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4:39
Today is Friday, January 9th, 2026.
4:42
We are live from the TVPN Ultra Dome.
4:45
The temple of technology, the fortress fortress finance, the capital of capital.
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Let me tell you about ramp. com. Time is money. Save book.
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Easy to use corporate cards, bill pay, accounting, and a whole lot more all in one place.
4:59
Um, I forgot in the Vanity Fair profile that we were pitching Julia Ramp so much.
5:04
She actually put it in the profile. It was very, very funny.
5:07
Anyway, if you haven't had a chance to read, we were in Vanity Fair uh yesterday.
5:10
Uh, should uh it's a fun piece.
5:13
Little little whirlwind tour of what a show that happened maybe six months ago.
5:17
So, a lot of things have changed.
5:18
Uh, but it's a good snapshot.
5:20
>> But you got up to speed. >> Yeah, it's fun. >> Yeah, >> it's fun.
5:22
Um, anyway, uh we have a massive show for you today, folks.
5:24
Uh n uh $15 billion raised by Andre Horowits.
5:31
We have a bunch of folks. We have four members.
5:33
>> I'm going to hit the gong just because >> hit the gong. Warm it up.
5:35
You got to warm it up because we got to hit it 15 times when we have Jen, Alex, David, George, and of course Ben coming on the show.
5:43
Hit that app loving Jordy.
5:47
Uh linear of course, Meet the System for modern software development.
5:51
Linear is a purposebuilt tool for planning and building products.
5:52
Um, we also have Jeremy Anttoveros from Semi analysis coming on to explain energy, to explain data center buildout and uh the the gas turbine infrastructure that's going into those.
6:05
Uh he did a great interview with uh Ben Thompson that dropped yesterday.
6:10
Uh we're going to dig in and go uh deep into uh apparent there's a bunch of fascinating things.
6:18
Apparently, there's like 10 terowatts of requests for data center capacity, which is like way more than anyone would ever build.
6:26
Uh, but it's because of this weird dynamic of you have to ask for more than you need because you might not get it.
6:31
And there's a whole bunch of interesting things.
6:33
He of course uh broke the story that uh Meta had completely changed their data center design.
6:40
They were optimizing for uh sort of energy efficiency before.
6:42
Now, they're much more focused on speed of development and scale.
6:46
Uh, and so we're we're going to be taking you all over the place today.
6:51
Uh, but we're gonna start with Steve Jobs, Apple.
6:53
We're going back into Certino because there's a rumor that Tim Cook might step down sooner than expected.
7:02
So, uh, this comes from, um, Tim Cook, uh, his compensation, we've talked about it a lot, 74. 29 29 million per year. His salary is 3 million. Stock awards 57 million.
7:18
Non-equity incentive compensation.
7:18
He gets 12 million uh $12 million bonus if he does well. He gets 21,000 in 401k.
7:22
Uh personal use of private jet 800k on that. That's nice to see.
7:30
>> Only 800k >> vacation cash out of 56k security expenses.
7:34
Uh they're paying $900,000 a year to secure him.
7:37
That's a that's got to be a whole team of people.
7:38
Uh probably some jacked tier one operators following him everywhere he goes.
7:42
Uh but he is he is rumored to be out.
7:44
Uh Apple Track says Apple CEO Tim Cook has told senior leaders that he is tired and would like to reduce his workload.
7:52
Uh rumors suggest he could >> doubt I doubt they wanted that quote specifically. >> Yeah. >> To leak.
8:02
>> Uh but it did via the New York Times.
8:02
Uh and uh so rumors suggest he could announce a plan to retire as early as this year.
8:10
Uh of course the the rumor uh is that John Turnis uh might step into that role.
8:17
Uh Mac Rumors has a uh a story here.
8:20
Uh with Tim Cook having recently turned 65 years old and a number of other senior Apple executives having already departed in recent months or heading for the exits, there has been a significant focus on Apple's plans for who will succeed Cook as CEO.
8:31
I I I was hoping for a Warren Buffett third act from Cook.
8:36
I was hoping for him to just say, "I'm just hitting my stride.
8:39
65 to 95, that's where I'm going to do my best."
8:44
>> Window seen any compounding yet.
8:46
>> It's a completely underrated era uh for business leaders.
8:49
If you can stay in the game and and and continue to compound from 65 to 95, that's where the sweet spot is.
8:56
You just get ready to lock in, not not not check out.
8:59
But he might be >> we love to joke about him being underpaid.
9:03
I actually think he is or he has been serious.
9:05
But for how big of a company he is and what he's done to the determinism of Tim Cook coming in and just absolutely cooking for >> as long as he has it will always be remembered. >> Yeah.
9:17
So several recent reports have identified Apple's senior vice president of hardware engineering John Turnis as likely to be named the next Apple CEO.
9:26
in the New York Times has now shared a profile of Turnis with some context on his expertise and how he's viewed within the company.
9:32
Uh, according to sources who spoke with the New York Times, Apple has begun accelerating his planning for Tim Cook's succession last year with Cook having expressed a desire to reduce his workload, while software chief Craig Craig Federiki, services chief Eddie Q, marketing head Greg Jaw uh Jaws, and retail HR chief Dedra O'Brien have all reportedly been seen as potential candidates.
9:54
Turnis appears to have shot to the front of the pack with Cook likely to remain as chairman of the company's board of directors.
10:01
Oh, so he's not completely out to pasture.
10:05
He'll be in the boardroom.
10:05
Uh Turnis is known for his expertise as an engineer, having worked on many of Apple's devices through although he is known quote more for maintaining products than developing new ones.
10:16
Uh big question about what what the next decade or two of Apple's product roadmap actually looks like.
10:22
How many more new products do they need?
10:25
They sort of have every they sort of have one thing in every category.
10:27
If we go through a major uh uh form factor shift, that could be an issue.
10:32
But in general, uh if you have someone who's really good at maintaining products and keeping dominant market share, driving up margins, that could be the right person for the job. Yeah.
10:41
>> Um quote about John Turnis, he's a nice guy.
10:44
Let's hear it from Sometimes Sometimes nice guys finish first.
10:46
You know, they always say nice guys finish last.
10:50
I think that's a bit of fake news.
10:52
Uh uh this is from former Apple engineer Cameron Rogers. Quote about John Turnis.
10:59
He's someone you want to hang out with. I love it. He's just a good hang.
11:03
Everyone loves him because he's great.
11:05
He has he made any hard decisions? No.
11:08
>> Taking shots at your boy.
11:08
Hey, we just like hanging out with the guy.
11:11
We just like hanging out.
11:12
Has he had to do any real work ever? No.
11:15
Has he has he made any a single hard decision in his life? No.
11:19
I'm sure that's not true, but it does characterize uh his role.
11:22
I guess he hasn't been in the CEO seat, so he probably hasn't had to make crazy decisions like, should we launch Apple Vision Pro now or later?
11:29
You know, he's not the one.
11:32
He's just like, "You told me to launch it. I got it done." Right? That's that's his role.
11:36
>> Should we make the iPhone less durable?
11:39
>> That's a hard decision.
11:39
Uh are there hard problems he's solved in hardware? Also, no. What? This is an insane quote. Wow.
11:48
Uh Turnis and others may quibble with that assessment.
11:51
However, as Turnis has been involved involved with a number of innovative products over the years, including spearheading effort to develop the iPhone Air and working on the upcoming foldable iPhone. That's exciting.
12:03
Uh Turnis is seen as a natural successor to Cook even with with an even temperament, strong attention to detail, and in an intimate knowledge of Apple's supply chain.
12:12
That's obviously very good.
12:14
Uh but he may not bring the visionary focus and willingness to take risks that Steve Jobs had, leading to debate among Apple employees about exactly what type of leaders >> we need to get the Germinator on. >> We do. Yeah. Yeah. Yeah.
12:26
Can you reach out to Mark German to try to get him on the show Monday?
12:32
>> Let's talk through all of these things.
12:33
There's so much to talk about here.
12:33
Uh before we continue our conversation, let me tell you about the New York Stock Exchange.
12:38
Want to change the world?
12:40
Raise capital at the New York Stock Exchange.
12:42
So uh there's this question will John Turnis if he steps into the role of CEO of Apple will he bring the visionary focus and willingness to take risks that Steve Jobs had?
12:54
That's a tall tall order.
12:57
I think Tim Cook's ex executed extremely well.
13:00
He hasn't even it doesn't really seem like he's tried to bring a a visionary focus.
13:04
He he's been the operator.
13:08
>> He's a supply chain visionary.
13:09
>> He's a yeah visionary in his own way.
13:11
Um, but you were thinking and we've been discussing this need for a Steve Jobs of AI, a visionary leader in AI.
13:19
We have a number of uh household name type CEOs, Sam Alman, Elon Musk, Dario Amade, uh, Demis at Google Deep Mine.
13:29
Um, but we don't quite have that Steve Jobs.
13:32
Maybe that's too tall of an order, but you still think it's necessary.
13:37
So uh walk me through your thinking.
13:39
Before you do, let me tell you about Shopify.
13:41
Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI agents.
13:52
>> Uh yeah, everybody's worried about uh not having a job because of AI.
13:55
Well, AI needs a jobs, too. They need a Steve Jobs. >> Yeah. Oh, I didn't get that. That's good.
14:01
>> Uh so uh yeah, I I we've talked about this a little bit this week.
14:04
I tried to summarize it today in the newsletter.
14:08
>> Uh, and I'll I'll kind of read through a little bit.
14:11
So, uh, I went back and looked at the history of the phrase techlash.
14:14
It was originally, uh, coined by Adrien Waldridge and The Economist in 2013.
14:18
He correctly predicted that quote, "The big developments of 2014 will be the growing peasants revolt against the sovereigns of cyerspace.
14:26
sovereigns of cyerspace. the silicon elite will be cease will cease to be regarded as geeks who happen to be filthy rich and become filthy rich people who happen to be geeks uh over the coming years he was uh entirely correct it was actually in 2018 that tech lash was the runner-up word of the
14:42
year >> so he he like called it perfectly obviously you had the Cambridge Analytica scandal uh which is actually finally going to be uh dramatized this year with the social network too >> that's coming out this year do we have a release date yet for that >> I don't think so Um, but it is in the works. Um, and then yeah, just growing
14:59
Um, and then yeah, just growing concerns about monopoly power, privacy, uh, democracy, censorship.
15:06
>> Really quickly, Tyler, October 9th, 2026.
15:09
>> Yeah, that's what I'm seeing as well. >> There we go. Okay, we do.
15:11
>> Okay, book the tickets now.
15:11
It's going to be an probably great.
15:15
>> This would be a good We should organize We should We should uh actually I don't know.
15:19
I I'm not sure that this movie is I I expect this movie to hit like 10% >> Yeah.
15:25
or potentially negative in comparison to the social network one. Agree.
15:29
And so I think it might be the kind of thing you get a bunch of people to go and it's just like okay that that was >> the social network the original movie is is a really good roarshock test for are you going to have a good time in tech?
15:39
Like if you ask someone who is thinking about working at a company or tech startup like what did you think of the social network and they're like oh I thought it was like awful and like I hated all of it and I there were no heroes.
15:50
Uh well they're probably not going to enjoy tech.
15:52
But if they came away from it being like, "Oh, well, it's actually really inspiring because he just coded a thing in his >> in his dorm room that became really big."
16:01
And yes, there was drama and fights over who gets what on the cap table, but uh even Eduardo Saver became a multi-billionaire.
16:07
So, you know, sort of an aim for the moon, land amongst the stars situation.
16:12
Uh, so yeah, I mean, uh, you could read it both ways, but I think most people, most tech insiders, if you ask them about the social, they were like, "That was inspiring.
16:23
I listen to the music all the time.
16:25
It inspired me to grind harder, basically."
16:28
>> Real quick, happy birthday to the chat. Happy birthday to you. Happy birthday to you.
16:38
>> Uh, >> Gemini 3 Pro, Google's most intelligent model yet.
16:40
state-of-the-art reasoning, next level vibe coding, and deep multimodal understanding.
16:46
>> Anyways, I'll continue.
16:46
So, first, Techlash is all about how is this impacting our mental health?
16:50
How's this impacting our democracy, uh the foundations of our country, society, privacy, uh you know, censorship, etc.
17:00
Uh the second tech lash has begun.
17:00
Feels like it started last year.
17:03
You know, this is one of those things like yeah, you don't really know.
17:06
like sometimes it takes a while to realize like okay we're we're in this thing now that we can look back and see how public opinion has been forming around this.
17:14
So yeah, uh I believe the average American believes that technology and now AI is now like a threat to their way of life.
17:21
So I was looking at >> there were rumors of the tech lash in 2024 when the image generators came out.
17:28
A lot of the arts community were saying this is really really bad.
17:30
It's going to put artists out of jobs.
17:32
uh the the the thumbnail uh community on YouTube was upset, but this year it's solidified around there's like three or four key points, key talking points.
17:43
If you talk to someone, why don't you like AI?
17:45
Well, it's it's uh stealing copyrighted information. It's slop.
17:49
It's putting people out of jobs.
17:52
It's stealing water and stealing power.
17:54
and stealing power. And each one of those >> the first tech lash was like okay these tech our lives are now existing in these platforms and they are in some ways more powerful than the government right and now uh I so I I was I pulled I I had Maslo's hierarchy of needs pulled up and I was just like going through and
18:10
looking at physiological needs right air water food shelter sleep clothing reproduction safety personal security employment resources health right all these different things and then you just go up and you can see that like there's good reason for the average American that just kind of believe like AI is going to mess all of this up, right? So,
18:26
So, starting at the bottom, Americans have heard that data centers use a lot of water, right?
18:31
It's not necessarily factual. >> Yep. Sure. Sure.
18:34
Water is used in the process, but we're not like, you know, blowing through water at the rates that the public sorts.
18:42
>> I was joking about this online.
18:42
I was hypothetically debating with a AI doomer about water usage.
18:46
Uh, well, are they long water stuff?
18:48
Because if if you if you believe that AI is going to use all the power and you bought GE Verona, you did very very well.
18:55
Uh but the water stocks have not mooned.
18:58
So hey Dels who think AI is going to use all the water, maybe you got to put on a long position.
19:05
>> Privatize a public utility, you know, become a monopouist.
19:08
>> Also, I mean, we're talking to Jeremy at semi analysis, uh who's sort of their power expert.
19:12
Obviously uh uh AI does use a lot of power and there's a lot of investment thesis that can be built on top of the semi- analysis energy model.
19:21
Uh so why doesn't semi analysis have a water model?
19:23
Oh because it's actually not a bottleneck to anything. >> Yeah.
19:26
So the power thing uh is is more real.
19:29
Uh people now just assume like if they I I have to imagine people are reading an article, oh your power bill might be going up.
19:35
If your power bill just goes up because it's a winner, you're like, oh thanks AI.
19:41
I I uh you know I didn't ask for this.
19:43
Uh so they've seen Terminator 2, so they can imagine kind of like the sci-fi scenario playing out. Uh that's one factor.
19:50
Uh if they're super online, they might have heard like the the Casey Hammer or other people have talked about this like solar panels, you know, an AI system just saying like, "Hey, actually this farmland, I could use it better than you humans."
20:02
>> Remember that Ilia video?
20:05
So he did an interview with the San Francisco Chronicle. It was this video.
20:09
It was like a video documentary almost where they were interviewing him, but there was no questions.
20:12
So, you never saw who was asking the questions, but he was giving his answers and he's sort of like sadly walking around on a gloomy beach. It's like very moody.
20:19
And >> I I would say it's he was oring. He looked sick. >> Yeah.
20:25
>> He was looking over the >> He did orura San Francisco a little bit.
20:28
But uh a as I was getting dressed up as him for Halloween, we were playing that video and the makeup artists who were who were uh applying the Ilas Sutzkver uh you know all the makeup to me were watching that being like that's not inspiring at all. >> Okay. Yeah.
20:45
And I didn't even include that in here, but that's like the reaction.
20:48
Like every time people hear leaders at Labs talk, they're like turn it off.
20:53
it off. as opposed to you could show someone uh an Apple ad or Steve Jobs clip and and it would be like oh dancing on your wired headphones with your iPod like I love music they're making music available great I love it and there were so many things that were just inspiring uh so continue
21:12
>> yeah continuing so uh yeah moving up the pyramid uh people have been told that AI is coming for their jobs some people have like actually had an experience that made them feel like whoa I I thought I was I thought what I did was unique and special, but now I'm watching my job, >> kind of do it on my own computer. Uh
21:28
Uh maybe, you know, imagine somebody that's driving for Uber and Lift and all day long they're driving and they're just seeing way they're sitting next to Whimos in traffic and you're looking over and there's no one in the seat. Like that's ominous.
21:38
That's that's that's going to be scary if that's how if house somebody puts food on their table.
21:44
>> Um and then every single CEO last year was saying like we have you know fortunately we have increased efficiency due to AI and so we've laid off 10,000 people, right?
21:52
And so a lot of that is just kind of like spin marketing etc.
21:56
But that's what people are hearing, right?
21:57
Uh and then you look at what our uh the AI leaders are actually saying.
22:02
So so Ilia uh talking for 10 minutes, people are like whoa that doesn't seem good.
22:06
Ilia is saying like >> he he's saying let's not do that.
22:08
He he's he's trying to prevent that bad scenario, but it still reads like whoa, I didn't realize they were taking that seriously. >> Yeah.
22:17
So you look at the quotes just you could easily look up quotes from Daario.
22:21
obviously had his quote, "AI could wipe out half of all entry-level white collar jobs and spike unemployment to 10 to 20% in the next 1 to 5 years."
22:28
>> Uh Elon had a good quote uh from over a decade ago.
22:31
He said, "With AI, we are summoning the demon."
22:33
Uh >> some people today might say the demon has been fully summoned. >> Fully summoned. >> Fully summoned.
22:40
>> Uh and Sam obviously said at one point, "AI will probably most likely lead to the end of the world, but in the meantime, there'll be great companies."
22:50
And so this kind of messaging, uh, credit to them, it's like super effective for fundraising, right?
22:53
If somebody's saying like all jobs will be wiped out, the world will be destroyed, but in the meantime, >> there's a lot of funds that are long demon, >> you know, you're just like the demons, >> the demon, the de the free cash flow from demons. >> Yeah.
23:07
So it's like if you're sitting there being like, if AI is going to eliminate my job, I want to own a piece of it.
23:11
So, you know, maybe maybe I can benefit from it. Um, >> uh, so yeah.
23:15
So the big issue is like anybody that's hearing all these >> like why would they actually be excited about AI, right?
23:21
Even though even though it is so incredible in so many ways, right?
23:24
I gave the example earlier this week of like AI just being like a >> uh a free sleep consultant for a toddler that just like one shots it and it's free, right?
23:34
>> Chad Health that launched this week.
23:34
I mean that that's very good news for a lot of people that uh you know can't see a doctor that often or just don't have the time or don't have the money.
23:42
There's a million reasons why that might be uh advantageous.
23:43
And yet it's it it it it's not that they're not pitching it like Steve Jobs pitched Garage Band which was like now anyone can be a musician.
23:54
Uh now anyone can be their own doctor is inspiring but it's just like they are fighting an uphill battle because of those other quotes. >> Yeah.
24:01
Uh so yeah and I and I was thinking about it's like if if you wanna uh if if somebody is kind of like generally scared of AI, who do who do you who like what do you what content do you point them towards?
24:12
Typically you'd want to point them towards the people building it, right?
24:14
Uh and say or or people around it, but even like Taresh is like a little bit maybe like too high level or uh not not high level enough actually, right?
24:23
It's like a little bit too ethereal, right?
24:25
Talking about all these different potentials.
24:27
But if you have them listen to like a Joe Rogan episode with one of these guys, it's going to be >> to be fair.
24:33
I not to debunk your piece, but I I do think Demis is pretty good.
24:38
>> I Yeah, Deus is great.
24:38
He's had he's >> he doesn't have one of those crazy quotes.
24:42
And there's been two documentaries about him.
24:44
Both of them are incredibly inspiring.
24:46
And when I hear him talk about uh AI curing cancer or humans curing cancer with AI, it hits a lot different because he literally has a Nobel Prize and and is solved.
25:00
>> The problem the problem if you look at if you just count up the views that Elon, Sam, and Dario have gotten in comparison to Demis. Yeah. Right.
25:08
>> He's much less of a household name and he's also not the CEO of of a big company because he's running the biggest lab in a big company.
25:13
Uh and so there's there there's that. He just doesn't >> Yeah.
25:16
So I so I've just been feeling like there's this uh >> gap >> gap Steve Jobs sized hole, right?
25:20
Uh he had plenty of concerns about techn technology. He shared them freely.
25:27
Somebody once asked him uh so your kids must love the iPad.
25:29
Then he he said my kids haven't used it.
25:31
He just said we limit how much technology we have in the home. Yeah.
25:36
>> Uh he he did talk about like losing the PC race to international business machines.
25:41
He said, "If for some reason we make some big mistake and IBM wins, my personal feeling is that we're going to enter a computer dark age for about 20 years."
25:49
Like you can imagine like Sam saying something like that around like you don't want and and you've seen the internal sort of messages between him and Elon talking about like losing to Google.
25:57
It's like oh we don't want Google to to control the AI god, right?
26:02
Um >> uh he also had a he had a 1994 uh Rolling Stones interview Rolling Stone interview.
26:08
Uh the the interviewer said, "Nevertheless, you've often talked about how technology can empower people, how it can change their lives.
26:13
Do you still have as much faith in technology today as you did when it when you started out 20 years ago?" Steve says, "Oh, sure.
26:20
It's not a faith in technology, it's faith in people."
26:22
Uh technology is nothing.
26:25
What's important is that you have faith in people, that they're basically good and smart, and if you give them tools, they'll do wonderful things with them.
26:32
It's not the tools that you have faith in. Tools are just tools.
26:35
They work or they don't work.
26:38
it's people you have faith in or not. Yeah, sure. I'm still optimistic.
26:40
I mean, I get pessimistic sometimes, but not for long.
26:44
Um, and I and and and part of this I just it feels like people have like are are part of it like fundraising, part of it's just how excited we are about AI, but like you're leaving humanity out.
26:55
So, there's this quote from Sam.
26:57
He says, "If AI stays on the trajectory that we think it will, then amazing things will be possible.
27:03
Maybe with 10 g of compute, AI can figure out how to cure cancer.
27:06
So, it's like that's a fine quote if you there's some way to look at and be like, okay, super >> this abundance. This is super exciting.
27:15
I'm I'm maybe more optimistic about AI.
27:18
Uh but he happens to he's saying that AI is going to figure out how to cure cancer, right?
27:22
And like if you've used these tools today, >> Yeah.
27:25
>> Yeah. uh and any and talk to people that are that are at the labs they're they the reality is like it feels much more likely that humans will use AI to cure cancer right thesis >> like Steve would have said if AI stays on the trajectory that we think it will then amazing things will be possible maybe with 10 gigawatts of compute
27:42
humans can use AI to cure cancer like small small tweak >> humanity it's a big it's a big difference and so uh I wrote the facts for the fact Steve Jobs was not one to shy away from impressive specs and massive scale but flipping the final line from AI will cure cancer to humans will use AI to cure cancer makes all the difference. Apple put human centrality
27:59
Apple put human centrality at the heart of everything they did.
28:03
Even when they were talking about something uh like a CNC to mill an aluminum block into a MacBook Pro, the focus was not on the CNC.
28:09
It was uh on what it allowed the human being to do. Right?
28:15
>> CNC is literally a robot.
28:15
It's computer numerical control.
28:18
But when you watch that al that uni-body presentation, it puts Johnny IVive at the center.
28:23
And it's like that I used the tool to create something beautiful out of this amazing material that I could never do with just my normal tools.
28:31
Like I could never chisel out an aluminum unibody. I need a CNC for that.
28:35
I have it and I can create something beautiful. >> Yeah.
28:38
Um so yeah, at the end of this I just said like I think AI has a massive narrative problem right now.
28:42
It the narrative is working within the industry.
28:45
It's not working for people that are outside the industry.
28:49
I really don't think it is a humanentral there in this future and we're not doing it right now and and I expect that >> I expect that everybody will will you know Elon has his own style of pitching all things and I don't think he's going to change.
29:10
I think that that other folks um maybe like Daario and Sam can, you know, make small tweaks that will go a long way. Yeah.
29:20
>> And and obviously there's there's founders that we don't even know their names yet that are going to be huge players in all of this as well. >> Definitely.
29:26
Uh before we move on, let me tell you about 11 Labs.
29:28
Build intelligent real time conversational agents.
29:31
Reimagine human technology interaction with 11 Labs.
29:33
Um, so there's uh some massive news from Meta.
29:38
They are doing a big deal with Oaklo uh to build nuclear power plants.
29:44
Uh we've been following the energy story very closely this week.
29:48
Obviously, we're talking to Jeremy in just a little bit.
29:50
We have some exciting guests next week.
29:51
Uh digging into how uh we are going to generate more power in this country.
29:56
Uh the headline from the Wall Street Journal is Meta unveils sweeping nuclear power plan to fuel its AI ambitions.
30:01
And we'll read through a little bit of this.
30:06
Meta Platforms on Friday unveiled a series of agreements that would make it an anchor customer for new and existing nuclear power in the United States where it needs city-sized amounts of electricity for its artificial intelligence data centers.
30:18
Facebook parent said it would back new reactor projects with the developers Terrap Power and Oaklo and has struck a deal with the power producer Vistra, which is up 11% today, uh to purchase and expand the generation output of three existing nuclear power plants in Ohio and Pennsylvania. So, they already exist.
30:37
There's probably some uh some work already done on the permitting side.
30:41
They're probably deeper in, but uh Facebook's just stepping up and saying, "Hey, we we're opening the pocketbooks.
30:48
We got the debt, we got the cash flow, we got the money to power this and take it across the finish line.
30:53
So, uh, Vista and Oaklo, both their shares rose about 15% after the stock market opened.
30:57
Terap Power is still privately held, so no movement there, but you imagine the secondary market is booming right now.
31:05
Uh, Meta aims to see the first new reactors delivered as early as 2030 and 2032, which feels like it won't matter because super intelligence will be here by then.
31:15
Certainly AI 2027 we're now we're now less than 12 months away from from the super intelligence if you believe the the most aggressive possible scenario.
31:27
>> I mean to give to give AI 2027 credit to date it's been it's been fairly on point. >> It has. It has.
31:34
And no one will correct you more quickly than Tyler Cosgrove over there.
31:38
Uh the ultimate agent killer.
31:41
Uh I I do think uh we were trying to do the number of days till AGI on the ticker and I think we got to go analog.
31:47
I've been enjoying moving the goalposts and I think we need a massive flipboard.
31:53
>> It's like the doomsday clock. We the clock.
31:55
Well, you know how um uh do you remember back in the old days when there was a movie theater and they would put up the letters on each of the like if if it was like Avengers, they would take an A and they would take a little sticker stick like suction cup on the end of a pole and they would put it up on the the marquee one letter at a time.
32:15
I feel like we need something much more analog to change the number of days till the singularity as we monitor it here on TVPN.
32:24
uh its purchase of nuclear power. >> Yes.
32:27
Uh we're we're very wide we're very eyes wide open that the schedule is challenging, but we think it's important to be bold, said the director of global energy at Meta. What a gig.
32:38
>> That's a great >> hitting.
32:40
>> I'm the director of global energy >> around the >> I'm the energy director. I'm the chief energy. >> Power this globe.
32:47
>> You're going through me uh soon.
32:47
I mean, you you got to be angling for a promotion there.
32:52
view Meta as like a a nation state. >> Yeah.
32:56
Well, that that so the problem is the globe. It's impressive.
32:57
Meta operates all over the globe.
32:59
But why aren't you thinking bigger?
33:01
Who's the director of solar system level energy development?
33:07
>> G galactic energy production.
33:07
Universal energy production.
33:11
You should be producing energy all over the universe meta.
33:15
You're thinking too small with merely focusing on the globe.
33:17
Uh, hitting those timelines for new reactors would require the companies to quickly select sites that would be acceptable to nuclear regulators, start working with utilities to secure grid connections, and get their manufacturing operations up and running, she said.
33:30
But it would also mean they have a chance to meet the urgent demand for more electricity to fuel AI computing.
33:35
And so, if you think about 2020, 2032, this stuff comes online, that's great.
33:42
But that feels like 2027 2028 we're going to see a mismatch in demand relative to production.
33:50
So we'll talk to Jeremy from semi analysis about how we can solve that in the interim.
33:54
Uh let me tell you about Figma before we move on.
33:55
Figma make isn't your average vibe coding tool. It lives in Figma.
33:59
So outputs look good, feel real, and stay connected to how teams build, create codeback prototypes and apps fast.
34:05
Um continuing um uh Oaklo and Meta uh making this announcement. 1.
34:12
2 gigawatts is the total size of this nuclear campus in Pike County, Ohio.
34:17
The agreement includes binding prepayment to support fuel procurement enabling Oakllo to advance early project work to and secure fuel adding new clean reliable power to the grid.
34:28
So uh >> yeah, Oakllo opened uh super high this morning and then is uh at at 115 and then has been trading down.
34:35
So, it's up 7% today, but up 28.
34:37
7% in the last five days.
34:40
So, uh it's almost like uh it's almost like somebody knew this was coming.
34:45
Um but uh this was a this was a fun article in the journal.
34:50
Uh were you happy to hear that AI is mining our trash for treasure? >> Trash economy. Trash economy.
34:54
We're going to be using cubes trash.
34:58
>> We're all going to be getting trash post AGI. >> Yes. Yes.
35:00
We're going to be using cubes of trash to uh to everyone will be rich because everyone will be everyone will have a cube of trash in the trash economy.
35:08
Uh the the headline from the journal is AI is mining our trash for treasure.
35:14
Uh >> plus hospitals embrace AI for better and worse and scientists create a robot smaller than a grain of sand.
35:21
>> So waste management the largest US trash hauler and recycler is spending on building and automating recycling facilities.
35:28
You you have to go back and imagine a Sopranoslike scenario where the mob is running trash management and just vibe coding and being like what model should we use to detect what's in the trash.
35:41
What what's actually happening here is that they have to sort out the recyclables because there are valuable things that get thrown away in the trash and the more that you can route things to different places the better.
35:50
So it's a difficult job that pays workers little and it's hard for companies to fill.
35:54
Who really wants the job of trash sortter?
35:58
>> That was like my first job picking up cigarette butts.
36:00
>> Yes, but you didn't have to sort them.
36:03
Um, you should you It's ridiculous.
36:05
>> Maybe I should have Maybe I should have found you.
36:07
>> Never figure out that they just have that, you know, that bucket that you put down and then you sweep into it. How did you not tools?
36:14
>> It was a It was like a dirt vacuum.
36:14
It was like consider vacuum.
36:18
>> It was like fine rock >> that was the ground.
36:20
And so if I was doing that, I would just be >> picking up rocks >> and then I'd have to be >> What about one of those grabber tools?
36:25
I still feel like at a certain point you weren't even operating at like monkey or dolphin level.
36:31
>> I was more like I was running. I know.
36:31
I actually was running around like a monkey.
36:34
Like I like the speed at which I could just be like running around.
36:37
>> But the monkey and the dolphin, they developed tools and you you were unable to develop tools and you suffered because >> I was promoted fairly quickly. >> Okay.
36:43
You you developed tools eventually.
36:46
Uh, thanks to recent advancements, some recyclers are now employing machines to do this dirty work.
36:51
Uh, this week, Ryan December, uh, reports on the recycling companies using AI to find valuable commodities in the trash.
37:00
So, um, here's a job that computers can take without much complaint. Sorting recyclables.
37:04
And before we read this, let me tell you about Lambda.
37:08
Lambda is the super intelligence cloud building AI supercomputers for training and inference.
37:14
uh that scales from one GPU to 100.
37:16
>> Do you have the uh do you have the honor of being uh serviced by waste management?
37:22
>> I don't know actually.
37:22
I think my town might have its own, but >> every time I use uh I interact with waste management. >> It's good. >> It's great.
37:30
Like it makes me wish that all utilities were privatized.
37:33
>> How does that how does that manifest?
37:35
>> I mean it's just the website is great. The support is great.
37:37
It everything about the experience is great.
37:40
When are you going to a website to interact with your trash? >> Just like moving.
37:44
Okay, I need new if you move.
37:47
Like there's all these things like interacting with California utilities.
37:51
>> My trash bin broke at one point and I needed a replacement. >> One click.
37:55
>> I bet waste management will have an agent that >> clog code.
37:58
Get me a new uh get me a new uh trash can.
38:02
I suppose uh for humans it is a foul labor laborious job that entails standing over a conveyor belt plucking beer cans and detergent bottles from a stream of refues.
38:13
The job pays little and is hard to fill.
38:16
At Murphy Road Recycling's material recovery facility near Hartford, the machines are taking over the dirtiest jobs.
38:22
A few workers remain on the line, mostly near the front to watch for hazardous items.
38:28
Otherwise, the system of conveyors, magnets, optical sorders, and m and pneumatic blocks run largely unmanned.
38:35
Watching over it all are computers that analyze material as it passes by about 7 miles an hour.
38:41
The device is made by Londonbased Gray Parrot.
38:43
That's a good name for a company.
38:45
Use artificial intelligence.
38:47
The African gray parrot, I think, is the smartest parrot.
38:49
Or maybe it lives the longest.
38:51
Um, use artificial intelligence to identify recyclables.
38:55
Flag food grade material. Gauge items mass. Assess market value.
38:58
They're doing DCF on every >> African gray parrots can live to 70 or 80. >> Let's go. Let's go.
39:06
>> Imagine just having the world's most wise parrot. Just with you always. >> Like it.
39:11
>> Tyler, you should get into birds. >> Yeah. Bird guy.
39:14
>> I don't know if we're uh I don't know if our office lease allows bird. >> What's your budget?
39:18
I was I think an African gray parrot is expensive.
39:19
I remember I was moving into a an apartment building and and I don't know why, but my friends were telling the landlord that we had that one of the friends that was moving in had a collection of African gray parrots, and they just thought it was the funniest thing to try and get this landlord to approve the African gray parrots in the in the apartment. It was very very silly.
39:44
>> Uh there's a store there's a store in LA called The Perfect Parrot.
39:48
>> Maybe you should go over there, Tom. >> Maybe.
39:49
Gold Rock's Mike Row is punching the air right now.
39:52
Dirty jobs, uh, getting displaced.
39:55
Um, so, uh, environmental concerns and the White House's push to boost domestic production of raw materials have turned attention to America's waist stream, which is full of valuable commodities.
40:06
Uh, the aluminum tariff, 50%, has lifted demand for scrap metal.
40:09
Meanwhile, pulp mill closures have left box makers reliant more than ever on old corrugated containers, and consumer good companies want to reclaim their bottles and jugs as states adapt adopt extended producer responsibility laws aimed at reducing plastic pollution. That's good news.
40:25
Uh there's really a lot of value in a lot of recyclables and garbage, says the founder and chief technology officer at AMP, a Colorado company that builds AI run recycling facilities.
40:36
The problem has been that the cost of pulling those materials out is similar to or greater than the actual value of those materials.
40:46
Recyclers believe that AI will allow them to efficiently mine our trash for treasure.
40:49
Gray Parrot's analyzers were shown recyclables thousands of times in conditions raising ranging from crumpled to perfectly intact until the computers could recognize materials. Perfect job for AI.
41:02
Uh the devices gather data about what is passing through the facility and which items aren't winding up where they belong.
41:07
It's helping us make adjustments to the system.
41:09
Uh Murphy Road executives say the technology allows them to sort up to 60 tons an hour of curbside recycling.
41:15
Um and some of these some of the some of the stuff that you can pull out of recycling is is remarkable, especially if there's batteries that can be disassembled.
41:23
There's a whole company, Redwood Materials, founded by JB Strabble, uh former co-founder of Tesla, early employee of Tesla, board member of Tesla, uh focused on re uh uh recycling EV batteries.
41:35
uh because obviously we have the rare earth elements, we make the magnets, we make the batteries, and then we just kind of trash them.
41:42
And if you can recycle them, that's obviously uh effective and valuable.
41:46
Uh sort of an interesting second.
41:49
>> What do you think about the name Redwood Materials?
41:52
>> Wouldn't you expect them to be working >> in wood? Wood, >> I guess. I don't know.
41:55
Yeah, I don't know why they call that.
41:56
I think they're out in Vegas.
41:57
They have a massive facility.
41:58
Uh I wonder how the business is doing.
42:00
I know they raised a bunch of money.
42:01
money. It was a massive capex intensive effort but it seemed like something that was uh uniquely powered by uh you know seeing the roll out of Tesla you know he JB Strable is working on Tesla seeing how many cars they're shipping watching all the batteries go out the door and
42:18
just thinking okay well something's going to happen with those in a couple years I should start building this business today >> well Crowdstrike your business is AI their business is securing it CrowdStrike secures AI and stops breaching Um, so let's move on to the big news of the day. Andre Horowitz raised $15
42:37
Andre Horowitz raised $15 billion. Uh, why are we here?
42:41
Why did we raise $15 billion?
42:43
Ben Horowitz wrote a piece on X.
42:45
Uh, you can go and read it. He's also joined.
42:48
>> By the way, Redwood Materials, the last round they raised was in October of 2025. I missed that. >> October of 2025. Oh, >> yeah.
42:55
So, very recently raised 350 million. >> Yes.
42:57
Uh, so, uh, massive suite of new funds.
43:00
The hall represents 18% of all venture capital dollars allocated in the United States in 2025. Uh >> yeah.
43:08
So should uh that that that was something I I was uh curious about.
43:11
Does this get sort of like backdated like this wasn't factoring into the data that we had from last year and now that it's or or was it already being >> uh counted in some way through through filings? Right.
43:23
Because you add you add an incremental, you know, 15 billion >> Yeah. funding change. I don't know. We'll have to ask them.
43:30
Um, but A16Z is now at 90 billion of AUMUum.
43:33
Uh, and it's split over a number of funds.
43:37
Growth, the growth fund got 6. 75 billion.
43:40
American Dynamism 2 got 1. 776, I believe. Right. Uh, or is it 1. 176 billion?
43:49
I I it's uh there's two different numbers here. Um, uh, apps 2 got 1. 7 billion.
43:55
Infrastructure, the second fund got 1. 7 billion.
43:57
bio and healthcare got 700 million and other strategies got three billion.
44:01
I wonder uh crypto is sort is sort of missing here.
44:06
I wonder if crypto is just on a different cycle or has some sort of different structure.
44:08
We'll have to ask them about that.
44:10
Um but uh very exciting and and uh feels like despite the headline of venture capital fundraising declining um certainly uh plenty of money to go around.
44:21
Well, I think both both Josh and Delian this week talked about kind of the K-shape uh and how uh emerging manager less emerging managers less new funds, but the uh the platforms have been uh doing just fine. >> Yeah.
44:37
Um yeah, I I I'm I'm I'm curious about this this Oh, the Okay. Okay. So, I I understand it.
44:45
So, uh, American Dynamism Fund 2 raised 1. 176 billion.
44:52
They already had a $600 million fund.
44:54
So, you add those together and you get the final amount of funding for American demi dynamism across the two funds. 1.
45:02
776 billion for American Dynamism.
45:04
And, uh, some cool trading cards going up from Andre.
45:09
Uh David Uolovich shares one of an Anderrol Fury drone uh flying across a mountain range uh for companies that support the national interest.
45:19
Katherine Bole had a different graphic uh with a horse which we love.
45:23
Play that horse sound uh with an American flag uh and the uh and the the Andre new font which is a very uh beveled and 3D looking uh metal texture. Uh very fun.
45:36
And uh >> PY has a new piece on uh on some of the history of the fund.
45:43
Uh the opening is quite uh quite fun. I'll just read it.
45:50
>> Before we do, let me tell you about Cognition.
45:51
They are the makers of Devon, the AI software engineer.
45:53
Crush your backlog with your personal AI engineering team.
45:56
Uh, Paky says, "Andre Horowitz hears your feedback that it's too loud, that it would shut up and dribble, that it should shut up and dribble, politically speaking, that you don't agree with the recent investment or two, that it's unbecoming, to quote the pope, that there is no way it will ever generate a reasonable return for LPs on such enormous funds. A6Z does hear you.
46:17
It has been hearing you at this point for nearly two decades, >> overnight."
46:22
>> And then he goes in uh to a bunch of the history and the news.
46:25
So, I I would I would encourage everybody to go uh >> to go read specifically.
46:29
There's there's a bunch of information on um on their actual returns, which is cool.
46:35
But, uh unfortunately, this went out right before we joined, so I have not >> been able to read it yet.
46:43
>> There, but there was some spice.
46:43
We got to get to the drama.
46:45
Uh so, Andre and Horus, they put out this image.
46:48
We Why we raise 15 billion. We're all in on America.
46:52
And what image do they use? They use Mount Everest.
46:54
They're climbing Mount Everest.
46:55
The the the uh the metaphor is clear.
46:57
It's the tallest mountain.
46:59
We're the tallest mountain in venture. We got the most money.
47:00
We're we're the biggest firm.
47:03
But a lot of people are saying, "Hey, why'd you use a Chinese mountain?
47:06
Why'd you use a Chinese mountain? It's Everest.
47:08
It's over there in China.
47:10
It's actually half in China, half in Nepal. It's more complicated."
47:13
But maybe it's foreshadowing.
47:15
Maybe it's foreshadowing.
47:16
You know, we're acquiring Greenland.
47:18
Maybe they know something we don't.
47:20
Maybe it's not going to be in China forever.
47:21
Maybe we we already we already named it.
47:23
Everest is named it by an American who uh I believe was the first person to climb it.
47:28
Um and uh >> yeah, and remember so so uh land acquisition, White House officials have talked about a $5.
47:34
7 billion payment for for Greenland, right?
47:38
That uh depending on what type of payment would be needed for a place like Nepal, right?
47:43
You can imagine it being potentially less than that.
47:47
So, uh, >> yeah, >> A16Z, they've got plenty plenty of cash.
47:51
But, uh, I'm super excited to have a whole host, uh, of folks from the fund.
47:55
Jen is joining, Alex, uh, Rampel, >> uh, David, and then, uh, Ben will cap it off at the end for his >> and Dan Primack is pulling out the spiciest quote.
48:05
VC industry shots fired by Ben Horowitz.
48:07
Ben says, "As the American leader in venture capital, the fate of new technology in the United States rests partly on our shoulders." That seems reasonable.
48:18
Um they're they're certainly up there.
48:21
Uh and uh leaders obviously by what definition, but uh they're certainly in the top with in terms of aumum.
48:28
Um and uh and the they I mean they do have a they do have a responsibility for >> and Josh Wolf yesterday was was saying that he expects uh at least one or two uh of these larger platform funds to go public.
48:47
>> Uh so we'll have to uh we'll have to get into that. >> Yeah.
48:49
I mean that that's a very interesting angle with Andre is because it's it's becoming such a large they call it platform fund.
48:55
Uh they're almost private equity type deals.
48:57
We've seen G General General Catalyst, buy a hospital network.
49:01
Like they're at a scale where they can keep a company private until they're a trillion dollar company, but they can also buy whole companies and roll things up and incubate stuff.
49:14
There's so much that you can do at this level.
49:16
And it starts to look like, is the comp actually Black Rockck?
49:18
Is the comp actually Blackstone?
49:20
And those two firms are worth 170 billion each, something around there. 90 billion each.
49:27
And so, uh, it's it's going to be it's it feels like it's going to be interesting to start seeing these firms more as financial institutions. Yeah.
49:36
With more traditional, >> not just a firm and institution. >> Yeah.
49:40
Not not that it's going to happen anytime soon, but it feels like, >> but this feels like it could be effectively a preIPO round, >> preo fundra. Maybe >> we will see. We will see.
49:49
But go read Paky's piece.
49:51
Uh and uh Sham Sankar uh says we should insist that all data centers that are built are architecturally beautiful in the neocclassic style.
50:03
>> Yes, I wanted to do an architecture deep dive.
50:05
Uh before we do, let me tell you about label box.
50:07
Delivering you the highest quality data for Frontier AI. Get in the box. The label box. >> Get in the box.
50:17
I love that they they gave us enough uh just enough rope to hang ourselves.
50:23
Uh so Sham Sankar, you know, he he wants data centers built uh that are architecturally beautiful in the neocclassical style.
50:30
You have you seen those photos of uh the AWS data centers that back up onto uh Virginia housing developments?
50:38
So, it it's just like an idyllic few uh houses that just look like a normal neighborhood and then just behind you massive white school box.
50:48
>> Like, I'm not leaving.
50:49
>> Well, now you don't even get a box, you get a tent because Meta is now they gave up on their previous uh architectural design and now it's just a tent, which maybe is more uh more aesthetic.
50:58
If you're going to do a tent Meta, I think you should make it like a circus tent.
51:04
Get some red and white stripes going.
51:06
Get get some constant uh you know clown music going >> get the get the workers in the data center to be wearing clown >> economic >> IRL slop. >> Yeah, exactly.
51:17
But uh there were some interesting um architectural debates uh that I wanted to go through before we go to the next one.
51:23
Let me tell you about MongoDB.
51:24
Choose a database built for flexibility and scale with best-in-class embedding models and reankers.
51:29
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51:34
So imagine being as locked in as the Keyoto architecture community was in 1397.
51:43
I cannot believe this was built 700 years ago. 1600 or 600 years ago.
51:46
Uh explain what >> So there there's some lore here.
51:51
>> Give me the lore, Tyler. >> Okay.
51:52
So So yeah, 1397 when it was built.
51:55
Um I think in >> maybe 1950.
51:57
Um so it was like a temple, right?
52:00
So there's there's monks that lived there. >> Okay.
52:02
Um, and I think it was 1950 years or 600 years. Okay.
52:08
>> Um, the one was living there and he burned down the temple >> and then he tried to like commit suicide right outside it. >> Why? >> Um, >> what's wrong? >> I don't know.
52:17
>> He just wasn't locked in.
52:18
>> No one knows what happened.
52:18
But um, but then so this is actually it was rebuilt and there's a good um, >> but it was rebuilt in the same style.
52:24
>> So the architectural style is truly from 1397. >> Yes.
52:27
I mean there's I think there's some questions about how much gold was actually used in the original uh design. >> Yeah.
52:32
>> But um yeah gold should be pretty fire resistant.
52:35
You know gold probably high mel I mean it's like a very thin covering.
52:40
It's not >> well that's that's a skill issue.
52:41
They should have made it out of solid gold.
52:44
Then a single ember you're trying to light it trying to get it started and the monk is just ah I can't get this gold building to melt. >> Yeah.
52:50
But there's a good uh Yukio Mishima book about this. >> Oh really?
52:52
There's a whole book just about this story.
52:55
>> It's like a fictionalized story of the of the burning. Interesting. Very cool.
52:58
Uh, how would you rate this out of 10, Jordy?
53:00
Would you live in this Keyoto temple?
53:04
>> If it was an Aman, yes, >> if it was an Aman spa. >> I'm kidding.
53:08
Uh, I do I like the water feature. >> The water feature.
53:11
>> I really want to bring back Moes, right?
53:14
The obvious thing that's missing from modern architecture.
53:16
People talk about the material use, the form factor, but the obvious, the elephant in the room is a lack of moes in moderndeed uh architecture.
53:25
We need to bring back moes, gators in the moes, potentially sharks in the moes.
53:31
>> I feel like sharks are a little bit safer in the moat cuz you can hang out water line.
53:35
Whereas if there's gators in your moat and you're on the grass next to your moat.
53:40
>> Yeah, people have like koi koiish, you know, ponds, but why not just go size it up a little bit? Go for the shark pond. >> Shark pond. >> Shark pond. Imagine. Yeah, people go out.
53:50
They like the being relaxed and kind of like feeding the uh >> Yeah. feeding the the the koi.
53:53
But, uh, imagine just, you know, throwing like chicken breasts into the water for a shark.
53:59
How relaxing that would be if you needed just, you know, 15-minute break from Yeah.
54:03
from work uh before you get back to your email job.
54:06
>> Well, if you're building a fintech company, you need a moat. You need Plaid.
54:11
Plaid powers the app you use, the apps you use to spend, save, borrow, and invest.
54:16
Secure securely connecting bank accounts to move money, fight fraud, and improve lending.
54:21
Now with AI, uh what about the architecture at the Charles de Gaul airport in France?
54:25
It's a cross-section of a wing complete with uh spar box.
54:31
I didn't know what that uh means.
54:33
Uh need uh Billy uh founder of Regent Aircraft uh been on the show.
54:38
He says we need more buildings modeled after airplane parts.
54:42
Uh I've seen this uh as well in a house.
54:45
Someone took an airplane wing, a physical real airplane wing, and built it into a house.
54:50
It sort of served as the unifying ceiling.
54:53
What do you think about living in an airplane wing? Did you do that?
55:00
>> Uh, if it was obviously, but >> I've seen I feel like I saw a house at some point that was built around uh 747. >> Yes. Yes.
55:08
Uh, well, you also might be thinking of John Travolta's house, which just often had a 747 parked outside, which he flew himself, which is incredible.
55:18
Imagine being so into private aviation that you learn to fly massive jets, and then land them at your house with your own with your own >> I put it in the timeline, guys, if you can pull it up.
55:29
There's something called the 747 wing house, >> uh, in California. So, let's pull up this. Let's pull.
55:36
>> I think I've seen this on on a show called Grand Design on Netflix.
55:38
I believe I watched a little mini documentary or an episode of reality TV about this. Let's see.
55:47
>> Yeah, this is the exact thing I remember watched.
55:49
>> I don't come across views like that more than once in a lifetime.
55:51
It is somewhere that once seen it would never >> reveal it. Reveal it. >> Reveal it. >> Reveal it.
55:56
Enough of the we get cactus outside.
56:00
>> Running water or even roads is an endurance test. Only the wings. There we go. Look at this thing. Two wings. Interesting. >> Oh, very cool.
56:10
>> That looks really cool.
56:12
>> We don't know how to make >> That's really cool.
56:13
You know, you know what this is?
56:15
I Every time you watch one of these episodes, it's always just some couple that's just maniacally focused on making this particular thing and they interview them and it takes like years to create one of these episodes. Oh, interesting. It's blurred.
56:29
I wonder why that that is. Um, very very odd.
56:30
But, um, it's always someone has a vision and then they think it's going to be easy and then they spend a decade building it and they have to check in with them.
56:39
We checked in with them four years later and they were still in production and still getting permits.
56:43
Uh, but eventually it does get built and it looks beautiful when it does.
56:46
And >> you got to really love the 747 to uh to be in love with this house.
56:51
I think it looks very cool. I'm glad they did it.
56:54
>> I flew on a 747 for maybe the first time to Europe. It was beautiful. It was amazing. >> The first time?
57:00
Yeah, 747s are pretty rare.
57:02
Like uh except for long haul international flights, you >> Yeah, you're an America guy.
57:07
>> I'm an American guy, so I'm usually 737 Max always like or or or a bus or Airbus.
57:12
Um but uh the the 747 it's got a special it has a special aesthetic to it because of the the smooth bump.
57:20
You get the second story, but only for the first half of the plane.
57:24
It's I mean it's the plane that we use Air Force One for uh that we use for Air Force One.
57:28
Uh whereas the competitor, which I believe is the Airbus A380, doesn't have the same aesthetic beauty.
57:34
It just I it's two stories the entire way.
57:37
It's very efficient, but it just doesn't have the same clean line as the 747, which is just so so iconic.
57:45
Anyway, Charles de Gaulle airport. Go check it out. Also, check out Reream.
57:49
One live stream, 30 plus destinations.
57:51
If you want to multiream, go to reream. com.
57:56
Uh, so >> check in on 262 Fifth A.
57:57
Sage, uh, Hunter Bournestine says, "It's a crime. It should be raised. Shame on S L."
58:08
>> He really dug into who built this. >> Wow. Moscow based. He's going at him. >> 26 residences.
58:13
He calls it hideous architecture.
58:15
He says it takes away Madison Square Park's views of the Empire State Building. Um, I don't know. What is that at the top?
58:22
That that that top is just >> Don't Don't worry about the gold cube, John. Don't worry. Don't worry about it. >> Don't worry about it. >> Don't worry about it.
58:31
It's just it's a gold cube. >> Wow.
58:34
We found a rare post here. Zero likes. 166 views.
58:37
First, except for the fact that I disagree with it.
58:41
I think it's actually sort of a nice building.
58:42
I think we just we generally need more buildings.
58:45
>> I think it just feels harsh because of the contrast to the building next to it. >> True. True. But uh I don't know.
58:49
I I was we'll we'll read this in the mansion section, but there's there's some interesting dynamics about uh how HOAs enforce uh aesthetics in communities and whether or not that's good or not.
59:01
Um in other news, they 3D printed a Starbucks.
59:07
>> Starbucks has a new drive-thru in Texas, the coffee giants, first 3D printed store in the United States.
59:13
>> It's funny, they've really made it look like it's 3D printed. >> Look at this. Look at this.
59:16
So, I mean, I I've talked to one of the there's a YC company that does this technique.
59:20
I know it looks so sloppy and and there's a little bit of like up at the top, it actually looks like there's a little bit of uh imperfection and randomness that looks sort of aesthetic.
59:31
It looks like it's sort of designed in the way that a log cabin, not every log is going to be perfect, but then you get to the middle section, it's like the tube that was pumping it was just not working.
59:39
If you scroll over to the left and then down a little bit, just down like that is messy.
59:42
Um, so this the way it shows up, you basically get like a crane with a gantry that can move the uh the nozzle in an X and Y axis and it just pours cement in loops, circles again and again and again.
59:57
>> Okay, I need to know I need to know how quickly they built this and how much it cost because if this came in at at 80%.
1:00:04
>> They said it was it was two two G's. Two grand now. Can you imagine? It's so cheap.
1:00:09
>> Starbucks was down to their last two grand >> and they're just like 3D print it. Yeah, I don't know. I think >> around 1. 2 million.
1:00:17
>> Okay, that's >> what is a normal what is the average Starbucks cost?
1:00:20
>> Standalone building cost.
1:00:23
>> Tyler asks, "Who is the architect?"
1:00:23
And Pete says, "Slop GPT."
1:00:25
Uh, people are not uh happy.
1:00:29
The US >> says you wouldn't download a Starbucks.
1:00:35
>> Uh, US graphics company says, "I have the sudden urge to insult this in biblical terms."
1:00:39
Yeah, people are not not very happy with this.
1:00:42
Uh it does see does feel like a lowquality print.
1:00:46
Hopefully uh the 3D printing company, you know, this is just a step in the road and they become more uh more aesthetic, more precise, I think. >> Okay.
1:00:54
So the total uh investment range for a Starbucks location is 760,000 to 2. 2 million.
1:01:01
>> See, that's not >> it's kind of like right in the range there.
1:01:07
>> It's the median cost, but one of the more ugly ones.
1:01:09
Uh I yeah >> well whether you're long or you're short Starbucks you got to do it on public.
1:01:14
com investing for those who take it seriously stocks options bonds crypto treasuries and more with damn great customer service.
1:01:23
>> Matt Steik says they save 10 bucks. >> Good to see you Matt.
1:01:29
Uh the wrath of naan says is comparing some uh architecture in Oslo Norway.
1:01:37
>> Wait going going back to the 3D for a second.
1:01:38
Could they not have found a material to just place on that?
1:01:40
Like it seems like this could be a great way to build a like the core structure. >> Yeah.
1:01:47
>> Couldn't you just put some Yeah.
1:01:47
plaster over it and just >> It seems like they wanted to >> prove that it was really put it in your face.
1:01:56
But the whole point of technology is not the technology itself. It It's what it enables.
1:02:00
So if you can build a Starbucks for half the cost, you know, twice as fast, that's amazing.
1:02:04
But it doesn't mean it has to look like it was 3D printed.
1:02:08
you you can you can uh plaster and spackle over any sort of rough material and then you can print you can basically stamp like brick texture into it or some cinder block texture into it and it's fake but it looks like what it looks like.
1:02:20
Um they didn't do any of that here.
1:02:22
They they really let the like the loose tubes really lay out.
1:02:28
It looks just >> looks like it looks like it looks like >> looks like a gingerbread house.
1:02:33
>> It looks like a kid's um >> uh a kid's you know school project. Yes. Yes. Yes.
1:02:38
Today we're using uh >> And you got to be like, "Oh, nice. Nice work. Nice work."
1:02:43
>> Those like tongue depressors and uh chopsticks or uh >> popsicle sticks.
1:02:47
>> Popsicle sticks and glue and the and the four-year-old went a little crazy with the glue.
1:02:51
The Elmer's came out in full effect with this Starbucks.
1:02:56
>> Cool that this is actually happening. >> Yeah.
1:02:58
>> Because this has been uh promised. Yes. >> Uh for a while. Yes.
1:03:02
>> I just hope they they refine the the design.
1:03:04
At the same time, I've talked to a number of startup founders who uh operate in the >> Trey says you're going to also build a Starbucks out of mud, but probably >> you probably didn't. >> Oh, wow. Okay.
1:03:16
So, um I've talked to a number of uh startup founders working in trying to develop cheaper housing, cheaper building materials, and they've all said the last thing that you want to 3D print is just a flat all.
1:03:29
Like 3D printing is great when you're talking about Lucas Zinger's hypercar and you need some crazy structure that can't just be mil, but with a with uh like we're very very efficient at making flat planes.
1:03:45
You can just take a you can just take a metal cube and slice it.
1:03:47
You can take a a bunch of wood and build a grid.
1:03:52
Like we're pretty efficient at just building flat walls.
1:03:53
You don't actually need 3D printing for that.
1:03:55
You need 3D printing for building some sort of special structure.
1:03:59
There was a rocket company uh was it relativity?
1:04:00
I don't want to get it wrong, but there was a rocket company that was saying, "Hey, we're going to 3D print um rockets and it and it would go and solder one piece after another in a in a cylindrical turb."
1:04:12
The only problem is that we know how to make cylinders really really effectively metal.
1:04:16
>> Yeah, we can just bend metal.
1:04:16
And so that's what uh what Blue Origin and SpaceX do.
1:04:20
>> Rockwood Rocket says Lincoln Logs Starbucks.
1:04:23
>> Lincoln Starbucks >> soft serve building.
1:04:26
>> It does look like soft serve. That's right. It Starbucks.
1:04:27
Yeah, maybe it's an ad for the McFlurry.
1:04:29
Maybe the McFlurry machine always works there.
1:04:32
>> DG says you could do a Sandcastle Starbucks.
1:04:34
>> Sand Castle Starbucks might be fun.
1:04:36
>> That could go pretty hard.
1:04:37
>> Well, maybe they need to do a Sandcastle uh National Museum over in Oslo, Norway.
1:04:42
But before we dig into this, let me tell you about Apploving Profitable Advertising made easy with Axon. ai.
1:04:45
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1:04:50
Um so he's comparing two images. One is from 1882.
1:04:55
It's the National Gallery.
1:04:58
And in 2022, they launched the National Museum.
1:05:01
And he claims that modern architecture is meant to demoralize you.
1:05:06
And you can zoom in on the side by side here.
1:05:08
The 1880s building is uh very ornate with lots of gold and brick and details and structure and windows and all sorts of things.
1:05:16
And the 2022 building looks like a black cube uh from uh the Borg or Star Trek. Uh >> really rough. some cool stuff.
1:05:24
You can do cool things with flat materials.
1:05:27
I've always liked the design of the Walt Disney Concert Hall, but it looks like this sweeping winged structure.
1:05:33
It's very uh innovative and unique.
1:05:36
This is a little boring, guys.
1:05:39
But at the same time, Oslo, it's a gloomy place.
1:05:42
It sort of fits in, I guess. I don't know.
1:05:44
Maybe the architects were depressed.
1:05:46
They had seasonal affected disorder. Sad.
1:05:51
>> Anyway, Steve is sharing.
1:05:51
Apparently, this was a proposal from a Norwegian architecture firm for the Obama presidential library in Hawaii, but it failed. >> Okay.
1:06:01
So, the Norwegians got it. Norwegians. Yeah.
1:06:03
Sometimes it's the flat black cube.
1:06:05
It's interesting because like the critique of the new Obama presidential library is that it's too Norwegian.
1:06:10
And it turns out he just went with the wrong Norwegians, I suppose, uh because uh they're sharing these uh sort of science science fiction looking renders.
1:06:19
These look beautiful with a wonderful water feature and this sweeping grass uh overlay that seems very cool.
1:06:26
Although it feels like you would be at risk of falling off the edge here.
1:06:30
They would have to put a railing of some sort.
1:06:31
Um but very very cool architectural designs and I would love to see more.
1:06:36
>> Uh pull up the Obama presidential library.
1:06:40
>> Does Trump get two presidential libraries, one for each term?
1:06:41
Has he already built one?
1:06:43
I know the plane's going there, right? Something like that.
1:06:47
Very >> uh I put I put the Obama one.
1:06:47
uh in the >> but if you're worried about a lack of gold in the presidential library architectural industry, I don't think you need to be worried for very long.
1:06:56
I think there will be a very ornate building coming in just a few years probably. And I'm sure the >> Yes.
1:07:04
So this is the this is what uh this is this was the winning uh bid. >> Yeah.
1:07:09
>> And they did this in power though, right?
1:07:12
>> This one is in Chicago.
1:07:13
>> This one's in Chicago. Okay. >> Not Hawaii. Yes.
1:07:14
Uh, and again, uh, maybe if they get a huge projector and put like a fireplace on the wall inside, it could be cozy.
1:07:22
>> But, uh, that doesn't look uh doesn't look crazy how tall >> it looks like a great place.
1:07:26
Um, potentially like the the the uh like a like if if the deep state felt like not super welcome in other buildings.
1:07:36
>> I want to see the aircraft that they're building inside there because that looks like a aircraft hanger for a UFO.
1:07:41
>> Yeah, >> it seems of alien origin.
1:07:42
Um well, Wrath of Naan is continuing to talk about uh architecture.
1:07:48
Uh he says, "Traditional Korean architecture with its visually rich harmonious patterns produces lower levels of visual stress than modern facads with repetitive patterns, hard lines, and high contrast materials, which are more likely to overload the visual system and contribute to discomfort, especially in dense urban areas.
1:08:11
There's some research that suggests that having variation in your architecture actually can reduce stress, which is fascinating.
1:08:20
Uh >> yeah, try to zoom in on this picture on the left if you click in because you can see the the one on the left.
1:08:25
It's it's way uh for something it just feels more organic or natural, right? >> Yeah.
1:08:31
And it's a pretty simple shift like >> and then if you go over to the right a little bit, >> it doesn't feel like they >> Okay, that looks like a prison on on the one side.
1:08:38
The left looks like, you know, they're gentrifying some area and on the right uh some part of like Mexico City and on the right it looks like a prison and it's only >> or a bank building in New York City.
1:08:48
But um yeah, it doesn't seem like it costs that much to create some variation and randomness in your architectural designs.
1:08:57
Maybe it's expensive, but um >> I want to see the new A16.
1:08:59
I think A16Z needs to build a like a massive gold uh super structure in the heart of San Francisco.
1:09:07
Just carve out uh you know the who knows what the fee structure is, but >> take half of it.
1:09:14
>> Take half of these and just build a mon a monolithic monument to >> Have you ever been to the uh Statue of Liberty?
1:09:24
>> I've never actually toured >> inside.
1:09:25
Uh, so there's a structure you can go inside of it and walk up the stairs and whatnot.
1:09:30
You could put offices in that.
1:09:31
You could build you could build a statue and then put your office inside the statue. That's thinking. >> I like that.
1:09:39
>> I think we should uh kind of look back to um Charlie Munger's design for the UCSB. >> Yeah. Dorms. Yeah. >> Dormzilla.
1:09:47
>> He just wanted Dormzilla.
1:09:49
>> He just wanted he wanted everyone to lock in and he was he was killed for it. It was ridiculous.
1:09:55
He was >> uh pull pull this up.
1:09:56
Uh University of California abandons plans to build windowless dorm the Munger Hall.
1:10:03
>> Uh he just wanted you to lock in.
1:10:03
But pull up this article.
1:10:05
You can see the design and just how many just how many rooms in this place are windowless?
1:10:10
It is uh very very powerful.
1:10:12
So on the outside it looks like >> it looks uh uh I think he just knew that uh people were only going to have a few by the time this was built.
1:10:23
people would only have a few years to escape the the permanent underclass and uh windows would uh distract people.
1:10:32
>> Um if you scroll down you can see the actual design.
1:10:35
>> Yeah, >> that is a there's a lot of >> it's a lot of windowless things.
1:10:39
Maybe he was just super pilled on VR at the time.
1:10:42
He was like everyone's going to be in the metaverse.
1:10:44
Everyone's going to be locked into their VR headsets.
1:10:45
Uh maybe >> Aqua says Munger was cooking.
1:10:48
Yeah, we we we should have let him cook. >> Yeah, we support him.
1:10:51
Um anyway, uh Gusto, the unified platform for payroll, benefits, and HR built to evolve its modern modern small and mediumsiz businesses.
1:11:03
Uh yeah, I mean the the the funny thing with trying to do that at UCSB is like the most popular freshman dorms at UCSB are actually like in an old like hotel.
1:11:12
So it's these two towers that like have these like incredible like 360 views.
1:11:17
Not 360, but like the mountains and the ocean.
1:11:20
And then you have like this huge like Olympic swimming pool.
1:11:23
So it actually feels like you're just staying >> at like a at like a Hilton or something like that.
1:11:28
So to go from that to windowless is uh just a little bit rough. >> Yeah.
1:11:34
Uh well underrated strategy buy a compound with your friend. Do you see this?
1:11:41
Former casino mogul Steve Wyn and financier Thomas Peter uh set a record when they bought a 4 and a half acre compound in 2024.
1:11:51
Um I I can't seem to add this to the list, but um it's it's in the Wall Street Journal today.
1:11:59
It's on the cover of the Mansion section.
1:12:01
Uh it's it's comparing Aspen to Palm Beach. Uh but it's very funny.
1:12:06
And it says uh five years ago, uh $20 million home sales in Aspen were rare, happening no more than a handful times in a year.
1:12:14
Uh an influx of the of uber wealthy buyers has now upended that norm, handing the affluent ski area, 34 deals above 20 million last year, up 161% from 2024.
1:12:29
Year-over-year growth almost tripling uh in that category.
1:12:31
Uh the median single family home sale price hit 13.
1:12:34
95 million during 2025's third quarter compared to 9.
1:12:41
97 million in Palm Beach, Florida.
1:12:43
Raising the question, has Aspen eclipsed Palm Beach as one of the priciest markets in the country.
1:12:48
Um long known as as playgrounds for the rich and famous, one sunny, one snowy, Aspen and Palm Beach are increasingly two sides of the same coin when it comes to luxury real estate.
1:13:01
Despite 2,000 miles between them, each is home to dozens of billionaires.
1:13:07
Restaurants like Sant Ambuse and boutiques like Brunell Cuchinelli have outposts in both local.
1:13:15
Some of the wealthiest people have property in both places, too.
1:13:16
People run in packs and they and they run to the same destinations, said Palm Beach real estate agent Dana Cotch.
1:13:24
Uh, the meteoric rise of Aspen's ultra luxury market has made comparisons between the markets unavoidable.
1:13:32
Both Palm Beach and Aspen saw deal volume and prices sore in 2020.
1:13:37
That's continued to be driven by strong financial markets.
1:13:40
The 1enters are making money handoverfist, said Aspen real estate appraiser Randy Gold.
1:13:46
Real estate, he said, is a hard asset that they can enjoy.
1:13:48
Both are small markets that are protected geographically, adding to their exclusivity.
1:13:54
Palm Beach is an island and I got to turn to M9.
1:13:59
>> Aspen is basically an island in the mountain surrounded by public land.
1:14:03
>> Once you're here, it's very private.
1:14:05
Each has a limited supply of homes.
1:14:07
There are only so many beachfront properties in Palm Beach and or homes on Aspen's Red Mountain, which has fueled major price appreciation in both.
1:14:12
The numbers are mind-boggling, but the reality is that is these properties are unicorns.
1:14:17
When they come up for sale, you have buyers out there who will pay a premium. Okay.
1:14:22
So, uh, Steve Wyn and Thomas Peter, uh, they both ho they both own homes in the same area in Palm Beach and they're known to be friends and they're both GOP donors.
1:14:33
They're neighbors in Florida and apparently they became close enough to go in on a $ 108 million Aspen estate together.
1:14:40
And so, uh, Wyn is the founder of, uh, the, uh, the Win Resort and Casino and the Bellagio.
1:14:48
Thomas Peter is the founder, chairman, and largest hair shareholder of Interactive Brokers.
1:14:52
So, he's made a ton of money.
1:14:55
Uh, uh, Thomas is worth 35 billion.
1:14:58
Steve Win is maybe worth 3. 4 billion.
1:15:00
So, one order magnitude gap between them.
1:15:03
And you wonder if it's win being like, I got to bring in some extra firepower on here. Let's go 50/50, brother.
1:15:10
>> Well, here here's the thing. How?
1:15:10
Like this sounds great in theory and then it's New Year's and both families want to be in Aspen, >> but it is 22,000 square foot compound.
1:15:22
You might just say, "Hey, we're doing Christmas together, New Year's together." >> I know.
1:15:27
But there's probably only one basting families that want to go be in a cabin. >> Yeah.
1:15:32
>> Oh, it's it's it's a tall order.
1:15:32
It's crazy to be like, "Oh, yeah.
1:15:34
Like, uh, bro, you're only little bro, you're only worth 3. 4 billion. Hit the couch. I I got the master. You got the couch.
1:15:43
Oh, you only put in 50 million into this compound.
1:15:46
But, uh, this is where it gets funny.
1:15:47
So, um, no one there's no reporting on like why they decided to buy this together, but uh, we have a clue because they they uh, the buyer is actually an LLC that they set up.
1:15:58
And the name of that LLC is Buddies Aspen. They're just buddies. We're Aspen buddies.
1:16:06
We're a couple of Aspen buddies.
1:16:07
And we went in on it together.
1:16:10
And so, uh, they bought a ma they bought an Aspen mansion together.
1:16:12
It's, uh, it's a very funny time.
1:16:14
Uh, the the other buddies who did not buy a mansion together are, of course, the Google co-founders who have both bought uh, property in Miami.
1:16:23
Uh, Larry Paige just spent 173 million on two Miami homes.
1:16:29
Some of them are very odd.
1:16:29
We'll we'll go into these.
1:16:31
First, let me tell you about Finn.
1:16:32
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1:16:38
So, Google co-founder Larry Page has bought two massive Miami estates for a combined $173 million.
1:16:46
According to people familiar with the situation, the deals come as Paige and other Silicon Valley moguls descend on Miami in the face of California's proposed tax on billionaires.
1:16:53
Delian called it just a little bit too early, but the move is finally happening.
1:16:59
Paige paid $101 million in December to buy one of the properties, a waterfront compound in Coconut Grove that had long been the home of the late restaurant tour Jonathan Lewis.
1:17:09
He then purchased a nearby Coconut Grove property for 71.
1:17:11
9 million from Aerys Sloan Landon Lindaman Barnett and her husband Roger Barnett.
1:17:19
>> Okay, let's pull up uh there was some uh interest in one of these homes that Larry bought. We can pull it up.
1:17:23
I put it at the bottom of the timeline. >> Yes.
1:17:26
Uh but uh one of the homes that uh that he purchased looks looks fantastic.
1:17:33
Looks like this jungle oasis.
1:17:33
And then you zoom in a little bit. >> Do the CSI enhance.
1:17:39
>> Enhance it a little bit start a little odd. It's a little odd.
1:17:44
>> Uh haven't uh uh it's not. It's just a sculpture. We can >> Let's see.
1:17:50
This is going to be a jump scare if it's anything but this. >> Yep.
1:17:53
So this No, you have to show the show the zoomed out picture because >> scroll down.
1:17:57
Show the zoomed out photo. Oh, wait. No, it's not there. Uh oh.
1:18:00
Don't don't scroll through too much.
1:18:00
We need to find the original photo.
1:18:04
>> Uh the the original photo is just >> Where did the original photo go?
1:18:07
Uh we'll find that and we'll tell you.
1:18:09
But if you but basically there's a there's a you know it's a stock it's a real estate photo.
1:18:16
It's a photo that was taken clearly the real estate agent hired before it was Larry's house.
1:18:21
>> Before it was Larry's house to be clear.
1:18:23
So this is the photo and then people started zooming in and you keep zooming in and you keep zooming in and you keep zooming in and you start seeing some very weird design and decor interior decorating decisions that uh tell a little bit of a weird story about whoever was here.
1:18:39
Usually these properties are staged before they are photographed. So >> who own choice?
1:18:46
>> Who owned it previously?
1:18:47
>> Also it's something that >> Tyler can you try to find out the the previous owner of this house? I don't know.
1:18:52
So, I mean, we we we we have we do have some uh Jonathan Lewis is one and Sloan Landaman Lindaman Barnett and her husband Roger Barnett are the others.
1:19:00
If this is Larry Page's new house, but I know Sergey also >> some guy named uh Jeffrey.
1:19:06
>> Oh, no, no, no, no, no.
1:19:06
Uh and they declined to comment.
1:19:11
Um, California's proposed ballot initiative would impose a one-time 5% tax on the assets of billionaires who would retroactively apply to those who were California residents as of January 1st, 2026.
1:19:20
Now, this proposal uh is not even on the ballot yet.
1:19:27
It's it's still being workshopped.
1:19:28
Uh, but uh many tech billionaires are not taking any chances and they're relocating as of January 1st or December 31st in many cases.
1:19:39
>> December 31st was really the day to send the press release.
1:19:41
It was it was pretty much every other day I'm showing property to a client from the San Francisco Bay area says de uh Dena Goldener of Douglas Elellman.
1:19:49
Every conversation I overhear they're talking about the wealth tax and how it's retroactive.
1:19:55
They're in a hurry and they're all looking at the same houses.
1:20:00
Uh several agents told the Wall Street Journal they couldn't talk about the deals because they'd signed non-disclosure agreements that could end their careers if broken.
1:20:05
Uh the former Lewis compound spans about 4 and a half acres on Biscane Bay in Coconut Grove, one of the city's most coveted neighborhoods.
1:20:14
Uh Lewis was the son of the late Peter B.
1:20:16
Lewis, one-time CEO of Progressive Insurance Company. What a great business.
1:20:20
Uh the property listed for 135 million in 2024, was most recently asking 115.
1:20:26
The estate has two primary residences.
1:20:29
One was designed for the Secretary of State William Jennings Bryan in the 1920s and Lewis built the other home for his father around 2002.
1:20:39
The other property purchased by the Barnetts for 45.
1:20:40
9 million in 2021 is less than a mile away.
1:20:43
Sloan is the daughter of billionaire George L.
1:20:48
Lindamman and Roger is the chief executive of health supplement maker Shakeley.
1:20:51
I don't know Shakeley actually.
1:20:53
Uh, the Barnett sold the San Francisco mansion to a billionaire Lo Lauren Powell Jobs, wife of the late Apple visionary Steve Jobs for around 70 million in 2024, setting a record for the California city.
1:21:05
The Barnett property wasn't on the market at the time of the deal, so little information is available.
1:21:10
Real estate data website property shark shows it was built around 2015 and spans 17,000 square feet with seven bedrooms.
1:21:16
Pa pa and Sergey Brin founded Google as Stanford students in 1998 and built it into the one of the world's most valuable companies were one of them.
1:21:24
Stepped back from active management in 2019 and maybe getting back in the arena during the AI boom.
1:21:29
Uh Paige is worth around $270 billion according to Bloomberg.
1:21:34
Uh in addition to his home in PaloAlto, he ob he obtained New Zealand residency in 2021.
1:21:42
Miami's ultra luxury market has skyrocketed in recent years. Uh in 20 25.
1:21:47
There were 19 sales above $50 million in Florida, compared with just 12 in New York and 10 in California.
1:21:53
Miami had four deals above hundred million last year.
1:21:55
Billionaire hedge fund hedge funer Ken Griffin paid 106 million for a company.
1:22:01
>> Miami really makes Southern California look cheap. >> It does.
1:22:06
>> Ask a Miami guy to watch him browse uh watch him browse Zillow. >> Yeah.
1:22:10
>> And they're like, "Wow, they're giving the houses away here."
1:22:12
>> Well, let me tell you about vibe. co Co.
1:22:14
where DTOC brands, B2B startups, and AI companies advertise on streaming TV, pick channels, target audiences, and measure sales just like on Meta.
1:22:21
Uh, and you know what else is surprisingly expensive? Nashville. I had no idea.
1:22:26
But there is a Nashville condo that quote where it's James Bond meets Lenny Kravitz.
1:22:36
And it just is for sale now for 33. 5 million.
1:22:39
So, looking to hang out with John Furantino out in Nashville, you got to pick this one up. It's 5,000 square feet.
1:22:48
>> Wait, doesn't John live in the Four Seasons? >> I think he might.
1:22:52
>> Not to dock, >> but if you want to get Volta from the source, you got to head to Nashville uh and hit uh John Fo on X with a DM.
1:22:58
Uh, in Nashville, where luxury home prices have skyrocketed in recent years, a penthouse at the Four Seasons Hotel and Private Residences is aiming for a record 33. 5 million asking price.
1:23:09
The condo unit is the city's most expensive home for sale.
1:23:14
The penthouse is also available.
1:23:17
You can rent it if you don't have 33 million to spare.
1:23:19
It's going to cost you $200,000 a month, and you got to commit to at least six months. But if you have 1.
1:23:26
2 2 mill burning a hole in your pocket.
1:23:28
You want to hang out in Nashville with one of the greatest idea guys to ever do it, John Furantino.
1:23:32
Uh maybe uh maybe >> just it's just funny.
1:23:36
I just realized that the guy selling this uh house is a buddy of mine. >> Oh, really?
1:23:42
>> Uh I actually bought my house through his office.
1:23:45
>> Jamie Parsons or >> This is uh Cortazo. >> Okay. Yeah.
1:23:48
Uh the newly completed Four Seasons in downtown Nashville near the Ascend Amphitheater. What? Ascend Amphitheater.
1:23:56
They're ascending out in Nashville. >> Whoa.
1:24:00
>> I I need >> Is that where you spend spent uh winter break? >> Yeah. >> Yeah.
1:24:04
The Ascend Amphitheater just looks maxing.
1:24:06
Uh John has been looking good recently.
1:24:08
He must have been spending some time there.
1:24:10
Uh it's a few minutes away walk away from Broadway and thorough a thoroughare famous for its bars and live country music.
1:24:16
About two miles away from Taylor Swift's longtime home in the city.
1:24:20
The penthouse spans roughly 5,000 square feet with three bedrooms and a balcony lined with Florida ceiling windows.
1:24:26
The unit has expansive views of the city and Cumberland River.
1:24:29
Uh Chris Cortazo, a Malibu, California real estate agent, bought the penthouse for 12 million in 2022 when it was just a shell.
1:24:37
There were no walls kitchen.
1:24:39
He said there was nothing there.
1:24:40
He spent two years building out the unit in an aesthetic he calls James Bond meets Lenny Kravitz, anchored by a circular floating fireplace. Wow. Floating fireplace. That's cool.
1:24:52
Um, the residence h the residence has about a million dollars in smart home technology.
1:24:57
He lives full-time in Malibu, but began visiting Nashville around 5 years ago, Cortazo did.
1:25:03
Uh, he also owns a roughly 150 acre farm outside the city, he said, and has spent uh only a few weekends at the penthouse since completing it earlier this year.
1:25:11
Cortazo is also listing the Malibu home of the late actress Shannon Doerty, a longtime friend of his.
1:25:15
Oh, I heard about this news.
1:25:18
uh that that property hit the market last year for 9.
1:25:22
45 million and has a listing price that has since been reduced to 8. 75 million.
1:25:26
Uh Nashville's luxury real estate market has surged over the past six years according to Parsons.
1:25:29
Uh while only one home traded for over 10 million in Nashville, Krueger said that she believes the figure uh almost hit 20 in 2025.
1:25:38
If Cortazo if Cortazo's home sells at or near its record asking price, it will set a record for Nashville.
1:25:44
Um, the current record is held by a suburban home on 50 acres that sold for 32 million in 2024.
1:25:51
Uh, so if you're looking to head over to Nashville, pick up this penthouse.
1:25:55
Um, I I've never lived in a in a in a penthouse, a condo like this.
1:26:01
I I would I >> then you've never lived >> I've never lived but personally I would be going for the 50 acre suburban home.
1:26:07
I I I too many dogs, too many animals around.
1:26:10
I want I want I want the steeds around.
1:26:12
I want to be able to ride the horses.
1:26:14
Uh, but for the right person in the right time of their life, I'm sure this is a fantastic pick pickup.
1:26:20
>> Uh, in other news, >> Phantom Cash, fund your wallet without exchanges or middlemen and spend with the Phantom Card.
1:26:29
>> Uh, France will delay the G7 summit to avoid conflict with mixed martial arts. >> Really?
1:26:37
>> On on Donald Trump's birthday? >> Yeah.
1:26:38
So, uh, they're going to delay group of seven summit to avoid a conflict with the mixed martial arts event planned at the White House on Donald Trump's birthday.
1:26:46
>> Do you think they have a group chat for the G7 >> and it was like, "Hey, can we get together? We got to get together.
1:26:51
>> We got to get together.
1:26:52
>> We got to do a summit. Let's do a summit.
1:26:55
>> G7 leaders, >> let let's do it."
1:26:57
And and and Trump's in there just being like, "Dude, I'm I'm I I already told Dana I'm in I'm I'm I'm I'm watching UFC that night.
1:27:03
It's happening in my house.
1:27:05
It's happening at my house.
1:27:06
It's going to be really awkward if I'm not there. >> I got to be there.
1:27:09
Let's plan another another summit, another time.
1:27:13
>> Uh this is this is interesting.
1:27:13
Um >> uh >> usually there's some big news that comes out of G7 summits.
1:27:18
Usually there's uh you know all the leaders get together, they're striking deals, they're talking to each other, there's something going on. >> Yeah.
1:27:24
So definitely worth still doing worth delaying but worth worth doing.
1:27:29
>> Well, speaking of Trump, uh Lip Bhutan is in his good graces.
1:27:31
Donald Trump posted his new best friend on Truth Social.
1:27:35
He says, "I just finished a great meeting with the very successful Intel CEO Lip Bhutan LBT as he's called for those who know.
1:27:43
Intel just launched the first sub 2 nanometer CPU processor designed, built, and packaged right here in the US of A.
1:27:51
The United States government is proud to be a shareholder in Intel and has already made through its USA ownership position tens of billions of dollars for the American people in just four months.
1:28:01
We made a great deal and so did Intel.
1:28:03
While our country is slipping into >> Oh yeah, by the end of the year I'm going to have a down.
1:28:10
Our country is determined to bring leading edge chip manufacturing back to America and that is exactly what is happening.
1:28:16
Uh and people are asking for particular uh financial advice which we won't which we will not give.
1:28:24
Um but Liputon also sat down with Howard Lutnik.
1:28:27
Uh Howard says uh just four months after the United States invested Intel, that investment is already delivering tens of billions of value to the United to the United States people.
1:28:38
That momentum continues with Intel's new 1.
1:28:40
8 nanometer processor and a major step towards bringing semiconductor manufacturing back home.
1:28:48
Let's play this clip from Lip Butan talking to Howard Lutnik.
1:28:50
I have the pleasure today of welcoming Lip Buu and he's come to the Department of Commerce to update us on how Intel has been doing since we made our historic investment in the company.
1:29:04
>> Oh, thank you so much.
1:29:04
I'm so delighted to come over here to see you.
1:29:06
We double the market cap is over 200 billion valuations and also very exciting we announced our products first time on the 18A production in series 3 uh processor with multiple of our customer in US globally and using that is the most advanced pro design and also using our most advanced eating productions >> right so for the United States we We love the fact that Intel is doing leading edge work in America. Right? 18A means 1. 8 nanometer. 14A is 1. 4 nm.
1:29:48
Think of how incredibly sophisticated and tiny that is.
1:29:53
And then packaging is you take this little little little little teeny thing and how you put layers and layers of sophisticated uh circuitry on top of it and you do it with you know just the most amazing technology doing that >> in America leading in America by a US company.
1:30:14
>> Get yourself an investor that talks about your company. So we're proud of you. >> This is >> okay.
1:30:19
We're rooting for you and we need you to be successful for a man. >> Thank you so much.
1:30:23
>> This is the new startup launch video.
1:30:24
You do a deal, you raise some money from a VC and you got to put out a music a video like that.
1:30:29
You guys sitting down on the couch next to each other with succession music and they explain your business. Shake your hand.
1:30:34
And uh >> there's so many new formats. >> Yeah, new format. Unexplored. Unexplored. Clone that one.
1:30:40
Call video production team. Get it done.
1:30:43
Uh, in some other news, US oil executive is commenting on Venezuela.
1:30:48
No one wants to go in there when a random effing tweet can change the entire foreign policy of the country.
1:30:55
And uh, deep dish and joyous lmao.
1:30:58
Uh, it is it is remarkable how online this uh, this administration is.
1:31:04
You saw during the during, you know, people have been celebrating the death of X and yet during the invasion on in one of the images of the of the war room on in the background on the TV was just axe.
1:31:18
com search for Venezuela.
1:31:19
Let's see what people are saying.
1:31:21
Uh, remarkable times we've >> next time they'll probably have uh Reggie's monitoring the situation dashboard that they should also be using railway.
1:31:30
Railway simplifies software development.
1:31:33
Web apps, servers, and databases run in one place with scaling, monitoring, and security built in.
1:31:36
Um, so, uh, I posted a, uh, piece about the Apple card and how it's changing from Goldman Sachs to Jamie Diamonds, JP Morgan, of course.
1:31:50
Um, and, uh, a software architect for Goldman Sachs's consumer bank, um, Matt Low Low uh, chimed in and says, "Good article.
1:31:58
I think the main reason it didn't work with Goldman Sachs is that it lost its high priority in a double whammy.
1:32:03
CEO David Solomon used a lot of his power to evolve the partnership culture to an exec first modern corporation. That's interesting.
1:32:12
Uh through that reorg speculate he had less political flexibility to defend Marcus from other partners who didn't want to wait for the consumer bank to scale up.
1:32:19
Marcus even grew through leadership turnover during the pandemic and made a huge acquisition of Green Sky.
1:32:25
it seemed to fizzle out and lost uh the continued ex exclus uh executive sponsorship it needed to keep going while reporting to an asset and wealth management division division.
1:32:34
Uh note in a couple in last uh in last in a in last couple weeks podcast with capital Solomon said the main reason for the windown was regulatory.
1:32:44
Uh interesting so just some extra context around the Apple card.
1:32:47
Uh well let me tell you about graphite and then we'll bring in our first guest of the show code review for the age of AI.
1:32:54
Graphite helps teams on GitHub ship higher quality software faster.
1:32:58
And without any further delay, let's bring in Jeremy from Sammy Analysis. How are you doing? Good to see you again. Second time on the show.
1:33:08
So excited to have you here. Happy New Year. >> Happy New Year. >> Happy New Year. How are you?
1:33:12
Are you uh are you shocked to see that uh the the G7 that's supposed to happen in France?
1:33:18
Aren't you in France right now?
1:33:20
>> I'm in France right now. Yeah.
1:33:20
Well, you're gonna have to wait for the summit because UFC takes priority in America apparently.
1:33:26
I don't know if you saw that. >> Yeah.
1:33:29
>> Anyway, um congratulations on the new article.
1:33:31
Uh I would love for you to uh set the table for us and explain sort of what were the questions that you were trying to answer.
1:33:38
What was the overall thesis that you came into this particular article?
1:33:42
How AI labs are solving the power crisis.
1:33:45
Uh and then I have a whole bunch of questions that I want to dig into. >> Yeah.
1:33:50
Look, the question that we keep receiving every day, every hour it seems, is how are we going to power the AI race?
1:33:56
Yeah, >> you know, uh is the grid able to handle all of that?
1:34:00
And look, last time I came in, I think I said, hey, there's like over half a terowatt of data requests, uh in all the US grid, an insane amount of requests.
1:34:09
And we we talk about sort of prisoners dilemma where because everyone is trying to find power then it creates sort of a vicious cycle of everyone starts being more speculative and putting requests everywhere and so basically the grid is overwhelmed. >> Yeah.
1:34:23
>> People cannot find energy.
1:34:23
Um and so that's why you're seeing the rise of on-site gas.
1:34:26
Uh which is something that a lot of people have been talking about.
1:34:30
But from our research, we just haven't found sort of any good any good way to understand what are people actually doing. What are the challenges?
1:34:35
What are the systems that people are actually deploying? Uh what's the benefits?
1:34:40
throughout the trade-offs and how to understand how to make sense of all of these new entrance.
1:34:43
Yeah, >> because one of the key highlights is okay, everyone talks about Ger Nova, everyone talks about Simmons energy, but we count actually 12 manufacturers that have secured orders of over 400 megawatts for US data centers on S gas power.
1:34:56
There's way more people in the pipeline, but essentially we wanted we wanted to to show people how are the labs solving the power crisis.
1:35:02
Uh talk about to some extent XAI was a bit of a pioneer because obviously it did that before everyone. Yeah.
1:35:10
>> And how are the other players following suit and uh actually solving this issue? >> Yeah.
1:35:14
Let's let's stay with that point about power requests from AI companies.
1:35:20
Uh that's expanded significantly. Correct. Isn't it?
1:35:22
It's over 10 terowatts now or something like that.
1:35:27
Everyone's spamming with these requests, isn't it? It's an insane figure.
1:35:29
Uh is that roughly correct or >> I don't know about 10 terowatts. >> Not it's over one.
1:35:37
>> Over a ter roughly a terowatt. roughly a terab.
1:35:39
>> Uh it's always complicated to know exactly. Yeah.
1:35:41
Um but roughly a terowatt.
1:35:43
Uh >> and what are the mechanics of a of a of a request for power?
1:35:46
Is that going to uh to uh governmentrun organizations?
1:35:50
Is that a permitting process?
1:35:53
Like what is the anatomy of actually a making a request for power if you're an AI company? >> Sure.
1:36:01
So typically you send a request to a trans transmission provider. Okay.
1:36:03
Uh, so say American Electric Power, the largest in the US. You send them a request. I want Power in Ohio. Yeah.
1:36:10
Um, you have to fill whatever some kind of form.
1:36:14
You tell them what you want by when you want it.
1:36:16
Um, and then if sort of that first phase moves through, um, you have to go through a system level study. >> Yeah. >> Okay.
1:36:23
And the reason we have to do that and that process, the reason it takes time is because the way the grid works is demand and supply have to be always perfectly synchronized.
1:36:31
And if they fall out of sick uh because there's too much supply or too much demand, then there's basically a blackout for everyone.
1:36:39
That's the worst case scenario to be clear. Uh but it's possible. It has happened.
1:36:42
It happened in Spain about a year ago >> um because of an issue on the supply side.
1:36:46
And so the implication is that if you want to interconnect a 1 gawatt data center, you're going to have a plenty of system level studies that are going to slow down the process.
1:36:55
>> Um and this is where you get into that sort of vicious cycle because everyone is sort of putting requests because they know it's going to take a while. >> Yeah.
1:37:01
Also, >> isn't there isn't there some people putting in requests just at from a speculation standpoint?
1:37:07
They're just like, "Hey, I know that if I get access to the power, I can resell it to somebody else, and if I just kind of lock into uh you know, you know, uh one of these uh >> deals, >> grids, basically giving me a contract, then I can go and flip it."
1:37:21
Is that is that happening?
1:37:24
>> Everyone wants me these days or gigawatts. >> Yeah.
1:37:27
>> So, you you try what you can to get some.
1:37:29
Um, and if you if you're for example, say you're based in Ohio, you typically operate in Columbus, Ohio.
1:37:34
Uh, then suddenly you tell your utility, hey, I I want another 500 megawatt. And they respond.
1:37:42
Actually, I've had like 10 other people ask me this.
1:37:43
So, you're going to be in the queue >> and there's 10 other requests I have to evaluate before I get to yours.
1:37:49
>> Is there but this is why some of the Bitcoin miners have done actually very surprisingly well in just sort of like pivoting to AI because they had they had the the pre-existing power deals in place, right?
1:38:02
>> Yeah, it's not in the queue.
1:38:02
It already exists because the queue is just an evaluation.
1:38:06
But then once you have the once you have everything approved, you have to build a substation.
1:38:09
You have to actually interconnect your data center to the grid and the crypto the Bitcoin miners, they already have the substation, they already have the transformers on site, they already have the energy flowing, the electrons are there.
1:38:20
Um, so for them, it's just about retrofitting and just leveraging the megawatts that they have.
1:38:23
Is there is there anything that uh I mean we were we were reviewing this uh this meta deal today and and they have uh someone on staff who's the director of global energy.
1:38:34
Is there anything that a team or one of these hyperscalers can do to move through the queue quicker?
1:38:40
I mean I imagine they can't just like overpay or bribe or it would otherwise just be an auction process.
1:38:46
But is there is it sort of a battle of the for is that actually happening?
1:38:51
Um I is there uh is it just a battle of a forums?
1:38:54
Is it the regulatory team that you have on site?
1:38:55
Is it is it different uh like scientists that are driving the work or is it just all the best legal team wins?
1:39:02
Like what is the anatomy of actually winning allocation in power?
1:39:09
>> So the first thing we have to flag is there there are many different transmission providers uh in the US.
1:39:11
So many different bodies that work differently. >> Okay.
1:39:16
>> But there's a few ways you can do.
1:39:16
So first of all, if you're a sophisticated end user, what you're going to do is analyze the grid um and try to understand where uh where does it make sense to have power from a I guess grid congestion perspective.
1:39:27
Analyzing the network, you realize, okay, this area probably should have free power.
1:39:32
So I'm going to talk to my utility and if you if you want to if you want to have a better chance of being ahead of others, then at least you have identified a specific spot that is likely to have available power.
1:39:44
>> Now, typically relationships obviously matter.
1:39:45
uh if you've been in the business for 10 years or whatever and you're good friends with uh you know sea level executives, you can perhaps move up the grid just because just because of trust.
1:39:54
It's it's it's not about necessarily bribing or something like that.
1:39:57
It's more about you have a whole lot of new entrance.
1:39:59
You have a whole lot of new entrance that don't have a lot of experience and then you have this other guy that maybe has been doing it for 10 years and has a lot of experience and success.
1:40:07
So obviously for the utility it's easier to trust the guy that has the track record and has the existing relationship.
1:40:12
So that's that's that that's one angle. Sure.
1:40:13
Um yeah >> uh I'm interested to know about your process to understand how much power each player is actually accumulating.
1:40:20
Uh I I've seen you know the semi- analysis watermarkked screenshots of data centers.
1:40:28
Is is satellite imagery actually that useful for understanding like the map of total data center capacity?
1:40:34
Are you looking at regulatory filings?
1:40:36
Are you looking at statements from the companies themselves?
1:40:38
from the companies themselves? like it feels like you're at least one or two clicks ahead of what the executives at these companies are publicly saying and you're act the purpose of semi analysis is to you know uh provide analysis and
1:40:54
data ahead of what's publicly available but what is the process for actually understanding Azure's compute capacity this year before anyone else does >> yeah sure thing so there's um there's different um to some extent lead times Um for us the the the way we do the the call it the short-term forecast. Shortterm being roughly next quarters
1:41:16
Shortterm being roughly next quarters extensive satellite imagery. We love satellites.
1:41:21
We pay a lot of money for satellites.
1:41:23
Every single blog these days you you see satellite pictures.
1:41:25
Um and it's pretty simple.
1:41:28
One thing is using historical imagery figuring out when did construction of specific building start.
1:41:34
>> Two is what's a typical time to build for an operator.
1:41:36
for an operator. Uh so you have to you have to get a sense of like you know um having reviewed many of their buildings how much how long do they typically take or uh sort of understanding the design patterns how maybe they can accelerate the build out to what extent >> um right and then if you know how how
1:41:53
long it takes and when started you can know when it's going to be operational then it's about the size it's also about if it's a large project how fast can you get it up to speed um because one thing is to build the shell and the other one is to build all the electrical the mechanical and obviously deliver sequentially data hold by data hold typically. So there's a bunch of things
1:42:08
So there's a bunch of things you can review. Uh we use all of it.
1:42:11
Satellites were big fans of course.
1:42:13
>> Um and like some of to us it's interesting because um we've been able to be very successful at predicting trends with hyperscalers by analyzing data because you have to think of it.
1:42:26
I'm I'm saying you can just use satellite imagery but you have to do it for hundreds of data centers.
1:42:29
Who has the time to do that way? We do. We're crazy. >> That's awesome.
1:42:35
But it worked out because if you think about it, Amazon, they accelerated growth, right, from 70% to 20% last quarter and a lot of people were surprised because people were saying no, they're losing AI.
1:42:44
Azure has accelerated, Google has accelerated and Amazon hasn't.
1:42:47
But actually, if you analyze data center construction, they've been accelerating like crazy on the construction side uh in the first quarter 2024.
1:42:54
In the fourth quarter 2024, takes a year for them to build.
1:42:58
Obviously, you see the acceleration fluid mechanically Q325, Q4 25. Uh that's one aspect.
1:43:03
The other one which is a bit more complicated is tracking the the leases.
1:43:06
Um and so sort of understanding where are the different hyperscalers leasing capacity from third party operators.
1:43:11
Uh the big guys are QTS you know digital realy Equinex and there's all the crypto miners that are basically doing the same thing.
1:43:17
And that's also something we track very closely.
1:43:20
Uh and it's complicated because some of that information isn't public.
1:43:23
But by triangulating many data points, you can actually get to the answer using only public data, which is what we do extensively.
1:43:28
And using permits, digging into filings and all of that is a huge part of the process as well to get to the answer. >> Yeah.
1:43:34
As I understand, >> how much how much uh is the are you guys benefiting from uh like actual AI tooling on the research side?
1:43:42
Like are you guys running like you know 20 agents in parallel that are you know, basically like looking at a lot of filing, trying to find them, monitoring them, etc.
1:43:53
>> Are you feeling an unlock? >> Yeah. Yeah.
1:43:56
So, we're using AI quite a bit.
1:43:58
Uh I think we can do more.
1:43:58
Uh I wish we could do more to some extent.
1:44:02
Obviously, it's bound by computer use.
1:44:04
Um there's some complications.
1:44:04
There's some portals for uh for per permit purposes, permit tracking purposes that we can automate.
1:44:11
But the problem is that if you think about there are so many states, so many counties, so many different things.
1:44:15
And some of them are fairly easy to use.
1:44:17
And so today's agents can actually automate the process.
1:44:20
Other ones are maybe more complicated, more archic, right?
1:44:22
Some of them you have a clean PDF.
1:44:24
Other ones it's like, you know, a scanner. It's written by hand.
1:44:28
There's a lot of difference when you're going to the the weeds of the permitting process uh in the US.
1:44:34
So we do automate quite a bit.
1:44:36
Uh what what we're starting to do this is pretty interesting project that we have on the data center side is a vision model where you can actually uh based on satellite imagery uh u detect real time sort of what's the status of construction and understand sort of the inflections that you see um as well um on the in on the planet. >> Yeah.
1:44:54
>> Yeah. Z uh zooming out it feels like uh I think you quoted it something like half a gigawatt of uh new data center capacity was being added for a period of year sort of linear growth uh and now we're seeing a break in the graph and
1:45:09
we're seeing exponential growth and I'm I'm wondering how you're thinking about there's always this question of like when will AI show up in the GDP statistics it's obviously a big business and there's a lot of revenue uh But we're but we're not seeing the 10% GDP growth just yet. Maybe that's coming. Uh Maybe that's coming.
1:45:26
Uh when are we >> seeing productivity growth?
1:45:28
I mean CNBC yesterday was trying to figure out why US economic productivity surged almost 5% highest in six years.
1:45:39
Maybe uh but I mean my question with regard to like overall US power generation uh are you expecting to see a meaningful acceleration a break in the graph there this year next year?
1:45:49
Uh or or is or is the data center overall energy picture still a small enough slice of the pie in terms of overall American energy production and consumption that uh we won't see it move the overall needle just yet?
1:46:07
Oh, it's already moving the needle.
1:46:07
It's just going to accelerate.
1:46:08
There's just one direction at least for the next call it two years.
1:46:12
Um, if you one thing you can do is a lot of the utilities are publicly traded.
1:46:16
So, you can go one by one.
1:46:17
Every single one of them, the only thing they're talking about these days is data centers is how much load growth I have and how how and then it's about capacity constraints.
1:46:24
Can I deliver on that on that demand?
1:46:26
But all of them are seeing tremendous load growth.
1:46:28
And if you think about the leading indicators on the data center side, so for us, we use two things on the if you think about self build.
1:46:35
So the data centers that are built and operated by hypers skaters construction starts are exploding.
1:46:38
So they're all massively accelerating.
1:46:40
They have accelerated tremendously versus 2022 and 23. So 24 was a big year. 25 insane.
1:46:47
Um so this is a leading indicator with regards to what's going to happen in 26 for capex for revenue and obviously for load growth because these days it's all correlated.
1:46:55
Um on the on the leasing side, same thing.
1:46:58
If you think about uh how much data center commitments um are the hyperscalers doing these days, it's also just up and to the right.
1:47:06
Uh 2025 has been an insane year uh for the leasing market.
1:47:09
And so everything points to 26 27 just uh accelerating.
1:47:14
Um and then if if you think about GDP growth because I think it's an interesting topic, there's uh two two things you can talk about.
1:47:19
One is on the infrastructure side and the other one is on the productivity side.
1:47:23
M >> um on on the infrastructure side, we you're already seeing it, but I think it's pretty easy to look at statistics.
1:47:30
You can look at data center contribution to GDP.
1:47:32
There's a bunch of stuff um from some of the agencies.
1:47:34
You can look at um computer investments.
1:47:37
There's a specific GDP road that tells you all of that is is exploding.
1:47:42
Um roughly speaking, a guesstimate is over 50% of GDP growth today's AI infrastructure. Yeah.
1:47:48
>> Which is kind of insane if you think about it, right?
1:47:51
And and you can do some monkey math as well, right?
1:47:53
You see Nvidia's revenue.
1:47:55
Uh what is it these days like 250 billion annualized or or more.
1:48:00
Um if you do the math, right, a lot of that is going to the US.
1:48:03
Now there's obviously it's complicated because there's imports and things like that you have to deduce, but you know, US GDP is over 40 trillion.
1:48:12
>> Uh right, 1% is 300 billion.
1:48:15
Easily year-over-year additions, AI for investment is over 300 billion. Sure. Right.
1:48:20
Power plants, data centers, chips and all that. >> Yeah.
1:48:23
And then that should drive significant GDP growth.
1:48:24
That's >> and then the second phase of this is uh on the productivity side.
1:48:27
Obviously you have to see to some extent you you you would expect to see the people that are providing that productivity to to be beneficiaries.
1:48:35
Um and so this is where it's important to track what are the AI labs doing, what are the startups doing, uh which is something we've been tracking pretty closely recently at analysis.
1:48:44
And so if you look at the AI labs, yes, they're all accelerating pretty pretty fast as well on the revenue side.
1:48:49
Like you see, you saw Open AI, tripling revenue, Antropic 10X and so on and so forth.
1:48:54
>> Can you uh take me through the latest bottleneck in gas turbines?
1:48:57
We had Blake Schaw from Boom on the show and it feels like he's expanding his business to build turbines.
1:49:04
And I'm interested in that specifically because uh we hear about nuclear power plants coming online.
1:49:12
That's obviously a very heavy regulatory burden.
1:49:14
Also, supersonic flight feels like incredible regulatory burden, but how difficult is it to just manufacture a new turbine or more of the same design, bring them online, actually ramp up capacity of natural gas turbines.
1:49:32
>> So, so typically to develop a new turbine, you're talking about seven to 10 years R&D process.
1:49:36
>> Um, so it's pretty fascinating because you have a few a few new entrance that are hitting the market today. Yeah. Uh a big one is Dan.
1:49:42
Uh Dan is providing roughly 2 megawatt of turbines to XAI.
1:49:47
>> Uh Dan, Korean giants on the nuclear side.
1:49:50
Um they've been developing their turbine for over 10 years.
1:49:52
Um and it's like, you know, perfect timing.
1:49:54
They have a >> Yeah, what amazing timing. That's great. >> That's pretty lucky.
1:50:00
Pro Energy is another interesting example also seven year R&D um R&D program and late 23 finally they got all the approvals.
1:50:08
finally they got all the approvals. uh it's just very a very uh complex technology a lot of very high precision materials so ramping up the manufacturing side is complicated another thing to to think about and uh that's the difference we have with folks like bloom is um what is the like how long can you make your investment when you build a new factory for gas turbines
1:50:25
or some of these systems and this is an interesting thing to analyze because some for some folks it's actually easier to build new capacity because their payback period is much higher and because their revenue per megawatt is higher and because the their cost is also higher just because the prices are going up because AI labs are willing to pay more for the turbines. >> So, so yes, but I'm more thinking about
1:50:44
>> So, so yes, but I'm more thinking about comparing different technologies.
1:50:46
Like if you think about Bloom Energy, the cost to buy fuel cells is is very high is much higher than buying a turbine. >> Sure.
1:50:54
>> But the flip side of this is that the payback period because the revenue is so high per megawatt, the payback period of building a factory is actually much shorter.
1:51:01
So for Bloom's perspective, they take less financial risk if they expand capacity and they manufacture more.
1:51:06
Yeah, >> pretty good position.
1:51:08
>> It makes a lot of sense.
1:51:09
>> How did you react to the meta Oaklo news from the this morning?
1:51:15
>> Well, I mean it's um I think all of the all of the all of these folks are um are looking for energy that is uh you know cheap, stable, are looking for ways to ensure their the continuity of their supply.
1:51:29
>> Um and it just makes sense for all of the hypers skaters to to to work with the nuclear nuclear companies.
1:51:32
It's not a surprise because everyone has done it already, right?
1:51:36
You saw Google as well with Chyros.
1:51:38
You saw a bunch of these deals already switched with Oak as well about a year ago.
1:51:42
So, not too surprised about this one. >> Yeah.
1:51:46
>> How much does the nuclear uh fision or even the fusion stuff got Google's uh partnered with Commonwealth Fusion Systems on a few things.
1:51:53
Um how much does that play into uh the analysis that you do when you're looking out six quarters?
1:52:00
Because when we saw the date 2029, 2032, 2035, our eyes kind of roll back in the in the bottom in the back of our head and say, well, that feels post singularity, so what's the point?
1:52:11
Probably important at some point, but uh certainly less of a less of a critical decision in the horse race of, you know, which lab will get power next month to train the next model that we're all going to be focused on. >> Yeah, exactly.
1:52:27
That's why if you read the report that we we wrote, it's all about gas because if you think about the next few quarters, it's gas.
1:52:32
There's just no other solution.
1:52:33
Nuclear is going to take a few years.
1:52:35
Solar and batter is not ready yet.
1:52:37
All of these other alternatives, I think they all have good potential and I'm sure we're going to see a lot of different solutions in 5 10 years, but today it's just gas.
1:52:46
>> So, so you're modeling energy. It's mostly gas.
1:52:48
Um uh any plans to mo uh to to model or uh or analyze or model water?
1:52:57
Is that important at all? >> Oh, interesting. Yeah.
1:53:00
Big topic these days, right? Yeah.
1:53:03
>> Um uh our view generally speaking is that water is not that big of a problem because in the data center space you have this trade-off between energy and water. Yeah.
1:53:12
Um and so you can actually enclose loop systems that consume pretty much no water in some cases zero water.
1:53:21
There is some water required uh just to to build the initial tank and the initial loop. Yeah.
1:53:26
>> But it's closed loop so you don't need water.
1:53:28
So what's the issue, right? >> Yeah. Exactly. Yeah.
1:53:30
It is it is a funny retort to anyone who's worried about the water uh the the AI water usage.
1:53:34
Just if it's important, why doesn't semi analysis talk about it ever?
1:53:39
Why are people not trading the water stocks if it's if it's important?
1:53:43
Um I am interested in the >> we might talk about it soon.
1:53:48
>> Yeah, I mean I'm sure there's some sort of angle, but uh on on the on the question of water usage, it does seem like uh Meta is moving from an air cooled system to a water cooled system.
1:53:57
I think I have that right.
1:53:57
They moved away from the H design of their data center.
1:54:01
Um can you tell me more about why the Hshaped data center was not suitable for water cooling?
1:54:07
It felt like a very modern building.
1:54:10
Uh why was it impossible to retrofit that?
1:54:13
Why did they have to go with an entirely new design? >> Yeah.
1:54:19
So the the the thing about the edge design above everything is it was really designed by Meta for uh leading cost efficiency.
1:54:27
>> And so typically the the ratio people use the PE which tells you what's the energy efficiency of a given facility.
1:54:32
Meta had the world's best uh the world's most efficient facilities.
1:54:34
most efficient facilities. um the the energy required to cool the data center was extremely low >> and that's because it had a fairly complex structure three stories um >> okay >> the drawback of that is is that the time to build a facility was about two years so that doesn't work in the AI era we're
1:54:49
talking about month right it's 122 days for XAI so you need to go faster so that's one of the main issues now the other one is regards to cooling um the the way that we're cooling this specific data ser is like it's I call it an air-to-air system you could you could simplify it and say They open the window. That's basically how they
1:55:06
That's basically how they cultivate this. They open the window.
1:55:11
Obviously, they have a bunch of >> We tried opening the window.
1:55:14
>> You know, I I actually I actually toured George Hans's uh uh he has a a miniature data center, just a couple racks of GPUs that he trains for uh autonomous driving for self-driving cars that he builds.
1:55:25
And uh and his cooling, it really is just like a window unit that just flows air through the this particular room in his office.
1:55:32
And and he he's using air. a car with no AC once. >> Open the windows. >> Just open the window.
1:55:37
>> It's a time honored tradition, but sorry I cut you off. >> It works. It works.
1:55:40
It doesn't work that well if your your hot is liquid cooled. Yeah.
1:55:45
Obviously, if you have a cold plate that goes through the chip, then the question is how do you cool uh the fluid that you put into the cold plate to remove the heat from the chip?
1:55:52
Yeah, >> opening the window doesn't work that well.
1:55:56
You can do some kind of retrofit with liquid to RCDUs. It's expensive. It's not very efficient.
1:56:00
Uh so the best way to do is to have a dedicated fluid cooling system which involves building a whole dedicated piping infrastructure and all of that which is what meta did their new data center can handle seamlessly uh liquid cool chips whereas the old one uh it was much more complicated.
1:56:16
>> Do you have a view on um you said uh Meta's uh Meta's previous data center I think it was 150 megawws um two years to build it.
1:56:27
Uh how fast are they now?
1:56:27
Are they at 6 months a year?
1:56:30
Do you have any idea of where they will be on the on the speed frontier since that seems so critical? >> Yeah.
1:56:38
So two two two and a half years roughly speaking.
1:56:40
Uh then they built some sort of rectangular design which is 12 to 15 months. Okay.
1:56:46
>> Uh and then they realized actually we need to go faster and that's when you started seeing the tents.
1:56:52
>> Um and these tents uh yeah the goal is to be be able to put out a GPU cluster in six months. One of these tents. Wow, that's fast.
1:57:00
>> And it's interesting because they go back to an air to air cooling system.
1:57:01
So what I told you earlier actually is wrong because despite hardware being increasingly liquid cooled, now they're doing air to air again opening the window. Sure.
1:57:13
But they have those side cars which are liquid to air which are expensive again. Okay.
1:57:15
It's one way to go faster.
1:57:18
That way you don't have to build a whole like piping in front and all that. >> Yeah.
1:57:21
Yeah, that makes a lot of sense.
1:57:23
Um what about um how the other hyperscalers are are are matching up in terms of in terms of speed, but also uh a lot of the other hyperscalers, a lot of the big tech companies had made commitments to maybe move away from natural gas to maybe go more uh net zero, more energy efficient, more carbon neutral.
1:57:45
uh that feels like the water debate is maybe a moot point but there will be some sort of uh climate discussion in the future as more and more natural gas gets brought online.
1:57:59
It is a fossil fuel after all or it is not a renewable energy source.
1:58:02
So, um, how how are are there any big tech companies that are grappling with that or struggling to get through previous commitments that they made um to, uh, to be more environmental or more net zero and now they sort of have to retool their business and messaging.
1:58:22
Yeah, you've already starting saying this in 2025, but in 2024 where they're all they all said uh for the time being we keep our commitment for whatever 2030 or something uh net zero, but uh short term >> we're going to have we're not going to be able to meet our goals and to uh I guess um clean our fleet as as as fast as we expected.
1:58:42
But yeah, there there's just no way.
1:58:44
Um so there are a few interesting things.
1:58:46
So the the first thing I would say is you're seeing some projects that are natural gas based but they have uh they have ways to become more sustainable.
1:58:54
For example, there's a it could be a site where you have great geology to do carbon capture.
1:59:02
>> So for Cruso has a one like that in in Wyoming.
1:59:05
So that's those types of projects obviously have a long-term potential as well because then you can meet your commitment uh if you're still committed to that.
1:59:12
It's unclear they're already that committed.
1:59:14
But other topic the the other thing is so Google say generally from our analysis Google seems to be still the most committed hyperskater.
1:59:23
Um and they're doing some pretty interesting stuff in in Texas right you saw the acquisition of intersect power.
1:59:28
They're building some of these some massive campuses in Texas where they actually have on-site solar energy and battery.
1:59:33
But to be clear it's not behind the meter.
1:59:35
The reason we talk don't talk about it in the um in the optical is because it's not fully off-grid.
1:59:40
Uh there's still a grid connection. >> Okay.
1:59:43
So it's not comparable to the off-grid deployments of folks with turbines and >> interesting. Yeah.
1:59:47
On on the Google topic, uh is there any sort of durable advantage in multi- data center training that you're seeing from Google?
1:59:55
Are are are you seeing evidence that they're leaning into that more?
1:59:58
Are they building more smaller data centers or are they also I I I don't know off the top of my head.
2:00:06
Are they competing with like the Colossus 2, these, you know, Mark Zuckerberg comes out with the picture of the cube in Manhattan?
2:00:11
And it's very clear that uh that Meta is in the one big massive data center race.
2:00:16
Uh at least they're trying to visualize it that way.
2:00:20
I haven't seen that from Google. Is that intentional?
2:00:22
Is there anything we can read into that about their actual training and deployment strategy? >> No, no, you're right. That's a good point.
2:00:30
It is it is interesting to to analyze the different I guess frontier AI training architectures from different players. >> Yeah.
2:00:37
>> If you if you look at the what Meta is trying to build in in Louisiana, >> uh it's 2.
2:00:41
1 gawatt campus for the first phase.
2:00:45
>> Um and they have individual buildings that are 400 megawatts each. Okay. >> Per building. >> It's pretty insane. Microsoft open.
2:00:52
>> But it's still split up. It's still split up.
2:00:54
Uh but then putting it all on the same campus, there's some sort of economy of scale around power generation or is it just or is the latency with the fiber connections actually relevant?
2:01:03
Uh and you wouldn't want to have it across town so you put it on the same campus like when would when would a a big tech player choose to split across state lines, across the country, across the world versus centralize everything in one campus?
2:01:20
So I would say for now Google is really the only one that has been that that had adopted this strategy and is very unique about it to some extent.
2:01:27
You could argue it's because of uh first of all they're the most sophisticated on the networking side for for a while.
2:01:33
Like that's one of the advantages with Google is for the last 15 years or whatever they've been the best at infrastructure on every single part of infrastructure and so networking they've been building their own fi fiber networks for a while and so they have much higher bandwidth inside of metro and between metros and other other hyperscalers because they've been doing that longer.
2:01:53
They've been planning ahead for for all of that. >> Yeah.
2:01:56
>> Yeah. Um so Google is sort of ahead of the others and on the tech side um they've uh they've figured out multi data center training from a from a model perspective way ahead of everyone else but they've been very open about this right you had a podcast from Jeff Dean for example a few months ago where he said openly yes we're doing a multi data
2:02:14
center it works pretty well >> yeah no one else has really done it uh at that scale for now we have a bunch of startups they're not doing it at scale so yeah just Google is better at doing it and >> what it enables them to do is And it's it's it enables them to to some extent have more options with regards to site selection. >> Yeah. >> Yeah.
2:02:32
>> Uh you they're not really limited to finding the one 2 gigawatt site or the one you know 1. 5 gig sites.
2:02:37
Uh they can just go around the metro maybe a 50 mile or even 100 mile area and find a bunch of sites that are each 200 300 400 500 connect them and bam they have a you know two giga campus. Yeah.
2:02:47
So that's the the strategy they're pursuing. >> That makes sense.
2:02:51
Last question for me and we'll let you get back to your day. I know it's late there.
2:02:54
Um uh have have uh AI workloads has a shift in AI workloads had any effect on power decision makingaking?
2:03:02
Uh it feels like you you go back a couple of years ago and uh the vast majority of power that was being used by AI was for training.
2:03:11
Now we're moving more towards inference.
2:03:13
Uh does that change the landscape of power acquisition for AI companies broadly or is it sort of an irrelevant point?
2:03:21
So first of all, I would actually disagree with the premise.
2:03:23
Uh based on our analysis, uh training is still the majority and it's growing equally as fast as inference.
2:03:30
>> Inference is surging, but training is surging as well.
2:03:32
And that's normal because you have an incentive to do it.
2:03:35
>> Uh everyone wants to, you know, invest in the model that is going to unlock revenue growth next year.
2:03:38
We haven't seen the limit.
2:03:41
So there's the incentives are aligned to invest today and that's what everyone is doing. >> Interesting.
2:03:45
Um anyways to answer your question yes inference does have uh different requirements.
2:03:50
There's different types of inference as well.
2:03:51
Um if you think about open AI for example they have two main businesses.
2:03:55
Chad GPT is a vertical application.
2:03:56
It's fully controlled by themselves.
2:03:58
So for them it's it can larger campuses can be gigawatt scale can be a few hundred megawatt.
2:04:04
It's going to be big campus anyways.
2:04:06
Uh they can make use of smaller ones.
2:04:08
If you think about it from an infrastructure perspective, uh what is their biggest pain point uh as a company is they want to maximize GPU utilization rate is the single largest expense by far is GPU.
2:04:18
So they need to maximize it and that's easier to do when you have large campuses.
2:04:21
So that's why you still see uh campuses are fairly large even for inference um they also in terms of latency that's a common sort of uh topic of discussion.
2:04:32
Do you need to be very close to the end users?
2:04:33
Well, if you think about it, what is actually consuming power for OpenAI?
2:04:37
It's, you know, deep research. It's GPD 5. 2 Pro.
2:04:41
Uh it's this thinking models and they they take minutes to answer and so you don't really need to be near the metro.
2:04:47
You can just uh be sort of far away and still find large pockets of power. >> Yeah, makes sense.
2:04:51
Uh well, thank you so much for coming on the show.
2:04:53
Uh congratulations on the progress.
2:04:54
Really appreciate the semi analysis is hiring, correct?
2:04:58
Can you take us on a brief summary of of roles or how to apply?
2:05:03
Oh yeah, we're hiring a lot of people.
2:05:05
So we have a careers uh section in our website.
2:05:08
So you can all check out uh we're looking for folks u in the AI space.
2:05:12
So if if you're interested in digging into what we call tokconomics, which is analyzing the economics of AI, analyzing the latest trends in terms of LLMs, different types of model architectures, reach out.
2:05:22
Uh if you're an engineer, you have experience with GPU clusters, uh reach out as well.
2:05:28
We're hiring to uh to increase our technical team.
2:05:30
uh inference max really cool project as well where we benchmark all of the different models.
2:05:33
If you want to work on inference max and work on TPUs and tranium and GPUs and AMD and Nvidia and all of that, reach out as well.
2:05:40
We have a lot of pretty cool offers.
2:05:41
Uh so you should all check out the website and uh yeah, it's a good good adventure. >> Amazing.
2:05:45
Well, thank you so much for taking the time to come up for us.
2:05:47
Great to see you and happy new year. We'll talk to you soon. >> Cheers. Goodbye.
2:05:53
>> Turbo Puffer serverless vector and full text search built from first principles on object storage.
2:05:57
fast, 10x cheaper, and extremely scalable.
2:06:02
>> Um, next we are entering our Lambda Lightning round with Andre Horow.
2:06:05
It's celebrating their $15 billion fund raise.
2:06:10
We have Jen Ka in the reream waiting room.
2:06:13
Let's bring her in to the TVPN Ultra Dome. How are you doing, Jen? Good to see you.
2:06:18
>> Jen, what's happening? >> Hey. Hey.
2:06:19
What's happening, brothers? >> Uh, not too much.
2:06:21
You're off to a banger start of the year. Congratulations.
2:06:24
Uh, break it down for us. What happened?
2:06:26
We knew we'd need a bigger gong for you guys in particular this year.
2:06:32
>> Maybe we have to distribute the gong hits across the four injuries and Horowits uh partners that we're talking with. We'll see.
2:06:38
>> You know what I have to say? >> There we go. >> There you go. Wait, what does it say? What does it say on it?
2:06:46
>> It says it's time to build, baby. >> I love it. I love it. That's fantastic. >> There we go.
2:06:50
You probably been hitting that a lot.
2:06:52
Do you do you do you just do like one hit every time you get off an LP? You got a new commit. Just a a light tap.
2:06:58
You probably had to do a few of them to get up to 15. >> Exactly.
2:07:01
It's not quite your 80inch one, but you know, next time I'll get a horse and we'll call it even. >> There we go.
2:07:06
Uh, how was how was uh how was how are the LP pitches uh going into this fund raise different than in previous years?
2:07:14
The markets evolved, technology has evolved, and Horowitz has evolved.
2:07:19
uh what were you saying that you felt like it was the first time you were saying to LPs this time around? >> Yeah.
2:07:27
So, so let me first break down.
2:07:28
So, $15 billion huge headline. Uh the number is huge.
2:07:31
But, you know, I I first I should foremost say I normally don't respond to online rumors, but I feel the need to do so at this moment that $15 billion is not for the Nepal or Himalayan or Greenland, right?
2:07:43
Let's spell that right now.
2:07:45
>> You you know people tease things all the time.
2:07:48
little little little breadcrumbs in the releases.
2:07:50
I'd like to see an American Everest.
2:07:52
I feel like I've heard the pitch for Greenland, the moon, the moon might be American at some point.
2:07:55
It already is in many ways.
2:07:57
Maybe Everest, but you know, you're putting it in startups.
2:08:01
You're putting in technology. >> Exactly.
2:08:03
So, so hope springs eternal.
2:08:05
So, so the prelim number, you guys covered this yesterday, but the prelim numbers for for NVCA came out to, you know, 66 billion.
2:08:10
So that actually ended up being what would have been equivalent to 22% of of what was raised in in 2025 with the $15 billion.
2:08:18
So >> wait, so so does the 15 billion get included?
2:08:21
Do they are they going to update the 2025 numbers or do they count it towards 2026 because it's actually being announced now?
2:08:31
>> Yeah, it's going to it's going to get counted for 2026.
2:08:32
So that that is that is forward.
2:08:35
So we're closing our fund today.
2:08:36
So that would be 2026 numbers. Yep. >> Cool.
2:08:39
Um and so huge calling now VC winter maybe you know potentially over for some folks.
2:08:44
for some folks. uh uh but >> fantastic >> but the uh the sentiment to answer your question so the sentiment from LPs is different in so far as that we are now this is the next the second set of funds that we've raised in this AI super cycle
2:09:01
>> and so we were oversubscribed in 3 months you know it >> was I think very clear for most people that AI is obviously taking over the world and particularly when LPs have conviction and also the right information, they will close quickly. So
2:09:14
So most funds, you know, the average VC fund takes probably close to over a year to fund raise.
2:09:19
And the reality is it's it's a tale of two cities.
2:09:22
If you have great companies, great performance, great DPI. >> Yeah.
2:09:28
>> It's very very easy to raise capital. >> Yeah.
2:09:31
>> Uh we are luckily in that camp.
2:09:31
If you don't, it's just a lot tougher.
2:09:32
And and by the way, let let me tell you also a story because it's related to on this liquidity topic that you guys um often times talk about and hear about from LPS.
2:09:41
So, you know, there's a lot of belly aching from LPs about liquidity, but the reality is it's in select companies.
2:09:48
So, we actually went through this whole exercise uh last year.
2:09:50
So, this was in the middle of liquidity concerns and this was early days of of you know, the the administration stance on on endowment tax cuts.
2:09:57
And, you know, we internally had this conversation said, gosh, you know, should we offer some liquidity particularly for some of our older funds um to our LPs?
2:10:05
our older funds um to our LPs? So we so we went around we called um all of our our LPs in those older vintages and specifically we had a stripe position seed position in fund one and then we had data bricks at the series A in fund three and we said hey you know we know
2:10:19
you're in liquidity crisis would you be interested if we got you some liquidity in those names >> and I'll tell you 30 out of 30 of those early L said absolutely not >> like we want liquidity >> you're telling me would I like to not ride my winners >> exactly exactly so there's subtlety in
2:10:38
that conversation which is like you know they want liquidity but they want liquidity not out of those names they want to ride those winners right they want to let them >> unfortunate want liquidity the most from the from the from the assets or the companies that you're least
2:10:50
>> yeah excited about which is this paradox interesting interesting um yeah that that makes sense uh talk about the split of strategies going on at Andrew and Horowitz today I think a lot of people were curious about crypto not being included in this suite of funds Is that just a different cycle? Is that a
2:11:06
Is that a mechanics thing?
2:11:08
What what's going on there?
2:11:09
Or is it truly like a completely separate thing and we'll be hearing about that later? >> Yeah.
2:11:14
So the so the latter so the funds that we raised and and announced today, it's five out of seven of our funds.
2:11:17
So crypto is offcycle and then so is our games fund. Okay.
2:11:21
So some more to come from that. >> Got it. Okay, that makes sense. >> Uh yeah.
2:11:25
How how uh are are LPs up to speed on this kind of like structure now?
2:11:32
now? You obviously don't have to go into a conversation explain Andre and Horowitz but uh most funds are not at the scale where there's like you know this multi- multiff fund approach is that like how much of the conversation
2:11:44
is about like okay like I'm giving you uh capital where is it going to be actually allocated and how is it going to be split across the funds is it just straight proa uh across the different strategies and funds or how does that work? >> Interesting. Yeah. >> Interesting. Yeah. >> Yeah.
2:11:57
So it's a that's a great question and in fact I think we're one of maybe the first who actually split our funds.
2:12:03
Most most firms just have a generalist fund that everything's out of one vehicle >> and we very early on preently realized we needed to decentralize as a firm and then also our funds as well to match that to the teams.
2:12:13
And so if you look at any of the individual teams the deal teams are no bigger than you know four to six people. >> Sure.
2:12:19
And so we're kind of similar to smaller funds and smaller firms but with the breath of course of of you know the Andre and Horitz umbrella.
2:12:26
And so for for LPs when they think about allocating to us most of them just say hey I want to follow you into all the different funds.
2:12:32
Um and they allocate Pratta and in fact we actually set up a vehicle to to allow them to do that.
2:12:37
Some folks pick and choose and our view is hey every single fund needs to stand on its own and it needs to earn zone keep from its LPs and sometimes those LPS might be different right?
2:12:46
Some MPs for example internationally can't invest into certain strategies like crypto for example maybe American dynamism.
2:12:51
So there's some there's some nuance there of which we we do uh account for. >> Interesting. Yeah.
2:12:57
>> Interesting. Yeah. uh how much uh how many questions are you getting from LPs about uh trying to predict the next next Andre strategy that might take place in this fund like Andre started as I mean you look back at the early like the fund one and it's basically a seed fund by today's standards growth was obviously
2:13:17
added on then bio then crypto and then liquids tokens like there's so many different strategies that if you went back to the dawn of Andre you would say well that doesn't fit in fund mandate uh and and we've seen uh firms buy hospital networks and do more private equity style deals, more do more secondary deals. Are LPs looking for you to lock a
2:13:36
Are LPs looking for you to lock a strategy or are they leaving you with a lot of flexibility?
2:13:40
Are they looking for guidance on what might happen in the next 10 years in terms of creative financial plays that you might be able to make? >> Yeah. So, it's funny.
2:13:50
Uh our first fund is funny you should say it's the size of a seed fund.
2:13:54
The first deal we actually did was the buyout of Skype, which is there's a there's a good story uh around that we made, you know, 4x return in 18 months and the rest is history.
2:14:03
But but you know, that that first >> Yeah, >> I always remember seeing that on Andre's uh website and it was like it wasn't a seed bet.
2:14:11
It was this weird deal and but it still panned out really well and it was like a great logo to have on the on the portfolio page, but for peculiar reasons. >> Yeah.
2:14:20
And there was a bunch of risk in it because everyone was like, "Oh, you won't get the IP because of of eBay and blah blah blah."
2:14:25
And then, you know, Microsoft ended up buying it.
2:14:26
But, you know, the the and then there's a whole story there because a lot of our LPs, suffice to say, after raising a venture fund, we're like, "What are you doing?"
2:14:34
>> Y ended up working out.
2:14:36
Nonetheless, you know, we we always talk about internally how, you know, the way the individual funds are set up now is almost in the incarnation of the original Andre Horitz from the size of the team, from the capabilities and resources on the operating front.
2:14:49
And so you've got these, you know, kind of seven different funds and teams that are effectively the incarnation of that first Andreason horror.
2:14:57
It's now replicated >> and that's actually how you scale.
2:14:58
We have 600 plus people at the firm now.
2:15:01
That's the only way you could actually nimbley move without getting mired in the morass of of bureaucracy and and oftentimes what big organizations end up being.
2:15:10
And so in some respects we don't necessarily we're not motivated by innovating into you know there's a lot of VC firms out trying their hand at private equity as you said buying hospitals um raising private credit strategies like that's not really of interest to us.
2:15:26
I think you mentioned at one point like going public like as long as Ben is CEO we are not a public be a public company.
2:15:32
Uh so we don't try to innovate on fund structure right we like boring vanilla VC >> kind of returns and you give us money and we'll send you back and and uh where we'll take risk and and innovation is on the companies we invest into.
2:15:45
>> How much do you involve individual GPS in the fundraising process?
2:15:48
Sounds like I mean a three-month process really not that long.
2:15:52
Are you are you tapping them in at at key moments because certain LPs want to understand like really get to know uh the individual uh investors or are you like aggressively trying to protect their time because their time is really best spent with uh you know founders and actually evaluating and doing deals? >> Yeah.
2:16:10
>> Yeah. And the so yes we try to protect our time but also at the same time like this is just like a company like a fund raise is a very important exercise and in fact you know a few years ago when people were asking whether we we would go away from the traditional fund structure you know Mark and Ben kind of
2:16:25
like the concept of pressure testing our thesis every couple years right you got to go out to your LPs you got to prove to them that your thesis you know is worthy of their capital and then it pressures you also sorry for for my voice here it's a little horse uh because I've been shouting you know, you're watching too often. >> Um,
2:16:43
>> Um, >> like why are the why are deadlines now? >> Exactly. Exactly.
2:16:47
Um, no, but that that kind of sentiment of pressure testing your thinking is incredible.
2:16:53
And it you guys know from fundraising, you know, with companies like you learn a lot through the course of that process as well.
2:16:59
So, so all of our GPS get involved.
2:17:01
All of them are in the meetings, you know, they're all talking to the LPS, they're shaking the hands, kissing the babies.
2:17:05
They are front and center of it. Mhm.
2:17:07
H how do you uh how do you realign the LPs from just endless AI questions and actually keep them interested in bio, healthcare, American dynism?
2:17:18
Do you do you try and like have the AI narrative cut across everything or is it drowning out the rest of the stories that you're trying to tell?
2:17:26
I think AI is similar to any platform shift where it's just going to infiltrate everything and it's like obviously in the zeitgeist, but eventually it's just going to go in the background just like cloud or >> Yeah, there was there was that quote from Mark in in the launch video that was like someday in 10 years we won't
2:17:40
talk about the internet because it'll just be everywhere and it feels like we're already uh I I like when companies uh I think this is the year where companies like maybe stop pitching AI as aggressively in taglines because you should just assume uh that a company is leveraging it to the fullest extent. >> Yeah. >> Yeah. >> 100%. Yeah. Yeah.
2:17:59
What else are you doing like that? >> 100%.
2:18:03
Uh but I I do think you know it's it's great too because I also think you know with this platform shift LPs can actually have a feel for how transformative this is themselves.
2:18:13
So our entire for example fundra process we tried to take a AI native first approach.
2:18:19
So we had an AI chatbot that was replicated.
2:18:20
I was about to ask >> in my in in in our data room, there was an AI gen in there.
2:18:25
Um, you know, there's AI chatbot that was answering any question in any hour of the day.
2:18:31
>> Um, and then our LPs also are playing with these tools themselves as well in their underwriting and their diligence, but also even individually.
2:18:36
I I'll uh I won't name the LP, but I was talking to an LP earlier this this morning who uh was playing around with Replet, and I was like, you got to try it.
2:18:44
Like just just code something that you wish, you know, you had access to.
2:18:47
and she's like, "Well, I really want to be able to code an app that can uh look at Pelaton classes and let me know when this instructor see I'm like trying to prompt it."
2:18:55
And she was able to do it literally in the course of the morning.
2:18:57
So, it's it's one of those things where I think these worlds are converging so quickly.
2:19:01
It's also almost great that we're just all we're doing is testing and trying and iterating and for the first time LPS as users can actually see the real world visceral impact to how they run their day-to-day life.
2:19:14
How uh what is what is general LP sentiment specifically around 2026?
2:19:17
What are what are expectations?
2:19:19
Obviously, we're expecting a slate of IPOs and that's uh very exciting if you've been in uh in these uh in these companies, these names for, you know, a decade or more at this point. >> Yeah.
2:19:34
Yeah, I feel like Elon dropped like an early Christmas present when he was uh it was like rumored to say that SpaceX might be going public in 2026 and everyone's like, "Oh, maybe we'll go public in 2026."
2:19:44
So, I I do think sentiment and people are are generally positive.
2:19:48
Um obviously, you know, we'll see where the IPO markets kind of turn out to be, but generally speaking, it's it's early.
2:19:54
It's off to a good start.
2:19:56
Like, we'll we'll see what happens.
2:19:56
But I I do think people are expecting more capital this year in a way that once one breaks through, it's going to be a watershed moment that might even top, you know, 2021 in terms of the amount of liquidity coming back to folks.
2:20:08
>> That's going to be exciting.
2:20:08
That's going to be exciting.
2:20:10
>> Was uh was 15 always the target or did you go out, you know, thinking that you do less and and uh and then you kind of upsized it based on demand?
2:20:21
>> Uh we had a range for our target.
2:20:21
Um, and we try to, you know, kind of keep uh in that range just to to avoid, you know, upset.
2:20:27
>> We knew it was possible because if if Maso can do a hundred, it's like, come on, can can we can we can we do 15?
2:20:36
>> I won't I won't make that comparison.
2:20:36
It is it is it is funny in retrospect, you know, that that vision fund, you know, >> the whole thesis was Yeah.
2:20:43
I looked I I completely blocked Vision Fund out of my head and uh and then I was like I I was researching before that.
2:20:51
was like, "Okay, 15 billion has to be the biggest fund venture fund ever."
2:20:54
And it was like, "Oh, no, of course fund."
2:20:57
>> Um, >> anyway, uh, well, thank you so much for coming on the show.
2:20:59
Congratulations on massive news and we will talk to you soon, Jen. >> Incredible work. >> Awesome. Great to see you again. >> Catch you later. >> Cheers.
2:21:07
>> Let me tell you about Vanta automate compliance and security.
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2:21:14
>> And thank you to the chat.
2:21:14
Uh, there have been some updates to Claude's policies.
2:21:19
Tyler is researching the story now.
2:21:21
and we will get to it as soon as we can.
2:21:24
>> Uh well, we have Alex Rampel from Andrew and Horowitz coming in Ultradome.
2:21:28
Welcome to the show, Alex. How you doing? >> Good. How are you? >> Beautiful background.
2:21:31
Uh fantastic American flag. What What a day. Congratulations. How are you doing? >> Good. Good. >> Fantastic.
2:21:39
>> Uh super excited to have you on.
2:21:39
I've uh I've enjoyed uh you're somebody who's I' I've uh read your writing and and listened to your your podcast appearances for a decade now and and always always appreciated your your point of view on on a bunch of different uh things. So, welcome to the show. >> Yeah, >> thank you.
2:21:58
Yeah, I'm I'm here to prove that I'm real. >> Fantastic.
2:22:00
I mean, >> it's like proof of life is very important increasingly, right? >> Yeah. Yeah, it is.
2:22:04
Uh I mean first time on the show.
2:22:06
Can you uh give us a little bit of the backstory, the journey to Andre and and uh and how long you've been there? >> Sure.
2:22:13
Uh so I've been here for 10 years.
2:22:15
Um previously been a long time >> success.
2:22:19
>> Uh previously longtime entrepreneur.
2:22:19
So kind of started by writing software when I was a kid in high school.
2:22:24
Actually even before that.
2:22:26
>> Um and then out of college I was like I graduated in 2003.
2:22:29
I was probably the only person from my class that just kind of became an entrepreneur right away. Yeah.
2:22:34
>> Um, and it wasn't because I was smart or dumb.
2:22:36
Probably more dumb than smart.
2:22:38
It's like I had a little business that I was running in college.
2:22:39
So, kind of kept doing that.
2:22:41
Met this guy named Chris Dixon. >> Yeah.
2:22:44
>> Who was at Harvard Business School when I was at Harvard College.
2:22:45
And you have to remember like 2002 when we met. The internet 1. 0 had just died.
2:22:50
Everybody lost their jobs. It was September 11th. It happened.
2:22:55
And what do you do if you're a dried up entrepreneur?
2:22:56
You go to business school.
2:22:58
I remember there's a company called Cosmo.
2:23:00
com, a huge hit that kind of went to zero. What did that guy do? He went to HBS. >> No way.
2:23:06
>> So Chris Dixon was there.
2:23:06
Um and he and I were like the only two people I I swear in like the entire state of Massachusetts that thought that the internet was still kind of cool.
2:23:12
We got introduced by a mutual friend.
2:23:14
Um had had a coffee at Aubon Pan, this like little East Coast chain, >> and then cooked up uh a product called Did They Read It, which is still around today.
2:23:24
It's an email tracking tool.
2:23:24
It embeds a tracking pixel in every email that you send out. Um that did pretty well.
2:23:30
Then we started the ventureback company together that became Side Adviser and that got acquired.
2:23:33
And then I started another company called Trial Pay >> to um like the thing that we learned at Side Adviser is that nobody likes paying for software.
2:23:42
Like you're willing to pay for an intangible good like a glass of wine.
2:23:45
$20 for that seems totally reasonable, right?
2:23:47
>> But paying $20 for one song on iTunes, there would be riots in the streets.
2:23:52
>> So the idea was I'll give you this digital good for free if you buy something else.
2:23:56
M >> and if you know how affiliate marketing works, it kind of plugged into that.
2:23:59
So it's like, hey, we'll give you this product for free if you sign up for Netflix or if you switch to GEICO or if you shop at the Gap or if you get a Discover card using the affiliate commission to go pay for the product that did pretty well.
2:24:10
Like it was like half of the revenue of Side Advisor.
2:24:11
It it was like for my from my little shareware business that I used to have back in the day. It doubled our revenue.
2:24:17
So I turned that into a company called Trial Pay.
2:24:18
Um that did great for a while.
2:24:21
Then it did terribly kind of resumed to okay, sold it to Visa.
2:24:22
Then along the way met this guy Max Levchin um after he had sold slide to Google and we cooked up a company called a firm.
2:24:31
So I co-ounded a firm with Max in 2012 um and actually brought a firm to and Horowitz as a funding opportunity which which they did.
2:24:43
>> Um and Chris Dixon kind of ended up talking me into joining here in 2015.
2:24:45
So I've been here ever since.
2:24:47
Uh how how quickly did you realize that that uh Chris and Max were special?
2:24:53
Because I imagine you you during those two periods you were meeting hundreds of different people.
2:25:00
I'm sure people wanted to build stuff with you, other entrepreneurs.
2:25:02
Uh and you picked well uh back to back uh and uh it's probably the hardest hardest uh you know one of the hardest things to actually clock at times. >> Yeah.
2:25:14
I mean I I think a lot of the greatest people they have two things in common.
2:25:17
they have this term that that's going around a lot like high agency like they don't just like follow the rules they just like take matters into their own hands and do something.
2:25:23
Um, and then they just kind of know the history of everything before.
2:25:27
Like they they just like students of history, philosoph like, you know, Chris was a philosophy major.
2:25:33
People don't know about him.
2:25:33
He went to like he he went to, you know, he got his bachelor's degree in philosophy, was going to do a PhD, kind of realized that was a bad idea.
2:25:40
Um, and then eventually went to business school, which was he will probably say the worst idea.
2:25:44
But, um, yeah, it was kind of self-evident.
2:25:47
I mean, Chris and I I mean, >> the history the history thing is a real thing.
2:25:50
Like if if you're talking to an entrepreneur that has been building their business for one to two years and you can tell them companies that in somewhat recent history in the last decade even that have like attempted that or companies that are adjacent and they're like oh I'm not familiar with that.
2:26:04
It's like immediately like such a bare signal because the red flag or the opposite like that's the red flag.
2:26:08
the whatever the opposite.
2:26:09
What's the opposite of green flag? That's what I'm saying.
2:26:13
>> But yeah, the green flag never flag. What's the green flag?
2:26:18
>> The the green flag is not only have do I know everything.
2:26:21
Um I mean I'll give you one example.
2:26:23
I think the Collison brothers went out to like Dehawk's ranch.
2:26:27
>> Like Dehawk started Visa.
2:26:27
He's kind of like a weird quasi communist even though he started one of the biggest companies in the world because Visa was meant to be this like it was a nonprofit.
2:26:34
be this like it was a nonprofit. Visa was a nonprofit until 2008 >> I don't know 2008 maybe 2009 it was the biggest IPO yeah >> that's right >> yeah but it was a nonprofit until then um a nonprofit like the NFL is a nonprofit like it makes a lot of money but it's owned by the constituents and the constituents that own Visa were the banks
2:26:52
>> and it's like okay I'm starting a payment company there were a lot of payment companies that came before but it's like who will that let's find this guy who's 90 years old who's moved outside of capitalism is working as a farmer just to learn from him and like I have this mental model that I now use for entrepreneurs and it's a memo that I've written that we use internally a lot. I got to say like the best
2:27:09
I got to say like the best entrepreneurs they have five things that that I look for.
2:27:12
They can materialize labor capital and customers and hopefully those are self-evident like you can get people to quit their highpaying job for like certain failure.
2:27:20
It's like the Ernest Shackleton thing.
2:27:22
It's like you wanted men for dangerous journey almost certain failure and death but if it worked you might be famous right it's like you want that very very hard to do you have to find people that can materialize capital it's like get people to give you money and the best the best sign of future fundraising success like if we do round end we want to make sure there's going to be a round
2:27:38
n plus one or you're going to be profitable on round end which is unlikely so are you good at fundraising can you get customers like imagine it's like I have two weeks of cash left please be my first customer I have none like who it's very hard to pull that off >> then you want to know the history of the space, which is super important to your point. You want that green flag version,
2:27:53
You want that green flag version, not just the intermediate, you know, what's the what's the the combination of green and red flag like the tur you don't want the turquoise or the whatever >> like you want the green flag.
2:28:04
This person knows everything that's tried before and they have a new angle of attack.
2:28:08
They're not going to learn on the job.
2:28:09
They've actually learned through history.
2:28:11
And then the last thing that I care about a lot, um, everybody in my my team knows this.
2:28:14
My favorite book is The Count of Monorista by Alexander Duma >> and it documents the story of this guy Edmund Dantes who's like wrongfully accused is like in prison for 17 years but then becomes the richest person in the world but doesn't give a Right.
2:28:29
It's like all the all the riches in the world do not matter. He wants revenge. >> Yeah. >> Right.
2:28:33
He or so you could either revenge kind of sounds bad like Old Testament but you either want revenge or redemption.
2:28:38
And some of the best entrepreneurs have this in common.
2:28:40
And the reason why it's so important from a venture lens is imagine that you're a 20-year-old kid.
2:28:45
You start a company and somebody offers you, I don't know, half a billion dollars to buy your company and you own 25% of it.
2:28:51
You're going to make over hund00 million.
2:28:53
You'd have to be insane to turn that down, >> right? >> Yeah.
2:28:58
>> And we need people that are insane that that actually are going for it's not that we don't want people that aren't capitalists that don't care about money, but it's like they care about if you've seen the movie Space Balls, it's like we're not doing this for the money.
2:29:08
We're doing it for a shitload of money.
2:29:09
Little little different here.
2:29:09
It's I'm doing it for another reason.
2:29:12
And like a great example of this is there's this guy Renault Lelanch who started a company called Lending Club. >> Oh yeah.
2:29:18
>> Um very famous company at the time.
2:29:20
There was like a der of IPOs.
2:29:20
Like Lending Club kind of gets to scale, goes public.
2:29:24
He gets fired from his board, ousted from the company.
2:29:26
He's probably made hundreds of millions of dollars.
2:29:29
He's the count of Monristo.
2:29:29
He's like, you know, those guys.
2:29:31
I'm going to start a new company.
2:29:33
I'm I'm going to start an upgrade.
2:29:35
And you know what he called his new company? Upgrade.
2:29:36
It does the exact same thing as Lending Club.
2:29:40
It's probably 10 times the size of Lending Club now.
2:29:41
And what's motivating him is not just the hopefully, you know, ton of money space falls quote, >> but he wants revenge. >> Yeah. >> He wants redemption.
2:29:50
>> And you see this with some of the best entrepreneurs like what is the driving motivation because when times get tough, like you need something because like there is no money.
2:29:59
Like if if your company's going to zero, uh if you're Eron Shackleton in the winter of Antarctica, like your voyage is not successful, right?
2:30:07
You you need something else driving you at that point and that's why that >> that metal is something that that I I find extremely valuable.
2:30:16
>> Have you seen Space Balls, Jordy? >> I have not.
2:30:18
>> You got to famous I famous I famously have seen >> he's seen no movies. He's not a >> question.
2:30:25
>> One of my uh probably like a I really I was going to say maybe I it's hard to exactly place a top 10 like I I loved your episode on uh invest like the best on operating systems.
2:30:35
How is AI kind of like updating your thinking on modes and operating systems and uh how somebody can create a lot of value with a startup? >> Yeah.
2:30:48
Well, I I think um well, maybe I can rewind a little bit and just because we announced this new fund raise, I can tell you exactly what we told our LPs in terms of like what we want to invest in at the application layer because I I do application layer stuff.
2:31:01
Um and it's really three things.
2:31:03
You know, category one is I call it green field bingo.
2:31:05
Um, and kind of maybe another way of answering your question is there's something that there's a quote that I use a lot.
2:31:11
The best companies have hostages, not customers, right?
2:31:12
Like that's why nobody likes using sales.
2:31:17
>> You got to be taking revenge.
2:31:17
You got to be taking hostages.
2:31:20
>> You know, it's it's very old testament stuff.
2:31:22
But the best companies have hostages, not customers.
2:31:24
Those are great companies to invest in, right?
2:31:26
And that kind of goes to to to the point that I was making like you know Netswuite, Workday, Salesforce, like they're all hated by their customers, but none of those customers can leave.
2:31:37
>> However, if you build a better version, like kind of a more AI first version of all of these companies and you're selling into the green field, >> um you've got a shot, right?
2:31:46
Because like I was the lucky enough to be the first investor in Mercury and Mercury worked not by stealing people from SVB. They just worked.
2:31:55
It's like, oh, you're a brand new company.
2:31:56
you can use shitty SVB or you can use really good mercury and that worked.
2:32:00
Whereas they never got customers from SVB until the weekend that SVB failed. Yeah.
2:32:04
Um so that green field opportunity for software like that is AI enabled in the same way that like that was true for cloud, right?
2:32:10
That was true for mobile.
2:32:12
It's like here is the new thing.
2:32:13
The incumbent will eventually build it.
2:32:16
Like another expression I use a lot is like the battle between every startup and incumbent is whether the startup gets the distribution before the incumbent gets the innovation.
2:32:21
The incumbent my my default assumption is that the incumbent normally wins. Mhm.
2:32:27
>> Because they have the distribution, they will get their act together three years later and with AI and cursor and everything else, they'll get their act together maybe three weeks later. >> Yeah.
2:32:35
>> So that the the the the kind of the might of distribution is very very powerful.
2:32:40
So one option is you just go into the green field.
2:32:44
So that's kind of category one is you know we we call it green field bingo. It's just like build.
2:32:49
We we have a bet that's just like Netswuite. It's better. It's AI enabled.
2:32:53
But they're not going to steal customers from Netswuite.
2:32:54
they're just going to get green field.
2:32:55
get green field. Category two is this kind of new super exciting category of software does labor and like there there is no incumbent software product for I don't know trial attorneys like it's called Microsoft Office but like Eve does that and does that really well there's no incumbent software product
2:33:13
for dental office receptionist but tenor does that and does that very well so that's a really these are all industries that I wouldn't say they've been untouched by software they've been untouched by specialty software >> and The reason why is because the market was perceived to be too small. >> And this is exactly what happened to
2:33:30
>> And this is exactly what happened to SAS.
2:33:31
Like fintech really changed SAS significantly because take I'm sure you've heard of Toast.
2:33:36
Um Toast is one of my favorite businesses.
2:33:38
It's like Square but it's only for restaurants.
2:33:42
It's this whole operating system for restaurants.
2:33:43
How many restaurants on their IBM PC Jr. in 1984 use software? Like zero. >> Yeah.
2:33:51
>> And how many of them would pay tens of thousands of dollars a year for software? Zero.
2:33:54
But they all need payment processing. They all need payroll.
2:33:57
They need these other services.
2:33:59
You kind of bundle them in with software.
2:34:00
And this is the really exciting thing about AI is you go say, "Hey, trial attorney, uh, I want you to pay $50,000 a year for software."
2:34:07
He said this 10 years ago. Like no way.
2:34:10
Like we'll pay for Microsoft Word because we use it to write demand letters. Like that's it.
2:34:14
>> And now you can say, "Hey, we'll handle all these cases for you that you could not handle profitably."
2:34:17
And that's AI plus software.
2:34:19
Now they are software buyers. So that's category two.
2:34:21
And then category three, I call the walled garden.
2:34:25
And I wrote a post about this a little while ago, but walled garden businesses are amazing because if you assume that in the world that we live in today, and this is another way of thinking about kind of um defensibility in AI, open AI has their sights kind of on everything, right?
2:34:41
Like anthropic probably has their sites on everything.
2:34:44
It's so easy to build everything.
2:34:46
>> So I don't know, have you guys heard of Open Evidence? >> Yeah. >> Yeah. >> Okay.
2:34:49
So, I I tore my Achilles uh in February, so almost a year ago. >> Sucks, right? It's all better now.
2:34:54
Um >> it was I was skiing in Japan. >> There we go.
2:34:59
That's a good reason to That's a good reason. >> There we go. There we go.
2:35:02
Um Termite Kelly's what do I do? So, I go to Chat GBT.
2:35:06
I'm in like the the clinic in Nico, Japan, talking to this Scottish doctor and he tell me, "Oh yeah, you only have surgery in the US.
2:35:12
Nobody does it outside the US."
2:35:13
I was like, "This guy's on crack."
2:35:15
Like, of course you have surgery to fix an Achilles.
2:35:16
I go to catch it, he tells me everything.
2:35:18
Um then I think I find this thing open evidence and it's like chat GBT but it has every single medical document in the world and imagine that tomorrow chat GBT 53 comes out it's AGI everybody agrees it's AGI human race is over but it has no medical data and then on the other side you have GPT 3.
2:35:37
5 and it has every single piece of medical knowledge ever known to mankind.
2:35:41
What would you rather use?
2:35:43
>> And the answer at least for me and I I did use this is open evidence.
2:35:45
There's so many businesses that look like this where they find some proprietary piece of data. >> Mhm.
2:35:53
>> They're the only ones that have because before you would have to sell data.
2:35:54
That was like your only that was your only hope as a business.
2:35:57
Um and like another example that I mentioned in this post, there's a company called VLEX and VLEX is this like 25-year-old European data business that bought up, you know, legal records in Spain to start and they would sell it to firms like Wilson Cinci that needed it for case law.
2:36:12
Um, now they sell an outcome because they're the only ones that have all the the records.
2:36:16
So you can char you can build a really interesting business if you're the only source of some unique form of data.
2:36:22
And I love businesses like that because that's the other sorry for being so long-winded here on the answer to your question, but um the the the businesses that can be very very large in AI that can grow very very quickly, you still need to make sure that they're fundamentally defensible.
2:36:38
And that's the really hard thing to disamiguate today, which is you can have things grow so quickly, but they can also go to zero so quickly because anybody can build software in like a weekend, which is both great and terrifying at the same time. >> Yeah, indeed.
2:36:52
Well, thank you so much for hopping on the show and breaking it down. >> Incredible overview.
2:36:57
>> Yeah, great to meet you.
2:37:00
>> We'll talk to you soon, Alex. >> Congrats.
2:37:00
Have a great rest of your day.
2:37:03
>> Let me tell you about console. com.
2:37:04
console builds AI agents that automate 70% of IT, HR, and finance support, giving employees instant resolution for pass for access requests and password resets.
2:37:13
And up next, we have David George. >> We are running late.
2:37:16
David, good to see you again. How are you doing?
2:37:20
Congratulations on all the progress.
2:37:20
How does this change growth, the growth practice?
2:37:25
Is this just more of the same strategy or can you do new things with this new fund?
2:37:31
>> It's more of the same, honestly.
2:37:31
Uh, first of all, I I'm still like thrown off because I've worked with Rampel for seven years and we're close friends and I just realized that his favorite book is Counter Money Cristo and that's my favorite book. We've never >> Yeah. Yeah. Yeah. It's a great one. >> Yeah.
2:37:48
No, more the same for the growth fund.
2:37:49
I mean, look, you know, the last uh the last seven years since we started it, it's been a pretty simple mandate.
2:37:55
It's like best, you know, best companies in the world, best founders in the world with huge ambitions.
2:37:58
Typically the bet that we're making is that it can be bigger than other people believe it can be.
2:38:04
Um you know PY wrote a whole a whole long 16,000word essay about this today.
2:38:09
Uh but if I were to summarize our views and what defines like you know quintessential growth investment for us it's it's a belief that it can be bigger than people would realize.
2:38:16
Uh and we got a ton of success stories on that.
2:38:18
So more of the same in terms of our strategy and it just so happens that we're on the back of like the best trend of my lifetime.
2:38:27
of my lifetime. Do you think there's something changing in the psychology of startup founders where uh the new crop of mega corns the SpaceX is it sort of gives the next generation permission to stay private longer maybe hey you know
2:38:44
previously it was maybe a hundred billion dollar IPO would be crazy big now we're maybe having a few trillion dollar IPOs happening soon all of a sudden the logically you know even if you're not in that category you're like I'll stay private until 100 billion. Is
2:38:57
Is the psychology changing for founders? >> Yeah, it is changing.
2:39:01
I'm going to talk about the psychology of founders in two different ways.
2:39:05
So, one that I'm more excited about like we can talk about capital markets and public markets and private markets.
2:39:09
The thing I'm more excited about is the psychology of the founders that has changed postco like this generation of founders is just way more hardcore.
2:39:17
M like I I for one am all for you know the being back in the office the working really hard you know unabashed you know pursuit of success and I think it's a big change like in the last five or six years that's happened.
2:39:32
Uh I think it's part of what's propelling these companies to be so good so fast.
2:39:35
Obviously AI is the big technological driver but I think the vibe shift is a huge part of it.
2:39:39
You know, we were looking last night at some stats and going back and forth on some of our best companies and we have a bunch of the AI native companies that are application companies that that are kind of 100 million plus 100 million to a billion dollars of revenue. Yeah.
2:39:54
>> Uh and we were looking at uh do we think they're running themselves differently?
2:39:59
So to this point of like, you know, different vibes, what they what they what they care about, >> and it turns out like the old rule of thumb for companies was, you know, if you look at like revenue divided by all their employees, it's like $400,000 of revenue per employee.
2:40:13
Like you look at like public software companies, that's kind of where it shakes out.
2:40:17
>> All these AI native companies, they were basically like 500,000, 900,000, 2 million, 2 million, 2 million, 5 million.
2:40:25
So, >> they're they're they're totally different.
2:40:28
I think they're being run totally differently.
2:40:30
Uh we're really excited about that.
2:40:32
And the biggest thing is just like there's a tsunami of demand uh coming their way, which I think enables them to run, you know, much much faster.
2:40:39
So, I'm super excited about that.
2:40:42
You know, as it relates to the the capital markets thing, the staying private longer, it's totally rational.
2:40:48
Look, there's a bunch of it that is our own, you know, sort of government doing as it relates to being a public company and how difficult and expensive that has become.
2:40:55
Um, you know, we have a robust private market.
2:40:58
Uh, it's it's been a benefit to us.
2:41:00
Uh, you know, it's allowed us to invest in a bunch of companies that otherwise would have gone public, you know, sooner, >> uh, when we can still invest in them and they're growing really fast.
2:41:11
Um, and, you know, the value proposition for founders is pretty good to be a private company.
2:41:17
uh you know they can they can stay private.
2:41:19
It's probably a little bit of a higher cost of capital for them.
2:41:21
Uh but the trade-off for them is you know they can sort of avoid the daily kind of volatility of of the stock price and what that means for >> pay more M&A options as well.
2:41:29
There's a lot of >> what is uh what is your day like?
2:41:32
What are your weeks what are your weeks like?
2:41:36
Cuz I imagine like you the the balancing and like prioritizing when >> most of it's adding Zoom to spreadsheets.
2:41:42
So okay, we got to add the model's breaking. The model's breaking.
2:41:46
No, but but uh I imagine it's hard to prioritize when you can write everything from like a a hundred million dollar check up to you know at times like you know >> multi-billion dollar rounds are coming together >> multi-billion dollar rounds are coming together like how like what what uh how do you prioritize your day and your week? >> Yeah.
2:42:04
Yeah, I mean the reason we raised this fund that's a little bit larger, you know, one, it's a reflection of the opportunity set and two, you know, we want to be able to say, hey, we can write a billion dollar check into a company directly out of the fund and we have resources to be able to do more than that beyond it.
2:42:15
But that was a big part, you know, if we're high conviction in a company, we want to be able to do that.
2:42:20
>> There's not very many of those.
2:42:20
And so, you know, we have to use our time wisely.
2:42:25
>> Fortunately, given our brand and given our coverage, you know, we're able to see most things.
2:42:29
We're able to meet a lot of entrepreneurs.
2:42:31
Uh and so you know we we we see you know probably as a firm hundreds of deals or investment opportunities or companies a week.
2:42:41
>> Uh and then you know we have the you know we have the the luxury of getting to kind of matchmake with the ones that want to work with us that we think are really special.
2:42:48
>> You know after this I I just uh you know was texting with a founder and and he was like he kind of cracked open the door that he might do a fund raise and uh and I'm like great. All right.
2:42:58
I'll meet you in our office in a couple minutes.
2:43:01
in their office at 4:00 like you know we we got to do it.
2:43:03
So the way I try to spend my time is like you know the thing that gives me the most energy is to to meet those founders and make investments. >> Yeah.
2:43:11
Well, we'll let you get back to chasing deals.
2:43:12
Good luck with that particular founder.
2:43:13
Hopefully that founder will be on the show ringing the gong in just a few weeks. >> Yeah.
2:43:18
This uh I'm excited to see what what you do with this uh with this new fun preparation, timing, opportunity.
2:43:22
Uh this is uh going to be an amazing chapter.
2:43:29
>> Well, have a great rest of your day, David. Good to good. We'll see you. Cheers.
2:43:33
>> And up next we have Ben Horowitz, the founder of Andrews and Horowits.
2:43:35
The Horowits in Andrews and Horwits.
2:43:37
Ben, >> how are you doing? Welcome to the show. >> Good. How are you guys? >> We're fantastic. Uh, massive news today. Uh, congratulations.
2:43:46
Obviously, we'll get into the the uh the the the fun structure.
2:43:51
I'm sure we'll have a bunch of questions there.
2:43:52
I wanted to kick it off with a reflection on your book, The Hard Things.
2:43:56
The Hard Thing About Hard Things.
2:43:58
uh what is the one piece of advice that you think has aged particularly well from that? What has never changed?
2:44:04
And then maybe you could take me through some things that might have changed in this era, bigger companies, AI.
2:44:09
Uh what what uh what do you go back to and what do you maybe think uh needs needs an update. >> Yeah.
2:44:18
Well, I like I think it's still like really hard to be an entrepreneur.
2:44:22
Um, and one of my favorite quotes in in the book is uh something uh Mark said to me um you know when things were extremely bad.
2:44:31
He said you know one day we'll look back on this chuckle nervously and change the subject >> I think how it felt. Yeah. >> Yeah.
2:44:45
>> He would always say is things get darkest before they go completely black. >> Yeah.
2:44:49
I mean, I it's it's underrated how how long you two have been in partnership beyond just this uh this firm.
2:44:56
Uh you've worked together for so long. >> 30 years. >> 30 years. What a run. An overnight success.
2:45:02
A true overnight success if there ever was one.
2:45:04
Uh how is how how do you two like to work together now?
2:45:08
How how is uh how is the day-to-day working at the firm?
2:45:14
>> Yeah, I mean I think that uh it works uh pretty well.
2:45:17
I mean we have pretty different roles.
2:45:19
So I I run the firm and then um you know Mark is kind of uh in a lot of ways the face of the firm.
2:45:26
Um and he also you know he gets very deep on specific things.
2:45:32
So policy um AI are kind of the two things that he's like super focused on right now. >> Yeah.
2:45:40
>> Um and you know he has many many ideas about you know running the firm and I have many ideas about things he does.
2:45:44
Uh and so you know it's very collaborative I would just say and you know we we argue all the time about everything. >> That's great.
2:45:54
As any good >> part some sometimes he's right sometimes I'm right. >> Yeah.
2:45:58
Well uh how is the structure of running the firm?
2:46:00
How is the structure of the firm changing in this era?
2:46:05
Obviously the numbers are bigger but on the fundraising side but maybe not on the team side. What's changing?
2:46:10
uh is there anything that you've felt like this technology shift requires different management of the firm? >> Yeah. No, for sure.
2:46:20
I think that you know what's happened is where we have such a powerful new technology platform >> that the number of uh really important companies that will be created out of it has just multiplied. >> Interesting.
2:46:36
>> Um and you know look the the tech industry itself used to just not be that big. >> Yeah.
2:46:40
Uh and now the tech industry is all industry. >> Yeah.
2:46:45
>> And that change has kind of what really changed the architecture of the firm.
2:46:48
So originally, you know, we look like every other venture firm.
2:46:52
We were, you know, a team of venture investors.
2:46:54
You know, we were a little different in that we had a more elaborate platform. >> Yeah.
2:46:59
>> Um but now what we've done is we've kind of subdivided the technology market into all of its submarkets.
2:47:05
all of its submarkets. of you know infrastructure applications you know crypto uh early stage stuff bio these kinds of things American dynamism and each of those teams is basically looks like the original Andre Horowitz
2:47:23
but they're independent of each other >> and that enables us to both kind of cover the whole market in a very very serious way but also be nimble and not have I mean you don't want 20 people in a room talking about a Yeah, >> like you're not going to get to the truth like that. You know, just uh in my
2:47:39
You know, just uh in my management experience, it turns out you can't have a conversation with 20 people have a presentation.
2:47:46
H how do you think about empowering the firm or the sub teams to become subject matter experts and actually uh investigate and prosecute deal thesis uh in entirely new markets where no one in the firm might have ever done an oil and gas deal or a solar deal or some bio thing that's entirely new and you have a team but there's you know new markets forming and new markets coming online as potential transformation targets for technology.
2:48:16
ology, how are you keeping the firm sharp on every corner of the global economy?
2:48:22
>> Yeah, so a lot a lot of times, you know, there are super experimental things that we'll look at, um, but we don't necessarily kind of build the organization around yet.
2:48:30
Um, and then, you know, but once we commit the flag, uh, then that, you know, our big commitment would be, okay, we'll create a fund around it.
2:48:41
So, you know, we did that with crypto.
2:48:43
We made the Coinbase investment before we had the crypto fund, but then we as we got into it, we said, well, like this is going to be a larger market and it's super different than everything we're doing.
2:48:55
So, uh, we need to commit around that.
2:48:57
More recently, you know, with AI, um, AI like the way you build AI companies, the nature of the AI founder is just so different than everything that we've seen before that we ended up bringing in a lot of expertise from the outside.
2:49:11
We um kind of reoriented everybody on the inside.
2:49:16
Like we we actually had um you know a huge amount of training materials and like you know basically exams to make sure that you know everybody who was work on that was what we call a AI native and understood like all aspects of it before getting into it.
2:49:33
just because you know uh the these things do tend to be different and this is why you see a lot of uh people age out of venture capital and then a lot of kind of firms um be not what's they once were you know they they were very important in 2015 but uh they didn't necessarily make the transition they didn't bring in the right kind of talent. >> Yeah.
2:49:55
H uh do as as when you're managing the firm, how do you think about uh the dividing lines and the walls between different funds, we've seen just with just with the Neoclouds, a lot of those folks started as crypto companies.
2:50:08
Uh then they became AI companies, but they're building things at such massive scale.
2:50:14
I wouldn't be as surprised to see them in an American dynamism portfolio because they're kind of sort of re-industrializing.
2:50:19
So do are you the person that the firm that one of the subdivision leaders comes to to say I want this in my fund. Um how does that work? >> Yeah.
2:50:28
So so there's not that much conflict in that you know the categories are pretty clear.
2:50:34
Um there are you know it happens occasionally where where they bump into each other but >> you know for the most part it's like what are you really trying to do?
2:50:43
Uh and then the entrepreneur will gravitate towards one of the funds um based on what they're trying to do.
2:50:52
Like it we want to sell things to the government. >> Yeah. >> Okay.
2:50:57
That's likely going to go into American dynamism whereas like okay we've got you know eight PhDs in AI that's almost certainly going to end up in infrastructure. >> Yeah.
2:51:09
>> You know kind of model world and that kind of thing. Yeah.
2:51:11
And so you know it's really matching the the funds are you think about markets of entrepreneurs and the funds are designed to address that market of entrepreneurs and those tend to be fairly distinct.
2:51:22
Now sometimes uh you know people will try to game us and they'll get rejected by one part and then they'll go to >> okay >> we we have very very very good comprehensive data on everything we've seen.
2:51:37
We've got extremely good systems.
2:51:39
So we c we catch those people that's good to know.
2:51:41
>> When did you realize a $15 billion fund was possible?
2:51:43
Was it was it did you did you imagine this kind of scale was possible from from inception or or was it a did you build? >> Yeah.
2:51:52
You know, our first fund was $300 million.
2:51:53
So we definitely weren't thinking about it then.
2:51:56
You know, we thought 300 million was a lot.
2:51:58
And people, you know, thought we were raising too big a fund in 2009. >> Yeah.
2:52:04
Um but no like what we've done is we we've kind of looked at the markets and said okay you know how big is this market and then what kind of fund do we need to kind of win in that market um and generate a large return and yeah we tend to have a a relatively optimistic view of the future.
2:52:27
I think there are some like cynical VCs out there and like when I was a boy valuation weren't this high. Yeah.
2:52:32
She's like, "Play the game on the field." >> Yeah. Yeah.
2:52:37
We we like to look forward and not look backwards.
2:52:40
And so, as a result, like something, you know, I think we have done a good job of getting ahead of the game.
2:52:47
Like when we raised fund three, which was a billion dollars, we got a lot of criticism from other funds going like that's crazy.
2:52:53
You know, no billion dollar fund has ever returned money. Y.
2:52:59
And we're like, well, okay, but like the world didn't look like this and software is eating the world and things are getting bigger and we think that like we can deploy a billion dollars and you know that fund um you know had Coinbase and Data Bricks and uh and Lyft and um Digital Ocean and uh GitHub and like a lot of you big outcomes >> and if we didn't have that much money it'd be a problem. >> Yeah.
2:53:22
Uh on that on that note of optimism and understanding the scale of the internet as it eats the entire world, how did you process the bubble talk that took place uh in the back half of 2025?
2:53:37
>> Well, you know, I was a CEO during another bubble. Yeah.
2:53:41
>> So, I know a lot about bubbles.
2:53:44
>> Look, I I think that um so there's a couple things that that I learned from the bubble that we were in. One was >> Sorry. Sorry. bubble gun.
2:53:54
>> We keep a bubble gun handy. >> Yeah.
2:53:56
Look, well, you know, one of the things um if you look back at that bubble, there were there were a lot of things that um were present then that are definitely not present now.
2:54:06
So, like probably the biggest being the internet.
2:54:11
Everybody knew the internet was going to be giant.
2:54:14
>> Um but, uh at the time that everybody was investing all the money, the internet was very very small.
2:54:19
So if you go back to 1996 at Netscape, we had 90% browser share and you know we had $50 million in revenue. >> Yeah.
2:54:30
>> So the entire or we had 50 million users, sorry, 50 million users.
2:54:34
So that the entire number of people on the internet was 55 million. >> Yeah.
2:54:39
>> So like so you're funding these companies and giving them a $10 billion valuation selling into a market of 55 million people like and then half those were on dialup.
2:54:48
So was limited in what you could do.
2:54:51
>> And so those valuations were running way way way ahead of the technology uh is kind of what caused the bubble. >> Mhm.
2:54:59
>> You know, if you look at AI, the technology is like working and getting to the world right now.
2:55:06
>> Like how many people are on chat GPT?
2:55:09
And you know, how is that business going?
2:55:11
It had I think zero revenue in November of 2022.
2:55:13
And I don't know what the current number is, but it's probably between 15 and 20 billion. >> Yeah.
2:55:19
>> Um like we've never seen that before.
2:55:19
So the things are working like the things that that that >> that were bubbleicious in uh 99 aren't quite the same.
2:55:28
But you know, to me the biggest thing uh that I learned was right before the bubble burst, nobody thought it was a bubble.
2:55:37
>> Um Warren Buffett, who had never invested any in any tech in early 2000s, started investing in tech. >> Wow.
2:55:44
So everybody capitulated and agreed prices would never go down.
2:55:46
Like that's what you need to get to a bubble.
2:55:49
It's a psychological phenomenon, you know, not a uh not a financial phenomenon.
2:55:53
And so, you know, right now with everybody talking about a bubble, it's like, "Oh, great.
2:55:59
We're not in a bubble because it's when nobody believes it's a bubble that it becomes a bubble."
2:56:05
Same with the financial crisis.
2:56:06
By the way, if you look at the price uh you know, the kind of interest you'd pay on like home loan debt >> in in uh in 2007, it was the lowest in history. >> Yeah.
2:56:20
>> Right before it all came crashing.
2:56:22
>> It should have been the highest >> right before everybody defaulted. >> Yeah.
2:56:25
>> You know, it was the lowest in history.
2:56:27
And that's because it was a bubble because everybody believed, hey, they're not building any more land anymore.
2:56:30
You know, like that's that's what's going on.
2:56:34
And so once you get into that kind of psychological convergence, yeah, >> that that's when you really get into like a really crazy bubble.
2:56:40
Now, look, in venture capital, >> um, everything is always priced at either half or double what it's worth.
2:56:48
Like that's the that's the steady state.
2:56:51
>> And so, are there going to be things that are, you know, priced way too high? Yeah, of course. Mhm.
2:56:56
>> Speaking of land, uh how are you processing the move out of California, the the news in California of the wealth taxes?
2:57:04
It a lot of folks are saying, you know, California might shoot themselves in the foot, kill the golden goose.
2:57:09
How have you been processing the news? Yeah.
2:57:13
I mean, so it it's very kind of like an interesting kind of view of the world.
2:57:18
I think that that that the you the groups in California have been kind of pushing this idea.
2:57:24
So, you know, we I go all over the world.
2:57:27
I've met like in the last year, you know, the president of Mexico, the president of El Salvador, um you know, the crown prince of Saudi Arabia.
2:57:39
So, like I'm always with world leaders or I've spent a lot of time with them and they always want to know like how do we create Silicon Valley here?
2:57:47
>> Um, and when you look at >> we want a golden goose.
2:57:50
>> We like your golden goose. We want one.
2:57:52
>> It's it's pretty remarkable that like we've repeatedly created companies with larger kind of GDP than most countries.
2:58:03
Like routinely we've done that.
2:58:03
Um, and so rather than asking like how did we do that?
2:58:10
It's like, well, how can we like rearrange it and, you know, run an experiment and see if it destroys it or not.
2:58:17
>> And so I I think that's probably the weirdest part of it for me that people would think about it that way.
2:58:22
Look, I mean it like look if you start confiscating wealth and you know taxing um unrealized capital gains for people who aren't liquid like so so actually we saw this in Norway.
2:58:35
So Norway has an unrealized capital gains tax and if and Norway's got like a lot of extremely smart people, great entrepreneurs, but they all left.
2:58:45
And when you talk to entrepreneurs in Norway, um they're like, "Well, I literally can't pay the tax uh because the the the company got marked up to whatever, a billion,$2 billion dollars and I own a lot of it and I can't get that money out. It's a private company." Yeah. >> And so I'm stuck.
2:59:05
So I I have to leave the country.
2:59:07
And there are no entrepreneurs.
2:59:09
There is basically no tech entrepreneurs in in Norway now.
2:59:10
And if you wanted to get, it's been so hard to break the Silicon Valley network effect, but this is the best strategy I've seen.
2:59:19
If you wanted to wreck the California tech eos, >> how are you processing?
2:59:25
>> how are you processing? How it feels like today we have this incredible optimism within the technology industry this incredible excitement and then outside of the technology you know your neighbor or somebody nearby has like this there's feels like this real tension and kind of fear from broader
2:59:42
society about the work that is being done within the technology industry and you see interviews that uh you know AI leaders will give where they'll say we're we're summoning the demon or or they'll say you know you know >> not the most optimistic story tellers we're going to end the the world will end, but we're going to create some great companies. So, I think people like
2:59:58
So, I think people like this the these these interviews and these quotes spread so quickly.
3:00:02
A lot of people have heard them and the question from the broader populace is like, hey, do we need to do this?
3:00:09
>> That's the optimistic vision. >> Yeah. Do or can we stop? Right.
3:00:10
Uh and and obviously technology is, you know, proven to be uh somewhat inevitable, relentless. >> Yeah. Yeah. Yeah.
3:00:22
So I I think the good news is it speaks to the importance of the moment.
3:00:26
So this is on the order of the microprocessor, the steam engine or something or electricity or something like that.
3:00:31
So and those things all turned out to be like really good for humanity.
3:00:38
>> Was there that much with with with electricity?
3:00:40
Was there like the level of fear?
3:00:44
Because there was people that would like go and obviously I know the stories of people that would like their job was to write the light the lamps, right? But Oh yeah.
3:00:52
Like if you go back and read about the beginning of electricity, it's wild.
3:00:56
Well, they made a law when automobiles first came out, there was a law in the United States that said if you're driving your car and you see a horse, you have to stop the car, disassemble it, and wait for the horse to pass.
3:01:12
>> Disassemble >> like like it was that level.
3:01:13
That was the regulatory idea.
3:01:14
So yeah, I mean I think it by the way watches were the same.
3:01:20
You know, when watches came out, there was like huge fear that like people would never be able to have a conversation again because they'd be just checking the checking the time always watch.
3:01:32
>> So, you know, these technologies like generate a lot of fear, but I think that, >> you know, the good news on it is, you know, this one is really important.
3:01:38
I think that the impact into the well-being of humanity is going to be bigger than certainly anything in my lifetime.
3:01:45
lifetime. And you know one of our bigger problems I think is there are people in the industry going for regulatory capture who kind of feed into the >> fear to the fear and then look there are also people who have just you know it's moving so fast it is actually freaked them out who are working on it and that's um >> how do you advise how do you advise uh portfolio founders or or even people at at the firm around processing noise I
3:02:13
think historically you know uh there wasn't like this constant chatter right we have like X now which is like a constant you know stream of consciousness from millions of people that are sharing their opinion and uh it's you know I know a lot of
3:02:27
entrepreneurs that uh you know one day everybody's saying that they're the greatest thing ever and then the next day uh you know people start to criticize and and how do you kind of like uh what's your what guidance do you give there? >> Yeah. Well, I think that like the world >> Yeah.
3:02:40
Well, I think that like the world of media changed and it's I I think it's tricky for people and companies to process because if you grew up in marketing um or in old media, your whole concept of the laws of physics is different.
3:02:57
Um so in old world you were always thinking defensively because there were there were very few channels to get your message out.
3:03:04
The format was very tight.
3:03:07
Um, you know, you could get a quote in here, you could get a few sentences before the host cuts you off or whatever. >> Uh, yeah.
3:03:14
You know, you guys watch CNN from time to time.
3:03:19
>> And so, like, in that world, the way you would think about media is just like, let's make sure we don't say the wrong thing.
3:03:25
Let's spend hours and hours crafting the message and so forth.
3:03:29
>> You know, in the new world, it's like wide open.
3:03:30
Um, there's media everywhere.
3:03:34
>> Uh, the formats are whatever you want it to be.
3:03:36
And so the right kind of way to think about it is you have to be interesting and don't worry about making a mistake because you can just come back tomorrow and flood the zone, you know, like just keep going.
3:03:48
>> Uh and that uh I think it's I found it very very difficult to reorient somebody who has spent a career in old media world kind of thinking in a new media way.
3:04:02
Um, and so the biggest thing that like I really talk to our CEOs about is like you've got to approach the you have to approach new media with new media thinking, new media people, that kind of thing.
3:04:15
>> And uh it it really it it's a remarkably opposite world.
3:04:22
>> It's like, you know, it's like you're landing on Mars and you're like, well, what the happened to gravity?
3:04:26
You know, >> different >> and you can't even say, well, no, gravity's different here.
3:04:30
because it's like no no gravity just is like I can't deal with the fact that that's just that's just the truth. >> Yeah.
3:04:40
>> Well, uh we would love to keep talking about media.
3:04:42
Very few things that uh that uh that we should bring the gong >> but we know you have a late you got late fees if you're late to meetings.
3:04:48
So this gong is for the whole >> A6 team.
3:04:54
>> Congratulations and uh we won't keep you any longer but come back on again soon and and congratulations.
3:04:59
Thank you so much for taking the time to see you guys.
3:05:03
>> We'll talk to you soon. Goodbye.
3:05:06
>> And uh with that, we need to check in on the Claude codes.
3:05:11
>> Eric just said that uh that they're good for the 10 bucks.
3:05:13
Torberg, >> he's got a you know, he's one minute late to his next meeting. Late >> fee. Oh, yeah. Yeah, that's right. That's right.
3:05:21
They have they have a late fee. >> Yeah.
3:05:23
For those for those that don't know, uh and partners, if they're late to uh if if they're late, >> they have phones, too.
3:05:28
If they have phones out, they get fined. >> Yeah. No, but it's late.
3:05:31
If you're late to a meeting with a founder that you're looking to invest in, >> uh, or you're just meeting, you got to pay if you're late.
3:05:37
So, >> uh, well, we should check in with Tyler.
3:05:41
Uh, there was some rumblings about a change to claude code.
3:05:43
Can you >> So, basically what happened was, um, >> okay, so, so when you get a cloud subscription, right, there's pro and max. Yeah.
3:05:52
>> Um, >> you get like, uh, claude code credits basically. >> Sure.
3:05:56
Um, and so what was going on was was there's like third party harnesses.
3:06:00
So there's one open code.
3:06:00
There's like a bunch of these.
3:06:01
Um, and they would basically use the the credits that you get from cloud code or from your cloud subscription like use and it's like they're like um you know open source agentic harnesses, whatever. >> Sure.
3:06:14
>> Um, >> so Anthropic stopped that.
3:06:15
So you can't use your bas you can't use your subscription uh as like the credit.
3:06:20
So you have to use the actual API. >> The actual API. >> Um, okay.
3:06:24
>> That's like the main thing.
3:06:24
It's like not to me it doesn't seem that crazy of a thing because you can still use it with API.
3:06:30
It's more >> Is it Is it an exchange rate thing maybe?
3:06:33
Like if I'm on Claude Pro or Claude Max, am I getting uh on the on a per dollar basis more tokens than I would if I Okay. >> Yeah.
3:06:43
That's why um there's like a lot of arbitrage, right?
3:06:45
Because >> they were getting arbed.
3:06:46
They said no more arbing us.
3:06:48
>> You can think of like uh cloud code is going to get much better if more people use it, right?
3:06:52
Because it's like an RL environment, basically. For sure.
3:06:53
So the the value of the data.
3:06:56
>> So they shouldn't be incentivizing people to go elsewhere, but they are still allowing people to go elsewhere just at the at the consistent API.
3:07:04
>> So you can still like it's like bring your own key. You can do that. >> Okay.
3:07:06
That doesn't seem like too >> it's not that crazy, but people are very mad.
3:07:09
They're canceling their cloud.
3:07:10
>> People are mad mad at Claude. So sad. >> Uh oh well.
3:07:14
Um I'm sure that they will figure it out and uh the uh the fun will um will continue.
3:07:20
Uh, we do have to cover another story in the AI world.
3:07:21
Uh, Logan Kilpatrick, friend of the show over at Google, he said, "I'm happy to share that we, the Google AI studio team, are now sponsoring Tailwind CSS, the project that had to lay off three people and it was very dramatic because it was 75% of the team, but their business model was not really working because they were selling templates, which of course could be assembled by AI agents in the modern era." I love this.
3:07:49
Logan said, "Honored to support and find ways to do more together to help the ecosystem of builders."
3:07:53
And I said, "You dropped this king."
3:07:55
And I gave him the Mario holding the crown.
3:07:58
If you scroll down, you should see it.
3:08:00
>> Uh yeah, this is great. >> That's me.
3:08:02
>> I expected this I expected this to happen pretty quickly.
3:08:03
I'm glad uh I'm glad Logan made this move and I think a handful of others did as well.
3:08:08
So >> uh hopefully Tailwind can hire back the uh handful of engineers that they were forced to let go. Yeah.
3:08:15
Uh and uh yeah, this should give them some more predictability while they figure out uh the next chapter. >> Yeah.
3:08:24
Well, uh in other news, OpenAI is reserving $50 billion for a stock grant pool.
3:08:29
Uh >> Jack Rain says 500 billion company doing 13 billion in revenue, projecting 50 billion in equity comp is so good.
3:08:36
So price >> of SF real estate is going up.
3:08:39
uh price of the the AI research are going up but they have the money to uh to distribute.
3:08:46
Uh that is a big equity pool uh but it's an opportunity to join preipo get some shares and uh hopefully do well for yourself.
3:08:53
Well, thank you so much for watching the show and tuning in today.
3:08:57
We will be back in the books Pacific on Monday >> only podcast and subscribe to our newsletter at tbpn. com.
3:09:06
And with that, we'll say goodbye and have a great weekend.
3:09:10
>> Have an amazing weekend.
3:09:11
>> Thank you for watching. >> We love you. >> See you Monday. Goodbye.