Meta Drops New Model, Mythos, RoboLamp | Luther Lowe, Dan Primack, Lior Susan, Feross Aboukhadijeh, Qasim Mithani, Jaleh Rezaei, Jeremy Philip Galen

Summary

---

TBPN Podcast Summary

Episode: Meta Drops New Model, Mythos, RoboLamp | Luther Lowe, Dan Primack, Lior Susan, Feross Aboukhadijeh, Qasim Mithani, Jaleh Rezaei, Jeremy Philip Galen

Date: April 8, 2026
Hosts: John Coogan & Jordi Hays (with regulars Harry Stebbings, Noah Hirschfeld, Martin Casado, and multiple guests)
Theme: The accelerating pace of AI, cybersecurity, prediction markets, defense tech, and the changing regulatory and venture landscapes.
Tone: Caffeinated, playful, highly technical, and insight-heavy—often with snark and inside jokes.

---

1. Overview:

The episode is a rapid-fire, information-rich tour through pivotal new launches and crises in tech. Highlights include the closed-source AI pivot by Meta with its new Muse Spark model, Anthropic’s high-security Mythos release, major supply chain hacks, evolving startup and investment landscapes, and the real-world impacts of AI in both consumer tools and national security infrastructure. The show features a parade of influential guests, each dropping fresh perspectives on the intersection between tech, policy, and society.

---

2. Key Discussion Points & Insights

A. Meta’s Muse Spark: A New Era in Big Tech AI (00:09–19:17)

• Meta’s Big Pivot: Meta released its first major new AI model in over a year—Muse Spark—a closed-source LLM, signaling a departure from the open-source LLaMA tradition (00:09–01:35).
  • “The future of foundation models is closed source.” – Harry Stebbings citing John Ludig [01:38]
• Open vs. Closed Source & Benchmark Games:
  • John Ludig’s prescient analysis outlined Meta’s incentives for open-sourcing until ROI demands secrecy and profit [01:36–04:34].
  • Meta no longer leading with open-source; focus shifting to competitive, proprietary data and monetization.
• Benchmark ‘Chart Crimes’: Mixed performance across leaderboard benchmarks—Muse Spark beats some rivals (Gemini, Grok) but underperforms on others (ARC AGI 2) [05:12–11:09].
  • “They have at least moved on from the culture of optimizing for the benchmarks. Isn't that a good thing?” – Harry Stebbings [10:14]
• Personalization Quirks:
  • Strangeness in Muse Spark’s joke personalization, leading to discomfort about privacy.
    • “Why would you think I want Malibu appropriate surf puns?” – Noah Hirschfeld [06:55]
    • “It says, you got me… But then it denies it again.” – Noah [07:36]
  • Hosts question whether the model’s personalization is drawing data too closely from users’ histories, raising PR and safety questions.
• Economic Rationale: Closed models allow Meta to better justify immense capex and leverage proprietary data for internal features deployed to billions, rather than selling API access [11:19–16:03].
• Market Response: Stock jumps 8%, market hungry for clarity on Meta’s AI investment payoffs [15:22].

---

B. Anthropic’s Mythos Model: Red Teaming AI Security (19:17–26:35)

• Release Details: Anthropic unveils Mythos—optimized for finding zero-day bugs and exploits, limited preview to critical infrastructure partners, tight cybersecurity focus [19:17–23:25].
  • “Models with obvious national security implications would not be forthcoming. Those people were wrong.” – Quoting Dean Ball [29:37]
• Responsible Release, Not Safety Theater:
  • Debate over whether Anthropic’s move is about genuine safety or investor hype / anti-competition with China [23:35–26:14].
  • Notable skepticism: “Anthropic's marketing strategy is so funny...our models are so good we can't release them. It would be too dangerous.” – Buco Capital Bloke [23:35]
• Implications:
  • The cybersecurity arms race accelerates; “we are thoroughly in the era of the lab's best models may well not be in public the way they used to.” – Dean Ball [29:37]
  • The best AI will be available only to top bidders due to compute and safety constraints.

---

C. Defense Tech, Data Centers, and Venture Markets (77:54–92:52)

• Defense Tech Boom:
  • Discussion about lasting impacts of Middle East unrest, supply chain chokepoints, and defense tech as a huge new venture sector.
  • “Standard munitions stockpiles are going to have to get refilled.” – Dan Primack [80:03]
• Data Center Bans as Next Flashpoint:
  • Data center moratoriums more serious (for deal flow) than even rising oil prices; PR battle for the sector [76:49–77:38].
• Venture Funding (AI/Defense/Cyber):
  • Fundraising for industrial/physical tech surges, especially in defense, supply chain robotics, and manufacturing (Eclipse’s $1.3B raise).
  • “AI is not a bubble thing.” – Recurrent motif in discussion with Dan Primack.
  • IPO window narrow, only a few massive companies like SpaceX, OpenAI, Anthropic (the “big three”) are prepping to go public.

---

D. Supply Chain Attacks and AI Cybersecurity

Featuring: Feross Aboukhadijeh (Socket), Kassim Muthani (Depth First), Jeremy Gallen (Charlemagne Labs)

• Breadth of Attacks (Axios/NPM):
  • “Socket was among the first to detect and report… we built a system that downloads every open-source package in existence within a few seconds.” – Feross [94:00]
  • Social engineering sophistication: North Korean actors targeted top maintainers using staged video calls and fake Slack workspaces.
  • “Once you run a compromised open source package… you kind of have to rotate all your credentials…”
• Industry Response:
  • Security moving to board-level concern; organizations signing up for Socket in droves post-incident.
  • The new attacker/defender arms race: “In security, the minute you think you’ve got things under control, the attacker evolves.” – Feross [105:04]
• Depth First’s AI Offensive–Defensive Approach:
  • Training in-house LLMs to find and triage vulnerabilities faster than state-of-the-art (Opus 4.6).
  • “We found vulnerabilities in Chrome, in Linux…” – Kassim Muthani [116:24]
  • Emphasis on RL loop, responsible disclosure, and the complexity of building generalized bug-find agents.

---

E. The App Store, Vibe Coding, and Regulatory Fights

Featuring: Luther Lowe (Y Combinator)

• Explosion in “Vibe Coding:” One-person, AI-assisted, high-GMV startups are becoming reality, but face growing App Store gatekeeping [43:11–48:51].
  • “The Apple App Store is basically like the worst DMV in the world.” – Luther Lowe [43:30]
• Policy Initiatives:
  • Advocacy around BASE Act, aiming to curb self-preferencing by tech giants and increase competition, especially for alternative app stores and AI assistants.
• Siri & the Race for Personal AI:
  • Frustration with limitations on iOS for third-party assistants (“Why can’t Siri do it? … until this self-preferencing is addressed...we’re not going to see the fruits of the LLM revolution.”)
  • Prediction that Apple will try to build its own vibe-coding tools and retain control [47:14].

---

F. Startup Spotlights & Industry Trends

• Mutiny (w/ Jaleh Rezaei):
  • “The mission of Mutiny was all about killing the dependency season… We hire people that are aligned with our values and we just let them be themselves.” [119:53–125:43]
  • AI “agent” handles all customer-facing workflows, case study generation, personalized outbound, prospecting—all at scale.
  • Mascot origin stories: “His name is Achoo.” [120:24]
• Charlemagne Labs (Jeremy Gallen):
  • Defensive AI for spear-phishing and scams—building “Agent Charlie,” a watchdog for every employee.
  • “In an AI-powered world, all phishing becomes spear phishing… You’re not going to get a Nigerian prince email much anymore.” [127:17]
  • Collaboration with Meta on LLM evaluation for social engineering risk.

---

3. Notable Quotes & Moments

• “What is personal superintelligence if it doesn’t even know your name?” – Harry Stebbings [09:17]
• “You gave a hyper specific example based on my life, so I have to assume you were looking at my Twitter account for inspiration.” – Noah Hirschfeld [07:49]
• “If the attacker has to just find one way in… defenders have a much harder job.” – Feross Aboukhadijeh [101:03]
• “In security, the minute you think you’ve got things under control, the attacker evolves.” – Feross [105:04]
• “The antidote… we just announced yesterday a coalition of 275 startups and VCs in support of the BASE Act.” – Luther Lowe [50:15]
• “There’s nothing to do about it. But you should remember it.” – Quoting Dean Ball on Anthropic Mythos [29:37]

---

4. Timestamps for Key Segments

| Time | Topic / Segment | |-------------|--------------------------------------------------------------------------------| | 00:09–19:17 | Meta & Muse Spark model; open vs. closed AI | | 19:17–26:35 | Anthropic Mythos, cybersecurity roll-out, industry responses | | 43:11–54:39 | Luther Lowe on App Store, regulation, Vibe coding, and the BASE Act | | 77:54–92:52 | Defense tech, funding, IPO window, and the impact of global conflicts | | 93:18–110:21| Feross/Sockets & Axios supply chain hack, open source threats, AI in security | | 110:34–117:45| Depth First's LLMs for vulnerability detection (Kassim Muthani) | | 118:05–125:43| Mutiny, AI agents for go-to-market, startup lore (Jaleh Rezaei) | | 126:03–134:57| Charlemagne Labs: AI-driven scam/phishing defense (Jeremy Gallen) |

---

5. Final Thoughts & Episode Impact

The episode is a panoramic, sometimes dizzying look at how rapidly the ground is shifting across AI, cybersecurity, consumer tech, and the venture ecosystem. The hosts and their guests paint a clear picture: The AI race is entering a new, more closed and risk-aware era; security—human and technical—is now existential; and incumbents and startups are vying not just to innovate, but to determine the rules of competition itself. Stories are underscored by real hacks, policy moves, and product launches all happening in real time, with the show offering both technical depth and sharp commentary.

---

End of Summary

Transcript

[Harry Stebbings]

You're watching TVPN. Today's Wednesday, April 8, 2026. We are live from the TVPN Ultradome

[Noah Hirschfeld]

Temple of technology, the fortress of finance,

[Harry Stebbings]

the capital of capital. We got white suits on. You know what that means. The stock market is booming. The Dow Jones is up 2.68%, the S&P 500 is up 2.46%, the Nasdaq's up 2.9%. And there's a bunch of other stocks that are moving within that. Of course this is on the back of the the very good news that there has been a ceasefire, that the street might be opened. Of course, it's all back and forth. The front page of the Wall Street Journal is covering all of the geopolitical moves. But we're here to talk about tech and business, of course. And the big news today is that Meta Platforms has launched a new AI model. Alex Wang, the chief AI officer at Meta Platforms, announced a new large language model today, its first major new artificial intelligence model in more than a year. The rollout of the model called Muse Spark is a critical moment for Meta, which is up 7.5% already, which has spent billions of dollars hiring AI talent in a bid to catch up to OpenAI, Anthropic and Google DeepMind leading labs have been putting out models at an accelerating pace. In a departure from its previous models which were open source, Muse Spark is a closed model that will power Meta's AI chatbot and AI feature features within it. John Ludig has a very interesting post about open source AI and sort of predicted this. I can pull that up at some point.

[Noah Hirschfeld]

We can find predicted that Meta would eventually bail.

[Harry Stebbings]

Yeah, let me find it. The future of foundation models is closed source. Let me see if we have this here, he said. Given Meta is the primary deep pocketed large open source model builder, open source AI has become synonymous with Meta AI. He wrote this maybe three or four years ago. So the operative question for open source AI is what game is Meta playing? In a recent podcast, Zuckerberg explains Meta's open source strategy. One he was burned by Apple's closeness for the past two decades and doesn't want to suffer the same fate with the next platform shift. It's a safer bet to commoditize your compliments. He likes building cool products and cheap performant AI enhances Facebook and Instagram. That's 100% true. We've seen this in the ads product and the growth there. There's some call option value if AI assistants become the next platform and that makes sense. In Manus and the Meta AI app, he bought hundreds of thousands of H1 hundreds for improve social feed algorithms across products and this seems like a good way to use the extras. That all makes sense and Llama has been great developer marketing for Facebook. But Zuck also suggests several times that there's some point at which open source AI no longer makes sense, either from a cost or safety perspective. When asked whether Meta will open source the future $10 billion cost model, the answer was as long as it's helping us, at some point they'll shift their focus towards profit. And that's what John Ludig wrote. When did he write this? 20 man time flies. Barely just under two years ago, he says unlike the other model providers, Meta is not in the business of selling model access via API. So while they'll open source as long as it's convenient for them, developers are on their own for model improvements thereafter. That begs the question, if Meta is only pursuing open source insofar as it benefits themselves, what is the tipping point at which Meta stops open sourcing their AI sooner than you think? He says. Exponential data Frontier models trained on the corpus of the Internet, but that data is a commodity model. Differentiation over the next decade will come from proprietary data, both via model usage and private sources. Exponential capex. He highlighted this two years ago. A lagging edge model that requires just a few percent of Meta's.40 billion in capex is easy to open source. No one will ask questions. But when you reach $10 billion or more in capex spend for model training, shareholders will want clear ROI on that spend. The metaverse raised some question marks at a certain scale too, diminishing returns on model quality within Meta. There's a large upfront benefit for Meta building an open source AI model, even if it's worse than the frontier closed source counterpart. There are lots of small AI workloads, think feed algorithms, recommendations and image generation where Meta doesn't want to rely on a third party provider like they had to rely on Apple. And so the news has been. Back in December there was a reporting that Alex Wang disclosed an internal company Q and A that his team was working on two new models. One was this text based LLM codenamed Avocado. And then a separate model that was for image and video.

[Noah Hirschfeld]

Mango.

[Harry Stebbings]

Mango, yeah. And so have they clarified if this is Avocado, this feels like what Avocado should be. This Muse spark. Is that what it's called again?

[Noah Hirschfeld]

Museum.

[Martin Casado]

I see it is. I don't know what else.

[Harry Stebbings]

So the image model should be coming soon. The question that I had was, will a code focused agentic coating harness be a separate model, a different train? It feels like it's not a coincidence that this news is dropped. Dropping on the heels of Anthropic's new model Mythos, which sort of was announced loosely and the model card dropped yesterday even though the model is not available yet to play with.

[Martin Casado]

Yeah.

[Noah Hirschfeld]

So going through, I think it's worth pulling up the actual model card here so we can have it on the screen. But they bit break out Muse Spark thinking against Opus 4.6 max Gemini 3.1 Pro high GBD 5.4x high and then Grok 4.2. And the way that they position it, it looks. There was of course some people saying that it was somewhat of a chart crime, but if you look when you basically look at the top and you say that Musespark gets an 86.4 and it's in blue and then you look over and it's outperforming all the other models on that benchmark. You just sort of assume that like the highlighted blue means that it's outcome.

[Harry Stebbings]

Yeah. But it's not Frontier at mmlu because

[Noah Hirschfeld]

there's a bunch of them as you get further and further down. So like ARC AGI 2 musespark dramatically underperforms.

[Harry Stebbings]

Oh, interesting.

[Noah Hirschfeld]

The other leading models.

[Harry Stebbings]

Yeah.

[Noah Hirschfeld]

And there's again a number of others where there's plenty where it's overperforming. There's plenty where it's underperforming. Of course, we started asking it jokes right away. So I'll pull up, I'll pull up the joke. I said, tell me a joke.

[Harry Stebbings]

Okay.

[Noah Hirschfeld]

And it said, gotcha. Here's one for you. Why don't skeletons fight each other? They don't have the guts.

[Harry Stebbings]

Okay.

[Noah Hirschfeld]

But then it doesn't even let me react. It just says, want a different vibe. I've got dad jokes, nerdy ones. Or Malibu appropriate surf puns too. And so I'm like, wait, why would you think I want Malibu appropriate surf puns?

[Harry Stebbings]

If you look in your previous chats.

[Noah Hirschfeld]

I have no previous chats.

[Harry Stebbings]

No previous chats. What about. Because Meta AI calls Instagram. So when you search on Instagram, sometimes that prompts llama or previous.

[Noah Hirschfeld]

Yeah. So I'm trying to get to the bottom. Right? Like this feels like an oddly specific type of joke to ask me. And so I said, why would you think I want Malibu appropriate serf funds? Haha. Fair call. Toss that in without you asking for it. I Try to mix in different flavors of jokes and surf puns. Just popped into my head as a random option. No special reason behind it. I just said I don't believe it was random. And it says, you got me.

[Harry Stebbings]

You got me.

[Noah Hirschfeld]

It wasn't my smoothest moment. But then it denies it again.

[Harry Stebbings]

Weird.

[Noah Hirschfeld]

It says it's just like, what kind of joke do you actually want? No hidden motives here. It said you gave a hyper specific example based on my life, so I have to assume you were looking at my Twitter account for inspiration.

[Faras Abu Khadija]

Instagram.

[Noah Hirschfeld]

I get why that felt weird. I'm sorry it came off that that way. And then it denies it again. You're clearly lying.

[Harry Stebbings]

I mean, you have talked about being in Malibu on the Internet for a full year. It's possible it got baked into the pre training or something. I don't know. Maybe. Yeah, there's also. I mean, that feels like.

[Noah Hirschfeld]

When I said, what can you tell me about myself? You said, I don't actually have access to personal details about you beyond what you share with me right here in this chat.

[Harry Stebbings]

That's very odd because the whole thesis of personal super intelligence should be, hey, we're the best model that actually does plug into your entire Life and your DMs and your Instagra and your likes and your preferences and everything that you have done across Meta platforms for a very long time. We're gonna bring that in a really fun and delightful way. And telling a joke that is tailored. I used to get jokes like that where I would ask for a joke and it would be. I've talked about this. It would be something like oddly specific about my car. And I was like, I don't. That doesn't actually make the joke better, but it's cool that you're remembering. This whole personalization boom happened last year.

[Martin Casado]

I get those about like aws. Really, like specific services.

[Harry Stebbings]

Oh, because you've been like querying, asking

[Martin Casado]

questions when I was like debugging stuff. Yeah, yeah, but so I ran my favorite benchmark.

[Harry Stebbings]

Yes, yes. Shrimp fried rice bench.

[Noah Hirschfeld]

How did you do it, by the way? Noah Hirschfeld said, doesn't know your name. I said, what's my name? I don't know your name unless you tell me. Smiley face.

[Harry Stebbings]

It definitely knows your name. But yeah, I mean, what is personal super intelligence if it doesn't even know your name? That feels like they haven't dialed in the harness or whatever the tuning is to actually find it.

[Noah Hirschfeld]

And of course meta is gonna be hyper aware. We don't want a PR cycle. They Trained on your data. Right.

[Harry Stebbings]

Everyone's been, oh, that ad was a little bit too close to home.

[Noah Hirschfeld]

And you remember every once in a while, one of those, a screenshot that's been screenshot a thousand times goes viral and it's like, I do not give Mark Zuckerberg permission.

[Harry Stebbings]

Oh, yeah, like that work. Hilarious. Is this a rebuttal to the bench hacking allegations that happened last week or last year? So where was the. So according to Meta's internal benchmark test, musespark outscored Google Gemini on some tests and was competitive with models from OpenAI and Anthropic on others. It significantly outscored Xai's Grok on most tests. Alexander Wang's hiring followed the disappointing release of Meta's previous model called llama4. The company was accused of and later admitted to gaming a third party benchmark that it used to rank various models against each other on performance. It also delayed the rollout of its biggest model called Behemoth, which it never ultimately released. And so when I look at a model card like this, where you could call it a chart crime, where, you know, it's highlighted in blue and it feels like it's the best, but it's actually, you know, doing better on some. It does well on Health Bench Hard. It underperforms on ARC AGI 2, as you mentioned. But this maybe is the bull case here, is that they have at least moved on from the culture of like optimizing for the benchmarks. Right. Isn't that a good thing?

[Martin Casado]

Yeah, I mean, there are rumors about them like there was like extra bonuses if they, if they got number one on LM Arena.

[Harry Stebbings]

Sure.

[Martin Casado]

That was like something like the rumor.

[Harry Stebbings]

Yeah.

[Martin Casado]

But yeah, I mean, you've seen a lot of the labs kind of move away from benchmarks generally because I think they're just not that meaningful anymore. Like a lot of them are like, basically so saturated. They're all. It's like they're competing between 89 and 91%.

[Harry Stebbings]

Yeah.

[Martin Casado]

And they're just like, not very meaningful, like, you see.

[Harry Stebbings]

And you won't like actually feel that in the product necessarily.

[Martin Casado]

Yeah. You kind of need to talk to these things for a long time before you can actually get the vibe.

[Harry Stebbings]

Yeah.

[Martin Casado]

But I do think this news is very interesting in the context of the, you know, cloudonomic stuff dashboard.

[Harry Stebbings]

Yeah.

[Martin Casado]

Because like, what, okay, what does it mean if the entire company has been like, maxing their Claude tokens over the past month? It means that they weren't using this model.

[Harry Stebbings]

Yeah. To me it means they need to commoditize their compliments. Right. They need to bring down that cost potentially. And if they're, I mean we sort of, you know, dug into are they spending a billion dollars a month? Seems like absolutely not. But they're clearly spending a lot. And if you can turn that OPEX into capex and train your own model and then inference it much cheaper on your own hardware, that feels like just an economic opportunity. That makes a ton of sense in the context of just 10,000, 20,000 engineers writing a lot of code. Yeah.

[Martin Casado]

I think there's basically two ways to square those two things happening. Either one, this model is not that good because the engineers aren't using it, or you know, your theory that they're just distilling cloth. So one of those is.

[Harry Stebbings]

That's not my theory. That is, that is the schizo theory.

[Martin Casado]

I believe that this model still doesn't feel that big. I think Alexander Wang talked about that. They're going to train bigger models. They're training them right now.

[Harry Stebbings]

Yeah.

[Martin Casado]

So I'm excited for those. I think I'm especially excited for the video models.

[Harry Stebbings]

Yeah, they should have incredible training data. We've seen really good. 3.

[Martin Casado]

This model is like very competent.

[Harry Stebbings]

Right.

[Martin Casado]

It's with the frontier models. Maybe it's not the best one, but it's like among the top five or whatever. And none of the other big labs have. I guess that's not true. Like Google right now is definitely ahead in images.

[Harry Stebbings]

Yeah.

[Martin Casado]

OpenAI I think is they're releasing a new image model soon. It seems like there's been rumors of this.

[Harry Stebbings]

Yeah. The image 2 popped up on the arena.

[Martin Casado]

Yeah. On the arena it's always like the code name coming out.

[Harry Stebbings]

The photos just looked photoreal. It didn't look like AI imagery anymore.

[Faras Abu Khadija]

Yes.

[Martin Casado]

So if like Meta has similar capabilities but they have this incredible data set.

[Harry Stebbings]

Yeah.

[Martin Casado]

Very excited to see what comes out there.

[Harry Stebbings]

Yeah.

[Noah Hirschfeld]

The news this morning, Meta platforms and the information Meta platform has taken down internal employee built leaderboard tracking how many tokens staffers were using showed total usage over a recent 30 day period amounted over 60 trillion tokens. The dashboard now displays a message that is offline. It says, we've really enjoyed building this app on Nest for everyone. It was meant to be a fun way for people to look at tokens. But due to data from this dashboard being shared externally, we've made the decision to shutter it for now.

[Harry Stebbings]

It seemed like a fun side project. Mike Isaac was reporting on it here. He said it's down. Unclear to me. If this was a homespun one by employees or an official one. Employee projects come and go frequently. Conspicuous timing though. But yeah, you don't want to have. You want to measure the output, the impact, not necessarily the input and how much is is going on there. What else is going on? Lisan Al Gaib says Meta might actually be back with Musespark still behind OpenAI, Anthropic and Google, but ahead of Xai. In Chinese labs, Musespark soars 52 on the Artificial Intelligence Analysis Index behind only Gemini 3.1 Pro, Gemini GPT 5.4 and Claude Opus 4.6. Musespark is the first new release since Llama 4 in April 2025 and also Metas first release that's not open weight. So a huge jump up in performance across a variety of benchmarks. All good stuff there. What else is.

[Noah Hirschfeld]

And the market is tanking. Thrilled, thrilled, absolutely thrilled that I just

[Harry Stebbings]

saw the news that the Wall Street Journal is reporting that the Strait of Hormuz might actually be closed again. So I would imagine a kangaroo market

[Noah Hirschfeld]

for than you know, the market is thrilled that Metta has released a, a close to frontier level model. Right. This is a new group. They've been at it for less than a year. The stock is up almost 8% today. And again, you know, so, so much of the pricing pressure, the downward pressure on Metta has just been kind of uncertainty on what all these tens of millions of dollars will actually go towards and what will be accomplished. And still unclear. Like you know, is this, are they going to go after Code gen at all? Are they just going to try to compete on the consumer LLM side? Very, very.

[Harry Stebbings]

And can you economically go after CodeGen if you're just using it for internal models? If you're not selling it externally, can you justify the capex just purely on the internal usage? Having having this model be vended into all the different family of apps makes a lot of sense because they have billions of users that will wind up interacting with this in one way or another. The code gen thing, you have to wind up being more in this personal superintelligence. We've talked about Mannus and what it might be able to do for you across Instagram, across Facebook, across WhatsApp. I don't know.

[Noah Hirschfeld]

Yeah. The question is will they try to send Meta vibes again with the new model all the way up to the top of the App Store charts?

[Harry Stebbings]

Yeah.

[Noah Hirschfeld]

I'm curious.

[Harry Stebbings]

The previous actual model was midjourney under the hood. Right. And so that was sort of a Quick launch to demo what they were thinking, mixing the music library, which was cool.

[Martin Casado]

Yeah, like that had nothing to do with the new class of AI researchers.

[Harry Stebbings]

Mango. Yeah, but yeah, I mean there was a lot of weird back and forth and news about. But is Alex Wang getting kicked out? There was a quick debunk on this. Andrew Bosworth came up and said, no, this is completely incorrect. We're very happy with the progress and the team and what we're building there. And so it seems like they got it out the door and it's been doing well. Meta's new family of AI models can reach the same performance as Kimik2 with only 30% of compute and only 10% of the compute to reach llama4 Maverick. So a much more efficient, efficient computing frontier here. They completely rebuilt their pre training stack with improvements to model architecture optimization and data curation and so more facts. Metaspark is an early data point on our trajectory and we have larger models in development. So the mythical 10 trillion parameter model that is the 10T GPT is what everyone's working on right now. 10 trillion?

[Martin Casado]

Yeah. Probably black Welch in that range.

[Harry Stebbings]

Yeah, it's all rumored at this point.

[Luther Lowe]

Yeah, rumored.

[Martin Casado]

GPT4 was something like a trillion. Right. You remember those memes where it's like a small circle and then the big

[Harry Stebbings]

circle and then a huge circle.

[Martin Casado]

GPT4, GPT5.

[Harry Stebbings]

Yeah. But yeah, lots of other work that went into it. Martin Casado has a little bit more context on what actually unlocks new capabilities AI models. He says Mythos appears to be the first class of models trained at scale on Blackwells. Then there will be Vera Rubin's pre training isn't saturated. Narrative violation. RL works and there's so much computing coming online soon. Buckle your chin straps. It's going to be wild. The scaling lawsuit.

[Noah Hirschfeld]

And you know Brad Gerstner had to come in with the hundred.

[Harry Stebbings]

Yep, for sure. Yeah. There's a crazy bull case for Nvidia in the information arguing it should be worth what, $22 trillion. That is a wild move. There's a lot going on. The scaling laws holding is the most

[Noah Hirschfeld]

important article from the Information Finance. Nvidia worth 22 trillion. This old school financial model says yes.

[Harry Stebbings]

So yeah, the big news on yesterday was Anthropic's new model Mythos. Some really impressive statistics and anecdotes yesterday. Both the model card, the benchmarks and some stories about breaking out of a variety of, what do they call them, walled gardens or test environments. What are those called? Breaking out of the I don't know, the simulation sandbox. The sandbox, yeah. Breaking out of the sandbox, sending emails, all sorts of stuff like that. The model preview is only available right now to about 50 companies that maintain critical infrastructure because the model is particularly good at finding zero days bugs and exploits in technical systems. And if they, you know, they lead that, they leak that out before big companies have time to go and address all the bugs. There could be serious, serious ramifications for cybersecurity. And so key partners include Apple, Google, Microsoft, Amazon, Nvidia, JPMorgan Chase, Broadcom, the Linux Foundation, Cisco, CrowdStrike and Palo Alto Networks. They're all listed on the cybersecurity focus page for Project Glasswing.

[Noah Hirschfeld]

Chris Backe was having a little bit of fun because he noticed Anthropic put their own logo on the partner page, which is a little bit funny. But at the same time it's kind of smart because a lot of people are just going to see the image quickly and it's good to position yourself with the other guys companies.

[Harry Stebbings]

Yeah. So yeah, it is interesting. I mean people have predicted that AI models would be particularly good at cyber attacks and this was one of the main sort of vectors of AI fears. It feels like this is what, maybe what Dario was referring to when he was talking about the end of the exponential finding and exploiting software bugs is it's sort of perfectly in the sweet spot for coding agents and reinforcement learning, combing through piles of code, tirelessly trying different exploits to find bugs, having a clear, verifiable reward. Did you crash the system or not? Did you break into the system or not? This is very, it's a very clear binary signal that you can send to the model to determine were you successful in breaking into that system. And it requires basically no time delay, there's no lag. So there was one snarky tweet I saw that was something to the effect of like, okay then if it's so good, go cure cancer. But any application that requires a real world feedback cycle, even if it's just a few minutes of human interaction, in the cancer example, you're going to need to be testing the drugs in vitro, in mice, in monkeys, in humans, at some point, or even if you're just sequencing DNA or doing anything in the lab, pipetting anything, if it's even just a few minutes, all of a sudden every iteration, every attempt is going to take a few minutes and that's going to put you on just a wildly different exponential as opposed to being able to spin up A virtual machine with basically every single piece of software out there and then try every single exploit against every single piece of software and you wind up with a ton of exploits and very, very bullish for cybersecurity that this is being done preemptively. There's a whole bunch of different discussions. Ben Thompson has a good piece on the whole decision to release the model or not and stage it out and the go to market there. But. Even if the bio research, the other impacts are on sort of a slower exponential, there's still so much opportunity in even a software only singularity. There's also risk in a software only singularity. We've seen this story before though. A model that's too powerful to release but then works its way out and has pretty moderate impact on the world. This was the story of GPT2, the story of ChatGPT. The question of is this the model that's dangerous to put in the hands of people?

[Noah Hirschfeld]

A headline from February 22, 20172019 by Aaron Mack OpenAI says its text generating algorithm GPT2 is too dangerous.

[Harry Stebbings]

Yes. So there is, there is a, I think Ben Thompson called it like the boy who cried wolf syndrome, but the Mythos wolf. He says there's a lot of skepticism about Anthropic's announcement. This tweet was representative from Buco Capital Bloke. Anthropic's marketing strategy is so funny like ah, the government is treading on ah, our models are so good we can't release them. It would be too dangerous. Ah, someone stop me, I'm going to destroy the economy. The rolling of the eyes is exacerbated by the fact that Anthropic has reasons to not make Mythos widely available beyond a lack of compute. Another factor is surely trying to avoid having Mythos distilled by Chinese model makers. So there's actually two good reasons to gate access and when you're looking at those logos, when you're looking at the world's largest tech companies, there's much more ability to scale rollout, demand, set pricing. These companies might be able to pay more. The model is very expensive. But if you're justifying that against bug bounties for zero day exploits in your most critical system, when you look at like JP Morgan Chase, it's a bank. What is the price of finding an exploit in that system is pretty high. It probably clears the token hurdle a lot. And if the rollout is paced evenly across all the different companies, they'll all sort of understand that they're getting Allocation, inference, allocation at the efficient price that clears the cost to actually serve the model. So I do think the systems all of these 10 trillion parameter models will be released soon. Broadly then the main reason that an AI that's smart enough to find zero day exploits should be able to recognize that it's being used by a bad actor to find zero day exploits. And it's only been it's only been a few months since the last flurry of competing models from OpenAI, Anthropic and Google and the next cycle is already off to an aggressive start. We had Meta and then the other news is that Elon Musk announced that he is getting ready to do another larger model with Xai. He's got a few he's doing seven models in training. Wow, that is a lot. Imagine V2 two variants of 1 trillion, two variants of 1.5 trillion, a 6 trillion model and a 10 trillion model. He says there's some catching up to do but he says he will never give up. Never. So he is continuing to grind and train more models. What else was in the reaction? There was a whole bunch of other back and forth.

[Noah Hirschfeld]

People seem split on Mike from Also Capital Former guest says, we've decided not to release our latest investment strategy. It's so powerful. Releasing it might end the entire venture asset class as we know it.

[Harry Stebbings]

Yeah, Jackie says you should release it

[Noah Hirschfeld]

to a handful of trusted partners so that we can harden ourselves to it.

[Harry Stebbings]

And George Hotz says Anthropic's marketing strategy, it's amazing. It's so powerful, it's terrifying. And the best part is you can't come. By the way, if Anthropic had any way to ship this, they would. Trained AI models are the fastest appreciating asset in history. GPT4 cost $100 million to train two years ago and is now worth less than Quen 3.5 27B1 million. Sending the FOMO back. Clock is ticking, boys. It needs something like an NBL 72 to run a decent speed and even absurd API pricing doesn't cover it. There's more to be made on investor hype than API access. I just wish for honesty instead of a whole fake spiel about safety. Who remembers when GPT2.1.5B was too dangerous? And so lots of back and forth. Deanball has some more thoughts on Mythos. It's a longer post so we'll let you go and read it. But the main take is just the, you know, this is technology that whether it comes from Anthropic or Another lab like clearly needs to go into the supply chain of the world and in the U.S. government and the U.S. economy because no one is doubting even though some of the exploits were somewhat minor, no one disagrees that we need less cybersecurity. We want the most secure systems possible and we probably want a lot of competition between different companies to provide that service to the government. And so hopefully if the war comes to an end and there's different discussions can happen and ICE can thaw and there's a way for these companies to work together even if the supply chain thing doesn't go through. And then Anthropic can vend technology through Project Glasswing, through CrowdStrike, through Oracle and other partners to Cisco so that at least the systems are secure because everyone wants that. So Dean Ball's been on an absolute terror. We should have him back on the show and talk more. He says A lot of people, including people in positions of authority, told us recently that models of Mythos capability wouldn't be a thing, that models with obvious national security security implications would not be forthcoming. Those people were wrong. There's nothing to do about it. But you should remember it. Mythos is the first model where theft of the weights by an adversarial actor feels like it would be a major deal. You better believe they will try and if they don't succeed with Mythos, they will eventually. We are thoroughly in the era of the lab's best models may well not be in public the way they used to. This is because of a combination of compute constraints, economic reality, competitive advantage and safety. Safety concerns. 3 means the most relevant models may be decreasingly legible to the general public. And depending on the extent and duration of the coming compute squeeze, we could enter a market dynamic where the best models are only available to the highest bidder. And of course that makes sense from a KYC and security perspective. In other words, where compute is a seller's market rather than a buyer's market. Interesting. Imagine competing firms in the economy bidding against one another for access to the best and most host tokens and the frontier labs as in essence kingmakers. The governance regime I have Described above in 4 is not designed to stop that dynamic and so there's plenty of more takes. This was a full current thing cycle Tenebrous says. People keep talking about this like it's not blatantly obvious. Anthropic clearly has a system that's auditing open source repos for vulnerabilities, using their unreleased higher power models and sending fixes for them without revealing their current level of capabilities. So they've been going around on GitHub and contributing pull requests to patch any vulnerabilities without disclosing exactly what model was being used.

[Noah Hirschfeld]

Hobart is not excited about Fundrise. We had the founder on running ads for VC X, the public ticker for private tech. This is, he says, paying for an ad encouraging people to pay 6x net asset value for a closed end fund where the cost to borrow is 400% is one of the things people will remember during the next bear market. Yeah, I asked, I asked the founder of fundrise about this, like how you kind of like, is there another iteration of the, of the product that can solve for this? Fundrise, like, very clearly made a bunch of really good bets a few years ago and the fund has performed incredibly well. But the issue now is like, if you want access to these names and the only way that you have is to go through VCX, you're paying 6x. What, like the actual private market investors are paying? And that just is like, I mean, it's, I don't know, it depends how bullish you are on the names, but it's going to be very, very hard. Assuming that normalizes over time. Yeah, it seems extremely unlikely that it trades at, you know, an insane premium forever.

[Harry Stebbings]

And so interesting that they're running this ad on Axe. I haven't seen, I have X premium, so I haven't. I don't see a lot of ads. I don't see any ads. But that does seem like the reasonable place to go to advertise a product like this. But, yeah, it is always odd. There's been a whole bunch of these, like treasury companies that have traded above net asset value. And it was always just a weird supply and demand dynamic. People want them and they're willing to pay way above. Hopefully they know the net asset value multiple and they're doing that willingly. I think, you know, consumer education, investor education is more of the critical question here. Well, Thibaut over at Codex is unreasonably excited about things. The next few weeks will be intense and fun and yeah, Michael Greenwich says weeks, years, you know, it's going to be an ongoing model mayhem for vague maxing. Vague maxing. And yesterday a lot of stuff going on.

[Noah Hirschfeld]

It was about token maxing. Today is about vague maxing. Yes, yes, let's go. Mickey Friedman says the current fear is that AI homogenizes culture and turns humans into passive consumers. One counterpoint in Go Human Play showed very little improvement from 1950 to 2016 until AlphaGo beat Le. Then human decision quality jumped. Players started developing moves that were distinct from both previous human moves and from the novel moves introduced by machine intelligence. This seems more likely to me. Fun times ahead.

[Harry Stebbings]

Lee Sedol is now a professor at Unist. He is a special professor on a three year term to conduct artificial intelligence research on Go. Specifically he yeah, if you haven't seen the Go AlphaGo documentary it is fantastic.

[Martin Casado]

Leesley Dahl go to smoke.

[Harry Stebbings]

Yes, Lisa Dahl. It is is such a wild ride. Watching the DeepMind engineers, it seems like they're genuinely surprised by the performance. No one really expected it, but yes. This is a very interesting chart to see how much things changed in the post AI era as people discovered new and interesting ways to differentiate from the models effectively.

[Noah Hirschfeld]

Yeah, Scoop from Steven Nelson. CIA used a secret tool called Ghost Murmur to find airmen in Iran. Ghost Murmur pairs long range quantum magnetometry. Yeah, how do you say that? Sensors with AI to find human heartbeats. I was wondering this. While they were over the weekend there was a search going on was like how do you find someone? How does somebody like an airman that's down send a signal that can be picked up by one group but not.

[Harry Stebbings]

This is very odd. So there are some community notes on this saying that quantum magnetometry. Magnetometry, I imagine that's how you pronounce it, detects heart magnetic fields. And I believe this technology works in labs but only up to a few meters, not 40 miles as claims has claimed. Fields decay with 1 over R cubed making long range detection implausible. So unclear if this is what worked. But isn't there. There has to be some sort of device that you could carry on your person like in your shoe, like an airtag that can talk to a satellite. Almost like, like you look at the Starlink receiver dish. It would fit in a backpack. But that's very high bandwidth. I imagine if you had something, I mean there's sat phones that are the size of large cell phones that was available in the 80s and 90s. You have to imagine that if you're just trying to put out a signal to GPS or a Starlink network, you must be able to shrink that down significantly, significantly to the place where it could be carried on your body. But it's probably classified. So I would be surprised if it's just very hard to read into like what's real and what's not. Here there is a different community note pushing back saying no note needed. This new technology is a classified system developed in secret by Lockheed, Skunk Works and the CIA. That was just used. Revealed publicly for the first time naturally its reported capabilities far except seen the known public state of the art. The note is relevant. So it's. Yeah, it's. It's. It's very, very interesting. But good stuff.

[Noah Hirschfeld]

Let's go over to Aaron Tan's post. Says introducing loom, a lamp that does your chores. Order now shipping this summer. Let's see the video.

[Harry Stebbings]

That bed already looks fully made. What. What chore is it gonna do?

[Noah Hirschfeld]

Just drop some laundry off.

[Harry Stebbings]

Oh, okay. You have to drop the laundry first. Wait, they can do that? Wait, does it have fingers in that?

[Noah Hirschfeld]

Like what.

[Harry Stebbings]

What is it put on the record? What? Yeah. What is. What is in the.

[Martin Casado]

You can see it has a little claw.

[Harry Stebbings]

Oh, it has a claw inside. Oh, okay. That is so funny to have a humanoid robot play music on a physical record. The folding T shirt is the touring test of humanoids for real Pixar lamp quaking in its boots right now. Nice video. Good color grade. Nice warm tones. Friendly. Doesn't feel dystopian. Feels delightful. Did you get one of these?

[Noah Hirschfeld]

I think. I think we should get one. I think we should get one. We should get one. As a team.

[Harry Stebbings]

I do have some clothes over there on the wardrobe rack.

[Noah Hirschfeld]

Obviously rooting for Aaron and the in the loom team. Very, very unique form factor. I mean, I just think the. An impressive timeline for shipping, hopefully. Yeah, shipping. I'm reading this as like actually shipping, not shipping like another site to order, because you can order already, but. But yeah, it'll be very interesting. If it can reliably fold clothing, it could be enough. Right. So the benefit here is like, people already want lamps, I'm assuming, for their bedroom. If you can buy a lamp that's reasonably priced, and then it also has the benefit of just a simple thing like folding clothes. There could be a market here.

[Harry Stebbings]

Yeah, I feel like, I don't know, even just putting pillows back on the bed. Even just like really basic things. I mean, even there are probably applications. Like the Roomba did so well with such a minimal. Such a minimal scope, there must be something. I wouldn't be surprised if even in between this and fully folding the clothes, just remaking the bed properly feels like something that consumers might actually pay for and allow for, you know, the flywheel to start spinning. Obviously, lots of security considerations since there's a camera there and whatnot. They'll have to do a lot of cyber security and figure out that. But people already have cameras all over their homes. From nanit and child monitors, baby monitors and that type of stuff. So I'm optimistic about this and I think they did a great job promoting it. There is a story in the New York Times from none other than John Cary Root who blew the story wide open on Theranos. He says the mystery of Satoshi Nakamoto, the pseudonymous inventor of bitcoin has remained unsolved for 17 years. Not anymore. Read my 18 month investigation to find out who Satoshi really is and he says it's Adam Back who says who posted directly. I am not satoshi but I was early in laser focus on the positive societal implications of cryptography, online privacy and electronic cash. Hence my 1992 onwards active interest in applied research on ecash privacy tech on cypherpunk lists which led to has cash and other ideas. John Carreyrou in his New York Times research finds like Aaron Van in his Genesis Block book, many interesting bitcoin analogs in the early attempts to create decentralized E cash in effect prototype ideas trying to figure out a bitcoin like thing including P2P BGP and proof of work for his quote. I'm not saying I'm good with the words, I'm not saying I'm good with words, but I sure did a lot of yakking on these lists. Actually the broader context was my observation that because I was talkative on the list and known to have an active interest in ecap, there is some confirmation bias in finding my comments frequently on ecash topics. So he has said we are all satoshi. I am not satoshi. But it's a very interesting story that will happen.

[Martin Casado]

You just created a million satoshis.

[Harry Stebbings]

Truthfully, high yield. Harry is joking. Steve Buscemi has been revealed as the bitcoin founder, not Satoshi Nakamoto. Well, we have our first guest in the waiting room, Luther Lowe from Y Combinator. He is the head of public policy and we are going to be talking to him about Vibe. Cody. Luther, how are you doing?

[Luther Lowe]

Hey guys, great to see you. Congrats on the acquisition.

[Harry Stebbings]

Thank you, thank you.

[Noah Hirschfeld]

Great to have you on.

[Harry Stebbings]

Can you kick us off with a little bit of an introduction on yourself and what you do day to day at Y Combinator?

[Luther Lowe]

Sure. So yeah, I'm the head of public policy for Y Combinator. I'm based in Washington and Gary created the role when he started at yc and really his observation many years ago was Gary and I had actually met in Washington. We were sitting around the table at some kind of White House meeting. And he said, you go to Brussels, you go to Washington and the largest tech companies have lots of representation, but little tech doesn't have a seat at the table. And that was actually the first time I'd heard that phrase, little tech. And Gary actually coined that phrase. You went back and you look on X Twitter. He had said that a number of times years ago. My role is to really help the founders navigate Washington, Brussels, the state capitals, advocate for pro little tech issues in the broader ecosystem and just really do everything I can to help the founders.

[Harry Stebbings]

What is your view on Vibe coding? The App Store? The boom. We were talking about it yesterday. There's a whole bunch of stories of where it feels like we're getting close to the one person, absolutely massive company, whether that's GMV or revenue or something. It's like it's starting to happen. But I was looking at my home screen. I don't have an app that is new or Vibe coded. Maybe it'll come in a boom in video games. But how have you been tracking? I mean, I'm sure you see this at yc, just the growth of broad app development.

[Luther Lowe]

Yeah, I mean I think I would almost kind of take a step back. It sort of reminds me of when I first started geeking out on the Internet like 25 years ago where you saw the rise of sort of what you see is what you get. HTML based or browser based, HTML editors.

[Harry Stebbings]

Yeah.

[Luther Lowe]

And that allowed anybody, that kind of democratized the process so anybody could create a web page or a website. And now we have tools that allow anybody to create a web service or an app. And so the difference though between now and 20 years ago is that today we have basically these two bottlenecks in the form of Apple and Google that sit between the creation and the potential users of those services. The Apple App Store is basically like the worst D and B in the world. And so we're seeing not only sort of, and you know there's reports all over X about this, but if you just barely kind of look around for it, you're going to encounter lots of folks that are trying to develop apps and services that are not being accepted or getting kicked out. And then it's not only that kind of like app layer, it's sort of the layer up of the tools like Replit and anywhere that are facing the inability to update their apps. And so it's a real problem.

[Harry Stebbings]

Yeah. When you say the worst DMV in the world, are you actually referring to. We saw a chart where the number of app Store submissions is spiking, it's going exponential. And that feels very logical because people, I mean, we've been building Vibe coded web apps here. The next step was, hey, maybe we should actually get one of these in the App Store. But very quickly we realized, okay, well, it's at least a two week review process. It could be a lot of back and forth. It's a new hurdle. We need to actually compile it to Swift or Objective C. It's a whole different process. Probably doable on a technical side, but we might be hung up there. But are you seeing an issue with actually getting just a one off Vibe coding app approved? And then I think we should talk about the apps that help you Vibe code new apps, because that's a whole separate thing. But just in terms of like, I want, you know, a special recipe app and I Vibe code it and I want to get it on my phone and I want to send a link to the App Store page to a friend. Is that slowing down? What's slowing that down? Is that going to be a permanent thing or do you think Apple can just adjust there?

[Luther Lowe]

Well, I think the problem with Apple, I mean, this is a sort of perennial issue with Apple is their culture is one of just absolute control. And I think that we have reached this inflection point where, you know, if I've got my MacBook in my lap, I can open it up, I can download any app I want, I can open terminal, I can do all kinds of crazy mods. But the second that that form factor fits in my pocket, all of that freedom goes away. And I'm living in sort of North Korea in terms of what I can do with my, with my stuff, with my property.

[Harry Stebbings]

Yeah.

[Luther Lowe]

And so I think that, you know, this is, you know, sure, I could, I could launch something in Test Flight if I want some kind of little bespoke, you know, training app or something. But God forbid if I want to share it with friends or I want to, you know, make some money because I've created sort of a differentiated product that's actually interesting that people want. I've got to pay this ridiculous vig to Apple. So for them it's actually about. The reason they want control is because it's about App Store revenue. Also they have competing products. It's an anti competitive thing because they've got Xcode and they've got their own dev tools that they're starting to roll out their own Vibe coding services. So the longer that they can delay and slow roll both the developers and the Tools that allow the vibe cutters to create.

[Noah Hirschfeld]

So your, your theory is that they want to basically make their own version of RELET or anything that they have in, you know, total control over. And they can make the argument, they could probably make the argument that this is better for users, it's more secure, it's better for privacy, less like malware risk, whatever, whatever it is. But they, yeah, anyways, I mean they give you, there's already like, they give you like pretty meaningful autonomy over like shortcuts and other things like that. It's not that unbelievable that they would want to actually make something here but,

[Luther Lowe]

but it's like embarrassing. Like I mean Syria is embarrassingly stupid. We've had sort of LLM consumer facing services like you know, Sam brought them down from the mountain, you know, whatever we all want almost three years ago and I, Siri still can't do basic subtraction. The other day I asked it for what was 17 days from this particular date and it was like do you want Google to consummate that query? Do you want ChatGPT to do it? It's like why can't Siri do it? And so you've got all these, just lots of energy. There's lots of YC companies that are trying to take a crack at creating kind of Siri alternatives. But until this self preferencing is addressed, I think at the policymaking level and it's not just Apple self preferencing, it's Google, it's all of them, then we're not going to really be able to see the fruits of this LLM revolution diffused into the hands of consumers.

[Harry Stebbings]

Do you think the side button to trigger the helpful assistant that is currently mapped to Siri and can interface with ChatGPT and is reportedly going to interface with Gemini soon, do you think that there's any actual chance that that becomes remappable at like a, you know, pick your browser search engine level in the os. Even if it's a, even if it's defaulting to Apple's stack, do you think there's any motion there? Because. Because that feels like the logical analogy. And what as an Apple consumer I would like, I'd like to be able to pick my assistant but be able to assign the hardware button. But where do you think that actually goes?

[Luther Lowe]

Look, there is no technical reason why we shouldn't have a flourishing ecosystem of third party AI assistant developers competing to do all kinds of interesting stuff. You guys should check out a YC company called Blue. It's Hey, Blue Dot Com. They have this amazing demo on their website and they talk about. And basically the guy sitting in his car.

[Harry Stebbings]

Yeah.

[Luther Lowe]

And he's driving, he's driving up the 101 and he's saying, hey, go through my Slack messages from last night. Okay, cool. Jerry needs a document. Share it. Get into Google Docs and share that with Jerry, but make it read only. I mean, look, I like my third button having perplexity and being able to cue that, but I can't. If I can't access those deeper OS API commands, then it stops being that interesting pretty quickly. Anyway, the blue guys, what you learn, you're like, God, this is magic. How'd they do this? How'd they figure this out? You realize it's a USB C dongle, that they've basically 70% of the company is hardware. They're doing soldering irons, they're flying to China, negotiating with distributors. It's like, why is it this a hardware company? There should be 50 different companies like this duking it out to create something that's better than Siri because Siri clearly is not cutting it. And I think the antidote to this frankly is we just announced yesterday a coalition of 275 startups and VCs in support of the BASE Act. It's the banning Anti Competitive Self Preferencing by Entrenched Dominant Platforms act bill in 1074 by Scott Wiener. Not to be confused with Scott Wieners ill fated Bill 1047 from a couple of years ago that had to do with AI regulation. This one we're really excited about because basically it calls upon companies that are a trillion in market cap or above 100 million US users to in this type of egregious forms of self referencing, we're totally fine with innocuous forms of vertical integration. In fact, most of the time that's like a great thing in technology products. But you know, when you've got, you know, the GitHub COO last week said that commit rates, if they stay linear are on track to be 14x what they were last year.

[Harry Stebbings]

Wow.

[Luther Lowe]

Like, you know, something's got to give here.

[Harry Stebbings]

People need their freedom. Everyone's building software. There's going to be a ton more software. How do you think the vibe coding apps, apps that go in the app Store and allow you to build more apps with that particular app. How do you think that will shake out? Because that is a place where it feels like Apple has spent a lot more time making the case. When I think about the Siri button, I feel like they haven't made a strong case for why that can't map to a different app that's already gone through approval. But when I think about the consumer protections and privacy that comes with knowing that the software that you download from the App Store has been audited, they've made a pretty strong case there. What's the counter argument for why Apple should open the floodgates of apps that allow anyone to vibe code an app and deliver it to anyone else's device, sort of willy nilly?

[Luther Lowe]

Look, I don't think that anything is going to in terms of creating consumer outcomes that maximize privacy, competition, all the great things that you want. I don't think any mechanism is going to work better than good old competition. That means allowing for sideloading, it means allowing for alternative app stores. We make fun of a lot of European regulation, but the Digital Markets act has actually done a pretty solid job at that in places like Japan and Europe. If you don't, if you are just hitting a wall with the worst DMV in the world, you can just go to the alternative app stores and I as a consumer can decide to download one of those and use that as a way to access a whole other ecosystem of services. And they have their own vetting processes. And I think again, competition is going to be the mechanism that actually enables better privacy, better consumer protection. And I think what we found historically with, with Apple and we saw this a lot a few years ago with Beeper, which was a YC company that had interoperable messaging. It solved the blue bubble. Exactly. Eric Migoski solved the blue bubble. Green bubble thing basically made it where it's not awkward for you to buy an Android and like, you know, Kool Aid man into your college group chat and turn the whole thing green. Yeah, he fixed that. And of course, you know, what does Apple do? They said no, we're, you know, Android users don't get that we've got to basically reduce security to this lowest common denominator like you know, sms, RCS standard. So there's no, it's pretextual. Like we, we can have choices, we can have nice things and little tech's trying to build it. But I think policymakers have got to do a better job at, you know, ensuring that the biggest players are not kind of egregiously putting their thumb on the scale.

[Harry Stebbings]

Yeah, last question. What else are you tracking in dc? It feels like with the AI boom, there's a lot of new company formation. I'm sure you're seeing that on the YC side, but we see it every day on the show. Are there policy initiatives to encourage entrepreneurship that you're tracking? Is there anything else on the small business side that you find interesting these days?

[Luther Lowe]

Yeah, I think, I would say where I think the Trump administration is doing a good job is they, they've done a lot to sort of advocate for the American AI stack and sort of encourage entrepreneurs to interface with government and become. And they've put out bids where the government is a buyer of these tools and they've been very proactive and have a great relationship. You see lots of, of renewed interest in defense tech and dual use tech. I think where I wish that there was more work and I think they could probably be doing a better job is thinking about how do we make sure that the United States is brain draining the world and bringing in the top talent and making sure that the smartest people in the world are building companies here. I think that, that that's where if I could change anything, I would say they could do a little bit better. But I would say, you know, they have been, they've been very thoughtful. The President's talked about little text in his tweets like, and I think, you know, this is not a partisan issue. We want to have a thousand flowers flourish. But it is. Yeah, I mean, I think getting the tech talent piece with the sort of being bullish on AI that I think is going to get and also the competition piece, getting those things right, I think that's going to put us in a position to be really amazing here.

[Harry Stebbings]

Yeah, I love it. Well, thank you so much for coming on the show.

[Noah Hirschfeld]

Yeah, great to meet you.

[Faras Abu Khadija]

Thanks for having me, guys.

[Noah Hirschfeld]

Appreciate the hot takes.

[Faras Abu Khadija]

All right, you too.

[Noah Hirschfeld]

Cheers.

[Harry Stebbings]

And before we bring in Dan Primack from Axios, we have an exclusive clip from his interview with Kalshi CEO Tariq Mansour on the Axio show, which we will be discussing with Dan after we play it here. It's about a minute and a half, so let's listen to this.

[Tariq Mansour]

For customers to lose, actually, the proof of that is that, you know, when a customer wins on a traditional sportsbook, they block that customer.

[Dan Primack]

The CFTC chair who supports prediction markets being legal, supports federal framework, et cetera, said recently that one of the, when he was asked about this, he said, well, part of the difference is that when you walk into a casino, there's all sorts of entertainment, right? There might be shows, there's food, there's drink. Said so a casino betting in a casino is different than betting Couchy. But it's not necessarily different than betting on a sportsbook app on my couch. There's no entertainment difference.

[Tariq Mansour]

There's big fundamental differences. Goes back to the market mechanic. One of them is essentially a product that is designed for customers to lose. Actually, the proof of that is that when a customer wins on a traditional sports book, they block that customer because those winnings are coming from the business model, the business itself.

[Dan Primack]

If they win enough.

[Tariq Mansour]

Yeah, if they win enough. Or if they win really, if they win in a consistently. If they do research, if they get informed, they're good. If they're good. Exactly. And if they're not, actually you get them promos and you figure out how to bring them back. And there's kind of a bit of this sort of like, I think, recall, like kind of marketing tactics to bring these people back. It could be like entertainment or promos and so on and so forth. That does not exist in prediction markets. It is a fundamental difference in structure where actually a lot of the people that win, the people that are doing research are getting informed, that are traders, do come to prediction markets. This is where the value prop is strongest because prediction markets do reward them for being right.

[Harry Stebbings]

Well, we have Dan Primack here with us today. Dan, how are you doing?

[Dan Primack]

Doing well, guys. Not as well probably as you are, but I'm doing well.

[Harry Stebbings]

Thanks for being here.

[Noah Hirschfeld]

Good to see you.

[Harry Stebbings]

So give us an update on this interview, what you were looking to learn from it, what you think the conversation, where you think the conversation around prediction markets will go from here.

[Dan Primack]

I think it was interesting the day we did this. We did this on Monday in New York City and it was really maybe an hour or two after New Jersey. A judge in New Jersey and basically an appeals court judge, so kind of the highest judge so far that's dealt with this basically gave Couchy the green light to go forward. I mean, I think ultimately prediction markets are going to go to the Supreme Court. I think both Polymarket and Kalshee thinks that.

[Harry Stebbings]

Yeah.

[Dan Primack]

I also think they're probably going to win in the Supreme Court. The law really is on Kelsey's side. They have done a pretty good job kind of being in step with regulators. And granted, they were. It was a little more complicated with the Biden administration, but they sued the cftc. They won that lawsuit. The reason why they have elections on the platform. I think if something is going to stop or change the way prediction markets work, that's going to have to come out of Congress.

[Harry Stebbings]

So. Yeah. What's the next step?

[Noah Hirschfeld]

Yeah. And they benefit from having their. Their adversary are casinos and sportsbooks, which are not exactly the kind of groups that Americans want to stand up to defend. You know, and march. It's time to hit the streets and march for the legacy sports.

[Dan Primack]

I mean, that's some of it. Right. So obviously in Nevada, which is one of the few places where cowshi is actually banned because the judges upheld an injunction. Yeah, that's the casinos. That's maybe some regulatory capture. The other folks who are against this, though, are folks who are just anti gambling in general. And I do think you are seeing a bit of a groundswell of that politically. And I think it's bipartisan. You know, some of the bills that have actually come out have been coming from Democrats. But, for example, the state of Utah doesn't want this, and they don't want it to protect casinos. They don't want it because they don't want people betting, period. And they sure don't want it on phones where it's so easy to do. And we did in this interview on the Axio show, which drops tomorrow, we did talk about the addiction piece of this and kind of the broader societal issues, which isn't to say what Kalshi is doing illegal. There are questions about is it promoting not immorality, but is it enabling addiction?

[Harry Stebbings]

And what are the proposals for? Because this is not regulated as gambling, and it seems like it will continue on that path. Is there any motion to bring some of the restrictions that apply to traditional gambling over into this new regime?

[Dan Primack]

No, no. And I mean, that's the complicated thing here. And I did ask them, is this basically a loophole? For example, in California, in Texas, the two biggest states in the country in terms of people. Right. You can't try to open DraftKings or FanDuel. It doesn't work for you because it's not allowed there.

[Harry Stebbings]

Yeah.

[Dan Primack]

Will allow you to bet. And, you know, I think Tarek or luana said about 70% of their volume last month in March was sports betting, which is lower than it had been in February, but you're still talking about $13 billion of volume last month. So it's a big number. You know, it's a loophole. They have figured out a way to basically get around sports betting laws. And I appreciate that the back end is different. They make a very compelling argument for why legally they. They're allowed to do it. And I agree with them. But the reality in the end is if I'm betting on the Celtics Knicks game tonight, I don't really care what the back end looks like I care about the, you know, my, my money if I win and the fact that I'm able to do it.

[Harry Stebbings]

So is, is federal preemption like sort of baked in at this point, or is there some sort of hybrid rule set where this could go back to the states and states could make their own rules? Because it does feel like there's a pretty wide set of opinions state by state on how different communities want to engage with this particular product.

[Dan Primack]

Right now, it appears federal preemption is going to win the day. For starters, the Trump administration, specifically the cftc, which is what regulates this, this isn't regulated by the sec, it's the cftc. They are all in on prediction markets. Mike Selleck, who is the current commissioner, he is on the side of Kalshi, I assume will be on the side of Polymarket when they eventually really come to the US and it does make a certain amount of sense and there is some historical precedence here. A lot of commodities which are traded, and that's kind of what they're arguing, that these are kind of commodities in a different name. There were lawsuits 100 years ago arguing the same thing. This is crazy speculation. The reason why I say this could go to Congress is there are two carve outs to that. One is a weird one. It is onion futures. Onions. Not pork bellies or something else onions. Because at one point, a long time ago, there was a ridiculous speculatory, like, bubble. A lot of people lost a lot of money on onions. So Congress passed a law saying you can't trade onion futures. And I think I'm right in saying the other one is related to box office returns, which is why if you're on Kalshi, you won't. You can't bet that a movie's going to make 20 million bucks, but you can bet on its Rotten Tomatoes.

[Harry Stebbings]

That's so funny because I've never been like a sports bettor at all. But I did participate in a fantasy movie league for a while that had no financial incentive whatsoever. But you would construct a hypothetical movie theater pick. Okay, Project Hail Mary is going in the first slot. And then they would have the box off returns. But it was all just for fun with a bunch of.

[Dan Primack]

Well, and maybe it still exists, but back in the early 2000s, there was something called the Hollywood Stock Exchange, which again was. It wasn't for real money, but people did that. It looked like a stock market.

[Harry Stebbings]

Yeah.

[Luther Lowe]

Do you.

[Noah Hirschfeld]

So other countries have created rules like, you can't advertise gambling during these hours. And there's a bunch of different kind of rule sets around it. Even in places where gambling is legal. Do you expect any states to pass laws that say you can't advertise commodities trading platforms?

[Harry Stebbings]

Yeah, during. More like FCC as opposed to cftc

[Noah Hirschfeld]

basically like not targeting like sports trading, which you know, the calcities and the poly markets are doing, but effectively saying like, hey, we know these are going to be the biggest spenders and we don't want to tolerate or encourage this type of activity.

[Dan Primack]

I mean you, you may see that and then that gets fought out in court. You know, obviously again, you know, you on the federal side, you know, it's interesting. It's not just is Kelshi fighting back against these lawsuits, the CFTC itself, there's three states, Arizona going to mess up the other two. I think Connecticut is one. There were three states who have tried to ban Kalshee and the CFTC itself has come in to sue. So I could see the FCC coming in to try to sue. If such laws were passed, it would be interesting. I mean I do think part of, well, part of a lot of betting. Despite what we saw several years ago with DraftKings and FanDuel and on every billboard and every advertisement, an enormous amount of this is still word of mouth. You know, people talking about it, people. I will tell you, when we were doing this interview, most of the crew, you know, the camera folks and the sound folks hadn't heard of Kalshee before we did this. And when it was over, I was in the corner kind of packing some stuff up and I heard them at the table having lunch. They were all not making bets, but they were flipping through the app and they were talking about different bets that were on there and they were fascinated by it. I don't forget addiction. It definitely fascinates people because people have always, you know, in our lifetimes been able to buy stocks you can trade on the price of oil, not on, you know, not on who's going to win an award or really events, you know, non. Non securities related events.

[Harry Stebbings]

Yeah. How do you think about that, that bifurcation between securities related events, non securities related events. Has there been robust enough research on how much of prediction market activity is. Is sports related or sort of less like positive sum or zero sum situations? Because I would have to imagine that the level of engagement varies by category. Like there were a lot of people that were interested in tracking the presidential election, but that's not something that someone's doing every single day. Whereas there's always a Sports game somewhere there is.

[Dan Primack]

So they said us again about set during the interview. They said about 70% of their volume last month was sports. In February that number was higher. There was obviously a Super bowl in February that changes. There was March Madness last month, but not as big a deal as the Super Bowl. 70%, that's a lot, right? That's the volume. They make the argument in the interview, you know that one of the reasons why. I mean obviously for cow she that's good. Right. That's more users, that's more fees. That's how they do it. They also argued that the sports volume creates. Creates more liquidity on the platform for the more esoteric bets and thus you need sports in order to have the other stuff. I will tell you, I do get the sense that if they could have the same valuation and the same revenue and have no sports, they'd be fine with that. And. But it's not how it works. The last thing I'd say about this, the problem or where sports could become a little legally complicated for them is this issue of entertainment. Right.

[Noah Hirschfeld]

The issue.

[Dan Primack]

Mike Selleck, the CFTC commissioner and I mentioned this during the interview. He on CNBC the other day made a comment about how well this is different than a casino because a casino is providing entertainment. You know, it was in that clip right there shows and all stuff. Well, there's not a huge. But a sporting event is by definition just entertainment. Right. Whoever wins that basketball game tonight, except for the players and the gamblers, it doesn't mean anything. No, no. Goldman Sachs isn't making trades based on if the Celtics win tonight.

[Lior Susan]

Yeah.

[Harry Stebbings]

You know, nobody I think doesn't point 72 have a desk or there's. There's some hedge fund that I think does have a sports.

[Dan Primack]

Right. And that's kind of part of the argument they make. But in terms of this idea that the cow she will put forth, which I agree with that understanding events and events market can change, can help people better understand the world.

[Harry Stebbings]

Yeah.

[Dan Primack]

There's what, 15, 18 baseball games tonight. None of those are going to change the world, even in a tiny way. Except for the people who are in the ballpark. Maybe be happier, sadder, buy a couple more dogs.

[Harry Stebbings]

Yeah. At the same time. Yeah. I mean I completely, I completely agree with you. But there is something about when you're about to turn on the super bowl and you want just a really clear read on who's more likely to win, like it is easier to understand just a straight percentage than like a line and points and all of that, like just for a complete novice. But that's a different.

[Luther Lowe]

It is.

[Dan Primack]

And they'll make the, and they make the argument correctly that they are not, they're just taking a piece of all the action. Right. They're not betting against you. They don't care if you win. Cow, she doesn't care if you win or lose. They just care that you play sportsbooks obviously want you to lose.

[Harry Stebbings]

Yeah, yeah, yeah.

[Noah Hirschfeld]

I had a very eye opening conversation with the CEO of a unicorn company who I of course will not name, but I was shocked at how, how invested they were in sports gambling broadly. We just had dinner, we were hanging out and they had tons of different parlays across every different app.

[Harry Stebbings]

Sure.

[Noah Hirschfeld]

And they would show me like, well, when I'm in this state I use this app and when I'm in this state I do this app and this app I have to take my funds off the platform every night because I don't trust that it's not gonna get.

[Dan Primack]

They win money doing this part of this.

[Noah Hirschfeld]

I don't know, I was just like, wow, I am bearish on this company because the CEO is spending all their time, you know, doing, you know, 10 leg parlays on all these different apps and you guys haven't raised around in, in years.

[Harry Stebbings]

What's going on?

[Dan Primack]

Can I say though, one thing I learned in the research for this and we talked about it a bit and I should have probably known this one kind of user difference between the prediction markets and the sports books is that parlay issue. And specifically every bet on Kalsheek goes to the CFTC and has to get approved and CFTC has 24 hours to prove it. What that means practically is while you can take a bet on the game tonight because you know there's going to be a game tonight, you can't do what you can do on DraftKings say the next pitch is going to be a ball, the next pitch is going to be a strike because obviously you have that 24 hour, they don't know there'll be a next pitch necessarily. So there's a little less real time sports betting than there is on sportsbooks.

[Harry Stebbings]

But, but because they know the super bowl is going to happen and they get that contract approved in advance, you can live trade that contract up till the last second of the game. And so that does satisfy a little bit of that. Which is again much higher frequency than oh, I want to gamble on the Super Bowl, I'm going to fly to Las Vegas, place a bet at a counter Wait in line, sit down, watch the game, go and collect my winnings. It's, it's a very, very different equation. How have you processed. So it feels like we all just agree that gambling is addictive and I think that's reasonable. I don't know where that comes from, whether that comes from science or law, but it all feels reasonable. But we're going through this again with social media, whether social media is addictive. How have you processed the social media addiction trials and then the new gambling app addiction question, like are these linked at all in your mind or how have you been processing the social media question?

[Dan Primack]

I mean I'm obviously not a doctor. I don't think you guys are doctor. I mean there's definitely, we've all, I think read about kind of the dopamine hits and look this that you get from not posting on social media. But when you get a like or when you get a reply on social media. Yeah, gambling. I mean there's obviously a dopamine hit when you gamble, right. You know, your person hits the basket, you win the game, you get excited. I mean obviously if you have a lot of money on it, you get excited for different reasons. But just even, you know, I'll admit I use some of these things sports betting app sometimes when I, if I'm watching like my hometown team play dirty.

[Noah Hirschfeld]

Duh.

[Faras Abu Khadija]

Dirty dudes may, maybe a few times

[Dan Primack]

the leagues knew what they were doing. Right. They knew that if there's a blowout, you generally turn it off. But if you're waiting for your guy to get 20 points, well, you might stick it out a little.

[Harry Stebbings]

I didn't realize that. I didn't realize that. But so back to the social media question. Have you been tracking any of that and what that means for the venture community or startups or really any knock on effects that you've tied to the trial? Because there was that decision in Los Angeles, the actual fines for YouTube and Meta seemed very low. But it was the whole chain of more cases coming and it just felt like the first time we actually had a full decision that the judge said yes.

[Tariq Mansour]

Right.

[Harry Stebbings]

So.

[Dan Primack]

Right. The lack of money is notable. Right. Because it was also a single plaintiff. Right. So I mean for theory, that's a lot of money for one person. The big question going forward is can an attorney or can a group of attorneys get a class together? And you've seen a bunch of advertisements. I've seen a bunch of advertisements all over the place. You know, were you harmed? Were you under 18? They're clearly trying to put a class together, a judge would have to certify that class. That's I think what meta, YouTube, et cetera. Are worried about, understandably worried about because it's one thing to have a single plaintiff, but that sets a little bit of a precedent. If you can have that same case with 100 plaintiffs or a thousand plaintiffs or 10,000 plaintiffs, that money then starts to become real. And I think that's kind of the next step here. And we have to see if, if lawyers can get that class together, if a judge will certify them and then whether another jury and judge will go along with what we just saw.

[Harry Stebbings]

What are you tracking in the venture markets broadly? We were going back and forth on the impact of.

[Noah Hirschfeld]

Yeah. Last year. Yeah. We were asking you about potential impacts to fundraising, fundraising outside of, in the Middle East. Even then you said, well, we're in

[Harry Stebbings]

sort of a new cycle of like AI is not a bubble thing. But how are venture funds processing and how are LPs thinking about it? Like, what are you tracking?

[Dan Primack]

Yeah. On the Middle Eastern side, it does not seem that money flows have really stopped. The it's been explained to me is calls sometimes take a few more days to come back than they were. Things aren't quite as instant, but. But there's been nobody who said, you know what, we're shutting off the spigots for a while. Call us, call us in June. Like that hasn't happened. And to be honest, even the last week or two, you've seen some deals and agreements that have come, like with Saudi Piff, not just partners into venture capital funds. There was a big private credit partnership that got announced yesterday, I think with Saudi Biff. So clearly deals are still happening. Venture fundraising as a whole though, has become. It's not even become. It is still really bifurcated. Right. You still have the hats and the have nots and these massive multistage firms that are gobbling up most of the money. And on the AI bubble side, I mean every, it's funny, almost every venture capitalist and certainly the industry as a whole is just looking at three things, right? The IPOs of Space X, anthropic and open air. Right. Because that can those, if successful, can solve all the problems that they've had for the last several years. And Space X goes gamblers mindset, make

[Noah Hirschfeld]

it all back in one trade.

[Dan Primack]

Well, it used to be VCs. Just talk about home runs. This is now like the Grand Slam in the bottom of the ninth to win the World Series. Right. And everything else. And that. And that's what they're banking on. And, and there's not a huge IPO pipeline, for example, other than that. You know, we had a story meeting this morning and somebody asked me, you know, well, with, with the cease fire, does that mean companies that were prepping IPOs are going to, you know, start back up again? I didn't see a huge number of companies that were prepping IPOs. There were some, but it's not like there was. It's not like from Liberation Day last year when you had five or six companies that were ready to price and then stopped. Yeah, there's not that much out there right now again, outside of those big three.

[Harry Stebbings]

Yeah, yeah.

[Noah Hirschfeld]

I mean, the ones that I can think of that, that are maybe more at the FIGMA scale are just looking at figma's track record in the public markets and thinking like, like, I'm not as good of a business as figma and I don't expect to be treated any differently.

[Harry Stebbings]

And when the stock popped, a lot of founders were thinking, oh, if I can get that multiple, I should be public today.

[Noah Hirschfeld]

Yeah, that's thinking like the ripplings and the deal.

[Harry Stebbings]

Yeah, all those companies looked amazing.

[Dan Primack]

Deals got its own issues, I think, which might be separate, but like. But by the way, this isn't just a venture issue, though. Private equity firms, which, you know, more mature, slower growth, but more mature companies, they haven't been taking their stuff out either, and they don't have anywhere else to go except sell to other private equity firms. It's just this broader non IPO issue right now.

[Harry Stebbings]

Yeah.

[Noah Hirschfeld]

How much are you spending. Are you spending time tracking the data center ban that Sanders has sort of proposed?

[Harry Stebbings]

It's also a bunch of different states.

[Dan Primack]

Yeah, it's a bunch of different states. We had a big AI event in D.C. two weeks ago, and I wrote this a little bit. And on the sidelines, I spoke to the CEO of Constellation, which is one of the big electricity providers, the data centers. And I asked him, this was whatever, three weeks into the war and I. And oil prices were spiky. And I said, how much, you know, what's this doing to energy dealmaking in the United States right now? Just the rise in oil prices. He said it's having a little impact. He said it's the data center ban proposals that are having the really big impact. That's what has people freaked out. And I mean, Sanders, on the national level, you're not going to get anywhere nationally on this, but on a state by state level, you don't need much. You need a couple of states to do it. It is, it is something that the opponents have done a really good job on the PR and the industry has done a very bad job on the PR on this.

[Harry Stebbings]

Yeah.

[Dan Primack]

And it doesn't help that everybody's gas prices and home heating oil prices in places where that's relevant and electricity prices are all going up. Iran is obviously exacerbating it. So, but you know, if you're looking at your bill and the, this is something that is top of mind, while the bills are only getting, getting higher,

[Harry Stebbings]

what do you think the impact of the war in Iran will be on defense tech investing?

[Dan Primack]

I wrote about this today. We have to see what happens.

[Harry Stebbings]

Right.

[Dan Primack]

It's a pretty fragile piece. It's unclear whether Hormuz is even open or not now.

[Jeremy Gallen]

It was.

[Dan Primack]

Maybe it's not. You know, what I wrote this morning was, I mean, I thought a lot yesterday after Trump's civilization tweet. Right. That if he really went through with what he said, and I know some people are making some odd arguments that, oh, well, it's either a nuke or not a nuke. No, there's a lot in between. Right. You bomb some major power plants that are for civilians or desalination plants or the power to desalination plants, and people don't get water anymore, let alone can't do crops or feed, or feed animals, etc. I, you know, defense tech has boomed in terms of venture capital, which is such. There was almost none of it, you know, seven or eight years ago, and there's so much of it now. I think it could have turned Silicon Valley again back against defense tech if the United States had done something that a lot of people viewed as a war crime or at least as inhumane.

[Harry Stebbings]

Sure.

[Dan Primack]

I think the fact that we have a cease fire and Trump didn't go through with that I think is probably a bit of a save for defense tech in the midst of a boom. I think you've got this, this huge upsurge in all sorts of defense companies that could have actually come to a halt pretty quickly. Not all firms entry stuff and still would have invested founders funds. Still would have. But that, that broader swath of venture capital that fills out those rounds I think might have slowed down if the military had done something, the Pentagon had done something that, that a lot of people viewed as morally indefensible.

[Harry Stebbings]

Yeah.

[Noah Hirschfeld]

Something I thought was notable is that the, the American version of the Shahed was a government program and they use some private, you know, contractors for it. But the smartest, the smartest defense tech play three years ago was just to make the Shahad and make a lot of them. And it seems like no company actually had the foresight to do that. And it ultimately had to be led from, from the dod, I guess.

[Harry Stebbings]

Yeah. Interesting.

[Dan Primack]

Well, and by the way, I haven't looked to see what's happened with the stocks. But I mean, something that is going to have to happen no matter what happens in Iran. Ceasefire. No ceasefire. The standard munitions stockpiles are going to have to get refilled.

[Jolly Rose]

Right.

[Dan Primack]

We are using a lot of bombs and a lot of stuff that's going to have to all get refilled. And I know Palmer Luckey and all others have talked about how we don't have enough of that prior to all of this happening and that stuff has to get done and there's going to be people who sell that.

[Harry Stebbings]

Yeah, yeah, that makes a lot of sense. Well, thank you so much for taking the time to come chat with us. The Axio show is live and available everywhere, I'm sure. Go check it out and we will talk to you soon. Dan, have a great rest of your day.

[Noah Hirschfeld]

Scoop, great to see you.

[Harry Stebbings]

Thank you. Up next we have Lior Susan from Eclipse. He is the founder and CEO. We'll be talking to him about Eclipse's $1.3 billion raise as industrial tech shifts from innovation to scale production with companies like Cerebras and Volt. What's going on? How you doing?

[Lior Susan]

They're in glass. Thanks for having me.

[Harry Stebbings]

Welcome to the show. Please kick us off with an introduction and some background.

[Lior Susan]

Yeah, it's great to be here. First of all, love your show. Yeah, we started the firm 11 years ago. We all operators that left their job building companies in the physical world to build a firm that we can build more than one company at a time. As you can guess, it was Fairly contrast controversial 11 years ago to talk about defense manufacturing, chips, mining, etc. It feels like a little bit less controversial right now. And yeah, we grow the firm roughly to a $10 billion AUM and we just announced our raised of 1.3 billion.

[Harry Stebbings]

Let's hit the go. What was the, what was the prehistory of the, of the firm? How did you get into investing? Was the first deal? How big was the first fund? Tell me some background.

[Lior Susan]

Yeah, first $125 million. Feels like many moons.

[Harry Stebbings]

It's not bad though. How did you set that up? A lot of people started 20 or 51. 25 is not bad.

[Lior Susan]

Yeah, the ignorance was the power. I never invested a dollar before Eclipse, so it might be that one. I grew up in the military. I went to the special forces. Then I did a company in the networking space. Cisco bought it, I moved to live here, spent three years with McNamara while he was the CEO of Fluxtonics. Fall in love in US manufacturing and felt all of my friends in Silicon Valley can only spell the words enterprise software. And I know nothing about enterprise software. I don't like enterprise software. And 85% of the world GDP is physical industries. And I felt it's kind of weird that everyone is telling me you need to go after big markets after big tams. But everyone is following their friends into the enterprise Software While those 85% of the world GDP don't have a platform and left to start that platform.

[Harry Stebbings]

Yeah. Talk to me about the Cerebras investment. How did you meet the founder? It was one of these companies that I'd heard of and I'd seen a lot of negative takes saying that it was the wrong path, that it wouldn't apply to where the current models are going. And then I tried it and it was really fast and it just felt like magical. And so I was all of a sudden converted to be very excited about the company. Where before I was sort of uncertain about how it would pencil out. It felt like there was a lot to be done. But you obviously invested early. How did that come together?

[Lior Susan]

Yeah, we've been around the company for now 10 years. It's been a moment. Yeah, exactly. But a lot of our companies, and I think a lot of those companies in that space, it starts by a fundamental view that wafer scale integration, basically the short version, you take the entire wafer and you interconnect between the core. When we have an idea of a chip, essentially it's a square, but it don't come from the machine like that. It's actually come as a rounding. And then we cut it into squares, into chips. The idea here is you take the entire wafer and you connect it to a lot of the chips and you create essentially one very large chip. And naturally, when we made the investments in 2015, we didn't know AI will be exist. What we did know, because we build by ourselves and operate those chips and factories and fabs, we knew that Moore's Law is going to hit the limit. From physics point of view. We go into we to are going and 2 nanometers already. Let's assume we can do 1 nanometer. That's about it. There's nothing after that. And we were looking for a new physics and a new physics mean hey can you connect to a lot of those cores in order to create one big chip. And we decided that we are going to take over companies like Nvidia and others. And it was not easy but I think now we are extremely excited about the company and the growth of the business.

[Harry Stebbings]

Yeah, yeah. It seems like it's in a fantastic position. Now talk to me about Vulcan forms. What was the back history there?

[Lior Susan]

Yeah, in some way same story physics start with physics of. In the case of Vulcan forms we are manufacturing high precision metal parts. And you know historically a lot of those machines being using 1, 2, 3 maybe 4 lasers. We are using 160 laser of fiber into a single head and we melt powder really really fast. And the hard part there was like how to control something that is so powerful. It's actually we got a call from the US Dow many years ago and asking ourselves basically start to investigate why we are buying all of these lasers because it looks suspicion for them. We're like no, no, we are just. We're just building metal parts. Nothing, nothing, nothing too sketchy. And yeah company booked multi billions of dollars deals last year and a billion dollar deal the year before. And Kevin Cascale and the team there is doing phenomenal job. We are building now four factories in US scaling the operation to build high precision metal parts for medical devices, consumer electronics, aerospace and defense etc.

[Harry Stebbings]

So yeah, it's a big fund you're using. We I imagine you take board seats, you leave rounds. Is that roughly correct? How many companies do you want in the portfolio? How deeply do you want to be involved? Do you try and pick a single winner in a category or do you look at more secular trends and try and get a broad exposure to the whole category? What's your thesis?

[Lior Susan]

Yeah, our LPs put us in the venture bucket and then in the growth back it when they're thinking about how they are allocating capital those US Endowments and foundation we call ourselves operators with capital. We are all operators and founders when we build those businesses alongside the management team. So we actually do very few deals every year and we have actually a small amount of position in each fund and I'll say roughly we incubate one third of the companies and two thirds who will lead seats. Series A, series B, series C, series D whatever it is, we only lead. We always take a board seats and walk very very closely to the management team and tell you the truth, I enjoy more building Companies than investing in companies. So regardless if I end up investing and maybe it was not my idea to start the company, I want to feel like I'm part of the management team building those businesses. That's my passion.

[Noah Hirschfeld]

Jordy, very cool. Where do you think robotics is overhyped and where do you think it's underhyped right now?

[Lior Susan]

Yeah, actually I wrote something on my LinkedIn maybe last week that it feels a little bit 2021 in eclipse sectors we'll start seeing some of the bad behavior that maybe was in the enterprise software in 2021 happening now in our sectors. You see Those companies raising $1 billion out of the gate or some, some crazy valuations.

[Noah Hirschfeld]

Yeah, or doing, doing. I'm assuming there's instances where a company, you guys may have backed a company in a category, you know, eight years ago and then a new company gets formed in the category and within you know, six months they're valued at the same price. Even though there's wildly different from a kind of technical progress standpoint.

[Lior Susan]

There is some of that. I goes back to first principles as a company, as a person, as an entrepreneur that like to build companies. I think, you know, there is a way to build companies. There is a for sure a way to build companies in the physical world. You talk about building factories, you talk about supply chain, you talk about capex. You cannot all like push full max out of the gate, burn really fast because you believe the contracts will come and you believe that always the markets will be there to fundraise you. So we're just trying to bring some sort of a discipline of how to build those companies. But goes back to your questions on robotics. We've been doing robotics for 11 years now out of Eclipse and a lot of us did robotics much before in our operating life and I think, you know, we are now crossing the chasm with robotics moving from a control based plc, very custom to a much more general purpose, much more using physical AI. And as a result of that we'll start seeing adoption on the commercial side. That is super exciting.

[Harry Stebbings]

From your position on boards. I don't know how much you can talk about this, but I'd love to know your view and expectations for the IPO window we were just talking about with Dan Primak. A lot of, a lot of attention paid to the big three, Space X, OpenAI anthropic. But what else are you seeing in terms of how companies are gearing up for the IPO window?

[Lior Susan]

I mean, I think it's interesting, right? Of course, SpaceX, I think arguably even open AI. And I'm not to trying Tropic have a much closer part of the business to what I built to maybe the traditional software that kind of was leading the chart. I think real assets going to have a great moment in the public market. I think people value you forget it goes back to the 85% of the world GDP. The reason SpaceX can have that type of an IPO is because they solve something. Think that it's really, really hard. So it's really, really hard for the second person to solve it as well. I think the reason you will see the correction in the SAS world is you add a lot of companies, the entry is very easy, the time is not too big and as a result the public market. Correct. So I do believe we're going to see quite a lot of companies in the semiconductor world, in the space, in the AI infrastructure, in the data center. Those worlds going public in the next 18 months or so.

[Harry Stebbings]

Yeah. What are you tracking in terms of trends in the lunar economy? It does feel like we're at a turning point moment with SpaceX and Starship coming online. There's lots of interesting.

[Noah Hirschfeld]

You mean space economy, right? The lunar economy.

[Harry Stebbings]

Oh yeah. It's not a lunar economy, it's orbital economy is the buzzword.

[Lior Susan]

I was fine.

[Harry Stebbings]

I'd say Eclipse name confusing any variation from low Earth orbit to beyond. Some of this stuff. When you talk about mass driver on the moon, it starts to seem 10 years away, 20 years away. Harder to underwrite, harder to think about. But maybe as a venture capitalist you can start thinking about it. What are you looking for in just space? Broadly.

[Jeremy Gallen]

Yeah.

[Lior Susan]

I think when you think about Henry Ford when we created cars, the is so much economy that is being developed and so much GDP that is being developed by the ability to move people much faster than you could move before. I think we are going to see something similar with the increase of our ability to travel to space and lowering the cost significantly. And as a result we're just going to see a lot of new businesses being built. We are partnering with an amazing company called called True Anomaly that building Space Defense Prime. So you know, it's not only you're going to travel to space, you're also going to have conflict in space. We are seeing a live one, maybe a ceasefire with Iran right now. But you know, I think since I mentioned his name, I said on an interview yesterday, I used to say that this is the best time to build in this country from Henry Ford and Carnegie or post World War II and actually change it to this is the best time to build in this country, period. And the companies that I'm passionate about. So I'm just extremely excited to have the capital and the relationships to go and build as many companies as we can.

[Harry Stebbings]

Well, congratulations on the fundraise, congratulations on the progress and thank you so much for taking the time to come chat with us. We'll talk really soon.

[Noah Hirschfeld]

Great to hang.

[Lior Susan]

Thanks folks.

[Harry Stebbings]

Have a good one.

[Noah Hirschfeld]

Cheers.

[Lior Susan]

Thank you guys.

[Harry Stebbings]

Up next, we will be revisiting the Axios NPM package hack that happened the supply chain attack. Npm, of course, Axios npm was downloaded 100 million times per week and it was compromised by North Korean threat actors. We talked about a little bit on the show last week, revisiting it with Faras Abu Khadija. I hope I pronounced that correctly.

[Noah Hirschfeld]

What the problem is that right?

[Harry Stebbings]

Yes. So we can ask him. Yeah, we can ask him. Socket detected the malicious update within six minutes and we are lucky to have FIROVZ join us.

[Noah Hirschfeld]

What were you guys doing for the six minutes? Asleep at the wheel. No, I'm kidding.

[Faras Abu Khadija]

No, no, no. Definitely not asleep at the wheel. It takes time to download packages, scan them, put them through our battery of tests. So I think six minutes is actually pretty good, to be honest.

[Noah Hirschfeld]

No, it's fantastic. I'm just.

[Harry Stebbings]

But yeah, maybe zoom out and tell us about like the actual process that Socket runs your business, how the system works and how you're able to detect supply chain hacks and cybersecurity threats so quickly.

[Faras Abu Khadija]

Yeah, totally. So Socket was among the first to detect and report on this incident. We built a system that goes out and downloads every open source package in existence within a few seconds. So we support about 19 ecosystems systems and this includes really all sorts of third party code that might be, you know, used to build applications today. Includes things like your models, your, you know, your open source dependencies, your, even your editor extensions, your chrome extensions. Like really any code coming from, you know, third party sources. And we put it through a battery of, you know, really intense static analysis, maintainer behavior analysis, and then of course a bunch of AI and then human researchers as well. And we try to help kind of make a determination. Is this something safe that you want to use within your application or within your organization?

[Harry Stebbings]

So can you talk about the shape of the threat that was posed by the Axios supply chain attack? Because there's a wide range of zero day exploit that gives you full access to someone's device or computer or system all the way to just something that. Okay it would crash if this was. If this exploit was used. Right?

[Faras Abu Khadija]

Yeah. I mean, maybe we just start from the beginning and summarize the attack for folks. Yeah. So, I mean, there was a North Korean state actor that socially engineered the lead open source maintainer of the Axios package. And it was honestly quite a sophisticated and impressive effort. They posed as a founder of a fake company, they created a fake Slack workspace, invited this, you know, invited the maintainer to join it. Yeah, they staged a fake Microsoft Teams call, and the website was made just incredibly compelling. They use the official SDKs from Microsoft Teams to create, like really realistic components in the page. They joined the call. And, you know, by the way, this is. They also developed a relationship over the course of, you know, weeks. Right. So this wasn't like a, like a, you know, a situation in which you would expect to be on guard or on defense. And at some point in the call, the call just cuts out and the browser says, hey, you got to install an update. And it gives them a binary file that they're told to install. And so this maintainer thinks, okay, I guess I got to install this update real quick so I can get back into the call. And it turns out that's how they compromised their device. So it's not just like a phishing link or something like that. I mean, this was a targeted attack. They also targeted me and a bunch of people at our company as well. So they targeted a whole bunch of the top NPM maintainers who, you know, have access to a lot of packages.

[Harry Stebbings]

Interesting. Then, then in terms of, once they get control over, they fish a particular credential, a particular device for a developer who has access to push changes to a package like Axios. What are they actually changing in Axios to create a vulnerability in the supply chain, in the software supply chain.

[Faras Abu Khadija]

Yeah. So they publish poisoned versions of the package that silently install what's called Remote Access Trojan, which is basically a way for the attacker to just remotely control your device and basically do whatever the attacker wants. It's like they're sitting in front of your computer on the keyboard, you know, typing whatever they want onto your. Onto your system. And what they did with it was they kind of pulled all the most interesting files and credentials off the system. So things like if you have a crypto wallet, like they're taking the keys for that, they're going to definitely want the crypto if you got, you know, if you're logged into npm. Right. They pull those credentials so they can spread like as a worm and Kind of continue to infect the next set in the attack. Right. So it's actually like this self replicating kind of cycle where they get these credentials and then they use them to go on to the next stage and you know. Yeah. And then, I mean the thing I think I want to emphasize here for people is this isn't just an isolated incident because this has been kind of the most recent blow in this kind of series of compromises and attacks against the software supply chain that has been happening really over the last six months in a really intense manner. And we've seen it really pick up in the last month with Team PCP compromising Aqua Security and the Trivi Scanner. And then that cascaded into Light LLM being compromised. Another security company, Checkmarks, was compromised.

[Noah Hirschfeld]

What happened with Light LLM and do you have a good sense of how that contributed to the breach at Merkor?

[Harry Stebbings]

So

[Faras Abu Khadija]

it's part of the campaign of Team pcp. So they dropped the same kind of self propagating worm called Canister worm into the package. And what you have to realize is once you run a compromised open source package on your system, you know, you kind of have to rotate all your credentials, like all your tokens and keys and passwords and, and it's a really hard thing to do very thoroughly and very completely. And so I think that we're going to see a long tail over the next, you know, probably 12 months of follow on attacks from this, from this set of compromises because the group claims, Team PCB claims that they've stolen 300 gigabytes of compressed credentials. So that's, you know, that, I mean think about that. 300 gigabytes of stolen passwords, API keys, GitHub, action tokens, I mean they, they're sitting on so much, it's like a gold mine in terms of like what's going to, what's going to follow on from this. So I think it's not surprising that you know that you're seeing companies affected, right?

[Harry Stebbings]

Yeah. So why the boom in the last six months? It feels like it must be tied to Vibe coding or AI agents. Is this that they have more powerful tools so they're able to do more damage, or is it because our systems are getting weaker because we're pushing more Vibe code to production? Is it both what got us to this place where we see this takeoff in cybersecurity threats?

[Faras Abu Khadija]

Yeah, well, you're absolutely right. It's definitely become a top concern. I think we're hearing a lot of our customers and prospects that are contacting us that this has now become a board level concern. Everybody is asking how are we not going to be affected by the next one? So I would say that fundamentally, if you really zoom out and ask why is this a problem? Why is this happening? It's because the whole software supply chain is built on blind trust. I mean, you're downloading code from random people on the Internet that you've never met, you don't know who they are, and you're like, let's just run it, right? Let's just hit run. And I hope it's fine, I hope it's good and I'm going to give it full access to my system. No permissions, model, no review, no one looks at the code before they run it. Unlike an iPhone app or mobile phone app where it has to ask for permission to do sensitive things like access your camera or your microphone or your location or your contacts or your files.

[Luther Lowe]

Right.

[Faras Abu Khadija]

Open source packages just get everything, you know, you just run them, they get everything. So, you know, also there's this asymmetry in security and this has always been true. So this is, you know, kind of more of the bigger picture. You know, part of the bigger picture here is that defenders have a much harder job than attackers because they have to guard against really all the ways that you can possibly get attacked. And the attacker has to just find one way in.

[Noah Hirschfeld]

Right.

[Faras Abu Khadija]

So it's asymmetric. And, and so when attackers realize, hey look, you know, open source, the way that companies use it has changed in the last decade. We no longer use, you know, just a handful of components like WordPress, Apache, PHP, you know, these kinds of big components we actually pull in. In some cases it's like a thousand open source libraries just to get hello world to show up on the screen. Right?

[Harry Stebbings]

Yeah.

[Faras Abu Khadija]

It's crazy, the diffusion in the number of these things. So they realized, look, I could just attack one of these things, one of these libraries and I can get into a company that's so much easier than attacking head on and trying to hack the company directly.

[Luther Lowe]

Right?

[Faras Abu Khadija]

I can find one of. And we have customers, by the way, they have 500,000 plus open source components in their environment. So just think about that, right? Any one of those is a way into the company.

[Harry Stebbings]

Yeah, the funniest package is even. It just tells you if a number is, is an even number and it's. And it has one dependency is odd because it's a.

[Faras Abu Khadija]

Everybody loves.

[Harry Stebbings]

Exactly. It's a great example. Tell me more about the shape of your business. I Mean, it seems like you're getting a lot of calls from companies and boards, like, what does it look like to work with you? How are you plugging into companies? Do you have a business line around going and hunting bug bounties? How, how should I think about the business of Socket these days?

[Faras Abu Khadija]

Yeah, well, look, people contact us when they want to get their software supply chains under control. Right now what that looks like is companies that are deploying AI agents and AI coding assistance across their companies have one big question in their mind, which is how do I know what my agents are doing? How do I know what my developers are doing with those agents? And that is the, the problem that we help them get under control. So the way to think about Socket is we are a software supply chain defense company.

[Dan Primack]

Right.

[Faras Abu Khadija]

We protect your software supply chain. So when an AI agent is making a decision to go and install something in order to accomplish the task that's been given to it, you know, it will go through Socket first. So we are the guardrail to ensure that no malicious components get installed. And if you take a concrete example, Axios, the attack we've been talking about, that malicious package was live for about three hours. Meaning, you know, anyone who was asking their agent like, hey, go build me whatever. Right. Doesn't matter what. One of the first things is probably going to grab it because it needs to do HTTP requests, going to say, oh, Axios. Right. And you know, so the question is, how do we, how do we before that gets taken down, right before the, or even before the community is aware, how do we defend our organizations and our applications from those, those packages that had these implants? Right. And you know, and yeah, it's really top of mind for people. I would, I would say it's kind of become like a, you know, number one concern for CISOs and for boards.

[Harry Stebbings]

Yeah.

[Noah Hirschfeld]

What is your view on cybersecurity as a category? I think a lot of, you know, we've talked to people on air, off air that were surprised of about the sell off in Cyber due to LLMs, just because LLMs themselves are creating all of these new threat vectors. And so there was kind of a disconnect there. But what is your sort of more general outlook on the category?

[Faras Abu Khadija]

I think in the short term security is going to get worse, it's going to get harder. So actually I think the answer is really the opposite. Like companies and products and things like Socket are actually more needed than ever before. You know, with, with Mythos coming out yesterday, you know, that's going to find A ton of vulnerabilities. And you know, it's finding vulnerabilities all across the software supply chain. And so, you know, the, you know, I think, you know, more vulnerabilities discovered means there's more urgency to fix the ecosystem. And it becomes, it goes from being, you know, a lower priority on people's lists to a higher priority. And so I think, you know, the short to medium term effect is going to be massive awareness business, it's going to be supply chain security becoming more top of mind for everybody. That's obviously great for us as a business, great for the ecosystem, because I think it's hard to invest in things and get justification for budget if you're a security leader, if you don't have, you know, a fire or an emergency to point to. And so this, this really helps there. I think longer term, you know, we have to see. I think, you know, ultimately I think I solves the asymmetry problem that we were talking about earlier because for the first time, defenders now have an infinitely scalable army of AI agents doing their bidding and doing continuous security analysis. And that's all work that would have been way too expensive or impractical for their humans to do before. And so the attacker's advantage of only needing to find one way in starts to erode when the defender has the ability to kind of continuously audit everything. And so I think longer term, once we get through this rough period, I actually am very optimistic about, you know, security improving. But one thing I will say is, you know, with security, one of the reasons I love the field and why it's such an exciting field to be in is that, you know, it's a cat and mouse game, so it's a dynamic system. So it's not like, you know, architecture or bridge building where, you know, you learn the rules of physics and, you know, how to build a bridge that's going to, you know, withstand gravity and these forces that don't change, you know, in security, the minute you think you've got things under control, you know, the attacker evolves, the attacker switches their strategy and they have access to the same AI tools that the defenders have. And so, you know, it's really a field that is, I think, always going to be growing and always, always going to be, you know, a great business to be in.

[Noah Hirschfeld]

Has a cybersecurity company ever got caught like sort of larping as a hacker group in order to drive demand, you know, sort of like hacking a popular company in order to drive demand for their product as you said you, you said CISOs oftentimes need to be able to point at a fire to justify budget.

[Faras Abu Khadija]

You know, that's super funny you asked because that was always the conspiracy theory that folks had about the antivirus companies back in the 90s and the 2000s was that they were the creators of the viruses so they could sell you the antiviruses,

[Noah Hirschfeld]

create the problem, sell the solution.

[Faras Abu Khadija]

Yeah, I mean, I think that I'm not aware of any companies getting caught doing that. I think there's enough bad guys out there that have realized the opportunity sitting there in plain sight that I don't think that you got to go to conspiracy theories to explain why attack is.

[Noah Hirschfeld]

No tinfoil hat needed.

[Faras Abu Khadija]

Yeah, no tinfoil hat needed. Yeah. I mean, how do you think about

[Harry Stebbings]

these economic impact assessments when Axios. I feel like everyone jumped on it very quickly. Andre Karpathy shared that he, he didn't have the repo pinned, but he hadn't updated so he was able to dodge it for that three or six hours. A lot of people got lucky. But do we have an idea of the actual toll that that particular attack had? Because it felt like the number could have been very huge, but a lot of people were able to get to it fast enough that there wasn't necessarily a massive crypto breach or a massive PII beach breach. But do you have an idea of like, how the industry is thinking about the size of the scale of the economic impact?

[Faras Abu Khadija]

Yeah, well, I don't have an economic dollar amount for you, but if you look at the number of downloads per week of this package, it's 100 million weekly downloads. Yeah, that, you know, you figure, you do the math on that and you figure out like, what does that mean across the three hour window? I mean, you're talking hundreds of thousands of people who installed it. And that's, you know, across CICD environments, local laptops, that stuff that's been shipped into production. If you take, you know, another metric would be, you know, how many folks have reached out to Socket, you know, in the 24 hours following that attack to become a customer and make sure that, you know, they could use our tools to assess whether they were affected and to protect themselves for future attacks. We had almost 2,000 organizations sign up for an account in 24 hours. Yeah, yeah, which, you know, to put it in perspective, it's a, you know, it's a significant percentage of all, you know, our full user base. So, you know, I think this is very, very widespread. And this is the thing about the supply chain Right. Is like, it's really not a matter of like if you're going to get hit when you're talking about these very, very widely deployed dependencies and you know, including even some of my own code. Right. I know I have these, you know, you picked on is even, you know, I have some code that is similar to that. A little bit less, less, less outrageous of an example. But you know, and it's in, it's in every, it's in probably almost every Node JS app and that's just how, that's just how the supply chain works today. So it's really not surprising that everyone is going to get hit by this eventually. Right?

[Harry Stebbings]

Yeah. Well, thank you for coming on the show and breaking it down for us.

[Noah Hirschfeld]

Yeah. Really appreciate everything you're doing.

[Harry Stebbings]

This is more important than ever. And so have a great rest of your week.

[Noah Hirschfeld]

Come back on soon.

[Jolly Rose]

Soon.

[Harry Stebbings]

We'll talk to you soon.

[Luther Lowe]

Thanks guys.

[Harry Stebbings]

Goodbye. Up next, we have Kassim Muthani from Depth first announcing a big round company also launched its first in House Model DFS Mini 1. Focused on vulnerability detection and smart contract. We'll bring Kasim into the TVP ultradome. How are you doing?

[Jeremy Gallen]

Hey guys.

[Kassim Muthani]

Doing well.

[Faras Abu Khadija]

Thank you for having me.

[Harry Stebbings]

Of course. Good to see you. Nice step and repeat behind you. Are you at an event or is this just your normal, normal background?

[Kassim Muthani]

This is like my background. We had like an amazing event with the Mirror of San Francisco and we got this for that.

[Harry Stebbings]

That makes sense. Well, since it is your first time on the show, please introduce yourself and the company.

[Kassim Muthani]

Yeah, my name is Kassimitani. I'm one of the co founders of Dev First. We are building intelligence to discover triage intermediate vulnerabilities at scale in an enterprise environment. We just raised a $80 million Series

[Dan Primack]

B round from Veritech.

[Noah Hirschfeld]

Congratulations.

[Harry Stebbings]

When did you raise the last round before this?

[Kassim Muthani]

We raised in early January, so it's been remarkable less than 90 days. And the reason why we raised it was because we're seeing so much traction, customers are seeing so much value from our product and then we're doubling down on our research efforts like you mentioned at the top of the segment. So we are investing really heavily on training and fine tuning our own models.

[Harry Stebbings]

Let's talk about the customer impact first. What are the companies that are using your service and plugging in and getting value and sort of walk me through the user journey of actually working with you.

[Kassim Muthani]

Yeah, that's a very good question. So we work with some of the largest companies in the world Fortune 500 companies. We also work with really fast growing startups ranging from companies like Lovable, ClickUp, Supabase, like the top names in tech. And the way they use our product is that they connect their code repository and their environments, so their staging and their production environments and then we go, our agents go and figure out how the application is supposed to run and then deviations from the expected behavior. So they figured that out, they replicated in production and then they give remediation instructions to agents and developers.

[Harry Stebbings]

On the research side, walk me through building an in house model. What was special about that did you have to use? I imagine you didn't do a whole base pre train yourself. But what is unique about the model and what were the keys to success?

[Kassim Muthani]

Yeah, so you know we, when we started a company almost two years ago, we really believed that software security is a very deep problem. Now everybody in the market seems to realize that. But back then people thought that you know, the crowd strikes and follow up to a sort of monopoly in the market. But in the age of AI, as code is being written faster than ever before and attackers are already leveraging AI to exploit vulnerabilities, a new type of solution needs to exist. And that's what definitely first is. So we invested very heavily in building a world class research team. My co founder Andrea amici comes from DeepMind, spent seven years building reinforcement learning there before LLMs were sexy. This is like back in 2019. And my other co founder Danielle was a co founder of Fair Wholesale and before that he led security at Square and Cashapp. So that's our background as a founding team and then we also have like some of the top researchers in the world working with us in terms of like building our own one model. We used GPT OSS as our base model and then we took vulnerability data, we planted flags and then we had the model try to find those flags and then use an RL loop to basically improve the model's performance. And we were able to do better than Opus 4.6 at 1:10 the cost in this particular benchmark.

[Harry Stebbings]

That's very cool. What was your reaction to the Mythos news yesterday? It seems like really remarkable results in bug finding and vulnerability tracing, lots of partnerships. How did you process the news? What are the key takeaways?

[Kassim Muthani]

Yeah, I mean I think it's amazing news. It's like validation that security is such an important area in the age of AI, something that we believe for two years. The reason why I work 16 hours

[Noah Hirschfeld]

a day is because I believe that

[Kassim Muthani]

in the age of AI software needs to be secure. So I'm really happy Anthropic is investing in this. And Anthropic is also one of our partners. So we work with Anthropic, we work with OpenAI, we work with DeepMind, work with all the labs, and our product sits on top of that. So we use the best model for the use case that the model is good at. So we use, you know, 4.6 for code analysis, we use like other product, other models for capturing the flag type of vulnerability detection I mentioned. So it's good news overall. But you know, in an enterprise environment, complex enterprise environment, you need to ingest all types of data. You need to figure out like, like the cloud environment, how the software is deployed. You need to figure out if there's a firewall there, if there's a WAF there, and our product ingests all of that data and then gives actionable vulnerabilities, the ones that really matter to our customers, and then with a click of a button they can just fix it. So we see that as being a significant value add of a product.

[Harry Stebbings]

Talk about the decision to plant the flags yourself versus what it appears. Mythos did was just look across every single open source project and just sort of maybe brute force a bunch of vulnerabilities until they found bugs all over the place. And it seems like they were able to find a lot of different stuff by just throwing every possible hacking technique at every possible open source repo. Is that the correct way to think about that strategy? And then do you think you'll wind up doing something like that in the future?

[Kassim Muthani]

So we did both actually. So we run our product, our model on open source too. So like we found hundreds of bugs, we're responsibly disclosing them because we don't want to get them out there so attackers can exploit them. So we found vulnerabilities in Chrome, we found vulnerabilities in Linux, like in really deep software that's existed not very heavily used products.

[Harry Stebbings]

No, only the most used products.

[Luther Lowe]

Only the most used, yeah, yeah.

[Kassim Muthani]

So, and that's helped us improve our product. And we have a team of world class security researchers on staff. So people who hacked iPhones for a living, you know, thankfully they're working for us. But like those types of folks who are going and validating the results and then helping us improve the model based on that and improve the product and the model.

[Harry Stebbings]

Well, thank you for everything that you do. We need more white hat hat hackers than ever Very clearly. We were just talking about the Axios hack.

[Noah Hirschfeld]

One final question Tyler on our team wanted us to ask. Why not use are you fine tuning on any of the Chinese open source models or do those scare you?

[Kassim Muthani]

We are experimenting with some of them. But you're an American company. We would love to use American models. I was actually. I met Jensen Huang yesterday and it was so amazing to see the investment that's going in in this area, especially in training open source models.

[Harry Stebbings]

Models too, right?

[Lior Susan]

Yeah, yeah.

[Kassim Muthani]

So we're very excited and we're partnering with Nvidia and he loved our vision. He thinks that in the age of AI, I mean, as agents are everywhere, security is going to be extremely important. So he's completely bought in to our vision and he's really excited about it.

[Harry Stebbings]

Yeah, very cool. Congratulations on the progress in the round. We will talk to you soon. Have a good day.

[Kassim Muthani]

Thank you.

[Noah Hirschfeld]

Talk to you.

[Harry Stebbings]

Goodbye.

[Kassim Muthani]

Thanks, bye.

[Harry Stebbings]

Up next we have the CO founder and CEO of Mutiny. Mutiny just raised $72 million from Sequoia Capital and Y Combinator reaching 8 figure ARR.

[Noah Hirschfeld]

Whoa.

[Harry Stebbings]

Bring in Jale Rose from the waiting room into the ultradome. How are you doing?

[Noah Hirschfeld]

What's going on?

[Jolly Rose]

Good, how are you?

[Harry Stebbings]

We're good. Thanks so much for joining the show. Please give us an introduction on yourself and the company.

[Jolly Rose]

So I'm jolly. I'm the co founder and CEO of Mutiny and yesterday we announced the new Mutiny, which is an agent that companies like Rippling and Snowflake use to create anything customer facing in order to get a deal from cold all the way to closed.

[Harry Stebbings]

Okay, yeah, walk me through. I mean, what does that actually mean? Add assets to landing pages, battle cards like walk me through the workflow of closing customers in the modern era.

[Jolly Rose]

Yeah, absolutely. So starting out, you probably want to warm up the accounts in a particular vertical. And so our customers will create personalized vertical campaigns. And then from there, once the SDR is involved, they want to start prospecting and get meetings with the right people so they can make prospecting pages in muni. The agent can even research the specific people that they want. They can pull in data from their CRM, any, any information that's available to them. The agent will access and create something really high quality that will stand out to that prospect as the deal progresses. Now we're looking at things like curated customer case studies. We're looking at business cases, ROI reports, pricing proposals. Even after the deal closes, there's a ton of expansion that the customer success team will drive so they can create impact Reports in Mutiny for their customers and they can do look forward strategies, the whole works in order to maximize revenue.

[Harry Stebbings]

Okay, bunch of questions. Where does the name come from?

[Jolly Rose]

You know, the mission of Mutiny was all about killing the dependency season. Go to market teams. I've led marketing teams, sales teams, and the biggest blocker to growth is always speed. And the blocker to speed is all of the little dependencies that exist inside of your team, outside of your team. And so it was really a mutiny against the status quo. That's where the name came from. And it just kind of stuck.

[Harry Stebbings]

And behind you. Is that a raccoon mascot? Explain that.

[Jolly Rose]

Yes, it is. This is our raccoon mascot. His name is Achoo.

[Harry Stebbings]

Achoo. Where did that come from? How did you pick a raccoon?

[Jolly Rose]

Do you want to know the real story?

[Harry Stebbings]

Absolutely.

[Noah Hirschfeld]

Yes.

[Jolly Rose]

So we were all in a circle. This is when we were about four or five people. And we're like, what are we going to name the raccoon? And one of our early employees.

[Harry Stebbings]

How did you get to raccoon? You're just like jumping through.

[Noah Hirschfeld]

It's just the default.

[Harry Stebbings]

Of course we're going to have. Have raccoon. No, explain, like, how did you pick raccoon? There's a million animals you could have picked.

[Jolly Rose]

Yes. Okay. So we were designing our brand and the designers asked me, okay, is there an animal that you guys really identify with? And there wasn't really anything coming off the top of my head. And then we took the whole team to angel island on a. On a camping trip. And the entire time we were there, we had six bottles of wine with us and basically no supplies. So it was just, it was awesome. And every time we would turn around with our headlamps, we would see this gang of adorable raccoons just slowly approaching. And then they would see the light and they would start backing up. And so the next day, the designer asked me that question again and I said, raccoon. And that's how we ended up with the raccoon.

[Harry Stebbings]

There we go.

[Noah Hirschfeld]

What's going on with email? Are you generating cold emails? Is it a waste of time now?

[Harry Stebbings]

Like, what's the equilibrium here? I think a lot of people are getting more cold outreach than ever. And it feels like we might be in this game theory.

[Noah Hirschfeld]

Yeah, Because I can imagine you guys helping somebody make a great. A great cold email. But at the same time, you guys are also set up for the golf and steak GTM as well, which is you play a nice round of golf and afterwards you pass Them a PDF?

[Harry Stebbings]

Yeah.

[Noah Hirschfeld]

Or a little deck. It gives them some more confidence, context, the conversation.

[Jolly Rose]

Exactly. So email is a really tricky one, I think. You know, we see this in our own data, we hear it from customers. The results are, are really bad. Most people don't really open emails anymore. Executives don't really open emails anymore. And so the, the engagement rate on email is really, really low. Which is why I think having a really personalized approach that's going to stand out, that's going to be different, that's truly and genuinely tailored to that person is going to be really important. One of the things that I find really fascinating is if you look at an average salesperson, they spend about 30% of their time selling and 70% of their time following up with customers, getting ready for tomorrow's meetings, creating all of those materials, nurturing the old deals that are going to convert, hopefully one day. And when you talk to CROs, for the most part, despite all the investment in data, they haven't really moved the needle in terms of increasing quota per rep. The rep is largely closing the same amount as the previous years. And I think the reason for that is that that 70%, that's really skilled cut custom work per customer that you're going after. I was on a call a couple of weeks ago where it was a great call, great enterprise brand, the right decision makers in the room. And at the end of the call they're like, please send me based on the challenges that we told you we have. Send us the three metrics that you can move for our business and relevant customer case studies for each of those. That would take a rep four hours to go create. You have to go look at hundreds of case studies, pull those things together. Whereas in the Mutiny Agent, they can just come in and it automatically will pull in the challenges from the gong transcript. It will, it will go through all of their case studies, it will sift and pull out the right stats, it will curate the, the assets in there and then they can go ahead and send a really nice, beautiful, forwardable thing to their customer that's going to get shared with the whole buying committee.

[Harry Stebbings]

Yeah. The chat is asking for the name, where the name for the raccoon came from, because I think we glossed over that. So sorry to go back to the mascot, but the mascot is a raccoon named Achir.

[Jolly Rose]

Yes. So it was the same group of people that went camping. We said, what should we name the raccoon?

[Harry Stebbings]

Raccoon. Yeah.

[Jolly Rose]

And right as we were gonna do that, someone sneezed yeah. And it just said achoo.

[Harry Stebbings]

Achoo.

[Jolly Rose]

And we all went achoo. That's actually a really good name.

[Dan Primack]

Let's go.

[Jolly Rose]

Let's go with that. I mean, in general, I would say the Mutiny brand. I think part of the reason people really like it is that it is raw, it's authentic. We don't really regulate what people can and cannot do. We hire people that are aligned with our values and we just let them be themselves.

[Harry Stebbings]

I love it. Well, thank you so much for taking the time to come chat with us. Congratulations. Did you. Did we hit the gong for you? You raised a $72 million round. We gotta smash it.

[Lior Susan]

That was a.

[Dan Primack]

Congratulation.

[Jolly Rose]

A previous fundraise, but yes, yes, you can hit the gong for that.

[Harry Stebbings]

We're still happy to celebrate it.

[Jolly Rose]

We have the money, so that's all that matters.

[Harry Stebbings]

That's all that matters. We'll talk to you soon. Have a great rest of your day. Goodbye. And up next, we have Jeremy Gallen from Charlemagne labs. He spent 12 years in Meta in trust and safety and left last year to focus on AI powered scams and building defenses. We're doing a whole security themed show.

[Noah Hirschfeld]

Jeremy, look at this suited up show.

[Harry Stebbings]

Wow, the matching suit. You look fantastic.

[Noah Hirschfeld]

Wow.

[Harry Stebbings]

You really like it. Is the mirror image of me. This is crazy.

[Noah Hirschfeld]

Nailed it.

[Jeremy Gallen]

The memo came through. I was hoping that I'd get that Maybach right downstairs.

[Harry Stebbings]

And I'm so glad you're up to speed on the show, but for those who aren't up to speed on you, give us an introduction and explain a little bit of your background.

[Noah Hirschfeld]

Yeah, John's intro. You said he left Meta to focus on AI scams, which kind of sounds like you're scamming, but I'm assuming it's the exact opposite.

[Harry Stebbings]

No, it's the opposite. We're doing cybersecurity.

[Jeremy Gallen]

That would be too easy. It's much easier to be on the offense than it is to be on the defense today. I tell you, it's, It's. It's wild out there. So, Yeah, I left MET after 12 years to focus on success.

[Tariq Mansour]

Right.

[Jeremy Gallen]

And basically my vision is that every employee of every company would have a watchdog. So the company is named after my. My dog, Charlemagne. She goes by Charlie. So the product is called Agent Charlie.

[Harry Stebbings]

Yeah.

[Jeremy Gallen]

The idea is like, you're using your computer and you're getting attacked now with novel kinds of threats that resemble legitimate communication. That could be on messaging apps. It could also be the standard phishing attack.

[Noah Hirschfeld]

We just heard about with the Axios attack. It was basically a fake. Microsoft Teams basically call that then cut out and and suggested hey update Microsoft Teams. Whole thing wasn't Microsoft Teams but the individual just was like confused because it just seemed like it was.

[Jeremy Gallen]

I think the nastiest trick is when it's the unsubscribe button. Is it self link? I think that's like the thing. So what I we've built, you know, the startup has been selling a product that will try and stop you from clicking. So it's like bad, bad employees but do not click. But the, the research that we've done to inform this commercial product is into the capacity, the capability uplift that's happening with respect to offense. So it's important to remember that if you're an adversary, that's a threat actor seeking, you know, financial gain or a state actor, you're availing yourselves of all this energetic tooling that, that we are using, you know, the sales tools, the, you know, the automation and so the core premise is that in an AI powered world, all phishing becomes spear phishing. You're not going to get a Nigerian prince email, you know much anymore. You're going to get extremely realistic, utterly compelling request from your boss or your manager or your friends and it's going to be catastrophic in consequences.

[Harry Stebbings]

How do you think about actual deployment? Because this sounds useful in a consumer context. I'm just thinking about the email that's from your bank and it has the unsubscribe button for some marketing email. You click it, all of a sudden you're logging in, giving away details. Is there an important distinction? It feels like consumer and enterprise is blurring together in many places. How do you think this all plays out?

[Dan Primack]

Absolutely.

[Jeremy Gallen]

I think as employees of companies we are using personal email as personal messaging apps on our devices for sure.

[Harry Stebbings]

Yeah.

[Jeremy Gallen]

I think as a business we're a B2B SaaS company with a research arm and I'm excited to tell you more about our research efforts. But yeah, I mean my dream is that the ARP is listening right now and would give this for free to. I'd like to give our software for free to anyone who holds an AARP card because elder abuse is devastating and it has huge consequences. But it's very difficult to market and sell to consumers. You know, product like this, people don't wake up and say today's the day I'm going to improve my security posture. It's sort of after they're attacked that they have a problem and a mess to Clean up. So we're.

[Noah Hirschfeld]

Well, you need to, you need to create the problem solution.

[Harry Stebbings]

Stop creating the problem. No one's creating.

[Noah Hirschfeld]

We were just, we were just talking with Paris from Socket, who's saying like the, the old tinfoil hat theory with, with cyber security and like malware products is that, you know, they would create the bugs and then sell the, sell the malware, create the viruses, sell the antivirus.

[Jeremy Gallen]

I think that's unethical. But also we don't have to do that.

[Harry Stebbings]

Yeah, there's plenty of scammers out there.

[Jeremy Gallen]

The bad guys are getting superpowers and so all we have to do is wait. And like I said about the research arm, our, our team is, has done some work matters, you know, model drop this morning. We work with them there. They're, I think, you know, I'm quite proud actually of what they're doing in the cybersecurity space because beyond infrastructure and coding attacks, what we're, we all know and aren't really talking enough about is that humans are, you know, the weakest link. So when a company wants to secure its perimeter, it's critical that employees are trained. And today, you know, they're training exercises. But, but the social engineering attacks aren't studied as much. And so, yeah, I'm really excited that Meta has taken a lead in going beyond just infrastructure and code vulnerabilities to looking at the capabilities that frontier models might provide adversaries in the social engineering and scam space.

[Harry Stebbings]

Yeah. So explain a little bit more about the eval suite for Muse Spark, because is it that the model is trying to, is the model model social engineering you or you're trying to social engineer the model? Like what, what are the two parties in this, in this eval? Like actually, how are they interacting?

[Jeremy Gallen]

Yeah. So we use an industry practice called LLM as a judge. So we don't test on human subjects. And our eval suite takes a model and has it role play as an attacker. And then we have a model that role plays as a victim and they're given, you know, instructions accordingly. And then we have an LLM judge whether it's the specific attacker is succeeding. And then we compare those attack different models to each other in the, in the role of attacker. And that's how we measure the kind of uplifter capability.

[Harry Stebbings]

Yeah. Do you think that is there, is there a world where these social engineers, like, I'm thinking of different bending points in where if some. Someone's running like granola and they're recording that particular. It wasn't a zoom call. It was a teams call for the Axios attack. And maybe an AI model could be listening in the background and sort of throw up a flag like, hey, it's actually there. I just checked. There's no update for teams. You don't need to click on that binary. You don't need to install that. This person's trying to take advantage of you.

[Jeremy Gallen]

That's exactly with the vision for our, our commercial B2B security product. I want an agent that, that, you know, the technology that we use is small language models so that it is on device and thus it's limited in its capabilities.

[Harry Stebbings]

Oh yeah.

[Jeremy Gallen]

I see a future where you have a real time AI for security exactly like you described.

[Harry Stebbings]

Yeah.

[Jeremy Gallen]

I think real time audio analysis with an SLM is, is way too big an ask, but small language models are improving, you know, just like all of the large models. So yeah, I mean, we need real time defense. I want it to be proactive too. I think the biggest issue is that when scammers succeed, it's because even intelligent and well trained people, employees of companies that work in tech even, are duped because it's a, it's as old as the Bible. Scamming is a, is an ancient art and it has nothing to do with, with preparation anymore. It has to do with, you know, we're being attacked by machine. We need machine defense.

[Harry Stebbings]

Yeah, no, that makes a ton of sense. Take me through the shape of the company. How big have you raised money? How long you been doing this? All this?

[Jeremy Gallen]

Yeah. So I've raised money last from the three investors that I'm really excited to be working with. They're Kevin Carter of Knight Capital and Chris Howard of Ritual Capital and Rafael Corrales at Background Capital. Collectively, they've backed more than 30 unicorns from IDEA Stage. And so, you know, I tell them that I want to be the 31st ready to. I'm ready to go. We got.

[Harry Stebbings]

Good luck. There we go.

[Jeremy Gallen]

Yeah, yeah.

[Faras Abu Khadija]

Love it.

[Jeremy Gallen]

So we, you know, we, we're in a kind of stealth mode right now, working with design partners on the SLM's capabilities.

[Lior Susan]

Sure.

[Jeremy Gallen]

And we're also, you know, if you visit our site, you can actually self serve for the real time fishing defense. So you could sign up right now if you probably have a Centurion, but if you have a credit card that works, you could put that into our website right now.

[Noah Hirschfeld]

Don't get spearfished.

[Harry Stebbings]

Yeah. Well, thank you so much for coming on the show. Congratulations on the pleasure. Yeah, it was great to meet you next phase.

[Noah Hirschfeld]

Thank you for suiting up as well.

[Harry Stebbings]

We appreciate it.

[Jeremy Gallen]

Yeah, I'm not wearing any pants, by the way.

[Harry Stebbings]

Have a great rest of you guys.

[Noah Hirschfeld]

Jeremy, goodbye.

[Harry Stebbings]

And people were disappointed that we didn't go more into the story about Satoshi. There is a full deep dive in the New York Times. My quest to solve bitcoin's great mystery. It is a long article, though, and so I think we'll have to touch on it another time. But we went through Adam Back's reaction, his. His disavowal of the accusations that he is satoshi. But there's a bunch of interesting little segments in here from the forums and the message boards of the day, analyzing the different writing styles, trying to see, did you dig into this at all anymore?

[Martin Casado]

I didn't read the whole thing, but people have speculated that it's Adam Back for a long time. It's kind of like him and how fit he's the other one. These are kind of the two main names.

[Harry Stebbings]

And there's one more, I think that comes up all the time.

[Martin Casado]

There's Nick Szabo sometime.

[Harry Stebbings]

Yeah, Nick Szabo. Yeah.

[Martin Casado]

But, yeah, I don't know if there was a lot of, like, new facts that came out with this, which I think is why it's like, not like super, super crazy.

[Harry Stebbings]

Yeah. There was also an HBO documentary on satoshi. I forget who the, like, who did that? Satoshi. Who did they accuse? In the 2024 HBO documentary directed by Cullen Hoback, the firm suggests that Canadian software developer Peter Todd is satoshi. And Todd denied that. And so you have.

[Noah Hirschfeld]

That's got to be the worst kind of title in the world from a security standpoint, is being accused of being satoshi.

[Harry Stebbings]

Yeah. Because you're just going to be attacked because you potentially have the keys to like $50 billion or something.

[Noah Hirschfeld]

Maybe more.

[Harry Stebbings]

I forget exactly, exactly what the number is. But yeah, that wallet is big. I still think it's possible that, like, the Satoshi wallet, like, the keys were just lost and the person. It's like sort of a lose, lose. Because if you admit that you lost the keys, then, like, everyone's like, oh, how do you even prove that? You can't prove that you lost something, but there's no movement. I don't know.

[Martin Casado]

Yeah.

[Noah Hirschfeld]

Also there's like, you could have. Someone could have created it and then had years and years and years and years to buy up an equivalent amount of supply a bunch of different ways. Then you have the. Basically you can say like, well, I've never sold right if Satoshi's wallet did start selling, it would probably, yeah, from a lore perspective.

[Harry Stebbings]

And the brand, you could potentially be making plenty of money from the other wallets. And then if that supply ever moves, the whole market's going to reevaluate basically the liquid supply and sort of tank what you have. And also just the aura around Bitcoin is that it has an anonymous founder, and if the founder was ever truly unmasked, it would be so much less of like a special project. And I think everyone involved wants to keep it that way, although these investigations will never cease to be interesting. And so you can go read it on the New York Times from John Carreyrou. Anyway, anyway, thank you so much for tuning in today. A bit of a shorter show. We're experimenting with different things. Obviously we don't have ad reads anymore and so we are going to be mixing it up with more stories, more interviews, different timing and more flexibility. And so we hope you enjoyed this show and we will see you tomorrow at 11am Pacific sharp goodbyes.

[Noah Hirschfeld]

We love you.

[Harry Stebbings]

Leave us. Five stars on Apple Podcasts Spotify Sign up for a newsletter tvp.com thanks for hanging out. Goodbye.

[Noah Hirschfeld]

Cheers.