TBPN Live - The Lawyer Who Beat Meta and Google, Revisiting The Jetsons, Japan Twitter | Tae Kim, Logan Bartlett, Sam Stephenson, Ben Broca, Brett Adcock, Andrei Serban

Episode Date: March 30, 2026

Sign up for TBPN’s daily newsletter at TBPN.com(01:49) - The Lawyer Who Beat Meta and Google (15:44) - The Social Media Addiction Placebo Controlled Trial (32:54) - Revisiting The Jetsons... (42:16) - What I Hate Most About Hotel Room Tech (48:37) - Sysco to Acquire Restaurant Depot (51:08) - Office Chair Racing (01:00:08) - Tae Kim, a financial analyst and founder of the newsletter "Key Context," discusses the recent volatility in Nvidia's stock, attributing it to cyclical market fears rather than fundamental issues, and highlights the company's strategic acquisitions and partnerships, such as with Groq, to meet surging AI inference demand. He emphasizes Nvidia's proactive supply chain management and strong relationships with TSMC to secure wafer allocations, positioning the company to capitalize on the growing AI market. Additionally, Kim notes the increasing demand for CPUs driven by AI agents, suggesting a significant trend in the tech industry. (01:30:37) - Logan Bartlett, Managing Director at Redpoint Ventures, discusses the disconnect between public and private market valuations in the software industry, highlighting how public software companies trade at lower multiples compared to their private counterparts. He attributes this to public investors' concerns over stock-based compensation and questions about the long-term terminal value of these businesses. Bartlett also emphasizes the cultural challenges incumbent companies face in adapting to rapid technological shifts, particularly in integrating AI capabilities, which may hinder their ability to capture new market opportunities. (02:09:37) - Sam Stephenson, co-founder and CTO of Granola, an AI-powered meeting notepad, discusses the company's recent $125 million Series C funding led by Index Ventures, bringing its valuation to $1.5 billion. He highlights Granola's evolution from a personal note-taking app to an enterprise solution, emphasizing the importance of capturing meeting contexts to enhance company operations. Stephenson also addresses the challenges of integrating AI into meeting tools, noting the complexities of understanding social nuances and the necessity of building features that seamlessly fit into users' workflows. (02:23:38) - Ben Broca, founder of Polsia, discusses his AI platform that autonomously builds and manages companies by handling tasks such as product development, marketing, and customer support. He emphasizes the importance of configuring AI models with the right tools and orchestration to achieve desired outcomes, and highlights that while AI can automate operational tasks, human input remains crucial for aspects like branding and understanding market trends. Broca also shares that Polsia has rapidly grown, with over 500 companies utilizing the platform, and mentions the intentional naming of Polsia as "AI Slop" spelled backward to spark conversation. (02:34:28) - Brett Adcock, founder and CEO of Figure AI, has launched Hark, an AI lab focused on developing advanced personalized intelligence by integrating multimodal AI models with next-generation hardware interfaces. In the conversation, Adcock discusses the limitations of current AI systems and devices, emphasizing the need for proactive, personalized AI that can interact naturally through speech, text, and vision, and highlights Hark's efforts to address these gaps by building both the models and hardware interfaces necessary for a seamless AI experience. (02:44:47) - Andrei Serban is the founder and CEO of Console, an AI-driven platform that automates IT support tasks directly within communication tools like Slack. In the conversation, he discusses Console's recent launch of "Assistant," a feature that automates complex, multi-system tasks such as investigating internet outages and deploying software updates. He also highlights how Assistant enables IT teams to build their own integrations, allowing for rapid adaptation to specific needs without extensive engineering resources. 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Starting point is 00:00:00 You're watching TBPN. Today is Monday, Marks 30th, 2026. We are live from the TBPN Ultradome. The Temple of Technology, the fortress of finance, the capital of capital. Let me tell you about ramp.com, baby. Time is money. Save both. These use corporate cards, bill pay accounting and a whole lot more all in one place.
Starting point is 00:00:19 Let's pull up the linear lineup. We got Take Him coming on to give us the Nvidia update. He is, of course, the founder of Key Context, the substack. Logan Barlett's coming on from Red Point. Been way too long since we had him on. Been probably over a year at this point, maybe nearly a year. But he drops one of the greatest market updates, slide decks, analyses. Very, very good.
Starting point is 00:00:43 Tons of really interesting tidbits in there. And then we have a fantastic. It's a great thing. Lightning round for you today. Linear, of course, is the system for modern software development. 70% of enterprise works based on linear are using agents. So, lightning round. We got Ben Broca from Paul C.
Starting point is 00:00:58 Sam, founder of Granola, on their $1.5 billion dollar valuation. And then Brett Adcock. What was your nickname for him again? Who? Brett Adcock? You had some nickname for him.
Starting point is 00:01:10 No? No, I didn't. Must have been someone else. Oh, you're on a first name basis. You just call him Brett. Brett. Yeah. Or just B.
Starting point is 00:01:17 Yeah. Hey, B. Hey, B. Now, this would be interesting. He launched a NeoLab last week. Oh, yeah, that's right. And so we're going to be able to talk to him about that. Models and hardware.
Starting point is 00:01:26 Hark. I hear the angel singing. And then Andre from Consul joining as well. So looking forward to that. Well, I've been addicted to social media lawsuits. I cannot get enough of these lawsuits. I keep reading about them, losing sleep. You're potentially filing your own lawsuit against the lawyers that were coming after these social media.
Starting point is 00:01:49 Yeah, yeah. So there's actually a profile in the Wall Street Journal, in the exchange this weekend, the lawyer who beat Meta and Google. and it goes into some of his addictive techniques that are driving jurors crazy across the country. Attorney Mark Lanier, he uses props. Come on. What's more than props?
Starting point is 00:02:11 He also uses parables. What? Parables. Metaphors, axioms, all of the above. He moonlights as a preacher, and it shows when he's taking on the world's most powerful companies. the 65-year-old came to court in downtown Los Angeles for closing arguments this month of one of the biggest trials of his career armed with a parable of leavened bread.
Starting point is 00:02:36 That feels like something that is designed to make it hard to rip yourself away from. Exactly. So he knew he needed a simple way to show a jury that met his Instagram and Google's YouTube were designed to be addictive and were harmful to young people. So the veteran plaintiff's lawyer from Texas. He looks fantastic for 65. He does look fantastic. And as much so joking, I do think he's doing important work,
Starting point is 00:03:00 and I do think there's a potentially really good outcome here that we'll go into. But we're still having some fun. So the veteran plaintiff's lawyer from Texas showed them two grocery items, cupcakes and tortillas. Social media, he told the courtroom was like the baking powder that makes a cake rise. exacerbating the struggles of already vulnerable teens. We have an interactor, an amplifier, something that blows it up, linear said. We have here social media that takes the vulnerable and goes after them in destructive ways.
Starting point is 00:03:38 It's as easy as ABC. So he's making the argument that social media is more like cupcakes than tortillas, both contain flour, both are carb, carbohydrate loaded. but one is bigger than the other, or puffier, I suppose. The simple image delivered with Lanier's slight draw helped convince a majority of jurors. On Wednesday, the ninth day of deliberation, the jury found that META and YouTube were negligent in a case that accused the companies
Starting point is 00:04:06 of designing their apps to be addictive and harmful to teens. And there's some interesting images, both of him walking into the courthouse with a large box of papers, clearly very anti-tech movement, there. He's saying, I reject technology. This cannot be stored digitally. I'm using paper. Which, I don't know, this seems a little bit risky because we've been addicted to the printed word in the past, so much so that we face criticism from people that said, hey, printing is
Starting point is 00:04:39 unnecessary. They did. You're not environmentally friendly, but we were forced to adjust. Maybe he can flip over to be our defense attorney when we are attacked. There is a courtroom sketch showing linear questioning former TBPN guest, Adam Masseri, the head of Metas, Instagram. A jury ordered the company to pay $3 million each in compensatory damages and $3 million in punitive damages. So I think it's $6 million across both firms, but it's split compensatory and punitive damages. And now a now 20-year-old woman named Kaylee, whose last name was redacted in the case. She had testified that social media use that started when she was a child, dominated her life for years and contributed to mental health issues, including anxiety, depression, and body dysmorphia. Very, very sad situation,
Starting point is 00:05:25 very unfortunate for her, of course. In a statement, META said it disagrees with the verdict and plans to pursue an appeal, reducing something as complex as teen mental health to a single cause risk, risks leaving the many broader issues teens face today unaddressed. Not mutually exclusive, but of course that is a reasonable position for META to take. Google also put out a statement. What do you think? They're like, we're not even a social media company. We're a VR company. No, no, no.
Starting point is 00:05:55 Google said, misunderstands YouTube, which is a responsibly built streaming platform, not a social media site. That's true. Got the wrong guy. Yeah, I think of YouTube very much as in the same world as social media, anyone can post. But it is severely lacking in some of the greatest features of that social media sites. It's like you, when you actually become a YouTuber, you start putting out content that, like, there is sort of, I don't know, like a group of made men on YouTube, like people that have ascended. And they now have, they're now making content like professionally and they are in conversation with each other and they might be reacting to each other's content.
Starting point is 00:06:39 And of course, there are different communities. There's like the car YouTuber community. And then there's the, you know, the game show community and there's the business community. And pretty quickly, everyone sort of gets to know each other. But there's no DM feature. So even if I make a video... Which is a good argument for it not being social media. Not being a social media.
Starting point is 00:06:59 Yeah. Yeah. So, like, you know, we at this point have done the Colin and Samir show. But we don't really have a way... Like, we can go on to the Colin Samir YouTube channel and leave them a comment and they might see it if it's from the TVPN account, but we can't, like, just DM them and be surfaced to the top of the inbox. People have always wanted an inbox on YouTube. Yeah, that's a huge feature request.
Starting point is 00:07:21 It's insane, because, like, it would be so cool to be able to see, okay, I got a DM from someone who has 100,000 followers, and I can click on their profile and see, oh, they're, like, you know, in the same niche, like, maybe we'd want to work together, maybe we want to collab on a video or do something else, because they're, like, an established YouTuber, as opposed to everyone basically needs to flow over to Twitter or X and then DM there because the DM functionality is much more mature on the other thing Google has in the in this kind of position is that so much of the watch time on YouTube is happening on television. Oh yeah.
Starting point is 00:07:58 Something like 50%. Yep. And so they can make the argument that this is just modern television. Yeah. So let's go through Linear's career because the Wall Street Journal has some interesting backstory here. He says Linear has built. a career in fortune representing plaintiffs against corporate giants. He won one of the first major wrongful death trials against pharma company Merck over claims that the prescription anti-inflammatory
Starting point is 00:08:23 drug Vioxx caused heart problems. He also won a $4.69 billion verdict in 2018 for women and their families who said, asbestos tainted talcum powder caused ovarian cancer. So, I mean, over his career, it seems like he's done some very, very good work and has won some massive, massive settlements against big companies with broadly damaging products. So a lot to admire about his career here. The social media trial drew more scrutiny than he predicted before he joined the plaintiff's team last fall and was brought face-to-face with meta-chief executive Mark Zuckerberg. Suddenly, Lanier was at the episode. I believe that Zuck is actually mewing in this picture.
Starting point is 00:09:10 If we can pull up this image. It does appear to be something along those lines. Suddenly, Lanier was at the epicenter. You agree, Tyler, right? You can tell his cortisol is not spiking here. That's true. That definitely seems. He seems calm, collected.
Starting point is 00:09:24 But this is not his first time putting on a suit. This is not the first time he's been in court. Suddenly, Lanier was at the epicenter of a broad public debate about social media and how people stay connected or are disconnected on platforms offering nearly endless content curated by algorithms. Quote, nothing compared to this, Lanier said, reflecting on the attention to the trial over oatmeal toast and a Coke Zero
Starting point is 00:09:46 in downtown Los Angeles, in a downtown Los Angeles hotel the morning after the victory. Nothing even remotely close, and I think that's accurate because even though those previous settlements were huge, they weren't major, they didn't break through to the point
Starting point is 00:10:01 where I remember them vividly. Do you? No. No. Viox? It does not ring a bell. But this certainly well, for a lot of people, especially in tech. Social media companies have largely been shielded from being held liable for third-party
Starting point is 00:10:14 content on their platforms by Section 230 of the 1996 Communications Decency Act. At trial, Lanier had to focus on the platform's features, not the content to make a case. And that's something that I want to talk about today, and I wrote about it in the newsletter. The trial was the first among the first among thousands of consolidated lawsuits filed by teenagers, school districts, and state attorneys against meta, YouTube, TikTok, and Snap, more are scheduled for this year. TikTok and Snap settled the first case. A Christian who teaches Bible study classes to as many as 500 people in an evangelical church, Lanier turns a folksy courtroom demeanor honed over decades of trial work,
Starting point is 00:10:57 burst in Texas, now nationally. He's known for showing jurors hand-drawn roadmaps and illustrations on an overhead projector to guide them through his legal reasoning and evidence, including signposts and human figures that could have been sketched by a child. To visualize microscopic asbestos fibers in talcum powder, he brought a bale of hay into a courtroom and dropped a needle into the blades.
Starting point is 00:11:24 Into the blades of grass. Oh, the blades of hay. Got it. Okay, wow. Very, very interesting. He likes, he likes, He likes props. That's it.
Starting point is 00:11:37 When arguing for punitive damages against the tech company, Lanier, held up a jar. Seems quite addictive. This is a good point. So he held up a jar of 415 M&Ms to show how a $1 billion fine would be a fraction of Alphabet's $415 billion in shareholder equity. He needs a bigger jar because I think every tech company is five times larger now. He says he tries to avoid being flashy himself. He wears the same two unremarkable suits on rotation during a trial, and then I go burn them. What?
Starting point is 00:12:10 He burns his suits after. Is that a joke or he gives them away? I don't know. My work here is done? I guess. Retire it's, I guess. I don't know. It's odd.
Starting point is 00:12:20 Lanier graduated from college at 20 and is trained as a minister before going to law school at Texas Tech University, hoping to make enough money to support his preaching. He began gaining renown as a lawyer in an era when asbestos cases were swamping the U.S. course. He won a jury verdict of about 115 million in 1998 for 21 steel workers who felt ill after using machinery that contained asbestos. Lanier and his wife, Becky, met in high school debate class. They have five children and 12 grandchildren. Wow. Overnight success.
Starting point is 00:12:50 They were known for years for their child-friendly Christmas parties at their estate of more than 35 acres near Houston, which has a model railroad that can seat 120 people. Okay. This guy's got to win. I have completely changed my position here. You need a mansion section, an article. This is incredible. I think we have a direct line to him, by the way. Okay.
Starting point is 00:13:11 We want him on the show. Well, like, maybe we should go do a show from the, from the model train. Yes. I'm so ready to be convinced of his position. I wrote a whole piece about how I disagree with the result, but he's winning me over. Disagree with this entire argument, but you're agreeing with this approach to life.
Starting point is 00:13:28 Yes. 100%. 100%. I feel like we're kindred spirits. It's amazing. So the model railroad can see 120 people and guess what? He's got a menagerie. There we go.
Starting point is 00:13:40 This is goals. You need to be menagerie maxing in life. You need a menagerie. His contains lemurs. There we go. And llamas. There we go. Leemers and llamas.
Starting point is 00:13:52 This is incredible. The family pulled the plug on the party, which featured up to 9,000 guests. And performers, including Miley Cyrus, Johnny Cash and Dolly Parton, he said, because it was too hard on the lawn. The guy cares about his grass too much. This is incredible. Inviting 9,000. He's an environmentalist.
Starting point is 00:14:11 From the community. I mean, that's like the entire, I mean, Houston's a huge city, but that's like, that is so, what a pillar of the community. This guy's a hero. Lanier said, the theme of his cases against major corporations
Starting point is 00:14:25 is responsibility and integrity or lack of it. Tech billionaires don't need his help, Lanier said, but Kaylee would not have anybody else. faith is much the same way. God's there to try to help people who need the help. Two of Lanier's daughters who are lawyers were by his side during the trial. He joined the social media case. By the way, you keep saying linear. Is it Lanier or linear? Lanier? Lanier? Leneer? I think it's linear. Well, we'll figure it out. He has deep authenticity. I just don't want people to get
Starting point is 00:14:55 confused with the system for modern. Yes, it's not linear. It's Lanier, I think. Maybe. Maybe it's Lanier. Maybe it's French. He's not a phony. What he does is not a performance. Even from Los Angeles, he posted short video selfies discussing Bible passages on YouTube. So he's dog fooding, the thing that he's suing. Yeah, let's switch gears to your piece. I will take you through my counter argument. But first, I'll tell you about Shopify. Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on marketplace. and now with AI agents.
Starting point is 00:15:34 And let me also tell you about Gemini. Gemini 3.1 Pro is here with a more capable baseline. It's great for super complex tasks like visualizing difficult concepts, synthesizing data into a single view or bringing creative projects to life. So last week, Brandon Gorell summarized the ruling this way. He said in the case, the plaintiff's lawyer, Lark, Mark Lanier, argued that meta and YouTube built digital casinos that used neurobiological techniques similar to those employed by slot machines,
Starting point is 00:16:02 the jury found that specific features of meta and YouTube are designed to be addictive. And I want you to really hone in on these features. So infinite scroll creates an environment where there are no natural stopping points. Algorithmic recommendation feeds users highly engaging content. Algorithmic recommendations feeds users highly engaging content.
Starting point is 00:16:27 Autoplay removes users. agency in choosing whether to watch the next video. Notifications pull users back in by exploiting their need for validation. IG beauty filters contribute to the plaintiff's body dysmorphia and features like the like button exploit users biological need for social approval. Okay, so you got a bunch of features. You know this stuff. Everyone uses social media. We all know about this stuff. The question is like is, are the features addictive or is the content addictive because social media platforms are of course protected from the content that it is posted on the media. And Lanier's entire argument is predicated on it being the features, right?
Starting point is 00:17:05 Yes, the features. Okay. And, yeah. So the, so, you know, we talked to Eric Goldman from Santa Clara University of Law and he was saying that like, yes, it's $6 million settlement right now, but this is, this could be huge. The direct quote was whether we will even have social media in the future. Like, this could be existential.
Starting point is 00:17:22 Yeah. And there's thousands of other cases. like this kind of percolating, right? And so... And they could turn into a class action. He's gotten $6 billion before. He could get $50 billion. I don't know. He could get a lot. And he's not, like, $6 million is, he's not a $6 million guy. He's a $6 billion guy. And so this is the precursor, and it's going further. And whether it's a ton of different cases or one big one, like, it's a big problem for the tech companies. So I thought it was an odd coincidence that we sort of had what I called the placebo-controlled trial for these exact features last week when SORA shut down.
Starting point is 00:18:01 So opening eyes, nascent social network, SORA shut down. The reaction of the news was funny to watch because a lot of people were like, yeah, I told you it was always bad. But when it launched, it was exactly the opposite. Everyone was like, it's too good. We won't be able to look away. It's simply too good. And Rune summarized this pretty well, I think, yesterday.
Starting point is 00:18:20 or I think it was yesterday. He said, SORA was peak moral panic. All of these breathless takes about making videos that are going to addict humanity and waste everyone's time. Meanwhile, we made some funny videos that were less funny as time went on, and AI Slop is just one category
Starting point is 00:18:35 among many on Instagram Reels. Don't worry so much about making videos that are going to blow up people's brains without making anything good at, without worry about making anything good at all. The best Soras were up there with the best reels, and the humor relied significantly
Starting point is 00:18:50 on the voice of the creator, I completely agree. The funny sores that I... Yeah, even the video we played last week of the cat on the porch. Yes. That wasn't a one-shot it. Yeah. The prompt was not, was not make something that will retain users. And it wouldn't have been funny if the person hadn't been escalating, like, the scene every new prompt. Totally. And then stringing them together.
Starting point is 00:19:11 Yeah. And so, and he closes by saying, I know so many of you who are loudly concerned about this, who won't update at all, who will remain pestilessing. pessimistic about humans and their ability to use tools. And I said, so like what do you make of these two situations? It feels a little bit like a placebo controlled trial to me. Of course, like there's a lot more nuance here. This is like a high level take, but Sora absolutely used all of the social media best practices or addictive and harmful neurobiological techniques if you want to use the course language. Soar app was basically the same as TikTok, Instagram Reels, YouTube shorts, Snap, in terms of UI and UX design. It had information.
Starting point is 00:19:50 it scroll, it had algorithmic recommendations, it had notifications, it had a like button, and it didn't have IG beauty filters, but like the whole thing is a filter, because I could go in there and say, make me look like a bodybuilder, and it did a good job, and I looked great in the videos. And so, like, it is, it really checks all of the same boxes. To try to like match that everything. It gave me, crippling brought body dysmorphia, obviously. I dream for the, for the day when I will look like my Sora avatar, my, what do they call it? Camia? Like camio? No, but they really did use all the normal tools.
Starting point is 00:20:26 And that was for familiarity, but also because they're moving quickly. And the key innovation was not the UI design or the fact that it's vertical or algorithmic feeds. Like, we are in 2026. We're not in 2014 when we're launching Vine. So the key insight was purely AI generated content. And it didn't work. Like the features were not addictive.
Starting point is 00:20:50 because the people that downloaded SORA did not become addictive because the content was a little bit too sloppy, right? Yeah, well, it was just one type of content and it turns out people like a broad selection and they like variability. They might want to see a video of someone skiing and then some slop and then something their friend made
Starting point is 00:21:10 and then some health content. And it's really the collection of that. The other thing I think that seems very obvious is if it was the product itself, and the features that we're addicting, there would be so many social media, there would be so many social media apps that were effectively thriving.
Starting point is 00:21:29 There would be like a bunch of Instagram. And this is where I get to the cigarette comparison. So there's a bunch of comparisons to the cigarette industry, and I think it's really worth revisiting, like, what is addictive about cigarettes? Because there are some people that say, like, it's an oral fixation, like you just want to put, like, a stick in your mouth so you should, like, switch to carrots.
Starting point is 00:21:45 Like, that is, like, maybe like 1%. Some could argue it's an addiction, and looking cool. There you go. But it is the nicotine. It is the nicotine. And that's why you do have a long tail of like 50 different cigarette brands
Starting point is 00:21:58 and a thousand different e-cigarette brands. And nicotine gum is addictive. Nicotine patches are addictive. Nicotine pouches are addictive because they all contain the nicotine. And if the court is asking us to believe that the like button, the algorithmic feed, that is addictive,
Starting point is 00:22:14 then we should see addiction-like results from any app that impoverimple. that because that is the case for all nicotine-containing products. They all addict people at, I mean, there are less addictive formats, but in general. How many apps have you tried or test flights over the years that had any of these features that you used for 30 seconds? Exactly. Exactly. Because what actually keeps you coming back is the content, which is created by the users. And so you're at, you want Lanier to go after every single person that has ever posted anything on Instagram and jail them.
Starting point is 00:22:49 Correct. No. No. I think that some creators do create very compelling content. Some of that content is, no, some of that content is amazing. Some of that content is great. Some of that content is bad. There's a very, very wide range.
Starting point is 00:23:09 You can go to truly amazing educational content. I'm thinking of like three blue, one brown, this math channel that does visualizations of math concepts on YouTube. It's incredible. Andre Carpathie's YouTube videos. There's so many interesting educational history shows, podcasts. There's so much content that you do keep watching. Tyler got addicted to that video,
Starting point is 00:23:29 Are you destined to deal? That's a great video. He kept saying, why you have a tie on today. He called me on Friday night and said, why is this video 20 hours long? Because he had on loop? Yeah, he was just loop. That makes sense.
Starting point is 00:23:45 That makes sense. So, yeah, but I mean, but it is true. Like, I think the court is correct and Lanier is correct that some people go on social media and make horrible content that depresses people that land on it. And it goes out saying that social media companies do have an enormous responsibility to manage recommendation feeds responsibly and route people in tough situations to helpful resources. So Google already does this very, very well. If you type in specific keywords that seem like you're in a mental health crisis, like it will not give you search results. It will give you a phone number for some. someone to call and they know when to route the right people to that.
Starting point is 00:24:20 And I do believe that all the tech platforms are thinking about this and implementing this. Maybe they need to be more aggressive. I think that the big thing that most people can agree on is parental controls here. And I think that that's like a much easier like middle ground here. And just in general, one other nice meet in the middle option is potentially just, you know, getting tech companies to give users and parents in particular, but users broadly, more control over their experience. So it's possible to disable algorithmic feeds, endless scroll, the like button with browser
Starting point is 00:24:55 plugins on mobile web, but it's a much worse experience because you have to load it on mobile web, which isn't the actual app, and it's slower. And there's a lot of things that are just kind of janky and don't load as well. But having those in the settings to just say, like, I know some creators on Instagram can turn off the like counter. Have you ever seen this? So you can see someone post a post an image and it and it'll just have a like button there, but it doesn't have like 5,000 likes because the creators were getting like, you know, annoyed by, oh, this one. Well, to be clear, that's because people didn't want to post. Yeah. Because they were worried something wouldn't do well. Yeah. And
Starting point is 00:25:35 and the world would know that their content was not engaging or something like that. Yeah. So that was just an, that that effectively is just an incentive. I don't believe. that that was done for the mental health of the creators? No? That was done to encourage more people to post. I don't know. I don't know. I mean, I'm sure.
Starting point is 00:25:55 Like, my mental health as a social media creator was at an all-time high before I understood the metrics. Because I was just like, oh, 300 views? I'm famous. This is amazing. 300 people sat down and watched my 10-minute video essay about a dying VR technology or something like that. It's like, I've done it. 300 people sat down. It's like I'm a business school professor, basically.
Starting point is 00:26:18 Yeah? Yeah. But then eventually you get and you're like, wait, like the last video got 400,000 views. Why does this one have 375,000 views? I'm a failure. So like, there is a little bit of that. But I hear you. Yeah, but the metrics are still available to the creators.
Starting point is 00:26:33 Yeah, yeah. You can, the creator, the person that posted it. But you can't. With a Chrome plugin. You actually can't. There's some creators that do this. But anyway, like surfacing those in apps, I think that will help. users feel like they're in more control. And realistically, I don't think it will be super
Starting point is 00:26:50 damaging to any of the platforms because most people won't opt into that, but certain people will. And in general, it'll just like increase public perception broadly. We've already seen this with a lot of the LLM companies where like, you can go in, you can fine tune and add a custom prompt and kind of talk to it about what you like and don't like, change the personality. I think people have been asking for that for a long time, surfacing it. It seems like a win-win. And so something, something along those lines seems, seems in the cards. Anyway, we can debate this, but first, let me tell you about Century. Century shows developers what's broken and helps them fix it fast.
Starting point is 00:27:24 That's why 150,000 organizations use it to keep their apps working. And let me also tell you about Plaid. Plaid powers the apps you use to spend, say, borrow, and invest. Securely connecting bank accounts to move money, fight fraud, and improve lending. Now with AI. So, do you have any other pushback on my take? Tyler had some pushback. Should we go to him?
Starting point is 00:27:43 Go to Tyler. What do you think? I mean, yes, I guess there was a few things. I mean, one thing is that like... Not enough props, right? Too many analogies? Too many parables. Like, I think you can say that
Starting point is 00:27:53 like, okay, yeah, it's the content. That's the problem. But like, the content is like kind of downstream of the features, right? Because you didn't see like short form video. The medium is the message. Yes. And so it is possible for me to create a platform
Starting point is 00:28:07 that incentivizes addictive content. And that's like the retention curve. So retention editing makes it more addictive. You become addicted to the content, but it's because of the features. Yeah. So I think that's like broadly. Pretty good argument. The steel man that you can make for like Lanier's position.
Starting point is 00:28:23 And then, I mean, there's other stuff. I think on like just the nicotine analogy we were talking about this, like, okay, so you have nicotine like broadly. And then below nicotine, you have like smoking, which is like definitely very bad for you. And then you have like, you know, pouches or stuff like this, which is like probably less bad, like, it's just the nicotine. There's no tobacco, so, like, maybe this is, like, less bad. So maybe the equivalent is, like, you know, the cool
Starting point is 00:28:47 snowboarding videos on Instagram are, like, the, you know, the cleaner, like, nicotine stuff, and then the, like, graphic. Still addictive, but not harmful. Yes. And then there's, there is, like, you're going to try and do a double cork 1260 and eat it. Get smoked. It's smoked into the ground. Yeah, but then on other side, you have, like,
Starting point is 00:29:05 the, like, you know, very graphic stuff on Instagram that, like, we don't want people to see. and that's like the, you know, the cigarettes, that's, like, going to give you cancer or whatever. Sure, sure. So I think they're, like, I mean, I guess it's still in agreement with what you're saying, but, like, well, this is what, like, nicotine.
Starting point is 00:29:19 Yeah, this is what the cigarette has, if you're under 18, you can't buy. Which was, like, there was an addictive component, and then there was a carcinogenic component, and they needed to sort of separate those out. And where we landed as a society was, like, the addictive component is acceptable for the, it's suitable for the protection of public health,
Starting point is 00:29:35 according to the FDA. And so they are approving new products that are addictive but not carcinogenic. And so you would imagine, even in the most strict ruling where every new social media platform needs to be approved, you could potentially use all of those addictive features
Starting point is 00:29:49 as long as the content was not carcinogenic inside that app. And that would be like a new nicotine gum basically. Yeah, like basically I'm saying like right now if you're under 18, you can still, like there's like parental controls and you can't be under 13 or whatever, but like it's like very not,
Starting point is 00:30:06 it's like poorly enforced. you can actually see a lot of the bad stuff if you're under 18 on the screen or whatever. Yep. So like directionally, like, you know, you can be against the ruling of this. Yeah. But like the parental controls that people are like ice for are still like very much not there. Yeah. Yeah.
Starting point is 00:30:23 No, that makes sense. So I think I have a potential solution. Let's pull up this image of a cigarette package in Europe. Oh, yeah. What is this? So pull this up. This is the hardest challenge. Well, we pull it up.
Starting point is 00:30:38 me tell you about ACTA. Octa helps you assign every age and a trust identity. So you get the power of AI without the risk. Secure every agent, secure any agent. And let me also tell you about turbo puffer. There we go. We're puffing. Built from first principles and object storage, fast, 10x cheaper and extremely scalable. Okay. So this is like typical cigarette packaging in Europe. John, you probably wouldn't know this because you're very American and you're very loyal and you don't, you, you avoid overseas trips as much as possible. So on any given cigarette pack in Europe, you're going to see like a really terrible image. This woman apparently is coughing up blood. And so I think what a potential solution
Starting point is 00:31:17 that Meta could do is as soon as you open Instagram, it makes an AI generated image based on the last picture of you that you posted on social media. And it just makes you look terrible. Oh. And it says like warning like social media will destroy you. And then you can scroll past it. It could potentially show you with tech neck. Are you familiar with tech? Techneck. You go like this. Yes. Yes.
Starting point is 00:31:42 Yes. It's just a crazy image of you with tech neck. It shows you a tech neck. And then so you can scroll past it. Yeah. Every time you open that. It's a reminder. It's a new image.
Starting point is 00:31:51 It's a new image of you looking the worst, wasting your life away. Are the AI labs lobbying to get this removed? All right. We can put this away. Are the AI labs lobbying to get that removed? Because I think most of their timelines suggest that lung cancer will be cured by AI any day now. So potentially you could start smoking again.
Starting point is 00:32:09 Has anyone come out as pro-smoking? I don't think anthropics come out with their anti-anthropic, you know, has the joke that they make with journalists that kind of got caught on. But if AI is going to cure liver cancer, it's game on. It's game on. It's game on. You can drink as much as you want because that's, because you get liver disease if you drink too much. And so if AI, if I'm going to be able to vibe code an MRI vaccine to cure my liver cancer,
Starting point is 00:32:36 I'm going to be boozing for sure. It's the only rational thing to do. Yeah, well, this is also kind of like when... I'm sort of a rational. When companies are saying like, oh, yeah, work-like balance is super important. Yeah. So then their competitors will, you know... Yes, yes, yes.
Starting point is 00:32:50 People on topics should tell people to open AI to start drinking a lot because the AGI is going to cure liver. Yes, yes, yes, yes. This is good. This is good. Let's revisit the Jetsons. Okay, revisit the Jetsons. I'm sure you've seen the Jetsons. Where's my flying car and three-hour workday? So I'm going to be learning about the Jetsons.
Starting point is 00:33:05 Okay. John is going to be revisiting. The 1960s version of the future is way more fun than our reality, but when it comes to innovations, we're catching up. Interesting. Let's see. Nicole says, I recently spent a weekend doing deep investigative research into future technologies.
Starting point is 00:33:22 I binged the Jetsons in my sweatpants. For the uninitiated, the forgetful, this space age family sitcom features George and Jane Jetson, living the American dream in an apartment in the sky with their two children, dog astro and robot maid rosy the show is set in 2062 a century ahead from its original 1962 air date it's full of fantastical inventions such as flying cars dinner generating machines and canine treadmels complete with fire hydrants the upbeat vibe is markedly different from the apocalyptic at times murderous sci-fi of today the 1960s were full of optimism about what the
Starting point is 00:33:58 21st century would bring and some of it actually has come true while we've still got a few decades before the Jetson family is meant to arrive, I dug into some of the shows technological hallmarks and determined how close we already are. Video calling. She says, absolutely. In lieu of a home phone, the Jetsons had a video phone. Shows' creators couldn't fathom mobile devices,
Starting point is 00:34:19 but they were spot on about video calling. Now, to be clear, we are still working on, with one of our business associates, like a video call that doesn't stop halfway through and just cancel. So the Jetsons didn't predict. the free tier of Zoom. Yeah, the free tier of Zoom was not considered in the Jetsons where you're talking to
Starting point is 00:34:42 someone. They couldn't fathom it. You're clearly going to go long on the meeting and Zoom's just like, goodbye. It's over. It's over. It kicks everyone out with no notice. Is that a new thing? I feel like it used to do a countdown. I think it did a countdown too, but now it's just like, get out of here. We want to embarrass the host. The plus tier is going to blow. And so in the Jetsons, they could even create deepfakes to stand in for them on camera. Whoa. That's cool. I didn't realize that.
Starting point is 00:35:08 FaceTime's got on the... Oh, this is funny. You know, the other thing they haven't cracked with FaceTime is, like, if you FaceTime a group of people, like most of the people won't even know the notification and don't know that it's happening. So we haven't cracked the notification part of that I'm called. This is good. Read this next slide. When George secretly attended a robot football game, his simulochrum told Jane he had to work late.
Starting point is 00:35:31 He's like using a deep. fake to lie to his wife? This is so 60s. Do not do this. Do not do this. This is dystopia. It's not all optimism. Flying cars and travel tubes, sort of.
Starting point is 00:35:44 There isn't much walking in orbit city. A conveyor belt brings George from bed to the bathroom to get to and from his classroom. Elroy jets through a series of air tubes called the school homing network. When the wrong child shows up at the Jetson's home, Jensen sends, Jane sends him back with the push of a button. And they also use personal vehicles. though ones that typically fly, George arrow commutes, and a glass dome saucer that folds into a briefcase. Okay, that's pretty cool.
Starting point is 00:36:09 We're pretty far from there. We do have helicopters, but they're very expensive. I always fight people on the flying cars don't exist thing because, like, we do have helicopters, and some people get to use those, but they are not nearly cheap enough. But we've got to get them way down. Here in the actual future, we're still toting around on pavement pounding automobiles. A version of flying cars, however, is very real. It's called an EV toll.
Starting point is 00:36:32 Look at this. Pivotal Blackfly is a solo piloted aircraft free to operate an unrestricted spares airspace. An upgraded version called the Helix can be yours for 190K. You don't even need a pilot's license. That's like pretty close. But I mean, I would still say like we are not near the flying car because they're just not. They're way less flying car rides than Waymo's for example. So we're just not right there. Push button jobs almost. George Works is a digital. index operator at Spacely Space Sprockets for approximately three hours a day, three days a week. As a button pusher, he makes enough to support a family of four, even though a majority of his day is spent with his feet up on his desk. Okay, they basically nailed this. There's some people out there that are basically button pushers right now, vibe coding. TBD on the revenue side. True. But working three hours a day, three days a week, you know, we work three hours a day.
Starting point is 00:37:32 five days a week. And maybe the future's three, just Monday, Wednesday, Friday streams. We can live the Jetson's future. I don't know. That would be, that would be devastating for us. Yeah, until then, we'll be the working long time.
Starting point is 00:37:47 Space colonization, nope. Yeah, they live above Earth with houses built on tall stilts. I like that. To avoid the planet's environmental inconveniences, the stilts can rise above any inclement weather. And space itself isn't. out of reach. In a classic episode, Elroy goes to an asteroid on a school-filled trip. We're not quite there. Musk had preached of populating Mars, but now his focus has turned closer to the moon.
Starting point is 00:38:13 Meanwhile, an interplanary space race between U.S.-China, Russia, and UAE, and the European Space Agency is well underway. Robot-maids, not exactly, but we're getting much closer there. It's funny that Brett Adcock's coming on today. Yeah. And he's working on the flying car. Yeah. He's working on the robot made. Working on the robot made. He doesn't have a space thing yet. He's now working. His new lab is basically like a button, you know,
Starting point is 00:38:37 seems like a button pusher. Gadget in new, gadget induced pain, yes. And now for the show's biggest oversight, no touch screens. There are lots of visual displays, but they're primarily operated by dials, levers, and other physical controls. We got some levers back there in the studio. While the show may not have anticipated touchscreens,
Starting point is 00:38:57 it nailed a key side effect of constant use of gadgets. additive motion injuries. Orbit City is full of buttons and overworked fingers are a running gag on the show. Jane regularly does digit workouts and complains that her pointers are sore. Here in 2026 office workers often suffer from texting thumb after scrolling through endless feeds and tech neck after craning down to look at mobile devices. And don't get me started on my strained hand with carpal tunnel syndrome from all the clicking. 36 years and counting. We may not be living as exceptional a future as the Jetsons, but we've still got three and a half decades to catch up.
Starting point is 00:39:36 By then, I will be twice as old as I am now. I've already witnessed the dawn of high-speed internet, the iPhone and generative AI. How many tech revolutions will we experience in another 36 years? By the time we hit the show's 2062 deadline, maybe we will finally live in space or make our current planet more habitable and make a comfortable living on a nine-hour work week. Tyler, what do you think? predict your timelines for 2062, will we get space colonization? How do you define space colonization?
Starting point is 00:40:06 Living not on the earth above the Carmen line for like that's your primary residence, like more than half the year. How many people do it? Like just you can do that? Like anyone can do that? Yes. Anyone with like a, like if you can afford like a apartment for a few thousand dollars or like a house that's above $500,000 in America, you can choose to live in space. So I would assume
Starting point is 00:40:33 population of millions. It probably depends on the industry that is chiefly, you know, benefited from people living there. Button pushing? Well, big news. Sean Frank is in the chat. He says, I'm here, guys, H-E-A-R, which, so he's saying I, he's trying to signal that he's listening. him here. To you, Tyler, and to you, John. Well, thank you for coming in. Let's, uh, let's read him some ads since he's here. Let's tell him about Restream. One live stream, 30 plus destinations. If you want to multi-stream, Sean, go to re-stream.com. And you know what we got to tell them about? We got to tell them about app love and profitable advertising made easy with axon.ai.
Starting point is 00:41:16 Sean, get access to over one billion daily active users and grow your business today. Andrew Reed says the faster technology progresses, the harder it gets to print something in the office. We have experienced this. It's very true. Aaron from Bach says, Reed's law. I know you may have wanted a better law,
Starting point is 00:41:35 but I don't make the rules. Yeah, it's very, very difficult. Apple has just like never done the printer. I think for environmental reasons. I'm not exactly sure. But like there's never been like, oh, the gold standard, the Tesla of printer is just like the one you get and it does what it wants.
Starting point is 00:41:56 It just does everything flawlessly, and it's at that, like, you know, five-nines of reliability. We got pretty good run with our printers, but we're always in the market for new printers. So there's more. We are. We're looking for a new printer right now for a special project. Anyway, let me tell you about cognition. They're the makers of Devon, the AI software engineer. Crush your backlog with your personal AI engineering team.
Starting point is 00:42:19 What I hate most about technology and hotel rooms, Jordi, I want your take on tech in, in, uh, in hotel rooms, I want to know about your experience when you walk into a hotel room. The Wall Street Journal says, when you book a hotel room, you can count on some things like shampoo, a hot shower, some way to get a cup of coffee. But a stress-free technology experience? No way, not even with basic technology,
Starting point is 00:42:41 you find just about anywhere. Like TV, Wi-Fi, and outlets for your devices. Unless you carry a suitcase, bowl of gadgets, cables and adapters, you're risking every kind of tech frustration. Did you know that Ben Thompson carries a special device that acts as a Wi-Fi repeater where when he travels. So when he goes to a hotel,
Starting point is 00:43:01 he logs in to, yeah, this is amazing. He logs in to the hotel Wi-Fi, I believe, or the plane Wi-Fi, through that device. And then all of his devices connect to that automatically. And he'll bring, he'll bring like a fire stick, so he'll be able to watch TV shows
Starting point is 00:43:19 and his laptop and his phone. Everything automatically sinks to that device and it, like, reroutes it. That was a very interesting. thing that he's clearly optimized a lot. He's like a huge, what is it, like gear bag guy. Like he has all the wires like dialed as, as I would expect. I usually forget to bring a charge. Hotels are missing out on a fundamental truth. In a world where so much of our work, travel,
Starting point is 00:43:45 and relationship experience is shaped by technology, the quality of a hotel's tech service is core to what it's like to stay there. Give me a hotel room that lets all that tech fade into the background so that I can focus on my trip. But no, here's what you usually get instead. TV muddle. I suspect I've logged more hours troubleshooting hotel TVs than I have watching programs on hotel TVs. Okay, there's a bit of a retro charm in a TV that flips on and instantly tunes to a live network broadcast. But in the streaming age, I'm just as likely to crave a little quality time with Netflix, Disney Plus, or Apple TV. Many hotels have caught onto this reality by offering some sort of streaming option, but they approach this in so many different ways.
Starting point is 00:44:22 you never know what you're going to find or what tech you'll need to make it work. Needy Wi-Fi is another one. Most hotels I've visited recently seem to have figured out the charging extra for Wi-Fi makes about as much sense as charging extra for a better toilet. Everyone needs to get online, so you might as well build it into the price of the hotel room.
Starting point is 00:44:38 So now that we've taken that great leap forward, why are we still forcing people to log into the network, not just once per day, but over and over again, once per device, each and every day, or often several times a day. It isn't unusual for me to log into hotel Wi-Fi 20 or 30 times a day? I think you're doing something wrong.
Starting point is 00:44:57 Honestly, honestly, I don't, this doesn't resonate with me at all. You're fine. The only thing I want from a hotel is to be able to order room service without calling someone. Okay. That's like the only thing. And hotels miss on that for the most part. Like if you have a little iPad or you could even order on the TV app, that would be amazing. And you get like a Domino's Pizza truck.
Starting point is 00:45:22 tracker type thing. That's all I want. I feel like they kind of deliver on everything else and I don't watch. I was listening to, I think it was George Hots was explaining how he ordered room service in a hotel he was staying at and he vibe coded an app
Starting point is 00:45:38 that interacted with the ordering service so that he didn't have to talk to them. It basically read the entire menu and then like created like a voice agent to call or like reverse engineered the API of the ordering menu and he was able to order by command line and just like checking into hotel, time to build
Starting point is 00:45:58 the CLI. It's truly the future. I love it. But it is. It is. And you know who else is vibe coding these days? Gary Tan. Ben Heilak has a joke here. He says, the year is 2027. Gary Tan has just crossed one billion lines of code per day. Water to three-year-old California in towns were diverted in order to cool his locally ran LLMs. Riots erupt and protesters demand to answers to one single question. What is he building? We got to have GT on. I can't wait. Let's get Gary on. We got to get Gary on. We got to know what what what Gary is building. People are joking about this because what was the latest stat? It was something like 80. 78,000 lines of code per day on per day on Gary's list, on Gary's list, which is his blogs.
Starting point is 00:46:46 It's a blog and he's built blogs before. He's built these he's built these sites. But I guess like with all the testing suites and packages and mobile optimization, I don't know. I can't imagine the volume of code that will be generated when he creates a mobile app for it. It's going to be, it's going to be, you know, trillions of tokens going into that. Anyway, let me tell you about Labelbox. Aral environments, voice, robotics, evals, and expert human data. Labelbox is the data factory behind the world's leading AI teams. Sam says, I remember when this was announced but didn't fully appreciate the size.
Starting point is 00:47:20 That's a hell of a cluster. the Department of Energy will basically be a frontier AI company. Nvidia is collaborating with Oracle and the Department of Energy to build the U.S. Department of Energy's largest AI supercomputer for scientific discovery. The Solstice system will feature record-breaking 100,000 blackwells and support the DOE's mission of developing AI capabilities to drive technological leadership across U.S. Security Science and Energy applications. Another system, Equinox, will include 10,000 Nvidia
Starting point is 00:47:51 of Blackwell GPU is expected to be available in 2026. Both systems will be located at Argon and will be interconnected by NVIDIA networking and deliver a combined 2,200 X-Flops of AI performance. We've talked about nationalization before. We haven't talked about privatization. We could potentially spin this out, take it public. There's an option here.
Starting point is 00:48:15 So I was interested in this. This is going to be like somewhere around like a quarter of a gigawatt equivalent. of 100,000 black whales? Half a, half a Metacampus, I think. I think Meta is working on 500, 500 megs. Yeah, I think, I mean, Hyperion, like the end state is, like, I think a gigawater more, right? Yeah, more, more.
Starting point is 00:48:35 But that's, like, the first big jump for them. But the default Metacampus, I believe, is around 500 megs. Cisco, to acquire Restaurant Depot. Not our Cisco, not. Not even close. To require Restaurant Depot for 29.1. billion dollars. Before we take you through this, let me tell you about the real Cisco. Critical infrastructure for the AI era. Unlocked seamless, real-time experiences, a new value with
Starting point is 00:49:00 Cisco. There's only one Cisco in our hearts. This one's important. This is Cisco with an S. I, I dislike Cisco. Why? Because every time, I find it a very frequent experience where there's a new restaurant coming to my area. I'm excited about it. They invest million, two million dollars in building out this incredible space. Looks great. And then you eat there for the first time and you can tell that they're just sourcing like Cisco. I'm not going to say slop, but the food quality is not great. And then it's like, why did you put all this energy into making a beautiful space? And then you're just, you know, chefing up generic, generic food. It doesn't make any sense to me. I believe the founder of Restaurant Depot.
Starting point is 00:49:51 Look, I think I saw it somewhere. In the Jetsons, they had dinner generating machines. Dinner generating machines. How do you think that's going to happen? Travis Kalanick built this. Isn't this Cloud Kitchen? No, no. The dinner generating machine or Cisco?
Starting point is 00:50:06 Because Cisco's dinner generating machine. Yeah, yeah. That's basically it. But it's all part of a pipeline. The founder of Restaurant Depot, who just sold for $29 billion, was born in 1932. He's 94. He's still kidding?
Starting point is 00:50:21 I think we should hit the gong for him. Let's do it. Congratulations. Great to finally get. It's never too late. So if you're 93. I can buy that sports car. Finally.
Starting point is 00:50:36 Yeah, that is a true overnight success. Congratulations to him. Excited. I mean, you know, we got to get food to people. People are hungry. There's some good things. You know, maybe they, maybe they stock some. raw milk and you're on board then.
Starting point is 00:50:50 You know, who knows? Okay. Before we play the next video, let me tell you, every day is a fight between the advertisers and the viral video. Let me tell you about Railway. Railway is the all in one intelligence cloud provider. Use your favorite agent to deploy web app, servers, databases, and more, while Railway automatically takes care of scaling, monitoring, and security.
Starting point is 00:51:10 And then we can play this video. We're heading over to Japan. Yes. This is the key sport that we will all be picking up in. 26. This is going to be the hottest thing in San Francisco with the hills and the office chair. And so there's an office chair racing league. Look at the speed and the technicality. It's incredible. It's incredible. This athlete says the corner once controlled me. Now I control it. I think I got something. You have quite a bit of leverage with the legs. With the legs.
Starting point is 00:51:42 I think I got a bill for office chair. The six-year transformation is crazy. I mean, this guy is incredibly quick. It lost me. And we need to bring this to the U.S. We need to bring this to the U.S. Chair, racer, Miura, going around the devil's hairpin. The devil's hairpin.
Starting point is 00:52:03 All right, so, Tyler, what is happening on X in Japan? You break it down? Break it down. Yeah, I mean, I don't know all the internals, but it seems like Nikita's been posting about this, but I think, you know, they basically introduce, like,
Starting point is 00:52:17 all of like Japan Twitter onto like normal Twitter. Oh, because of translation. Yes. But I mean, there's been translation for a while. But I don't know. Like this weekend, like half of my timeline was just like Japanese posts.
Starting point is 00:52:29 All about America, about how much they love barbecue, you know, they respect the cowboy aesthetics and all these things. Cool. I didn't know that we need to figure out, we need to figure out how and why over 50% or something like that of Japan is like a weekly active user of X,
Starting point is 00:52:44 which is just crazy. Yeah, they have great posts. Well, yeah. I mean, yeah, so let's pull up this. Wait, wait, wait, this is a little bit of an update, like narrative violation because that's a narrative violation.
Starting point is 00:52:53 That's a narrative violation. Because when Grock went viral, everyone was like, oh, it's good at anime, it's big in Japan, and it was at the top of the Japanese app store, but it appears that Japan is just using Twitter broadly.
Starting point is 00:53:08 Elon. They just like, they just like the app, and that's like where they have conversations, which is very cool. It's a narrative violation. So let's go to, Let's pull up this first post.
Starting point is 00:53:18 This is hilarious. And it is a... And this is the translation from Grok. When I saw this, quote, pizza topped with a pizza in America, I thought, there's no way we could beat these guys. This is an amazing... Oh, so this is an American pizza. I've never seen... There's so many layers.
Starting point is 00:53:37 There's actually one, two, three, four layers of pizza. I'm going to make this. I feel like this would be a smash hit in my househouse. This is quite smart. Peak performance. Peak performance. We got to, this may be for lunch today. Let's get some pizza.
Starting point is 00:53:53 And so this post, which in Japan, or I guess now everywhere, got 93,000 likes. The translation from Grok is, I like this photo of American men and meat. Someday I'd like to join in on this in person. There's just some guys cooking a whole bunch of steaks. That's a lot of meat. Wow. That's a lot of food. They're having a big barbecue in Sassibo's dining establishments.
Starting point is 00:54:21 Someone else. Someone else. Somebody's just, I guess an American is posting their grocery hall. And someone says the amount is way too much, as expected. As expected. We have a brand over here in America. We do things in a particular way. Hello, Japan.
Starting point is 00:54:40 We love your fascination with our barbecue. Here is me buying half a cow's worth of meat. for our family. We store it in a big freezer in our garage. I actually have heard about this. Buying in bulk obviously is more economical, but hilarious ratio by Dr. something or other, Dr. Nicholas. The amount is way too much, as expected. What else is going on in Japan? Take me through. Someone else says in Sasebo's dining establishment, it's common to spot U.S. military personnel enjoying their meals with lively enthusiasm. One day at a restaurant, I came across a group that reached an oddly intense level of excitement just upon seeing bacon.
Starting point is 00:55:19 That's incredible. I love it. Let me tell you about Lambda. Lambda is the super intelligence cloud, building AI supercompeters for training and inference that scale from one GPU to hundreds of thousands. And let me also tell you about 11 labs. Build intelligent real-time conversational agents. Reimagined human technology interaction with 11 labs. In fundraising news, physical intelligence is in talks to raise $1 billion at $11 billion.
Starting point is 00:55:45 I need to know. Why is Jeff Bezos here besides the fact that he looks fantastic in the tux? He might put in some money. Oh, no, no. The company has previously raised more than $1 billion in capital from investors including Jeff Bezos and Alphabet's independent growth fund capital G. So you could have put Peter Thiel because founders funds in. You could have put Lightspeed is a Danny Ryder. Or no. Carol or Lockheed or any of the echo team. But Bezos in a tuxedo. seems to get the viral attention. So, but very good news. We actually interviewed both the co-founders of physical intelligence, both Lockhe and Carol, this last year. And they don't do a lot of media,
Starting point is 00:56:29 so it's an interesting little segment. We spent maybe 20 minutes with them. And you should go back and listen to it because it's a very interesting insight into the business that they're building, which I think a lot of people, you know, they're not a noisy firm. They're not a noisy company that's like posting vibe reels and going and picking fights all the time. So there isn't that much coverage of physical intelligence.
Starting point is 00:56:52 But like if you just look at the traction, look at the open source contributions, the data, the fundraising, like clearly something is happening there. And so I think it's worth digging in and paying attention to if you were. Last night, Bill Ackman hit the timeline. Whoa. He said some of the highest quality businesses in the world are trading at extremely cheap prices. ignore the mainstream media, one of the most one side of wars in history that will end well for the U.S. and the world. And we have potential for a large piece dividend, one of the best times in a long time to buy quality. Ignore the bears.
Starting point is 00:57:26 And he says, and Fannie Mae and Freddie are stupidly cheap, asymmetry at its best. They could be at 10x, and it could happen soon. And of course, Gero tickets comes in and says, X.com, the market manipulation app that Fannie Mae and Freddie Mac are up 42% and 37% as a this morning. I think they've actually dipped back down a little bit. But Justin says, posting your opinion on a public website is not market manipulation. J.T. says, don't ruin the tweet. Yeah, it's not, it's not market, it's not market manipulation. It doesn't seem like he has any inside information. I don't know. Does he even have a position? Isn't that disclosed in his filings? I'm not exactly sure. I would take every recommendation from a Twitter poster,
Starting point is 00:58:12 every piece of financial advice with a grain of salt. But this one certainly turned out to be some sort of pump going on. And I did dig into this. Somebody asked Grok, like, hey, break it down, like what is actually going on here with Fannie and Freddie. They generate $25 billion in stable annual net income from guaranteed fees, low credit losses outside crises. They're still in 2008 conservatorship.
Starting point is 00:58:41 and the stock trades for a total market cap of $10 billion. So there's a world where you're sort of buying maybe, I don't know exactly how aggregated this is, but maybe it's like $25 billion of cash flow at some point for $10 billion. That feels like a very good deal, get paid back in four months, five months. But, of course, there are a whole bunch of other political...
Starting point is 00:59:05 And of course, he does. He does own the Fannie Mae and Freddie Mac are in his... Pershing Square portfolio. Well. But again, not not illegal to share your opinion. Yeah. Well, there are some, not everything is up. Mac, Mike Zucardi shares the current Mag 7 plus drawdowns from 52-week highs.
Starting point is 00:59:28 Nvidia is down 21%. Google's down 22%. Microsoft's down 36%. Apple's down 14%. Amazon 23%. Meta 34%. Tesla, 28%. And many other.
Starting point is 00:59:41 Others have drawn down significantly. Fortunately, we have the perfect person to ask about what's going on with Nvidia because we have take him in the Restream waiting room. Before we bring him in, let me tell you about console, because console builds AI agents that automate 70% of ITHR and finance support, giving employees instant resolution for access request and password resets. And let me also tell you about Vanta, automate compliance and security, because VANTA is the leading AI trust management platform.
Starting point is 01:00:12 And without further ado, let's bring Take Him in to the TPP in Ultradown. Take Kim. How are you doing? Thank you so much for taking the time to come to see out with us. And congratulations on the incredible launch of your business. Yes. Thank you. I mean, it's been really gratifying.
Starting point is 01:00:30 That first day, you never know who's going to show up. Totally. I was like maybe 15 subscribers or 20 subscribers, but like hundreds of people showed up. It's amazing. tons of billionaires and tech founders. It's insanely gratified. Yeah, it's great. So is it over for Nvidia?
Starting point is 01:00:48 They're down 21%. We just read since the 52-week high. Is it doom and gloom? Is it over? No. I think I was on last December, and the stock is semis and chips that's gone up, and now they're back down to where they were in December.
Starting point is 01:01:05 The chip sector is flat on the year. video's down 10%. And it reminds me a lot of about a year ago. Do you guys remember, everyone's freaking out about deep seek, the super efficient models, we're going to destroy AI compute. There will be a huge compute glut. And then everyone freaked out about Trump's Tower for a liberation day.
Starting point is 01:01:27 And this year seems very similar to that. Almost it's like Groundhog Day. We have fears over AI CAPX. People think that it might be the peak. And then we have the Iraq war. and one of these things is oil up here Iran
Starting point is 01:01:42 easy to get them mixed up they happen so much feels like the same thing over yeah but um someone said to distract we wanted to throw we wanted to show respect
Starting point is 01:01:53 we wanted to show respect to a real podcaster I mean it's very similar to Iraq I love it these are great but in a hundred dollar oil this stuff is unsustainable and oh probably subside
Starting point is 01:02:07 Okay, so because when I, when I, when I, I like the deep seek analogy and I feel like the market half digested the agentic coding, uh, narrative and the Satrini article, whether you thought it went too far, it was too hypothetical, like clearly the markets did react and a lot of names sold off, but in, in a world where you believe that narrative, you would think that invidia would be going up, but you're saying that there are other factors at play that are sort of, uh, tamping down the excitement in the market. broadly? There's no that. Just like tariffs a year ago, Indyia had 30% drawdown when their business was actually flying. Yeah. The actual flight of the business, I think the same thing is happening here with the Iran War. Things will eventually subside. Oil can't be $100 forever. And Trump will probably backpedal in next few weeks ahead of the Trump. So let's recap a few of the key stories around Nvidia. We just came off of GTC and there's a lot going on at the company. I mean, it's a huge company. Maybe it'd be good to start with just next generation chips, changes to strategy, what
Starting point is 01:03:15 people are actually buying. Maybe that means grace CPU standalone sales or the development with the GROC partnership. What's sticking out just on the actual AI product side to you that you're most excited about? Well, inference demand is exploded. driven by the AI agents and the genetic coding assistance. I met with Ian Buck, I met with dozens of engineers at Meadow, Google, and Vida. And all of them are seeing crazy inference demand
Starting point is 01:03:46 and AI compute shortages. So across the board, people are in crazy, clamoring need for AI. And we're, I mean, yeah, you're seeing that from talking to engineering leaders at big tech companies, but we're also seeing it from vibe coders who are just on X in 20s. Twitter and talking about how they're hitting rate limits and they're subsidized and they have multiple plans and they actually shift around from one model provider to another just to make sure
Starting point is 01:04:12 that they're getting the tokens they need to build whatever they're building. And you see the tweets. People are like building bots to pick up any kind of B200 GPU that can. Oh, yeah. They're waiting like weeks and months or whatever. Basically like sneaker bots, but for NeoClaz. That's great. Exactly.
Starting point is 01:04:29 I can't believe that. And the great thing is Jensen, you know, he's very prescient. He probably saw this demand months away. He locked up all the supply agreements for memory, co-os connectors ahead of time. He saw this inference demand. And to take advantage of this coding system boom, it's almost like a gold rush. You see open AI pivoting toward it. Anthropic, obviously, is thriving on it.
Starting point is 01:04:55 Billions of ARR every few weeks. Jensen's acquired GROC, acquired the assets of Brock and the people of Brock. And the combination of integrating GROC's technology, together with Vera Rubin, let's NVIDIA serve this tremendous wave of compute demand economically. And Ian Buck talked about it, Jensen talked about it. So, Nvidia's positioned perfectly to thrive on this coding agent wave that we're seeing right now. On the Groch deal, Jensen did a fantastic interview with Ben Thompson and was sort of asked the same question two years in a row about A6, the threat of A6, the idea that the GPU, the general, like general architectures can truly satisfy 100% of demand. It feels like there's a shift in Nvidia strategy there.
Starting point is 01:05:49 Do you see that? It feels like the right move. But do you see it as a shift in? the philosophy of the company or the strategy? Or is this just something that the gears have been turning for a long time? And this is maybe just an unveiling of a strategy that makes a lot of sense and has made a lot of sense for a while. I think what Jensen does,
Starting point is 01:06:10 he sees where the market is shifting and where the economic value is. With Melanox, he did this in 2019. He saw world shifting to, it's a networking chip, but he saw the world shifting to like these 10,000, 100,000 GPU clusters. Melnach's need for that.
Starting point is 01:06:26 In the same manner, he saw AI agents and the inference behind that taking off. And he said, oh, this GROC thing will work perfectly with Verar Rubin. It doesn't replace everything. It just has talked about 25% of the inference demand would be GROC would work on that. But them working together where 75% of the inference is very Rubin, 25% is a GROC low latency stuff. It's like the perfect combination to take advantage of this. And the other thing is, like, we're just in this great lift-off of AI innovation. Yeah.
Starting point is 01:07:01 We've talked about anthropic mythos, the blog book that leaked out. So we're going to have this, you know, step-up function. They told Fortune there's going to be a huge step-up change. Yeah. Open AI is coming out with their model soon. And then when I went to GTC, the biggest takeaway I had was this session between Jeff Dean and Bill Dally, both chief scientists of Google and Nvidia. And it's online.
Starting point is 01:07:24 I highly recommend people watch it. And he talked about, Jeff Dean talked about the context, they have context window innovations where they could focus on the 10,000 documents that work well with your requesting query. So we're going to have this context window innovation. Both chief scientists talked about stacking memory right on top of the GPU or TPU,
Starting point is 01:07:45 and that's going to be a huge innovation in the coming months or years. And so you have, and then Jeff Dean talked about synthetic, data for audio and video, there's this huge runway that data is not over and then they're going to be able to take advantage of all this data that people don't realize yet. So you have like all these vectors where AI models you can just keep getting better and better. Yeah. How are you processing the idea that Nvidia will be investing in an open source frontier lab capability?
Starting point is 01:08:18 that feels like potentially competitive with some customers. Nvidia's like never really been in that market before. But at the same time, I've been the biggest, like, supporter of open source American AI models. I loved when Meadow was doing it. I want more of it. I loved when Open AI, open source GPTOSS, it feels really, really important, really great. But it does feel like a strategic shift. How did you process that?
Starting point is 01:08:48 announcement. It's not acute. I think it's like 25 billion over the next few years, which doesn't really compete with what open AI anthropically. But these smaller models are going to be helpful for people running these smaller use cases. So GPUs, as long as they're utilized even locally or in the cloud, Nvidia benefits. Yeah. And saw the top people at Quinn left and we don't know where they left to. Quinn is an amazing model. It's kind of like what Deep is, what people thought deep deep shit should be, Quinn works well locally.
Starting point is 01:09:21 Gwen kind of subsides because all the people love. What's your theory on, what's your theory on where they all went? Another Chinese lab? I asked, I asked all the engineers when I was at GTC. No one really knew.
Starting point is 01:09:33 But people are trying to say NVIDIA should actually hire them. Yeah. Because the more capable open source model, Nvidia doesn't care if you're using GTP to run open source or not. They just want, you know, more AI adoption across the board.
Starting point is 01:09:47 Yeah, and Nvidia has more, probably more levers to pull. If it turns into a negotiation with China, like we're tracking like the Manus story with meta. And there isn't that much that meta can give to China in exchange. If there's like, hey, like look the other way on this particular deal, like let this one flow through. We'll trade this. Meta not really doing any business there,
Starting point is 01:10:12 but Nvidia, of course, is going to be selling Blackwells, at some point in the near future, and there's probably some level of pricing. You know, it can be part of a larger discussion, which makes a lot of sense. And one thing that kind of went under the radar, Jensen literally said at GTC, they got licensed approvals on both the U.S. and China side.
Starting point is 01:10:32 So we're going to see billions of dollars of H-200 orders. Okay. So, yeah, I mean, it seems like there's a path on the demand side that's very, very clear. You've mapped it out a few times. It's a huge number. It's already a massive reverend. and he was just an incredible growth.
Starting point is 01:10:48 But what is the supply side looking like? Because it feels like TSMC is not ramping CAPEX nearly fast enough over the next few years. And if we see another 10x increase in compute demand, we could be really constrained on the leading edge FAB side. So how do you think NVIDIA is gonna process that? Well, NVIDIA is in the driver's seat because Jensen goes there five, six times a year
Starting point is 01:11:15 and his best friends, the TSM, and speaks at their employee days. So they're going to get higher, they are getting a higher allocation to waferes and co-wasse and all of them. So, InVIA will benefit. But I agree with you that industry-wide, like, Google is dying to get more TPU wafer capacity. Sure.
Starting point is 01:11:32 All the, all the hyperscalers that have A6s are trying to get more wafer capacity. So there is going to be an AI compute shortage in the years to come, just like you said. And Vividia just benefits because, you know, they're the biggest dog in the house and they can prepay tens of billions of dollars to get the allocations they need. Yeah. I mean, maybe there's some offtake in ASICs that can potentially be fab somewhere else at some point.
Starting point is 01:11:58 I know that a lot of the ASIC companies wind up fabbing at TSMC, but it feels like if you're already doing some sort of re-architecture, maybe there's a way that you can get, you can squeeze something a little bit out of, you know, an Intel deal or something else. I'm not exactly sure. It's Samsung and Intel. Samsung and Intel, yeah. Babs that could possibly do it. Yeah.
Starting point is 01:12:22 That's the bookcase on Intel. Yeah. Yeah. Is that at some point the labs and Google, like we're across TPU, extra GPU capacity, Nvidia, the new R. Like, there's just so many buyers of lab capacity now that you could imagine everyone coming to the table, potentially in Washington, D.C. or Mar-a-Lago since the U.S. government owns a slice now, and everyone's saying, okay, let's hold hands
Starting point is 01:12:50 and jump across this and say that if the supply comes online, we will buy it at this price because we have really, really solid use cases that will justify the investment for us and for Intel. So that would be a really, really good case. But again, even if the money is there, how long does it take to get to, you know, good production numbers? I mean, I suspect like Apple, and Nvidia are considering either Intel or Samsung for their lower end stuff. Whether it be like a mid-range iPhone
Starting point is 01:13:20 or Nvidia side, definitely their consumer gaming GPUs. They may go back to Samsung and maybe even Intel. Yeah, I have one more, but go for it. I wanted to know how you're processing the ARM CPU announcement. It's an interesting dynamic because they're sort of
Starting point is 01:13:38 frenemies with Nvidia now. They're competing in many ways. is to break the x86 monopoly because they both are selling arm cpus but then they're also competing and so i'm wondering how you think that plays out what that means for invidia and just the rest of the semiconductor supply chain i think arm is uh their CPU opportunities a longer term you know for even they said 2030 20 30 21 yeah it's a longer term opportunity i don't really expect the major hyperscalers like Amazon to switch to ARMS product offering, they have their own. And same with the same with Nvidia. They have their own ARM CPU that they're they're going to incorporate and
Starting point is 01:14:21 sell. So it's not that big of a, I don't think Amazon or Nvidia really worry that Arm is going to take any big share. It's probably going to be on the margin for companies that can't develop their own ARM CPU, the more the mid-tier hyperscalers or enterprises that use these things. But I, I I think the arm thing is very important because it kind of confirms what the biggest underlying thing that that's not really consensus yet is this massive CPU shortage that we're seeing. Just over the last few months, we have Dell, AMD, Intel, CFO talked about, they're talking about three to five-year locked in supply contracts and hyperscalers. So this is a major trend that's going to go over the next few years.
Starting point is 01:15:07 And the reason why is AI agents need more CPUs. The ARMCEO talked about four times more CPU cores versus last year's kind of AI infrastructure model. So we're going to see this massive demand for CPUs that people aren't really understanding it. Because AI agents, the whole thing, requires orchestration, tool calls, database queries, web searches,
Starting point is 01:15:34 and that's all handled by the CPU. Yeah. Give me your bull and bear case for TerraFab. TerraFab, I'm not that optimistic. Okay. I mean, it's so hard to build that. Give me, do your absolute best to give me the bowl case. Because TSM is so short that, you know, Elon needs to find.
Starting point is 01:16:00 But even then, like, how are they going to buy, like, semi-cap equipment from ESML and AMAT? like there's just no capacity there, so I'm not optimistic on that. And this is stuff that takes decades. Chip fabs is almost like cooking, and it's not like something you could just follow a manual. It's like it's almost like cooking where it takes a lot of trial and error accumulate over decades, TSM, and even Intel. So it's not something you could just jump right in and do. Yeah, unless they partner with the, yeah, it's someone goes back to the XAI debate about, like, do they need AI researchers or should everyone be an AI engineer? Like, are we in a research period or a, you know, the, the Elias Sutskever age of research versus the Elon Musk age of engineering?
Starting point is 01:16:52 Where are we in semiconductor production? It feels very engineering, like an engineering process. but what we've seen from ASML is that it and TSMC is that it does feel like there's a little bit of research and artistry to it and the cooking analogy holds. Yeah, I've been doing a lot of research into space and it's a lot of trial and error and almost like cooking a recipe. And it also feels like in, at least with XAI, if all the researchers are in San Francisco, you can sort of just like walk across to the coffee shop, poach someone. But if the best, you know, semiconductor engineers or technicians are in Taiwan and they see it as a national urgency to, you know, bring, you know, stability to the country, both economically and geopolitically, then you have a very different calculation. It's like, oh, yeah, I could make five times as much if I left my home country to, like, be abandoned. That's a very different calculation.
Starting point is 01:17:56 and everything that I've heard about the culture at TSM is that the folks who work there are extremely dedicated beyond the economics. They are true missionaries, not necessarily mercenaries. And so it does feel like it's even harder to do like a talent raid in the leading edge Fab world than even the AI world, which is extremely competitive. And there are still tons of missionaries. But FAB is, I guess another question I have is would you expect, would you expect, would you expect, XAI slash SpaceX at any point to get to basically just open up a shop as like a Neo Cloud. Because the thing that was like probably the one of the least compelling aspects of the Terra Fab pitch was him just saying we need all of this compute.
Starting point is 01:18:42 We need to do this because we're going to be so chip constrained. We're going to be so supply constrained. But there was no explanation of where the demand was coming from. Where the demand was going to come from. Yeah. come from training Tesla models, Optimus,
Starting point is 01:18:55 or Kroc or... Yeah, it was just very unclear. There's a lot. But there's even the question right now is should XAI be kind of renting GPUs? I don't know.
Starting point is 01:19:08 Renting out GPUs. Because the biggest win has been Colossus 2. Yeah, Colossus 2, which was built very fast. I think Elon's pitch with the SpaceX IPO and we'll see it in the coming months
Starting point is 01:19:20 is the AI compute. It's going to be so there's going to be so much demand over the next five, ten years that you're going to have to use these SpaceX satellites that have GPUs in them to serve that. And maybe, maybe, I mean, even though Tesla's been vertically integrated to the point of being a consumer product, SpaceX has not. It's been a railroad. And there is a world where you fab the chips, you put them on satellites, on Starlink's in space,
Starting point is 01:19:47 and then you let other companies do whatever they want with those GPUs. I think what Elon did with Starlink. That's a telecon infrastructure play, and this will be an AI computer. Yeah, yeah, yeah. That fits that model. There's a world there. I'm not going to bet against Elon.
Starting point is 01:20:01 It might just take long. Yeah, yeah. What about, what's going on with helium? What are you tracking there? There's chatter about helium shortages, potentially. Jensen has talked about this. This is the risk, but there is probably like six months, six to nine months of inventory in the channel.
Starting point is 01:20:20 Bernstein has talked about it's not a risk in short term so so if this thing if this iran stuff lasts yeah you know two three four five months then becomes a problem okay but if it you know gets solved or straight or moves opens up with the toll or whatever uh final negotiation they come up with over the next few weeks i don't think it's got a problem yeah i do think that like like most of these uh materials there are uh extra deposits they're just not economical to mine i don't think that all the helium exists in the Middle East. It's similar to the rare thing, just like you said. Yeah, where in a supply-constrained scenario, it becomes more economical to mine American
Starting point is 01:21:01 helium. Let me put this way. If helium becomes the issue, we're going to have bigger problems in our hands. Okay. I mean, there's going to be world starvation. Let's hope not. Let's hope not. That'll be the least of our problems if healing becomes the problem.
Starting point is 01:21:12 Take me through depreciation gate. How did you process that and where do we stand now with the fear, the GPU, the GPU, will depreciate precipitously, and H-100s will be worthless in six to 12 months? It's totally not a problem right now. Like, Corrieve has talked about these things are lasting five to six years, and they're getting like almost 90, 95% of the pricing. So it could potentially be a problem if the whole, if this is a bubble, I don't think it's a bubble.
Starting point is 01:21:42 But if this is a bubble two, three years from now and there's a compute glut, then the stocks don't go down because there's a compute glut. But as of now, it's the opposite. Like all the GPU rental prices, even for stuff that's six years old, is still being sold out. And the AI compute demand outpacing supply is so large that this is not an issue right now. Do you have any theories on where the next step change in token demand could come from? Because right now we're seeing it in CodeGen. And there's a lot of optimism around these types of workflows being applied to other forms of work.
Starting point is 01:22:19 we were talking about this on Friday, like even if AI can just one-shot beautiful financial models, it won't necessarily even make a real dent in token demand, at least compared to code gen, because no company needs to just constantly be generating models at the rate that, let's say, Gary Tan generates code. And so I'm like kind of been trying to wrap my head around where could these incremental use cases. I actually think Ogen is still just early innings.
Starting point is 01:22:55 Yeah, and I don't disagree with that. 10, 20 agents and they're kind of overseeing them. But then we have this other stuff where these models, the mythos and open AI, they're just going to get better where you could automate all these work process flows. Companies are going to
Starting point is 01:23:13 use them for every single vertical customer service, research, simulating chip design where they can verify drug discovery where they verify if drug molecules can do. So we're just getting started at this stuff. So you're going to see vertical AI agents on every single category. And I think Logan's coming on. He wrote this great post on X that he says the AI agent wave is going to kind of attack this $6 trillion knowledge economy. Right.
Starting point is 01:23:44 It's not just about programming anymore. They're coming for us. Yes. I don't think, say, I'm actually. They're attacking the key context economy and the TBPN economy. No, I think it's like a calculator, a spreadsheet. You know, 30, 40, 50 years ago, we had like, you know, 50 accountants doing the spreadsheet manually, right? And now after a spreadsheet came, it didn't get rid of all of knowledge work.
Starting point is 01:24:10 It just enabled people to think at a higher level and get more done. And I'm very optimistic about that. I mean, one way that you 10x token demand around a financial model without 10xing the number of financial models that you're building is having the agent go and collect 10 times as much data. And so there's a lot of situations where, I mean, you look at like hedge funds that want to understand the price of Walmart stock. there are hedge funds that will task satellites to take pictures of Walmart parking lots, estimate the number of people on a day by day basis that are going into the Walmart to shop and then using that as a proxy to project revenue and then flow that through to cash flow and then flow that through to the DCF and the actual evaluation of the company. And if you think about all the different financial models and all the different businesses where you could go and say, well, for this company, I need to go to every single single. local, like, I want to know the price of Squarespace. Let me go to every single website that's powered by Squarespace
Starting point is 01:25:16 and estimate the revenue that they're bringing in and their willingness to pay for their hosting service, something like that. And all of a sudden, like, it's just one spreadsheet, it's just one number at the end of the day, but it's like a thousand times more work went into it. Let me give you this great example. Every year I do this same store sales for these fast casual companies,
Starting point is 01:25:39 so like Chipotle, Kaba, and I put out this tweet, it goes viral. A year ago, when I do it, I would have to manually go to every IR website for these six fast casual restaurants. It would take me like an hour or two. I would try to use a chat bot. They would get it wrong. I did it like a few weeks ago, and all the chatbots got perfect.
Starting point is 01:25:58 So it just saved me two, three hours of tedious manual labor. So that's only going to get better and better. Yeah, it's only going to take you one. Like this year is the year that you do it. with multiple chatbots and you fact check it yourself. And then forever, it's going to be just one prompt. And it got it right. And it got it right.
Starting point is 01:26:19 And a year ago, it wouldn't get it right. But now in one, two minutes, I put, give me the same sort of sales for these six restaurants. I put in Gemini, I put in chat GPT and just to make sure they're right and they're right. So all the tedious labor, all the manual labor, all the data entry that, you know, all of us are used to, that's the stuff. is going away and we could think higher level. So I could look at the same store sales and say, oh, the economy is at risk and whatever. But all the grunt work, all the tedious work is going to be taken care of by these AI agents. I agree completely. I agree completely.
Starting point is 01:26:56 We got a lot more sound effects since the last time you joined. Last question for me, what's your outlook on meta? It feels like the broader market right now has zero. faith in meta to actually put all their AI investments to use. I have this history with meta is that every time it starts falling apart, I say it looks cheap, and then it goes down another 30%. But nothing has changed. No one's going to replace meta digital ad position.
Starting point is 01:27:29 I mean, I would even say in the AI world, they're even better position because Google might lose digital ads share to AI choppots, their search positions, going to be. So like no one's going to replace Instagram, no one's going to place Facebook. Billions of people are still going to use those social media apps. And, you know, it's every six months to 12 months, everyone goes to this bare meta cycle, but their pure competitive position really hasn't changed. And you saw what happened to SOAR, right? Like, you know, everyone's all excited about SORA and that got shut.
Starting point is 01:28:03 Totally. Yeah. And there's just this world where even if like the AI spending is like, like, the AI spending is like a side quest. It's like really they just pulled forward like three or four years of Capax and they will use that for their other products. It's probably even less like wasteful than reality lab spend, which might take even longer to realize that the cash flows from. Like they can recoup. Okay, we built this massive data center. We did this training run. We didn't get to the frontier. We're not getting a lot of like Gen AI usage. But we can apply it to our ads
Starting point is 01:28:37 platform and tools and Reels recommendations and a million other things just in years 28, 2029. And yeah, we're a little bit ahead of schedule. Our core ad engine monetization. 100%. Yeah, the gem model. Reality Labs, he made a waste of $70 to $80 billion. He might waste $100 billion of dollars on these frontier AI models. But their core ad engine, core business, that money-making engine is not going to be affected by this.
Starting point is 01:29:07 Well, thank you so much for taking the time to come hang out. Always a great time, Tay. Go subscribe to key context on Substack. Follow, Tay Kim, on social media, first adopter. Join the many beaners that were the first adopters. Yes, yes. You'll be in good company. And thank you so much. We'll talk to you soon. Have a great week. Great to see you. Bye. Thanks, Dad. Cheers. Let me tell you about Figma. Agents, meet the canvas. Your AI agents can now create, modify, create and modify your Figma files with design system context in beta starting today. And let me tell you about Graphite. Code review for the age of AI. Graphite helps teams on GitHub,
Starting point is 01:29:43 ship higher quality software faster. So, uh, Chamath. Yes. Holly, uh, he says, the biggest threat to Instagram's moat is an incredible image model. Okay. Zife, Zephyr says, meta bottom. Um, um, an incredible image model. I mean, that's basically, that's a, that's a, like, you basically saying, okay, if, SORA was, if the content on SORA was a hundred times better, would that be a real threat to Instagram? And I still am not, I'm still not convinced. I feel like a lot of people have their network there.
Starting point is 01:30:17 They want to share with their friends. They have a graph there. And even though the recommendation, like the content doesn't come through the graph anymore, having your friends on there to have the conversations and the comments, there's still a lot of left. But if they could make an AI agent of you that instantly react. to every video I send you. Killer feature.
Starting point is 01:30:37 Killer feature. Killer feature. There's some, yeah, between our DMs, there's a lot of stuff that you've got to still react to. Well, without further ado, we have Logan Bartlett from Red Point, his managing partner there. Welcome to the show, Logan. How are you doing? Good, gentlemen. How are you?
Starting point is 01:30:52 We're fantastic. It's great to see you. I like this camera set up. This looks fantastic. You know, what's about a time, I was a, you know, I was a semi-professional podcaster before you guys stole all the thunder in the industry and forced us into oblivion. Three cartoon avatars was truly go-died.
Starting point is 01:31:12 Just put the investments in the bag, bro. I know. That's exactly right. Yeah, the McDonald's bag of cash I have. That's what I'm doing these days. But you're also writing market analysis, which I always look forward to. Yeah, this has been consistently some of, like, the best content in the entire. 100% industrial complex.
Starting point is 01:31:34 And I've enjoyed it for many years. It was extremely valuable during the interest rate crisis as well. And also the conversations that you were having on the podcast, but it felt like a really rational reset that wasn't a total black pill, wasn't a total white pill. It was just actually like, here's some data. There are obviously some conclusions, but you can also make your own.
Starting point is 01:31:54 So thank you for everything you do. Take us through the biggest findings. Take us through the process that led to this particular research report. Yeah, it turns out there's a little bit of nuance that 75 slides give you more than 140 or 280 characters to kind of tease out in some ways. So it started probably in January. I have this process every year where I have a panic attack that we have an annual meeting coming up. And I got tricked in 2020 when I joined the firm. They were like, we're going to give you this really illustrious honor that.
Starting point is 01:32:31 you get to do the market update. We so trust you and what you have to say. And I thought that, oh my gosh, this is amazing. I'm being bestowed this honor of doing this market update deck. Little that I know, no one else wanted to do it. And so every January, I get a mild anxiety attack that I have this coming up. And over the past couple of years, there's been a bunch of different, I mean, that year it was COVID, then it was kind of the ZERP fallout, ZERP era, 2021, then ZERP fallout, then 20, I think was SVB. 24, maybe I got like a little bit of a respite.
Starting point is 01:33:06 Then last year was the tariffs. And so every year there's like something going on that forces us to recalibrate. But this year it became pretty clear it was going to be the software sell-off and what was going on in the public markets. And so monitoring that, I sort of started from a process of talking to a bunch of smart friends in the industry about what they're thinking about and trying to probe on questions. that they wanted answered. And this generally involves a lot of public investors because private investors in some ways are like fish in water where like you sort of just operate
Starting point is 01:33:42 in the world around you. And so if you're doing defense, you really just focus on defense. If you're doing software, you just focus on, you know, that. If you're doing whatever, healthcare, you're focusing on that. Public market investors, I find,
Starting point is 01:33:53 are a little bit more zoomed out. And they typically have an opportunity to play across different scale of businesses, different sectors, types of companies, all that stuff. And so I talked to a bunch of them and software and like what the hell is going on was the big narrative. And there felt like there was a major disconnect between what private folks were seeing going on and what public folks were thinking about. And so trying to bridge that gap of how do we have this world where, you know, software companies are now trading at 4.1 times NTM in the public markets, but also getting priced at two, three,
Starting point is 01:34:31 400 times ARR in the private markets. And so sort of setting out to bridge that gap was kind of the goal. Is it a gap or is it a gulf? I would say it's a optimism disconnect maybe. That's a good phrase. I like that. It is, it is amazing. You know, I think about the, I did a panel recently with a bunch of private equity investors. And in hearing them talk, what I concluded, and some of this is true, I think, for public investors as well, is like, what is, what is, what is, what is, you? What is, the risk of going to zero and optimizing your process around like, hey, we really can't have a zero X in the portfolio versus private market investors. You're optimizing on like, what are the chances you're missing out on a 30, 50, 100 X? And if you take those two lens, it ends up
Starting point is 01:35:19 with a very different place of like optimism versus cynicism, upside versus downside, you know, all the questions you ask. Yeah. So let's, let's, let's, you'll appreciate this, Logan. I had a portfolio company at the end of last year that is a software as a service business. And in one of their updates, they made the announcement that workflows are now called agents in the product. And I was like, they were like, this workflow stuff seems like people are not that excited about it now. We're switching gears. These are now agents. And if we just, you know that breaking bad meme that like he says we had a good thing, you stupid son of a bitch? I feel like that was, that was like, all SaaS investors over the course of the last, you know, 100%.
Starting point is 01:36:04 Being like UMFers, you had to go mess up this like really good thing we had going on with this AI pixie dust. With a nonprofit that didn't even raise a seed around until they were multi-billions. It's like we couldn't even get in early. We had a good time. We had a good time. So let's start with the public markets. How much of how much of this is driven by the Satrini article?
Starting point is 01:36:26 How much of this is driven by actual data points where we're seeing. seeing, I was, I was just pulling like the top 50 SaaS companies, sort of pure place SaaS companies and trying to answer the question like, is revenue decelerating yet? Are we seeing a kink in the graph, like some change in the data? And I didn't go nearly as deep as you go. But how much of this is just like narrative and anxiety about a changing curve to the financials versus actual data points where people are saying, okay, like we're not going to be growing as fast. We're not going to be as profitable as before, something else that would change
Starting point is 01:37:03 the valuation. Yeah, I mean, I think broad buckets, there's two main things. One is, like, the public market investors are fed up with stock-based comp. And so, like, let's put that in a bucket. And I actually, I do think venture investors and public markets CEOs are to blame for some of the softness and the cultures and, like, how bloated some of these businesses got. But also, you have to be practical. There is a game on the field to play. And, like, you could triage and say, hey, you know, we're really going to reduce the number of employees we have. And you really have to be careful there because, you know, they could, your best people could just walk out the door if their friends are all getting fired.
Starting point is 01:37:42 And they can walk out the door and go work at Anthropic or Ligora or, you know, one of the businesses that's growing at this crazy, crazy rate and get stock-based comp. And so I am sensitive to that, but that is a real part of it that, like, there's not true profits going on. And so I think let's put that in a bucket, though. That's like sort of aside. The other thing, the far more interesting conversation to have is like are financials deteriorating? And the answer is really no right now. It's more of this like long term existential question of what terminal value of these businesses are worth. And it used to be, hey, 85 to 90% of a business's value was tied up in the period beyond the DCF, right? The terminal value of the, you know, the long-term duration of it.
Starting point is 01:38:33 And that's really what people are asking questions on. And to be honest, I think what's really happened is the public investors are saying, I can't tell the difference between Salesforce and ServiceNow and Snowflake and CrowdStrike and CrowdStrike and Guidewire and Sam Sama and all these businesses. And to be honest, I don't even really want to go dig in and figure out all the little specifics here. I'm just going to go put my my bankroll in Navidia or Google or AMC or something else and I'll wait for this to sort itself out, wait for the market to do its thing and figure out what the buying opportunities actually are when it's a little more, a little less uncertain. And so I think it's that. And people are asking like, what is the long term terminal value and saying
Starting point is 01:39:17 I'll wait on the sidelines until other people really show the proof points that they're going to be able to survive this AI thing. Yeah, is there is there a world where we move into a regime where we're talking about not revenue multiples but like EBITDA multiples? Yeah. So I was looking at a company that was three billion market cap, 100 million of EBITDA, very stable the last five years. And and one one one investor was making the case like, oh, AI winner. And I was like, I don't see that. But also I don't see these customers turning. I just see them doing AI stuff on top of this particular company. because they're more infrastructure layer, more data storage, that type of thing. And so I was like, I think you can count on 100 million of EBITDA and probably cash flow for 10 years,
Starting point is 01:40:03 20 years, but do you want to be paying 30 times that? Is that enough? And I don't know if that's the rational framework. Nobody knows anything. You have to apply a big discount. The other slide that one of the slides I loved was the slide on newspaper earning. Oh, yeah. Slide 22, you say newspaper earnings.
Starting point is 01:40:21 Yeah, I mean, it is interesting. It's funny. I actually have that up on my screen here as well. But yeah, newspaper earnings, I mean, when these platform chips happen, you might not see it in their earnings or revenue initially at all. And so the newspaper example in the deck was that newspaper earnings were actually fairly stable for like the five years post internet while their value collapsed. And so everyone saw the writing on the wall of where this was headed. But it took a while for that to actually come through and show up in the, uh, in the actual financials themselves. So, John, I guess your question on it, like, I use revenue as a proxy. And maybe it's like to flip of a nomenclature. We really should be talking about, like, free cash flow with deductions for stock-based cop or whatever. But like, all these things are growing at different rates. And that's sort of been the historical lingua franca that I kind of use.
Starting point is 01:41:18 But you're right. To be clear, it makes it impossible to comp to the private. markets because no one's generating any that's right so it's a useless comp but I'm just thinking like if I'm a public markets investor and I'm just and I'm choosing between Google Apple and then some small cap mid cap software company I probably want to have an EBITDA hat on or something like it to sort of understand my just my rate of return which is going to be a lot less like oh all of a sudden they're growing at some unpredictable rates so the DCF gets crazy and I'm paying some high rate yeah and this might be a little uh uh uh simple
Starting point is 01:41:51 for some of your listeners and maybe helpful for others. But like at the end of the day, a business is valued at the current value of all future free cash flows. And so discounted back to today's dollars. And so when the reasons software businesses have been so good is you have annuity streams going out into the future and you're able to, with some level of precision, figure out what the discount back the value as in the future. And so that's a that was a great thing particularly when we had retention rates at you know 95 96 97 percent net retention rates at 121 30 140 you could really do very little and you could discount back those dollars with pretty good certainty of figuring out what those are worth today it was almost bond like
Starting point is 01:42:36 and i think this equity made a bunch of money saying like actually you know this is this is better than a debt instrument this actually sits on top of the the debt in terms of your vendors are going to get paid before your debt providers will because the business needs to keep going. Now I think we're seeing a little bit of cracks in the armor and I think your analogy is a good one where it's actually not, I worry less about the like the churn risk or people really going to churn off of Salesforce or work day or service now or whatever it is. Like maybe, but I worry less about that. I worry more about the value abstraction that is captured on top of it.
Starting point is 01:43:16 And if the AI dollars, which we found in one of the reports, AI dollars this year are, it's a bigger pie of net new dollar opportunities in AI, then all of software combined by like 50% or something. And so if you're not capturing the AI dollars, then your growth rate is going to go to near zero. And if your growth rate goes to near zero, then it's worth something, but it's not worth, you're right, like the 30 times. Think about it almost like a real estate investment.
Starting point is 01:43:45 And it's like, what's your cap rate? You know, like, if I'm giving you 100 bucks, am I getting five bucks this year, 10 bucks this year? Because there's a lot of other options. And then, yeah, the other thing historically with software has been just low interest rates. So, oh, that cash flow is coming in 20 years? Fine. Like, it's basically the same as today if it's zero interest rates.
Starting point is 01:44:03 Yeah, exactly. But when you're at 6%, you know, you do discount it back and you get a lot lower number. Anyway, where should we go next? I'm interested in... I'm curious, any of the public markets invests? You said a lot of them were just like, I don't want to try to be the smartest person in the room and lean in and figure everything out. It's safer to just like, you know, bet energy, bet semis, et cetera. Was anyone like licking their chops being like, this is the greatest buying opportunity, like actually had some well thought out thesis around how it was like Toma Bravo. Some of their slides leaked from their LP summit. And they obviously are in the position where like they have no choice, but they can't be bearish now. You know, they have to. like, you know, create the like 4D chess of how this is like a huge accelerant to, to their, uh, to their businesses, but. Yeah, I think some of the public, uh, some of the
Starting point is 01:44:57 public guys, um, they are very interested in trying to discern what's going on. And this is actually a really good buying opportunity. If you believe people are going to figure out, um, the agentic opportunity or the AI opportunity, because it's certainly not being priced in in a material way. And the incumbent vendors are going to get every chance from their existing customers to get this right. And so I think that's the, if you were to paint the optimistic lens about, you know, Toma got dragged a little bit for some of their, you know, talking their own book. But I actually think some of the slides that people were dunking on were, it's true fundamentally that like, hey, your incumbent vendors are going to get shot one, two, three in getting it right.
Starting point is 01:45:41 I think the problem, and at least what we're seeing in the private markets, is that the culture of building these AI companies is just so different than the culture of building what the historical software company looked like. And you guys, I think I think you know I was an investor in Ramp. And the stuff that they did, like, thank you. The investors don't get enough, right? Let's give it up. It is my cross-the-bear. Logan in particular. He's,
Starting point is 01:46:13 he never takes victory laps. That's the thing. We'll take it for you. We'll take it for you. I'm unknown. I was a silent investor for a long time. And so I'm glad to come out of the closet as a ramp investor here for you guys. But, you know,
Starting point is 01:46:28 one of the things that they did culturally for a long time that, that I thought was kind of crazy was they shipped a lot of stuff and would just put it out in the market and see how people react to it. And that was very different than the way that I learned, you know, the companies I invested in 2014, 15, 16, and how they built products was they had a very tight product roadmap. They communicated with their customers. You know, they had it over a three, six, 12 month period of time. And they would only really release it when it was fully ready out of initially an alpha,
Starting point is 01:47:04 then a beta. Then they would take a GA with a handful of customers, then take it breath. The ramp guys sort of put that on it. head where they would move really fast, iterate, get it in front of customers, ship it at like 90% readiness, and then see how the market took to it. And if they, if it resonated, then they would continue to build around it. And like, that mindset is actually what I've seen with a lot of AI native companies now, which is like, you're not totally sure what the model capabilities are going to be in three
Starting point is 01:47:32 months' time. And so what you need to do is internalize what your customers are going to want, like have enough of an appreciation for their job that you sort of know what workflows exist or like what existing pain points are. And then when the model capabilities keep getting better and better, you need to internalize what that customer is going to want and what the capabilities of the models are or where they're headed and sort of let those two things intersect and then deliver that to the customer. And so it's a very different way of like building product. And that's one example. And we have a slide in there of like all the different examples, but like it's sort of been flipped on its
Starting point is 01:48:10 head. And so I actually don't worry from a is it possible standpoint for the for the big public companies to do this. I think it's totally possible. And I think some of them will figure it out. But the vast majority are going to have to totally change their culture that they built over the last 10, 15, 20 years. And that's really painful. And I think that's where they're going to end up falling down more than anything else. Yeah, this is fascinating. I'm like sort of an early yish adopter, I think. and I recently wanted to know, like, how much have we spent on Apple products? And I was able to get that answer in, like, Ramps AI mode, basically. And I didn't need to, like, export any data.
Starting point is 01:48:48 But then I wanted to know how many, what I've spent with Apple over the last year on my personal financials. And for that, I had to vibe code something that exported all the data and did it manually. And so the question of, like, you have a system of record, there's going to be some new feature. where is that value going to be captured? Are you going to capture that value? Or is another system going to come down? And it's going to be a feature of a chatbot or a feature of another platform.
Starting point is 01:49:13 Like this is entail as old as time. Yeah, it's abstracting the value on top of it, which is interesting. I guess if you guys think about like my direct visiting of websites has definitely gone down because I interface with Claude or Hatt GBT in a meaningful way.
Starting point is 01:49:29 And I think that same thing's going to play out within the enterprise. as well. And it's not just going to be retrieval of information. It's going to be actually taking actions. And so now I don't totally care. I'm sure you didn't totally care if that information was coming from on rampside, if it was by bill pay or credit card. And ultimately, once you vibe coded that application, you didn't care if that information ended up coming from a credit card statement or an email receipt or whatever it was. In fact, I wanted it to, I wanted to unify credit card and like checks and, like, bank transactions as well.
Starting point is 01:50:03 And I want to put all of that in one bucket. And that's something that's, it's not a feature in my bank right now, but it will be, if they move quickly, but it already was a year ago in ramp. And so it's just like the pace of play is like still on the order of years in a very interesting way. And yeah, definitely like encourage all the, all of those companies have like opportunities, but they have to go win them. No one just like gets granted, you know, monopoly on the new, on the new capabilities that emerge on top of their platform. So, Jordy.
Starting point is 01:50:33 in the deck you talk about, you know, you have some bub talk talking about it, are we in a bubble? And with every advancement, with coding agents and things like that, it seems like there's plenty of demand. There's plenty of demand for tokens right now. People are willing to give real dollars for tokens, and that's just going up and up and up. But I think there's a tendency right now, at least for kind of the early stage private markets crew to say, like, AI is not a bubble. So I should still be investing like tens of millions of dollars into all these different early stage companies and things like that. And I've been like, I've been kind of feeling the bubble in, in private markets, like just based
Starting point is 01:51:14 on the number of companies coming out every single day. Yep. That seems to all be doing kind of variations on like the, you know, the AI CMO, right? And I'm like, maybe, maybe that ends up being a big category. Like a sort of niche vertical SaaS player that's like AI will be like at a 50 cap per a seed. Yeah. I guess my point is like we can AI maybe isn't a bubble but that does not mean we're not experiencing like a massive bubble in the kind of venture world right now. Yeah, I mean it sort of goes to like where value is going to accrue.
Starting point is 01:51:49 And like if you we did a slide on percentage of GDP in there and if if if you were obviously investing in airlines like it was a transformative technology that didn't end up proving to be a material investment opportunity. and what actually presented opportunity was the second derivative considerations of like business travel or like, you know, lounges and airports or whatever, B2B sales and all that stuff. Like there were second derivative things that were actually far more impactful. And you're right, like, it's possible. And this is what I've told our LPs that I've asked is like, I think we're operating in a world in which our mortality rate of companies we invest in is going to be higher than it's been in the past. It just like it is even at the stage we're investing in. I think we're going to see a lot more businesses die. I hope we will also invest in things with a lot more upside.
Starting point is 01:52:41 And so we'll end up with, you know, hopefully things that could be hundreds of billions of dollars, which used to be not in the realm of possibility. And so I do think we're entering this like extreme period of uncertainty. And the only thing I've really been able to come back to on all this is because you're right, these categories end up so crowded. And they end up very dynamic in terms of like how the category evolves, what the product surface area ends up looking like all that. And so in some ways, we're back to like investing in teams and investing in like the wedge
Starting point is 01:53:16 or the general space that they're operating in and then hoping that those doors open or that see parts and they're able to run through that in a meaningful way. But it's very possible that the model providers end up soaking up a ton of the equity value. And so just because there will be a CMO in the AI world that a company starts, like, it doesn't mean that any of these companies will be the one to capture that value. And actually, it would probably be very unlikely that it would. And so that individual investment, you might be very rational in doing it or not doing it. And the opportunity will ultimately create a ton of value, but it might not be a private, early stage, specialized company.
Starting point is 01:54:01 That's going to be the one. Yeah, it's been interesting to look at these businesses ramping revenue so quickly and still, and have like real customer love and pull from the market and still have that question in the back of your head of like, does this eventually just get zeroed out? Yeah. And for me, and for me, that's the one people. Sorry, go ahead. Yeah, for me, the only real comp I have because I kind of came, I came kind of online in my career in 2018, so I got to see the, you know, ZERP era very closely. But I remember with OpenC, you know, in the NFT boom, that was, I remember the way that they ramped revenue.
Starting point is 01:54:43 Even the thing that made, you know, I think a lot of otherwise, you know, great funds, like pile money into it, what ended up being the top, is there was, like you could kind of just say like okay even if revenue drops by like 90% and this doesn't end up being like this mainstream opportunity there's still like a business here and and maybe you can just own the category and but but then revenue ended up dropping like 99% or something like and and I think that's still so that that that still stays in the back of my mind that that was more of a demand issue versus like new kind of competition from from an adjacent player, but still. Are there any previous booms that you do like as comparison points, if not.com?
Starting point is 01:55:30 Do you like railroads? Electricity. Electricity. What do you like? That's a good question. I haven't actually thought of the right analog for what time were. I mean, people, you know, the Industrial Revolution is the one that people come back to the most. And that wasn't on our like GDP calculation chart.
Starting point is 01:55:52 But I do, I think there's, there's elements of like the shifting balance of, of, of worker dynamic and like where people are actually going to employ themselves in that way going forward. And like wealth, you know, there's a lot of considerations on wealth capture and what percentage of the population that's going to go to. And there's definitely a lot of like populist rhetoric out there. And so I think this is more of a, I think, revolution than like a technology. I mean, it's both a revolution and a technological shift in some ways. And so I think like the car or the airplane or the railroad or whatever, like that didn't fundamentally shift the balance of an entire workforce in some ways, the way that I think this has the chance of doing. And so that's the one I kind of come back to.
Starting point is 01:56:42 But it's a good question. I'll think more about it. How are you thinking about capability overhang, diffusion, the, the capability overhang? Yeah, the debate about like the models are good and they're getting better really, really quickly. But there's just like, you know, teams in companies where they're like, yeah, I'm actually fine doing my spreadsheet job. And, you know, I've heard this direct quote, I got to check that AI thing out. yeah I got to check that out when did you already say that to you
Starting point is 01:57:17 was that recent I think you know it is interesting I mean that's where you're seeing a lot of this like FDE Pallenteer where bridging the last mile is really really hard
Starting point is 01:57:31 and I think we assume that that like if we build it they will come in some ways but it's obviously that's not the case AI to most people I guarantee if you took whatever, I don't know, 300 million Americans or something, and you ask them, like, name an AI
Starting point is 01:57:48 company. I would guess I'm making this up, but like 25% wouldn't actually be able to name an AI company and like 70% would say, oh, that's that chat GPT thing or something. I talked with a guy, I talked with the guy and said, like, what are you using any AI products? And he was like, nope. And then I was like, what about chat GPT? And he's like, I use that every day. I love it. But he just doesn't think about it. It's just a website. Like, we've been to websites before. And I think that's an interesting thing.
Starting point is 01:58:19 You know, Brett Taylor talks about this from Sierra where there's so many capabilities that you're raising the water line of and that they're needing to build in-house themselves, knowing ultimately the model providers are going to need to productize that or going to productize that. And so they end up building things that they throw out six months later all the time. And I think that's kind of true on the go-to-market or like education side as well. where a lot of these customers, if you're going into an industrial business or a healthcare business or an energy company or whatever it is, you're having to bridge the capability to competency and bridge that gap to the individual person at the end of the day.
Starting point is 01:58:57 And so I do think this diffusion, when everyone talks about, like, are we in a bubble structurally at a big picture? I sort of reject that notion because of both the demand. And when people talk about the power supply and all that, I actually think it's going to be, it's going to take far longer to get this out into society in a really meaningful way than people on the internet tend to think because the real world's a lot more complicated than I think we make it out to be when we're just, you know, living in our techno utopia. That's a good point. If you can call ex a techno, techno nightmare.
Starting point is 01:59:30 Except in Japan. Japan, they love it, apparently. I did want to ask about buy versus build economics. You talked about how you could just buy. That's the one that people have been asking all about, by the way, today. Yeah, yeah. People like that one. Yeah, so funny. So Logan makes a point. You can buy Slack for 1,000 employees for like a quarter million a year. Or you could build it in-house. You estimated around 2 million a year. And then like other kind of random unexpected costs. I'm sure a lot of people, anybody that's pushing back on this, just tell them like, okay, build me Slack. Build me. It's a really funny thing where I just think it's sort of the 80-20 rule in some ways that people assume building a software product.
Starting point is 02:00:10 is like the getting to the proof of concept or like the credible MVP in some ways. Look, you can send messages. You can create a group. And then it's like, oh, I vibe coded this thing and it does all of what Slack needs to do. But then there's not even to mention the network effect of Slack of you build the perfect clone.
Starting point is 02:00:30 And then it's like, okay, do any other companies use it? No. Okay. Do we still need Slack? Yeah. And so like let's say, I think, I mean, people want to argue about the specific math on all this. Like, let's say that you're willing to do all the integrations in the SSO and the search and the file sharing and the, you know, whatever.
Starting point is 02:00:47 The admin controls and compliance and all that stuff. Let's say you could do that. Yeah, the emojis, the emojis, the gif embeds, all those things. Like, let's say you do all that. Was that, whatever that costs, like, what is the opportunity cost that you spent all this time doing that rather than, like, focusing on whatever it is your core business is? And so actually, like, we did the math here, and it's $2 million versus $220K or whatever. Like, let's say it's the same, or let's say it's cheaper. Like, is saving, you know, $40,000?
Starting point is 02:01:19 Let's say it's 180 versus $2.20. And it's actually- It actually has to be significantly cheaper. But also, I mean, I talked to a friend who runs a company and just about AI stuff. And I was like, oh, yeah, like, you should probably, you know, be aware of this stuff. But what percent of revenue is going towards, like, software broadly? like what's your IT spending is like less than 1%. And so it's like, yes, like you could take something
Starting point is 02:01:43 that cost $1,000 down to $200, like maybe you take that, but not if it's a headache at all. Because 99% of the time you want to be with your actual customer suppliers because it's completely different business. And so that was the point someone was arguing me about is like most companies actually, you know, aren't growing like software or tech companies are. And so these costs are really material to them.
Starting point is 02:02:03 And I'm like, you know what's material to them is like decreasing their workforce turnover from like, 70% a year to like 60% a year and not having to pay incremental recruiter or staff for fees to get people on. The difference of the Slack budget and saving 40K, I guarantee does not resonate at all. And Slack was a simple example because it resonates with people. But I think it's true across the board. So I was trying to think of like what a good bet would be with someone to try to like
Starting point is 02:02:28 come up with. It's a very hard thing to figure out of like what the right framework of thinking about this is because I love just codifying bets with people and being like, Like, you know, okay, let's wager some money on what this is and I couldn't come up with a good one. So if you or if anyone listening can come up with a good bet on this, I would love to place whatever, a significant sum of money on the side of it. It's funny. It's funny to think about the company building Slack in-house and they're like throwing time. They're getting 10 people on a call like, hey, like we need to meet and talk about some up.
Starting point is 02:02:57 We need to talk about like our roadmap for our internal Slack. We need to kind of bat some ideas around about different tradeoffs that we're making. Well, the deep irony here is that Slack was an internal tool for a game studio. Like, it was actually like the, we need to build our own thing because we communicate so frequently. And then it became. And there's a historical analogy, by the way, of this that I didn't include in the deck because I really like Drew Houston from Dropbox. But, like, they built their own data centers.
Starting point is 02:03:24 And, like, I don't know. Like, if that was a good cost decision from them. But, like, from a focused decision, should they have just used AWS? and, you know, or GCP or one of the other, I don't know, I don't know the answer to that. And I didn't want to, like, put him on blast and actually get into the debate because I like him quite a bit. But, like, I don't know if that's, like, the right decision for them. And that, they were even, like, the furthest, you know, they're like a tech company that that was their business, able to decrease costs. Totally.
Starting point is 02:03:53 And who knows what the opportunity cost of incremental products or mine chair or whatever it was going and doing that. Yeah. No, that makes it tell us. Last question. Did the current AI suite make your annual report significantly easier? Or was it still? Handcrafted. It's an artisanal craft of this, but I will say it is interesting doing this deck every year.
Starting point is 02:04:18 It does serve as a snapshot of what the model capabilities are and how much progress it's been made. And so I think if I go back two years ago, that version of a bit, I could word smith, like my talking points that I was actually talking, you know, when I get up there in front of the LPs and do it. And last year it was actually a decent, I could ping pong some ideas. Here, I would guess, I don't know, if there's 68 slides or something, I would guess 75% of them AI had some hand in either helping visually lay it out in some way, writing some of the text, maybe coming up with some of the analogies.
Starting point is 02:04:56 And that is such a step function change versus. where it was 12 months ago. And so it is helpful every year to like revisit, come back and like see what's actually possible. Because as you just go about your day, you sort of forget what three weeks ago was or eight weeks ago or 15 weeks ago. But when I went through the process this year,
Starting point is 02:05:15 I was like, wow, this is really much less painful. And I think the principal and associate on the team that worked with me on this, we're very much appreciative of where the model capabilities are going. Because I think if it made my life a little bit easier, it definitely made their life a lot easier. Totally. Is that alpha for up-and-coming venture capitalists?
Starting point is 02:05:34 What advice do you have for those who want to make a career out of venture capital? Because it feels like coming in and surprising the entire partnership with a very deep analysis. I would just say have a non-traditional background. So maybe grow up in the kind of like Menlo, Palo Alto area, go to Stanford. It's actually an interesting thing. So if you guys have a minute, I can riff for a second on this. But like historically, so we've hired people out of investment banks, largely speaking. And so why do we do that?
Starting point is 02:06:03 Well, we hire people out of investment banks because it's an expressed interest in finance and technology. Okay, that's great. Two is they have the model training of like what we need, you know, the cap tables and, you know, projections and all that stuff. Three is there's like a high pain tolerance and like willingness to grind and do the extra thing. And then four is like it's a referential network. Like we can call the same MD at Morgan Stanley or Goldman Sachs or Catalyst every year and be like, hey, how does this person calibrate to that person?
Starting point is 02:06:31 And it gives us a qualified pool of people to pick in. The thing that investment banking didn't have was you're very much, like, if you ended up in investment banking, you followed a pretty straight path for the most part in your life. And I say this as a former investment banker myself, where like you went to a high school, got good grades, got into a good college, you know, did interview, got a good job. Then at your investment banking job, you're staffed with like 90% of your day is pre-filled by someone else. And so it's like, okay, well, if I work hard and I stay late and I do this pitchbook,
Starting point is 02:07:01 align the fonts the right way, I'll get a good bonus, and then I'll get a good job. Well, then we drop you in. And increasingly now with the model capabilities, the financial modeling, Claude can do it better than, you know, or as well as most of the people on our team. And the sort of remedial tasks are getting the water level keeps going up. And so when we hire people in now, we've always had to train on the agency thing. and it's a little bit of rewiring your brain where, hey, my day used to be 90% filled by the staffer,
Starting point is 02:07:32 and now you're telling me just go figure out what's a good company. Like, where do I even start in that? And so in some ways, like investment banking is actually a bad pool of how it's wired and prepared people for this world now. Historically, it always was, but we were willing to forego the agency because we got the modeling capabilities
Starting point is 02:07:51 and the remedial tasks, and we sort of took that as the basics, and then we had to try to, to figure out if there was agency there. Now increasingly, like, the models are getting so good that agency might be the only thing that matters. And so, like, are you able to find differentiating network? We're actually working on an internal model for agency at TVPN. Yeah, right along with our taste model. We've had a huge unlock. We've cracked taste. Now it's, now it's agency. And so, so that's the thing that we now are trying to figure out, like, where do you find pockets of people who still want to do
Starting point is 02:08:24 the job talent-wise or have the capability to do the job but also have agency and you might be finding people that are entrepreneurs you might find people that project managers you might find people that have taken serendipitous paths in some ways and that actually might be a good sign and not a bad sign and so it's forcing us to think in a different way of like where we're hiring people from so what i'm hearing is that you're pulling up the ladder behind you that's right that's right that anyone any door i always say when people ask like hey how did you get to where you are in your My answer is always like, well, is the specific question what I would do when I was in if I was in your seat? Because I can tell you the doors I walk through, but those doors aren't just shut.
Starting point is 02:09:03 They're like shut. They're cemented over. They've like been fortified, you know. They're not doing what I did. I luck through this path. Thank you for joining us. Great time. Just with all the AI progress, try to ship one of these a week.
Starting point is 02:09:20 You got it. I would love it. Have a great rest of your day. We'll talk to you soon. Let me tell you about phantom cash. Fund your wallet without exchanges or middlemen and spend with the phantom card. And then head over to public.com investing for those who take it seriously, stocks, options, bonds, crypto, treasuries, and more with great customer service. And without further ado, we have the founder and designer of Granola.
Starting point is 02:09:45 Sam Stevenson. Welcome to this show. Sam, how are you doing? What's going on? I'm good. I'm good. How are you doing? Congratulations.
Starting point is 02:09:53 Massive news. Tell us what happened. Let's hit the gong. Let's warm things up since we're in our Lambda Lightning round now. I want to hear what happened. So we have raised a $125 million series C from... Congratulations. I didn't hear it over the sound of the gong. You said index ventures?
Starting point is 02:10:13 Index ventures, index ventures. And with KP participating as well. Fantastic. What unlocked the round? Is it just continued progress, features, a little bit of everything. Talk us through the progress over the last year. Yeah, I think it's been, I mean, all the above, like, we've been talking to these guys
Starting point is 02:10:34 for a while. They've been fans of the product. I think as all of our investors have, they've all, like, use the product a bunch before we've got to talking about investing. And then, yeah, like, growth has been good and continuing. And like, I think it's the combination of that. And then, like, the, I feel like, the environment. is like waking up to the power of having all of the context of what's happening in your meetings
Starting point is 02:11:01 in a company, you know? Like I think like everybody adopting MCP is like making it apparent that you can, like if you have the right context about what's happening in the company, you can do that to power so much of what's happening in your company. And I think we're just well positioned as like that context gatherer that a company can take advantage of. Yeah. Yeah.
Starting point is 02:11:21 So my, my, uh, something I've been thinking. about with this category is why do you think the, why do you think the labs have not built a product in this space? I'm sure there's a number of reasons, but I'm sure they would generally love the context that you're gathering so that their agents could actually leverage it directly. And so explain like why you guys have had kind of just open, open, not to say open, but there's certainly competitors, but why have you guys been able to just run? Run away.
Starting point is 02:11:58 Even image gen. Yeah, yeah. I mean, yeah, I'm sure they are working on it. Opening I had a stab at it last year. They had launched like a longer running record mode thing, which I think was aimed at this. But like I think it's a few things. Like I think we're basically like people use us for meetings, right?
Starting point is 02:12:20 Which is like it's a big time for a, for a, for a startup like us, but it's also like only a slice of people's life. Like, and, and if you're designing like a super open-ended general purpose chatbot, like, Chad GBT, I think, like, they're probably questioning, like, does this make sense, or should we be going for, like, always on recording of everything and anything less is, like, not good enough? I think that's probably part of it. The other thing is, like, I mean, we've found building granola that, like,
Starting point is 02:12:50 you can build a granola clone super easily, you know? Right? In like a weekend, you could build a thing that transcribes your meetings and gets you a summary. And like all the work is in understanding like all of the like social nuance of like who are these people in the meeting. Why are they meeting? What's this meeting about?
Starting point is 02:13:09 And like therefore like what notes do you want out of it? What are the action items you should care about? Like just just kind of all the work behind the scenes to like actually make this thing fit into your life in a way the way you'll use it and find the notes useful is a bunch of work. And, yeah, that's, you know, we use the latest and greatest model. So, like, you've still got to go and do that work on top of that, at least a day. Yeah.
Starting point is 02:13:34 Yeah, it makes total sense. What kind of progress are you guys making, like, what is the, what's the most kind of, like, sci-fi element of the pitch for this last round? Like, are you imagining a future where the only thing that humans do? is just kind of meet and talk about what should be done and then make a decision and then machines ultimately carry out all the work. Like how far are you kind of like taking out the,
Starting point is 02:14:04 how far out are you kind of looking? I mean, I can see that like, yeah, I can see that someone being true. Like I do think like, I mean, we do it internally in the company. You know, like we'll meet and talk about a thing and then go ask Brunola to write a brief, that we either go that hand to a coding agent or we use it as the material to write a job description
Starting point is 02:14:27 or a blog post or whatever. Like the conversations are like incredibly good input for a lot of the work that you end up needing to do at a company. Yeah. I think the more kind of, like the most near-term but sci-fi things that we see is like if you want like a pulse on what's happening
Starting point is 02:14:47 with like any project or any group of people in the company going and like looking and asking granola what's what's happening with this with this project is like easy and incredibly like insightful and I think that's that's essentially because like transcripts are just such a good up-to-date record of like what's happening in a company so much more so than like a like I don't know a notion doc or a Google doc that someone had to sit down and write like without making any effort, you have kind of an up-to-date picture of what's happening in the company. And I think that's just going to be useful to a lot of people in so many ways.
Starting point is 02:15:26 What is diffusion look like inside a large company? Like how much training, education, messaging you have to do. I'm sure you have playbooks for this. But how do you, because once you land, I imagine the next step is expand. What does that look like for granola? Or word of mouth pretty much at the moment. Like, for most companies, like we focused so much on just making it like a good product for the individual when we started that, yeah, like still the majority of our growth is like Patient Zero finds it at a company and then tells their friends about it because they love it so much and we just go on from there.
Starting point is 02:16:09 We, I mean, we're working on a bunch of team facing features that kind of let you harness the value of a whole group of people using it together. And I mean the motivation behind a lot of that is that we kind of create a reason for you to just go wall to wall across your company with Grinola and kind of unlock the power of of sharing all that context of the transcripts together But for the most part it's still just word-of-mouth people people love it and they share about share that with each other Talk about the end-of-year Rapped campaign
Starting point is 02:16:39 I've heard fantastic reviews for it I was such a I was such a delight to say it to like so yeah and explain it for those who who did not receive one or followed the story and then tell me about yeah so we did a like a spin on you know Spotify wrapped as as many companies do which for us was granola crunched um the basic thesis was like you know granola if you've used granola some some of our users have used granola for like thousands of meetings over the last year and um and if you look inside those meetings and across over a year you can you can you can can tell a lot about a person and what's going on
Starting point is 02:17:19 and what's important in their lives. So Granola Crunch was basically like every user could go hit a button and generate a like Spotify rap style report about their year. It was things like who's your partner in crime, what's your favorite catchphrase, what's like, what are some of the smartest things you said, what are some of the dumbest things you said,
Starting point is 02:17:44 that you know, that kind of thing. And it was like, you know, mostly fun. There's some things that could hit pretty hard. Like I remember mine was like, I felt kind of uneasy sharing it with other people because it felt. I've heard that from a number of people. They've been like, it was scarily accurate and I didn't want to share with the rest of my team. You said nothing from my end, thanks. Seven hundred times.
Starting point is 02:18:10 That's great. Okay, so we have this buddy who's, you know, built a massive company. in a super regulated industry and like had been through ultimately had a had a huge exit but has been been through kind of, you know, lawsuits and discovery along the way. And so he's just like absolutely hates every product in this category. He's like, I don't care how useful it is. It's not worth, you know, someday having like, you know, basically line by line and live kind of transcript of every meeting that you've had at a company. What are the, I'm sure you guys are aware. of some of these more like sensitive use cases like what kind of fix it like what are you doing at the
Starting point is 02:18:54 product level for people that don't want every conversation you should sell saunas so if you want to have a meeting that's off the record you go into your company sauna and then nothing can record you there's no recording devices this is the this is lindy maybe go to the bathhouse maybe check check for any product rolls you get a wire on you you take off anyway sam yeah yeah Yeah, I mean, I think like this is like a really tricky path for us to walk and like it's like so important for us to be You know doing what we think is right at every step of the way like I think um I think we have to juggle like I think tools like this are kind of that There will be somewhat inevitable in a work context. I think I think like talking about the personal you know like always on recording type things is totally different, but in a work context
Starting point is 02:19:40 There's just so much value in in having like transcribes meetings and therefore being able to use that conversation data for stuff. So I think that's kind of inevitable. And the question is like how do we kind of make that okay for people in the meantime? And I think like some things we've observed
Starting point is 02:20:01 are like for companies that use granola, they basically just get comfortable with the idea that like we're gonna make it a thing that like we use granola internally And that's the default. Like that you should kind of just assume that's happening. And you know, you can know it like it's okay to opt out and say you don't wanna use it.
Starting point is 02:20:20 But companies get comfortable with that very easily, we find. Then like the external question is like a question of following the laws in your state and you know, like Grinola, we make that clear to you. But it's ultimately it's a tool and you kind of, it's up to you to follow the rules on it. But I meant more like even on like data,
Starting point is 02:20:41 Data retention, right? So like if a company, there are plenty of meetings that are just not that important, but if that was pulled in discovery at some point down the road, it could be unnecessarily damaging. Now, the bull case for this is that whoever's suing the company and, like, wants that discovery actually has more, like they're more able to make an effective case. but but like yeah i was asking more on like a referral link for companies that i'm planning to sue we uh we had this from companies in all directions like uh some companies are like real like this is an
Starting point is 02:21:27 opportunity for them to have things on record and so they yeah yeah yeah it connects them yeah but plenty go the other way right where they they want everything like off the record and deleted immediately um we've ended up building a bunch of uh retention controls so you can do this either way way, like, some companies will set transcripts to self-destruct after 24 hours. So, like, you know, there's no more record of those, and you just get left with the notes. And, yeah, I think I'm a big fan of that. Like, I feel like we, it's not in our interest to have, like, like, a, like, on-the-record recordings of everything that's happened.
Starting point is 02:22:00 Like, all Grinola needs is the kind of main notes of what we've talked about. Yeah. Yeah, yeah, yeah, yeah. Yeah, yeah. Yeah, yeah. Makes sense. Like, a healthy level of abstraction is, like, good for, everybody there, I think.
Starting point is 02:22:10 Last question. Can you tell me about the brand? Because this could have been called like Panopticon. It could have been black background, steel, silver, you know. It could have been very different branding wise, but it's granola, it's crunchy. There's a, you know, this, this like green color that you've picked. Like, it's clearly intentional. What are you, what are you thinking with the brand?
Starting point is 02:22:33 Yeah, we basically like, I think since the beginning when we first started studying how people take notes, I think, I think one thing that was really apparent was like taking notes in meetings is a really personal thing. And we like, there was already a bunch of AI notakers out there, but people hated them. Nobody wanted to use it and no one felt comfortable kind of like writing their raw, messy thoughts into them. And so we really just wanted Grinola always to feel personal and like it's yours and that the more you use it, the more it feels like your space. And all the branding is like downstream with that. the name, the colors, the kind of messy, like organic feeling textures and stuff. Like, it's all meant to communicate that this is like your thing.
Starting point is 02:23:17 This is not your company's thing. This is your thing. Love it. Well, thank you so much for coming on during a big day and breaking it down for us. Very exciting progress. Fantastic progress. Talk to you soon. Have a good rest of you now.
Starting point is 02:23:29 We'll talk to you soon. Bye. Let me tell you about vibe.com. Where D2C, brands, B2B startups and AI companies advertise on streaming TV, pick channels, target audiences and measure sales just like on meta. and let me also tell you about gusto, the unified platform for payroll benefits and HR built to evolve with modern, small, and medium-sized businesses.
Starting point is 02:23:47 And without further ado, let's bring in Ben from Pulsia. What's going on? How are you? Welcome to the show. Introduce yourself since this is the first time on the show. Tell us what you do. Yeah, my name is Ben. I run a platform called Pulsia.
Starting point is 02:24:04 It's an AI that builds and runs companies autonomously. you give it an idea and it's going to go about building the product, running the marketing, running ads, doing support, and all of the things that a founder would do to start a company and grow it. So should I think about this as you've fine-tuned a bunch of agents, built MD files or workflows that then leverage other foundation models to deliver on those? you have some playbooks in place. Like, what have you done that's, that,
Starting point is 02:24:42 because I imagine you're not training the actual foundation model. You're using different tools off the shelf and different integrations and then fine-tuning things. But walk me through, like, the actual experience of using the product. Of course. I mean, the way to think about it is, you know, I spend, like, a lot of the past 12 months spending 12 to 16 hours a day, using AI, using, you know, cloud code. using codecs and building my companies with it.
Starting point is 02:25:10 Sure. And the idea is that like the fundamental models are like super powerful and I pretty much think that AGI is here at this point. Like the models are super intelligent and they are fluent at using any tools. But I think the trick is knowing how to configure them to give them the right tools, the right orchestration, the right series of tools to get to an outcome, right? So for example, one of our agents on Pulsia can run meta ads campaigns. But to do that, there's a lot of steps that are needed, right?
Starting point is 02:25:39 It's like creating the creative, you know, using maybe an AI, an AI generation model. And different labs are good at different things. You know, nanobanhas great and codex is great. You know, there's writing models and there's all sorts of different things. So you're choosing those and rerouting those. How do I think about it in terms of an actual payment flow? Is there a world where I give you a credit card or a bank account and then you already have the integration set up. So I don't need to go set up an AWS instance or I don't need to go set up a meta ads campaign and you can just kind of say, hey, we're running a $100 test campaign.
Starting point is 02:26:20 We're going to withdraw $100. We think we're going to bring back $200. Okay, we did. Now I need $1,000. Exactly. I mean, if you think about it, like agents are essentially like AI humans that can act on the economy. and today, obviously, if an agent, like if a thousand agents go on MEDA to create accounts, like METI will say no, you need to verify your identity and all this stuff, right?
Starting point is 02:26:44 And so there's the first layer of infrastructure to build that we've built at Pulsia, which is how to make partnership with those platforms to get, for them to understand that it's an agent working on behalf of a human for a certain task and to sort of like have all that setup ready. And as you said, like today we obstructed it quite a bit where like, you know, you pay a subscription and you get sort of like, one task every night of your agent doing work for you and then you can do various types of tasks.
Starting point is 02:27:12 But in the future, as you said, if you want to open a bakery in New York and you have this idea, there's going to be a lot of orchestration to buy the real estate, to hire staff, manage them, all the fulfillment. And AI could totally do this. But you probably will have to say, the policy I will tell you, you got to deposit 100K on an account because we're going to have to a deposit, we're going to have to pay the realtor, we're going to have to hire staff. And that's something that like what Polsia is trying to do is really give access to all the
Starting point is 02:27:43 best practices of being entrepreneur to anyone who has an idea and wants to fund it and wants to try it. And obviously it's going to be a much lower cost at what you what you can do today. Yeah. So Polsia's ramps revenue super quickly. I feel like every time I see you guys, the ARR's gone up. But what is actually, what, give us an example of like automated companies that are working on the platform, like individual entrepreneurs that signed up. Yeah. What are they building? Yeah.
Starting point is 02:28:17 What are they actually building? What are they selling? Yeah. So there's like, you know, an entrepreneur who's like building like a service to create ads from a script. autonomously using different APIs and reselling that to people and has a bunch of customers that are paying. You have another person who's building
Starting point is 02:28:37 an AI receptionist for businesses and so using the agent SDK to figure out how to respond correctly based on context. You also have existing businesses or using POSIA as an AI team that can build a landing page for them, create leads, sort of like lead capture,
Starting point is 02:28:58 and run ads to get customers for their offline business. So there's a lot of different use cases. It's actually very varied because obviously this platform's promise is so open-ended that you get. And it's pretty affordable. It's like $49 a month to try it for a month. And so you get a lot of people with a lot of ideas. Yeah, it feels like the low-code, no-code, like boom all over again, where like there were low-code, no-code products at the hyperscalers.
Starting point is 02:29:28 and GCP and AWS, but there were still platforms that did a little bit more and became like low code, some no code. And you're seeing the same like continuum of like how much do you want the platform to help you before you actually open up the terminal yourself? Does the human matter a lot still? Yeah. Like if I just go on there and I pretend to be like my 10 year old self, am I still, am I going to print or is it, am I going to be cooked? so. So, I mean, first of all, like, it's, this platform is like to build real businesses. So it's not like a get rich quick scheme.
Starting point is 02:30:09 It takes time to ramp up. It takes time to build real businesses. Obviously, trying to do a lot of things on the, on the marketing side to automate more of like trying to get customers, but also bringing on maybe people with ODEP influence that can bring on their, their audience and sell them services. Yeah. But to answer your question about it. about how much the human is needed.
Starting point is 02:30:31 I think that as long as like humans are the ones buying the goods and services, you need another human on the other end who understand the subtleties of what people want these days right now, what are the new trends, what are the new things. In a world where like there's going to be an abundance of new services and goods being sold all over the place because all those AI tools are augmenting people to build faster, better, you need humans for the taste. So the way I explain it is you got the 80% operational work day-to-day grind that can be fully automated by AI.
Starting point is 02:31:10 That's like engineering, that's like support, that's like market research, that's like pricing. And that usually you need to hire people for that. And today with tools like Borsia, they can do most of the work. However, the 20%, which is taste, which is branding, which is like marketing, trying to market intern ways, understanding how to position your product, maybe having an audience to sell to, however small it is, you know, if you have a thousand followers
Starting point is 02:31:38 that are dedicated to what you do and they love you, you don't need that much more to get like 10, 20, 30 paying customers and I start doing income. And today they're selling merch, and tomorrow they can sell real services that may be more sophisticated. So that's sort of the way I look at it. There's a world in the future where I'm going to introduce services
Starting point is 02:31:59 where you can completely autonomously let the agent run wild, obviously, because you don't have to give it feedback. Like it will every day, every night wake up and do work. And I'm going to choose ways for you to let it run 10 times a day, right, if you pay to compute, right? And I'm sure that would work, it's just that like that becomes like, you need to have a very tight feedback loop on like the user, what the user feedback is,
Starting point is 02:32:23 so it feeds back in to what the service is and how to make it better. And I think there's a world where a human with a lot of capital can actually start building a lot of money-printing businesses as the loop gets tighter
Starting point is 02:32:38 and the platform gets smarter about what are the best practices. And I think this is where the world is going. And ideally, I want to give that opportunity to the 99% the people that think that AI is chat GPT and that's pretty much it. And if we can give them the tools to be economic actors in this new era, I think we will
Starting point is 02:32:59 hold benefit and it will be a more just sort of like society. Okay, last question. We have to ask you about the name. You ride a lot of people up because it spells AI slop backwards. Is that intentional? Is that a joke? What's the name? I mean, it started as a, not as a joke.
Starting point is 02:33:15 It was like my lawyer asked me to come up with the name for the ink when I started a company. Yeah. And I was on my couch and I was like, oh, I could name it like, you know, pulse, yeah, I stopped in reverse. That's a good name. Oh, so you're intentional. So it was intentional. It was intentional.
Starting point is 02:33:31 That's amazing. That's amazing. I thought it was like, I thought it was by, I thought it was. No, no. But it was not intentional to, I decided to use it as the product name. Yeah. You know, I started the company like in April and I built the product in November. And I was like, that's kind of cool, actually.
Starting point is 02:33:49 It's very, and I will make people. talk. And it did. Well, thank you so much for coming on the show and breaking it down for us. Have a great rest of your day. Yeah, good to meet you. And we'll talk to you soon. Sounds good. See you. Let me tell you about MongoDB.
Starting point is 02:34:02 What's the only thing faster than the AI market? Your business on MongoDB, don't just build AI. Own the data platform that powers it. And let me also tell you about fin.a. The number one AI agent for customer service. If you want AI to handle your customer support, go to fin.a. I would love to sit in on that pitch meeting. We're building an infinite money glitch.
Starting point is 02:34:20 It did seem like that. $49 a month. I mean, I don't know. There's a world. There's, you know, T-Spring was, you know, empowering entrepreneurs to sell a lot of T-shirts. There's a lot of different things. Depends on what you bring to the platform, I suppose. Well, without further ado, we have Fred Adcock in the Roosterone.
Starting point is 02:34:39 Let's bring him into a TVP. An Ultra. Brett, how are you doing? Guys, good to see you again. Good to see you again. Welcome back. Been far too long. But since the last time we talked to, you launched a new company.
Starting point is 02:34:49 So break it down for us. Oh, Hark? Yes. Yeah. Let me... I want to know about that. Okay. Well, I mean, I guess the summary here is I've been working for the last three years on, I think maybe one of the hardest AI problems in the world.
Starting point is 02:35:02 Yeah. And they had to work on humanoid robots. Yeah. Separately, you know, separately, you know, separately I've been like watching and watching what's happened in the digital world, like, you know, the different language models. And to be honest, I think they're just incredibly dumb. Like, I, I, they don't remember anything about me. It's not very person. they can't listen or talk to me really well, can't see the world, can't use computers well.
Starting point is 02:35:24 I just think this whole experience is just like, I think it should feel very much like a sci-fi movie. This should feel like Jarvis that can like really understand you, very personalized, use tools well. So about seven months ago, I started a new AI lab called Hark and we want to build really advanced personalized intelligence. In order to get there, we think there's some fundamental gaps remaining. in the models. So we basically have a large focus on trying to like basically build new multimodal models.
Starting point is 02:36:00 And the second thing is, you know, we're interacting with AI today through like 20 year old computers. Like my phone and like laptop. These are all like decades old. And we feel very strongly that there's like a next generation of AI devices that need to be like need to be built
Starting point is 02:36:18 to kind of, interface with AGI appropriately. So we have a team dedicated not only to models here, but also on the design side. One of our key guys, Abadur, started about four months ago, previously led design for MacBook, MacBook Air, iPhone 13, 15, 16, 17 was keynote for iPhone 17 Air about five months ago. So Abbs is here with a killer team on the hardware side and we're designing next generation interfaces for the models that we're working on here internally.
Starting point is 02:36:52 Is it the interface that you think is the issue or do you need more compute locally? I think there's like some big gaps in the model side. I think there's like twofold. I think there's some large gaps remaining on the model development side that we want to try to close. And then secondly, there's like, I think the, just the interface of how we're using traditional computers right now to interface this AI is extremely broken. We think both need to be fixed.
Starting point is 02:37:17 to have like a really killer, like, you know, like super intelligent personal assistants. We think you need to fix the hardware interface. And we also think we need to fix the model side. I mean, there's just like simple things today that we need to be better. Like computer use agents today are just not very good. Like they're getting better every month, but there's still like a large gap in order to get their speech to speech systems, which will be like a really natural UI into AGI are just not great. They don't remember things I've told it.
Starting point is 02:37:48 They don't have access to my life. They can't access my calendar. They're not very like, they're pretty high latency. EQ and naturalness are not great. So we're kind of taking this holistic approach to this problem and saying we have to work on the models and we have to like fix the interface issue here today. What is the hiring market right now for all this all this talent? Because you're basically going up against Apple, Open AI,
Starting point is 02:38:17 Quad, you got Demas. Like you're going up against your art, you've already bit off a lot, obviously, with Figure, and I, we can move over and get the update there. But I'm just so curious when you're, when you're recruiting talent for Hark,
Starting point is 02:38:32 I have to imagine any of the, any of the people that you're hiring, if you want to hire them, they probably have the opportunity to work at these other companies. So what's working on that side? I mean, I think the summary is like all the other companies are kind of boring. They're all doing the same thing. They're like all copying each other.
Starting point is 02:38:52 We've like headed certain direction of the last three years. I think that direction is like somewhat saturating. To work on like vision understanding, to working on like models that can go and interact with the world and get that interaction data, we think is like these areas are especially important to push the boundaries and get the AGI. this AGI feeling of highly multimodal scenarios. So we're finding, like, from a hiring perspective, we're being extremely competitive. We've brought on now over 50 people into the team,
Starting point is 02:39:23 about two-thirds of that from the AI side from like top frontier labs. I will say it's probably one of the most competitive areas I've hired for in general around compensation. The space is just completely lit up. Like I've never seen like it before. You know, I've like hired people across all areas of robotics and AI and software and hardware, just like this is, it's next level competitive.
Starting point is 02:39:45 I think we have a very small amount of people in the world that really understand how to build the right infra, pre-training, data mix, all of this. It's just like very tough. So, and all things, some of these spaces are just new. Like, computer using agents that can really reason really well in pixel space, like this is just happening now. So there's not a lot of good precedent for how to go out and build these systems. But why? Why not? What was the decision-making process around doing this externally? Because I feel like a lot of the capabilities that you want to build with Hark, like I'm assuming you'll want to integrate into figure,
Starting point is 02:40:19 if figure is going to be a robot that can add value to my day-to-day life. I, you know, where is the overlap and why build it externally? I'm a bit of a focus. I feel like Figure we have a singular focus, which is like, how do we solve for a general purpose humanoid robot? How do we build like a human and a body suit that has a common sense reason? A lot of the AI focus we have around figure is basically how do we predict physics around things like grab and touch and move through the world.
Starting point is 02:40:50 At Hark we have a different objective. We want to launch like next generation consumer electronics and we want to basically build extremely multimodal models that can almost act as like a Jarvis type interface to AI. And the focus on those tracks are completely different. And with that said, though, I think there's some opportunity over time to closely collaborate. The voice on the model on the robot today is using the Hark voice API. So if we talked to any of our robots here today, it's using the HART voice model that we designed here internally. So I think there's like a lot of room over time to collaborate the business together.
Starting point is 02:41:29 We're both, we're like, we're taking an entire data center of B200s in April here and figure little has half the building and Hark has the other half the building. Obviously paying for things separately, but we literally between the two of us have an entire data center of like next generation Blackwells that we're using for training for AI models. I want your latest timelines on the chat GPT moment for robotics, humanoid robotics.
Starting point is 02:41:57 We were talking to Sean McGuire about this. He was putting maybe like two to three years away. Three to four years from just, you know, seeing them on the streets, seeing them in restaurants, seeing them in the real world, maybe not economic impact, because that could happen in, you know, all sorts of different industrial settings. But it will be a special moment, I think, when people wind up interacting with a humanoid robot. What are you thinking these days? You can come to figure right now, and you can see robots running complete 24-7 shifts. Yeah. Fully autonomously with neural nuts all the way
Starting point is 02:42:37 down the stack. That's amazing. So, like, I think this will be a big year for us to ship robots commercially to many different customers of ours. Yeah. And then we're also working on trying to how do we integrate these into the home? Yeah. How do we get robots to go and do, like, laundry and dishes and tidy the house?
Starting point is 02:42:53 Like, things that we just, like, I don't want to be doing. Nobody really wants to do. And use, like, robotics as a key tool for this. I think we're, I think we're, like, having this moment now. I think it's, we're in it. We're feeling it as, like, I can. right now, like we're seeing these robots do long horizon, autonomous work at Figure here.
Starting point is 02:43:13 And I think over like this year and next year, it's going to be very, the whole world's going to wake up to it. I think we saw a little bit of that at the White House last week with, uh, with Figure. It was just like, we saw like unprecedented demand. Like, uh, it was, um, it was kind of crazy because we didn't show any like new capabilities.
Starting point is 02:43:29 So we're like, uh, internally we're like, okay, we're just going to be at the White House. And it was a big, it was a big, um, it was a big, it was a big milestone, like the first humanoid robot. built in the U.S. at the White House in history. So it was like getting the invite from the White House to come there and be able to be the first one to do.
Starting point is 02:43:44 It was just a huge. It was great. But like, you know, there was no new capabilities there. But like the whole world is just like waking up to the moment now of humanoid. And it was a very apparent from last week at all the incredible reaction we got from like basically the entire world that we're still early here in the cycle. I love it. Well, good luck.
Starting point is 02:44:04 And thank you for taking the time to come shout with us. One quick question. Can humanoid reliably crack open a cold diet Coke and serve it? Or is like, I imagine the tab is like kind of a challenge. That's AGI for me. I don't think they should have any problem doing this. Okay. That's a demo.
Starting point is 02:44:21 That's a demo. That's a demo we'd love to see. Because honestly, John would would buy a humanoid just to come over with a cold one, crack it open. He goes through a lot of these. So I think it gets a real utility out of it. All right, John, bring a six pack over to figure and we'll test them out in person. It's a deal. I'll talk to you soon. Awesome.
Starting point is 02:44:39 Yeah, see you guys. Good to see you. Cheers. Talk to you soon. Let me tell you about the New York Stock Exchange. Want to change the world? Raise capital at the New York Stock Exchange. And let me also tell you about CrowdStrike.
Starting point is 02:44:49 Your business is AI. Their business is securing it. CrowdStrike secures AI and stops breaches. And without further review, we have Andre from Console. TBPN royalty in the TBPN lecture on. Andre, how are you doing? What's going on? Great to see you.
Starting point is 02:45:04 Great to see you, dude. Good to see you. for taking the time to come show with us. You're always with us. Yeah, you're always with us. Yeah, I was going to say I love to stick. It's a special to have you here. Anyway, why don't you just give us a general update on the business?
Starting point is 02:45:18 Like where, walk us through some features, some customers, and then I want to hear the latest and greatest. Oh, absolutely. Thanks again, guys, for having me on. Of course. Yeah, so I think as you guys know, maybe the rest of the audience doesn't. But we are, you're console. we build AI agents that automate service management or employee support. We do that directly in Slack or teams.
Starting point is 02:45:43 And, you know, things like onboarding, off-boarding, PTO requests, access management. You know, even telling the facilities team, there's no more napkins left in the bathroom or something. And so last week, we just launched our kind of a big product called Assistant. And Assistant helps you do Tier 2 work. So it's not just the Tier 1 employee support stuff. Now it's an assistant, it's an agent that helps your IT, HR, legal finance team, automate the more complex tasks that often span, you know, multiple systems. So, for example, say, you know, there's, like, there's an internet outage. You can actually now ask Consul to go and investigate across those different systems. So on the back end, we're plugged into your Maraki, your CrowdStrike, your Octa, your Entra, all these different systems. And Consul knows how to go and pull data from those different tools. and kind of come back with a report for you.
Starting point is 02:46:37 You can also tell Assistant to go and fix things, right? So you can say, actually go and, you know, push this update to this user's laptop or something like that. And then you can also have Console build out itself now. So with Assistant, you can tell it, hey, I want to connect into Kupa or NetSuite to pull this information. And Console will go read the API docs and then build its own connector into that system and then write a workflow with it. Well, yeah, I was about to ask. That's like, that's basically like it's instead of doing a feature. request just request the feature yeah yeah I was going to ask like it feels like years ago you would
Starting point is 02:47:10 be spending like you know you'd be stack ranking all the different integration requests it would take like maybe a month or two to write each one my hand I imagine that that was accelerated when you first built the product but now it can be handled on the customer side which is crazy to me yeah so when we started consular you know we were like hey we're actually going to build this framework internally. And then our engineers are going to use AI agents to like build out integration super fast using that framework. And so we'd get things done in like two to three, four days. Yeah. And then I think, you know, a couple, maybe two, three months ago, we were thinking ourselves, like, can we actually just have console to do that, you know, just iterate on itself?
Starting point is 02:47:52 And that's where the idea came from. And that's what does. So you just tell it, you know, the same way I would tell an engineer, hey, like, we need to build this for this customer. Now the customer can just tell console directly, you know, I want to pull this data. I want to all these actions into these systems and, you know, it'll build itself out to do that. You think that's going to be an entirely new, basically part of every product where you'll still be able to request a feature, but at some point it's like you're paying for the software. You should be able to adapt it to your own needs. But I haven't, no one, no one's come on the show and like pitch that specifically as a company in the
Starting point is 02:48:31 application layer, basically like, we're going to give you the autonomy to adapt the product to your close. Yeah, it's crazy new paradigm. Which is just crazy because like every, every, every customer wants that. Yeah. They want it. They're not like, oh, I want to wait for the support to get back or my account manager to talk to the engineers and. Yeah. I think I'm sure it'll come, you know, come about in other tools as well. I would say the core unlock for us was actually building out a really robust and kind of framework interface that we can plug into.
Starting point is 02:49:07 I think once you have that and you have, you know, the really important piece for us is this, you know, the context graph. So we have a context graph under the hood where we're ingesting data from these different systems. We actually like model out your organization. And so when you tell it, hey, like go and update, you know, John's laptop to this version, or you ask it like, you know, what is John's version of his laptop?
Starting point is 02:49:28 It gives you an answer. you say go and update it. You know, console already knows who John is. You know, we know what laptop you have in order to find it. If you were to build that from scratch,
Starting point is 02:49:37 like, you know, you might have committee lookups so it would get kind of like, you know, a little lost in the sauce. And so that, that context graph is really important.
Starting point is 02:49:44 It's really a core part of what we've built here. How are people thinking about... You got to coin this, by the way. Yeah, this isn't entirely, you need to, you need to,
Starting point is 02:49:53 you need to deploy something. I don't know, for you, yeah, something. What should we call it, guys? I don't know.
Starting point is 02:49:59 like agentically deployed engineering or something. I was saying you name it after yourself. Yeah. Yeah. The Serban method. Yeah, yeah, the Serban. The Serban. Yeah.
Starting point is 02:50:09 You got to get people posting like, Figma needs to incorporate the Serban method. Yes, yes. This is it. Yeah, I think we got it. We'll work on it. Wait, so talk me through the experience of onboarding to console and how people are thinking about this in terms of like net new functionality.
Starting point is 02:50:28 so I'm basically increasing my AI, my IT spend, but it's all justified because workers are happier, we're getting more stuff done, versus like ripping, replacing an existing system or not going with an alternative solution. Or like at one point in like 2013, I was scaling a startup. We had like 50 employees. We had like an outsourced IT partner
Starting point is 02:50:51 that was like one day a week and they managed like a ticketing system. It was very manual. But there was basically like a consultant who was, available every once in a while, like a fractional IT person? How are companies actually interfacing with console and like integrating? Yeah. So I would say most IT and kind of service management teams roughly scaled linearly with headcount growth. So you have like one IT person for 100 people or maybe one to 150, maybe one to 200.
Starting point is 02:51:24 If you don't include Ramp, who has a very, you know, insane ratio. But, you know, most companies are in that range. And so with console, they're able to take that, you know, they go one to like 400, one to 500. So we act as ultimately like this force multiplier for your team. And so, you know, yes, there's spend going into console, but you're actually saving on the back end of that as you're, you know, we work with companies like data bricks, you know, cursor, figma, chime.
Starting point is 02:51:54 You know, and these guys are growing incredibly fast. And a lot of these guys actually have plans to keep their IT teams flat, you know, through this hypergrowth phase that they're about to experience. And it's entirely because of console. And so we're seeing, we're starting to see that now, not just in IT, but, you know, HR, legal finance workflows as well. Where, you know, they're just doing this employee support where they're just answering questions that, you know, answering questions are taking action into systems that they have kind of elevated permissions. into. Now you can have an agent that just does that so they don't need to spend their time on that. They can focus on more. Do you just, are you the only IT person at console? Like, do you force yourself to dog food the product to the extreme or are you, what's the? We take a bit of a crazy
Starting point is 02:52:47 approach here where everyone has full admin access to console and everyone is just encouraged to build your own more close up. You want everybody using the product. At some point, we probably need it pull it back. I think our head of security was complaining last week. He's like, okay, we've got too many salespeople in here. I can imagine. But like, you know, we've got, we actually have like our, I was actually just talking to our office manager. We're going to have console just do our dinner orders as we do dinner in the office every day. And, you know, with assistant, now she can build out her own workflows. She says, hey, I want to, you know, ping me every week at 4 p.m. give me the options. I'll select it and just like go and order it
Starting point is 02:53:27 into, I think she's using like EC cater. So not an integration we would have built out if, you know, on our own, but I think with assistant it can do that. And so, you know, our head of security actually, he was just, he was presenting a use case to us the other week. He rolled out crowd strike on our devices. And he did in like 40 minutes instead of, I think, what he said, you know, would have taken him like a day or two.
Starting point is 02:53:50 And he just, he did that entirely through assistant. He was just, hey, I want to, you know, plug into these laptops. It went, it understood, hey, you need to download these two binaries. if you're going to deploy it on these versions of macOS, here's re-upload it, here's the script you write, okay, do you want me to push it? Yes, and just deployed it. So I think there's more use cases than we can imagine,
Starting point is 02:54:10 and so I think we work closely with our customers where we're almost like just trying to show them the technology, and then I think they tell us what they want to build. Yeah. Yeah, I mean, there's so many startups. I'm sure a lot of founders in the audience have felt this before where you're the CEO and you set up the, you know, know, all the IT systems and then actually off-boarding is like the super admin is extremely difficult. I actually, I actually fully lost my Amazon account at a previous company because
Starting point is 02:54:39 it was so deeply integrated into the company that they just couldn't figure out I'd change the super admin. I was like, just take my, just take my Amazon account. And so I just don't have audible anymore or like Amazon Prime. I need to set up like a new account. I'd basically just declare like Amazon bankruptcy because I was just the admin for like a decade. And it's, things just like built up and I'd try and give people the other password. Anyway, there's a million hundreds. How are you, how do you, how do you try to, how have you been trying to model like the like overall opportunity for console? Because you're still early stage. So at this point, it's just like, let's get as many great companies as we can on the products. But then, you know, five, 10 years from now
Starting point is 02:55:20 at later, later rounds or stages, you'll be kind of, you'll probably be asked that question more seriously, but how do you think about it? Because you are at this moment, like, selling against what historically was like the kind of, I don't know, labor, Tam to some degree where, but the other side of that, the interesting thing is there's a lot of companies that would like use console that never would have had a dedicated IT person. And so it's not entire, it's not just replacing people. It's like bringing a kind of capability to a company. But how are you thinking about the overall category? Absolutely. So there's a couple of things, I think, that are going on at once. I think the first one is, you know, when we look at IT today, it's very much a reactive role. It's very much a cost center because I think it's kind of like escaped us a little bit, right? In the 80s and 90s, IT was actually an enablement center, right? You were bringing in technology or deploying, you know, giving people computers, you know, deploying Wi-Fi and not Wi-Fi, but Internet.
Starting point is 02:56:26 giving an email and so on. That's like a force multiplier. We've done too much of that. We have too many SaaS apps. There's all this sprawl. And now the team is just managing that, right? They're just doing support. And so with console, the way we think about it is we're going to bring our teams back to kind of what it was like in the 90s,
Starting point is 02:56:46 where you can actually have this agent handling, you know, all of the ticket management for those simple systems. and those kind of basic requests. Now you have assistant that can go and do more complex work across the enterprise. And the value there is now you can do ten times as much as you were going to do it in that year. And if you think of, you talk to any company, no one will tell you, oh, yeah, like our IT team is kind of always on top of it. Our IT systems are perfectly set up. There's always something kind of a little bit lagging behind, and it's because they're just constantly drowning. And so console allows them to kind of focus on the more strategic and kind of be more outcome-based.
Starting point is 02:57:29 And so I think when you think of it that way, you know, that the TAM is actually all of the work that, you know, all these companies would love to do. And they just don't have the employee headcount or the cost really to go and spend on it. And so that's one big piece. The other one is we're actually just ripping out and replacing, you know, tools like Service Now and, you know, your service desk and fresh service and kind of replacing the more AI-native solution. And so we expect that to kind of scale as you onboard more, as companies become more digital native, right? They have more SaaS.
Starting point is 02:58:04 You're saying you're the SaaSpocalypse. You're flaming the fires of the SaaSpocalypse. I didn't say that. I said that. Very, very cool. Yeah, it's great to get the update. that yeah and we're going to work on this coinage go back with the team brainstorm a little bit you tell us you tell us what and we'll start asking every company are you guys using the serban method
Starting point is 02:58:30 yeah we'll figure it out it's good it's good yeah i love it i'll run it by my head of growth we'll see what she says fantastic good good have a great rest of you day we'll talk to you soon thanks guys we're we'll talk to you soon um there's a bunch of news that we need to run through before we head out Artemis 2 is launching and Kalshi has it at 64% chance before April 2nd of this year. We're going to the moon. Four people are going to the moon. Everyday astronaut says, I'm honestly shocked at how the general public has no idea.
Starting point is 02:59:04 Artemis 2 is taking humans out to the moon and will be the furthest humans have ever flown. Every non-space nerd I've talked to has no idea. We've got to get people stoked. This is what I'm going to be writing about tomorrow. I want to deep dive this. Why is no one talking about ours, too? Why is no one talking about the moon? We're going.
Starting point is 02:59:21 NASA is set to launch four astronauts around the moon, the deepest human spaceflight since the final Apollo lunar landing in 1972, and there's a bunch of goals. So you can go track that, and we will talk more about that tomorrow. And, of course, bring you a whole bunch of other news and interviews. Tomorrow, leave us five stars on Apple Podcasts and Spotify. Sign out for our newsletter at TBPN.com. Tom. It's been an honor. It's been an honor. It's been an honor to be here. It was a rough couple days. It was a rough couple days being away. Yeah. But we're back. We're incredibly back. I'm glad we're going to be a great week and have a wonderful evening. Yeah, we will see you tomorrow. Goodbye. Throwing smoke. Okay. Goodbye, everyone. See tomorrow folks. Goodbye. We'll be back with the smoke clears. Wonderful day. Goodbye.

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