3 Stories Of People Making Millions In Weird Ways

0:00:05 All right, Sean, there’s a documentary that R and I were texting about, did you see it?
0:00:06 It was called Martha.
0:00:07 It was on Netflix.
0:00:08 It was about Martha Stewart.
0:00:12 I haven’t seen it, but I actually don’t know really anything about her.
0:00:13 Great.
0:00:18 This is so great, because Martha Stewart was a beast.
0:00:29 I really couldn’t tell you five things about Martha Stewart, so like, was she kind of the
0:00:34 first influencer like a celebrity influencer who then started launching products or what’s
0:00:35 the story?
0:00:37 Martha Stewart was a killer.
0:00:39 She was a total shark.
0:00:40 She was way sharkier.
0:00:46 If you only know her as her put together image of like this like housewife who cooks, everything
0:00:49 I’m going to say is going to blow your mind because she was a total shark.
0:00:51 So I’m going to give you a little bit of her background.
0:00:55 So basically she’s born and raised up in the East Coast.
0:00:57 She goes to Columbia University.
0:01:02 While she’s going to school, she becomes a model because she was a cute woman when she
0:01:03 was young.
0:01:04 Yeah.
0:01:05 Yeah.
0:01:06 Wow.
0:01:07 She was fantastic.
0:01:08 Yeah.
0:01:09 Good for her.
0:01:10 Very pretty woman.
0:01:11 Yeah.
0:01:12 Go Martha.
0:01:14 She gets married at a young age, like 19 or 20 years old, but graduates Columbia and her
0:01:18 father-in-law helps her get a job as a stockbroker.
0:01:22 And by the way, she studied architectural history or something like that at Columbia.
0:01:23 Something to do with stocks.
0:01:28 And so at the age of like 24, 25, she gets a job and you’re probably wondering how on
0:01:31 earth did Martha Stewart become a stockbroker?
0:01:36 Well, I am wondering when her father-in-law first met her, he was like, you have this
0:01:37 like it factor.
0:01:39 Like you are so charming.
0:01:43 You are so put together because she had this vibe at a very young age in her 20s.
0:01:46 Like she dressed it fantastically.
0:01:47 She was very charismatic.
0:01:50 She was clearly driven and hardworking.
0:01:55 And this small like 10 person operation that was a stockbroking brokerage, they needed
0:01:56 a saleswoman, a salesperson.
0:01:58 And it was all men at the time.
0:01:59 I think this was in the 60s.
0:02:00 It was all dudes.
0:02:03 It was a very male dominated industry.
0:02:08 But she comes into this interview and eventually works there and they comment on how she’s
0:02:12 dressed like perfectly, like so perfectly that you’re sort of intimidated when you first
0:02:15 meet her because she’s like perfectly put together.
0:02:19 But then she’s like really charming and warm and you’re like, oh, I like you.
0:02:25 And so she starts like as a salesperson basically at the stock company, really working out with
0:02:28 clients and getting them to like trust them and things like that.
0:02:29 And she kills it.
0:02:30 And so listen to this.
0:02:36 At the age of 26, according to this documentary, she said she was making $135,000 a year, which
0:02:41 equivalent today is a million dollars a year at the age of 26 as a stockbroker.
0:02:46 Pretty crazy that she went from being a model to a stockbroker in that short amount of time.
0:02:47 And she kills it.
0:02:48 And she does it for like six or seven years.
0:02:50 Like it’s like a legitimate career for her.
0:02:54 And she suggests that one of her clients buy this stock that was like a dollar and it went
0:02:56 to like 10 bucks.
0:02:57 So it killed it.
0:03:00 Then they bought a little bit more and it goes something huge like to 50.
0:03:04 It was like this massive stock and it made these clients all this money.
0:03:07 But then the $50 stock goes right back down to like eight or 10 bucks.
0:03:10 And so technically her client had still made a bunch of money.
0:03:13 But that roller coaster ride of like making a little bit of money, then making a ton of
0:03:15 money, then losing a ton of money.
0:03:17 And like left her kind of distraught.
0:03:20 And so she bailed because of that like journey.
0:03:21 And so she quit.
0:03:27 And so when she’s like 30 years old or late 20s, she moves out to actually where I’m living
0:03:28 now, Westport, Connecticut.
0:03:29 She was like, you know, I want to have a kid.
0:03:33 I want to like try this housewife life, whatever, and do this thing.
0:03:37 And she moves out here and she sits around for a very short amount of time and she’s
0:03:38 like, all right, I got to do something.
0:03:39 Like I can’t just sit here.
0:03:44 And so they buy this like kind of shitty house and she like totally turns around and
0:03:45 redust the whole thing all by herself.
0:03:46 She paints it.
0:03:47 She builds this beautiful garden.
0:03:53 She learns how to raise goats and chickens and like plant her own garden and like creates
0:03:57 this amazing like a state out in Westport, Connecticut, which now it’s fancy.
0:03:59 Back then it wasn’t particularly fancy.
0:04:02 And so eventually she gets really into this and she’s like, you know, I kind of like this
0:04:04 housewife life.
0:04:08 What if I start hosting some dinner parties and she creates these lavish, amazing dinner
0:04:12 parties and eventually all these rich guys who come are like, Hey, do you want to like
0:04:14 cater my party?
0:04:15 And so that’s what she starts doing.
0:04:20 And so she builds a business as a caterer that she said made her a millionaire.
0:04:26 All right, let’s take a quick break to talk about our sponsor today HubSpot.
0:04:30 With smaller budgets and sky high expectations, growth is feeling pretty painful right now.
0:04:35 But HubSpot just announced more than 200 product updates to make impossible growth feel impossibly
0:04:36 easy.
0:04:39 Like Breeze, it’s a new suite of AI tools that will help you say goodbye to your busy
0:04:41 work and hello to better work.
0:04:44 Breeze Intelligence, which will give you the richest, most comprehensive picture of your
0:04:48 prospects and customers and reimagine marketing and content hubs to attract and convert more
0:04:51 leads and send your revenue soaring.
0:04:58 Visit HubSpot.com/Spotlight to learn more.
0:05:02 And her whole shtick back then for this catering business was she goes, I’m going to make everything
0:05:03 by scratch.
0:05:07 And so Westport, Connecticut, where about an hour and 10 minutes from New York City.
0:05:10 At this time, people start realizing that she could actually operate on like three or four
0:05:12 hours of sleep.
0:05:15 And so she would go to like catering, the catering business, by the way, it’s like, that’s like
0:05:16 the hardest thing on earth.
0:05:17 Right.
0:05:18 It’s brutal.
0:05:19 It’s a really hard business to pull off.
0:05:24 And so she was famous for going to the farmers markets in New York at four a.m. getting all
0:05:27 of her produce and then going in the morning and baking all of her food.
0:05:33 And so her famous saying as her catering business was basically I make everything from scratch.
0:05:38 And not only does she just make stuff from scratch, one time she saw this brochure that
0:05:41 like was doing a recreation of like the pilgrim’s Thanksgiving.
0:05:45 And there was like a basket of fruit that was like overflowing and she was like, that’s
0:05:46 what I’m going to do.
0:05:50 And so she was famous for creating these like charcuterie boards of like overflowing meats
0:05:51 and fruits.
0:05:53 And she says something that was actually really inspiring.
0:05:57 She was like, I wanted to turn this into experience and like, I wanted to make this like fruit
0:05:58 board.
0:06:00 She was like, it sounds trivial, but that was my art.
0:06:04 And I was going to make like these baskets of fruit overflow with strawberries to show
0:06:08 that this table is where like generosity like, like, you know, like an abundance and all
0:06:09 this stuff.
0:06:10 And it’s a massive hit.
0:06:16 She builds us into a big business to the point where a few years in, she goes and she caters
0:06:19 a, I think it was like Penguin Publishing or something like that.
0:06:23 Like one of these publishers party, she caters it and it’s a really big deal.
0:06:27 You know, she’s doing like the Met, all these museum and art museums in New York.
0:06:31 And this is a big deal that she’s doing this catering company or this publishing company.
0:06:35 And they start talking to her and they’re like, dude, you are amazing.
0:06:37 Do you want to write a cookbook for us?
0:06:38 And so she does.
0:06:43 And it takes her like a few years, like three or four years because she’s super hands on
0:06:44 on writing this book.
0:06:47 And they were like, Hey, so we’re going to want you to do this cookbook, just put in
0:06:48 a bunch of recipes.
0:06:50 It’s a black and white photos.
0:06:52 And she was a nobody and she goes, not a chance.
0:06:57 We’re doing colored photos and we’re actually going to do like 500 photos and I just give
0:06:58 me the budget.
0:07:02 And I’m going to like hire a photographer friend and we’re going to go and like organize
0:07:07 all these photos and take all these lavish photos at my house that I made because we’re
0:07:12 going to make this like the Martha Stewart cookbook where at the time, typically a just
0:07:13 been recipe.
0:07:15 She was like, no, we’re going to add in about like my lifestyle.
0:07:16 We’re going to add these photos.
0:07:17 One of the photos.
0:07:18 And this is like her kitchen.
0:07:19 Look how lavish that is.
0:07:27 Like, what do you see the most full kitchen I’ve ever seen literally 9,000 pots and pans
0:07:29 hanging above her and then she’s surrounded.
0:07:32 She’s like her kitchen looks like a charcuterie board.
0:07:35 It looks like an overflowing charcuterie board, but she’s one of, she’s like a piece
0:07:36 of salami in the middle.
0:07:43 And that’s like the whole, her whole shtick, basically she, she says this, she’s like,
0:07:47 I’m going to sell perfection because she was, she was a perfectionist.
0:07:50 She was actually a pain in the ass to work for.
0:07:54 And the first book was called entertaining and it was about like entertaining guests,
0:07:55 basically.
0:07:58 And like creating an atmosphere of like warmth and things like that.
0:07:59 And it was a massive hit.
0:08:02 It sold 650,000 copies.
0:08:03 What do you think?
0:08:06 I feel like Nick Gray is the new Martha Stewart.
0:08:08 I’m just going to put that out there.
0:08:11 What Nick Gray is doing with the two hour cocktail party.
0:08:14 I think he’s just a, he’s just a young Martha Stewart right now.
0:08:15 Yeah.
0:08:21 Well, and she was like one of the early influencers because this was in the 80s.
0:08:26 This is when like mass media is really becoming a thing and it’s a massive hit.
0:08:30 And so like these women buy these books because it’s not just about cooking.
0:08:35 It’s about like being better, being aspirational, like perfecting a craft.
0:08:38 And she sold the sht out of this lifestyle and it was her lifestyle.
0:08:43 And she basically said in the documentary, she was like, I had visions early on of creating
0:08:48 this Martha Stewart media company all about me because I’m great.
0:08:52 Like I am what she’s like, she was very confident about that opening up the business plan.
0:08:54 Like, all right, Martha Stewart’s media company.
0:09:00 It’s about me next page because I’m great next page.
0:09:04 But she was, I mean, she was so like, there’s a lot of bad stuff that has gone on.
0:09:08 Like basically her husband cheats on her, she cheats on her husband.
0:09:10 Her daughter’s like, dude, she was a cold mom.
0:09:11 People complain working for her.
0:09:14 They’re like, dude, she’s just a fucking asshole.
0:09:20 And she was like throughout the documentary, they get her on camera being rude to her employees.
0:09:24 And so yeah, she’s like a perfectionist and she, she, she was like, I’m not, I’m not sorry
0:09:25 for that.
0:09:26 I’m a perfectionist.
0:09:27 But this forward through the business side.
0:09:31 So she does the cookbook, cookbooks a hit, massive hit.
0:09:37 And eventually one thing leads to another where Kmart, which was just like Kmart today
0:09:42 back then it was like, you know, lower, lower status store.
0:09:45 She partners with them to create like a line of betting when people are like shocked.
0:09:47 They’re like, why would this upscale woman do this?
0:09:49 And it turned out to be a great move.
0:09:50 It was really cool.
0:09:55 And then she partners with time and she creates a series of magazines and she’s the editor
0:09:56 of the magazine.
0:09:59 It goes really well, but she’s like, I want to own this son of a bitch.
0:10:05 And so she raises $85 million and she buys the magazine and three or four years later
0:10:07 takes it public.
0:10:10 And I showed the financials of her business.
0:10:14 It was basically, I think it was called Martha Stewart Omni Media.
0:10:19 Basically the, she buys the business and like something like three years later takes it
0:10:20 public.
0:10:28 In year three, it’s doing $130 million a year in 1997, $130 million in revenue.
0:10:29 And it’s a behemoth of a business.
0:10:31 So basically they’ve got the TV show.
0:10:34 They have tons and tons of magazines.
0:10:37 They have merchandising like the Kmart deal.
0:10:39 It just crushes it.
0:10:40 And it goes public.
0:10:48 And she becomes the first ever self made women’s billionaire in America and just annihilates
0:10:49 it.
0:10:51 But then something really bad happens.
0:10:57 So basically she’s worth like 400, 500, 600 million at this point because the stock was
0:10:58 going up and down.
0:11:01 Apparently she calls her stockbroker.
0:11:03 She’s like, Hey, I want you to sell this one stock.
0:11:07 So she sells this one stock and she made like 30 grand off of it.
0:11:10 Turns out a lot of people think that it was insider trading.
0:11:15 And so the DOJ like interviews her and figures out this whole thing and does this massive
0:11:16 investigation.
0:11:20 Turns out the charges of, of, of insider trading are dropped.
0:11:22 They’re like, you did not insider trade.
0:11:23 However.
0:11:25 So, sorry, she sold her own stock or she sold a different stock?
0:11:26 Oh, sorry.
0:11:27 Just a different, just a stock.
0:11:28 And only 30K.
0:11:29 So why was it a big deal anyways?
0:11:34 It was, so it was a big deal because we’re just, we’re, we’re basically there was like
0:11:37 Enron and a bunch of things like this were happening at the time.
0:11:41 And the DOJ was like, any insider trading, any like corruption, we’re going to go, we’re
0:11:44 going like really hard against all of this.
0:11:45 And so she like sell some stock.
0:11:46 It’s suspicious.
0:11:51 Turns out that the, the CEO of this, of the company whose stocks she sold, he was in fact
0:11:52 corrupt.
0:11:53 And they’re like, but you knew him.
0:11:54 What is going on?
0:11:55 You knew that this drug wasn’t going to pass.
0:11:57 You sold the stock, whatever.
0:12:01 The DOJ investigates her and they’re like, you actually, that looks clean.
0:12:02 It looks like you didn’t know anything.
0:12:08 However, when we interviewed you, you told us some small fact about how you were on a
0:12:09 schedule to sell this stock.
0:12:12 Turns out you weren’t on a schedule.
0:12:13 And so you lied to us.
0:12:18 And so we were going to put you in federal penitentiary for five months for lying, not
0:12:25 for insider trading, but for lying about this like somewhat not that big of a deal fact.
0:12:29 And so kind of bullshit kind of not like she did lie, but like she got five months in the
0:12:31 federal penitentiary and she’s like 50 years old.
0:12:35 And at the time, when all this trial shit happened, that’s when we realized that Martha
0:12:40 Stewart, she’s, she’s kind of bad.
0:12:45 She’s bad because there’s all these stories where the, it comes out, she’s a little rude.
0:12:50 And so, for example, her stockbroker has this assistant who would talk to Martha mostly
0:12:55 and like, there’s examples of like the stockbroker’s assistant being like, dude, she was the meanest
0:12:56 person ever.
0:13:00 But one time she called and I had to put her on hold and I go back to talk to her.
0:13:04 She goes, Hey, if you don’t change that waiting music, that tacky waiting music by the next
0:13:07 time I call, I’m going to have you fired.
0:13:11 And just hung up, just like hung up, like there’s like repeatedly like a bunch of stories
0:13:17 where she just didn’t, she was not like very kind to people and that kind of swayed public
0:13:18 opinion of her.
0:13:21 She goes to jail for five months and it sucked.
0:13:22 It sucked for her.
0:13:23 It was not good.
0:13:29 She went to jail and she ends up doing Justin Bieber’s roast, which again changed public
0:13:33 perception of her because at this point everyone was like, man, it’s kind of fun seeing Martha
0:13:39 Stewart kind of downfall because she was perfect woman, like effort, kind of nice.
0:13:40 Like it brings, brings me up to see this.
0:13:42 Yeah, I knew she was so perfect.
0:13:43 Yeah.
0:13:47 But she roasts Justin Bieber and she’s just like hilarious.
0:13:52 She talks about how she like shanked bitches in prison and how she like made this shank
0:13:57 with just like a piece of a pencil and some bubble gum and you could do one too at home.
0:13:59 I’ll show you how like, it like kind of humanized her.
0:14:01 It was pretty cool.
0:14:04 But her getting arrested, it decimated the stock.
0:14:08 So she was like on the documentary, she was like, I think I would have been worth $10
0:14:09 billion.
0:14:11 But when I got arrested, my stock went way down.
0:14:16 They ended up selling the company for like $300 million.
0:14:20 And it was kind of like the, it could have been like a great company, but it kind of
0:14:21 wasn’t.
0:14:25 And then there, throughout this whole thing, this whole documentary, Martha like has shown
0:14:31 time and time again, she’s a bad, bad woman, like in all sense of the word as in like,
0:14:32 she’s brutal.
0:14:33 She’s smart.
0:14:34 She’s conniving.
0:14:37 Her stock is only going up in your books.
0:14:38 That’s all I’m hearing.
0:14:42 All I’m hearing is like, let’s just summarize.
0:14:46 Good looking lady already off to a good start.
0:14:51 Then goes from model to sales slash stockbroker.
0:14:52 All right.
0:14:53 Amazing.
0:14:54 One interesting thing.
0:14:55 That’s cool.
0:14:56 Two interesting things.
0:14:57 You have my attention.
0:14:58 Third interesting thing.
0:15:03 Self-made, first kind of major tradwife influencer.
0:15:05 Does the cookbooks, does it her way?
0:15:08 Is ruthless with the details.
0:15:11 Has a no nonsense attitude.
0:15:12 She’s a stickler.
0:15:15 These are all, I mean, these are your safe wards, dude.
0:15:18 These are all the things that you enjoy.
0:15:21 This is really up your alley.
0:15:22 How do you feel about Martha Stewart right now?
0:15:25 Because it sounds like even when she’s bad, it just made her more good in your books.
0:15:26 Sorta.
0:15:27 I mean, she paid the price.
0:15:31 Basically, her husband left her, her kids, like she’s got a bad relationship with her
0:15:36 children because of the way she behaved and she basically, she’s 83 now, by the way.
0:15:39 I didn’t realize how old she was and like she hasn’t had a relationship since her husband
0:15:41 and her broke up.
0:15:43 She paid the price.
0:15:48 There’s a cost to be the boss, you know, and she paid it, but she is in fact the boss.
0:15:53 So I do have a lot of respect for her and I also think that there’s downsides to achieve
0:15:54 what she achieved.
0:15:56 But I’m shocked you didn’t know that.
0:15:57 Did you know any of this?
0:15:58 Like how she’s like…
0:15:59 Not really.
0:16:06 I knew she had like a cookbook or was on TV and that she sold like stuff to women.
0:16:08 That’s kind of the extent of what I knew about Martha Stewart.
0:16:10 Dude, she’s great.
0:16:15 And so another big takeaway, and I’ll wrap up here, is how big of a company you could
0:16:19 start and have just off the back of one person.
0:16:24 Like it was the Martha Stewart brand and she was like into that.
0:16:29 Like a lot of people would be fearful of like having that burden, having that on their back
0:16:34 of like literally a thousand plus employees and billions of dollars of value.
0:16:38 And she was totally into it and she loved it and I love those types of personalities.
0:16:39 Right.
0:16:41 But it sounds like this company wasn’t that good.
0:16:50 And your numbers table here, by 2001, it says total revenue 295 million, net income 21 million.
0:16:52 Which is obviously that’s good.
0:16:57 That’s not nothing, but that’s not a $10 billion company to make 21 million a year of net income.
0:17:03 And then it says from 2003 to 2015, which is like three presidents, it says consecutive
0:17:06 annual losses every year except for one year.
0:17:08 So was this really a good business?
0:17:11 Or was this actually just a lot of work for nothing?
0:17:12 No, it was good.
0:17:15 I mean, you have to think of a few things.
0:17:18 One, you know, it was making $300 million a year in revenue and a lot of it came from
0:17:22 publishing and publishing means subscription magazines.
0:17:24 So like that’s like pretty good.
0:17:27 But then the internet came and just completely like obliterated that industry.
0:17:31 I mean, that was like magazines are probably like the worst industry to be in.
0:17:35 So like, yeah, there’s a lot of what ifs and the timing was such that she got arrested and
0:17:40 also like, you know, Amazon was created and the internet was created.
0:17:46 So, yeah, there’s a lot of like what ifs, but I feel like if she was, I think she was
0:17:50 like 30 years too early, like I think if she had the internet, she could have become a
0:17:58 juggernaut because it sounds like her talent and her ruthlessness, that combination was
0:17:59 going to serve her well.
0:18:02 And it just she needed the she needed a better medium.
0:18:06 If she could have just own her own Instagram and TikTok channels and built everything off
0:18:11 the back of that, you know, I think she would have been the number one sort of like women’s
0:18:12 or mom influencer.
0:18:17 She arguably was that anyways of her era, but the market a hundred X’d.
0:18:18 Yeah.
0:18:19 Yeah.
0:18:25 I mean, like I think a lot of these like big celebrities, I think it was a little bit easier
0:18:30 to be a big celebrity in the 80s, 90s and early 2000s because there was less of them.
0:18:35 Now anyone with a cell phone can become a celebrity in like six or 12 months.
0:18:39 So it’s hard to say, but by the way, her businesses, her businesses still do like a billion a year
0:18:40 in sales.
0:18:41 Okay.
0:18:42 Gotcha.
0:18:44 You have something in your notes here.
0:18:46 Typical day of 60 year old Martha Stewart.
0:18:47 Yeah.
0:18:48 Read that.
0:18:51 It says she’s 60, but she looks a decade younger.
0:18:55 She’s been up since 430 a.m. She answers her email at five, takes a three mile walk with
0:18:56 her trainer at six.
0:18:59 She tours her garden at seven as when she tours her garden.
0:19:02 She’s thrilled to discover a duck and 13 ducklings in the swimming pool by 730.
0:19:05 She’s whipping up corn gruel for a visiting waterfowl.
0:19:09 I don’t even know what any of these words are animal and building a wooden ramp to help
0:19:11 them get in and out of the pool.
0:19:12 A duck.
0:19:13 Okay.
0:19:14 She’s doing all this stuff for a duck.
0:19:17 Her TV crew arrives at eight, her makeup a 30, and then she’s shooting her TV segment
0:19:18 by 9 a.m.
0:19:19 Yeah.
0:19:20 She’s crazy.
0:19:21 She’s crazy.
0:19:26 I literally woke up like 19 minutes ago and I rolled out of bed and I put on this hat
0:19:28 and then I started eclectic play.
0:19:30 I don’t think, I don’t think I’m built for this.
0:19:31 She’s a machine.
0:19:34 You know how like people say stories of like how Trump can only operate on three hours
0:19:35 of sleep.
0:19:36 That’s like a real thing, by the way.
0:19:39 There’s like a, it’s like, I forget what the name of it is like a thing.
0:19:43 She’s another person that she’s famous for only sleeping like three hours a night.
0:19:50 All right, my friends, I have a new podcast for you guys to check out.
0:19:56 It’s called content is profit and it’s hosted by Louise and Fonzie cameo and it’s brought
0:19:59 to you by the HubSpot podcast network.
0:20:03 After years of building content teams and frameworks for companies like Red Bull and
0:20:08 Orange Theory Fitness, Louise and Fonzie are on a mission to bridge the gap between content
0:20:09 and revenue.
0:20:12 In each episode, you’re going to hear from top entrepreneurs and creators and you’re
0:20:17 going to hear them share their secrets and strategies to turn their content into profit.
0:20:21 You can check out a recent episode called the secret to content that converts and they
0:20:27 break down our buddy Alex Hermozzi’s blueprint for effective video production.
0:20:35 So you can check out content is profit wherever you get your podcast.
0:20:36 Perfect segue.
0:20:39 Can I tell you what my best topic was that I wanted to talk to you about?
0:20:40 Yeah.
0:20:41 Osempic for sleep.
0:20:49 So there’s a guy, his blog is Isaac.net and he wrote this post about sleeplessness and
0:20:54 he basically says that there’s a set of people that are famous who have the short sleeper
0:21:01 genes, a set of genes for where about four to five hours a night is a full night’s rest
0:21:02 for them.
0:21:06 And he says that Mozart, Thomas Edison, Sigmund Freud, Margaret Thatcher, Obama, and he’s
0:21:11 like even my labmate, this guy’s a researcher, he’s like have this thing called short sleeper
0:21:13 syndrome.
0:21:19 And people thought that short sleeper syndrome would be you sleep less and maybe you’re able
0:21:23 to operate that way, but you know, it’s got to be bad for you.
0:21:26 Sleep we know is sort of the best thing for you and restores the brain and the body and
0:21:27 all your function.
0:21:30 And so these people must be dying younger and have more disease, right?
0:21:32 And it’s like, no, actually they don’t.
0:21:36 These people just simply have the benefit without the cost.
0:21:40 They sleep, you know, they need about three hours less sleep than the rest of us.
0:21:46 But they don’t pay the price in terms of, you know, the health consequences of that.
0:21:49 And so he goes on this post and he basically outlines that.
0:21:52 Who are these people, by the way, in this photo?
0:21:56 So he says, you know, my favorite family is this family called the Johnsons from Utah.
0:22:02 And the Johnsons from Utah are a set of researchers and I think a bunch of them have this short
0:22:05 sleeper genetic makeup.
0:22:09 And so they’ve been researching this for a while and it’s about, you know, 1% of people
0:22:14 have this thing where you don’t need as much sleep and it does not seem detrimental to
0:22:17 your health or your productivity.
0:22:19 And they’ve studied why is this?
0:22:20 What is it?
0:22:22 Is it one gene?
0:22:23 Is it not?
0:22:27 And they’ve basically like, there’s four kind of like protein changes that they’ve noticed
0:22:32 of, you know, variations in the glutamate receptor, GRM1, blah, blah, blah.
0:22:33 So there’s these four things.
0:22:38 And then they’ve done some tests in mice and others where they do like knockouts.
0:22:41 So they’ll knock out one of the genes and they’ll see if it, you know, makes the mouse
0:22:44 sleep less or sleep more and they try to understand that.
0:22:49 Can you do that to like, when you say knockout, does that mean like you’re a living being
0:22:51 or when they reproduce?
0:22:53 A living being.
0:22:54 That’s how the body works.
0:22:55 You could just like.
0:23:00 I said that with so much confidence for somebody who has no idea, but I think that you could
0:23:01 do that.
0:23:02 I’m a bio major.
0:23:03 You could check that.
0:23:04 That’s a fact, Jack.
0:23:07 But I don’t know if you could do, I don’t know if this is done at the embryo or in the
0:23:08 living thing.
0:23:10 But the point is they’ve tested this in mouse models.
0:23:12 Mouse models don’t always apply to human models.
0:23:14 So there’s some question there.
0:23:19 But the, the researcher sort of points out actually, you know, usually when mouse model,
0:23:23 when things that work in mice don’t work in humans, it’s cause they tried it and it worked
0:23:28 for the first time in mice and then it takes a long time to even try it in humans and maybe
0:23:29 it won’t work.
0:23:32 It’s like, in this case, we’re observing it actually in humans and then we went back
0:23:38 to mice and tried to recreate that those genetic mutations or those genetic changes.
0:23:41 And so this is really exciting.
0:23:46 So what he’s talking about is like in the same way that we found drugs like ozempic,
0:23:53 which could modify your appetite, it could change your need for food in a way that had
0:23:56 all these downstream health benefits, right?
0:23:59 You change your need for food, you reduce your need for food, now you eat less, obesity
0:24:04 goes down, they’ve seen that it helps with things like addiction to alcohol or there’s
0:24:06 like all these other things that people are noticing with these.
0:24:08 That’s the ozempic case.
0:24:10 This guy is saying you could do the same with sleep.
0:24:11 And is this guy Isaac?
0:24:15 Is he the researcher or is he just blogging on this?
0:24:17 He’s a researcher who is blogging about this.
0:24:18 Wow, got it.
0:24:21 And he’s basically saying that like potentially we could create something that does the same
0:24:28 thing that how ozempic reduced your need for food, that we could reduce your need for sleep
0:24:33 and make you mirror these people who have this already where they don’t suffer the consequences
0:24:34 of less sleep.
0:24:38 Like you do the math and you’re like if you’re saving three or four hours a night of sleep,
0:24:43 you basically, it’s like the world’s best longevity trade.
0:24:46 So what most people are trying to do with longevity is like, oh, if I’m living till 80,
0:24:47 can I live till 90?
0:24:50 If I’m living 90, can I live till 100, 100, 110?
0:24:55 And they’re trying to push off the like that last marginal decade of poor health where you
0:24:59 can’t walk as much, you can’t see as well, you know, if you’re in pain, all that stuff,
0:25:01 you’re trying to push that back as far as you can.
0:25:04 This would make it so that you actually just live better.
0:25:07 Like the days where you’re healthy, you have more days, you’re awake for more of the time.
0:25:13 And it’s the equivalent of an extra 10 years, but you get the 10 years, not at the end,
0:25:17 you get it sort of all along the way while you’re in your best health of your life.
0:25:19 And that would be the promise of this.
0:25:20 And so how exciting is that?
0:25:24 I feel like it’s possible that somebody’s going to make an ozempic for sleep and it’s
0:25:29 going to allow us to, instead of needing eight hours, I can sleep for five and feel just as
0:25:31 good as I would on eight.
0:25:35 Somebody says, this is like adding 10 more years to your life, an 80 year lifespan, eight
0:25:42 hours a day to sleep compared to 80 years with four hours of sleep, that’s 10 years.
0:25:43 This is amazing.
0:25:47 On top of that, by the way, there’s people who suffer from insomnia and narcolepsy and
0:25:49 like, there’s all these actual like sleep apnea.
0:25:52 There’s all these things that affect people’s sleep.
0:25:55 Maybe you could alleviate those along the way, right?
0:25:58 Like if, you know, there’s, there’s thousands of Americans who have those problems, could
0:26:00 you also improve those?
0:26:01 Okay.
0:26:02 First of all, this is amazing.
0:26:03 This is great.
0:26:04 Fine.
0:26:05 I’m reading his blog.
0:26:06 His writing is really great.
0:26:09 It doesn’t write like a, that’s why I was shocked that he’s a researcher because he’s,
0:26:14 I think like there’s like a quote where he goes, this is crazy.
0:26:17 Like they don’t, they don’t normally say things like that.
0:26:18 Yeah.
0:26:19 They don’t have personalities usually.
0:26:20 This is profound implications.
0:26:22 By the way, he’s 22 years old.
0:26:28 He’s a PhD student at MIT, exploring brain simulations as alternative path to beneficial
0:26:29 AI.
0:26:35 And in the past, he skipped out of high school in rural Austria to graduate early in his
0:26:36 gap year.
0:26:40 He created a $1 million non-profit and ran the most viral tech conference of the year
0:26:43 that had Sam Altman and others come.
0:26:51 He’s a self-taught Mandarin last year and did his undergrad at Berkeley in two years.
0:26:52 Guy’s a winner.
0:26:53 Doing well.
0:27:02 And he owns Isaac.net, like great down my name, Isaac with a K.
0:27:03 This guy is great, man.
0:27:09 Well, what I was going to say was, is this, I’ve never, I’ve, I’ve heard of, you know,
0:27:14 that gene a little bit that you’re discussing, but it’s just funny that there’s just some
0:27:18 kid with a 22 year old with a personal blog.
0:27:20 And this is the first time that I’ve ever heard about this.
0:27:21 Is this-
0:27:22 That’s what I’m saying.
0:27:26 But if he, if he’s just talking about his blog, is this like something that actually
0:27:33 has, like, why is there not more press or press releases on this topic?
0:27:34 Is it actually legitimate?
0:27:35 There is now.
0:27:36 We just broke it, dude.
0:27:37 This was the tipping point.
0:27:40 You’re going to see other people working on this, you’re going to see people talking
0:27:43 about this, there’s going to be misinformation everywhere.
0:27:44 It’s going to be great.
0:27:49 The story is awesome just because I like Isaac and also I would like to do, I would like
0:27:50 to not sleep.
0:27:57 I would either be skinny, like Ozempic, and not, and eat less or be like chubby or whatever
0:27:58 you like.
0:28:01 No dude, if I could sleep only five hours instead of eight, I’m going to give a shit.
0:28:05 I would be the fattest man on earth to do that, no, just joking, but like, that is a,
0:28:10 that is a way better superpower to need less sleep, to get back three hours a time every
0:28:11 day.
0:28:12 That’s debatable.
0:28:16 I think that people will always prefer to be skinny over sleep.
0:28:17 Less sleep.
0:28:18 You’re dumb.
0:28:19 That’s so dumb.
0:28:23 If they prefer to be skinny over, like, have an extra three hours of life every day.
0:28:28 If the average 25-year-old, if you’re like, look hot or live to 90 versus 80, they’re
0:28:31 going to choose hot over sleep any day of the week.
0:28:34 Well, this is why we don’t ask 25-year-olds questions.
0:28:36 The brain is not fully formed yet.
0:28:37 This is a great find.
0:28:45 His blog, according to similar web, just shot up to 125,000 visitors in October.
0:28:46 What did he, like, before it was new thing?
0:28:49 I published this in November, so that’s kind of cool.
0:28:51 So Ben found this and he sent it to our friends.
0:28:58 Our friend invested in a company that made a GLP-1 drug and, like, sold for billions
0:28:59 of dollars.
0:29:04 And so he sent this to him because he’s like, oh, you, like, you did that early Ozympic thing
0:29:05 before.
0:29:08 Ozympic was like a known thing, like, seven years before he invested in this company that
0:29:10 was going to work on, on that.
0:29:12 And it paid off in a big way.
0:29:15 So he sent it to him and that guy was like, I don’t know how you found this.
0:29:17 This is the best thing I’ve read all year.
0:29:20 Like, I’m so excited about what you just sent me.
0:29:25 And it was such a great example of Ben being Ben, where Ben has on one side a really curated
0:29:29 feed where he’ll find interesting things like this, like, he’ll be, he doesn’t follow many
0:29:32 people, but he’ll be following a guy like this Isaac guy.
0:29:35 And then he knows who to route the information to.
0:29:39 And it’s, he’s like a, he’s like FedEx, like he doesn’t touch the package.
0:29:42 Like, when I, when I get this, I immediately start doing research.
0:29:43 I write notes.
0:29:44 I go talk about it.
0:29:47 I’m not passing it to somebody smarter.
0:29:49 Ben’s like, he’s like a FedEx guy.
0:29:53 The package comes off the conveyor belt, he grabs the box, tosses it in the truck, drives
0:29:56 it to the address, drops it off and doesn’t ask any questions about what’s inside.
0:29:58 He just knows that’s useful for you.
0:30:00 I think this is useful for you.
0:30:02 And he just does that all day.
0:30:03 I had him like add me to all these group chats.
0:30:06 Like he was always texting people, but I said, yo, just add me, I just want to be a part
0:30:07 of these.
0:30:12 So now I’m in probably like 60 group chats where it’s me, Ben, and a mutual like acquaintance
0:30:13 or friend.
0:30:15 And he’s just doing this all day.
0:30:18 He’s just routing packets to each other, to different people about, I think you’re into
0:30:20 this kind of thing.
0:30:21 That’s ridiculous.
0:30:22 How is he going to monetize it?
0:30:24 Can he ever monetize this?
0:30:25 Ben?
0:30:26 Yeah.
0:30:27 Dude, we monetize this phenomenally.
0:30:29 This is the secret of Ben.
0:30:31 He just tries to be useful.
0:30:33 And then he’ll be like, Hey, yeah.
0:30:38 Remember that guy, like you met a year ago who you then didn’t talk to ever again.
0:30:39 I’m like, yeah, I think so.
0:30:40 I think I remember that guy.
0:30:41 He was cool.
0:30:42 He’s like, yeah.
0:30:47 We text daily and he’s got this new thing and it’s taking off and he wants us to invest.
0:30:49 He’s not letting anyone else in.
0:30:50 And then we invest in it.
0:30:55 It’s incredible how this karma just comes back 10-fold for Ben and he never asks for
0:30:56 anything.
0:30:57 He never asks.
0:30:58 It’s amazing.
0:31:02 He texts me like a fair bit, like just like, solve this thing.
0:31:03 You might like it.
0:31:08 Like, you know, I saw I’m the recipient of some of these things and I, I hate texting.
0:31:12 Like I hate like being at my computer and like constantly having to go back and forth
0:31:16 with 10 different people, which is how a lot of people’s computers look right now where
0:31:18 you’re like, it’s between Slack and messages.
0:31:22 You’re just like going back and forth with 15 or 20 people at all times.
0:31:23 And you’re like, what did I do all day today?
0:31:24 I just like chatted.
0:31:25 I just chatted.
0:31:28 And so I don’t like doing it.
0:31:32 Do you fall into that trap like throughout the day where you’re like, dude, I just like
0:31:33 texted people all day.
0:31:38 Yeah, I like Slack because I like my projects that I’m working on, but I don’t text much.
0:31:39 I’m a very bad text here.
0:31:41 And if anyone’s out there who’s texting me, I really apologize.
0:31:44 I probably have not texted you back.
0:31:47 So I’m prolifically bad at it.
0:31:49 Ben is prolifically great at it.
0:31:52 And that combination has really helped.
0:31:53 The combination has really helped.
0:31:55 And now people don’t, they just bypass me altogether.
0:31:57 They go to him and it hurts my feelings sometimes.
0:32:01 I’m like, wait, I thought I was friends with this person, but now I understand why.
0:32:02 Because he’s just a better person.
0:32:03 He’s a better texture.
0:32:09 In fact, he was like, I need to make a shirt called I reply because that’s my thing, dude.
0:32:10 I reply.
0:32:11 It’s pretty easy.
0:32:14 And I was like, you should write like the modern day how to win friends and influence
0:32:16 people because that’s what he does.
0:32:21 He wins friends and influences people with the most basic, the most basic of things.
0:32:24 And I was like, you couldn’t sell a…
0:32:29 The thing you do creates like tons of value, tens of millions of dollars in value for us.
0:32:34 You couldn’t even teach people this because you would say what you do out loud and they’d
0:32:35 be like, that was it.
0:32:38 I showed up for the seminar for that.
0:32:39 That’s basic.
0:32:40 It’s basic as hell.
0:32:41 But that’s what he does and it works.
0:32:42 That’s insane.
0:32:43 I think it’s funny.
0:32:50 By the way, Google, Isaac Freeman, very good looking, young, stylish black dude.
0:32:52 This guy’s got it all.
0:32:55 This guy’s got it all.
0:32:58 If he just becomes an astronaut, he’s basically the modern day James Bond.
0:33:01 I mean, he’s got like cool glasses and a jawline.
0:33:02 Yeah.
0:33:06 Get him over.
0:33:08 You said you had a bunch of exciting things.
0:33:09 You want to do it all?
0:33:12 By the way, you know, we don’t judge a book by its cover.
0:33:14 So like, you know, looks, looks do matter.
0:33:15 Let’s be clear.
0:33:19 We try not to judge people by their looks first.
0:33:23 But once we take a look at what you do, we then go and take a look at how you look.
0:33:25 And it either is like a plus 100 or it’s a minus 100.
0:33:31 It’s a huge multiplier on my opinion of you and how much I’m going to remember you afterwards.
0:33:32 I will never forget this guy.
0:33:33 Yeah.
0:33:37 Like if he were dorky looking, I’d be like, yeah, makes sense.
0:33:38 Right.
0:33:47 And then I see what he looks like and I’m like, oh, it’s tough to be like looking at.
0:33:50 But by the way, most people when they have an avatar as their Twitter profile, it’s
0:33:54 because they’re goofy looking and the avatar is better looking than that.
0:33:55 They’re making me question everything.
0:33:58 Like there’s a reason I have a cartoon profile picture.
0:33:59 All right.
0:34:00 Look at me.
0:34:01 If you’re on YouTube, look at me.
0:34:03 This is why I have a cartoon profile picture.
0:34:04 Okay.
0:34:05 That’s the rule.
0:34:09 It’s like when someone quotes you revenue, they would have said profit if they had it.
0:34:10 Right.
0:34:14 If somebody talks about users, they would have quoted revenue if they had it.
0:34:17 Normally, if somebody’s got the looks, they’re going to put their face as the profile picture.
0:34:19 This guy defies all convention.
0:34:23 I asked someone what the revenue was recently and there are like eight figures.
0:34:30 If you include the dot zero zero, that’s pretty funny.
0:34:33 That was pretty good.
0:34:35 All right.
0:34:36 A quick break.
0:34:40 I know that if you’re listening to my first million, that means you love numbers.
0:34:44 Well, I’ve got a new podcast called money wise and the premise is simple.
0:34:45 We talked to high net worth people.
0:34:51 So people who have somewhere between 50 to $500 million and we start with simple premise,
0:34:56 which is tell me exactly how much money you have, how much money you make every month,
0:35:01 what your portfolio looks like, how much money you spend every month, and every other bit
0:35:05 of information that involves your net worth and your spending.
0:35:09 And the reason we do this is because I want to demystify money.
0:35:14 So we just had this woman named Ann who has a $94 million portfolio after selling her
0:35:18 business and she spends $360,000 a month and she talks about where the money is and what
0:35:20 she spends it on and why she spends that much.
0:35:21 What if it makes her happy or not?
0:35:26 And then we dive deep on different topics like children buying versus renting, giving
0:35:27 money away.
0:35:30 We basically are having a conversation that I see a lot of rich people having behind closed
0:35:31 doors.
0:35:32 We do it publicly.
0:35:33 So check it out.
0:35:38 It’s called money wise and you can find it wherever you get your podcasts.
0:35:39 You want to do another thing?
0:35:40 Yeah.
0:35:41 All right.
0:35:42 I got some cool stuff.
0:35:44 Oh, you got to do this poly market whale.
0:35:45 Okay.
0:35:46 Yeah.
0:35:47 This is all right.
0:35:54 Let’s cue the music.
0:35:55 Million dollars isn’t cool.
0:35:56 You know what’s cool?
0:35:59 A billion dollars.
0:36:03 So you’ve heard this story, I think, but can I just explain a little bit of the detail
0:36:04 here?
0:36:05 Amazing.
0:36:06 I read about it a little bit.
0:36:07 Do we even know who this person is?
0:36:08 Yeah.
0:36:14 So the election was happening what 10 days ago or so and the big news was sort of, I
0:36:15 guess like there’s a battle going on.
0:36:17 There’s Republicans versus Democrats.
0:36:18 Great.
0:36:19 There’s Trump and Kamala.
0:36:20 Great.
0:36:23 They were supposed to be at that, but there was, there was an undercard to the pay-per-view.
0:36:24 And so who was the undercard?
0:36:25 Okay.
0:36:28 If Trump and Kamala are the main event, then I think the undercard, a lot of it was like
0:36:31 mainstream media versus social media, right?
0:36:37 You had like Twitter and blogs versus MSNBC and whatever, and they were, they were giving
0:36:38 you different narratives.
0:36:39 Right.
0:36:45 And so, you know, Joe, Trump and Vance go on Joe Rogan, Kamala goes on Saturday Night
0:36:49 Live and, you know, the view or 60 minutes or like, you know, these like traditional
0:36:50 media.
0:36:51 So that was one battle that was going on.
0:36:58 By the way, who would have thought like you seem like Theo Vaughn, uh, being like a needle
0:36:59 mover.
0:37:00 Insane, right?
0:37:01 I was saying this the other day.
0:37:05 I think that going on Theo Vaughn needs to be part of the national standard for an election.
0:37:07 Like I need to know if my president’s going to be a good hang or not.
0:37:09 And I think Theo is the one who could save us there.
0:37:10 Yeah.
0:37:11 That was insane.
0:37:14 So under that, then you have like the billionaire backers.
0:37:16 You got Elon on one side, you got more Cuban on the other.
0:37:19 And it’s like, they’re going around, they’re promoting, they’re using their money and their
0:37:20 voice to do it.
0:37:21 What was the other battles?
0:37:26 One of the other battles was polls versus crypto prediction markets.
0:37:29 So the polls were telling a story at the time, pre-election.
0:37:35 The polls were saying razor thin margin, toss up these swing states too close to call.
0:37:37 It’s a 50/50 election right now.
0:37:41 Like we don’t, it is too hard to tell who’s going to win.
0:37:45 And the prediction markets, which were people betting money, were saying something different.
0:37:50 They were saying 65, 35, Trump going to win.
0:37:52 And they’re different things, right?
0:37:55 A poll is, you know, you go out and you ask people, who are you going to vote for?
0:37:58 A prediction market is, who’s going to get the most votes?
0:38:02 So they do tell different things, but the reality is still the same, which is that if
0:38:07 the polls were accurate, that it was a 50/50 toss up, it’s going to be a razor thin margin,
0:38:09 then the betting market shouldn’t have such a big sprint.
0:38:13 There shouldn’t be a big favorite versus a big underdog.
0:38:14 And what was the polly market spread?
0:38:16 I think it was like 75, 25?
0:38:18 No, it was a little less.
0:38:20 It was about 63, Trump, but then it got to 65.
0:38:25 And then like as the election started, when the news was saying, you know, we’re still
0:38:29 too early, the odds were just jetting in Trump’s direction.
0:38:35 They knew earlier than the exit polls or the news was willing to report about how much
0:38:37 of a landslide this was going to be for Trump, which it was.
0:38:38 Okay.
0:38:42 So before it happened, there was a question of like, is the prediction market actually
0:38:43 predictive?
0:38:45 And there were some legitimate skepticism.
0:38:49 So the pro side was the betting market versus the poll market.
0:38:55 The betting, even just alone, should we care what polly market says?
0:38:59 And on one hand, the polly market being the platform where you could take these bets.
0:39:00 Exactly.
0:39:04 And so you, the plus side would be to say, well, these are people betting their own money.
0:39:05 So skin in the game.
0:39:09 And so if you see a lot more action coming in on one side, that means the sort of the
0:39:15 wisdom of the crowds and the actual free market believes the odds are this.
0:39:18 And that might be better than just the polls where people say, they’re just saying what
0:39:19 they’re going to vote for.
0:39:22 And it’s a small sample, but who knows?
0:39:23 Maybe they’re lying.
0:39:25 Maybe it’s just too small of a sample to know.
0:39:28 Maybe it’s not indicative of, there’s no skin in the game there.
0:39:30 So on one hand, you said skin in the game.
0:39:35 On the other hand, you would say, polly market, never heard of it, banned in the US, all the
0:39:38 betting action was from international.
0:39:40 So over $3 billion is bet on the election.
0:39:44 None of this was Americans because you can’t use polly market in America.
0:39:46 Then it’s also crypto holders, right?
0:39:47 Because polly market is a crypto betting thing.
0:39:51 So you’re like, oh, maybe there’s a bias crypto holders are more libertarian, maybe they’re
0:39:54 going to go more right, right, right leaning.
0:39:56 And so it’s what they want.
0:39:57 And Trump’s pro-crypto.
0:39:58 Yeah.
0:40:02 But maybe they’re voting on what they wish for and not what it actually is.
0:40:03 Okay.
0:40:05 So there were some question marks.
0:40:09 Then there was one more, then the news came out and said, you know, we can’t trust polly
0:40:12 market because it’s manipulated.
0:40:13 Manipulated how?
0:40:17 It’s manipulated because a couple of whales are betting heavily on Trump and that’s swinging
0:40:18 the odds.
0:40:22 So it’s actually, this is not what the crowds think, it’s really a couple of whales that
0:40:23 are influencing us.
0:40:24 And they saw that.
0:40:27 And you can see on polly market the size, like, can I see that?
0:40:29 Oh, someone just put this million-dollar bet in.
0:40:34 I can go on polly market right now and look at the top 10 betters and what they are bet
0:40:38 on, how much volume they’ve bet this year and how much their P and L is, are they up
0:40:39 or down?
0:40:46 So Theo4, I think is the biggest one on the platform and he has made a profit of $22 million
0:40:47 this year.
0:40:48 Exactly.
0:40:49 So that’s one user.
0:40:51 But you can go user by user and you can see, oh, this guy’s just betting on everything
0:40:54 or this guy’s one huge bet or whatever, right?
0:40:58 So you can go look at any better P and L on polly market.
0:41:02 So what they found was they were like, hey, there’s a couple of bets here that were in
0:41:07 the tens of millions on Trump and actually it all came from the same guy.
0:41:11 And what they were thinking was that there’s four big accounts that bet $28 million and
0:41:15 actually it turns out now after the fact the guy came out and said it, he had 11 accounts
0:41:23 and he bet $40 something million and he, $40 or $50 million and he made about $80 million
0:41:24 as a profit actually.
0:41:29 Sorry, I don’t know the exact bet amounts, but I know he made, he made $80 million profit
0:41:30 in the end.
0:41:31 A French guy, I think.
0:41:32 A French guy.
0:41:34 So they were like, who is this French whale?
0:41:38 And the story behind it’s pretty interesting because this guy was a trader.
0:41:40 He’s like, he’s taking finance.
0:41:45 He lived in the U.S. at one point, but basically he’s like, he’s like, I’m trying to remain
0:41:46 anonymous.
0:41:47 I’m trying to…
0:41:48 By the way, how on earth would a journalist find this person?
0:41:49 That seems really hard.
0:41:50 That’s a great scoop.
0:41:52 So on Polymarket, you could see the bet.
0:41:53 So you can go see, wow, this is a huge bet.
0:41:56 Then you go look at the account, you try to figure out whose wallet is this.
0:42:00 And because crypto is, there’s a public leisure, you can actually trace back and try to find
0:42:01 it.
0:42:02 And there’s a company called Chainalysis.
0:42:03 Do you know Chainalysis?
0:42:06 I’ve heard of it just like as a headline.
0:42:11 They’re basically the government goes to Chainalysis and says, we need to know who owns this wallet.
0:42:15 And they can go and do the forensic analysis of every transaction that wallet’s done and
0:42:19 tries to figure out the root wallet and who owns that wallet.
0:42:22 And so that’s, and this is like a $10 billion company, Chainalysis.
0:42:24 We have to do a breakdown of this company.
0:42:25 This sounds fun.
0:42:26 Yeah.
0:42:27 They’re a fascinating company.
0:42:31 And so they came out and they did this analysis and there’s like this web of the accounts
0:42:32 and like…
0:42:34 Dude, this is like all the best stuff.
0:42:38 Like crime and crypto stories are the best stories.
0:42:40 And so like working at this company would be super exciting.
0:42:41 And by the way, there’s no crime here, right?
0:42:42 So…
0:42:43 I know, but you know what I mean.
0:42:44 Totally.
0:42:46 So they come out and they say, all right, well, dude, how did you know?
0:42:49 Why did you make such a massive bet on Trump?
0:42:51 And this is where the story gets really interesting.
0:42:57 He says, he’s like, I didn’t trust the polls, but I trust polling.
0:42:58 What do you mean?
0:43:00 He goes, I commissioned my own polls.
0:43:04 There’s a French guy who commissioned polls in America to inform his own bet.
0:43:08 And what he did was he paid a polling company and he said, I want you to go and I want you
0:43:11 to ask them, but don’t ask them who they vote, who they’re going to vote for.
0:43:14 Because that’s what polls often ask is, what do traditional polls ask?
0:43:16 Are you likely to vote?
0:43:18 If you’re going to vote, who are you likely to vote for?
0:43:19 Are you certain of that?
0:43:20 You know, whatever.
0:43:22 Is there anything that’s going to change your mind?
0:43:24 Well, and I think they also ask, who do you…
0:43:26 I think they ask it in a weird way as well.
0:43:31 I think they also ask, who do you think your friend is going to vote for?
0:43:33 Notice that’s what this guy did.
0:43:34 Oh, God.
0:43:35 So this guy did was called the neighbor method.
0:43:38 And what he says is he says, don’t ask them who they’re going to vote for.
0:43:40 I don’t want to…
0:43:43 People are indirect and people don’t want to reveal their own preferences.
0:43:46 But if you ask them a specific question, which is, who do you expect your neighbor to vote
0:43:48 for?
0:43:53 They will indirectly reveal their own preferences and what they believe is going to happen.
0:43:57 And he believed that the neighbor method is a more predictive method.
0:44:01 And when he did this, he commissioned this poll, paid a major US pollster to go do these
0:44:03 polls for him.
0:44:08 Just like, you know, the DNC and the RNC, they’ll pay pollsters to go run their independent
0:44:10 polls that they’re not reporting to the public.
0:44:13 And he wanted them to measure this neighbor effect.
0:44:18 And what he found was that the results were, quote, “mind-blowing to the favor of Trump.”
0:44:21 It showed a Trump landslide.
0:44:23 And so he thought, now this is mispriced.
0:44:27 The media is telling you that this is 50/50 razor thin.
0:44:32 But actually, my polling is showing that, actually, this is going to be a major landslide
0:44:33 for Trump.
0:44:34 It’s overwhelmingly in favor of Trump.
0:44:35 So now the bet is mispriced.
0:44:39 So he places this huge bet on Trump.
0:44:40 And it turns out he’s correct.
0:44:43 And his final quote was, “Public opinion would have been better prepared if the latest polls
0:44:46 had measured using the neighbor effect.”
0:44:49 And he specifically didn’t just bet on the overall victory.
0:44:54 He bet on specific swing states where he thought, people think this state is closer than it’s
0:44:55 actually going to be.
0:45:00 It’s going to be more in favor of Trump using this neighbor method, which is just insane.
0:45:03 And now, of course, the French government is trying to ban the polly market.
0:45:04 We, we, guys.
0:45:05 This guy nailed it.
0:45:10 Two words, “bonjour,” my friend.
0:45:11 Yeah.
0:45:16 Fuckin’ A. First of all, what I respect about this is…
0:45:17 Everything?
0:45:18 Go.
0:45:19 I don’t respect everything about it.
0:45:26 I don’t love, I don’t love gambling like this, but people who have conviction on something,
0:45:29 like they do their own analysis and they’re like, “No, this is the answer.”
0:45:34 Even though all the quote smart people or everyone’s, the establishment is saying this.
0:45:39 But I, I did my own research and then he did the big part, which is he bet $30 million
0:45:40 or whatever of his own money.
0:45:46 I think that is like, those types of people fascinate me because that takes so much conviction.
0:45:47 Yeah, exactly.
0:45:51 This is, I mean, the guts that it, the brains and the guts, right?
0:45:59 And that’s how I think the theme of the year is like, you see someone like Elon, who basically
0:46:04 swings the election, who catches a rocket out of, you know, catches a rocket with some
0:46:10 chopsticks, you know, is working on self-driving cars, helps co-found open AI, which is changing
0:46:11 the world.
0:46:13 The guy is just, you know, like firing on all cylinders.
0:46:14 And it’s like, why?
0:46:17 What is it, what is different about this guy?
0:46:19 And it’s the combination of the brain and the balls, right?
0:46:22 Like, there are other people as smart as Elon Musk.
0:46:25 There are other people who have, you know, the risk-taking guts as Elon Musk, but the
0:46:27 combination is rare.
0:46:33 And then you add on top of that, the willingness to, you know, absolutely work to the bone
0:46:34 as well, right?
0:46:37 And then you add on top of that, like sacrifice your own life.
0:46:38 Yeah.
0:46:41 So he’s, you know, top 0.1% in like five things.
0:46:46 And then it’s like, oh, if you just multiply 0.1% times, you know, five times over and
0:46:50 over again, you end up with like one in 10 billion, which is like, oh, that’s actually
0:46:51 the ratio.
0:46:52 We do have one Elon out of the entire human population.
0:46:54 Dude, I thought it was impressive.
0:46:59 I was like, Justin Timberlake, you can sing, dance and act.
0:47:00 And you’re funny.
0:47:05 You know what I mean?
0:47:06 It’s super bad.
0:47:10 Elon just really stepped it up.
0:47:14 Oh, that’s a great call.
0:47:16 Is polymarket going to sustain after this?
0:47:18 Of course not, right?
0:47:19 Okay.
0:47:20 So I’ve been a big polymarket fan.
0:47:24 I was using polymarket before they banned it, like, you know, way back in the day.
0:47:26 You’re also a little bit of a DJN.
0:47:27 Yeah.
0:47:28 But I think a lot of people are.
0:47:29 Okay.
0:47:33 How much money have you and you first, by the way, you called this gambling.
0:47:34 I don’t believe that this is gambling.
0:47:39 Um, betting is like, well, like, for example, uh, you own stock.
0:47:43 Do you believe that you’re gambling gambling when you, when you buy a stock?
0:47:44 I guess.
0:47:45 What are you doing when you buy a stock?
0:47:46 Right?
0:47:47 Like, yeah, you are.
0:47:52 Um, I guess you would have to say that there’s, it’s not as binary, but there’s levels or
0:47:54 like there’s, it’s a scale.
0:48:01 So but yeah, you are just like if you buy car, you and I, it exists on a spectrum.
0:48:02 Yes.
0:48:07 So, so like, you know, the, with a stock, the chair, the, you know, the, the old fashioned
0:48:09 way of looking at it is I’m not buying, I’m not gambling.
0:48:15 I’m buying a piece of ownership in a company that produces goods and for, it’s like, yeah,
0:48:16 all right, cool.
0:48:19 He really in practice treats it like that.
0:48:23 Meaning you’re not sitting there like, you know, you’re, you’re not sitting there waiting
0:48:24 for dividends.
0:48:27 You’re not, you’re not trying to, you know, own this piece of this company because you
0:48:31 think it’s going to, you know, exit at a later date when it’s a public stock already, right?
0:48:35 Like you’re basically saying, I believe that, you know, the future earnings of this company
0:48:40 are going to be X and that, that’s why owning this is good because the share price is going
0:48:42 to go up because the earnings are going to go up and they’re maybe going to go up at
0:48:47 a faster rate than the current price of the earnings, current price of the stock indicates.
0:48:48 That’s what you’re supposed to buy, right?
0:48:53 You’re supposed to buy a stock that you think is going to, you know, appreciate over time.
0:48:58 I think that poly market has the ability to do that in a bunch of interesting ways.
0:49:06 So first there are the other speculation slash betting gambling type of use cases.
0:49:11 So speculating on prices of things, speculating on sports game, you know, sports outcomes
0:49:12 of games, right?
0:49:15 Like sports betting is obviously a huge deal.
0:49:16 So there’s those use cases.
0:49:17 There is an interesting thing.
0:49:24 So I’m guessing you didn’t read Vitalik’s blog recently about, about this.
0:49:26 That’s an accurate guess.
0:49:29 Vitalik, who’s the creator of Ethereum wrote a great blog post.
0:49:33 Vitalik’s one of my favorite entrepreneurs and thinkers on the planet.
0:49:38 So the blog post is called, I guess, from prediction markets into finance, into finance.
0:49:39 Info finance.
0:49:44 He, he’s like, you know, I have written a lot and I’ve supported poly market.
0:49:49 And many of you who know me might be surprised by this because Vitalik is sort of notoriously
0:49:53 like not into the like crypto casino side of life.
0:49:54 Like he’s not price based.
0:49:56 He’s not trying to get rich as like his primary motivation.
0:49:57 He’s kind of like a prude.
0:49:59 He’s a purist.
0:50:03 And so like it’d be like, why, why do you care so much about these like prediction markets
0:50:04 as people gambling?
0:50:05 Who cares?
0:50:09 And he’s like, because I don’t see it as that, I actually think that there’s another
0:50:13 category here that’s overlooked and it’s called info finance, information finance.
0:50:14 And he gives some examples.
0:50:17 So he’s like, poly market was two things at once.
0:50:22 He goes, on one hand, it’s a betting site for the few people that want to bet and gamble.
0:50:26 But for the rest of us, we could look at how the gamblers are betting.
0:50:29 And that would, for them, it’s served as a news site.
0:50:31 It was like, oh, wow, Trump is doing better.
0:50:35 Trump is improving in the same way that the polls are supposed to be part of the news.
0:50:38 The prediction markets were actually better news information.
0:50:39 So it was information finance.
0:50:43 So he’s like, that’s the first level, which was even if you’re not participating in the
0:50:47 betting, trying to, trying to make a buck, it is very useful that other people are doing
0:50:50 that, because it’s a new, it’s another source of information.
0:50:52 He’s like, it’s not, it should not be the only source of information, but it should
0:50:53 be another one.
0:50:59 He talks about the elections in Venezuela, how like, you know, basically he was watching
0:51:03 how people were protesting, how it was getting manipulated and blah, blah, blah, how poly market
0:51:08 was actually a very useful source of information for him in understanding what was going on
0:51:09 in Venezuela from an informational point of view.
0:51:10 All right.
0:51:11 So that was one.
0:51:12 Then he’s like, okay, what’s the other use case?
0:51:16 He’s like, so imagine a company.
0:51:20 So like, you know, I don’t know if you saw like Chipotle or Starbucks, uh, like Starbucks
0:51:21 just hired the Chipotle CEO.
0:51:22 Did you see that?
0:51:23 Yeah.
0:51:27 And he’s, um, the headline is that he’s working from home, even though he’s making everyone
0:51:28 else go back to work.
0:51:29 Right?
0:51:30 Yeah.
0:51:31 And he’s like private jetting in and out.
0:51:35 But like this guy’s kind of famous for like, he trims the menu, he cuts costs and he like,
0:51:37 he basically improves margins.
0:51:38 That’s what this guy’s known for.
0:51:42 And so the amazing thing was that guy, he’s that, he’s that guy.
0:51:48 And so like, uh, he’s him when it comes to markets, because when he switched teams, they
0:51:52 paid him a bunch of money and I was like, wow, what a huge stock package for a CEO is
0:51:54 like a hundred million dollars or whatever, whatever the number was.
0:51:56 But the stock jumped like $20 billion or something.
0:52:00 Like it was like, I’m making up numbers here because I didn’t plan to talk about this.
0:52:05 But like the stock jumped in a disproportionate way based on just the news that this guy was
0:52:06 coming over.
0:52:10 And so like, it was a great trade for them to overpay this guy, this talent, because
0:52:15 it immediately improved the overall value of the company, just the news of him joining.
0:52:19 And so Vitalik actually was like, just like there’s, today we’re looking at these as prediction
0:52:23 markets, you could actually use this as a decision market, meaning a company or a group
0:52:28 of people could set, could basically, in the way that that guy, Theo, paid for a private
0:52:31 poll to get information.
0:52:36 You could actually set up a prediction market and say, a decision market and say, should
0:52:43 we hire this CEO or what will the, that should be, what will the share price be in six months
0:52:46 if we hire Brian Nichols?
0:52:50 And if the share price expectation is really high, it tells you in advance, without having
0:52:55 to hire him yet, what the market reaction is going to be to making this decision.
0:52:57 Does that make sense?
0:53:01 And so you can actually create decision markets and it would be worth basically, basically
0:53:06 paying to, paying participants to go pick a side and make a bet in order to gather information
0:53:10 that will help you make a better decision about what you’re going to do.
0:53:15 And so he’s like, there’s, you can actually improve judgment if you were to, if you were
0:53:17 to make this decision.
0:53:21 And so I thought that was pretty interesting and he talks about, he goes through, you know,
0:53:24 how this might, how info finance might affect all these other things.
0:53:26 So for example, scientific peer review.
0:53:31 So right now in science, you submit a paper and he, there’s something called the replication
0:53:36 crisis, which is that famous results that end up being, you know, go into books and
0:53:40 in the news or whatever, then they can’t be reproduced, that study can’t be reproduced.
0:53:44 It’s like, is it even like the definition of good science is that it’s a reproducible
0:53:47 experiment, but that’s not happening.
0:53:51 And in fact, there’s not really a big incentive to go reproduce these because the incentive
0:53:55 is come out with a new finding, you get published, you get the glory, you get the funding for
0:54:00 your lab, spending your resources to reproduce a somebody else’s science, somebody else’s
0:54:01 big news.
0:54:03 It’s not really a good use of time.
0:54:09 And he talks about how prediction markets could actually create incentives for people
0:54:12 to go and try to reproduce these studies because you could have people betting on if this is
0:54:14 reproducible or not.
0:54:18 And so you’ll be able to profit off of knowing that this, this is going to be reproduced
0:54:19 or not.
0:54:22 So it’s pretty interesting to see how that might be applied in all these other ways.
0:54:25 I haven’t read this other than what you just told me and skimming it here.
0:54:27 First of all, this is like an amazing blog post.
0:54:32 I need to go read this second, if you go to his blog, if you go to like his other posts,
0:54:36 he’s publishes like a in depth post like every three days.
0:54:43 How amazing is this that we have access to a genius like this who just like shares his
0:54:44 thoughts.
0:54:48 And by the way, they’re like, if you read just the headlines and then click the articles,
0:54:50 they are not just like half ass block.
0:54:53 These are like in depth things that he’s publishing a shit ton.
0:54:58 How special of an era are, do we have, or we can like go and just read his thoughts.
0:54:59 That you get access to this.
0:55:00 Yeah.
0:55:04 And the beautiful thing about his stuff, which is I think hard to, because, you know, I was
0:55:06 thinking about this with podcasts.
0:55:11 It’s amazing now that there’s podcasts with, you know, like when we started this, I felt
0:55:14 like there was a slight differentiator in the business podcast space because we were
0:55:18 not just journalists, nor were we like never has been.
0:55:19 We had like done it.
0:55:24 We had started many companies or we’re in the process and we had, you know, sold companies.
0:55:25 We had done real things.
0:55:30 And so that was kind of like a interesting, Oh, what if you actually had a podcast from
0:55:35 from entrepreneurs who were actually like more successful than the average podcast.
0:55:38 Let’s say, I think you’re looking for the term for us by us.
0:55:39 We flew booted.
0:55:40 Yeah.
0:55:45 But now you, you have all in, you have, now you get to see billionaires, you know, doing
0:55:46 this read.
0:55:47 Hoffman has a podcast.
0:55:49 You know, Zuck is going on podcasts.
0:55:53 There’s like, who doesn’t have a podcast at this point, right?
0:55:54 And I think that’s really cool.
0:55:58 And the same thing is happening in sports, athlete, current athletes, past athletes now
0:55:59 have sports podcasts.
0:56:03 Whereas before the only sports pots you get was like, you know, hardcore fan in his in
0:56:08 his base mom’s basement, you know, ranting about his team or, you know, a journalist.
0:56:10 And now you have this like this third thing.
0:56:13 And the third thing is like somebody who’s actually been there and done that, who gives
0:56:16 their perspective, not to say it’s always better, but like, it’s interesting that that’s
0:56:18 now another good one to us.
0:56:22 But the problem with something like, let’s say, all in or other podcasts like that is
0:56:24 like, you have to always parse the agenda.
0:56:30 So it’s like, wow, this guy’s really bearish on nuclear and really pro-solar that you go
0:56:34 look into Chimás profile and it’s like, Oh wow, he’s made like enormous bets on solar.
0:56:36 And like, that’s just, he’s talking his book in a way, right?
0:56:37 And it’s okay.
0:56:43 You can talk your book, but it’s, you have to constantly do that, like underwriting yourself
0:56:46 as a listener to be like, are they, you know, what’s the bias here?
0:56:47 Yeah.
0:56:51 The beautiful thing about Vitalik is that the guy is such an uber nerd that like, you
0:56:55 can actually take him at face value and it’s so nice to have somebody you could take at
0:56:56 face value and other people might disagree.
0:56:57 I don’t care.
0:57:01 I take him at face value and I followed this guy for like, you know, eight years straight
0:57:06 now and I’ve, this guy’s done nothing to make me think he’s just trying to pump his bags.
0:57:12 In fact, he actively does things against his bags, you know, not pumping Ethereum or talking
0:57:16 about where it lacks or what’s slow about it and, you know, under promising what it’s
0:57:17 going to be.
0:57:21 And I think that that is, that’s great that we have access to this guy who is not trying
0:57:23 to take something from us in the process.
0:57:25 That’s a very good speech on this guy.
0:57:29 I’m going to, like, I don’t even think you could subscribe to his like, I don’t, there’s
0:57:33 not even an email form dude, his blog, like, so he publishes on, all right.
0:57:38 So listen, October 29th, October 26th, October 23rd, October 20th.
0:57:41 He’s been writing these posts a lot.
0:57:46 And those posts that I just said, I just put them into a word counter.
0:57:49 One of them was 6,000 words.
0:57:54 Now, I don’t know, like, I don’t know how Bitcoin work.
0:57:58 The dramatic look you just gave me when you said that, like I was supposed to like audibly
0:57:59 gasp.
0:58:02 Dude, that’s so much work.
0:58:03 I’ve written a lot of blog posts.
0:58:09 A 6,000 word blog post would take me 40 hours probably, right.
0:58:13 It’s so much work with you.
0:58:17 When you are this guy and you create Ethereum, is it one of the things where like, you’ve
0:58:19 created it and you can now walk away?
0:58:22 Or does it like, is it like a house and you got to like maintain it?
0:58:25 No, he’s actively working on it.
0:58:26 Like, I don’t know.
0:58:29 Is it like a thing where you’re like, I mean, it’s bigger than just him, obviously.
0:58:32 But like, yeah, he’s, he’s, you know, actively dedicated his life to this.
0:58:34 Like, you got to like, re-roof it every once in a while.
0:58:36 I don’t know how these things work.
0:58:37 Like Ethereum.
0:58:41 I don’t know, like, did you just, like, Ethereum was like a 10-year roadmap.
0:58:43 And so he’s just, it’s not even like re-roofing it.
0:58:47 It’s like building a hotel one floor at a time and people are staying in the hotel.
0:58:51 But you told them from the beginning, this is a 50-story hotel.
0:58:54 And I haven’t even built all those other things that we’re going to need in order for
0:58:55 this to work.
0:58:56 Like, there’s no elevators yet.
0:58:57 I know.
0:58:58 We’re going to make elevators.
0:58:59 For now, we take stairs.
0:59:00 So, transaction fees and all that.
0:59:05 The reason I’m asking is, how on earth is he writing this much stuff while doing like
0:59:06 a full-time job?
0:59:08 Because Ethereum doesn’t work like that.
0:59:10 It’s not like he’s sitting there coding all day or managing people.
0:59:12 Like, it’s not a company.
0:59:16 It’s like a nonprofit foundation, open-source project, of which he’s like a steward and
0:59:17 a champion.
0:59:20 But he’s not like, he doesn’t have like 25 direct reports, you know what I mean?
0:59:22 Does he have a girlfriend or wife yet?
0:59:23 I’m not sure.
0:59:27 I’ve seen a bunch of pictures, but it’s so hard with him to tell what’s a meme and what’s
0:59:31 like reality because he’s like so meme-able that like, when Bitcoin, when Ethereum price
0:59:35 goes down and then they post the pictures of him, they’re like, “God damn it, it’s because
0:59:36 he has a girlfriend.”
0:59:37 By the way.
0:59:41 Like, it’s his girlfriend, it’s going to be like, which way is it going to go?
0:59:45 So, it’s November 13th, we’re recording this exactly one month ago.
0:59:50 I came on this podcast and I said, “Tim, can I give you my one minute case for Bitcoin?”
0:59:56 And you literally rolled your eyes and audibly groaned at me and said, “Haven’t you already
0:59:57 done that?
1:00:00 Like, are you talking about why you like Bitcoin again?”
1:00:04 I just want to say, the price is up 47% since I did that rant.
1:00:05 All right.
1:00:09 Well, are you like that French dude?
1:00:11 Are you the French guy?
1:00:16 Did you, were you smart or just, or were you smart and ballsy or just…
1:00:17 Go back and listen to it.
1:00:20 It’s in the episode called, “Did the creator of Bitcoin get unmasked at the 30-minute
1:00:21 mark?”
1:00:23 No, I’m not debating if you said that.
1:00:24 I’m saying did you make your own…
1:00:27 I’m saying go listen to the case and say, did I get lucky or was I smart?
1:00:28 Did I have a reason?
1:00:29 No, that’s not what I’m asking.
1:00:31 What I’m asking is, did you make the bet?
1:00:33 Well, of course.
1:00:35 What do you mean?
1:00:39 Well, what I’m saying is, did you just say it was going to be good or did you actually
1:00:40 invest your own money into it?
1:00:41 Oh, dude, I’m polymarket, bro.
1:00:43 I was just getting in the game.
1:00:47 Does gambling on polymarket mean you have Bitcoin?
1:00:49 Well, it’s like polymarket versus a poll.
1:00:51 A poll is just saying what you’re going to do.
1:00:54 Polymarket is putting your money up saying what you think is going to actually happen.
1:00:56 I put my money up and said what I thought was going to happen.
1:00:57 Yeah.
1:01:00 I mean, it’s had a hell of a run, almost as good as Palantir.
1:01:02 Everything’s fucking crazy right now, though.
1:01:03 Like everything, when I look at…
1:01:05 Everything’s a little too crazy.
1:01:07 Everything’s too crazy.
1:01:08 It wouldn’t be…
1:01:11 I don’t know anything about anything, but it seems like it’d be a good time to make the
1:01:12 opposite prediction.
1:01:13 So, yeah, you were right.
1:01:16 It’s just like, how long are you going to be right for right now?
1:01:17 Everything is just like insane.
1:01:18 Yeah.
1:01:19 Yeah.
1:01:26 Of course, these are one-month fluctuations or nothing, but I guess the reason I thought
1:01:30 it was bullish was because it was the same reason that the thing is pumping right now.
1:01:37 Because there was a whole bunch of big things, like for example, that the government was
1:01:42 going to be pro-Bitcoin, which was always the biggest risk of Bitcoin, was like, “Oh,
1:01:46 even if you’re right about that technology being better, the government will never allow
1:01:47 this.”
1:01:51 Dude, the guy who’s going to become president is saying, not only will he allow it, he’s
1:01:55 bought and sold by the crypto donors now, and both sides are.
1:01:59 And I don’t know if you saw the Congress and the House of Representatives Senate, all that
1:02:00 shit.
1:02:07 There’s like 140 pro-crypto people now in active government, which is like…
1:02:11 That number was zero seven years ago, and I just felt like these things were not priced
1:02:12 in properly.
1:02:16 Now they’re talking about a Bitcoin strategic reserve for the country itself.
1:02:20 These things, once you’d go in, it’s almost impossible to unwind these things.
1:02:24 And I just thought that when a top two or three risk gets de-risk, that should change
1:02:26 your underwriting on the price.
1:02:27 And I thought that that wasn’t happening.
1:02:30 For some reason, the price was flat, and people weren’t paying attention to that one
1:02:31 fact.
1:02:32 What a world.
1:02:33 So in summary, I was right.
1:02:34 Thank you.
1:02:35 You were right.
1:02:36 You absolutely were right.
1:02:37 Everything is insane at the moment.
1:02:42 I hope your prediction will be true for many, many, many more months and many more years,
1:02:45 but it’s definitely making me nervous at the moment.
1:02:46 Everything is insane.
1:02:47 That’s where we end.
1:02:48 That’s where we end.
1:02:49 It’s been a fantastic podcast.
1:02:53 To Martha Stewart, to Bitcoin, to the Polymarket Whale.
1:02:54 That’s called…
1:02:55 Thank you for your service.
1:02:57 Hot, hot heat.
1:03:01 The hot, hot heat was served.
1:03:02 You’re welcome.
1:03:03 All right.
1:03:04 That’s it.
1:03:04 That’s the pod.
1:03:05 .
1:03:13 Thank you.
1:03:15 ♪ Back, right ♪
1:03:25 [BLANK_AUDIO]