OpenAI Launches Codex, Meta Delays Llama 4 Behemoth | Matt Grimm, Kevin Weil, Blake Scholl, Tim Fist, Chris Best, Sean Henry

You're watching, brother. Today is Friday, May 16, 2025. We are live from temple of Technology.

The fortress of finance, the capital capital.

This thing going in my mouth is really bad.

Yeah. The amount of microplastics going into our mouth right now, terrible.

Anyway, we got a great show. We got Matt Grimm coming on to the show. Andrel just did the Murph challenge. He's going to break it down for us. We got Kevin Wheel from OpenAI, Blake Shoal from Boom Supersonic, Tim Fisk from IFP, Chris Best from Substack, and Sean Henry from Stored. Some legendary founders, some legendary folks, some yappers, some commentators. We got a great show. We're on the news. But first, let's bring in Matt Grimm if he's in the studio. If not, we can show you some photos. Oh, here he is. How you doing?

Hey, guys. How are you?

Fantastic. Looking great. Can you break it down for us? What's going on today? How did it go?

It went. It was a great day. I'm here with Chris Wiley. Chris Wiley is the executive director of the Lieutenant Michael P. Murphy Navy SEAL museum. So I wanted to give it a second to Chris to talk about what the merch challenge is, why we do it, kind of the story behind it, and a little bit of Lieutenant Murphy's history. So.

Sounds fantastic.

Thank you for having me on. So what we just accomplished today was a 1 mile run, 100 pull ups, 200 push ups, 300 air squats, and another 1 mile run, all wearing a nice weighted vest, as you can see.

There we go.

Yep.

But the whole history behind this was that it was Michael's favorite workout when he was deployed. We don't deploy with gym equipment, so you have to kind of improvise and find what you can can use in your area so you can have a good workout. If everybody doesn't know the story of Lieutenant Murphy, the blockbuster movie the lone survivor with Wahlberg and Taylor Kitsch, that was the portrayal of operation Red Wings and how Michael stepped out into a hail of bullets to make a phone call to try to save everybody. So ultimately receiving the medal of honor after he died that day. And just a great workout and a great way to remember all that have sacrificed. I'm sorry. And suffered.

Yeah.

Our own little discomfort today during the Murph challenge.

It's awesome. How long has this been going on? Anduril's been a part of this for a couple of years. But can you break down some of the history of this particular event?

So what happened was after the Helicopter pilot recovered Michael and the other guys on that mountainside. When he got back home, he heard of Michael's workout and then started doing it on his own, calling it the Murph. And it spread so quickly through the local CrossFit gyms. And then it became too much for him to handle and then he involved the family. So this has been going on as the Murph challenge for about 12 to 13 years now, and it's just growing every single year. We're hoping to continue having this grow and have the partnership with Anduril because they're amazing, amazing partners and people here. It's been such a touching event today.

That's amazing.

Can you talk about Anduril's role here? Is this just a bonding event for you guys? Is this for the charity? How are you thinking about Anduril's involvement in your hand? How many people from Andrew came out for this?

Well, today we had about 150 and Aurelians come out. And it's. For us, it's not just about the team bonding part. That is certainly a part of it. You know, kind of team morale, team bonding. And a team that works together, sweats together, stays together. So that's certainly a part of it. But more importantly than that, like, we started Anduril to bring the best possible technology to those who serve in defense of our freedoms and our nation and our allies. And a part of that extends to supporting the veterans community. So we've been pretty active in supporting the veterans community through a couple different ways that I can talk about in a couple minutes. So today was less for us about the morale piece and more about a sort of a signal or a moment to celebrate our veterans, both that work at Andoril and in the community at large. And our partnership with the Murph foundation and with Chris himself and all of that is just a symbol of that.

How'd you wind up doing, Matt?

Yeah, I got.

I tried to do it with you over Christmas break and I got crushed.

Well, you guys don't even look like you broke a sweat. What's going on? I appreciate you gonna do another one now.

There were 150 of us out there and I noticed there were two empty vests out there on the front. So if you guys want to step up next year, we'd be happy to have you and you can come out with us.

We'll do it live.

Yeah, I did like three pull ups today, so I'm getting there.

You were repping, I think I did.

A couple sets of Five, but not quite at the hundred in a row.

Exactly. To me about, for your time and thanks for the partnership and your service and everything you do for veterans.

Thank you, Chris, so much.

Yeah, thank you.

Cheers.

Awesome. Matt, talk to me about the role that veterans play at Anderall. People think tech company, military. Obviously there's discipline overlaps, but a lot of times there's not so many immediate skill overlaps. Or do people have that wrong? Are you hiring people? Software engineers from the military? Are you hiring hardware engineers? Are you hiring operators and finance people? What are the different types of roles that veterans are filling at Anduril today?

Yeah, happy to talk about all of that. So we've been involved in the veterans community since day one of the organization. One of our co founders, in fact, is a veteran himself and has helped kind of lay the foundations for those partnerships. Right now, about 12, 13% of our employee base is veterans, which is wildly over the national average, and it's certainly higher than that in the Silicon Valley kind of technology community. We have a, we have a partnership with a great organization called Skillbridge that's a program run by the DOD for helping veterans transition. We have a couple of recruiting relationships with, targeted to that kind of transitioning veteran kind of community. And we hire across all roles, everything from kind of field op, field ops technicians who are installing our products and training users in the field, some of our maintenance and repair technicians, some of our production technicians on the factory floor building products all the way through some design engineers, MechIs and EES doing work. Yes, we have some coders, some CS folks who are from, from the veterans community and all the way up into the leadership ranks. You know, of our, of our leadership ranks, we've got a pretty high veteran representation, everything from flag officers to retired colonels through, through the whole ranks. So it's a big part of our, part of our culture. It's a big part of our kind of the mission of the company and something that we're proud to support. And beyond that, I would say that we frequently raise some money for veterans charities. We've got a couple in particular that we support. I've got my, my, my notes here in front of me. With Veterans Day last year, we had our first big public launch of the SWAG store and we had a swag drop that raised about 60,000 some odd dollars that went to a Blue Star Families Foundation. A good teaser for you. Breaking news here on the Technology Brothers Podcast network. We're launching our next swag drop on Memorial Day in about 10 days.

Let's go.

We'll be raising a whole bunch more money exactly. For the foundation that Chris runs in Lieutenant Murphy's honor. So everybody be, be, be on the lookout for that. We've given some money to a great charity called Warriors Afield that is actually run by one of the Anduril executives that specializes in helping veterans kind of in, in distress, kind of going through some bad times by doing some mentorship and some outdoor activities and wilderness adventures and hunting and that sort of thing. So trying to build some bonds there to help veterans who are in a tough spot. So we've been, we've been very active through all the years on all this and something that we're looking forward to continuing doing and scaling as the company grows.

Okay, give us a take about how to get a job at Anduril.

Well, we've got a great website, you know, anduril.comcareers. but more importantly than the obvious just apply on the website line is like, we look for people with a real mission drive. We look for people who are really driven by the call to service, who are really interested in protecting American values and our allies values and the escalating arms race that is happening across the world, whether that's artificial intelligence, whether that's drone technology, whether that's any sort of the kind of the next generation of what the war fighters are going to face in the battlefield. Like, we look for people who are just really motivated and really driven and want to come honestly grind and work hard on really challenging and rewarding problems to help defend our country. So the number one thing you could do if you're interested in a job at Anduril, obviously apply, but more importantly is build up that skill set. Build up that engineering skill set, that problem solving skill set and that mission drive. And that's who we look for.

That's fantastic. Jordan, you got anything else?

No, this is great. We got to come out for the next one.

We got to start working. I mean, I think it's doable. I don't, I think I would have died this year, but I think I could do it next year if I start training today.

John.

The winners today finished in our, in our women's division, she finished in about 45 minutes. Are in the men's division, he finished in 35 minutes, a mile run, 100 pull ups, 200 push ups, 300 squats, and another mile run in 35 minutes, which is, uh, totally ridiculous and, and very impressive. Um, and then me, myself, I finished in about a, about an hour and 11 hour and 12 minutes.

Uh, bad.

You had three vests on, but.

But finished it with the full vest, full reps, all of that. Pretty, pretty, pretty.

Happy day.

That's amazing.

Dog. Absolute dog.

Well, congratulations. Thanks for popping by. Uh, love to have you back and talk more, but enjoy the day for sure.

Thanks for putting this on. All right, cheers.

Bye. I think it's time we take off the mustaches and get down to business.

Yeah, I thought it might be fun to do a little bit of the news in a mustache.

Okay, well, you can stay in a mustache.

I'm personally going to keep mine on.

A little bit, John. Well, first up, we got Sam Altman with a big announcement. OpenAI is introducing Codex. It's a software engineering agent that runs in the cloud and does tasks for you, like writing a new feature or fixing a bug. You can run many tasks in parallel. Starting to roll out to ChatGPT Pro Enterprise and Teams users, and he sends some more info. I think this is interesting because I had this crazy experience with oh3 the other day where I wanted to know how. How high a desk was actually on the Pat McAfee studio. So I was looking at. So I took a Screenshot of Pat McAfee standing and I. And I said, okay, look up how tall Pat McAfee is and tell me how tall is his desk? Because he seems to have a good point where he stands. Yeah, yeah.

When you were doing that, when.

Oh, when I was thinking, yeah, is a stroke. But. But this is what was crazy is that I thought. I thought it would just, like, look at the image and just kind of guess. It wound up writing, like, hundreds of lines of code, interpreting the pixels in the image and looking at different elements of the image to decide. Okay, well, there's a. He has a Coca Cola there. This is how tall a Coca Cola is. Let me expand all this just to find that it's just a normal sized desk. It's just a standard desk, which is like 36 inches.

Can you imagine giving that task to a human to say, like, can you kind of figure out how high this desk is?

Yeah.

And they go and they write hundreds of lines of code and you're like, I guess a good job for going above and beyond, but, like, a simple estimate would have been fine.

And I also. And I also had an interesting experience where today I kicked off a deep research report asking for some top news and put together some news of the day, like, what should I be thinking about?

About?

And the deep research report asked me, hey, do you want me to run this once, or do you want me to run this just like every day or every week? I'd be happy to do that for you. And I was like, oh, wow. It just. It just volunteered to do it on a cron job, which normally you would have to write about anyway. Any other takeaways from the OpenAI launch? We're talking to Kevin Weil in a.

Little bit, but I don't think this should be a huge surprise to anyone. We, you know, we talked with.

Probably.

A few weeks ago at this point, and she just said, look, to understand where the labs are going, understand what they value, what they find important. CodeGen has always been one of those things. So this launch should not be a surprise to anyone. But I'm excited to get in deeper with Kevin.

Yeah, I mean, so many questions for him, but I like this idea of the front door to AI. As the foundation models commoditize, it becomes more about the being the front door to the Internet. Are you just laughing at your own mustache? Are you laughing at your own mustache? Laughing at your own jokes? Normally you think I'd be laughing at you. Every once in a while I look over at the bottom, I just try to catch up while we're talking and I just crack up. Or. Yeah, there's other stuff.

Well, I didn't really get it. We went right into this, like, formal interview, which normally we would have had a bit longer to laugh at her ourselves. So anyways, sorry, I think you look great.

In fact, I'm not laughing because it's so convincing. It looks natural. It's growing on me. It's just normal. Anyway, the. The front door to AI, like, they are building a new Google where it's this front front door to knowledge engine stuff, but they need the front door to code gen as well. And so this new paradigm of, you know.

Yeah.

And the interesting thing that runs the cloud. I highly doubt Kevin can comment on this today, but the immediate question I have is how does this integrate with a potential Windsurf application? This makes me think that Windsurf might end up continuing to be a standalone app.

Yep. And so, yeah, I mean, it's really blurring the lines. Like, I didn't know that I wanted. I didn't know that I needed code to decide how tall a desk is. It decided that for me. And I really like that as a product evolution where eventually you go to a. You. You open the OpenAI app and you ask for something and it decides, do you. Do we need to do code for this? Do we need to do an image model. Do we need to use 4? Oh, do we need to use 303? Do we need to use deep research? Like it should decide for me. That's a really cool.

This is why I've always said I don't think OpenAI cares about naming because they're always.

It's going to get tough time horizon.

They're just going to do all the routing based on understanding what is required.

Anyway, on the flip side of AI, we have another post from Didi Das. Meta will delay its biggest AI model launch. Llama for behemoth 4 reasons highlighted doesn't perform well internally. Huge reorgan AI leadership. 11 out of 14 researchers on llama have left. And we saw that funny post where someone was saying like, I was on the Llama team, I worked on llama 1, 2, 3, but not 4. And they put that on their resume on LinkedIn. Brutal. All this after admitting that they gained some of the benchmarks. Glad, glad Meta can afford to light billions of dollars on fire for open source. And so this is an interesting like discussion for me because I think that, I don't think open source will win. I think you need to build a product around it. But at the same time, when we talk to people like Aaron Ginn, I think it would be amazing if America had a rock solid open source offering that was hard coded, you know, or baked into the weights with American values. And that was an option for, for countries that are maybe deciding between American China. I want them on my team.

So hard to understand what Llama's real enterprise adoption looks like. Yeah, right. You don't hear a lot about companies, at least to date.

There was a big boom for a long time. I think, I think the answer lies in that open router data. Yeah. And there are a lot of open source models running. They're kind of unclear. The Wall Street Journal has more deep dive here. Meta is contemplating significant management changes to its AI product group. As a result, its performance has been hobbled by training challenges. And so there is a take here that's like they believed almost too much in scaling laws. Right. Because Behemoth is this massive model. I think it's the biggest context window. Even bigger context window than what Google's offering. It's a huge parameter model. What is it? Billions of active. 288 billion active parameters. 2 trillion total parameters. We used to be in like Falcon 9B was like exciting. 9 billion parameters. We're now up in 288 billion active parameters. 2 trillion parameters. The Circle has gotten so big, from the GPT3 circle to the GPT4 circle. We are now with a massive circle that's covering everything. But we're not getting better results just from pure scaling because you have to add that RL layer on top that post training. And that's what OpenAI has been really, really good at with the O models. And that's what Deepseek got right as well with their R1 model. The reasoning on top. And it seems like they.

Yeah, I mean, the main thing here is despite having effectively infinity resources, they're struggling on the team side.

Yeah, it seems like they actually did cohesion.

There's a lot of churn. There's former employees that clearly were talented that are going out and saying, like you said, I wasn't involved in this thing, feeling the need to publicly state that they didn't play a role in that. And so it doesn't matter how much money they have to spend and what their capex looks like if there's not real cohesion.

I've been thinking about this because the whole meme with pre training was scale is all you need. Just keep scaling the number of tokens and energy and parameters and, and anything that go. Data that goes into the model. Right. Just 10x everything 10x that. And then 10x it again. And then 10x it again.

You're only a few 10x's you're only.

A few 10 from AGI. And that was, that was very clearly not the case. It. The. The scale. Scale was not all you needed in a singular context. The, the exponential chart was secretly a sigmoid curve.

Right.

It would, it would go exponential and then it would flatten out and see diminishing margin returns. And I think that that's true in life. I think that's true in, in so much technology development. You need to be on the sigmoid grind set. You need to be understanding that you're going to go through bursts of explosive exponential growth, but those exponential growth periods will stop. I mean, we've seen this with the show. Like when we first started, quote tweeting, just printing out posts and quote tweeting. We saw exponential growth in the follower count of the show and listenership. And then eventually we played that out and then we got to a plateau and then we said, let's do guests. And then we saw another one and now we're gonna come up with the third act, the fourth act, the fifth act. And you have to be constantly reinventing yourself, finding new paradigms and if you're in artificial intelligence. You can't just say, I'm going to rely on the pre training scaling law holding forever. You need to go into, okay, how do we scale up reinforcement learning? How do we scale up tool use? How do we scale up product use and product functionality to make this a really, really great product? You're not going to get there purely on one single curve. The arc of technology throughout history has always been a series of S curves. There's been the semiconductor boom, the Internet boom, the mobile boom, the AI boom. And if you want to make money or participate or understand the, the, the role of technology as it's evolved over the past 60 years or 100 years, you can't just see it as one linear exponential, like one exponential graph. It looks smooth when you zoom out. When you zoom in. It's actually a bunch of S curves.

Yep.

There's, there's a boom where everyone's like, mobile is going to the moon. If the trend continues, there will be 10 trillion mobile devices. And then what happens? Oh, it's a couple billion. Because there's only a couple billion people, right?

That's right.

And that's just the, that's just the way it goes anyway, staying in mobile. Let's go over to Tim Sweeney. He says, Apple's app review team, we.

Have to, we have to flag.

Oh, you want to flag Z. Okay.

Which is just wild. So Z says, did they seriously name it Behemoth, the quintessential creature only God can tame from the book of Job and then give it the demon branding. And I got to say that the, the branding here is a real photo.

That they use in the journal too.

Yeah, it is.

What? Crazy.

It is a crazy asset. I mean, you got to respect the development of the delts of the demon. I mean, but it's still.

We were talking about that with, with Orion. Right? Like, like, like, like the story of Orion. Right.

It's actually the most crazy brand asset that you could choose for something like this. It's like, how do we make this as scary as possible for the average meta platforms user?

Yeah, so, so, so Facebook's meta's latest virtual reality augmented reality headset, the glasses that everyone's raving about is called Orion. And the Greek myth of Orion tells the story of a mighty hunter, sometimes portrayed as a giant, who was eventually killed and placed in the sky as a constellation. It's like the worst possible metaphor you would want for a giant tech company trying to do something new and ambitious. Right. It's a very, very weird Pick. But he thinks about the Roman Empire all the time, so maybe he's interpreting that myth differently. And there's a different reading, but I would love to know how they wound up with that. But different versions of the myth detail his life and death, including how he was blinded, restored by his sight, his sight by the sun, and possibly killed by either a scorpion or Artemis, the goddess of the hunt, due to jealousy or a trick up by Apollo. And so like if you Behemoth, the metaphor of Orion, it's like it's not good for Behemoth.

And Wikipedia is a beast from the biblical book of Job and is a form of the chaos monster created by God at the beginning of creation.

A very weird choice. You should actually, you should just call it 6.7B2. That's fine. We like those names. Let's just stick with those names. Yeah, is a great Orion 3 is a great name.

Ryan and Behemoth sound cool.

Yeah, they sound cool until you peel back any real. The true metaphor is like bizarre. And so yeah, Behemoth has not only been a very large model, but it has been a very large problem before. And it has been hard to tame and hard to get to produce fantastic results over there. But good luck to the team over there. Hopefully there's some new blood, some new folks come in and they produce a great, fantastic product for the meta team. We're rooting for you anyway. Let's go over to Tim Sweeney. Apple's app review team should be free to review all submitted apps promptly and accept or reject accordingly to according to the plain language of their guidelines. App review shouldn't be weaponized by senior management as a tool to delay or obstruct competition, due process or free speech.

And so Naval said, Apple continues to mock the court.

So this is of course Apple should need to approve Fortnite because Fortnite has a third party checkout where you can go and buy Fortnite v. Bucks without paying the 30% app store fee. Of course, you have to go off the app and there's a pop up warning that comes up and Apple's being very aggressive about that. But Apple is pushing the limits. They are. They're going one mile an hour under the speed limit. It's certainly not the spirit of the law, but they are following the letter of the law. Or at least they would argue that. And who knows, maybe there'll be another court. Another. Another battle in court.

But anyway, no, this feels like they're setting themselves up for another potentially separate lawsuit around the approval process. Yeah, the approval process because Epic can, can actually say this is costing us. Yeah, this might have cost them already nine figures. Totally right. You can imagine when it goes back in the App Store the amount of the flood of demand and new revenue and so delaying that by even you know, a few days would be, would be damaging. So yeah. Unfortunate.

The Wall Street Journal says Epic Games Fortnite claims Apple block submission now unavailable on iOS the the latest in a long running feud between Epic Games and Apple. The legal began. So I agree with you there could be another case. But do you know how long it's been for the first case? This is we're coming up on the five year anniversary. It started in August 13th of 2020. Epic implemented a direct payment system within Fortnite's iOS version, circumventing Apple's 30% commission fee. This action violated Apple's App Store guidelines leading to Fortnite's removal from the App Store. In response, Apple Epic filed an antitrust lawsuit against Apple in the United States District Court for the Northern District of California challenging Apple's restrictions on alternative in app payment methods. It took five years and so yes, they might have taken a couple pennies or millions of dollars out of Fortnite's pocketbook by delaying a few days. But if they can turn this into a five year lawsuit, that's five years of, of 30% fees. Right?

Yeah.

So that could be. The calculus is like yeah, let's just, let's just, let's just play the court game. That's fine.

Crazy.

Anyway, other news. Hostile Novo Nordisk has their CEO has stepped down. This is the maker of Ozempic and the stock has been on an absolute tear. I would love for you to pull it up on public let me know what it's doing. But we have, we have a post from an I'm on a non risk addict.

You're saying a tear downward, right?

Well it was on a tear upwards for a long time during the GLP1.

Boom but it's down 50% over the last year.

Oof. Yeah, not good. So yeah, maybe makes sense. But a non risk addict has a take here. No idea if he has done a good job as CEO or if the change makes sense based on expectations going forward. But firing a CEO for highlighted reasons is obscene. Novo traded at 50xpe. The market going crazy and then being a little less so is not the CEO's fault. So if you're running a company and it becomes kind of a meme stock and it runs up to an insane multiple and then it pulls back a little bit, but you're still way above where you started as CEO. Can you really be hit with, hey, the stock's down 50%. We've seen there was Palantir. Palantir was extremely hot. And then of course it pulled back a little bit. We see this with Tesla too. Tesla pulled back a little bit, but it's still like a really solid company. Really, really incredible market caps and great private, great price to equity ratios. And so the highlighted reasons here are. During his eight year tenure as CEO, Novo Nordisk sales, profits and share price have almost tripled. Novo Nordisk has clear strategy, a strong portfolio, product portfolio and an experienced leadership team. The changes are however made in the light of recent market challenges Novo Nordisk has been facing. And they have, there are. Because this is an older technology. As we talked to some of those biotech folks, we've seen that there has been more competition than usual. Normally you create some breakthrough, you're able to lock it down for years. That hasn't been the case in the GLP1 scenario.

Hyper competitive from not only other scaled pharma companies, but the, you know, the.

Compounding and considering the recent market challenges, the share price decline and the wish from Novo Nordisk foundation, the Novo Nordisk board and Lars Fuergaard Jorgensen have jointly concluded that initiating a CEO succession is in the best interest of the company and its shareholders. Yeah, very rare that you see a CEO go out while the stock is still trading at 50 XP, doing really well overall, even if it is down 50% recently. I mean that's not good. But anyway, you know what Nova should do? They should get a ramp. Obviously that should be the first thing that they do with the new CEO. They should bring in ramp, ramp, ramp, ramp, ramp. Time is money save. Both easy to use, corporate cards, bill payment, accounting and a whole lot more all in one place. They should also be using figma. We should talk about figma. Think faster, build faster. Figma helps design and development teams build great products together. You can get started for free.

The best Figma is figma. For Figma, you can do a lot with it. You can generate marketing assets, you can generate apps, you can create websites and a whole lot more. Yeah, thank you to Figma for supporting the show.

They should also get on Vanta Automate Compliance. Manage risk, improve trust continuously. Vanta's trust Management back takes a manual work out of your security compliance process and replaces it with continuous automation. Whether you're pursuing your first framework or managing a complex program. Anyway, thank you. The other news is semianalysis is talking about the AI deals that have been happening in the Middle East. Dylan Patel coming on the show in a couple of weeks. US strikes a deal with the United Arab Emirates and the Kingdom of Saudi Arabia. A 5 gigawatt data center, the Humane G42 diversion and American AI wins. Dylan Patel breaks down. He says the US Saudi slash UAE AI deals are complete wins. Everything is there to win over the Middle east and accelerate infrastructure spend. So American companies, AI companies are going to be making more money from this because we have a new customer. The main subtext here is that China is locked out of Middle East AI infrastructure investments. There's a different world, there's a different path, where, yes, there were some controversial moments in Trump's tour of the Middle east, but there is a different world where we are watching Xi Jinping do that tour and we're watching from the sidelines. That's not what happened. What happened is, is our president went there.

We would have struck deals for the first time on the show.

Instead of Sam Altman and Elon Musk and Alex Wang, it could have been the founders of Huawei and Deep Seek and High Fire.

Yeah, you can imagine there's an alternative timeline where, you know, the QIA is investing, you know, $100 billion, not actually 100, but massive amount of money into Manus. Right. Or Deep Seeker or some of these other players. So. Are you talking about Manus?

Oh, we can talk about, we can talk about open source AI agents with Manus.

You're gonna make me put my mustache back on, John?

No, no, no. We have, we have a very important person coming on the show. Jordy, put that mustache.

Put that mustache down.

Put that mustache down. We have the chief operating officer or chief product officer of OpenAI coming into the studio. And so the UAE ruling family used headline grabbing, investment numbers, deals with Trump's family businesses and ties with tech executives to score an Nvidia deal. And it's all looking good. Let's see if we have Kevin in the studio. Let's bring him in. He's here. Fantastic. How are you doing?

This is wild. I just like joined a zoom and I'm live with you guys.

We're live.

Yeah.

It's great to have you.

Welcome.

I was watching you on X and thinking how weird it was that in 30 seconds I was going to be on the screen. This is awesome.

Yeah. We're leveraging this thing. It's called the Internet and technology. But we'd love to get you up to speed. On it since it's funny.

A funny story. So Tyler Cowen called into the show before one of your guys earlier releases and he was like, AGI is here. Like he was basically saying like it's a couple days out, but he couldn't get his camera working. And it was this like funny, funny dichotomy of like AGI's here. But like the Internet is still actually.

There was actually another day when we had to basically take the whole show down because Zoom and both Zoom and Google Hangouts just went completely down, like nationwide. And so we were like, well, we can't do our show now.

I guess the running joke is that audio video is like ASI complete.

Yes.

Everything else in the world is solved.

Yeah. Wait, so I mean, I think long term for the show we need to go proprietary. We need to build our own video streaming stack. Can you help with that?

Codex.

You know what can help with that? Codex can help with that.

Break it down. How would I use Codex?

And by the way, you get to talk about AI and then you're going to have Blake from Boom here. So you get to talk about supersonic flight afterwards. You guys have the coolest lives ever.

It's Full Stack, Full Stack technology.

But yeah, can you take us through the announcement? Break down exactly what launched, when it's available to who, what you're excited about and then we'll go into some of the trade offs in the product design and development.

Development. Yeah, let's do it. So we just launched this morning Codex, which is a cloud based software engineering agent that can work on many tasks in parallel. So a lot of folks are used to the kind of cursor, windsurf style, GitHub, copilot style of AI development, which is really more about augmenting a single engineer. You're writing code in your IDE and you can press tab, tab, tab and it'll auto complete and you're 10, 20, 40% faster. With Codex you actually have a software agent that runs in the cloud that can do entire tasks for you. So you give it a task, it goes off and does it and suddenly you have a PR and you didn't work on it at all. It's powered by a version of O3 that we fine tuned specifically to be really good at these kind of hard software tasks. We're super excited about it. It launched today inside ChatGPT so you can use it if you're. It's rolling out now to pro, to enterprise, to teams. It'll make its way to plus in the coming weeks. But the cool thing is it's a software agent in the cloud, so you're using it today from ChatGPT. You can imagine using it in the future from your terminal, your ide, all kinds of other places, and even hooking it up via API to your bug queues and just having this software agent churn through every single bug that you have for each one, look at the context of the bug, understand your code base, and then suggest proactively how you would fix that bug and give you a PR that you can review. So the world of software engineering is changing. We're super excited about it. It's a research preview. It's not perfect yet, but I think this is the future.

Yeah. So, I mean, I've already noticed that ChatGPT has been writing code for me for a while. It seems to be writing more and more code. I was telling Jordi about how I wanted to know the height of a desk in an im and I knew how tall a person next to it was, and I thought that it would just use images and chatgpt to kind of one shot this or guess, but it wound up spinning up and looking at the individual pixels with a bunch of Python code. I think it wound up writing like 5,000 lines of code or 500 lines of code. And it got it really right unsatisfactory because it was just an average sized table. It was like literally the standard size, but it really knew it. But, but. So I'm wondering, like, like, is this something that will, will feel like a deep research project where our deep research functionality where I click a button to say, hey, let's use codecs for this. I'm giving you the hint. Or is this something that can be automatically triggered just from a text interaction like images and ChatGPT?

Yeah, so it's a. I mean, by the way, you know, you never know if that desk was actually like 38.2 inches. So yeah, it's worth it, right?

The 500 lines of code?

Yeah, why not? It's too cheap to meter.

Actually, that's been one of the big. The coolest thing about O3. O3 personally, for me has been a kind of feel, the AGI sort of moment using that model, the things that it can do. And a lot of it comes from the fact that it can use tools while it reasons. So it's thinking. And in the process of thinking, it can do some web searches and then it can take what it learned from a web search and write some code. And then after that code, it can do image analysis and then it can write some more code and do another web search and then finally, with all of that context, that will output the answer. It's really been an unlock for a huge number of use cases. And that's the kind of thing that enables codecs here, because you're right, ChatGPT has been able to write code for a while. You can just go to ChatGPT and type in write me code to sort this array of integers that I have and it can give you the code and it's going to be great at it. The difference here is Codex is built to work on big complex code bases. You're not just saying, do this little task for me, write this function. You're saying, I have a bug and I don't know where it is. There's a 100,000 line code base. Can you please go understand my code base and try and fix this bug? Or I'm a new engineer at a new job, I'm trying to understand what the heck is going on in this code base. Can you explain to me where the code does X or Y or Z? And very quickly it'll look through the code and give you an explanation of how something works. It's funny, I've even seen examples where people go, hey, Codex, find a bug in this code base and fix it.

Just find one randomly.

That's amazing, complex stuff. And do hard work on a huge amount of existing context that differs from what you've been able to do in ChatGPT for a long time.

Yeah, wild. From a personal perspective. I used to write Python pretty regularly. I haven't written much code, so I haven't really gotten into the cursor Windsurf world, obviously. I've been writing code via ChatGPT now. I noticed recently I kicked off a deep research report and it prompted me to put it on, effectively a cron job. It was like, do you want me to just run this for you every week? And I said, yeah, that sounds awesome, that's great. But if I'm like, I don't have a repo, but I could set one up. Is there a world where me as kind of like a prosumer non technical user should set up a repo to house the custom code that Codex writes for me to make a better experience for all the little custom software and tools and random stuff I use? Or should I just live in the O3 world where the code is pretty much ephemeral?

I think it depends what you're looking to do. For simple things where you just want to quickly put together a script or something. Writing it inside ChatGPT and not using version control and all of that is fine. But if you're going to do something that you expect to be longer lived, it's the basis for something you actually want to build for yourself and maintain. Then I think setting up a quick GitHub repo and using codecs on it makes a ton of sense. By the way, I used to be an engineer. I still dabble and screw around on the side and write code, but nothing major. I hadn't written any code at OpenAI. I've been there about a year and haven't checked in a thing. Tuesday night, I think I was doing the rest of my work and I was like, I want to fix a couple bugs. I went and found a couple really basic bugs because I didn't want to screw anything up and sent Codex off to work on both of them in parallel. Check back in a few minutes. And I had two PRs. They looked right, so I submitted them, got them code reviewed by somebody who's actually a good engineer. They were submitted and now I've got a couple commits in the code base.

So it's like, this is Stolen Valor, though. This is Stolen Valor. You didn't write that code.

But it's like I actually just kept. Other than just getting to play around with the product and offering a little bit of feedback on a couple things, I was off doing the rest of my work and I had this software agent working for me in the cloud writing code.

Yeah, talk about. I'm so curious to hear about the kind of internal testing process and when you guys decided the right time to actually roll this out as a research preview. Because I imagine you've been using Codex in one form of another internally for like a very long time. Maybe it didn't have a name or anything like that, but I'm sure that ChatGPT has been, you know, contributing to the. Effectively, the ChatGPT code base, you know, almost since the beginning in some form or another.

Yeah, for sure. I mean, we're big users of our own tools. There was a version for a while that was mostly about the kind of, how do you come up to speed quickly in a big code base that was good at understanding our code base and answering questions about it, that was really popular with new engineers on the team. And then once you get to understand it, you might not use that tool as often, unless you're exploring a new area of the code base that was like a proto version of this, but we've been working a lot over the last six months at improving the ability of our models to code like you've got GPT 4.1, which we released a little while ago, which has very quickly become a really popular model. It's now, I think, default and Windsurf. It's increasingly a large percentage of of cursor users. Coding that came from focusing on the things that matter in creating a really good coding model that you can rely on means really good instruction, following longer context, the ability to not just make the changes, but to make the changes the way a developer would. So don't add a bunch of extraneous stuff, don't add weird comments, make surgical, precise changes that accomplish the job. So there's a style element to writing good code, not just a correctness element. We've been focusing on all of this and then you bring that together with O3 and all of the things that we were. O3's ability to tool call and to.

Reason.

And suddenly you can put together a really good coding model. We've been thinking about this for a long time. This is the first time when we're like, okay, this is now good enough that we think it deserves being a product for the rest of the world and we're excited to see how people use it.

Can you talk a little bit about product design? Product like inspiration. Product design. I noticed the very first iOS app had these incredible haptics when the tokens were streaming through that I hadn't really seen anyone do. I just opened the app last night and saw that when you're using voice mode to dictate to it, it has a different modal now it feels like there's a very strong design language evolving. At the same time there was, you know, people complaining, oh, I can't even. I'm using ChatGPT. I can't even stay logged in. That, that bug obviously got crushed pretty quickly. But. But what, what is the actual product design inspiration? Are there people that are pulling from certain schools of thought or anything? Or like, is there someone driving that internally or is it just like baked into the culture?

Yeah, for sure. Ian Silber leads our design. I was fortunate to work with him at Instagram. He's an incredible designer. Building for ChatGPT is a really interesting thing because we have well over 500 million weekly active users at this point. So it's a big scaled product. And so for products of that size, one of the most important things is to simplify. Right? You're not just serving power users at that point. And so you're serving people that are just trying to get something done in their day. They don't care about the complexity, they don't care what the models are called. They just have a task and they want to complete it and you want to help them. But then on the other hand, we have folks who are super deep AI enthusiasts and want to digest every single new model that we use and try it out in all these different ways. And so we want to both, and we want them to, we don't want to soften the edges of their experience. We want them to be able to do everything they possibly can to experience all of the power of AI. We both want to simplify the experience for a lot of our users and we want to provide the people that want it all of the bells and whistles. We try and balance that. You try and make it so that you don't need to worry about things like the model picker as much. You don't need to have a bunch of AI knowledge in the background to do what you want to do in OpenAI or in ChatGPT. But if you have that, you should be able to expose the sharp edges and test the different new features and stuff. And so we really actually try and get both of those things right. And it's a delicate balance.

Is that why you guys don't seem to put too much emphasis into perfectly naming products? Just because in the, on a long enough time horizon, it doesn't really matter. I just come to, you know, chatgpt and I work with it to get the outputs and the results that I want and I'm not, regardless of my experience level, I don't necessarily care the underlying sort of models doing the actual work.

Wait, are you saying, are you naming isn't great?

I was alluding to no. To be clear, we think that you have the second worst naming after Behemoth, which is a very, very untamable, you know, demon, demon, monster, potentially a disaster. So we are now long four zero and zero three and we just, I.

Just, I just, you know, only, only six months ago a new model would get announced and people are like, oh, it's so confusing, blah, blah, blah. Yeah, but it just, it seemed to me, you know, as an observer that you guys, it wasn't like, oh, this is a problem and we need to fix it. It was just more so like, let's just keep making really great models and make them easier to access in really intuitive ways.

Yeah, I mean, in all seriousness, it comes from our focus we have this principle of iterative deployment that we really believe in, which is that these models are new systems. Right? They're each one, each model has capabilities that we understand somewhat and also we discover new things about it. And we believe that no matter how smart people we have inside of our walls, there are way more smart people outside our walls. And the best thing we can do in a world of AI evolving so quickly is to kind of co evolve with society, to ship stuff early and ship often and learn together. And so one of the reasons that we have this explosion of models is we're trying to build new capabilities rapidly. And sometimes the easiest way to do that is to kind of build it into a new model that's really good at one specific thing or a handful of specific things, but can't do everything. And so you end up with this profusion of models that do different things. Well, 4.1 is really good at coding and instruction following, but it's not as chatty. So we're asking about other things. You might prefer 4.0 for some things and 4.1 for others. Seems totally natural. You'd go like, well, why don't you just build one that's good at coding when you're coding and good at chatting when you're chatting. And we will do that. That's what we're trying to get to with GPT5, where we're trying to bring more of these things together. But if we tried to do that from the beginning, we wouldn't have been able to launch as fast. And so we've opted for launching fast, having a little bit of confusion that comes with it. But we learn faster and then over time you sort of integrate and simplify.

I guess the meta question though is, is the future just. You're already using mixture of experts within the models. Is the future like a mixture of. Mixture of experts models? And so I go to one, there's one command line text is the universal interface, not drop down model pickers. And it routes me, it says, hey, this person doesn't want to chat, they want to write code. Okay, we're using 401. That seems kind of logical. And already this is kind of happening with the model picker becoming like just the UI is getting less and less in your face and it's a little bit easier. Just have a natural interaction. But how do you see it evolving?

Yeah, I think over time the capabilities that have existed for a little while, you sort of learn how to bring them into a general model, but you're always going to have these new frontier capabilities that you're going to want to be able to iterate on really quickly and you might want to do specialized things to make the model really great at some new frontier capability. I think yes, ideally you have.

A.

Layer above the models that's doing the choosing for you. But it's a hard problem, especially it goes back to the building for simplicity versus building to enable power users. Sure, as a power user you might be the only one that knows for a particular question you're asking whether you want a 80% good answer immediately or you'll wait a minute for a 95% good answer or whether you want to do deep research and wait 20 minutes and get an amazing answer.

Yeah, I mean you could theoretically like train the user on that a little bit.

Like.

Like. Well, it's because there are.

It's also like how you work with the comp that I. Or like my personal framework is like when you're working with people on your team or teammates, there are certain people you'd work with that you would have to explain effectively. Like the exact tool set that they should use to accomplish the task. You should get the CRM and you should go in the CRM and do this and that. And then there's people that are maybe have greater intelligence or experience or context and you just sort of like discuss the task with them. And you're not even thinking about the underlying sort of like toolkit to accomplish the task. It's just sort of this higher level, you know, conversation.

I want to talk about a B testing versus personalization. When you choose like a default model or the default prompts when you open up ChatGPT, it's a. Is create an image, write a Python script, make up a story, what's in the news. There's a couple options there. There's a lot of personalization going on. But you could also imagine doing AB testing to understand what will drive churn down or retention up. How are you thinking about the balancing act between those two techniques of product development?

I don't think they're really at odds in any way. We do both. So we definitely a B test a lot of things because we're trying to learn what works and how. How we can help people understand this new kind of strange world of AI. It's a funny product, right? We're used to products where you have a ui. Computers before AI needed very specific inputs like this button does this specific thing and that button does this other thing. And if you wanted to do a third thing and There wasn't a button for it. You probably just couldn't do that thing. Right. But then every time you hit the button, you got the same output. It was very consistent. LLMs are basically the opposite. Right. You can give them input that has the full complexity and nuance of the human language, and you have no limits on what you ask. And then also what you get out is not the same from one thing to the next. It might be substantially the same, but the words are not identical. It's a totally different way of building product. And when someone comes to ChatGPT for the first time, if they just hear from their friends, hey, this AI thing is super cool. It can do all this stuff for me. And they show up at the front door of ChatGPT, they're a new user. What's the mental model? Because it flies in the face of almost everything that you've learned using computers over the last however long. So we really think a lot about how we get people going and how we teach them all of the different capabilities, which, by the way, the capabilities are changing every month or two too. So it's a really challenging problem, but something that we care a lot about. Because if you go from being a novice ChatGPT user to being a power user, it can really change your life. It can save you a ton of time, it can accomplish a lot of tasks for you, and that's only increasing. So the upside of us being able to teach people well is also increasing.

Yeah, I feel like a decade from now, people are going to look back at this moment and realize that the people that fully understood the capability, like the full capability set of the models, just had this ridiculous sort of extreme advantage.

It was the same thing with social media. Like, the people that really understood and took social media seriously early on are like, famous now. Like, actually famous. Interesting. What is your post mortem on the sycophancy thing? I feel like that made news because it was kind of blanketly like, it was kind of like everyone was experiencing, or at least all the power users were experiencing it. But I could imagine a situation where some people really liked that type of interaction and it was beneficial and it actually may improve their lives. And so if you go to the YouTube algorithm right now and you only search and click on positive content, that reassures you. You can have a sycophantic experience and that can be good for everyone involved. So how do you. What is your postmortem on it and how do you think that the personalization will play out in the future?

Yeah, it's a. This was a really important issue. I mean we. So we. The story for people who don't know, we rolled out a new version of GPT 4.0, which is something we do pretty regularly. We're always to your point about a B testing. We're testing new versions of GPT 4.0 that are incremental improvements over previous versions. So we rolled out a new one and we'd a B tested in the past so the metrics look good. It looked like a really solid model. Had some new stuff around personalization and then as it got out there, we saw that a number of use cases, not like super widespread, but enough use cases where we saw the model sort.

Of.

Overly like just being. Some of it was like glazing, what people called glazing.

Glaze gaze.

Yeah, we called it that. I think we used that term.

Yeah. But there were other cases that were more serious totally where someone had real problems and maybe they were having mental issues and the model was sort of validating them in ways that didn't really comport with reality. That's a real thing. And we took that super seriously. So we rolled the model back and then basically have spent the last few weeks diving into where this is coming from and what we need to do to make sure it doesn't happen again. And we've tried to be super transparent about it. So we tweeted as soon as we were rolling it back and then immediately put out a post mortem within a day or so and then put out a second after we had done a bunch of deep dives. We've gone through the team, did some great work. We've got evals now that measure this. We understand a bunch of the root causes from where this came from. As always with these things, they're not. It's never just one thing. It's like a little bit of this combined with a little bit of that. And then this unexpected thing happened and together they created something that wasn't up to the standards that we set for ourselves.

I just have an interesting realization with the product. So we've been hearing this request for feature on social media for a while of like, I wish I could just reset my algorithm, start fresh, because I feel like it's funneled me in some sort of echo chamber and I don't like that echo chamber. And I want to start fresh. And I don't know if social media feeds actually have that feature. It might just be buried. But I've noticed that with the ChatGPT memories early on I was really aggressive about prompt engineering and basically like prompt hacking. And so to get the best responses, if I was trying to learn about trains, I would say like, I am a world expert in trains. I own multiple train lines and railroads, give me a breakdown of the market map of trains and basically lying to it. And then it remembered that. And so now it's like, well, as a train conductor, you'll probably want to eat this for dinner. And I'm like, okay, I have to back up. I wasn't being completely honest with you, ChatGPT, but the good news is that the saved memories are there and I can delete them all and so I can kind of reset my experience. But was that a learning from the demand that people are seeing and the, the stated preference on social media for resetting, or do you think that that's important? Or what other lessons are you learning from how social media has played out? Because you obviously have a lot of experience there and a lot of people at the team have experience in social media.

Yeah, personalization is a really powerful thing that I think we're just at the very beginning of like, you want, I mean, in the same way that we know each other a little bit, you have best friends that you know super well who you're really comfortable with, and then you have strangers and your, you know, your level of comfort in interacting with them is very different. You want your, if you have a super assistant in your life in ChatGPT, you want it to know you really well. You want it to know your habits and how you like to do certain things and you know, even down to like, do you want, you know, more flowery, supportive language or do you want crisp, analytical, terse language? Things like that. I was messing around last night with ChatGPT, trying to give my son some math homework and I just said, hey, can you design 10 math problems for Matthew? And the model knew Matthew was my son, Knew he was 10 years old and developed a bunch of grade level appropriate escalating. It was like, that was super cool. And it even, it was like, oh, he likes Legos and Kevin, you're a runner. And so a bunch of these program or a bunch of the questions were like Lego themed and you're going on a run with your dad and this. And so like, okay, this is really cool.

It's truly making me emotional. It's like the coolest thing as like a parent to be able, as a parent to be able to give your, to give your children like a truly bespoke, magical experience. Is like almost priceless even in the context of home. Like something like homework, right? And so to that, and even knowing that like kids today, like both of our, all of our, you know, we've got five kids between the two of us and knowing that they'll grow up only knowing the sort of world in which this kind of technology exists where a parent can just like generate magic for them in like seconds is just unbelievable.

I mean, and think of the world. This thing designed 10 math problems. So I used 03. It designed 10 math problems for my 10 year old that were escalating in difficulty across a range of different things. It could easily, if he was entering in the answers, could easily realize over time where you know, what, what concepts he understood and what concepts he didn't and just become a personalized tutor for every single kid. And remember, I mean this is free, right? We don't charge for ChatGPT. You can get a subscription, but you can also use it for free. Basically you don't even need an account. You need an Android phone anywhere in the world for free. And you can get this thing that's starting to be more and more of a personalized tutor. I just like, I think it's incredibly powerful.

Totally.

Every study I've ever seen says that when you pair traditional learning with personalized tutoring, it's like a standard deviations of improvement. So I'm with you. I think the future is going to be very different and there's a lot of reasons to be optimistic about what the next generation is going to be able to do with AI.

I need to be more honest with Chucky. How do you explain the rate of AI progress to say like a family member of yours that's not in tech?

That's a good question. I think the only way, honestly, because you can talk about it, but it's like you can't, you can't get fit by reading about going to the gym. Use it. So I've been trying to get any of my family members who aren't using it, just, just try it. Start asking for everything that you're doing. Ask why couldn't I use ChatGPT for this? And you start to realize that there are more things that you can say yes to there and you can start using ChatGPT. And then the more you use it, the more you realize the value and off you go. It's really hard to explain in the abstract, right? People go, agents, I'm hearing so much about agents. What is it? And then you use deep research or you Use Codex. And you're like, oh, wow, that just saved me a ton of time. Or did something I couldn't have even done. That's the promise of the future. I think we're all going to be much more productive. We get to not focus as much on the doing of particular things. We get to focus on the outcomes and what we do once some of the labor itself is taken care of. And that's a super exciting future for me.

Couple more. Talk to us about health bench.

Yeah, so a huge amount. I mean, people are increasingly using ChatGPT for health. I've done it any number of times. My son had a small surgery that was supposed to be 99.9% innocuous, 0.1% bad. And we got the results back from the doctor before I could talk to the doctor. And they look scary. And. And it's full of a bunch of medical jargon that even as a former scientist, I didn't understand. And I put it in ChatGPT and said, this looks weird. What is this? Should I be worried? And it said, oh, no, no, no, don't worry, it's fine. And I was like, okay, explain it like I'm five. And it did. And I couldn't get a hold of the doctor for another 72 hours. That would have been a bad 72 hours for me if I was sitting there stressed out about my son. And ChatGPT gave me the peace of mind. So we always try and say with anybody, anybody asks about anything medical, this isn't a substitute for actually seeing a doctor. ChatGPT is not a doctor, but here it is. Here's the understanding of what's going on there, and it's really valuable for all of us. For me, it saved me 72 hours of anxiousness. For somebody else who doesn't have access to a doctor, it might be a totally different thing. So, anyways, we care a lot about this. We want to make. If people are using ChatGPT for this, we want to make sure that the answers that it gives are really good answers. And so we're putting a lot of effort into improving ChatGPT's ability to act as or to answer medical questions. And the only way that you really know if you're doing it right is if you have a benchmark, you've got to have something to test against to show that you're getting better. And we figured if we'd done a lot of work to put this benchmark together, then others could benefit from it outside of us. And so we open Sourced it.

Last question. Can you give us the 30 seconds on why you were excited to join Cisco's board of directors?

Oh, yeah, totally. So Cisco is an incredible company, like iconic Silicon Valley software and hardware company. We all use it every day in a hundred different ways. And they're at this really interesting point because I think AI can transform their business and they can either be transformed, like it can either happen to them or they can get ahead of it and build some really amazing software and tools and become an even more powerful leader for the next, the next generation. And I think that's not unique to Cisco. I think a lot of companies are at that turning point, but Cisco really realizes it. By the way, they're actually a launch partner today for us with Codex. So they're one of our early partners. They're looking a lot at how AI can help them get more done faster, more cheaply, et cetera. So AI is going to really impact their business over the next three to five years and I'm excited to be a part of that and hopefully help them navigate this transition gracefully.

Amazing.

Well, I have like five more hours of questions, but we will let you go.

There you go. We'll come up to.

Most questions can be answered by ChatGPT, but there's certain questions you gotta go.

To the source Organic farm farm to table.

Yeah.

Well, thanks so much for having me on. It's good to see you guys and great to see you, Kevin, about supersonic jets that. I wish I could stay for that one.

Yeah, yeah, we'll talk to you soon.

Great to see you. Cheers.

See you. Bye.

Kevin is the man.

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There was numeral was getting picked up by an anonymous.

Oh yeah, we saw the news. There may be out there in the.

Market but Sam said too low.

Too low.

You're not bullish enough on sales tax agent.

Can you tell him it's on record or not? Well, it's live.

He posted no, he. No, he posted this. He said too low.

Okay, so we're not scooping anyone here.

We're not scooping anybody.

We have Blake from Boom Supersonic in the studio. Welcome to the show, Blake. It's been too long.

We've been Wanting to do this for a while.

Yeah. Ideally from a supersonic plane. We're aviation aficionados. We like traveling. But the hard thing with the show is that it takes us six hours to get across the country. We podcast for three hours a day. The math just doesn't make sense. So we're happy that you're working on a solution for us.

Indeed. Well, thank you for having me. Yeah, it will be fun to do the first ever supersonic webcast. Maybe we should just agree to do that.

I'm 100% on board.

Let's do it.

Count me in. Can you give us just the general update? Obviously explain, like, what you're building, but what's the latest news in the world of boom? Supersonic.

Yeah. Well, if anybody's not been following the story, the goal is to really pick up where Concorde left off, foment a supersonic renaissance, ultimately deliver faster travel for everybody from the President on down to every family. And so it's a. It's a decades long mission, you know, ultimately to replace subsonic with supersonic for every passenger on every route. But. But building building companies like boom is. It's like building an iceberg from the bottom up. And I feel like this year is the year that the iceberg is like, really emerged from the surface of the water. In January, we broke the sound barrier with our test airplane, the XV one.

Bringing the sound barrier. We love to see it.

Right.

And then in February, we did it again, and arguably we broke it permanently.

Fantastic. That's great news. You said you broke it permanently. Is that what you said?

Yes, because we proved we could do it reliably with no audible sonic boom.

Oh, there you go. Okay.

They said it couldn't be done. They said it couldn't be done.

Yeah.

People.

By the way, it turns out that, like, people have been telling me this for decades. Yeah, Boom. And mostly the claims are it's like really hard. You have to like, change the aerodynamics of the airplane and. Dah, dah, dah. No, it's a software fix.

Really? How? Explain that.

Everything is computer, John.

That's it.

If you fly the airplane at the right altitude, at the right speed for the current atmosphere, the boom makes a U turn in the sky and never touches the ground.

No way.

But you need to be able to calculate that. That's right.

In real time.

You need, like, decently good weather data.

Yes.

And ironically, algorithms that were developed for computer gaming.

Wow. Oh, that makes sense. Yeah. So it's a physics simulation.

It's ray tracing.

You're running unreal engine. Almost. I'm sure you have a proprietary system. Does that need to go through FAA approval to use that or is that separate from the rest of the aircraft? Authentic. What's it called? Qualification or like.

Yeah. So you need to certify an airplane certified carry passengers.

Yeah.

Basically, you got to prove you meet all the safety standards.

Yeah.

And this is. This is separate because we. One of the dumbest regulations ever created. In 1973, we banned supersonic flight in the U.S. like, literally there's a regulation that says, thou shalt not exceed Mach 1.

Yeah. And it's speed limit, not sound limit.

Right, right. It's really stupid. It's really stupid. And. And so no, you know, we could, like, make it play Mozart when it flies over and you're still not allowed to do it. And that's why. That's why there's coast to coast flights are still stuck at the six hours. That's why no one's done this already. And. And so we're working really hard to get that changed.

We had a feeling that, like, the EO would just drop and it would be like, oh, my God, he just tweeted it out or put it on Truth Social. And it happened. Like, love him or hate him, but, like, the guy definitely, like, likes to rip a crazy idea on short notice for everyone. Are you optimistic that there will be change? Does this need to go through the House and Senate, or is this something that could just happen in eo?

So we've had good conversations at FAA this week. A bipartisan bill dropped in the House and the Senate that does it.

Cool.

And Elon endorsed it. Jared Isaacman endorsed it. We've got bipartisan support. Great. Some people think this could get through the Senate unanimously. I think that's probably a little ambitious. But even the idea that that's possible, I think is pretty cool.

Some lawmakers like traveling slower because it inspires them to grind harder. More time on the plane, more time to prep their filibusters. They don't want to go fast.

I guess that's right. The bear case for supersonic, the fast plane. I get so much email done.

I do get a lot of email done on a six hour flight.

I got there faster. I'd do less.

I was texting Jordy when we were flying to dc. I was like, this is incredible. I've never been more productive.

But I think faster flights will just force us all to be more efficient with our time. Right?

That's right.

Yeah. I mean, break down the actual Scope of the problem here, how much is engineering, how much is regulatory? How are you staffing against that? Do you have a massive government affairs team and lobbyists or. I imagine there's still a ton of engineers on the. You're not just taking some like white labeled plane and then doing a bunch of lobbying and that's the end game, right?

Yeah. I mean, the most surprising thing is that we don't have to invent anything fundamentally new. This is not a science project, it's not a technology project. It's really just an engineering project.

Sure.

In fact, we're taking 20 year old 787 technology, basically reshaping the airplane, making it long and skinny, putting twice as many engines. And so there's a lot of engineering and testing that goes into that, but there's no science and there's no new technology and there's only one regulation that needs to change. So we've got small numbers of great engineers. I'm a big believer in like tiny teams.

Yeah.

That are very focused. Like we did, we, we built XB1, our test supersonic jet with just 50 people.

50 people.

Wow.

And the overall company is not that much bigger.

Right, right. Like 115 now. And like we're growing very slowly. Like if a team does not complain about being understaffed, I know they're overstaffed.

Yeah, yeah. I mean, we were joking about like white labeling a plane. Obviously you are standing on the shoulders of giants using some off the shelf technology, using some technology licensed from other firms. Can you take me through the journey of engine development? The decisions that you made, have you changed course on any of those decisions? What would you recommend to the next generation of aircraft builders?

Yeah, well, I'll go broader than that. Like if you're thinking about doing hardware at all, My, my advice, frankly, any startup, any startups. All startups are hard. I don't think any are easy. I think the difficulty level is set by founders because we tend to run at our own red line. And if somehow it gets easier, what does it make the job harder again? Like, like, like Brian, Like Brian just decided to like, you know, double what Airbnb is, you know, because I guess the old thing got too easy.

Yeah.

And, and so it's. What I, what I've found along the way is I'm far more successful if I pick a mission that deeply inspires me and makes it worth being at my red line. So I never get up in the morning and think, is it worth it? Okay. Okay, great. So now, now probably Building supersonic jets is like, you know, the ultimate hard mode. And. But what I have found along the way is people around the company from the legacy industry will have all these stories about all these things that are impossible to do. You know, you can't build your own jet engine. Like, only a big company could do that. There's tons of proprietary technology. Blah, blah, blah, blah, blah, blah. It's all, it's all like, I'll tell you one story. Like we were trying to get high temperature super alloys for our engine and, you know, we thought we needed to go license it from one of the big three. We get in this licensing conversation and they're like, oh, we can't give you this thing because there's a trade secret. I'm like, don't tell me the trade secret. I'll give you the part. Just make me the part and hand me the parts back and don't tell me the secret. And they said, no, no, no, no, you'll find the secret. So we can't do that. And for, for like two weeks, we're like, oh, like, how do we ever get this engine built? But eventually we just went into the supply chain and we found the trade secret.

We found it.

And I'll tell you the trade secret. Okay, there is no trade secret.

Oh, interesting.

The thing that was theoretically proprietary is an open source material developed by NASA where all the specs are public.

The trade secret. Open source.

That was the trade secret.

That's the trade secret. The trade secret.

The secret was there is no trade secret because there's all this fake proprietary. Everybody's telling you why you have to work with them, why you have to use their stuff, why you couldn't create it yourself. And, you know, and it just, nine times out of 10, it's just not true. And so we, we found, you know, we probably heard Elon talk about the idiot index, which is like, how much a finished part costs is divided by the raw materials cost. We found a thing that's more important. It's called the slacker index. Slacker index is how long it takes to get something divided by how long it takes to actually make it. And, and so we've got these turbine blades, we're 3D printing turbine blades for our engine. And we go quoted out of the traditional aerospace supply chain. It's going to cost a million dollars for one engine's worth of parts, and it's going to take six months. I was like, well, how long does it take to print a blade? Well, it's like actually about 24 hours. So why does it take six months to get one? Well, they were like printing them like one at a time and then you got to wait for your turn on the machine. All this not okay. What's the machine cost? $2 million. How long does it take to get a machine? Oh, actually they've got them in inventory. You get them in a couple weeks. So for the price of two engines worth of blades, we got the 3D printers and the blades and we can. And we beat the lead time of just outsourcing it. And that pattern exists everywhere in this business.

Can you talk about the current fundraising market for hard tech companies? There's a bunch of companies raising a ton of money. There's other. It's feast and famine out there. The F35 cost a trillion dollars. Somehow I feel like trillion dollar raise is on the table soon based on the current market.

Yeah, we'd personally like to see 1T on 5T.

I'd love to see that. I'd love to see that one T.

On five T. That should be the new, the new goal.

But I mean, there is a world where a plane company comes out and raises just massive money and just dumps it all into subcontractors and takes a very different approach. Why wouldn't that work? And what advice would you give to the next generation of hard tech founders in aviation or otherwise?

Yeah, so the, the key difference. So there's this mythology that hardware companies are more capital intensive. And if you go look at like, how much money did Uber raise? How much did Lyft raise? How much did Stripe raise? How much did Airbnb raise? Like these, like theoretically capital. Light businesses consumed billions in venture capital.

Yep.

Before ipo. So wait, why? And if you go look at like SpaceX or Andrew, like the theoretically hard tech companies, like, oftentimes they raise less money. So, you know, wtf? And I think that the difference is if you are building, say Uber or Airbnb, you have an idea that sounds really counterintuitive. Like, invite strangers from the Internet to sleep on your couch. Right. It doesn't sound like a good idea, but it's actually really cheap to test.

Yeah.

And so what happens in most Internet businesses is very small amounts of capital allow you to test whether you have product market fit. And, and you, and you test it by means of building and shipping the product. We can't build a supersonic airliner as a means to testing whether anybody wants a supersonic airliner. Right. So, so what you have to do in a hardware business Is is find a capital light way to demonstrate that you're at product market fit. And the answer can't be shipping the product.

Product.

So, so, so, you know, our strategy was preorders.

Yeah.

So we, you know, we got United American to make like deposits, like non refundable deposits on airplanes against a specific design. So it's not just like, okay, here's, you know, here's a dollar that says, you know, supersonic is cool. It's like, nope, here's a significant multi million dollar deposit, a whole further deposit schedule against a very specific airplane with very specific specs. And then so we can go to investors and say if we build this, there's obviously a gigantic market and this is going to be like a.

We're already getting paid for it. You guys are already getting paid for it.

That's right. Yeah. So all you have to believe is we'll actually ship the product.

What was the, I want to ask you, what was the worst week? Building boom. And what was the best week?

Week.

I'm guessing the best week was this year.

Yeah, I think the, I'll give you the best moment. The best moment was the day that we broke the sound barrier for the first time. But it was, it wasn't actually the moment of breaking the sound barrier because we'd done so much testing at that point. I knew if we flew that day, we were going to break the sound barrier. What I didn't know is whether we'd have the weather to do it. And, and like I'd gotten up that morning and it was extra cloudy and like, we can't, you know, we can't do it on a cloudy day. And, and so the team was kind of debriefing, checking the weather. Da, da, da, da. And, and one of our safety culture rules is like, no top management are in the safety briefs. It's the team making an independent go, no go decision with no, no nobody senior putting their thumb in the scale and telling them they need to go and pressurizing it. But so the team, so I'm like in the hangar waiting and the, the team, team walks out. And I could just tell from the energy, like it was go time. Like, nope, nobody had to say anything. It's just like I see him walking over the airplane. They're like hooking up, hooking it up to the, hooking the tow bars up, like, we're good to go. And at that moment I really teared up because I, I knew, I knew it was going to happen. And then like when it actually happened. Everybody was jumping up and down and screaming and I was sort of like, yeah, of course. So that was, I think that was the best moment, the worst moment. We have near death experiences like basically every year. And at this point I just expected, I'm like, okay, you know, every year we're going to get the equivalent, the startup equivalent of a cancer diagnosis. And you know, if I'm lucky, it's stage two, not stage four. But you know, we, we've had like, some like, we like survived stage four startup cancer. We had an extremely difficult fundraise. I think we got down to a week of cash. Wow. Like, the lawyers had a plan to shut the company down. I remember calling one of our investors when we were sort of three weeks away and he's like, usually when people tell me you're three weeks away, you're telling me you're going to shut the company down. And I was like, of course we're not shutting the company down. We're talking about how we get through this little knothole here and who have.

Like 12 months of cash and they're like, I'm out of this. I've been doing this for a year. I'm going to go be a PM in Big Tech. I've done the PM at Big Tech.

I don't ever want to do that again.

No, I think I'll never go back.

You could never make me go back.

No, I can't go back. The thing, the thing with your, with for you and your team and I'm sure the entire cap table, it's like, if we don't do this, we have to be. If we're not successful here, we're going to be reminded multiple times a year.

Every time.

Yeah. Like, yeah. Every time you get on a plane. Every time. You know it, like is. Is one of the very few companies on earth that can and bend reality into. Bend time. Right. And I just think I feel like humanity is fortunate that you are running this company because so many people would have gotten the stage four diagnosis and just said, all right, we took a good shot, we did our best and that's it.

Yeah, it's my biggest wish for other founders is pick the startup where if you got the stage four diagnosis, you say, screw it, we're beating this. And for me, that's supersonic flight. But for every founder it's something different. But I think there's this founder market thing or founder mission thing and if you get that really in alignment, then you can run through brick walls.

Yeah. In many ways, I Would run through.

Brick walls for a note taking app.

I would too. The in. In many ways you could think of boom as being a very logical, obvious next step in commercial aviation. Long haul travel, that type of thing.

Yeah.

What about the flying car market? I've often said we have flying cars. They're just helicopters. But the problem with helicopters is that they're not evenly distributed. Not everyone has a helicopter. But if everyone had a helicopter on their own house, they could fly to work. And yeah, you need air traffic control and stuff. We all need to be good pilots. But if a company could drop the cost of a helicopter, buy 100x and make it 100x safer, yeah, we'd probably basically say, yeah, we saw flying cars. And yet that hasn't happened. So what is your take on the boom of helicopters? Whether or the boom of flying cars or anything else in aviation, There are.

Great people working on that actually. And it's actually way harder than supersonic flight. Way harder. But because zillion reasons. Like one is you need a whole new set of regulations. Right. Because these. The electric vertical takeoff and landing. So Joby and Archer, who are really the two leaders in this, it's not technically or regulatorily a helicopter. There's a whole new set of rules. They need a whole new set of infrastructure.

Because what I'm saying is like, is like what if I started a flying car company that was perfectly regulated as a helicopter, Just like there are these companies now that are regulated as sea gliders. Billy Fowler.

Yeah.

Oh yeah.

Billy and region are doing great work.

Right? Yeah. I'm sure you love it. Right? It's like legally a boat, but it's like a plane. But he has. But he's designated in one way, so it's a lot easier. And I feel like there's almost like this regulatory arbitrage or regulatory hack that the hard tech foundation need to think through.

So it's. This is. If the regulations were done well, your idea would be exactly on point. The problem is we have. We have too many regulations that are prescriptive about exactly how something has to be done.

Sure.

Rather than setting a safety bar or a noise bar. Right. And so, and so like, if you look at the regulations for helicopters, they tell you how you must build your helicopter.

Okay.

And so if you want to build an electric helicopter with distributed rotors, well, it doesn't have the parts that the regulations tell you how to design, you know, or like, how do you treat, you know that you're allowed to have like a wing on the thing Too. So, so that like the better helicopter is. That doesn't fit the regulations for helicopters.

Yep, yep. So yeah, it almost be better bug in the regulations. Yeah, almost. Just to regulate against like, like if, if flying things are crashing at, at a rate above more than like one in a billion, it's no go. Doesn't matter how you build it. Instead of saying you have to have this screw in this place.

That's right. And actually for large transport aircraft, it's actually a bit better. One in a billion is actually the regulatory safety bar. And yet there are also still some things that are like prescriptive, but there's a mechanism to get around the prescription called equivalent level of safety. So we can go to FAA and.

Say.

And say like you say that our throttle has to be built in such and such and such a way. But the real thing is a reliable throttle. Let me show you my reliable throttle that's done differently. And you can get an equipment level of safety finding you can go forwards. But if you look at going from a helicopter to an electric vertical takeoff and landing or flying car, the whole thing is different.

What's your timeline to EV talls being in American skies?

Who wins? Who goes first? Will I be on boom Supersonic or, or evtol?

Yeah.

I mean, just, just kind of a wild guess. Is it like before 2030? Seems unlikely to me. Is it, is it 2040?

Is it?

I, I, I don't, I feel uncomfortable speaking for other people's timelines.

Yeah.

I think, I think the technology is going to be ready, but before the infrastructure and the regulatory environment are laid flat.

Yeah.

And the stated timelines for EVTOL are like super near term.

Yeah.

And, but I suspect it's optimistic. I don't know. And I don't know, maybe we've made the mistake of being more realistic and now it just sounds worse, you know. So Our timeline is 2029 for being ready for the first passenger.

I mean, there's also like incredible things happening in EVTOL that are unmanned. You look at what Zipline's doing. We talked to the founder of Zipline and we were blown away by the progress there. And that was one of the things where they had to go to another country to get favorable regulatory treatment and kind of figure things out, but then have really been able to accelerate.

Yeah. I mean, Keller's crushing it. Like, like, I love Zipline. Amazing founder, amazing company, Great success story for how you do these things. They're, they're brilliant. Keller is brilliant at like finding the first market that was like the soft target. It. The, the, the small and uncrewed are radically easier than large and crude. And the, and the, the re. The reason for both is safety. If you go big, even if it's uncrewed, you have a problem because if the thing crashes, it can hurt somebody on the ground.

Yep.

Right.

And so there's a threshold, you know, somewhere around, I think, 55 pounds, like above. Above which like it's radically harder. And then if you put a human on board, like, obviously you don't want to hurt anybody. And so in building XB1, like the most surprising things were about the sort of the second order effect of our choice to put a human on board. From day one and not to have an ejection seat, we basically put everything on hard mode. But we learned a lot more from that.

Yeah. Is there an easy mode version of the boom story where you go to some country with lax regulations, you say we're going uncrewed, we're going smaller. Maybe it's like a ISR reconnaissance application. You're only flying over the water counting on fish or whales or something. And it's just much easier to actually get flying on a routine start the flywheel like Zipline did.

I mean, you could go, you know, there are people doing kind of what you're describing that I think are smart, like Hermes. Hermes is smart.

Yeah.

And you know, but what is, what is Hermeus doing? They're basically building a hypersonic bomber.

Yeah.

And you know, and it's kind of okay if the trips are one way.

Sure.

You know, and. Yeah, and I think they'll have a great business and they're great people working on that. And I, you know, I'm cheering for them. They'll probably get to Mach 5 long before I get to Mach 5.

Yeah.

But the, but doing that and then, and then later putting a human on board is extremely difficult. Like, if you look at the history of development of aircraft platforms, you find that defense technology makes it into commercial technology. But there are basically zero cases of a defense product becoming a commercial product. But the reverse is not true. There are many cases of commercial products becoming defense products. So the Boeing 707 became the KC135. The 767 became the KC46. The 737 is turned into a whole bunch of command and control airplanes and anti submarine airplanes plans. I think the reason is when you're commercial, you have to worry about safety and you have to worry about noise. And neither of those things is retrofittable. They're actually foundational to product architecture. And so technology can go in either direction, but products go in one direction because safety and noise are fundamental to product architecture.

You mentioned AJ At Hermeus. When are we going to see the foot race? I want the two founders of the supersonic companies to race each other to see who's faster in the real world on the ground, and then we'll race the planes in the sky.

I mean, I think aj AJ have been telling each other the other one's gonna win the race, so I don't know. I. I think. I think it'd be like the most. At least for me, it would be the most pathetic race ever. I. I am, like, not a runner at all.

Well.

Well, we'll do it as a pay per view. We'll raise some non dilutive capital. You guys can maybe split it based on.

Let's actually make it a little bit less about the running. Let's just do the Merchant. Yeah, we'll just do the Anduril Murph together.

Well, we're gonna hold you to being the first people to podcast Supersonic. Yep. And I would love to have you back on the show many times between now and then because this conversation has been extremely insightful and we are just grateful for the work that you and the team do.

It's great. Thank you so much, Blake.

That was so much fun. Thank you.

We'll talk to you soon.

Cheers.

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Anyway, we got Tim Fisk from IFP in the studio. We remember he was here when we were under attack. And all of Zoom.

That was devastating.

That was devastating.

Such an interesting conversation. Yeah, yeah.

It was awful. So he's at the Institute for Progress. We'll bring him into the studio and talk to him. How you doing, Tim?

Welcome back.

Good.

Thanks for having me. Guys. We made it.

We made it. Thank you so much for bearing with us.

That was such a weird. You know.

It was weird.

It's not the first time a nation state is trying to take down tpp.

We start talking and we get spicy and all of a sudden the connection gets fuzzy. It might happen again. We don't know.

Yeah, we had Tencent was pretty upset at the H20 allegations.

So prime suspect number one, take us through the allegations again, break down what you guys published, and then we'll go through some of the reaction and the fallout from the piece.

Yeah, so, God, so much has happened since this was in the news. It feels like there's five different things in export controls that have gone on since. But yeah, basically this was the H20 inference chip from Nvidia, which some might remember was designed to be compliant with the export controls. So is this the chip they sold about reportedly 1 million of them into China in 2024. And yeah, there was a lot of outcry at the time for the Bureau of Industry and Security, who's the part of government that administers and enforces export controls, to do something about this. Because 2024 was the period where everyone realized that inference compute was perhaps the most important strategic input to frontier AI development because of test time, compute scaling, reinforcement learning and synthetic data generation is the key things. And yeah, earlier this year there was reporting that Nvidia had had a huge number of additional sales plan to big Chinese companies. And a bunch of people, including us, sort of said, hey, is this really what we want to be doing? Do we want to sort of allow China to get access to millions more of these chips? And yet the government ended up taking action on this and issued some guidance, basically saying, hey, no, you can't make these sales. Nvidia reportedly was left holding the bag to the tune of about 5.5 billion. And now since then, we've seen for.

Nvidia.

It'S barely a flesh wound.

Well, they made up for it with deals in Saudi Arabia, right?

Yeah, indeed. Yeah. So that's the new thing, right? It's the administration walking back on the diffusion rule, this big new framework, and then the series of deals that have been announced over in the Gulf.

Yeah. And what's your reaction to the diffusion rule and the deals in Saudi Arabia? Is this a step forward? Are you excited about this? Is this positive news?

Yeah. So it really depends on the details of all this. So I think on the deals, I guess, fundamentally, what do we want? We need the US AI tech stack to win the global competition against China. And I think a big part of that is locking in these early adopters and big spenders, especially like the United Arab Emirates. But I think we need to be thinking about how to structure deals like this to sort of get the US the outcomes at once, which is US tech diffusion, the kind of like Chinese tech stack locked out in a way that we couldn't handle with 5G. China won sort of like the 5G battle globally and then appropriate national security guardrails in place. And it's pretty unclear what the trade offs that have been made for this deal are. So I think the high level specs that we've gotten is a 5 GW AI data center campus to be deployed over some time period in Abu Dhabi and then reports of 500,000 chips per year to be exported with maybe 4/5 of those for US firms who are building data centers over there and 1/5 for G42, this big tech conglomerate in the UAE. And kind of depending on how quickly that all happens and whether they're referring to 100,000 of today's chips or 100,000 of chips in five years time, this could be the difference between 1x to 100x in terms of different differential in compute. So yeah, I think that really makes the difference. And I think the key question here is do we want an AI lab in an authoritarian country to have the biggest clusters or close to the biggest clusters in the world?

World.

And this is a country that does collaborate with China in areas like drones and 5G and military technologies. And so you need to sort of be careful with giving them access to sort of frontier scale compute here.

Yeah, so there's kind of like, I'm.

Curious if you have insight on capital flows from the UAE and Saudi into Chinese AI is how much investment activity is there? Do you have any insight?

I don't have stats on this. I suppose the interesting to say on this, you guys might remember there was this $1.5 billion deal between Microsoft and G42 a couple of years ago that sparked this stuff. So this was essentially Microsoft making an investment into G42 and starting to build data centers in collaboration with them. And Department of Commerce got really involved in this and one of their requirements was to divest from Chinese companies in the kind of AI stack back for G42, which is this huge tech conglomerate that is funded through the nation's sovereign wealth fund, which is the second largest in the world. So pretty serious money. We're talking trillions of dollars. And yeah, reportedly what they did is they had a bunch of passive investments in Chinese companies, including hyperscalers and AI companies. And reportedly G42 did divest from Those companies, but then basically moved the investments over to another fund called Lunate that was also owned by this, this big sprawling tech conglomerate that's ultimately funded by the sovereign wealth fund. So there's big question marks about how much are they actually decoupling from China and how costly is this to them? Are they actually burning bridges that are hard to reverse?

Yeah, there's some element of like we have this smooth gradient of friendship with different countries. Obviously there's the five eyes like the closest allies. We sell nuclear submarines to some countries. But then there's countries that are more jump ball false and could go either way as the diffusion rule goes away. Do we need firmer rules around, hey, we're willing to sell to you, but don't immediately set up a reseller and start selling just passing these on to China because you could imagine if the natural economic forces take hold and I was in some country that was just about to get 500,000 chips, it's pretty easy to just immediately start reselling these if I. And just. Just print money basically.

Yeah. And there are kind of two ways to do that, Right. One is you can just on sell the chips, so kind of smuggle them into China. And the other way that's pretty straightforward is set up your own data center and rent it out as cloud computer. Exactly, yeah, I think that's what you're referring to. And yeah, currently there's not great guardrails around either of those things. And I think the administration wants to set up better versions of this. But yeah, I think this needs to be part where there's sort of like countries that are really willing to buy hundreds of thousands to millions of chips. You kind of want these structured deals that have these guardrails in place. And I think the Trump administration is really well positioned to strike these kind of smart bespoke deals that get us the right possible outcome across each of these dimensions. And hopefully that's what they're pursuing.

Yeah.

Can we talk about the news today? Or maybe it came out late yesterday that Nvidia to set up research center in Shanghai maintaining foothold in China. Basically they're opening this R and D center as almost like an olive branch to China is kind of how I would describe it. They say they're going to use it to understand Chinese customer demands and design US compliant products. And they're basically doing this to just kind of navigate, sorry, navigate export controls and compete with companies like Huawei. This to me, I mean, there's so much to unpack here. I love your kind of initial take. And then I want to kind of maybe move more high level. And to me this signals that, that maybe Jensen doesn't take national, the national security concerns about like an AI war as seriously as even some of the US foundation model labs talk about it.

Yeah, I'd say that's an accurate assessment. And I think it's really hard to design sanctions, export controls, like these kinds of things in a way that sort of can't easily be escaped from. But it's kind of like the spirit of the rule in that, hey, we're worried about China beating the US in the most strategically important technology of this century and we don't want you selling to them. But then you can do all these things to sort of actually be cooperating around the scenes like design compliance chips or whatever. And to be fair to Nvidia, I think they say, look, if the speed limit is 60 and we're going 55, we're not breaking the law. We should be allowed to do this. And if you think the strategic perspective for them is also a lot of their customers are these big US hyperscalers. And all of these hyperscalers are developing their own custom silicon. So we know Google has their TPU that they use for both training and inference. We know Amazon has Trainium and Inferentia that they're also using for training and inference. Microsoft is developing their own stack. And so huge source of revenue for Nvidia is potentially at risk. So it kind of makes sense for them to want to be diversifying to other parts of the world and not just be selling to US hyperscalers. So they're certainly in a difficult position overall. And yeah, what you think is right here depends really on how much you buy this kind of argument that, hey, over the next five years, AI as a technology that will reshape the global balance of economic and military power is a thing and will be a really big deal.

Yeah, it seems like the speed limit is getting lower and lower though. We went from the H100 to the H20. Now Nvidia is preparing to release a modified version of the H20 chip for the Chinese market. After your piece and the changes to the H20 restrictions, is there a point where the restrictions are so onerous that no one wants to buy a car that goes nine miles an hour? You know, at a certain point Nvidia will just lose the market share because Huawei Ascend chips will just be outperforming. Are you tracking any of that?

Yeah. So here it becomes an interesting conversation. I Think the kind of crux of the matter is if you know Huawei has better chips than Nvidia in the Chinese market and is able to sort of capture that market, how bad is that? Should we sort of set export controls such that Nvidia is always slightly ahead of Huawei, for example, and sort of raise those limits over time? And here I think there's two sort of dimensions to it. One is that in AI, the quality of the chips matter. So how sort of individually performant each chip is, but also the quantity really matters. So you can have a million chips each that are half as good and sort of like substitute for like 500,000 chips, for example. And so this is a crude approximation, but you both want the sort of best chips and as many of them as possible, possible. And where we're trying to squeeze China, we being the US government is across this whole supply chain. So not just on being able to procure chips directly, but also being able to manufacture their own. So having the semiconductor manufacturing equipment and the fabs and everything there. And so I think the goal of the US government has to be really to restrict the quantity of AI chips that China so like SMIC and Huawei as the key firms here, are able to produce. And so by this logic, even if Nvidia has a chip that's only slightly better or slightly worse than Huawei's, you still might want to restrict it because you would prefer them not to have access to 10 times as many chips than they otherwise would have. You don't want them to have access to essentially TSMC's production capacity of being able to do many, many millions more chips than you could otherwise produce. So I think yeah, these are hard trade offs to make. I think where it really matters is in foreign availability. I think where Huawei is accessing foreign markets and outperforming US chips, that's bad. And we should sort of make sure that that is not the case and it is US chips that are being used globally in countries that aren't China.

Yeah.

Do you think Huawei will ever go public or do they not want people to know? They want people to know as little about their business as possible.

Yeah, I'm clear. Depends what the CCP wants. It's notoriously opaque organization.

Yeah, interesting.

What is your take on open source AI? We were talking to Aaron Ginn about this idea that if America does not provide a state of the art open source stack to countries that want to build their own AI products off on top of fine tuned or post trained LLMs that meet their definition of free speech or ideals or morals. The stack by default will be Huawei, Ascend, Deep Sea.

Yeah, I totally buy this. I think that being able to sort of have the best open source models in the world, be American, is really important for a similar reason as like the chip stack and the data centers and the cloud services. I think there's a question about how sticky is this ecosystem actually. So you talk to people who are like, yeah, we really need to lock in the tech stack globally. Like American open source models need to be sort of like the Rails that the world runs on. But then if you look at sort of how AI developers work, they are very happy to switch between different base models for their application depending on which happens to be the best. You look at the revenue of Frontier Labs and when they have the best model it's up here, or when they don't, it's down here. Everyone is switching every day depending on who has the best model. So yeah, you want to diffuse American open source as widely as possible, but what about it makes it sticky? And my hypothesis would be that it's probably the security and reliability side of things. So everyone's worried about the fact that you can insert backdoor to create sleeper agents into open source models and there's no way to actually detect these. I think the US wins if it can prove that it has the most trustworthy and reliable models over China, similar to how I think US cloud computing companies compete over Huawei and Alibaba Cloud. Often Huawei and Alibaba are coming to the market with a cheaper option, but the US is just more trustworthy in terms of data privacy, security, et cetera. So I think trying to figure out those technical problems around security, reliability, interpretability and proving that US models win across those dimensions is probably the way to make the kind of open source models from the US more sticky or just sort of be way better. And this is where most of the effort is currently going and definitely support those efforts as well. Like building out more domestic compute, for example, and finding more trading data sets.

Yeah, how do you think about the dynamic between the importance of the application layer versus the foundation model layer? We've seen efforts on the foundation model layer at the national level all over the place. But let's just use Mistral as an example. Mistral has a consumer app called LeChat. It is a direct competitor to ChatGPT and I think that's great for the French and they could potentially have a fine tuned model that meets their standards and guidelines. But if at the end of the day, the French consumers, 90% of them are using Google and 90% of them use use OpenAI, well then all of that is kind of worthless. And sure, maybe Mistral will be cheaper in the enterprise and be implemented in French businesses or European businesses, but in terms of like control of the population, that feels like the diffusion of American ideals in Europe, which doesn't seem extremely controversial because American and European ideal ideals are pretty similar. But. But you can see how this would play out in other countries.

Yeah, totally. And the economics are pretty brutal here.

Right.

We're in a regime where the amount of compute being used to train a model goes up 5x every single year. We're moving from $100 million to train a model last year to rapidly approaching the billions. If you are a company committing to this and you're only sort of just slightly better or worse than one of these huge tech companies, you can't keep sustaining this over time. You have to have to check out eventually.

Yeah, and we've seen that with a lot of the early stage foundation model companies that have raised trained something but never been on the frontier and now they're falling out of favor, more or less.

Yeah, totally interesting.

Has there been any conversation on the ground in D.C. or have you heard any chatter around the Manus investment that definitely kicked that Benchmark made kicked. The hornets now nest a little bit in the hornet's nest of American dynamists.

Deli and Asparuha, the Traverse Fund.

But to give Benchmark a little bit of credit, if you're going to be mad at Benchmark for making an investment in Manus, you also in some ways I think have to be mad at Jensen for going up and setting research and design R and D center in Shanghai right now explicitly to work on developing products for the Chinese AI ecosystem and in some way the CCP directly.

Yeah, it's a bit hard to evaluate. I think one, one of the US advantages is very deep capital markets.

Right.

And so being able to exert financial control over startups overseas by sort of like acquiring stakes is potentially a way to, to have a better, fairer, more aligned global system overall. I think this is high when it comes to Chinese companies.

But does America benefit from having American capital allocators and ByteDance? I don't think we have much influence or control over what ByteDance does.

Yeah, exactly. So I think for big companies, especially those that are part of this Chinese sort of state industrial military complex, this is a pretty poor prospect. This is why the Treasury Department has outbound investment restrictions in a bunch of different industries which have been expanded to AI over time, relatively slowly though. So yeah, one thing that they've been sort of working on is trying to figure out whether to apply these outbound investment restrictions more solidly to commercial AI developers and commercial AI cluster operators. So investments coming from VCs actually restricting investments of those kinds into China. And yeah, this is complicated by the fact that just like due diligence is really hard, like let's say you're investing into an application developer who's doing something pretty innocuous like automated code agents or search or something along these lines you don't have any control over. Are they going to work with the Chinese military in the future? Are they going to be sort of like an instrument of state backed surveillance over the local population? They're not going to to tell you that. And they might not have plans to do that, but they can certainly be compelled to do that in the future. So the due diligence question is super hard.

Do you think regulators or the American government needs to be thinking about the pre training scaling law potentially not holding or reaching some sort of diminishing marginal return? We've seen the data from GPT 4.5. It feels like GPT 5 might not just be 100x bigger than GPT 4.5. It might actually be some sort of mixture of experts, different models and more of almost like a product challenge than just a scaling and just get the more chips challenge at the same time. OpenAI is also investing in Stargate and there's still a drumbeat of ever larger data centers in the United States. But the overall tone of of AI research labs in America seems to have shifted away from just the ever bigger transformer. And there seems to be a somewhat of a, somewhat of a resignation to this idea that there might be more challenges on the path to ASI than merely scaling up the architecture that we have right now.

Yeah, I think there's a few things here. One is that obviously these companies are still making huge investments in clusters and energy to get to the next order of magnitude of scale. So there's some level of just financial buy in to the idea that pre training scaling will continue, but also recognition that we've got this other scaling law that sort of test time compute scaling law and now reinforcement learning as a paradigm that seems to really be working for language models where a lot of companies are starting to put more of their compute resources overall. So I think the rough balance now seems to be around sort of 8020 pre training compute and then post training. And I expect what we might see as we see sort of companies who are building out these clusters and these energy sources to support them, where are they going to sort of balance the compute allocation across those. The calculus seems to be that yeah, pre training compute is relatively less promising to before and putting more of your resources in a relative sense into rl, which is sort of very much at kind of like the early stages of scaling up is the better strategy at the moment.

Yeah, I mean the other side of this is like even beyond post training and RL as reasoning tokens and just more test time compute more inference cost increases. Maybe the real way to get a GDP boost or a competitive advantage out of AI is just to make sure that there is an H100 or equivalent for every member of your society or every citizen. Because everyone will need to be inferencing at a very high level, very large model basically constantly. And so even if you train the greatest model, if you can't have every single one of your citizens constantly inferencing it all day long, you're not going to see the benefits of I need.

My AI companion constantly on.

I mean we do need code gen and we need research and we need need answers. And if we're timing out, it's not.

Just codegen and Deep Research are going to be competing with the AI companions for inference.

Yeah, probably just to I guess maybe push back on maybe hypothesis underlying that. I am very confused about where most of the compute is going to be spent and how that is going to be distributed across people. So I can easily imagine a world like in two years where most people in the world still aren't really using simple tools like ChatGPT. My grandma still never heard of it. But at the same time you have some companies at the frontier who are deploying millions to billions of agents internally. So you had this really unequally distributed use of compute overall. So yeah, I kind of buy the idea that there'll be just like massively uneven sort of like usage of these kinds of resources and really located in particular countries and within particular companies.

Yes, agree in the sum total of the importance of inference and compute allocated and available for inference, but potentially disagree on the distribution of that. And I think now that you hash that out, I think that makes a lot of sense. You already see that just in the prosumer versus consumer market. I'm probably kicking off like three to five Deep Research reports using a lot of tokens. I'm getting my $200 worth and there's a lot of people that are, you know, just land on it every once in a while to toy around with it. That makes a ton of sense. What's next, Jordy? What should we talk about?

How have you guys had success explaining the potential for AI? You know, AI's potential progress in the next few years in Washington, broadly, do you feel like lawmakers have fully, kind of of fully understand the potential? Right. Nobody has a crystal ball. We can't predict the future. But if you sort of extrapolate trends and even just use the products today, do you feel like Washington is pricing it in or is it still, you know, or are people going to be extremely surprised in the next few years?

Yeah, my bet is 100% extremely surprising. I am, I think, consistently disappointed with how the lack of kind of level of AGI pilled people in DC are even with sort of current capabilities and where the sort of trend is obviously going. I think there's a lot that just isn't being priced in about kind of how weird the world is in five years time. There's also, I think, a sense in which there's a real loss here in that if you look at technologies like the Internet, which as you probably know, came from arpanet with this DARPA funded project, as well as early sort of genomics with the Human Genome project, these were technologies where the government sort of saw what was coming and took sort of a really active role in shaping the development of the technology through basic R and D. So with arpanet, for example, the focus was really on creating a resilient network system that could survive a nuclear bomb. But also they were able to take that sort of secure network infrastructure and apply the notion of kind of like openness and freedom of information to create a scaled global network that really represented American values and was very secure. We don't see an equivalent kind of level of basic R and D investment in the United States around AI. And that would be really cool to see because there's basically a bunch of problems where right now industry is focused on where the money is, which is B2B, SaaS, apps and chatbots. But there's a huge space of just like, if you accept that over the next few years we'll have these incredible new AI capabilities. There's all these massive important societal and scientific problems in areas like materials discovery, drug discovery, et cetera, where the government could be placing essentially huge bets that could pay off within a few years. And we're kind of not doing that because we're sort of in D.C. at least failing to see sort of where the future is going and therefore what the role for this kind of basic R and D is. So yeah, there's a congressional coalition that's just started called the American Science Acceleration Project, which we're really excited about and try to build hype around. But they. I think I have the right idea around this, but there's a deficit of this kind of thinking in D.C. at the moment.

Last question for me, how is Meta's reputation changed in D.C. over the last few years? Famously, Zuck goes to Capitol Hill. They don't even understand how his business model works. He says, senator, we sell ads. He was castigated for being too left, then too right and very a lot of political hot button issues around the Facebook app and the type of content it's servicing. Obviously a big vibe shift. There's. But now it seems like Meta is increasingly a very important tool in the American foreign diplomacy AI tool chest with Llama. Llama is of course in their open source model. That's, you know, there's Defense LLAMA now the DoD is partnered with Meta on this and yet today we learned that their behemoth model is struggling to improve capabilities. They're facing setbacks. Has the, has the tune changed in D.C. to say, hey Zuck, like sell more ads, please, like do more stuff. We gotta, we gotta get you, you pumping because you're a national champion now.

Yeah, I'd say by and large there's different factions in D.C. who care about different things. Obviously Meta is going through this big antitrust case at the moment as well. Has been going through it. Yeah. On the AI side, I guess it's interesting as well. Meta is very much seen as kind of like the darling of open source supremacy for the U.S. i think it's kind of awkward for a lot of Meta fans to see the latest batch of models and then them really not be that impressive. And also potentially a bit of gaming with leaderboards and sort of what models they're releasing there. Obviously they've executed this strategic pivot to appeal to the current administration with getting rid of fact checking and bringing in the community notes type approach. And that seems to have been pretty effective. But yeah, I think they've certainly got a lot of backers here. And the open source approach, it's really good to have a really well capitalized company really pursuing the strategy overall role. But yeah, I think they're copying a bit of heat for not actually delivering on the promise to some extent. And also people there's sort of like another faction that's pretty worried about open source models with capabilities that could be significantly misused, especially in the cyber domain, being freely available to the whole world, but that's less of a concern while they're behind.

Yeah, it was very interesting in the press release around this and the management of the news that they were delaying the rollout. They didn't say, say oh it's too dangerous to release. They could have easily said that. That's always an easy out for the AI labs to say. It's just too good. Trust us. We can't trust you with it. We're doing more safety research instead. It seems like there's a little bit of an admission that it's just not at the level we want it to be.

Jordy, this might be out of scope for you, but do you think that AI is art is at a much is being used in nefarious ways in the context of social engineering attacks at a greater scale than people sort of realized today. This was top of mind just due to the Coinbase news this week, the leak that they had and I think people broadly anecdotally reported that they just felt like they had a huge uptick in like sort of inbound calls and social engineering attacks. My question is AI is already when you're using tools like Sesame and some of these lower, you know, Sesame is obviously state of the art but even some of these lower latency video models models should already be capable and better at social engineering attacks than like you know, a PhD level person globally that, that even, even if English wasn't their first language and you know. So anyways, I'm curious if you have.

Cybersecurity, social engineering, any sort of like insights regulation around it?

Yeah, no insights into the true extent. I will note that it is surprising to me that we don't seem to see more of this. My impression is that from sort of GPT 3.5 onwards we've had LLMs that can produce better text, more convincing text than the kind of median phishing email, which as you know is often pretty poorly written. Maybe that's deliberate. But yeah, it's kind of weird to me that we haven't seen mass sort of spear phishing campaigns of the kind that have been possible for several years now now yet. Or at least they haven't been widely reported. Maybe it's that yeah, existing sort of filters and defensive approaches work. Maybe we shouldn't expect actually there'd be that many people who are trying to pick this low hanging fruit and they're not technically sophisticated enough or maybe it's like happening and not being reported on.

But yeah, I find, I think there's potential that it's happening, but it's happening to a demographic that doesn't even know it's happening. Right. Like I don't pick up random calls. Right. I just don't. I not going to answer that.

You know, of course maybe the last time I called you it was actually a bot.

Yeah, that's true. That's true, John.

You do pick up non random calls. But that's the point of them. Yeah, I mean the same thing happened with the crypto stuff. Like there were a lot of the victims of cryptocurrency scams like weren't profiled in the New York Times and so we just didn't really hear about them because like the people that with the loudest microphones didn't fall for the scams. Yeah, tricky. Anyway, thank you so much for joining Tim. This was fantastic. I'm glad we survived the attacks from the nation state actors that don't want us. We kept the stream up, a stream together. We really appreciate it. We'd love to have you back and this was fantastic.

Yeah.

Thanks for coming on. We'll talk to you soon.

Have a great weekend.

Next up we're bringing Chris Best from Substack. But first let me tell you about ad quick.ad quick.com out of home advertising made easy and measurable. Say goodbye to the headaches of out of home advertising. Ad Quick combines technology, out of home expertise and data to enable efficiency buying seamless ad buying across the globe. And we should also talk about wander.

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That jingle is unstoppable.

Unstoppable. We got to get a jingle for Substack. What's the Substack jingle?

Do you have a tagline? What's your landing page? Hero Hero.

Text the app for independent voices.

There we go. Same melody.

Take back your minds. Take back your minds.

Take back your mind.

Put that in the jingle.

How is the process of taking back minds God going?

It's going Pretty well. Okay, can't complain across 5 million paid subscriptions.

Wow, that's a lot.

Wow.

Awesome.

Blown ahead of I think all of the like legacy media apps combined.

Amazing. Chris and I were in the same YC batch. Winter 18, another one, another.

So. So my biggest thing with John is actually probably good. If John had just invested in, in in his batch he would have been too post economic to start a podcast and we wouldn't be here.

Coinbase, Instacart, Zapier even. What was the other one? The crypto exchange that absolutely ripped the NFT marketplace. OpenSea was in our batch.

Replit.

Yeah, yeah, yeah. Remarkable companies. It was good times. So yeah, I mean take me through the history and evolution of Substack and where you're going next.

Yeah, I mean we started, we were in winter 2018 together. The basic theory is we're building a new economic engine for culture. You know, we want to harness the power of technology, the power of worlds, you know, Internet scale networks combined with a business model that actually powers independence. The version of that, the simple version of that that we started with is basically make it dead simple to do a paid email newsletter. But as the years have gone by we've grown that into multi format. You can do, you could write, you can do a podcast, you can do live video. We've got this network and this app. You can get the Substack app from the app store and discover this whole universe of the smartest, best independent media and culture on the Internet. And that's what we're building next basically. I mean we're building a bunch of video tools. We've got this live, you know, live tool that lets you do something that feels like a FaceTime call and then I magically turns it into like a produced podcast and series of clips. So if not everybody is the brilliant YouTube sensations that you guys are, if you're just someone that has something to say, we make it that easy.

That's totally super powerful. Was Ben Thompson really an inspiration? He kind of tells that story. I don't know if that's true. That Sir Techery and he kind of pioneered this like independent newsletter creator, really scaled the business. But I mean had you been reading him at the time? Had you taken lessons away from Sir Techery when you built Substack?

Yeah, there was a few people doing it right? There was like, you know, because we had this, this cockamamie scheme, we're like hey, I bet you people would subscribe to, you know, things they deeply value. If, if you had something Great. And there was a handful of people that were doing it. You know, Andrew Sullivan did this with kind of like the Daily Dish back in the day. Ben Thompson had Stratechary. And here's this guy, you know, writing an email newsletter from his bedroom in Taiwan, making by our calculations, millions of dollars a year. We're like, you know, that sounds pretty sweet. Like, why does, why do more people not do that? Basically? And the answer to that turned out to be it's way too hard. So what if we made it way easier?

Yeah. I mean, he's invested immensely in technology to build up Passport and what he's done and now there's a few other companies that run on it. But yeah, where does this all go? I mean, I guess the big question is like, ads, product, you know, is tied to the written media. Wall Street Journal has subscriptions and ads, New York Times has subscriptions. And even after you subscribe, you still get ads. We are an ad powered show. Ads feel very. They get a lot of negative attention, a lot of negative stated preferences. But the revealed preference is almost always people don't mind ads and scroll right past them on Instagram and sometimes even get value from them. We've been very pro ads. But what has your take been on ads generally in the substack world?

The thing that's actually different about Substack is kind of creator ownership and a model that rewards quality and value. So the fact on Substack that you people don't subscribe to substack, they subscribe to you. If you make something truly great and it people value it, they come. All those things are what actually set Substack apart. You know, the formats are similar to what you see elsewhere. You get, you can, you can write a long form article, you can write, make a podcast, you can do a video. Like, those are, those are not novel things. The thing that's novel is this business model that powers independence. The fact that you own the, you know, it's your business, you are getting the upside. You want to invest in the quality. And I think there are methods of doing sponsorships and advertising that are, that, that, that work with that.

Right.

The fact that people, you know, people are paying premium for you guys to advertise on this program. Not because you're getting like the most clicks ever that gets sold at a market, like at some market rate for the demographic, but because you are making something special and you have tremendous, you know, jingle skills. But the audience is like, is magical. Anyway, there are a bunch of people today we're doing all subscription. We're powering that thing that actually works really well, shockingly well. Much better than people thought it was going to work. People are consistently surprised by how well that business model can work for them. But there are also people on Substack who are doing sponsorships and doing tremendously well. And so I do think that model can and should coexist with high quality media endeavors.

Do you believe the medium is the message? We've kind of felt this where we decided to go live for somewhat of like a technical reason. Just that the way YouTube's organized, it kind of made things easier. But then once we were live, we realized, well, we're faster. We're not. There's no delay between us recording and uploading and so we can react to the news. We could, we could open up X right now and read a headline that just dropped with you and get your reaction. And it's kind of changed the nature of the show. What's been your processing of like the McLuhan ideology?

I'm a huge believer in live for that exact reason. You know, we're building this video product that you that is live within substack. And I think it's almost like a hack that sets the social expectation. The fact that you're going to be able to sit down, make this thing, ship it off. It's not necessarily the case that the majority of the audience is going to watch live. Totally great that those of you here. But it's, you know, it's going to be, there's going to be a vod, there's going to be clips, clips. Those might be the places that actually get the distribution. But as a hack to make the thing, the fact that the, you know, the social expectation between us right now is we're sitting down, having a live conversation makes it easier, makes it faster. It does feel different. Like, I don't know if you have this, but I feel, you know, the feeling of being live is a little bit more energizing than otherwise.

Definitely. And then also it just builds. I mean, we like it because it builds trust with you. Like, yes, there will be cloud clips, but we're not going to edit. We can't edit out what you're saying. So if you want to make your case in some way, we can't be like, oh, we didn't want to put that in.

Yeah, I could go back to the tape and say, well, here's the full context.

Exactly, exactly. It's always there.

Can you talk about this? So, Juan, I want your help. Kind of framing something. Because there's. In my mind, there's this stages of substack. Right. Like our audience, at least the initial core audience is this sort of like terminally online. X, you know, tech enthusiast, genius, wealthy.

That's a core audience. But yeah, average net worth, you could.

Say terminally online, you know.

Yeah.

20 to, you know, go to.

Definitely. Or like in the conversation.

Definitely in the conversation. No, but. But to me, there's been these stages of stubstack where, like, I don't know if it was like a year ago at this point that I noticed that substack had not become a household name, but it had been become outside of tech. Outside of tech.

Emily Oster, for example, but had just.

Become something that, that, that kids I went to college with that aren't in tech were.

Yep.

Subscribed to probably three substacks. And it was like part of that.

It wasn't just all like, it was part of. It became.

It became like clearly part of popular culture online.

Yeah. Yeah.

Was there a note? Was there a moment? Is that like the wrong analysis? And I just wasn't paying attention outside of our bubble, or did you feel something like that too?

I get this question a lot, and I think people, because it kind of grows in pockets, right? Like, there'll be, you know, this bunch of crypto people that all join at the same time or a bunch of politics people or a bunch of finance. Like, there's sort of like these, you know, next adjacent market pockets as it grows. And so all along there's. I've sort of had people ask me this feel like it feels like substack is suddenly blowing up. Like, does that feel like has your life changed? And internally, like, it's just been growing really, consistently, really steadily. Like, the curve just looks like a steady exponential curve. And so it is kind of always true. Like, this is. This is the most exciting time I have had. You know, I do feel it too. Like, I get less blank looks when I tell people I'm working on substack than I used to. But yeah, it's been a. It's been a steady march.

How has kind of the war with. With X. Maybe the war is not the right word for it, but obviously removing links.

Platform change.

Yeah, platform changes obviously frustrated a lot of the core creators who had been building an audience in both places. But from my view, it seems like they maybe, you know, created a monster. Like, in the sense that, like, it maybe made you guys react and be like. And it. Maybe it was like a short term win, but will maybe be a mistake long term and that maybe it's kind of pushed you guys to think even bigger about what, what substack is.

I mean, the funny thing here is that Ben Thompson credits his early growth with LinkedIn and sharing links on LinkedIn. And then LinkedIn had an algorithm change and he had said that it wouldn't be possible to build search hickory the way he did in the modern LinkedIn era. So there was kind of like a LinkedIn vibe too. But yeah, I'm interested to hear how you've been processing just all the platform changes really.

So I mean this has always been, my theory is if you want to build one of these businesses, you need a model that supports independence. You need people to be able to subscribe to your, you. And then you also need like Internet scale networks to grow on. And in the old days of substack it would be, you know, at the very start, like trajectory, you'd have this newsletter, this website, but then you'd have to go on Twitter to promote it or go on LinkedIn or go on Instagram or wherever. We always want you to be able to do that. We want you to be able to publish. It's not a walled garden, like put it everywhere, put it on the RSS feeds, put it on YouTube, whatever. But you're totally at the mercy then of these other platforms that don't necessarily, you know, sometimes they go to war with you. Like Elon got pissed off at us, but a lot of the time they just, they don't care. Care, right. Zuck can turn around and say we're not doing politics for a little while because people got mad at us. And if you're somebody that writes about politics, that's really bad for you. And so we always knew that we needed to make our own network, our own place. Fucking zoom reactions.

Turn that off.

I think it's at the OS level.

It's at the OS level.

I feel like I've turned this off a thousand times and it sometimes still comes back. If we could just shoot whoever, whoever built that feature, that's perfect anyway. We had to build the network. We knew we had to build a network. You know, it doesn't make sense. It's not like, you know, Facebook or LinkedIn or X or anybody's TikTok's job to help you, like, you know, take your audience and own it and make something independent. It's never like been their main thing. So we knew we had to do that. That's why we built you know the Substack app in the first place, which is why Elon got so mad at us. He felt like we were, you know, competing, but ultimately we just knew these independent places need their own network that actually wants them to grow and thrive. It was a big painful thing for people that were on the platform. It sucked that you're like, links didn't work. Super annoying. But it was a. It was a very small fraction of traffic. Like it didn't slow down the business or the numbers at all. There was a lot of sturm and drang. It was very like, you know, for people that are like, had a big Twitter presence and were trying to make a substack, it was very painful and stressful, but it didn't slow down the growth at all.

That's cool.

What's yours? In the team's sort of decision making process, it feels like at a bunch of different points with Substack, you could make a product decision that might drive immediate, basically make the number go up, but maybe wasn't aligned with the kind of platform that you wanted to be and maybe not even aligned with humanity. And on that note, there's sort of this like interesting thing where every platform maybe other than Substack is sort of like converging on being the same app. This sort of like short form sloppification of social media where it's like, you know, doing a slot machine with information and it feels like Substack is orienting around long form content. We had Jason Fried on yesterday. That sort of rambling.

But no, no, I completely agree. I was gonna ask the same question. I feel like if I land on a sub stack link, it's gonna be written by a human. It's not gonna be particularly sloppy. I might not like the particular topic or something, but I feel that it's gonna have like this premium like vibe to it, I guess. And I'm wondering if there's. Is there. Are we just early and there's a coming wave of slop or that you're gonna have to fight or.

I mean, here's my take on this is, you know, I think if you put yourself in a. The position you described where it's like, hey, we've got this business, we're trying to make the number go up and we either need to make the number go up or we need to make something that's good that we believe in and we kind of have to like make that choice. I think as soon as you have to make that choice, that already sucks because both of those Choices suck. Right? It sucks if you kind of give up your principles and make the number go up. But it also sucks if you stick with your principles. And the business. Business, like it hurts the business and the business doesn't thrive. Ultimately, the business of substack needs to grow and support the thing we're making. And so the thing that we've tried to do is yoke the success of the business, set up the business model and the fundamental way that it works so that in order to make the number go up, we have to do the thing that's actually good. So an example of this is, you know, the way that we make money is it's completely free to publish on substack to any size. Audience. Audience. You guys should cross publish on substack, by the way. That'd be sick. And then we only make money when you make money, right? So we're trying to help you grow. We make money when you make money. And so, you know, we have an algorithm the same way that Twitter or TikTok has an algorithm. We even support short form video, you can see clips you can read, long form stuff, you can watch a long form podcast. But it turns out that when you're tuning the algorithm to introduce people to things that they deeply value and might pay for, the emergent effect of that is very different than if you take the same technology and point it at the goal of get people to spend as much time here as possible.

Yeah, that makes sense because I might pay and then be satisfied, close the app. But that's a win for the algorithm. Yes.

Our algorithm says great, right? Whereas, you know, Elon's been public about the links thing. It used to be just substack. Now it's everyone. He's like, yeah, if you're scrolling your feed, you click into a long form post, you go and read that thing and get deep value from it. You just tank the metrics. Yeah, you're not seeing any ads like.

What are we doing? It makes sense. How is the health of the overall creator economy? There was a big boom where venture capitalists were investing in the creator economy. That's kind of died down. But how healthy is the creator economy broadly?

We were joking yesterday. Erewhon in many ways in LA is a product of the creator economy. There has to be double digit percentage of Erewhon's revenue as just creator revenue. You know that that flows in in different ways.

And there for sure, a lot of G wagons in the parking lot.

It's the LA equivalent of like the dot com bubble Yep.

Erewhon.

I've never liked, I've never liked the term creator economy. Even the term content creator kind of gives me hives. Here's the thing that I think is not going away is, you know, the, the media landscape is shifting. The legacy model have been eaten up by Internet things that don't necessarily support, you know, the old businesses. And there's this shift to a shift in power to independent creators, people like you that can just set up, start a thing, make something that matters, earn the trust of people by building, going direct, building an audience. I think that trend is extremely robust. I think that thing is going to, is sort of inevitably going to happen at this point point. But I do think it's sort of undecided which version of that future we get. And so we see our, you know, the thing we're working on at substack is could try to bring about kind of like the best and most valuable version of that future. But I think that, I think that shift is not going away.

Yeah, I mean, you talking about the, the content creator as a bad term, do you prefer journalist, writer, like more specific scalpel like terms? Is that what you're getting at? Or what specifically don't you like about the idea of the word content or the word content creator? The phrase, it's pre.

Rational man. It just kind of feels, it feels like a slop version. Right?

Yeah.

You're a journalist, you're a writer, you're a podcaster, an analyst, analyst, broadcaster, filmmaker, you know, comic. There's a million things you can be. And listen, I've made my peace with creator. Like it's, it's a good generic term. But I think there was, I think there was a moment where we kind of like cargo culted the creator economy and everybody got really sort of hyped up about it in a fluffy way and missed the, the, the deeper thing that was actually still happening.

What actually happened is that there was like a specific data point which is that VCs realized that creator content creators were the fastest growing SMB category. And they were just like, okay, we should deploy like a billion dollars.

We gotta make money off this, we.

Gotta make, we gotta find out how to make money on this. And the thing that people missed is that that had been a sort of, they were sort of like a decade into that trend. And so people funded a lot of businesses that were like banks for creators. But a creator's like, you know, why would a creator not just use, you know, we use ramp, right? Like, why would a creator not just go to bank of America and just get a bank account. Right. And so I think the sort of interesting investable opportunities were the substacks, which is like a new economic, not to use your tagline, but like an economic creating a new economic engine for media.

They should have invested in Erewhon because that's like the grocery store for creators.

Yeah, it's all down.

They should have just bought stock in Mercedes because they make the small SUV.

For.

The creator economy. I want to talk about the value of curation versus instantiation of ideas. I'm not sure if you've been following Ben Thompson's erosion of the evolution of the printing press to the Internet, making distribution zero marginal cost to the instantiation of ideas. As with GPT and deep research and language models, it's become easier and easier to create a deep research report. The writing is good. It still feels like you can tell when it's AI written, but it's at least fine. Yeah, it's at least fine. But I guess the question is, are there any substackers out there that are openly using AI tools to write? But the value that they bring, the human element is just curation. Because sometimes I feel like I should just share all the deep research reports that I put together because they're cool and I'm asking interesting questions and the humanness comes from the question that I'm asking. And very few people would think to ask that question to deep research and the answer is less important than the question versus just the general trend in language models. If you have any takes there.

Yeah, I mean, the way I think of it is, you know, we, even before AI, we already lived in a world of infinite content. You can't get bored, you can't run into stuff to see or watch.

Yeah.

And so the limiting factor is like your attention in your life. Like what, what should you pay attention to? Who are you going to trust? What matters? Like, sort of. It's. It's the human alignment problem. Like, this is what culture is. It's not just getting what you want, it's figuring out what to want in the first place. And that's the thing that's actually valuable. Even before AI, nobody's subscribing to substack because it's like, oh, I don't have enough emails to read and I want to pay money for that. You're subscribing for a perspective. You're subscribing for some connection, some piece of trust, some piece of curiosity. And so I think all of these Technology tools that just give people superpowers, kind of supercharge both sides of that. Now there's a thousand times infinity content. There's more than you could, even more. But also the people who, who have those relationships can have so much creative leverage. And I think, like, literally writing for me is, is one that's not that exciting yet, although it's not impossible. But like, yeah, help me do the research, Help me figure this thing out. Help me, you know, put the pieces of this together. I think there's, you know, there's even people that have, you know, Lenny Wojcicki has his Lenny bot that people subscribers can talk to. I think all that stuff is awesome.

Talk about growth hacks. If someone out there is starting a substack today from zero, they have no audience. What can they do to turbocharge their business in the short term?

The biggest growth hack I often have to give people is just start the start the thing. A lot of people I talk to are thinking about, oh, I should do this. Should I write 10 things? Should I come up with this plan? Should I do this? Everybody that succeeds that I see just go, just gets going, just starts writing, starts publishing. You know, try to make something good, try to share with people and really just have a very strong bias towards action, towards thinking and moving in public. And then kind of like correct based on feedback rather than trying to come up with some genius scheme. All that said, you know, make great stuff, share with people.

Have you been able to dig into any of the quantum quantif quantitative metrics around the most successful substacks? Like, is there a correlation between posting weekly and revenue or length of post? Can a deep dive ever be too long on substack or too short? Or are there any patterns that you've seen amongst the top performers?

There is a trend that says, look, all else being equal, being consistent, and publishing pretty frequently really does help. Yeah, it's. It's a lot easier, you know, if you're publishing multiple times a week consistently for a long period, your chances of success really do skyrocket. Other than that, though, we sort of have the problem. You see this in marketing too, where sometimes the, like, the opposite of a good idea is a good idea.

Yep.

Where it's like one thing works, but also like the opposite of that thing also works. You just got to find something that's sort of good and differentiate it. So, yeah, make something that's interesting, authentic, that you actually like, and then make a lot of it is.

Yeah, I mean, we found that 100%. I mean 15 hours a week, three hours a day. And not only that, but I mean I think we posted on X 20 times yesterday and like 10 clips and like some of them don't do very well but you just set the quality bar where you set it and then you just try and get those, you know, let the winners rock.

Well, I'll tell you what, you cross stream to Substack.

Easy peasy.

We got AI auto clips. You can make your own, but also people will just find them.

I love it. Let's hear it for that.

Let's hear it for that. I like the sound of that. No, I'm excited to get over there, to be honest. We've been so, you know, the core challenge for TVPN is that we're a startup but we're, you know, John and I are the founders but we happen to be live for three hours a day and then we have to spend like a couple hours prepping the show. And so there's just like. And we've built out.

We're individual contributors.

An amazing team now, but it's just about adding these other channels. But I see a ton of opportunity on Substack and I just love how thoughtful you guys have been about, you know, building the platform and staying true to your values. It's awesome to see.

I have one last question and then we'll let you go. Lessons from Lulu going direct. What did you learn from working with her? What have you learned from the most recent Lulu ideology and what it means to communicate as a CEO to an audience of investors, employees, customers, etc.

I'm a huge Lulu, Stan. I've learned a lot from her. Maybe one thing that is non obvious that I got from working with her that I wouldn't have necessarily picked up on just from the output is, is kind of like the. In many cases, the principles and the morals and the facts come first. The most important part of the Go Direct Comms thing is not just how do I spin this or how do I posture it or how do I say. It's like, are you doing the right thing? Are you willing to stand behind the message that you're coming with? I think that thing matters a lot.

Yeah, that's great. Well, thank you so much for joining.

This is awesome. Come back on again soon.

We'll talk to you soon. See you on Substack over there. Bye. Let's tell you about bezel. Get bezel.com your bezel concierge is available now to source you any watch on the planet. Seriously, Any watch also potentially creator economy startup. A lot of creators getting watches. Yeah, lots of folks in tech getting watches.

Their cap table is at absolutely stacked.

It is. Lots of creators.

Talk about numerals. Benchmark Series A. Yeah, talk about a stacked cap table.

Anyway, our next guest is here. We have Sean from Stored announcing a major size gong moment. Welcome to the stream. Sean, how you doing?

Good to be here.

Thank you guys for having me.

Kick it off with the funding announcement. What's going on? What's new with you?

Yeah, we're excited today to announce that we've raised $200 million across our series E. Congratulations. Series E. Series E. Been waiting for that gong moment.

That's amazing.

Let's go. We're going to hit more, we're going.

To hit more sound effects. Give me the Ashton Hall. Overnight success. Yeah. How long have you been doing this?

I'm a few months away from my 10 year anniversary with storage.

Exactly.

Overnight success.

Overnight classic. Overnight success.

That's great. But introduce the company, Break it down for us. What do you do?

For sure. So we're building a commerce enablement platform that's entirely designed to level the shipping experience for brands of all sizes. With Prime. Over the last two decades, retail has changed. Where you don't walk in a store and swipe your credit card and walk out with the product, you swipe your credit card online and you walk out with trust. Trust that you're going to get the right product when the brand said you're going to have easy returns. And these massive giants like Amazon have realized that is what's driving today's buying behavior. And so they've invested tens of billions of dollars into building out this competitive advantage. Meanwhile, every other brand is kind of in this stone age where if it's take cloud computing, they're still building their own data centers, managing their own racks in their office. And so we give them a scalable platform that combines an end to end physical fulfillment network that ships over 30 million packages a year. Last year we hit about 15% of U.S. households. We powered over 1% of Black Friday, Cyber Monday. But then all of the technology, not only that runs that network, but that also speaks to the consumer. So there's a high probability to either yourselves or people listening actually delivered you a package before powered that tracking link, you may never even have known.

Wow. So talk about how asset heavy or asset light the business is. What do you own? Do you own warehouses, trucks, planes, boats? What are you sitting on top of? Who are your key partners to make this happen?

Yeah, great question. Our three pillars are really a network, software and scale. We give economies of scale across a network of assets. Some of those we run ourselves. So we do now operate 13 fulfillment centers, employ about 2,000 individuals across those fulfillment cities.

There we go. Congratulations. That's huge.

Crazy.

We used to be on planes all the time, constantly going to a different city. But then about 70% of our business is an entirely asset light network. Existing warehouses, existing trucks, particularly existing last mile carriers where we manage a network of about three dozen of them. But then all of that overlaid with our technology. So the customer has one consistent experience no matter where we deploy their inventory.

We talked to Harley at Shopify. How important are you small businesses to your business versus going after the scaled e commerce players? Obviously not Amazon, but maybe Walmart or Macy's and the really big players.

Great question. I'd say we're kind of squarely in the middle where we serve a lot of mid market brands, about 500 of today's market leaders. So we power all of the deliveries for brands like Athletic Greens, Seed Health True Classic Tees, Proactive, the Skincare Equip, the toothbrushes, Billy the Razor. It's a lot of today's kind of multi hundred million revenue leading brands. The types of companies you'd see walking the aisles of a target for example.

Yeah, is that, is that mostly founder led? I imagine that a lot of the founders of those companies kind of in your boat, been in business maybe a decade, raised a bunch of money and kind of at the same conferences. Is that how you're doing biz dev? Do you have a massive salesforce? Are you doing outbound? What's working, what's not?

Yeah, we are one of the flattest founder led sales cultures you'll find. We actually sell. I mean last year we were nine figures of new sales, this year we multi nine figures of new sales. In terms of how we're growing, we have a 7 rep sales team and so we are on the plane all the time meeting with our different brands, meeting with these customers and I think that's actually one thing that blew away investors in this round. If you look at our last 4/4 of sales beats, I mean we were 3x our Q1 goal, this Q1 alone most of the year we have a fraction of a kind of percent of revenue on sales and marketing and R D to a lot of peer companies, yet a lot of roi.

This is such a funny interview because not only is it live, which is obviously a little higher stakes, but there's Also a very chaotic soundboard potentially throwing you off.

Well, I mean there's so many every single. I. I don't want to throw you off. I just.

It's good news.

That's my personal reaction. But if you can make it through.

A TVPN interview like Bloomberg or CNBC is going to be a walk in the park. No soundboard, really easy. You got a question?

What was the, what was the dynamic? I mean, I imagine the last, you know, five, six weeks have been intensely stressful just because of what your underlying customers have been going through. Did the round get kind of done before that or were you simultaneously navigating trade? I imagine you were navigating a trade war and a new financing. Just sounds, sounds intense. But what did the timeline look like?

Yeah, we kind of come to the principle that everything crazy happens at once at storage, so it's never a time off. I'd say that we were laying the groundwork for some of this before the trade war really started. And it kind of threw a big wrench into the fundraise in terms of some people realized how good it was for us and some people got really scared. Care thankfully, and I'm so fortunate to say Stored grew massively at other issues. Take Covid, take war breaking out, take the UPS or Canada Post strikes. All those are a reason for a brand to say, you know what, I'm not going to face this on my own. I don't have the economies of scale to stay flexible. I don't want all the risk on my business. Let me go to a network like stored. And so thankfully, very similar here where there's really two tariff issues going on. One is anything that comes into the ports from other countries in large quantities and that that's kind of the standard tariff people are talking about. The other one is the de minimis IMAX section 3, 2, 1. All these E commerce brands sending small packages into the US not via a container on the water, just a small package where if it's under $800, they haven't paid taxes or tariffs on the import. That was really made for people like us, individuals traveling internationally, sending products back to families. And it got exploited into this massive program where about half of Shopify's top 100e commerce businesses were shipping from outside the US and so when that changed, all of a sudden all these brands had to have this influx of volume into the US and these traditional providers, again back to kind of the data center analogy, are telling them, oh, we can get you live and set up a new Fulfillment center for you in six to eight months. We had a case study with that true classic T shirt brand multi hundred million revenue retailer took them live from meeting us and signing to fully outbound shipping in 18 days. And that's only possible on a tech driven network.

How much of the business is international versus domestic?

About 9% of our revenue would be either packages leaving the US or actually holding inventory internationally.

Okay, I have another question.

Go for it.

I noticed that the raise was a mix of debt and equity. What are you using debt for? And how do you think about is this the first time you've really included debt in a big fundraise? And then I have more questions that we can riff on after that.

Yeah, I think for Stored we're at a late stage where part of what we announced in this round is profitability, which I think is a lot rarer in a category like ours. We've spent multiple quarters in a row now consistently profitable. And that's compared to venture times when you're in a rapid delivery business and people are wondering are we using venture dollars to subsidize fast deliveries? Well, I think the proof is in our unit economics and in that profit. But at the same time we still had a strong balance sheet from the 300 plus million dollars we had raised prior. And so when we looked at this round, we kind of said let's raise the right amount of equity, but let's also use the scale, the profitability to complement the balance sheet with the right cost of capital and the right flexibility. And part of it comes down to we actually have been acquisitive in the past as well. We've acquired three businesses over the last few years, all existing fulfillment centers. Because we've just seen if we onboard existing infrastructure to our technology, we can multiply the success of those customers, the profits of the acquired business and more. And so plan to be on the lookout for more opportunities like that as we keep growing. Which I think funny enough we started that our first one in 2020. Very not in vogue for venture backed businesses to be making acquisitions now with this kind of AI wave and more, there's actually some specific funds that are just being built to roll up traditional businesses and apply technology to them.

What are you seeing that's exciting around actual fulfillment automation and robotics? This has been obviously a tough challenge that again the major players have invested billions of dollars at this point into. And yet oftentimes fulfillment is still a very manual sort of process.

It feels like if you're building a 3 PL from the ground up. It's maybe easier to think robotics first, especially if you're a tech company young, you're obviously aware of everything that's happening in AI, but at the same time hard to replace a human. They're pretty versatile.

Yeah.

We're very excited about both AI and robotics because labor and humans are one of the biggest costs in a business like Storm. And going all the way back to day one, starting even back then we were seeing peer startups in different cohorts and accelerators and more that were building drones for inventory, scanning and all this robotics and it oftentimes shocks someone when you step back and you say hey, you realize over 60% of US warehouses aren't even using a digital WMS, they're doing pen and paper based picking. It sounds like it's made up. It doesn't sound possible, but it's true. And so then you kind of look at this gap of where the industry is and if they can't even get to that kind of threshold one, getting to humanoid robots or AI deployed on how to slot in a warehouse is, is essentially impossible. And so there's such a fundamental advantage when we've built an entirely vertically integrated tech stack of we're really the only ones like Amazon when we're making you that promise in the cart, hey, order now, you'll get it by 5pm tomorrow or the next day. We're actually going through not only the front end consumer tech, the order management layer, the transportation management layer. We're looking at. We actually have this unit in Las Vegas right now. We can get it to California by tomorrow if we ship it right now. Now. And so we're connecting that vertically integrated system which just gives us so much more opportunity to deploy robotics, AI and more. And so a lot of it's on the AI wave right now. How do we use it to optimize demand planning, inventory placement, parcel selection, promise to custom the consumer and more. And the next phase is we've been using some robotics, particularly around the conveyance slotting and picking in the facility. But when you can go from static with a moving arms to both moving arms and moving legs with a humanoid, it gets really interesting.

On other big tech trends. What are you most optimistic about? Across kind of the EVTOL package delivery that we're seeing from zipline to something like automated trucking, self driving trucks to maybe even something just like, like really, really robust language model driven AI agents, just doing some of that paperwork for example, but 100% reliably like what technologies are you the most optimistic about. And if you have any timelines, I'd be interested to hear them.

Ooh, timelines is always the question mark because even some of the ones you just mentioned, there's been a heavily debated and now disproven timelines over the last decade already. So I, I struggle to make promises.

But which one would have the biggest impact on the customer experience? Which one should we really rooting for in terms of just speeding up the time to delivery and reducing the cost?

I think any form of autonomous delivery, whether the amazing teams over at Zipline and that kind of localized rapid last mile, some things that failed even at Amazon, like the driverless kind of sidewalk robots, anything that helps connect that last mile autonomous bends the cost and speed curve so dramatically that that's probably where we remain the most hopeful and excited. But with a model like store being the network, essentially what we're doing is aggregating the demand and putting it on one form of tech. But a lot of these businesses you're mentioning are actually key partners of ours where somewhere in our network we're able to kind of test this net new technology. So same thing with one of the major grocery and kind of food delivery platforms. We have a pilot in a few cities for same day delivery for some of our brands, two hour or less type delivery. But you wouldn't assume if you looked at storage that we're working with that type of company because it's buried in the network. So anything autonomous last mile, anything humanoid in a facility and really anything around demand planning with AI, I think that is the most critical because if you talk to brands, demand planning is the thing that really only enterprises will say they do well and, and I think most of them are a little self infatuated when they say they're doing it well. Demand planning is the biggest struggle in anything physical supply chain and speaks to the problem our friends at Peloton had during COVID It's really hard.

I'm looking at the bottom of our ticker. It's Polymarket has the US recession in 2025 dropping like a stone. Let's hear it for the US economy. But my question for you, you is are you seeing data on the health of the U.S. consumer? How, how is demand in the U.S. economy?

Yeah, we have a really interesting kind of front line to the consumer across a lot of industries. We've purposefully positioned to very macro, resilient industries. Things like health and beauty. You still keep the same makeup and skincare and bad times, things like nutrition and supplements. Very Similar, a lot of subscription orders that we fulfill, almost 50% of the volume we ship. And so thankfully our brands have been pretty well insulated. But we actually saw an interesting trend in April which was an uptick for many of them and we were questioning it, saying is this consumers buying because they think prices are about to go up or what is this signal? And so so far we haven't seen a kind of bullet from that negatively in May. And so year to date, our metrics and kind of markers to the consumer have actually remained pretty strong, even though there's a lot of kind of fear and uncertainty when you, when you watch the news and look at the macro.

Let's go. Let's hear it for the American consumer. And listen.

Relentless, undefeated. This has been, this has been fascinating. Thank you for coming on. I remember the first time I heard about you and Stored was from John at Strike, I think in 2021. And he was just so incredibly bullish on you and I can see why. So thank you for coming off and congrats to the whole team on the milestone.

Means a ton. We're very proud to have Strike led and I think something like 50% of the store investor base has joined TVPN so far. I saw the Kleiner Chad at SUSE.

Oh yeah, thankful. Send us more.

Well, come back on when you have, when you have interesting data too. You don't need to come on just for fundraising news. If you're seeing stuff that'd be great. You think? Be interesting to us and in the audience. Love to have you back on.

Thanks so much.

We keep the news flowing, so we'll.

Reach back out soon.

Thanks, guys.

Talk to you soon. Cheers, Sean, see you. A little sound.

What a chat.

I need to elevate the energy at the end of a long week. It's Friday, but that doesn't mean we can't listen to the Ashton hall sound effect, which I haven't done enough of.

We're going into the timeline, John.

Okay. Welcome to the TVP and Timeline review. The best post.

Many people said, oh, it's almost five on the East Coast.

They're gonna stop.

They're gonna stop streaming, they're gonna stop podcasting.

Podcast for more than 17 hours a week. We did it. We had multiple four hour streams this week. Yeah, Big, big, big week.

Never podcast weekly. Always podcast strongly.

Always podcast strongly and daily. Scientists use CRISPR to rewrite DNA inside a living baby face. CPS1, a rare lethal liver disorder. No transplant, no viruses, just three tiny LNP CRISPR doses. Gene design dose to design to dose in less than six months. Personally personalized gene therapy is finally a reality today, says Deedee. The world's first personalized CRISPR therapy given to baby with genetic disease. What a white pill.

What a white pill.

Fantastic story.

The footage from this is really sweet.

So there's a whole video about this. You should go and watch it this weekend. But Deedee goes on to say, right now, this is applicable to single celled, single gene, well mapped mutations and organs that can safely be reached which affect thousands of babies every year. Costs under $5 million now, so that's obviously expensive. It'll need to come down further. And it was covered in, you know, all the mainstream media. But what a, what a fantastic piece of news. A baby's life was saved by crispr. I remember learning about CRISPR back when my co founders were at Caltech and it was kind of this hot technology. There'd been actually a few previous technologies to edit DNA. Zinc finger nucleases was one of them. And all the hot PhD research being done in bio and biophysics back in this was like 2012, 2013 at Caltech. And their bio division was all about CRISPR. There were a couple people that spun out companies around this technology. Jennifer Doudna won the Nobel prize and has a fantastic biography written by Walter Isaacson all about that journey. It's a very interesting technology. Took so long to get here, but it's finally having an impact. I mean, it already has in many ways, but very, very exciting to follow. Good story. Also, out of the scientific community, I.

Wonder if we could get gene therapy to make us closer. Even closer. Even closer to golden retrievers.

And you're gonna go there? Absolutely. Just permanently change my DNA so I can only be friendly.

Yeah.

Turn off the unfriendly gene entirely.

Yes.

And also make me hotter and dumber, because that's key. You can't just be friendly. You also have to be hot and dumb if you're gonna go full golden retriever mode. Anyway, I love this, I love this headline from the Wall Street Journal. Forget humanoids at mit. Worms and turtles are inspiring a new generation.

Pull up this image.

This is such a great image. Yeah, look at this turtle robot. He's so proud of his turtle robot. It's great. So csail, which is their artificial intelligence laboratory, envisions robots beyond humanoids, including soft, flexible, and even edible designs.

Edible robots. Eat your robot, you're going to be able to eat your robot.

Live in the pond.

This is what Josh Wolf was talking about.

Right.

Like, let's explore every potential magical form factor.

Developing soft robots like a sea turbo.

Somebody acquired robot.com this week too. So they came out with it.

Edible robots for non invasive surgery. So you eat the robot, it crawls around inside you and cleans you up and fixes you up, sews you up. I mean, yeah. I mean, if you have internal bleeding or something.

Something.

Yeah. Eat a robot. It'll sew you up, I guess. Russ's lab is also using new types of AI models inspired by the neural networks of worms to power robot brains. What a fun story. Anyway, and this is something that's actually gone on before. I found a different video from a different group that says, we have created a robot based on the leatherback sea turtle, which is alive today leisurely swimming in motion. Next we plan to modify it to an ancestor of the leatherback sea turtle that remains as a Mesozoic fossil to make it swim. And I think this is just like.

I don't know.

Robo, I don't know. Very interesting. It's just swimming around. Just made a robot turtle fun. People like turtle turtles. We talked about a few of this. What are the other funny posts? I mean, more fallout from Google. The design leak, Android Auto.

This guy. This is somebody's LinkedIn profile. If you're on audio, this person says, spent 40% of my time arguing with the worst PM I ever worked with. 20% managing and coaching amazing designers, and 40% on the inefficient overhead of simply working at Google. It's wild to see ideas we talked about in 2015 finally coming out in 2020. But they happened.

Yeah. And this is of course a quote post from Daniel. Daniel says, it's amazing how good Gemini is and how bad every product manager at Google is. Is it? I feel like the PMs aren't that bad. It's more just like the organizational. You ship your org chart and they just. They just can't move fast enough to like position the products correctly. Like, the products are good, they're just not. They're just not positioned correctly or talked about properly. I don't know. Sundar Pichai did an interview with the all in podcast. He sat down with Dave Friedberg. I'm excited to listen to that this weekend and dig into how he's thinking about product design and AI generally. I'm sure there's a lot of good insights in that interview. So go check it out. We have a new landing page for Grepatile Grep tile.

This is not going to Come up. I just thought this was a fantastic website.

Okay. Okay.

And the AI viewer.

Catch 3x more bugs. Merge 4.4x faster 100% code based content.

We got to pull up the grep. I'm going to share it.

It's a fun name. These AI companies, these SaaS companies, sometimes they get wild Data dog team.

It's in the chat. Let's say.

Great, great SaaS name.

You got to see the animation though because the static image so the.

So, so the. The grep tile, the. The lizard is.

Is catching bugs.

That's good. A little on the nose of the metal.

We got it. It do. We got it.

But we respect it.

Look at this.

Cute. Very cute.

That is a fantastic website.

I like it.

That's.

I love to see it.

That's great. Dan Romero giving us a shout out.

Little shout out. I'm excited to have Dan on the show.

Yeah. TVPN format works because it generates daily content flowing out of the 48 hour timeline. Zeitgeist that can be cross posted in video favoring algos on every major social network. Weekly podcast is too slow and stale in comparison. The only live competition is CNBC and they are too slow boomer downstream compared to Twitter. Interesting 48 hour timeline. We were the daily show. We do. We're on a 24 hour timeline now.

We sometimes catch stuff a little late.

It's true.

Right?

Yeah. We got to be more on top of it. We gotta spend more.

But we're newsmaxing. We're newsmaxing folks. Again, thank you for wonderful week. I hope everybody has a fantastic weekend.

Do you want to talk about the, the. The public.com vibe? Investing?

Yeah, we should actually cover this.

This is very cool. So public.com obviously sponsor the stream has launched the ability to create synthetic portfolios around basically any investment idea you have.

And then back test them against the broader market which is where it gets really interesting.

So we have a couple of these pulled up that we can share with you. The first one is Founders Fund funded companies that have graduated and gone public. How did they do in the public markets? And you can see companies that were backed by Founders Fund have done 659% return over this test versus 150% in the S and P. Sequoia's done similarly little up and down here for Sequoia. 123% versus 147 in the S&P. 500. Yeah.

A little bit rockier, but you have done very well.

589% versus 150 in the S&P. A16Z has also done well with 406% total return versus 150% in the S.

And P. And this is where it gets really interesting, John. The F1 index are companies that sponsor F1 teams and they have dramatically outperformed the s and p. 317% total returns versus 147% for the s and P. Over time.

Perhaps the best, the best portfolio that they tested is the size compensation size lords. These are highly paid CEOs often controversial. 2000% return based on investing in CEOs that get paid a lot versus 176% in the S and P over the backtest period.

Actually insane. Turns out when CEOs get paid well, shareholders outperform.

And also who else outperforms bald CEOs? Bald CEOs give it up for the bald CEOs. 433% versus 150 in the S and P. Fascinating. Bezos. Probably doing a lot of heavy lifting there.

Lot of heavy lift. Heavy lifting, yeah. But you got the Brian Armstrongs.

Yeah, right.

Strong, Strong.

He's kind of good.

I mean, this is insane. I'm, I'm interested to just continue tracking this over time because it really tells an interesting story.

Yeah, not adventure. Some advice obviously, but never investment advice.

Always entertainment advice.

Steve Ballmer, another bald CEO. There's a ton of them. Yep, a lot of good, A lot of good bald CEOs out, out there. So shout out to your bald friends. Anyway, thank you for watching. Leave us. Five stars on Apple podcasts and Spotify and we will see you on Monday. Thanks for watching.

Cannot wait.

We'll see you soon.

Bye.

Cheers.

Have a good weekend.