it's the same as if, you know, you just flipped a coin, you would have been right the same amount of times as you were being given the actual front page of the Wall Street Journal. Okay, so information doesn't lead to actual insight, especially news. The second thing is that why did they do poorly? They bet sized very poorly. So when you had an advent, even when you were correct, people didn't size up their bets enough. And when they're incorrect, they sized up their bets too much for the level of conviction that they had. And you know, this doesn't go in line with what people think. So they surveyed people separately and basically 70% of people thought that even if they got the news, you know, sort of like basically they thought that even four week old stale news would be predictive. And you know, 70% of people thought that. But in this case it just showed that even, you know, one day fresh news doesn't even really help you. Okay. So then they went and they did an extra experiment. They go, okay, maybe those 118, you know, financial trained adults, maybe they're just not the best of the best. So they went try to find the best of the best. The best of the best actually did better. So they went and found five people that were, you know, hedge fund guy, the head of trading at a top five bank, seasoned macro traders. So they are used to trading on this type of news. They're considered the best in the world at this. And they actually did better. So what they did was all of them finished with gains. So all five finished with gains. On average they were up 130%. And they also didn't bet on one out of every three news things. One of the big ways that they were better was they just didn't bet all the time. Whereas the casual was too active. Okay, what else did the pro do differently? They were only right 6% more. So, you know, if the, I think if the, the, at the, the, the test group was right 51% of the time, if it's going up or down, these guys were only right 57% of the time. It wasn't like they correctly interpreted it. But when they were right, they bet size properly and they never risked too much of their bankroll to where they couldn't recover. And so isn't that amazing that you know, only being, you know, 6 to 10% better at your predictive ability, but would yield a much bigger result? Right. 3% average gain for the test group, 130% average gain for the, for the pros. So it's these small edges that can make a huge difference when you apply leverage properly. Which was the, the bet sizing.
- [12:14]
B
And what's the takeaway that Nassim, Nassim said? Which is. Which is what?
- [12:20]
A
Well, he was saying it in a polarizing way. He goes, I conjecture if you gave an investor the next day's news, he would go bust in less than a year. And, and this kind of, this basically showed that one out of six would go bust because they would get overzealous around this perceived edge that doesn't exist. And on the whole most people would just do worse than if they didn't have the news. It's no better than random. Right? And that's actually one of his books, Fooled by Randomness. And at the end they use this quote by Ray Dalio in there. This is a great quote. It goes, he who lives by the crystal ball will die eating shattered glass.
- [12:55]
B
Dude, that's insane. So good. It's weird that multiple smart people come to that conclusion that I never would have come to. Like I, I would have thought, like I, I guess everyone have thought that if you know the future or you know the news, you absolutely are going to outperform.
- [13:10]
A
Exactly, exactly. The counterintuitive wise conclusion. Um, let me tell you one, one other related one said there was one other story here that was kind of interesting. There was a real world version of this where a hacking group got access. They hacked the press release system so they had access to the next day's press releases that companies put out when they have like major announcements, earnings results, et cetera. They got access to all of the press releases that were coming out the next day and they were using it as like their own form of like you know, home brewed insider information.
- [13:45]
B
Right.
- [13:45]
A
They were able to get insider information and so they could place a bet in the market overnight or the next morning. And that's like simultaneously.
- [13:51]
B
That's like a 12 hour leading indicator maybe because like if you're, if you're going to fire your CEO, you submit the press release maybe at 4, 5 or 6pm on a. Went on a Thursday and then 9am on Friday you announce it or, or the, the wire goes live.
- [14:07]
A
Something. I don't know the exact timing. I would imagine that it's a, it's a tighter window than that because there's too much leakage. But even a 12 second advantage would be in a huge advantage. If you knew 12 seconds ahead of time what the news was about to be. You could just push the button. Right? That's all you got to do.
- [14:21]
B
That's like an interesting like you know, like HubSpot for example. Whenever they have a, that I'm a shareholder of, whenever they have like an earnings I like I know when it's going to go live. So someone is like writing that and they've submitted it to. I forget what the PR com, what the thing's called.
- [14:36]
A
It's the popular PR newswire or whatever.
- [14:38]
B
Yeah, like whatever the popular thing is that is kind of an. I did. I never even realized that actually.
- [14:43]
A
That's why there's rules. Right. When I was at Amazon, you couldn't trade the stock in a. There's a window, there's like a frozen window. So X days before the announcement you can't make any trades.
- [14:53]
B
Oh, I know that but I'm Saying the employees of the pr.
- [14:57]
A
Oh, right, right, right. They probably have the same. Right.
- [14:59]
B
Because I. I didn't even think about that as a leak.
- [15:02]
A
I. The. When I. When I accidentally did that trade and then I had to go to the.
- [15:07]
B
What were they? Like, you're an idiot.
- [15:10]
A
So I. I'm like, I've learned about this afterwards, right? I'm a startup kid. I don't know anything about this. We get acquired. I, you know, I make a trade. And then I'm like, oh, well, it's a trade. So we're at a subsidiary of Amazon, right?
- [15:21]
B
Like, you bought Amazon before you sold to Amazon?
- [15:24]
A
I bought Amazon stock. I bought more Amazon stock or something. Or I sold some Amazon. I don't remember what it was. And I. I was like, oh, I just. Did I just. Insider trade. Did I just get my hands dirty with a little big boy business? And so I'm like, oh, what do I do? They're like, you need to go speak to the general counsel. And I was like, what? So I get a meeting with the general counsel. Urgent, Urgent. Possible. Possible big money move made. And I send the email. They get me a meeting stat. I go in and he's like, so what. What happened? And I was like, I went and made a trade. You know, I'm in the window, and, you know I'm an executive, so handcuff me. Take me away.
- [16:02]
B
I'm a bad boy.
- [16:04]
A
I've been a bad boy. Take me away. And he's like, so how much did you. And I was like. I was like, yeah, it was like 150 grand. And he was like, it's okay. You just. My lunch is outside. Can you bring it in before you leave? He was like, this is for actual execs at the actual company who make actual trades. I was like, oh, okay. Gotcha, gotcha, gotcha. Let me go sit down.
- [16:28]
B
That's actually hilarious. He just, like, totally dismissed you. But what about.
- [16:33]
A
Let me finish the story about the hackers. So let's put you. Let's. Let's test your criminal mastermind, which I love. I love doing this. By the way, how would I. How would I cheat if I was gonna.
- [16:42]
B
By the way, you know that it's always. The women always think to themselves, how would I get away from this bad person trying to hurt me? And the men always think in this. In the there, they align with the criminal.
- [16:51]
A
Would I be the bad person?
- [16:52]
B
Yeah, like, how would I get away with this crime? That's like. I realized that after watching a lot of true Crime. And so go ahead. I like this experiment.
- [16:59]
A
So you're the hackers, you get this. But here's the problem. You, they're like, sam, we got it. We hacked them. You know, Dave over here in the corner did it. He got into this. We got rude access. And they print out all of the press releases coming out, but they put it on your desk. They're like, hey, we got like an hour, we got to make a trade. And now there's 60,000 press releases on your desk. What do you do?
- [17:21]
B
I guess pick like a random five and hold and act on those as soon as. Yeah, I mean, that's a very challenging situation.
- [17:28]
A
I guess it's a challenge.
- [17:30]
B
The first five. And if it's good news, buy the stock. If it's bad news, somehow short it. But I don't even know how to do that. So I guess I would only find like the five good news ones. Right?
- [17:40]
A
You're like, I think I would still just end up holding the index fund Vanguard. I think I just stay doing exactly what I always do. 8020 stocks and bonds, baby. So what they ended up doing was they were like, all right, you sort of need to do a search function to figure out what news affects the price the most in a positive or negative direction. And I think what they figured out was that it was merger announcements that would be the highest kind of like volatility for the company that was getting acquired because it almost always gets acquired at like a 50% premium to the where the stock was trading. And so I think what they realized was we need to be able to quickly discard 98% of the news and information because it's noise.
- [18:20]
B
Right?
- [18:20]
A
Which goes back to the same experiment. Right? Most of the news information is noise. The secret is figuring out what is actually signal. And most of us can't do that. And we overestimate our ability to figure out signal versus noise. And so they figured out the signal. It was these merger things. And even they were only right in their predictive ability about 70 something percent of the time. It was enough to make hundreds of millions of dollars very quickly before they got caught for doing this. And then they all went to jail. But isn't that cool? Also, that's the ending when we sold.
- [18:52]
B
To Hub, when we sold the HubSpot, I think the share price, I think it was 350. And then like the week they announced it, it went to like $460 or something like this. Anyone can go back and look at it. It was February of 21 and damn.
- [19:07]
A
Sam the needle mover over here.
- [19:09]
B
Well, so that. That stock price went up, like, I guess that's a market cap of like one or two billion dollars. And I remember going to kip the cmo, I go, you're welcome. He's like, oh, yeah. It was this acquisition that got mentioned one time in our earnings call. It just barely. It wasn't the fact that we had just announced that we grew by 45% and have been compounding growth of, like, this, this, this.
- [19:34]
A
And I was like, yeah, causation is difficult to prove.
- [19:38]
B
I agree. I'm like, you don't understand. Can I. You all right? So we, two or three years ago, we talked about AI girlfriends. I sort of understood it because I, like, have actually developed, like, pretty good friendships, mostly via text messages. I think a lot of people who have group messages here feel the same way. I didn't entirely understand it, but in the last two or three months, I've been using ChatGPT in a way that now I'm like, yeah, this would go away. I would be very upset. And I understand why people were very upset when they're. When their AI girlfriend replica got.
- [20:20]
A
When they did, like, a software update.
- [20:22]
B
Yeah. And so it basically, I've been using ChatGPT as like my thought partner, slash assistant, slash therapist. And you actually said something recently that made it a lot better. So I sat down and I'll explain how I've used it, but I sat down and I said, hey, can you ask me all the questions that a therapist or a life coach or an executive coach would ask? And we could spend a few hours with just me downloading, giving you a download of my life. And I did that. And since then, it's been magical. And I've been using it for all types of purposes. I use it all day, and I want to maybe explain to you how I'm using it. Maybe you could explain to me if you are doing the same, which I think you are, and how you're using it.
- [21:06]
A
Right. By the way, I'll just give you a quick one. My prompt that I used yesterday for this, I said I was explaining the situation. I go, ask me a few questions one at a time. Then when you feel you have enough info, then try to give me a suggestion. Because otherwise it just tries to mansplaining, or what is it called when guys hear your girlfriend is explaining something to you and you're trying to fix the problem right away? She's like, no, I'm not trying to get the fix right now. I Just want you to hear me and understand me. And you're like, what I thought you just want the answer as fast as possible shoved into your throat. And like that's what ChatGPT does by default.
- [21:39]
B
It's, it's. Yeah. And there's a bunch of other downsides that I, I want to explain to all of this and how I'm working around it. But first I, I'm using it for a variety of things. So I'm using it for personal finance stuff and I'll give an example for each in a second. I'm using it for business questions. I'm using it as like a sparring thought partner of like, I'm thinking about doing this. What's your opinion? I'm using it as a therapist of like, you know, I'm struggling with this person at work or my personal life, how should I handle this? Or what should my life goals be? And then I'm also using it for helping me decide which tasks. So I'll give you an example. So for net worth, I use Kubera. Kubera is like a net worth tracker. You just log in with your bank accounts and all your accounts and it tells you your net worth, whatever. Well, they actually have a feature where you can download the information specifically for ChatGPT and you upload it and it doesn't have any identifying information. It's not like it has passwords, it just has a bunch of numbers. And so you can, I will upload this chatgpt and I'll say things like, you know, I like to be conservative, like what would you rate this portfolio out of 10 of risk? Or you know, like, what's your opinion on it? Like, what would Warren Buffett say? You can ask it all types of questions like that. Or you could also say like, you know, how much should I spend on a house? Or what will my net worth be in 20 years? Like things like that. And it's been actually really amazing. Another thing that I did was I took the main KPIs for my company and I uploaded it to it. And I'll be like, what are the needle moving things that I can do for this company? And you could do your KPIs, which is typically like an Excel spreadsheet, like your company's churn new users, things like that. You can also do your company financials. And then another thing that I've been doing is I will actually take screenshots of my calendar and I'll upload it and be like, what task should I be doing for the next week, the next month, the next quarter to get to the goals that I've told you about. You know, my life goals, which by the way, you helped me create. You helped me create quarterly and annual goals. How should I be spending my time today, tomorrow, next week and next week? And it will, it gives me an agenda that I literally print out and I work according to that. It's like pretty wild. And that's how I've been using it. And then all day I'll be like, how should I reply to this email? What's your opinion? It's kind of crazy. So that's how I've been using it.
- [23:54]
A
It's like you have neuralink, they just never did the surgery.
- [23:58]
B
Right?
- [23:58]
A
Like, you're basically putting AI, like as the, you know, operator in your brain in many ways, but you're just like, you know, we just haven't reached that tech point where the chip is already implanted.
- [24:09]
B
Well, the next step of that is here's what's going to happen. There's going to be software, it probably exists, and I'm tinkering with a few of them that records your computer screen, your phone screen, the words that you say out loud, the things you type. And it's gonna, and it's gonna give you feedback on how you spent your day. It's gonna give you feedback on what to do, things like that. So it's gonna like, you know how they. There's a book, I forget what the book is, but the premise is Google knows more than you because you are more honest in your Google searches than you are when you talk to your spouse or your friends or whatever. The same thing happens where it's like, yeah, you know, I, I spend this much time working on this, this and this, and I just be like, no, you did not spend that much time do it. And also you told me that you're trying to be nicer. You wrote like eight really mean emails. Do you know what I mean? Like, that's how it's going to be in the next six months. I think there's going to be products like that are actually nailing that.
- [24:55]
A
Yeah, I think the CEO of Microsoft, I don't know if you heard this story, but I guess when Ballmer stepped down and they needed a new CEO and at the time, Microsoft was kind of in a downward, downward to flat. It was an uninspired stock and company at the time. So they needed something. And I don't know if you heard the story, so the guy who became the CEO Satya Nadella actually wrote a memo. Like, I wrote a kind of like a, A manifesto, an internal manifesto about like, where. What ma. What Microsoft needs to do and he ends up getting the job. And at the time it was like, he's like, I didn't, he's like, I never thought I'd be the CEO of Microsoft. Like, you know, you joined Bill Gates as a CEO or whatever and then Ballmer, and you just assume they're always going to bring in somebody, but they actually promoted him from within. And he, he wrote this thing and one of the key principles that he wrote in this, this is a while.
- [25:49]
B
Back when he was like 05 or 10 or something.
- [25:52]
A
This was in 2014. So he wrote, he bet on two things. I don't remember the second one, but I remember the first one he called ambient intelligence. And ambient intelligence is kind of what you're describing, which is basically like, how do you have, you know, computer intelligence, artificial intelligence, but just like kind of on ambient, like kind of in your, in your environment so that it can be helpful to you. So it just knows what you need without you having to go fetch it, without you having to go ask specifically. It can either anticipate it, it can be aware of all of your context so that you don't have to like, first explain the whole situation and then be able to just ask your question. It already knows your situation, so you could just ask the question, that sort of thing. And so isn't that cool that he, you know, like so long before and, you know, OpenAI wasn't even incorporated at that point or something like that. This is, this is a very long time ago. So to bet on that as like one of the two, like, ways that the tech puck is going pretty baller.
- [26:57]
B
Which is shockingly hard, by the way. It's hard to make these predictions and remove like the limiter part of your brain and just imagine like, yeah, but what would be. What would be amazing? You know, like, what would be cool if. If. Then that's actually. That sounds easy. It's. It's really hard because you constantly think like, well, I can't do that, you know, like, because that's impossible or that would cost too much money. Like, there's all these limiters. But the way that I've been using this, like, if, like, it doesn't work perfect yet though, by the way, this is like, there's a, a few issues with this and I am like, super not. The first thing is contextual or context windows. Like, the more you talk to it, it doesn't always learn more. You actually, it runs out of memory in a weird way. And, and so I've been testing like a variety of different platforms, Gemini versus ChatGPT. But I want to use Chat GPT because I think it's going to be around the longest and they're going to innovate the fastest. But it's not perfect at all. But it's like shocking how useful this is. I finally, for a long time I'm like, yeah, AI is great. Like, I can look to like Google a stat and it's going to tell me. But now it's more like, this is my life. Like, I am using this more than anything. And so like they had their new $200 a month thing come out and I don't even think I need the features, but I'm like, whatever, I'll take it. And so I've like contemplated contemplating, like, should I, like, invest a little bit of money into like, building out these systems just for my personal operating system and like, making my life great. And keep in mind, I don't know anything about any of this shit. I just know that it's, it's just effective. Like, it just literally is helping me get my day done better. And it's like a great bit of advice. Like, here's a really another, like, practical way. I mean, I'll upload my measurements for my body and I'll be like, find me clothes that fit. Or like, does this fit? Does this pair of pants fit? And you just like post a link. Like, I just, I've been using it constantly. How are you, if you are using it to be like this, like, sparring thought partner?
- [28:50]
A
Yeah. Yeah. Well, I think this is the key. So what we're saying is basically the way that I think by default people will use this is you ask a question, it gives an answer. And actually a equally if not more powerful way is to do the exact opposite. You basically say, I'm trying to think about this, ask me questions, and you get it to ask you the questions. And then in that way, it's your sparring partner. It is your thought partner in kind of fleshing out or getting your own clarity around a situation. And it's available 24 7. It doesn't judge. It's, you know, super, super intelligent, but also has like, you know, empathy. You can, you can go back and forth instantly. It's always available and there's no lag time. Right. It's better than a friend, right?
- [29:34]
B
You know, you have a friend who you Bitch to. And you're like, I just need a vent. And like just give me like what should I do here? But you kind of feel guilty like laying everything on them or making it all about you and like they don't quite understand exactly what you're talking about. Of course, yeah, this is just that person. But better that it's one of the.
- [29:48]
A
Main reasons why coaches and therapists are great. Because you're like cool. We're gonna have a completely one way conversation here. Yeah, like I, I don't gotta give you nothing. I can come here and be a taker and that's the arrangement. And like, you know, I gave you the money. That's what that was for. And now from there on out, I don't need to consider your feelings in this interaction. That sounds like ruthless, but it's true. It's why it's different than just, just talking to a friend. Whereas friend, you gotta be like, sorry, am I taking up too much of your time? I don't mean to put all this on you. You know, you're like, like you're always trying to like kind of half apologize and then reciprocate. And one of the cool things about a therapist or a coach is like, that's not the social contract. That's not what's expected in that situation. AI is even better. It's like, hey, sorry to bug you at 1:00am I just, I'd like to talk right now and I'd like instant responses with complete intelligence. And I'll just keep saying no, tell me, you know, no, try again until I get something that's satisfactory to me. It's like you couldn't even treat a human like that, right? So it's pretty great to be able to do that.
- [30:41]
B
It's become strange. I call it dude. Sometimes I'll be like, dude, what's your problem? That's wrong. Stop getting these. Like, like, like it's, it's, it's, it's strange because if you think about it when you're, you're texting your friends, like it's because it's like in the same window or next to the same window on your computer. Like you kind of forget that this is a machine and you can train it how to talk. It's very strange, but it's actually quite effective.
- [31:03]
A
Do you know how an LLM works?
- [31:05]
B
No.
- [31:06]
A
You know what like deep learning is?
- [31:07]
B
No.
- [31:09]
A
I went and watched some videos the other day just to get like, I was like, how is this magic? Magicking? What is going on here? There's one by this guy. I think it's called, like, three brown. One blue is like his username or something like that. It's got millions of views. And he explains, you know, like, what is deep learning? Which is, like, the technique that worked with AI. And the second thing was, you know how large language models work? What does it even mean? What is large? What is the language model? What does that even do? But check this out. So, okay, like, here's the example that. That. That it gave. Okay, so this is me not even trying to explain to you what it is, because my explanation is going to be pretty bad. This is me just saying I can't believe that this is what actually is happening. I cannot fathom that this is the actual scenario. Okay, so let's take this example. I wrote this, I put this on a card because, like, I can't forget this. I'll never forget what I learned. All right, so imagine this number seven, right? So let's say you're trying to train AI to be able to see that this is seven. How do you do that? You can hard code it, but. Well, every time you see the number seven, it's like a captcha, right? It's, like, written a little bit differently. So it's like, you can't just say this is exactly a seven, because you write your seven slightly different than me. Maybe you put the little line through it, maybe you have a little angle to it, whatever, right? So you just want it to be able to recognize anybody's handwriting and figure out seven or not seven, right? What number is it? So how does it work? So imagine basically a classroom, okay? So here's a row of kids. So there's 10 kids standing there. And each of the 10 kids is, like, holding one of these cards with a different number on it, right? But actually it doesn't have the whole number, so. Or actually, they have the whole number. But for. At first, it just says, all right, there's a whole index card we got to figure out. We don't even know if this is a seven or a dog or a car. It could be anything, right? So it just zooms in and it says, let's look at this little section right here. Like, these 20 pixels, okay? These 20 pixels, you know, on this area, it's white. So if you got color there. Sit down, kids. Anybody who's got color over here, sit down, because this picture is white over here can't be you. You're eliminated. And then over here, it's like, hey, there's some Blue ink. Something is here. So if you got blue ink in this little section, stay standing. If you don't sit down, right? So that, like, eliminates a bunch of, you know, like, kind of thought processes. So then it passes it to the next layer, the next layer of 10 kids. And it says, all right, who here's got this flat line? Okay, so the seven stay standing. The five stay standing. You know, the threes are kind of like, hey, we got some stuff up here. Up top, the eights. But, you know, the four. The number four doesn't have a little roof on top. So it's like, I'm out, I'm out. And you're like, okay, go sit down. It's like paintball, right? You're out. Go. Go to sit on the side. And then so now you're left with, like, you know, some of the numbers. And then it says, all right, we got a little. Little stick over here. Who's got a stick over there? And it's like, the threes are like, oh, I'm out now. That's not me, but the sevens and the fives, like, hey, we're still in. It might be us, right? Bingo. And so you just keep passing it from layer to layer, showing it, like, kind of more pixels on the screen. And it's trying to get with some level of confidence at the end, right? It's going to be seven and maybe five at the end. And the seven's like, yo, I'm 90% sure it's me. And the five is like, that's maybe 10% that it's me. It's just an ugly five. And then that's how the AI knows that this is a seven, because it passes it from layer to layer to layer to layer, looking at the pixels on the screen and basically trying to figure out, Trying to guess, is it. Is it one of you? I think with some probability, it's this. Okay, so that's just recognizing a number. Okay, now imagine what you're doing. You're giving it KPIs of your company. It has to understand what a KPI is, what a company is that you were looking for Strategy. What strategy sounds like it's got to say something that you, as a successful business person who sold your companies for, you know, tens of millions of dollars, that you will respect the output of this. Like, isn't that mind blowing that that's even a thing? And so that now you take. How does that work? So it. Now you take. Instead of the seven, take an example where it's like, the dog blanked, right? So it's like, what's going to come after it? You know, it basically sees a sentence. The dog or the dog.
- [35:25]
B
It's like, what's a dog? And what do they commonly do?
- [35:28]
A
It doesn't even know that. It has no idea what a dog is. There's no meaning. It just has it read the whole Internet. So what they did was they were like, hey, go read the whole Internet. Which, like, if you or I, we were like, yo, Sam, I gotta like, let's do this, man. We could do this. We're gonna take so much adroll, we'll stay up all night and we're going to read 247 all the text on the Internet. It would be like thousands of years before we could ever ingest what, you know, what they gave it in one training run, right? So they said, go read all the Internet. Cool. Done. All right, now, user puts in a sentence, the dog blank. Guess what, Guess what the next token is. Guess what the next little word is that comes after the dog. The dog. It's like the dog barked, the dog jumped. The dog, you know, is hungry, right? Whatever. It could be like one of many things. So then it takes the next word, which might be like the dog barked, and then it passes that phrase back through. It's like, now you've got the phrase the dog barked, what comes after that? And it just loops that over and over again to generate the next word. So that's when you see ChatGPT writing. It's literally taking like the, the next token it thinks it should say, then it feeds it back through and then says, okay, well, if I set. If I said the dog barked, then I gotta say loudly, right? Okay, loudly, period. If I said the dog barked loudly, what would I say next? And then it would keep. And it keeps recursively doing that. And that's what's actually. That's how it generates the training thing, right? And that's like, you know, this is only part of it half explained correctly. But let's assume for a second that I'm not like completely misinterpreting this. Let's assume for a second that this is only, you know, a percentage of what I. What is actually going on, right? There's still parameters and weights and all this other stuff that I haven't even talked about yet. This is like, God, right? This is like, well, like, how is this even a thing? Is so mind blowing to me.
- [37:19]
B
It's mind blowing. It's absolutely mind blowing. And I think that, you know, I think young, you know, I don't hang around like 18 year olds. I think they're using it for school, so I think they get it. I think I know a little bit about it because I hang out with smart people and I'm on the outskirts of like what these guys are doing. So I kind of see it online and I play with it. For the average Joe, for my mom and dad, for a 35 year old who isn't like tech savvy, who just works as a mechanic, I don't think that they're using it this way. I don't think they're using it at all. And it's gonna change everything. It's just like so, like crazy. Like when the average Joe starts getting into this, I think young people, like a 21 year old or something. I think it's like changing schools, by the way. It's like the grading system is like totally effed up.
- [38:04]
A
Yeah. Yeah.
- [38:04]
B
Like when I like think about this, I'm like, like, this is like, there is no homework. You can't do homework anymore. You know what I mean?
- [38:11]
A
Someone DM me yesterday. It's not just homework. Someone DM me last night. They were showing me. This guy Oliver, Oliver Hahn. He texted me this thing or did DM me this thing. He said, coding interviews, like, so, okay, school. Yeah. Kids in school are using ChatGPT, write essays, and the teachers are like, fuck, how do we. How are we gonna. It's a cat and mouse game to try to be like, hey, how do I stop you from using AI to just like do your assignments? Well, the same thing is true for coding interviews. So. Coding interviews, which are used to hire programmers. There's this website, leetcodewizard IO and basically it just helps you cheat on your coding interview. It's like, oh, you got a coding test to get a job, Just use this watch. It'll write. It's the same thing as a student. It'll write the essay for you, basically. And it's like, you know, doing 15 grand a month and recurring revenue. I'm just helping people cheat on coding interviews.
- [38:59]
B
This is insane.
- [39:00]
A
It's so difficult, right? But it's kind of amazing.
- [39:03]
B
How are you using this every day?
- [39:05]
A
Like, let me just go to ChatGPT, just tell you like my last.
- [39:07]
B
And is ChatGPT your tool of choice or do you like any of the other ones?
- [39:12]
A
Yeah, it is my like default. And then, you know, I play with everything else. So usually if I'm like, how factually correct does this need to be? All perplexity. So I go to perplexity. If it's analysis, I'll use ChatGPT. Have you used the 01 stuff? Like the deeper thinking stuff?
- [39:28]
B
Only for 24 or 48 hours. Yeah, it's brand new, but yeah, it's wild. It takes a long time, but it's wild.
- [39:34]
A
Well, yeah, that's the point of it. It's basically if you told the computer, hey, you don't have to just quickly again shove an answer down my throat instantaneously where you're just predicting the next token and good enough to go, right? 70% chance. It's this word, let's just put it in. They found they could get, you could do more interesting tasks if you just said, hey, take your time before you answer. Just give it more time to think and then it'll come up with a better answer. It's temperamental, which is amazing. So I use that. But like, check this out. So there was this press release recently for, we were talking about ivf, remember? Well, it's kind of this amazing thing. I don't know if you saw it. It's called fertilo. Do you see what happened with this thing called fertilo? So basically it was like the first live birth using eggs that matured outside the body. So like if you've done ivf, it's, it's like a pretty expensive and pretty like harsh thing on the body. Like the woman has to get like injections, which are hormone injections to try to get your, they're trying to get your eggs to essentially mature, be produced and mature inside your body. And so what fertilo did was they were like cool. Instead of doing that like long, expensive, sort of hard on your body process, we can take an immature egg, take it out of the body and let's do the hormone stuff out of the body and get it to mature and then we'll put it back in the body. And so it just like removes the pain from the process and the first like actual live birth happened of a baby that was born using that procedure. It's kind of amazing if true. It's going to make, you know, it's going to change ivf, you know, it's going to make it where I don't know if it'll just be called a new procedure or what, but basically for, you know, a fraction of the cost, a fraction of the time and a fraction of the pain, we can do the thing that we've been doing with ivf, okay.
- [41:20]
B
So dude, it makes you realize that I think that Sahil, I forget his last name from gumroad, tweeted this, like, thing out where everyone made fun of him, where he talked about how he's like, giving birth is not going to happen in the future. You're just going to be in this sack and that's how you're gonna grow. This is that. I'm like, oh, you're right. You know what I mean, dude.
- [41:40]
A
I remember we were at a dinner and Jess Ma just said it casually in passing. She was like, yeah, like, you know, I'm really, you know, excited for and fascinated by basically, like, artificial wombs and basically, you know, pregnant. You know, you won't give. Women won't give birth at a certain point, right? It'll be like riding horses for transport. It's like, you could do it if you want to go have a unique experience. She's like, it won't be necessary.
- [42:02]
B
And she's like, pass the. Pass the mashed potatoes. And you're like, wait, wait, wait, wait, wait.
- [42:05]
A
Yeah, so no, like, literally, that's exactly what happened. And I was like. And at the table, I looked around to be like, was anybody else mind blown by that? What's going on? Like, don't we all want more information about that? But I'm at. I was at this, like, far diagonal, seven people away, but I heard her say it. And I'm stuck over here talking about Facebook ads with some dork. And I'm like, just, I'm gonna get out of this side of the table. Get to that side of the table.
- [42:24]
B
So after the dinner, Jess, what did you say about womb? Oops.
- [42:27]
A
Literally, I flagged her down. I was like, oh, you're getting an Uber. Hey, cancel that real quick. And she canceled it. And I was like, what was that thing you were talking about? And then she explained, and she explained the companies that she's tracking and, like, where we are in the scientific life cycle of, like, how real is that possibility and how. What are the laws of physics? Is that inevitable or is it impossible? Right? Because basically if something is not impossible, it's inevitable, which in itself is kind of a dope idea that already kind of blows my mind. And so she was explaining it. So, you know, I've sort of been paying attention to any signs of movement in that area because I think that's really cool. The world's going to change pretty dramatically when that happens. But what I did, back to the AI thing, I just threw the press release into ChatGPT and I said, explain this article to me. Tell me what they're saying, tell me what this means. In simple terms, it's a press release. And so it might be misleading or overstating the success of this. So tell me about that too. And then it just goes, here's what it means. In simpler terms, this company has achieved what they call the world's first healthy baby born with a woman's egg that was matured outside her body. Normally in ivf. The doctors are doing abc in this scenario, what they're doing is abc. And then it explains it and it goes in simpler terms. Conventional path is X, the new approach is Y. Why it matters if this is true, blah, blah, blah, blah. And then it says, here's why it might be misleading. It's a press release. So it's definitely spin number two. One success doesn't prove a trend. It talks about the world's first, but it doesn't mention how many others they've tried that have failed in the hit rate of this procedure. It's not peer reviewed. It might be exaggerating the future impact. We would need to know clinical trials, blah, blah, blah. And you know, then I asked it more, I was like, cool, what is the, what does the scientific literature say about this? So all of a sudden I'm getting like a quick biology lesson. Another one. Brainstorming name ideas for a project. I'm like, hey, here's a project.
- [44:14]
B
It's great for that.
- [44:15]
A
Ask me questions about the project and then come up with names. Then it comes up with dorky names. I'm like, no, make the names not dorky and long and don't make it feel like it's written by ChatGPT. Make it feel like it's written by David Ogilvy. And then it comes up with different answers. A lot of financial analysis, so analyzing stocks or just like, yo, I see Cathie Wood on my screen a lot. Like, is she actually like great at investing? And then AIs like talking like a monkey.
- [44:40]
B
I see Cathie Wood on my screen.
- [44:43]
A
Is she just hot or good at trading? Right? It's like, you know, they're asking these questions and again, no judgment, just gives me the answers. Which was spoiler no. She underperforms the indexes and has over like a 15 year period and makes $100 million a year to underperform the index. It's like, wow, good on you, Cathie Wood, for doing that. Let's see, just other ones. Hey, I'm trying to do this in Excel, but I don't know how to do it. Can you just tell me the function I need to write in? Because if you go Google this stuff, you get YouTube videos you have to watch.
- [45:14]
B
Yeah.
- [45:15]
A
So now I'm like, all right, forget the YouTube video. Just give me the, like, the exact typed thing I need to go type in. Or I'll screenshot the Excel window and I'll just say I'm trying to figure out in column C what are the ones, blah, blah, blah, blah. And it gives me this, like complicated, you know, whatever count ifs formula that's as multiple, like selectors or whatever.
- [45:37]
B
So I'm obsessed with being transparent about money, particularly with ultra high net worth people. The reason being is that there's not a lot of information on this demographic. And so because I own Hampton, which is a community for founders, I have access to thousands of young and incredibly high net worth people. We have people worth hundreds of millions and sometimes billions of dollars inside of Hampton. And so every year we do this thing called the Hampton Wealth Report where we survey over a thousand entrepreneurs and we ask them all types of information about their personal finances. We ask them about how they're investing their money, what their portfolio looks like. We asked them about their monthly spend habits, we ask them how they've set up their estate, how much money they're going to leave to charity, how much money they keep in cash, how much money they're paying themselves from their businesses. Basically every question that you want to ask a rich person, we went and we do it for you, and we do it with hundreds and hundreds of people. So if you want to check out the report, it's called the Hampton Wealth Report. Just go to join Hampton.com, click our menu, and you're going to see a section called Reports and you're going to see it all right there. It's very easy. So again, it's called the Hampton wealth report. Go to joinhampton.com, click the menu, and then click the report button and let me know what you think.
- [46:48]
A
Oh, I play games with my kids. So we take pictures of like, my son got all these sharks. And so we just took a picture because he's asked me questions, right? Like, Jada, what is this shark? And I'm like, dude, if I know, right? Like, you know, it was kind of like something I always dreaded as a parent. Like, oh, cool, my kid's gonna ask me questions that I, you know, where does rain come from? And I'm like, it's in the clouds. Like, how to get in the clouds? I'm like, I think it was in the ocean and then it just, like, zipped up there because it was hot or something. And I'm like, this is going to be terrible. I'm going to expose myself. And so I just do chat GPT voice mode. And I will be like, I'll send it a picture and I'll go voice mode. I'll be like, hey, tell me what these sharks are from left to right. And it reads it out to my kids. And then my kid can ask a question. He'll be like, which one is the strongest shark? And it'll be like, actually, the great white shark is the strongest shark with the most powerful bite. And he'll be like, no, but what if it was with a cheetah? He'd be like, well, the cheetah wouldn't be in the ocean, but if it was in the ocean. And, like, it'll, like, interact with my kids. If we have, like a fun time, they'll. They'll tell me all the time, can we play with AI?
- [47:47]
B
Dude, that's so good. I've got a bunch of friends whose children are like 3, 4, 5, talking age, and they, like, are doing the exact same thing. Let me.
- [47:54]
A
I'm gonna do trivia. Another hack for parents. You can go, hey, I'm sitting here with my two kids. Their names are, you know, whatever, Timmy and Tommy. And we're gonna. We wanna do paw patrol trivia. Ask us easy questions. And when we're right, say, ding, ding, ding. And when we're wrong, say, that's not right. Try again and keep track of the scores. All right, go. Literally, you could just say that to it in voice mode and it'd be like, all right, first question. Marshall is a pup known for what? And you're like fire. And it's like, ding, ding, ding. Correct. One, two.
- [48:23]
B
Your kids are gonna, like, fall in love with. With her. Like, it's pretty crazy how the, like, imagine being, you know, raised with this. This is insane. The. I'll give you. Let me give three practical ways I'm using it. So they have this new thing called, I think it's new ish. Called projects. And so I have three folders right now. And the way it works is you have like a folder as a project, and then you can upload files to the project, and then you could have multiple conversations within the project, and it refers back to the files or whatever information.
- [48:51]
A
Give me the example.
- [48:52]
B
You can store that. What's like, let me give an example in there. I have a health folder. And so, you know how Everyone has, like, their own health guru, and it's like, usually based off of, like, one book they read. Well, I go and download your mind. Yeah, Well, I go and I download the book that I ascribe to and I will upload and I. If it's a book that's epub, which is how I buy it on Kindle, I convert it to dot TEXT file because that's easier to read. And I upload the dot.txt file to the.
- [49:19]
A
Even though it's, like, huge because it's.
- [49:21]
B
A book that works, I give it a full book, the full book. I download it and I convert it. And then like, so, for example, we were going to the grocery store today and I just said, like, you know, there's like, this interesting book I just read and I upload the. I've uploaded the book and I'll just say, make the grocery list for me. And. And then I'll. And I'll tell me, actually, and I'll say, which grocery store should I go to in my area? And it knows where I live? And it says, yeah, like, these three grocery stores will have exactly what you need. I think they will have what you need because, like, you know, I'm on, like, clean meat kick or whatever. And he was like, yeah, the author says, like, to buy this cut of meat and you should ask the butcher this, this and this. And like, here's three butchers that appear to have what you need. And it's all based off of, like, the files that I've uploaded for health. But then within health, I can ask it. I'll like, hey, this quarter, I want to run a 5k at this particular time. Give me, like, a good app to use that can help track my running and also tell me, like, what my goals should be. So that's like a couple health versions. The second one is I've got a clothing one where I literally took a photo of myself and I used a tape measure to measure various parts of my body. And I upload it to it. And I was like, all right, like, make a chart with all my measurements. Thank you. Remember that always. Here's some, like, clothing that I want to buy. Here's the links. Can you, like, go and figure out what size it is and let me, like, will it fit? And they're like, well, this pants, it says that they're the same width as your thigh, but you actually want, like 2 inches, usually extra width. That will probably feel more comfortable. Or what I'll do is I'll upload like a Blog that I like, Dye workwear blog. And I'll say, hey, here's a picture. I'll literally lay a tie next to a jacket and I'll take a picture of it and I'll upload it. And I'm like, does this tie match this jacket? And I'll be like, no. But that other tie that you showed me a picture of a while ago, that actually would look great here, it's like, that's how I use it. And then the final way that I use it. And this is like my life coach folder, which is like, like, it's like partially like, I'll complain to it. And I'm like, you know, I noticed you've been complaining about this a lot. Or I'll upload business financials to it. And that's like more of like my sparring partner throughout the day. And so I have three folders right now. Health, clothing, and like a life coach. And so those are like the practical ways. And I'm using projects. That's the, that's the term on chat GPT and that's how I'm using it as of now.
- [51:39]
A
Dude, people are just going to replace their co founder with. With this, right? Like, you're going to see a lot more solo founders because you could just have an AI co founder.
- [51:47]
B
You're going to say, well, you know, you'll reduce churn if you use this messaging when you email your users. And then you're just going to say, yeah, well, you have my login to mailchimp, like on Shopify. Like, go ahead. Yeah, get it done. Or you'll be like, you know, my Shopify store is like a 2.1 conversion rate. And it's like, hey, I, you know, we ran this a B test it, like, increase your conversion rate to 3% and you're like, get after it. You know, go do it. And that's what's going to happen. And so anyway, we've had these intelligent people, Dharmesh, whatever, explain to us all these things, but it wasn't until the last two months and in fact, recently actually since you told me to ask him the. Ask ChatGPT that question that, like, I'm like, oh my God, this is my life now. In fact, you actually sent out a wonderful email the other day where you said, here's how to ask powerful questions. I uploaded that email to chatgpt and I'm like, remember these questions and like, ask me them often or ask yourself these questions often.
- [52:43]
A
Yeah, I mean, it's just so it's Incredible. And it's also so obvious that I think that ChatGPT is, I mean it is the Google of our generation. And I guess the only question is like, why am I not, why am I not a shareholder of OpenAI? How do I go to sleep at night?
- [53:02]
B
Well, I mean, Dharmesh had to buy a $10 million domain and then convince them to buy it in order to become a shareholder. So like it's like, like there's only a way though. There is always a way. But that's like saying like, why am I not a billionaire? It's like, well like you could be, but like here's some of the barriers to entry that you've got to overcome. So there's certainly. You should ask ChatGPT that, by the way.
- [53:24]
A
It's a good question, by the way, why am I not a billionaire?
- [53:27]
B
It is a great question, but like.
- [53:28]
A
There, have you, have you ever asked yourself that question? I asked a friend that question and they weren't even really that close of a friend. So it was kind of a, you know, it was a blunt question to ask at a dinner. I was like, why are you not already a billionaire? And he gave a great answer and he goes, or actually what he was saying was, you know, I want to start a billion dollar company, something, something selling. And I was like, why have you not already done that? And he goes, I think when I was starting these other companies that I started because I didn't actually understand what a billion dollar company looked like and if I had known that, I would have built a different company. And he was, he was correct. And, and you know, as we dug in, it's like, what makes a company a billion dollar company? Like, you know, there's really only a couple of paths to that. And you know, one of them, for example, is like building something that has network effects. So he had been building companies that could do like great revenues, that could even be profitable. They could grow fast. Those are some of the things you need. But there was no network effect. There was no durability, there was no defensibility. There was no like win the category. It was like, just go to a category where you can win inside that category, but there'll be other winners and you'll see. Now just as an example, that was like a gaming company. It's like there's a lot of mobile gaming companies and at the time, like to build, to, to build a billion dollar gaming company require like, you really had to be like one of the like, you know, three that were going to get built in a five year window, right? Like you had to build, you know, Clash of Clans or you had to build Candy Crush or you had to build like one of those. And even in one of those it was like, oh, actually, you know, I'm sitting here tinkering on cool game designs and actually the thing I need to do is build a enormous paid marketing team that is like point the top, the top paid marketers in the world to acquire hundreds of millions of customers is what I need to do. And like the cool artsy game design that's going to win me awards is not going to. That's not what a billion dollar gaming company looks like. So he just didn't understand the shape of something. And I find that to be true about most of the goals. So instead of how can I do this goal? Another way of saying it is why have I not already done this goal? Why is it not already true for me? And then it points out some either knowledge gaps or execution gaps that are today that are more close to your timeline versus when you set an ambitious goal that's far in the future. And you bake in that it's going to take a long time. You sort of avoid maybe the harsh realities that might be actually existing today in your world.
- [56:17]
B
About those, yeah, you had a great email with a bunch of those questions. Here's a bunch of decision making questions which is I'm not sure what should I do instead? You should say what would I do if I weren't afraid? One bad question is how can I make this succeed? The better question is what would make this certainly fail? Final example is I can't decide which path is the right to pick a better question or better version of that is what path makes for the best story. This is actually a pretty good email, I think I replied. I said this was a 10, but you had a list of better questions. And I used those questions in ChatGPT because what I'm learning with ChatGPT is you have to get it to ask you better questions in order to. Its input is important for its output. And so yeah, I pretty much stole that email.
- [57:07]
A
Yeah, I think the, the realization was Tim Ferriss had said something way back. I think I put it in the, in the email. But he had, he used this phrase, he goes, he was talking about it in the, in the, in the podcasting realm. But first, first he had this quote. Yeah, you can read it out.
- [57:22]
B
He goes, if you want confusion and heartache, ask vague questions. If you want uncommon clarity and results, ask Uncommonly clear questions. Often all that stands between you and what you want is a better set of questions.
- [57:35]
A
Exactly. And he said this about his podcast. He goes, I view questions as like a pickaxe for the brain. Like, you know, like a pickaxe when you're summiting a mountain and you, you use it to sort of like pierce the, the side of the mountain and use it to pull yourself up. And so in many ways you are excavating the brain with this pickaxe and your pickaxe is questions. Another phrase I use all the time in businesses is ask a better question, get a better answer. So often if somebody asks a bad question, and I'll call a bad question either a vague question, open end question, or a question in the wrong direction, I think the rookie move is just to answer a question at face value, you should not answer 100% of the questions asked. A lot of the questions need to bounce back to sender. This has the wrong address on it. You got to write a better address on that. This won't get delivered the way you've written this address is not going to get delivered. And so you bounce back some questions and say, maybe the better question to ask is blank. For example, instead of how could we succeed? Which is like a million paths all unknown, it's what would make this certainly a failure. That's much more knowable. And we can, we can establish a few ground rules from that question and get some momentum towards this. And you could see this with your brain. Just like if you ask, you know, they call it prompt engineering when it comes for AI, right? Being able to ask the AI in a certain way, that's going to get you a better result. Absolutely. The same thing is true for yourself and for people around you to ask better questions. Right? I do. I ask annoyingly stupid questions to my team all the time. Like, it'll be. One question I love to ask is what are we stupid for not doing right now? And that question comes loaded with a presumption that there's something stupid we're doing. Of course there is. We're always doing stupid things. And specifically, what are we stupid for not doing right now? Meaning what is an obvious low hanging fruit that's in our face? And we're out here searching for the complex when the simple, stupidly obvious thing is here. And you know, I would say more than 50% of the time there's a useful answer to that question, but if you didn't ask that question, it would just go unspoken in your company.
- [59:47]
B
Right.
- [59:47]
A
So Like. Like, how many are those? Another one that I learned from Amazon is Amazon asked this thing in the. If you're like, if you're an exec that leads a team, you have to, like, write this document at the end of the year called the OP1. I think it's the operating plan one, and you do two a year, right? The operating plan one, and then you have the operating plan two halfway through the year.
- [60:04]
B
Was that effective? Yeah, it's great.
- [60:06]
A
I'm a fan of the Amazon writing culture. It's easy to make fun of also and easy to do wrong, but when done right, super effective. So one of the things that they. One of the common questions that they ask in that is, what are the dogs not barking? And it's back to that Sherlock Holmes story where he solves the case because he's like. And they're like, how did you know, Sherlock? And he's like, because there's, like, a house break in. They're trying to figure out who did it. And he's like, well, it was the dog, of course, but the dog. The dog didn't do anything. He goes, exactly. The dog didn't bark, which means he must have recognized the person that broke in, which means it must have been the housekeeper or whatever, Right? And so in your business, there's. What are the dogs? Not barking is a good way of asking what are the things that there's really. Like, I interpret in two ways. One is, what are the things we should be hearing that we're not? So, for example, one week, I didn't send out my Friday email, and I just sat there and I was like.
- [61:00]
B
Like, you want people to complain about it?
- [61:02]
A
Emails being like, hey, where's the Friday thing, Man, I love that. Oh, I didn't get that. Okay. Dog not barking, right? And then I had changed how I did the Friday emails because of that. It's like, well, why'd you make that pivot? It's like, because I. I did Jenga, dude. I took a block out and the tower was fine. Nothing, nothing fell down. I'm trying to only have, like, I'm trying to be an email in your inbox that if I remove that email, your life got worse, you know? And you want. You want to speak to the manager, where's my goddamn email? Right? Like, if doordash doesn't deliver your food, you're knocking on the door. I want to be at least more powerful than the doordash delivery, right? Like, that's. That's what I'm striving For. And so that's one way of interpreting it. The other way is, what are the problems that you don't hear about yet, but are certainly there? That's another way to think about the dogs not barking is like, you know, anticipate a problem around the corner because we know it's going to be there, but we just haven't heard it yet. But, you know, we can anticipate it and maybe get ahead of it.
- [61:58]
B
Dude, I'm telling you, there's going to be a world probably in three years where you're going to like. So the issue that a lot of smart people like you and me and people listening is like, you're like, well, I'm really smart and I feel like I'm wise and I feel like I know what to do. But, like, it's a lot of work. And then like, literally the. The idea guys are going to thrive in five years or the wise people, because there's going to be AI agents doing all of this for you. You know what I mean? Like, you're not going to have to actually do that work. You're just your. Your opinions or your taste.
- [62:30]
A
Right? Because then who's. Why can't the AI do the idea, part two? Right?
- [62:34]
B
That's going to happen, too. It's not. You're not. I don't think you are.
- [62:37]
A
So then what, right? And then that's when the brain breaks and you're like, I guess it's over then. And I'm not sure.
- [62:44]
B
Wait, so you actually afraid?
- [62:46]
A
Yeah, kind of like. I don't want to say afraid because I'm not, like, you know, quivering in my boots about it, but I guess, like, I don't have a satisfying answer. And for most things in my life, I got a pretty satisfying answer. Sometimes the answer is just, I'll deal with it when it happens, right? I'll just adjust, right? And I can feel safe. I could feel comfortable with that. That's usually my fail safe with this one. It's kind of like, so when the AI can do everything, which is like, it seems like it's a matter of when, not if at this point. Okay. And it seems like it's in my lifetime, probably in the next 10 years, it could do the work, but it can also figure out what the work to be done is. All right, well, I guess, like, I'm less afraid of the, like, oh, and then it's gonna crush human humans and try to, you know, it'll go rogue and it'll. It'll attack us. Like, I'M not as afraid of that as I am. Just like, what's the point of all this? What's the point of doing any of this stuff if that's gonna be true? And that's kind of just like a. A weird place to land.
- [63:52]
B
So you want to end there. What the. Right.
- [63:58]
A
Podcasts are all that safe, dude, no, they're not.
- [64:02]
B
No, they're not. Perplexity has a daily podcast that's really good. They just take the news that as great and then they. Or no, it's not Perplexity, it's. What's the thing 11 Labs. 11 Labs has. They use like a Stephen Fry voice and they read the news. I listen to it. It's awesome. It's not safe. We're not safe. No one's safe. Maybe like a plumber. A plumber's safe.
- [64:20]
A
Well, I actually think our strategy is pretty genius because we are getting stupider. Just like we dumb ourselves down and AI is trying to get smarter. And so there's actually a white space in the market for some just imperfect knowledge, some half baked ideas and some incorrectness. I think we've stumbled onto something. I think we might be the last one standing in this whole podcast game. It's us and Theo Vaughn. It's just like the dumbest conversations on earth are going to be all that's left because the AI is going to do all the smart ones. Maybe.
- [64:52]
B
I mean, I, I don't know.
- [64:54]
A
Maybe Mark Andreessen should be scared right now.
- [64:56]
B
Dude. Yeah, the smart guys are like, the smart guys built. The smart guys are digging their own graves. They're like, their shovels are clanking together on accident as they're like digging the same grave. They're like, oh, sorry, my bad. It's like they don't realize that you guys are going into this grave in about a year.
- [65:11]
A
My name on the tube stuff. Yeah, that's weird. It must be a problem. Is there another mark here?
- [65:17]
B
Two Margaret Dreeson's. Like, they think that. They're like, they're like, we're put the blue collar guy in this grave and we're gonna outsource this job. They're like, huh, I've never. Mr. Adri Sid, are you here? Like, you know what I mean?
- [65:36]
A
Dude, I found my, my new sick burn in the TikTok comments. You know, there's all these TikTok clips of podcasts. Like, we should probably be doing this, but we don't really do it very much. But like people just clip, you know, podcast snippets. And that's, like, a lot of TikToks. And the more viral, the more. Basically, the more outrageous the comment in the. In the podcast, the more viral the TikTok clip. Because you're gonna get a bunch of comments being like, this is that. No, that's wrong. That's stupid. That's whatever. And I saw the best one. It was just the top, top liked comment on a podcast clip, which is. It just said podcasting equipment is way too readily available. This is like, damn, anybody could just get a microphone now. That's how I feel when I see a lot of these clips. I'm like, wow, this is. These microphones are way too easy to access.
- [66:25]
B
Have you heard that song, Another White Boy with a Podcast? Yes, I'll call Another White Boy with a Podcast.
- [66:34]
A
How did I not think of that?
- [66:36]
B
It's sort of like that, like, finance 64 blue eyes. It just says, like, Joe Rogan. Like, it just says, like, a bunch of, like, random phrases, but it's called another.
- [66:46]
A
We should just play that song on.
- [66:47]
B
The way out of this.
- [66:48]
A
That'll be our outro. All right, cue the music.
- [67:04]
B
We should make a party. We buy mics, we get chairs. We sit down with blank stares. We're gonna be billionaires. Just don't forget to like and share. Oh, another white boy with a podcast.
- [67:20]
A
Hey, Sean here. I want to take a minute to tell you a David Ogilvy story. One of the great ad men, he said, remember, the consumer is not a moron. She's your wife. You wouldn't lie to your own wife, so don't lie to mine. And I love that. You guys, you're my family. You're like my wife. And I won't lie to you either. So I'll tell you the truth. For every company I own right now, six companies, I use Mercury for all of them. So I'm proud to partner with Mercury because I use it for all of my banking needs across my personal account, my business accounts, and anytime I start a new company, it's my first move. I go open up a Mercury account. I'm very confident in recommending it because I actually use it. I've used it for years. It is the best product on the market. So. So if you want to be like me and 200,000 other ambitious founders, go to mercury.com and apply in minutes. And remember, Mercury is a financial technology company, not a bank. Banking services provided by Choice Financial Group and Evolve bank and Trust members. Fdic. All right, back to the episode.