TBPN - Deel–Rippling Update, Microsoft Bets on Agents | Shawn “swyx” Wang, Augustus Doricko, Brad Porter, Kian Sadeghi, Kathleen McMahon, Chungin “Roy” Lee

Episode Date: June 4, 2025

(03:02) - Deel-Rippling Drama (09:58) - Microsoft Bets on Agents to Fuel AI Growth (30:43) - Snowflake Buying Crunchy Data for $250M (45:57) - Augustus Doricko. Augustus is the founder and CEO of Rainmaker, a California-based startup using drones and advanced modeling to modernize cloud seeding and address water scarcity in the American West. A former UC Berkeley physics student and Thiel Fellow, he previously co-founded Terra Seco, a company that automates groundwater compliance. Doricko integrates his Christian faith with a mission to "terraform" arid regions, aiming to revitalize agriculture and infrastructure through scalable weather modification. (01:00:46) - Brad Porter. Brad is the founder and CEO of Collaborative Robotics (Cobot), a startup building AI-powered collaborative robots designed to work safely and intuitively alongside humans in sectors like logistics, healthcare, and manufacturing. Before founding Cobot in 2022, Porter served as VP and Distinguished Engineer at Amazon Robotics, where he led the deployment of over 500,000 robots across global fulfillment centers. Cobot's first robot, Proxie, launched in late 2024 and is already in use by companies like Maersk, Mayo Clinic, and Moderna. (01:18:04) - Kian Sadeghi. Kian is the founder and CEO of Nucleus Genomics, a consumer health platform offering whole-genome sequencing and polygenic risk scores for over 800 conditions, aiming to make personalized medicine accessible to all. Motivated by a cousin's sudden death from a suspected genetic disorder, he left the University of Pennsylvania in 2020 to start Nucleus from his bedroom, later securing $32 million in funding from investors like Founders Fund and Seven Seven Six. In 2025, Nucleus launched a service analyzing embryos for disease and longevity risk, sparking ethical debates about the future of reproductive genetics. (01:32:03) - Kathleen McMahon. Kathleen is the Head of Life Sciences at Palantir Technologies, where she leads product strategy, customer operations, and business development for the pharmaceutical and biotech sectors. Under her leadership, Palantir's Foundry platform has been instrumental in supporting organizations such as the National Institutes of Health and the UK's National Health Service in areas including clinical research, vaccine distribution, and biomanufacturing. McMahon has also co-founded a stealth startup focused on AI and platform technologies. (01:48:06) - Chungin “Roy” Lee. Roy is the co-founder and CEO of Cluely, a San Francisco-based startup that offers an AI tool designed to assist users during tasks like job interviews, exams, and sales calls. Originally developed as "Interview Coder" while Lee was a student at Columbia University, the tool led to his suspension and eventual departure from the university. Despite the controversy, Cluely has raised $5.3 million in seed funding and reports over $3 million in annual recurring revenue. (02:09:59) - Shawn “swyx” Wang. Shawn is the founder of Smol.ai and editor of Latent Space, a newsletter and podcast exploring the rise of the AI engineer. After transitioning from a finance career, he led developer experience at AWS, Netlify, Temporal, and Airbyte, and authored The Coding Career Handbook to guide developers in career growth. Wang is known for his “Learn in Public” philosophy and for organizing the AI Engineer Summit, fostering a global community of applied AI practitioners. TBPN.com is made possible by: Ramp - https://ramp.comFigma - https://figma.comVanta - https://vanta.comLinear - https://linear.appEight Sleep - https://eightsleep.com/tbpnWander - https://wander.com/tbpnPublic - https://public.comAdQuick - https://adquick.comBezel - https://getbezel.com Numeral - https://www.numeralhq.comPolymarket - https://polymarket.comAttio - https://attio.comFollow TBPN: https://TBPN.comhttps://x.com/tbpnhttps://open.spotify.com/show/2L6WMqY3GUPCGBD0dX6p00?si=674252d53acf4231https://podcasts.apple.com/us/podcast/technology-brothers/id1772360235https://youtube.com/@technologybrotherspod?si=lpk53xTE9WBEcIjV

You're watching TVPN. Today is Wednesday, June 4th, 2025. We are live from the TBPN Ultradome, the Temple of Technology, the Fortress of Finance, the Capital of Capital. We have a great show for you today, folks. A story that we've been covering for months now is continuing to develop and is now in the pink pages of the Financial Times. This is the Rippling Deal drama.

It continues. and in their briefing section it says Silicon Valley spy drama a feud between two startups over alleged corporate espionage rare case where the drama does not involve the media actually

a feud between two startups over alleged corporate espionage has taken a new twist after a 12 billion dollar HR software group deal claimed that rival Rippling had directed one of its staff to pilfer its assets. So they're going back and forth. And today, Deal's firing back. Now, I heard

a little bit about this story. We kind of, the rumor mill was, was churning over this idea that, you know, Deal had something up their sleeve and they were going to fire back. Of course, that's the way these things go as the, as, as these, you know, battles evolve. The interesting thing, there's a couple interesting things in here, is that the, the, the, the, the, the, the, the, the, the, The Rippling allegations resulted in a lawsuit and ultimately, I think, criminal charges. So Rippling alleged earlier this year that a staff member at Deal had been spying on behalf of Deal. This is, of course, that send that watch to London moment.

Send that watch to London. The employee watched themselves. I'm actually disappointed, John, that is such an incredible line in Silicon Valley history. I'm sad that people don't use it more. It really failed to break through. Yeah. Yeah, it's, you know, we were discussing this earlier about this is like the most dramatic story in, of the year in Silicon Valley. And yet I've talked to multiple people in Silicon Valley who have just completely missed it.

Because it's just, it's, it still is just HR, IS, Enterprise, SaaS drama. Those people simply do not care. They just don't. You have to really pay them to care. You have to get some sort of like payout system going like acts to be like, every time you pay attention to this, you know, you're going to get a money. micropayment. Yeah, I mean, they're just, it just doesn't have kind of the, the weight of like Elon, Doge, Tesla, humanoid robots, AI, AGI, AI, AGI, AI, Doom, right? It's just, it's just payroll, after all.

Forget it, Jake. It's just payroll. Uh, well, anyway, uh, in new legal filings seen by the Financial Times deal has countered that Rippling has been actively engaged in a carefully, this is a quote from that, uh, in a carefully co-coordinated espionage campaign through which it infiltrated deals customer platform by fraudulent means and pilfered the company's most valuable proprietary assets what's interesting is that they they they they're stopping short of of naming like a spy right um and so the the the the uh the actual uh approach here deal has sought to dismiss rippling's initial claims of direct corporate espionage and has filed a lawsuit in delaware alleging that this rival is trying to impugn uh deal's reputation

and its latest filings were lodged yesterday as an amendment to that case. It alleges that Brett Alexander Johnson, so when I haven't not met, Ripling's competitive intelligence manager posed as a customer in access details of deals, products, and business practice over the course of six months. Now, what's interesting is that, like, access details of deals, products, and businesses. So this sounds like they were asking customers for what deal was doing, maybe. Instead of, say, going inside of Deal Slack, like there's no allegations that they were inside of Deal's corporate systems,

which is a very distinct line to cross. And so obviously, this story is evolving. And we've invited Alex, the founder of Deal on the show. Would love to get his side of it. Would love to get Parker on as well. But, of course, our worst enemies, the legal compliance teams that enterprise startups are getting. They can figure out some type of settlement agreement that involves a sort of MMA-style paper-view on TVPN.

I was going to say cage match. It's like at a certain point, they'll reach some sort of, you know, end to the story, but I'm sure that will still be bad blood. Totally. So why not solve that in the octagon? Yeah, in the octagon. Yeah, I mean, we've been teased so many times with, oh, is, is Trey going to box, Jason, in Calicanus or is Zuck going to fight Elon? Like this could be maybe third

times the charm here. Yeah, maybe this is the one that gets it done. It's going to happen. Fantastic. In Dubai. Yeah, we'll bring it out to the Gulf of course. To the Gulf of course. For some reason it'll happen in the Gulf. I think just the purses haven't gotten quite big enough, right? Like you see some of these boxing paper views

easily into the nine figures. If we can, you know, position this as non-dilutive funding for these startups, maybe there's some thing to be done. Maybe that would get them over the line of saying, yep, I'll put on the gloves. I'll get in the cage. Yeah. Yeah. I mean, it's been a fascinating story. Obviously, these things move like extremely slowly as they go through the courts. So it feels like, you know, with FTX or Theranos, like we got the bombshell accusations. Then it took like a year or two

to get any sort of, to move past like alleged wrongdoing to actually understanding the scope of what happened. But I'm sure that the courts are working through it and we will be following it the entire time. The lawsuit, this is from TechCrunch, which is turning 20 years old next week. The lawsuit is also full of insults hurled at Rippling's CEO Parker Conrad and mentions his troubles at his previous company's benefits irrelevant, in my opinion. At times, there's nothing wrong with having a couple thrown a couple back in the office. Wait, he had some unfortunate that things happen at Zenefits. Really?

Really? I'm hearing this for the first time. You got the sound effect now. I missed it on the first attempt. At times the complaint ventures into psychoanalysis territory. To understand Conrad is to understand rippling. The suit claims. Man, everyone's chirping.

But, you know, I think this show, we want to be independent. So we're taking the side of KOTU because KOTU is invested in both. Yes. Yes. Let's give it up for... Let's give it up for diversification. Crossover allocators. Yes, just, just heads I win, heads I win tells you, tells you this.

Exactly. That is the real game. Yeah, we've talked about this before. Ultimately, there's hundreds of billions of dollars of payroll market cap, and they can both be big businesses, and hopefully they get over, you know. And maybe this is all a sideshow for what's really going on at ADP. I mean, this all comes down to both companies racing to, develop quantum payroll.

Quantum payroll. For sure. And that's kind of the real story. And then it's just the drama floating up to the surface. Yeah. And so, yeah, they're, they're, they're, um, they're, um, they're, um, they're, um, they're, they're, um, they're, interesting timing too, because wasn't it just yesterday that deal said it had been profitable for years and is generating over one billion in annual revenue?

And so I wonder if there's a sequence of events here where it's like, okay, take a breather, be really silent for a while, then come out with some, some promising news about the financial health of the company, then fire back in the media and in the courts with a with a counter suit. But, you know, unclear. And it doesn't seem like it's quite as aggressive as what Zenefits found or Rippling found. It's certainly not as, it doesn't take you on as much of a journey. It's not a smoking gun.

Yeah, yeah. I mean, the, the tech wrench article here actually says when Y Combinator grad co-tool launched an agentic security platform last month, among other things, sets up honey pots. Its ad was a spoof on how Rippling's corporate spies said he was caught. And so clearly it's become a small meme within Silicon Valley. Anyway, if you want to save time and money and not have any headaches in your back office. Have you noticed, by the way, that when I point at you, it pops up on both cameras.

So I can actually get two hands at one point. Oh, you can. good um there we go anyways go to ramp dot com easy use corporate cards bill payments accounting and a whole lot more all in one place ramp ramp ramp anyway um using ramp is a joy yes it is uh people have said that that you know corporate cards and spend management

platforms are boring yeah but anybody that says that clearly has not use ramp we were we were just pitching ramp too we did a photo shoot you yesterday and we were pitching ramp to our to the photographer telling him hey we never miss a moment we never miss a moment yeah hey those receipts he was he was tagged automatically he was by the end I mean he was convinced by the end I think he was ready to he was ready to switch yeah and you should be too thank you to ramp anyway we have a story here Microsoft bets on agents to fuel next chapter of AI growth yeah so we heard that that quote from satcha Nadella that uh the amount of inference that's happening on Azure has five-axed,

and they're generating, I think, hundreds of billions of tokens at this point. Trillions. Trillions of tokens. It's absolutely massive. So the question is Microsoft's in a perfect place to deploy agents. They have the distribution, but who's actually behind this team? And we said yesterday they already have 70% of the Fortune 500 using co-pilot. Yes.

Which is tough to say what that means, right? evaluate what that usage actually looks like but yeah how would we even do that I mean because it's it's they were obviously very successful with teams right they got teams into everyone and they really did switch over and spike the growth that company in that product at the same time you know Google's been quoting saying that they're using generative AI search results and it's it's kind of it kind of counts but it kind of half counts and you have to like discount it a little bit because It's not a consumer choice to move over to that product.

It just kind of happens naturally. And so it's interesting to dig into Microsoft strategy because they seem to be, the way I heard it described was that Sachi Adela has obviously done a fantastic job as CEO of Microsoft and he's carved out a ton of territory in artificial intelligence. The question is, how much can he hold on to, right? And this isn't to say that like seeding ground,

is a loss necessarily. It could be the strategic move, but there's this question of like, even just to the point of I want to be a leaser, how much CAPEX do I actually want to be spending? Do I want to own the land? You could vertically integrate all the way down in the AI factory, but they're partnering with people.

They're leasing. They also own data centers. And there's a question of do they, you know, Microsoft has an AI research team that at one point was training models. Now they seem to be much more model agnostic. and you saw that with Microsoft build where Sautja highlighted the importance of being able to choose your own model,

which is something you can do on GCP and AWS as well. But Microsoft has really leaned into that, even with intelligent model routing within different open AI and Lama instances and there's lots of different ways that they've plugged in. So let's dig into how they're betting on agents. This is from the information. In March at a Microsoft All Hands meeting,

one of the company's newest executives, J. Parique, laid out a rough vision of Microsoft's path forward in artificial intelligence. AI models made by OpenAI and others were quickly becoming commoditized by more efficient models from DeepSeek and Microsoft's own research arm that performed nearly as well for a fraction of the cost, Parik said. Sitting alongside Chief Executive Officer Satcha Nadella and Chief Technology Officer Kevin Scott, that meant it would soon become easier for companies to build their own AI applications

and that Microsoft could cash in on that growing market by redoubling its efforts to sell them tools for doing so, said Perique. In recent months, Nadella has made similar comments and staff meetings telling employees that Microsoft needs to focus on platform, platform, platform, a refrain, harking back to a speech by Nadella's predecessor, former Steve Balmer from the late 1990s in which he uttered the memorable chant, developers, developers, developers, and if you haven't had a chance to go listen to Steve Balmer's interview on Acquired, it is fantastic. They've been posting a bunch of clips.

I've listened to most of it. He really opens up and it's just an incredible piece of history. It is. It's really fun. There's a clip going up right now where Balmer talks about when he took over as CEO from Bill Gates. And essentially, him and Gates didn't talk for a full year. Wow. Even though Gates said, hey, I want you not just to be a figurehead.

I want you to actually be the CEO. That means I will report to you. You're the boss. But they didn't really, he, the way he described it was like, they just didn't really know how to, how to deal with each other anymore. How to like, how to work together. It's very interesting. Like, like somewhat emotional even.

Wow. Anyway, Nadell is clearly, you know, paying, paying homage to Steve Balmer, but also focusing on this idea of platform, platform, which is similar to developers. Like, he wants developers on top of the platform. But you need, you need to put a little twist on it. I'm actually excited next week at Demo Day with YC. Yeah.

I want to get a sense of how many companies are building on the broader Microsoft platform, Azure, etc. We talked to someone at last demo day who was there handing out tons of credits. Yeah, yeah, yeah, Britain. Yeah, it was kind of a... I'm sure he'll be back there. He runs their startup team. And so, yeah, I mean, I can imagine if the platform is offering a lot of flexibility around these tools, like building on top of that platform lets you switch in and out of different models very quickly,

means you don't have to shift as soon as a new model is going viral. You're just like, okay, I just swap it into my Azure stack. I don't even need to set up billing on a new platform. The comments from Nadella and Parique reflect a subtle but important shift in AI strategy at Microsoft. No big tech company has benefited more from the frenzy around AI than Microsoft, whose 3.44 trillion market capitalization makes it the world's first or second most valuable company depending on the week. NVIDIA took the crown on Tuesday. Wow, let's hear it for NVIDIA.

So so far the bulk of the company's AI revenue has come through its relationship with OpenAI and there's this really interesting Jeffs just unbelievable. It's crazy. He's doing so well. Yeah. So there's a good chart here from the AI bonanza. Most of Microsoft's estimated AI revenue so far has come from its relationship with Open AI, which includes revenue sharing and leasing Azure servers. So they're making about an estimated $10 billion this year from Open AI. And then a three years. billion from other AI sales to bring their total AI revenue to 13 billion, which seems significant given how nascent this industry is. What are the what are the is that revenue that open AI is passing back to them? Yeah. Yeah. Yeah. Yes. So they get so they get a they get a they get a revenue share from from from selling open AI products from from from vending GPT4 as an API. Open AI also is paying Microsoft to to lease Azure servers for training and inference.

And then I believe that they're entitled to a cut of revenue or profits up to that $100 million cap, right? I wouldn't assume has kicked in at all yet. Yeah, me either. I thought it was like net earnings. Yeah. Yeah. But clearly, that's crazy. 10 billion.

Yeah. I mean, it makes sense. Like Open AI is training and the GPUs are on fire and they need to scale. And so, you know, even if they were, even if they had no relationship with Open AI, you would imagine they'd be load balancing across the different hyperscalers and and and trying to soak up GPU capacity wherever they could and so you know if you look at which is just crazy so the numbers Microsoft invested a billion in 2019 two billion in 2021 10 billion in 2020 and then 750 million late last year so and then they're 10 billion then they're generating you know obviously

it's not necessarily super high margin but it's a lot it's a lot I mean the margin of of Azure is not low. It's, you know, over 30%, right? So they are particularly... And they still own half of 49% of Open AI Global LLC. It's amazing. Sacha, it's the best. But again, it's like, you know, he doesn't own it all.

And so as, as Open AI kind of goes more independent, how much can Sacha, like, hold on to in terms of, like, the consumer AI market. If, if the, if the narrative around Open AI as the, what did Ben Thompson call it? Like the unwilling consumer tech company or like the unexpected consumer tech company like if Open AI becomes the next Google

what will that relationship with Microsoft look like? Because they could I mean they're building their own servers with Stargate and so that revenue could go away over the long term even though it seems like they will be partnered for a very long time. Anyway, we'll have to dig into it more. We want to have some Microsoft folks on the show

and I would love to know how Azure is tracking against inference versus training loads, because we didn't get that from Jensen in the NVDI earnings call, but that seems to be an important question that is on everyone's mind. As we hit the GPD 4.5 and the pre-training scaling kind of wall, obviously the hope is that we shift to inference very smoothly, and GPU demand continues to grow and the overall industry grows very quickly, but it's still like an open question.

We don't have a lot of hard data on what's happening there. Anyway, Microsoft is particularly bullish. This is from the information, of course. Microsoft is particularly bullish on a new category of AI applications called agents, which will be able to carry out tasks. This is maintaining a spreadsheet to keep track of unpaid bills or patching websites after outages with minimal human oversights.

Agents are all the rage throughout the tech industry, not just at Microsoft with other enterprise giants like Salesforce Service Now, SAP, rushing similar products to market. The growth of agents could take off with cheaper AI costs leading to the rise of what some executives call the agentic web in which most of the world's computer power

by autonomous AI software. We need to figure out and understand agent force, which is Salesforce's digital labor platform, what adoption actually looks like over there. From my sense is like they're force feeding people where it's like, hey, you like our CRM, you will also enjoy our digital labor platform. And if you don't buy it, you will, you know,

we're just going to charge you more. Yeah, yeah, yeah. There's a lot of these products that are that are seeing, like, rocketed adoption based on, I mean, it's almost like the bull case for some of Google's tools that like V-O-3, you know, we were joking about that post yesterday, that like some of the products are amazing but hard to find. But at least you know that if a Google model is going viral,

it's authentic. Like, people really love it. Versus there, it's rarely just, oh, they just stuffed it in everywhere and like it doesn't really count. Like the numbers don't really count. Because it's like it's pretty hard to go and find these models versus, you know, if Microsoft chooses to, you know, roll out copilot in, in every installation of teams by default, that could, that could trigger a lot of like daily active users. But are they really getting those tools or are those tools just kind of sitting in the background and then. And then companies are going to other more focused, more dedicated startups or businesses for those agentic workflows. Anyway, for Microsoft, taking advantage of the shift toward agents means making new inexpensive models available on Azure.

And as an alternative to larger models, embracing open source protocols that make it easy possible to build agents and launching new products that let customers set up their own custom built agents. Perich said at an event connected to Microsoft's Build Conference, our goal is to build a new stack that allows anyone to build AI-driven applications and agents and orchestrate them. At the center of the shift, is Perique, a former meta-executive who joined the company in October

in an unnamed role. Very cool. Just like, hey, we just want you. Off the org chart. Off the org chart. Just the playbook. In January, he became head of a newly formed unit called Core AI. that unified groups from across the company,

including the company's developer platform GitHub, its internal developer division known as DevDiv, and several teams that previously ported to Azure head, Scott Guthrie, and were focused on and focused on running AI models on cloud. Service Perik now oversees more than 10,000 staffers at Microsoft. Let's see, Eric, for massive org. He's got almost 5% of the org chart reporting to him. He's definitely on the org chart now.

Good luck getting him in the same room. Yeah, you're going to have to rent a basketball stadium to have your staff meeting. I'm sure Satya could arrange that. After this story was published in the Dowland Wednesday, announced another reorganization to staff focused on agents, consolidating executives running LinkedIn, Office 365, and business applications

under executive vice president Rajeshire Jha, whose groups will, those groups will aim to sell out-of-the-box agent applications to customers, while Perix unit focuses on getting companies to build their own agents on Azure. So a little bit of a divide between, what's being vended into the office customers and what is more on the Azure side and enablement of developer workflows on top of Azure. I'm surprised Microsoft hasn't slapped some agents in LinkedIn yet, you know?

I got to. Should be able to have an agent that just replies. That's where Clippy needs to come. Yeah, bring us Clippy. We got to bring back Clippy. I think we can make it happen. We're so ready. He saw you on the show and the entire time.

We'll just be like the bulk case for Clippy. I really think, I really think it could make. Like actually we don't have any questions. Like we really just pitching you. We're just going to be pitching you on. Yeah. I mean,

yeah, Microsoft is one of those brands that's like, it's still cool. But it, but it's not fun. You know, it's a little bit, like serious business and just having a little,

Clippy used to be so much fun. It's cool because it's such a, it's so efficient, behemian, and reliable. Yeah. And it's reinvented itself multiple times. But they also have Xbox, you know.

They like to have some fun. They like to play some Call of Duty. They literally own Call of Duty. Like, that's pretty sad. We need to get a racing simulator here at the new studio. Speaking of games and a golf simulator in the green room to just let, let guests, you know, start to get warmed up. Flight simulator. That's been like a 30-year project.

Anyway, if you're designing for anything really, get on Facebook. Figma.com. Think builder, build faster. Figma helps design and development teams. Build great products together. Go to figma.com to get started. It is the backbone of the show. I want to see if they even put customer logo. Okay, so they do. You're really into the customer logos. I am. I just think people need to understand like the range. Coinbase, dribble, Dropbox, GitHub, Herman Miller, Microsoft, New York Times, One Medical. Racqueton Slack. They got them all. They got them all.

And you should be on Figma 2. Go check them out. Try some of their new products. They are fantastic. Yeah. They are going to be... So this is another quote from Danny Fish, a Janice Henderson investor, portfolio manager who oversees two funds that hold a total of

$800 million in Microsoft stock. He says, there are going to be software companies that are able to embrace and adopt that, and there are going to be software companies that are going to find highly disruptive to their models. Microsoft ability to embrace that will be really important. So you want to offer enough tools to empower the companies, but you also need to allow the flexibility.

So you don't lose companies who migrate off platform because they're just like, I'm going to build everything myself with new, you know, I'm going to vibe code a bunch of agents and I don't need you for anything. You want to have like the full continuum and seems like Microsoft's in a position to kind of like index the market. It will be interesting to see we should start pressing, pressing more of the founders that come on that are building kind of like agentic enterprise workflows and see how they're positioned against Microsoft. Are they seeing Microsoft deal cards go up against them when they're when they're pitching? Or is it like purely additive? Because I feel

like probably for the Fortune 500 you get a very white glove experience with Microsoft and they tell you every product they're working out. But in in more like the SMB self-serve market, it might just be a situation where you, you know, see a viral video or get an intro from an investor and then you start spinning up. Yeah, I really want to get a better sense of what B2B agents are getting, have sticky usage. Yep. I can imagine the, obviously you see it in developer tooling. Seems like it's getting there and legal. Sales, I think, is happening.

But at the points that I notice it are when the person, you know, You know, the agents are sort of messing up and saying, you know, hey, I enjoyed hearing you on X podcast talking about Y subject with Z person. And so like actually saying that. Yeah. I got an email today of somebody that said, I enjoy, Jordy, it was great hearing you on X podcast talking about why this. Wait, wait, but it hadn't populated it? It didn't populate it. Oh, it made a mistake.

That doesn't even feel like an LLM here. hallucination. That feels more like if statement gone wrong. If statement gone wrong. Well, I mean, maybe for the one person that went on a podcast that's just named X to talk about Y. To talk about Y. Because there's Y combinator to talk about, there's probably somebody who goes by the name Z out there, right? It's actually surprising that nobody said drop the combinator. Just Y. Just Y. I mean, that's what happened with the YMCA. They call it just the Y. Yeah. Just the white, go vertical with white combinator. Perique was impressed by the team of Microsoft employees

who developed auto-gen and open source framework for building AI agents and aimed to move more of those employees into his unit, including researchers that were previously within Microsoft's research unit led by Peter Lee, but a Microsoft Research Vice President who oversees generative AI research, pushed back on Perich's attempt to move the researchers to his organization, according to someone who spoke to her.

So the information is kind of digging into like all the internal politics at a 220,000 person organization as you're trying to build a different team, kind of build a green field AI agent strategy. There's obviously a lot of chips moving around the board, a lot of internal resources changing hands, and you want to hold on to your best people.

The internal politics at Microsoft must be staggering, given the scale. I mean, it's like Washington, D.C. in size, so it makes sense. A nation state. Yeah, I mean, 220 people. is 220,000 people is like a small city, like a medium-sized city, actually. Yeah, it's basically the size of Qatar, I think.

Wow. Like the actual residence? Does Microsoft have a 747 yet? They probably should get one. Yeah, they should. I heard a funny thing that apparently the, apparently the Qatar jet was up for sale for like three years. And I think maybe no one, no one wanted to buy it because it had been like so overly retrofitted to be like opulent. We were like,

There's too much gold. There's too much gold. It's flowing. It's hurting the gas mileage. Like this plane is now too heavy. Yeah. So there's 380,000. Okay.

So it's close to quite a bit more. But Microsoft could look to acquire a small nation state to rebrand it as Microsoft. Microsoft land. I mean, it's the ultimate, it's an ultimate out-of-home ad. Just to be on the map. Yeah, yeah, yeah. Well, speaking of out-of-home ads, go to adquick.com. Out-of-home advertising made easy and measurable.

Say goodbye to the headaches of out-of-home advertising. Only AdQquick combines technology, out-of-home expertise, and data to enable efficient, seamless ad buying across the globe. We did a photo shoot yesterday. We're going to be going up on a bellboard, baby. I can't wait for this. I need to ask our photographer. I need to get these ASAP. I'm so excited.

We'll be dropping on the timeline. Stay tuned. And please subscribe to us on Acts. follow the at TVPN on X. I don't know why you would see this and not be subscribed. There are plenty of people. There are actually surprising.

Or something. Maybe you've been, maybe it's like, oh, it's too much content. A, let the algorithm sort it out. But B,

just give us a follow just for a little bit. We're so close to 64,000, which is another doubling. We'll be doing something to celebrate. So thank you. And in other news, Snowflake is buying crunchy data for $250 million.

This is from the Wall Street Journal. The cloud data company aims to attract customers who want to build their own artificial intelligence agents. Let's give it up for a base hit for these investors. Yes, 250. It probably didn't return the investors fund entirely, but it's still a fantastic outcome. Hopefully for the team. And so we got it. We have to do like a database day or get a bunch of start talking to some of these database folks because Snowflake's,

Snowflake, Data Bricks, Pallenteer, they're all making. making serious moves in this space and they're all kind of moving to different layers of the stack. Like data bricks is now more of this like data lake like data unification layer and then Palantir sits on top as like the ontology layer actually understanding how all the different data interacts and so they're kind of playing nice and a snowflake and Palantir used to be kind of comped directly to each other but they've they've diverged in the public markets. but still, you know, Snowflake's like a fantastic and like incredible story of an incubation. It's our Hill Ventures that went massive and IPO and went into the tens of billions of dollars.

Databricks is also up there in the tens of billions of dollars. A lot of people are waiting for them to IPO. And so it's a very interesting dynamic. Now, Databricks bought Neon, a similar database startup in a deal valued for about a billion. Now Snowflake is buying Crunchy Data. Great name. Yeah, Crunchy Data. The naming schemes in the enterprise SaaS, like deep down are just wild and entertaining.

Like Datadog remains one of my favorite startup names of all time. I mean, yeah. It's so funny. Data dog. I mean, you have last YC demo day. We met the founder building Pig. Pig was great too. We got to check in on pig.

We got to check in on pig. I don't exactly remember what they do, but I remember the name. Yeah, yeah. It'll only be a matter of time until we see like the, the, you're now searching Pig AI. And luckily I was able to find it, pig.dev. There we go. An API to launch and automate Windows desktops. Let's hear for Pig. Let's hear for Pig. It's just a great name. I think, you know, if Pig is successful, it will inspire a generation of companies named after animals. Yeah. Monkey, goose. Yeah. Horse.A. We don't have any animal. name companies. Although we do want animals to start sleeping on eight sleeps.

That's something we're pushing for. We think animal testing is going to make a big comeback in the mattress market. Eight sleeps are so comfortable. We're going to have, your dog should be sleeping on eight sleep. How'd you sleep last night? I think I had a rough night. I was up at five on the grind. Let's see. I actually didn't, I didn't get the hours in. You didn't get the hours in? I slept for six hours and 50 minutes. I got an 84. Oh, you spoke to me again. It's so close.

I got six and a half. So close, but so far. Yeah, it happens. It happens to the best of us. Anyway. It's pretty sunny, funny. My son came in our room at probably like 2 a.m. I was half asleep.

But then he just slept like perpendicular. Compendicular to us. Yeah. So he was getting two different temperatures. Like half his body was getting, you know, my wife's temperature, half the other, which had to have been a funny, I mean, just weird, weird experience. But he was sleeping well. He was a sound asleep when I left.

Yeah, yeah. I remember showing my son the eight sleep half. And I just had. You know how you can see like the left side and the right side and like what the temperatures are? Yeah. And he was like, and me for the center. And we're like, no. They don't make that yet.

Also, go back in your room. Go back in your room. I had to pull up startups named. after animals because there are actually a few male chimp, post gaiter. Mule soft. Post hog. Post hog. Post hog is like pig.

It's the same thing. A hog and a pig. Post hog is one of the greatest things over. Yeah. I mean, it's an iconic. It's like postmodern. Like post hog. Like we are post hog.

We are now in domesticated hogs, which are pigs. So pig in many way is the post-hog. Yeah. I don't even know if they do the same thing. Task rabbit, survey monkey, hippo and It was a big, the zebra. Yeah. Tractive.

Okay. Okay, now we're going. Now we're hallucinating. We're hallucinating. Fat llama? Fat llama? Appear to peer rental platform. Let's go.

Fat llama is a great name. Lunch badger. A cloud service is a man. These are hallucinated. This is not real. No. It's real. It's in a crunch base.

Let's go. I mean, if it's in crunch base, it's. Well, is it in crunchy data? But the thing that stands out about pig is that it doesn't add anything before. for or after. No, no, no. It's like ramp. Yeah.

Or like Vanta, automate compliance, manage risk, prove trust. Continuously, Vanta's trust management platform takes the manual work out of your security and compliance process and replaces it with continuous automation, whether you're pursuing your first framework or managing a complex program. Back to Crunchy Data. Crunchy data has roughly 100 employees scaled pretty quickly. They'll join the company once the deal closes, which is expected to close in the next couple weeks.

Crunchy Data will be part of an offering called Snowflake Postgres. The vision here is that Snowflake Postgres will simplify how developers build scale, build, deploy, and scale agents and apps. Very relevant to that Microsoft story we were talking about earlier. With that in mind, it was important to acquire a company that was not just engineering and quick experimentation. Crunchy Data is a cloud-based database provider that helps large businesses and government agencies use Postgres without needing to manage infrastructure themselves.

I've used Postgres before. There are some offerings. It's crazy. I didn't realize Crunchy Data was founded in 2012. Well, overnight success. Overnight success. You love to see it. Congrats on the $250 million sale.

How much did they raise, I wonder? I'll find out. There's a couple other deals. Snowflakes offers a platform for storing, organizing, and analyzing data across multiple cloud providers, including AWS, Azure and Google Cloud. The company, which went public in 2020, grew rapidly during the pandemic as more companies migrated their data to cloud storage from on-premise data warehouses, which is, it's crazy that we're still in like the cloud migration era from on-prem data warehouses.

The cloud data has existed for a decade and still happening. And if the AI rollout is any similar or if it tracks similarly, it's like we can be talking about agents for the next decade and just continually rolling these products out in a very, very slow takeoff scenario. Crunchy data only raised 14 million. Wow, there we go. Very efficient. Very efficient.

Well, speaking of other efficient businesses, there's a story from our friend Chris Best in the information. He says Apple's app store changes, quote, have been fantastic. And this is why I wanted to highlight the efficiency. He said substack was accidentally cash flow positive in the first quarter of this year. Fantastic. Growth has been translated to revenue. Best said the customer. company, which was founded in 2017, was accidentally cash flow positive during the first quarter of

2025. That said, substack is not focused on profitability right now. He said, as it hopes to continue investing in growth. Said that substack apps, users are heavily in the U.S. where Apple has been ordered by federal court in Northern California to allow Apple owners to offer users alternative payment mechanisms allowing Apple to, allowing apps to bypass Apple's 15 to 30% fee for in-app purchases. had Apple been taking

yes if you went in the app and then you subscribe to a substack and you use the in-app payments flow they would take 30% of that on an ongoing basis I didn't even know that was possible I've never signed up for a substack in yep yep

that's crazy because this this yeah I mean it's a digital product right and so it is it well it's interesting because audible has found a way to get a found this by credits and stuff. Credit system, which is just so annoying. Yeah, I think that that's a bigger negotiation

because it's Amazon. Yeah. And I think, I think, I think Apple had more leverage over substack, but we should have Chris back on the show and ask about how it actually works. But yeah, I mean, if you're, I feel like most substack users would be actually fine going through a web flow. Yeah. It's not as much of like an impulse purchase.

You really, you know, you're, you have a relationship with the substacker that you're subscribing to. You kind of understand. And there's, And it's pretty easy to message. I feel like the average substack user probably understands a little bit more about the Apple App Store tax. There are also desktop respectors. Exactly. There's a lot of corporate athletes.

Corporate athletes. You know, people that are sitting in front of their computer all day long. Yep. And what better place to buy things than the computer? Buying things on the computer is really historically and still today. Just a fantastic experience. It's fantastic. Especially when you have your sales tax automated with numeral.

That's right. Numeral HQ, put your sales tax on autopilot. Spend less than five minutes per month on sales tax compliance. You know, you may be able to avoid the Apple tax, but you will not be able to... Not this one. Avoid state sales tax on software and consumer goods. Sales tax, AGI. Yes.

Anyway, sub tax now has more than 50 creators who are making millions of dollars per year on the platform. Best said, the platform overall has more than 50 million... five million paid subscribers. Yeah, Subsack is such a... I didn't realize they raised so much, but that's great that they're profitable. Yes, I mean,

uh, I, I think this is such a great story where they, this is a business that, that raised ahead of where they were. Sure. And then a lot of people wrote them off. Yep,

because they were like, wait, this is just a media business with a take, you know, a take rate and, and all the stuff and, and what Chris has been able to do, over the past year, you know, when we had them on the show, I was, I was kind of asking, you know,

has it felt like Substack has broken through really into culture, becoming like a real brand itself outside of, you know, Twitter, right? Because they basically got, like, Elon came for them hard. Totally. And that was like somewhat warranted because they launched like a competitive product. I thought the competitive product happened like as a response to the link band. I thought that was the sequence of events. It was, It was links being getting deprioritized somewhat and then Substack launching a post competitor, which I don't even know if I don't even know if I agree that that was like the right move. I haven't really played with that product.

Well, they, you know, it seems obvious that X was going to ban links. Yep. Either way. Yeah. That hurt Substack. Yeah. It hurt the writers on Substack. Sure.

And was the right decision for for X. Yeah. but but yeah so there was a link suppression and then and then and then and then and then Substack Lamesh one of the co-founders called Elon Musk a propagandist with more conflicts of interest than El Chapo but ultimately interesting I had never I never I never picked this up what apparently Musk had had made some type of proposal to buy substack in 2023. Yep, but probably after that they restricted links.

Yep. And Twitter formerly had bought another publishing platform. Yeah. I don't remember the name, but they rolled that in. And then I think they closed it down. And now you just have the ability to write pretty long posts. You can post articles, X articles, directly on X. And I think that it's weird because we have yet to

see, like we are an example of, uh, of a media business or a show that just said, we will play the game by Elon's rules on X. So we, we, we don't, we don't think about links at all. We think about what are the, what are the products that X loves? Text posts, memes, images, video uploads, live streams. And we do those very, very well. And that's what we focus on and we don't so so we're not intention we're like leaning into what the platform loves yeah we should actually consider doing articles on X the question is what would it look like if you tried to build a sub stack like business like you're you're just a writer and your output is articles and well use X's subscription

tools and the articles feed to have that experience of one free article a week and then one paid a week and you try and build up the book of subscription business on your ex account. I've seen some people that have subscriptions turn on. I think I actually technically have subscriptions turned on. I think only Gary Tan is like the one who subscribes me. Shout on Gary Tan. Thank you.

It just like throws me a couple of things. Yeah. Ultimately, the thing what's interesting about substack is they were, you know, effectively benefited from ZERP in terms of access and capital. And people started to write them off because I don't think, I think at times their growth was not best in class. They were just sort of chugging along. and if he had originally had this idea of,

hey, we're going to build this publishing platform that's going to allow independent, you know, sort of citizen journalism and writing to flourish. And then we're going to launch this sort of social network with streaming and all this stuff. That at certain times would have been hard to believe, but they actually have executed that to a T.

And now when you go on substack, it does feel like a social network, you know, based on email as a sort of backbone. So I'm excited to follow their progress more and eventually get really set up on substack ourselves. Yeah. So next up, we have Augustus DeRico coming in. There's an article in semaphore today.

China boosts use of cloud seeding to combat droughts. And we wanted to have him come in and break it down for us. The headline is China stepped up cloud seating in the face of severe drought. the country's grain growing regions in the north have been parched for months leading to concerns over the harvest. Though some scientists are skeptical over cloud seedings effectiveness and environmental impact, several countries have begun deploying it. China is already the world's leading user of weather modification firing chemical compounds into clouds to spark precipitation and has conducted more, conducted 20% more than by this time last year, apparently causing a one-third

increase in rainfall. That seems pretty significant. So let's bring in Augustus DeRico and have him break it down for us. How you doing Augustus? Good to hear from you. I don't know. That sounds like the cruise ship or something. Yeah. Yeah. Welcome. That's the sound that that August that's in Augustus wake, you know. Yeah. I think so. It's great to have you. Yeah. Thanks, man. That and size gongs. That and size gongs. Update soon. Wait. You got to listen to this one. Journalists on the horizon. Stand by. Great.

Who was the guy that was responsible for posting the state, try to stay focused on the mission GIF a while back when I got that text. I got like a hard eyes text about like, oh, I liked your appearance on TVPN. Good social media intern there. Yeah, yeah, yeah. Yeah, the team's grown over here. We got a good crew coming together. There's vibe coding happening over in that part of the studio.

There's a lot of production stuff going on. It's been a fun time. Sweet. Yeah, bring it down. I'm here to ring the alarm bell. Totally transparently, there are really big problems on the horizon, both with China's domestic weather modification program and then their international one. The article that you read or that you're referencing talks about how China is actively retrofitting their wing long twos, right?

Talk about like nominative determinism. Cool name for a drone. But it is the essentially Chinese equivalent of the MQ9 Reaper. and they're using it for cloud seeding and weather modification operations all across the country. A lot of that is to fill up the snowpack in Tibet and then use that as a natural water tower for runoff for all of their urban, industrial, agricultural, and environmental assets in China. So that's that unto itself is insane. To re contextualize people, the Chinese Meteorological Administration has about a $300 million

budget for weather modification. They have 38,000 employees exclusively working on weather modification. and they have two universities that offer bachelor's degrees in weather engineering, not meteorology, not atmospheric science, specifically engineering the weather. So they are driving extraordinarily hard on this domestically just for their own water supply, just to green deserts, just to keep their cities and industry humming. The problem is the international implications of this, right? We are in a, and like I critique people all the time for saber rattling with China needlessly, but the Wingwong 2 has been sold and is being operated in countries across the world,

namely Saudi Arabia and Egypt for defense applications, right? So that has its problems for defense, but also for weather modification. The CMA has explicitly said they want to export cloud seeding as a means of soft power to control water supply and weather across the world. They already collaborate very closely with the Thai Royal Rainmaking Department, and they can easily retrofit these drones that they've sold. for defense applications. The Royal Rainmaking Department. Wow. Great name. Great name. But they can easily retrofit these drones for weather mod as well across the world and then not only control the

shipping and receiving and the ports, not just the energy infrastructure, nice, but also the water supply and weather. And President Lyndon B. Johnson said, whoever controls the weather controls the world. And right now we're trending towards a world where China controls the weather and subsequently the world. And it's really rainmaker technology corporation representing the United States against the CMA. So President Donald Trump, if you can hear us, Secretary Rubio, if you can hear us, the State Department should be involved in this soft power conflict on weather modification internationally. How are you thinking about the current pitch for weather modification? Because it feels like this news out of China has a few different hooks, as well

as agriculture and drinking water, much of China is reliant on hydro power for electricity. Sichuan in the southwest gets 80% of its power from dams, meaning that droughts can lead to electricity shortages. I mean, I know we have the Hoover Dam, but is hydroelectric power important in America? Obviously, power is top of mind for everyone, but in America it feels like the narrative has shifted to nuclear and solar. But is there a world where we could be getting more out of our existing hydroelectric assets and there's maybe a narrative there or not? A hundred percent, right? Nuclear is awesome.

And I'm super excited for Ballartomics to turn a thousand reactors online and their gigacites and produce the world's energy. But it's going to take at least a year for that to start. And it'll probably take years longer still until that's our main form of stable base load. Solar is great, but we have nighttime still. And Reflect Orbital hasn't solved for that problem. So we need stable baseload and we need clean baseload. And hydroelectric power across hundreds of dams in the American West produces hundreds of gigawatt hours.

And we can refill our own dams to increase more stable, clean baseload with cloud seeding. Where these dams are drying up right now, we can increase supply. You know, 80% of, you mentioned Sichuan, 80% of Columbia's power comes from hydroelectric as well. And they're going through a drought right now. And so they have rolling blackouts because there's not enough power there. Both domestically, for our own energy production, we could use cloud seating to breathe. more hydroelectric. And then internationally, again, as a means of collaborating with other countries, let's call it, and ensuring that, like, they have American interests in mind,

we can produce more water and hydro for them. Can you talk about the Chinese approach to cloud seating versus what you're doing in the American approach? I feel like a lot of times when we see a competitive dynamic emerge between China and America, there's only a small tweak between the way Instagram Reels are served versus TikTok or, you know, DJI drones versus GoPros. It's usually just the scale and efficiency and reliability of Chinese technology, but there isn't usually that much of a shift in the underlying strategy. Are they using the same chemicals? Do you think we should be using different chemicals from their mix?

Are they using different drones or are they shelling this stuff into the, into the atmosphere with Howitzers? Like, is there anything that we can learn that might not be IP protected that we could safely port back? Is there anything that we should change based on what we're hearing from over there? China is throwing the kitchen sink at weather modification research. So they're doing drone-based aerial cloud seating. They're doing ground generator-based cloud seating. They're doing acoustic cloud seeding research, meaning they have these huge 130 decibel speaker systems where they just blasted up clouds. They put them all in Tibet.

So even though it's like destroying the ears of Tibetan villagers, they're trying to shake water out of the clouds. So that they have a bunch of other photonic stuff. They're doing a ton of research, but really the big and important aspect of this is their sophisticated military retrofit of drones for long endurance missions, their radar research for detecting phase change in cloud. And then lastly, I think the thing that they have like the most serious. edge on the United States and anybody else in the world then is their ice nucleation agent and their particulate. They're doing a bunch of nanoparticle design.

So super, super small scale particle coating is titanium dioxide on top of these salt crystals, among other things that are way more efficient at nucleating ice and subsequently creating snow or condensing stuff in cloud. Raymakers doing research into that right now, but that's where China far and away has the biggest lead on the nanoparticles that they're using. using. How about your challenges at home with various states and regulators? What's the update there? So 31 states proposed legislation to ban all forms of weather modification this year. Almost all of them dropped that legislation because one. Because of you? Because of you? Was it? Did you? Me and the

Rainmaker team did a lot of work around state capitals. I've got like a regular barbershop in Tallahassee and a few other state capitals to tune the mull it up before I testify. But the one state that did ban it was Florida. Florida made weather modification a class two felony. So if I were to work there, I'd go to prison for five years. And that, I think, unto itself, is not the huge problem. Fine. Sure, you're depriving Floridian cattle ranchers and orchards from having as much water as they want, and they do have wildfires and droughts. So it hurts the state of Florida. But the real problem is the canary and the coal mine in terms of American political sentiment,

particularly Republican political sentiment, right? There's this whole conversation around the tech right and who is pro-innovation and who is not, is the Trump administration pro-innovation? Seems so for the most part. But unless we have clear federal regulation on weather modification and a public stance in favor of this, then we're going to lose control of the weather to China. What about desalination? It's something that we were doing in America.

We kind of fell off. It feels like the nuclear story. And it just feels like I'm going to hear a story in the next few years of like, oh, yeah, China just figured it out. And now they have like a bunch of desalination plants. And we're behind on that too. Are you tracking it at all? So desalination is largely held up by the California Coastal Commission.

And then like HOA is basically that block the construction of desal. An interesting stat that I- Does it smells bad? No, just because it looks ugly. D-South sounds fine. It's just like a bit, well, it looks, I should say. It looks industrial, right? It looks like a big, beautiful oil refinery, which I have to be in Montana, personally.

But, you know, folks in Newport Beach, less so. DeSalle is great. And if we come up with some really sophisticated new reverse osmosis membranes or catalytic desalination methods with good electrical engineering. We can make it more efficient. But the problem with desal still is that we have to move that water from the coasts. Like it's a non-starter for Nevada or Colorado or Utah to get desalinated water. What you can do, though, is cloud seed obviously, right? You can produce water anywhere where there are clouds with our tech. Yeah, I remember Blake Masters was saying when he was running in Arizona, he was saying,

like the future of California is nuclear power desal, and then we need to reroute the Colorado River to hydrate the inner states. Is there a world where you could build? I mean, you mentioned it looks like an oil and gas refinery. Can you build like an offshore oil rig essentially? Or is it just like it's not economically dense enough? Water is not the same as oil, so you're not going to be able to pay to put it on a truck and then bring it in. It just doesn't make sense to do it that way. Yeah, exactly. It must flow. I was talking to some commodities traders the other day and I was trying to like come up with some crazy derivatives for water.

Water. But like, you know, it's it's it's it's sense for a barrel, right? And it's just as it's almost as heavy as oil. So you can't convey this. You know, 13% of all of the electricity in California is used just moving water around. What? That's crazy. Wow.

Yeah, like the central valley exists just because we pump all of that. stuff from the Sacramento, Delta, and American River down into the valley and elsewhere. Like, there's this huge, huge unknown problem, which is like, because we don't have enough water, we have to dedicate so much of our energy resources just to moving it around where we could just be producing it in the Ceras. That's what rainmaker's doing. Interesting. Anything else you're tracking from China?

So I guess one thing that I will say in terms of like this soft conflict is we had a customer meeting in the Middle East. And a day before we had the scheduled meeting, they said, hey, sorry, we have to go to a last minute trip to China to go talk about the Winglong 2. So we're trying to qualify Rainmakers' vehicles in the Middle East right now so that we are clearly at parity with their system capabilities and then can be selected over the Chinese. Yeah, the challenge, if you look at the precedent for sort of state-backed companies out of China, they're willing to sell out a loss for years. And so, you know, I have no insight into whether they would try to attempt that in cloud seating, but it wouldn't exactly be surprising, which I'm sure is a competitive dynamic that you're thinking about. Every single international office that we go into to talk about our work, we see a stack this high.

of purchase orders from China and then one that's like two pages thin that that's that's from American companies so yeah it's absolutely a problem wow part of this article highlights this idea that grain growing regions in China have been parched this month for or four months are we in a particular like global drought is this unique to China are we experiencing drought in America like what is the state of drought Generally, you mentioned that there are different pockets around the globe, but is this particularly bad year? The trend lines bad overall? Or, I mean, we saw the fires and that felt, it felt very visceral in California and Los Angeles, but you never really know when you zoom out where we are on the trend line.

So we had out of distribution high amounts of precipitation this past year in California. In California. Yeah. And even still, we had the wildfires, right? You know, the thing that I think is a good reference point is the California Department of Natural Resources water supply strategy. They explicitly plan for half a million to a million acres of farmland in the Central Valley to turn into desert in the next five years just because there's not enough water. So even when we have boom years and the reservoirs are all full and there's tons of snowpack and everybody gets to go skiing in Tahoe, there's not enough water for current demand. And that's in part just because population is growing, right?

Like we built the Central Valley water project to turn the Central Valley from a desert and swamp into the most productive agricultural region in the world. And we wouldn't have the U.S. population that we do now if it weren't for that water project. And so we just need to produce more if we want to maintain agricultural and economic growth. Makes a ton of sense. Well, good luck out there. We hope you can strike some big deals on the back of this news. You know, we've got to be competitive. Thank you for fighting on America's behalf.

We'll talk you soon. Come back soon. Later. Cheers. See you. Bye. Next time, we have Brad from Cobot coming in the studio talking about collaborative robots. I'm very interested to talk about the SIM to Real Gap, which we covered yesterday.

We will welcome Brad to the studio. How are you doing? Welcome to the show. Thank you for joining. What's new? Oh, fantastic outfit. There we go. Welcome to the show.

Amazing. Looking great. What's the occasion? First, introduce yourself. please, but explain why the fantastic outfit today. Are you doing real work? Yeah. That's right.

Yeah, hi, I'm Brad Porter. I'm founder and CEO of Collaborative Robotics. Yeah, this is how you tell whether a robotic company is really in production or in the field, if they're wearing their safety vets. And I was at our deployment with Mariske yesterday. And so had this handy and thought, there we go. I'd bring it out for you guys.

Yeah, so I mean, to the degree that you can talk about it, what exactly are you doing for Maersk? That sounds like important work. Yeah, we're helping them in, in transload operations, in moving, in unloading ocean freight containers and loading out onto tractor trailers. The, you know, they load carts, industrial carts, full of kind of up to 1,500 pounds worth of generally boxes of product for retailers. And then we help with the moving the carts because moving those heavy carts around all

day long is is pretty, pretty taxing work. And we've got, you said 1,500 pounds. How big is one of those boxes? Like I'm familiar with like a 55 gallon drum. I'm familiar with like a palette of goods that you might see in an Amazon warehouse. How big are we talking? Yeah. So think of this as as the types of boxes and that would,

would flow to a to a retailer, right? To a big box retailer. Sure. And so they're unloading those from ocean containers onto carts that are about three and a half foot wide by about six and a half foot long. And so they just load up as many as they can on the cart and then take it to, you know, usually these are getting dispatched out to big box stores. And so, you know, there might be six tractor trailers that are getting loaded up to go to six

different stores in a region. So we're working in the Sumner, Washington area, so out of Seattle port and helping basically get distribution out to Pacific Northwest. Can you talk about some of the differences about unloading at a port versus what Amazon's Kiva systems does within the warehouse and because some of the different challenges that you face versus what Kiva's doing? I imagine that there's some learnings that cross over, right? Yeah. So the way you can think about logistics is there's inbound flow, you know, products coming from manufacturers around the world, a lot of it coming from China.

And then that ends up in some distribution warehouse ready for people to buy. So it might end up in your in your local big box retail or you can just go and, you know, buy a fan off the shelf. it ends up in an Amazon warehouse, an Amazon fulfillment center. So the inbound side of that is to unload the ocean containers and then bring it to, you know, some place where it's being stored or bring it, you know, to a retail store or to an Amazon fulfillment center. And then an Amazon fulfillment center, yeah, that Kiva network or now Amazon Robotics, what

they call kind of the Hercules drives, is their storage array. So Amazon will have multiple mezzanine decks of those kiva pods full of all kinds of things that you might buy from Amazon. Literally can have a million different skews in a building. And then when you order it, almost immediately the system knows where, it has lots of those and they're stowed across Amazon's network. It quickly calculates where's the most optimal place to deliver this to you. And then a robot goes and gets that shelf and brings it to a picker, brings it to someone who pulls it out of those shelves, puts it into a tote, and then those totes get routed to a pack station, gets packed, thrown,

and then it gets sorted to a truck, and then usually either to FedEx or UPS or Amazon's delivery network or to USPS. Amazon can kind of deliver into any of those outbound delivery networks. And so, so yeah, three phases coming in from the manufacturers, stored and ready to be bought, and then shipped to you. Where are we at in the kind of AI journey of these collaborative robots? I imagine that there's tons of work that can be done with just hard-coded business logic, drive two feet forward, take a left.

And it kind of just is almost like a conveyor belt on on On wheels versus you know the far future where the robot has a brain and is just making completely independent decisions and decides where it goes and problem solves and reasons and and we're on the cusp of that But I imagine that there's a there's a journey that we're going through And so walk me through where we are in terms of that journey Yeah, so we've made a lot of progress from the days where you just like follow the tape line on the floor. Yep. Right.

Now robots can generally sense and perceive and navigate commercial environments autonomously quite well. Usually at human walking speeds, maybe a little faster, but the kind of self-driving problem is reasonably well solved in commercial spaces at those types of speeds. And that's generally done with a LIDAR. And maybe, you know, stereo depth cameras.

And so, you know, LiDAR base slam is how it localizes. And then navigation and planning. And that can be done in a way where it can detect humans, obstacles, navigate around things. And that's the capability our robot has. And it can do that in hospitals, in, you know, ultimately airport, stadiums, in and around people quite safely. That technology works.

What's coming now is you can talk to robots. And the robots will make the high level plan and instruct that where we need to get to is what we can do with our hands, right? Where, you know, like open up your AirPods case and pull up. It's a very complicated set of motions that we do without thinking about it. We don't quite have that capability yet. Got it. Talk to me about the LIDAR supply chain and cost structure in your business. It's been a controversial debate point for a long time in autonomous vehicles.

But if the economic model works, it feels like it's just pure value add. Is the cost of LIDAR getting lower? Are you thinking about solid state LIDAR coming down the pipe or is it already available? Are you banking on a reduction in LIDAR costs over the long term? Or does your business model just by nature of how much value you're adding your fine pay in 50K? paying 50k or something like that if that's the number I don't know yeah LIDARs that are in the kind of they used to be 50k they're in the kind of three to six thousand dollar range right now yeah and so you're right you do have to add enough value you're not going to put that on your Rumba

yeah right but you can put that on an industrial robot and and get a payback obviously we'll want to keep seeing those costs continue to come down but uh but it's not a it's not a prohibitive element for a lot of the work that needs to get done on can you can you talk about form factors broadly and and what guided you you're thinking towards the proxy the initial product and other products in the suite feels like you guys distinctly chose not to do humanoids even though I'm sure various vc thought hey why don't you have you guys thought about doing humanoid seems like a demo have you seen this viral video for Boston dynamics. Yeah. So I'm curious, you know, kind of the decision making that went into the current and pending form factors.

Yeah. So, I mean, as much as like the humanoid hype seems to have been peaked in the last, you know, 12, 18 months, I think Elon did a lot to kind of fan that. Humanoid robots have been around for quite a while. Agility systems have been aptronic. These guys have been at it for a while. And so, so when I was leading robotics, for Amazon, we studied deeply humanoid in 2018. I went through my hype phase on humanoids in 2018. I got really excited about them. What agility was showing at the time and legged mobility looked like it could actually work and it does. And so I had my team at Amazon do a full analysis of everything we weren't gonna automate it another way

where a humanoid could help. And I remember reviewing this paper, there were 40 different use cases where a humanoid could be great, right? And then we looked at all 40 use cases and we said actually to solve these problems, we don't need a humanoid. And in fact, a humanoid's kind of too complicated.

You really want wheels, you kind of want to move more than three and a half miles an hour. And is the number of motors a potential issue too from a degradation standpoint? It's like, you know, we've talked to other robotics founders that say, you know, I'm using robotic arm in my facility and we already have to replace those motors all the time and then a humanoid might have an order of magnitude more and actually be less productive than

some type of robotic arm. So the number of motors really does drive the overall cost. It also drives the complexity of the controls, right? And so you get into a world where you need AI-driven controls. But the problem, the real problem that people don't talk about very much with humanoids is getting strength out of rotational motion is very hard hard, right? You're effectively, because you're just doing a short throw. You don't have the kind of momentum flywheel effect as you get the torques rolling on your electric vehicle, right? You're moving through very short distances. So all the power is basically your electric magnet and then your rare earth magnets. And so you end up needing bigger and bigger motors to get that kind of power.

And so, and then you want to wind them with the absolute highest density you can. And so they end up, And then you want to run them at almost the peak current that you can to get the most strength. So the problem is humanoid robots either have to put this way big motor that doesn't look right in the shoulder. But what they're typically doing is they're hand winding the motors, they're pushing the current to the max, and even then they're getting maybe 60% the strength of humans. And they burn those motors out. So the motors are very expensive and they burn them out very quickly and they're still not

as strong as a human. And so it just, it, we need some breakthrough, you know, the pneumatic, like, you know, Boston Dynamics had that Atlas robot that like could do backflips and everything. Pneumatic is 10x the, the power of an electric, right? And, but you can't, you can't really make that system reliable in production. So do you think there are, you think there are more consumer use cases for the humanoid form factor, maybe around the home? How do you think about applications outside of industrials? You know, I have struggled to find someone, someone mentioned one to me the other day that seemed great, which is like is walking your dog. I think humanoid walking the dog would be would be quite interesting, quite cool. I suppose you could have a quadruf-man's best friend's best friend.

But otherwise I am not bullish. I do think there's some some cool robots recently that are more kind of friendly, look like a kind of playing a game with a kid. Like I think kind of the emotional companion idea is quite interesting. But yeah, getting the strength is tough. I mean, even just thinking about the human arm, like the force that's generated from the human arm is from like the bicep muscle, which is much bigger than the actual joint. And so if you put a motor on that joint, you're not using this.

You know, it's just absolute canons. There is, there is a humanoid company that's trying to create the muscle fiber. and pull that, and that sounds like some of the pneumatic projects, and maybe it'll be a hybrid. In terms of training and AI development, there's been this talk about the SIM to Real Gap. I don't know how closely you've been tracking this, but obviously generating data for robotics has been very difficult,

but now there's this new paper that semi-analysis was talking about yesterday, all about training and simulation, basically Unreal Engine, you build the robot virtually, you have it walk around, learn as much as it, it can in thousands of years of artificial data, then there's going to be a gap between what it experiences in simulation and reality. And so what you do is you take what it's learned in simulation and you run that on a robot in a cage basically wired up with a power cable so that it can run forever. And it tries to do the moves that it learned in simulation. It messes

it up. But then that generates more data that feeds back in. Does that seem like power generation, all the mechanical issues aside, does that seem like an interesting path to go down for actually solving the algorithmic and like the AI piece of understanding how these robots will actually choose what motors to move at what times? And do you have any experience generating data? Just kidding.

I'm just kidding. Former CTO of Scale AI, if anyone listening, that's not familiar. No, that's... So, so the challenge in robotics first is how do you get, I mean, it's the same in large language. Well, what's the pre-training phase, right? How do we get some base level in pre-training in large language models?

It's to kind of understand how words are likely to follow each other, right? Just statistically. So motor actions, what's what's likely to, you know, to cause the arm to move forward and things like that? But the hard part in any AI system are the edge cases at the end when you're interfacing with the real world, right? And, you know, fortunately, we have all this large language model data. We have all this data from the Internet to give us reference examples of what the real world of language looks like, right? And so we refine on that.

and then we use human preference to refine even further, and that's how we get, you know, chat GPT. In the, in the robotics world, data from simulation, data from multiple robots, data from teleoperation, all of these are kind of techniques people are using to feed some data into, you know, what's kind of the pre-trained base model that gets some statistical correlation. But when it comes to learning the edge cases, right? it comes to, hey, that doorknob is higher than this other door knob or the doornob turns upward instead of downward. You, you and I actually self-play to figure that out. We come up to a doorknob that doesn't, it's funny, we have a door at Cobot that you can

either push the handlebar or there's a handle. Well, everyone tries to push the handle, and then the door doesn't open and you have to push the, and so humans get confused too, and we do this kind of refined self-play. I think right now we're very much focused on the pre-training phase, just how do we get enough data to have something that like roughly moves its hand toward the door. Sure. To really solve this problem, though, we've got to learn how to self-play in the real world like you or I do because there's all kinds of novel stuff we're going to run into solving real problems. Well, good luck with that. It sounds like an easy task, but I'm sure you're up to the task.

It's been fantastic talking to you. Yeah, this has been super insightful. Yeah, I mean, it's such an exciting industry because it's really just like we're still just on the early, the early part of the S curve. And there's going to be fantastic advancements. So good luck. The future is going to be amazing. Awesome.

Thank you guys. Appreciate you coming on. We'll talk to you soon. Thanks, Brad. Thanks so much. Talk to you soon. Next up we have Keon from Nucleus coming on with a big announcement. Something like 10 years in the making, close to it, maybe seven years.

We'll bring Keon in. Let's play some soundboard. How you do it. Welcome to the show. That's a great intro. Their tweets are flying. Oh, my God. You guys seeing this?

Yes. You seeing this? See this? Riggi down for us. Explain what's happening. There's nothing like a launch day. I'm trying to figure out, guys, is this? Is this Gattaca or is it there a nose?

Because people can't make up their mind. Oh, yeah. We're going to find out. They're trying to figure it out. What's going on? Let's get some context thought. audience, nucleus has launched nucleus embryo, the world's first genetic optimization software. Basically, parents can give their children the best starting life.

They can pick their embryo based off of physical characteristics like eye color, IQ. They can go to disease risks like cancers or heart disease. Basically, we really believe parents can get old information that exists about their embryos, and they can pick however they want. For me personally, you know, it's been 10 years in the making. The journalist actually covered it today in the Wall Street Journal. Was a journalist that covered my gene editing, you know, where, how to make. in Brooklyn 10 years ago.

Yes. Wow. Overnight success. You know, it's a long time in genetics. Yeah, so break down the state of the art because like embryo screening exists. I think most parents in America, at least if they do the means, do some sort of screening while the embryo is growing. Is this purely for IVF?

Is this just going a layer deeper? And then I want to talk about the regulatory and FDA component as well. Yeah, let's talk about it. So, basically, if you go to an IVF clinic, today, you're a couple. The vast, vast, vast majority of clinics. The first thing I actually understand is that the IVF process is principally controlled today by clinicians or doctors. Honestly, couples don't have as much liberty in our prospective as they should.

It's their baby. It's their embryos. They should have the right to those, that information, and they should pick off any vertical. However, today in the clinic, what generally happens is people test embryos for very rare and severe genetic conditions. For example, like a chromosome abnormality, like Down syndrome, for example. Or even a condition like cystic fibrosis or Tasex or PQU, right? These are conditions that are very rare that maybe someone might have a carrier for cystic fibrosis,

but again, it's pretty rare. Then there are conditions that we've all heard about, things like breast cancer, things like corny artery disease, the things that actually kill the vast majority of people today, right? Chronic conditions kill the vast majority of people today. Those conditions are just not tested for in the clinic, even though we have very good science, actually, that can make those predictions. How do we know this as a DNA company as well? That's what we do, right?

We build models that predicts disease and the way you, test those models in adults. So we go from adults to embryos is actually because we can basically well validate these models to show that they work in both the embryonic context and in the adult context. And so what we're really doing is we're going from, okay, instead of just looking for really severe like down syndrome cystic fibrosis, why not do breast cancer? Why not do heart disease? Why not do colorectal cancer? Why not do schizophrenia? Why do Parkinson's? But then why stop there? And this is really the important thing. Because ultimately, you know, if you think about diseases and traits, the extreme version of any trait is actually a disease, right?

Height is a great example of this. One extreme end is like, you know, John, for example, he's like Marcus syndrome. Then the other end is like me, dwarfism, right? It's like the disease on both ends, okay? So, you know, so, you know, IQ is another example of this. One end is like, you know, autism. The other end, it can actually be some sort of, you know, cognitive basically challenge that people have.

And so when you think about it, when we start realizing that people have drawn a line in the sand saying you can get, you know, rare diseases, you can't get. common diseases, but then they really say you can't, can't get any traits like height, even though the best predictor we have today actually in the world, the best polygenic predictor is for height. So as a company, we've kind of completely reimagined this and said, wait a second, what's going on here? You should have access to the entire stack.

Rare diseases we do, cystic fibrosis, common diseases like breast cancer and also traits all the way up to something like IQ. Yeah, so, I mean, that test, are you just giving people the data? because I imagine that once you get into particular recommendations, that's more of what I'd expect a licensed doctor to need to do. Well, yeah, my sense is that you can allow people to get the data from their doctor and then feed it into nucleus. Is that correct?

So that is correct. And actually, we have a couple, there was like 10 announcements today. You know how we do it. We like to do 10 announcements in one day. We are actually very, very excited to announce a huge partnership with genomic prediction. So genomic prediction is actually the oldest embryo testing, a company that exists. They've done genome-wide tests on embryos for almost a decade at this point. And I think they've done over 120,000 couples for PGTA, which is a specific kind of test.

And so we're actually partnering with them. So we make it very easy for genomic prediction customers to request their files and actually port it over to nucleus. But really, this isn't just for genomic prediction customers. Anyone who's undergoing IVF can go to their clinic and say, I want my embryo's data. You can take that data, you can upload it to nucleus, and then all of a sudden, you know, the application of DNA makes this technology universally accessible. Now, how much of the benefit is actual algorithmic analysis bringing in other data points to contextualize the data versus just better UI and better hydration of existing text?

Because we had a friend on the show who was talking about getting some medical results from a doctor. the doctor's office was closed. It took two days until the doctor was going to be able to interpret the results. He was able to just take a photo, upload it to ChatGPT and say, hey, is this really, really bad? Should I be panicking? Because it seems somewhat out of the range. And ChatGPT was able to say, hey, you still got to talk to the doctor. But this isn't the craziest thing I've ever seen.

This isn't way out of distribution. And so that's almost like a pure UI layer, but extremely valuable. I know it might not be like the right narrative for some people that it's like, not as innovative, but I think that like all that matters at the end of the day is giving people benefits. It's always both. It's always both. You, you have fundamentally technology, just for technology's sake, it's not

siliconized about, right? It's still about making something that people want, okay? And if you can actually use. So you think about the nucleus innovation, it's, it's too prompt, okay? One is in the informatics, right? You know, I've been doing this for five years. Sure. I almost, I would argue to myself that I probably spent too much time, you know, developing

the science, right? Sure. Science in a nutshell, it's not actually very useful. You need to expand access to it. So on that point, we'd, you know, you know, You do multiple different kinds of analyses that make it such that we can actually provide the most comprehensive analyses that exist today. But moreover, and this is really the, I think a key point to your point, John, is people

understand them. People can see them. I mean, you can pull up the platform. I'm not sure if you guys have shown already, but it's very easy to sort, compare your embryos, you can actually name your embryos, you can stack rank your embryos, you can understand what the score means, we lead with overall risk, or we tell you, for example, instead of saying you're in the 99% off for genetic risk for condition, which, you know, what does it mean we say hey you have a 5% chance or the like of let's say schizophrenia or some other

other words by even overall risk people have a much greater intuitive understanding of the results we're communicating to them we have genetic counselors on hand so this really is a what are we shown here we show you we showed you're showing uh yeah yeah yeah we pulled up here so it's another thing that's a fun one that's an easter egg that's an easter egg that's the that's the kind of approach that we're taking here and i think consumers are responding to it right people want to have access to their data the clinician the doctor shouldn't decide what embryo implant you should Okay, so talk to me about what requires FDA approval, obviously new medical devices. Like, if you were developing a machine to take in an embryo and sequence the DNA,

I would expect that the FDA would want an approval for that medical device. But if you are taking data and just showing it to a customer in a different UI, that feels like probably a very light FDA process. And then there's probably a continuum in the middle where once you're making a recommendation, they have rules around that, right? We as a company do not tell you which embryos are implant. Sure. You know, basically parents, the couple has complete agency to decide

how they want to use the information to implant their embryo. Moreover, let's be clear, height, right? I mean, can height analysis be a medical device? You know, that doesn't even make sense, right? IQ height, there's traits, for example. We all, you know, traits are something that I don't think necessarily belongs and even the kind of infrastructure thing about medical care, right? These are things that go beyond medical care.

things like, you know, that people just kind of intuitively know and that there are DNA tests done every single day DTC for these analyses because they're not disease analyses, right? So we do both diseases and traits to be clear. My point is many of these innovations, you have to wonder, like, you know, should the government say if someone can or cannot pick their embryo based off height? That doesn't seem right to me. I think it should be in the complete liberty of the individual to decide that. Yeah, but I mean, we're a democratic country. And so if a huge swath of the population says that the FDA should review that type of test or that type of analysis... It could happen.

I mean, the FDA reviews all sorts of different stuff. And so I guess the question shifts to like, do you expect a change from FDA on the way these analysis tools are regulated? I think right now the most important thing is. just putting these high-quality, rigorous science results in people's hands and then helping them, basically have healthier children, helping them give their child the best start in life. You know,

I think that generally speaking that, that, you know, people should have more liberty, more choice in medicine. I think the broader longevity trend actually touches on that point as well. Yeah. So that's what we're excited to do at Nucleus.

Yeah, I mean, the fact that you're partnering with a company on, on actual, on the actual, like, medical device side, like they are doing the sequencing the embryos like that really takes it out of the Theranos question entirely in my mind I think you feel like you should be beating the drum there a little bit more it's like like we didn't say we created some new device but I don't know we ship that's the difference I know it's live and saw baby don't look at it go use it that's that's that's the evidence

why is there putting okay um I love the visual of John and his wife selecting between embryos and it's like six 10 or seven two tough Well, if we go at the 610, he has, you know, potentially fly commercial once in his life. We can actually play this game right now. Okay. Here, we're going to play a game right now. I'm going to put in the chat.

Okay. Your embryo.com. Okay, everyone listening to this. Pick your embryo.com. I'm going to go to it. Oh my God. Here we go. Little Easter egg here.

Okay, let's see what's more important to John? Intelligence or muscle strength. Come on. Oh, absolutely muscle strength. Let's go. We're the future's bodybuilding. Let's go. Yeah.

John would take a, he would, he would, He would happily have a 5-2 son if he had, you know, top 0.01% bodybuilding genetics. Exactly, yeah. Okay, so which one is the list? Lifespan or height? Come on, lifespan. Lifespan, let's go. Let's go.

Let's go. Maybe low depression. You got to be golden retriever mode. You got to be, uh, you need low depression. You need low depression. You need low. No, C.D. I don't mind bouncing around a bunch.

Okay. Let's go. Risk taking anxiety. Uh, let's go high risk taking. There we go. God, okay. Is this some generate stuff going on? This is great.

Nadia. I got Nadia too. The enduring athlete. Let's go. Physically strong, cautious, built to last. This is great.

Is this driving a lot of attention, a lot of downloads? Is this going viral yet? It seems like something that's designed to be shareable. I think it just dropped it right now. Technology brothers, we got you the exclusive. Let's go.

Let's put it out there. You know, they can pick your embryo. People say, what's it like? Maybe you're not doing IV. Yeah, no problem. It's funny.

Only 9% of people choose Nadi Yeah. Okay. Well, we're contrarian. We like that here. Yeah. That's fun. It's great. Oh, well, well, congratulations on the news. Congratulations on the launch. Yeah, the pace is wild. Last thing, what's going on with, have you seen these just blood billboards? Oh, yeah. They're all over L.A. So, so there's someone who's running a campaign right now, justice for Elizabeth Holmes claiming that Theranos was not the scam. People think it was. And there's a, there's a documentary. coming out and there's billboards all over L.A. for just blood. Like, it's just blood. It's not that big of a deal. And John, just be clear, there's an exclusive on technology where it's next week about from this person, right? They're going to tell their story next week just to make sure you invite them already. I hope we're, we're, we are toying with the idea that someone reached out to kind of connect us. We're thinking about doing it, but we're not, we're not 100% sure that it would be appropriate

for the show. Based on the website, I don't know if it's appropriate. Yeah, it doesn't look like it was designed with Figma. So I don't know. We can't quite do it. It's a little bit. The team definitely doesn't use linear. Yeah, but they claim that Elizabeth Holmes has been proven innocent, and so it's a bold claim. We like to see people making bold claims.

By what jury is my question. The jury of someone who knows HTML. Keon, always a great time. The energy is off the charge. Electric. Thank you for coming on, firing us up. Congratulations on the launch. We will talk to you soon.

Talk soon. Twitter for sure, okay? Yeah, we'll see you there. Bye, guys. Bye. He's going through launch day right now, which is just like, you know, 40 notifications every minute forever. I love it.

Well, next up we have Kathleen from Valthos coming into the studio. Welcome to the stream. How are you doing, Kathleen? Nice to meet you. Good. Thanks for having me on, guys. Nice to meet you. Great to have you.

Would you mind kicking it off with just a little bit of an intro for those who might not know? Yeah, absolutely. So I have been at Palantir for the last seven years. I built our life science practice. there. So taking some of the same platforms that Palantir uses in defense and intelligence and a bunch of industries and then bringing those primitives over to pharma and biotech and researchers who need to study biomedical data in a secure and collaborative way. So really building out end-to-end drug development workflows all the way from early discovery. But then I left a couple months ago

and now I'm working on something new. Very cool. So yeah, happy to chat with you guys. Yeah. Awesome. I wanted to get your immediate reaction and help us kind of contextualized the news that came out yesterday or the day before, which was that two Chinese nationals have been charged by U.S. federal authorities with conspiracy and smuggling after attempting to bring a dangerous biological pathogen, which I'm going to botch the name into the United States. This fungus is classified in scientific literature as a potential agro-terrorism weapon due to its ability to devastate key crops such as wheat, barley, corn, and rice, causing a number of issues there. So I wanted to kind of get a, you know, you don't have to go into too much detail, but kind of a high level background on bioterrorism broadly, kind of maybe some like prominent examples.

And then even just get your immediate reaction to the news, you know, is this kind of thing surprising to you? Or are you surprised that we're not hearing more headlines about it all the time? Yeah, totally. So I think to the second question first, it's like a bad surprise, obviously, but we are absolutely entering this era of an elevated risk of biothrots. So sadly, I don't think it's something that we should be that surprised about. I think this story in particular, and we don't know that many details on the story, so I won't speak too much to it.

But the one, it highlights how easy it is, really, to have any biological material pass across borders, that obviously both natural or unnatural. And then the second is that any kind of agricultural pathogen is also an enormous threat. So I think when people think biodefence and bioterrorism, they think anthrax or smallpox, which is obviously horrible. But the idea that you can introduce a pathogen that would devastate one of our primary crops that would have massive health impact, but it would also completely destabilize our economy

and send us into something far worse than what we would see with COVID. So I do think when we and governments think about biodefense, it's very much both in terms of human health and agricultural help. But to your other question on what's the primer on biodefance, what are we worried about? I think there's always been this. So we've always had the problem that people study the most pathogenic organisms in the world. They usually do it in a biosafety lab, a BSL lab. These are all over the world. Some regions are obviously more secure than others. So there's always this threat of something natural leaking or being used maliciously. But basically two things changed recently. It made that a lot worse. One is that our ability to edit genomes and actually

start changing those pathogens, there's a bunch of new tools to do that. So like things like CRISPR, which you hear about usually in the medical sense of editing a genome are available on pathogens, synthesizing new nucleotides and new DNA to do that with. Also now commercially available, like we could order nucleotides or you could print them out in some cases in a desktop printer. So that made it, now we're dealing with things that nature has never seen. And then in the last couple years with large language models or biosespecific language models, we have this idea of AI uplift. So it means that someone like us, not to underestimate your biological skills, but could actually be coached into how do we use these tools guided all the way into making something that is actually way worse than anything nature has ever seen. And this isn't like science fiction.

Like Anthropic talked last week, I think, about Claude 4. they did internal safety trials. They noticed an uplift that goes way beyond just, oh, it's easier to Google a paper about how to do this. And really into that, allowing a novice to access something dangerous. So they released Cloud 4 with new security standards to try to combat that. But a lot of models aren't like that. Not everyone has those security standards, you know.

Yeah, this has happened like, what is it, Timothy McVey? Looked up how to build the bomb with fertilizer and built, and basically blew up like a massive government building. And the wreckage from that was insane if you think about what it would take a terrorist to work in a biosafety lab. It's obviously very complex, but getting easier as you can have an LLM coach you through the process, essentially, right? Is that roughly the nature of the threat? Yeah, both in terms of the actual steps to take and then what to change about a virus that would make it either evade some kind of countermeasure, which is like some kind of medicine that we have for it, or be more infectious. And I think the real, like, what has a lot of attention in ways on people's minds is that we're not talking about like a state-sponsored nuclear program that you need these like massive budgets and facilities to make something like that.

Like it's a laboratory and a computer. So it's a really different dynamic of threat than what we've been dealing with in the past. And it kind of self-replicates by itself. It's like the whole goal. It's an interesting story to me because obviously over the weekend there was the Ukraine story around. Operation Spider-Web and that was relatively asymmetric and that whatever the cost of the operation,

the trucks and the drones, just even if it was $100 million, which seems really, really high, right? Even if it was taking it, you know, huge teams. It destroyed, you know, a billion plus of assets on the other side. And then when you

talk about bio-warfare and bioterrorism, it's like, okay, one or two people with access to a lab could potentially do billions and billions of dollars of damage. Do you think this is a wake-up call or this will be a wake-up call for the government broadly? How do you expect, you know, what are the different kind of ways in which the United States can defend itself from these types of, you know, obviously this wasn't whatever's being reported isn't a direct tack, but a potential threat

in the future? Yeah. I mean, the good news is DOD here, MOD and the UK, there's a lot of lot of defense organizations already thinking about this and really trying to get ahead of it. It means that we have way more to do, but at least it's on the agenda. And I think it comes down to the best defense would be to prevent this from happening. So putting better safeguards on models, putting really strong regulation on synthesis. So who can synthesize what, how do we track that? That's great. There's actually some legislation in the works on both of those things. But that, that works domestically and it works to contain an accident. But if we're actually talking about international collaboration,

like those kinds of regulations are not really enough. So the way, then we get into thinking, how do you deter something like this to your point? Like, what is the defense against this? And there's really like three pillars that go into it. The first is how quickly can you detect that something happened? So in this case or in future cases, do we immediately know that something new is circulating,

that it's high risk to, us that it maybe will evade any kind of countermeasure that we have. And can we know that before it's an outbreak? And, you know, we're sampling from a hospital. And then that leads into the second one, which is how fast can we design or update a countermeasure? So like an antibody or some kind of biologic to combat that. And that is really like if we can diagnose and develop as fast as possible, then these weapons are much less powerful because you're not talking about billions of damages, you're talking about a couple cases that are quickly contained. And the last part, of course, is attribution. So if you can actually say, where did this come from? Did it come from

nature? Did it come from engineering? Did it, you know, did it come from nation state? That lets you bring the rest of the DOD and the State Department and our allies towards preventing something in the future. And if you can get that cycle down to hours really in terms of detecting, stopping, and then attributing, then you actually have a really robust profile for defense. And there's a bunch of new tech that's going to help make that better. So this is scary, but it also is, there's good news on the horizon, too. Can you talk a little bit about the bio practice at Palantir? I mean, there's been a lot of potentially like misunderstanding or misinformation about

how Palantir works. You know, I think most people who understand the company at this point understand that it is a, it is an ontology platform that is on top of a large database. But I think what I'm struggling with is I understand. if you're using like the Airbus case study, you have a database with all the different parts of the airplane, and then Palantir understands, helps you understand how the different pieces

and the lead times for, you know, this screw and this seatbelt and this engine part fits all together. So if you're demand planning or figuring out how to manufacture airplanes, that's a very helpful tool to understand your supply chain. That makes sense to me in the very concrete widgets business that is airplane manufacturing, although it is obviously very complex.

In the bio or pharmaceutical space, I don't really understand the nature of how large these data sets are. Are we talking about trial data or manufacturing? Is it all of these above? How does all that fit together when you're thinking about applications of understanding large data sets in just the bio world broadly? Yeah, definitely. So some of it is more similar to what you described with Airbus.

We're talking about manufacturing. We're talking about something that's like it's a process with a lot of moving parts, how do you make these all synchronous and update when you need to? There's also obviously biologics manufacturing. Some of it is more in the logistics end, which Palantir also talks about quite a bit. So when you're running a trial, making sure that patients and the medicine that they need are in the right place at the right time with the right support staff, that actually looks pretty similar to coordinating flight routes or staffing a hospital. So those parts are super similar to the rest of Palantir. The part that's probably most unique is when we're actually

talking about that trial data or talking about patient level information. And there it really gets back to some of the core concepts of Palantir is how do you work with multimodal data and see patterns across it? So if we're looking back historically on all trials that we've run and we want to start trying to identify what kind of patients have the best response to this or what are potential side effects, can you start linking together data that's from like a medical record with samples from a lab, with sequencing data if you have it? And can you do that in a little? way that is completely secure, completely auditable, and complies with all the regulation in the space. And that's really the niche, the Pallantir. Maybe it's not always well understood to put

into you, but that is what that platform was built for. Can you talk a little bit more about the, I don't know, like the long-term future of what you're building. I know that you can't go into it too much, but like there are a bunch of different vectors and opportunities around what we're building in bio and what we're trying to prevent. There's almost like a, like, there's a little bit of game theory going on here. So what would you like to see the United States really, really dominate going forward? And where are the biggest opportunities to both increase biosecurity and then also help accelerate the developments that we need, the good stuff?

And that is what I'm most excited about, all of these technologies that are really scary when we're talking about them like this, actually do have the potential to give us this enormous global advantage in our bioeconomy and how we respond to these threats and make medicine too. It's two sides of the same coin. I think the two areas that we're most excited about. One is on that detection pillar. So right now, a lot of the ways that we understand what's going on around us is super analog. We have like a list of pathogens we're looking for. We test and we get a yes or no if those exist and not much more than that. We've already seen a shift in this space towards sequencing,

so actually getting the DNA sequence from anything that's in the environment or any sample, so that both broadens the scope of what we're looking at, rather than just having tunnel vision on the pathogens we know about, which means that we can start detecting unknown unknowns and things that we've never seen and make a risk assessment. Also using sequence data lets you have this much deeper level of insight into what the risk is, rather than just there's virus here, you could say these mutations make it more adapted to this type of host or make it more dangerous or make it evade a certain type of medicine that we already have. And then you can take all that information that you get on this more robust detection layer and use it to drive countermeasure

design. So we now have like every biotech that you guys talk to probably talks about programmable therapeutics, where we're moving to this era where you can update based on how the targets update. And if we have this deep level of intelligence, we can also start thinking about rather than have a stale stockpile of medicines that were made 10 years ago, can we actually see a threat immediately change the countermeasure and then start deploying that immediately? So I think getting that cycle down really tight, that's what the future is, hopefully. Are we testing enough? I know when I go through TSA at LAX, someone who was doing research, maybe for the CDC I talked to, was saying that they basically just focus on LAX because that's like the biggest hub of virus. It's going to freak everyone out who flies.

It's like if you're going to get sick, like if you go to LAX, that's where it all starts. It's like a petri dish. I know that they swab my hands for, I think it's like bomb making materials, but should they be swabbing my hands for new pathogens? Should we be doing more in the detection? Should we be sequencing random farmland

to see if there's new invasive pathogens. It could be a, targeting our crops, like, and then like, how do we even pay for that? Is that something that the government should foot the bill or, or corporations should be incentivized to pay for? What is the actual like upping the amount of data that we're ingesting look like? Yeah. I mean, I'm always going to say more data is better.

Yeah. But the question's like, yeah, how do we, how do we get more data? How do we incentivize more data, buy more data, you know, test for more data? Yeah, absolutely. Absolutely. So I think there, of course, we should collect more. The type of sequencing actually helps drive down the cost because you can target a wider range of things you might worry about rather than setting up individualized programs for specific pathogens when maybe that's not the threat. But I actually think the, with the caveat of more data is always better, we actually do collect a lot of this data today. You don't necessarily see it because some of it is in wastewater or environmental samples, like you're saying. We don't always extract. that much intelligence from the data that we do collect. So we know that a sequence exists. We might not necessarily know what that means in terms of health

or the impact of that variant or that mutation. So I do think there is benefit and there's like cost-effective benefit for collecting more. But a big piece is just of the data that does come in. How do we build the right models and the right software to interpret that? Makes sense. It makes a lot of sense. I think that covers it for now.

I would love to have you come back on when you're ready to talk more about specifics on what you're building. And I feel grateful that you and the team are doing what you're doing. Thank you. And just work a little bit faster, please. Awesome. Thank you for coming on and giving us some insight here. And congrats on starting the founder path. Thanks very much, guys. Great chatting. And I hope to chat soon. Cheers. Thank you. Next up, we have Roy from Cluelly coming back.

for an update he's hired 50 interns I think or something close to it he said they're bringing every intern on they're bringing every intern on we got every intern coming in well welcome to the studio Roy how are you doing oh boom let's go there they are I think we're overpowering you can you can you can you can you can you can you're zoomed out all the way so we can see everybody we got a small army this is incredible uh how How big is the team kick us off? How many you got at this point? The team is 11 full-time plus the interns.

How many interns you got so far? Interns. Bro, we're closing in on 50, brothers. Let's go. That's amazing. Congratulations. What are they all doing? How do you manage everything?

Is it just, is it purely social media? Is that what you want them to focus on? Growth. Yeah, yeah, growth marketing. Like the only goal of the company is get one billion eyeballs on to Cooley. So we have unrestricted creative freedom and permission to do anything and everything. Just make the company go viral. Every single person you see behind you has over 100,000 followers on some social media platform.

Wow. Wow. That's remarkable. Me too now. Me too now. Yeah? There we go. There you probably popped.

What's working? What platforms have actually been driving the most growth? I mean, I'm sure you've run a lot of tests. What have you learned that you can share? bro Ben take it away bro let's hear you see it's been really good we just hit 10 million views today um it's been eight days wow there we go hoping to get 100 million views in the next month what what what platform specifically are the most fertile ground for uh targeting your specific customer because you can imagine that uh there's a lot of folks who are AI curious on X but then

there's much broader more viral audience more general audience on platforms like TikTok YouTube Instagram, what's working, and what is the next, next platform that you're going to be focused on. Yeah, well, we're trying to go viral on every platform, regardless. But the main thing right now is Instagram Reels. Oh, Instagram Reels. Interesting. And what is the main value prop that you're hitting people with? Is it still the cheat on test thing? Or have you evolved at all? What? Still? Actually, interviews, yeah. Interviews. Okay. And has there been, this was controversial when you launched it. Is it still controversial in the comments? Are you getting flamed?

Has anyone big dunked on you and has that driven virality? Is that actually a net positive? Instagram is not like Twitter. You could post the craziest shit on Instagram and they will still not think it's controversial. Really? So to make it controversial. Like we have to engage in bait some other way. Like it's cheating tool is controversial on Twitter.

But on Instagram, you could have like a white guy say the N word 10 times and it's still not controversial. Like you need crazy shit on Instagram. That's what we crack. person here has like very great viral sense. Yeah. And watch the reels that do go viral. You see there's like ways that we've engaged in beta the videos.

And this is what we'll keep doing to a, probably a billion views a month. It's probably, how long does it take to figure out if an intern is cracked? Is it like an hour or two hours? How much time do you need? For me personally, me personally probably like 10 minutes, but for anybody watching, probably would take like one or two weeks. There we go, there we go. How do you guys think about product marketing?

Obviously, you're just going viral everywhere, getting all this attention. How do you make sure that it, that it, uh, while he's shaking his head on the way, doesn't think about, it's not about the product. It's about the attention. Attention is all your name. You guys make anything go viral. Yeah. Um, yeah, but, but how do you, the side of the street, you know, you, uh, make some

UGC videos, make some Twitter posts, you know, you can sell anything. You know, in 2025, product doesn't matter. You know, I could jack off off the side of a building, sell some videos of it for 20 bucks each, make two trillion dollars. It's crazy. Two trillion. That's intense. How do you guys think about burn?

Is it on your mind at all? I don't know if you saw the last tweet, but as of literally like two days ago, we're still, we're still cash-fell positive. We're still fucking profitable. We're still profitable. Let's give it up for the property. Let's hear it.

It sounds. So you're charging for the product and people are paying. Are they at all satisfied or did they feel like they got scammed? Bro, like the product works. You're either using this as a consumer and it's working because like, like you're passing your interviews and or if it doesn't work, you're not going to complain to me because I'm going to go right to your employer and tell them, yo, guess just complain about using the problem. Like, I'll get your blacklisted if you complain really.

Um, where, how are you thinking about how do you, how are you guys thinking about product evolutions? What do you want to add to the product? Obviously, uh, you want to help people cheat on everything. Where, where are you going to help people cheat next? We don't care about like the product is going to be led by the virality of the content. We have video ideas right now that we're going to. to try to push for different use cases. We're going to see which ones go consistently the most viral.

If you can make something go more viral, then you can just build the technology after you have all the attention. So we'll figure out the exact use cases and exact niches we're going to quintuple down on once these guys get to work. What formats on Instagram Reels are like the most modern in terms of consistently viral? Like you mentioned like man on the street interviews, what do you do for a living? That's always been a fertile ground. What about, uh, I see a lot of those like mobile game ads. that look like, you know, you're fighting down some sort of bridge and then you go into the game. It's actually just match three.

What, what, what are the different formats that you like to pull from? Every week, there's two new ones. And at any point, there's probably 10 to 20 viral trends that is happening. And these cycles so quick, you need to keep your finger on the pulse. These things will like expire immediately. You need to be on the ball. And like, if I, if I told you right now, by the time people watch this on YouTube, like, it would have all been expired. Well, they were live.

So give us the latest and greatest. Like what's going viral today? Well, right now we got 10 million views using a Snapchat format. Okay. Viral for like the last three years, to be honest. Okay. And I think that like we just have to get people who continuously scroll TikTok like six hours a day. Yeah.

But what's the actual format that you use? Like describe the video. What is the hook? Like break it down for me like you're explaining the, like the art behind the viral format. There's a caption. It starts with a face, usually a handsome dude or a pretty girl. They're saying, damn, this interview is starting with the interviewer started with the hard questions.

I should have been a CS major, not a business major. That's in Gave because people are saying like, bro, like CS is way harder than business. Then it turns around the interview asks like, like, hey, how are you doing? Why should we hire you? And then this guy uses Cluey to generate a response, but he can't fucking read the response. So he reads it hell autistically like, oh, I revel in detail. And then that's that is like another conversation. point like people are cooking on the guy because he can't read properly.

The guy is like doing a really dumb interview using create. That's great. How are you guys using AI generated content internally? I know a lot of these videos that you guys are creating are just typical social media, vertical video. Do you have an intern that's just generating basically copy and pasting making a bunch of other V-O-3 or any of these tools relevant? Anything clicking?

Not not yet. I think there's still like a 10% left before they cross the uncons. Canney Valley. And the biggest thing is that people need to think your video is real. That like like that is a difference between 100k views and 10 million views if people think it is real. Yeah, what? A.I. CEO is bearish on AI. What about uh? Yeah. What? Google needs like 10 more Chinese researchers to like figure it out. And once once, once they push out the latest update then then B. O3 will be there. But right now we need real people. Yeah. Yeah. Uh, well, I mean, what about just using AI as like stock.

footage replacement, not as the lead-in for the video, not the entire video, but just like sprinkled in to illustrate a point, you know, an establishing shot of like a building, a helicopter pulling into a building. Like that, that historically has been kind of something that you would reach to, you know, Adobe stock video for V-O-3 feels like it's there, but are you not drawing on that at all yet? If there's a viral format when we need it, maybe we'll use it. But right now, like, it's really brain dead to go viral. on Instagram. Yeah.

Formats are in our hard. You don't need a helicopter. You need a guy, a camera, a really shitty camera. I need a computer. I mean, what about like those kind of like AI mashups like Harry Potter Balenciaga or the kangaroo with the plane ticket getting on the plane? Like AI content can go viral when it's really, when it's like inspired almost by a human.

It's not entirely AI generated, but it's using the tools effectively to create something that's like still catchy. Do you think you'll be using any of that anytime? probably very soon we're scaling up like what you see right now is probably about less than one percent of what the size will be by the end of this like we are profitable we're not trying to be profitable we just keep making so much money we can't help it so we're really scaling this up to I'm not even trolling you 1,000 creators are going to be shipping out content we're doing a complete internet takeover okay so so so why in house why like like why do they even have to be

employees what couldn't you turn this into like a multi-level marketing scheme or something a pyramid scheme? We're going to do this. Oh, that's what you're going to do. Okay. MLM. MLM.

Amel. Are you guys worried that you could be infiltrated by journalists. I'm sure they're circling the house right now. The hit pieces are going to come. We're doing a softball interview right now. I mean, the person that's brave enough to try to do a hit piece on the Kluley Army is it's going to be. I bet they're dying too.

Look, more eyeballs is better. There's no companies that ever died from a founder being too controversial. You got a deal fucking infiltrating with genuine spies and they're still doing fine, bro. You have a worker 17 guys. They're still kicking like no confidence ever dies from being too controversial. You die because you don't make enough fucking money. Yeah, yeah, yeah, yeah. Speaking of making money, what's the pricing model right now?

Are you doing anything on price discrimination? Is there a super high tier if you get a whale? What does it clearly whale look like? Can I spend $2,000 a month on this service? Yeah, you should add a tipping feature too. Yeah. People should be able to tip you guys if they have a good experience. You should add really financialization pay as you go, high interest rate loans,

just really push it. Make it sports gambling in there maybe. Just throw it all in. Yeah. I mean, it's $20 a month for $100 a year. And our top line revenue is really being driven up by enterprise. You're going to have to talk to sales team to get a custom quote. But, you know, like, there's a lot.

Are you serious? Is that more on the sales side? Who are the enterprise? So you sell the SDRs? You guys laugh because you think I can't sell enterprise because I'm... No, I don't believe it. I trust. Like these 20, these Fortune 500 CEOs like these are like 35 year old dudes who sit there

school people who are laughing at my post. Yeah, yeah, yeah. Yeah, no, it seems legit. It makes sense. No, I believe it. But, but I mean, you're not going even higher tier. Like, what's the $2,000 month, Cooley Vision? For a for consumer, there's a lot more we can do with more compute.

But right now, we're like, to be honest, I didn't expect to grow this The edge team is quite small. I'm going to spend a lot of time trying to hire more competent engineers. We have a lot of back-block tasks that we need to fill out, especially for this last contract that we signed. So we're full-time focusing on the one big guy that we got right now. And after that, then we'll try and skill this up. But right now, we're focused on the one big client that we signed. Yeah.

Talk about your compensation strategy that people want to know. You said you can raise infinite capital and you're so confident, I believe you. But I'm curious to get some more insight there. Bro, I feel like it's so retarded to be a company. Sorry, am I allowed to say that? No, you're not allowed. No, this is a family-friendly show. It's very stupid to be a company.

Like, try to race to the bottom to see how little you can pay your employees. Bro, if I'm making hell of money, we're all making hell of money. Like, I'm trying to pay them more to see if, man, like, maybe tomorrow will start being like cash flow negative. But I just can make a money, bro. Like, I would like to pay these guys what they're worth. And the output is fucking insane. We did 10 million UGC views in what, like eight days. Like you don't see this sort of traction in any company and you don't see killers like this in any company.

Unless you're paying these motherfuckers like what they're worth, bro. Like one. Maxed out contracts. Maxed out contracts. Exactly. Yeah. What about devices? I mean, it seemed like this would be a natural fit for some sort of AI wearable or other platform.

Is there an app coming or are you interested in what's happening with Johnny Ive and Open AI? What was your take on the device world? We're very interested in the hardware space. We've got like a million things cooking on hardware. We got people in the garage right now working on. You don't even know about, bro. Like we're bringing manufacturing back to America and it all starts at the Cluey garage. Let's go.

I love to see it. Nobody, you know, they doubted, but you guys are reindustrializing America. You guys really are the hard tech up there. They're working on brain chips down there. Yeah. Brainships. Brain chips. That's the future.

There we go. There we go. The new NeurLink. Yeah, I mean, I, you know, there's a world in the future where you guys actually just roll up Neurlink and Open AI. For sure. For sure. Fully umbrella. Yeah, definitely. It's possible. I'm excited to offer acquisitions for both of those companies. Yeah. It's in the roadmap. It's on the road map. All right. This has been a lot of fun. I'm excited for you guys. It is. And I have no doubt that you'll go from, you know, 10 million views a week. 10 million views a week to 100. And I'm excited to see you guys hit that bill. million view mark very soon so keep it up we are all very entertained and uh rooting for you shish shit i love the energy thanks man we appreciate you joining better guys we'll talk keep having fun bye you know what he needs he needs linear he needs linear to manage all his interns

sounds chaotic in there yeah it's uh use the platform purpose built to design and build the best products on earth oh you know that they already i bet they already use linear to be honest meet the system for modern software development, streamline issues, projects, and product roadmaps. Go to linear and get started today. I wanted to go through the Serra Guo piece because we are having Sean on because he is throwing the AI engineer World's Fair and he's going to be joining with some other folks breaking down what's going there. We can kind of revisit this Serra Guo post, which we talked about later, possible topics for

her keynote. Apparently she completely revised everything, but I really liked it. She wanted to talk about AI native U.S. Not just chat skins. Vertical AI surge. That was something we were discussing earlier. Multimodal frontier video, 3D audio retrieval plus long-term memory, synthetic data flywheels, obviously super important. The Sim to Real Robotics push. Closing the autonomy gap, robust agentic workflows, cell scale, digital twins and programmable biology, compute geopolitics, world models for zero shot planning and RL environments that actually generalized. She has mapped out the true surface area, but more recently, she authored a post an article on X, directly on X.

You can read the full thing at her ex page, Serenormis, on taste. And I thought this was an interesting post. Lulu quote tweeted, and she says, Stripe returns errors in plain English. Quote, that card number doesn't look right, not error underscore invalid parameters. because developers debug at 2 a.m. Spotify's shuffle isn't random. It avoids playing the same artist twice in five songs. True random feels broken.

Engineered random feels right. Notions drag handle appears only on hover. Six dots arranged in two columns, not three lines, not always visible. Because permanence is clutter and six dots whisper, grab me, while three lines shout, I'm a menu. This is taste, the relentless, almost painful ability to know. what should exist, what shouldn't, and where quality matters. It's the difference between shipping a product and shipping a point of view.

The best founders understand that taste is a competitive advantage that compounds. It runs deeper than pixels. It's in your code base, your culture, your cap table. And I'm just thinking about the Clue lead taste, which is just like the most maximal possible. Just maxing everything. He's max maxing. He's max maxing. He's such a character.

I love that we can have them on and then have someone, you know, like a public company CEO on the same. We got range. We got range. It's fine. Think of it like a restaurant. That was absolutely wild. He,

uh, we should probably text the families and say, you know, don't play this in front of the kids. Yes. But, uh, he knows, you know,

the level, you know, he, he, he, he, he's thinking of how do I get the max amount of attention out of each incremental word.

Totally. It's not just each incremental post. He knows what he's doing. I, I am like systemically offending. people in multiple ways in a single sentence. But at the same time, like he's entitled to be his own personality. Yeah.

And I do think, you know, not to get completely sidetracked now that we're on to the next topic, but I do think, you know, an enterprising young journalist might want to take a crack at Roy just because it will turn into a feud. Yep. It will probably be good for both of them. It will be very beautiful. It's WWE. It's WWE.

Paywall the article. He's become a little bit of a heel of tech. Like he's somebody that people like love to hate. It's like, how do you take the YC playbook and just run the opposite of it? Yeah. Like it is it is the inverse of the YC playbook, which is,

you know, be loud before you're confident in your business model and confident in your product. The question is just like at some point getting, yeah, it can't all be style. There needs to be some substance. You have to actually build a product

that people will be, that people will love. You have to make something people want. want. And so we're not seeing that side right now, obviously, at least not in public interviews. But I hope that he can turn it off incrementally and eventually probably need to turn it off 90% of the time because, yes, attention is really, really important right now, but at a certain point, you have to just deliver on the core metrics and the value problem. Or else someone else will come along and offer something with, yeah, they won't have all the style, but they will have

Yeah, and I think there's a venture capital firm out there that even now would give him an income, just seeing even that interview. Yeah, yeah. See that and be like, I'll give this, I'll give this team another 10 mil. Yeah, to go figure it out. To go keep figuring it out, right? I mean, attention is incredibly valuable. But he's also, but he's also being smart and that he's figured out. He basically has the world almost convinced that he's going to burn through every dollar he has in the next two months.

Oh, totally. Which is pretty, but behind the scenes, he's like, well, I'm actually making money. Yeah, I mean, Avi shipment at Friend was going through a similar thing where there was that big story about, oh, he raised like a $2 million seed round and he bought a $1 million domain. And everyone was like, oh, he's so wasteful. But then, of course, he would like finance the domain. So it was really just adding like an incremental like 30K of burn per month. And it wasn't really like he didn't take that whole hit up front. And then he was able to kind of build the business.

Yeah. And he's making a category bet on AI companionship. Yep. And having friend.com is a great, is, will lead to increased marketing efficiency over time as he starts to scale. Well, anyways, you should go back to this completely different article. You know what he should do. He should get a watch on Bezell.

Talking about taste.com. Really start flexing on people. Your Bezell concierge is available now to source you any watch on the planet, seriously any watch. So go to getbezzle.com. So Sarah goes on to say, think of it like running a restaurant. It's so funny compared to this. taste thing to this. It's like the most serious post. There's the most silly, just silly hype train over there. Think of it like running a restaurant. Anyone can follow recipes, source ingredients,

and serve food. But the difference between a forgettable meal and a Michelin Star isn't just technique. It's the chef's palate. Their ability to know when something needs more acid, when a dish has one element too many, when to stop plating. Software is the same. But products aren't just feature complete. They're composed. And we see this with like a lot of the best software products. The software is more like art than science in terms of like the design and how you're interacting with the user. So Sarah says it's easy to say, hard to do. Everyone claims to have taste now. It becomes the new product market fit a term so overused its lost meeting. Founders drop. We're taste driven in pitch meetings. VCs nod knowingly. Nobody defines it. Most companies

confuse taste with aesthetics. They hire a design agency, pick a nice font and call it, But real taste runs deeper in the error message, the loading sites, the loading states, the features you killed because they were merely good, not essential. Real taste hurts. It's saying no to features that would triple your tam. It's spending a week of it's spending a week perfecting an interaction that users will barely notice consciously. It's choosing the harder technical path because the UX is 10, 10% better. If your taste doesn't cost you something, it's not taste, it's preference. The pain compounds daily a fortune five. 500 prospect wants a demo tomorrow. Do you ship a half-bake feature or the half-ass collateral or lose the deal? The entire AI landscape reshuffles every three weeks. Do you chase every new model or trust your vision? Your competitor just ship something flashy.

Do you match it or hold your ground? Anyway, we'll have to have Sarah on the show to recap her talk. But right now, I believe we have Sean coming in to the studio to tell us about the AI Engineering World's Fair. We're very excited to have him join the show. Thanks so much for hopping on. I wish I could be there. I have the biggest fomo I've ever had with any tech conference because the lineup

seemed absolutely fantastic. Unfortunately, I have a large family and a studio that is covered in junk and we're moving in. So I appreciate you taking this remotely and we'll have to do the next one in person. But thanks so much for joining today. How are you doing? Hey, guys. Glad to be back. It's funny because your setup looks so great on camera.

I'm just imagining the mess that it's off camera. Oh, yeah, yeah. Yeah, yeah, it's definitely a work in progress, but part of the brand is, of course, just showing the nice parts. But congratulations. This is many years in the making. Can you give us a little bit of the history, the plan, and then I want to go into some of the hot topics that you've been discussing today? Yeah. I guess this is the fourth conference we've done.

And I started this basically right after the sort of chat GPT movement and talking with enough developers. and understanding that the people who can wield LM APIs are going to be way more powerful than people who just chat with products. And this is actually going to widen a lot because they can basically wield serverless intelligence. And so I coined, you know, I sort of popularize the term AI engineer.

Andreik Arpathy sort of endorsed it. He said that he does believe that you can get very far without ever training anything, which is a big thing for him to say because I think the status quo at the time was, you know, it's high status to trade models. totally scientist but now

it's actually consensus now that you want to work on rappers rather than models and there are many many multi-billion dollar companies that have spoken at AI engineer that reflect that fact

yeah and yeah so like and there was a big shift there where there was a moment where fun like the vibe had shifted a little bit to like the application layer but there was still the idea that if you were going to build

an AI legal startup you were going to train an AI legal foundation model and now it's moved all to post-training all to RL and how you're how you're prompting and how you're integrating and ultimately like the user interface and so yeah it makes a ton of sense and I'm sure there's a ton of companies that are beneficiaries of that boom yeah and it's not even companies it's more just like customers sure because the foundation model labs are never going to work directly with like your healthcare system like it's

going to be like a bridge that comes up and does that. The Foundation Model Labs are not going to work directly with lawyers. It's going to be Harvey. You know, I think so that that directly led into the rise of vertical AI-enabled SaaS. And I mean, that's right. It's right. But yeah, I'm sorry. That's a slack thing that has.

By the way, the conference is still going on. We just had the morning keynotes. I have my chat with Greg Brockman later today. Fantastic. And he doesn't know this, but I might as well just share this. but like we have a nice little cameo from Jensen Huang coming by. No way. That's great.

So we're trying to level up. The cat, he knows this morning were fantastic. Like the Microsoft, you know, they like really went on there. They're going so hard after the AI audience. We were just reading about that and the information. Platform, platform, platform, platform says Satya. Yeah. Yeah.

I think they see this as their chance to overtake AWS. That's great. Wow. But like AWS is also, you know, also sponsored. They've been like having a very strong presence with us. So like we just want to be the vendor neutral place, right? Like all the big clouds, all the big labs. We have the DMCP team here with the entire steering committee presenting as well.

And we just want to be for developers. Like this is where you, this like kind of the trade show. You come to hire people, learnable what's new and upscale. I have a couple more questions. How long do you have exactly five minutes or? I can go to like 1.130. Okay, great. Yeah.

We had a guess and I moved into a different day. Okay, first, perfect. So I want to know about the mix of attendees. How many folks are trying to start venture-backable application layer AI companies versus, is there a new trend of someone who's building more of a vibe-coded, almost lifestyle-type AI-driven business? Are there folks from either companies that have established themselves and are now trying to bolt on AI? Or are there lots of folks that are working for large companies and just want to stay ahead and become AI engineers? What's kind of the shape of the audience, if you can characterize it at all?

Yeah. So we do surveys, but we don't know specifics to that high-level granularity. I would say about 50% are people working. at medium to large size companies and trying to upskilled. And then the others are smaller companies. And our most popular title is like founder or CXO of like a smaller startup. And those are venture backable. And I think mostly that's just a function of us being in San Francisco.

Yeah. Because obviously we will have that startup bias. I do think that one thing, I kind of don't really care about this whole lifestyle versus venture back thing. because, for example, I have a tiny teams track that is speaking this year. Tiny teams is something that I'm trying to push as an idea of companies that have more millions in ERR than employees. Right? So your revenue efficiency is so high because obviously if you pay each employee less than a million dollars,

you're probably profitable. And therefore, you don't actually need the venture money except to points of marketing. And that's your choice. You can be profitable. I have a six-person team making more than $40 million. And yeah, I mean, it's absurd. Like the amount of leverage you can get with, with agents and also building AI products for other people to use where you're just kind of passing through or slapping a margin

on top of the tokens that you resell from the big model labs. I think that really makes a lot of sense. Totally. Has the narrative of like, oh, if you're building an AI, like you're going to become obsolete by Google or open AI is going to steamroll you in their next dev day, keynote. Has that narrative dissipated and what, if so, what's driving it? Is it kind of the pre-training scaling law, the wall that we're kind of seeing with GPT 4.5? Are you guys still, I don't know if he was still talking about that. I mean, everyone, you know, everyone's moved on.

Yeah, we've moved on to different time, right? Like, yeah, I think most people have agreed. Like, there are still new pre-trains happening, especially with the open source model that OpenE Eyes is working on. Sure. But yeah, I mean, I think, We've seen it come and go in a lot of times. So, for example, we have opening I launching ChattyPGy Codex, which is just head on a direct Devon competitor. You know, Devin's not worried because they, you know, have been doing this for two years,

and they're much more polished in terms of the integrations, and they have different things that their customers already like. And so I think it's just like everyone is going to need their version of a thing. And so this is the sort of house store band version of what Chatschipzee Codex could be. And it's not competitive just because the ocean is so huge for software engineering. And Devin has at least established the category by being first there. And I think you can see similar versions of that across the domain. Yeah, I haven't really seen anything there yet.

Although it's not to say that it doesn't happen. It does happen. For example, with the first wave for GPT3 startups like Jasper. But I mean, yeah, so far there's no fear of that, in fact, that people are very excited to beat the Foundation Model Labs. Like this is where the engineers meet the lab people and lab people train them on how to use their LEMs. And I think that's a perfectly harmonious relationship, to be honest. I haven't seen any of it.

What was your reaction to the news around Anthropic and Windsurf yesterday? A little bit of drama on the timeline. So, yeah. Give us a walkthrough for those who might not be familiar of what happened. And then I'd love your analysis. Yeah. So the history of this is that. Winserve is an independent company that basically kind of followed cursors, footsteps, and launched

an AI agentic idea. They've done very, very well for themselves in a very short amount of time. I think they launched, we're the first podcast that they launched with in October or November last year. And then there's the rumors that they got acquired by Open AI for $3 billion. Those are rumors that are unconfirmed by both sides. I've talked to both sides. Yeah, I've been fascinated how everybody just takes it as fact.

I take it as fact. He wore two polos. Yeah, he wore two polos. But again, at no point, every news outlet, legacy news outlets have been reporting it as fact, even though no side has verified it and nobody said it closed or anything along those lines. Yeah, the only thing I can say is, wind surface speaking tonight right before Great Brockman goes on. And there's a reason. Exciting.

We're not dropping a ton of alpha, but I'm just saying, like, I'm not, that's all I can say. That's what I'm allowed to say. Yes, of course. And I think that, so there's a, there's a, there's a relationship there. As there is a fact that both cursor and windsurf had benefited a lot from their relationship with Anthropic because Quad 3.5 and 3.7 have for whatever it's worth been regarded as the best coding models.

Yep. Open. I will disagree. Gem and I will disagree, but whatever. Like the community has voted. Yeah. So overnight, I think like two days ago, day ago and thopic cut off the first-party access to Claude to for Cloud to WinServe.

This is their top model and now they just don't have access as a first-party tool. You can for example still bring your API key and use your accounts on WinServe, right? You can't just like WinServe I'm going to pay you 20 bucks, use your account, whatever, I just don't want to worry about the rate limits and stuff. That's gone winter. They just woke up overnight and that's gone. So a lot of people are very upset. This is a very big no-no. know if you're like aiming to be any sort of like credible LLM API provider to just cut off access.

Google hasn't done that even though, you know, if you take the sort of rumors of the acquisition on face value. But I think this does lead credence that I think Anthropic at least thinks that wind surface is just a competitive product now. So I think like in so far as you're putting odds on whether the acquisition actually closes, the odds have moved up. Interesting. Yeah.

The other factor that's interesting is how much does this benefit cursor if you're a developer who loves various Claude models and now maybe you have a reason to go spin up? You know market share of cursor versus windsurf? I don't like estimations. What is that? I think the numbers I've seen, I saw it on my timeline on Twitter. I didn't save it in just request. But someone please look this up.

It's something like windsurf is 5% of cursor. Wow. Because based on the market. caps, I would assume that Winsurfs like 30% of cursor. So the thing that you don't see there is Cursor has entirely developed business on the IDE. Sure. With Winsurf used to be codium, which used to be like this GPU service GPU company that has significant LLM inference for enterprises.

Like they spent the last four years doing that. Yeah, yeah. So they're buying that team, that revenue, that products, as well as Winserve. Oh, interesting. Yeah, that makes a lot of sense. What, how do you think that the, uh, agentic coding market is shaping up. We've been kind of talking about,

maybe it's three different markets. Like I can go to GPT, like I can go to O3, and I can ask it for a question, and it will just write code and write Python and execute it. And I don't even have to tell it to write code. It's just if I ask a question that requires code, it will write some code. Then, of course, the Open AI now has codex.

And then they also potentially have windsurf or, you know, you can think about the IDE's as a different entry point into that market. Are we seeing like a true permanent bifurcation between synchronous and asynchronous AI coding usage? Or do you think these all blend together at some point? Yeah, I think that actually you're just catching up

on something that has already been a thing. That was the divergence and actually the converging. So it already started that you had the synchronous ones like cursor Windsor and then you had asynchronous ones like Devon and factually AI, for example. Yeah. And they were all sort of like what we call the developer inner loop,

which is hands-on keyboard coding. Developer outer loop, which is PR review and all that kind of stuff. Or like file an issue, make a PR, that kind of stuff. So those are merging. The explicit goal of codex, sweet agents, something I'm going to talk to Greg about later today,

is that they will merge those paradigms, just that they're merging the reasoning models and the sort of instant thinking models with GPT5. And that totally makes sense. It's technically really hard to do because once on your machine and one's cloud. And also they're just different set of user experience paradigms. Is my video freezing, by the way? It is.

It is. But you look great. You look great. I see you guys. How seriously do you take Google's coding agent jewels? Do you think it's just an experiment that they're putting out there? Do you think they'll actually invest in it and try to get real adoption? You're trying to get me in trouble.

You're conflicted. I'm sure Google has is a part of Google's great. And we love. Products wise, they have had hits like NOPLM that then have failed to continue the momentum for whatever that

and I think that is I think that most people are extremely unfair to No Pocelm. I think they have shit really well. It's just that you'll never repeat the initial wave of excitement that they had. Totally. We just never will. Yeah. And I mean, notebook L.M seems interesting because that feels like a case study in if you're

a startup and you're fast following and innovation that actually came out of a hyperscaler, that's where you turn into a bullet point on the next dev day or something like that. Because notebook LM, it felt like there was this amazing, tremendous momentum online. Everyone was excited. And then it was kind of faltering. And it was like, oh, there's no app. So maybe I'll build the app. And I'm sure some people built notebook LM apps or notebook LM spinoffs.

And then it just took, it just took six months. And then now there's an app. And now, and I'm sure they will be iterated on this. And so, yeah, yeah, I know to some degree. But, but I think the lesson is probably like, yeah, there's probably some narrow window where you can cash grab as kind of like a cynical like ripoff startup. But like realistically, if you, if you found out about the concept of turning a deep research report into an audio product from

notebook L.M, like, you might be just behind the ball. And so, like, you don't have the right to own that market long term. As opposed to, you know, I think Devon, Cognition, like, they have more of a right and factory, they have more right to continue to fight with

Google's, uh, Jewel's product because they were really there earlier. They can issue, they issued the original hype and, and, and, and, brokered a whole bunch of enterprise contracts and like kind of got a couple years down the road before. So they're not like a fast follower to big tech. They're actually, big tech is maybe fast following them. Yes. I think, I think they just boils on to

execution and everything, right? Yeah, of course. And I think like that's, that's one of the reasons why we've actually somewhat broadened out from just engineering to we've added AI product management and AI design. Okay. And I think that really good, this is, this is product management. This is a straight up. Can you keep up the momentum? Can you listen to your users? Can you come up with creative new stuff that keeps the momentum going. And some teams can, and some teams cannot. The only thing I can say with regards to Google

and the fate of jewels is the initial, the founding PM of Noble Gellem left. And she's speaking here with her own startup. Oh, yeah. It's like, it's really hard to keep employees of people who like start interesting products for Epic Lab because they will get any number,

any amount of money thrown at that. Yeah. And it out. The budget capital strike again. $20 million seed round, 10 million of secondary if you quit your job right now. Probably not that extreme. I wanted to ask you about Git. I wanted to ask you about GitHub.

How much do you think Satya cares about, you know, GitHub? Do you think he's, you know, really pushing the team on that? Yeah, is that an important wedge into the AI coding market? Because obviously they were first with GitHub co-pilot. And you can imagine that it's just a phenomenal distribution channel. And when you look at the value of and the way Microsoft executed around teams rolling into, you're already using Outlook. Now you're using Teams instead of Slack.

You could imagine really great adoption, maybe not at the most cutting edge companies that are hyper online, but we could see one of those charts where we're like, oh, wow, like Microsoft's really crushing it in developer tooling. I mean, absolutely. I think it's extremely core. What would you put GitHub co-pilot revenue at right now if you had to hazard, I guess? 500. $500 million? Yeah. You nailed it? Like, standalone, that is a publicly listed company. Wow. Yeah. Yeah. Yeah. That's like the perfect bar. I mean, here's the challenge, right? Here's the challenge is that no one is talking about GitHub co-pilot. Is that a challenge? It's inside of Microsoft. Yeah.

I mean, no one's talking about. No, I know, but, you know, nobody's saying, like, look what, you know, nobody's sitting there being like, I'm blown away by co-pilot, right? Yeah. I think, I think that people who live in the Microsoft stack are, because that is what they have access to and, like, their company agreements are. I think on Twitter, there's a novelty bias, right? Totally.

People always want the new thing. they want to support the little guy. I support the current thing. You want to support the current thing. Here's the mental framework I want to leave you guys with on that stuff. It's data gravity and the most is a thing. Data has attracts the compute, attracts the money,

attracts stickiness. Once my is one place, everything else moves towards that data. And if my code, my code is the most valuable form of data I have. That's the most expensive. expensive data to acquire. So if my code already lives with you, then it's much easier for my coding agents to also live with you.

And so they have a home turf advantage. I think the GitHub acquisition back in the day was one of the smartest and most enterprise decisions in developer tools history. So I think you should take that point of view. So like that moat is so strong, like any, like try to be like a no name random DevTools startup that comes up and says, hey, give me access to your code base. Like, I need to run agents on it. They're like, no.

Like, I'm already doing it. Yeah, what happened with Codex yesterday? There was one user that was reporting that, uh, private repo information was leaking from one to another or something. Was that user error? Did you, did you track that at all? No, you're probably getting busy to it. No, I was running the conference.

Yeah. And individual things are going to happen. Yeah, of course. It's, I think GitHub's reputation is going to last it through that. I think it has to be really egregious for, for, for, for that. that kind of stuff to stick through. Yeah. Yeah, I mean, I think like more broadly, I think that there's a standard stack of what we are calling, what Andre Carpathie is calling the L-MOS, right, that I think you guys are kind of going and learning about. But I think it's pretty well established

by anyone who works in software agents, coding agents, which is want a sandbox, you want a browsing environment, you want branching, you want fine-tuning on your code base. Like, there's just a standard stack of things that cloud code codex jewels cognition um factory and anyone else in this field they're all converging on the same thing and it's just who does it best and who reaches who solves it for their customers best i think that's that's going to be the name of the game for now makes a ton of sense uh do we have to roll over to the next person uh no because uh okay you're good he had to yeah i mean i guess my question on data gravity is uh it it seems like uh if we compare the evolution of video generation models,

Google has a really amazing cornered resource in YouTube because that data is so big, it's so many tokens. It's growing. It's growing and it also hasn't been like exfiltrated to the public web. But it feels like GitHub, although it is a massive data set, it's not nearly as big. I think somebody collected at like 100 million tokens or something.

It's just not, no. No? Is it? Way bigger? Well, public repos, because I don't think that they can train on private repos, right? Or can they? Who, GitHub? GitHub. GitHub. I don't think they will let themselves. Yeah, they wouldn't. Yeah. I don't know. 100 million just sounds way too low. And that's my, that's my gut reaction. Sure, sure, sure. Keep going. So the question is like, how durable is the data moat at encoding versus in video generation? Purely, I'm just thinking about the raw. data set size of YouTube has to be orders of magnitude larger than GitHub. And so I would imagine that it's, it's Microsoft probably has a less durable advantage versus Google's like kind of march down the video generation pathway if it's truly

restricted by data. Not all data is comparable like that. So you're comparing verifiable data to unverifiable data. So code can compile. And if it runs, if it runs, you can do more code like. that, and that creates the URL loop that, unless you generate synthetic data for more code. With videos, you have what you have. And you can train on that.

You're technically not even allowed supposed to train on that, but who knows what Google's doing behind the scenes? Well, I think Google can train on public YouTube videos, right? I don't know. I imagine that, like, I've posted videos on YouTube. I imagine that I've opted in at some point. I think there was like a big fuss with MKBHD and all the other guys. Yeah.

picking up a fuss about this, you remember? Sure. So I'm just, I don't know. I'm not a lawyer, but like, I'm sure it's a completely untested clause that just has to go to court. Yeah. I just want to say if, uh, to Google, if you remove John's rate limits on V-O-3, you can train on our back catalog. Full permission. Please.

Yeah, I think, I think there is that diversity of opinion, right? Like, do you want to just like give yourself to the machine or do you want to keep your data to yourself? And it's like, there's no one between. Like, you're either one or the other. It's a very strange dichotomy. Like, many things in life are a spectrum, this one is not. Like you run into someone, they're either maxi, privacy maxi or they're like an AI maxi. Yeah, yeah, yeah, no, that makes sense.

What else is on the cutting edge of debates that are kind of raging at the conference this year versus prior years? We've lived through like the P. Doom debate. We've lived through like the Leopold-Oshend-Brenner era. We've shifted to the geopolitics debates, but what's kind of on the frontier of like hottest topics to discuss? First of all, Leopold was right. And I don't know if people know that he was on earlier's team when the sort of board drama happened. And he was like directly connected to it. Anyway, we haven't lived through it.

We are living through it. It is happening. It is directly leading to the geopolitics because he was foreseeing that. And he was exactly right. Yeah. But the way I would kind of characterize, at least my takeaway, was that his piece was a little bit of a pivot from the paper clipping doom and a shift to geopolitical competition in AI. Is that a mischaracterization? No, nailed it.

Okay. But like, he was right. Yeah, no, no, I completely agree. I completely agree. I'm just wondering if it's like, if the consensus is that he was right, then the book is closed. We're not debating that anymore. What are we debating? What's the more modern?

Are the debates. Yes. Yeah, how to do great AIP-Ming. Sure. How to run a tiny team. Yep. We have a robotics track for the first time that is, Tesla Optimus is speaking, physical intelligence.

Cool. Waymo. Waymo just overtook Lyft. Yeah, yeah, I saw that. That already. Voice is the hottest thing in terms of multi-modalities. Like everyone's sort of building with voice because I think it's like finally good enough. Yep.

And I think maybe the last thing I'll highlight to you is we are also emphasizing security for the first time. Security is like kind of a boring topic. Nobody really wants to talk about how to secure your system, but like they actually do now because they have real money running through their product. So there's all that. And then that is like roughly important, equal in size to the excitement about MCP. And so we have an entire MCP track with the Anthropic team here. Because it's because they're nice enough to come by. And that fills up the whole ballroom that we have. So are we going to get payments in MCP? Is there a subtrack for putting stable coins in there or something like that?

There's nothing in the official spec, but we have a number of people and we have a speaker talking about the sort of MCP economy that's being enabled. I do think that remote MCPs and authorization give you the foundation for basically just remote agents that you can buy and hire. That's effectively what it is. It's just that we're still in that stage where these things are still trivial enough that you can actually just write your own. So you have to overcome that build versus buy for this to.

actually kick off. Okay. And I would just say, like, I'm not at all a crypto person, but I would say that the crypto people have been ahead of us here, and they haven't found that much yet, you know? No, makes sense. But they're actively hunting. And if anyone finds it first, it will be them. It's circles presenting here, Solana presented in my previous conference.

And they're all on it. Stripe is also on it with their stable coin thing. Something's going to happen here. Bridge. Yeah. In robotics, are we getting to a point where? where we're starting to see an ecosystem of companies pop up like we've seen. No, it's just, it's just.

Yeah, so they're all vertically integrated. Sure. They're all building their stack. I don't see like any horizontalness. Nothing. That's what you're going for. That's exactly what I was asking. Yeah.

Yeah, it's so weird. I think, you know, there's just so much custom needs that you have to sort of reinvent the universe every time. The one thing that does reuse bots is a Cloud Chef, which is, a very young company, but I ran across them when I tried their food. So they're a kitchen robot. They do demonstration learning from a single shot from, let's say, like a Michelin chef, and you just give it an ingredient, and you will just flawlessly just kind of repeat that cooking for you,

and you can hire it for $12 an hour. So it's meant to directly replace human labor, which is very expensive and very labor-intensive and unreliable. Let's put it that way. And they use, they can live on top of it. of any other robot arm or Tesla Optimus substrate. Got it, okay. Because it's more about the robotic sort of framework

than it is about the individual hardware. And I think like that is the first time I've seen that happen. I'm like relatively new to this, but like this is the first time I'm like, oh, okay, like he's actually pretty confident. He transfers across any system as long as they have the minimum required set of device drivers basically.

And I'm like, yeah, that's cool. Like yeah, yeah, so he's speaking tomorrow. What about other pieces of the robotics data stack? Are we thinking about like data brokerage or kind of like a scale AI or maybe scale AI actually working to generate more robotics data? Anything on like the SIM to Real Gap? I saw some semi-analysis data, some way of a paper that was pretty cool. So I would say that as an industry practical conference, those are just in the domain

of research right now. It's in research. Yeah, it's like there's there's a lot of papers out there. Jim Fan had a fantastic talk at Sequoia. that I recommend everyone watch if you haven't seen it about the physical Turing test. How you need to just do a lot more simulation. And there's a lot of work being done on this. I think Google Genie is the other one that I would recommend people to.

There's like a really interesting tie in between like the generative video world and the robotics world that. You wouldn't necessarily expect them to you like spend some time in that. But we just haven't focused on it because people cannot get jobs in it. Like I want people to get jobs at my conference. That's like almost the whole reason that's the whole point. I bring the companies, I bring the engineers, they meet, they fall in love with each other. That's like, to be that's like the most fulfilling thing. Can you give a high level update on the hiring market today?

What it's fact, what's fact, what's fiction? Yeah. You know, it's one of those things people love to, you know, talk about how bad things are. And yet every company that I know is like can't find people and maybe there's a talent kind of gap there. But what's your read? Yeah, I mean, I think both are right, which is weird. This is actually the topic of my conversation with Greg Brockman later today, because half the people I meet at my own conference are worried for their own jobs, right?

They do ask about this. It's not like they're not, they're blind to it, but they're just like, I'm here to see what else I need to do or how does my skill set need to change for the future. And nobody knows, you know, everyone says the trite thing, which is like, oh, I'm going from I write the code to I manage things that write the code so I become an engineering manager but like what does that mean in practice? How much knowledge do you need to supervise an agent?

You actually kind of need a lot when it goes when it goes off track. So like that's super unknown. I do think that the juniors, the like fresh out of college students, they're a little bit cooked unless they're good. So it really amplified skill that sheep. It really, really, really do by skill of sheep. Yeah.

Yeah. It's a hard thing to, to, you know, try to tell somebody, you just need to be five times smarter than you are. And then the job and then you'll have like a bunch of offers. But I also think, I also think that the solution here and we, we just hired an intern who already shipped a new product. He started Monday. He just shipped something relatively simple, but it's cool to get. directory. He just sent us a V1 of that product that he built last Thursday. We saw it and we were like, this is super cool. Why don't you start on Monday? And it's that one kind of interaction that can get

your foot in the door that allows you to develop skills and build relationships that, you know, hopefully we, you know, we work with him for a long time. But even, you know, I'm sure people are already seeing him at TVPN and we'll probably try to poach him before the end of the summer. So all you use, it is, It is like a changing shape of the software engineering employment because I feel like the vibe coders can come into organizations that might not have a full engineering department and then have an impact because of the way the tools work. But it's certainly a lot of change very quickly. I would say that's not the consensus yet that I hire a chief vibe code officer. Because humans are still very much needed to patch the gaps that the models are not good at. and it's really painful when they do go wrong and they do go wrong.

You know, I think like all the hype that you see on Twitter fails to admit, like what happens like one month, two months, three months after. And that's honestly what you get paid to do as a software engineer, make maintainable software and not being filled all the time. I've even seen people repurpose old projects and say, I vibe coded this in 24 hours and everyone's like, wait, now this was published in 2019. Like you spent months on this and you're just hyping this up.

That's misinformation. I can't govern. I pay attention to what people say there. I do care what people report for themselves that they've done at serious companies. So one thing I would highlight there is booking.com did about 10 company years worth of migrations in three months with their sort of automated code migration that they did it with source graph. So we did a talk with them at my conference in New York in February, which, if you want to look that up. So like those that company has been around for like 14 15 years. That's that's a serious code base right. Yeah totally. They're just reporting their success.

They got nothing to gain from selling you on it. They're just, they're just happy about it and they want to teach others. So you want to look for those. They're not trying to sell you anything. They're just like reporting like their progress at a real company. And it's that's really what I try to optimize for for the conference. It's hard because not everyone's incentivized to do it. You just have to create an environment where they get something out of it. it by meeting their peers at a thing like this. Well, give us the plug. Where can people watch your talk with Greg Brockman later today?

Yeah, it's on YouTube. YouTube at AI.Engineer. Fantastic. About DOT. And yeah, what would you ask him? I mean, you're having him on eventually. So, you know, what's like the way that you would open the conversation? Ooh, that's a good question.

For Greg, there's a lot but I mean the question that I feel like is at the top of mind in like Ben Thompson world this week is

the shift from training to inference and how workloads are shifting this was in the context of Nvidia earnings but Greg obviously has intimate knowledge and so Open Eye is obviously going to do

larger and larger or training runs, but they're also doing tons and tons of inference. How is that shifting? And then what I want to know, and I don't know how much he can speak to this, is like where, how will, if we get to a world where we're in 80% inference, 99% inference, something really extreme, does that change the type of data centers we're building? Does that change the chips that we're demanding?

Are we moving to ASICs? Are we moving to FPGAs? Something like that to like speed up the actual inference. workloads at what point do we actually bake these models down if they're deemed like good enough and then we're like orchestrating them if we hit a plateau that might make sense at the same time if there's a lot of promise on algorithmic progress and we're expecting like oh yeah we're gonna leave the transformer behind eventually well then yeah you don't want to bake all that down so I think that that's like it's a little bit more of like a semis question but it is an interesting question for him as well as he's like seeing the workloads it is very relevant he he does have a role to play in Stargate that I'm not super clear about I'm going to ask them about. Yeah. And yeah, I mean, I would say that nobody's betting on the end of transformers. Yeah.

I just a very small, very small number of people that are just experimental. And it's really about just scaling the RL. Yeah. I mean, there is this interesting thing that's happening. I believe images in chat GPT seems to be using a number of different algorithms combined. So there's a little bit of diffusion in there potentially. There's some transformer-based stuff. I don't know if you have a, if you're pushing back on that.

I'm not. There's a strong hypothesis based on the hints that they have dropped from the people that worked on it. Yeah, that there's multiple algorithms at work, right? It's a diffusion head. Yep. The rest of it is just regular 401. Yep. And that's so good at Chad and has decent world knowledge.

Yep. There's not like a ton of complexity there beyond that that we'd know of. Yeah. And so what I'm interested in is like we saw the demo from, uh, from Google. on diffusion, text-based diffusion, 900 tokens a second. I've heard good reviews about that. I've heard kind of mixed reviews on that.

Maybe it's not a path. But what does the future of an LLM look like if we're applying the same path that we've seen in images where we're seeing an ensemble of models come together to create a better, like even more multimodal, multi-multu- like multi-architectures.

Because it feels like we're moving, moving further and further away from the single big transformer being the answer to everything. And so what does that mean? Are we going closer or farther away from the single big transformer that is like the god in the weights? Yeah, this is where I can offer a little bit of coaching for your audience. And maybe you, you guys have talked to a lot of people. So I don't know. This is where people usually say the term, make sure of experts. And they're wrong to use that. And sometimes they say make sure of agents, make sure of experts. They're incorrect. Anyway, we have talked with a lot of the Frontier Lab researchers.

None of them believe that that is the way forward. That is an optimization for the current thing, which is... Which one? A mixture of experts in that way? Like a mixture of architectures. Mixed of architectures. Okay. Yeah, so experiments, for example, with Jamba, from 1821 in Israel, where they mix, for

example, like a mamba layered with transformers. That seems to be promising, but even Noghazir, a correct character was just using the scaling out transformers. I asked a variant of the question you just stated to Nome Brown in an upcoming podcast that we did, we recorded it who haven't released it, he's the same way. He's like, anything you're trying to do fancy around mixing a weird architectures, it's just not going to scale, just scale the basic thing. And he's pretty strongly convicted in that.

I know people I can name a Gemini who is also pretty strongly convicted in that. I have a reason to suspect otherwise. Obviously, you can't shut this, shut down anything because it might be true. I'm just telling you what the people working on this would say because I asked the same. The last thing I wanted to kind of cover, I would want to get a sense of, you know, prediction markets are pricing in that Google continues to dominate on benchmarks, How much is Open AI even going to, how much do they even care about being at the top of benchmarks? Is it purely an ego thing or is it just about, you know, usability and value for users and code quality and things like that?

It's usability and value. I think you need to notice that the benchmarks that Google talks about at Google I.O are no longer the benchmarks that Open AI measures itself on. And, you know, I want to stay friends. But like, there are some that are more sus than others. Sure. And I think, like, at the end of the day, the customer will win. The only one that has not, there's clearly been caught out kind of lying, kind of like being, whatever, like, underperforming. I got to say it, it's Apple.

When they launched Apple Intelligence, we were all very excited about the Apple Intelligence paper, which is beautiful documents that had no. no evils apart from their own internal e-vails. So they were not accountable to the standard set of e-vails that everyone else has, right? So step one is you should try to hold yourself to some public benchmark. I know flawed, just do it, you know?

But and then, so Apple did not do that. And then like now there's a question of like, are you holding yourself to a benchmark that can be games? And there's been accusations of Elamarina being games. And unfortunately, that's what Google has put all its chips on. They may do that for Gemini 3. but for 2.5, that's what they did. And probably because they spent the last year doing it.

It's all revenue from here on out. Like, that is the benchmark. GitHub co-pilot, 500 million, size gone for GitHub. Revenue is also tricky. Yeah? You guys know how, like Gemini, I don't know if you know, Gemini gives a billion tokens the day per human. What?

Wait, you're a personal IP token. Okay. I'm cheating you. You can, you can set up a camera right now, run Gemini 2.5 flash on it, run like a frame of seconds and ask you to do whatever you want for free. Wow. It's absurd. So they are going to market.

Thank you. Intelligence is too cheap to meter. We love to hear it. Okay. Like that chart that you saw at Google I.O. where their tokens went like this. Now you know why it's free. Yeah. Yeah. Yeah. Yeah. I mean, they also have a very, very good model. Don't get me wrong.

But I'm just like revenue is a short-term play. Like you're trying to maximize revenue now, you might cut up, cut up yourself from getting the largest data set in the world, which is the early adopted humans that are going to give you their data because they're like, train on me, daddy. You're giving to me for free. Like, whatever, train on me. And that's a deal that lots of people, I think the theme that we talked about is lots of people are going to make. This is free. Why? They can eat your data.

Codex is free. Why? So I talked about this in one of my recent posts. Like the marginal cost of software has has gone down to zero. And like, can it go negative? Will I start paying you for me for you to use me? Absolutely, because then you'd become my labeler. Yeah.

You're a labler I can never pay for. You know, usually have to like hire someone like the Philippines or something. We've maxed them out. So now I got I got to pay someone in Silicon Valley to label my software. So I might as well just give you my coding agent for free or like even honestly just pay you for good. feedback on my coding agents. And why should it stop at like $20 a month when like there people in New York, who I've heard by the way, get, they're like, they hire former bankers, they hire a form of hedge fund guys, pin in 500K a year to label. It's wild. Well, thank you so much

for hopping on. Good luck with the rest of the conference. Let's make this a regular thing. This is fantastic conversation. Thank you for taking the time. And we'll be there next year. Yeah. Whether you like it or not. Fantastic. You're invited, for sure. We'll talk to you soon. Thanks so much for hop around. Thanks, Sean.

Bye. Cheers. Fantastic. Well, we got to tell you about wander. Find your happy place. Find your happy place. Book of Wander with inspiring views. Hotel great amenities,

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What? Only now. And Josh Koestner says, I'm deeply proud of the tenacity and persistence of the Oscar team. We've been humbled many times from down 95% from our IPO to now entering the Fortune 500. I am excited for all that is ahead of us. Wow. Congratulations to Josh Kushner.

That is a phenomenal run. Amazing. And somebody else was quote tweeting this saying that. But there's only two people who have incubated a Fortune 500 company who are actively investing. And it's Palantir with Peter Thiel and Founders Fund and Josh Kushner would Thrive and Oscar. So what a phenomenal run. It is rare, but the incubations are starting to work. And the incubations will continue until morale improves.

They will continue. Until the global economy is growing at 10% a year. Anyway, every person who works in tech needs at least five non-tech friends to interact with closely on a weekly basis so they can understand how the general public actually thinks, says Kit Volta. You posted this from a different account. It was a copy pasta. Somebody copied the whole thing. So I found the original. I shared the fake one, the rip-off.

I shared a rip-off. Yeah, you shared a rip-off. And it got community noted and I found the original one. Read it here. Wait, so somebody just stole it? Yeah. Yeah. They didn't even screenshot it and put it in.

bang her that is they actually but 20k on this post the repost has 15k likes and so it got but it got community noted this is a copy paste I you feel like that could be uh that could be like automated in acts where it's like this is the exact same text as has been posted elsewhere you should just know that you should maybe go to the source on this if somebody's posting the exact same thing except you know Josh Stein would get that every day because he's constantly boasting good morning we are going to win and so he would have the note every single day um JT Jira tickets says web You mean digital physiognomy? Very funny.

Oh, you put another one in here from JT. Guy who is burnt out from his six figures, five hours a week, big tech job. You got to just hit the roof and just get some sun, you know. Anyway, Pavel has a good one. I don't think Waymo can work in New York City because during rush hour, you need to break the law to get anywhere. And I'm not sure how you can get away with embedding that in software. And I.B. says, Travis would have gotten it done. Never too late.

Somebody says full self-driving gladly speeds for me. I thought this was good from Will two thick scoops. Okay, sounds good. Thank you. And it's Jersey Mike's order pickup at 1248. Dutch government collapses over migration dispute. Why is this? This is a Gmail.

Oh, it's just rolling up multiple emails or something. This is Apple AI summary. Oh, yeah. Apple AI strikes again. Apple intelligence is the summaries are so good. It's genius. 75,000 likes, that's a lot of attention on that. You've got to upgrade folks.

You're missing out of entertainment. I would pay Apple to help me produce Apple intelligent viral bangers. Yeah. I want to wrap up, but we got to say congratulations to Jesse Michaels. He got on Joe Rogan. He said it was the honor of a lifetime to sit down with a goat himself, Joe Rogan. Many people have called him a young Rogan. I've called him that.

He is fantastic. He's been on a fantastic run with American Alchemy, his podcast. He's climbing the charts. If you're into aliens, AI, Apocalypse, Bob Lazar, nuclear weapons, secret anti-gravity research, go check out the Jesse Michael's Joe Rogan Experience episode. It's episode 2,331. Rogan's putting up big numbers.

He's giving us a run, but we're catching up. It's wild. In other years, lastly, I just wanted to cover this quickly. AMD has acquired Breem. Oh, okay. It's been reported today to help reduce Nvidia's market dominance when it comes. to AI hardware. Talking to George Hots and we're going to have him on the show,

but he's been back in AMD. We got Dylan Patel coming out on the show Friday. We'll ask him more about AMD and they're playing to unseat Kuda as the dominant AI platform. And we have other news. We are officially, we have doubled the size of the show. Once again, Jordi hit that gong. Hit the real, hit the real gong for me.

Grab this. We're going to gong cam. We got 64,000. followers on X. Thank you for everyone who's been around. Oh, there we go. That's great. Thank you for watching. Thank you for supporting us. It's been a fantastic journey. It is a pleasure doing business. We got the whole crew in the studio. We got a whole bunch more cameras here. We're growing every day. Damn, we got the studio cam. The studio cams going. Thank you for watching. Thank you for all the support. Live us a five-star review and Apple podcast and Spotify. Yeah, I feel like we're doing

low there. Yeah, it doesn't really make sense. But if you're on Apple, And you're listening, and you haven't left us a review. We'd love a review. So thank you so much. And we'll see you tomorrow. We have an awesome day. We have a bit of an AI day coming together with folks from OpenAI and Anthropic coming on. It should be a great show.

So stay tuned. We'll see you tomorrow and have a great rest of your Wednesday. Goodbye. Cheers.