Speaker 1:
00:00You're watching TVPN. Today is Tuesday, 05/20/2025. We are live from
Speaker 2:
00:04the Temple Of Technology. The fortune finest. The capital of capital.
Speaker 1:
00:07And we are recapping Microsoft Build, which was yesterday, and Google IO, which is today. We have a bunch of folks coming on from Google. And but we're going through what happened at Microsoft. Obviously, they're going even deeper into artificial intelligence, talking about the agentic web, the future where the robots do your work for you and work while you sleep.
Speaker 2:
00:30This is why we do three hours a day, folks.
Speaker 1:
00:32Yep. So we can cover it all.
Speaker 2:
00:33Gonna have time to watch. We listen to the full thing
Speaker 1:
00:37every single day. Crazy amount of news and deep dives this week specifically into AI. Obviously, Microsoft and Google are doing big keynotes right now, but, Bloomberg has a fantastic deep dive into OpenAI's Stargate. And then there's also a profile by the same journalist in Bloomberg about Dario Amade over at Anthropic telling his soul story. And so, basically, everyone's getting coverage, and AI is the only thing people care about.
Speaker 1:
01:07And so that's what we're talking about today on That's right. The show. But let's give you a little bit of a recap of the news. So Microsoft Build twenty twenty five opens Satya Nadella calling for an open agentic web. There's new copilot features, open protocols.
Speaker 1:
01:23They're going all in on MCP model context protocol that, standard, not a particular tech product, obviously defined by, Anthropic, but then open sourced and then adopted by both Microsoft and Google. So, the narrative is MCP one, basically. And MCP became a very hot button issue. Lots of people posting threads on the news.
Speaker 2:
01:43It's goaded yet, but it's definitely in the conversation.
Speaker 1:
01:46It seems it seems like it could be goaded. It's doing quite well. It's getting massive adoption. And most importantly, I think it's, like, it's not it's more of a standard than a particular product. And so you're not seeing a wave of startups, but you're seeing startups use MCP.
Speaker 1:
01:58And then Elon Musk joined Satya Nadella, on stage via Zoom, presumably or or or probably Microsoft Teams, I guess, that they called in from, and confirmed that Azure will host XAI's Grok three and Grok three Mini. And he kind of talked about his vision for Grok being a truth seeking LLM and focused on foundation, a foundation model built on physics and first principles, which has been his, his goal with that. But if you look at Satya Nadella's pitch now for the host the models that are hosted on Azure, it's really just everything. Can Everything. They even have so they have the you you can swap quickly between even DeepSeek is on there, and there's a version of DeepSeek that's been fine tuned by Microsoft's AI internal team.
Speaker 1:
02:48There's all the LAMA models. There's all the OpenAI models.
Speaker 3:
02:52Now the
Speaker 1:
02:52Gronk models.
Speaker 2:
02:53It out.
Speaker 1:
02:54Yeah. Maybe. They
Speaker 2:
02:56found him. They asked him to leave. So Now they're hosting it.
Speaker 1:
02:59We're good. Yeah. And and then there's even there's so so many models now that Azure has a model router for OpenAI models. So you can import the Azure OpenAI model router, and and then it will decide what the cost benefit is for the individual model that you're using. Oh, do you have a do you have a plug?
Speaker 1:
03:21Or I guess we're I guess we have
Speaker 4:
03:23oh, no.
Speaker 1:
03:24I got this one. Cool. Okay. And so, yeah, you should go watch the full, conversation between, Microsoft CEO Satya Nadella and Elon Musk. He says with Grok 3.5, which is about to be released, it's trying to reason from first principles.
Speaker 1:
03:38Also, I I saw a ton of, Tesla battery packs show up.
Speaker 2:
03:41For product managers who have been Oh, yeah? You know, spending their entire life figuring out how to think from first principles that that Rock five will just do it out of the box.
Speaker 1:
03:50Yeah. Yeah. It's a golden age for people that never learned first principles.
Speaker 2:
03:53You can
Speaker 1:
03:54just say think from first principles.
Speaker 2:
03:55Yeah.
Speaker 1:
03:55Do it for me. Yeah. Just do Golden retriever mode all over again.
Speaker 2:
03:58Yep. Bold. We've been calling
Speaker 1:
03:59Bull market.
Speaker 2:
04:00Prediction at
Speaker 1:
04:01time. Been dumb.
Speaker 5:
04:03Here we are.
Speaker 1:
04:04Dan Shipper summed it up. Yesterday, Microsoft rolls out MCP to support support to Windows. Today, Google officially supports MCP in the Gemini SDK. It's over. MCP wins, and that makes a lot of sense.
Speaker 1:
04:15It's a standard that everyone's building against now, and we we imagine that that will continue because once you have Google and Microsoft and Anthropic, everyone has to conform to it.
Speaker 2:
04:25Coordinating with Dan, but hoping to get him on the show Thursday. He's got some news
Speaker 1:
04:29to share. So Another big announcement from Google IO. They, have real time Google Meet translation is live now. I feel like we've seen this demo ten years in a row, but it feels like it's finally here. And so there's a video where you can be talking to somebody in a different language, and it will live translate what you're saying into the local language so you can just have a conversation.
Speaker 1:
04:55Obviously, this is a it's like one of the most obvious AI use cases. It's something that Google should do. It's something that seems, like, extremely beneficial for for humanity across the board just like pure alpha. So excited to see that. They're also releasing a diffusion language model that I want to dig in with the Google team more on because, we've seen image models move away from diffusion into more token based structures and and and transformer based architectures.
Speaker 1:
05:24Now language models are going into diffusion. So I don't know enough about this, but I'm gonna be digging in this week. They also launched DeepThink 2.5 Pro, new enhanced reasoning mode for using, Google's research in parallel thinking techniques, meaning it explores multiple hypotheses before responding, basically branching all the different trees. There's already a little bit of this going on in OpenAI's deep research product, but, obviously, it's a very competitive space. This enables it to handle incredibly complex math and coding problems more effectively.
Speaker 1:
05:58And I was excited about Google Gemini. I've become more bullish on the product since I sent you those incredible AI generated videos that are generated from v o two. And so I went in to Gemini because, remember, I I generated three or four of those videos, and then it gave me a time out. And it said, look. I know that you've spent millions of dollars with Google over your career
Speaker 2:
06:23Course of your career.
Speaker 1:
06:23$20 is the most money I could accept from you. That's possibly charge you an extra dollar to make one more of these videos.
Speaker 2:
06:30200 just doesn't show The
Speaker 1:
06:31GPUs are on fire.
Speaker 2:
06:32Even though you would pay 2,000.
Speaker 1:
06:34And we have even though we have a hundred billion of dollars of cash, we have to rate limit you. Yep. We couldn't possibly light another GPU on fire for you right now.
Speaker 2:
06:43We should ask
Speaker 1:
06:43There's no price.
Speaker 2:
06:44We should ask Logan later around rate limiting and and the plans there.
Speaker 1:
06:47Hopefully, it was a very frustrating experience for me because I would have paid more in that moment to generate one more photo of a Lamborghini Urus with a TVPM livery driving around a track, but I couldn't do it. And and it was it was not possible. I mean, I guess I probably could've if I got a separate Google account with a separate Gemini Pro subscription, maybe on a separate phone, and then how to do that.
Speaker 2:
07:08Yeah. Huge opportunity right now to create a a basically a bundled Google subscription where you subscribe to a service that then aggregates, like Yes. Yes. You know
Speaker 1:
07:19Yeah. Yeah. Yeah. Yeah. It's of like how there's how the banks have s FDIC insurance, and you're insured for up to, like, a hundred thousand dollars, then $250,000.
Speaker 1:
07:27So some people would take, you know, oh, spread spread a million dollars across 10 accounts or five four accounts. You need to do that with Google so you don't hit the rate limits, clearly. So they put me on a timeout. They said, John, you've you you have generated too many of these, of these GT three RSs and TPP deliveries. You need to take a break.
Speaker 1:
07:45We'll see you one day from now. Okay? One day.
Speaker 2:
07:48You can come back.
Speaker 1:
07:49Come back. It's been three days now since I did that.
Speaker 2:
07:52The I'm sending those somebody. You're of a typical workflow with a human. Right? You maybe get a few iterations and they say, hey. I gotta go to sleep.
Speaker 1:
08:00I gotta take a break.
Speaker 2:
08:01I'll see you tomorrow.
Speaker 1:
08:01Yeah. You're overworking me, boss. Yeah. And so it it told me to take a break. It said one day.
Speaker 2:
08:05We'll see if are the agentic web.
Speaker 1:
08:07Monday night. I remember what it said. It said Monday night, you can create more. So I wanted to go and create one today because it's Tuesday. And I said generate a vertical video 16 by nine of Sundar Pichai arriving at Google IO in a Waymo and waving to a crowd of adoring fans who were taking pictures of Android And it says, too many requests in a short time period.
Speaker 1:
08:24Try again later. So, again, a weird thing where, like, the product is amazing, but I can't access it enough, and I keep being frustrated with the actual rollout of these products. But, hopefully, it's getting better. I do wonder if they're getting slammed right now because of Google IO. Everyone's testing out the new model, and so they really are under a ton of demand.
Speaker 1:
08:44What was interesting is that it it it didn't generate any videos for me today. And immediately, it just said it just said too many requests in a short period of time. It didn't say if that if it's too many requests from me because this is the first request I've sent in today. And so I was very unsure of what's going on there. It's just their system's under load timing.
Speaker 2:
09:02It to address you as boss man? Because it might be more, it it would feel a little bit better if it said, hey boss man, that's enough today. Instead of just, you know, hitting
Speaker 1:
09:13I'm working hard.
Speaker 2:
09:14Feeling like you're hitting those rate limits. I'm working hard.
Speaker 1:
09:17What else?
Speaker 2:
09:18Going back a little bit, one thing that stood out to me, seeing Elon and Satya Yep. Having a conversation Oh, working on this product launch Sure. Felt significant to me because it was not too long ago that Microsoft was named as a defendant in the OpenAI lawsuit. Mhmm. Right?
Speaker 2:
09:34Elon's lawsuit against OpenAI. Yeah. Yeah. Microsoft was a defendant. And at a certain point, I believe it was in 2023 as well, Elon was threatening to sue Microsoft for training on X or Twitter Oh, interesting.
Speaker 2:
09:51I didn't know that. And so these two haven't exactly had the best relationship. I mean, clearly, like, they're on an individual level. Yeah. Yeah.
Speaker 2:
10:00But the the partnership now is cool to see just given that there had been quite a bit of friction over the last couple of But the funny thing is Musk was actually way back in the day an intern for Microsoft Windows in the nineties. So very
Speaker 1:
10:18bold circle story about him trying to get a job at Netscape with Marc Andreessen, and he didn't make it past, like, the first round. And so he went to, Microsoft. That might be wrong, but there's something about, Elon, before he started Zip two, was kind of moving around the valley at different tech companies. It's funny to imagine intern Elon
Speaker 2:
10:36Me. Let me look it up.
Speaker 1:
10:37Writing some code for for Microsoft Office at the time or something. But now now they're partnering in I mean, it's all part of Satya's strategy to be model agnostic. Yep. It's always felt like Microsoft Research has been behind the curve on LLM training. Like, Zuck, although although Llama has kind of hit a rough patch with Llama four.
Speaker 2:
11:00Apparently. So Elon was rejected from a job Yeah. At Netscape.
Speaker 1:
11:06Yeah. That's right.
Speaker 2:
11:07He sent in his resume, showed up at the office Yep. Even lingered in the lobby, but no one acknowledged him.
Speaker 1:
11:14Wow. Just Mark Andreessen walking by, mocked. And now and now Mark's in XAI.
Speaker 2:
11:21Yeah. Now they're boys. Ripped a big check.
Speaker 1:
11:23And a bunch of other companies too. But it's great. What what a full circle story. But yeah. So, I mean, Satya obviously is is positioning Microsoft to be model agnostic and wants to be a vendor of this in the cloud platform.
Speaker 1:
11:36And I think that's it seems very good for for Azure in the idea that if you're a business and you're building on Google, you might feel like, oh, they're going to really push the Gemini models on me. Maybe I get locked in at some point. Maybe that gets expensive. But if I'm on Azure, I can dance around between different OpenAI models and different LAMA models and different Grok models and have a lot more flexibility because Satya has kind of said like, hey, we're not, you know, going to push you towards a particular model or particular Yeah. Regime.
Speaker 2:
12:13Also release an open source Versus code, you know, sort of like Copilot product, which is big. So anyways, reaction to that was
Speaker 1:
12:24Project Padawan.
Speaker 2:
12:25Was positive as well.
Speaker 1:
12:27GitHub Copilot graduates to a full coding agent. Project Padawan GA for for Copilot Enterprise and Pro Plus capable for autonomous feature work bug fixes and refactors. And so everyone's kind of moving into autonomous coding agents. We're having Scott Wu from Cognition on the show on Wednesday tomorrow, to talk about the landscape. And, we're also having Lee Marie from, Kleiner Perkins on Friday to talk about the same thing, this idea that how is the AI coding landscape shaping up?
Speaker 1:
12:58Is it one market, two, three, four? It feels like there's as as we were talking about it a little bit earlier, it felt like there are there's AI code that's written. I mean, you just gave an example where you asked it to count you asked ChachiPT to count the number
Speaker 2:
13:16of white boxes or something.
Speaker 1:
13:18Happened there?
Speaker 2:
13:18So basically, x AI Yeah. Got received a 68 Tesla Megapacks, which is gonna power Colossus two
Speaker 1:
13:26Mhmm.
Speaker 2:
13:26Which is their second data center.
Speaker 3:
13:28Yeah.
Speaker 2:
13:28And there's this sort of above ground image, and I initially saw the image and I didn't somebody else had had sort of counted them up. So I asked ChatGPT to count and it and it spent thirteen minutes attacking the problem by by writing code. In that time, of course, I just like, you know, looked at the x axis and the y axis and multiplied and got the right number. But chat GPT was running in the background, know, attacking it in the most sophisticated way possible. What the number I wanted to figure out that was interesting is that the retail value of the Megapacks, which of course you can buy on the Tesla website Mhmm.
Speaker 2:
14:125,000,000, comes out to around $850,000,000
Speaker 1:
14:18Wow.
Speaker 2:
14:18Just on Megapacks, which is about half of their 2024 revenue, right?
Speaker 1:
14:23Wait. Half of who's?
Speaker 2:
14:23Not XAI's. Okay. X's revenue,
Speaker 1:
14:26which is how we find them. Yeah. Yeah. XAI doesn't have
Speaker 2:
14:28any revenue really yet. X has graduated.
Speaker 1:
14:31Yeah. But they raised a lot of money, they're they're spending on Tesla Megapacks. That's wild.
Speaker 2:
14:34Yeah. And I'm interested to see how ultimately exactly how this new round shakes out. There's been rumors Oh, yeah. Around the new fundraise for
Speaker 1:
14:43a while final details of that round haven't been announced yet.
Speaker 2:
14:46Right?
Speaker 1:
14:46Yeah. It's still just rumors. That's interesting. I wonder thirteen minutes is fast, but not that fast. I wonder if there's a world where OpenAI has a function it can call to, like, Mechanical Turk or Scale AI to just have put a human on the case.
Speaker 2:
15:00Well, it failed.
Speaker 3:
15:02It failed?
Speaker 1:
15:02So I mean, it didn't even do it in thirteen minutes?
Speaker 2:
15:04It just it just basically timed out because I could see it working and
Speaker 1:
15:08Just writing code.
Speaker 2:
15:08You know, taking all these different cracks at it.
Speaker 1:
15:11Yeah. So so imagine To
Speaker 2:
15:13to its credit, it would have taken a human
Speaker 1:
15:15Not thirteen minutes to count those.
Speaker 2:
15:17No. Just manually counting them, like what I did. Yeah. Not I didn't actually go line by line, but like Yeah.
Speaker 1:
15:24You do some multiplications.
Speaker 2:
15:26Twenty seconds. But Twenty seconds. But if if a human had to run take that many attacks at solving it
Speaker 1:
15:33It wouldn't. Like, what I'm saying is that is that you kick off this, how many whites or how many white squares are in this image? And it just displays that to a mechanical turk who's just sitting there doing random tasks all day long. And they just one shot it in, you know, two minutes.
Speaker 2:
15:47Yeah. This is what I was talking about over the weekend. I was joking around. I'm sure some people took it seriously. But I was saying, met somebody in The Philippines whose job is to make investment decisions Yeah.
Speaker 2:
15:58For a firm that claims to use AI. That's the final, the final boss of of of using AI. Yeah. But but it's really, you know, mechanical Turk is just, you know, using
Speaker 1:
16:12Yeah.
Speaker 2:
16:13Using outsourced labor to just make all investment decisions.
Speaker 1:
16:16The the overall announcement at any of these keynotes is always, we're 90% of the way there. And the last 10% will be another 90% of the way there. But, I mean, there are some there are some impressive, you know, announcements and and steps forward, but, obviously, there's a lot there's a lot left to do. So Copilot Studio, just running through what else Microsoft announced. Copilot Studio now supports multi agent systems so developers can build agents that delegate tasks to one another with mice Microsoft three sixty five agent builder.
Speaker 1:
16:46NL Web debuts as HTML for the agentic web, letting any size any site expose a conversational endpoint discoverable by AI agents. So an AI agent shows up, and it can just chat with your website. We talked about Project Padawan, GitHub Copilot graduating to compete in that space with Codecs from OpenAI. And now just in the OpenAI world, you have three products that effectively write code. You can just go into o three or even four o, and it can write a little bit of Python like you experienced, which can have mixed results but is sometimes extremely useful.
Speaker 1:
17:22You have codecs that can actually plug into a GitHub repo and and go and write some code and fix bugs and whatnot. And then you have Windsurf, which can sit in your IDE alongside and be kind of that ground up adoption. And so there's one mental model where there's, like, the consumers are going to ask questions, and they don't even know that they should be thinking about writing code. Code will be written. They might never see that code if they don't unfold the reasoning tokens.
Speaker 1:
17:49On the flip side, you might have someone who's using codecs to change bugs and make small changes in a GitHub repo without really opening up an IDE constantly, but they're just they're just interacting with code, they're aware of what should be done, what should be built. Then you have a product like Windsurf where for basically a full time programmer, they're they're working in code constantly, and they're solving problems at a much higher level than any of the agents can actually do, but they are enhanced and sped up by these, you know, AI AI IDEs that are speeding up their their workflows. And then, potentially, you have this top down enterprise AI, which is what Scott's building with Cognition where, you know, there isn't as much of a groundswell around Devon as a consumer tool. But as I understand it, Devon is something that's been pushed top down on big corporations as something that that needs to be rolled out, and it has much more of a like an enterprise sales, like, go to market and sales cycle. So interesting to see if that if that model holds of, like, four distinct markets, like consumer, prosumer, ground up enterprise, top down enterprise.
Speaker 1:
19:07I don't know if that's the right way to think about it, but I think that's something we'll be digging into over the over the next couple days. Yeah.
Speaker 2:
19:13I mean, some combination of product led and enterprise Yeah. Is probably the winning combo
Speaker 1:
19:18long term. They all seem to be getting adoption and printing money. The the question's just, yeah, churn and and and how the market looks in the really long term. It is interesting because, like, AI coding tools, it does feel like it's a massive market. You looked at the numbers for Just how much money is spent on software engineering.
Speaker 1:
19:35It's huge. Spend. And then it's also just a completely new market in the sense that there isn't anything that's like, really established. Like, they're not really displacing spend on anything else. It's all just incremental and additive.
Speaker 1:
19:47So it's kind of hard to hard to handicap exactly what you're going after. Yeah.
Speaker 2:
19:52I thought this post from Caleb Harris was an interesting call out. He says, last night I dropped 12 backlog bugs from Linear into Codex and launched. Reptile found some nits in the reviews but they were almost entirely correct and then spur QA tested almost entirely human out of the loop at this point.
Speaker 1:
20:09That's awesome.
Speaker 2:
20:10And yeah. Well, good time to tell you
Speaker 1:
20:12about Linear. Linear is a purpose built tool for planning and building products. Meet the system for modern software development, streamline issues, projects, and product road maps.
Speaker 2:
20:23Anyway Thank you, John.
Speaker 1:
20:24Also launched Copilot tuning, which allows companies to fine tune their models with their own data to create domain specific agents. Windows AI Foundry launches as a local platform on Windows and Mac for training and fine tuning and running LLMs with Foundry Local. Azure AI Foundry models adds Grok three, which we talked about. MCP gets first party support. Windows subsystem for Linux, a bunch of other stuff.
Speaker 1:
20:48SQL Server 20 twenty five hits public preview. Let's go SQL Server. Huge for the database engineers in the crowd.
Speaker 2:
20:57Let's give it up. Let's give it up.
Speaker 1:
21:00Anyway, the the I think the big definitive analysis of the the the postgame on Microsoft Build came from Ben Thompson. But Derek Thompson, no relation, I believe, but maybe there's
Speaker 2:
21:11Thompson are boys.
Speaker 1:
21:12Brothers. Derek Thompson
Speaker 2:
21:14wild.
Speaker 1:
21:15He wrote, Abundance with Ezra Klein. He says fascinating, Ben Thompson's, vision of the future of the Internet, I e, the agentic web. Scenario is before I go to sleep, I tell Chatuchipiti, plan my five year old's birthday next Saturday. Budget $500 when you've made the reservation. Email these two these 20 people a printable invitation to attend.
Speaker 1:
21:36Also, my wife wants to go to England in mid July, find five plausible flights for the family, make several distinct itineraries. Finally, please edit this work memo. When I go to sleep, the AI agent negotiates slots with two bowling alleys, buys a cake, emails, printable invites, plans the trip, copy edits, etcetera. This presents an interesting economic challenge. What happens to ad revenue when more traffic is just AI?
Speaker 1:
21:57Ads make little sense when the reader is a robot. Well, maybe instead, sites ask agents to make tiny payments that are fractions of a cent every time they call up an article. Ben suggests the use of no fee stablecoins, blockchain dollars, but I think microtransactions could work with old fashioned dollars. I have no idea if this cashes out, but very interesting vision of how AI would necessarily transform Internet economies as traffic shifts to from humans to agents. Interesting.
Speaker 1:
22:25So I wanna I wanna dig through this, Strathecari article, but I also
Speaker 2:
22:29And this is significant because so every business, every consumer tech company eventually becomes an advertising business Instacart to Uber to Apple. Yep. And if you remove these ad businesses, it typically will just rip out a lot of the actual earnings. Right? Because advertising tends to be very high margin.
Speaker 2:
22:54And so what what I think we're gonna see is ultimately this kind of drawn out war between agentic software and the old internet, where the old internet doesn't wanna let go of advertising. Yeah. And so I think that, you know, micro track transactions are potentially somewhere that you could land.
Speaker 1:
23:16It's interesting to dig through. I'm not entirely sure that language models and AI agents will be entirely resistant to advertising. Yeah. Because I imagine No, but it's
Speaker 2:
23:26it's more so if you're Uber Yep. And you have a great ad ads business.
Speaker 1:
23:31Yep.
Speaker 2:
23:32Are you thrilled to have an agent trawling and and booking things and buying groceries and all this stuff? You're not. Right? You're like, I would prefer
Speaker 1:
23:41unless the ads that you run on your platform influence the future training of those AI models. So for example, if an LLM is training on transcript of this show right now, and then we start talking about how Ramp can save time and money.
Speaker 2:
23:57Well, it does, John.
Speaker 1:
23:57Yeah. Yeah. Exactly. We're we're we're stating the facts here. Yeah.
Speaker 1:
24:01And we're explaining that Ramp has easy to use corporate cards, bill payments, accounting, and a whole lot more all in one place.
Speaker 2:
24:06Not even to mention Ramp Travel.
Speaker 1:
24:07We didn't even get to mention rent ramp travel, which makes travel so seamless and and streamlined.
Speaker 2:
24:14It every time we hit the road.
Speaker 1:
24:15We do. And so an LLM, as it's trolling through the Internet, it comes across, you know, a host red ad like that that influences the future recommendations it makes. Right? It gets baked in the training data. So perhaps ads could be just as as as influential in the sense that, you know, LLMs are simulating human behavior.
Speaker 1:
24:37Everyone likes to say that advertising doesn't work on them, but time and time again, data shows that it does. And so if you have an agent that's actually perfectly simulating a human, it should also be simulating receptivity to advertising. You would think that it would.
Speaker 5:
24:52That's right.
Speaker 1:
24:54But but let's dig into Ben's article because I think I agree, and I think you agree more than we're we're letting on right now. But let's dig into it. So he starts with this with this, 2014 article in the Atlantic by Ethan Zuckerman, about, like, the death of the web. I remember this, this iconic article. He says, from Ethan Zuckerman, I have come to believe that advertising is the original sin of the web, the fallen state of our Internet as a direct
Speaker 2:
25:23Nobody's taking this serious.
Speaker 1:
25:24Taking this seriously. Yeah. I forget what what Jordy has Jordy has a laugh track now. It's called the Internet's original sin.
Speaker 2:
25:36Keep going, John.
Speaker 1:
25:37You're gonna make this very hard. The fallen state of our Internet is a direct, if unintentional consequence of choosing advertising as the default model to support online content and services. Through successive rounds of innovation and investor story time, we've trained Internet users to expect that everything they say and do online will be aggregated into profiles, which they cannot review, challenge, or change that shape both what, both what ads and what content they see. Outrage over experimental manipulation of these profiles by social networks and dating companies has led to heated debates amongst the technology savvy the technologically savvy, but hasn't shrunk the user bases of these services as users now accept that this sort of manipulation is an integral part of the online experience. Marc Andreessen.
Speaker 1:
26:28Mark Andreessen. Mark Andreessen, who was there when the web was born, explained in a twenty nine p nineteen podcast why this sin was committed. The quote is edited lightly for clarity. One would think the most obvious thing to do would be building in a in the browser the ability to actually spend money. Right?
Speaker 1:
26:46You'll notice that didn't happen. And in a lot of ways, we didn't even think it's unusual that it didn't happen because maybe that shouldn't have happened. I think the original sin was we couldn't actually build economics, which is to say money into the core of the Internet and there and so therefore, advertising became the primary business model. We tried very hard to build payments into the browser. It was not possible.
Speaker 1:
27:07We made a huge mistake. We tried to work with the banks, and we tried to work with the credit card companies. It was sort of this classic single point of failure bottleneck or, at least in this case, two points of failure. Visa and Mastercard essentially had a duopoly at the time, and so they were just literally if they didn't want you to be in the switch, they didn't want you to be able to do transactions. You simply weren't going to do it.
Speaker 1:
27:29And what's interesting is, like, I feel like the modern entrepreneur, like the the the Sam Altman style dealmaker, if you transported it back in time, you put the you can just do things mindset in there, you'd just be like, oh, yeah. Like, the whoever's building the browser did some crazy deal with Visa and is bundling these transactions. And so, yeah, they're totally waiving the 3% fee, but they're aggregating this way and they're also investing.
Speaker 2:
27:53It's interesting.
Speaker 1:
27:53One thing watches the other.
Speaker 2:
27:55It's interesting that the credit card companies at the time too, you can imagine I would pay an incremental fee to have my credit card data perfectly stored in my browser. Yeah. You could capture bips on that pretty easily.
Speaker 1:
28:08Yeah, totally.
Speaker 2:
28:09Like there's And so you think there would have been a deal to be done. Yeah. Remember, this was at a time when people were scared of the internet. Yeah. People generally weren't even fully convicted at the time that it was it it still had nonbelievers.
Speaker 1:
28:24I wonder if it was more of a failure of imagination from Visa and Mastercard executives or a failure of aggression in the deal making of the web one point zero entrepreneurs? Because the web, whatever generation we're in right now
Speaker 2:
28:41You think you're basically saying entrepreneurs today are built different.
Speaker 1:
28:44It's not just that they're built different, it's that they're very willing to go and do crazy deals with huge companies. Yeah. Like, I mean, think about
Speaker 2:
28:53company's changed company Well, thing that's real back then there was more, there was more almost technical risk something like Totally. No, it's so reasonable now.
Speaker 1:
29:04Didn't happen, but
Speaker 2:
29:05yeah, yeah, mean a lot
Speaker 1:
29:06of it's the maturity of the Today
Speaker 3:
29:07there's
Speaker 1:
29:07People take startups seriously. But I'm thinking of that, What what is that Onker Jane company where you can pay your rent with credit card? And Wells Fargo, like, totally took a bath on the deal, at least in the short term. You remember this? It was some sort of
Speaker 2:
29:22credit card. Built?
Speaker 1:
29:23Built. Yeah. Built rewards. And so, like, doing a deal with Wells Fargo at that scale as, like, a startup is crazy. But, like, Ankur is clearly just a really, really great, like, deal maker, and so he was able to get it done.
Speaker 1:
29:37And if if points on housing actually does plant pit like like, play out to be a real thing in a big business, like, it will be on the back of that crazy deal that needed to get done to make this happen. Like, it wasn't just gonna be some ground up Yeah. Small company deal.
Speaker 2:
29:54Like, you had to go in
Speaker 1:
29:55and do this this big thing.
Speaker 2:
29:56Yeah. It's interesting in some ways
Speaker 1:
29:58It's also got Now, Apple
Speaker 2:
29:59on the board. Apple Pay enables would have been the goal at this time. It does it effectively at the hardware layer. Yeah. Yeah.
Speaker 2:
30:07Yeah. Yeah.
Speaker 1:
30:07It's not even that good.
Speaker 2:
30:08I think it's pretty it's getting to the point where it's pretty good.
Speaker 1:
30:12Yeah. Yeah. It's pretty good. But I mean, still, like, you you hit web checkout for all time and have to hit the autofill, which is like such a kludge because it could just not even be there. Yeah.
Speaker 1:
30:22It could just be as native as you click a link or, you know, even just like the integration of email or the integration of the the the share sheet. Like, there's so many different aspects that are built into the web browser natively. Like, the ability to play video on the web. Like, that was something that all the browsers needed to figure out. And, like, it just works now.
Speaker 1:
30:42Like, every browser supports video. Mark Anderson was talking about, all the different things, like like, why the hyperlinks are blue. Like, he's the one that decided that. Because he was like, we need hyperlinks, so we we should make them blue. And it's like, there could have been a version of money.
Speaker 1:
30:57So, anyway, Ben Thompson goes on to say, I think Andreessen is too hard on himself, and I think Zuckerman is too harsh on the model Andreessen created, on the model injuries and created the conditions for. The original web was the human web, and advertising was one of the best possible ways to monetize the scarce resource in digital human attention. The incentives all align. Users get access to vastly to a vastly larger amount of content and services because they're free, which I really like. It's great that anyone can access the Internet for basically free, and they can go all over, and most of these services are free.
Speaker 1:
31:34The information spreads very quickly. Content makers get to reach the largest
Speaker 2:
31:38possible doesn't spread quickly. Always is a non Yeah. But there's the black market of PDF
Speaker 3:
31:44Yeah. As
Speaker 2:
31:44well that I think it's Paula has talked about. Yeah. Yeah. Yeah. Definitely.
Speaker 2:
31:48In SV.
Speaker 1:
31:49Yeah. Mean, this is get to reach the largest possible audience because the access is free, and advertisers have the opportunity to find customers they would never have been able to reach otherwise. Yes. There are downsides to advertising, Zuckerman fretted about, but everything is a trade off. And the particular set of trade offs that led to advertising the advertising centric web were on balance, a win win win that generated an astronomical amount of economic value.
Speaker 1:
32:14Yeah. It's hard to go back and play play out the Google story and say, oh, they left a lot on the table.
Speaker 2:
32:19It's like Yeah. In so many ways, content content wants to be free. Right? The second that you put web pages or anything behind a paywall Yeah. The attention they get drops by 99%.
Speaker 2:
32:32Yep. Usually more. Great. Totally. And
Speaker 1:
32:35Yeah. It's just it's just way better to be advertising led. It's way better to just, you know, as you're talking about one story, start talking about Figma, you know, think bigger, design, build faster. Figma helps design and development teams build great products together. You can get started for free.
Speaker 1:
32:50Anyway.
Speaker 2:
32:51It is the backbone It's the backbone. Of our show and we can't thank them enough.
Speaker 1:
32:57Okay. Thank you. Moreover, I disagree with Andreessen that he we could have ended up with a better system if the banks and credit card companies had been willing to play ball. In fact, over the last thirty years, the credit card companies have, in particular, have in part, thanks to companies like Stripe, gotten their digital acts together and are integral to a huge amount of web based commerce, which itself is driven through digital advertising, the largest category of advertising for both Google and Meta. That too is human in the biggest in that the biggest outcome of digital advertising is physical products and real world experiences like travel.
Speaker 1:
33:29Digital products like apps and games, meanwhile, are themselves pursuing human attention. What was not viable in the nineteen nineties nor at any time since then was something like microtransactions for content. One obvious problem is that the fee structure of credit cards don't allow for very small transactions. Another problem is that costs to, to produce content are front loaded, and the potential payoff is both backloaded and unpredictable, making it impossible to make a living. The biggest problem of all, however, is that microtransactions are antihuman, forcing a potential content consumer to continue continually decide on whether or not to pay for a piece of content is alienating, particularly when plenty of alternatives for their scarce attention exist.
Speaker 2:
34:10I I really believe that a large amount of the sub stack economy Yeah. Is effectively crowdfunding
Speaker 1:
34:16Mhmm.
Speaker 2:
34:16Somebody's ability to just nerd out on a specific set of topics.
Speaker 1:
34:21I agree.
Speaker 2:
34:21And I think it's beautiful.
Speaker 1:
34:22I agree. It does seem like if there's yeah.
Speaker 4:
34:25Sorry.
Speaker 2:
34:25Yeah. Was just gonna say, but a lot of the content creators that are paywalled on Substack would be bigger and more influential if it was just completely free.
Speaker 1:
34:34Right? Yeah. Yeah. There's a big question in my mind of like, where does investigative journalism go in the era of going direct in modern tech media? Like, where is tech Seymour Hirsch?
Speaker 1:
34:48Like, you need someone who can just be like, Seymour Hirsch was just on the payroll of big newspapers for a long time and then
Speaker 2:
34:56could go
Speaker 1:
34:56and, like, hang out at a bar and talk to former soldiers about what they did in Vietnam and then figure out that the Mai Lai massacre happened and, like, uncover this, like, massive scandal. And we see this in Silicon Valley where there are companies that are like, you're not gonna be able to put a bunch of sponsored content on a takedown of some company that's defrauding their investors. The the win case is the John Kerry Roo story with Theranos where he was able to be on the Wall Street Journal payroll for a long time, hunt that story down for a long time, do a lot of sourcing and a lot of confirmation because it's extremely risky to write something negative about a $10,000,000,000 company that has incredible resources. I mean, they hybrid
Speaker 2:
35:37You kind of need the heat shield Totally. A big organization.
Speaker 1:
35:40Totally. Yeah. And also just you need to be able to pay your mortgage while you're doing the and not publishing and just doing nothing basically. Yeah. And being a % focused on chasing down a really big story.
Speaker 1:
35:53And then when you do it, there's a huge outcome because he of course sold a book and then the rights to the documentary and the movie and the TV show and all this stuff. And I don't even know if he's I don't know what he's up to now, but it seems
Speaker 2:
36:06like he worked
Speaker 1:
36:07out really well. Yeah. It'd be great to get him on the show. Here if he's getting back in the game, digging into some of the the some more testing. Yeah.
Speaker 1:
36:15Mean, Theranos two point o is coming right now.
Speaker 2:
36:17He's like, I'm back.
Speaker 1:
36:18He's like, I'm I'm I'm ready to start talking to the employees of this new the new blood testing company.
Speaker 2:
36:22It would have been a huge missed opportunity to not just name the company Theranos two point o Inc.
Speaker 1:
36:27Yeah. That'd be great.
Speaker 2:
36:29I mean
Speaker 1:
36:29Do do we know what the name is yet?
Speaker 2:
36:31I don't know if I missed it.
Speaker 1:
36:32But we'll have to look it up. Anyway, subscriptions do work at smaller scales, says Ben Thompson, because they are ultimately not about paying for content but giving money to another human, which you've mentioned, or human institution from the local news business model, which Ben wrote. It is very important to clearly define what a subscription means. First, it's not a donation. It is asking a customer to pay for money for a product.
Speaker 1:
36:55What then is the product? It is not, in fact, any one article, a point that is missed by the misguided focus on microtransactions. Rather, a subscriber is paying for the regularly regular delivery of well defined value. Each of those words is meaning is meaningful. Paying a subscription is ongoing commitment to the production of content, not a one off payment for a one off one piece of content that catches the eye.
Speaker 1:
37:17Regular delivery. A subscriber does not need to depend on the random discovery of content. Said content can be delivered to the subscriber directly, whether it be email, a bookmark, or an app. Well defined value, a subscriber needs to know what they are paying for. The last point is the crux of why many ad based newspapers will find it all but impossible to switch to a real subscription business model.
Speaker 1:
37:38When asking people to pay, quality matters far more than quality, and the ratio matters. A publication with one valuable article a day about a well defined topic will easily earn more subscriptions than one with three valuable articles, but 20 worthless ones covering a variety of subjects. Yet all too many local newspapers built for ad based business model that calls for daily content to wrap ads around spend their limited resources churning out daily filler even if those ads no longer exist. Ben says, I expect that this model will endure in the age of AI. Obviously, I'm biased at this point, but in a world of infinite content on demand, common content becomes community.
Speaker 1:
38:17And if I'm successful, this essay will generate a lot of discussion amongst a lot of people precisely because it is both original and widely accessible, funded by an audience that wants me to keep writing articles exactly like this. So, of course, Ben writes free articles and then also private ad supported articles and goes back and forth. So he gets a little bit of reach.
Speaker 2:
38:35So he goes in here, the death of the ad supported web. The ad supported web, particularly text based sites is going to fare considerably worse. In fact, the most substantive pushback to my defensive advertising was in my own excerpt. Most ad supported content is already terrible. Thanks to the bad incentives, bold suckerment, and injuries and bemoaned and the impossible economics enabled by zero marginal cost content generation and consumption.
Speaker 2:
38:59Google, in its most idealized form, aggregated content consumers aggregated content consumers by mastering discovery in this world of abundance, directing users to exactly the site they were looking for which was monetized through ads that were sold and served by Google. Indeed, this is the great irony in the ads antitrust case in which Google is currently embroiled.
Speaker 1:
39:20Luke Souffert asked on mobile dev memo. I've heard arguments that because Google suppressed competition in open web advertising markets, those markets should flourish when Google's monopoly is broken. But my sense is that this ignores two realities. First, the cons that consumer engagement has shifted into apps and walled gardens irreversibly. Of course, like, most people get their news from X or Instagram or Facebook.
Speaker 2:
39:41Yeah. And this was the logic for X to say, yeah. We don't want you posting links. Yep. We're fine for you to post an excerpt or little bit higher.
Speaker 2:
39:50Because we want you to click into the content Yep. And see another ad and then click out, go see something else, see another ad Yep. And just do that forever.
Speaker 1:
39:58And second, that Google was keeping the open web on life support and the open web's demise will be hastened when Google no longer has an incentive to support it. What happens to the open web when its biggest, although albeit imperfect benefactor loses the motivation to sustain it? Well, everyone's going in the walled garden. Walled gardens like social networks are both more attractive to most users and also better for advertisers. Google might soon lose what little motivation they had left to support the open web.
Speaker 1:
40:27However, that's not Google's and the web's only problem. Why go through the hassle of typing a search term and choosing the best link, particularly if search results are polluted by an increasingly overwhelming amount of SEO spam now augmented by generative AI when ChatGPT or Google itself will simply just give you the answer that you're looking for.
Speaker 2:
40:45In short, every leg of the stool that supported the open web is at best wobbly. Users are less likely to go to ad supported content based websites even as the long tail of advertisers might soon lose their conduit to place ads on those websites Yeah. Leaving said websites even less viable than they are today and they're barely hanging on as it is.
Speaker 1:
41:04I mean, I can you think
Speaker 2:
41:05of a single example of this is like historically trying to find an ingredient, like a Oh, yeah. A recipe. Right? You're like, I wanna make oatmeal.
Speaker 1:
41:13Yeah.
Speaker 2:
41:14And the site, like, berries the the only information you actually need, which is, like, how much how many how many cups of oatmeal to water, the ratio or whatever. And you have to see you have to scroll by, you know, two pop ups and six ads to get to that little nugget of information. And now it can just be immediately surfaced by an LM.
Speaker 1:
41:34I'm trying to think about the last time I visited, like, a truly ad supported website. Like, I'm scrolling through here, and it's just it's just nothing in my tabs. Like, everything is either a, like, a a marketplace that monetizes by transaction fees or a paywalled website for news or just Google search generally finding stuff. But, like, there are very, very few websites that I visit today on a regular basis that are purely ad supported. Like, I do go to The Wall Street Journal or The Economist or Strathecari or any of these, but none of them are purely ad supported.
Speaker 1:
42:18The Wall Street Journal does have ads, but they also have a big paywall in an actual subscription fee. So it's interesting. Yeah, the open web, I mean, is it dying or is it already dead? Like, seems like like no like like, you know, the the the Vice News and the BuzzFeed, like that boom and bust has already happened.
Speaker 2:
42:37Yeah.
Speaker 1:
42:38So I don't know. Anyway, he moves on
Speaker 2:
42:41to me. Yeah. Mean Yeah. What do you think? It'd be interesting to try to honestly run a deep research report on trying to understand traffic to these websites that are effectively dying but not dead.
Speaker 2:
42:53Right?
Speaker 1:
42:53I wonder what the best example
Speaker 2:
42:55I would imagine like how many websites have recipes cooking various things that still get people trickling in and they're technically still monetizing. Maybe webbing menu is probably not. Question is like at what point does it cost more to even host the website than it's generating traffic, right?
Speaker 1:
43:16Yeah. Mean, there's been a couple of those
Speaker 2:
43:18rollouts Because if you're making, whatever, if you're making a thousand dollars a month in ads Yeah. And it costs you a couple hundred bucks to maintain the website, in theory, would just keep that running indefinitely.
Speaker 1:
43:31Yeah. I mean, TechCrunch was obviously famously ad supported. They were bought by Regent, which is a private equity roll up of of brands. Let's look at their portfolio. It's all very hyper specific stuff.
Speaker 1:
43:45They own TechCrunch now, but they also own computer world, network world, PC world, Macworld, TechHive. They own Cheddar News. They own Defense News, Air Force Times, Navy Times, Army Times. So I imagine that Navy Times is probably ad supported. I mean, I'm just clicking around on the website, and there's not a lot of, like, paywalls I'm hitting, but they are running ads.
Speaker 1:
44:09And I'm sure that they have other ways to monetize, whether it's through premium, you know, reports or maybe conferences or something like that. But in general, it seems like there aren't that many companies. I would struggle to name companies that are generating over a billion dollars in revenue off of purely ad based website. That's not an ad exchange, for example.
Speaker 2:
44:31Yeah. Right? I doubt it exists.
Speaker 1:
44:32It doesn't really exist. Anyway, so Ben takes all of this. I, all this, like, preliminary thesis and and weaves it into Microsoft and the open agentic web. Says this reality is the fly in the ointment of an intriguing set of proposals that Microsoft Microsoft put forward yesterday at the Build twenty twenty five developer conference about the open agentic web. And so the quote from the CTO is the thing that is super important if you think about what an open agentic web could be is you need agents to be able to take actions on your behalf.
Speaker 1:
45:05And one of the really important things about agents being able to take actions on your behalf is that they have to be plumbed up to the greater world. So you need protocols, things like MCP and a two a and things that are likely going to be emerging over the coming year that will help connect in an open, reliable, interoperable way, the way agents that you are writing and agents that are being used so actively now by hundreds of millions of people to be able to go access content, to access services, to take action on behalf of users in fulfilling the tasks that have been delegated to them. One aspect of this vision of the agentic web, says Ben Thompson, was Microsoft's commitment to MCP, which we talked about a little bit, created by Anthropic. Scott told Nile Patel, an excellent interview on The Verge, that while MCP wasn't exactly what he would have designed from scratch, ubiquity is more important than semantic differences, particularly when you're trying to create HTTP for AI agents. The second part of Scott's vision was something Microsoft created called NL Web, natural language web, and these are natural language interfaces for websites that make them more directly accessible for agents.
Speaker 1:
46:09He says if you think back to the web, we have HTTP, and then we had things that sit on top of HTTP, like HTML mainly, that are opinionated about the payload. So today, we're announcing an NLweb. The idea behind NLweb is that it is a way for anyone who has a website or an API already to very easily make their website or API an agentic application, lets you implement and leverage the full power of language large language models to enrich the services and products that you're already offering. And because NL Web endpoint the every NL Web endpoint is by default an MCP server, it means that those those things that people are offering up via NL Web will be accessible to any agent that speaks MCP, so you really can think about it a little bit like HTML for the agentic web. I always thought this was odd because I thought that the that the layer to go between APIs and HTML for an agent to just transform HTML into something that an agent could understand would be very, very simple.
Speaker 1:
47:06I didn't think that we'd need a new protocol, but it seems like it's getting tons of adoption. So I guess this makes sense. We've done a bunch of work already with our partners who have been really excited to be able to very quickly get to implementation and prototypes using NL Web. They've worked with TripAdvisor, O'Reilly Media, a ton of really great companies that offer important products. So Scott concluded by reemphasizing how important it was that layers that the layers of the agentic web be open and use the evolution of the Internet as his reason of why.
Speaker 1:
47:35So he says, so the last thing that
Speaker 2:
47:37I wanna say before handing things back over to Satya is just sort of press on these two points about why open is so important here. You know it is unbelievable. What can happen in the world when simple components and simple protocols that are composable with one another are out there, exposed to the full scrutiny and creativity of every developer in the world who wants to participate or who has an idea. This thought game that I play with myself all the time is trying to imagine what the web would have looked like if one of the actors in the early development of the web say the browser manufacturers, browser manufacturers
Speaker 1:
48:08is a terminology. Marc Andreessen a browser manufacturer.
Speaker 2:
48:12Yeah. He made his money in in browser Domestic
Speaker 1:
48:16browser manufacturing.
Speaker 2:
48:17Domestic browser manufacturing. American dynamism browser. So had decided that they wanted to vertically integrate and own the entire web. A % of the web would have been dictated by the limits of their imagination. Yep.
Speaker 2:
48:30And it's just obvious with thirty years of history Yep. That that wouldn't have been a very interesting web. True. The web is interesting because Think of it of the iPhone Yep. App layer.
Speaker 2:
48:39Yep. If Apple wasn't controlling, it would be extremely chaotic, but there would undoubtedly be sort of cool, you
Speaker 1:
48:47know Yeah.
Speaker 2:
48:48Things that would emerge.
Speaker 1:
48:49Yeah. I'm kind of split on it because like there's so much creativity that you can do within a JPEG or an MP4. And so if you get on YouTube, I mean, requires more production value. But we are not constrained by anything other than just pixels here. And we can put tickers and do all sorts of things within the confines of the m p four box.
Speaker 1:
49:11I guess it is a little bit more narrow than than a web UI that anyone can use and click around. So we in in some ways we are being constrained, but they're like, just scroll on on any social network and you see the amount of creativity that that occurs even within the constraints of like Yep. No links. Right?
Speaker 2:
49:30Yeah. Despite Apple's control of the App Store, you still get the benefits of the web Yeah. Which he goes on to describe here. The web is interesting because millions, tens of millions, hundreds of millions of people are participating to make it this rich dynamic thing. That's what we think we need with Agentic Web and that's what we're hoping you all can get get inspired to go work on a little bit to riff on and to use the full extent of your imagination to help make this thing interesting.
Speaker 1:
49:54Yeah. So he says, so back to Ben Thompson, he says, I think the widespread adoption of MCP is a protocol layer and NL Web as markup layer sounds excellent. The big hole in Scott's proposal, however, was pointed out by Nile Patel in that interview. That's the piece that on the web right now seems the most under threat, the underlying business dynamics of if I start a website, put a bunch of schema on it that allows search engines to read my website and surface content across different distributions. I might add an RSS feed, which is a standardized distribution everyone agrees on.
Speaker 1:
50:23There's lots of ways to do this. But if I wait if I make a website and I open myself up to different surfaces, what will I get in return for that is not necessarily money. In almost every case, not money. What I'll get is visitors to my website, and I'll monetize them however I choose, selling a subscription, display ads, whatever. That's broken, right, as more and more of the answers appear directly, particularly AI based search products, traffic to website has websites has generally dropped.
Speaker 1:
50:46We see this over and over again. What's going to replace that in the agentic era where we've created a new schema for agents to come and talk to my website and receive some answers? What's going to make it worth it? And this is a good question. Scott, in his answer, noted that websites would be able to communicate to agents that that they wanted to make available and on what terms along with some vague hand waving about new advertising models and transactions.
Speaker 1:
51:09That last point is valid. TripAdvisor sells hotel rooms. O'Reilly sells training courses, and you can see a world where websites based on transactions can not only benefit from exposing themselves to agents, but in fact, transact more and potentially pay an affiliate fee, Patel. So, yeah, I mean, if you're if you're searching for a car and you're searching across eBay and Auto Tempest and Cars and Bids and Bring a Trailer, all of a sudden, it doesn't really matter if someone's landing on your website. All that matters is that their transaction transacting and that they found the car that they're looking for.
Speaker 1:
51:41And so for all those transaction based websites, they're going to do fine. Yes, someone who's just making content and putting ads on it is kind of screwed.
Speaker 2:
51:50I don't know about these transaction based sites, I mean, I'm thinking of cars as an example, right? You have CarGurus, you have probably what cars.com.
Speaker 1:
52:00Bring a trailer, cars and
Speaker 2:
52:01vehicles, these bunch of Yeah, the ones. But imagine a world where I just have CarGurus is like an ad based business model, they want to drive leads dealerships and get that. That In a world where I just say, hey, find me every single Ford GT between this year and this Yep. That's publicly available online. Bring me the contact information and actually reach out to the Yes.
Speaker 2:
52:24Yes. But So are
Speaker 1:
52:26You think I don't think you can disintermediate entirely. I think that I I think that the agent would would say, hey, there's a Ford GT that's available and bring a trailer right now. Here's the current price. Do you want me to sit here and bid on it for you?
Speaker 2:
52:37Yeah. But here's the issue though, because I can have the you could have the agent, like in theory, the agent would go to CarGurus and fill out the form and tell the dealer, process a lead to the dealer, and the dealer's like, thank you for this lead CarGurus. If I sell the car, I will pay you a fee, or maybe it's just paid up But the issue is an agent could theoretically just like find the, see the image of the car, and then find, do an image search.
Speaker 1:
53:02Maybe. Yeah.
Speaker 2:
53:04I I'm just saying do an image search and be like, oh, I found this exact car and this exact photo that the dealer posted on their own site.
Speaker 1:
53:10On their own website.
Speaker 2:
53:11And I'm not gonna pay CarGurus. I'm just gonna Sure. Sure. Find. And I'll actually call the dealer that they have it.
Speaker 2:
53:17I'll negotiate on your behalf. Then
Speaker 1:
53:18But people already do
Speaker 2:
53:19that. CarGurus is cooked. Yeah. Yeah. They already do that.
Speaker 2:
53:22But it's just much more scalable to say
Speaker 1:
53:25Yeah. But I mean, that's not that's not a a marketplace. Like like if you are on Bring a Trailer and you see a car, like, you generally can't disintermediate
Speaker 2:
53:33Bring a Trailer.
Speaker 1:
53:34Like like, so if you are a platform that's that's bringing liquidity to the market and bringing listings that don't exist elsewhere on the Internet. But, yes, I mean, people see this with Airbnb where they see a beautiful place and they're like, I'm going to go just look up this place and see if they have their own website. But a lot of people that are selling a one off car don't have a website where they're listing their car. Like, somebody might do that. Maybe in the future, you would just you would just, know, post on X, hey.
Speaker 1:
54:01I'm selling my car. I have it listed on Bring a Trailer, but you can just negotiate
Speaker 2:
54:04Well, funny. So one of the one of the companies that's probably pretty cooked in this new era is Internet Brands, And they own WebMD. They own But all the way through, they own Ford truck enthusiasts. They own RenLis.
Speaker 1:
54:18That's They
Speaker 2:
54:20own the Dodge Forum. Like some of these more community based sites, I think are gonna be fine.
Speaker 1:
54:24Yeah. Yeah.
Speaker 2:
54:25Because it's a place where a discussion is happening. But again Oh, well. Sites that are purely indexing
Speaker 1:
54:34seem So, yeah. Ben Thompson goes on and says, the original sin of the Internet lacking native payments was not, in my opinion, a sin at all. Advertising supported the human web, not because Andreessen failed to make a deal with the credit card companies, but because it was the only business model that made sense. No. The real neglect and missed opportunity in terms of payments is happening right now.
Speaker 1:
54:55Microsoft is on to the right idea with its adoption of MCP and in in introduction of NL Web, but its proposal by virtue of not including native payments isn't nearly compelling as it should be, as compel as compelling as it should be. The key difference from the nineteen nineties is that on the agentic web, native digital payments both are both viable and the best possible way to not only keep the web alive, but also in the process create better and more useful AI. And so he goes on to talk about stablecoins and agentic microtransactions. Let's start with the viability. This is from Bloomberg.
Speaker 1:
55:30Stablecoin legislation overcame a procedural blockade in the US Senate marking a major victory for the crypto industry after a group of Democrats dropped their opposition Monday. The industry backed regulatory bill is now set for a debate on the Senate floor with a bipartisan group hoping to pass it as soon as this week, although senators said a final vote could slip until after the Memorial Day recess. So, hopefully, this passes, and we can talk to everyone on Crypto Day about this, next week. That'll be a lot of interest a lot of fun. Ben goes on to say, I know I've driven longtime Strataker readers a bit batty with my long running and still enduring in the face of massive grift and seemingly unending scandals interest in crypto, but stablecoins are genuinely a big deal.
Speaker 1:
56:10I wrote a brief explainer last fall when Stripe acquired Bridge, and so I'm sure most people are familiar with stablecoins. He goes on to say stablecoins solve several of the microtransaction problems I listed above, including dramatically lower or no fees and the fact that they are infinitely divisible and thus can scale to very small amounts. Stablecoins, by virtue of being programmable, are also well suited to agents. Agents, meanwhile, are much more suited to microtransactions because they are not in the end simply software making a decision. Because they are in the end simply software making a decision unencumbered by the very human feeling of decision paralysis.
Speaker 1:
56:44So an agent can just go around and make a bunch of microtransactions. The entire digital ad ecosystem, he writes, is an example of deterministic agents making microtransactions at scale. Every time a human loads a web page, an awe inspiring amount of computation and communication happens in millisecond in milliseconds as an auction is run to fill the inventory on that page with an ad that is likely to appeal to the human. These microtransactions are only worth fractions of a penny, but the aggregate volume of them drives trillions of worth of value. The problem, as I and Patel both noted, is that this ecosystem depends on humans seeing those web pages, not impersonal agents impervious to advertising, which destroys the economics of ad supported content sites, which in the long run dries up the supply of new content for AI.
Speaker 1:
57:32OpenAI and Google, in particular, are clumsily addressing the supply issue by cutting deals with news providers and user generated content sites like Reddit. This, however, is bad for the sort of competition Microsoft wants to engender and ultimately won't scale to the amount of new content that needs to be generated. What is possible, not probable, but at least possible is to, in the long run, build an entirely new marketplace for content that results in a new win win win equilibrium. First, the protocol layer should have a mechanism for payments via digital currency, stablecoins. Second, providers like OpenAI should build an auction mechanism that pays out content sources based on the frequency with which they are cited in AI answers.
Speaker 1:
58:09And this is kind of already happening with Spotify. Right? Like, there's a whole bunch of music on Spotify. They have a whole pool of capital from all their subscribers. And then the more listens that they get, the more money flows in.
Speaker 1:
58:19And it's not really an ad based auction system. It's more like just dividing up the pie.
Speaker 2:
58:24The thing there, and it's a good comp, is that that was happening from the very, very beginning in the initial
Speaker 1:
58:31Yeah.
Speaker 2:
58:31Deals that Spotify did with record labels to get the music on in the first place. Yep. And now we're in a situation where all the LLMs are just using the internet.
Speaker 1:
58:42That's not true though. Like OpenAI has a deal with The Wall Street Journal.
Speaker 2:
58:46They have some deals, but they certainly don't have deals with every book they've ever ingested.
Speaker 1:
58:51No. No. No. But you imagine that they'll kind of go down the power law curve of like the most important information sources and broker deals more and more and more, which is what Spotify did at the beginning because they
Speaker 2:
59:03had
Speaker 1:
59:02No.
Speaker 2:
59:03That if they're sued.
Speaker 1:
59:04Remember, like, they had then they have
Speaker 2:
59:05been sued. They've been sued a ton.
Speaker 1:
59:06And then Over and over. So so so they get sued, then they settle, and then they do a deal. And, like, yeah, it's a little messy, but it's fine because at the end of the day, The Wall Street Journal has a deal with OpenAI where OpenAI can ingest information from this, surface it, and chat GPT results, and The Wall Street Journal gets paid for that work. And and I don't know the structure of the deal, but I imagine that it's something like like, you know, we're generating this much money from people searching, and and you're driving 1% of our value, and so we'll give you 1% of the cut or half a percent. We'll split it with you.
Speaker 1:
59:39Just like, you know, if you're Taylor Swift on Spotify and you're getting, you know, 1% of the listening time, they'll give you half a percent of revenue or something like that. Right? Is that not crazy?
Speaker 2:
59:50Is that crazy? I love it theoretically.
Speaker 1:
59:52I think that's like what what's happening. And and the problem is
Speaker 2:
59:54that gonna need to
Speaker 1:
59:55go down the stack until it's self serve. Because if you want the open web, you can't do individual deals. And so eventually, anyone can go on Spotify. Like, we're on Spotify. We get, I think we get a check.
Speaker 1:
01:00:05We get a check from Google, at least. And in theory, it's like we don't need to do a deal with Spotify. Of course, Joe Rogan did do a deal with Spotify directly, like The Wall Street Journal did a deal with OpenAI.
Speaker 2:
01:00:15Yeah. But
Speaker 1:
01:00:16whole, say podcasts go on Spotify. Spotify automatically runs ads and and does premium plays and then sends them a check.
Speaker 2:
01:00:23It's just such an interesting dynamic. Right? Because
Speaker 1:
01:00:27Why would
Speaker 2:
01:00:28it play
Speaker 1:
01:00:28out so different?
Speaker 2:
01:00:29So often LLMs are not just serving the content. No. They're effectively remixing it.
Speaker 1:
01:00:36Totally. Right? But
Speaker 2:
01:00:37but And the precedent historically
Speaker 1:
01:00:39They're hitting the page.
Speaker 2:
01:00:40Historically, if the journal went into the, you know, somebody from the journal goes into the library, public library, reads a bunch of books, forms its own kind of summary of Yeah. Nobody's getting paid for that, right? Yeah. But And so there's an arg the the models can make an argument that there's enough precedent that says there's nothing illegal about ingesting
Speaker 1:
01:01:04Yeah.
Speaker 2:
01:01:04That's true. Information.
Speaker 1:
01:01:05But there is this there is this win win win that Ben Thompson's talking about, this this idea that Google has an incentive to keep the open web alive, and the LLM providers might have a similar incentive because they want more journalism and more facts to hit the Internet that they can scrape and pull into results. True. And so what is the value of a single Wall Street Journal page loading logged out? Right?
Speaker 2:
01:01:29Yeah. Can see a scenario or something else. I'll fracture this. Where it's like net new content or something like that, where like OpenAI doesn't deal with Substack.
Speaker 1:
01:01:38Why not every time? Why not on a user basis? I asked for a summary of the Wall Street Journal Mansion section.
Speaker 2:
01:01:47No. I'm I'm saying And
Speaker 1:
01:01:48it went read 10 articles. No. I'm saying
Speaker 2:
01:01:49every time. I'm saying every time. I'm just saying it's possible that there needs to be some type of cutoff date where, you know, again, how does this actually it sounds really simple in finding this win win win, but the actual mechanics of getting a deal done between the Internet and a relatively small group
Speaker 1:
01:02:12Yeah.
Speaker 2:
01:02:12Of foundation model providers. Yeah. But again Are
Speaker 1:
01:02:16you saying that there's a tremendous amount of complexity?
Speaker 2:
01:02:19I'm saying there's a tremendous amount of complexity, John.
Speaker 1:
01:02:21Because that's exactly what Ben Thompson's concluded with. He said there is, to be sure, a tremendous amount of complexity in what I'm proposing, and the path to marketplace for data generation is quite unclear at the moment. Who, however, could have predicted exactly how the ad supported web would have evolved or centrally designed the incredible complexity that undergirds it? This is where Scott's exhortation of openness is spot on. A world of one dominant AI making business development deals with a few blessed content creators and scraping the carcass of what remains on the web for everything else is a far less interesting one than one driven by a marketplace, auctions, and aligned incentives.
Speaker 1:
01:02:58To get there, however, means realizing that the Internet's so called original sin was in fact key to realizing the human web's potential, while the actual mistake would be in not building payments now for the coming agentic web. And so bull market in stablecoins. We can see stablecoins trading at $1.0001.
Speaker 2:
01:03:20Funny Buy it now. It's it's so funny because everybody's so bullish and convicted on stablecoins now but it's like No way. Do how do we make money on this? Money on this.
Speaker 3:
01:03:30How do we
Speaker 2:
01:03:30make money? I don't think it's launching the next circle, right, or another stablecoin provider even though that clearly is a great business if you look at
Speaker 1:
01:03:38Yeah.
Speaker 2:
01:03:39You know, some of the different providers. I was actually wanting to get, there had been rumors that Circle is Yeah. Talking with Coinbase and Ripple about a sale because they put out their s one. Mhmm. The market hated it, and they're basically like, you are completely dependent on on Coinbase
Speaker 5:
01:04:00Mhmm.
Speaker 2:
01:04:01In many ways and paying all such a large part of your revenue to Coinbase, you know, does this so anyways, could make a lot of sense for those two to join forces, but Coinbase is also dealing with a lot right now.
Speaker 1:
01:04:16Yeah. Well, that concludes Microsoft. And we've talked about Google a little bit. Should we move over to Stargate and I would like to do that, guy. We're taking a full tour today.
Speaker 1:
01:04:29We we're we're just going around the horn to all the big labs. One story after another.
Speaker 2:
01:04:34We gotta get boots on the ground and Abilene.
Speaker 1:
01:04:38Yeah. We gotta go there. I mean, Chase was was texting me earlier. We gotta have him on the show, but I think visiting would be worth it. It seems like, Sharon Gaffare, I don't know if I'm pronouncing that right, but Sharon over at Bloomberg, got an exclusive look inside project Stargate, the $500,000,000,000 AI infrastructure project, including an on the ground tour of its first massive data center in Abilene, Texas with interviews of Sam Altman.
Speaker 1:
01:05:05Love it. She's been on absolute tear. Wrote this today. Dropped the anthropic profile of Dario yesterday. Just banger after banger.
Speaker 1:
01:05:15So inside the first Stargate AI data center, OpenAI, Oracle, and SoftBank hope the site in Texas is the first of many across The United States. Let's dig in. Trucks carrying concrete and electrical wiring plot over red clay weaving in between cranes and excavators. Two symmetrical buildings stand in a massive plot of land where thousands of people in brightly colored vests work day and night to construct six more near identical structures that will make up the first site for Stargate project. Stargate is collaboration between OpenAI, Oracle, and SoftBank with promotional support from Donald Trump.
Speaker 1:
01:05:46Love it.
Speaker 2:
01:05:47Throwing that in. Yeah. Still unbelievable that they got him to just go and and announce it even though
Speaker 1:
01:05:54The guy loves building in America. You know? This is like his whole brand.
Speaker 2:
01:05:58Showbiz.
Speaker 1:
01:05:58Loves build the big things. To build data centers and other infrastructure for artificial intelligence throughout The United States. The companies have pledged to spend as much as $500,000,000,000, a number so large it's hard to believe it'll actually happen. But at least for one for this one, in Abilene, Texas, a 80 miles west of Dallas, Chase Lockmiller says they're good for the money. Chase Lockmiller.
Speaker 1:
01:06:24Chase.
Speaker 2:
01:06:25This is an incredible
Speaker 1:
01:06:26He chases the energy. He locks it down. Then it's Miller time. Chase Lockmiller, baby. He's up Chase.
Speaker 2:
01:06:31Determinism is wild. Let's pull up
Speaker 1:
01:06:33a photo of Chase. He's looking great. He's hanging out.
Speaker 2:
01:06:36An absolute dog.
Speaker 1:
01:06:37Yeah. He's been on this for so long.
Speaker 2:
01:06:39Lochmiller is the co
Speaker 1:
01:06:40founder. Or years ago. You can go to the next slide. It's where he's more centered. I met him four or five years ago when they were doing oil and gas flaring for crypto mining.
Speaker 1:
01:06:50And it was Yeah.
Speaker 2:
01:06:51There was
Speaker 1:
01:06:51And it was AI mean, the business was doing really well.
Speaker 2:
01:06:53It's funny because it's funny because it was very low status to do the crypto to AI pivot. Totally. Yet you get Corweed and Crusoe out
Speaker 1:
01:07:01of it.
Speaker 2:
01:07:02Yep. Killed absolute monsters.
Speaker 1:
01:07:04Always ignore the meme. Whatever
Speaker 2:
01:07:05the meme
Speaker 1:
01:07:06means, just ignore it. Build a GPT wrapper and sell it to OpenAI for 3,000,000,000. Like, pivot from crypto to AI and IPO for 40,000,000,000. Do it. It's fine.
Speaker 1:
01:07:14It doesn't matter. Ignore what the haters think.
Speaker 2:
01:07:17Yep. Ignore. So Locke Miller is, of course, the co founder and chief executive officer of Crusoe. That's A startup that helps develop AI data centers. Crusoe's cost to build the one in Abilene are expected to reach 12,000,000,000, Locke Miller says, and that's not counting the billions of dollars worth of Nvidia Corp chips that will be installed in the finished facility.
Speaker 2:
01:07:36Love it. I've never built anything of this scale, Lochmiller says. I've had to learn a lot on the job. So the three main companies behind Stargate could say the same thing. OpenAI knows AI, but has relied on Microsoft for data centers.
Speaker 2:
01:07:48Oracle knows databases, but only holds 3% of the cloud market. Softbank once raised a hundred billion dollar fund, but that didn't go so well. Let's give them some time. Let's let them cook, you know. Where's his name?
Speaker 2:
01:08:03Ten year ten ten year horizon. We got a got a few years left on that one.
Speaker 1:
01:08:06Oh, yeah. We we got to pivot really quickly to the to The Economist because The Economist has an article about will OpenAI ever make real money? We should do a whole deep dive on this one. But the way they describe SoftBank is hilarious. Here, it says, they're they're talking about, the latest OpenAI fundraising.
Speaker 1:
01:08:28Happily for the CFO of OpenAI, money men swept up in the AI mania need little persuading. They're falling over themselves to fund OpenAI. On May 13, SoftBank, a Japanese tech piggy bank, said that its $30,000,000,000 investment in the firm was unaffected by OpenAI's recent decision not to ditch its odd governance structure, a nonprofit board with peak control of its for profit arm. It's a whole it's a whole great article. I mean
Speaker 2:
01:08:58We were talking about this off air. I mean, it's absolutely credit to Sam
Speaker 3:
01:09:02Yeah.
Speaker 2:
01:09:03For not completing the conversion, but not having to renegotiate at least the top level numbers. Yeah. Yeah. The 30 on three thirty or whatever it was. Masa was One of the best deal makers of all time.
Speaker 2:
01:09:18And Masa doesn't clearly Yeah. Clearly doesn't care what price he Yeah. Like Just wants
Speaker 1:
01:09:24get simultaneously, the SoftBank deal is like crazy and unprecedented and wild and Japanese piggy bank and all that. But the premise of like, will soft will OpenAI ever make real money is like ridiculous to me.
Speaker 2:
01:09:35Will the next will the next consumer tech giant make money online?
Speaker 1:
01:09:42Will a company 500,000,000 users make money?
Speaker 2:
01:09:45I was saying this yesterday off air. Was like, you remember it was only, it was less than a year ago, people, Anthropic was ripping. Yep. Yahoo, narratively. And everybody was just saying, yeah, open AIs, Yahoo, open AIs, Yahoo.
Speaker 1:
01:10:00I was thinking about this a lot and I was like, what what was the problem with Yahoo? Like, they got like like, they they got disrupted by Google obviously, but like more specifically what happened? Like, it was it was a shift from from non algorithmic links, right, to a better algorithm in PageRank. Like, it was a development of a better algorithm that really smoked them. And I'm wondering, like, is that is that a point of fragility for OpenAI?
Speaker 1:
01:10:32Like you could imagine someone comes up with a different model for AI. Like they say like the transformer architecture is fundamentally not it. It's v one and we're coming out with v two and it's a completely different architecture. Two Fine. Maybe that happens.
Speaker 1:
01:10:48Is OpenAI agile enough to implement that within six months? Like, probably. Right? If Deepsea can clone transformers and reasoning models in just a few months, you would think that like, I guess the question is, like, Yahoo failed not just because Google invented PageRank, which sorted the links by the number of links to a specific website. And so if everyone is linking to Stratechery and you search for tech news, that increases the PageRank and that shows up at the top.
Speaker 1:
01:11:17And that was the key insight by Larry Page, the creator of PageRank, and created much, much better results. Like when you went to Google, it was dramatically better of a product. I remember when it came out. Like I was a kid and I remember using AltaVista.
Speaker 2:
01:11:33You're what? Like
Speaker 1:
01:11:3430? 30 at that point? Yeah, yeah, exactly. Like a little late, late teen. I think I was actually like eight or something.
Speaker 1:
01:11:41But anyway, so so I had been using Yahoo and AltaVista, and you would search, and it would just be kind of like random links, or they'd be, like, kind of curated. It would literally just be it would it would basically just search based on the keyword. So if you search for, like, tech news, you would more than likely just see, like, technews.com come up because it had really strong, like, SEO just from keyword searching.
Speaker 2:
01:12:05Yep.
Speaker 1:
01:12:05Google brought in PageRank and said, well, if if doesn't matter that Strathecory, the name the word doesn't make any sense, and Ben Thompson never actually writes, I am tech news, technology news, hashtag technology. It doesn't matter that he says that. All that matters is that everyone is linking to Strathecory, and it's actually a great source for tech news. And so we're gonna put that at the top of the results. Now that was a better algorithm, and and it was a better product very quickly.
Speaker 1:
01:12:30But if Yahoo had implemented PageRank, which I don't know if it was, like, patented or something, but if they'd been able to
Speaker 2:
01:12:35to
Speaker 1:
01:12:36keep up with that, people probably would have just stuck with Yahoo for a lot longer. But something about where the company was and the culture didn't allow them to upgrade their search results, and so they fell behind very quickly. And so for OpenAI to become the Yahoo of AI, there would have to be a new company that comes out with a dramatically different technology or paradigm and either is able to patent it or or keep it locked up in some way that OpenAI can't just port that innovation back. Because they've obviously been able to do that with other advances in image models that are happening elsewhere, reasoning or tool use. Like, it would be crazy.
Speaker 1:
01:13:11And this is something that's always interesting in tech is like there just don't seem to be that many patents that hold. Like, amazing would it be if you're just like, I'm the person that thought of MCP, or I'm the person that thought of image diffusion. And Yep. I have the patent, and so I'm the only one that can build the company, or you have to pay me to license this. Like, that's just not a conversation at all.
Speaker 2:
01:13:31How many designers, for example, have patents from big tech companies and then can leave and effectively rebuild the same feature
Speaker 1:
01:13:38as your And the patents don't even seem to hold. Like like, did you know that the swipe down to refresh, pull to refresh, that was patented by a designer at Twitter, like ten years ago or fifteen years ago.
Speaker 2:
01:13:52Potentially, they created the slot machine for the
Speaker 1:
01:13:55Yeah. Endless scroll was
Speaker 2:
01:13:57another Slot machine for
Speaker 1:
01:13:58the mind. Yeah. Endless scroll. Well, now now you don't even really pull to refresh. I mean, I guess you do every once in while, mostly it's just endless scroll.
Speaker 1:
01:14:03But that was another thing that was invented at one of the big tech companies and then immediately ported across every other platform. And, like, Stories. Snapchat, Evan Spiegel created snore the Stories format. Thank you, Evan Spiegel, for creating Stories. We love innovation.
Speaker 2:
01:14:19Thanks for creating a low risk way to just share what you're up to.
Speaker 1:
01:14:23Really shuffled stories. But he wasn't able to patent it or, like, or, like, you know, keep Meta from rolling out to every single thing. LinkedIn has stories now, and and there's this question. It's like, it's kind of this weird failure potentially of the IP system. Maybe it's better because stuff just goes everywhere.
Speaker 1:
01:14:39But if you're if you're OpenAI and you're on top of the of of the innovations that are happening even at other labs, you would imagine that you'd be able to port back anything and stay on top as long as you're that front door and you have the scale that Yahoo or Google eventually got to, hundreds of millions of users, you should be fine. Anyway, that was just my thinking on the the Yahoo thing. It feels like a stretch. Yep. Especially given the recent the recent innovations.
Speaker 2:
01:15:05Totally. Anyways, back to back to Abilene. Yeah. Where we don't use Manus. Use we use chat GPT around these parts.
Speaker 2:
01:15:16Anyway, so the the article here is pointing out that OpenAI SoftBank and Oracle Yeah. Are funding this $500,000,000,000 project and yet none of them have Hyperscalers. Hyperscalers sort of data center
Speaker 1:
01:15:30Microsoft, but yeah.
Speaker 2:
01:15:31Experience. No, Microsoft, I mean, Microsoft is not in Stargate. It's OpenAI, SoftBank, and Yes,
Speaker 1:
01:15:39yes, true, true, true. And so the only companies that have built cloud infrastructure on
Speaker 2:
01:15:42this scale
Speaker 1:
01:15:43are Amazon Oracle. Microsoft.
Speaker 2:
01:15:44Yeah, Oracle knows databases, but they only have 3% of the cloud market. Right?
Speaker 1:
01:15:48Oh, the Don't count that. Ellison is in Don't count out Larry. Oh, yeah. Right. Oh, sure.
Speaker 1:
01:15:54You're in the you're in the truth zone. Larry's good. Larry's good. Don't don't comfort Larry. Larry's on top of
Speaker 2:
01:16:01it. Will defend
Speaker 1:
01:16:02Larry. He's years old, he looks like he's 42. He looks great.
Speaker 2:
01:16:06Incredible. And he follows DBPN.
Speaker 1:
01:16:08Yeah. He's gonna be fine.
Speaker 2:
01:16:09We love you, He's
Speaker 1:
01:16:10gonna he can he can build some cement. He's got chase on the case.
Speaker 2:
01:16:13That's right. He's got chase on the case. Anyway, so in interviews with Bloomberg Businessweek, the CEOs of OpenAI and SoftBank acknowledged that they've promised a lot and that to some extent they're figuring things out as they go. And we knew this, right? They announced this.
Speaker 2:
01:16:26It was like, you know, Elon was pointing it out, he was saying, where's the money coming from? Yeah. It's very, you know, pulling $500,000,000,000 together is not not the easiest thing in the world. Yeah. So they just they dismissed critics, the loudest being Elon Musk who says the full scope will never be realized because they don't have the money.
Speaker 2:
01:16:45We don't and Masa says, founder of SoftBank Yeah. Infamous Japanese piggy bank is this article. And The Economist says, we don't need $500,000,000,000 in one day. We'll go step by step.
Speaker 1:
01:16:58Do you think more founders should be pitching stuff like Stargates? Like, yeah. Like, I I need to realize by full vision, I need 500,000,000,000. I don't need it right now. So, like, if you're if you're gonna come at me for that, that's ridiculous.
Speaker 1:
01:17:09Like, I didn't say I needed it right now. Yeah. But over the course of this company, we will consume 500,000,000,000 capital. Yeah. Mean, a lot of the nuclear companies might.
Speaker 1:
01:17:18You know? Who
Speaker 2:
01:17:19knows? They produce trillions. So OpenAI CEO Sam Altman knew they'd need construction crews and lots of computers. Yep. We're gonna need Computers.
Speaker 2:
01:17:27Hey, folks.
Speaker 3:
01:17:28We're gonna
Speaker 2:
01:17:28need lots of computers.
Speaker 1:
01:17:30We're gonna need computers.
Speaker 2:
01:17:31But data centers also have extensive electricity and water needs to keep the machines running at a safe temperature, often requiring infrastructure upgrades that can take years for Abilene, which will have a mighty capacity of point two gigawatts. The team built its own gas power plant to get the place running more quickly. Yeah. The the We talked a little bit
Speaker 1:
01:17:51Augustus, but there's this whole meme about like, every time you search GETGPT, it like pour empties out an entire lake and like we're running out of water. And like, I mean, I'm sure it uses some water, but I have no idea exactly how that's calculated. And that feels like something that's
Speaker 2:
01:18:05been Yeah, question is what percentage evaporates during cooling process? Yeah. And is it
Speaker 1:
01:18:12Like a lot of a lot of cooling systems are pretty closed loop because you're just piping you're piping the water through through tubes, and then the water goes onto the chip. The chip heats up. The water goes the water gets hot, and then you pipe the water out. That's like a a water cooled GPU rig on like a gaming PC.
Speaker 5:
01:18:30Yeah.
Speaker 1:
01:18:31And like, yeah, you need to change out the water every once in a while, but like not constantly. And so it's not like, I I I I do wonder how what the actual impact scale is here. And I bet that there's a lot of people with, like, the incentive to say, just use any water.
Speaker 2:
01:18:44Or, like, you just get way
Speaker 1:
01:18:45too much water.
Speaker 2:
01:18:46I wonder if you could rip out the the parts of an air cooled Porsche Yep. And potentially use those.
Speaker 1:
01:18:52Yeah. Air cool I want an air
Speaker 2:
01:18:53cooled And then Elon could take the air cooled Porsches and put engine swap Tesla motors into that.
Speaker 1:
01:19:00I I I think we wanted this supercharged AI factory. Factory. Just pipe the pipe the air back in to accelerate it. Take the exhaust fans and reroute them right onto the chip.
Speaker 2:
01:19:11Yeah. So anyways, Sam knows he's gonna need a lot of computers. Yeah. But they also have extensive electricity and water needs. So Abilene is gonna have 1.2 gigawatts.
Speaker 2:
01:19:22Team built its own gas power plant to get the place running more quickly. Cool. One of the things that really surprised me as we were starting to dig into this, Altman says, was just how many things feed into the mainline. The mainline is still being assembled. At the Abilene site in March, some rooms are in the process of being wired and are off limits due to the risk of electrocution.
Speaker 2:
01:19:41In the future, tubes will pump cooling liquid around servers, which will be loaded with NVIDIA graphics or sorry, GPUs to the physical Oh,
Speaker 1:
01:19:50GPU actually stands for graphics processing unit. Yeah. As they thoughtfully noted in this piece.
Speaker 2:
01:19:54It's good to note. It's good to note. If you've been living They also contextualize it
Speaker 1:
01:20:07telling you what a GPU here is. It's not only a graphics processing unit. You can think of it as the physical brain of AI.
Speaker 2:
01:20:14Something there.
Speaker 3:
01:20:15Something there.
Speaker 2:
01:20:16P b PBAs.
Speaker 1:
01:20:18This is this is this is ripped straight from a SoftBank deck. Yeah. It's like they're talking to the same audience. Retail. Yeah.
Speaker 1:
01:20:25For now, those tubes dangle from the ceilings beside half lit hallways. We're trying to deliver on the fastest schedule that a hundred megawatt or greater data center has ever been built, Locke Miller says, from this front seat of a buggy on a ride to the construction site. In this moment, speed matters a lot. The big reveal for Stargate was at the White House on day two of Trump's second term. I didn't I forgot it was so early.
Speaker 1:
01:20:49Altman, Sohn, and Oracle chairman Larry Ellison stood behind
Speaker 2:
01:20:52This was so funny too, remember, because it was it was Elon and Sam, like, both around the White House on the same day in the midst of this battle. Dude. A little bit of an awkward
Speaker 1:
01:21:04Have you have you seen this this picture of Masa getting hype monged so bad by Larry?
Speaker 2:
01:21:10It's brutal. Billy John, you're gonna bring up hype mogging.
Speaker 1:
01:21:13It's a sensitive topic on the show.
Speaker 2:
01:21:15It's sensitive topic.
Speaker 1:
01:21:16But we but I mean we we Pull
Speaker 2:
01:21:18we should pull it we should pull it up.
Speaker 1:
01:21:19We gotta call it out. Anyway, lavishing praise and crediting him with help making the pass the project possible. The whole production came together in a matter of days according to a person familiar with the events planning who asked not to be identified. Stargate's real origin, according to Peter, the vice president of infrastructure and strategy at operations at OpenAI, Hochelay Hochelay, I'm not sure how to pronounce the last name, goes back to a research paper published at the beginning of the decade written by a group at OpenAI that included Dario Amade, who'd go on to start one of the company's main rivals, Anthropic PBC. The paper describes so called scaling laws.
Speaker 1:
01:21:58This is GPT two, which we've talked about a bunch, which assume that the more capable AI requires ever more data and computing resources. What's interesting is, like, we're talking about increasing the ooms, but, like, this has to be synthetic data at this point because we've kind of already hit the data wall, I believe, or are we because I don't know if there's ever anyone We're expanding it. Yeah, but I don't know that anyone's really mapped out like 10x. Yeah, check out that photo. Rough podium situation.
Speaker 1:
01:22:28Trump's also pretty big too. Larry's pretty big. But, yeah, Masa. Well Tough presentation.
Speaker 2:
01:22:36Still a size lord.
Speaker 1:
01:22:37Yeah. Makes up for it with the checks he
Speaker 2:
01:22:39rips. Yep. OpenAI, as many know, already had a contract designating Microsoft its primary financial backer as its exclusive cloud provider, but Altman decided he'd eventually need other options. Oracle was looking for partners for the future complex in Abilene and was talking with Musk before Altman came in. Says a person familiar with the discussion.
Speaker 2:
01:23:00Musk obviously chose Memphis for x AI, so went a different direction.
Speaker 1:
01:23:05Oh, this is cool. Altman picked the name Stargate because of one of OpenAI's early data center designs resembled the ring shaped portal that could open a wormhole in the 1990 science fiction movie of the same name. Also a TV show. You ever watched Stargate? Absolutely not.
Speaker 1:
01:23:21Next question. After half a year of Altman selling the idea to prospective backers, Stargate really came into focus in mid twenty twenty four, and he says he sound he found himself in a lot of Zoom meetings.
Speaker 2:
01:23:33Also a CIA project around mind reading.
Speaker 1:
01:23:37Oh, I don't know. I'm not familiar with that one. Look it up. Chat can can The hardest part was figuring out what shape of the what the shape of the deal would be. Would it be part of OpenAI?
Speaker 1:
01:23:45Should it be a separate entity? You know they love separate entities over at OpenAI, so we know where they landed on this one. Should we just try to get one company to build it all for us? That's
Speaker 5:
01:23:54the Stargate
Speaker 2:
01:23:55project was a classified United States Army program. Wasn't affiliated with the CIA, but it was initiated in 1977 by the DIA and SRI International to explore the potential of psychic phenomena in intelligence gathering and military applications.
Speaker 1:
01:24:11How'd it go? Did they were they successful?
Speaker 2:
01:24:13I mean
Speaker 1:
01:24:14Seems like it.
Speaker 2:
01:24:15I'm sure I'm sure they I'm sure they cooked.
Speaker 1:
01:24:17So OpenAI is responsible for the operation of the business and will be its main customer. SoftBank handles the financial side, including raising additional funds for Abilene. Oracle will lease the data center and fill it with servers. Crusoe declined to comment on whose else is going in. OpenHand and SoftBank will each put in 19,000,000,000 to start.
Speaker 1:
01:24:35Oracle and another equity partner, Abu Dhabi based investment firm, MGX, are on the hook for 7,000,000,000 apiece according to a person familiar with the matter. So, yeah, I mean, 19 and 19 plus 7 and 7, you're getting up into the forties, fifties, sixties, billions. Not bad. It's not 500, but they're getting there. They're within 1 oom.
Speaker 1:
01:24:56That's what they gotta do.
Speaker 2:
01:24:57Striking distance.
Speaker 1:
01:24:58Each project will be financed individually with a mix of equity and debt with data center firm Primary Digital Infrastructure is helping orchestrate the financing. JPMorgan Chase is, doing some loans.
Speaker 2:
01:25:11Yeah. So if you have money over at Chase, you're I would say at this point entitled to say that you're a financier of Abilene of the of the project in Abilene.
Speaker 1:
01:25:21That's great. For future sites, SoftBank has held talks with dozens of lenders and alternative asset managers. Although, it's yet to secure a deal, and some of those conversations have slowed due to global market volatility. But now we're kinda flat. Maybe the markets open back up and things move on.
Speaker 1:
01:25:37That's a structured financing that SoftBank has done many times in the past, so we are very confident. And, yeah, I mean, SoftBank took ARM private, and so they're clearly they're clearly capable of operating at this scale. It's not not crazy. Not everyone is so optimistic about SoftBank's ability to execute. The last time SOWN did anything close to this scale was the Vision Fund, which depended on a $45,000,000,000 contribution from Saudi Arabia's largest sovereign wealth fund.
Speaker 1:
01:25:58Imagine clipping two and twenty on that. SoftBank's fund racked up losses most disastrously disastrously on the
Speaker 2:
01:26:06on the office's
Speaker 1:
01:26:07real estate startup WeWork.
Speaker 2:
01:26:08Sometimes I get crazily overexcited and I make a mistake like WeWork, but when you have the conviction and the passion, Masa's mistake was not backing, what's the new company?
Speaker 1:
01:26:20Cruiser?
Speaker 2:
01:26:20No, no, no, the new real estate company by Newman.
Speaker 1:
01:26:25Oh, don't know.
Speaker 2:
01:26:25Andreessen did.
Speaker 5:
01:26:26Flow?
Speaker 2:
01:26:26Flow. He should have doubled down. Yeah. But when you have the conviction in the past and you actually learn from those mistakes and the scars, and that will make you stronger. I've made so many more mistakes that I think I'm a little stronger than in the past.
Speaker 1:
01:26:37He's been very wrong, but he's also been very right. And he's been right more than he's wrong, and so he's still in the game. And as long as SoftBank is cooking as a company, he can keep ripping checks.
Speaker 2:
01:26:46Yeah. I mean, it's his calculus is, I believe Yeah. Can be done on a napkin. And this is just my guess.
Speaker 1:
01:26:54It's huge napkin.
Speaker 2:
01:26:55He has a very large napkin, and it's basically if I buy
Speaker 5:
01:26:5910% off, then If
Speaker 2:
01:27:00I buy 10% of OpenAI, and it's a trillion dollar company someday, I'm gonna do very well. Yep. And I'm gonna lever up to do that. So my actual return on equity Yep. Is gonna be fantastic.
Speaker 1:
01:27:13It's amazing.
Speaker 2:
01:27:13And he's gonna be laughing, and this is I
Speaker 1:
01:27:15mean, this is like, this is, like He's a gambling guy. It's not as crazy as
Speaker 2:
01:27:19thing goes. On Masa. One of the best books on Masa is called the gambling man. That's the context you need. Yeah.
Speaker 2:
01:27:25We did a whole deep dive on it.
Speaker 1:
01:27:27Complicating matters are Trump's tariffs. Cost calculations swing every time the president changes his mind, but the trend line is expected to go up on, is expected to go up on aluminum, steel, and other construction supplies, not to mention NVIDIA GPUs, which are made mainly by Taiwan Semiconductor Manufacturing Co, TSMC. Sohn says he expects no significant impact from the trade policies, and I think he's right. I think this is what Trump wants, and I think all of these will get will get car routes, and they've already been negotiated down. So I I'm not too worried about that.
Speaker 1:
01:27:56Trump I I I think the bigger question here is just, like, like, what is the return to scale? Because we've seen the scaling laws kind of maybe potentially drop in terms of pretraining wall and whatnot. And so the question is just, like, what does a 10 x larger facility actually get you? It better be worth it because we know the we know the economics of GPT four training run were great. Like, they they printed tons and tons of $20 a month subscriptions off of that, and I think the total cost was, a hundred million dollars.
Speaker 1:
01:28:26Now you're up at 10,000,000,000. Can you get everyone on a $2,000 a month subscription? If you can, no big deal.
Speaker 2:
01:28:32Well, yeah. And a lot of I mean, won't a huge amount of Stargate's resources just go towards servicing Yeah.
Speaker 1:
01:28:39Models inference. Potentially. But I mean, I I feel like a lot of the narrative is like training. But, know, obviously it will be both.
Speaker 2:
01:28:48Alibaba chairman Joe Tsai has raised the possibility that we're in the middle of a data center construction bubble. And obviously, Amazon, Microsoft have pulled back on some data center plans.
Speaker 1:
01:29:01Altman is undeterred, still seeing compute capacity as precious resource. We need more compute, more capital. He says, we want to have we want to have access to a lot more of the machinery to make AI and run AI. And, I mean, yeah, like, the GPUs do go on fire, and there are limited resources still even with the models. I mean, obviously, there's a ton that you can do
Speaker 2:
01:29:21on complex models. Getting rate limited by Google as a paid customer.
Speaker 1:
01:29:27Yeah. It's insane. Like, it is the biggest bull case for Build More
Speaker 2:
01:29:30Yeah.
Speaker 1:
01:29:31Data centers. But I I I honestly put that less on on on their cloud offering than just some PM was like, oh, no one would wanna generate more than three videos in one day
Speaker 2:
01:29:43or whatever. Totally.
Speaker 1:
01:29:44Or like, let's just roll this out slowly. Altman is undeterred, still seeing computing capacity. The Abilene skyline is made up largely of buildings constructed in the nineteen twenties during the Texas oil boom. Among the city's major employers is a nearby air force base and cheese production plant that opened in 2022. Meanwhile, activity at the Stargate site spanning 900 acres larger than New York City's Central Park moves at the pace of a boom town.
Speaker 1:
01:30:10And I was I was talking to some real estate folks, and I was saying, like, you should probably just go to Abilene and start building, like, Walmarts and gas stations and everything because, like, it really will be a boom town. They're gonna be building this for a long time. Yes. These are gonna be somewhat human resource light, but there still will be a ton of people working there, ton of people getting paid a lot. They'll want bars and restaurants and, like, the local economy should like, it would be impossible for it not to flourish.
Speaker 1:
01:30:38Like, the the economy booms when you put in, like, a soccer stadium. Like, you're talking about
Speaker 6:
01:30:43Yeah.
Speaker 2:
01:30:43I wonder if there's if there's been any people going I mean, I'm sure the Stargate project in general has just been buying up surrounding Yeah. Land to just sort of mitigate potential risks Yeah. And future issues. But if you own, like, an acre, even just a single acre that's not connected to roads at all within this area, you could probably end up selling it for Yeah. That's smart.
Speaker 1:
01:31:07You know, millions on and make them build the data center around you. So you just Do
Speaker 2:
01:31:11you need a helicopter
Speaker 1:
01:31:12to get in? Helicopter. You just look every you have this quaint little house on the prairie.
Speaker 2:
01:31:17And then all It's own little microclimate because, like, the heat coming off.
Speaker 1:
01:31:21Have you seen that photo in Virginia where basically there was, like, this nice little house, and then AWS and Amazon just built up these massive and so you just see this nice house and you pan up, and it's just as far as the eye can see data centers. It's like
Speaker 2:
01:31:35Beautiful.
Speaker 1:
01:31:36Rough. The team behind the Abilene Data Center conceived under the codename Project Ludacris. Nice nice code name. First put shovels on the ground in June of twenty twenty four. Crusoe decided to fly in workers from all over the country because of the city's because the city of a 29,000 people didn't have a labor force large enough to support it, Locke Miller says It's project A
Speaker 2:
01:31:5729,000 is way more than I had originally kind of imagined for this
Speaker 1:
01:32:02Probably got some good high
Speaker 2:
01:32:03school football more like a city than a Yeah. People like to position Abilene as like, oh, this queen Don't
Speaker 1:
01:32:10cheat Abilene. It's projected to take slightly more than two years for the entire project to go from start to finish, although parts of the data center are slated to go online sooner. Towns like Abilene are usually on the losing end of technological change, which tends to create most jobs in the largest cities, and data centers traditionally don't employ that many people. Crusoe has promised officials that the Abilene site will deliver 357 full time jobs once construction has finished. That's not that much, actually.
Speaker 1:
01:32:39That's pretty small. I thought it'd be higher.
Speaker 2:
01:32:41For a $500,000,000,000 project.
Speaker 1:
01:32:42Well, guess it's 10,000,000,000 in this version or what do they A little bit more. 10 or 50. But yeah, that is crazy low numbers. But the AI agents
Speaker 2:
01:32:51Hate to be contributing to this. I backed a company that makes robots for data centers.
Speaker 1:
01:32:59Reducing it from three fifty. We're gonna get that number down to five. Yeah. That's the goal.
Speaker 2:
01:33:03Yeah. I mean, it's basically the idea that, like, data centers are flat. Yeah. And there's like routine maintenance that
Speaker 1:
01:33:11needs to done. It's reasonable.
Speaker 2:
01:33:12And it's like very much a controlled environment. Yeah. Yeah. Just driving a little walley style robot around makes a lot of sense.
Speaker 1:
01:33:20We're talking about like how much of a boom town is. Like, 375 jobs for now.
Speaker 2:
01:33:25On a base of a 29,000
Speaker 1:
01:33:27That's like nothing.
Speaker 2:
01:33:28Existing Nothing.
Speaker 1:
01:33:29People. I I feel like there will be more knock on effects, though. Anyway, the Apple Inc What about
Speaker 2:
01:33:34the chip there's Chipotle Yeah. Opportunities. Yeah. Those 357 people are gonna be eating a lot of double steak, guac, burrito bowls.
Speaker 1:
01:33:44Yeah. So The Abilene government is hopeful that it is the start of something bigger. The city and county agreed to extend significant tax breaks to get the deal done, and local officials saw an influx of requests in the days after Stargate was announced from housing developers, infrastructure energy infrastructure vendors would be investors and other municipal governments desperate to bring jobs to their town. It will impact the rest of the economy, our restaurants, our homebuilders, our Chipotles, with many new people coming in and taking these jobs. The city was able to accommodate Stargate's waters water needs, which are small compared to a typical server farm due to a novel cooling method that recycles most of the liquid.
Speaker 1:
01:34:19Let's hear it for the fake news that ChatGPT is destroying the ocean. It's not true. Like, they figured out how to recycle the water, of course, because water's expensive, and why would you waste it? The trade off is that the day is Yeah.
Speaker 2:
01:34:33It's not the water is not being massively contaminated, like, in oil fracking fracking.
Speaker 1:
01:34:39And so they need a ton of electricity. Data centers of this scale are unprecedented. The this was cause for concern where the memory of twenty twenty twenty one Texas blackouts, which led to the death of six people in the county, still fresh in people's minds. Much of the blame for those outages belongs to Texas's deregulated energy grid, but the flexibility that comes with the lack of regulation was part of the allure for Stargate. Crusoe went out and bought gas turbines and oversaw the construction of a natural gas plant on-site,
Speaker 2:
01:35:10which will supplement coded.
Speaker 1:
01:35:12The what the data center can get from the local utilities. Yeah. I talked to an investor who was who knows Chase and was like, he's just he has an uncanny ability to find energy, which is like, I don't know, something I wouldn't even think about in terms of like what the skills of a founder are necessary. But he's like extremely good at finding like, opportunities and pockets of energy Okay. That are being underutilized.
Speaker 2:
01:35:35So I'm technically millennial, but I was fairly close to being Gen Z Yep. By a few days. Yep. Is that, like, riszing energy? Like,
Speaker 3:
01:35:43I'm just
Speaker 2:
01:35:43trying to put it he's an energy he's an energy
Speaker 1:
01:35:47No. It's like Rizzler.
Speaker 2:
01:35:48Is that what
Speaker 1:
01:35:48you're saying? Like there
Speaker 2:
01:35:49I think there are a lot of there are a lot
Speaker 1:
01:35:51of companies out there that think kind of along the lines of, like, a single energy source. So Yeah. There is a lot of of natural gas here. Chase is very good at putting together different opportunities. There's a existing plant.
Speaker 1:
01:36:04We can build a new plant. There's wind, solar. Like, they're very energy agnostic, but how do you piece all those together to create the to meet the actual demand on an ongoing basis? Stargates to Stargates' critics, the idea that the project's backers could maintain this pace and scale across the country is reason to think they're living in a fantasy. Amade, cocreator of the scaling laws, publicly questioned Stargates' seriousness, calling it chaotic.
Speaker 1:
01:36:29Musk, breaking with Trump, called it fake. Altman's retort, he says all sorts of crazy stuff. Salesforce, CEO Mark Benioff said in a post on X in April that Stargate signaled an end to the honeymoon between OpenAI and Microsoft. The project does reflect a shift in the relationship between the two companies. They revised their cloud contract in January to allow OpenAI to use other vendors such as Oracle as long as Microsoft has still has right of first refusal.
Speaker 1:
01:36:54Microsoft doesn't intend to invest in Stargate but was listed by OpenAI as a technology partner in the project. And this was interesting because they
Speaker 2:
01:37:02Can I just put your logo on the deck, please? Can I please just put your logo on the deck?
Speaker 1:
01:37:09This amazing thing. Microsoft is providing exchange.
Speaker 2:
01:37:11There's this amazing there's this amazing line from this guy, Aaron, a buddy of mine.
Speaker 1:
01:37:17We'll be using Microsoft Excel on-site. They're a technology partner.
Speaker 2:
01:37:20Yeah. That's it. Yeah, he once said He once said,
Speaker 1:
01:37:23quote, well, I'm good for my 80,000,000,000 He's just like, I'm good for my $80,000,000,000 generically. CapEx it'll happen somewhere. It's not necessarily an investment starting.
Speaker 2:
01:37:31I'm going butcher the exact quote, but Aaron Frank has an iconic post at one point, or maybe he just said this to me in person. He just said, some people just want to see my name in their, some people just want my name in their deck. Because there was like this fintech boom and people would just come to him and be like, please can I give you 50 bips to just like put your name? Because like that, like at some point What did
Speaker 1:
01:37:52he do? What's his name?
Speaker 2:
01:37:52He created the card that became the Apple Oh, okay. What what was it called again? You don't even see that. The Apple push Okay. No.
Speaker 2:
01:38:02Apple card. Remember Was it called
Speaker 1:
01:38:04the Apple card?
Speaker 2:
01:38:04I think it was called the Apple card. But his his company, like, became that. Yeah. Apple Card. You don't hear much about the Apple Card.
Speaker 1:
01:38:11They had a deal with Goldman and then they kind of, like, fell off and maybe they're not doing it anymore. Did people get those? I never had one. Was it good? Did they have, like, cash back on stuff?
Speaker 2:
01:38:19It pretty good. Okay. Anyway. Unlimited daily cash back.
Speaker 1:
01:38:23I'm not really the credit card points maxer or into credit
Speaker 2:
01:38:27Never been big into that world.
Speaker 1:
01:38:28Never. Two management consulting coded. It's like every every guy I know who works like McKinsey or Bain or BCG is like, oh, I'm spreadsheet of points. I'm just like, I don't care. Just tell me which card I'll get and I'll use that for a decade and they'll they'll squeeze me for annual fee probably.
Speaker 1:
01:38:44And I'm probably, like, way underwater on it because I'm not points maxing.
Speaker 2:
01:38:48Yep.
Speaker 1:
01:38:48Anyway, if things go as planned, Abilene could serve as a model for the next of Stargate's developments. The day after Altman first visited the Abilene site in early May, he testified before congress asking to for help to fast track data center permitting on future locations. The the first site was incredible. We need a lot more of that. Crusoe is evaluating another potential spot in Amarillo, Texas, which it hopes could be part of Stargate according to a person with knowledge of deliberations who asked not to be named.
Speaker 1:
01:39:14OpenAI has said it's also looking in several states, including Oregon, Pennsylvania, and Wisconsin. And while Stargate might rent data centers already built being built elsewhere, meanwhile, OpenAI and Oracle are taking the spirit of Stargate International with an AI data center under development in Abu Dhabi, which will not be part of Stargate LLC, but will count OpenAI as a customer. It's, simple. If all that wasn't enough, Stargate could even expand to include semiconductor production according to Altman, perhaps as soon as next year. I think of Stargate as the AI factory.
Speaker 1:
01:39:47If you don't have to be involved here, maybe we wouldn't. But if we could just magically spin up all the compute that we needed in the sky, but at this kind of scale, he can't do that. And so there's another interesting angle here, which is, the idea of building an AI data center in space. We're having a couple folks to come on the show maybe next week to talk about that. There's a company that's thinking about doing it.
Speaker 1:
01:40:10There's some investors that are looking into it.
Speaker 2:
01:40:12It's Sounds silly.
Speaker 1:
01:40:13Sounds extremely buzzwordy and sci fi. It's like hard tech space and AI and data centers. But think about it. You get you get energy from the sun from solar panels basically for free. And then you also get cooling because you're in the vacuum of space and it's cold for free.
Speaker 1:
01:40:30And so you don't need probably water cooling, and you don't need as much energy. And so the economics might work out potentially in GB.
Speaker 2:
01:40:38Land.
Speaker 1:
01:40:39Pretty yeah. You don't need land. And so you've cut out a bunch of costs and then added Starship or or Falcon nine launch costs, which are significant John. But maybe small.
Speaker 2:
01:40:49I cannot wait for the day where a satellite is gibbling for me. Just knowing that I can create the most silly picture in my mind Yep. And then send it up to space to get made and then have it sent down.
Speaker 1:
01:41:04And so
Speaker 2:
01:41:05Just send it back whenever you get around to it. Yep. Could be tomorrow.
Speaker 1:
01:41:08And then it says, you've run out of requests. Don't
Speaker 2:
01:41:12Too much Gibley.
Speaker 1:
01:41:13Do anymore.
Speaker 2:
01:41:13When's the last time you saw Gibley?
Speaker 1:
01:41:15It's been a while. I have been using I've been using images in chat GP chat GPT a lot, but on a a lot more, like, practical sense, just trying to visualize different things. I like their
Speaker 2:
01:41:29library I told you I've using I've been using chat GPT image images to get my three year old to eat dinner.
Speaker 1:
01:41:39Yeah, said that was working really So it's basically
Speaker 2:
01:41:41bite by bite I will generate a new, if you take another bite of chicken and chew it well, I'll generate another picture of me as a dinosaur.
Speaker 1:
01:41:50My new my new go to Ghibli, instead of asking, turn this into a Studio Ghibli, I just say, turn these turn the image into bodybuilders. And I've had been having a lot of luck with that. I I I sent one to the chat. We'll try and pull it up. But
Speaker 2:
01:42:04Get this pulled up. It's
Speaker 1:
01:42:06It's great.
Speaker 2:
01:42:08Oh, but that's that's the original picture. Yeah.
Speaker 1:
01:42:11That's the original picture. Yeah. This is the So we'll
Speaker 2:
01:42:12pull up the original picture first of the OpenAI team. Team. There they are.
Speaker 1:
01:42:16Yeah. Okay. And then can you can
Speaker 2:
01:42:19you make them look like Yeah.
Speaker 1:
01:42:22For sure. Yeah. Yeah. I enjoy that. Also just making, yeah, just a lot of Cadillac Escalades with GT3 liveries and a lot of, TBPN merch ideas.
Speaker 1:
01:42:37A lot of stringers, a lot of suits with with ads on it. Speaking of which, we should do some ads. Go to Vanta.com. Automate compliance, manage risk, prove trust continuously. Vanta's trust management platform takes some annual work out of your security and compliance process.
Speaker 2:
01:42:51You're doing anything important, you probably should be on Vanta.
Speaker 1:
01:42:54For sure.
Speaker 2:
01:42:55You heard it here first. Heard it Go to Vanta.com.
Speaker 1:
01:42:57You should also get a numeral sales tax on autopilot. Spend less than five minutes per month on sales tax compliance. Benchmark series a. Benchmark series a. Anyway, do we have time to do wait.
Speaker 1:
01:43:10Well, we only have fifteen minutes until our next guest.
Speaker 2:
01:43:12Do a little timeline?
Speaker 1:
01:43:12We should do a little timeline. It'd be good. We got Austin Allred coming in. We're gonna ask him about AI coding in the era of agents. We can cover Dario maybe tomorrow.
Speaker 1:
01:43:22I also wanna go through oh, we didn't get a chance to dig through, Craig Federighi and the Apple AI piece in Bloomberg, but there are some really hilarious, points in here. One is that, apparently, when Steve Jobs was trying to acquire Siri, he called the CEO and said, I'd like to buy the company. I think this is the future of computing. I think voice interfaces, artificial intelligence, this is what Apple needs. We wanna buy your company, bring them in house.
Speaker 1:
01:43:56The CEO of Siri said, no. I don't want to be part of Apple. I'm good. And Steve Jobs proceeded to call him every single day for twenty four days straight before he got the deal done.
Speaker 2:
01:44:06Insane.
Speaker 1:
01:44:07Absolutely insane. You don't hear about that a lot.
Speaker 2:
01:44:10Yeah. You you have you get this idea in your head of of somebody that is a demigod figure and you think that they don't have to be cringe to get things done. Yep. And turns out sometimes you gotta cringe max
Speaker 3:
01:44:26Yeah.
Speaker 2:
01:44:26And and do whatever it takes and sometimes that's calling somebody every single day.
Speaker 1:
01:44:30It must just be so funny to pick up the
Speaker 2:
01:44:33phone. Imagine you're like
Speaker 1:
01:44:34The twenty fourth
Speaker 2:
01:44:34mile. Imagine you're like, yeah walking your dog or you know. It's like Steve Jobs calling again. Oh, he's leaving a voicemail.
Speaker 1:
01:44:42Oh, hey, Steve.
Speaker 2:
01:44:43Hey, bud. How you doing?
Speaker 1:
01:44:44Yep. Still not interested. Still building my company. Still grinding.
Speaker 2:
01:44:49Steve Jobs Steve Jobs get sort of total privileges to call people bud.
Speaker 1:
01:44:56Oh, yeah. Totally.
Speaker 2:
01:44:57One of the few
Speaker 1:
01:44:58When you're at the top
Speaker 4:
01:44:58of the
Speaker 2:
01:44:59few that earned it.
Speaker 1:
01:45:00When you're the greatest entrepreneur of all time.
Speaker 2:
01:45:01So if you're not Steve Jobs, don't use the
Speaker 1:
01:45:03that from your vocabulary. Let's go to some timelines. Zach Kukhoff's talking about, oh my god, we're really gonna speed run 2,008 with collateralized both Yes.
Speaker 2:
01:45:12Florida's losses have widened as more consumers fail to repay loans. Unfortunate. Learning, you know, basically probably speed running Mhmm. Risk management that credit card companies have done for a really long time.
Speaker 1:
01:45:30I wonder what's actually going on here because the whole, like, yes, you can buy now, pay later on your burrito. That's silly. But that's probably not the vast majority of their underwriting. Right? Like, that's the meme, but that's not actually what's driving buy now, pay later activity.
Speaker 1:
01:45:45And I wonder if in the lead up to IPO, they they loosened underwriting restrictions to try and ramp volume. And because it seems like Klarna have they gotten out? No. Right? They they're they're they're not public yet.
Speaker 1:
01:45:58Right? They have not successfully IPO ed. And so I imagine that in the lead up to the IPO, they're trying to do a bunch of things. There's the whole that whole new cycle around, oh, we're not gonna hire anyone. We're gonna use AI for everything.
Speaker 1:
01:46:09Obviously, that's sending a signal to the market that, hey. We're gonna be an ultra efficient business. The margins are gonna dramatically improve. We are taking AI super seriously at this company. And so, you know, our OpEx should be really low over the long term.
Speaker 1:
01:46:23You can underwrite the the IPO against a really low SG and A cost. Right? Yeah. And then also on the revenue side, they're probably say they're probably trying to do everything they can. Maybe they went too far, and now they're generating losses, which is obviously not Yes.
Speaker 2:
01:46:40Issue is they doubled losses. So their net loss for the first three months of 2025 was around $100,000,000 A year ago for the same period, was $47,000,000
Speaker 1:
01:46:50Is this from like the S1 or something? Like, why is this data public?
Speaker 2:
01:46:56I think they're they're trying to get out, and so I imagine they need to do some type of reporting. Revenue increased 13% year over year to 700,000,000 for the quarter. And again, this is a company that in 2021 was valued at $45,000,000,000. Most recent private mark was around 15. So unclear what they'll do.
Speaker 2:
01:47:22They put their IPO plans on a hold last month along with StubHub, and again, they had been on this marketing tear, right? Remember the CEO came out? Yeah, yeah, yeah. And he was like, we're using AI for We're letting everyone go. And then he says, actually, no, we're not doing It's not good enough yet.
Speaker 1:
01:47:41I don't like when the IPO window is closed. I like an open window. Yeah. I like companies going out every day.
Speaker 2:
01:47:47I like You punched a hole in the wall at the gym when you heard I remember I When the IPO window closed. When it closed.
Speaker 1:
01:47:54When it closed. Yeah.
Speaker 2:
01:47:55I was like, John, why is your hand two feet into or sorry. Why why is your fist two feet into the wall, John? You were trying to
Speaker 3:
01:48:02Yeah.
Speaker 2:
01:48:03I was just get
Speaker 3:
01:48:03it out.
Speaker 1:
01:48:03You're trying to Too frustrated.
Speaker 2:
01:48:06Pissed off.
Speaker 1:
01:48:07Well, if you're trying to track all these IPOs, trying to get it on the action, head over to public.com, investing for those who take it seriously. They got multi asset investing, industry leading yields, and they're trusted by millions. Also, Jordy, how'd you sleep last night? I put up some good numbers. I'm climbing up the ranks.
Speaker 1:
01:48:23I'm getting back in
Speaker 2:
01:48:24the game. I might
Speaker 1:
01:48:25have beaten you
Speaker 2:
01:48:26back to
Speaker 1:
01:48:27back days. Let's see. How'd you do? What's your number? What's mine?
Speaker 2:
01:48:32No. You go first.
Speaker 1:
01:48:33Okay. Well, one second. Get a pod five ultra. They got a five year warranty, a thirty night risk free
Speaker 2:
01:48:41trial at 80, John. Free return. I'm sure you beat me.
Speaker 1:
01:48:45Oh, got a 94.
Speaker 2:
01:48:47Smoked. Smoked. Get out
Speaker 1:
01:48:49of here.
Speaker 2:
01:48:49Get out of
Speaker 1:
01:48:50try. 96, actually. 96.
Speaker 2:
01:48:5290 6. Really deep. Boom. 90 I'm proud of you.
Speaker 1:
01:48:57Yeah. Still not good on the consistency. Going to bed at all random times. Waking up pretty consistently. Five forty five.
Speaker 1:
01:49:04Anyway.
Speaker 2:
01:49:05Alright. Going We kind of covered this already. This from the lion does not concern himself with SOC two compliance. That's because the lion uses Vanta. Right?
Speaker 2:
01:49:16Exactly. So I don't need to be concerned. Maybe we need post.
Speaker 5:
01:49:19Yeah. This is
Speaker 2:
01:49:20an ad. Hey. This is an ad. For sure. Andy, you gotta be disclosing.
Speaker 1:
01:49:24Yeah. You have to do hashtag ad
Speaker 2:
01:49:26or Maybe he just loves Vanta so much.
Speaker 1:
01:49:27It's possible. It could just be UGC. Yeah. Yeah. Anyway, obviously, don't concern yourself with SOC two.
Speaker 1:
01:49:33Be a lion and get on Vanta.
Speaker 2:
01:49:36Art over at Brex announced a partnership with Zip, a big procurement platform. Apparently, Zip is taking a step back from the corporate card market, and so this partnership allows them
Speaker 1:
01:49:49to each Oh, interesting. Okay. That that makes a lot more sense. So Zip had a corporate card Yeah. And now they're just partnering
Speaker 2:
01:49:54Roll it back.
Speaker 4:
01:49:54With with Brax
Speaker 1:
01:49:55for this.
Speaker 2:
01:49:56Brax had a procurement product
Speaker 3:
01:49:57Yeah.
Speaker 2:
01:49:58Which they rolled out.
Speaker 3:
01:49:58And that
Speaker 1:
01:49:58kind of happened too with with Stripe had a corporate card for a little bit and then stopped that. Right? Isn't that what you
Speaker 2:
01:50:03Everybody was like, wait. Corporate cards, good business. Yeah. We should do corporate cards. Yep.
Speaker 2:
01:50:08Turns out hard to hard to do.
Speaker 1:
01:50:10Yeah. Well, there's always a question about, like, where does the corporate card sit? Because Stripe does not sit in the same place as, like, Ramp in terms of, like, the CFO suite. Like, it's a it's more of a, like, almost a developer tool.
Speaker 2:
01:50:21It's less their initial wedge.
Speaker 1:
01:50:23But Yeah. Yeah. But it's it's less about, like, an accounting product. It's more about like the payments and engineering product. Although obviously it's very tied, but I don't think Stripe's ever gone into travel or, you know, bill pay.
Speaker 1:
01:50:39Like they haven't focused on that as much. Anyway, Art says, this is two YC companies with cultures of shipping fast and collaboration creating something truly special.
Speaker 2:
01:50:48We love to see YC companies. Obviously, the most We love it. The recent collaboration between Deal and Ripley. Oh my god. Also YC companies Yes.
Speaker 2:
01:50:56Yes. Hasn't is smooth. Right? More sort
Speaker 1:
01:50:59of to us.
Speaker 5:
01:50:59Yeah. A
Speaker 1:
01:51:00little tumultuous. Necessarily call it collaboration.
Speaker 2:
01:51:03Well, they were partnered in some ways because they were both
Speaker 1:
01:51:05It was the employee. Yeah. They were paying the same employee. Yeah. Anyway
Speaker 2:
01:51:11Back in 2021,
Speaker 1:
01:51:13Art approached Zip's CEO because I saw Zip doing something remarkable in the enterprise segment, a market Brex was determined to win. At the time, the CEO of Zip pushed back saying Brex was too focused on startups. What would he get from this? Fast forward to March 2024. Brex has built their base of enterprises, and many were demanding our products to work seamlessly together.
Speaker 1:
01:51:32Both companies had also retrenched to focus on core strength. Zip stepped back from card. We stepped back from enterprise procurement. This is a classic competitors turned cocreator story. Zip brings world class procurement orchestration.
Speaker 1:
01:51:44Brex brings global card capabilities and spend management across 50 countries. So congratulations to Art and Brex. Art,
Speaker 2:
01:51:52fellow LA guy.
Speaker 1:
01:51:55Hey. And I have some advice for Brax. Why don't you run a billboard to promote this on Adquick? Yeah. Get some I mean, Brex actually has a ton of billboards.
Speaker 1:
01:52:06Right?
Speaker 2:
01:52:06They I mean, they they ran
Speaker 1:
01:52:07a ton the campaign in many ways. They did invent the billboard. They should get on ad quick.
Speaker 2:
01:52:11Economy on their backs They did. In 2020, '20 '19. Right? Yeah. It was like, it was hard to get a billboard because they were on all of them.
Speaker 1:
01:52:18So head over to adquick.com. Art, out of home advertising made easy and measurable. Say goodbye to the headaches of out of home advertising. Only ad Quick combines technology out of home expertise and data to enable efficient seamless ad buying across the globe. Double kill.
Speaker 2:
01:52:33Great. Great transition, John. We got a post here from TJ Parker who will be on the show Thursday. Again, he's coming back on. He says, one thing I'll never understand about healthcare startups is the instinct to take a strategic route rather than an administrative tactical approach.
Speaker 2:
01:52:49You don't need a top to top meeting to get in network with a payer. Just fill out the paperwork. You don't need a strategic relationship with Quest LabCorp to integrate scheduling or get competitive pricing. Just work with an existing vendor. If things go well, can elevate to strategic relationship over time, but you'll never get off the starting line with the strategic approach.
Speaker 2:
01:53:10Will has a has a funny reply It's very funny when people tell me they're struggling with getting in to in touch with payers. It's like, have you tried going in the front door? Timeless advice, timeless wisdom.
Speaker 1:
01:53:23I wonder what's going on here. Is this because there's a lot of, like, tech people who think I'm gonna build tech for health care, and then they're just completely unfamiliar
Speaker 2:
01:53:31with all about partnerships versus
Speaker 1:
01:53:33just Or they're unfamiliar with this market structure because TJ has been I mean, he was a pharmacist before. Right? Like, he really understands the industry and has continued to understand the industry even post exit. Whereas I think a lot of people are like, I build software. I know that health care is a problem, so I'm going to build health care software, But they don't understand, like, the structure of the market at all or how the deals get done, and so they gotta learn stuff from from TJ's posts.
Speaker 1:
01:53:58Anyway.
Speaker 2:
01:54:00We got a post here from Andrew Reed. In the news, Authentic Brands buys Dockers from Levi Strauss, a little mix up in the pants market. A little switch up and Andrew says, Docker, the containers overlapping with Dockers, the pants, both making hundreds of millions selling to system admins. Yeah. You know, Andrew Yeah.
Speaker 2:
01:54:25It's really beautiful.
Speaker 1:
01:54:26He's a great investor, but he puts his pants
Speaker 2:
01:54:28on one leg at a time like anyone else. Yep.
Speaker 1:
01:54:31Let's get him some Dockers. Let's see.
Speaker 2:
01:54:32Get him some Dockers.
Speaker 1:
01:54:33I somehow think he's
Speaker 2:
01:54:34We should get him
Speaker 1:
01:54:35too stylish for that.
Speaker 2:
01:54:36Yeah. I can't see him wearing Dockers, but we should get him a TBPN tie
Speaker 1:
01:54:40Yeah. Tie would be he'd
Speaker 2:
01:54:42been working on. Yeah. With ads on
Speaker 1:
01:54:43that report. Last time he came on the show, he's he's wearing a actually really nice Figma sweatshirt, but didn't have a collar. So, you know, docked some points from that.
Speaker 2:
01:54:53Yep. Docked. Docked.
Speaker 1:
01:54:57Well, you know, we should also tell you about wander.
Speaker 2:
01:55:01Find your happy place. Find your happy place.
Speaker 1:
01:55:04Book a wander with inspiring views, hotel graded minis, dreamy beds, top tier cleaning, and twenty four seven concierge services, vacation home, but better folks.
Speaker 2:
01:55:11John Andrew, founder Wander was teasing
Speaker 1:
01:55:13Mhmm.
Speaker 2:
01:55:14How excited he is about some big news. And I couldn't possibly guess what the news is, but we're gonna have him on the show
Speaker 1:
01:55:20talk to a friend of the show. Says OpenAI tried to partner with Google to use its search API to part to power real time results in ChatGPT's search offering. Google said no, citing too many complexities, and this is from, Michelle Fradin or Fradin. Interestingly, she was at Sequoia. She was on the FTX deal and then went over to OpenAI right before the Sam Altman firing.
Speaker 1:
01:55:43And so it was just, like, chaos for a while, but it seems like she's settled in over at OpenAI and is doing well. But getting some pushback from the Google folks. She says, we hope you're doing well. We wanted to follow-up on our discussions over the past few weeks regarding using Google Search API to help power ChatGPT's SearchGPT prototype and search functionality in ChatGPT. As mentioned, we are currently testing a prototype, SearchGPT, and with and to learn more about how users and publishers use AI chat experiences coupled with real time information and search like features.
Speaker 1:
01:56:13On July 25, the day of our public announcement, we reached out to Google about using its search API. We believe having multiple partners, in particular Google's API, would would enable us to provide a better product to users to not just destroy you. We also understand Google publicly offers its custom search JSON API to developers looking to incorporate Google search results into their products, providing additional precedent for us to work together. So basically asking, hey. You have this service that you offer to a lot of people.
Speaker 1:
01:56:41Like, can you offer it to us? And they're like, absolutely not.
Speaker 2:
01:56:44Hey. Do you mind letting the fox into the henhouse?
Speaker 3:
01:56:49Jenna, summarize
Speaker 1:
01:56:50this email.
Speaker 2:
01:56:51Fox is sending the email to a chicken in the henhouse. Hey. I'd love
Speaker 1:
01:56:57to come in. I'd love
Speaker 2:
01:56:58to come in and check out the house. I thought I might ask. It seems like a great house. I think my I think the other foxes in the fox house would like it.
Speaker 1:
01:57:09They like it.
Speaker 2:
01:57:15Google's like, the the the chickens over in the hen house are like, I think it'd be kinda complicated. Yeah. As Google said We're
Speaker 1:
01:57:23gonna decline this because we believe that you are a a wolf in sheep's clothing. Very hilarious. Well, yeah, cheers to Sundar for not letting the fox in the hen house. And he lives to fight another day. Built his own Gemini.
Speaker 1:
01:57:39Built his own apps. And we're excited to talk to some folks Frankly, built different. Google. Built different. We're we're excited to talk to some folks over Google about, you know, with the the the the the hen house protection strategy Yeah.
Speaker 1:
01:57:50And the Fox Defense Defense System.
Speaker 2:
01:57:52The Fox Defense Network. The Fox Defense Engine.
Speaker 1:
01:57:57Should we talk about Coinbase? Ugh. This is a rough one. Mark Alarrington is very upset with the Coinbase news. He says, I'm a longtime investor and champion of Coinbase.
Speaker 1:
01:58:06Something that has to be said, though, this hack, which includes home addresses and account balances, will lead to people dying. It's it probably already has. The human cost denominated in misery is much larger than the $400,000,000 or so they think it will actually cost the company to reimburse people. The consequences to companies who do not adequately protect their customer information should include, without limitation, prison time for executives. Very disappointing Coinbase right now.
Speaker 1:
01:58:28Using the cheapest option for customer service has its price and Coinbase's customers will bear that cost. And so
Speaker 2:
01:58:34Yeah. So for context Yeah. If anybody was living under a data center
Speaker 3:
01:58:38Yeah.
Speaker 2:
01:58:39Coinbase effectively was offshoring their CX function. Mhmm. Certain CX reps had access to consumer data
Speaker 1:
01:58:50Account balances.
Speaker 2:
01:58:50Including home addresses and account balances, which they then effectively sold or were bribed into passing to nefarious groups, who then were threatening Coinbase saying they were gonna leak it. Coinbase came out and said, you know, kick rocks. We're gonna pay basically a bounty that leads to the arrest of these people. Yep. The issue obviously with home addresses and account balances being online is that bad actors could just find a home address.
Speaker 2:
01:59:19With somebody with a high Bitcoin balance, go there and say, with a, you know, the threat of physical violence and say, send me your Bitcoin right now, or even worse, abducted. And so Michael is basically saying that there's gonna be a, you know, real, real consequences here. Coinbase came out and said, anybody that sort of falls to various social engineering hacks due to the, you know, they're basically gonna reimburse them. Apparently they expect to spend quite a lot of money, hundreds of millions of dollars to reimburse those people. But Michael is saying that the the true cost is much higher.
Speaker 2:
01:59:56And apparently, there had been just like a bunch of other issues here. I mean, who knows what's actually going on. I'm sure that
Speaker 1:
02:00:04I do wonder, like, how much of a cost center is customer service for Coinbase? Like, seems like it's a big company, very profitable, has done very well. Like, if they doubled the cost of the the, like, the the expense, like, would it get better? Is is customer service really like a like a, something that we're spending more money on is a lever, or is this something that's, like, a little bit more intractable? The other interesting thing is, like, I do wonder like, the Internet is pretty locked down, I feel like.
Speaker 1:
02:00:36Like, it it it is like, yes, there are addresses that can be sold in the dark web, but, like, it's pretty hard to just put up something that is illegal on the internet. Like all the major platforms take it down, Google shadow bans it, the links get banned, the browsers can be it's
Speaker 2:
02:00:54not that crazy Yeah. It's fairly easy for this information to just be like a file Yes. An Excel file
Speaker 1:
02:01:00Yes. But at the same time
Speaker 2:
02:01:01criminals can transact and sell multiple times.
Speaker 1:
02:01:04At the same time, like, let's say that I'm like a you know, the type of criminal that does that does just show up to a house and put a gun in someone's Well,
Speaker 2:
02:01:12real the immediate risk is social engineering. It's somebody calling you from a number that's spoofing Coinbase and saying, hey. Yes. I noticed some activity. Yes.
Speaker 2:
02:01:20I need you to verify this. Give me this code. So that's the immediate risk. Second order effect is that a criminal could just show up at somebody's house and demand Yeah.
Speaker 1:
02:01:27Yeah. Yeah. Yeah. So so the type of criminal that just shows up at people's houses, like, how are they actually gonna get this information? Because they're not just gonna Google it, it's not just gonna show up there.
Speaker 1:
02:01:37They're gonna have to find it somewhere on, like, through some sort of hacker network. Are they paying for this? Like, it feels like this information can be somewhat controlled. Like, credit card numbers leak all the time, and and, like, the the global cybersecurity industry is pretty good at making these not just proliferate to, like, script kiddies and, like, random criminals. Like, yes, there are organizations that try and, like, programmatically, like, run up a ton of charges and just, like, spam the network.
Speaker 1:
02:02:08But in terms of, like, these one on one dangerous interactions, like, I'm not so sure that it's going to happen, like, en masse. Obviously, it'd be terrible if it didn't. It's a very big deal, and it should be taken very seriously. I do I do wonder if there's a way to to kind of, like, like, not allow this information to proliferate. Ironically, like, if what if it goes in the blockchain and it's just available?
Speaker 1:
02:02:33It's like it's a very naughty issue with, like, you know, censorship and and things. But Balaji had a good response here to Arrington. I don't have it clipped, but we'll have to talk to him about, like, the future of KYC. His argument was that, like, part of the problem is that Coinbase is required to keep all this information when when they they might not actually need to if the government didn't require it. And so it's this double edged sword of the more information that you keep on someone, the more information that Totally.
Speaker 1:
02:03:01Can be leaked. Anyway, we'll dive into that more next week. For now, we have Austin Allred, coming in to the studio. How are doing, Austin? Good to hear.
Speaker 7:
02:03:11Hey. Good. How are guys doing?
Speaker 2:
02:03:13What? Going on? How are you?
Speaker 3:
02:03:15I'm good. Yeah.
Speaker 7:
02:03:16Hanging out.
Speaker 1:
02:03:17Well, yeah. I wanted to
Speaker 2:
02:03:18have you
Speaker 1:
02:03:18on the show for a few reasons. Obviously, there's a lot of stuff happening with
Speaker 2:
02:03:23Yeah. What's this agents. What's what's this whole AI thing?
Speaker 1:
02:03:26Yeah. What's this whole AI thing?
Speaker 7:
02:03:28Whole AI thing. Haven't heard about it. Yeah. I mean, the eye level is Maybe
Speaker 3:
02:03:33you start
Speaker 1:
02:03:33with, like, a introduction on yourself and and and what what you're up to now, what you've done in the past, and then we can kind of go into, the structure of, of AI in the workplace, how people are learning to use AI, and then kind of some of the disruption that's potentially happening with AI tools actually replacing jobs.
Speaker 7:
02:03:52Yeah. For sure. So a little bit of background, cofounder of BloomTech, which used to be known as Lambda School before a trademark lawsuit. Yep. It's technically still the same company.
Speaker 7:
02:04:03But about eighteen months ago, we started talking to people about this newfangled AI thing and, you know, if it had any impact within engineering teams. And, frankly, I was pretty skeptical in the early days. Mhmm. But we sent out a research team. They looked at what everybody was doing.
Speaker 7:
02:04:19And at the time, it's not quite that way anymore, but there were a handful of people who had, you know, sat in the basement playing with LLMs, seeing if they could make them write real code for a couple of years. And when we saw that, we were like, oh, wow. This is actually working. It's not mainstream at all yet, and at the time, even less so. And then working with a couple of those companies that we were so we started training engineers to, you know, use AI really well.
Speaker 7:
02:04:45And it's one of those things where there are no best practices. Everybody's learning more every day. The game completely changes every day, let alone every week. And then one of the companies we are working with brought us in to do a, you know, fully intensive hundred hour a week, find all the people with ninety eighth percentile IQ and above, fly them into Austin, train them over the course of ten weeks to be expert at using AI, and kind of staying on that that cutting edge, riding that wave up, and then they hire them on the other side and and pay us to do that. Now we're expanding that to more companies, but I basically spent the past several months holed up in a little office with a bunch of sweaty people trying to figure out how to max out AI and figure out how to stay on the the cutting edge of using AI to build software.
Speaker 1:
02:05:34Is the shape of that more, like, PM who's now able to write code or instantiate their ideas in code, or is it software engineer who understands some basic programming that can then write more functional code or just be more performant? Like, which which angle? Is it both, or is one is one narrative driving more of, like, AI adoption?
Speaker 7:
02:05:58Yeah. I'd say, it's more the latter. So the more experience you have as an engineer, the more it sucks to start using AI because, you know, you're going from here to here as far as code writing ability goes. Yeah. So in the early days of Gauntlet, we forced everybody you know?
Speaker 7:
02:06:16And the more senior you are, the more you hate it. We say you can't write code manually. We put software on everybody's computer that, you know, watches them, and AI has to do all of the code writing for you. And everybody thinks that that's the dumbest thing they've ever heard, and they fight against you for a week, week and a half. And then, you know, the more senior you are, the longer it takes for you to actually get to parity.
Speaker 7:
02:06:40But it's you you'll never go back once you get there. It will it has fundamentally changed the software industry forever in ways that people don't fully appreciate yet. Entire companies are going companies are gonna have to rethink the way they do everything.
Speaker 3:
02:06:58Mhmm.
Speaker 7:
02:06:59And we're only seeing the very, very, very early stages of that.
Speaker 2:
02:07:03Do you guys have your own kind of messaging internally with the students around the framing of like vibe coding? Because it maybe is it's like this cool viral phrase people Yeah. It's kind of different when wander Carpathian does it. It's it's it's also different if you're doing it in this hyper intentional way Yeah. Trying to effectively get to the same quality and consistency as regular software engineering, but just doing it in a super AI native way.
Speaker 7:
02:07:33Yeah. I feel like that's muddied the waters quite a bit. I mean, the when I say vibe coding, most people imagine somebody who doesn't understand software kind of blindly trying to one shot applications
Speaker 3:
02:07:45Yeah.
Speaker 7:
02:07:46Which it's incredible that that works at all. But when we think of, you know, whether you call it vibe coding or some people call started calling it super building internally. I don't know if that ever, made it out. But using AI to write performant enterprise grade bulletproof software, there's not a great distinction for that out in the market, but we do view it very, very differently. There's a time and a place for both.
Speaker 7:
02:08:10You know? If you're writing your own personal software or little internal tools, like, yeah, just blindly telling an LLM to do something might work. But most of what our engineers are doing would work in, you know, very enterprise, very legacy, very big, large scale applications. You know, security is taken care of. The the formatting is done correctly.
Speaker 7:
02:08:32It's it's scalable and secure and all the things that software needs to be.
Speaker 2:
02:08:36What are you seeing the most success with in terms of tools? There's so many different options every week. There's a new tool, right? It's hot. You know, maybe they were using Devon at some point and then they're using Claude and then they're using now Codex.
Speaker 2:
02:08:54What what what's your kind of how how are people prioritizing? Are they using things like Replit? You know, what does that actually what does the stack look like?
Speaker 7:
02:09:03Yeah. It it's not an exaggeration to say that it changes every week in a very fundamental way. So, you know, I remember when Claude three seven came out. Before Claude three seven came out, pretty much everybody was using Claude three five as their daily driver. And I feel like Claude three seven was the first kind of breaking point where that became no longer true anymore.
Speaker 7:
02:09:27So before, Claude had basically a monopoly. If you were to walk around the gauntlet offices, and ask everybody what they're using, 95% was Claude three five. With three seven, it worked better for some people's workflows and worse for other people's workflows. Grok is gaining ground. It it doesn't you know, most people don't have API access to it yet, so that's a, you know, you have to use repo prompt for something to get it into your IDE.
Speaker 7:
02:09:56So that's a, you know, separate thing. I would say, on average, if for people who are working on really big, really enterprise applications, Cloud three five still seems to be winning out even over Cloud three seven. And Gemini, I think, kind of changed the game. When was that? Was that two weeks ago or a year ago?
Speaker 7:
02:10:14I kinda lose track at this point. But it has a much broader context window. So if you have a small code base, you can get most of the code base inside the context window as opposed to Cloud three five. Cloud three five is has proven to be better for more surgical stuff. Cloud three seven is like Cloud three five, but it kind of runs away and tries to do a lot.
Speaker 7:
02:10:37So some people like that. Some people don't. Every engineer ends up with their very ordinate, well orchestrated workflow at Vauntlet, and they, you know, they do things their own way, whether it's, you know, hey. I build all the front end stuff really, really well and make sure that's all working, and then I'd try to build a back end behind that, or I diagram everything and plan everything out with a model like o three, and then I'm creating a checklist and pulling pieces off
Speaker 2:
02:11:01the checklist.
Speaker 7:
02:11:02Every everybody has slightly different workflows, but, it's
Speaker 5:
02:11:07So what are what are
Speaker 7:
02:11:08you seeing on the Twitter?
Speaker 2:
02:11:09What are what are you seeing on the other side on the on the on the hiring side? Are companies expressing preferences already to you to some degree around, hey, you know, this is the stack we're using internally. We want people to kind of be ramped already on on this set of tools, or is it more kind of, you know, bring your own, toolkit?
Speaker 7:
02:11:31Yeah. So there's there's, there's spectrum, of course. On one side, I would say the companies that I I call them the companies that don't really get it yet Mhmm. They're like, okay. Give me somebody who has five years of experience with TypeScript and they understand a little bit of AI and we'll drop them into our traditional engineering org.
Speaker 7:
02:11:53The companies that are on the other side of that spectrum are more actually, this what was this entire team can now be one person, and what language we use matters a whole lot less than how good they are at utilizing AI. Because anything that you don't know AI is better at writing code academically than any engineer you're going to talk to.
Speaker 3:
02:12:15Mhmm.
Speaker 7:
02:12:16Knowing how to get it to write the right code at the right time in the right place is where all of the magic happens. So on the other end of that spectrum, there are companies who are I mean, the average company that we bring into Gauntlet and we show them what students are doing, they walk away saying, oh my gosh. I need to rethink our hiring. I need to rethink our entire strategy. Our road map needs to change.
Speaker 7:
02:12:37It is a fundamentally different world when you're utilizing AI in the correct way. And and then, I guess, even further on the other end of the spectrum, there are a lot of companies who tried it once and wholesale rejected it and aren't going to really use it. Or if an engineer does it at all, it's on their own time and against the will of the manager. There's more of that than people would anticipate if you're spending all day on x like I am. But but, yeah, there's a pretty broad spectrum.
Speaker 7:
02:13:08And I go back and forth with, frankly, how much time I'm going to spend trying to convince people to do it all the right way or to experiment with new ways of building companies versus just, okay. You know what? I'm gonna go create a holding company and spin up 10 companies myself and show everybody what can happen. I go back and forth on that, but but yeah. It's it's wildly wildly different.
Speaker 2:
02:13:30Mhmm. What is the what what's your read on the on the hiring market right now? Obviously, was big headlines. Maybe it was last last week, I believe, midweek, Microsoft. Again, our our read on that situation was Microsoft has always taken taken the approach of kind of cutting the bottom 3%.
Speaker 2:
02:13:50There still was a bunch of stories that came out from people being like, I've been here however many years working twelve hours a day.
Speaker 1:
02:13:57Clarna says they're not gonna hire anyone, but kinda went back on that. Like, yeah, overall hiring market temperature. What's it looking like?
Speaker 7:
02:14:04I mean, I think so, first of all, I agree with you that when there's a 3% rift, that's rarely actually a rift. That's performance management being done in this kind of way as possible so you can give people severance, which if you hear a company like Microsoft with as much cash as they have, you probably should do it that way.
Speaker 1:
02:14:21Yeah.
Speaker 7:
02:14:22That said, generally say generally speaking, what we're seeing is a if you're really, really good at being an AI engineer I mean, we had there were times when we had multiple billionaires wandering around our office with printed out offer letters for people begging them to come work for them. That's what it looks like if you're really good at AI. Most companies are not really understanding that, so that's not everybody. It is interesting. I I think it's fair to say the junior engineering market is completely decimated.
Speaker 7:
02:14:56It's pretty well gone. Even I mean, if you're at at Stanford, maybe you can get an okay internship somewhere, but it is it's Armageddon to be done.
Speaker 1:
02:15:08Mean that, like, junior engineers should be vibe coding companies and starting more apps and trying to just, like, build lifestyle businesses almost? Like, what what is your advice for people entering the workforce in software engineering capacities?
Speaker 7:
02:15:23Yeah. That's a really good question. It's a it's a tough one, because the the way that I describe it is someone who's not very good at AI and AI engineering can still get roughly the output of, you know, starting junior engineer out of AI, and that's what a lot of companies are doing. Instead of hiring a junior engineer, I'll just get, you know, the output that I need. There's still and there always is crazy demand for senior and, you know, high end and everything else.
Speaker 7:
02:15:54I think it'll take a while to figure out how that plays out because the flip side of that is you don't get super senior engineers if you don't have junior engineers. My and then you talk to the universities, and the average university that I talk to is closer to explicitly and permanently forbidding any type of AI usage in the classroom than they are to interweaving it or adopting it in any material way.
Speaker 1:
02:16:24Why is that?
Speaker 7:
02:16:25Because it's cheating. It's so much better at writing code than you are that the professor has no idea if you know how to write code because the AI will write the code for you.
Speaker 1:
02:16:37Can I send him I talked to much that is passed?
Speaker 2:
02:16:39I was at the I was at the park a couple days ago and was, you know, at the swings, you know, pushing
Speaker 1:
02:16:47Sure.
Speaker 2:
02:16:47The little guy. And there was another dad there who was a teacher and he said that that a high school teacher, he said they basically now wait homework at effectively zero. Like, it's like kind of check the box that maybe contributes to like a few percentage points of your grade and then tests are now just
Speaker 1:
02:17:04Yeah.
Speaker 2:
02:17:05A % because it's the only environment in which you can actually prove.
Speaker 1:
02:17:08Would you advise people to learn to code now or has the idea of learning to code changed in some fundamental way?
Speaker 7:
02:17:17So I still think I I feel like I'm almost on an island on this. I still think you should learn to use AI. And if you want to use AI in software environments, you should learn to code. Mhmm. Now to me, that looks very different than it did five years ago.
Speaker 7:
02:17:34And our, you know, our learn to code, business, we've we've basically shut down. It no longer operates. I'm not interested in teaching people to code in the traditional way. Now the flip side of that is, normally, when you would train people to code, you would start kind of close to the metal and at the bottom of the stack. And so you would start with, okay.
Speaker 7:
02:17:56Let's write binary, and then we'll figure out how to write some, you know, low level Java. And, eventually, a year and a half later, you start actually building programs that can do things that are interesting to you. The right way to learn to code is actually, in my mind, the inverse where you start by building applications and then you figure out what's broken and what's missing and what you don't understand. And the thing that is different about that than, you know, just creating a different curriculum is AI understands that. AI understands, you know, so we had software that would basically watch what you were doing on your computer.
Speaker 7:
02:18:34And from that, we could derive what CS principles you understood, what CS principles you didn't understand. We could have AI generate a custom curriculum that, you know, meets those guidelines specifically. And we can fill any gaps in a way that I would have killed two a decade ago training people how to code. So I think you can actually just start by building stuff and then figure out how it works down and, you know, start at the top of the stack and slowly work your way down. And to what extent you get down the stack depends on what you want to do.
Speaker 7:
02:19:05Right? Not the average engineer today isn't, you know, playing with a Linux kernel or writing c. They're Yeah. You know, writing JavaScript, and they're building applications. Yeah.
Speaker 7:
02:19:15To be at that level, you can probably get there relatively quickly. But I think, I'll credit Martin Casado, from a sixteen z with this, who said, basically, for to be a good engineer, you've always wanted to understand one layer of the stack beneath what you were actually working on. Yep. And I think that remains true.
Speaker 1:
02:19:35Yeah. Give me your view on the AI software engineer market. OpenAI now has, like, three offerings between, you know, o three. We'll just write code randomly for you. Codex is a new product.
Speaker 1:
02:19:50They now own Windsurf. There's top down enterprise companies like Cognition and Devon. There's bottoms up enterprise like Windsurf and, Cursor. How does this all play out? What do you look what what are you seeing in the, like, new this entirely new market of AI tooling?
Speaker 7:
02:20:10Yeah. My my first point here is, we're in an incredibly lucky position because as a as a consumer, you don't have to predict who will win. You can just figure out what's gaining momentum and latch on to the best. Yep. And so, you know, I have a lot of empathy for the companies trying to build those products and spend a billion dollars building a model.
Speaker 7:
02:20:31And if something is 1% better, I'm switching to it tomorrow. So that's a great place to be in as a consumer. How is that playing out? I think everybody's trying to fight similar battles.
Speaker 3:
02:20:42Mhmm.
Speaker 7:
02:20:43Cursor and Windsurf, I think, are uniquely positioned because they're focused primarily on the UX of the experience as opposed to the data. It's kind of in AI company's DNA to think that every problem is a data problem, and they're generally speaking right. But where Krish and Winsorfer are getting better and better is, okay. It's really cool that there's this model. I'd say, on average, that is the problem that AI companies have.
Speaker 7:
02:21:10People have no idea what they can do with the models or how they should be using them. I think that gets simplified over time the same way every product becomes you know, I shouldn't have to know whether I want to use o three mini or four o. No normal human's ever going to care about the difference between those. So I think they'll just get better and better. Who wins?
Speaker 7:
02:21:30I I I don't
Speaker 1:
02:21:33have a clue.
Speaker 2:
02:21:33Trillion dollar question.
Speaker 1:
02:21:35Yeah. It is. If you you'd probably be a VC if you're in that game. But thanks so much for stopping by. We'd love to have you back.
Speaker 1:
02:21:41This is this is great.
Speaker 2:
02:21:43Yeah. Keep us keep us posted. We'll talk to soon. Cheers, Austin.
Speaker 5:
02:21:46Bye. Have a one. See you.
Speaker 1:
02:21:47Next up, we have Jeff Morris Junior.
Speaker 2:
02:21:50Junior himself. Coming in from
Speaker 1:
02:21:52chapter one ventures.
Speaker 2:
02:21:54He's got some big news today. We'll let him Are you are you ready to stop Okay. Welcome, Jeff. Jeff. How you doing?
Speaker 2:
02:22:01Welcome to the studio. Welcome. Come on in. He is. You.
Speaker 2:
02:22:06How you doing? Technology brother.
Speaker 5:
02:22:08Welcome to the a life life goal achieved. I feel like I'm like
Speaker 2:
02:22:12Let's go. Let's go.
Speaker 5:
02:22:14No. I've seen I've seen this progress, and I'm just such a big fan of of you both. And I won't flatter you for twenty minutes, but but really, guys are are killing it. It's awesome.
Speaker 2:
02:22:23Well, I remember, I think we got breakfast burritos in Santa Monica, like, right around the time that we were starting the show. And you probably thought I was a little bit crazy for going full time on a podcast. Yeah. But but you you never you you always had faith. Yeah.
Speaker 2:
02:22:39I think you saw the the potential from the beginning. So it's great. Great to have have you on and maybe give a quick intro and then I'll let you talk about the the the news today, and then we'll get into a bunch of other stuff.
Speaker 5:
02:22:51Yeah. So I've I've been an investor, I guess, the past five years full time, started a firm called Chapter One. We call ourselves the product fund mainly because all of our backgrounds are in product engineering, design, data science, and kind of take a product centric view towards what we invest in. But prior to that, grew up in the Bay Area, probably most famously as an operator, was a VP of product at Tinder for a bunch of years, ran revenue over there kind of during, like, the hyper growth period of 2015 to 2019 when the company was growing. And then now now we're in the venture firm full time, and and, yeah, we've, evolved quite a bit.
Speaker 5:
02:23:34Today, we're sharing some of that news.
Speaker 2:
02:23:36Amazing. What's what's the news? And, we're we're we're not quite set up to have multiple guests on, but we'll have to have your new partner or new GP. So why don't why don't you break down the news and and kinda talk about the evolution of the firm?
Speaker 5:
02:23:50Yeah. So the big news today is Jameson Seadell is being promoted to a general partner. We started the firm in 2019 when there we go. You know, I think it it kinda marks a a moment in time for us as a venture fund, but also maybe more broadly in venture. We started chapter one as a solo GP firm when being a solo GP, I think, pretty, new, but also, I call it trendy in 2019.
Speaker 5:
02:24:17And, the it's been just really interesting to see the peer group go in different directions of people who were solo GPs at the time. Some have continued on that path. Other people have gone back to operating. And then I think there's another cohort of people who want to build partnerships and firms. And so I think, you know, there's all these right ways to do venture, whether it's building a firm, equal partnerships, so the GPs, and there's this constant debate.
Speaker 5:
02:24:45But I think we've, really been clear on what we wanna become. And today, building a partnership is is obviously, what what we're announcing today.
Speaker 2:
02:24:55That's amazing. Had this been your plan from the beginning? Like, did you realize quickly that that you wanted investing at the firm to be a team sport versus something that, you know, was was more of this, again, solo endeavor, at least like it was in the beginning?
Speaker 5:
02:25:12I think a lot of us in 2019, like, really like, we had a plan, but it wasn't Since concepts of a plan. What we've become. And so I think I I realized in, like, 2020, probably a year and a half, two years in that I didn't wanna just do it on my own. And I think there's a lot of people who are who are really happy with that lifestyle. And, frankly, it's probably a better financial decision just to do, raise funds, do it on your own.
Speaker 5:
02:25:39But but I think to be competitive and to build a great product for founders, you likely can do a better job of that if you bring on partners and build a firm. And so that was the goal in 2021. It took a while to figure out who that person would be and also the right way to do it. So a lot of people will tell you to kind of, like, promote people from within, build you know, you kind of, like people buy into the culture. They know what what what what you're doing, and and you you kind of elevate internally.
Speaker 5:
02:26:13Then other people will say go like, go find a superstar externally, which which at times we also thought about doing. So, you know, like, do you wanna go bring bring, like, a fancy GP spinning out or or maybe a former CEO type? And, those things are just really hard to to get right. And so I think we were really lucky where Jameson was doing an outstanding job internally, bought into what we were doing. And it's kind of like a head coaching search.
Speaker 5:
02:26:43Right? You guys kind of in a TVPN model. Like, it's really, I think, a learning to go hire, like, the big fancy, head coaching name, but oftentimes, like, promoting the person from within, is the best move because they know they know your players, your players trust them, and they know the system. And I think and maybe, like, the Boston Celtics did that really well. Right?
Speaker 5:
02:27:08And so I think it's really I think that's kind of the decision most most firms have to make as as they're growing their teams.
Speaker 1:
02:27:17She's focused on I mean, in her bio, she says, AI, ML, infra. How are guys making money off of Stargate? There's 500,000,000,000 floating around. What's the angle? We were talking about just go set up a Chipotle there, become become a, you know,
Speaker 2:
02:27:35a Don't just set
Speaker 6:
02:27:35up a Chipotle owner.
Speaker 2:
02:27:36Set up set up like a the the basically recreate the prod the 02/2007 Chipotle Yeah.
Speaker 1:
02:27:42Yeah. In Abilene. In Abilene.
Speaker 2:
02:27:44Massive opportunity.
Speaker 1:
02:27:45There's 357 workers there. But, I mean, seriously, like like, obviously, there's this AI boom. A lot of the Yeah. A lot of the trains have left the station. I don't imagine you're participating in the next OpenAI round.
Speaker 1:
02:27:58But but but how do you make money in the in the current AI boom, or or is it, or are we under, like, the next next trend?
Speaker 2:
02:28:06Yeah. I think there's a
Speaker 5:
02:28:07couple angles. Like, one is, location. So there's Jameson lives in London.
Speaker 2:
02:28:12Mhmm.
Speaker 5:
02:28:12I think there's a popular narrative right now that all the, like, all the value is having value creation is happening in the Bay Area. And so, obviously, I grew up in The Bay and I live in Los Angeles, and we've made a decision to to focus kind of on the other most important areas in the in in tech. And so her view, and it's my view being spending more time in London, is that there's actually a lot of talent in the in the universities at Cambridge, Oxford, etcetera. And, also, we we had a conference in London maybe two months ago, and we had the founder of Granola. We had, you know, Anthropic.
Speaker 5:
02:28:51We had, all a lot of people from JeepMind.
Speaker 4:
02:28:54Second
Speaker 1:
02:28:55is to help those founders, like, escape the backwater that is The UK and the Europe? Because I can't imagine that they're gonna try and build businesses there. Right? That that's crazy.
Speaker 3:
02:29:06Yeah. Insane.
Speaker 1:
02:29:07So, like but it makes
Speaker 2:
02:29:09it makes because you go
Speaker 1:
02:29:09there, you give the money, and you tell them, here. Go to San Francisco because then you have an actual shot. Is that the plan? I think
Speaker 2:
02:29:17think it's a it's a bit,
Speaker 5:
02:29:20like there's the there's, like, the the Project Europe movement, which obviously, like, love Harry and think that's important. But there's another views. It's, like, meeting founders where they are today and often that that is, hey. We wanna raise the seed round and and go, you know I mean, the story
Speaker 1:
02:29:36of Tropicana and granola. Right? Like like Yeah. International founders who eventually came to The US. There's always this question I have about, like There's also Sweden.
Speaker 1:
02:29:43Right? Sweden's pretty goated, pretty good.
Speaker 2:
02:29:46The Nordics. The Nordics.
Speaker 1:
02:29:48Yeah. There's something There's something special.
Speaker 5:
02:29:50There's something for you there.
Speaker 1:
02:29:51There's always the capital flow. Like, there are a lot of great LPs there that wanna invest in American companies. There's lot of founders that wanna come invest in America. Obviously, there are some great companies in Europe where we're we're we're joking around. But but but getting that capital flow right so you don't just expatriate US dollars to underperforming countries is probably a risk you want to avoid.
Speaker 1:
02:30:10But at the same time, it's probably really underpriced assets that are gonna go find niche markets all over the world. You know, who knows? Maybe the next power law company comes from some bizarre country like
Speaker 3:
02:30:20Do
Speaker 2:
02:30:20you have do you have strong beliefs around the intersection of AI and crypto? There's been a lot of different attempts and people attacking it from different angles. You obviously have backed a bunch of crypto companies Yeah. Historically.
Speaker 1:
02:30:35Yeah. How do we make money off of stablecoins? Ben Thompson was writing about this today, how stablecoins are gonna power Well, were we were Genetic Web, and I want get on the action. I'm super long on stablecoins, but they haven't moved at all. My portfolio is flat.
Speaker 2:
02:30:50No. It is it is a tough thing where everyone's just so bullish on stables, and yet and yet it's kind of unclear.
Speaker 1:
02:30:56Could we do, like, a meme coin about stablecoin? USD on pump.fund. Just USD coins.
Speaker 2:
02:31:02Potential potentially. Just 1,000,000,000,000 something there.
Speaker 1:
02:31:05USD. It should be a dollar eventually.
Speaker 2:
02:31:08No. But but more
Speaker 5:
02:31:09seriously Zero zero fiat backing. It's just it completely unbacks It's just complete meme.
Speaker 2:
02:31:14Yeah. Unstablecoins. Yes. I think people have
Speaker 1:
02:31:16tried tried it. Everything's been tried. But but, seriously, like, stablecoins, what is exciting or or, again, like, with the Bridge acquisition, is that the end of the story or the beginning?
Speaker 5:
02:31:27I think you've seen a lot of app application layer payments use applications that are using TibbleCoins to enable their payments, but there's not there hasn't been a lot of value accrual to, like, net new Circle competitors who are trying to compete with the Tether or USDC. Yeah. And so stablecoin's, like, the easiest thing to talk about at a AGM or LP conference because it's like, okay. Like, I can kinda see that use case. And so I think there's there's a shift to to emphasizing stablecoins
Speaker 2:
02:32:03Yeah.
Speaker 5:
02:32:03Today. I think the combination of, like, stablecoins and agents starts to get like, it does make sense, but it's it's gets pretty pretty blurry in, like, the current use cases of of of agents and and what's possible today. Mhmm. I don't for what's worth, we don't have a strong belief on the intersection between crypto and AI today being there's there aren't a lot of the the primary use case we like is giving open source developers a way to actually make money. Like, I think that's a pretty clear thing that's been missing if you look at any open source ecosystem ecosystem.
Speaker 5:
02:32:41So you look at, I don't know, like, now as a researcher, different like, BitTensor is trying to do this a a little bit too, but the yeah. I I I I think the the worlds are are very separate today if you go spend time in the Bay Area and actually talk to the best AI researchers like this. Nobody cares about crypto in the Bay Area for the most part, and that's totally okay. Like, I kind of like that crypto's, still very weird and unlike by by most people.
Speaker 1:
02:33:11Let's get Linus Torvalds a mega yacht. Let's get Guido van Rossum a private jet. This guy created Linux. Like, Guido created Python, open source software. He didn't get comped.
Speaker 2:
02:33:23Let's get him some stables.
Speaker 1:
02:33:24Immense, immense value.
Speaker 2:
02:33:26Let's get him some greenbacks on chain.
Speaker 1:
02:33:28Exactly. I I I wanna talk about the, the the the venture dynamics for, these mega platform funds and smaller funds. There was this, there was this trend during the ZERP era where it seemed like the mega funds were just preempting everything. You had the crossover investors, and that made it pretty hard for early stage investors to kind of make the decision on whether or not to write pro rata checks into the in into their earlier portfolio because they just wrote the seed check. Maybe they did find the great company early.
Speaker 1:
02:34:02But then there was this pressure to say, hey. These companies are graduating to series a immediately.
Speaker 2:
02:34:08Yeah. Wanna defend your ownership.
Speaker 1:
02:34:10Exactly. Exactly. And so has has that dynamic changed, or has the early stage market adjusted to spinning up growth vehicles so that they can ride that wave as the overall market gets hotter? I mean, some of these some of these rounds for these AI companies, they get up, series a at a hundred million, like, happens pretty frequently now. And how do you set yourself up for that as a manager?
Speaker 5:
02:34:34I think that's probably the the hardest part of 2019 to 2021 vintage. Right? Yeah. And you look back at at your follow on decisions and, at least speaking for ourselves, I think that was probably the the part of our investment we wish we could get back the most.
Speaker 1:
02:34:50Yep.
Speaker 5:
02:34:51And so, like, today, the markups are are just as crazy
Speaker 3:
02:34:55Mhmm.
Speaker 5:
02:34:56Except there's there's obviously more revenue that you can you can kind of lean on to underwrite the companies. And, so it's actually it might be harder today because you have like, before, it's like, okay. Like, Excel or Index is marking up the company. We did the seed. You know, we should maybe do the series a out of principle.
Speaker 5:
02:35:16Now it's now it's like, okay. One of those firms is doing it, plus they have, you know, 10 or $20,000,000 in revenue. And so it's it's equally hard. And I think for seed managers the growth fund thing for seed managers is pretty much done from what I've seen. Like, people aren't going to raising growth funds.
Speaker 5:
02:35:35And if they do, they have to have a very special reason why they're the seed fund who can do both. So I think there's a lot more like, we've seen SPV volume pick up again. That's become a bigger part of the ecosystem. And then I think a lot of a lot of LPs are looking for co invest. Like, that's always been the case, but especially so today, I think you see a lot of LPs coming to funds so they can co invest, and that's, I think, a bigger trend today than when I started in 2019.
Speaker 2:
02:36:03What's the sophistication level when they're looking at co invest opportunities? Are they saying, okay. I'm gonna back an emerging manager, let's say, 30,000,000 fund, and then I'm planning to do one or two co you know, take one or two co invest opportunities per fund and really just try to get into those winners? Or is there more of a, you know, we just want broad direct exposure and, you know, I'm curious what what you've seen or or what you're seeing broadly.
Speaker 5:
02:36:32Yeah. Think it's both. Our preference is that you do broad exposure mainly because the odds of of doing one co invest and having that be
Speaker 2:
02:36:42Yeah.
Speaker 5:
02:36:42The the right company are just extremely low. And so we, you know, we don't we don't do a ton of SPVs, but the messaging is always, like, please don't overshoot on on any single deal because if you're doing a series b SPV, and we all know the amount of risk even at the series b that and especially today, like, that's even more pronounced. And so, but, yeah, I think I'll
Speaker 1:
02:37:12series b risk is more pronounced now?
Speaker 5:
02:37:15I think if you look at the the amount of competition, the amount of change happening on a daily basis in in just technology advancements and then the pricing and size of these rounds Mhmm. I would think if we look back two or three years from now, we'll we'll see the series b risk in 2025 was probably on par with the 2021 vintage would be my would be my guess.
Speaker 2:
02:37:42Call it a bubble. It's crazy. I mean, I I just see this having probably 60 plus different angel investments. Now I'll get an update and see that a company is getting a markup. I'm like, I don't really think like
Speaker 1:
02:37:59They're there, yeah.
Speaker 2:
02:38:00They've made progress. Yeah. Are they any closer to being a business that truly has the intrinsic
Speaker 1:
02:38:06used to be, like, pre IPO. Yeah. It used to be, like, this is an extremely solid business, like, within, you know, within sight lines of, like, true profitability and, like
Speaker 2:
02:38:17I think we need a I think we need a new stock exchange probably in Texas just called DOGS. DOGS. Which is like venture backed venture backed companies that like have a little bit of revenue, so got a lot of work to do. Let's just get them out in the public market. Let's let them trade at $23,000,000 Yeah.
Speaker 2:
02:38:32Clear the pref stack and then maybe they hundred x. Right? Maybe they figure it out. Right? Yeah.
Speaker 2:
02:38:37So anyways, the
Speaker 1:
02:38:38the Well, what was that what was that SPAC that that holds
Speaker 2:
02:38:41There's that one there's that one destiny right now.
Speaker 1:
02:38:43I don't
Speaker 2:
02:38:44know if you've seen this.
Speaker 1:
02:38:45Yeah. Yeah. Yeah. Jeff, it's The inverse destiny of the dogs, the companies that are underperforming private markets. You wrap all those into a SPAC.
Speaker 2:
02:38:52Yeah. Investors can kind of sell to dogs. Take a little bit
Speaker 3:
02:38:55of a loss.
Speaker 1:
02:38:56But it has to be a you're like, yeah. Maybe there's
Speaker 2:
02:38:58one banger in here.
Speaker 1:
02:38:59It's There's something there.
Speaker 2:
02:39:01There's already businesses that The buy The bad But yeah, this Index Destiny, I don't know if you've seen it. They hold a bunch of basically SP
Speaker 1:
02:39:12They have like some legit exposure to SpaceX. But they trade it like 10 times the underlying asset value.
Speaker 5:
02:39:17Yeah. That is crazy.
Speaker 1:
02:39:18It's like I mean, people want access to this stock. They're going
Speaker 2:
02:39:22for it. Destiny Tech one hundred. Anyway, we'll build that one. Last question I have. What's your updated thinking on incubations?
Speaker 2:
02:39:29I know there's some stuff in the works that you probably can't announce, but, is that, is part of bringing on a GP to to free you up to to kind of be able to spend a bit more time on on internal stuff?
Speaker 5:
02:39:44That's been a a part of our stretch we wanna expand on. I think we're doing one incubation, which I'd love to come on the show Mhmm. In, like, three months to announce. It's, partnering with a really big piece of IP, like a a globally known piece of I IP to build an application for that property. And so I'm I'm I'm really excited about this because, obviously, building software
Speaker 1:
02:40:08payroll software. It's Mickey Mouse payroll software for sure. It's
Speaker 2:
02:40:13Honestly, good execution in payroll, you're at least a hundred million dollar company. Yeah.
Speaker 3:
02:40:17And so you slap some Mickey
Speaker 5:
02:40:18Mouse IP on That's actually kind of genius. It's Mickey Mouse payroll.
Speaker 2:
02:40:23Just hypercommodity. Like, you go after these markets are just hyper commoditized. Yeah. You say like, yeah, we're partnering with with Disney. It's just gonna be Disney themed
Speaker 1:
02:40:31Oh, you don't want the Batman VPN? Why don't you want the Batman VPN? You don't want the Dark Knight protecting you while you're browsing online? You're
Speaker 2:
02:40:41gonna go
Speaker 1:
02:40:41with what? Nord? What's Nord?
Speaker 2:
02:40:43Honestly Why not Jeff? This is your new this is your new playbook. You live in LA. Let's Yeah. Let's go on a road show.
Speaker 1:
02:40:50Let's build some
Speaker 2:
02:40:50genius. Enterprise SaaS meets legacy IP, buying it for pennies on the dollar.
Speaker 1:
02:40:56Yeah. You give them
Speaker 2:
02:40:56like 5% of the company. Yeah. Good to go. Anyways, I do know I do know what Jeff's
Speaker 1:
02:41:01What if Tony Stark built your ERP? Ironman ERP. Stark. Stark ERP. Stark Enterprise ERP.
Speaker 1:
02:41:11This is the Jeff
Speaker 2:
02:41:12could actually run this playbook. It'd be great. Kinda love this. Yeah. Definitely definitely come back on.
Speaker 2:
02:41:18I think it's gonna really break the Internet when you launch it. So I'm excited to see it.
Speaker 5:
02:41:23Alright. I'll talk to Thanks, guys.
Speaker 2:
02:41:24Congrats again to the whole team. Cheers.
Speaker 1:
02:41:26Next up, we got Cliff Weitzman coming in from Speechify. Great entrepreneur, great founder, good friend of mine.
Speaker 2:
02:41:33Are we talking about business or lifting?
Speaker 1:
02:41:35We're talking about lifting mostly. So he he's been on an absolute tear in the gym. He's super jacked. No. It's not a joke.
Speaker 1:
02:41:43It's not a joke.
Speaker 2:
02:41:44Hit the Ashton Hall. Hit the Ashton Hall. Bring bring Cliff in. Welcome to the stream, Cliff. Welcome to the stream.
Speaker 1:
02:41:51Oh, we were expecting shirtless.
Speaker 2:
02:41:52John said you're gonna be shirtless. Yeah. Yeah. We could
Speaker 6:
02:41:54we be shirtless as well.
Speaker 1:
02:41:55Yeah. No. No. Clipers.
Speaker 2:
02:41:56We're we're making TBP and stringers.
Speaker 1:
02:41:58Yeah. I I I I worked out with him in in this building where we record this. He put up some fantastic numbers on the bench press, showed me a spreadsheet where he's what's it called? Thor two point o?
Speaker 6:
02:42:11That's right.
Speaker 1:
02:42:11He's trying to become Thor two point o. And so I've been telling him I'm trying to do Thor three point o, and it's been getting under his skin. But
Speaker 6:
02:42:19has the lit
Speaker 7:
02:42:21Yeah. In his gym.
Speaker 1:
02:42:22How's it been?
Speaker 3:
02:42:23All the
Speaker 6:
02:42:23PRs of anyone who's ever worked out in that gym.
Speaker 1:
02:42:26Yeah. Yeah. Yeah. We're we're we're getting there. Are are you in LA now?
Speaker 1:
02:42:30Well, where are at these days?
Speaker 6:
02:42:33I'm in LA. Nice. Nice. I'm in LA in Studio City. Yep.
Speaker 6:
02:42:37But I'm about to we we move every four months or so. So I'm about to do SF, New York, Prague, back to New York, London, Rome, back to London, back to New York.
Speaker 2:
02:42:49Those are all four month those are all
Speaker 6:
02:42:50four months. So
Speaker 1:
02:42:53you're playing, like,
Speaker 6:
02:42:53two years out? That's the next that's the next forty days.
Speaker 1:
02:42:56Okay. Okay. So then bounce around.
Speaker 6:
02:42:58Back based in Florida for
Speaker 1:
02:43:00for a
Speaker 5:
02:43:00set period
Speaker 1:
02:43:00of time. Okay. Yeah. So so, I mean, take us through the structure of the business. Obviously, you can travel a lot, but I it's a fantastic story, and I just wanna hear, what you built, how you wound up there, and kind of the the the state of the union with Speechify.
Speaker 2:
02:43:13Yeah. Give I I guess to give people a sense for the scale which I think is important Please. Because typically people just think companies are big if enough VCs post about it but you haven't raised very much money. Speechify has over 500,005 star reviews, over 50,000,000 users, Chrome extension of the year, app of the day. I'm just gonna keep I'm gonna hit this a couple times.
Speaker 2:
02:43:36But, but, anyways, continue.
Speaker 1:
02:43:39Yeah. Yeah. Take us through it.
Speaker 6:
02:43:41Yeah. Happy to share more. So I'm super dyslexic, and I have ADHD. So first, second, third, fourth grade, I had a really tough time learning how to read. And when I was in right about to start college, I built this text to speech tool that would read out everything to
Speaker 3:
02:43:54me. Mhmm.
Speaker 6:
02:43:54And in high school, my mom used to read my summer reading books to me. And just we didn't have time to finish the summer reading book for college. So I cobbled together this thing that would read the stuff into my iPhone, and then I listened to it on the plane, and it And when I was in school, I studied renewable energy engineering at Brown. I ended up building about 36 different products, everything from three d printed skateboard breaks, the iPhone apps, and websites, and payment systems.
Speaker 2:
02:44:18Wait. Skateboard breaks?
Speaker 6:
02:44:20Skateboard breaks.
Speaker 5:
02:44:20I'll show
Speaker 2:
02:44:21you example. Yeah. Tell tell me tell me about that.
Speaker 1:
02:44:23Do you wanna go slower?
Speaker 6:
02:44:24So, if you ride a longboard or a skateboard and you go down concrete hill Yeah. Don't wanna stop by putting your face against the pavement.
Speaker 3:
02:44:35Oh,
Speaker 6:
02:44:35yeah. Three d printed the series of brakes that would attach to the back axle
Speaker 1:
02:44:38Oh, wow. That actually works really ah, that's great.
Speaker 2:
02:44:41That's a good Good luck there.
Speaker 1:
02:44:42That that's probably gonna be huge on Shark Tank. That's, like, the perfect brush for that. Yeah.
Speaker 6:
02:44:46Could have been on the tank.
Speaker 2:
02:44:47Oh, you did? No way. That's the most Shark Tank could have been.
Speaker 6:
02:44:50I was considering going on the show, but it's like you end up sitting for, like, forty eight hours in a trailer waiting to get called. Oh, wow. Other big opportunity that I had at the same time was, Shark Tank isn't worth it enough. Yeah. So at a certain point, I realized that software is much better.
Speaker 6:
02:45:03So I built this kinda meme maker, on a flight from an airport to SFO, published it, checked in on it thirty, forty days later, and it had 90,000 users. And I was like, oh, software's way easier than injecting molding stuff and way easier than, like, boron doping silicon wafers. My thesis was on a more efficient solar cell that I was building. I was like, alright. And around this time, I read this paper about narrow applications of deep learning.
Speaker 6:
02:45:29A bunch of academic papers, one of them was called WaveNet about autoregressive speech that came out of DeepMind. And I was like, I can make a 100 x better text to speech experience and a 100 x better audiobooks experience.
Speaker 3:
02:45:41Mhmm.
Speaker 6:
02:45:41And I wasn't sure what to work on. I knew I didn't wanna go get a job at Google or Palantir or Meta. And I was like, alright. Well, I don't know what I wanna do, so let me just write. So I wrote a 30 page paper about my world views.
Speaker 6:
02:45:54And the conclusion was I wanted to be the person that I needed the most when I was a kid, and the thing I really needed was someone to do my readings for me. Mhmm.
Speaker 3:
02:45:59I was
Speaker 6:
02:46:00like, okay. I'm gonna fully send it on this. So I convinced two of my professors to sponsor me to stay in school as a visiting scholar. Basically, I guess, taught classes. I got to be on meal plan, live on campus, use the gym, but not pay tuition or do homework.
Speaker 1:
02:46:10Gym's important. Amazing.
Speaker 6:
02:46:12I was gonna do that, work teaching computer science over the summer, unlimited indefinitely until something took off. And so six months in, it took off. And so now there's, like, 50,000,000 people who use it. But the goal is to make sure that reading is never a barrier for learning for anyone no matter what your background is. So if you download the Speechify iPhone app or Chrome extension or Mac app or Android app, it lets you take a picture of a physical book.
Speaker 6:
02:46:36It reads. It gives you play buttons throughout the Internet. It's like the voice of the Internet. You click play. It reads.
Speaker 6:
02:46:41And it coaches you to listen fast. So I listen to two audiobooks a week. I've done that since I was 14. So I've read more than 1,800 books by listening.
Speaker 1:
02:46:48Listen on, like, three x or something?
Speaker 6:
02:46:50Yeah. I listen on three x.
Speaker 1:
02:46:51That's so intense.
Speaker 6:
02:46:53And so Right?
Speaker 2:
02:46:54Listen to the
Speaker 1:
02:46:54whole show in just one hour because it was a three
Speaker 2:
02:46:57hour show. A one hour show.
Speaker 6:
02:46:58Why streaming doesn't work for me? It's gotta be something that I could react.
Speaker 1:
02:47:01We're we're in RSS feed. We're in we're in we're on YouTube, so you can pull it in there. Listen.
Speaker 6:
02:47:05That's exactly what I do. I I shopped live streams, you know, 80%.
Speaker 1:
02:47:09Yeah. Yeah.
Speaker 2:
02:47:10Yeah. Yeah.
Speaker 1:
02:47:11Catch up at the end.
Speaker 6:
02:47:12But, look, I I learned English when I was 13. So in the beginning, I would listen at point seven five x speed, build up to point five, two x, 2.5, three x. And I'm obsessed with biographies, theology, philosophy, fantasy. And so in the beginning, nobody wanted to back a dyslexia education startup. AI was not yet hot.
Speaker 3:
02:47:31Mhmm.
Speaker 6:
02:47:31The toughest point was around 2017. We didn't have the level of engagement and retention that I wanted, and there were a bunch of other sexy projects I could have done. But from first principles, my conclusion was I think that the trend that I boast back is narrow applications of deep learning. Today, we call it generative AI. From a supply side and from a demand side, it's audio as a user interface.
Speaker 6:
02:47:54And I was like, the intersection of these two, if I wanted to build something in that intersection, it's Speechify. So I might as well stick with it. I ended up putting a gigantic help button on the app. It made, like, 20% of the screen real estate, bright red, helps slash message us. And if you clicked it, just put you into an iMessage conversation with me.
Speaker 6:
02:48:10So, like Oh, wow. I didn't need you to enable notifications. There was no intercom. There was no Yeah. Email.
Speaker 6:
02:48:14And if I messaged you back and you didn't respond, I would FaceTime audio call you. It's a spreadsheet of all of our users. And if for whatever reason you didn't use the product, I would call you every day until you used it. Once you didn't use it, and then the product became really good.
Speaker 1:
02:48:28That's amazing.
Speaker 6:
02:48:30We when we were 25, 18 of the folks who worked at Speechify were previously either CEO, CTO, or VP of engineering at their last company. A lot of them were x y c founders or folks who exited their company after their series a. Nice tidbit on fitness. 12 of the original teammates got six packs within ten weeks of joining. And we had and we have had at least 17 people who gained 10 pounds of muscle, in the first ten
Speaker 2:
02:48:53It's amazing. It it everyone is back in India.
Speaker 6:
02:48:58And we get a big Airbnb in a different city every four months or so. And so at the time, we were in LA. Mhmm. And I convinced one person to move from India, One person to move from Bulgaria, One person to move from Mexico, One person to move to San Francisco. And I went and bought a bench press, and I rented a truck, installed it in the apartment in my room.
Speaker 6:
02:49:14And so we had me and Valentin were sleeping in
Speaker 2:
02:49:17And that's, like, the only kind of weights you need. Right? It's just a bench.
Speaker 6:
02:49:21Right? Everything And, actually, it gets even more deep because I went up to Marin to make sure that I was buying food for my parents because I didn't want them to go out during COVID. And so two of the guys were in the apartment working out just body weight.
Speaker 3:
02:49:34Mhmm.
Speaker 6:
02:49:35And they did a DEXA scan before and after, and they found that they had to, like, not gain any muscle even though they were working out like animals. And I was like, no. You guys need more weight. And so I brought
Speaker 3:
02:49:43the bench
Speaker 6:
02:49:44press. And we had two guys sleeping in a bedroom in the living room that we partitioned with a window, two guys sleeping in the bed in the in the room, and then one guy on an air mattress. And that was, like, the best time ever. Like, incredible time. Yeah.
Speaker 6:
02:49:57And then we found just very strong product market fit, ended up scaling really quickly. We closed partnerships with all the top publishers to resell our audiobooks and ebooks. My little brother Tyler started coding when he was seven, building drag all the websites. When he was 80 tons of assembly to hack video games. He went to Exeter for high school, skipped four and a half years of math, skipped five years of computer science, did Stanford as an undergrad, dropped out to run a cybersecurity company, went back to Stanford to do his master's in AI.
Speaker 6:
02:50:21And I was like, hey. If you can help me build a model that, will compile in three x real time, has better quality than any API that's currently out there, and meets the following requirements, I will, like, do anything. You know? I I gave him a very nice compensation offer, and he did it. Took him about ten months.
Speaker 6:
02:50:36He joined Speechify five years in as head of AI, so now we have a 40 person AI engineering team, and we make the highest quality digital voices in the world. We are the largest supplier of speech AI in the world for consumers. And then so that's, like, level one, level two, level three. The vibe now is we make everything modal multimodal. So if you imagine that 5% of the population would read books for fun on their own, and let's imagine 15% of the population would listen if you provided it as audio, now we're using text to video models to turn everything into, like, a full audio and visual experience.
Speaker 6:
02:51:05That's, like, super high level for Speechify, but happy to riff on anything.
Speaker 1:
02:51:09How big is the company now?
Speaker 6:
02:51:10We're a 76 people now.
Speaker 1:
02:51:13Wow. That's huge.
Speaker 6:
02:51:14About 32 countries. So a hundred five software engineers, 40 people on the engineering team, and the
Speaker 4:
02:51:19rest is growth.
Speaker 1:
02:51:20Yeah. So
Speaker 2:
02:51:20Talk about talk about the things that Venture has tried to make you the the Venture industrial complex has maybe tried to make you do that you've rejected because in in a in an alternate reality, you would have raised $500,000,000 by now and, you know, and and, you know, decided not to do that, and that's influenced a lot of decisions, I'm sure.
Speaker 6:
02:51:42So part of it is the fact that between the ages of 14 and 18, I read 461 books. A lot of them were about economics, philosophy, biographies, and I also listened to a lot of fantasy. And you listen to fantasy, you think, would I make the decision this character would have made in this point in time? Mhmm. So my favorite book is the way of kings by Brandon Sanderson.
Speaker 6:
02:52:03I'm obsessed with this character named Kaladin. I base my entire leadership style after Kaladin. And so when I was writing that 30 page paper to figure out what I wanted to do in my life, I became one of those lucky kids who, when they were 21, figured out what they were put on earth to do. And for me, was to solve dyslexia. And so I love what I do.
Speaker 6:
02:52:25Like, I wake up every morning early, and I go to sleep very late. I sleep very little because I just I can't get enough of working on this. And so I don't wanna sell it. I wanna own as much of it as possible, and I consider equity wholly. Mind you, I was a solo founder for five years working on Speechify.
Speaker 6:
02:52:41And, again, we had an amazing leadership team that, blood, sweat, and tears, we figured out how to hire. Last year, 50,000 people applied to work in the technical positions of Speechify, ten thousand people to the asynchronous engineering challenges. But we had, like, incredible offers for our series a from, like, literally the top firms. We said no. They doubled the offers.
Speaker 6:
02:53:02We still said no because I didn't wanna sell 20% of the company. And even with seed, we just picked folks who we thought were really good. So founders of Instagram, of Twitter, of Robinhood, of, you know, all these companies that I could learn from with the consumer subscription really well. And that was was key. So for example, Dylan Field from fig Figma taught me a ton very early on.
Speaker 6:
02:53:25And my nuance is if you take money from a fund, by and large, they have a fiduciary duty to their LPs. If you take money from an individual, they have just a duty to themselves. And so you get a Rolodex to someone who's really great, but you're not beholden. That being said, there are some businesses where it makes a lot of sense to raise money. In our case, we have a very simple business.
Speaker 3:
02:53:46Mhmm.
Speaker 6:
02:53:46And we understand the user extremely well, and it's a very niche audience initially for people who have dyslexia, ADHD, low vision, autism, anxiety, concussion, second language learners, and then the entire productivity suite. And at this point, we worked on Speechify for eight and a half years, so it's really hard to catch up to the product innovations as well as the AI side. And so we are always talking to investors. And don't get me wrong. We have raised money from, you know, funds as well.
Speaker 6:
02:54:11But we just done it where we typically look for three things. Number one, it's folks who either I have an evergreen model so they can ride with us because I'm gonna be CEO of speechify in eighty years. They have a history of philanthropy and education or an experience with dyslexia or ADHD in their family, and we think really highly of them. They can see around corners that we can't. Either they've done an amazing job taking multiple companies public, or they've backed founders in ways that
Speaker 2:
02:54:36You would go public?
Speaker 6:
02:54:38We would go public, but into the future, not in the
Speaker 3:
02:54:41short term.
Speaker 1:
02:54:42Yeah. Well, what are you thinking about competition from the hyperscalers, the big tech companies, Google IO is today. Microsoft had their, build keynote yesterday. It seems like an obvious place that, competition could come from, and yet, on the product side, a lot of the big tech companies just don't seem to be iterating on the application layer side as fast as most people expected. So what's that been like?
Speaker 1:
02:55:08Has anything slowed you down over the past two years with competition from the big guys?
Speaker 6:
02:55:12Oh, they've helped us a ton. So I'll give you two heuristics that are relevant to any founders, then I'll give you the specifics on Speechify. The first one is, in my personal opinion, value accrues at the application layer more than it accrues at the model layer, and models become commoditized. But
Speaker 2:
02:55:26ever did you ever doubt yourself? Did you ever think, oh, maybe value is gonna accrue
Speaker 3:
02:55:31to the the model layer?
Speaker 2:
02:55:32Because there were there was, like, a there was, like, a eighteen month period where everyone was like
Speaker 1:
02:55:36Models will do everything.
Speaker 6:
02:55:37Well, I'm I'm giving you what my opinion is today, and and the only reason I have a strong opinion is I've gone deeper into it than almost anyone has. Right? We bought millions of dollars of h 100 GPUs. We set them up in our own data center. We have a 40 person team who does research and development on models.
Speaker 6:
02:55:53So the second part I was going to say is, but if you really wanna be indestructible, you gotta own both the model and the data and the application layer. Mhmm. And that's what made ChatGPT and OpenAI so successful is they had, Brockman work on the user facing side, and they had Ilya work on the research side. And if they just had the research, they'd just be another lab.
Speaker 2:
02:56:11Mhmm.
Speaker 6:
02:56:12It application layer that made it incredible. And, so that's that's the first thing. Because you wanna be able to control the quality and the cost as well as the user experience. And then why did WhatsApp get acquired by Meta for $19,000,000,000? It's because they had all the users.
Speaker 6:
02:56:25And so you own the end relationship. You wanna have the phone number, the credit card, the email of that user, which we talk in a minute about kind of the changes that came with Apple. So that's the first thing. The second thing is and this is very unique. Sorry.
Speaker 6:
02:56:38Not unique. Ubiquitous. If you are Apple, Meta, Google, Netflix, there is no point in doing any project unless you think that project is going to make you 1 to a hundred billion dollars per year in the long term.
Speaker 2:
02:56:50Mhmm.
Speaker 6:
02:56:51We had a point where we introduced translation into Speechify. This is in twenty twenty, twenty twenty one. And Mike Krieger, is the founder of Instagram, CTO of Instagram, was like, you should consider removing this feature. And I'm like, are you kidding me? Do know how long I spent building this feature?
Speaker 6:
02:57:04But I have respect for Mike, so I took it out. Install to trial increased. Activation increased. Users use the product more. And I was like, shit.
Speaker 6:
02:57:11I gotta remove this.
Speaker 2:
02:57:12Why?
Speaker 6:
02:57:13Why? Because it was distracting. Speech adviser one thing, to give you the best experience listening to something. The second you add an extra button, users go down that path. So you know Interesting.
Speaker 6:
02:57:23Yeah. It has a problem, but they had
Speaker 2:
02:57:24a control. Have such insane scale that you could immediately see something that
Speaker 6:
02:57:30again, just removing some complexity. Back back then, we didn't have mad scale, but you could see it in three days of usage. Like, there's there's enough. No. So Clippy is horrible because Word is horrible because the design is terrible.
Speaker 6:
02:57:42But you know who has amazing design? Google. Yeah. One one text field. Who else has amazing design?
Speaker 6:
02:57:49ChatGPT. One text field, one button, and that's why they're successful. If they had multiple buttons, they would be far less successful. Now here's the key. Text to speech is buried five levels deep in the menu.
Speaker 6:
02:58:00When I was 19, I made a video on YouTube under an anonymous account because at the time, I was embarrassed for people to learn I was dyslexic. And it was called how to text to speech Mac free. And if you search that phrase on Google even today, my video from when I was 19 is number one. Why? Because it's so difficult to activate text to speech that you need 19 year old Cliff to show you how to do it.
Speaker 6:
02:58:18And you can't pause. You can't play. And by the way, if you wanna listen like me, what I ended up doing in college is I would use the terminal to change the speed because the GUI didn't go fast enough. And it backed down. I had to restart my computer.
Speaker 6:
02:58:31So I was restarting my MacBook multiple times a day when I was in college. And then I was like, screw this. I'm gonna build a Mac app with keyboard shortcuts. I'm gonna build the thing that OCR is the screen. And so my dream is for Google in mobile Chrome to add a gigantic play button that appears in every website that lets you listen to it.
Speaker 6:
02:58:47Why? Because it will make everyone addicted to listening. And then when they wanna listen to a long PDF and they wanna do it offline or they wanna do it in my voice or Stoop Dogg voice or their own voice or they wanna translate it to another language, or they wanna scan a physical document. Google doesn't cover that. Apple doesn't cover that, and people use multiple platforms.
Speaker 6:
02:59:03So you need to use Speechify. Yeah. And so Speechify is the premium experience for text to speech. What I need is for people to become educated about the idea that you can listen to stuff. And so a lot of our work over the last eight years has been to educate the market.
Speaker 6:
02:59:16And so there's really two goals. Number one, build the most exceptional product. Like, extreme prod we have four core principles. Extreme product quality, leading with love, frugality, and speed. So we talk to users a lot.
Speaker 6:
02:59:26We take really good care of each other. We don't waste money on anything. We build our own SaaS tools. It would move really fast. We ship a lot to production.
Speaker 6:
02:59:33And the second goal is to educate people that, hey. You can practice being a fast listener. And if you practice, anyone could do it. My dad is 65 years old, and English is not his first language. And the joke we have in my family is he wishes he had a mute button for me, and I wish I had a speed up button for him.
Speaker 6:
02:59:50That's very sweet. He now listens at two and a half x speed to everything. And so my life is better because my dad listens and talks faster now, But anyone can learn how to do this. It's just a matter of practice. When you come into first grade, no one expects you to be a good reader.
Speaker 6:
03:00:03First, second, third, fourth, fifth, twelfth grade. We expect twelve years for you to become a good reader, but you can become a good listener after listening to 15 audiobooks. You're not gonna be good on the first one. You're not gonna be good on the tenth one. And being a good listener means three things.
Speaker 6:
03:00:15Number one, you can do something else and listen at the same time. Drive, cook, walk, whatever. Number two, you can listen to more than two x speed. Number three, five weeks later, I ask you about the book. You have great retention of everything that you read in the book, and it will not happen when you start.
Speaker 6:
03:00:28You have to practice. But here's the thing. Reading is a hack we invented. Right? 24 characters on some dead trees.
Speaker 6:
03:00:34Listening, we evolved to be good at listening. Right? Telling stories over the fire. So if you were a bad listener, you were removed from the genetic pool. If you're a bad reader, you were not removed from the genetic pool because, otherwise, I wouldn't be around.
Speaker 6:
03:00:45And so when you read, 30% of your brain is dedicated towards decoding. 70% is comprehending. When you listen, like, 3% is dedicated toward decoding. The rest is comprehending. And so you can understand a lot better.
Speaker 6:
03:00:59And once you practice listening fast, you have that skill for life. And especially if you have ADHD and you get distracted easily, the speed of listening matches the speed at which their mind is working, and that helps people focus, especially in school but also in work. And so that's the goal of the company is to just make that accessible to everybody. And right now, there's 450,000 audiobooks, but there's hundred million books. We make all those accessible plus your emails, plus PDFs, and everything else.
Speaker 2:
03:01:21Amazing. Incredible. You are cracked. Wish we had more time.
Speaker 1:
03:01:26Yeah. We're get a workout in soon.
Speaker 5:
03:01:27We will.
Speaker 2:
03:01:28Yeah. Come by before you before you take off.
Speaker 6:
03:01:30Yeah. We gotta make sure you break that PR.
Speaker 1:
03:01:32Yeah. Yeah. I'm working on it. I I I think I'm pretty close. We'll talk to you soon, Cliff.
Speaker 1:
03:01:36Thanks for
Speaker 2:
03:01:37coming on. You're the man.
Speaker 6:
03:01:38You got it. Bye. Bye.
Speaker 2:
03:01:41Bunch of VCs are gonna reach out to
Speaker 1:
03:01:42you now. He really is a fantastic business. Let me tell you about Bezel. Go to get bezel.com. Your Bezel concierge is available now to source you any watch on the planet.
Speaker 1:
03:01:54Seriously, any watch. They got Rolexes. They got the GMT Master two, the Batman, the precursor to the Batman payroll suite or the Batman.
Speaker 2:
03:02:05You're really onto something there.
Speaker 1:
03:02:06I think it's good. I think that's the future. The Disney payroll. I mean, Logan Paul Logan Paul has a energy drink. Why not?
Speaker 2:
03:02:15Jake Paul has deodorant. Jake Paul has deodorant. Why doesn't Batman have
Speaker 1:
03:02:18a ERP system? Why not? Or Shaq payroll. Shaq payroll. Shaq payroll would be pretty good.
Speaker 1:
03:02:26Before we bring in the Google folks, we should talk about Joe Wisenthal. He says, your neighbor is online. He thinks the bricks are creating a new currency that will soon replace the dollar. He thinks Blackstone owns 60% of single family homes. He's Lon Cardano.
Speaker 1:
03:02:40And this is a response to Bucco Capital bloke who says, your neighbor isn't online. He doesn't think about tariffs. His Honda CRV only has 80 k miles on it. Good for another hundred k. He doesn't have an opinion on the rating of our sovereign debt.
Speaker 1:
03:02:52Only the only inflation he cares about is shrinkflation, yet his four zero one k goes up just the same. I think the the Blackstone owning 60% of family homes is the funniest meme. This whole idea of, like, you know, oh, like Blackstone's the most powerful financial institution in the world just because they index everything.
Speaker 2:
03:03:10Anyway turning single family homes into pods.
Speaker 5:
03:03:12They are. Alright.
Speaker 1:
03:03:14Let's bring in
Speaker 2:
03:03:15You know what time it is.
Speaker 1:
03:03:16There they are. Extreme.
Speaker 2:
03:03:18You, Shay. How you doing? What's going on?
Speaker 1:
03:03:21Congratulations on today. What's new? Would you mind introducing yourselves and then just giving a quick breakdown of what's going on today over at Google?
Speaker 8:
03:03:29Yeah. I can go first. I'm Tulsi. I lead the product team for Gemini.
Speaker 1:
03:03:32Cool.
Speaker 4:
03:03:32And I'm and I work on some of the Gemini developer tools.
Speaker 1:
03:03:35What are the top three announcements today? What's the most exciting thing? What is the the one takeaway for the audience?
Speaker 8:
03:03:44Oh, I'll start with one takeaway. I think the one takeaway is, like, Gemini, at least from my perspective, Gemini 2.5 is just getting better. Mhmm. And it's not just getting better in terms of, like, the quality of the models themselves. Mhmm.
Speaker 8:
03:03:57But we're now bringing that capability everywhere. So AI mode is coming to everyone, which is kind of our advanced version of search.
Speaker 3:
03:04:04Mhmm.
Speaker 8:
03:04:05Gemini is coming to glasses, which is gonna be amazing. Gemini is coming in even better ways to Gemini app, with more rate limits and just more access and better features.
Speaker 1:
03:04:19I was gonna have to spend glasses. Is this like a return
Speaker 2:
03:04:21of Google Glass? Is this a new Yeah. So so part of the issue for for us today is that we got to watch like twenty minutes of IO. Yeah. Then we'd start our So we still have to catch up.
Speaker 2:
03:04:33But yeah. And then and then it's good you mentioned rate limiting because I was worried I was going to have to spend this entire conversation moderating John asking for higher rate limits from you guys. Hit on
Speaker 4:
03:04:46VO2. Whatever you need. Next week, we'll make it up.
Speaker 2:
03:04:50Anyways, sorry, Tulsi. Can continue.
Speaker 8:
03:04:53Oh, no. I think it just it's a it's like an exciting time for for us because I think the models continue to get better. We released a new version of Gemini 2.5 Flash today. We introduced, like, improved versions of 2.5 Pro with the deep think, kind of deeper reasoning version of the model. And so I think the models are getting better, but it's also amazing to now see them actually really landing in Google products in in a very real way.
Speaker 2:
03:05:16Yeah.
Speaker 8:
03:05:16I don't know what what are your takeaways or top three are.
Speaker 4:
03:05:19Yeah. I think my my TLDR is Google's firing on all cylinders across every vertical, across every dimension, and, like, IO is this, like, manifestation of this actually happening where you just, like I'm like, holy like, even as someone who spends all day working with Tulsi, working with our teams, seeing this happen, like, IO is this crazy reminder of, like, just how much breadth Google has in in the in the product areas and just how many people the model innovation touches. And it's, yeah. I think today's a celebration of all that hard work and and making all that happen.
Speaker 1:
03:05:50Yeah. How do you think about the messaging from, like, the continuum of, like, cons Google is so big that, like, consumers will watch a developer focused keynote. Some of the products that are launched are very consumer facing, but then there's obviously developers that wanna build on top of these tools. And then there's also stock analysts that are probably watching for how things are going on benchmarks or MAUs or any new data points. And so what are you focused on kind of messaging to the different audiences?
Speaker 1:
03:06:17Is there a concept of speaking to multiple audiences, or do you just try and laser focus it on on dev specifically?
Speaker 8:
03:06:23No. I think we really do wanna speak to multiple audiences. I think you hit the nail on the head in saying, like, there are definitely experiences that we talk about here at IO that are very consumer focused.
Speaker 1:
03:06:31Yeah.
Speaker 8:
03:06:32We also know, though, that developers are trying to build for consumers.
Speaker 3:
03:06:35Sure.
Speaker 8:
03:06:35Right? So when you showcase amazing consumer experiences, you are also able to speak to devs because you can speak to them about how you actually were able to build that experience and what they can do
Speaker 1:
03:06:44Yep.
Speaker 8:
03:06:44To build experiences like the ones that you're trying to build. Right? And those and so I think there's an art to try to figure out what are the right demos, what are the right stories that really can land cross audience.
Speaker 3:
03:06:54Yep.
Speaker 8:
03:06:55And then we try to create sections that are maybe more targeted. So for example, I spoke earlier today. Logan spoke in the developer keynote, really targeted at developers and what developers can do. And then there are obviously sections around search or glasses or Gemini app that are much more targeted at consumers.
Speaker 4:
03:07:10Walk straight off the dev demo stage right here. Yeah. It's true.
Speaker 3:
03:07:14Yeah. You were
Speaker 2:
03:07:14you said you could do two, and you also said your keynote was starting at
01:30. I was like, are you worried somebody might ask an an extra question?
Speaker 8:
03:07:21Be in multiple places at once. It's a skill.
Speaker 1:
03:07:23This is amazing. How important do you think those demos are? Because, you know, we saw ChatGPT break through with the the the Studio Ghibli moment. Everyone was memeing the Ghiblis. I was recently using v o two to generate video of of cars with specific liveries and decals on them driving around, and the result was fantastic.
Speaker 1:
03:07:45But it hasn't broken through in the same way even though I feel like the model and just more importantly, the accessibility because I was able to generate a video from a Gemini chat box, and I didn't have to go to a different app for that. And I saw in the Apple App Store, the the Gemini promoted post is basically like v o two is here.
Speaker 2:
03:08:07And the output was so good that I showed it to somebody, and they
Speaker 1:
03:08:11They thought it
Speaker 2:
03:08:11was said he was John had generated an image of a Lamborghini that had full TBPN branding on it. And I showed it to somebody, and they're like, when did you do that? And I was like, they were like
Speaker 8:
03:08:22That's right.
Speaker 2:
03:08:23Was this how you made
Speaker 4:
03:08:24your promo video? It was really just VO behind
Speaker 1:
03:08:26the scenes.
Speaker 2:
03:08:26That's our that's our next promo video.
Speaker 8:
03:08:28Actually, also, on that note, you I think you probably haven't seen that part of the keynote yet, but we shipped VO three today
Speaker 3:
03:08:33Oh.
Speaker 8:
03:08:34And it's awesome. And it had audio. It's it's amazing.
Speaker 1:
03:08:37Oh, that's very cool. Yeah. I was thinking about that because it was missing audio, and I was like, is the missing thing. I need to go find another model and then figure out how to inference that or whatever. But, yeah, I mean, in terms of in terms of creating these, like, memeable moments or something that can go viral, is that something that's even thought of?
Speaker 1:
03:08:52Or is it more just like turn it loose and hopefully
Speaker 2:
03:08:55Well, yeah. I think the question is, like, you know, you wanna distribute the capability. And the question is, like, is that Google's job, or is it the developers building on your guys' platform to do that sort of last mile delivery to users?
Speaker 1:
03:09:08Yeah.
Speaker 4:
03:09:09Yeah. I think the use case that is is actually really important because I think despite, like, we're I feel like we're all sort of seeing everything that's happening and we're close to it, but, like, there's so many people who have no idea, and it's like every day Mhmm. I think we need, like, a tracker of, like, the number of new people entering the AI world every day. But, like, I imagine it's, like, some reasonable percentage of all people who are using these products. And, like, you know, most products are still a blank empty chat screen somewhere.
Speaker 4:
03:09:35So, like, showing that use case of what's possible is super important. And I feel like a lot of the demos from my o today were, like, pushing that frontier in a in a really meaningful way. But I think also to answer the question of, like, whose responsibility is it? Like, I think Google, we get to do both, which is fun. Like, we get to go and build a lot of these use cases for developers and make it possible for them to, you know, bring that to their consumers.
Speaker 4:
03:09:57But then we also get to be, like, dog food and, like, really walk the walk and build those consumer experiences ourselves and find a way to make a a memeable moment.
Speaker 1:
03:10:06Yeah. How how much of, what is announced are more, like, showcases that could be built into other products long term? Because I was looking at somebody was saying, like, Google Assistant has less five star ratings than Gemini. But you could imagine Gemini being, like, a demo for what's coming in Google Assistant, but it seems like Gemini has just gotten so big that it's, like, bigger than Assistant now. And so you have this weird thing where you're experimenting in this fun sandbox.
Speaker 1:
03:10:36But if you're really successful, then people just start using that and then you just move off of the other thing. Is that is that, like, a deliberate part of the strategy or just, a natural outgrowth of, like, the modern AI development strategy that you put stuff out and if it goes really big, you just let your winners ride?
Speaker 8:
03:10:52I think it's a it's a good problem to have, I think, if we're in a world where the experiments we're trying or the new kind of surfaces we're building or the new types of use cases we're building actually really resonate with users, and then we're in a place where we actually wanna build those and scale those out. Yeah. I think what we're trying to do so at the end of the day, what we wanna build is products that people love and really wanna use. Mhmm. Right?
Speaker 8:
03:11:12And I think there's three ways you can do that. You can try to build new features into your existing products. I think in a lot of cases, makes sense. Right? So for example, like AI mode on search Yeah.
Speaker 8:
03:11:22Today. Yeah. Yeah. But in some cases, if you do too much of that, you bloat the existing product. It becomes harder to use and understand versus being able to create a new surface where you actually can really rethink the UX, really rethink how users are supposed to think about the product.
Speaker 8:
03:11:36And then you can look at that and say, well, does this really make sense as a standalone, or does it actually, merge with other ways that users are using different products. Right? And it actually fits into their existing workflows in some way. And so I don't think we wanna pigeon holes ourselves into just, hey. We need to consistently build on one product.
Speaker 8:
03:11:53Yep. Right? We wanna give ourselves the flexibility to create ways for users to build new mental models
Speaker 2:
03:12:00Yeah.
Speaker 8:
03:12:00And then figure out how those things come together.
Speaker 4:
03:12:02And I think this search example is actually a great one because you if you saw, we announced deep research, in the Gemini app came out, I think, all the way back in December, and it was, like, pioneered the deep research category, and Google launched that in in the Gemini app. People love it. It's it's a crazy product experience. And then, like, that's now like, I think the the, you know, the feedback was this is an incredible experience. Not everyone in the world is a Gemini app customer.
Speaker 4:
03:12:25There's a whole lot of people in search, and, like, now I think it's called deep search is available as part of AI mode inside of just, like, basic Google search, which is gonna reach, hopefully, even many, many For a larger search. Millions of more users that are using the search. Billion.
Speaker 3:
03:12:39Couple billion. Yeah.
Speaker 2:
03:12:41Just a just a b too.
Speaker 1:
03:12:43Talk about MCP. Was there was there, like, a sigh of relief that Google's leaning into MCP? Was it ever a question, or was it something that was, like, pretty easily adopted across Google?
Speaker 4:
03:12:56I think it's been fascinating to see, like, how quickly the world has, like I feel like with standards, like, people I feel like are often, like, very slow moving to be like, do we adopt this? There's, like, a whole, you know, many year battles with different standards competing. And I feel like everyone was just like, MCP came out. Everyone's like,
Speaker 1:
03:13:13okay. We'll use MCP. Yeah. XQCD it's that XQCD meme. There's 10 standards.
Speaker 1:
03:13:18We need another we just need one standard. Now there's 11 standards. But in this case, we actually got the good ending.
Speaker 4:
03:13:24It's important, though. Like, I think developers are building stuff. I think in this moment where, like, you know, the world is still trying to figure out how to build robust agentic systems, like Yep. Having people not spend all the time just rewriting the same framework 50 times over, like, is I think is, like, actually a net benefit for the world. So and I think the the team that built that built MCP at Anthropic did a really, really good job, and it was a smart move by them to, like, actually make it an open standard, which, they could have easily not done.
Speaker 4:
03:13:52And I think it's it's the right thing for the ecosystem.
Speaker 8:
03:13:54Put developers first in in, I think, the right way.
Speaker 1:
03:13:57Yeah. What what is the overall messaging to developers? It seemed like Satya on stage at at Microsoft's build was very much like, we host every single model. We'll we'll give you deep seek if you want. We're partnering with X.
Speaker 1:
03:14:11Google, in my mind, has always just been like, look. We invented the transformer. We have the biggest, like, best models that we're we're dominating the Pareto curve. Are are you guys seen more as, like, a one stop shop, or do you think there'll be more model agnosticism in the future with regard to GCP?
Speaker 4:
03:14:28I think GCP already has this. So g c like, we do like, I just said, you know, Tulsi and the team do a great job with Gemini models. We want the world to use Gemini. But Yeah. GCP does actually have, like I think it's over a 75 different models that are available through the model garden.
Speaker 4:
03:14:42You can get Anthropix models. You can get a lot of models. So I think the and, like, for customers on cloud, like, that makes perfect sense. They need that. Like, that's a requirement.
Speaker 4:
03:14:51Like, the world doesn't wanna, you know, be locked into a single model. But I think, like, we get to see these, like, really, really interesting experiences that can only be built on into Gemini because of the, like, stack of of Google's model innovation. So we're gonna keep pushing on on Gemini models too.
Speaker 8:
03:15:07That's the goal.
Speaker 1:
03:15:08Yeah. And then on the, developers that might be working with Google, I imagine that the conversation is a little more nuanced, if you're actually scaling a growing app on on on Google infrastructure? Like, I ran into a rate limit as a random user. But, if you're actually thinking about scaling a startup, unless you're thinking about building Stargate, you're probably able to scale pretty efficiently. But have you been seeing companies run into, any sort of, like, scaling rate limits or challenges as they kind of grow on Google?
Speaker 4:
03:15:43Email me. My email my email's online. I'm on Twitter fourteen hours a day. So whatever you need, email me. We'll make sure it doesn't happen.
Speaker 4:
03:15:50I think in general, like, this is, like as far as, like, a class of problems that developers have in this moment, I think they're, like, very real. Like, I I hear this and see people all the time.
Speaker 1:
03:15:59A lot.
Speaker 4:
03:15:59Yeah. The challenge is, like, compute is, a it's, literally a currency almost. So, like, we have to make sure we get the right to the right people who are actually building stuff. And, like, it is a it's not an easy process to do that. But I think if people need stuff, please reach out to the team.
Speaker 4:
03:16:13Actually, reach out to Tulsi too.
Speaker 2:
03:16:16We'll get Yeah. Spread the spread the love. You know? Don't just send your don't just don't just create CX tickets for Logan. Maybe talk about a couple of the the other kind of product level announcements.
Speaker 2:
03:16:30You guys had Joules, an asynchronous coding agent. You wanna speak to that a little bit? I'd curious to get your Yeah.
Speaker 8:
03:16:36We're really excited about Jules. So, actually, like, at Jules.Google today, you can sign up for the beta. But, basically, the idea with Jules is we really wanna start, thinking through more and more use cases for how we can build essentially, assistance for an agent of assistance for developers. Mhmm. Right?
Speaker 8:
03:16:55And so you can think about Jules as trying to take aspects of the workload that are frustrating, that are time consuming, and can actually operate on them in the background. Right? So the example I gave earlier today is Node. Js, being able to, like, update an outdated code base, for, like, the latest version. Right?
Speaker 8:
03:17:12But I think it's really about how can you actually be able to assign tasks and let the model run and complete those tasks and come back and actually then have this, like, relationship with the developer, where these tasks can get completed, can come back, can iterate together, and and build that kind of collaboration setup.
Speaker 2:
03:17:28And you can run multiple at once?
Speaker 8:
03:17:31You can run multiple
Speaker 6:
03:17:31at once. And I think
Speaker 4:
03:17:33in classic Google fashion, you can sign up and use it for free right now, which I think is really cool. Like, I think part of this is if you look at what's Google's job in the world right now, like, I think part of this is, like, we have the stewardship role of making sure, you know, developers, people who are using search, all etcetera etcetera, like, know what's happening with this AI technology and can actually get their hands
Speaker 8:
03:17:52on this. Yeah.
Speaker 4:
03:17:53Can try it and, like, know that it's available to them. So anyone can sign up. I think the queue time for tasks is kind of high right now because everyone is flooding Jules. But, hopefully, as they scale up capacity, we'll
Speaker 1:
03:18:03Yeah.
Speaker 8:
03:18:03I mean, also and I think, like, what what's been actually really exciting today is to see and get the feedback on Jules because we've obviously been trying it internally and and using it. But actually getting it in the hands of real developers, getting that feedback. That's how we can actually, a, prioritize what types of activities do we need to prioritize in Juuls, what use cases and features are most valuable for developers, how do we build that up. And so it's actually, like, a very self fulfilling prophecy, I think, for for how this will go, hopefully.
Speaker 1:
03:18:30Yeah. Amazing. Have either of you had a chance to actually sit and get the Project Starline demo? I remember a couple years ago, this is the the three d how would you describe it? Three d video conferencing?
Speaker 1:
03:18:42Yeah.
Speaker 8:
03:18:42The like, video conferencing plus plus.
Speaker 1:
03:18:44Yeah. Yeah. Plus plus. And and and there were a whole bunch of videos, from influencers who were there who got the demo and, like, blown away. And they were like, I filmed it with my camera, I you can't really see the effect, but you'll see my reaction.
Speaker 1:
03:18:58But it's it's exciting that it sounds like that's going into production in partnership with HP, but, is there anything else to to say there? Have you had a reaction or, or any any test demos?
Speaker 4:
03:19:09I'll be honest, which I've had I had that same experience that the influencers had, which is I used the the project Starline room to take us to take a meet call. But I
Speaker 2:
03:19:18was meeting with someone who wasn't in one of the other room. So I
Speaker 4:
03:19:21have no idea. Like, maybe I looked different or something like that, but they weren't. They were just
Speaker 8:
03:19:25like They were a normal They were
Speaker 2:
03:19:27a Yeah.
Speaker 4:
03:19:29But it looks cool. Like, I I I'm I'm hopeful.
Speaker 3:
03:19:32I'm hopeful.
Speaker 8:
03:19:32Yeah. It's a very cool
Speaker 3:
03:19:33setup.
Speaker 4:
03:19:33As somebody who works at home too much, I'm interested so that people can sort of feel my presence hopefully in the future.
Speaker 2:
03:19:40Well, if you get in your car and drive, you're gonna miss all the DMs from developers that are, you know That's
Speaker 8:
03:19:45you need Logan to stay home with his star line setup.
Speaker 2:
03:19:47Stay locked in.
Speaker 1:
03:19:48Yeah. I mean, we've been kind of in, like I mean, I I remember I bought a three d TV, like, like a decade ago probably, and we've been waiting for like, okay, yeah, four k, we can't really see anything past four k, but something like this would be very, very cool if it were
Speaker 2:
03:20:00Notebook LM number four in the charts. Oh. Big launch, new mobile app. I'm sure you guys never lost faith internally, but I think people externally were kind of Yeah. Had been frustrated because they liked the product so much.
Speaker 1:
03:20:15We felt like it just didn't
Speaker 2:
03:20:16feel like it wasn't getting kind of the investment. Any any color to add there?
Speaker 4:
03:20:23Lots of notebook l m progress. I think people sort of felt this, which is interesting, and I've had we had a bunch of conversations around why, but it was like the team is still cooking, like they're still shipping a bunch of stuff. Think that I think part of it was like the expectations were just, like, super, super high now because a lot of the stuff they shipped was awesome. But they had a ton of new features that just landed, and it's been awesome.
Speaker 8:
03:20:41I think also this team is one if even if you look at the history of NotebookLM, like, we actually shipped NotebookLM relatively quietly, and then it got a lot of pickup because it was just such an amazing product to use. And so I think we've taken this strategy with NotebookLM where we've sort of tried to lead with the product leading almost Yeah. Yeah. As opposed to just trying to, like, cook up a bunch of noise. And I think the NotebookLM, his team has just been silently making the product better and better and better.
Speaker 2:
03:21:04But, like Yeah.
Speaker 4:
03:21:05We are gonna have Tulsi cook up a bunch more noise for Notebook. This is a great
Speaker 1:
03:21:09way for
Speaker 8:
03:21:09you to get more
Speaker 4:
03:21:10more tweets. It's just firing off Notebook. Well, good.
Speaker 2:
03:21:13I mean, the fact that there was like organic real pull from the market and it wasn't just like, hey, we have a bunch of distribution. Let's make everybody aware of this right away.
Speaker 3:
03:21:22Yeah. Yeah. What was
Speaker 1:
03:21:23the original notebook, Ellen? Because, I mean, there's research previews. There's developer previews. Now there's alphas, betas. I feel like there's 25 different ways to say, like, don't hold us accountable to that we're launching this product.
Speaker 1:
03:21:36What is the actual flow these days for just getting a product? Wasn't wasn't Gmail in beta for, like, a decade or something like that? This is kind of, like, in in tech culture broadly. But, I mean, a lot of things people are just like, if I can use it, I expect it to be a consumer product. But did did did NotebookLM go through, like, a particular pipeline, or do you have, like, a a structure for these launches over there?
Speaker 4:
03:22:00Yeah. NotebookLM came through, Google Labs. Google Labs is Josh. I don't know if y'all follow Josh Woodward, but Josh Woodward runs Google Labs and the Gemini app now. And Gemini app is obviously generally available and not in Labs, but Labs does all the early stage bets.
Speaker 4:
03:22:14So actually, AI Studio, the project that I work on Yeah. Out of Labs. Same with the Gemini API. Notebook at them. Juuls came out
Speaker 8:
03:22:22of Today, some things we showcased. So we showcased today, showcased Pinhole. Showcased Stitch and with jewels.
Speaker 2:
03:22:30Yeah.
Speaker 8:
03:22:30Right? All of these are products that kinda came out of And it's like
Speaker 4:
03:22:33a it's like a
Speaker 1:
03:22:33Break those down really quickly? The those other labs products, Stitch and
Speaker 8:
03:22:37Yeah. So, I mean, you you we're actually demoing Stitch earlier. Right?
Speaker 4:
03:22:41Stitch. Yeah. I didn't Josh demoed Stitch right before I got on stage, but, Stitch, similar sort of vibe coding, vibe designing setup Cool. Where you can go in and ask the models to, like, go and build native mobile apps, I think, is what it's actually built on
Speaker 8:
03:22:55the box. And then Pinhole basically builds off the magic of v o three and sort of multi multimodal generation. So I think, really, what we're trying to do with labs is or Josh is trying to do with labs, what we're trying to do with labs is use it as a way to take these technologies and start testing what new surfaces, what new UX, what new types of products can you build.
Speaker 1:
03:23:16Yep.
Speaker 8:
03:23:17And then, like, ideally, like NotebookLM, they're well loved, and we actually, like, can hit a moment in the market where we can find new product market fit. And that's really why we're trying to create this incubation engine. And then we can take those ideas and both bring them to our products as well as actually ship them as stand alone products.
Speaker 4:
03:23:33And principally, they're they're also, like, close to the model teams. So it's not this, like, you know, they're they're the the, you know, they're collaborating with Tulsi's team. Like, the PMs are all sitting in the same places. So there is this, like, innovation at the model level Yeah. Turns into innovation at the product level.
Speaker 4:
03:23:49And I think those teams are, like, some some of the first recipients of that stuff.
Speaker 1:
03:23:52Yeah. Yeah. It's interesting because, like, I I I feel like Gemini has a voice mode now that you can click over and and talk to the LLM, and it's kind of, like, almost a separate feature path from just dictating and then having it read to you even though that's a very similar auditory experience. You could imagine NotebookLM being, like, a feature inside the Gemini app, but right now, it's kind of going down separate tech trees and That's
Speaker 8:
03:24:14it. Kind
Speaker 2:
03:24:15of is.
Speaker 1:
03:24:15So we we brought
Speaker 4:
03:24:16audio overviews and deep research. And, like, I think the interplay between these things are, like, all kind of connect. I think there's, like, some, like, very bespoke notebook LM stuff that you'll, like, probably not have in the demo app. But I think the stuff that works, like, there's no reason to not. It's, like, all it's all under Josh's umbrella.
Speaker 4:
03:24:32So, like, he gets to easily be able to bring those
Speaker 8:
03:24:33Yeah. And I think, like, the underlying technology, like Logan said, we're we're trying to make sure that the model teams in these products are very close together. So for example, NotebookLM has now native audio, which is what so one of the things we talked about today, which is really, like, Gemini being able to natively generate audio, which makes it more, like, multilingual friendly, more natural. And so that kind of technology, a, we can use to make NotebookLM better. We're also bringing that to Gemini Live.
Speaker 8:
03:24:59We're bringing that to, you know, other parts of the Gemini app over the course of the next, you know, months. And I think that kind of synergy means that you're gonna get the best of these experiences depending on your use case in different places.
Speaker 1:
03:25:12Yeah. I've I it's an interesting product challenge. I've run into weird scenarios with ChatGPT deep research. I'll generate some huge research report, and then I'll be like, listen to like, read this to me. But it clearly gets lost once it's reading halfway through and starts hallucinating and stuff.
Speaker 1:
03:25:27So, like, there's some interesting challenge to actually make all of this like, if you generate 5,000 words of text, actually getting it into the human's brain, it's not enough just to be like, here's your research report. Like, you actually have to make it accessible.
Speaker 4:
03:25:40Deep research audio overview, I think, is that flow. Like, makes sense. Does work. It's like you It's actually awesome. Because the deep research reports are, like, 46 pages.
Speaker 3:
03:25:48I'm like Yeah.
Speaker 1:
03:25:48Exactly. I don't have time for that.
Speaker 3:
03:25:49Like, like, there's no 46
Speaker 8:
03:25:51whole pages. 46 pages. I'm gonna
Speaker 5:
03:25:53be good.
Speaker 1:
03:25:54Like, give me one
Speaker 4:
03:25:54pager or give me, like, three minutes of someone, like, you know, having a casual conversation.
Speaker 1:
03:25:59Give me a YouTube short generated by v o three. That's what I need.
Speaker 2:
03:26:03Yeah. Yeah. Makes sense.
Speaker 4:
03:26:05We're eventually, YouTube are just gonna be an audio overview
Speaker 2:
03:26:09Yeah. Yeah.
Speaker 4:
03:26:09With In the future. You know, your own bespoke taste. Yeah.
Speaker 2:
03:26:14Yeah. Yeah. We're not letting Notebook LM disrupt us. We're coming into the show completely unprepared Yeah. But we listened to a ten minute Notebook LM Yeah.
Speaker 2:
03:26:22On the thing we're about to talk about so we have a little bit of context. Anyways, you guys have been shipping like crazy. What can people expect from you now? Are you gonna rest on your laurels? Are you gonna, you know, you know, just get a little overconfident or is it, you know, business as usual?
Speaker 2:
03:26:39Time. Back to the grind.
Speaker 4:
03:26:41A little overconfident, I think, will be good because I think, like, we've done a lot of there's there's just been so much stuff that the team has done. So I think, like, people should be proud of all the work that's gone into it. But I think the work just starts now.
Speaker 2:
03:26:53I was
Speaker 4:
03:26:53just I woke up this morning, and I was like, I'm writing the doc about how we need to go heads down for the next six months and
Speaker 3:
03:26:58land the
Speaker 4:
03:26:5950 things that need to happen because there's, like, so much stuff that's still cooking in the pipeline, and it's gonna be awesome to see all that land.
Speaker 8:
03:27:05Yeah. I think also, like, we're really I really do think we're hitting our stride in so many of these areas.
Speaker 2:
03:27:12It feels like it. It feels like some of the posts, like, even Sundar's posts, like, over the last twenty four hours, I was like, he's feeling good going into IO. You could tell. You could tell. So the energy the energy is palpable.
Speaker 8:
03:27:24That's great. And so we wanna I think we wanna use that energy. Like, I think I think the momentum coming out from today is really about, like, okay, how do we take the excitement? How do we take the energy? How do we take the feedback and, like, actually really use it to continue to just build awesome things?
Speaker 8:
03:27:39So I think we're just at the beginning. Like, this actually really is the start of of what's gonna be an exciting rest of the year, I think.
Speaker 4:
03:27:45And we'll make sure that you two are in person for the next
Speaker 8:
03:27:47Oh, yeah. We can't
Speaker 2:
03:27:48wait. Yeah. Let's do it.
Speaker 4:
03:27:50More than twenty four hours heads up
Speaker 5:
03:27:52if you wanna come in person.
Speaker 2:
03:27:53Yeah. Yeah. Yeah.
Speaker 1:
03:27:54Yeah. Need a whole calendar for these things.
Speaker 2:
03:27:57Yeah. Amazing. Well, thank you both for for making time to come on. It's really great to And congratulations on all the progress. Congratulations.
Speaker 2:
03:28:04We'll do it again soon.
Speaker 8:
03:28:04You. Thanks for having Talk
Speaker 1:
03:28:05to you soon. Cheers. All
Speaker 2:
03:28:07right. Have fun, Yeah.
Speaker 1:
03:28:09The interesting thing is
Speaker 2:
03:28:09They are cooking.
Speaker 1:
03:28:10They are cooking. I mean, yeah, they delivered in a bunch of different ways. I mean, obviously, like, you know, what, like tech Twitter is not real life in many ways. And you see that with the Gemini Maos and DAOs and just five star ratings and stuff. But I mean, saw it with the video I generated, like the models are really, really good.
Speaker 2:
03:28:32They're really
Speaker 1:
03:28:33They're performing really well.
Speaker 2:
03:28:34I feel like Google has been, so much chatter on Twitter of people making fun of, oh, I was in Gmail and I asked it to do this.
Speaker 1:
03:28:42Yeah, some of products are misses for sure.
Speaker 2:
03:28:44Yeah, but clearly they're aware of deficiencies and like rapidly shipping on a bunch of different dimensions. Yep. And that, you know, the energy they even are bringing to this call and the fact that they're going, even just going direct.
Speaker 1:
03:29:03Think the really interesting thing is like Super bullish. Mark Andreessen had that quote about like Chat, OpenAI is becoming Google, Google's becoming OpenAI. You remember this? He said this to us. And I think his take was that like, know, OpenAI is becoming a consumer tech company and Google's most advanced in research.
Speaker 1:
03:29:24And I think that's going back to the Yahoo question we were talking about is like if they're using like they invented the transformer. Right? And so if there is a new architecture and it does come out of like an academic lab, it's totally possible it comes out of DeepMind again, right? Like they did invent the transformer there and Ilya just kind of picked up the paper and was like, this is amazing. We need to implement this and go really hard at this.
Speaker 1:
03:29:47And then everyone did. Yeah. But it would be very interesting to see, like we didn't even get to the diffusion language model, but what other foundational innovations they're trying? Because they've been ahead of the curve on getting bigger context windows, faster inference on that Pareto frontier. And if there's a new paradigm and they implement it quickly, like, that could be an entirely new thing.
Speaker 1:
03:30:12Very interesting.
Speaker 2:
03:30:13Yeah. Overall, Google has been so successful for so long and so dominant that I think that it creates this effect where people almost want them to lose
Speaker 1:
03:30:22Of course.
Speaker 2:
03:30:23Or want them to, you know, get taken down a notch in some way.
Speaker 1:
03:30:26But they're going go through us because we will take a bullet for Big Tech.
Speaker 2:
03:30:30We will. We We would. We will. We won't.
Speaker 1:
03:30:35Won't because we won't have to because you will never challenge the supremacy
Speaker 2:
03:30:38of Big is one of the greatest high technology companies in history It's true. And it deserves to be celebrated. I I we need to just put this phrase to bed, but founder mode Yeah. Like Google feels like at an individual level Mhmm. People are, you know Yeah.
Speaker 2:
03:30:55Taking, you know, massive autonomy and and really have a lot of momentum. And even I'm I'm on jewels.google.com right now.
Speaker 7:
03:31:01Yeah.
Speaker 2:
03:31:02And they're rate limited, but it looks and feels like the product that a startup would create.
Speaker 1:
03:31:08It's good.
Speaker 2:
03:31:09It looks like they just raised like 300 on a billion.
Speaker 1:
03:31:13They probably did
Speaker 2:
03:31:13from Internally. Internally. Internally. Well, anyways, we should get out of here. Did get some extra context on the Coinbase Oh, yeah?
Speaker 2:
03:31:24Issue. A friend Not a of the show said, re Coinbase hack. He was sending it live while we're in that. He said the information that isn't the customer data is sold at a granular level, I e info on the individual. So it'll go on a dark web market and be sold individually based on the Bitcoin balance of the individual.
Speaker 2:
03:31:45Think of it like a standard three tier regular silver and gold would be a balance over 50 k. Mhmm. And these accounts are already vulnerable to like sim swapping and things like that. Yeah. So anyways, appreciate the intel.
Speaker 2:
03:32:01The lone ranger shot that over to us.
Speaker 1:
03:32:04Very helpful.
Speaker 2:
03:32:05But
Speaker 1:
03:32:06Anyways to Tyler Cowen, a friend of the show who's made the Time Magazine list of the 100 most influential people in philanthropy. So congratulations to Tyler Cowen. And we will see you tomorrow.
Speaker 2:
03:32:21We'll see you tomorrow, folks.
Speaker 1:
03:32:22To your day. We'll see you on Wednesday.
Speaker 2:
03:32:24Fun show. Bye.
