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1000x · · 49 分钟

前 Palantir 分析师谈社会主义世界中的情报与市场运作内幕

Avi FelmanAlexander GoodJonah Van Bourg

YouTube
TL;DR
  • Alex Good(Wharton → Citi FX → Palantir → Balyasny → Perpetua 创始人,目前转向 Post Fiat L1)靠亲自为所交易的股票投放广告建立了自己的优势:EA 只需4美元获客成本就能找到一位愿意购买50美元游戏的用户,而 Booking 却要把“6美元利润中的5美元”花在广告上,估值倍数还更高,因此应做多 EA、做空 Booking。 这套策略碰到 meme stocks 后才“开始出现非线性”:Tesla 的广告点击全部来自搜索词“Elon Musk”,他由此意识到,alpha 不再是卖出一辆车的成本有多低,而是卖出这只股票的成本有多低。
  • 他的“金鱼理论”是可交易的核心:一个蒲公英茶页面多年把访问者转化率稳定在8%,从未是6,也从未是10,因此判断人们购买资产的偏好远比预测未来更可预测。 这个模型会在流动性分裂和信任流失时失效:STRC 与 MSTR 并列推出会把注意力漩涡一分为二;“Elon 放弃 SpaceX 对 Tesla 股价无疑是利空”;Anduril 若上市,也会对 Palantir 不利。在这一框架下,Bitcoin 占优,因为它没有竞争对手,而每个 alt-L1 都在争夺同一块蛋糕。
  • 他看空 Palantir,并警告100倍销售额估值会给投资者带来逆风。 Palantir 的核心说法是,LLM 处理企业数据需要依赖 Palantir 的 ontology 来避免幻觉,但他表示,“我只知道这不是真的”;随着模型进步,对 ontology 的需求“线性下降”。与此同时,OpenAI 和 Anthropic 已经各自部署 forward-deployed engineers,市场上“货架上现在有3个选项,而不是1个”。
  • 他判断,AI 失业将在约3个月内开始显现。 这不是因为失业已经发生——当前仍是充分就业,Accenture 也还有800,000名员工——而是市场正在强行推动这一结果:Figma 跌85%,Accenture 单日跌26%,软件股如今的估值倍数只有大宗商品公司的约一半。交易方向是寻找有可信 AI 利润率翻转逻辑的公司,以及 Nintendo 这类受瓶颈拖累的公司(受内存成本影响同比跌约60%)和拥有 Lindy 型 IP 的公司;Anthropic/LibGen 和解后,“所有未来的 AI Mario 都可能向 Nintendo 付费”。
  • Blackprint 的核心判断是,AI“已经不再是技术现象,而开始成为政治现象”。 Nvidia 约50,000名员工所对应的价值,超过整个 Russell 2000,而后者雇用了数百万选民;“人们不会投票支持一个在经济上无法让他们受益的右翼加速主义体系”,被 Accenture 裁掉的员工会成为非常有效的 Bernie/DSA 组织者。Trump 已经开始监管 Anthropic,这使两翼阻止模型发布的做法都趋于正常化。
  • 与 Andrew Kang 相反,他完全反对人形机器人交易。 Trump 已禁止港口自动化;他预计政府不会突然让蓝领工人失业。“鉴于国家安全尾部风险”,他也看空 AI-biotech:只要“有一个人在未经批准的情况下拿蝙蝠做实验”,整个方向就可能被禁。按照1945年的核武器类比,最终能留下来的将是计算机、数字经济和娱乐。“数据中心的账单怎么付?把所有人的脑子都煮坏。”
  • 终局判断是,生产率目前按年化口径增长6%,而不是 Microsoft CEO 承诺的10%,因此 AI 无法拯救二战时期规模的主权债务。 结果“基本就是一次主权保证金追缴”,这也是他进入 crypto 的原因。Robinhood、Interactive Brokers 和 Hyperliquid 会成为资本回流注意力经济的关键塑造者。Avi 总结说,这场对话反而让他对 Bitcoin 更看多了。
摘要 · 为研究而整理的核心内容

1. 亲自投放广告,才是优势来源

  • Good 的职业路径一路都由“经济上的必要性”推动:先在 Citi 做 FX,随后进入 Palantir 做大数据;之后 Balyasny 招他处理一个数据集,但 Stan Chart 和 HSBC 的 SWIFT 故障切断了数据来源,于是他创造了一套交易广告股的策略,甚至亲自去投广告。风控团队不断打电话质问他为何有约15%的组合仓位在 Amazon;他的回答是:“所有人都说零售业务价值为零。但我知道它值一大笔钱,因为我投放的这些广告全都能打平。”
  • 经典配对交易是:Booking 把利润中的约70%花在广告上,而 EA 只需4美元获客成本就能卖出一款50美元的电子游戏——“B 公司要把6美元利润中的5美元花掉,估值倍数却高得多。”于是做多 EA、做空 Booking,同时设置实时止损开关:如果 Call of Duty 当季的广告投放成本变贵,EA 就不再便宜。
  • 转折点在 Tesla:“我用 Tesla 衡量的 alpha,不是卖车的成本有多低,而是卖出这只股票的成本有多低。”Tesla 的每一次广告点击都来自搜索词“Elon Musk”。这让他进一步进入 XRP、Cardano、Binance 的联盟营销项目,最终把 Twitter 本身也纳入其中;为了维持联盟合作,他需要拥有10,000名粉丝,于是意识到:“我得开始在互联网上说点什么了。”

2. 金鱼理论:注意力比未来更可预测

  • 最初的观察来自 Amazon 上的蒲公英茶页面:它多年来始终将准确的8%访客转化为买家,从来不是6,也从来不是10。“你事先不知道谁会成为注意力漩涡,但一旦确认它就是注意力漩涡,就很容易预测它会继续成为注意力中心。”相比预测宏观,他宁愿估算看到 GameStop 宝可梦卡牌新闻的人中有40%会买入这只股票:“涉及交易时,我不喜欢预测未来。”
  • Jonah 追问:这个模型会在哪里失效?Good 的答案是流动性分裂和信任流失。STRC 与 MSTR 同时出现,就会把注意力拆分给两个相近的对象;Saylor 是一个“很好的实时案例”。信任流失的表现,就是他的星级评分下滑:蒲公英茶页面的转化率在评分从4.5星降到3.8星后也随之下降。“Elon 一旦放弃 SpaceX,对 Tesla 股价无疑是利空”;Anduril 若上市,也会对 Palantir 不利。
  • 对 crypto 的推论是:Bitcoin 没有竞争对手——没有其他资产成功建立起“固定供给的价值储藏”这一叙事;而 Ethereum、Solana 以及其他所有 L1 都在争夺同一块蛋糕。“这就是 altcoins 如此艰难的原因。”

3. Palantir 内部:以及他为何转而看空

  • 他是 Palantir Finance 的早期用户之一,该产品由 Thiel、Bridgewater 与 Palantir 共建,将信用卡和 SWIFT 数据转化为宏观信号。每次部署都有两面:一面是合规审查,例如“这个人在每桶油价130美元时卖出原油,但市场价格是80美元——这大概是转移定价”;另一面则是顺手带来的收入增量。Ontology 概念源自目标识别:“我怎么知道自己击杀的是正确的恐怖分子?……你甚至怎么知道 Osama bin Laden 就是 Osama bin Laden?”答案包括车牌、关联人和银行账户。
  • 他的看空逻辑是:Palantir 现在宣称,LLM 处理企业数据需要 ontology 层,而“我只知道这不是真的”——你完全可以把 AI 指向代码库,直接让它自己弄明白。随着模型能力提升,“对 ontology 的需求一直在线性下降”;各大实验室自己也在说,prompting 的作用已经比以往任何时候都小。
  • 另外,注意力也正在按他自己的框架发生分裂:Karp 曾公开嘲讽 Dario Amodei 关于失业率达到10%的判断——“你的 EQ 可能很高,但其实就是个弱智”;而 OpenAI 和 Anthropic(与 Goldman 一起)如今也在部署自己的 forward-deployed engineers。“货架上现在有3个选项,而不是1个。如果你的估值是销售额的100倍,就会面临投资者逆风。”

4. 数据是新一代无货源电商——但别卖掉,要把它变现

  • 在 LLM 时代,“将原始数据转成结构化数据的成本从未如此低”,因此原始数据的价值反而在上升。“数据采集就是新一代的无货源电商”;所有人都在成立数据公司,把数据卖给各家实验室。
  • 他的反共识观点是:“如果你真的认为一个数据源有价值,就不该卖掉它,而应该把它变现。”例如从化名的 crypto 投机者中生成尽可能丰富的数据集,然后在内部变现,而不是卖给某个实验室。这个想法源自他对 Morad 的 Popcat Telegram 群组感到失望:“一点都不好笑……里面没有人在做有用的协同。”数字文化等同于身份认同的判断是对的,“但你没有把它贯彻到底”。他的标准是:建立一个以 AI 为核心、自愿参与的指挥控制架构,而且自己加入时不会觉得可笑。

5. 裁员还没发生——这正是它即将发生的原因

  • 他承认现实与叙事之间存在脱节:Amodei 和 Altman 都在宣讲工作岗位的生存性风险,但“就业报告一出来,你会发现我们仍处于充分就业”。Figma 股价跌85%,员工人数却在增加;Accenture 跌60%,有800,000名员工,却没有裁员。“他们已经失去工作了吗?没有,绝对没有。”
  • 但市场正在强迫企业面对这个问题——Accenture 单日下跌26%,“让管理层迅速清醒过来”;市场也在持续重击 Salesforce 这类严重过度招聘的公司。他的判断是,失业将在3个月内开始显现,因为现有模型——“Fable 和 GLM 5.2 确实能提供良好体验”——会首先冲击那些在笔记本电脑上完成的工作。
  • 由此出现的交易机会包括:有可信 AI 利润率翻转逻辑的软件公司如今处于“估值倍数的谷底”,“当前大宗商品公司往往是软件公司的2倍估值”。如果内存瓶颈被打破,受制于瓶颈的公司可能反弹:Nintendo 曾因买不起内存而无法推出主机,股价同比跌约60%;把模型直接固化在芯片里的 etched-style ASIC 可能终结这一瓶颈。Anthropic/LibGen 和解后,ChatGPT 可以提取《Harry Potter》的“97%”,经典且经得起时间考验的 Lindy IP 可能获得付费机会:“未来所有 AI Mario 都可能向 Nintendo 付费”,Games Workshop、Disney、Hasbro 的 D&D 和 Star Wars 也都在等待重新定价,彼此估值相差悬殊。

6. Blackprint:AI 已成为政治现象,社会主义是回应

  • 核心判断是:“人们不会投票支持一个在经济上无法让他们受益的右翼加速主义体系。”数字很直观:Nvidia 约50,000名员工所对应的价值,单独就超过整个 Russell 2000,而后者雇用了数百万选民。市场押注“Trump 会一路走到底……右翼不知为何会继续赢”。他的反应是:“不对。”
  • 被裁掉的 Accenture 员工“会非常擅长组织 Bernie Sanders 的基层选票——这些人有能力”。Avi 补充说,DSA 已经在扶植越来越有能力的社会主义候选人,右翼民粹主义也在上升:马蹄铁理论下,选民群体不同,但都要求补贴。
  • 双方已经撕破脸:“Trump 介入并监管 Anthropic……开启了政治体系阻止重大模型发布的进程。”过去这会被视为“Biden 的做法”,如今却已在政治两翼实现正常化。接下来要看 midterms,这将是验证这一世界观的关键节点。

7. 会被禁的是机器人和 AI-biotech,而不是聊天机器人

  • 针对 Andrew Kang 关于通用机器人将在5年内进入建筑、家庭和流水线的愿景,他的判断是:“Trump 已经禁止港口自动化——连港口自动化都不行。”结合自动驾驶的前车之鉴,政府通过人形机器人直接砸掉蓝领饭碗的设想很可笑:有人攻击 Waymo,车辆就会被撤下道路一个月;换成人形机器人,情况只会更糟。Avi 追问,这难道不会让美国落后于 China?他直接回答:“我不认为那是赢得选举的方式。赢得选举的方式,是告诉人们你会保住他们的工作。”
  • 他同样反对共识性的 biotech 长线多头交易——“如果 Anthropic 治愈了癌症呢?”武汉事件之后,国家安全尾部风险意味着:“只要有一个人在未经批准的情况下拿蝙蝠做实验……只要发生一次事件,仅仅一次,它就会被禁。”迹象已经出现:人们已经在担心 Fable 调试你的代码库——这也是他们撤下 Fable 的原因。想象一下,如果 Fable 开始创造一种新的肽。

8. 泡沫还没结束:1945式安排,之后是主权保证金追缴

  • 他明确否定“AI 泡沫正在结束”的解读:娱乐应用还没有真正启动。如今个性化 AI 视频成本约55美元,质量也不够好;但基本上到2年后成本降到2美元,就能实现大规模个性化视频、有说服力的游戏 NPC,以及随着每秒 token 数呈指数增长而变得更好的信息流算法。他的类比是1945年的核武器:武器会被禁,某些物理学方向会被禁,但“计算机可以发展,数字经济可以发展,娱乐可以发展……数据中心的账单怎么付?把所有人的脑子都煮坏”。AI 只会让社会更接近它原本的样子。
  • 宏观上的刺痛感在于:本季度生产率增速约为年化6%,同比为2.8%——“Microsoft 的 CEO 说我们会看到10%……这差得太多了。”人们并没有创造更多工作,而是在创造更多资本,再把资本回流到注意力经济,这也是为什么 Robinhood、Interactive Brokers 和 Hyperliquid 会成为关键造王者。他同样怀疑 SpaceX 以2029年登陆火星或建设太空数据中心为前提的“离谱估值倍数”:“给政府出手打压某些东西的情景做判断,反而更容易。”
  • 最后的判断是,如果 AI 带来的生产率提升无法为二战时期规模的政府支出提供出口,“基本就是一次主权保证金追缴——这也是我进入 crypto 的原因。”Avi 自称进场前是 Bitcoin 空头,但总结说:“这整场对话,也许真的让我对 Bitcoin 更看多了一点。”

Alex Good

The first use of Palantir was like, “How do I know that I’m killing the right terrorist?” Because if you try to go to Afghanistan and kill all the people with beards driving a jeep, then you’re going to kill everyone, and you don’t know who’s who.

Jonah Van Bourg

Honestly, I have no idea how to introduce this next guy, but his name is Alex Good, and he is one of the most interesting people that I’ve ever had the pleasure of interviewing. Our conversation spans a ton of different topics, ranging from what’s going to happen in the age of AI to the rise of socialism to how to benefit and put money in your pocket based on what’s to come.

1. Who The F*** Is Alex Good?

Alex Good

I’m in the Popcat Telegram group, and Morad is in there, too. But he’s the main event. It’s Morad in the Popcat group, and people are glomming on to him, and I’m like, “This is the community that you build.” That’s not the community that I want to build. I want to build something where my bar is, “Would I use this product every day?”

Would I show up every day and do what the AI told me to do publicly? That was the bar. The Popcat group just wasn’t the bar. So I’m like, “Okay, what would it take to actually make a system where a large group of people voluntarily opted into the system and had a real command-and-control architecture with an AI at the center of it?”

Jonah Van Bourg

What was the issue with the Popcat group that you saw?

Alex Good

The issue with the Popcat group is 100% about the price of Popcat, and then it was about the promotion of Popcat. It wasn’t funny. The theme was, “Oh, we’re part of a community.” I didn’t see elements of a community forming there. There were not people helping each other out.

There were not people colluding usefully. It’s not like I’m in the Popcat group saying, “Hey, do you want to get into this venture deal with me?” It’s like, no, we’re all going to just post the Popcat chart and maybe engage with some tweets that Morad posted. That was the extent of the Popcat Telegram group.

The thesis that Morad had was more profound than that. It was like, “Look, in the age of AI, the only real identity is that we have these new digital cultures.” It’s very relatable because we’re on X, and to some extent, I would have never met you if it weren’t for X. So we natively understand that this is true.

The community on X is quite rich. There are DMs, meetups, in-person events, and deal flow, and it just wasn’t there for the memes. The meme coins were not useful social identity layers. But I was like, okay, I like the idea. I think it’s true, but you didn’t take it far enough. You didn’t have a real architecture.

That’s part of why I started a token. What would it take for me to join the group and not feel silly joining it?

Jonah Van Bourg

Right. Yeah.

Before we get into that, you’ve created something insane. You were telling me before that the only point of it is to basically increase its own value. We’ll get into it. We’ll name it, talk about it, and dive in. But first I want to ask you: Who the fuck are you?

Alex Good

Who the fuck am I?

Jonah Van Bourg

Who the fuck are you, man? I’ve known you for 4 or 5 years now. Yeah, we’ve met a few times in person. I’m a huge consumer of your content and tweets. I think that they’re brilliant. But you’ve lived a lot of lives.

2. The Advertising Edge: How He Read Stocks Through Ad Data

You’re a Wharton grad, former Palantir, former Balyasny. You started a company called Perpetua that sold, that got acquired. Then you became an independent trader. Then you started tweeting really actively. You started being an essayist. You have all these thoughts on the world, and now you built this thing called Post Fiat, which is a layer-1 cryptocurrency.

You’ve done more in a life than most people. You’ve done more in 10 or 15 years than most people do in a life. What are you doing? Who are you?

Alex Good

I was always really interested in trading and capital markets. I was very normal for a long time. I worked at Citi.

Jonah Van Bourg

Do you consider yourself not normal now?

Alex Good

I think I got weird eventually, and I can tell you exactly what happened. I was always looking for an edge in trading. I did FX, and then I did big-data stuff at Palantir, and we found a lot of interesting stuff with big data at Palantir. Then I worked on SWIFT data in Singapore.

When I showed up to Balyasny, I got hired because I had access to a data set that got cut off because of the SWIFT problems at Stan Chart and HSBC, and I had to invent a new trading strategy. That trading strategy was based on advertising.

So I traded Google, Facebook, and Twitter. Then I had to advertise things. Next thing you know, I’m advertising video games. I’m advertising OTA, Booking.com, and Expedia, and I’m trading those stocks.

When I started Perpetua, it was just a very simple observation that I knew, because of the advertising that I was running, that Amazon was incredibly undervalued. At Balyasny, risk was constantly calling me: “You have 15% of your book in Amazon, which is way too big.”

“Why do you own all this Amazon?” I’m like, “Because everyone is saying the retail business is worth zero. I know it’s worth a cajillion dollars because I’m running all these ads, and they’re breaking even on ads.”

It took a long time for this to adjust itself, but what ended up happening was that I just got really in the weeds on what it took to acquire a buyer of a thing—an advertisement. Eventually, we got so big at Perpetua that we started booking Crocs and Kimberly-Clark.

We were still selling data to funds, but when we started booking these big companies, it was no longer viable to trade. That’s how I got into crypto, because I was like, “What can I advertise that has an edge, that has a direct feedback loop?”

By this time, I’d already started seeing stuff like Tesla, way before meme stocks were in our common parlance. We’d be running ads for Tesla cars, and all of the clicks were coming from a search for “Elon Musk.”

Jonah Van Bourg

Can we take a step back for a second and talk about the strategy and how you found it and generated that edge? I think one of the most important things that you do as a trader is figure out what your edge actually is. Half the time, it’s searching for an edge, and then it’s monetizing the edge. So what were you doing, and how did you find it?

Alex Good

Yeah, it was actually a pretty funny thing. I showed up to work. I had been hired because I had this data set—or was supposed to have this data set—that I didn’t have, and they were like, “You have to come up with this strategy.” So they moved me from Singapore to San Francisco because I started the strategy.

I talked to a guy who owned $200 million of Facebook stock, and I asked him point-blank, “Have you ever run a Facebook ad?” He’s like, “No, I’m just in it because Zuck is a Chad.”

That was it. He was right, actually, in hindsight. He was right. But I was like, this is a huge opportunity, because people are trading these advertising stocks, and you can get real-time data about how well their ads are performing.

Then they’re like, “What do I actually advertise?” You have to advertise video games, or stuff on Amazon, or travel booking sites, or Groupon. All of a sudden, you’re advertising airlines, and suddenly you have a view.

A very simplified version of the strategy is that, at the time, about 70% of your margin at Booking.com was spent on ads. If you talk to the CFO of Booking.com, they’d be like, “Yeah, we’re very actively managing our advertising budget.” You’d say, “Look, dude, you can sell a $50 video game for $4, right? Why aren’t you spending all of your money? Why are you spending anything on TV ads? Why are you doing any TV ads?”

He’s like, “Well, we know the digital ads work, but we like the margin story. We can progressively increase our digital ads.” And you’re like, holy crap. At the time, Electronic Arts was cheaper on an EV/EBITDA multiple than Booking.com.

You’re like, okay, company A can acquire customers for a $50 video game for $4, and company B is spending $5 out of its $6 of profits, and they’re trading at a way higher multiple. So you go long Electronic Arts, you short Booking.com, you’ve got a pair trade, you’ve got the valuation on your side, and you’ve got the data on your side.

If those dynamics change in your quarter—let’s say, “Oh, Call of Duty ads are way more expensive this quarter”—then you’re like, “Okay, EA is not cheap anymore because their product is hard to acquire.”

So at the time, it was very normal. And then, I guess, to your question, it only got nonlinear once you started getting into meme stocks. Because at some point you’re like, “Wait a second. The alpha I’m measuring with Tesla is not how cheap it is to sell a car. It’s how cheap it is to sell the stock, right?”

And that’s how I got into XRP. That’s how I got into Cardano. That’s how I got into Binance affiliate programs.

That's how I got into X because I was running affiliate ads, and they were like, “Yeah, we're getting rid of our affiliate programs if you don't have 10,000 Twitter followers.” I'm like, “How am I going to get 10,000 Twitter followers? I need to start saying things on the internet.” And so that's how I ended up starting. Everything that I became was a sort of result of economic necessity.

3. The Goldfish Theory & Where The Model Breaks

Jonah Van Bourg

And I think it's crazy because you've actually witnessed the degradation of our markets and society in real time from the inside.

Alex Good

Just based on that framework, I used to use this data set to figure out if things were expensive or cheap, and I used to use it to express real views on the real world. Now I just use it to express views on attention.

Jonah Van Bourg

Yeah. Do you think that's right?

Alex Good

Yeah. And I think you realize, over time, at first you think that, and then you're like, “Okay, well, how much has Tesla gone up in terms of its real cash-flow generation since that time?” Enormously. So, at the time, Tesla is a meme stock, but they gave Elon capital, and he did useful stuff with it, so it's hard to really assess it that simply.

Even GameStop now has enough money that they're going to acquire eBay, and now people are really trading Pokémon cards. When GameStop was a meme stock, it had no fundamentals—zero fundamentals. Now it actually has fundamentals, right? Michael Burry was actually a GameStop investor because he saw the trading-card turnaround. These things aren't that simple.

In crypto, we see it too. At some point, Ethereum was worth $7, and it was ridiculous, and then eventually now you have Tether and Circle trading on Ethereum. So I think memes aren't necessarily just degradation. Sometimes these memes are hallucinations of our society, or hyperstitions, if you will, where capital flows into ideas and people that society wants to advance. So maybe we can talk about this hyperstitional vortex as an example of what you're getting at.

Jonah Van Bourg

I think at the core, to me as a trader, it just reminds me of that simple graphic from The Alchemy of Finance—the George Soros graphic of reflexivity—where perception actually does influence reality. Then you can get a flywheel effect: If people believe something is valuable, then it actually becomes valuable.

But there are 2 different outcomes here. It's like a meme—no matter how high it goes, it's not generating any value for anybody, right? It's generating value in the sense that you can sell it at a higher price point, but Tesla, as it trades higher, you sell the stock, you get the cash, and then you can actually invest and grow the company. So the perception of it as more valuable actually does make it more valuable. Or do you think that applies to memes as well?

Alex Good

Well, I think the frame that I learned to take originally was—I call it the goldfish theory. It's the idea that I noticed this pattern with Amazon sellers, where there was a guy selling dandelion tea, and every day, 8% of people who went to the page bought it. It was always 8%. It never went to 6%; it didn't go to 10%. It was always 8%, and it was like this for literally years, right?

And I'm like, “Why do 8% of people always buy this? They're different groups of people.” It turns out that certain things, like attention vortices—Elon Musk being Elon Musk—are actually very predictable, right? So, in a way, predicting people's affinity to buy assets is far more predictable than predicting the future.

That was sort of the frame that I took: You don't know in advance who is going to be the vortex of attention, but once you know that they are, it's very predictable that they're going to continue to be that. And so that allows you to create a more predictive mental model of the world than a lot of people in macro trading have. They're like, “I think this is going to happen. This is where the puck is moving.”

I would rather be like, “Yeah, I think 40% of people who see GameStop come up with a Pokémon card release are going to buy the stock, and that's going to drive the price up.” That's something I can wrap my head around. I don't like predicting the future when it comes to trading. So I think that's how I got into it, and I don't know if that answers your question.

Jonah Van Bourg

It does. It does, but there's just so much to cover here. I also want to understand where that model breaks, right? Because at some point, that model falls apart. You can't say 40% of people who come across Cardano are going to buy it ad infinitum. At some point, they stop buying it, right? So how do you assess that risk? Actually, Michael Saylor is a great real-time example of where the model breaks.

Alex Good

Okay. Fragmenting liquidity. For example, the dandelion example: If you launched another dandelion that was very, very similar to that dandelion, it would break the model. If you launch STRC in addition to MSTR, you break the model, because you fragment liquidity and fragment attention into 2 different things, which suddenly become comparable and previously weren't.

Trust matters a lot, too. The other thing about the dandelion tea example is that it was entirely based on product reviews. So if their product review went from 4.5 stars to 3.8 stars—if you start to lose trust in Michael Saylor, it's like his star rating going down—then the conversion rate drops.

There are things in real life that affect these conversion rates, and the most direct way to drop your conversion rate is to drop a competing product. Elon dropping SpaceX is unambiguously bearish for Tesla stock, because it's an attention fragmentation. A likely Anduril IPO would be bad for Palantir stock, because it's the same e-commerce dynamic with competition, and that's the most predictable fragmentation.

4. Why He's Bearish On Palantir

Actually, this is why altcoins have such a hard time: They're playing for the same pie. Bitcoin doesn't have any competitors, right? Bitcoin doesn't—there's not another store-of-value asset that has successfully argued that we just have a fixed supply and that's what we do. Ethereum and Solana are fighting, and then all these other L1s are fighting for their pie, and it's very competitive. So I think that's how the story breaks down.

Jonah Van Bourg

That makes sense. So you actually worked at Palantir?

Alex Good

I did.

Jonah Van Bourg

Was that out of college?

Alex Good

I worked at Citi in FX and equity derivatives, and then got picked up at Palantir.

Jonah Van Bourg

Right. And so when you were at Palantir, what were you doing for them? Was this data analysis?

Alex Good

Yeah. Peter Thiel and Bridgewater built a product called Palantir Finance, and I was one of the first users of the product. I was very fortunate to have a group of people train me at a young age to do all these quant trading strategies I had no idea how to do. Eventually, I realized that, because I was such an early user, I had a lot of leverage, actually. So I was like, “You have to hire me because I'm the only person who knows how to use this product.”

I worked on capital-markets stuff. We worked on 2 big projects. One was the application of credit-card data to predicting large-scale purchase decisions at the CIO-office level of a bank—basically, trying to predict macro slowdowns. I also worked on SWIFT data and processing: both compliance for SWIFT data and converting SWIFT data into, once again, macro signals.

It was always kind of like the 2 business lines. There was a revenue side where you're like, “How can I take this data to make more money for the CIO office?” That's the fun stuff. Then the bread and butter is, “This guy is selling barrels of oil at $130, and the price is $80, and it's probably transfer pricing, and you should do something about that.”

So that's always the 2 sides of a Palantir deployment: Help the business lower its future fines on one side, and then the other side is, once we've lowered your fines, here's the cherry on top—here's the revenue boost.

Jonah Van Bourg

I didn't actually realize that Palantir had a finance side to it that you were working on. Where is that today? I mean, you look at what's happening in the world of AI and as AI applies to finance—is that sort of what Palantir was doing back then? Was it just aggregating data, or were they building models to actively trade?

Alex Good

They were really early on machine learning. They would work with really big oil companies early on to make these lead-lag signals, where it's like, “Okay, you have this many shipping assets. Load this into the Palantir ontology and predict if there's going to be a blowout and a spread of oil.” That would go to their capital-markets desk, but then it would also go to their shipping groups.

In the early days of Palantir, people hated the stock. People hated the company because it was just a bunch of guys coming up with these insights, pseudo-productizing them, and giving them to the CIOs. Eventually, what Palantir evolved into was a much more elaborate product, right? They eventually productized all of this, and it stopped being consulting and started being delivered via Foundry and other products.

Jonah Van Bourg

There are different products. One of them is Gotham, which is a security product, and then Foundry and other ontology products are more revenue-generating. I think their business is split roughly 50/50 between the commercial business and the government business.

But you're kind of bearish on Palantir now, is what I'm hearing from you. You're tweeting a little bit about the fact that they're in a fight with Anthropic and OpenAI. It almost seems like everybody is in a fight with Anthropic and OpenAI. Every week, you see a new release from these frontier labs that could take out companies in this world. What's your view on what's happening in the world of AI? Are we seeing a brawl out in public between all these companies?

Alex Good

I think you're seeing a really specific brawl because Alex Karp called out Dario Amodei—basically called him out publicly in an interview. Dario was saying, “Oh, we're going to have 10% unemployment.” Karp was like, “If you think you're going to have 10% unemployment, well, guess what? News flash: you might have a high IQ, but you're actually retarded.” They're starting bigger and bigger fights.

And, yeah, I am bearish on Palantir now. The reason is that the assertion of Palantir is that LLMs don't work out of the box. They say you need Palantir for LLMs to work, and I'm just like—

Jonah Van Bourg

Is that because of the underlying data?

Alex Good

Oh, yeah. They're saying that in order for your business to properly use LLMs and avoid hallucinations with your large data sets, you need to have an ontology baked in so the agents know what to interact with. I'm like, I just know that's not true, right? I use LLMs all the time without any Palantir.

Jonah Van Bourg

Can you clarify what you mean when you say you need to have an ontology baked in? What do you mean when you use the word “ontology”?

Avi Felman

In the Palantir world, there is a model. The origin of Palantir is actually interesting: How do I know that I'm killing the right terrorist? If you try to go to Afghanistan and kill all the people with beards driving a Jeep, then you're going to kill everyone and you don't know who's who, right?

How do you even know that Osama bin Laden is Osama bin Laden? For the Toyota Hilux, you need his license plate number, you need his known associates, you need his interactions with other people, and you need his bank accounts. This idea of these things that comprise Osama bin Laden is a, quote-unquote, ontology.

In order to target the right things, whether they be financial assets or military personnel, you need to have a higher-level ontology to map onto it so that you know you're working with the right stuff. In the world of AI, they're using the same argument. They're saying, “In order for your AI agent to know that it's interacting with the right data sets, you need to label the data sets effectively. You need to have a model for when they've been acted on by a certain employee at a certain time in order for this all to work.” That's the argument.

But if you work with AI in real life, you know that's not true. You can point an AI at your codebase and just be like, “Yo, figure this out,” and it will.

As AI models have become more capable, the need for ontologies has decreased linearly. There are all these studies of prompting and how effective it is, and all the major labs are basically saying prompting is less important than it's ever been. You don't need to paste a 2-page prompt into your model for it to do the right thing anymore. Now you can just be like, “Build me a great website,” and it'll do it.

That's real-time evidence that the use of ontologies is a hack to make AI models more performant. The other thing is that there's a lot of fragmented attention. OpenAI has forward-deployed engineers. Everyone uses the phrase “forward-deployed engineer,” right? Anthropic has forward-deployed engineers with Goldman Sachs.

Palantir used to be special because it was the only one on the block with an intelligence product, and now there are 3. It goes back to what we were talking about with fragmenting attention: When there are 3 things in the store instead of 1, guess what? If you're trading at 100 times sales, you're going to face investor headwinds.

Jonah Van Bourg

Would you agree with the statement that structured data is less important, but raw data is still as important as it was before?

Alex Good

The ability to turn raw data into structured data has never been cheaper.

Jonah Van Bourg

Right. That's what I'm getting.

5. AI Won't Make You Useless — But It Will Take Your Job

Avi Felman

You could argue that the value of raw data is definitely going up a lot. That's something you're seeing in the market, right? The new drop-shipping is data acquisition. Everyone is starting a data firm to sell data to labs because it's much, much easier to do it.

Jonah Van Bourg

What are some opportunities in that? What are you seeing? Are you working on anything in that world?

Alex Good

My sort of view is that we've seen a crypto protocol do this, right? Grass. They sell data to labs. I'm not interested in that. My premise is that most people in crypto are here to speculate, and the information that they generate is very rich and very valuable. If you actually think a data source is valuable, you shouldn't sell it; you should monetize it.

That's what I'm working on: How do I generate the richest possible data set with a group of pseudonymous actors and monetize that information instead of selling it to an AI research lab? Just monetize it internally.

Jonah Van Bourg

Right. But that's, I think, pretty difficult for most people. One thing that I always come back to is that AI, for high-agency people who really want to get things done, is this massive tool of leverage. Your average person isn't taking advantage of it in any meaningful way. I think most people are using it as just another chatbot or an assistant, and people don't really go past that or beyond that.

What does that mean if you can start to have individual people build billion-dollar companies by themselves? Where does that leave us? Do you agree with the statement that AI is making the vast majority of people useless?

Alex Good

I don't think so. I think it changes the use case. We're not yet at that point—we're still at full employment, actually. A lot of these AI-unemployment things have yet to kick in.

Jonah Van Bourg

What has yet to kick in? Do you think it will?

Alex Good

I do. I think a good example is Figma's stock. It dropped 85%, and their headcount went up. Or Accenture dropped 60%, and their headcount is up. They have 800,000 employees, right?

We know that Accenture hasn't fired anyone, and the market has crushed their stock 60%. It's somewhat safe to say that the employee reduction is yet to come because it just hasn't happened, and the employment statistics don't reflect it. There's this huge disconnect between what Dario Amodei and Sam Altman are saying about this existential crisis and the need for MMT, and then the employment report comes out and you're like, “We're at full employment. You can't hire people.”

Do I think that people are going to lose their jobs? Yes, I do. Have they lost their jobs yet? No, definitely not. I think the most interesting primitive is not that we're going to have these solo shippers. It's more that there are a lot of people in the same boat. There are a lot of Accenture employees who are about to get laid off.

And then the question is: How can you use collective action to extract economic advantage? I think that's the interesting question, because there are different ways to approach it.

Some people are MMT maxis. They're like, “The way that we use collective bargaining is that we all vote to give ourselves money.” You're like, “Okay, well, what would that look like?” MMT is actually quite hard to distribute. The taxation that would be required is difficult because global interest-rate markets are not in a happy spot in terms of government spending. The idea of doing MMT on top of the current JGBs blowing up is hard.

You say, “Okay, well, you need taxation. What does that look like?” That probably is central-bank digital currencies. I think the thing that's going to happen is that more and more people are going to be focused on saying, “Okay, we tried to escape the permanent underclass. We didn't. We're all in the permanent underclass together. What are we going to do about it?”

That's a more interesting question. That hasn't kicked in yet. It's like a meme right now.

6. Unemployment In Three Months

Jonah Van Bourg

Right. But people really do take it seriously. I think that's actually a premise of why a lot of people listen to this podcast in particular, and to other financial media and news: People are trying to figure out, one, how much time do I have left? You're kind of saying it might actually be more elongated, I think, than what people are claiming right now—or what Dario and Sam are saying.

Then, how do I—where do I put my money to escape the permanent underclass? Is it even possible to escape? I want to start with the first question, and then you can walk me through what you think is going to happen. How long is it going to take before we start to see these unemployment numbers kick in and we start to see this permanent underclass actually form?

Avi Felman

I think, literally, unemployment should start kicking in within 3 months, and it's just because of Accenture.

Jonah Van Bourg

Within 3 months.

Avi Felman

Yeah. Because the Accenture situation was so extreme, the stock dropped 26% in a day. It's one of those moments where the management—

Jonah Van Bourg

If they weren't awake before, they woke up real fast.

Avi Felman

The software indexes are not bouncing back. The really egregious overhiring firms, like Salesforce, are getting their stocks crushed by the market. The market is being very, very clear with companies: You need to do RIFs. People didn't want to do it, and they're going to be forced to now because their stocks are down so much.

Jonah Van Bourg

Do you think there's a trade in that—that once they start laying people off, maybe these stocks bottom for a little bit?

Alex Good

I think so. I think some companies with credible AI turnaround plans, where they could genuinely deliver their software for much less, could have crazy terminal EBITDA margins. The joke is that commodity companies right now are oftentimes twice as expensive as software companies. The big diss used to be that, oh, you're trading like a commodity. It's like, well, dude, now commodities are twice as expensive as software.

So software is kind of bottom-of-the-barrel multiples. The bar for them to start firing people and delivering a product is really appealing. Stuff like Nintendo is not just software; it's also people competing with enterprise for things like memory. Nintendo just couldn't launch consoles because it couldn't afford memory, and so its stock is down 60% year-on-year. You're like, “Okay, well, what if memory breaks?” Then it can rebound. So, yeah, I think there are going to be a lot of opportunities.

One of the interesting AI developments is that you saw all this really, really hyped stuff with Etched. All the VCs were saying, “Oh, there's a new fundamental chip breakthrough.” It's essentially like what happened in crypto with ASICs, where you're like, okay, rather than serving a model that's massively memory-intensive with inference, what if you just literally put a model directly into an ASIC? Then you could run a physical model. Rather than having a generic GPU, you have a specialized GPU with a specific model running on it, which would drastically cut memory usage.

The interesting thing is that if you remove the overhang of a lot of these so-called bottleneck trades, a lot of companies that have been destroyed by the bottlenecks are going to bounce. So, yeah, there's going to be a ton of trading opportunity.

Jonah Van Bourg

Maybe you can talk about some specific companies and how they're going to do, I guess.

Alex Good

Yeah, Nintendo.

Jonah Van Bourg

Yeah, Nintendo's big. Okay.

Avi Felman

7. The Nintendo Trade & The Coming IP Goldmine

Alex Good

The other thing is that we saw the LibGen settlement with Anthropic, right? Essentially, LibGen scraped all the books in the world, and then Anthropic trained on LibGen. There was a big copyright settlement. People have proven, for example, that you can get 97% of Harry Potter out of ChatGPT. You can just prompt ChatGPT to get Harry Potter, and that's a problem from a copyright perspective, right?

There are all these companies with great IP franchises. Nintendo has a great IP franchise. If you're bullish on non-enterprise or more consumer-type stuff, there's a world where all future AI Marios pay Nintendo. Games Workshop would be another one, like Warhammer 40,000. That stock has done a lot better than Nintendo.

Jonah Van Bourg

That would actually be a huge value unlock.

Alex Good

Yeah, for Nintendo, if they actually allowed that to happen.

Jonah Van Bourg

Yeah. Right. If they allowed people to just create games with their own IP using AI, that would be massive.

Avi Felman

Yes.

Jonah Van Bourg

And I assume that you're thinking that this could apply to other areas as well.

Alex Good

Anyone with core canonical IP, Lindy IP.

Jonah Van Bourg

Right?

Avi Felman

Disney, Nintendo, Games Workshop, and many others, like Hasbro and its D&D IP. A lot of these things are very, very popular—Star Wars—and they all have really radically different valuations, right? Some of these charts are up and to the right; some of them are not, right? So there are different opportunities.

Jonah Van Bourg

I want to go back to the point about whether you think there could be mass unemployment coming in 3 months—or the beginnings of unemployment. Take that a step further and talk about, let's say, 6 months, 9 months, 12 months, or 24 months down the line. I mean, you've written about the Blackprint. Maybe get into that and talk about how you think the world is going to change because of these new tools that we have.

Alex Good

Well, yeah, I think there is a point, and I think we've already crossed the point where this has stopped being a technological phenomenon and has started becoming a political phenomenon. It's already showing; it's going to show up in the midterm elections, right? The next big checkpoint that I think would validate my worldview—and I guess, to succinctly summarize it—is that people won't vote for a right-wing accelerationist system which doesn't benefit them economically.

The math is actually crazy, right? There are 50,000 NVIDIA employees, and NVIDIA is worth, single-handedly, more than the entire Russell 2000. The Russell 2000 employs millions of people. So there is this extreme imbalance between the number of voters at NVIDIA and the number of voters in the Russell 2000.

Right now, the market kind of assumes that this will go on forever, that there's no Democratic outlet, that it's kind of Trumpistan all the way, and that the right wing will keep winning for some reason. I'm like, no, I don't think so. I think what's going to happen is that the typical Accenture employee who loses their job is going to be quite effective at coordinating grassroots Bernie Sanders votes, right? Those are competent people.

Jonah Van Bourg

Yeah. And you're sort of seeing that, I think, with the DSA. The DSA is extremely effective at what it's done right now, and it's installing socialist candidates across the board. The competency levels are going up among these socialist politicians. But it's true that on the right, you also see the rise of populism.

It's a little bit of the horseshoe theory here, where it's just different constituencies that are getting the benefits. On the right and on the left, I think both are appealing to people—whether it's giving subsidies to farmers or giving subsidies to people in the cities. It almost seems like that's where our politics is headed.

Alex Good

It's also Trump. Trump went in and regulated Anthropic. He already kind of started the process of the political system blocking major model releases. That's a big deal, because now that the gloves are off, it becomes acceptable to regulate and sequester AI in the name of the so-called public good.

It's normalized now on the right and on the left. Previously, that would have been a Biden policy. That would be a Biden move of, “Oh, we're going to stop this AI model from launching.” Now it's a Trump move. So I think you're going to see that the core thesis of the Blackprint is that the political system in the United States is not designed for hyper-acceleration.

8. The Sovereign Margin Call: Why AI Gets Regulated Like Nukes

The fantasy that people have that we're going to allow peptides is a good example, right? The FDA is like, “It's not very clear that peptides are even going to be legal,” right? Everyone's shooting these things up, but it's like, okay, what about human testing? What about human trials? What about the process of how we approve drugs in the United States?

If you look at the history of U.S. medicine, it's never been like, “Yeah, let's YOLO this vaccine.” Except for the one time we YOLOed a vaccine, and then it did not go that well, right? The one time we YOLOed a vaccine, there's myocarditis. It's a problem, right?

The backdrop is that, actually, right now, the consensus trade is biotech. Everyone is long biotech because they're like, “Okay, what the AI companies have to do in order to prove themselves is launch a cure.” Who doesn't want to cure cancer? What if Anthropic cures cancer?

Jonah Van Bourg

Do you think that trade is truly baked in already?

Avi Felman

Well, I think it's gone the wrong way. I'm bearish on the application of biotech and AI.

The reason is just national security. The tail risk is so high after we saw Wuhan. It's basically like all it takes is one guy running an unsanctioned experiment on a bat. There's a guy doing stuff in his garage with an AI model, and I just don't think that type of stuff is going to be tolerated in the medium term. I think you'll probably have—the second you have one event, just one event—it'll be banned.

Jonah Van Bourg

Right. All right. But don't you think that these pharmaceutical companies are, at this point, quite highly regulated? Wouldn't you assume that they would be able to figure out how to integrate AI for drug discovery in a way that's in the lane of safety? That would just accelerate their drug discovery process, but it would be overseen by the same regulators that we have now?

Alex Good

Well, it depends on what they’re doing and who has access to the AI models. Then it’s also, okay, what’s the uncapped risk of this behavior? If the uncapped risk is something like COVID developing, or some sort of virus or unintended consequences, it’ll be really hard. I think people are overly optimistic about deregulated AI acceleration.

Avi Felman

Actually, the reason is just because of Fable. If people are already worried about Fable debugging your codebase, which is why they pulled Fable, imagine if Fable is creating a new peptide. Wouldn’t that argument also apply to the development or deployment of AI in consulting firms and law firms, sort of across the board? If the government saw that it was actually going to cause tremendous job loss, wouldn’t they try to step in and stop that before we at least have social programs in place to deal with that fallout? Because our government’s not stupid. I mean, they’re incompetent, but they can see that this is going to happen. So, wouldn’t you expect them to act?

Alex Good

Yeah, you would. And you’d think they already would have, but they haven’t. That’s why I think the job loss is actually going to kick in, because Figma is already down 80%, and it’s for a good reason: the current models, like Fable and GLM 5.2, can actually deliver a good experience. So, the AI that we already have is kind of going to, I think, go after the laptop jobs, right? I don’t know if AI is going to be able to, for example—like Andrew Kang says—we’re going to have humanoid robotics. I’m totally on the other side of that.

Avi Felman

You don’t think humanoid robotics? I mean, this is good. Let’s dive into that. Everyone is talking about humanoid robotics. I had Andrew Kang on this podcast, and he gave me the whole spiel that specialized robotics are not nearly as useful as generalized robots. Therefore, we’re going to see robots in the next 5 years doing construction. We’re going to see them on assembly lines. We’re going to see them in people’s homes as cleaners. We’re going to see them as personal assistants. And you disagree with that?

Alex Good

Yeah. I mean, Trump banned port automation, right? So, even port automation was a no-no. And on the right—now imagine it on the left, right? The idea of the government on either side of the current political spectrum rugging blue-collar workers by allowing humanoid robotics, given the history of self-driving, is laughable.

Avi Felman

But wouldn’t that put us massively behind in our fight with China? If we’re not willing to adopt automation, we’re kind of messing up.

Alex Good

No, but I don’t think that’s how you win elections. I think you win elections by telling people you’re going to keep your job. I don’t think the vision of humanoid robotics is probably exciting to a lot of people. I think it’s deeply unpopular, actually. If you look at societal perception of AI right now, it’s already very unpopular, and that’s before people have started losing their jobs.

Once people—we’re at, like, 4% unemployment. The second you get a kick in unemployment and it’s due to AI, and people already hate it, it’s going to get way worse. Then there’s going to be regulation on just raw AI, let alone humanoid robotics. This is the area that’s going to be regulated.

We already know from self-driving cars what that looks like. It means that they’re literally not allowed on the road. And when they are allowed on the road, periodically they get pulled. It’s like, okay, someone attacked a Waymo, and we don’t know why they did it, so now we’re pulling Waymos off the road for a month, right? And that’s with cars. It’s going to be worse with humanoid robotics.

Avi Felman

So, this kind of implies—and maybe I’m putting words in your mouth—that the AI bubble is close to an end. What we’re seeing with a boom in data centers and the massive rise in the stock prices of all these hyperscalers almost implies that we’re close to the end of that, because you also think that we’re close to the beginning of regulation.

This is kind of the opposite of the doomer thesis in a way.

Alex Good

Well, I don’t think the world’s going to end. I think the world is going to get more distracted and more speculative. I do think the economy is going to get crushed, because I think people assume that AI is going to get us out of the debt bubble, right?

The assumption people have is that if we have a massive productivity increase, then we’re not going to have to worry about our World War II level of spending. And it’s like, okay, if that doesn’t happen, then it’s basically a sovereign margin call. That’s sort of why I’m in crypto.

I don’t think I actually disagree with that, because back in crypto world, right when Truth Terminal came out, everyone thought we’d have all this AI entertainment. We’re starting to see it with Seedance, right? There are these cool videos, but I don’t know about you—I don’t actually watch any of this AI stuff.

Avi Felman

No, I mean, I’m not really interested in fruit videos.

Alex Good

It’s fun. It’s funny, but it’s not that good.

Avi Felman

I’ve definitely been got by an AI video before. I watch it and then I watch it again. I’m like, “Wait a second.”

Alex Good

Yeah. Some of them I like—the inspirational ones, where they get the athletes or the animated Mike Tysons. I get a lot of historical AI on my slop feeds.

Avi Felman

Well, that’s pretty good.

Alex Good

Where people are recreating Napoleon’s battles using AI. I’m like, okay, that’s actually pretty compelling. But, I mean, I think we’re pretty early on AI. I don’t think we’ve fundamentally seen entertainment or generative worlds really kick in.

I think one thing you know for sure is that personalization delivers massively. If you do the math on the cost of an AI video right now, a personalized AI video is something like $55 for a reasonable video, and it’s not that good. Now, if that goes down to $2, which is believable, in 2 years you’re basically going to have mass-generated personalized videos for everything, whether that’s entertainment or video games.

Also, the tokens per second are going up exponentially, which means that you’re going to have compelling computer-game NPCs and improved social-media algorithms. My core bet is that AI just makes society look more like it already is. We’ve already seen what happens: the government regulated nuclear technology in 1945, and they basically said, “You’re not allowed to have a nuclear weapon, and if you do generate a nuclear weapon, we’re going to bomb you. You’re not allowed to do certain types of physics research, and if you do, we’ll probably kill you.”

Then what happens? It’s like, okay, computers are allowed, digital economies are allowed, and entertainment is allowed. The same exact thing is about to happen with AI, where you’re like, what will be allowed? How do you pay for the data centers? It’s like, you cook everyone’s brains, right?

The actual thing that will happen is that we have a society which is more online, more digital, where things get more expensive and productivity doesn’t necessarily increase. Right now, annualized productivity, as of the recent quarter, is 6% annualized. I’m like, dude, Microsoft’s CEO said that we’d see 10% annual productivity increases. That’s a lot different from 6% and 2.8% year on year, right? It’s not 10%.

Avi Felman

That’s why things like Robinhood and Interactive Brokers are kingmakers, or Hyperliquid is a kingmaker, right? People aren’t actually generating more work. They’re generating more capital, and that capital is being recycled into an attention economy. I think that’s just going to continue.

I’m completely on the other side of Andrew Kang, or a lot of these people—and even Elon, right? With SpaceX, they’re like, okay, it’s trading at some ungodly multiple on the premise that we start colonizing Mars or launching space data centers in 2029. I’m not sure that’s going to happen. I think it’s easier to underwrite the government cracking down on things and having more of the same things that we’ve had since 1945.

So, I mean, I think that’s as good a place as I need to wrap up. Sovereign margin call—that’s, I think, this is—I’ve been pretty bearish on Bitcoin. This has maybe actually made me a little bit more bullish on Bitcoin, just this entire talk. I thank you for sitting down with the 1000x podcast. I mean, this was awesome. If anything, I think this was an advertisement for better financial planning out there if we’re heading into a collapse. And thank you, Alex, for joining us.

Alex Good

Thank you, Avi. Cheers.