Anthony Pompliano

Why Are Bitcoin & AI Stocks CRASHING?!

🇬🇧 EN🇪🇸 ES
45:38 min youtube 2026 Semana 26 🇪🇸 ES

Resumen

TL;DR

  • La tesis central de Jordi Visser es que el trade de IA no se ha roto; la caída reciente se parece más a un pánico de mitad de ciclo dentro de un buildout largo que al final del tema.
  • Su cuello de botella de mayor convicción sigue siendo memoria, chips, energía y capacidad industrial, por eso mantiene la mirada en nombres del supply chain de IA y lee Micron, Intel y TSMC como piezas estratégicas, no solo como trades tácticos.
  • En crypto, cree que el trade de debasement se está lavando, no muriendo, y que los agentes de IA junto con la tokenización pueden preparar el terreno para la próxima gran ola de Bitcoin.

◆ Primero las anclas: la caída parece pánico, no ruptura de tesis

La idea más limpia del episodio es que Visser no cree que el trade de IA se haya acabado. Describe la semana como un freakout impulsado por posicionamiento, apalancamiento y miedo a que por fin exploten los nombres más crowded. Su respuesta es que seguimos en la segunda o tercera entrada de un buildout mucho más largo. Para él, la corrección dice más sobre el sentimiento que sobre la curva real de adopción.

â–¶ La memoria sigue siendo el cuello de botella clave

La parte más específica de la conversación es la tesis de escasez de memoria. Visser sostiene que la IA agentic dispara la demanda de memoria porque los agentes necesitan más contexto, más historial y más estado persistente. Lo compara con añadir de golpe miles de millones de nuevas bocas que alimentar: los precios suben porque la demanda corre mucho más rápido que la oferta. Por eso cree que Micron todavía tiene bastante runway, incluso si el crecimiento deja de ser explosivo y pasa a ser simplemente muy alto. Para él, esto no es solo hype: es una restricción real de oferta dentro del stack.

★ IA como carrera industrial y geopolítica, no solo software

Visser amplía la tesis más allá de semis. Dice que los gobiernos ya están tratando memoria, foundries, chips, tierras raras y capacidad industrial como activos estratégicos. Por eso conecta Intel y TSMC con política de capacidad nacional más que con el típico análisis de earnings trimestrales. La idea es que la IA ya forma parte de una carrera geopolítica, así que la capa de infraestructura puede seguir atrayendo capital incluso cuando el relato de mercado se tambalea.

â—† Carrera de modelos: Claude y ChatGPT se despegan de Gemini

Una de las llamadas más concretas a nivel de aplicación es su cambio de uso entre modelos. Visser dice que hace dos meses su workflow estaba más repartido, pero ahora Claude y ChatGPT representan alrededor del 90% de su uso. Dice explícitamente que Gemini ya no es un contendiente real para él, citando menor calidad del modelo, fuga de talento y la distracción de Google por tener que gestionar un negocio incumbente enorme. El mensaje de fondo es que la carrera de modelos se está concentrando y que esa concentración favorece a los líderes.

▶ Los agentic loops son a la vez monetización y shock laboral

Su implicación más importante aguas abajo gira en torno a los agentic loops. Argumenta que todavía existe una gran brecha entre CEOs que pagan por IA y empleados que realmente la usan bien. En el momento en que unos pocos power users dentro de una empresa aprenden a correr workflows agentic de verdad, estarán entrenando el sistema que sustituirá a parte del resto del departamento. En su visión, ahí está tanto el verdadero upside de ingresos para Anthropic y compañía como el riesgo real de destrucción de empleo más rápida de lo que descuenta el mercado.

â—† Stripe, solopreneurs y volumen para crypto

Visser también conecta IA con rails de comercio. Su lectura sobre Stripe es que la IA facilita crear software, pero el unlock real está en convertir esas apps en negocios mediante pagos, monetización y eventualmente comercio entre agentes. Ve eso como algo silenciosamente importante para crypto porque más comercio agentic implica más volumen transaccional, y crypto sigue necesitando actividad y throughput más que narrativas. Por eso no trata IA y crypto como mundos separados.

★ Bitcoin, oro y plata: washout del debasement, no muerte de la tesis

En macro, dice que el trade de debasement se había vuelto demasiado consensuado. Oro, plata y Bitcoin quedaron metidos en la misma cesta, y ahora ese posicionamiento se está limpiando a medida que ciertos comentarios hawkish reactivan temporalmente la narrativa de dólar fuerte. Pero no cree que hayan desaparecido ni el déficit, ni la deuda, ni las presiones estructurales de debasement. Para él, el unwind es más de positioning y sentimiento que de tesis a largo plazo rota.

â—† Buscar el alpha

La ventaja escondida del episodio es que Visser no compra el pánico generalizado. Está separando compresión de múltiplos de corto plazo de escasez estructural en infraestructura de largo plazo. Si tiene razón, la mejor forma de expresarlo no es “compra cualquier acción de IA”, sino enfocarse en los cuellos de botella, los líderes de modelos y los rails que monetizan la actividad de agentes. Esa es una tesis bastante más precisa que la cesta genérica de IA.

  • Alpha de supply chain: sigue viendo memoria, chips, energía y capacidad industrial como la capa escasa que más importa.
  • Alpha en la carrera de modelos: su propio uso se ha consolidado en Claude y ChatGPT, lo que interpreta como evidencia de liderazgo cada vez más estrecho.
  • Alpha laboral: los agentic loops pueden ser el puente entre demos impresionantes y ROI empresarial real, pero ese mismo puente acelera recortes de empleo.
  • Alpha en crypto: si los agentes de IA aumentan la velocidad de transacción, tokenización y rails blockchain podrían beneficiarse más de lo que hoy descuenta el mercado.
Activo / Tema Señal Por qué le importa
Micron Sigue alcista pese al pánico La demanda de memoria por agentes, humanoides y autonomía parece estructuralmente tensa.
Intel Ángulo de capacidad estratégica La foundry doméstica y el buildout industrial pesan en una carrera armamentística de IA.
TSMC Infraestructura crítica Muestra hasta qué punto el mundo sigue dependiendo de capacidad de fabricación élite.
Claude / ChatGPT Líderes de uso Ve cómo la brecha de producto se abre frente a Gemini y otros.
Stripe Rail de monetización para apps de IA Convierte código en actividad económica real y en comercio entre agentes.
Bitcoin / crypto Washout dentro de una tesis más grande Debasement, tokenización y crecimiento transaccional impulsado por agentes siguen importando.
El giro: Visser en el fondo está diciendo que el mercado está confundiendo un problema de capacidad con un problema de tema. Si la IA sigue avanzando, los ganadores probables serán quienes controlen los chokepoints: memoria, compute, capacidad industrial, modelos top y los rails que permiten transaccionar a los agentes.

► Resumen por capítulos

1. Intro (0:00)

Pompliano enmarca el episodio alrededor de la caída de IA, la escasez de memoria, la debilidad de crypto y qué partes del stack de IA siguen siendo relevantes para cartera.

2. Is the AI trade over? (1:13)

Visser dice que el pánico es real, pero que la idea de fondo es otra: la IA sigue en buildout largo y la caída actual se parece más a un freakout que a una ruptura estructural.

3. Micron, memory shortage, & the AI supply chain (4:11)

Defiende que la demanda de memoria se ha disparado por la IA agentic y que Micron sigue beneficiándose de un cuello de botella genuino aunque el crecimiento se desacelere desde niveles extremos.

4. Intel, TSMC & the AI arms race (9:54)

Esta parte empuja la idea de que la infraestructura de IA ya es capacidad estratégica nacional, no solo un tema de mercado, lo que respalda nombres ligados a foundries y resiliencia del supply chain.

5. Claude vs. ChatGPT vs. Gemini (13:11)

Visser dice que su uso se ha concentrado en Claude y ChatGPT mientras Gemini se ha quedado atrás, reforzando su visión de que el liderazgo se está estrechando muy rápido.

6. Agentic loops & job displacement (24:26)

Argumenta que los agentic loops son el unlock empresarial clave y que pueden traducir el entusiasmo por la IA en disrupción laboral real mucho más rápido de lo que espera la mayoría.

7. What is the impact of regulation? (29:50)

Su tesis es que la regulación puede ralentizar el buildout, pero no frenarlo, y que la presión política crecerá a medida que la IA agrave debates sobre desigualdad y redistribución.

8. Stripe, solopreneurs & AI commerce (34:55)

Stripe aparece como ejemplo de cómo la IA pasa de crear apps a monetizarlas, con el comercio entre agentes como posible motor adicional para la actividad crypto.

9. Bitcoin, gold & the debasement selloff (38:12)

Visser sostiene que el trade de debasement se está limpiando porque se volvió crowded, no porque la tesis de deuda, déficit y pérdida de valor monetario haya desaparecido.

10. Tokenization & bitcoin's third wave (43:11)

Conecta agentes de IA, mayor velocidad transaccional, tokenización y utilidad blockchain en un setup más alcista a largo plazo para crypto.

11. Jordi’s upcoming video (45:04)

El episodio cierra con un teaser del próximo vídeo de Visser.

Generado con algoritmo v2.1-anchor-first · modelo openai-codex/gpt-5.4 · 2026-06-27T14:06:12Z

Transcripción

[0:00] Here's the reality. We are in still the
[0:02] second or third inning of what will be a
[0:04] long buildout. Artificial intelligence
[0:06] is the most important thing to happen to
[0:09] the human race from the basis of making
[0:12] things cost less and solving some of the
[0:14] world's problems that have been with us
[0:16] for a long time. Turning longevity into
[0:18] something that's parabolic. Turning the
[0:20] market into something that's parabolic.
[0:22] most importantly allowing
[0:23] democratization of education,
[0:25] democratization of people to have as
[0:27] much information as the people I started
[0:29] at the beginning that say this always
[0:31] ends badly. And this has been the thing.
[0:33] And so what's going on guys? Today we
[0:35] got a great conversation with Jordy
[0:36] Visser. He's an extremely successful
[0:38] macro hedge fund manager. And now he's
[0:40] here to explain to us what's going on
[0:42] with the AI trade, which names he likes,
[0:44] which ones he doesn't. Is he worried
[0:45] about the big memory shortage? Is the AI
[0:48] trade over or not? What's it mean for
[0:50] your portfolio? We talk about the
[0:51] debasement capitulation and what's going
[0:53] on with Bitcoin, gold, silver, and then
[0:55] of course we get into SpaceX and what's
[0:57] going on with Anthropic and Claude and
[0:59] OpenAI and Gemini and Google and many
[1:01] other names. This conversation is going
[1:03] all over the place, but it is ultimately
[1:05] Jordy and I trying to figure out what
[1:07] the heck's going on in the world and
[1:08] what does it mean for his portfolio, my
[1:09] portfolio, and yours. Here's my latest
[1:11] conversation with Jordy Visser. All
[1:13] right, Jordy, the AI trade seems like
[1:15] it's over. Everything's going down.
[1:17] People are very upset. Should we just
[1:19] pack it up and go home? What what
[1:21] exactly is going on here?
[1:23] >> Yeah, it was a a freakout week. Um
[1:27] ending or at least Micron is changing
[1:30] the tone. Um, it's very funny
[1:34] spending your time and your life talking
[1:36] to people about a particular trade and
[1:40] uh the people that I've known in the
[1:41] industry a long time like myself. So
[1:45] people like me, they just know that
[1:47] number one, things like this don't end
[1:49] well in their head. Even though that may
[1:51] not be the case, they in their head they
[1:53] know it. So they believe that all retail
[1:56] traders and all people that have been
[1:57] riding momentum will eventually get
[1:59] blown up. I see the leverage. I see all
[2:01] of this stuff. So this week when SKHX in
[2:05] particular in the Korean market was
[2:06] effectively limit down
[2:09] every single like overnight podcast,
[2:12] everything in X was it's here. This is
[2:14] going to be a crash. You're going to
[2:16] watch what happens. Once Micron's done,
[2:18] everything will go down. And because I
[2:20] have a thematic portfolio with 100
[2:21] names, 100 names is a lot of AI names.
[2:24] It crosses from chemicals to industrials
[2:26] to um drug companies to uh you know
[2:31] semiconductor and a whole bunch more. So
[2:34] it was down big on one day
[2:37] and everyone was freaking out and people
[2:39] reached out. So on Tuesday I did a video
[2:41] and I basically just said to to people
[2:45] here's the reality. Um, we are in still
[2:48] the second or third inning of what will
[2:50] be a long buildout. And I'm going to say
[2:52] it to everyone who listens to us every
[2:54] week.
[2:55] Artificial intelligence is the most
[2:57] important thing to happen to the human
[2:59] race from the basis of making things
[3:03] cost less and solving some of the
[3:05] world's problems that have been with us
[3:06] for a long time. Turning longevity into
[3:08] something that's parabolic. Turning the
[3:10] market into something that's parabolic.
[3:12] Most importantly, allowing
[3:14] democratization of education.
[3:16] democratization of people to have as
[3:18] much information as the people I started
[3:20] at the beginning that say this always
[3:22] ends badly and this has been the thing
[3:24] and so Micron comes out obviously the AI
[3:27] trade is not over um I will do a lot on
[3:30] the video this weekend to just show the
[3:32] quotes they've got long-term commitments
[3:35] from so many different people now
[3:37] they're supply and demand will be out of
[3:39] balance until 2028 that doesn't mean
[3:41] that's definitely going to happen but
[3:43] the reality is the AI portfolio video
[3:46] and the way that things moved. I'm going
[3:48] to say it again and again. The world
[3:50] changed in October of last year or
[3:52] November of last year when Opus 4.5 came
[3:55] out. We've gone from 4.5 to 4.6 and 4.7
[3:58] to 4.0 to Mythos to Fable 5 to the
[4:01] government basically taking control of
[4:04] it and GPT 5.5 is out. The AI trade is
[4:07] doing excellent and the second half of
[4:09] the year you will continue to see
[4:11] strength.
[4:11] >> So there are I'm going to call it
[4:13] closing the gap. There are two things
[4:15] that I have heard this past week that I
[4:17] need to come and talk to you about. You
[4:18] got to tell me whether these make sense
[4:20] or not. The first one, let's start with
[4:22] is Micron. So my understanding is that
[4:25] Micron's last quarter that they just
[4:27] reported, they did more in revenue than
[4:30] Nvidia did when Nvidia was a $4 billion
[4:33] company. Four trillion four trillion
[4:35] dollar company. Sorry, you know, the
[4:36] numbers are getting so big here. B,
[4:37] what's the difference?
[4:38] >> Um, a $4 trillion company. Today, Micron
[4:41] is not a $4 trillion company. And so is
[4:44] it as simple as just like that gap
[4:46] closes and Micron's going to be a $4
[4:47] trillion company?
[4:50] >> Um if it were only that easy, but I will
[4:54] say this. Um it will be very surprising
[4:57] if they don't get up to two trillion
[4:59] over the course of the next year. Here's
[5:02] the thing about it. Um and again, I love
[5:04] doing these weekly videos because there
[5:06] are certain things that just stand out.
[5:08] the the one I did on on Tuesday was
[5:11] meant to go through this concept that
[5:12] I'm really trying to do to help people
[5:14] which is there's noise which is this is
[5:16] a bubble. So because the agentic world
[5:21] started the amount of memory that was
[5:23] needed was far different than any time
[5:24] in history and it was the gateway. So it
[5:26] was literally and I and I I can the only
[5:29] analogy I can use is we have a certain
[5:32] amount of food on the planet. We've
[5:34] always heard that we could run out of it
[5:35] that prices could go up. You know what
[5:38] would cause it to really be in trouble
[5:40] and make the prices go up dramatically
[5:42] is if all of a sudden there was an extra
[5:44] 4 billion people on the planet tomorrow.
[5:47] That's what happened with memory. The
[5:49] amount of memory that is needed because
[5:51] of AI agents which need to think about
[5:54] the past and this and go through it and
[5:56] connect changed overnight. And we have
[5:59] another 5 to 10 years of this because
[6:01] humanoids need even more. Autonomous
[6:04] vehicles need even more. That is and
[6:06] they talked about this. Micron talked
[6:08] about it on the earnings call. You can't
[6:10] have something without coming up with
[6:12] the correct analogy. So I just want
[6:14] everyone to hear it. If 4 billion people
[6:16] entered the planet today and we went up
[6:18] by 50% the amount of people, we wouldn't
[6:20] have enough food. You prices would go up
[6:23] dramatically. So inflation doesn't
[6:25] always come from speculation and from
[6:27] money and all this stuff. Sometime it
[6:29] comes from oh my god we have to feed all
[6:32] of this 4 billion people. And in the
[6:34] case of digital agents, the food I've
[6:36] said it before, it's compute and compute
[6:39] is chips and energy.
[6:40] >> So when you look at these kind of
[6:42] limiting factors, one thing that you've
[6:43] said to me is that maybe the pace we're
[6:45] growing, even though it feels like we've
[6:47] got a limitation to growth, maybe the
[6:50] right pace to be growing. What do you
[6:52] mean by that?
[6:53] >> So um, and this is what I wanted to make
[6:55] sure people realize from the midcycle
[6:58] slowdown because when you say something
[6:59] like midcycle slowdown, everyone's like,
[7:01] should I get out? And the answer is no.
[7:02] you should just expect it to not be as
[7:04] easy. Um,
[7:06] Micron's not going to be growing their
[7:08] earnings at the pace they did from the
[7:10] fourth quarter of last year to the
[7:12] second quarter of this year. When you
[7:13] look at the numbers and when I show you
[7:15] the income numbers, they are massive to
[7:19] change. They did more in the first two
[7:21] quarters of this year than I think the
[7:23] last 10 years combined. So, is that is
[7:27] that going to continue? No, it's not.
[7:29] Like, will they grow? Yeah. But if
[7:31] you're only growing at 50% from 400%,
[7:35] that's the second derivative kicking in.
[7:36] You're slowing down. Yeah. So, it's not
[7:39] a down trade. It's just a a slowdown.
[7:42] So, I think the this has mainly been
[7:45] because of price increases and because
[7:47] there's a bottleneck. They are spending
[7:49] money on capex to produce more. They
[7:52] just can't make enough anymore to
[7:54] satisfy all the demand that's there. So,
[7:56] demand went up too fast. A lot of this
[7:58] is for future use. And so, are we going
[8:01] to need all of them? No. But like I
[8:03] said, humanoids are coming and there's
[8:04] other things coming. So, if people doubt
[8:05] it, they're making a huge mistake. In no
[8:08] way, shape, or form is Micron a short.
[8:09] For traders who want to make it go
[8:11] from,300 to,00 be my guest. I got out
[8:14] way too early. So, you're talking to
[8:16] someone who didn't expect the stock to
[8:18] just continue to go like this. But part
[8:20] of the reason I got out is because
[8:21] Marll, which is another memory play in a
[8:24] different way that benefits from the
[8:26] fact that memory shortage is there. I
[8:28] like that. So the pace thing you're
[8:30] mentioning and what I say to people,
[8:32] Taiwan Semi is preventing us from
[8:34] growing too fast. If we had enough
[8:36] memory right now, I think the
[8:38] capabilities would be going so fast that
[8:40] it would leave a lot of workers in the
[8:42] dust. So sometimes government's job is
[8:44] not to stop things from happening. It's
[8:46] to slow things. Sometimes the
[8:48] bottlenecks of the physical world
[8:50] actually end up being something good
[8:52] because it keeps things in check. And I
[8:53] just want to remind people for all the
[8:55] things we're talking about in AI, the
[8:57] S&P 500 as of when I came in here with
[8:59] you is up less than 8% in the first half
[9:02] of the year. That number might sound
[9:05] okay. That is not a big number for all
[9:07] of this bubble talk and enthusiasm. The
[9:09] hyperscalers are horrible. Like this
[9:11] month, you've got record falls. I think
[9:12] Microsoft I think Microsoft is having
[9:15] its worst month since 2008. The Niki is
[9:19] up 45 or 48%. The Cosby is up over 100%.
[9:24] Taiwan is up over 50%. So the US is
[9:28] actually not benefiting as much. And
[9:30] this is this benchmark arbitrage thing
[9:32] that I talked about which is this. The
[9:34] receivers are getting most of the money.
[9:36] Well, the problem is in Taiwan and in
[9:39] Korea, the receivers are higher weight
[9:40] in the index. Same thing in Japan. In
[9:42] the US, the hyperscalers are the higher
[9:44] weight. That's why the index is having a
[9:46] hard time. That's why we do this show to
[9:47] talk about the things that are going.
[9:49] The slowing of the pace is actually a
[9:51] good thing because I think too fast
[9:52] would be worse for the worker world.
[9:54] >> The other close the gap is Intel and
[9:57] TSMC.
[10:01] >> Yeah, this is uh uh an interesting story
[10:04] and again we've reached a point where
[10:06] some people have to listen to I think
[10:08] Scott Besson had a speech at the uh was
[10:12] it at the New York athletic uh economic
[10:15] club.
[10:15] >> Okay. It's a really important speech for
[10:18] people to to go read or just go through
[10:20] the transcript or upload it into an LLM.
[10:23] And the reason is because he talks about
[10:26] the strategic nature of AI. He talks
[10:30] about needing to have the industrial
[10:32] capacity that we've been in this place
[10:35] where we've been over consuming for a
[10:37] long period of time and now we need to
[10:39] be producing what we need and we cannot
[10:41] be dependent on the supply chains of the
[10:43] world. Now, we learned this through the
[10:45] tariffs last year. One of the good
[10:46] things that the tariffs did last year
[10:48] for everyone who just wants to be
[10:49] political is we learned that um we're a
[10:52] little bit screwed on the infrastructure
[10:54] side of AI. We don't have the rare earth
[10:56] we need. There's a lot of things that we
[10:58] don't have everything of and we need to
[11:00] build that capacity which is why Intel
[11:02] fits in well with Taiwan Semi because if
[11:05] you would have listened to the
[11:06] conversation and when the government
[11:08] made a strategic investment into Intel
[11:11] they were basically saying okay we have
[11:13] to support this company because we need
[11:14] this we need to invest in it we need to
[11:18] have the CPUs we can't have the foundry
[11:20] the biggest one of the biggest
[11:21] foundaries in the world one of the three
[11:23] biggest in the US and not be running at
[11:26] full throttle
[11:27] We need a terra fab. We need all this.
[11:29] So Besson really talked about the fact
[11:31] that this is a strategic need. Now in
[11:34] Micron's
[11:36] earnings call, the CEO specifically said
[11:40] memory is a strategic asset. So whatever
[11:44] people's view is of AI, they think it's
[11:46] a bubble. The governments of the world
[11:48] are in a massive race for military
[11:52] dominance, for mythos versus deepseek.
[11:55] Deepseek just had a funding round. Only
[11:58] one investor got voting rights. That
[12:00] would be the Chinese government. So,
[12:03] we're just in this thing of AI is a
[12:05] military asset and they're in there
[12:07] going through it. And you want to invest
[12:09] in the things that are going to build
[12:11] the AI, maybe not as so much as the
[12:13] people that are going to monetize the
[12:14] models.
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[13:11] Should the government just print
[13:15] trillion dollars and go hire all of the
[13:19] top AI uh scientists and just say sit
[13:22] here and beat the private companies?
[13:26] >> I honestly don't think anyone can catch
[13:29] up to what's going on. I think this has
[13:31] become something um
[13:35] Google had two very senior people leave
[13:37] this week. I don't know if I said it
[13:39] with you or if I said it on on on my my
[13:43] YouTube, but I made a comment that a lot
[13:46] of people reached out on and I said
[13:48] Google's not a player in this anymore
[13:49] for me. Um,
[13:52] two months ago, yeah, two months ago,
[13:56] I would say Claude was about 35% of my
[14:00] usage. Chat GPT was probably about 25
[14:05] and then Google was probably about 20.
[14:07] And then Grock would be another one and
[14:09] perplexity would be another. What has
[14:11] happened now is that Chachi PT and
[14:14] Claude are effectively 90% of my usage.
[14:18] The other three have become less
[14:22] important to me.
[14:24] >> Why?
[14:26] >> Because Gemini I Gemini's model is
[14:30] nowhere near as good as ChatBT 5.5 or
[14:33] Opus 4.8. Plain and simple. They haven't
[14:35] released a new thing in a long time.
[14:37] They're behind. They're losing quality
[14:40] people. And I think part of the reason
[14:41] is because they have one disruption that
[14:44] those two companies don't have.
[14:45] Actually, they have many. First of all,
[14:47] Google has about 200,000 employees.
[14:50] They're $3 trillion.
[14:52] Anthropic is what$ 1.5 trillion in the
[14:55] private market. They have less than
[14:57] 5,000 employees. So if you're a person
[15:01] who cares about working with the best
[15:03] models, if you care about working on the
[15:05] best things, you've got that. Google has
[15:07] to work on Google Cloud. They have to
[15:09] make sure that workspace is working and
[15:11] all these other things. So they actually
[15:14] are distracted to some degree because
[15:15] they have to keep the revenue focused on
[15:18] these other products and anthropic and
[15:21] open AI are just trying to get
[15:23] enterprises to adopt. So, I think we've
[15:25] reached a point that because of the
[15:28] belief of recursive self-improvement,
[15:30] that if you are number three, which is
[15:32] where Gemini is, they're number three.
[15:34] Number three with open source up with
[15:37] the other two is a very dangerous
[15:39] position. So, I would never say go out
[15:41] and short Google for it to go down
[15:44] because they're cashri. They're in
[15:46] everyone's life and they're not going
[15:47] anywhere. But they're they're seem to be
[15:51] entering into the same problem or a
[15:53] different variety that Meta, Microsoft,
[15:55] and even Amazon have been in for at
[15:56] least a while, which is these companies
[15:58] have not done well. Their multiples were
[16:00] high. They're overowned by everyone. And
[16:02] they've kind of fallen into an Nvidia
[16:04] thing where Nvidia is going through
[16:05] multiple compression. Google is too. So
[16:07] Gemini is just not there for me. And
[16:08] Nano Banana was the main reason. And I
[16:11] didn't even put this into context. Did
[16:13] you use Nano Banana?
[16:14] >> I did. Okay. Okay.
[16:15] >> Part of it was because of the cool name
[16:17] and then part of it was so for me Nano
[16:19] Banana obviously the image generation
[16:20] was supposed to be like it's you know
[16:22] best feature or whatever. Um I think out
[16:24] of habit I will still go sometimes to uh
[16:27] to Gemini and use uh for image
[16:30] generation but what I find is that um
[16:33] Chad GBT has become better you know it
[16:37] is at least in my mind it's a it's a
[16:39] jump ball now 50/50 whether I go to
[16:41] Gemini or Chad GBT and I don't think I
[16:43] have a great heristic. So it's like
[16:45] Gemini definitely lost the like pole
[16:47] position on image generation for me and
[16:49] so now they share it with Chachi.
[16:51] >> So I I've said this before um Gemini is
[16:55] very medicinal to me. It's literally
[16:57] like medicine. It's very academic. I
[16:59] didn't like school. So I never really
[17:00] liked going to Gemini. I don't like the
[17:03] the way it feels. I use it as my fact
[17:05] checker. I used to use it for Nano
[17:07] Banana as well. And I used to rave about
[17:09] Nano Banana. But then when GPT 5.5 came
[17:12] out, that all changed.
[17:14] >> And I find the images are faster and I
[17:17] find they're better in using them there.
[17:20] And so I' I don't know where Gemini is
[17:22] going to fit in, but if they don't get
[17:24] another model out soon, I would not be
[17:27] surprised to see more defections. And by
[17:29] the way, these were not minor people
[17:31] that left Google. This is some of this
[17:34] is about science as well. And I think
[17:36] Demisabis,
[17:38] Nobel Prize winner,
[17:40] he's not Google, he's DeepMind. These
[17:42] were DeepMind people. Like, it's a
[17:44] little bit worrisome to me that people
[17:45] are leaving. And I'm sure they got paid
[17:48] a billion dollars uh to go to Anthropic.
[17:50] These guys have the money, they have the
[17:52] growth, they have the appeal at this
[17:54] point, and this is what happens when
[17:56] you're number three and there's open
[17:57] source models that are have better
[17:58] models than you do.
[17:59] >> I would love to know how these top
[18:02] people are getting recruited right now.
[18:03] Is it like super Russian spy? Like see
[18:06] him at a coffee shop, slip him a note,
[18:09] or is it like just send him a a LinkedIn
[18:11] request? I mean, you know, I mean,
[18:12] because it's not like, hey, we're trying
[18:14] to recruit a marketing associate, right?
[18:15] I mean, we're talking about in some
[18:16] cases this is a billion dollar
[18:19] compensation plan.
[18:20] >> And so, we heard, you know, Zuck was
[18:22] personally reaching out to people or
[18:24] whatever. Okay. But like
[18:26] >> is anthropic like what what's the game
[18:28] here? It would be fascinating to
[18:29] understand
[18:30] >> and I'm sure at some point we will
[18:32] especially if so I don't want people to
[18:35] think I I don't know how open AI and
[18:39] anthropic
[18:41] are going to be able to monetize every
[18:43] like I'm still very worried about the
[18:46] revenue situation relative to the capex.
[18:49] I think this is very challenging as a
[18:52] user in thinking about how this is going
[18:54] to work out for everyone. So, I I'm I'm
[18:57] not so sure that the revenue growth for
[19:00] these companies is going to be as easy
[19:03] as what the charts suggest.
[19:06] I know everything's parabolic right now.
[19:08] I know the reasons why everyone jumped
[19:10] in. I know that token maxing helped
[19:12] them, but now I think everyone is
[19:14] looking at this going, how do we reduce
[19:16] the cost? And I think everyone's going
[19:19] to figure out a way to reduce the cost
[19:20] quickly. And so, there might be I called
[19:22] this a capex air pocket. I still believe
[19:25] for the next three to six months, even
[19:27] with the Micron news, it doesn't change
[19:29] the fact that the rate of change and the
[19:31] expectations on the positioning is going
[19:33] to go through a little bit of a shakeout
[19:35] for a while.
[19:36] >> There was a article written about
[19:38] Anthropic this past week and um I'm just
[19:41] going to read you a couple data points
[19:42] from it. Uh Anthropic stickiness shows
[19:44] in three data points. Uh it's got a net
[19:47] dollar retention of over 500%.
[19:49] Nine of the Fortune 10 are customers and
[19:53] a sales cycle can sign two 8 figure USD
[19:57] contracts in a single meeting. Okay. On
[20:00] valuation, the 2026 series G was a $380
[20:05] billion post money. But then if you fast
[20:08] forward to um the series H which was 3
[20:12] months later they went from $380 billion
[20:15] to $965 billion post money valuation. So
[20:20] you know approximately a 3x but here was
[20:23] the kicker. Anthropic reportedly has
[20:26] turned cash flow positive with a free
[20:29] cash flow margin of 15 to 20% and a
[20:31] gross margin of 60 to 70%. Now, I don't
[20:36] know if that's true or not.
[20:37] >> Mhm.
[20:38] >> But if Anthropic is throwing off 15%
[20:40] free cash flow, growing at the pace that
[20:43] they are reportedly growing at the size
[20:46] >> Mhm.
[20:47] >> guys doing, you know, 1020 billion
[20:50] dollars of free cash flow already. Like
[20:53] they started what, four years ago, five
[20:55] years ago?
[20:55] >> Yep.
[20:56] >> To do that, I only know of one company
[20:59] in the world who's ever done this before
[21:00] and that's Tether.
[21:01] >> But Tether isn't growing that much,
[21:03] right? because they're growing but it's
[21:04] just not at this rate like this. So you
[21:07] look at this and you say
[21:09] is anthropic undervalued
[21:12] >> uh based on the last 6 months you can
[21:16] put whatever valuation you want. This is
[21:18] different than SpaceX. Um this is
[21:21] actually something where you can say and
[21:22] and I I want have
[21:25] >> shots fired.
[21:27] I again I'm I'm I'm not a value investor
[21:30] and I'm not here to to go through it but
[21:33] again when when when I get asked the
[21:35] question and go what do you think of
[21:37] SpaceX and I give an answer you don't
[21:39] believe you don't believe the TAM of
[21:41] space and I go okay I I just I don't
[21:45] understand you know in my head as much
[21:48] as I'm I'm a uh a a futurist and I think
[21:51] about all the world I don't understand
[21:54] how the money in the future fits into a
[21:57] world with Mars and with the moon. So,
[22:00] at some point there's a cut off for me
[22:02] where I'm not really sure what that
[22:04] means. And so, in a public company, I
[22:06] just don't get it. With Anthropic,
[22:08] >> that that might be the point, Jordy.
[22:09] >> Yeah. I And trust me, I'm I'm That's why
[22:12] I stick with the right now with the
[22:13] physical hardware.
[22:14] >> Well, Anthropic though, if you look at
[22:16] it, let's just say it's doing 20
[22:18] billion. I don't like to do public math,
[22:19] but that's like 50 times,
[22:21] >> you know, free cash flow.
[22:23] >> Yep.
[22:25] at the pace at which they're growing.
[22:27] They're adding, you know, they're
[22:28] growing 25 30% month over month. Like
[22:30] that doesn't seem crazy to me at all.
[22:32] Actually, it feels like maybe this thing
[22:34] should be like $2 trillion.
[22:35] >> But again, you if you keep extrapolating
[22:38] things into the future on this, you run
[22:40] into a problem as you get into AGI and
[22:42] you get into RSI. And that's the part
[22:43] like I don't know what it all means when
[22:45] you get to that point. I I I just think
[22:48] people have to keep that in mind like
[22:50] taking the world of the past and saying,
[22:52] "Well, we're going to grow revenues."
[22:53] Okay, great. Where's it coming from?
[22:55] >> Mhm.
[22:56] >> And I can make the argument as to where
[22:58] it's coming from. And I know that for me
[23:00] as a power user, I pay 200 a month. I'm
[23:03] not getting charged for the tokens.
[23:05] >> There's no way they're profitable on
[23:06] you.
[23:06] >> No, there is no way they're profitable
[23:08] on me. And I know that I'm not using the
[23:10] API and I'm not and I'm avoiding
[23:12] OpenClaw for a lot of the work that I
[23:14] would need to do on and I'm just using
[23:15] it in terms of paying the $200.
[23:17] >> Do you get throttled while you're using
[23:19] it on the 200? Not I I don't think I
[23:24] don't think I'm that
[23:27] >> like the velocity isn't there so I don't
[23:29] need to throttle you.
[23:29] >> I'm I'm using it all day long, but it
[23:32] really is
[23:35] I'm I'm doing a lot of brainstorming and
[23:37] I'm filtering things in my head before I
[23:38] go in there and I'm trying to get
[23:39] answers quickly and I work through
[23:41] through things. If people have gotten to
[23:42] know me, you know, I can go a mile a
[23:45] minute speaking and I can pull things
[23:46] out of my head that have been sitting
[23:48] there for weeks. I can go back 10 years.
[23:49] I can remember something. I can do this
[23:51] with people very quickly. But with an
[23:53] LLM, it's very focused. It's like, I
[23:55] have this thought. Let's go through it.
[23:57] It gives me an answer. I go back and
[23:58] forth, back and forth, back and forth,
[23:59] back and forth.
[24:01] >> But if the questions are good and you're
[24:03] and you're good at saying, don't give me
[24:05] a long-winded answer, you actually cut
[24:07] down on your token usage dramatically.
[24:09] Now, when I'm building stuff and I'm
[24:11] going through it,
[24:13] >> that takes more time. That's a lot more
[24:15] code, but I think I'm s succinct in what
[24:18] I want and I think I've already done the
[24:20] prep work on my own. So, I haven't
[24:22] gotten to the point of loops. And this
[24:23] is what I wanted to say to you. And this
[24:25] is the part where I think the most
[24:28] important thing that's happening right
[24:30] now is this concept of loops.
[24:33] And this is where
[24:34] >> agent loops or agentic loops.
[24:36] >> Yeah. So there's been a huge gap between
[24:39] the CI the CEOs of companies loving AI
[24:43] and paying anthropic lots of money and
[24:46] then the employees using it.
[24:48] >> There's been a huge gap. So the surveys
[24:50] all say the same. Like CEOs all love it
[24:53] and say it's going to change their
[24:54] business. Employees
[24:56] aren't so excited. Now I'm not sure it's
[25:00] just because it's going to take their
[25:01] jobs. I actually think they don't know
[25:03] how to use it. Now, if you have a 100
[25:06] employees in a department and two of
[25:08] them are power users, meaning they love
[25:10] it and they're figuring ways to do it.
[25:12] So, people understand what loops are,
[25:15] the agents are figuring stuff out on
[25:18] their own, but they do need the human
[25:19] context and they need to learn
[25:21] everything going on in the business. So,
[25:22] if you're in a marketing area of of
[25:25] CocaCola and there's a 100 employees and
[25:28] two of them are using Claude in a really
[25:30] really good way and the Agentic Loops
[25:33] are being used by those two people and
[25:36] the other 98 are doing something
[25:38] similar, then these people are training
[25:40] their replacements at this point. That's
[25:43] the thing that we're entering into this
[25:44] dangerous point. And this is where the
[25:46] job losses could come much faster. And
[25:48] that's where Anthropic's revenue gains
[25:50] to me are going to have to come from.
[25:51] The total compensation and everything
[25:53] that happens in this country is about
[25:55] $20 trillion a year. If you can get rid
[25:58] of a bunch of employees and right now,
[26:00] so people remember, we are not creating
[26:02] jobs. So yes, the last two months we
[26:04] created a couple hundred thousand or
[26:06] 300,000. Most of them were in the
[26:07] healthcare side, but over the course of
[26:09] the last year, there's almost been no
[26:11] job creation. The reason that matters is
[26:14] because in the history of this market,
[26:16] the way that we got more G nominal GDP
[26:18] was you get more employees every single
[26:20] year. And then in recessions, you don't
[26:22] hire people, you fire them and it goes
[26:24] down. We are growing rapidly without
[26:27] hiring people. So that means the profits
[26:29] are going into the companies because
[26:30] they're actually not firing people at
[26:32] this point. They're just not hiring
[26:33] them. If they get to the point that the
[26:35] loops are there, and this is why people
[26:36] need to pay attention. The agentic loops
[26:38] are not only important for the
[26:39] businesses, but they start to become
[26:41] important for the commerce side because
[26:43] it means people are learning how you're
[26:44] doing stuff on your computer. And then
[26:46] as a consumer, Alexa and Siri and all of
[26:50] those things that we haven't seen work
[26:52] yet, they're going to start to work as
[26:54] part of the next thing, which is the
[26:55] connection of Agentic Loops with Agentic
[26:57] Commerce.
[26:58] >> Did you see the clawed tags?
[27:01] >> Yes. I was listening to a bunch of
[27:02] people talking about a bunch of podcasts
[27:04] on the way here.
[27:04] >> I I feel like that's going to end up
[27:06] being right along with this, right, of
[27:09] you know, if you have a company and you
[27:12] have people who work remotely,
[27:14] >> you do not talk to them
[27:16] >> on the phone, in person, maybe even in
[27:18] meetings a lot. It's it's literally
[27:20] Slack. There are certain people who work
[27:22] at some of our companies who I
[27:24] communicate with 99% through Slack and
[27:29] maybe once a month or something, you
[27:30] know, we do something on the phone or
[27:32] video or I'm in a meeting and they're
[27:34] there, you know, uh, virtually,
[27:35] whatever.
[27:37] But what's the difference whether it's a
[27:38] human or it's AI on the other end if
[27:41] you're talking in Slack and it's doing
[27:43] like that? To me, this is one of these
[27:45] moments where I'm like, I'm gonna I just
[27:47] saw more of the future than I knew two
[27:50] weeks ago, and it feels pretty
[27:52] disruptive.
[27:53] >> Andre Carpathy said, "This is way bigger
[27:55] than you think it is." And I agree. Now,
[27:57] again, I just mentioned loops.
[28:00] You're talking about tags.
[28:03] The main thing people have to understand
[28:04] is all of this changed in November of
[28:07] last year. So when you get to a point
[28:10] where the computers are actually solving
[28:13] stuff, what just happened with open AI
[28:16] and jalapeno
[28:19] an AI chip?
[28:22] So I've mentioned this before, but we
[28:24] solved the vaccine issue during COVID
[28:29] when a vaccine would normally take four
[28:31] years to go from okay, how do we go? It
[28:33] might take more. and it was done and we
[28:35] had the blueprint before a single person
[28:37] died in the United States of America.
[28:39] It's an amazing thing to think that AI
[28:41] was able to take the blueprint and then
[28:44] create the specs of a vaccine and then
[28:47] it had to go through the process which
[28:48] took another 9 months which was
[28:49] fasttracked. So now you go forward these
[28:53] AI the jalapeno AI chip where open AI
[28:56] worked with Broadcom which is a
[28:57] disruptive thing for Nvidia
[29:00] well that took 9 months to go from
[29:03] idea designed and AI was a major part of
[29:06] this so again when people start thinking
[29:09] about where we are that's why I always
[29:10] say the world changed in November of
[29:12] last year there wasn't a chat GPT moment
[29:15] for most of you but for people that were
[29:17] power users they felt it and so when
[29:19] Andre Carpathy split He was the one that
[29:21] basically said the world changed in
[29:24] November and that was a month after he
[29:25] was on a faint very big podcast saying I
[29:28] don't see any agentic stuff for another
[29:29] decade. You have to think about how
[29:31] wrong he was, how fast it's going. And
[29:34] as I said last week, Leopold wrote this
[29:36] paper. This is happening faster than
[29:38] even he predicted. And I think that's
[29:41] the issue is that people have to just
[29:42] accept that loops, tags, all of this
[29:45] stuff, those are all getting to the
[29:47] point where you don't need as many
[29:48] employees.
[29:49] regulation is rapidly running to keep up
[29:53] here. What is the impact of that going
[29:55] to be?
[29:57] >> I mean, for people who uh don't like
[29:59] change, it'll slow things down. Um we're
[30:02] obviously seeing election results which
[30:04] are indicative of um a continuation from
[30:08] what the voters voted for in New York
[30:10] City. You're getting more and more of
[30:13] this story. you're getting more and more
[30:14] empowerment when you're seeing Bernie
[30:16] Sanders rise again into some form of
[30:18] this and scare both the Republican party
[30:21] but also a major part of the Democratic
[30:23] party. Um
[30:24] >> guy has nine lives, man.
[30:26] >> Yeah, it's a it's amazing. I mean, the
[30:28] water in Vermont and Maine is very good.
[30:30] So, you're getting lots of lots of
[30:32] spring water keep you young. Um I
[30:36] it won't stop artificial intelligence.
[30:38] Um, I think David Freeberg on the All-In
[30:43] podcast gave a great commentary on this
[30:46] uh a week and a half ago and he
[30:49] basically said it's like the internet.
[30:51] You can't stop it and we haven't even
[30:54] built the data centers yet and we're
[30:56] talking about the agentic world
[30:57] accelerating. We need the data centers
[30:59] for uh longevity and for all kinds of
[31:02] things but we don't know how many we
[31:04] need. We actually don't know because the
[31:06] progress is going so fast. So, as much
[31:08] as I think the government will delay
[31:10] things, they'll create issues on things,
[31:12] they might make it more challenging,
[31:15] they might tax things, I mean, in Korea,
[31:17] we got another
[31:19] movement towards this unrealized capital
[31:22] gains tax. for everyone out there who's
[31:24] forgotten about crypto and confiscation
[31:28] and a lot of movements on the
[31:31] distribution wealth whether it's in uh
[31:34] the Netherlands whether it's in
[31:35] Switzerland whether it's in uh
[31:38] California you can go through places I
[31:40] mean the rise of socialism because of
[31:42] the distribution of wealth is there and
[31:44] I think AI only makes the situation
[31:46] worse and when I mention tags and loops
[31:48] to to bring up what you said I don't
[31:52] need tags
[31:54] because I don't have any employees. So,
[31:56] I'm actually working with my employee
[31:59] every single day on the brainstorming
[32:01] side of how to build things out. I want
[32:03] people to understand the same thing
[32:04] happens for loops. Meaning, I will start
[32:07] doing loops because I'll take my
[32:09] process, the workflow that I do, and
[32:11] have the agents run and improve on it.
[32:13] So, I'm going to do something this
[32:15] weekend and show people like this is a
[32:17] process I've shown you on how I go from
[32:19] a transcript to a thematic portfolio.
[32:22] That process is five different parts. An
[32:26] agent loop can do that and go through it
[32:28] and then check for new information. Give
[32:30] me a new one. Go through it. Check it.
[32:32] Oh, a new transcript came out. Is this
[32:33] fit the theme? Should we change names?
[32:35] Like, it just continues it. So, it's
[32:37] like an endless loop of just getting
[32:39] better. Those are the things that impact
[32:42] workers. Those are the things that allow
[32:44] companies with lots of employees to
[32:45] figure out how to get rid of them while
[32:48] entrepreneurs I think are benefiting
[32:50] faster and Stripe has highlighted that.
[32:52] But I really believe that entrepreneurs
[32:54] have a huge advantage in this world.
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[34:52] Go upgrade your portfolio today. talk a
[34:55] little about the stripe sessions and and
[34:56] what uh what they're talking there with
[34:58] the soloreneurs.
[34:59] >> Um
[35:01] so we talked about this last year. I
[35:03] watched my first stripe session last
[35:05] year. Um after I watched I watched the
[35:07] one the year before because I like
[35:09] seeing um how things change. And
[35:12] Stripe's a very important company in the
[35:14] United States of America. It's not only
[35:16] just a big private company, but the
[35:18] future of finance is dependent on what
[35:20] Stripe is doing. And now you have all
[35:22] the banks and crypto. For everyone who
[35:24] listens to you, Stripe is a really
[35:26] important player in the crypto world.
[35:28] Um, my entire business is on Stripe.
[35:32] It's a great thing. I mean, taxation in
[35:35] other countries and everything along
[35:36] those lines. It just makes running the
[35:38] business much easier. And on the Stripe
[35:40] sessions, they if you just watch the
[35:43] keynote, first of all, you see these
[35:45] charts and you see these numbers going
[35:47] parabolic, but this is all about AI. So
[35:50] a lot of what they talked about is in AI
[35:54] if you want to build an app now it's
[35:55] easy you go do it in code so we see how
[35:58] many apps are being built but to take an
[36:00] app that does something and then turn it
[36:02] into money where you're getting the
[36:04] money so it becomes a business well then
[36:05] you need a CFO you need an well stripe
[36:09] projects allows you to go from this to
[36:11] that and they showed a demo of how you
[36:13] can hey you built your app that's great
[36:15] now let's turn it into where you make
[36:17] money so now it's not just the coding on
[36:19] one end the coding from actually being
[36:21] in the place where you can collect the
[36:22] money and go through it. The last thing
[36:24] is for the agents to talk to each other
[36:26] and to start commerce and they talked
[36:29] about the growth in that. The reason
[36:31] that's important is because that is the
[36:33] network effects for crypto. So you'll
[36:35] start to see benefits coming through the
[36:37] crypto world as the volumes pick up.
[36:39] That's what we need. We need volume. We
[36:41] need activity. And they talked a lot
[36:43] about it. And I just want to make sure
[36:45] people realize we can't actually get to
[36:47] that point where the network effects
[36:48] take off and the agents are doing
[36:50] commerce until the first two stages
[36:52] happen. You needed the coding to get to
[36:54] a level that it could actually replace
[36:56] humans. We did that. And so people
[36:59] understand the importance of coding.
[37:00] There would be no GDP in the world if we
[37:02] couldn't communicate with each other.
[37:05] Communication for human beings allows
[37:07] business to actually happen. We talk
[37:09] about things. You sell things. You do
[37:11] that. You explain it. The language of
[37:14] digital employees is code. So the code
[37:17] allows them to talk with each other and
[37:19] go through it. So we needed the code. We
[37:20] needed them to be able to code on their
[37:22] own. Once we hit that point, then they
[37:25] can start building not just the apps,
[37:26] they can start building the the
[37:28] financial part. And then you those
[37:29] guardrails are there and then the agents
[37:31] start doing stuff with each other. And
[37:33] on there they talked about the fact that
[37:35] certainly by 2030 but even sooner more
[37:38] transactions will be happening via
[37:41] agents than humans. And when we get to
[37:43] that point the only thing that works to
[37:46] deal with the transactions is not
[37:47] physical money. It's stable coins. It is
[37:50] actually on the guard rails. And so the
[37:53] stripe thing is a very important kind of
[37:55] gateway between the prior world and the
[37:57] future world. And I think for people in
[37:59] crypto who are depressed because of the
[38:02] bare market, the bare market continues.
[38:04] Um the AI agents at the critical point
[38:07] of what Stripe said is the commerce
[38:09] isn't happening yet, but we're getting
[38:11] there pretty soon.
[38:12] >> It's uh it's fascinating to kind of see
[38:14] how fast this is all going. Um one of
[38:16] the narratives that's changed
[38:17] significantly is uh the debasement
[38:19] trade. Uh Bitcoin, gold, silver,
[38:22] everything selling off. Uh I think
[38:23] you've called this the debasement
[38:25] capitulation.
[38:26] They're still debasing the currency.
[38:28] >> Yes.
[38:29] >> So, what's going on? Why is Bitcoin,
[38:31] gold, and silver all selling off?
[38:33] >> Um, I think last year, not just last
[38:35] year, but the last two years, uh,
[38:40] there were two, let's say, bubbles. And
[38:44] when I say bubbles, things that both
[38:47] retail and institutions agreed on. So,
[38:50] AI, no, retail loves AI institutions for
[38:53] the most part. there. The the older you
[38:55] are, the more you think it's a bubble.
[38:58] Nobody who thinks AI is a bubble thought
[39:00] gold was a bubble. Gold was the way
[39:02] bears got to come out and go, I'm
[39:03] bullish on something. It's just gold.
[39:06] They're also all bearish on bonds.
[39:08] Nobody owns bonds. Why would you own
[39:10] bonds? Like inflation's on the higher
[39:12] side. So the debasement trade is not
[39:15] just long gold, long silver, long
[39:16] Bitcoin. And yes, Bitcoin was part of
[39:18] it. Until October of last year, Bitcoin
[39:21] was outperforming the stock market.
[39:23] Bitcoin was outperforming bonds
[39:25] significantly. So gold, silver, and
[39:28] Bitcoin get lumped in. It's amazing how
[39:30] Bitcoin gets lumped into software. We
[39:32] got a bare market in that. It gets left
[39:34] it gets it gets put in with the
[39:36] debasement trade. Now the debasement
[39:38] trades washing out. You got gold and
[39:39] silver going down because Kevin Walsh
[39:41] came out and said, "Well, I think I'm
[39:44] going to be more hawkish." And everyone
[39:45] said, "That's it. Dollar rallies.
[39:47] Everything's good." And I'm like, "We
[39:49] still have a deficit. We still have
[39:50] massive debt. nothing is going to change
[39:53] because he speaks a certain language and
[39:55] we've got a lot of people I mean Warren
[39:57] Pies put out a great chart this week I
[39:58] was going to send it to you which just
[40:00] showed the
[40:02] the part of the economy that is now cons
[40:05] the information and computer side versus
[40:09] residential investment
[40:12] residential investment is not moving
[40:14] which means house prices are not moving
[40:15] which is where the bulk of Americans
[40:17] would like to see this bull market AI
[40:20] going up does not benefit benefit
[40:21] everyone the same way. So I I think that
[40:24] the basement trade has reached a point
[40:25] where because bond yields
[40:28] or bonds just stay stable. They don't do
[40:31] anything. Uh this was really people had
[40:34] reduced in their wealth management
[40:36] portfolio. I think some pension funds
[40:38] had done this. We had a scenario that we
[40:40] were overweight this debasement trade
[40:43] underweight bonds and when the trade
[40:45] starts doing poorly and it coincides
[40:47] with us running into the end of a
[40:49] quarter and everyone should remember
[40:51] this. Bitcoin is now an asset that
[40:53] people invest in. It's part of the asset
[40:55] allocation process. People make
[40:57] decisions at the end of a quarter and
[40:59] you tend to get a lot of people that are
[41:00] bailing out. You also have people
[41:02] shorting the hell out of the thing
[41:03] because I'm reading more Michael Sailor
[41:05] stuff and that Micro Strategy is going
[41:07] to blow up and they're going to have to
[41:08] sell. So we really have the mob is not
[41:11] involved, meaning retail is not
[41:13] involved. It's a bare market. You have
[41:16] institutions that hate Bitcoin. You have
[41:17] the debasement trade going down. You
[41:19] still have the software names like Adobe
[41:21] and Salesforce not bouncing at all.
[41:23] Bitcoin is just lumped in with a bunch
[41:24] of bad stuff right now.
[41:26] >> When will it recover?
[41:28] >> Uh again, I I'm for me this is a very
[41:32] simple thing. Um, and I say simple
[41:34] because
[41:36] it's what I do believe in terms of the
[41:38] endgame for AI,
[41:41] AI agents and the network effects
[41:43] happening and the amount of volumes that
[41:46] will be going on. The economy will
[41:48] change forever. There are two things
[41:50] that will happen and I've mentioned this
[41:52] on here at least a few times. when
[41:54] Caitlyn Long wrote a piece about the
[41:57] velocity of money changing. Now, this is
[41:59] a Tradfi banker who understands GDP and
[42:03] I we both respect Caitlyn a lot. Um, she
[42:07] knows that world really well and so do
[42:10] I. Velocity of money has been a dead
[42:12] thing and the reason it's been dead is
[42:14] because the world's assets have gone up
[42:16] so much. So, when you go through the
[42:18] whole what Bitcoin represents, it
[42:20] represents the fact that the fiat assets
[42:22] have gone up so much. the distribution
[42:24] of wealth has gotten worse and it makes
[42:26] people angry and the government just
[42:28] keeps solving this problem. They're not
[42:29] going to need to do that anymore. And
[42:31] the reason they won't need to do that is
[42:32] a combination of demographics. So there
[42:35] is 700 plus trillion dollars of wealth
[42:38] on the planet. It's in assets. Twothirds
[42:41] of those assets are in dormant assets.
[42:44] It's money. A house is money. If you can
[42:47] get cash for it, you can go spend it.
[42:49] It's money. It's like what SpaceX was.
[42:52] SpaceX was a dormant asset. It was a
[42:54] private thing. And over the course of
[42:56] the next few months, a lot of people are
[42:59] going to be millionaires and actually
[43:00] can go cash in their money. You'll have
[43:02] billionaires that can go cash in their
[43:03] money. Then they can turn around and go
[43:05] spend that money. They can go buy
[43:06] houses. They can do whatever they want.
[43:08] But it was a dormant asset that you'd
[43:09] have to go through hurdles to go borrow
[43:11] against. With tokenization and with AI
[43:14] agents transacting a lot, the velocity
[43:16] of money is going to increase
[43:17] significantly. And when the velocity of
[43:19] money goes through, people have to
[43:20] realize that GDP at the end of the day
[43:22] is a total sum of transactions and
[43:24] transactions are going to be happening
[43:25] faster. And the pieces of the pie that
[43:27] make up public companies are middlemen.
[43:29] They're taking taxes on all of this
[43:31] stuff. And so there'll be less taxes in
[43:33] terms of the the friction that goes on.
[43:36] And every year it'll get less and less.
[43:38] So, I've always believed that the third
[43:39] wave of crypto, which in Elliot wave
[43:42] terms means the most explosive one would
[43:45] happen when the agents came. And I just
[43:49] want to leave people with one other part
[43:50] of Elliot wave. If I'm right about that,
[43:53] and I believe AI is the durable part.
[43:56] So, for those of you who are bearish AI,
[43:58] where Bitcoin is gone to me is if AI
[44:00] collapses, which to me is not going to
[44:02] happen. AI is a real thing. It's going
[44:04] to keep moving forward. AI agents are a
[44:06] real thing and we just keep making
[44:07] progress. As that goes for the end of
[44:10] the second wave, you need people
[44:13] believing that we're going back to the
[44:16] depths. Now, the depths of FTX and all
[44:18] of that, this is not that. There are
[44:20] real people buying real businesses at
[44:22] dirt cheap prices right now. And I know
[44:24] some of the same people you do that are
[44:26] involved in this. These are really good
[44:29] people that have built businesses before
[44:31] that see value in this because they see
[44:33] the what the NFTs will be be as a
[44:36] positive thing, the need for them, why
[44:38] the blockchain is necessary in a world
[44:39] of deep fakes. All of these thematic
[44:41] things that I've written about in my
[44:43] Substack for 18 months, they're still in
[44:45] play. So, I think people just need to
[44:47] remember things change very quickly.
[44:49] Micron was
[44:52] $60 when you and I started this.
[44:55] It's now 1,200 and change. Things can
[44:59] change very quickly.
[45:03] >> It's a big move.
[45:04] >> All right. Well, thank you very much,
[45:05] Jordy. Anyone who uh needs something to
[45:07] do on Sunday morning, listen, this guy's
[45:09] got a banger coming out. I'm telling
[45:11] you, I know some of the little details
[45:13] of this video, you need to go and watch
[45:14] it tomorrow morning. Uh all you do is
[45:16] you just go Jordy Visser on YouTube. Go
[45:18] watch. Of course, if you're going to
[45:19] watch the video, you might as well, you
[45:20] know, help him out. Hit the subscribe
[45:22] button. Maybe put a little like, little
[45:23] thumbs up on uh YouTube. Neil, the CEO
[45:25] of YouTube, he likes that. He says, "Oh,
[45:27] Jordy's popular. Let me give him a
[45:28] little boost on uh this video." So, make
[45:31] sure you subscribe to to Jord's YouTube
[45:33] channel. Give him a a like on the video,
[45:35] and we'll do this again. I'll see you
[45:37] next week from Maine.

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