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TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays from 11–2 PT on X and YouTube, with full episodes posted to Spotify immediately after airing.
Described by The New York Times as “Silicon Valley’s newest obsession,” TBPN has interviewed Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella. Diet TBPN delivers the best moments from each episode in under 30 minutes.
You're watching TBPN.
Speaker 2:Today is Monday, 03/30/2026. We are live from the TBPN UltraDome.
Speaker 1:The temple of technology, the fortress of finance, the capital of capital.
Speaker 2:Let me tell you about ramp.com, baby. That is money. Say both of these. Use corporate cards, bill pay accounting, and a whole lot more all in one place. Let's pull up the linear lineup.
Speaker 2:We got Tae Kim coming on to give us the NVIDIA update. He is, of course, the founder of KeyContext, the substack. Logan Bartlett's coming on from Redpoint. 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.
Speaker 2:Very, very good. Tons of really interesting tidbits in there. And then we have a fantastic
Speaker 1:It's a great
Speaker 2:lightning round for you today. Linear, of course, is the system for modern software development. 70% of enterprise workspace on Linear are using agents.
Speaker 1:So lightning round, we got Ben Broca from Polsia. Sam, founder of Granola Yeah. On their 1 and a half billion dollar valuation. And then Brett Adcock.
Speaker 2:What was your nickname for him again? Who? Brett Adcock. You had some nickname for him.
Speaker 1:No. Right? No? No. I didn't.
Speaker 1:You called. You're on a
Speaker 2:first name basis. You just call him Brett.
Speaker 1:Brett. Yeah. Or just b. Yeah. A b.
Speaker 3:That makes sense.
Speaker 1:A b. Okay. Now, this will be interesting. He launched a NeoLab last week.
Speaker 2:Oh, yeah. That's right.
Speaker 4:That's right.
Speaker 1:So we're gonna be able to talk to him about that. Models and hardware.
Speaker 2:Hark. I hear the angels singing.
Speaker 1:And then Andrei from console joining as well. Fantastic. Looking forward to that.
Speaker 2:Well, I've been addicted to social media lawsuits. I cannot get enough of these lawsuits. I keep reading about them. Who's in sleep?
Speaker 1:You're potentially filing your own lawsuit against the lawyers Yes. That Yes. Were coming after these social media.
Speaker 2: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 are driving jurors crazy across the country. Attorney Mark Lanier, he uses props.
Speaker 2:Come on. Come on. What's more to do with props? He use he also uses parables. Okay?
Speaker 2: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 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.
Speaker 2: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 Meta's Instagram and Google's YouTube were designed to be addictive and were harmful to young people. So the veteran plaintiff's lawyer
Speaker 1:We just say he looks fantastic for 65.
Speaker 2:He does look fantastic. And and I and as much as I'm joking, do think he's doing important work and I do think there's a potentially really good outcome here that we'll that we'll go into. But we're still having some fun. So the veteran so the veteran plaintiff's lawyer from Texas showed them two grocery items, cupcakes and tortillas. Social media, he told the the courtroom, was like the baking powder that makes a cake rise, exacerbating the struggles of already vulnerable teens.
Speaker 2:We have an interactor, an amplifier, something that blows it up, Lanier said. We have here social media that takes the vulnerable and goes after them in destructive ways. It's as easy as ABC. So he's making the argument that social media is more like cupcakes than tortillas. Both contain flour.
Speaker 2:Both are carb carbohydrate loaded, but one is bigger than the other or puffier, I suppose. The simple image delivered with linear's slight drawl 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 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.
Speaker 2:He's saying, I reject technology. This cannot be stored digitally. I'm using paper.
Speaker 1:Which, I don't know, this seems a little bit risky because we've been addicted to the printed word So in the much so that we face criticism Yeah. From people that said, hey, printing is unnecessary.
Speaker 2:It did. You're Yeah. Not environmentally friendly, but
Speaker 1:And we were forced to adjust.
Speaker 2:Maybe he can flip over to to be our defense attorney when we are attacked. There is a there's a courtroom sketch showing linear questioning former TBPN guest, Adam Osseri, the head of Meta's Instagram. A jury ordered the company to pay $3,000,000 each in compensatory damages and 3,000,000 in punitive damages. So I think it's 6,000,000 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.
Speaker 2:Very, very sad situation. 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.
Speaker 2:What do think?
Speaker 1:They're like, we're not even a social media company.
Speaker 2:We're a VR company.
Speaker 1:No. No. No. Google said Oh, yeah. Misunderstands YouTube which is respond which is a responsibly built streaming platform, not a social media site.
Speaker 2:That's true.
Speaker 1:Got the wrong guy.
Speaker 2:Yeah. I've I I think of of YouTube very much as 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 like you if you when you when you actually become a YouTuber, you start putting out content that like there is sort of a I don't know, like a group of made men on YouTube. Like, people that have that have ascended and they now have they 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. Of course, there are different communities.
Speaker 2:There's like the car YouTuber community. And then there's the 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
Speaker 1:Which is a which is a good argument for it
Speaker 2:Not being social media.
Speaker 1:To be not being a social media.
Speaker 2: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. We can go on to the Colin and Samir YouTube channel and leave them a comment, and they might see it if it's from the TBPN 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.
Speaker 1:Yeah. That's a huge feature request.
Speaker 2:It's insane because like it would be so cool to see to be able to see, okay, I got a DM from someone who has a 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 the DM functionality is much more mature on on
Speaker 1:The other thing Google has in the in in this kind of position is that so much of the watch time on YouTube is happening on television. Oh, yeah. Something like 50%. Yep.
Speaker 2:Very different.
Speaker 1:So they can make the argument that this is just modern Yep. Television.
Speaker 2:Yep. So let's go through Lanier's career because The Wall Street Journal has some interesting backstory here. He says Lanier has built a career and 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 drug Vioxx caused heart problems. He also won a $4,690,000,000 verdict in 2018 for women and their families who said asbestos tainted talcum powder caused ovarian cancer.
Speaker 2: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 plaintiffs team last fall and was brought face to face with Meta Chief Executive Mark Zuckerberg. Suddenly, Lanier was at the
Speaker 1:that Zuck is actually mewing in this picture. If we can pull up this this image.
Speaker 2:It does appear to be something along those lines. Suddenly, Lanier was at the epicenter
Speaker 1:You agree, Tyler. Right?
Speaker 5:You can tell his cortisol is not spiking here.
Speaker 2:That's true. That definitely seems he seems calm, collected. 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.
Speaker 2:Quote, nothing compared to this, Lanier said, reflecting on the attention to the trial over oatmeal toast and a Coke Zero in Downtown Los Angeles hotel in a Downtown Los Angeles hotel the morning after the victory. Nothing even remotely close, 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 where, like, I remember them vividly. Do you? No. No.
Speaker 2:Vioxx? It it does not ring a bell. But this certainly will for a lot of people, especially in tech. Social media companies have largely been shielded from being held liable for third party content on their platforms by section two thirty of the 1996 Communications Decency Act. At trial, Lanier had to focus on the platform's features, not the content to make a case.
Speaker 2:That's something that I want to talk about today and I wrote about 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 case, settled the first case. A Christian who teaches bible study classes to as many as 500 people in evangelical church. Lanier turns a folksy courtroom demeanor honed over decades of trial work, first in Texas, now nationally.
Speaker 2:He's known for showing jurors hand drawn road maps 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 bought he brought a bale of hay into a courtroom and dropped a needle into the blades. Into the blades? The blades of grass. Oh, blades of hay.
Speaker 2:Got it. Okay. Wow. Very, very interesting. He yeah.
Speaker 2:He he he likes he likes props. That's it. When arguing for punitive damages against the tech company Lanier held
Speaker 1:up Quite a jar addictive.
Speaker 2:Of this is a good point. So he he held up a jar of 415 m and m's to show how a $1,000,000,000 fine would be a fraction of Alphabet's 415,000,000,000 in shareholder equity. He needs a bigger chart 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.
Speaker 2:What? He burns his suits after? Is that a joke or he gives them away? I don't know.
Speaker 1:My work here is done?
Speaker 2:Guess. Retire it? I don't know. It's odd. 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.
Speaker 2:He began gaining renown as a lawyer in an era when asbestos cases were swamping The US course. He won a jury verdict of about 115,000,000 in 1998 for 21 steel workers who fell 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.
Speaker 2:Overnight success. 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 a 120 people. Okay. This guy's got to win. I have completely changed my position here.
Speaker 5:I need a mansion section article.
Speaker 1:I think we have a direct line to him, by the way. Okay. We want him on the show. Well, like this is Maybe we should go do a show from
Speaker 2:Yes. The
Speaker 1:from the model train.
Speaker 2:Yes. I'm I'm so ready to be convinced of his position. I I I wrote a whole piece about how I disagree with the result but he's winning me over.
Speaker 1:Disagree with this entire argument but you're agreeing with this approach to life.
Speaker 2:Yes. 100%. 100%. I feel like we're kindred spirits. It's amazing.
Speaker 2:So the model railroad can see a 120 people and guess what? He's got a menagerie.
Speaker 1:There we go.
Speaker 2:This is gold. You need to be menagerie maxing in life. You need a menagerie. His contains lemurs
Speaker 1:There we go. And llamas. There we go.
Speaker 2:Lemurs and llamas. Thank you. 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.
Speaker 2:This is incredible. Inviting 9,000
Speaker 1:He's an environmentalist.
Speaker 2:From the community. I mean, that's like the entire I mean, Houston's a huge city, but that's like that is so so what a pillar of the community. This guy's a hero. Lanier said, The theme of his cases against major corporations is responsibility and integrity or lack of it. Tech billionaires don't need his help, Lanier said, but Kaylee would not have anybody else.
Speaker 2: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
Speaker 1:By the way, you keep saying linear.
Speaker 2:Is it linear or linear? Linear. Linear. Linear. Linear.
Speaker 2:Linear. I I think it's linear. Well, we'll figure it out. He has deep authenticity. You don't want
Speaker 1:people to get confused with the system for modern talk stuff.
Speaker 2:Yes. It's not linear. It's linear, I think. Maybe it's Lanier. Maybe it's French.
Speaker 2:He's not a phony. What he does is not a performance. Even from even from Los Angeles, he posted short video selfies discussing bible passages on YouTube. So he's dogfooding, the thing that he's suing.
Speaker 1:Yeah. Let's switch gears to your piece.
Speaker 2: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 marketplaces, and now with AI agents. 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.
Speaker 2:So last week, Brandon Guerrell summarized the ruling this way. He said, In the case, the plaintiff's lawyer, Mark Lanier, argued that Meta and YouTube built digital casinos that used neurobiological techniques similar to those employed by slot machines. 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.
Speaker 2:Algorithmic recommendation feeds use highly users highly engaging content. Feeds algorithmic recommendations, feeds users highly engaging content. 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.
Speaker 2:Okay. So you got a bunch of features. You know this stuff. You everyone uses social media. We all know about this stuff.
Speaker 2: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 is posted on
Speaker 1:Lanier's entire Lanier's entire argument is predicated on it being the features. Right?
Speaker 2:Yes. The features. 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 $6,000,000 settlement right now, but this is this could be huge. The direct quote was whether we will even have social media in the future.
Speaker 2:Like this could be existential.
Speaker 1:Yeah. And and there's thousands of other cases like this kind of percolating. Yep. Right? And so And they could
Speaker 2:turn into a class action. He's gotten 6,000,000,000 before. He could get 50,000,000,000. I don't know. He could get a lot.
Speaker 2:And he's not like, million is he's not a 6,000,000 guy. He's a 6,000,000,000 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 Yeah. The tech companies.
Speaker 2: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. So OpenAI's 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.
Speaker 2:We won't be able
Speaker 6:to It's look simply
Speaker 1:too good.
Speaker 2:Simply too good. And Rune summarized this pretty well, think yesterday or I think 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 among many on Instagram Reels.
Speaker 2:Don't worry so much about making videos that are going to blow up people's brains without making anything good at without worry worry about making anything good at all. The best sores were up there with the best reels and the humor relied significantly on the voice of the creator. I completely agree. The the funny sores that I
Speaker 1:Yeah. Even the video we played last week of the cat on the porch. Yes. That wasn't Yeah. One The
Speaker 2:prompt was not make something that will retain users.
Speaker 1:And it wouldn't have been funny Yeah. If the person hadn't been escalating like the scene Totally. Every new prompt and then cheering them together.
Speaker 2: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 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.
Speaker 2: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. So our app was basically the same as TikTok, Instagram Reels, YouTube Shorts, Snap, in terms of UI and UX design. It had infinite scroll. It had algorithmic recommendations.
Speaker 2: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 To all of the same try to
Speaker 1:like match that every It
Speaker 2:gave me crippling body dysmorphia, obviously. I I dream for the for the day when I will look like my Sora avatar, my my what what do they call it? Cameo? My cameo? No.
Speaker 2:But they they really did use all the normal tools and 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.
Speaker 2:Like the features were not addictive because the people that downloaded Sora did not become addictive because the content was a little bit too sloppy, right?
Speaker 1:Yeah, well, it was just one type of content. Exactly. And it turns out people like a broad selection and they like variability. Yes. They might want to see a video of someone skiing and then some slob and then something their friend made and then some health content.
Speaker 1: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 were addicting, there would be so many social media there would be so many social media apps that were effectively thriving. There would be like a bunch of Instagrams.
Speaker 2:And this is where I get to the 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. That is like And and maybe like 1%.
Speaker 1:Some could argue it's an addiction to looking cool.
Speaker 2:There you go. But 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 and a thousand different e cigarette brands. And nicotine gum is addictive.
Speaker 2: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, then we should see addiction like results from any app that implements that. Yeah. Because that is the case for all nicotine containing products.
Speaker 2:They all addict people at mean, there are less addictive formats
Speaker 1:in How apps have you tried or test flights over the years that had any of these features Yeah. That you used for thirty seconds
Speaker 2:Exactly. Exactly. Because what actually keeps you coming back is the content which is created by the users. And And
Speaker 1:so you're at you want Lanier to go after every single person that has ever posted anything on Instagram and jail them. Correct?
Speaker 2:No. No. I think that some creators do create very compelling content. Some of that You
Speaker 1:want to jail the
Speaker 2:best creator? Is no. Some of that content is amazing. Some of that content is great. Some of that content is bad.
Speaker 2:There's a very, very wide range. 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. Andrei Karpathy's YouTube videos.
Speaker 2:There's so many interesting educational history shows, podcasts. There's so much content that
Speaker 1:Yeah. Got addicted to that video, Are You Destined to Deal? Anyway, he kept
Speaker 5:saying That's a great video.
Speaker 1:He kept saying
Speaker 2:why That's why you have a tie on today.
Speaker 1:He he he called me on Friday night
Speaker 2:Yep.
Speaker 1:And said, why is this video twenty hours long?
Speaker 2:Because he was on loop? Yeah.
Speaker 1:He was just looping.
Speaker 2:That makes sense. That makes sense. So yeah. But I mean, it is true. Like like I think the court is correct and and Lanier is correct that some people go on social media and make horrible content that depresses people that land on it.
Speaker 2:And it goes without 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 someone to call. And they know when to route the right people to that.
Speaker 2: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 plug ins on mobile web, but it's a much worse experience because you have to load 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.
Speaker 2:But having those, like, in the settings to just say, like, I 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, 5,000 likes because the creators were getting, like, you know, annoyed by, oh, this one
Speaker 1: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 and the world would know that their content wasn't engaging or something like that.
Speaker 2:Right? So
Speaker 1:So that 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.
Speaker 2:I don't know. I don't know. I mean
Speaker 1:I'm sure.
Speaker 2:Like, they they they're 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 ten minute video essay about a dying VR technology or something like that.
Speaker 2:It's like, I've done it. 300 people sat down. It's like I'm a business school professor, basically. Yeah? Yeah.
Speaker 2: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 but I hear
Speaker 1:you. Yeah. But the metrics are still available Yeah. To the creators.
Speaker 2:Yeah.
Speaker 1:Yeah. You can the creator
Speaker 2:But you
Speaker 4:can turn them
Speaker 2:off with a Chrome plugin. You actually can't. There's some creators that do this. This. Anyway, surfacing those in apps, I think that will help users feel like they're in more control.
Speaker 2:And realistically, I don't think it will be super damaging to any of the platforms because most people won't opt into that, but certain people will. And in general, it'll 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 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 seems in the cards.
Speaker 2:Anyway, we can debate this, but first, let me tell you about Sentry. Sentry shows developers what's broken and helps them fix it fast. That's why a 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 save, borrow and invest securely connecting bank accounts to move money, fight fraud and improve lending now with AI.
Speaker 2:So do you have any other pushback on my take Tyler had some pushback. Should we go to him?
Speaker 1:Let's go to Tyler.
Speaker 5:What do think? I mean, yes. I guess there was a few things. I mean, one thing is that like
Speaker 2:Not enough props. Right? Too many analogies? Too many parables?
Speaker 5:Like, I I I think you can say that like, okay, yeah, it's the content that's the problem. Mhmm. But, like, the content is, like, kind of downstream of the features. Right? Because you didn't see, like, short form video
Speaker 2:The medium is the message. Yes. And so it it is possible for me to create a platform that incentivizes addictive content. And that's like the retention curve. So retention editing makes it more addictive.
Speaker 2:You become addicted to the content, but it's because of the features.
Speaker 5:Yeah. So I I think that's like broadly
Speaker 2:Pretty good argument.
Speaker 5:The steel man that you you can make for Yeah. Like Lanier's position. Yeah. And then, I mean, there's other stuff I I think on, like, just the nicotine analogy, we were talking about this, like Mhmm. Okay.
Speaker 5:So you have nicotine, like, broadly, and then below nicotine, have, like, smoking, which is, like, definitely very bad for you.
Speaker 2:Mhmm.
Speaker 5:And then you have, like, you know, pouches or stuff like this, which is probably less bad, like it's just nicotine, there's no tobacco, so like maybe this is like less bad. So maybe Yeah. The equivalent is like, you know, the the cool snowboarding videos on Instagram Yep. Are like the, you know, the the cleaner like nicotine stuff and then the like.
Speaker 2:Still addictive but not harmful.
Speaker 5:Yes. And then there's unless you're Jordan, you're
Speaker 2:gonna try and do a double cork twelve sixty and and eat Get smoked. Get smoked into the ground.
Speaker 5:Yeah. But but but then on the other side, you have like 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 the cigarettes that's like gonna give you cancer or whatever. Sure. Sure.
Speaker 5:So I I think they're like I I mean, I guess I still agree with what you're saying, but like
Speaker 2:Well, nicotine Yeah. This is what
Speaker 3:the cigarette If you're under 18, you
Speaker 5:can't buy.
Speaker 2: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, 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 as long as the content was not carcinogenic with inside that app.
Speaker 4:Yeah. And that would be like
Speaker 2:a new nicotine gum, basically.
Speaker 5: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 you if you can't be under 13 or whatever, but like it's like very not it's like poorly, know, enforced. Like you can actually see a lot of the the bad stuff Yeah.
Speaker 2:You're under
Speaker 5:18 on Yeah. Or whatever. Yep. So like directionally, there you know, you can be against the the the ruling of this Yeah. But, like, the the parental controls that people are, like, asked for are still, very much not there.
Speaker 2:Yeah. Yeah. No. That makes sense.
Speaker 1:So I I I think I have a potential solution. Let's pull up this image of a cigarette package in Europe.
Speaker 2:Oh, yeah. What is this?
Speaker 1:So pull this up.
Speaker 2:Let's pull up.
Speaker 1:This is the hardest challenge.
Speaker 2:While we pull it up, let me tell you about Okta. Okta helps you assign every agent a trusted 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.
Speaker 2:Were search. Built from first principles in optic storage. Fast, 10 x cheaper, and extremely scalable.
Speaker 1: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 avoid overseas trips as much as possible. So on any given cigarette pack in Europe, you're gonna see like a really terrible image. This woman apparently is coughing up blood.
Speaker 1:Yes. So I think what a potential solution 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.
Speaker 2:It could show you
Speaker 1:And then you can scroll past
Speaker 2:I could potentially show you with Technek. Are you familiar with Technek? Yes.
Speaker 1:Yes. It's just a crazy image of you at Tech neck
Speaker 2:It shows
Speaker 1:and you a then so you can scroll past it Yeah. Every time you open that app, it's a new image. It's a reminder. It's a new image of you looking
Speaker 2:Yeah.
Speaker 1:The worst, wasting your life away.
Speaker 2:Are the AI labs lobbying to get this
Speaker 1:right, can put this away.
Speaker 2: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. Has anyone come out as pro smoking?
Speaker 1:Don't think anthropics come out with These are They're anti anthropic, you know, has Yeah,
Speaker 2:anti sunscreen.
Speaker 1:The joke that they make with journalists. Yeah. They kind of got caught on anti But if
Speaker 2:AI's 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 the thing because you get liver disease if you drink too much. And so if AI if I'm going be able to vibe code an mRNA vaccine to cure my liver cancer, I'm gonna be oozing for sure.
Speaker 2:It's the only only rational thing to do.
Speaker 5:Yeah. Well, this is also kind of like
Speaker 1:when Sort
Speaker 6:of a rational one.
Speaker 5:When companies like are saying like, oh, work life balance is super important. Yeah. So then their competitors will, you know
Speaker 2:Yes. Yes.
Speaker 5:Because it's like yeah. People on topic should should tell people to open AI to start drinking because AGI is gonna cure liver disease.
Speaker 2:Yes. Yes. Yes. Yes. This is good.
Speaker 2:This is good.
Speaker 1:Okay. Let's revisit the Jetsons.
Speaker 2:Okay. Revisit the Jetsons. I'm sure you've seen the Jetsons.
Speaker 1:Where's my flying car and three hour work day? So I'm gonna be learning about the Jetsons. Okay. John is gonna be revisiting. I version of the future is way more fun than our reality.
Speaker 1: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. I binged The Jetsons in my sweatpants.
Speaker 1: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 Rosie. 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 treadmills complete with fire hydrants. The upbeat vibe is markedly different from the apocalyptic, at times murderous, sci fi of today. The nineteen sixties were full of optimism about what the twenty first century would bring, and some of it actually has come true.
Speaker 1:While we've still got a few decades before the Jetsons family is meant to arrive, I dug into some of the show's 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. Just Show's creators couldn't fathom mobile devices, but they were spot on about video calling.
Speaker 2:Now now, to be clear, we we are still working on with one of our business associates like a video call that doesn't stop halfway through
Speaker 4:Yeah.
Speaker 2:And just cancel. But
Speaker 1:So the Jetsons didn't predict the free tier
Speaker 2:of Zoom? Yeah. The free tier of Zoom was not considered in in the in the Jetsons where you're you're clearly gonna go long on the meeting and Zoom's just like, goodbye.
Speaker 1:It's over.
Speaker 2:It's over. It kicks over now with no notice.
Speaker 1:Is that a new thing? I feel like it used to do a countdown.
Speaker 2:I think it did a countdown too, but now
Speaker 1:it's just Now they're just like, we wanna embarrass the host.
Speaker 2:The plus tier is gonna
Speaker 1:blow So in Jetsons, they can even create deep fakes to stand in for them on camera.
Speaker 2:Woah. That's cool. I didn't realize that.
Speaker 1:FaceTime's kinda got on there. Oh, this is You know the other thing they haven't cracked with FaceTime is like if you FaceTime a group of people Yeah. Like most of the people won't even get notification and don't know that it's happening. So we haven't cracked the the notification part of
Speaker 3:Yeah.
Speaker 1:Yeah. Call.
Speaker 2:This is good. Read read this next slide. When George secretly attended a robot football game, his simulacrum told Jane he had to work late. He's like using a deep fake to lie to his wife. Great.
Speaker 2:This is so sixties.
Speaker 1:Do not do this.
Speaker 2:Do not do this. This is dystopian. Flying cars. It's not all optimism over over
Speaker 1:Flying cars and travel tubes, sort of. 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 Jetsons' home, Jensen sends Jane sends him back with a push of a button.
Speaker 1:And they also use personal vehicles, the ones that typically fly. George arrow commutes and a glass dome saucer that folds into a briefcase.
Speaker 2:That's cool. We're 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 people some people get to use those, but they are not nearly cheap enough. But we gotta get them we gotta get them way down.
Speaker 1: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 eVTOL.
Speaker 2:Look at this. Pivotal Blackfly is a solo piloted aircraft free to operate in unrestricted spares airspace. An upgraded version called the Helix can be used for a 190 k. You don't even need a pilot's license. That's like, pretty close.
Speaker 2:But, I mean, I would still say, like, we are not near the flying car because they're just not. Like, it it there are way less flying car rides than Waymo's, for example. So we're just not right there. Push button jobs. Almost.
Speaker 2:George works as 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 for to support a family of four even though majority of his day is spent with his feet up on his desk.
Speaker 1:Okay. They basically nailed this.
Speaker 2:There's some
Speaker 1:people out there that are basically button pushers right now. Vibe coding. Yeah. TBD on on the revenue True. But
Speaker 2:Working three hours a day, three days a week. You know, we we we work three hours a day, five days a week. And maybe the future's three just Monday, Wednesday, Friday streams, we can live the the Jetsons future.
Speaker 1:And we work I don't know. That would be That be devastating for us.
Speaker 2:Yeah. Until then, we'll be
Speaker 1:working space colonization. Nope.
Speaker 2: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.
Speaker 2:We're not quite there. Musk had preached populating Mars, but now his focus has turned closer to the moon. Meanwhile, an interplanetary space race between US, China, Russia, and UAE, and the European Space Agency is well underway. Robot maids, not exactly, but we're getting much closer there.
Speaker 1:It's funny that that Brett Adcock's coming on today. Yeah. And he's working on the flying car.
Speaker 2:Yeah. He's working on the robot maid.
Speaker 1:Working on the robot maid.
Speaker 2:He doesn't have a space thing yet.
Speaker 1:He's now working his new lab is basically like a butt, a button pusher.
Speaker 2: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.
Speaker 2:While the show may not have anticipated touchscreens, it nailed a key side effect of constant use of gadgets, repetitive 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.
Speaker 2:Thirty six 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. 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 thirty six years?
Speaker 2: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?
Speaker 5:How do you define space colonization?
Speaker 2:Living on the earth above the Karman Line for like, that's your primary residence, like more than half the year.
Speaker 5:How many people do it? Like, just you can do that? Like anyone can do that?
Speaker 2:Yes. Anyone with like an like like if you can 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 you can choose to live in space. So I would assume like population of millions.
Speaker 5:I I it probably depends on like the industry that like is chiefly, you know, benefited from people living there.
Speaker 2:Button pushing?
Speaker 5:I could say. Okay.
Speaker 1:Big news. Sean Frank is in the chat. He says, I'm Hey. Guys, h e a r, which he's trying to signal that he's listening. I am here.
Speaker 1:To you, Tyler.
Speaker 2:To you, John. Well, thank you.
Speaker 1:Great to see you.
Speaker 2:Let's let's read him some ads since he's here. Let's tell him about Restream. One livestream, 30 plus destinations. If you want a multi stream, Sean, go to restream.com. And you know what we got to tell him about.
Speaker 2:We gotta tell them about app love and profitable advertising made easy with axon.ai. Sean, get access to over 1,000,000,000 daily active users and grow your business today.
Speaker 1:Andrew Reed says the faster technology progresses, the harder it gets to print something in the office. Have experienced this. It's very true.
Speaker 2:The brothers.
Speaker 1:Aaron from Box says Reed's Law. I know you may have wanted a better law, but I don't make the rules.
Speaker 2:Yeah. It's it's very 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 printers, just like the one you get and it does what it want.
Speaker 2:It just does everything flawlessly, and it's at that, like, you know, five nines of reliability. We've had 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.
Speaker 2: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. What I hate most about technology in hotel rooms, Jordi, I want your take on tech in in hotel rooms. I want to know about your experience when you walk into a hotel room.
Speaker 2: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 you find just about anywhere like TV, WiFi 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 WiFi repeater where when he travels.
Speaker 2:So when he goes to a hotel he logs into yeah. This is amazing. He logs in to the the the hotel WiFi, I believe, or the or the or the plane WiFi through that device and then all of his devices connect to that automatically. And he bring he'll bring like a fire stick so he'll be able to watch TV shows and his laptop and his phone. Everything automatically syncs to that device and it like reroutes it.
Speaker 2:But 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 as I would expect.
Speaker 1:I usually forget to bring a charger.
Speaker 2:Hotels are missing out on a fundamental truth. In a world where so much of our work, travel 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 model.
Speaker 2: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 on to this reality by offering some sort of streaming option, but they approach this in so many different ways.
Speaker 2:You never know what you're going to find or what tech you'll need to make it work. Needy WiFi is another one. Most hotels I've visited recently seem to have figured out that charging extra for WiFi makes about as much sense as charging extra for a better toilet. Everyone needs to get online, so you might as well bill it into the price of the hotel room. So now that we've taken that greatly forward, why are we still forcing people to log in to 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?
Speaker 2:It isn't usual it isn't unusual for me to log in to hotel WiFi 20 or 30 times a day. I think you're doing something wrong.
Speaker 1:Honestly honestly Just I don't
Speaker 2:Five g.
Speaker 1:I don't This doesn't resonate
Speaker 2:No? With me at all. You're fine.
Speaker 1:The only thing I want from a hotel
Speaker 2:Yeah.
Speaker 1:Is to be able to order room service without calling someone.
Speaker 2:Okay.
Speaker 1:That's like the only thing. Yeah. And and hotels miss on that
Speaker 2:Yeah.
Speaker 1:For the most part. Like if you have a little iPad or you could even order on the TV That would be amazing.
Speaker 2:Did you?
Speaker 1:And you get like a Domino's pizza tracker type That's all I want. Yeah. I I feel like they kinda deliver on everything else Yeah. And I don't watch.
Speaker 2:I 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 that interacted with the ordering service so so that he didn't have to talk to them. And it basically, like, read the entire menu and then, like, created, a voice agent to call or, like, or, like, reverse engineered the API of the ordering menu. And he was able to order by command line just, like, while checking into hotel. Time to build a CLI. It's truly the future.
Speaker 2:I love it. But it is. It is. And you know who else is vibe coding these days? Gary Tan.
Speaker 2:Ben Hylak has a joke here. He says, The year is 2027. Gary Tan has just crossed 1,000,000,000 lines of code per day. Water to three year old Californian towns were diverted in order to cool his locally ran LLMs. Riots erupt and protesters demand answers to one single question.
Speaker 2:What is he building?
Speaker 1:We got to have GT
Speaker 2:on. I can't wait.
Speaker 1:Let's get Gary on.
Speaker 2:We gotta get Gary on. We gotta know what what Gary is building. Are people are joking about this because what was the latest stat? It was something like
Speaker 5:eighty Seventy eight thousand
Speaker 2:Seventy eight thousand lines code.
Speaker 5:Per day on per day. Think on Gary's list. On Gary's list. Which is his his blog. It's a blog.
Speaker 2:And he's built blogs before. Like, he's he's built these he's built these sites. But, you know, I guess, like, with all the testing suites and packages and mobile optimization, I don't know. I can't imagine the the the the volume of code that will be generated when he creates a mobile app for it. It's gonna be it's gonna be, you know, trillions of tokens going into that.
Speaker 2:Let me Anyway, tell you about Labelbox. RL environments, voice, robotics, evals, and expert human data. Labelbox is the data factory behind the world's leading AI teams.
Speaker 1:Sam says, I remember when this was announced but didn't fully appreciate the size. 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 US Department of Energy's largest AI supercomputer for scientific discovery. The Solstice system will feature record breaking 100,000 black wells and support the DOE's mission of developing AI capabilities to drive techno technological leadership across US security, science, and energy applications.
Speaker 1:Another system, Equinox, will include 10,000 NVIDIA Blackwell GPUs 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 exaflops of AI performance.
Speaker 2: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.
Speaker 5:So I I I was interested in this. I I looked this is gonna be like somewhere around like a quarter of a gigawatt. Okay. Equivalent Perfect. Of a 100 thousand black
Speaker 2:bills. Half a half a Metacampus, I think. I think Metacampus is working on five hundred five hundred megs.
Speaker 5:Yeah. I I think I mean, Hyperion, like, the end state is like I think a gigawatt or more.
Speaker 2:More. More. But that's like the first big jump for them. But the default Metacampus, I believe, is around 500 megs.
Speaker 1:Cisco, to acquire Restaurant Depot.
Speaker 2:Not our Cisco.
Speaker 1:Not Not even close. Acquire Restaurant Depot for $29,100,000,000.
Speaker 2:Before we take you through this, let me tell you about the real Cisco. Critical infrastructure for the AI era. Unlock seamless real time experiences and new value with Cisco. There's only one Cisco in our hearts.
Speaker 1:This one's important.
Speaker 2:This is Cisco with an s.
Speaker 1:I dislike Cisco.
Speaker 2:Why?
Speaker 1:Because every time I I find it a very frequent experience where there's a new restaurant coming to my area. Mhmm. I'm excited about it. They invest million, $2,000,000 in building out this incredible space. Looks And then you eat there for the first time and you can tell that they're just sourcing like Cisco.
Speaker 1:Interesting. I'm not gonna say Yeah. Slop. But Okay. The food quality is not great.
Speaker 1: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 food? Doesn't make any sense to me, but I believe the founder of Restaurant Depot Look. I think I saw it somewhere.
Speaker 2:In the Jetsons, they had dinner generating machines. Dinner generating machines. Where how do you think that's gonna happen?
Speaker 5:Travis Kalanick built this. Yeah. Isn't this Cloud Kitchens?
Speaker 2:Yeah. No. No. The dinner generating machine or Cisco? Because Cisco's Dinner generating machine.
Speaker 2:Yeah. Yeah. That's basically it. But it's all part of a pipeline.
Speaker 1:The founder Yes. Of Restaurant Depot What happened? Who just sold for 29,000,000,000. Okay. Was born in 1932.
Speaker 1:Woah. '94.
Speaker 2:You still
Speaker 1:kicking? I think we should hit the gong for him.
Speaker 2:Let's do it.
Speaker 1:Congratulations on that. Great to finally get a solid exit. It's never too late. If you're 93
Speaker 2:can buy that sports car.
Speaker 1:Finally. Finally.
Speaker 2:Yeah. That that is a true overnight success. Congratulations to him. Excited. I mean, you know, we gotta get food to people.
Speaker 2:People are hungry. There's some good things, you know. Maybe Yeah. Maybe they they stock some raw milk and you're on board then, you know. Before play the next video, let me tell you every day is a fight between the advertisers and the viral videos.
Speaker 2:Let me tell you about Railway. Railway is the all in one intelligent cloud provider. Use your favorite agent to deploy web app servers, databases, while Railway automatically takes care of scaling, monitoring, and security. And then we can play this Okay.
Speaker 1:We're heading over to Japan.
Speaker 2:Yes. This is the key sport that we will all be picking up in 2026. This is going be the hottest thing in San Francisco with the hills and the office chair.
Speaker 1:And so
Speaker 2:there is an chair
Speaker 1:racing league. So look at the look at the speed and the technicalities It's incredible. Corner. It's incredible. This athlete says the corner once controlled me, now I control it.
Speaker 2:I think I got I think I got something.
Speaker 1:You you have quite a bit of leverage.
Speaker 4:Yeah. With the legs?
Speaker 1:With the legs.
Speaker 2:I think I got a build for office chitters.
Speaker 1:The six year transformation is crazy. I mean, guy is incredibly quick.
Speaker 2:He lost me.
Speaker 1:And we need to bring this to The US.
Speaker 2:He lost me. Let's go over here.
Speaker 1:We need to bring this to The US. Chair racer, Miura. Going around the devil's hairpin.
Speaker 2:The devil's hairpin.
Speaker 1:Alright. So Tyler, what is happening on X in Japan?
Speaker 6:Yes. Can you
Speaker 1:break it down? Break it down. Yeah.
Speaker 5:I mean, I I don't know all the internals, it seems like like Nikita's been posting about this, but I I think, you know, they basically introduced like all of like Japan Twitter onto like normal Twitter.
Speaker 2:Oh, because of translation?
Speaker 5: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. All about America, about how much they love barbecue, that you know, they respect the cowboy aesthetics and all these things.
Speaker 1:Cool. I didn't know we how need to figure and why over 50% or something like that of Japan is is like a weekly active user of x, which is just
Speaker 2:Well, yeah.
Speaker 1:Mean So let's pull up
Speaker 2:this This is a little bit of an update, like, narrative violation because that's a narrative violation. I know. That's a narrative violation. Because when Grok went viral, everyone was like, oh, it's good at anime. It's big in Japan.
Speaker 2:And it was at the top of the Japanese app store. But it appears that Japan's just using Twitter broadly. Elon. They just like the Yeah. They just like the app.
Speaker 2:And that's like where they have conversations, is very cool. That's a narrative violation. Let's go to
Speaker 1:Let's pull up this first post.
Speaker 2:This is hilarious.
Speaker 1:It
Speaker 2:is The person's a pizza?
Speaker 1:And this is the translation from When I saw this quote pizza topped with a pizza in America, I thought, there's no way we could beat these guys. Is this is an amazing I've never I've never seen
Speaker 2:There's so many layers. There's actually one, two, three, four layers of pizza. I'm gonna make this. I feel like this would be a smash hit in my heart.
Speaker 1:This is this is is quite
Speaker 2:This is elite. Quite smart. Performance. Peak performance. We gotta this maybe is for lunch today.
Speaker 2:Let's get some pizza.
Speaker 1: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.
Speaker 2:It'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 they're they're having a big barbecue in in Sasebo's dining establishment.
Speaker 1:Someone someone else someone else
Speaker 2:What happened?
Speaker 1:Somebody's just I guess an American is posting their, their grocery haul and someone says the amount is way too much, as expected.
Speaker 2:As expected. We have a brand over here in America. We do things this particular way. Hello, Japan. We love your fascination with our barbecue.
Speaker 2: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 doctor something or other, doctor Nicholas.
Speaker 2:The amount is way too much, as expected. What else is going on in Japan? Take me through.
Speaker 1:Someone else says, in Sasebo's dining establishment, it's common to spot US 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.
Speaker 2:That's incredible. I love it. Let me tell you about Lambda. Lambda is the super intelligence cloud, building AI supercomputers for training and inference that scale from one GPU to hundreds of thousands. And let me also tell you about Eleven Labs, build intelligent real time conversational agents, reimagine human technology interaction with eleven labs.
Speaker 2:In fundraising news, physical intelligence is in talks to raise $1,000,000,000 at 11,000,000,000 Okay. Valuation.
Speaker 1:I need to know. Why is Jeff Bezos here besides the fact that he looks fantastic in the tux?
Speaker 2:He might put in some money. Oh, no. No. The company has previously raised more than 1,000,000,000 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.
Speaker 2:You could have put Lightspeed as a Danny Ryan
Speaker 1:Reynolds. Carol or Lockheed.
Speaker 2:Yeah. Or
Speaker 1:But Bezos any of the actual team, but
Speaker 2:seems to get the the viral attention. So but very good news. We actually interviewed both the cofounders of Physical Intelligence, both Lockheed and Carol, this last year. And they don't do a lot of media, so it's an interesting little segment. We we we spent maybe twenty minutes with them.
Speaker 2:And you should go back and listen to it because it 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. But, like, if you just look at the traction, look at the open source contributions, the data, the fundraising. Clearly, is happening there.
Speaker 2:And so I think it's worth digging in and paying attention to if you're
Speaker 1:Last night, Bill Ackman hit the timeline.
Speaker 2:Woah. I didn't
Speaker 1:Some of the highest quality businesses in the world are trading at extremely cheap prices. Ignore the mainstream media. One of the most one-sided wars in history that will end well for The US and the world, and we have a potential for a large piece dividend. One of the best times in a long time to Ignore buy the bears. And he says, and Fannie Mae and Freddie are stupidly cheap, asymmetry at its best.
Speaker 1:They could be a 10 x and it could happen soon. And of course, Jira tickets comes in and says x.com, the market manipulation app that Fannie Mae and Freddie Mac are up 4237% as of this morning. I think 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. JT says, don't ruin the tweet.
Speaker 2: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.
Speaker 7:Is he does he even have
Speaker 2:a position? Isn't that disclosed in his filings? I'm not exactly sure. I would take every recommendation from a Twitter poster, 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 I did dig in to this somebody asked Grock, like, hey.
Speaker 2:Break it down. Like, what is actually going on here with Fannie and Freddie? They generate 25,000,000,000 in stable annual net income from guaranteed fees, low credit losses outside crises. They're still in 2,008 conservatorship, and the stock trades for a total market cap of 10,000,000,000. So there's a world where you're sort of buying maybe I I don't know exactly how aggregated this is, but maybe it's like 25,000,000,000 of cash flow some point for 10,000,000,000.
Speaker 2: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 a bunch of other
Speaker 1:political issues. He does own. Fannie Mae and Freddie Mac are in his Pershing Square portfolio. Well But again, not not illegal to share your opinion.
Speaker 2:Yeah. Well, there are some not everything is up. Mike Zuccardi shares the current MAG seven plus drawdowns from fifty two week highs. NVIDIA is down 21%. Google is down 22%.
Speaker 2:Microsoft down 36%. Apple is down 14%. Amazon, 23%. Meta, 34%. Tesla, 28%.
Speaker 2:And many 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 IT, HR, and finance support, giving employees instant access instant resolution for access requests and password resets. And let me also tell you about Vanta, automate compliance and security, because Vanta is the leading AI trust management platform. And without further ado, let's bring take him in to the TBPN UltraDome.
Speaker 2:Take him. How are you doing? Thank you so much
Speaker 3:guys again.
Speaker 2:For taking the time to go to chat with us.
Speaker 1:And congratulations on Yeah. The launch. Launch of your business.
Speaker 3:Yes. Thank you. I mean, it's been really gratifying. Yeah. That first day, you never know who's gonna show up.
Speaker 2:Totally.
Speaker 3:I was like, maybe 15 subscribers or 20 subscribers, but like hundreds of people showed up. Amazing. Tons of billionaires and tech founders. It's insanely gratifying.
Speaker 2:Yeah. It's great. Incredible. So is it is it over for NVIDIA? They're down 21%.
Speaker 2:We just read since the fifty two week high. Is it doom and gloom? Is it over? No. I
Speaker 3:mean, I think I was on last December and Yeah. The stock is semis and chips have gone up and now they're back down to where they were in December. Yeah. The chip sector's flat flat on the year. NVIDIA's down 10%.
Speaker 3:And it reminds me a lot of about a year ago.
Speaker 2:Yeah.
Speaker 3:Do you guys remember Everyone's freaking out about deep seq,
Speaker 1:the Yeah.
Speaker 3:Super efficient models. We're gonna destroy AI compute. There'll be a huge compute glut, and then everyone freaked out about Trump's tariff wars, the preparation day. And this year seems very similar to that. Almost it's like Groundhog Day.
Speaker 3:Mhmm. We have fears over AI CapEx. People think that it might be the peak. And then we have the Iraq war. And one of these things is Iran.
Speaker 3:Oil up here. Iran.
Speaker 1:Yeah. Easy to get them mixed up. Yeah. They happen so much.
Speaker 3:Feels like the same same thing over. But
Speaker 1:Sorry to distract. We wanted to throw we wanted to We wanna show respect. Yeah. Wanted to show respect to
Speaker 2:a real podcaster. I
Speaker 3:mean, it's very similar to Iraq, that's that's
Speaker 2:my These are great.
Speaker 3:But in a $100 oil, this stuff is unsustainable and it'll probably Okay.
Speaker 2:So so so because when I when I I like the deep sea analogy and I feel like the market half digested the agentic coding narrative and the Suttrini article, whether you thought it went too far or was too hypothetical, like clearly the markets did react and a lot of names sold off. But in a world where you believe that narrative, you would think that NVIDIA would be going up. But you're saying that there are other factors at play that are sort of tamping down the excitement in the market broadly?
Speaker 3:There there's no doubt. Just like tariffs a year ago, had 30% drawdown
Speaker 2:Yep.
Speaker 3:When their business was actually flying
Speaker 8:Yeah.
Speaker 3:The actual fund out of the business. I think the same thing is happening here with the Iran war.
Speaker 1:Mhmm.
Speaker 3:Things will eventually subside. Oil can't be $100 for forever, and Trump will probably backpedal in the next few weeks Mhmm. Ahead of the Trump
Speaker 2:So let's 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 people are actually buying. Maybe that means Grace CPU standalone sales or the the development with the Grok partnership.
Speaker 2:What's sticking out just on the actual AI product side to you that you're most excited about?
Speaker 3:Well, inference demand is exploding driven by the AI agents Sure. At the coding assistance.
Speaker 5:Yeah.
Speaker 3:What I met with Ian Buck. I met with dozens of engineers at Meta, Google, NVIDIA, and all of them are seeing crazy inference demand and AI compute shortages. So across the board, people are in crazy clamoring need for AI.
Speaker 2:And we're and we're I mean, we're 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 and Twitter and talking about how they're hitting rate limits and they're they're subsidized and they have multiple plans and they actually shift around from one model provider to another just to make sure that they're getting the tokens they need to build whatever they're building.
Speaker 3:And you see the tweets like people are like
Speaker 2:Yeah.
Speaker 3:Building bots Yeah. To pick up any kind of b 200 GPU that can that
Speaker 1:Oh, yeah.
Speaker 3:That they're waiting for weeks and months or
Speaker 1:They're like sneaker bots but for Neo Clouds. That's crazy.
Speaker 3:Exactly.
Speaker 2:I can't believe that.
Speaker 3:And the the the great thing is Jensen, you know, he's very prescient. He probably saw this demand months away. He locked up all the the supply agreements for memory, CoOS, you know, connectors ahead of time. He saw this inference demand. And to take advantage of this coding system boom, it's it's almost like a gold rush.
Speaker 3:You see OpenAI pivoting toward it. Anthropic, obviously, is thriving on it. Billions of ARR every every few weeks. Yeah. Jetsons acquired Grok.
Speaker 3:Acquired the assets of Grok and the people of Grok. And this the combination of integrating Grok's technology together with Vera Rubin lets NVIDIA serve this tremendous wave of compute demand economically. And Ian Buck talked about it. Jensen talked about it. So NVIDIA is positioned perfectly to thrive on this coding agent wave
Speaker 2:Yeah.
Speaker 3:That we're seeing right now.
Speaker 2:On on on the Gurak deal, Jensen did a fantastic interview with Ben Thompson and was sort of asked the same question two years in a row about ASICs, the threat of ASICs, the idea that the GPU, the general, like like, general architectures can truly satisfy 100% of demand. It feels like there's a shift in NVIDIA's strategy there. Do you see that? It it it feels like the right move, but do you do you see it as a shift in the philosophy of the company or the strategy? Or 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?
Speaker 3:I think what Jensen does, he sees where the market is shifting and where the economic value is with Mellanox. He did this in 2019. He saw
Speaker 2:2018? World Bye.
Speaker 3:Shifting to it's a networking chip, but he saw the world shifting to, like, these 10,000, a 100,000 GPU clusters and Mellanox need for that. In the same manner, he saw AI agents and and the inference behind that taking off. And he said, oh, this Grok thing will work perfectly for everyone. It it doesn't replace everything. And just as talk about 25% of the inference demand would be Grok would work on that.
Speaker 3:Yeah. But them working together where 75% of the inference is Verruban, 25% is a Grok low latency stuff, that's it's like the perfect combination to to to take advantage of
Speaker 2:this. And
Speaker 3:the other thing is, like, we're just in this great lift off of AI innovation. Yeah. We've talked about Anthropic Mythos, the blog Yeah. Blog post that leaked out. So we're gonna have this, you know, step up function.
Speaker 3:They they told Fortune there's gonna be a huge step up change. Yeah. OpenAI is coming out with their model soon. And then when I went to GCC, the the biggest takeaway I had was this session between Jeff Dean and Bill Dalley, both chief scientists at Google and NVIDIA. And it's it's online.
Speaker 3:I highly recommend, people watch it. And he talked about Jeff Dean talked about, the context to have context window innovations where they could focus on the 10,000 documents that that work well with your your request and queries. 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, and that's going to be a huge innovation, in the coming months or years. And so you have and then Jeff, can you talk about synthetic data for audio and video?
Speaker 3:There 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 keep getting better and better.
Speaker 2:Yeah. How are you processing the idea that NVIDIA will be investing in an open source frontier lab capability That feels like potentially competitive with some customers. NVIDIA has, 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 Meta was doing it.
Speaker 2:I want more of it. I loved when OpenAI, open source GPTOSS. It feels really, really important, really great, but it does feel like a strategic shift. How did you process that announcement?
Speaker 3:It's it's not acute. I think it's like 25,000,000,000 over the next few years, which doesn't really compete with what OpenAI Anthropi doing.
Speaker 2:Yeah. Guess These you're
Speaker 3:these smaller models are gonna be helpful for people running these smaller use cases.
Speaker 2:Sure.
Speaker 3:So GPUs, as long as they're utilized even locally or in the cloud Yeah. NVIDIA benefits.
Speaker 2:Yeah.
Speaker 3:And saw the the the top people at Quen Yeah. Left and we don't know where they went left to. Quen is an amazing model. It's kind of like what deep deep is Yeah. What people thought deep deep should be.
Speaker 3:Quen works well locally. Yep. Quen kind of subsides because all the
Speaker 1:what's your theory on where they all went? Another Chinese lab or
Speaker 3:I asked I asked all engineers when I was at GTC. No one really knew. But people are 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 GPU to run open source or not.
Speaker 3:They just want, you know, more AI adoption across
Speaker 2:the And NVIDIA has more probably more levers to pull if it if it turns into a negotiation with China. Like, we're we're 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, look the other way on this particular deal. Like let this one flow through. We'll trade this.
Speaker 2:Meta not really doing any business there 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. It can be part of a larger discussion, which makes a lot of sense.
Speaker 3:And one thing that kind of went under the radar, Jensen literally said at GTC, they got license approvals on both The US and China side. So we're going to see billions of dollars of h 200 orders.
Speaker 2:Okay. So yeah. I mean, it seems like 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.
Speaker 2:It's already massive revenues, just an incredible growth. 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 10 x increase in compute demand, we could be really constrained on the leading edge fab side. So how do you think NVIDIA is going to process that?
Speaker 3:Well, NVIDIA is in the driver's seat because Jensen goes there five, six times a year and he's best friends at TSMC and speaks at their employee day. So they're gonna get higher they are getting a higher allocation to wafers and Sure. And all that stuff. So NVIDIA will benefit. But I agree with you that industry wide
Speaker 2:Yeah.
Speaker 3:Like, Google is dying to get more TPU wafer Sure.
Speaker 7:Test. Sure.
Speaker 3:All the all the hyperscalers that have ASICs are trying to get more wafer capacity. So there is gonna be a AI compute shortage shortage in the years to come, just like you said.
Speaker 2:Yeah.
Speaker 3:And NVIDIA 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.
Speaker 2:Yeah. I mean, maybe there's some offtake in ASICs that can potentially be fabbed somewhere else at some point. I I don't I 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 rearchitecture, 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 I'm not exactly sure.
Speaker 3:But It's Samsung and Intel are their
Speaker 2:only Samsung and Intel. Yeah.
Speaker 3:Fabs that could possibly do it. Yeah. That's the bookcase on Intel.
Speaker 2:Yes. Yeah. Is that is that at some point
Speaker 3:labs
Speaker 2:and and Google, like, like, we're across TPU, extra GPU capacity, NVIDIA, the new R, like there's just so many buyers of lab capacity of fab 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 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 that will justify the investment for us and for Intel.
Speaker 2: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?
Speaker 3:I mean, I suspect, like, Apple and Nvidia are considering either Intel or Samsung for their lower end stuff.
Speaker 2:Yeah.
Speaker 3:Whether it be like a mid range iPhone or Nvidia side, definitely, their consumer gaming GPUs still. They may go back to Samsung and maybe even Intel.
Speaker 2:Yeah. I have one more, but go 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 frenemies with NVIDIA now. They're competing in many ways to break the x86 monopoly because they both are selling ARM CPUs, but then they're also competing.
Speaker 2:And so I'm wondering how you think that plays out, what that means for NVIDIA and just the rest of the semiconductor supply chain.
Speaker 3:I think ARM is their CPU opportunity is a longer term, you know, for even they said 2030, 2031.
Speaker 2:Yeah.
Speaker 3:It's a longer term opportunity. I don't really expect the major hyperscalers like Amazon to switch to arms, you know, product offering. They have their own. And same with same with NVIDIA, they have their own arm CPU that they're they're gonna incorporate and sell. So it's not that big of a I I don't think Amazon or NVIDIA are really worried that ARM is gonna take any big share.
Speaker 3:It's probably gonna 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 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.
Speaker 2:Yeah.
Speaker 3:Just over the last few months, we have Dell, AMD, Intel CFO talked about they're talking about three to five year locked locked in supply contracts from hyperscalers. So this this is a major trend, that's gonna go over the next few years. And the reason why is AI agents need more CPUs. On the ARM CEO talked about four times more CPU quarter cores versus last year's kind of AI infrastructure model. So we're gonna see this massive demand for CPUs that people aren't really understanding yet because AI agents, the whole thing requires orchestration, tool calls Yep.
Speaker 3:Database queries, web searches, and that's all handled by the Yeah.
Speaker 1:Give me your bowl and bear case for TeraFab.
Speaker 3:TerraFab, I'm not that optimistic. Okay. I mean, it's so hard to
Speaker 2:Give me
Speaker 1:the give me do your absolute best to give me the bull case.
Speaker 3:Because TSMC is so short that, you know, Elon needs to find. Even then, like, how how are they gonna buy, like, semi cap equipment from ESML and AMAT? Like, there there's just no capacity there, so I'm I'm not optimistic on that. And this is this is stuff that takes decades. Chip fabs, it's almost like cooking, and it's not like something you could just follow follow a manual.
Speaker 3:It's like it's almost like cooking where it takes a lot of, trial and error accumulated over decades, TSMC and even Intel. So it's not something you could just jump right in and do. Yeah.
Speaker 2:It it somewhat goes back to the yeah. It somewhat goes back to the x AI 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 Ilya Setskiver age of research versus the Elon Musk age of engineering? Where are we in semiconductor production? It feels very engineering, like like an engineering process.
Speaker 2:But what we've seen from ASML is that it and 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
Speaker 3:of research in this space, and it's a lot of trial and error and Yeah. Almost like cooking a recipe. Recipe.
Speaker 2:And and and it also feels like in at least with x AI, if all the researchers are in San Francisco, you can sort of just like walk across to the coffee shop, poach someone. But if if the best if the best, you know, semiconductor engineers or technicians are in Taiwan and they see it as a national urgency to bring stability to the country both economically and geopolitically, then you have a very different calculation. It's like, oh, yeah, could make five times as much if I left my home country to like be abandoned. That's a very different calculation. Everything that I've heard about the culture at TSMC is that the folks who work there are extremely dedicated beyond the economics.
Speaker 2:They are true missionaries, not necessarily mercenaries. And so it does feel like it's even harder to do like a talent raid in in the leading edge fab world than even the AI world, which is extremely competitive and there are still tons of missionaries. But
Speaker 1:I guess another question I have is would you expect would you expect x AI 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 compelling aspects of of the TerraFab pitch was him just saying, we need all of this compute. Mhmm. We need to do this because we it we're gonna be so chip constrained. We're gonna be so supply constrained.
Speaker 1:But there was no explanation of
Speaker 2:Where the demand is coming from.
Speaker 1:Where the demand was gonna come from. Is it gonna come from
Speaker 2:Training Tesla models, Optimus Or or Grok or
Speaker 1:Yeah. It was it was it was just very unclear.
Speaker 2:It was
Speaker 1:a lot. But there's even the question right now is should XAI be kind of renting GPUs? I don't know. Don't know.
Speaker 2:Renting out GPUs. Renting out because Yes. Because Because the biggest win has been Colossus Yeah. Colossus two, which was built very fast.
Speaker 3:I I I think Elon's pitch with the SpaceX IPO, and we'll see it in the coming months, is the AI compute. It's gonna be so there's gonna be so much demand over the next five, ten years that you're gonna have to use the SpaceX satellites that have GPUs in them to Yeah. To serve that today.
Speaker 2:And 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 Starlinks in space, and then you let other companies do whatever they want with those GPUs.
Speaker 3:Think what Elon did with Starlink. I mean, that's a telecom infrastructure play, and this will be a AI compute Yeah.
Speaker 2:Yeah. Yeah. There's fits that model. There's a world there.
Speaker 3:I'm not gonna bet against Elon. It might
Speaker 2:just take long.
Speaker 1:Yeah. Yeah. What about what's going on with helium? What what are you tracking there? There's chatter about helium shortages potentially.
Speaker 3:Jensen has talked about this. This this is a risk. But there is probably like six months, six to nine months of inventory in the channel. Bernstein has talked about it's not a risk in short term. So so if this thing if this Iran stuff lasts
Speaker 2:Yeah.
Speaker 3:In, you know, two, three, four, five months, then becomes a problem.
Speaker 7:Okay.
Speaker 3:But if it, you know, gets solved or moves opens up with the toll or whatever final negotiation they come up with over the next few weeks, I don't think it's gonna be a problem.
Speaker 2:Yeah. I do think that, like like, most of these materials, there are extra deposits. They're just not economical to mine. I don't think that all the helium exists in The Middle East that
Speaker 3:would very to the rare earth thing.
Speaker 2:Yeah.
Speaker 3:Just like you said.
Speaker 2:Yeah. Where where you know, supply constrained scenario, it becomes more economical to mine American helium.
Speaker 3:Let let me put this way. If helium becomes the issue, we're gonna have bigger problems on our hands.
Speaker 2:Okay.
Speaker 3:I mean, there's gonna be world starvation.
Speaker 2:Let's hope not. Let's hope not.
Speaker 3:Bad. That that'll be the least of our problems if human becomes the problem.
Speaker 2:Take me through, depreciation gate. How did you process that, and where do we stand now with the fear that GPUs will depreciate precipitously and h one hundreds will be worthless in six to twelve months.
Speaker 3:It's it's totally not a problem right now. Like, CoreWeave has talked about these things are lasting five to six years Mhmm. And they're getting, like, almost 95% of the pricing. Mhmm. So it could be potentially be a problem if the whole if this is a bubble, I don't think it's a bubble.
Speaker 3:Yeah. But if this is a bubble two, three years from now and there's a compute glut, then
Speaker 2:Yeah.
Speaker 3:The stocks don't go down because there's a compute glut. But as of now, it's the opposite. Like Mhmm. You know, all the GPU rental prices even for stuff that's six years old is still being sold out and it the AI compute demand outpacing supply is so large that this is not an issue right now.
Speaker 1:Do you have any theories on on where the next step change in token demand could come from? Because right now we're seeing it in code gen and there's a lot of optimism around, these types of workflows being applied to other forms of work. But we were talking about this on Friday. Like, 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 to code gen because no company needs to just constantly be, you know, be generating models at the rate that, let's say, Gary Tan generates code. And and so I'm I'm like kind of been trying to wrap my head around where where could these incremental use cases I
Speaker 3:actually think code gen is still just early innings.
Speaker 1:Yeah. And I I don't disagree with
Speaker 3:Ten, twenty agents and they're kind of over 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 use them for every single vertical, customer service, research, simulating chip design where they they can verify drug discovery, where they verify drug molecules can do. So so we're just getting started at this stuff. So you can you're going to see vertical AI agents on every single category.
Speaker 3:And I think Logan's coming on. He wrote this great post on X Yeah. That he says this the AI agent wave is is going to kind of attack this $6,000,000,000,000 knowledge economy. Right? It's not just about programming
Speaker 1:coming for us. Yes.
Speaker 9:I don't think say, I'm actually
Speaker 1:They're they're attacking the key context economy and the TBPN economy.
Speaker 3:No. I I think it's it's it's like a calculator, a spreadsheet, you know, thirty, forty, fifty years ago, we had, like, you know, 50 accountants do doing the spreadsheet manually. Right? And now after a spreadsheet came, it didn't get rid of all of knowledge work. It just enabled people to to think at a higher level and get more done.
Speaker 3:And Yeah. I'm very optimistic about that.
Speaker 2:I mean, one one one way that you 10 x token demand on around a financial model without 10x ing 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 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 loc like, I want to know the price of Squarespace. Let me go to every single website that's powered by Squarespace and estimate the revenue that they're bringing in and their willingness to pay for their hosting service, something like that.
Speaker 2:And all of a sudden, like, it's just one spreadsheet at it's just one number at the end of the day, but it's like a thousand times more work went into it.
Speaker 3:Let me give you this great example. Every year, I do this the same store sales for these fast casual companies Sure. Like Chipotle, Cabba, 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.
Speaker 2:Yeah.
Speaker 3:It would take me like an hour or two. Yeah. I would try to use a chatbot, they would get it wrong. Sure. I did it like a few weeks ago and all the chatbots got perfect.
Speaker 3:So it just saved me two, three hours of tedious manual labor. That that's only going to get better and better. Yeah.
Speaker 2:Yeah. It's only going to take you one like like, this year is the year that you you do it with multiple chatbots and you fact check it yourself, and then forever, it's going to be just one prompt. And
Speaker 3:And they get and they got it right. Like, a year ago, wouldn't get it right. But now in one, two minutes, I put give me the same store sales for these six restaurants. Yeah. I put in Gemini.
Speaker 3:I put in ChatGee PT, and just to to to make sure they're right, and they're right. So Yeah. That that all all the tedious labor, all the manual labor, all the data entry that, you know, all of us are used to, that 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 gonna be taken care of by these AI agents.
Speaker 2:I agree completely. I agree completely.
Speaker 1:We got a lot of a lot more sound effects since the last time you joined. Last last question for me. What's your outlook on on meta? It feels like the the broader market right now has zero faith in Meta to actually put Yeah. All their AI investments to use.
Speaker 3:I have I have this history with Meta is that, you know, every time it starts falling apart, say it looks cheap. And then it goes down another 30%. But nothing has changed. Like, no one's gonna replace that as digital ad position. I mean, like, I would even say in the AI world, they're even better positioned because Google might lose digital ads share to Sure.
Speaker 3:Chop chatbots, their search position going in the future. So like no one's gonna replace Instagram. No one's gonna replace Facebook. Billions of people are still going to use those social media apps.
Speaker 5:And Yeah.
Speaker 3:You know, it's every six six months to twelve months, everyone goes through this bare meta cycle, but their pure competitive position really hasn't changed. And you saw what's happened to Sora. Right? Like, you know, everyone's all excited about Sora and Yeah. And that that got
Speaker 2:Totally.
Speaker 3:The shot.
Speaker 2:Yeah. And and there's just this world where even even if, like, the AI spending is like a side quest, it's like really they just pulled forward, like, three or four years of CapEx and they will use that for their other products. It's probably even less like wasteful than Reality Labs spend, which might take even longer to realize the cash flows from. Like they can recoup, okay, we built this massive data center. We did this training run.
Speaker 2: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 platform and tools and Reels recommendations and a million other things just in years 2028, 2029. And, yeah, we're a little bit ahead of or
Speaker 3:ad engine monetization.
Speaker 2:100%. Yeah. The gem model.
Speaker 3:Reality Labs Yep. He made a waste of 70 to $80,000,000,000. He may waste a 100 billions of dollars on on these frontier AI models.
Speaker 2:If the business is good.
Speaker 3:Ad engine, core business, that money making engine has it's not gonna be affected by this.
Speaker 2:Yeah. Well, thank you so much for taking the time to come hang out. Always a great time, Tay. Yeah. Go subscribe to Key Context on Substack.
Speaker 2:Follow Tay Kim on social media. First adopter.
Speaker 1:Join the many beaners that we're the first adopters.
Speaker 2:Yes. Yes. You'll be in good company. And thank you so much. We'll talk to you soon.
Speaker 2:Have a great week.
Speaker 1:Great to
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Speaker 1:So Chamath.
Speaker 2:Yes. Holly What do say?
Speaker 1:He says, the biggest threat to Instagram's moat is an incredible image model.
Speaker 2:Okay.
Speaker 1:Ziff Zephyr says meta bottom.
Speaker 2:An incredible image model, it should be
Speaker 1:totally different. That's a that's a like you're basically saying, okay, if Sora was if the content on Sora was a 100 times better Yeah. Would that be a real threat to Instagram? I don't And I still am not I still am not convinced.
Speaker 2:I feel like a lot of people have their network there. They wanna share with their friends, and 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.
Speaker 1:If they could make an AI agent of you that instantly reacts to every video I send you Killer feature. Just goes.
Speaker 2:Killer feature. Killer feature. Jump in there. Between our DMs, there's a lot of stuff that you gotta still react to. Well, without further ado, we have Logan Bartlett from Redpoint, his managing partner there.
Speaker 2:Welcome to the show, Logan. How are you doing?
Speaker 6:Good, gentlemen. How are you?
Speaker 1:We are fantastic. It's great to see you.
Speaker 2:Like this camera setup. This looks fantastic.
Speaker 6:You know, once upon a time Yeah. I was, you know, I was a semi professional podcaster before you guys stole all the thunder in the industry and forced us into oblivion.
Speaker 2:Three cartoon avatars was Back to Marty. Go decks. Just put the investments in the bag, bro.
Speaker 6:I know. I know. That's exactly right. Yeah. The McDonald's bag of cash I have.
Speaker 6:That's what I'm doing these days.
Speaker 2:But you're also writing market analysis which I always look forward to.
Speaker 1:Yeah. This has been consistently some of like the the best content in the entire 100%. PC industrial complex and I've enjoyed it for many years.
Speaker 2:It was extremely valuable during the interest rate crisis as well. And 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. So thank you for everything you do.
Speaker 2:Take us through the biggest findings. Take us through the process that led to this particular research report.
Speaker 6:Yeah. It turns out there's a little bit of nuance. That 75 slides give you more than a 140 or 280 characters to kind of tease out in I some so it started it started probably in January. I have this process every year where I have a a panic attack that we have an annual meeting coming up. And I got tricked in 2020 when I joined the firm.
Speaker 6:They were like, we're going to give you this really illustrious honor that 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 did I know no one else wanted to do it.
Speaker 6:And so every every January, I get a mild anxiety attack that I have this coming up. And over the past couple 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 'twenty three, I think, was SVB.
Speaker 6:'twenty four, maybe, I got, like, a little bit of a respite. 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.
Speaker 6: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 in the world around you. So if you're doing defense, you really just focus on defense. If you're doing software, you just focus on that. If you're doing whatever, healthcare, you're focusing on that. Public market investors, I find are a little bit more zoomed out and they typically have an opportunity to play across different scale of businesses, different sectors, different types of companies, all that stuff.
Speaker 6: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 software companies are now trading at 4.1 times NTM in the public markets, but also getting priced at two, three, 400 times ARR in the private markets. And so sort of setting out to bridge that gap was kind of the goal.
Speaker 2:Is it a is it a gap or is it a gulf?
Speaker 6:A gulf. I would say it's an optimism disconnect maybe.
Speaker 2:Good phrase. I like that.
Speaker 6: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 the risk of going to zero and optimizing your process around like, hey, we really can't have a 0x in the portfolio versus private market investors, you're optimizing on like, what are the chances you're missing out on a thirty, fifty, 100x? And if you take those two lens, it ends up with a very different place like optimism versus cynicism, upside versus downside, you know, all the questions you ask.
Speaker 2:Yeah. So let's let's
Speaker 1:You'll start with 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 they made the announcement that workflows are now called agents in in the and I was like they were like, yeah, this workflow stuff seems like people are not that excited about it now. We're we're switching gears. These are now agents.
Speaker 1:And if we
Speaker 6:just Do you know that Breaking Bad meme that like he says we had a good thing you stupid son of a bitch? Like that was that was like all SaaS investors over the course of the last, 100 you know percent. Being like you MFers, you had to go mess up this like really good thing we had going on with this AI pixie dust.
Speaker 2:With a non profit that didn't even raise a seed round until they were multi billions. It's like we couldn't even get in early.
Speaker 6:We had a good time.
Speaker 2:We had a good time. So let's start with the the public markets. How much of how much of this is driven by the Citrini article? How much of this is driven by actual data points where we're seeing I was I was just pulling, like, the top 50 SaaS companies, sort of pure play SaaS companies and trying to ask answer the question, like, is revenue decelerating yet? Are we seeing a kink in the graph, like some change in the data?
Speaker 2:And I didn't go nearly as deep as you go. But but how much of this is just like narrative and anxiety about a changing 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 the valuation.
Speaker 6: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 market CEOs are to blame for some of the softness in the cultures like how Yeah.
Speaker 6:Bloated some of these businesses 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 they could your best people could just walk out the door if their friends are all getting fired. And they could walk out the door and go work at Anthropic or Ligura or 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.
Speaker 6:And so I think let's put that in a bucket, though. That's like sort of a side. The other thing, the far more interesting conversation to have is like, are financials deteriorating? And the answer is really no right 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' value was tied up in the period beyond the DCF, right?
Speaker 6:The terminal value of the long term duration of it. 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 Guidewire and Samsara 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 bankroll in Nvidia 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.
Speaker 6:And so I think it's it's that. And people are asking like, what is the long term terminal value and saying, I'll wait on the sidelines until other people really show the proof points that they're gonna be able to survive this AI thing.
Speaker 2: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 for these software companies? So I was looking at a company that 3,000,000,000 market cap, 100,000,000 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.
Speaker 2:But also, also I don't see these customers churning. I just see them doing AI stuff on top of this particular company because I they're more infrastructure layer, more data storage, that type of thing. And so I was like, I think you can count on a 100,000,000 of EBITDA and probably cash flow for ten years, twenty years, but do you want to be paying 30 times that? Is that enough? And I don't know if that's
Speaker 6:a rational
Speaker 1:framework. Nobody knows nobody knows anything.
Speaker 7:You have to apply a big discount. The the the
Speaker 1:slide that one of the slides I loved was was the slide on newspaper earnings. Oh, Take 22. You say newspaper
Speaker 6:It isn't interesting. It's funny. I 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.
Speaker 6: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 actual financials themselves. So John, I guess to your question on it, like I use revenue as a proxy Yeah. And maybe it's like too too flip of a nomenclature. We really should be talking about, like, free cash flow with deductions for stock based comp or whatever. But, like, all these things are growing at different rates, and that's sort of in the historical lingua franca that that I kind of used.
Speaker 6:But you're right.
Speaker 2:Be clear, makes it impossible to comp to the private markets because no one's generating any any That's 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 sort of understand my just my rate of return, which is going 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.
Speaker 6:Yeah. And and this might be a little simple for for some of your listeners and maybe helpful for others. But like at the end of the day, a business is valued at the the current value of all future free cash flows. Yeah. And so discounted back to today's dollars.
Speaker 6:Yeah. And so when when the reason software businesses have been so good is the the you you have annuity streams going out into the future, and you're able to, with some level of precision, figure out what to discount back the value as in the future. And so that was a great thing, particularly when we had retention rates at 95%, 9697%, net retention rates at 120%, 131140%, 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. And I think this equity made a bunch of money saying, like, actually, you know, this is this is better than a debt instrument.
Speaker 6:This actually sits on top of the the debt in terms of your vendors are gonna 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. Are people really going to churn off of Salesforce or Workday Yep. Or ServiceNow or whatever it is? Like, maybe, but I I worry less about that.
Speaker 6:I worry more about the value abstraction that is captured on top of it. 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 than all of software combined by, like, 50% or something. And so if you're not capturing the AI dollars, then your growth rate is gonna 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 Think times
Speaker 2:about it almost like a real estate investment. It's like, well, what's your cap rate? You know, like Totally. If I'm giving you a $100, am I getting $5 this year, $10 this year? Because there's a lot of other options.
Speaker 2:And then, yeah, the other thing historically with software has been just low interest rates. So, oh, oh, that cash flow is coming in twenty years? Fine. Like, it's basically the same as today with zero interest rates. Yeah.
Speaker 2: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
Speaker 1:Did I'm I'm curious. Any of the public markets investors, 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, etcetera. Was anyone like licking their chops being like, this is the greatest buying opportunity, like actually had some well thought out thesis around how because like Toma Bravo, some of their slides leaked from their LP summit, and 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, four d chess of how this is, like, a huge accelerant to to their to their businesses.
Speaker 1:But
Speaker 6:Yeah. I think some of the public some of the public guys, 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 gonna figure out 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 And so I think that's the you were to paint the optimistic lens about, you know, Thoma 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 were dunking on were it's true fundamentally that like, hey, your incumbent vendors are gonna get shot one, three in getting it right.
Speaker 6: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 culture of building what the historical software company looked like. And and you guys, I think I think you know I was an investor in in Ramp. Yeah. And and and the stuff that they did, like,
Speaker 2:they do. Investors don't get enough credit. Let's keep it up. It is my crossbarrier. In particular.
Speaker 2:He's he's I know. He never takes victory laps. That's the thing.
Speaker 1:We'll take
Speaker 6:it forward.
Speaker 2:We'll take it forward.
Speaker 6:It's I am I'm unknown. I was a silent investor for a long time. And so it's I'm glad to come out of the closet as a ramp investor here for you guys. Know, one of the things They threw
Speaker 5:you out. Yeah.
Speaker 2:Of the
Speaker 6:things they did culturally for a long time 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.
Speaker 3:Yeah.
Speaker 6:And that was very different than the way that I learned, you know, the companies I invested in twenty fourteen, fifteen, sixteen and how they built products was they had a very tight product roadmap. They communicated with their customers. You know, they they had it over a three, six, twelve month period of time. And they would only really release it when it was fully ready out of initially an alpha, then a beta, then they would take a GA with a handful of customers and take a. The ramp guys sort of put that on its 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.
Speaker 6: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 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 building product.
Speaker 6:And that's one example, and we have a slide in there of all the different examples. But it's sort of been flipped on its head. And so I actually don't worry from a is it possible standpoint for the big public companies to do this. I think it's totally possible. And and I think some of them will figure it out.
Speaker 6:But the vast majority are gonna have to totally change their culture that they built over the last ten, fifteen, twenty years. And that's really painful. And and I think that's where they're gonna end up falling down more than anything else.
Speaker 2:Yeah. This is fascinating. I'm like sort of an early ish adopter I think. And we 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. But then I wanted to know how many how about 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.
Speaker 2:And so the question of like you have a system of record, there's going to be some new feature. Where 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 like this is in tale as old as time.
Speaker 6:Yeah. It's abstracting the value on top of it which is Yep.
Speaker 4:It's tough.
Speaker 6:Interesting. I mean, I guess if you guys think about like my direct visiting of websites has definitely gone down because I interface with Claude or And Hirsch at TBP in a meaningful I think that same thing is going to play out within the enterprise as And it's not just going to be retrieval of information, it's going 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 ramp side, if it was by bill pay or credit card. And ultimately, once you five 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.
Speaker 1:Like, you
Speaker 2:In fact, I wanted it to I wanted it to unify credit card and like checks and like bank transactions as well. 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.
Speaker 2:Yes. No one just, like, gets granted monopoly on the new capabilities that emerge on top of their platform.
Speaker 1:So Sorry, in the deck, you talk about, you know, you have some bub talk talking about it. Are we in a bubble? And and with 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. Mhmm.
Speaker 1:People are willing to give real dollars for tokens and that's just going up and up and up. And 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 on the number of companies coming out every single day Yep. That seem to all be doing kind of variations on like the, you know, the AI CMO. Right?
Speaker 1:And I'm like, maybe maybe that ends up being a big category.
Speaker 2:Like a sort of niche vertical SaaS player that's AI will be like at a 50 cap Yeah. For a seed.
Speaker 1:Yeah. I guess my my 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 Mhmm. In the kind of venture world right now.
Speaker 6:Yeah. I mean, it sort of goes to like where value is gonna accrue. 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 in airports or whatever, b to b sales and all that stuff. Like, were second derivative things that were actually far more impactful.
Speaker 6:And you're right, like it's possible. And this is what I I I've told our LPs that have asked is like, think we're operating in a world in which our mortality rate of companies we invest in is going 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. And so we'll end up with, hopefully, things that could be hundreds of billions of dollars, which used to be not in the realm of possibility.
Speaker 6: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 in all of 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 we're we're back to, like, investing in teams and investing in the wedge 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.
Speaker 6: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'd 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 that's going to be the one to
Speaker 1:The Yeah. It's been interesting to to look at these businesses ramping revenue so quickly and still and 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? Mhmm. You know? Yeah.
Speaker 1:And for It's me interesting that's
Speaker 2:the one people.
Speaker 6:Sorry. Go ahead.
Speaker 1:Yeah. For me, the 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 I remember with OpenSea, you know, and the NFT boom, that was you I I remember the way that they ramped revenue. Even even the thing that made, you know, I think a lot of otherwise, you know, great funds, like pile money into it, what at 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, you know, opportunity. There's still like a business here and maybe you can just own the category and but then revenue ended up dropping like 99% or something like And I think that still So that still stays in the back of my mind.
Speaker 1:That that was more of a demand issue versus like new kind of competition from from an adjacent player. But but still Yeah.
Speaker 2:There any previous booms that you do like as comparison points? If not, .com? Do you like railroads?
Speaker 1:Electricity. Yeah. Electricity. Yeah.
Speaker 2:What do you like?
Speaker 6:That's a good question. I haven't actually I haven't actually thought of the right analog for Yeah. What time we're I mean, people, the industrial revolution is the one that people come back to the most, and that wasn't on our GDP calculation chart. Yeah. But I do I think there's elements of the shifting balance of worker dynamic and like where people are actually going to
Speaker 2:Totally the leverage.
Speaker 6:Deploy themselves in that going forward. 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 technical I mean, it's both a revolution and a technological shift in some ways. And so I think like the car or the aeroplane 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 but it's good question.
Speaker 6:I'll think more about it.
Speaker 2: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 yeah.
Speaker 2:I I gotta I've heard this direct quote. I gotta check that AI thing out.
Speaker 6:Oh, yeah.
Speaker 2:I gotta check that out. And When did Jordi say
Speaker 6:that to you? Was that recent? I think you know, it is interesting. I mean, that's where you're seeing a lot of this like FDE Yeah. Palantir era where bridging the last mile is really really hard.
Speaker 6:Yeah. 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, don't know, 350 300,000,000 Americans or something and you ask them like name an AI company. I would guess I'm making this up, but like 25% wouldn't actually be able to name an AI company Yeah.
Speaker 6:And like 70% would say, oh, that's that chat GPT thing or something.
Speaker 1:I talked with a guy I talked with a guy and said like what what AI are you using any AI products? And he's like nope. And then I was like what about ChatGPT? And he's like I use that every day. I love it.
Speaker 2:But he just doesn't think about it. It's just a website. Like we've been to websites before,
Speaker 6:you know. And I think that's an interesting thing. You know, Brett Taylor talks about this from Sierra where there's so many capabilities that you're raising the waterline of and that they're needing to build in house themselves knowing ultimately the model providers are gonna 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.
Speaker 2:Interesting.
Speaker 6:And I think I think that's kind of true on the go to market or like education side as well. Yeah. Where like 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, like you're having to bridge the capability to competency like bridge that gap to the individual person at the end of the day. And so I do think this diffusion, when everyone talks about 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 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'd make it out to be when we're just living in our techno utopia.
Speaker 1:That's a good point. If you can call ex a techno techno nightmare. Except in Japan and Japan is seemingly I I did want to ask about buy versus build economics. You talked about how you could just buy.
Speaker 6:That's the one that people have been asking all about by the way today. Yeah. Yeah. People like that one.
Speaker 1:So Logan makes a point. Can buy Slack for a thousand employees for like a quarter million a year or you could build it in house. You estimated around 2,000,000 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
Speaker 6:It's it's a really funny thing where I just think it's sort of the eighty twenty rule in some ways that people assume building a software product is like the getting to the proof of concept or like the credible MVP in some ways.
Speaker 1:Look, can send messages. You can create a group. Yeah. And then it's like, oh,
Speaker 6:I do you vibe coded this thing and it does all of what Slack needs to do. But then there's
Speaker 1:Not even mention the network effect of Slack of you build the perfect clone and then it's like, okay, do any other companies use it? No? Okay. We still need Slack.
Speaker 6:Yeah. And so so like let's say I I think I mean, people want to argue about the specific math on all this, but like let's say that you're willing to do all the integrations and the SSO and the search and the file sharing and the, you know, whatever. The admin controls and compliance and all that stuff. Do that. Yeah.
Speaker 6:The emojis, the gif embeds, Like, those let's say you do all that. What's that whatever that cost, like, is the opportunity cost that you spent all this time doing that rather than focusing on whatever it is your core business is. And so actually, did the math here and it's 2,000,000 versus 2 and 20 k or whatever. Let's say it's the same or let's say it's cheaper. Is saving $40, let's say it's $1.80 versus $2.20.
Speaker 1:And it actually has to be significantly But
Speaker 2:but also, I I mean, I talked to a friend who runs a company and just about AI stuff. And 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? He's like less than 1%. And so it's like, yes, like you could take something that costs a thousand dollars 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 a completely different business.
Speaker 2:And so
Speaker 6:That that was the point someone was arguing me about is like most companies actually, you know, aren't growing like like software or tech companies are. And so these costs are really material to them. And I'm like, you know what's material to them is like decreasing their workforce turnover from like 70% a to like 60% a year and not having to pay incremental recruiter or staffer fees to get Like, people The difference of the Slack budget and saving 40 ks, 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 So I was trying to think of what a good bet would be with someone to try to come up with It's a very hard thing to figure out of what the right framework of thinking about this is because I love just codifying bets with people and being like, you know, okay, let's wager some money on what this is and I couldn't come up with a good one.
Speaker 6:So if you or if anyone listening can come up with a good bet on this, I would love to place whatever, a significant money on
Speaker 1: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 we need to talk about like our roadmap for our internal Slack. We need to kind of bat some ideas around about different trade offs that we're making.
Speaker 2: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
Speaker 6:there's a historical analogy by the way of this that I I didn't include in the deck because I I really like Drew Houston from Dropbox. But like they built their own data centers and like I don't know. Like Yeah. If that was a good cost decision from them, but from a focused decision, should they have just used AWS Yeah. And, you know, or GCP or I one of the other know the answer to that, and I didn't want to put him on blast and actually get into the debate because I like him quite a bit.
Speaker 6:Like, I don't know if that's the right decision for them. They were even the furthest you know, they're like a tech company that was their business, able to decrease costs. Totally. And who knows what the opportunity cost of incremental products or mind share or whatever it was going and doing that.
Speaker 2:Yeah. No. That makes a ton of sense.
Speaker 1:Last question. Did did the current AI suite make making your annual report significantly easier or was it still Handcrafted. Handcrafted.
Speaker 6:It's an artisanal craft to this, but I will say it is interesting doing this deck every year. It does serve as a snapshot of like what the model capabilities are and like where, how much progress it's been made. And so I think if I go back like two years ago, that version of it, I could wordsmith 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, 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.
Speaker 6:And that is such a step function change versus where it was twelve months ago. And so it is helpful every year to revisit, come back and 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 fifteen weeks ago. But when I went through the process this year, 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 were 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.
Speaker 2:Totally. Is is that alpha for up and coming venture capitalists? What 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
Speaker 1:I could would just say have a nontraditional background.
Speaker 2:Yeah.
Speaker 1:So maybe grow up Well, that's the thing in Palo Alto area. Yeah. Go Stanford. Stanford.
Speaker 6:GSBPN. So so if you guys have a minute, I can 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? Well, we hire people out of investment banks because it's an interest in finance and technology.
Speaker 6:Okay. That's great. Two is they have the model training of like what we need, you know, the the cap tables and and, you know, projections and all that stuff. Three is there's like a high pain tolerance and like willingness to grind and do extra thing. And then four is like it's a referential network.
Speaker 6: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? And Mhmm. It gives us a qualified pool of people to 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 you you went to a high school, got good grades, got into a good college, you know, did interviews, got a good job.
Speaker 6:Then at your investment banking job, you're staffed with like 90% of your day is prefilled by someone else. And so it's like, okay, well, if I work hard and I stay late and I do this pitch book, 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 this staffer and now you're telling me just go figure out what's a good company? Like where do I even start in that?
Speaker 6: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 and the remedial tasks. And we sort of took that as the basics and then we had to try to figure out if there was agency there. Now increasingly, the models are getting so good that agency might be the only thing that matters. And so are you able to find differentiated
Speaker 1:We're actually working on an internal model for agency at TBPN. Yeah. We did a huge unlock. We cracked taste. Now it's agency.
Speaker 6:So And so that's the thing that we now are trying Like, to figure do you find pockets of people who still want to do 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 are 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.
Speaker 2:So what I'm hearing is that you're pulling up the ladder behind you.
Speaker 6:That's right. That's right. That any door I always say when people ask like, hey, how did you get to where you are in your career? My answer is always like, well, is the specific question what I would do if I was in your seat? Because I can tell you the doors I walk through, but those doors aren't just shut.
Speaker 6:They're like shut, They're cemented They've like been fortified, you know. They're not doing what I did. I lucked through this path. Fuck.
Speaker 2:Thank you for joining us. Great. Always a great time hanging out.
Speaker 1:We'll Just talk to just with with all the AI progress, try to ship one of these a week.
Speaker 6:You got it. I was No. We
Speaker 2: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 exchanging your middleman and spend with the Phantom card, and then head over to public.cominvesting for those who take it seriously, stocks, options, bonds, crypto, treasuries and more with great customer service.
Speaker 2:And without further ado, we have the founder and designer of Granola, Sam Stephenson. Welcome to this show. Sam, how are you doing?
Speaker 7:What's going on? I'm good. I'm good. How are you doing?
Speaker 2: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.
Speaker 7:So we have raised a $125,000,000 series c from Congratulations.
Speaker 1:I didn't hear it over the sound of the gong. You said Index Ventures?
Speaker 7:Index Ventures. Index Ventures. And and with KP participating as well.
Speaker 2:Fantastic. Very lucky. What unlocked the round? Is it just continued progress, new features, a little bit of everything? Talk us through the progress over the last year.
Speaker 7:Yeah. I think it's been I mean, all the above. Like, we've been talking to these guys for a for a while. They've been fans of the product. I think as all of our investors have, they've all, like, used the product a bunch Yeah.
Speaker 7:Before we've got to talking about investing. And then, yeah, like like growth has been good and continuing and like I think it's a combination of that. And then like the I feel like the the environment is like waking up like to the power of of of having all of the context of what's happening in your meetings in in a company, you know? Yeah. Like I think like everybody adopting MCP is like making it apparent that you can, 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.
Speaker 7:And I think we're just well positioned as like that context gatherer that a company can take advantage of.
Speaker 1:Yeah. Yeah. So my my 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 and and so and so explain like why you guys have had kind of just open open not not not to say open but there's certainly competitors but like why have you guys been able to market run then.
Speaker 2:Run away? ImageGen. Yeah.
Speaker 7:Yeah. I mean, yeah. I'm sure they I'm sure they are working on it. Like, OpenAI had a stab at it last year. They had like a launched like a longer running record mode thing, which I think was aimed at this.
Speaker 7:But like a I think I think it's a few things. Like, I think we we're basically like people use us for meetings, right, which is like it's a big term for a for a startup like us, but it's also like only a slice of people's life, like and and and if you're designing like a super open ended general purpose chatbot like JaiGPT, I 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 and anything less is is like not good enough. Mhmm. I think that's probably part of it. The other the other thing is like I mean, we found building Granola that that like you can build a Granola clone like super easily, you know, right?
Speaker 7:In in like a weekend, could build a thing that transcribes your meetings and gets you a summary. Yeah. And like all the work is in understanding like the all of the like social nuance of like who are these people in the meeting, why are they meeting, what's this meeting about 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 a bunch of work and yeah, that that's you know, we use the latest and greatest models, so like you've still gotta go and do that work on top of that at least today.
Speaker 1:Yeah. Yeah. It makes total sense. What what kind of progress are you guys make? Like, what is the what's the most kind of like sci fi element of of the pitch for this last round?
Speaker 1: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 like, how far are you kind of like taking out the how far out are you kind of looking?
Speaker 7:I mean, I can see it. I can see that like yeah. I can see that someone being true. Like, I do think like I mean, we do it we do it internally in the company. You know, we'll we'll we'll meet and talk about a thing and then and then go ask Grunala to write a brief that we either get their hands to a coding agent or or we use it as the material to write a job description or a blog post or whatever.
Speaker 7:The conversations are like incredibly good input for a lot of the work that you end up needing to do at a company.
Speaker 8:Yeah.
Speaker 7:I think the like the more kind of like the most near term but sci fi things that that we we see is like if you want like a pulse on what's happening with like any project or any group of people in the company. Going and like looking and asking Granolah what's what's happening with 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 a I don't know a Notion doc or a Google doc that someone had to sit down and write like you know, without making any effort, you have kind of an up to date picture of what's happening in the company. And that's, I think that's just gonna be useful to a lot of people in in so many ways.
Speaker 2:What is 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 like land, I imagine the next step is expand. What does that look like Yeah. For Granolah?
Speaker 7:All word-of-mouth pretty much at the moment, like for most companies. Like, we we focus so much on just making it like a good product for the individual when we started that, yeah, like, 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 because they love it so much and and we just go on from there. 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 Grunella and kinda unlock the power of of sharing all that context as the transcripts together. But for the most part, it's still just word-of-mouth.
Speaker 7:People people love it and they share share that with each other.
Speaker 2:Talk about the end of year wrapped campaign. I've heard fantastic reviews for it.
Speaker 7:That was such a that was such a delight to to like explain
Speaker 2:it for those who who did not receive one or followed the story and then tell me about
Speaker 7:so we did a like, a spin on, you know, Spotify wrapped as as many companies do, which for us was granola crunched. The basic thesis was like, you know, granola if you if you've used granola some some of our users have used granola for like thousands of meetings over the last year. And and if you look in the inside those meetings and across over a year, you can you can tell a lot about a person and what's going on and what's important in their lives. So granola crunch was basically like every user could could go hit a button and generate a like Spotify rap style report about them about their year. It was things like like who's your partner in crime?
Speaker 7:What's your favorite catchphrase? What's like what are what are some of the smartest things you said? What are some of the dumbest things you said?
Speaker 2:That, you
Speaker 7:know, that kind of thing. And it was like, you know, mostly fun. There's there's some there's some things that could hit pretty hard like a like a I remember mine was like, I felt kind of uneasy sharing it with other people because it felt
Speaker 2:of people. They've been like, it was scarily accurate and I didn't want to share it with the rest of my team. Because I really understand You said
Speaker 1:nothing from my end. Thanks.
Speaker 2:700 times. Yeah. That's great.
Speaker 1:Okay. So we we have this buddy who's who's, you know, built a massive company in a super regulated industry and, like, had been through Oh. Ultimately a had a huge exit but has been Yeah. 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.
Speaker 1: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 Every live kind of transcript of Yeah. Every meeting that you've had at a company. What what are the I'm sure you guys are aware of of, you know, some of these more like sensitive use cases. Like, what kind of fix like, what what are you doing at the product level for people that don't want every conversation sell saunas.
Speaker 2:So if you wanna 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.
Speaker 1:Maybe. Go to the bathhouse. Maybe check check for any product roles.
Speaker 2:You got a wire on you? You take off
Speaker 1:Anyway, Sam. Tell.
Speaker 7:Yeah. Yeah. Yeah. I mean, I think like this is like a really tricky path for us to walk and like it's 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 I think we have to juggle like I think tools like this are kind of that they they will be somewhat inevitable in a in a work context.
Speaker 7:Think I think like talking about the personal, you know, like always on recording type things is totally different, but in a work context, there's just so much value in having like, you know, 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 how do we kind of make that okay for for people in in the meantime. And I think like some things we've observed are like for companies that use granola, they very like they basically just get comfortable with the idea that like we're gonna make it a thing that like we use granola internally and and that's the default like that you 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 you don't wanna use it. Yeah.
Speaker 7:But companies get comfortable with that very easily, we find. Then then like the the external question is like a question of following the laws in your state and and you know, like Granolah, we make that clear to you, but it's ultimately it's a tool and and you kind of it's up to you to follow the rules on it.
Speaker 1:But I meant more like even on like data data retention. Right? So so Right. Like a like if a company there 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.
Speaker 1:Now, the bull case for this is that whoever's, you know, suing the company and like wants that discovery actually has more like, they're they're more able to make a a a an effective case. Yeah. But but but like, yeah, I was asking
Speaker 2:for companies that I'm planning to sue?
Speaker 7:We we had this from companies in all all directions. Like Yeah. Some companies are like real like this is an opportunity for them to have things on record and so
Speaker 1:they Yeah.
Speaker 7:Yeah. But plenty go the other way, right? Where they they want everything like off the record and deleted immediately. Yeah. We've ended up building a bunch of retention controls so you can do this either way like some companies will set transcripts to self destruct after twenty four hours.
Speaker 7:Mhmm. So that like, you know, there there's no more record of those and you just get left with the notes. Sure. And yeah, I think I'm a I'm a big fan of that. Like I feel like we there's it's not in our interest to have like a like a real like on the record record recordings of everything that's happened.
Speaker 7:Yeah.
Speaker 2:Yeah. Makes sense.
Speaker 7:Like a healthy level of abstraction is like good for everybody there, I think.
Speaker 2:Last question. Can you tell me about the brand? Because this could have been called like Panopticon or it could have been black background, steel, silver, you know. It it could have been very different wise, but it's granola, it's crunchy, there's a, you know, this this like green color that you picked, like it's clearly intentional. What are you what are you thinking with the brand?
Speaker 7:Yeah. We basically like, I think since the beginning when we first started studying how people take notes, 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 notetakers out there but people hated them. People nobody wanted to use it and no one felt comfortable kind of like writing their raw messy thoughts into them. Yeah.
Speaker 7:And so we really just wanted Granolah always to feel personal and like it's yours and that the more you use it, the more it feels like your space. Mhmm. And all the all the branding is like downstream of that. Like the name, the the colors, the kind of messy like organic feeling textures and stuff like
Speaker 2:Yeah.
Speaker 7:It's all meant to communicate that this is like your your thing. This is not this is not your company's thing, this is your thing.
Speaker 2:Love it. Well, thank you so much for coming on during a big day and breaking it back Very for exciting progress.
Speaker 1:Fantastic progress.
Speaker 2:Talk to you soon. Thanks a lot. A good rest your
Speaker 1:good hanging, Sam.
Speaker 2:We'll talk to you soon. Bye. Let me tell you about vibe.co. We're d to c brands, b to b 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, unified platform for payroll benefits and HR built to evolve with modern small and medium sized businesses.
Speaker 2:And without further ado, let's bring it bring in Ben from Polsia.
Speaker 1:What's going on? How are you doing, Ben?
Speaker 8:Hey, guys. How are you?
Speaker 2:Welcome to the show. Introduce yourself. This is the first time on the show, tell us what you do.
Speaker 8:Yeah. My name is Ben. I run a platform called Polsia. Okay. It's an AI that builds and runs companies autonomously.
Speaker 8:Yeah. You give it an idea and it's gonna go about building the product Yeah. Running the marketing, running ads, doing support
Speaker 2:Yeah.
Speaker 8:And all of the things that a founder would do to start a company and grow it.
Speaker 2: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 what have you done that's that 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.
Speaker 8:Of course. I mean, the way to think about it is, you know, I've I've spent like a lot of the past twelve months spending twelve to sixteen hours a day using AI, using Yeah. You know, Cloud Code Yeah. Using Codecs. Yeah.
Speaker 8:And and building my company companies with it. Sure.
Speaker 1:And
Speaker 8:the idea is that, like, the the fundamental models are, like, super powerful, and 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. Yeah. 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?
Speaker 8:So for example, one of our agents on Polsia can run meta ads campaigns.
Speaker 2:Sure.
Speaker 8:But to do that, there's a lot of steps that are needed. Right? It's like creating the creative, you know, using maybe an AI, an AI generation model.
Speaker 2:Yeah. And different labs are good at different things. You know, Nano Banana is great and Codex is And, you know, there's writing models, and there's all sorts of everything. So you're choosing those and rerouting those. How do I think about it in terms of an actual payment flow?
Speaker 2: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. We're going to withdraw a $100. We think we're going to bring back 200. Okay. We did.
Speaker 2:Now I need a thousand.
Speaker 8:Exactly. I mean, if you think about it, like, are essentially like AI humans that can act on the economy. And and today, obviously, if an agent like, if a thousand agents go on Meta to create accounts, like, Meta will say, no. You need to verify your identity and all this stuff. Right?
Speaker 8:And so there's a first layer of infrastructure to build that we've built at Polsia, which is how to make partnership with those platforms to to get to 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 set up ready. Mhmm. And and as you said, like, today, obstructed it quite a bit where, like, know, pay you pay a subscription and you get sort of, like, one task every night of, you know, your agent doing work for you, and then and then you you you can do various types of tasks. But in the future, as you said, you know, if you wanna open a bakery in New York and you have this idea, there's gonna be a lot of orchestration to, like, buy the real estate, to buy to hire staff, manage them, all the fulfillment, and, like, an AI could totally do this. But you probably will have to say, they Polsia will tell you, you gotta deposit a 100 k on an account because we're gonna have to do a deposit.
Speaker 8:We're gonna have to pay the the realtor. We're gonna have to hire staff.
Speaker 2:Yeah.
Speaker 8:And and that's something that, like, what Polsia is trying to do is really give access to all the 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 gonna be a much lower cost than what you what you can do today.
Speaker 1:Yeah. So Pulsi has ramped revenue super quickly. I feel like every time I see you guys, the the the ARR's gone up.
Speaker 5:I have four
Speaker 1:actually what what are give us an example of, like, automated companies that are working on the platform, like individual entrepreneurs that signed up.
Speaker 2:Yeah. What are they building?
Speaker 1:Yeah. What what are they actually building? What are they selling? Yeah.
Speaker 8:So So there's like a, you know, an entrepreneur who's like building like a service to create ads from a from a script, you know, autonomously using different APIs and reselling that to to people and like has a bunch of customers that are paying. You have another person who's building an, like, AI receptionist for for businesses, and so using, like, the agent SDK to, like, figure out how to respond correctly based on context. You also have existing businesses who are using Polsia sort of like as a as an AI team that can build a landing page for them, create leads, sort of like lead lead capture, 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 Yeah.
Speaker 8:That you get and it's, you know, it's pretty affordable. It's like $49 a month to try it for a month. Woah. And so you get a lot of Right. People with a lot of ideas.
Speaker 2:And Yeah. It feels like the low code, no code, like boom all over again, where, like, were low code, no code products at the hyperscalers and GCP and AWS, but there were still platforms that did a little bit more and became, like, low code, some no code, and 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.
Speaker 1:Does the human matter a lot still? Yeah. Like, how much I just go on and and I pretend be like my 10 year old self, am I still am I am I gonna print? Yeah. Or is it am I am I gonna be cooked?
Speaker 1:So
Speaker 8: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. 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 ODF influence that can bring on their their their their audience and sell them services. Yeah.
Speaker 8:But to answer your question about how much the human is needed, I think that you you 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 gonna 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 I explain it is you got you got the 80%, you know, operational work day to day grind that can be fully automated by AI. That's like engineering, that's like support, that's like market research, that's like pricing. And that usually, don't need to hire people for that, and today, with tools like Ponsiere, they can do most of the work.
Speaker 8:However, the a the 20%, which is taste, which is branding, which is like marketing, and, you know, trying to market in certain ways, understanding how to position your product, maybe having an audience to sell to, however small it is, you know, if have a thousand followers that are dedicated to what you do and they love you, you don't need that much more to get, like, ten, twenty, 30 paying customers and start doing income. Mhmm. And today, they're selling merch, and tomorrow, they can sell Yeah. Real services that may be more sophisticated.
Speaker 2:Makes sense.
Speaker 8: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 where you can completely autonomously let the agent run wild, obviously, if you because you don't have to give it feedback. Like, it will every day every night wake up and do work, and and gonna choose ways for you to let it run 10 times a day, right, if you pay if you pay the compute. Right?
Speaker 9:Yeah.
Speaker 8: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, so it feeds back in to what the service is and how to make it better. And I think there's a world where, like, a human with a lot of capital can actually start building a lot of, you know, money printing businesses as the loop gets tighter and the platform gets smarter about what are the best practices. And I think this is where the world is going. And ideally, I wanna give that opportunity to the 99%, the people that, like, think that AI is charge EPT, and that's that's that's pretty much it.
Speaker 8:And if we can give them the tools to to be economic actors in this new era, I think we will hold benefit, and it will be a more a more just sort of, like, society.
Speaker 2:Okay. Last question we have to ask you about the name. You rattled a lot of people out because it spells AI slop backwards. Is that intentional? Is that a joke?
Speaker 2:What's the name?
Speaker 8:I mean, it started as a not as a joke. It was like my lawyer asked me to come up with the the name for the ink when I started the company. Yeah. And I was on my couch and I was like, oh, I could name it like, you know, pulsate. I slept in reverse.
Speaker 8:There you That's a good name.
Speaker 2:Oh, so you intentional.
Speaker 1:So it was intentional.
Speaker 8:It was intentional.
Speaker 1:I thought it was I thought it was by I thought it was
Speaker 2:No. No. Decided
Speaker 8:to use it as the product name. Because, you know, I started the company like in April and I built the product in November. Mhmm. So I do and I was like, that's kind of cool, actually. It's very and I will make people talk.
Speaker 8:So and it did.
Speaker 2:Well, thank you so much for coming on the show and breaking it down for us. Have a great rest of your day.
Speaker 1:Yeah. Good to meet you.
Speaker 2:And we'll talk to you soon. See you. Let me tell you about MongoDB. What's the only thing faster than the AI market? Your business on MongoDB.
Speaker 2:Don't just build AI. Own the data platform that powers it. And let me also tell you about fin.ai, the number one AI agent for customer service. If you want AI to handle your customer support, go to fin.ai.
Speaker 1:I'd to I'd love to sit in on that that pitch meeting. The Yes. We're building an infinite money glitch.
Speaker 2:It it does 9 seem like
Speaker 1:dollars a month.
Speaker 2:I mean, I don't know. Like, there there there's a world there's a lot you know, Teespring was, know, empowering entrepreneurs to sell a lot of t shirts. There's a lot of different things. Depends on what what what you bring to the platform, I suppose. Well, without further ado, we have Brett Adcock in the Rooster Room.
Speaker 2:Let's bring him into the TBPN Ultra. Brett, how are you doing?
Speaker 4:Guys, good to see you again.
Speaker 2:Good to see you again.
Speaker 1:Welcome back.
Speaker 2:Been far too long. But since the last time we talked to you, you launched a new company. So break it down for us.
Speaker 4:Oh, Hark? Yes. Yeah. Let me
Speaker 2:I want to know about that. Yeah. Alright. Well,
Speaker 4: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 Yeah. Doing AI to work on humanoid robots. Yeah. Separately, you know, separately, I've been like watch I'm basically using and watching what's happening in the digital world,
Speaker 6:like Mhmm.
Speaker 4:You know, the the different language models. And to be honest, I think they're just incredibly dumb. Like, I I they they don't remember anything about me. It's not very personal.
Speaker 7:Yeah.
Speaker 4:They can't listen or talk to me really well, can't see the world, can't use computers well. I just I just think this whole experience is just I think it should feel very much like a sci fi movie. Should feel like Jarvis that can, like, really understand you, very personalize, use tools well. So about seven months ago, I started a new AI lab called HARC.
Speaker 1:Mhmm.
Speaker 4:And we want to build really advanced personalized intelligence. In order to get there, we think there are some fundamental gaps remaining in in the models. So we basically have it we basically have a, like, a large focus on trying to, like, basically build new multimodal models. And the second thing is, you know, we're interacting with AI today through, like, 20 year old computers. Mhmm.
Speaker 4:Like, my phone and, like, laptop, these are all, like, decades old. Mhmm. And we feel very strongly that there's a next generation of AI devices that need to be built 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, Abidur, started about four months ago, previously led design for MacBook, MacBook Air, iPhone thirteen, Fifteen, sixteen, seventeen was keynote for iPhone 17 Air about five months ago.
Speaker 4:So Abs is here with a killer team on the hardware side, we're designing next generation interfaces for the models that we're that we're working on here in 2020.
Speaker 1:Is it the interface that you think is the issue, or do you need more compute locally?
Speaker 4:I think there's, like, some big gaps in the model side. I 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. Mhmm.
Speaker 4:We think both need to be fixed. To have, a really killer, like like, you know, like super intelligent personal assistant, 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 not great.
Speaker 4:Mhmm. They don't remember things I've I've told it. They don't have access to my life. They can't access my calendar. They're not very like, they're pretty high latency.
Speaker 4:EQ and naturalness are not great. So we're kind of taking this holistic approach to this problem and saying we got we have to work on the models and we have to, like, fix the interface issue here today.
Speaker 1:What is what is the hiring market right now for all this all this, Alex? Because because you're basically going up against Apple Mark's OpenAI You got Demis. Like, you're going up against you're you've already bit off bit off a lot, obviously, with with Figure, and I'm I we can move over and and get the update there. But I'm I'm just so curious when you're when you're recruiting talent for Hark. I have to imagine any any of the any of the people that that you're hiring, if you wanna hire them, they probably have the opportunity to work at these other companies.
Speaker 1:So what's what's working on that side?
Speaker 4:I mean, think the summary is like all of the other companies are kind of boring. They're all doing the same thing. Mhmm. They're they're like all copying each other. We've like headed a certain direction the last three years.
Speaker 4: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 ex like, these areas are especially important to push the boundaries and get to AGI, this AGI feeling of, like, highly multimodal scenarios. So we're finding, like like like, from a from a hiring perspective, we're being extremely competitive. We've brought on now over 50 people into the team, about two thirds of that from the AI AI side from, like, top frontier labs. I will say it's probably one of the most competitive areas I've I've hired for in general around compensation.
Speaker 4:Yeah. 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 Different. Software and hardware.
Speaker 4:Just like this is it's it's next level competitive. I think we have a very small amount of people in the world that really understand how to build the right infra, pretraining, data mix, like, of this. It's just, like, very tough. So and all the some of these cases are just new. Like, computer using agents that can really reason really well in pixel space, like, is just happening now.
Speaker 4:And so there's not a lot of good precedent for out for how to go out and build these systems.
Speaker 1: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 wanna build with Hark, like, I'm assuming you'll wanna integrate into Figure. If Figure is going to be a robot that can add value to my day to day life, I I you know, where where is the where is the overlap and and and why why build it externally?
Speaker 4:I'm a big fan of 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 in a bodysuit 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. At Hark, we have, like, a different objective.
Speaker 4:We want to launch, like like, next generation consumer electronics, and we want to basically build extremely multimodal models that can almost, like, act like as like a Jarvis type interface to AI. Mhmm. And the the the focus on those tracks are completely different. And with that said, though, I think there's, like, some some opportunity over time to closely collaborate. The voice on the model on the robot today is using the HARC voice API.
Speaker 4:So if you talk to any of our robots here today, it's using the HARC voice model that we designed here internally. So I think there's, like, a a lot of room over time to collaborate the business together. We're both we're we're, like, we're we're taking an entire data center of b two hundreds in April here, and Figure literally has half the building and Hark has the other half the building. Obviously, paying for things separately, but we, like, literally between the two of us have an entire data center of, like, next generation black wells that we're using for training for AI models.
Speaker 2:I want your latest timelines on the ChatGPT moment for robotics, humanoid robotics. We were talking to Sean Maguire about this. He's he he was putting out maybe, like, two to three years
Speaker 1:Three to four.
Speaker 2:Three to four years, from just, you know, seeing them on the streets, seeing them in in restaurants, seeing them in the real world. Maybe not economic impact because that could happen in 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?
Speaker 4:You can come to Figure right now, and you can see robots running complete twenty four seven shifts
Speaker 2:Yeah.
Speaker 4:Fully autonomously with neural nets all the way down the stack.
Speaker 2:That's amazing.
Speaker 4:So, like, I think this will be a big year for us to ship robots commercially to many different customers of ours.
Speaker 2:Yeah.
Speaker 4:And then we're also working on trying to how do we integrate these into the home? Yeah. How do we get robots that go and do, like, laundry and dishes and tidy the house? Like, things that we just, 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 I think we're we're, like, having this moment now.
Speaker 4:I think it's we're in it. We're feeling it as like, I I right now, like, you're we're seeing these robots do long horizon autonomous work at Figure here. And I think over, like, this year and next year, it's gonna be very the whole world's gonna wake up to it. I think we saw a little bit of that at the White House last week with with Figure. It was just like an we saw, like, unprecedented demand.
Speaker 4:Like like, it it was it was kind of crazy because we didn't show any like new capabilities. Yeah. So we're like, internally we're like, okay, we're just going be at the White House. And it was a big it was a big it was a big milestone. Like the first humanoid robot, you know, built in The US at the White House in history.
Speaker 4:So it was like getting, like you know, getting getting the invite from the White House to come there and be able to be the first one to do it was just, like, huge it it was great. Like but, like, you know, there was there was no new capabilities there, but, like, the the whole world is just, like, waking up to the moment now of humanoids. And it was a bit very apparent from last week at all the the incredible reaction we got from, like, basically the entire world that this is we're still early here in the cycle.
Speaker 2:I love it. Well, good luck and thank you for taking the time to come chat with us.
Speaker 1:One quick question. Can humanoids reliably crack open a cold Diet Coke and serve it? Or is it like I imagine the tab is like
Speaker 2:Tab must
Speaker 1:be kind of a challenge.
Speaker 2:That's AGI for me.
Speaker 4:I don't think they should have any problem doing this.
Speaker 2:Okay. We can
Speaker 1:happily That's a demo. That's We'd love to see because honestly John would would buy a humanoid just to just to come over with a cold one, crack it open. He goes through a lot of these so Okay. We could get some utility out of it.
Speaker 4:Alright, John. Bring a six pack over to Figure and we'll let's test them out in person.
Speaker 2:It's a deal. I'll talk to you soon. Awesome.
Speaker 4:Yeah. See you guys.
Speaker 1:Good to see week. Cheers.
Speaker 2:Talk to you soon. Let me tell you about the New York Stock Exchange. Wanna change the world? Raise capital at the New York Stock Exchange. And let me also tell you about CrowdStrike.
Speaker 2:Your business is AI. Their business is securing it. CrowdStrike secures AI and stops breaches. And without further ado, we have Andrei from console. TBPN royalty.
Speaker 2:I'm Andrei.
Speaker 1:How are doing? What's going on?
Speaker 2:Great to see you.
Speaker 1:Great to see you, dude.
Speaker 9:Good to see you guys.
Speaker 2:So much for taking the time to come show up with us.
Speaker 1:You're always you're always with us. Yeah. You're You're always with us.
Speaker 9:Yeah. I was gonna say love the sneakers.
Speaker 1:Special to have you here.
Speaker 2:Anyway, why don't you just give us a general update on the business? Like, walk us through some features, some customers, and then I wanna hear the latest and greatest.
Speaker 9:Cool. Absolutely. Thanks again, guys, for for having me on.
Speaker 2:Of course.
Speaker 9:Yeah. So I think as you guys know
Speaker 1:Yeah.
Speaker 9:Maybe the rest of the audience doesn't. But we are your a console. We build AI agents that automate service management or employee support.
Speaker 2:Yeah.
Speaker 9:We do that directly in, you know, Slack or Teams. And, you know, things like onboarding, offboarding, PTO requests, access management, you know, even telling the facilities team there's no more napkins left in 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 two work. So it's not just the tier one employee support stuff. Now it's an assist it's an agent that helps your IT, HR, legal, finance team automate the more complex tasks that often span, you know, multiple systems.
Speaker 9:So for example, say, you know, there's an Internet outage, you can actually now ask Console to go and investigate across those different systems. So on the back end, we're plugged into your Meraki, your CrowdStrike, your Okta, your Entra, all these different systems, and Console knows how to go and pull data from different those different tools and kind of come back with a report for you. You can also tell a system to go and, like, fix things. Right? So you can say, actually, go and, you know, push this update to this user's laptop or something like that.
Speaker 9:And then you can also have console build out itself now. So with the system, you can tell it, hey. I wanna connect into Coupa or NetSuite to 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.
Speaker 2:Wow. Yeah. I was about to
Speaker 1:ask. That's basically like it's instead of doing a feature request, just request the feature.
Speaker 2:Yeah. Yeah. I was gonna ask like, hey. It feels like years ago, you would 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 by hand.
Speaker 2: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.
Speaker 9:Yeah. So when we started Consular, you know, we were like, hey. We're actually gonna build this framework internally, and then our engineers are gonna use AI agents to, like, build out integrations super fast Yep. Using that framework. And so That's what I
Speaker 8:would expect.
Speaker 9: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 to ourselves, like, can we actually just have console do that you know, just iterate on itself? Yeah. And that's that's where the idea came from, and and that's what it does.
Speaker 9: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'm gonna pull these, you know, I will pull this data. I'm gonna all these actions into these systems and
Speaker 2:Yeah.
Speaker 9:You know, it'll build itself out to do that.
Speaker 2:How are
Speaker 1:people You think that's gonna 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 Yeah. Needs. But I haven't no one no one's come on the show and like pitch that specifically Yeah. As as a company in the application layer basically like, we're gonna give you the autonomy to adapt the product to your Yeah.
Speaker 1:It's crazy new paradigm. Which is just crazy Yeah. Because like every every sat like, I just
Speaker 2:Every customer wants that. Yeah. They want it.
Speaker 1:They're not like They wanna Oh, I wanna wait for Yeah. Support to get back or my account manager to talk to the engineers and Yeah. And
Speaker 9:Yeah. I think I'm sure it'll I'm sure it'll come, you know, come about in in other tools as well. I would say the core unlock for us was actually building out a really robust and, like, kind of framework interface that, you know, we can plug into. Mhmm. I think once you have that and you have you know, the really important piece for us is this, you know, the context graph.
Speaker 9:So we have a context graph under the hood where we're ingesting data from these different systems, and 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? It gives you an answer. You say, and update it.
Speaker 9: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, like, you know, you might have too many lookups, it would get kind of, like, you know, a little lost in the sauce. And so that that context graph is is really important. It's really a core part of what we've built here.
Speaker 2:How are people thinking about?
Speaker 1:You gotta coin this, by the way.
Speaker 2:Yeah. This
Speaker 1:is an entirely you need to you to
Speaker 2:Or deployed something. I don't know. Forge it. Yeah. Something.
Speaker 2:It's
Speaker 9:definitely What should we call it, guys?
Speaker 2:I don't know. Like, agentically deployed engineering or something is is is I
Speaker 1:was saying name it after yourself. Yeah.
Speaker 2:Yeah. Serban method.
Speaker 1:Yeah. Yeah. The Serban. The Serban. Yeah.
Speaker 1:You gotta get you gotta get people posting like Something like that. Figma needs to incorporate the Serban method.
Speaker 2:Yes. Yes. This is it. Yeah. I think we got it.
Speaker 1:We'll we'll work on it.
Speaker 2:Wait. So so talk me through the the experience of of onboarding to console and how people are thinking about this in terms of, like, net new functionality. 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 start up.
Speaker 2:We had, like, 50 employees. We had, like, a an outsourced IT partner 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 how are how are companies actually, like, interfacing with console and, like, integrating?
Speaker 9:Yeah. So I would say most IT and kind of service management teams roughly scale linearly with headcount growth. So you have, like, one IT person for a 100 people or maybe one to one fifty, maybe one to 200 if you don't include Ramp who has a very, you know, insane ratio. But 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.
Speaker 9:So we act as ultimately, like, this force multiplier for for your team. And so, you know, yes, there's there's spend going into console, but you're actually saving on the back end of that as you're you know, we we work with companies like Databricks, you know, Cursor, Figma, Chime.
Speaker 6:Founder. You
Speaker 9: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 this hyper growth phase that they're about to experience, and it's it's entirely because of of console. And so we 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 they're just doing this employee support where they're just answering questions that, you know, answering questions or 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.
Speaker 1:They can What's what's your approach? Do you do you just, are you the only IT person at console? Like, you force yourself to to dog food the product to the extreme or are you what what's the
Speaker 9:We we take a bit of a crazy approach here where everyone has full admin access to console, and everyone's encouraged
Speaker 2:to build
Speaker 1:their own work. That's probably smarter. You want everybody using the product. At
Speaker 9:some point, we probably need to pull it back. Yeah. I think our head of security was complaining last week. He's like, hey. We've got too many salespeople in here.
Speaker 9:I can imagine. But, like, you know, we've got we actually have, like, our I was actually just talking to to our office manager. We're gonna have console just do our dinner orders as we do dinner in the office every day. And, you know, with with assistant, now she can build out her own workflow. She says, hey.
Speaker 9:I wanna, you know, ping me every every week at 4PM. Ask, give me the options. I'll select it, and just, like, go and order it into I think she's using, like, e c cater. So not an integration we would have built out if if, you know, on our own, but I think with the assistant, it can do that. And so, you know, our head of security, actually, he was just we he was presenting a use case to us the other week.
Speaker 9:He rolled out CrowdStrike on our devices, and he did it in, like, forty minutes instead of, I think, what he said. You know, it would have taken him, like, a day or two. Yeah. And he just he did that entirely through assistant. He was just, hey.
Speaker 9:I wanna, you know, plug into these laptops. It went. It understood. Hey. You need to download these two binaries if you're gonna deploy it on these versions of macOS.
Speaker 9:Here's reuploaded. Here's the script you write. Okay. Do you want me to push it? Yes.
Speaker 9:And just deployed it. So I think there's there's kind of a lot there's more use cases than we can imagine, 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 what they wanna build.
Speaker 2:Yeah. Yeah. I mean, there's so many startups. I'm sure a lot lot of founders in the audience have have felt this before where you're the CEO and you set up the, you know, the all the IT systems, and then actually offboarding is, like, the super admin is extremely difficult. I actually I actually fully lost my Amazon account at a previous company because it was so deeply integrated into the company that they just couldn't figure out how to change the super admin.
Speaker 2: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 and basically just declare like Amazon bankruptcy. Because I was just the admin for like a decade, things just like built up and I and I try and give people the other password. Anyway, there's a million How are you
Speaker 1:how are you how do you 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 Sure. At this point, it's just like, let's get as many great companies as we can Yeah. On the products.
Speaker 1:But then, you know, five, ten years from now 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 Yeah. 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.
Speaker 1:It's like bringing a kind of capability to a to a company. But how are you thinking about the the overall category?
Speaker 9:Yeah. Absolutely. So there's a there's a couple of things, I think, that are that are going on at once. I think the first one is, you know, when we when we look at IT today, it's very much a reactive role. It's very much a cost center because I think we've just it's kind of, like, escaped us a little bit.
Speaker 9:Right? In the eighties and nineties, IT was actually an enablement center. Right? You were bringing in technology or deploying you know, giving people computers or, you know, deploying Wi Fi and or not Wi Fi, but Internet, you know, giving them email and so on. That's like a force multiplier.
Speaker 9:We've done too much of that. We have too many SaaS apps. There's all this sprawl, and now all your you kind of the the team is just managing that. Right? They're just doing support.
Speaker 9:And so with console, the way we think about it is we're gonna bring our teams back to kind of what it was like in the nineties where you can actually have this agent handling, you know, all of the the the ticket management for those those simple systems and those those kind of basic requests. Now you have assistant that can go and do more complex work across the the enterprise, and the value there is now you can do 10 times as much as you were gonna do it in, you know, in that year. And, you know, 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, you know, perfectly set up.
Speaker 9: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 to kind of focus on the more strategic and kind of be more outcome based. 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 the employee headcount or or the cost really the the to to to go and spend on it. And so that's that's one big piece. The other one is we're actually just ripping out and replacing, you know, tools like ServiceNow and, you know, Jira Service Desk and Freshservice, and kind of replacing it with a more AI native solution.
Speaker 9:And so we we expect that to to kind of scale as as you onboard more as as companies become more digital native. Right? They they have more SaaS
Speaker 2:You're saying
Speaker 1:you're the SaaS pocalypse. You're flaming the you're flaming the fires of the SaaS pocalypse.
Speaker 9:I didn't say that.
Speaker 1:I said that.
Speaker 7:There you go.
Speaker 1:Very very cool. Yeah. It's great great to get the update that yeah. And and we're gonna work on this coinage. Go back with the team, brainstorm a little bit.
Speaker 1:You tell us you tell us what and we'll start asking every company. Are you guys using the Serban method? Yeah. We'll figure it out.
Speaker 2:It's good. It's good. Okay. I love it.
Speaker 9:I'll run it by my head of growth. We'll see what she says.
Speaker 2:Fantastic. Good.
Speaker 1:Great to see you.
Speaker 2:Have a great rest your day. We'll talk
Speaker 7:to you soon.
Speaker 9:Thanks, Good see you. Alright.
Speaker 2:Thanks a lot. We'll talk to you soon. There's a bunch of news that we need to run through before we head out. Artemis two is launching, and Kashi has it at 64% chance before April 2. We're going to the moon.
Speaker 2:Four people are going to the moon. Everyday Astronaut says, I'm honestly shocked at how the general public has no idea Artemis two 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 got to get people stoked. This is what I'm going be writing about tomorrow.
Speaker 2:I want to deep dive this. Want Why
Speaker 1:is no one talking about
Speaker 2:our Why is no one talking about the moon? We're going NASA is set to launch four astronauts around the moon, the deepest human spaceflight since the final Apollo lunar landing on '9 in 1972. And there's a bunch of goals. So you can go track that, and and we will talk more about that tomorrow. And, of course, bring you a whole bunch of other news and interviews tomorrow.
Speaker 2:Leave us five stars on Apple Podcasts and Spotify. Sign up for our newsletter at tbpn.com.
Speaker 1:It's been a Nice see you. It's been an honor.
Speaker 2:It's been an honor
Speaker 1:to to be here. It was a
Speaker 2:rough couple days. It was a rough couple days being away. Yeah. But we're back. We're glad to
Speaker 1:be back.
Speaker 2:I'm glad.
Speaker 1:It's gonna be a great week and have a wonderful evening.
Speaker 2:Yeah. We will see you tomorrow. Goodbye. Throwing smoke. Throwing smoke.
Speaker 2:Okay. Goodbye, everyone.
Speaker 1:See you tomorrow, folks.
Speaker 2:Goodbye. We will be back when the smoke
Speaker 1:clears. Wonderful day. Goodbye.