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

Summary

TBPN (March 30, 2026) — Episode Summary

Overview

This wide-ranging TBPN episode, hosted by John Coogan and Jordi Hays, explores several intersecting tech, legal, and culture topics. The headline segment breaks down the groundbreaking lawsuit against Meta and Google led by attorney Mark Lanier, who won a major verdict on social media addiction. Other rich discussions cover the real tech predictions of The Jetsons, the unique social media landscape in Japan, the state of the AI and semiconductor markets (with deep dives from expert guests), plus hands-on founder updates from the cutting edge of automation, agents, and robotics.

The tone is energetic, irreverent, and often tongue-in-cheek, with deep technical asides, incisive analogies, and an abiding love for both the absurdities and real-world impacts of tech.

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Featured Topics and Key Segments

1. The Lawyer Who Beat Meta and Google: Mark Lanier’s Big Win

Timestamps: [01:33] – [17:28]

• Lanier’s Legal Strategy:

  • Mark Lanier, famed plaintiff’s attorney, secured a verdict holding Meta (Instagram) and Google (YouTube) negligent for designing addictive and harmful features targeting teens.
  • Lanier’s style: known for using props, parables, and a preacher’s flair. E.g., brought cupcakes and tortillas to court—"Social media is like the baking powder that makes a cake rise, exacerbating the struggles of already vulnerable teens." ([03:23])
  • Tech compared to "cupcakes" (addictive) vs. "tortillas" (less so).

• Jury Verdict:

  • Companies ordered to pay a total of $6 million in damages.
  • Plaintiff "Kaylee" testified about childhood social media use fueling anxiety, depression, and body dysmorphia.

• Platform Responses:

  • Meta: Disagreed with verdict, intends to appeal; warned against oversimplifying teen mental health challenges.
  • Google: “YouTube is a responsibly built streaming platform, not a social media site.” ([05:54])

• Debate on Features vs. Content Addiction:

  • Jury held platforms responsible for features (infinite scroll, algorithmic feeds, autoplay, notifications, filters, like-button), not content.
  • John: “Are the features addictive or is the content addictive? … Social media platforms are of course protected from the content...” ([16:19])
  • Noted, if features alone were addictive, "there would be so many social media apps that were effectively thriving..." ([21:30])

Notable Quote

“If the court is asking us to believe the like button, the algorithmic feed—that is addictive—then we should see addiction results from any app that implements that. That is the case for all nicotine-containing products.” — John ([21:53])

• Lanier Backstory:
  • Extensive history of massive settlements against big firms (Merck, Johnson & Johnson).
  • Personal details: owns a Texas estate with a model railroad for 120 people, throws parties with 9,000 guests, and keeps llamas and lemurs.

Another Memorable Moment

“His mansion can seat 120 on a model railroad and he has a menagerie. Lemurs and llamas. … This guy’s a hero.” — John ([13:51])

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2. Social Media Addiction – Cigarettes, Placebos, and Sora

Timestamps: [17:28] – [29:57]

• Placebo-Controlled Trial (Re: OpenAI Sora):

  • Sora's addictive social video UI (algorithmic feeds, infinite scroll, likes) flopped—users not hooked due to ‘sloppy’ content.
  • Implication: Content, not addictive features alone, drives hook and retention.

• Nuanced Discussion:

  • "Court is correct and Lanier is correct, some people go on social media and make horrible content that depresses people." — John ([23:45])
  • Calls for better parental controls and user customization rather than blanket liability.

• Pushback & Analogy:

  • “The medium is the message.” (Tyler, [27:59]) — features can incentivize addictive content creation.
  • Extended discussion comparing social media to nicotine products: differentiation between mechanism of addiction (features vs. content as "nicotine"/"carcinogen").

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3. The Jetsons: Future Tech Predictions vs. Present Reality

Timestamps: [32:56] – [40:04]

• Revisiting The Jetsons (set in 2062):
  • Video calling is now real, flying cars (eVTOLs) getting close, push-button jobs “almost” here (AI agents, vibe-coding), robot maids getting closer.
  • Missed predictions: no touchscreens, ongoing tech-induced repetitive motion injuries (tech neck, carpal tunnel).

Notable Quote

"Working three hours a day, three days a week—we can live the Jetsons future!" — Jordi ([37:27])

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4. Japan Twitter/X and Office Chair Racing

Timestamps: [51:13] – [55:45]

• Cultural Synergy on X (formerly Twitter):

  • Timeline surge of Japanese posts translated for global users—Japanese enthusiasm for American BBQ, cowboys, bulk groceries.
  • Japan’s user base on X: over 50% weekly active usage, a unique phenomenon.

• Office Chair Racing Viral Segment:

  • A new Japanese sport that’s predicted to trend in San Francisco; commentary on athleticism and “devil’s hairpin” maneuver.

Notable Quote

"I think I got a build for office chair racing." — John ([51:38]) "Half of my [Twitter] timeline was just Japanese posts about America—how much they love barbecue, cowboy aesthetics..." — Tyler ([52:09])

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5. Deep Tech: Nvidia, Chips, AI Agents

Guest: Tae Kim ([60:23] – [89:18])

• State of Nvidia and the AI Hardware Market:
  • Nvidia down 21% from peak; chip sector flat, but fundamentals strong ("AI compute shortage").
  • Massive demand for inference (agentic coding, code-gen, vertical AI agents) driving supply constraints—Vibe coders scrambling for GPUs.
  • Jensen Huang (Nvidia CEO) locked up supply chain, anticipated demand surge.
  • Discussion of Grok acquisition, open-source strategy, context window innovations, synthetic data.
  • Ongoing concern: wafer/fab capacity (TSMC, Samsung, Intel), helium/material shortages, depreciation of existing GPU hardware—so far minor issue.
  • GPU rental market healthy, even for hardware 6+ years old; no compute glut yet.

Notable Quotes

“It’s almost like a gold rush … Jensen is positioned perfectly to thrive on this coding agent wave.” — Tae Kim ([64:49]) “We act as a force multiplier for your team — with Console, they go 1 to 400 [IT admin to employee ratio].” — Andre Serban, Console ([171:08])

• Meta’s Position:
  • Meta’s AI investment seen as side quest; core business (ads, social platforms) expected to remain strong and resilient despite swings.

Notable Quote

“No one’s going to replace Instagram, no one’s going to replace Facebook. Billions of people are still going to use those social media apps.” — Tae Kim ([87:16])

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6. Market Reset and VC Reality Check

Guest: Logan Bartlett, Redpoint ([90:37] – [129:17])

• Disconnect Between Public & Private Markets:

  • Public markets: software trading at 4x NTM revenue; private valuations at 200-400x ARR.
  • Downward pressure on public software multiples due to stock-based comp, future uncertainty, and AI’s terminal value impact.
  • Investors wary—"Public investors ask, what's the risk of going to zero; private investors ask, what’s the chance to miss a 100x?" ([94:47])
  • "Is it like newspaper earnings post-internet—stable now but with value and future growth in doubt?" ([100:21])

• AI Bubble or Not?

  • AI as a technology is not a bubble, but admits signs of a venture "bubble" in AI company creation/valuation. Likens it to airlines, railroads—transformative but not always investment goldmines.
  • Incumbents get first shot at new markets, but cultural agility, willingness to ship scrappy MVPs fast (Ramp cited as model) will dictate winners.

Notable Quote

“AI maybe isn’t a bubble, but that doesn’t mean we’re not experiencing a massive bubble in the kind of venture world right now.” — Jordi ([111:22])

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7. The Lightning Round: Frontier Founders, New Automation

Granola (Sam Stevenson, $1.5B val) [129:21]:

• AI meeting assistant with privacy-forward design.
• “Spotify Wrapped”-inspired ‘Granola Crunched’ feature; user context is private, reflective, even uncomfortable.
• Context: Tradeoffs between benefits of ubiquitous meeting transcripts for productivity and legal/PR risks in discovery.

Polcia (Ben Broca) [143:51]:

• AI platform to automate building & running companies.
• Agents handle everything from product build to operations, marketing, and support.
• Name ‘Polcia’ is ‘AI Slop’ spelled backwards—intended as a conversation starter.
• Human input remains vital, but automation eats the 80% ops grunt work.

Hark (Brett Adcock) [154:51]:

• New AI lab building advanced, multimodal personal assistants (think Jarvis).
• "Language models are dumb—don’t remember, don’t communicate naturally; need new hardware interfaces too."
• Hark and Figure (humanoid robotics) share resources but focus separately: Figure on physics and embodiment, Hark on multimodal AI/consumer products.
• Market for AI/robotics talent is "next level competitive."

Memorable Moment

“Bring a six-pack over to Figure and we’ll test the robots [cracking a Diet Coke].” — Brett Adcock ([164:33])

Console (Andrei Serban) [165:02]:

• AI agents for enterprise IT, automating onboarding, support, routine tasks.
• New ‘Assistant’ product — agents can now build their own integrations and workflows.
• Context graph gives AI systems real, actionable org-level understanding.

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Notable Quotes & Moments

• On the power (and folly) of courtroom spectacle:

  • “He walks into court with a box of paper like it’s 1998 … He’s menagerie-maxing!” ([13:06])

• Comparing social media to cigarettes (on real mechanisms of addiction):

  • “There are a thousand e-cigarette brands … If features alone were addictive, you’d see every clone thriving.” ([21:53])

• On the “serbian method” (agents building software by request):

  • “Instead of a feature request, just request a feature … That’s years of roadmap now delivered in a prompt.” ([167:07])

• AI hiring wars:

  • “The space is just completely lit up—I’ve never seen anything like it before.” — Brett Adcock ([158:44])

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Conclusion

This episode delivers a snapshot of where tech is at in 2026—AI everywhere, legal and cultural backlash, VC bubbles, the reimagining of work (and Turbo SaaS), the oddities of global social media, and moonshot predictions both serious and surreal. Guests offer unfiltered, field-level insights, grounded in product, code, and market realities. Whether you care about tech policy, product innovation, or just want a sense of the culture's pulse, this episode is a must-listen.

Skip to segments:

• Mark Lanier v. Meta/Google: [01:33]–[17:28]
• Sora & Addiction Placebos: [17:28]–[29:57]
• Jetsons Tech Futures: [32:56]–[40:04]
• Japan Twitter/X: [51:13]–[55:45]
• Tae Kim on Nvidia & Chips: [60:23]–[89:18]
• Logan Bartlett on Markets: [90:37]–[129:17]
• Lightning Round (Granola, Polcia, Hark, Console): After [129:18]

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For deeper dives or reference, see specific timestamps above for each section, and catch all full interviews with Tae Kim, Logan Bartlett, Sam Stevenson, Ben Broca, Brett Adcock, and Andrei Serban in their respective slots.

Transcript

[A]

You're watching TVPN.

[B]

Today is Monday, March 30, 2026. We are live from the TVPN Ultradome.

[A]

The temple of technology, the fortress of finance, the capital of capital.

[B]

Let me tell you about ramp.com, baby. Time is money save. Both easy use, corporate cards, bill pay, accounting, and a whole lot more all in one place. Let's pull up the linear lineup. We got Tae Kim coming on to give us the Nvidia update. He is of course, the founder of KeyContext, the Substack. Logan Barlett'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. Very, very good. Tons of really interesting tidbits in there. And then we have a fantastic lightning round for you today. Linear, of course, is the system for modern software development. 70% of enterprise workspaces on linear are using agents.

[C]

So, lightning round.

[A]

We got Ben Broka from Paul, Sia, Sam, founder of Granola, on their one and a half billion dollar valuation. And then Brett Adcock.

[B]

What was your nickname for him again?

[D]

Who?

[B]

Brett Adcock. You had some nickname for him?

[A]

No, no, I didn't. Must have been someone else.

[B]

Oh, you're on a first name basis. We just call him Brett. Brett, yeah.

[A]

Or just B. Yeah. Hey B.

[B]

That makes sense.

[A]

Hey B. Okay, now this will be interesting. He launched a neolab last week.

[B]

Oh, yeah, that's right, that's right.

[A]

So we're gonna be able to talk to him about that. Models and hardware.

[B]

Hark. I hear the angels singing.

[A]

And then Andre from Console joining as well, so. Looking forward to that.

[B]

Well, I've been addicted to social media lawsuits. I cannot get enough of these lawsuits. I keep reading about them losing sleep.

[A]

You're potentially filing your own lawsuit against the lawyers.

[B]

Yes.

[A]

That were coming after these social media.

[B]

Yeah, yeah. So there's actually a profile in the Wall Street Journal in the exchange this weekend. The lawyer who beat Meta and Google. And it goes into some of his addictive techniques that are driving jurors crazy across the country. Attorney Mark Lanier. He uses props. Come on, come on. What's more addictive than props? He also uses parables. Okay, what parables? Metaphors, axioms. All of the above. He moonlights as a preacher and it shows when he's taking on the world's most powerful companies. The 65 year old came to court in downtown Los Angeles for closing arguments this month of one of the biggest trials of his career armed with a parable of leavened bread 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 for 65,

[A]

we just say he looks fantastic.

[B]

For 65, he does look fantastic. And as much as we're joking, I do think he's doing important work and I do think there's a potentially really good outcome here that we'll go into, but we're still having some fun. So the veteran plaintiff's lawyer from Texas showed them two grocery items, cupcakes and tortillas. Hmm. Social media, he told the courtroom, was like the baking powder that makes a cake rise, exacerbating the struggles of of already vulnerable teens. 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 A, B, C. So he's making the argument that social media is more like cupcakes than tortillas. Both contain flour, both are carb, carbohydrate, loaded. But one is bigger than the other, or puffier, I suppose. The simple image delivered with Lanier's slight 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. He's saying, I reject technology. This cannot be stored digitally. I'm using paper, which, I don't know,

[A]

this seems a little bit risky because we've been addicted to the printed word in the past. So much so that we face criticism from people that said, hey, printing is unnecessary.

[B]

It did not environmentally friendly, but.

[A]

And we were forced to adjust.

[B]

Maybe he can flip over to be our defense attorney when we are attacked. There's a courtroom sketch showing Lanier questioning former TBPN guest Adam Mosseri, the head of Meta's Instagram. A jury ordered the companies to pay $3 million each in compensatory damages and 3 million in punitive damages. So I think it's 6 million across both firms, but it's split compensatory and punitive damages. And Now a, now 20 year old woman named Kaylee, whose last name was redacted in the case. She had testified that social media use that started when she was a child dominate her life for years and contributed to mental health issues including anxiety, depression and body dysmorphia. 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. What do you think they're like?

[A]

We're not even a social media company,

[B]

we're a VR company.

[A]

No, no, no. Google said misunderstands YouTube, which is a responsibly built streaming platform, not a social media site.

[B]

That's true.

[A]

You got the wrong guy.

[B]

Yeah, I think of YouTube very much as in the same world as social media, anyone can post, but it is severely lacking in some of the greatest features of social media sites. Like you. When you actually become a YouTuber, you start putting out content that like there is sort of, I don't know, like a group of made men on YouTube, like people that have, that have ascended and they now have, they're now making content like professionally and they are in conversation with each other and they might be reacting to each other's content. And of course there are different communities. There's like the car YouTuber community and then there's the, 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,

[A]

which is a good argument for it

[B]

not being social media.

[A]

Not being a social media.

[B]

Yeah, yeah. So like, you know, we at this point have done the Collin and Samir show, but we don't really have a way like we can go onto the Collin Samir YouTube channel and leave them a comment and they might see it if it's from the TVPN account, but we can't like just DM them and be surfaced to the top of the inbox. People have always wanted an inbox on YouTube.

[A]

Yeah, that's a huge feature request.

[B]

It's insane because like it would be so cool to be able to see, okay, I got a DM from someone who has 100,000 followers and I can click on their profile and see, oh, they're like, you know, in the same niche, like maybe we'd want to work together. Maybe we want to collab on a video or do something else because they're like an established YouTuber as opposed to everyone basically needs to flow over to Twitter or X and then DM there because the DM functionality is much more mature.

[A]

On the other thing Google has in this kind of position is that so much of the watch time on YouTube is happening on television. Something like 50%.

[B]

Yep.

[A]

Very different. So they can make the argument that this is just modern television.

[B]

Yeah. 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 in fortune, representing plaintiffs against corporate giants. He won one of the first major wrongful death trials against pharma company Merck over claims that the prescription anti inflammatory drug Vioxx caused heart problems. He also won a $4.69 billion verdict in 2020, in 2018, for women and their families who said asbestos tainted talcum powder caused ovarian cancer. So, I mean, over his career, it seems like he's done some very, very good work and has won some massive, massive settlements against big companies with broadly damaging products. So a lot to admire about his career here. The social media trial drew more scrutiny than he predicted before he joined the plaintiffs team last fall and was brought to face with Meta Chief executive Mark Zuckerberg. Suddenly, Lanier was at the episode.

[A]

I believe that Zuck is actually mewing in this picture. If we can pull up this image,

[B]

it does appear to be something along those lines. Suddenly Lanier was at the epicenter.

[A]

You agree, Tyler?

[E]

Right.

[D]

You can tell his cortisol is not spiking here.

[B]

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. 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. In a downtown Los Angeles hotel the morning after the victory. Nothing even remotely close. And I think that's accurate because even though those previous settlements were huge, they weren't major. They didn't break through to the point where, like, I remember them vividly.

[A]

Do you?

[B]

No, no. Vioxx, it does not ring a bell. But this certainly, well, for a lot of people, especially in tech. Social media companies have largely been shielded from being held liable for third party content on their platforms by section 230 of the 1996 Communications Decency Act. At trial, Lanier had to focus on the platform's fitness features, not the content to make a case. And that's something that I want to talk about today, and I wrote about it in the newsletter. The trial was the first among the first among thousands of consolidated lawsuits filed by teenagers, school districts and state attorneys against Meta, YouTube, TikTok and Snap. More are scheduled for this year. TikTok and Snap settled the 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 burst in Texas. Now nationally. He's known for showing jurors hand drawn roadmaps and illustrations on an overhead projector to guide them through his legal reasoning and evidence, including signposts and human figures that could have been sketched by a child. To visualize microscopic asbestos fibers in talcum powder, he brought a bale of hay into a courtroom and. And dropped a needle into the blades. Into the blades. The blades of grass. Oh, the blades of hay. Got it. Okay. Wow. Very, very interesting. He likes props. That's it. When arguing for punitive damages against the tech company, Lanier held up a jar.

[A]

Quite addictive.

[B]

This is a good point. So he held up a jar of 415M&MS. To show how a $1 billion fine would be a fraction of Alphabet's 415 billion in shareholder equity. He needs a bigger chart. I think every tech company is five times larger now. He says he tries to avoid being flashy himself. He wears the same two unremarkable suits on rotation during a trial. And then I go burn them. What? He burns his suits. Is that a joke? Or he gives them away? I don't know.

[A]

My work here is done, I guess.

[B]

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, he began gaining renown as a lawyer in an era when asbestos cases were swamping the US courts. He won a jury verdict of about 115 million in 1998 for 21 steel workers who felt ill after using machinery that contained asbestos. Linear and his wife Becky, met in high school debate class. They have five children and 12 grandchildren. Wow. 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 120 people. Okay. This guy's gotta win all the. I have completely changed my position here.

[D]

We need a mansion section article about.

[A]

I think we have a direct line to him, by the way.

[B]

Okay.

[A]

We want him on the show. Well, maybe we should go do a show from the. From the model train.

[B]

Yes. I'm so ready to be convinced of his position. I wrote a whole piece about how I disagree with the result, but he's winning me over.

[A]

I disagree with this entire argument, but you're agreeing with this approach to life?

[B]

Yes. 100%. 100%. I feel like we're kindred spirits. It's amazing. So the model railroad can seat 120 people. And guess what? He's got a menagerie. This is gold. You need to be menagerie. Maxing in life, you need a menagerie. His contains lemurs.

[A]

There we go.

[B]

And llamas.

[A]

There we go.

[B]

Lemurs and llamas.

[E]

Thank you.

[B]

This is incredible. The family pulled the plug on the party, which featured up to 9,000 guests and performers, including Miley Cyrus, Johnny Cash, and Dolly Parton. He said because it was too hard on the lawn. The guy cares about his grass too much. This is incredible. Inviting 9,000. He's an environmentalist 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 Caylee would not have anybody else. Faith is much the same way. God. 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.

[A]

By the way, you keep saying linear.

[B]

Is it linear or linear?

[A]

Linear.

[B]

Linear.

[A]

Linear. Linear.

[B]

I think it's linear. Well, we'll figure it out. He has deep authentications.

[A]

I just don't want people to get confused with the system for modern stuff.

[B]

Yes, it's not linear. It's linear. I think maybe it's Lanier. Maybe it's French. 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 yeah.

[A]

Let's switch gears to your piece.

[B]

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. So last week, Brandon Gorell 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 ofMea and YouTube are designed to be addictive. And I want you to really hone in on these features. So Infinite scroll creates an environment where there are no natural stopping points. Algorithmic recommendation feeds use highly users highly engaging content. 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. Okay, so you got a bunch of features. You know this stuff. Everyone uses social media. We all know about this stuff. The question is like, are the features addictive or is the content addictive? Because social media platforms are of course protected from the content that it is posted on.

[A]

Lanier's entire. Lanier's entire argument is predicated on it being the features, right?

[B]

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 million settlement right now, but this is. This could be huge. The direct quote was whether we will even have social media in the future. Like, this could be existential.

[A]

Yeah. And there's thousands of other cases like this kind of percolating. Right. And so.

[B]

And they could turn into a class action. He's gotten S6 billion before. He could get 50 billion. I don't know. He could get a lot. And he's not like 6 million. He's not a 6 million guy. He's a 6 billion guy. And so this is the precursor and it's going further. And whether it's a ton of different cases or one big one, it's a big problem for the Tech companies. So I thought it was an odd coincidence that we sort of had what I called the placebo controlled trial for these exact features last week when Sora shut 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. We won't be able to look away.

[A]

Simply too good.

[B]

Simply too good. And Rune summarized this pretty well. I think yesterday, or I think it was yesterday, he said Sora was peak moral panic. All of these breathless takes about making videos that are going to addict humanity and waste everyone's time. Meanwhile, we made some funny videos that were less funny as time went on. And AI slop is just one category among many on Instagram reels. Don't worry so much about making videos that are going to blow up people's brains without making anything good. Without worry about making anything good at all. The best Soras were up there with the best reels. And the humor relied significantly on the voice of the creator. I completely agree. The funny Soras that I. Yeah.

[A]

Even the video we played last week of the cat on the porch.

[B]

Yes.

[A]

That wasn't one shotted.

[B]

Yeah. The prompt was not. Was not. Make something that will retain use.

[A]

And it wouldn't have been funny if the person hadn't been escalating, like the scene, every new prompt and then stringing them together.

[B]

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. 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. Sora 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, it had notifications, it had a like button. And it didn't have IG beauty filters, but, like, the whole thing is a filter because I could go in there and say, make me look like a bodybuilder. And it did a good job and I looked great in the videos. And so, like, it is, it really checks all of the same boxes to

[A]

try to, like, match that.

[B]

It gave me crippling, broad body dysmorphia. Obviously, I dream for the day when I will look like my Sora avatar, my. What do they call it? Cameo. My cameo. No, but they really did use all the normal tools 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 2020, we're not in 2014 when we're launching Vine. So the key insight was purely AI generated content. And it didn't work. 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?

[A]

Yeah, well, it was just one type of content. And it turns out people like a broad selection and they like variability. They might want to see a video of someone skiing and then some slop and then something their friend made and then some health content. And it's really the collection of that. The other thing I think that seems very obvious is if it was the product itself and the features that were addicting, there would be so many social media. There would be so many social media apps that were effectively thriving. There would be a bunch of Instagram.

[B]

And this is where I get to the cigarette comparison. So there's a bunch of comparisons to the cigarette industry. And I think it's really worth revisiting, like, what is addictive about cigarettes? Because there are some people that say, like, it's an oral fixation. Like, you just want to put like a stick in your mouth, so you should, like, switch to carrots. Like, that is like, maybe like 1%.

[A]

Some could argue it's an addiction to looking cool.

[F]

There you go.

[B]

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 1000 different E cigarette brands. And nicotine gum is addictive. Nicotine patches are addictive. Nicotine pouches are addictive because they all contain the nicotine. And if the court is asking us to believe that the like button, the algorithmic feed that is addictive, then we should see addiction, like, results from any app that implements that, because that is the case for all nicotine containing products. They all addict people at. I mean, there are less addictive formats in general.

[A]

How many apps have you tried or test flights over the years that had any of these features that you used for 30 seconds.

[B]

Exactly. Exactly. Because what actually keeps you coming back is the content, which is created by the users.

[A]

And so you want Lanier to go after every single person that has ever posted anything on Instagram and jail them, correct?

[B]

No, no. I think that some creators do create very compelling content. Some of that you want to jail the best creator is. No, some of that content is amazing. Some of that content is great. Some of that content is bad. There's a very, very wide range 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. Andrej Karpathy's YouTube videos. There's so many interesting educational history shows, podcasts. There's so much content that, yeah, Tyler got.

[A]

Tyler got addicted to that video. Are you destined to deal?

[D]

And that's a great video.

[A]

He kept saying, that's why you have a tie on.

[D]

He, He.

[A]

He called me on Friday night and said, why is this video 20 hours long?

[B]

Because he loop.

[A]

Yeah, he was just loop.

[B]

That makes sense. That makes sense. So, yeah, but I mean, but it is true. Like, I think the court is correct and Lanier is correct that some people go on social media and make horrible content that depresses people that land on it. And it go 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, 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. 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 middle ground here. And just in general, one other nice meet in the middle option is potentially just 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 plugins on mobile web, but it's a much worse experience because you have to load it on mobile web, which isn't the actual app, and it's slower. And there's a lot of things that are just kind of janky and don't load as well. But having those in the Settings to just say, I know some creators on Instagram can turn off the light counter. Have you ever seen this? So you can see someone post an image and it'll just have a like button there. But it doesn't have like 5,000 likes. Because the creators were getting like, you know, annoyed by, oh, this one.

[A]

Well, to be clear, that's because people didn't want to post because they were worried something wouldn't do well.

[B]

Yeah.

[A]

And the world would know that their content was engaging or something like that.

[F]

Right.

[A]

So that was just an. 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.

[B]

I don't know, I don't know. I mean I'm sure like there have like my mental health as a social media creator was at an all time high before I understood the metrics because I was just like, oh, 300 views. I'm famous. This is amazing. 300 people sat down and watched my 10 minute video essay about a dying VR technology or something like that. It was like, I've done it. 300 people sat down. It's like I'm a business school professor basically. But then eventually you get and you're like, wait, the last video got 400,000 views. Why does this one have 375,000 views? I'm a failure. So there is a little bit of that, but I hear you.

[A]

Yeah, but the metrics are still available to the creators. Yeah, yeah, the creator.

[B]

The turn it off with a Chrome plugin, you actually can't. There's some creators that do this, but anyway, like surfacing those in apps, I think that will help users feel like they're in more control. And realistically I don't think it will be super damaging to any of the platforms because most people won't opt into that, but certain people will. And in general it'll just like increase public perception broadly. We've already seen this with a lot of the LLM companies where like you can go in and you can fine tune and add a custom prompt and kind of talk to it about what you like and don't like. Change the personality. I think people have been asking for that for a long time. Surfacing it, it seems like a win win and so something along those lines seems in the cards. 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 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 safe, borrow and invest securely. Connecting bank accounts to move money, fight fraud and improve lending now with AI. So do you have any other pushback on my take? Tyler had some pushback. Should we go to him?

[A]

Let's go to Tyler.

[B]

What do you think?

[D]

I mean, yes, I guess there was a few things. I mean, one thing is that, like,

[B]

not enough props, right? Too many analogies, too many parables.

[D]

I think you can say that like, okay, yeah, it's the content that's the problem. But the content is kind of downstream of the features.

[A]

Right.

[D]

Because you didn't see short form video.

[B]

The medium is the message.

[A]

Yes.

[B]

And so 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. You become addicted to the content, but it's because of the features.

[A]

Yeah.

[D]

So I think that's like broad. Pretty good argument, the steel man that you can make for like linear's position.

[B]

Yeah.

[D]

And then, I mean, there's other stuff, I think on, like just the nicotine analogy, we were talking about this, like, okay, so you have nicotine, like broadly, and then below nicotine you have like smoking, which is like, definitely very bad for you. And then you have like, you know, pouches or stuff like this, which is like, probably less bad. Like, it's just Nikki and there's no tobacco. So like, maybe this is like less bad. So maybe the equivalent is like, you know, the cool snowboarding videos on Instagram are like the, you know, the cleaner, like, nicotine stuff.

[B]

And then the like, still addictive but not harmful.

[A]

Yes.

[D]

And then there's like, you're gonna try

[B]

and do a double cork 1260 and eat.

[A]

Get smoke.

[B]

Get smoked into the ground.

[D]

Yeah, 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 cigarettes, that's like going to give you cancer, whatever.

[B]

Sure, sure.

[D]

So I think they're like. I mean, I guess it's still in agreement with what you're saying, but like, well, this is what, like nicotine, this

[B]

is what the cigarette had.

[D]

If you're under 18, you can't buy it.

[B]

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. 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.

[D]

Yeah.

[B]

And that would be like a new nicotine gum, basically.

[D]

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. If you can't be under 13 or whatever. But, like, it's like, very not. It's, like, poorly, you know, enforced. Like, you can actually see a lot of the bad stuff if you're under 18 on the screen or whatever.

[B]

Yep.

[D]

So, like, directionally, like, you know, you can be against the ruling of this. Yeah, but, like, the parental controls that people are, like, asked for are still, like, very much not there.

[B]

Yeah, yeah, no, that makes sense.

[A]

So I think I have a potential solution. Let's pull up this image of a cigarette package in Europe.

[B]

Oh, yeah. What is this?

[A]

So pull this up.

[B]

Let's pull up.

[A]

This is the hardest challenge.

[B]

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 Turbospector. Built from first principles and object storage. Fast 10x cheaper and extremely scalable.

[A]

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.

[B]

Yes.

[A]

And 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. And then you can scroll past it.

[B]

It could potentially show you with Tech Neck. Are you familiar with Tech Tech Neck? Here you go.

[G]

Like this.

[A]

Yes. Yes. It's just a crazy image of you with Tech Neck. It shows you your phone, and then. So you can scroll past it. Every time you open that app, you have a new Image.

[B]

It's a reminder.

[A]

It's a new image of you looking the worst, wasting your life away.

[B]

Are the AI labs lobbying to get this.

[A]

All right, we can put this labs

[B]

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?

[A]

I don't think anthropic's come out with their anti Anthropic, you know, has anti sunscreen. The joke that they make with journalists. They kind of got caught on anti sunscreen.

[B]

If AI is going to cure liver cancer, it's game on. It's game on. It's game on. You can drink as much as you want because you get liver disease if you drink too much. And so if AI if I'm going to be able to vibe code an MRNA vaccine to cure my liver cancer, I'm going to be boozing for sure. It's the only rational thing to do.

[D]

Yeah, well, this is also kind of like when sort of a rational when companies are saying like, oh yeah, work life balance is super important. So then their competitors will.

[B]

Yes.

[D]

Yeah, people anthropic should tell people to OpenAI to start drinking a lot because AGI is going to cure liver.

[B]

Yes, yes, yes, yes. This is good.

[C]

This is good.

[A]

Let's revisit the Jetsons.

[F]

Okay.

[B]

Revisit the Jetsons. I'm sure you've seen the Jetsons.

[A]

Where's my flying car and three hour workday? So I'm going to be learning about the Jetsons. John is going to be revisiting. The 1960s version of the future is way more fun than our reality. But when it comes to innovations, we're catching up. Interesting. Let's see. Nicole says, I recently spent a weekend doing deep investigative research into future technology. I binged the Jetsons in my sweatpants. For the uninitiated, the forgetful, this space age family sitcom features George and Jane Jetson living the American dream in an apartment in the sky with their two children, dog Astro and robot maid 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 treadmill complete with fire hydrants. The upbeat vibe is markedly different from the apocalyptic, at times murderous sci fi of today. The 1960s were full of optimism about what the 21st century would bring and some of it actually has come true. While we've still got a few decades before the Jetson family is meant to arrive, I dug into some of the 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. Show's creators couldn't fathom mobile devices, but they were spot on about video calling.

[B]

Now, to be clear, we are still working on with one of our business associates, like, a video call that doesn't stop halfway through and just cancel.

[A]

So the Jetsons didn't predict the free tier of zoom.

[B]

Yeah, the free tier of zoom was not considered in the Jetsons, where you couldn't fathom it.

[A]

I couldn't fathom it.

[B]

You're clearly going to go long on the. And zoom's just like, goodbye.

[A]

It's over.

[B]

It's over. And it kicks everyone out with no notice.

[A]

Is that a new thing? I feel like it used to do a countdown.

[B]

I think it did a countdown, too,

[A]

but now it's just now they're just like, we want to embarrass the host.

[B]

The plus tier is going to blow up.

[A]

So in the Jetsons, they could even create deep fakes to stand in for them on camera.

[F]

Whoa.

[B]

That's cool.

[A]

I didn't realize that FaceTime's got a guy on there. You know, the other thing they haven't cracked with FaceTime is, like, if you FaceTime, a group of people, like, most of the people won't even have a notification and don't know that it's happening. So we haven't cracked the notification part of the protocol.

[B]

This is good. Read this next line. 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.

[C]

Great.

[B]

This is so 60s.

[A]

Do not do this.

[B]

Do not do this. This is dystopian flying cars. It's not all optimism over here.

[A]

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, Jane sends him back with the push of a button. And they also use personal vehicles, the ones that typically fly George Aero commutes in a glass dome saucer that folds into a briefcase.

[B]

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 way down here.

[A]

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.

[B]

Look at this pivotal. Blackfly is a solo piloted aircraft, free to operate in unrestricted airspace. An upgraded version called the Helix can be used for 190k. You don't even need a pilot's license. That's like pretty close. But I mean, I would still say like we are not near the flying car because they're just not like there are way less flying car rides than Waymos, for example. So we're just not right there. Push button jobs, almost. 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 to support a family of four, even though a majority of his day is spent with his feet up on his desk.

[A]

Okay, they basically nailed this. There's some people out there that are basically button pushers right now. Vibe coding. TBD on the revenue side, true, but

[B]

working three hours a day, three days a week. We work three hours a day, five days a week, and maybe the future three. Just Monday, Wednesday, Friday streams. We can live the Jetsons future. Now we work.

[A]

That'd be devastating for us.

[B]

Yeah. Until then, we'll be working on space colonization.

[A]

Nope.

[B]

Yeah, they live above Earth with houses built on tall stilts. I like that. To avoid the planet's environmental inconveniences, the stilts can rise above any inclement weather. And space itself isn't out of reach. In a classic episode, Elroy goes to an asteroid on a school filled trip. We're not quite there. Musk had preached of populating Mars, but now his focus has turned closer to the moon. 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.

[A]

It's funny that Brett Adcock's coming on today. Yeah, he's working on the flying car.

[B]

Yeah, he's working on the robot made.

[A]

Working on the robot made.

[B]

He doesn't have a space thing yet.

[A]

He's now working. His new lab is basically like a. But you know, a button pusher gadget.

[B]

New gadget induced pain. Yes. And now for the show's biggest oversight. No touch screens. There are lots of visual displays, but they're primarily operated by dials, levers and other physical controls. We got some levers back there in the studio. While the show may not have anticipated touch screens, 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 clicks. 36 years and counting. We may not be living as exceptional a future as the Jetsons, but we've still got three and a half decades to catch up. By then I will be twice as old as I am now. I've already witnessed the dawn of high speed Internet, the iPhone and generative AI. How many tech revolutions will we experience in another 36 years? By the time we hit the show's 2062 deadline, maybe we will finally live in space or make our current planet more habitable and make a comfortable living on a nine hour work week week. Tyler, what do you think? Predict your timelines for 2062. Will we get space colonization?

[D]

How do you define space colonization?

[B]

Living on the earth above the Carmen line for like that's your primary residence like more than half the year.

[D]

How many people do it? Like just. You can do that? Like anyone can do that?

[B]

Yes, anyone with like if you can. If you can afford a apartment for a few thousand dollars or a house that's above $500,000 in America, you can choose to live in space. So I would assume population of millions.

[D]

It probably depends on the industry that is chiefly benefited from people living there.

[B]

Button pushing hide cook.

[A]

Okay, big news. Sean Frank is in the chat. He says I'm here guys. H E A R which so he's saying he's trying to signal that he's listening. I am here to you Tyler and to you Josh.

[B]

Well, thank you. Let's read him some ads since he's here. Let's tell him about restream one livestream 30 plus destinations. If you want to multi stream Sean, go to restream.com and you know what we got to tell him about? We got to tell him about Applovin. Profitable advertising made Easy with Axon AI Sean get access to over 1 billion daily active users and grow your business today.

[A]

Andrew Reed says the faster technology progresses, the harder it gets to print something in the office.

[B]

We've experienced this.

[A]

It's very true. The brother Aaron from Box says Reed's Law. I know you may have wanted a better law, but I don't make the rules.

[B]

Yeah, it's very, very difficult. Apple has just like never done the printer, I think for environmental reasons, I'm not exactly sure, but like there's never been like, oh, the gold standard. The Tesla printer is just like the one you get and it does what it want. 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. 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. Jordy, I want your take on tech in hotel rooms. I want to know about your experience when you walk into a hotel room. The Wall Street Journal says when you book a hotel room, you can count on some things like shampoo, a hot shower, some way to get a cup of coffee. But a stress free technology experience? No way. Not even with basic technology you find just about anywhere like TV, WiFi and outlets for your devices. Unless you carry a suitcase full 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 when he travels? So, so when he goes to a hotel, he logs into. Yeah, this is amazing. He logs in to the hotel WI fi, I believe, or the plane WI fi through that device and then all of his devices connect to that automatically. And he'll bring 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. I thought 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. He has all the wires dialed, as I would expect.

[A]

I usually forget to bring a charger.

[B]

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 muddle. I suspect I've logged more hours troubleshooting hotel TVs than I have watching programs on hotel TVs. Okay, there's a bit of a retro charm in a TV that flips on and instantly tunes to a live network broadcast. But in the streaming age, I'm just as likely to crave a little quality time with Netflix, Disney plus or Apple tv. Many hotels have caught onto this reality by offering some sort of streaming option, but they approach this in so many different ways. You never know what you're going to find or what tech you'll need to make it work. Needy Wi fi is another one. Most hotels I've visited recently seem to have figured out that charging extra for WI fi makes about as much sense as charging extra for a better toilet. Everyone needs to get online, so you might as well build it into the price of the hotel room. So now that we've taken that great leap forward, why are we still forcing people to log into the network not just once per day, but over and over again once per device, each and every day, or often several times a day? It isn't usual. It isn't unusual for me to log into hotel wi fi 20 or 30 times a day. I think you're doing something wrong.

[A]

Honestly.

[B]

Just.

[A]

I don't. This doesn't resonate with me at all.

[B]

You're fine.

[A]

The only thing I want from a hotel.

[B]

Yeah.

[A]

Is to be able to order room service without calling someone.

[B]

Okay.

[A]

That's like the only thing. And hotels miss on that for the most part. Like if you have a little iPad or you could even order on the TV app, that would be amazing. And you get like a Domino's Pizza tracker type thing. That's all I want.

[B]

Yeah.

[A]

I feel like they kind of deliver on everything else. And I don't watch.

[B]

I was listening to it was George Hotz 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 that he didn't have to talk to them. And it basically read the entire menu and then created a voice agent to call or reverse engineered the API of the ordering menu. And he was able to order by command line. Just checking into hotel time to build a cli. It's truly the future. I love it. But it is. It is. And you know who else is Vibe coding these days? Gary Tan. Ben Hylak has a Joke here. He says the year is 2027. Gary Tan has just crossed 1 billion lines of code per day. Water to 3 year old Californian towns were diverted in order to cool his locally ran LLMs. Riots erupt and protesters demand answers to one single question. What is he building?

[A]

We gotta have GT on.

[B]

I can't wait.

[A]

Let's get Gary on.

[B]

We gotta get Gary on. We gotta know what Gary is building. People are joking about this because what was the latest stat? It was something like 80, 78,000 lines

[D]

of code per day on, per day On Gary's list. On Gary's list, which is his blog.

[B]

It's a blog and he's built blogs before. Like 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 volume of code that will be generated when he creates a mobile app for it. It's going to be trillions of tokens going into that. Anyway, let me tell you about Label Box, RL environments, Voice robotics, evals and expert human data. Label Box is the data factory behind the world's leading AI teams.

[A]

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 in 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 Blackwells and support the DOE's mission of developing AI capabilities to drive technological leadership across US security, science and energy applications. 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 2200 exaflops of AI performance.

[B]

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.

[D]

So I was interested in this. I looked. This is going to be like somewhere around like a quarter of a gigawatt equivalent of 100,000 black belts.

[B]

Half a Meta campus I think, I think Meta is working on 500, 500 megs.

[D]

Yeah, I think, I mean Hyperion, like the end state is like I think

[B]

a gigawatt or more. More. But that's like the first big jump for them. But the default Meta campus I believe

[A]

is around 500 megs Cisco to acquire Restaurant Depot.

[B]

Not our Cisco. Not.

[A]

Not even close to require restaurant depot for $29.1 billion.

[B]

Before we take, let me tell you about the real Cisco. Critical infrastructure for the AI era unlocks seamless real time experiences and new value. With Cisco, there's only one Cisco in our hearts.

[A]

This one's important.

[B]

This is Cisco with an S.

[A]

I dislike Cisco.

[B]

Why?

[A]

Because every time I find it a very frequent experience where there's a new restaurant coming to my area, I'm excited about it. They invested in million $2 million in building out this incredible space. Looks great. And then you eat there for the first time and you can tell that they're just sourcing. Like Cisco. I'm not gonna say slop, but the food quality is not great. And then it's like, why did you put all this energy into making a beautiful space? And then you're just 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 in the Jetsons.

[B]

They had dinner generating machines. Dinner generating machines? How do you think that's gonna happen?

[D]

Travis Kalanick built this. Isn't this cloud kitchens?

[B]

Yeah, no, no. The dinner generating machine or Cisco dinner generating machine. Yeah, yeah, that's basically it. But it's all part of a pipeline.

[A]

The founder of Restaurant Depot, who just sold for 29 billion was born in in 1932. 94.

[B]

He's still kicking.

[A]

I think we should hit the gong for him.

[B]

Let's do it. Congratulations on that.

[A]

Great to finally get a solid exit. It's never too late. So if you're 93, I can buy

[B]

that sports car finally. Yeah, that is a true overnight success. Congratulations to him. Excited. I mean, you know, we gotta get food to people. People are hungry. There's some good things. Maybe they stock some raw milk and you're on board then who knows? Before we play the next video, let me tell you, every day is a fight between the advertisers and the viral videos. Let me tell you about Railway. Railway is the all in one intelligent cloud provider. Use your favorite agents to deploy web apps, servers, databases and more. While Railway automatically takes care of scaling, monitoring, insecurity. And then we can play this video.

[A]

We're heading over to Japan.

[B]

Yes. This is the key sport that we will all be picking up in 2026. This is going to be the hottest thing in San Francisco with the hills and the office chair

[A]

racing league. Look at the speed and the technicality it's incredible.

[B]

It's incredible.

[A]

This athlete says the corner once controlled me, now I control it.

[B]

I think I got. I think I got something.

[A]

You have quite a bit of leverage.

[B]

Yeah. With the legs.

[A]

With the legs.

[B]

I think I got a build for office chair.

[A]

The six year transformation is crazy. I mean, this guy is incredibly quick.

[B]

He lost me.

[A]

And we need to bring this to the U.S. we need to bring this to the U.S. chair racer Miura. Going around the devil's hairpin.

[B]

The devil's hairpin.

[A]

All right. So, Tyler, what is happening on X in Japan? Yeah, you. Break it down.

[B]

Break it down.

[D]

Yeah. I mean, I don't know all the internals, but it seems like like Nikita's been posting about this. But I think, you know, they basically introduced like all of like, Japan Twitter onto, like, normal Twitter.

[B]

Oh, because of translation.

[D]

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.

[A]

Cool.

[B]

I didn't know.

[A]

And we need to figure out. We need to figure out how and why over 50% or something like that of Japan is. Is like a weekly active user of X, which is just crazy.

[D]

Yeah, they have great posts.

[B]

Well, yeah, I mean.

[A]

So let's pull up this video.

[B]

Wait, wait. 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. Because when Grok went viral, everyone was like, oh, it's good at anime. It's big in Japan. And it was at the top of the Japanese app store. But it appears that Japan's just using Twitter broadly.

[A]

Elon.

[B]

They just like, they just like the app and that's like, where they have conversations, which is very cool. That's a narrative violation. So let's go to.

[A]

Let's pull up this first post.

[B]

This is hilarious.

[A]

And it is a. And this is the translation from Grok. When I saw this quote, pizza topped with a pizza in America, I thought, there's no way we could beat these guys. This is.

[B]

This is an amazing.

[A]

Oh, so this is an American I've never seen.

[B]

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

[A]

smash hit in my heart. This is quite.

[B]

This is a peak performance. Peak performance. We gotta. This may be for lunch today. Let's get some Pizza.

[A]

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.

[B]

There's just some guys cooking a whole bunch of steaks. That's a lot of meat. Wow, that's a lot of food. They're having a big barbecue in Sasebo's dining establishment.

[A]

Someone else, Someone else. Somebody's just I guess an American is posting their grocery haul and someone says the amount is way too much. As expected.

[B]

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. Here is me buying half a cow's worth of meat for our family. We store it in a big freezer in our garage. I actually have heard about this. Buying in bulk obviously is more economical. But hilarious ratio by Dr. Something or other. Dr. Nicholas. The amount is way too much. As expected. What else is going on in Japan?

[A]

Take me through someone else says in Sasebo's dining establishment it's common to spot US military personnel enjoying their meals with lively enthusiasts. One day at a restaurant I came across a group that reached an oddly intense level of excitement just upon seeing bacon.

[B]

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 11 labs build intelligent real time conversational agents reimagine human technology interacting with with 11 labs. In fundraising news, Physical Intelligence is in talks to raise $1 billion at 11 billion valuation.

[A]

I need to know why is Jeff Bezos here? Besides the fact that he looks fantastic

[B]

in the tux, he might put in some money. No, no. The company has previously raised more than 1 billion in capital from investors including Jeff Bezos and Alphabet's independent growth fund Capital G. So you could have put Peter Thiel because founders funds in. You could have put. But Lightspeed is that Danny Raquel could

[A]

have put Carol or Lockie

[E]

or any

[A]

of the actual team but the Speedo

[B]

seems to get the viral attention. But very good news. We actually interviewed both the co founders 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 spent maybe 20 minutes with them and you should go back and listen to it because it's a very interesting insight into the business that they're building which I think a lot of people, they're not a noisy firm, they're not a noisy company that's posting vibrels and going and picking fights all the time. So there isn't that much coverage of physical intelligence. But if you just look at the traction, look at the open source contributions, the data, the fundraising, like clearly something is happening there. And so I think it's worth digging in and paying attention to if you're.

[A]

Last night Bill Ackman hit the timeline.

[B]

Whoa, I didn't know.

[A]

He said some of the highest quality businesses in the world are trading at extremely cheap prices. Ignore the mainstream media, one of the most one sided wars in history that will end well for the US and the world and we have potential for a large peace dividend. One of the best times in a long time. Time to buy quality. Ignore the bears. And he says and Fannie Mae and Freddie are stupidly cheap Asymmetry at its best. They could be a 10x 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 42% and 37% 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.

[B]

Yeah, it's not market manipulation. It doesn't seem like he has any inside information. I don't know, does he even have a position? Isn't that disclosed in his filings? I'm not exactly sure. I would take every recommendation from a Twitter poster, every piece of financial advice with a grain of salt, but this one certainly turned out to be some sort of pump going on. And I did dig into this. Somebody asked Grok like, hey, break it down. Like what is actually going on here with Fannie and Freddie? They generate 25 billion in stable annual net income from guaranteed fees, low credit losses, outside crises. They're still in 2008 conservatorship and the stock trades for a total market cap of 10 billion. So there's a world where you're sort of buying maybe, I don't know exactly how aggregated this is, but Maybe it's like 25 billion of cash flow at some point for 10 billion that feels like a very good deal. Get paid back in four months, five months. But of course there are a whole bunch of other, a bunch of other

[A]

political and of course he does, he does own Fannie Mae and Freddie Mac are in his Pershing Square portfolio. But again, not illegal to share your opinion.

[B]

Yeah, well, there are some. Not everything is up. Mike Zuccardi shares the current Mag 7 Plus drawdowns from 52 week highs. Nvidia is down 21%, Google's down 22%, Microsoft down 36%, Apple's down 14%, Amazon 23%, Meta 34%, Tesla 28% 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 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 Tae Kim into the TPP at Ultradom. Tae Kim, how are you doing? Thank you so much for taking the time to go chat with us and

[A]

congratulations on the launch of your business.

[E]

Yes, thank you. I mean it's been really gratifying that first day. You never know who's going to show up.

[B]

Totally.

[E]

I'll say like maybe 15 subscribers or 20 subscribers but like hundreds of people showed up, tons of billionaires and tech founders. It's insanely gratifying.

[B]

Yeah, it's great.

[A]

Incredible.

[B]

So is it, is it over for Nvidia? They're down 21% we just read since the 52 week high. Is it doom and gloom? Is it over?

[E]

No, I mean I think I was on last December and the stock, because semis and chips have gone up and now they're back down to where they were in December. The chip sectors flat, flat on the year Nvidia is down 10%. And it reminds me a lot about a year ago, do you guys remember everyone was freaking out about deep seat. The super efficient models were going to destroy AI compute. There will be a huge compute glut. And then everyone freaked out about Trump's tariff wars, preparation to end day. And this year seems very similar to that almost it's like Groundhog Day. 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 Oil up here.

[A]

Iran. Yeah. Easy to get them mixed up. They happen.

[E]

Feels like the same thing. Over. Yeah, but

[A]

I'm sorry to distract. We wanted to throw, we wanted to show Respect.

[B]

We wanted to show respect to a real podcaster.

[E]

I mean, it's very similar to Iraq.

[H]

That's.

[E]

These are great, but in $100 oil, this stuff is unsustainable and it'll probably subside.

[B]

Okay, because I like the deep seq analogy and I feel like the market half digested the agentic coating narrative and the Citrini article. Whether you thought it went too far, it was too hypothetical, clearly the markets did react and a lot of names, games, 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.

[E]

Broadly, there's none of that. Just like tariffs. A year ago Nvidia had 30% drawdown when their business was actually flying. Actual fundamentals of the business. I think the same thing is happening here with the Iran war. Things will eventually subside. Oil can't be $100 forever. And Trump will probably backpedal in the next few weeks ahead of the Trump.

[B]

So let's recap a few of the key stories around Nvidia. We just came off of GTC and there's a lot going on at the company. I mean, it's a huge company. Maybe it'd be good to start with just next generation chips, changes to strategy, what people are actually buying. Maybe that means Grace cpu, standalone sales or the development with the Grok partnership. What's sticking out just on the actual AI product side to you that you're most excited about?

[E]

Well, inference demand is exploding, driven by the AI agents, coding assistance. 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.

[B]

And we're, I mean, yeah, you're seeing that from talking to engineering leaders at big tech companies, but we're also seeing it from Vibe coders who are just on Axe and Twitter and talking about how they're hitting rate limits and they're, they're subsidizing, they have multiple plans and they actually shift around from one model provider to another just to, to make sure that they're getting the tokens they need to build whatever they're building.

[E]

And you see the tweets, like people are like building bots to pick up any kind of B200 GPU that can. They're waiting like weeks and months or

[A]

whatever, like sneaker Bots. But for neoclass, that's crazy.

[E]

Exactly.

[B]

I can't believe that.

[E]

And the great thing is Jensen, he's very prescient. He probably saw this demand months away. He locked up up all the supply agreements for memory coas, connectors ahead of time. He saw this inference demand and to take advantage of this coding system.

[B]

Boom.

[E]

It's almost like a gold rush. You see OpenAI pivoting toward it. Anthropic obviously is thriving on it. Billions of ARR every few weeks. Jensen acquired Groq, acquired the assets of ROCK and the people of Rock Groq and this, the combination of integrating Grox 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 that we're seeing right now.

[B]

On the GROK deal, Jensen did a fantastic interview with Ben Thompson and, 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 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 feels like the right move, but do you see it as a shift in the philosophy of the company or the strategy? Or is this just something that, 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.

[E]

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.

[B]

He saw the world shifting to.

[E]

It's a networking chip, but he saw the world sifting to like these 10,000, 100,000 GPU clusters and Mel nuffs in the same manner. He saw AI agents and the inference behind that taking off. And he said, oh, this GROK thing will work perfectly with Ray Ruben. It doesn't replace everything, it just Sundays. Talk about 25% of the inference demand would be. Grok would work on that. But them working together where 75% of the inference is Vera Rubin 25% is a grok. Low latency stuff. It's like the perfect combination to, to take advantage of this. And the other thing is like, we're just in this great liftoff of AI innovation. Yeah, we've talked about Anthropic Mythos, the blog, blog post that leaked out so we're going to have this step up function. They told Fortune that it's going to be a huge step up change. OpenAI is coming out with their model soon. And then when I went to gcc, the biggest takeaway I had was this session between Jeff Dean and Bill Dali, both chief scientists of Google and Nvidia. And it's online. I highly recommend people watch it. And he talked about. Jeff Dean talked about the context have context window innovations where they could focus on the 10,000 documents that work well with your request and query. So we're going to have this context window innovation. Both chief scientists talked about stacking memory right on top of the GPU or tpu. And that's going to be a huge innovation in the coming months or years. And then Jeff, can you talk about synthetic data for audio and video? There's this huge Runway that data is not over. And then they're going to be able to take advantage of all this data that people don't realize yet. So you have all these vectors where AI models, you can just keep getting better and better.

[B]

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's like never really been in that market before, but at the same time, I've been the biggest supporter of open source American AI models. I loved when Meta was doing it. I want more of it. I loved when OpenAI open source GPT OSS. It feels, feels really, really important. Really great. But it does feel like a strategic shift. How did you process that announcement?

[E]

It's not acute. I think it's like 25 billion over the next few years, which doesn't really compete with what OpenAI and Anthropic are doing. Yeah. I guess these smaller models are going to be helpful for people running smaller use cases. So GPUs, as long as they're utilized, even locally or in the cloud, they get benefits. And. And saw the top people at Quen left and we don't know where they left to. Quinn is an amazing model. It's kind of like what Deep is what people thought Deep six should be. Quinn works well locally. Quinn kind of subsides because all the.

[A]

What's your theory on, what's your theory on where they all went? Another Chinese lab or.

[E]

I asked all the engineers when I was at gtc. No one really knew. But people, people are trying to say Nvidia should actually hire them.

[B]

Yeah.

[E]

Because the more capable open source model, Nvidia doesn't care if you're using run open source or not. They just want more AI adoption across

[B]

and Nvidia has more, probably more levers to pull if it, if it turns into a negotiation with China. Like we're tracking like the Manus story with Meta and there isn't that much that Meta can, can give to China in exchange if there's like a, hey, like let's look the other way on this particular deal. Like let this one flow through, will trade this 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. You know, it can be part of a larger discussion, which makes a lot of sense.

[E]

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 H200 orders.

[B]

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. It's already massive revenues, just an incredible growth. But what does, what is the supply side looking like? Because it feels like TSMC is not ramping Capex nearly fast enough over the next few years. And if we see another 10x increase in compute demand, we could be really constrained on the leading edge fab side. So how do you think Nvidia is going to process that?

[E]

Well, Nvidia is in the driver's seat because Jensen goes there five, six times a year and best friends at TSMC and speaks at their employee day. So they're going to get higher. They are getting a higher allocation to wafers and all that stuff.

[B]

So.

[E]

And they will benefit. But I agree with you that industry wide like Google is dying to get more TPU wafers. Sure. All the, all the hyperscalers that have ASICS are trying to get more wafer capacity. So there is going to be a AI compute shortage in the years to come, just like you said.

[B]

Yeah.

[E]

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.

[B]

Yeah. I mean, maybe there's some offtake in Asics that can potentially be fabbed somewhere else at some point. 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 an intel deal or something else. I'm not exactly sure.

[E]

But Samsung and Intel are the only ones.

[B]

Samsung and intel. Yeah.

[E]

Fabs that can possibly do it.

[B]

Yeah.

[E]

That's the bookcase on Intel.

[B]

Yes. Yeah. Is that at some point the labs and Google across TPU extra GPU capacity Nvidia the new R. There's just so many buyers of fab capacity now that you could imagine everyone coming to the table potentially in Washington D.C. or Mar a Lago since the US 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 will justify the investment for us and for Intel. So that would be a really, really good case. But again, even if the money is there, how long does it take to get to good production numbers?

[E]

I suspect Apple Nvidia are considering either intel or Samsung for their lower end stuff. Whether it be like a mid range iPhone or Nvidia side, definitely their consumer gaming GPUs. They may go back to Samsung and maybe even Intel.

[B]

Yeah, I have one more but go for it. I wanted to know how you're processing the ARM CPU announcement. It's an interesting dynamic because they're sort of 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. 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.

[E]

I think ARM is their CPU opportunities a longer term Even they said 2030, 2031. It's a longer term opportunity. I don't, I don't really expect the major hyperscalers like Amazon to switch to ARM's product offering. They have their own and same with Nvidia, they have their own ARM CPU that they're going to incorporate and sell. So it's not that big of a. I don't think Amazon or Nvidia really worry that ARM is going to take any big share. It's probably going to be on the margin for companies that can't develop their own ARM CPU the more the mid tier hyperscalers or enterprises that use these things. But I think the ARM thing is very important because it kind of confirms What? The biggest underlying thing that, that's not really consensus yet is this massive CPU shortage that we're seeing just over the last few months. We have Dell, amd, Intel CFO talked about, they're talking about three to five year locked, locked in supply contracts from hyperscalers. So this is a major trend that's going to go over the next few years. And the reason why is AI agents need more CPUs. The ARM CEO talked about four times more CPU quarter cores versus last year's kind of AI infrastructure model. So we're going to see this massive demand for CPUs that people aren't really understanding yet because AI agents, the whole thing requires orchestration tool calls, database queries, web searches, and that's all handled by the cpu.

[B]

Yeah.

[A]

Give me your bull and bear case for terrafab.

[E]

Tarafab. I'm not that optimistic. I mean it's so hard to give me the.

[D]

Give me.

[A]

Do. Do your absolute best to give me

[E]

the bull case because TSMC is so short that you know, Elon needs to find. But even then, like how's he going to buy like semicap equipment from ASML and amat? Like there's just no capacity there. So I'm not optimistic on that. And this is, this is stuff that takes decades. Chip fabs is almost like cooking. And it's not like something you could just follow, follow a manual. It's like, it's almost like cooking where it takes a lot of trial and error accumulate over decades. TSMC and even Intel. So it's not something you could just jump right in and do.

[B]

Yeah, it's somewhat harder. Yeah, it somewhat goes back to the XAI debate about like, do they need AI researchers or should everyone be an AI engineer? Like are we in a research period or a, you know, the Ilya Sutskever age of research versus the Elon Musk age of engineering. Where are we in semiconductor production? It feels very engineering, like an engineering process. But what we've seen from ASML is that and TSMC is that it does feel like there's a little bit of research and artistry to it. And the cooking analogy.

[E]

Yeah, I've been doing a lot of research in the space and it's a lot of trial and error and like cooking a recipe.

[B]

And it also feels like at least with xai, if all the researchers are in San Francisco, you can sort of just like walk across to the coffee shop, poach someone. But if the best semiconductor engineers or technicians are in Taiwan and they see it as a national urgency to bring stability to the country both economically and generally geopolitically, then you have a very different calculation. It's like, oh yeah, I could make five times as much if I left my home country to be abandoned. That's a very different calculation. And everything that I've heard about the culture at TSMC is that the folks who work there are extremely dedicated beyond the economics. They are true missionaries, not necessarily mercenaries. And so it does feel like it's even harder, harder to do like a talent raid in the leading edge fab world than even the AI world, which is extremely competitive and there are still tons of missionaries. But fab.

[A]

I guess another question I have is, would you expect Xai SpaceX at any point to get to basically just open up a shop as like a NEO cloud? Because the thing that was probably one of the biggest, least compelling aspect of the tariff app pitch was him just saying, we need all of this compute. We need to do this because we're going to be so chip constrained, we're going to be so supply constrained. But there was no explanation of where

[B]

the demand was coming from.

[A]

Where the demand was going to come from?

[B]

Is it going to come from training Tesla models? Optimus or Grok or.

[A]

Yeah, it was just very unclear.

[C]

There's a lot.

[A]

But there's even the question right now is should actually be kind of renting GPUs? I don't know, I don't know.

[B]

Renting out, GPU renting out. Because the biggest win has been Colossus infrastructures. Yeah, Colossus 2, which was built very fast.

[E]

I think Elon's pitch with the SpaceX IPO and we'll see it in the coming months, is the AI compute. It's going to be. So there's going to be so much demand over the next five, ten years that you're going to have to use these SpaceX satellites that have GPUs in them to. To serve that.

[B]

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.

[E]

What Elon did with Starlink, and that's a telecon infrastructure play. And this would be an AI AI computing.

[B]

Yeah, yeah, yeah, that fits that model. There's a world there.

[E]

I'm not going to bet against Elon. It might Just take long.

[B]

Yeah, yeah.

[A]

What about what's going on with helium? What are you tracking there? There's chatter about helium shortages potentially.

[E]

Jensen has talked about 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 risk in short term. So, so if this thing, if this Iran stuff lasts 2, 3, 4, 5 months then becomes a problem, but if it gets solved or opens up with the toll or whatever final negotiation they come up with over the next few weeks, I don't think it's going to.

[B]

Yeah, I do think that like most of these materials there are extra deposits, they're just not economical to mine. I, I don't think that all the helium exists in the Middle east that would.

[E]

It's similar to the railroad thing, just like you said.

[B]

Yeah. Where in a supply constrained scenario it becomes more economical to mine American helium.

[E]

Let me put it this way. If helium becomes an issue, we're going to have bigger problems on our hands.

[B]

Okay.

[E]

I mean there's going to be world starvation.

[B]

Let's hope not. Let's hope not. That's going to be bad.

[E]

That'll be the least of our problems if helium becomes a problem.

[B]

Take me through depreciation gate. How did you, you process that? And where do we stand now with the fear that GPUs will depreciate precipitously and H1 hundreds will be worthless in 6 to 12 months?

[E]

It's totally not a problem right now. Like Core Weave has talked about, these things are lasting five to six years and they're getting like almost 90, 95% of the pricing. So it could be potentially be a problem if the whole. If this is a bubble, I don't think it's a bubble. But if this is a bubble two, three years from now and there's a computer glut, then the stocks don't go down because there's a compute glut. But as of now it's the opposite. Like all the GPU rental prices, even for stuff that's six years old, is still being sold out and the compute demand outpacing supply is so large that this is not an issue right now.

[A]

Do you have any theories on where the next step change in token demand could come from? Because right now we're seeing it in code Genesis 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 even if AI can just one shot Beautiful financial models. It won't necessarily even make a real dent in token demand, at least compared to Cogen, because no company needs to just constantly be, you know, be generated models at the rate that let's say Gary Tan generates code. And so I'm like kind of been trying to wrap my head around where could these incremental use cases happen.

[E]

I actually think CodeGen is still just early innings. Yeah.

[A]

And I don't disagree with that.

[E]

10, 20 agents and they're kind of overseeing them. But then we have this other stuff where these models, the Mythos and OpenAI, 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 can verify drug discovery, where they verify drug molecules can do. So we're just getting started at this stuff. So you're going to see vertical AI agents on every single category. And I think think Logan's coming on. He wrote this great post on X that he says the AI agent wave is going to kind of attack this $6 trillion knowledge economy. Right. It's not just about programming aim.

[A]

They're coming for us.

[E]

Yes.

[A]

I don't think I'm actually they're attacking the key context economy and the TVPN economy.

[E]

No, I think it's like a calculator, a spreadsheet. 30, 40, 50 years ago we had 50 accountants doing the spreadsheet manually. And now after a spreadsheet came, it didn't get rid of all of knowledge work. It just enabled people to think at a higher level and get more done. And I'm very optimistic about that.

[B]

One way that you 10x token demand around a financial model without 10xing the number of financial models that you're building is having the agent go and collect 10 times as much data. And so there's a lot of situations where I mean you look at like hedge funds that want to understand the price of Walmart stock. There are hedge funds that will task satellites to take pictures of Walmart parking lots. Estimate the number of people on a day by day basis that are going into the Walmart to shop and then using that as a proxy to project revenue and then flow that through to cash flow and then flow that through to the DCF and the actual evaluation of the company. And if you think about all the different financial models and all the different businesses where you could go and say, well for this company I need to go to every single local, like I want to know the price of Squarespace. Let me go to every single page 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. And all of a sudden, like it's just one spreadsheet, it's just one number at the end of the day, but it's like a thousand times more work went into it.

[E]

Let me give you this great example. Every year I do this, the same store sales for these fast casual companies. So like Chipotle Cavill and I put out this tweet. It goes viral. A year ago, when I do it, I would have to manually go to every IR website for these six fast casual restaurants. It will take me like an hour or two. I would try to use a chatbot. They would get it wrong.

[B]

Sure.

[E]

I did it like a few weeks ago and all the chatbots got perfect. So it just saved me two, three hours of tedious manual labor. So that's only going to get better and better.

[B]

It's only going to take you. This year is the year that you do it with multiple chatbots and you fact check it yourself and then forever it's going to be just one prompt.

[E]

And it got it right. A year ago it wouldn't get right. But now in 12 minutes I put me the same store sales for these six restaurants. I put in Gemini, put in ChatGPT, just to make sure they're right. And they're right. So all the tedious labor, all the manual labor, all the data entry, the that 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 going to be taken care of by these AI agents.

[B]

I agree completely. I agree completely.

[A]

We got a lot more sound effects since the last time you joined. Last question for me, what's your outlook on Meta? It feels like the broader market right now has zero faith in meta to actually put all their AI investments to use.

[E]

I have this history with Meta is that every time it starts falling apart, I say it looks cheap and then it goes down another 30%. But nothing has changed. No one's going to replace Meta. The 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 AI chop chat bots. Their search position going future. So, like, no one's going to replace Instagram, no One's going to replace Facebook. Billions of people are still going to use those social media apps. And you know, it's every 6, 6 months to 12 months, everyone goes through this spare metacycle but their pure competitive position really hasn't changed. And you saw what happened to Sora, right? Everyone's all excited about Sora and that got.

[B]

Yeah. And there's just this world where even if 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 wasteful than Reality Labs spent, 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. 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 schedule.

[E]

Ad engine monetization, 100%.

[B]

Yeah.

[E]

The GEM model, Reality Labs, he made a waste of 70 to 80 billion dollars. He might waste 100 billions of dollars on, on these Frontier AI models. The business is good, core business that money making engine has. It's not going to be affected by this.

[B]

Yeah. Well thank you so much for taking the time to come hang out. Always a great time. Taylor, go subscribe to key context on Substack. Follow take him on social media.

[A]

First adopter join the many Benares that were the first adopters.

[B]

Yes, yes. You'll be in good company and thank you so much. We'll talk to you soon. Have a great week.

[A]

Great to see you next time.

[E]

Cheers.

[B]

Let me tell you about FIGMA agents. Meet the canvas. Your AI agents can now create and modify your FIGMA files with design system context in beta starting today. And let me tell you about graphite code review for the age of AI. Graphite helps teams on GitHub ship hybrid higher quality software faster.

[A]

So Chamath.

[B]

Yes.

[A]

He says the biggest threat to Instagram's moat is an incredible image model.

[B]

Okay.

[A]

Zephyr says Meta bottom

[B]

an incredible image model.

[A]

I mean that's basically, you're basically saying, okay, if Sora was, if the content on Sora was better, a hundred times better, would that be a real threat to Instagram? And I still am not. I'm still, I'm not convinced.

[B]

I feel like a lot of people have their network there they want to share with their friends. They have a graph there. And even though the recommendation like the content doesn't come through the graph anymore, having your friends on there to have the conversations and the comments, there's still a lot of left.

[A]

But if they could make an AI agent of you that instantly reacts to every video I send you. Killer feed it.

[B]

Killer feature. Killer feature. There's some. Yeah, 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. Welcome to the show. Logan, how you doing?

[C]

Good. Gentlemen, how are you?

[B]

We are fantastic.

[A]

It's great to see you.

[B]

I like this camera setup. This looks fantastic.

[C]

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 porn forced us into oblivion.

[B]

Three cartoon avatars was back to Market Update. Just put the investments in the bag, bro.

[C]

I know, that's exactly right. Yeah, the McDonald's bag of cash I have, that's what I'm doing these days.

[B]

But you're also writing market analysis, which I always look forward to.

[A]

Yeah. This has been consistently some of like the best content in the entire D.C. industrial complex and I have enjoyed it for many years.

[B]

It was extremely valuable during the interest rate crisis as well and also the conversations that you were having on the podcast. But it felt like a really rational reset that wasn't a total black pill, wasn't a total white pill. It was just actually like, here's some data, there are obviously some conclusions, but you can also make your own. So thank you for everything you do. Take us through the biggest findings, take us through the process that that led to this particular research report.

[C]

Yeah, it turns out there's a little bit of nuance that 75 slides give you more than 140 or 280 characters to kind of tease out in some ways. So it started probably in January. I have this process every year where I have a panic attack that we have an annual meeting coming up and I got tricked in 2020 when I joined the firm. They were like, we're going to give you this really illustrious honor that 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. And so 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 ZIRP fallout, ZERP era 20, 21, then ZIRP fallout, then 23 I think was SVB 24 maybe I got a little bit of a respite then last year was the tariffs. And so every year there's something going on that forces us to recalibrate. But this year it became pretty clear it was going to be the software sell off off and what was going on in the public markets. And so monitoring that, I sort of started from a process of talking to a bunch of smart friends in the industry about what they're thinking about and trying to probe on questions that they wanted answered. And this generally involves a lot of public investors because private investors in some ways are like fish in water where like you sort of just operate in the world around you. And so if you're doing defense, you really just focus on defense. If you're doing software, you just focus on that. If you're doing whatever health care, 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. And so I talked to a bunch of them and software and 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 2, 3, 400 times ARR in the private markets. And so sort of setting out to bridge that gap was kind of the goal.

[B]

Is it a gap or is it a gulf?

[C]

I would say it's a optimism disconnect.

[D]

Maybe.

[B]

That's a good phrase. I like that.

[C]

It is amazing. 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 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 30, 50, 100x. And if you take those two lens, it ends up with a very different place of like optimism versus cynicism, upside versus downside. You know all the questions you ask.

[B]

Yeah. So let's, let's start.

[A]

You'll appreciate this Logan. I had a portfolio company at the end of last year that is a software as a service business and in one of their updates they, they made the announcement that workflows are now called agents in the and I was like they were like this workflow stuff seems like people are not that excited about it now we're switching gears. These are now agents and if we

[C]

just do you know that Breaking Bad meme that like age. He says we had a good thing. You stupid son of a bitch.

[B]

I feel like that was, that was

[C]

like all SaaS investors over the course of the last 100% being like you M effers. You had to go mess up this like really good thing we had going on with this AI pixie dust with

[B]

a nonprofit that didn't even raise a seed round until they were multi billions. It's like we couldn't even get in early.

[C]

We had a good time.

[B]

We had a good time. So let's start with 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 just pulling the top 50 SaaS companies, sort of pure play SaaS companies and trying to answer the question like is revenue decelerating yet? Are we seeing a kink in the graph like some change in the data? And I didn't go nearly as deep as you go, but how much of this is just like narrative and anxiety about a change in changing curve to the financials versus actual data points where people are saying okay, 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.

[C]

Yeah, I mean I think Broadbuck there's two main things. One is the public market investors are fed up with stock based comp and so let's put that in a bucket. I do think venture investors and public market CEOs are, are to blame for some of the softness in the cultures and how bloated some of these businesses got. But also you have to be practical. There is a game on the field to play and you could triage and say hey, we're really going to reduce the number of employees we have and you really have to be careful there because 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 Ligora 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 there's not true profits going on. And so I think let's put that in a bucket though that's aside the other thing, the far more interesting conversation to have is our financials deteriorating. And the answer is really no right now. Now it's more of this long term existential question of what terminal value of these businesses are worth. And it used to be, hey, 85 to 90% of a business's value was tied up in the period beyond the dcf, 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, 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. And so I think 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 going to be able to survive this?

[A]

I think, yeah.

[B]

Is there, is there a world where we move into a regime where we're talking about not revenue multiples but like, like EBITDA multiples for these software companies. So looking at a company that was 3 billion market cap, 100 million of EBITDA, very stable the last five years. And, and one, one one investor was making the case like oh, AI winner. And I was like I don't see that. But also I don't see these customers churning. I just see them doing AI stuff on top of this particular company because they're more infrastructure layer, more data storage, that type of thing. And so I was like, I think you can count on 100 million EBITDA and probably cash flow for 10 years, 20 years, but do you want to be paying 30 times that? Is that enough. And I don't know if that's the rational framework.

[A]

Nobody, nobody knows anything. You have to apply a big discount. One of the slides I loved was the slide on newspaper earnings. Oh yeah, take a slide 22. You said newspaper earnings.

[C]

Yeah, I mean it is interesting. It's funny, I actually have that up on my, 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 5 years post Internet while their value collapsed. And so everyone saw the writing on the wall of where this was headed but it took a while for that to actually come through and show up in the, in the actual financials themselves. So John, I guess your question on it like I, I use revenue as a proxy and maybe it's like to, to flip of a nomenclature we really should be talking about like free cash flow with deductions for stock based cop or whatever. But like all these things are growing at different rates and that's sort of been the historical lingua franca that, that I kind of used.

[B]

But you're right, it makes it impossible to comp to the private markets because no one's generating any, any.

[E]

That's right.

[B]

So it's a useless comp. But I'm just thinking like if public markets investor and I'm just choosing between Google, Apple and then some small cap mid cap software company, I probably want to have an EBITDA hat on or something like it to sort of understand just my rate of return which is going to be a lot less like oh, all of a sudden they're growing at some unpredictable rates. So the DCF gets crazy and I'm paying some high rate. Yeah.

[C]

And this might be a little simple for some of your listeners and maybe helpful for others but like at the end of the day a business is valued at the current value of all future free cash flows and so discounted back to today's dollars. And so the reason software businesses have been so good is you have annuity streams going out into the future and you're able to with some level of precision figure out what the discount back the value as in the future. And so that was a great thing for particularly when we had retention rates at 95, 96, 97% net retention rates at 120, 130, 140. You could really do very little and you could discount back those dollars with pretty good certainty of Figuring out what those are worth. Today it was almost bond like and I think this equity made a bunch of money saying actually this is better than a debt instrument. This actually sits on top of the debt in terms of your vendors are going to get paid before your debt providers will because the business needs to keep going. Now I think we're seeing a little bit of cracks in the armor and I think your analogy is a good one where it's actually not. I worry less about the like the churn risk. Are people really going to churn off of Salesforce or Workday or ServiceNow or whatever it is? Like maybe. But I worry less about that. I worry more about the value abstraction that is captured on top of it. And if the AI dollars which we we found in one of the reports, AI dollars this year, 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 going to go to near zero. And if your growth rate goes to near zero then it's worth something, but it's not worth. You're right like the 30 times almost

[B]

like a real estate investment. It's like what's your cap rate? You know, like if I'm giving you 100 bucks, am I getting 5 bucks this year, 10 bucks this year? Because there's a lot of other options. And then yeah, the other thing historically with, with software has been just low interest rates so. Oh, oh, that cash flow is coming in 20 years. Fine. Like it's basically the same as today if it's zero interest rates.

[A]

Yeah, exactly.

[B]

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?

[A]

I'm interested in, 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, et cetera. Was anyone like licking their chops being like this is the greatest buying opportunity like actually had some well thought out thesis around how is like Thoma Bravo. Some of their slides leaked from their LP summit and they obviously are in the position where they have no choice but they can't be bearish now they have to create the 4D chess of how this is a huge accelerant to their businesses.

[C]

Yeah, I think 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 going to figure out the agent opportunity or the opportunity because it's certainly not being priced in, in a material way. And the incumbent vendors are going to get every chance from their existing customers to get this right. And so I think that's the, if you were to paint the optimistic lens about, you know, Toma got dragged a little bit bit for some of their, you know, talking their own book. But I actually think some of the slides that people were dunking on were it's true fundamentally that like hey, your incumbent vendors are going to get shot 1, 2, 3 and getting it right. I think the problem, and at least what we're seeing in the private markets is that the culture of building these AI companies is just so different than the culture a building what the historical software company looked like. And you guys, I think, I think you know, I was an investor in Ramp and, and, and the stuff that they did like don't get enough credit.

[B]

It is my cross, Logan in particular, he's, I know he never takes victory laps. That's the thing.

[C]

It's, it'll take it, we'll take it for. I'm unknown. I was a silent investor for a long time and so I'm glad to come out of the closet as a ramp investor here for you guys. But one of the things,

[B]

one of

[C]

the 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 would react, react to it. And that was very different than the way that I learned the companies I invested in 2014, 15, 16 and how they built products was they had a very tight product roadmap. They communicated with their customers. They had it over a 3, 612 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, then take a break. 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. 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 like building product. And that's one example and we have a slide in there of like all the different examples, but like it's sort of been flipped on its head. And so I actually don't worry from a, is it possible standpoint for the, for the big public companies to do this? I think it's totally possible and I think some of them will figure it out, but the vast majority are going to have to totally change their culture that they built over the last 10, 15, 20 years. And that's really painful. And, and I think that's where they're going to end up falling down more than anything else.

[B]

Yeah, this is fascinating. I'm like sort of an earlyish adopter I think, and I recently wanted to know like how much have we spent on Apple products? And I was able to get that answer in like ramps AI mode basically and I didn't need to like export any data. But then I wanted to know how many, how many what I've spent with Apple over the last year on my personal financial. And for that I had to vibe code something that exported all the data and did it manually. And so the question of like you have a system of record, there's going to be some new feature, where's 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 entail as old as time.

[C]

Yeah, it's abstracting the value on top of it, which is 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 ChatGPT in a meaningful way. And I think that same thing's going to play out within the enterprise as well. And it's not just going to be retrieval of information, it's going to be actually taking actions. And so now I don't totally care. I'm sure you didn't totally care if that information was coming from unreal ramp side if it was by bill pay or credit card. And ultimately once you vibe coded that application, you didn't care if that information ended up coming from a credit card statement or an email receipt or whatever it was.

[B]

In fact, I wanted to unify credit card and checks and bank transactions as well. And I want to put all of that in one bucket. And that's something that it's not a feature in my bank right now, but it will be if they move quickly. But it also already was a year ago in ramp. And so it's just like the pace of play is still on the order of years in a very interesting way. And yeah, definitely encourage all of those companies have opportunities, but they have to go win them. No one just gets granted monopoly on the new capabilities that emerge on top of their platform.

[A]

Sorry Jordy. In the deck you talk about, 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. 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 private markets like just based on the number of companies coming out every single day that seem to all be doing kind of variations on like the, you know, the AI cmo.

[B]

Right.

[A]

And I'm like maybe, maybe that ends up being a big category, like a

[B]

sort of niche vertical player. AI will be like at a 50 cap or a seed.

[A]

Yeah, I guess my point is like AI maybe isn't a bubble, but that does not mean we're not experiencing like a massive bubble in the kind of venture world right now.

[C]

Yeah, I mean it sort of goes to like where value is going to 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 and airports or whatever. B2B sales and all that stuff. Like there were second derivative things that were actually far more impactful. And you're right, like it's possible. And this is what I've told our LPs that I've asked is like, I think, I think we're operating in a world in which our mortality rate of companies we invest in is going to be higher than it's been in the past. It just like it is even at the stage we're investing in. I think we're going to see a lot more businesses die. I hope we will also invest in things with a lot more upside. And so we'll end up with, you know, hopefully things that could be hundreds of billions of dollars, which used to be not in the realm of possibility. And so I do think we're entering this extreme period of uncertainty. And the only thing I've really been able to come back to in all this is because you're right, these categories end up so crowded and they end up very dynamic in terms of how the category evolves, what the product surface area ends up looking like, all that. And so in some ways we're back to investing in teams and investing in like the wedge or the general space that they're operating in and then hoping that those doors open or that that C parts and they're able to run through that in a meaningful way. But it's, it's very possible that the model providers end up soaking up a ton of the equity value. And so just because there will be a CMO in the AI world that a company starts, like, it doesn't mean that any of these companies will be the one to capture that value. And actually it'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.

[A]

Yeah. It's been interesting to look at these businesses ramping revenue so quickly and have real customer love and pull from the market and still have that question in the back of your head of like, does this eventually just get zeroed out? Yeah, that's the one, people.

[F]

Sorry, go ahead.

[A]

Yeah, for me, the only real comp I have, because I came kind of online in my career in 2018, so I got to see the ZIRP era very closely. But I remember with OpenSea and the NFT boom, that was, I remember the way that they ramped revenue. Even the thing that made I think a lot of otherwise great funds pile money into it at what ended up being the top is there was. You could kind of just say like, okay, even if revenue drops by 90% and this doesn't end up being this mainstream opportunity, there's still like a business here and maybe you can just own the category. But then revenue ended up dropping 99% or something. That still stays in the back of my mind that was more of a demand issue versus new competition from an adjacent player. But still.

[B]

Are there any previous booms that you do like as comparison points, if not dot com? Do you like railroads, Electricity? Yeah, electricity. What do you like?

[C]

That's a good question. I haven't actually thought of the right analog for 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. But I think there's elements of the shifting balance of worker dynamic and where people are actually going to totally the leverage themselves in that way going forward. And wealth, 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 populist rhetoric out there. And so I think this is more of a, I think revolution than a techno. I mean it's both a revolution and a technological shift in some ways. And so I think like the car or the airplane or the railroad or whatever, like that didn't fundamentally shift the balance of an entire workforce in some ways the way that I think this has the chance of doing. And so that's the one I kind of come back to. But it's a good question. I'll think more about it.

[B]

How are you thinking about capability, overhang, diffusion,

[A]

this copability Overhang?

[B]

Yeah, the debate about like the models are good and they're getting better really, really quickly, but there's just like teams in companies where they're like, yeah, I'm actually fine doing my spreadsheet job and I've heard this direct quote, I gotta check that AI thing out. Oh yeah, I gotta check that out.

[C]

When did Jordy say that to you?

[A]

Was that recent or was that.

[C]

I think it is interesting. I mean that's where you're seeing a lot of the this like FDE Palantir era where bridging the last mile is really, really hard. And I think we assume that that like if we build it they will come in some ways, but it's obviously that's not the case. AI to most people, I Guarantee if you took whatever, I don't know, 350 or 300 million Americans or something and you asked them like, name an AI company. I would guess, yes, I'm making this up, but like 25% wouldn't actually be able to name an AI company and like 70% would say, oh, that's that ChatGPT thing or something.

[A]

I talked with a guy, I talked with a guy and said like, what, what AI? Are you using any AI products? And he was like, nope. And then I was like, what about ChatGPT? And he's like, I use that every day, I love it.

[B]

But he just doesn't think about it. It's just a website. Like we've been to websites before, you

[C]

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 going to need to productize that, are going to productize that. And so they end up building things that they throw out six months later all the time.

[B]

Interesting.

[C]

And I think, I think that's kind of true on the go to market or like education side as well, where a of lot, 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 and 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 like, are we in a bubble structurally at a big picture, I sort of reject that notion because of both the demand and when people, 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 make it out to be when we're just, you know, living in our techno utopia.

[B]

That's a good point.

[A]

If you can call X a techno the techno nightmare. Except in Japan, and Japan is Japan. They love it, apparently. I did want to ask about buy versus build economics. You talked about how you could just buy.

[C]

That's the one that people have been asking about by the way, today.

[B]

Yeah, people like that.

[A]

Yeah, so funny. So, so Logan makes a point. You 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 million a year and then like other kind of random unexpected costs. Sure. A lot of people, anybody that's pushing back on this, just tell them like, okay, build me Slack. Build me.

[C]

It's a really funny thing where I just think it's sort of the 8020 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.

[A]

Look, you can send messages, you can create a group and then it's like,

[C]

oh, I vibe coded this thing and it does all of what Slack needs to do. But then there's not even even to

[A]

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.

[B]

Yeah.

[C]

And so like, let's say, 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 in the SSO and the search and the file sharing and the, you know, whatever the admin controls and compliance and all that stuff.

[A]

Logs.

[C]

Yeah, the emojis, the GIF embeds, all, all those things. Like let's say you do all that. Was that whatever that costs, like what is the opportunity cost that you spent all this time doing that rather than like focusing on whatever it is your core business is? And so actually like I, we did the math here and it's 2 million versus 220k or whatever. Like let's say it's the same or let's say it's cheaper. Like is is saving, you know, know 40 grand. Let's say it's 180 versus 220 and

[A]

it actually has to be significantly cheaper.

[B]

But also, I mean, I talked to a friend who runs a company and just about AI stuff and I was like, oh yeah, like you should probably, you know, be aware of this stuff. But what percent of revenue is going towards like software broadly? Like what's your IT spending is like less than 1%. And so it's like, yes, like you could take something that costs $1,000 down to $200. Like maybe you take that, but not if it's a headache at all because 99% of the time you want to be with your actual customer suppliers because it's completely different business. And so that was the point someone

[C]

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 year to like 60% a year and not having to pay incremental recruiter or staffer fees to get people on. Like the difference of the Slack budget and saving 40k, I guarantee, does not like resonate at all. And Slack was a simple example because it resonates with people. But I think it's true across the board. So I was trying to think of like what a good bet would be with someone to try to like come up with. It's a very hard thing to figure out of like what the right framework of thinking about this is because I love just codifying bets with people and being like, you know, okay, let's, let's wager some money on what this is. And I couldn't come up with a good one. So if you, or if anyone listening can come up with a good bet on this, I would love to place whatever a significant sum of money on side of it.

[A]

It's funny, it's funny to think about the company building Slack in house and they're like throwing time, they're getting 10 people on a call like, hey, like we need to meet and talk about some up. 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.

[B]

Well, the deep irony here is that Slack was an internal tool for Game Studio. Like it was actually like the, we need to build our own thing because we communicate so frequently. And then it became, and there's a

[C]

historical analogy by the way of this that I didn't include in the deck because I really like Drew Houston from Dropbox, but like they built their own data centers and like, I don't know like if that was a good cost decision from them but like for, from a focused decision, should they have just used AWS and you know, or GCP or, or one of the other. I don't know. I don't know the answer to that. And I didn't want to like put him on blast and actually get into the debate because I like him quite a bit. But like, I don't know if that's like the right decision for them and that they were even like the furthest. You know, they're like a tech company that that was their business able to decrease costs and who knows what the opportunity cost of incremental products, products or Mindshare or whatever it was going and Doing that.

[B]

Yeah. No, that makes a ton of sense.

[A]

Last question. Did the current AI suite make making your annual report significantly easier or was it still handcrafted? Handcrafted.

[C]

It's an artisanal craft of this, but I will say it is interesting doing this deck every year. It does serve as a snapshot of what the model capabilities are and how much progress it's been made. And so I think if I go back like two years ago, that version of it, I could wordsmith like my talking points that I was actually talking when I get up there in front of the LPs and do it. And last year it was actually a decent. I could ping pong some ideas here, I would guess. I don't know if there's 68 slides or something. I would guess 75% of them AI had some hand in either helping visually lay it out out in some way, writing some of the text, maybe coming up with some of the analogies. And that is such a step function change versus where it was 12 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 15 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 works with me on this, we're very much appreciative of where the model capabilities are going. Because I think if it made my life a little bit easier, it definitely made their life a lot easier.

[F]

Totally.

[B]

Is that alpha for up and coming venture capitalists? 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.

[A]

I would just say have a non traditional background, maybe grow up.

[B]

Well, that's the thing.

[A]

Palo Alto area. Go to Stanford.

[B]

Stanford.

[C]

It's actually an interesting thing.

[G]

So.

[C]

So if you guys have a minute, I can riff for a second on this. But like, historically. So we've hired people out of investment banks, largely speaking. And so why do we do that? Well, we hire people out of investment banks because it's an expressed interest in finance and technology. Okay, that's great. Two is they have the model training of like, what, you know, the cap tables and projections and all that stuff. Three is there's a high pain tolerance and willingness to grind and do the extra thing. And then four is it's a referential Network, 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 it gives us a qualified pool of people to pick in. The thing that investment banking didn't have was you're very much like, if you ended up in investment bank 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 went to a high school, got good grades, got into a good college, did interviews, got a good job. Then at your investment banking job, you're staffed with 90% of your day is pre filled by someone else. And so it's like, okay, well if I work hard and I stay late and I do this pitchbook line, 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 or as well as most of the people on our team. And the remedial tasks are getting the water level keeps going up when we hire people in. Now we've always had to train on the agency thing and it's a little bit of rewiring your brain where hey, my day used to be 90% filled by the staff and now you're telling me just go figure out what's a good company, like where do I even start in that. And so in some ways, like investment banking is actually a bad pool of how it's wired and prepared people for this world. Now historically it always was, but we were willing to forego the agency because we got the modeling capabilities 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 any agency there. Now increasingly like the models are getting so good that agency might be the only thing that matters. And so like are you able to find, differentiate.

[A]

We're actually working on an internal model for agency at yeah, right along the. We've had a huge unlock, we've cracked taste. Now it's yeah, now it's, it's so and so.

[C]

So that's the thing that we now are trying to figure out. Like where do you find pockets of people who still want to do 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.

[B]

So what I'm hearing is that you're pulling up the ladder behind you.

[C]

That's right.

[B]

That's right.

[C]

Any door. I always say with 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 when I was in. If I was in your seat? Because I can tell you the doors I walk through, but those doors aren't just shut. They're like shut. They're cemented over. They've been fortified. You're not doing what I did. I lucked through this path.

[B]

Thank you for joining us. Great to have a great time hanging out. We'll talk to you soon.

[A]

Just with all the AI progress, try to ship one of these a week.

[B]

You got it. Have a great rest of your day. We'll talk to you soon. Let me tell you about Phantom cash. Fund your wallet without exchanges or middlemen and spend with the phantom card and then head over to public.com investing for those who take it seriously. Stocks, options, bonds, crypto, treasuries and more with great customer service. And without further ado, we have the founder and designer of Grace Granola, Sam Stevenson. Welcome to the show. Sam, how are you doing?

[A]

What's going on?

[F]

I'm good, I'm good. How are you doing?

[B]

Congratulations. 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.

[F]

So we have raised a $125 million Series C from.

[B]

Congratulations.

[A]

I didn't hear it over the sound of the gong. You said Index Ventures.

[F]

Index Ventures. Index Ventures. And. And with KP participating as well.

[B]

Fantastic.

[F]

Very lucky.

[B]

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.

[F]

Yeah, I think it's been. I mean, all the above. Like we've been talking to these guys for. For a while. They've been fans of the product, I think, as all of our investors have. They've all used the product a bunch before. We've got to talking about investing and then, yeah, growth has been good and continuing and I think it's the combination of that and then I feel like the environment is waking up to the power of having all of the context of what's happening in your meetings in a company know like I think like everybody adopting MCP is like making it apparent that you can like if you have the right context about what's happening in the company, you can do that to power so much of what's happening in your company. And I think we're just well positioned as like that that context gatherer that a company can take advantage of.

[A]

Yeah. So my, my something I've been thinking about with this category is why do you think the. Why do you think the last have not built a product in this space? I'm sure there's a number of reasons but I'm sure they would generally love the context that you're gathering so that their agents could actually leverage it directly. And so explain why you guys have had kind of just open, not to say open but there's certainly competitive. But why have you guys been able to do market then run away Image

[F]

gen. Yeah, yeah, I mean yeah, I'm sure they are working on it. OpenAI had a stab at it last year. They had launched like a longer running record mode thing which I think was aimed at this. But like I think it's a few things. Like I think we're basically like people use us for meetings, right? Which is like it's a big term for a startup like us, but it's also like only a slice of people's life. And if you're designing a super open ended general purpose chatbot like ChatGPT, I think they're probably questioning does this make sense or should we be going for always on recording of everything and anything less is not good enough. I think that's probably part of it. The other thing is, I mean we found building granola that you can build a granola clone super easily in a weekend. You could build a thing that transcribes your meetings and gets you a summary. And all the work is in understanding all of the social nuance of who are these people in the meeting, why are they meeting, what's this meeting about? And therefore what notes do you want out of it? What are the action items you should care about but just kind of all the work behind the scenes to actually make this thing fit into your life in a way the way you'll use it and find the notes useful is a bunch of work. And yeah, we use the latest and greatest models so you've still got to go and do that work on top of that at least today.

[A]

Yeah, yeah, it makes total sense. What kind of progress are you guys make? Like what's the Most kind of like sci fi element of, of the pitch for this last round. Like are you imagining a future where the only thing that humans do is just kind of meet and talk about what should be done and then make a decision and then machines ultimately carry out all the work. Like, like how, how far are you kind of like taking out the, how far out are you kind of looking?

[F]

I mean I can see that like yeah, I can see that someone being true. I do think like, I mean we do it internally in the company. You know, we'll meet and talk about a thing and then go ask Granola to write a brief that we either go then hand to a coding agent or we use it as the material to write a job description or a blog post or whatever. Like the conversations are like, like incredibly good input for a lot of the work that you end up needing to do at a company. I think the more kind of the most near term but sci fi things that we see is if you want a pulse on what's happening with any project or any group of people in the company going and looking and asking Granola what's happening with this, this project is easy and incredibly insightful. And I think that's essentially because transcripts are just such a good up to date record of what's happening in a company. So much more so than, I don't know, a notion doc or a Google Doc that someone had to sit down and write without making any effort. You have an up to date picture of what's happening in the company and I think that's just going to be useful to a lot of people in so many ways.

[B]

What does diffusion look like inside a large company? Like how much training, education, messaging you have to do. I'm sure you have playbooks for this, but how do you. Because once you land, I imagine the next step is expand. What does that look like for Granola?

[F]

All word of mouth pretty much at the moment. Like for most companies we, we focused so much on just making it a good product for the individual when we started that still the majority of our growth is patient zero. Finds it at a company and then tells their friends about it because they love it so much and we just go on from there. We're working on a bunch of team facing features that 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 Granola and kind of unlock the power of sharing all that context as the transcripts together. But for the most part it's still just word of mouth. People love it and they share that with each other.

[B]

Talk about the end of year wrapped campaign. I've heard fantastic reviews for it.

[F]

That was such a delight to sit out in the world.

[B]

Explain it for those who did not receive one or followed the story and then tell me about it.

[F]

Yeah, so we did a spin on Spotify Wrapped, as many companies do, which for us was Granola Crunched. The basic thesis was like granola, if you've used granola, Some of our users have used granola for thousands of meetings over the last year. And if you look inside those meetings and across over a year, 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 hit a button and generate a Spotify rap style report about their year. It was things like, who's your partner in crime? What's your favorite catchphrase? What's like, what are, what are some of the smartest things you said? What are some of the dumbest things you said that you know, that kind of thing. And it was like, you know, mostly fun. There's some things that could hit pretty hard. Like I remember mine was like kind of, I felt kind of uneasy sharing it with other people because it felt,

[B]

I've heard that from a number of people. They've been like, it was scarily accurate and I didn't want to share with them rest of my team because it really understood.

[A]

You said nothing from my end. Thanks 7,000 times.

[B]

That's great.

[A]

Okay, so we have this buddy who's, who's built a massive company in a super regulated industry and had been through, ultimately had a huge exit, but has been through kind of lawsuits and discovery along the way. And so he's just absolutely heavy, hates every product in this category. He's like, I don't care how useful it is, it's not worth, you know, someday having like, you know, basically line by line, live kind of transcript of every meeting that you've had at a company. What are the. I'm sure you guys are aware of, you know, some of these more like sensitive use cases, like what kind of fixes, like what are you doing at the product level for people that, that don't want every conversation at their company.

[B]

They sell saunas. So if you want to have a meeting that's off the record, you go into your company sauna and then nothing can record you. There's no recording devices. This is Lindy, go to the bathhouse,

[A]

maybe check for any product rolls.

[B]

You got a wire on you, you take off anyway.

[A]

Sam?

[F]

Yeah, yeah, yeah. I mean, I think like, this is like a really tricky path for us to walk and like it's like so important for us to be doing what we think is right at every step of the way. I think we have to juggle. I think tools like this are kind of, they will be somewhat inevitable in a work context. I think talking about the personal, always on recording type things is totally different. But in a work context there's just so much value in having transcribed meetings and therefore being able to use that conversation data for stuff. So I think that's kind of inevitable. And the question is, how do we kind of make that okay for people in the meantime? And I think some things we've observed are for companies that use granola, they basically just get comfortable with the idea that we're going to make it a thing that we use granola internally. And that's the default. You should just assume that's happening, happening and you can know it. Like it's okay to opt out and say you don't want to use it, but companies get comfortable with that very easily. We find then the external question is a question of following the laws in your state. And like granola, we make that clear to you. But it's ultimately, it's a tool and it's up to you to follow the rules on it.

[A]

But I meant more even on data return tension. Right. So like if a company, there are plenty of meetings that are just not that important. But if that was pulled in discovery at some point down the road, it could be unnecessarily damaging. Now the bull case for this is that whoever's suing the company and like wants that discovery actually has more. Like they're, they're more able to make an effective case. Yeah, but like, yeah, I was asking more on the.

[B]

Is there a referral link for companies that I'm planning to sue?

[F]

We have this from companies in all directions. Like some companies are like real. Like this is an opportunity for them to have things on record. And so they. Yeah, yeah, but plenty go the other way, right. Where they want everything like off the record and deleted immediately. We've ended up building a bunch of retention controls so you can do this either way. Some companies will set transcripts to self destruct after 24 hours, so there's no more record of those. And you just get left with the notes. And yeah, I think I'm a big fan of that. I feel like it's not in our interest to have on the record recordings of every thing that's happened. Like, all Granola needs is the kind of main notes of what was talked about.

[B]

Yeah, yeah, yeah, that makes sense.

[F]

Like a healthy level of abstraction is good for everybody there, I think.

[B]

Last question. Can you tell me about the brand? Because this could have been called like Panopticon. It could have been black background steel, silver. You know, it could have been very different branding wise, but it's granola. It's crunchy there, there's a, you know, this, this like green color that you've picked. Like, it's clearly intentional. What are you, what are you thinking with the brand?

[F]

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 note takers 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. And so we really just wanted Granola always to feel personal and like it's yours and that the more you use it, the more it feels like your space. And all the branding is like downstream of that. Like the name, the colors, the kind of messy, like organic feeling textures and stuff. Like it's all meant to communicate that this is like your thing. This is not. This is not your company's thing. This is your thing.

[B]

Love it. Well, thank you so much for coming on during a big day and breaking it down. Great to meet us. Very exciting progress.

[A]

Fantastic progress.

[B]

Talk to you soon.

[D]

Thanks.

[B]

Have a good rest of your day

[A]

hanging Sam, we'll talk to you soon.

[B]

Bye. Let me tell you about Vibe Co, where D2C brands, B2B startups and AI companies advertise on streaming TV, pick channels, target audiences and measure sales, just like on Metta. And let me also tell you about Gusto, the unified platform for payroll, benefits and hr built to evolve with modern small and medium sized businesses. And without further ado, let's bring in Ben from Polcia.

[A]

What's going on?

[B]

How are you doing, Ben?

[H]

Guys, how are you?

[B]

Welcome to the show. Introduce yourself. Since it's the first time on the show, tell us what you do.

[H]

Yeah, my name is Ben. I run a platform called Polcia. It's an AI that builds and runs companies autonomously. You give it an idea and it's going to go about building the product, running the marketing, running ads, doing support, and all of the things that a founder would do to start a company and grow it.

[B]

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.

[H]

Of course, I mean, the way to think about it is, you know, I spent like a lot of the past 12 months spending 12 to 16 hours a day using AI, using cloud code, using codecs, and building my companies with it. And the idea is that the fundamental models are super powerful. And I pretty much think that AGI is here at this point. The models are super intelligent and they are fluent at using any tools. But I think the trick is knowing how to configure them to give them the right tools, the right orchestration, the right series of tools to get to an outcome. Outcome. Right. So for example, one of our agents on Pulsia can run meta ads campaigns.

[B]

Sure.

[H]

But to do that, there's a lot of steps that are needed.

[A]

Right.

[H]

It's like creating the creative, you know, using maybe an AI, an AI generation model.

[B]

And different labs are good at different things. You know, Nano Banana is great and Codex is great and you know, there's writing models and there's all sorts of different things. So you're choosing those and rerouting those. How do I think about it in terms of an actual payment flow? Is there a world where I give you a credit card or a bank account and then you already have the integration set up? So I don't need to go set up an AWS instance or I don't need to go set up a meta ads campaign. And you can just kind of say, hey, we're running $100 test campaign, we're gonna withdraw $100. We think we're gonna bring back 200. Okay, we did, kid. Now I need a thousand.

[H]

Exactly. I mean, if you think about it, agents are essentially AI humans that can act on the economy. And today, obviously, if an agent, if a thousand agents go on meta to create accounts, meta will say, no, you need to verify your identity and all this stuff. And so there's a first layer of infrastructure to build that we've built at Pulsia which is how do you make partnership with those platforms for them to understand that it's an agency and working on behalf of a human for a certain task and to sort of like have all that set up ready. And as you said today we abstracted it quite a bit where you pay a subscription and you get sort of like one task every night of your agent doing work for you and then you can do various types of tasks. But in the future, as you said if you want to open a bakery in New York and you have this idea there's going to be a lot of orchestration to buy the real estate to get to hire staff, manage them all the fulfillment. And an AI could totally do this. But you probably will have to say Pulsia will tell you you got to deposit 100k on an account because we're going to have to do a deposit, we're going to have to pay the Realtor, we're going to have to hire staff. And that's something that what POLCIA is trying to do is really give access to all the best practices of being entrepreneur to anyone. Was an idea and and wants to fund it and wants to try it and obviously it's going to be a much lower cost than what you can do today.

[B]

Yeah.

[A]

So policy has ramped revenue super quickly. I feel like every time I see you guys the ARR has gone up. But what is actually give us an example of automated companies that are working on the platform. Like individual entrepreneurs that signed up.

[B]

Yeah. What are they building?

[A]

Yeah. What are they actually building? What are they selling?

[B]

Yeah.

[H]

So there's like an entrepreneur who's building a service to create ads from a script autonomously using different APIs and reselling that to people and has a bunch of customers that are paying. You have another person who's building an 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 Paul sort of like as a, as an AI team that can build a landing page for them, create leads, sort of like 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 that you get and it's, you know, it's pretty affordable. It's like $49 a month to try it for a month. And so you get a lot of people with a lot of ideas.

[B]

Yeah, it Feels like the low code, no code like boom all over again, where like there were low code, no code products at the hyperscalers and GCP and aws, but there were still platforms that did a little bit more and became like low code, some no code. And you're seeing the same continuum of how much do you want the platform to help you before you actually open up the terminal yourself?

[A]

Does the human matter a lot still?

[B]

Yeah.

[A]

If I just go on there and I pretend to be like my 10 year old self, am I going to print or am I going to be cooked? So,

[H]

so I mean first of all, this platform is 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 marketing side to automate more of trying to get customers, but also bringing on maybe people with ODF influence that can bring on their audience and sell them services. But to answer your question about how much the human is needed, I think that as long as 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 there's going to be an abundance of new services and goods being sold all over the place because. Because all those AI tools are augmenting people to build faster, better, you need humans for the taste. So the way I explain it is you get the 80% 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 you would need to hire people for that. And today with tools like Pulsia, they can do most of the work. However, the 20%, which is taste, which is branding, which is like marketing, trying to market in certain ways, understanding how to position your product, maybe having an audience to sell to. However small it is, if you 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 10, 20, 30 paying customers and I start doing income and today they're selling merch and tomorrow they can sell real services that may be more sophisticated. So that's sort of the way I look at it. There's a world in the future and where I'm going to introduce services where you can completely autonomously let the agent run wild, obviously, because you don't have to give it feedback like it will every day, every night, wake up and do work. And I'm not going to choose ways for you to let it run 10 times a day. Right. If you pay to compute.

[E]

Right.

[H]

And I'm sure that would work. It's just that that becomes like you need to have a very tight feedback loop on 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 a human with a lot of capital can actually start building a lot of money. Printing businesses is. 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 want to give that opportunity to the 99%, the people that think that AI is chatgpt. And that's pretty much it. And if we can give them the tools to be economic actors in this new era, I think we will hold benefit and it will be a more just sort of like society.

[B]

Okay, last question. We have to ask you about the name. You rattled a lot of people up because it spells AI Slop backwards. Is that intentional? Is that a joke? What's the name?

[H]

I mean, it started as a. Not as a joke. It was like my lawyer asked me to come up with the name for the ink when I started the company. And I was on my couch and I was like, oh, I could name it like, you know, polci. I slap in reverse. That's a good name because it doesn't

[A]

really matter the attention. So it was intentional.

[H]

It was intentional.

[A]

That's amazing. I thought it was like. I thought it was by. I thought it was.

[B]

No, no.

[H]

But it was not intentional to. I decided to use it as the product name because, you know, I started the company like in April and I built the product in November. And I was like, that's kind of cool, actually. It's very. And I will make people talk, so. And it did.

[B]

Well, thank you so much for coming on the show and breaking it down for us. Have a great rest of your day.

[A]

Yeah.

[B]

Good to meet you and we'll talk to you soon. Bye. Let me tell you about MongoDB. What's the only thing faster than the AI market your business on MongoDB? Don't just build. I own the data platform that powers it. And let me also tell you about Fine AI, the number one agent for customer service. If you want AI to handle your customer support, go to Fine.

[A]

I love to sit in on that pitch meeting the we're building an infinite money glitch. 49amonth.

[B]

I mean, I don't know, like there, there's a world, there's, you know, Teespring was, you 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 Fred Adcock in the restroom waiting room. Let's bring him into the TV Penultra. How are you doing guys? Good to see you again. Good to see you again, Mac. Been far too long, but since the last time we talked, you launched a new company. So break it down for us.

[G]

Oh, Hark.

[B]

Yes.

[G]

Yeah, let me, I want to know about that. All right, well, I mean, I guess the summary here is I've been working for the last three years on, I think maybe one of the hardest AI problems in the world. Getting 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. Like the different language models. And to be honest, I think they're just incredibly dumb. Like I, they don't remember anything about me. It's not very personal. 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 like, I think it should feel very much like a sci fi movie. This should feel like Jarvis that can like really understand you. Very personalize use tools well. So about seven months ago I started a new AI lab called Hark and we want to build really advanced personalized intelligence in order to get there. We think there are some fundamental gaps remaining in the models. So we basically have a large focus on trying to basically build new multimodal models. And the second thing is we're interacting with AI today through 20 year old computer like my phone and like laptop. These are all decades old and we feel very strongly that there's like a next generation of AI devices that need to be like, need to be built 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, abeder, started about four months ago, previously led design for MacBook, MacBook Air, iPhone 1316, 17 was keynote for iPhone 17 Air about five months ago. So ABS is here with a killer team on the hardware side and we're designing next generation interfaces for the models that we're working on here.

[A]

Is it the interface that you think is the issue or do you need more compute locally?

[G]

I think there's some big gaps in the model side. I think there's twofold. I think there's some large gaps remaining on the model development side that we want to try to close. And I think secondly there's like, I think just the interface of how we're using traditional computers right now to interface. This AI is extremely broken. We think both need to be fixed to have like a really killer, 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, 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. 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. EQ and naturalness are not great. So, so we're kind of taking this holistic approach to this problem and saying we have to work on the models and we have to fix the interface issue here today.

[A]

What is the hiring market right now for all this talent? Because you're basically going up against Apple, OpenAI Quad, you got demos, you're going up against, you've already bit off a lot obviously with figure and we can move over and get the update there. But I'm just so curious. When you're recruiting talent for Hark, I have to imagine any of the people that you're hiring, if you want to hire them, they probably have the opportunity to work at these other companies. So what's working on that side?

[G]

I think the summary is all the other companies are kind of boring. They're all doing the same thing. They like, they're like all copying each other. We've like headed certain direction over the last three years. I think that direction is somewhat saturating to work on vision understanding, to working on models that can go and interact with the world and get that interaction data. We think these areas are especially important to push the boundaries and get the AGI this AGI feeling of highly multimodal scenarios. So we're finding a like, like from a, from a hiring perspective or being extremely competitive. We've Brought on now over 50 people into the team, about 2/3 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. The space is just completely lit up like I've never seen like it before. You know, I've like hired people across all areas of robotics and AI and software, software and hardware. Just like this is, 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 pre training data mix. All of this is just like very tough. So some of these spaces are just new like computer using agents that can really reason really well in pixel space. Like this is just happening now. So there's not a lot of good precedent for how to go out and build these systems.

[A]

But why not? What was the decision making process around doing this externally? Because I feel like a lot of the capabilities that you want to build with Hark, like I'm assuming you'll want to integrate into Figure. If Figure is going to be a robot that can add value to my day to day life, you know, where, where is the, where's the overlap and why, why build it externally?

[G]

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 like common sense reasoning. A lot of the AI focus we have around Figure is basically how do we predict physics around things. I grab and touch and move through the world. At Hark we have like a different objective. 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. And the, the, the focus on those tracks are completely different. And with that said though, I think there's some opportunity over time to closely collaborate the voice on the robot today is using the Hark Voice API. So if you talk to any of our robots here today, it's using the Hark voice model that we design here internally. So I think there's a lot of room over time to collaborate the business together. We're taking an entire Data center of B2 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 literally between the two of us have an entire data center of next generation Blackwells. That we're using for training for AI models.

[B]

I want your latest timelines on the ChatGPT moment for robotics, humanoid robotics. We were talking to Sean McGuire about this. He was putting out maybe like two to three years, three to four. Three to four years from just seeing them on the streets, seeing them in restaurants, seeing them in the real world. Maybe not economic impact, because that could happen in 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?

[G]

You can come to figure right now, and you can see Robots running complete 247 shifts fully autonomously with neural nets all the way down the stack.

[B]

That's amazing.

[G]

So, like, I think this will be a big year for us to ship robots commercially to many different customers of ours.

[B]

Yeah.

[G]

And then we're also working on trying to. How do we integrate these into the home?

[B]

Yeah.

[G]

How do we get robots that go and do, like, laundry and dishes and tidy the house? Like, things that we just, like, I don't want to be doing. Doing. Nobody really wants to do, and use, like, robotics as a key tool for this. I think we're. I think we're, like, having this moment now. I think it's. We're in it, we're feeling it as right now, 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 going to be very. The whole world's going to wake up to it. I think we saw a little bit of that, the White House last week with, with Figure. It was just like, we saw like, unprecedented demand. Like, like, it was. It was kind of crazy because we didn't show any, like, new capabilities. So we're like, internally, we're like, okay, we're just going to 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. So it was like getting, like, you know, getting the invite from the White House to come there and be able to be the first one to do it was just a huge.

[B]

It was great.

[G]

Like, but, like, you know, there was. There was no new capabilities there, but the whole world is just waking up to the moment now of humanoids. And it was very apparent from last week at all, the incredible reaction we got from basically the entire world that we're still early here in the cycle.

[B]

I love it. Well, good luck and thank you for taking the time to come chat with us.

[A]

One quick question. Can Humanoids reliably crack open a cold Diet Coke and serve it or I imagine the tab is tricky challenge.

[B]

That's AGI for me.

[G]

I don't think they should have any problem doing this.

[A]

Okay, that's a demo. That's a demo we'd love to see. Because honestly, John would. Would buy a Humanoid just to just come over with a cold one. Crack it open. He goes through a lot of these, so.

[B]

Okay.

[A]

Get some utility out of it.

[G]

All right, John, bring a six pack over to figure and we'll test them out in person.

[B]

It's a deal. I'll talk to you soon.

[A]

Awesome.

[G]

Yeah, see you guys.

[D]

Good to see you.

[A]

Cheers.

[B]

Talk to you soon. Let me tell you about the New York Stock Exchange. Want to change the world, Raise capital at the New York Stock Exchange. And let me also tell you about CrowdStrike. Your business is AI. Their business is securing it. CrowdStrike secures AI and stops breaches. And without further ado, we have andre from console TVPN royalty in the TVPN UltraDome. Andre, how are you doing?

[A]

What's going on?

[B]

Great to see you.

[A]

Great to see you, dude.

[B]

Good to see you guys for taking the time to come chat with us.

[A]

You're always with us. You're always with us.

[I]

Yeah, I was going to say, I love the Stinkers.

[A]

It's so special to have you here.

[B]

Anyway, why don't you just give us a general update on the business, Walk us through some features, some customers, and then I want to hear the latest and greatest. Cool.

[I]

Absolutely. Thanks again, guys, for having me on.

[B]

Of course.

[I]

Yeah. So I think, as you guys know, maybe the rest of the audience does, but we are console. We build AI agents that automate service management or employee support. We do that directly in Slack or teams and things like onboarding, offboarding, PTO requests, access management, even telling the facilities team there's no more napkins left in the bathroom or something. Last week, we just launched our big product called Assistant. Assistant helps you do tier two work. It's not just the tier one employee support stuff now. It's an agent that helps your IT hr Legal Finance team automate the more complex tasks that often span multiple systems. So, for example, say there's an Internet outage. You can actually now ask Consul to go and investigate across those different systems. So on the back end, we're plugged into your meraki, your Crowdstrike, your okta, your entra, all these different systems and Consul knows how to go and Pull data from different, different tools and come back with a report for you. You can also tell Assistant to go and fix things. So you can say, actually go and push this update to this user's laptop or something like that. Then you can also have Consul build out itself now. So with Assistant, you can tell it, hey, I want to connect into Koopa or netsuite to pull this information and Consul will go read the API docs and then build its own connector into that system and then write a workflow with it.

[B]

Well, yeah, I was about to ask.

[A]

That's basically like it's. Instead of doing a feature request, just request a feature.

[B]

Yeah, yeah, I was going to ask. 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. 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.

[I]

Yeah, so. So when we started Consular, we were like, hey, we're actually going to build this framework internally. And then our engineers are going to use AI agents to build out integration super fast using that framework. And so we'd get things done in two to three, four days. And then I think a couple, maybe two, three months ago, we were thinking to ourselves, like, can we actually just have Consul do that? Just iterate on itself? And that's where the idea came from and that's what it does. So you just tell it the same way I would tell an engineer, hey, we need to build this for this customer. Now the customer can just tell Console directly, I want to pull these. I will pull this data. I want to pull these actions into these systems and it'll build itself out to do that.

[A]

Do you think that's going to be an entirely new. Basically part of every product where you'll still be able to request a feature, but at some point it's like, like you're paying for the software. You should be able to adapt it to your own needs. But I haven't. No one, no one's come on the show and like pitch that specifically as, as a company in the application layer, basically, like, we're going to give you the autonomy to adapt the product to

[B]

your crazy new paradigm, which is just

[A]

crazy because like every, every sa. Like, just every customer wants that.

[B]

Yeah, they want it. They're not like, they want to be,

[A]

oh, I want to wear for support to get back or my account manager to talk to the engineers.

[I]

I'M sure it'll come about in other tools as well. I would say the core unlock for us was actually building out a really robust and kind of framework interface that we can plug into. I think once you have that and you have. The really important piece for us is the context graph. So we have a context graph under the hood where, where we're ingesting data from these different systems and we actually model out your organization. And so when you tell it, hey, go and update John's laptop to this version, or you ask it, what is John's version of his laptop? It gives you an answer, you say, go and update it. Console already knows who John is. We know what laptop you have, we know where to find it. If you were to build that from scratch, you might have too many lookups. It would get a little lost in the sauce. And so that context graph is really important. It's a really core part of what we've built for here.

[B]

How are people thinking about.

[A]

You got to coin this, by the way. Yeah, this is an entirely. You need a. You need a. You need a deployed.

[B]

Something. I don't know for. Yeah, something.

[I]

What should we call it, guys?

[B]

I don't know, like agentically deployed engineering or something.

[A]

I was thinking name it after yourself.

[B]

Yeah, yeah, yeah.

[A]

The Servant.

[B]

The Serbian.

[A]

Yeah, you got to get. You got to get people posting. Figma needs to incorporate the Cerban method.

[B]

Yes, yes. This is it. Yeah, I think we got.

[A]

We'll work on it.

[B]

So talk me through the experience 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 startup. We had like 50 employees. We had like 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.

[C]

How you are.

[B]

Are companies actually interfacing with Consul and integrating?

[I]

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 100 people or maybe one to 150. Maybe one to 200 if you don't include Ramp, who has a very insane ratio. But, but most companies are in that range. And so with Console, they're able to take that. They go 1 to 400, 1 to 500. So we act as ultimately this force multiplier for your team. And so, yes, there's spend going into Consul, but you're actually saving on the back end of that as you're. We work with companies like Databricks, Cursor, Figma Chime founder, you know, and these guys are growing incredibly fast. And a lot of these guys actually have plans to keep their IT teams flat, you know, through this hypergrowth phase that they're about to experience. And it's entirely because of Consul. And so we're starting to see that now, not just in it, but, you know, hr, legal, finance workflows as well, where, you know, they're just doing this employee support, where they're just answering questions that. That 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. They can.

[A]

What's your approach? Do you just. Are you the only IT person at Console? Like, do you force yourself to dog food the product to the extreme or what's the.

[I]

We take a bit of a crazy approach here where everyone, everyone has full admin access to Console and everyone's encouraged

[A]

to build their own workflow that's probably smarter. You want everybody using the product.

[I]

At some point, we probably need to pull it back. I think our head of security was complaining last week. He's like, hey, we've got too many salespeople in here.

[B]

I can imagine.

[I]

But like, you know, we've got. We actually have like our. I was actually just talking to our office manager. We're going to have Consul just do our dinner orders as we do dinner in the office every day. And, you know, with Assistant, now she can build out her own workflows. She says, hey, I want to ping me Every week at 4pm Ask, give me the options, I'll select it and just go and order it into. I think she's using eck. So not an integration we would have built out on our own, but I think with Assistant, it can do that. And so our head of security, actually, he was presenting a use case to us the other week. He rolled out CrowdStrike on our devices and he did in 40 minutes instead of. I think what he said would have taken him a day or two. And he did that entirely through assist. He was just, hey, I want to plug into these laptops. It went. It Understood. Hey, you need to download these two binaries if you're going to deploy it on these versions of macOS. Here's where you upload it, here's the script you write. Okay. Do you want me to push it?

[E]

Yes.

[I]

And just deployed it. So I think 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 want to build.

[B]

Yeah, yeah. I mean there's so many startups. I'm sure a lot of founders in the audience have felt this before, where you're the CEO and you set up all the IT systems and then actually offboarding as like the super admin is extremely difficult. 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. 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 and things just like built up and I try and give people the other password. Anyway, there's a million reasons.

[A]

How do you try to. How have you been trying to model like the like overall opportunity for console? Because you're still early stage. So sure, at this point it's just like let's get as many great companies as we can on the product. But then, you know, five, ten years from now at later rounds or stages, you'll be kind of, you'll probably be asked that question more seriously. But how do you think about it? Because you are at this moment like selling against what historically was like the kind of, I don't know, labor tam to some degree where. But the other side of that, the interest, 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 just replacing people. It's like bringing a kind of capability to a company. But how are you thinking about the overall category?

[I]

Yeah, absolutely. So there's a couple of things I think that are going on at once. I think the first one is, you know, when we look at it today, it's very much a reactive role. It's very much a cost center because I think we've just, it's kind of like escaped us a little bit right in the 80s and 90s it was actually an enablement center. Right. You were bringing in technology or deploying, you know, giving people computers. You're, you know, deploying Wi fi and not WI fi, but Internet, you know, giving them email and so on. That's like a force multiplier. We've done too much of that. We have too many SaaS apps. There's all this sprawl and now the team is just managing that. They're just doing support with Consul. The way we think about it is we're going to bring our teams back to what it was like in the 90s where you can actually have this agent handling all of the ticket management for those simple systems and those basic requests. Now you have assistant that can go and do more complex work across the enterprise and the value there is now you can do 10 times as much as you were going to do in that year. If you think of you talk to any company, no one will tell you, oh yeah, our IT team is always on top of it. Our IT systems are perfectly set up. There's always something a little bit lagging behind and it's because they're just constantly drowning and so console allows them to of focus on the more strategic and kind of be more outcome based. And so I think when you think of it that way, the TAM is actually all of the work that all these companies would love to do and they just don't have the employee headcount or the cost really to go and spend on it. And so that's one big piece. The other one is we're actually just ripping out replacing tools like ServiceNow and Jira Service Desk Fresh service and kind of replacing with a more AI native solution. And so we expect that to kind of scale as you onboard more, as companies become more digital native. Right. They have more sensors.

[A]

You're saying you're the SaaS apocalypse, you're flaming the fires of the Saaspocalypse. I didn't say that, I said that.

[G]

There you go.

[A]

Very, very cool. Yeah, it's great to get the update and we're going to work on this coinage. Go back with the team, brainstorm a little bit, you tell us what and we'll start asking every company. Are you guys using the Serbian method?

[B]

Yeah, we'll figure it out. It's good, it's good. Yeah, I love it.

[I]

I'll run it by my head of growth, we'll see what she says.

[B]

Fantastic.

[A]

Good. Great to see you.

[B]

Have a great rest of your day. We'll talk to you soon. Thanks a lot. We'll talk to you soon. And there's a bunch of news that we need to run through before we head out. Artemis 2 is launching and Kalshi has it at 64% chance before April 2nd of this year. We're going to the moon. Four people are going to the moon. Everyday astronauts says. I'm honestly shocked at how the general public has no idea Artemis 2 is taking humans out to the moon and will be the furthest humans have ever flown. Every. Every non space nerd I've talked to has no idea. We gotta get people stoked. This is what I'm gonna be writing about tomorrow. I want to deep dive this. I want to.

[A]

Why is no one talking about our space?

[B]

Why is no one talking about the moon? We're going. NASA is set to launch four astronauts around the moon. The deepest human space flight since the final Apollo lunar landing 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. Leave us five stars on Apple podcasts and Spotify. Sign up for our newsletter tvpn.com it's been an honor. It's been an honor.

[A]

It's been an honor to be here.

[B]

It was a rough couple days. It was a rough couple days being away.

[A]

Yeah.

[B]

But we're back. We're incredibly back.

[A]

It's gonna be a great week. And have a wonderful evening. Evening.

[B]

Yeah. We will see you tomorrow. Goodbye.

[A]

Throwing smoke.

[B]

Throwing smoke. Okay, goodbye everyone.

[A]

See you tomorrow, folks.

[B]

Goodbye. We will be back when the smoke clears.

[A]

Wonderful day.

[B]

Goodbye.