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Episode #106: The $30 Trillion Question: Inside Anthropic's Audacious IPO Play

Episode #106 · September 10, 2026 · 1h 5m

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About this episode

In this episode of the Stewart Squared podcast, host Stewart Alsop and guest Stewart Alsop II tackle Anthropic's upcoming IPO and what it means for the broader tech landscape. They compare it to SpaceX's recent public offering, examining how Anthropic's projected $30 trillion in potential revenue stacks up against current performance and whether the company can sustain its growth amid mounting customer frustration with usage limits and pricing. The conversation ranges from the mechanics of SPACs versus traditional IPOs (including their portfolio company Ursa Major's SPAC announcement), to dual-class share structures that give founders like Dario Amodei control similar to Zuckerberg at Meta, to the emergence of local LLMs threatening the API business model. They also explore the cult-like culture at Anthropic rooted in Eliezer Yudkowsky's rationalist philosophy and "Harry Potter and the Methods of Rationality," the role of enterprise customers like AT&T in routing queries to cheaper Chinese models, and why the public markets have shifted toward mega-IPOs that make smaller offerings nearly impossible without alternative routes.
Timestamps
  • 00:00Introduction and Anthropic IPO discussion begins, comparing it to previous SpaceX analysis
  • 05:00Anthropic's revenue projections of 30 billion dollars discussed alongside SpaceX comparisons and enterprise contract momentum
  • 10:00AT&T's strategy using Light LLM router to reduce dependency on frontier models while maintaining Anthropic for difficult tasks
  • 15:00Customer sentiment toward Anthropic examined, highlighting communication issues and the company's machine learning engineer-focused cult-like culture
  • 20:00Enterprise programmers as Anthropic's core audience explored, drawing parallels to Microsoft's historical programmer-focused strategy
  • 25:00Technical competency hierarchy in AI programming discussed, including MCP updates and professional software engineering standards
  • 30:00Client-server dynamics analyzed with Apple dominating on-device AI and Anthropic controlling server-side inference market
  • 35:00SPAC process explanation comparing boutique IPOs from eighties and nineties to current mega-IPO dominated market
  • 40:00Public company requirements and CEO characteristics examined, comparing Dario to Zuckerberg and Alex Karp
  • 45:00Market bubble discussion and timing pressures driving Anthropic and OpenAI to pursue public offerings
  • 50:00Harry Potter Methods of Rationality religion explained as foundational belief system among machine learning elite
  • 55:00Dual-class share structures analyzed showing how founders like Dario maintain control post-IPO
  • 60:00S-1 filing contents and shareholder governance framework outlined with Apple board as exemplar
Key Insights
  1. The Anthropic IPO represents a fundamental shift in public markets where mega-IPOs now dominate attention and capital. Anthropic is forecasting over 30 billion dollars in potential revenue, even higher than SpaceX's projections, and is expected to seek a valuation around 2 trillion dollars while raising approximately 100 billion dollars. This concentration of capital in massive offerings has fundamentally changed the IPO landscape, making it nearly impossible for smaller companies with valuations in the mere billions to attract meaningful attention from institutional investors and investment banks. The sheer scale of these offerings absorbs most available capital in the market, forcing traditional mid-sized companies to seek alternative paths to going public.
  2. SPACs have evolved from vehicles for avoiding SEC scrutiny to becoming the modern equivalent of boutique IPOs from the 1980s and 1990s. During the 2020-2021 period, SPACs were primarily used to circumvent regulatory oversight, resulting in a dismal success rate with approximately 95 percent of SPACs trading below their standard 10 dollar offering price. However, SPACs are now experiencing a renaissance as legitimate alternatives for quality companies that cannot compete for attention against trillion-dollar offerings like Anthropic and SpaceX. Companies like Ursa Major, valued at 2.3 billion dollars, are using SPACs as a viable path to becoming public companies, provided they treat the process with the same seriousness as a traditional IPO and maintain proper quarterly reporting and governance standards.
  3. Enterprise customers are developing sophisticated strategies to reduce dependency on expensive frontier AI models, fundamentally challenging Anthropic's growth projections. AT&T serves as a prime example, having implemented an internal routing system using Light LLM that standardizes most programming tasks to cheaper Chinese open-source models while reserving Anthropic's Claude only for the most complex edge cases. This approach has resulted in flat growth from AT&T rather than continued expansion, suggesting that as enterprises mature in their AI usage, they will increasingly commoditize routine tasks and limit expensive API usage. This pattern mirrors the gradual enterprise adoption of SaaS between 2010 and present, where initial resistance gave way to widespread adoption, but ultimately led to sophisticated cost management strategies.
  4. There is significant cultural disconnect between Anthropic's leadership and its user base that could undermine long-term customer loyalty. Anthropic operates as what could be described as a cult-like organization centered around machine learning engineers who subscribe to rationalist philosophy and beliefs in technological singularity, stemming from Eliezer Yudkowsky's writings including "Harry Potter and the Methods of Rationality." This creates a situation where the company treats non-machine-learning-engineer users, including paying subscribers and enterprise customers, as essentially irrelevant to their ultimate mission. Examples like their confusing communication about rate limit increases demonstrate this disconnect, fostering ill will among users who feel treated like children rather than valued customers, though this may not matter as much for enterprise contracts managed by sophisticated IT departments.
  5. The rise of local LLM inference on consumer hardware threatens to disrupt the centralized API model that underpins Anthropic's revenue projections. With Apple M-series Mac Minis now available for lease at 200 dollars per month, the same price as Anthropic's premium subscription, and capable of running powerful open-source models with only electricity costs, a fundamental shift is occurring in the client-server dynamic of AI services. Apple is positioning itself as the dominant player on the client side with on-device AI capabilities, while Anthropic focuses on server-side inference, but as more developers and power users gain the technical sophistication to run local models, the question becomes whether Anthropic can maintain its premium pricing and growth trajectory when an increasing portion of inference moves to edge devices.
  6. Dual-class share structures have become the standard governance model for founder-led technology companies going public, prioritizing visionary control over traditional shareholder governance. Following examples set by Google, Facebook, Palantir, and SpaceX, Anthropic is expected to implement a dual-class structure where Dario Amodei and potentially his sister retain voting control despite owning a minority of economic interest. This structure, where Class B shares carry 10 to 20 votes each compared to one vote for publicly traded Class A shares, allows founders to pursue long-term visions without quarterly pressure from institutional shareholders. While this prevents the collective shareholder activism that historically provided governance oversight, it has proven successful for iconic CEOs like Mark Zuckerberg, though it fundamentally changes the relationship between public companies and their investors compared to the traditional structure from the 1980s and 1990s.
  7. The current AI boom represents an acknowledged bubble, but one without clear historical precedent for predicting its resolution or timeline. The traditional rule that "if everyone is asking whether we're in a bubble, we are, and if everyone is trying to predict when it ends, it already has" is being violated because people have been calling this a bubble for three years without resolution. The desperation of both Anthropic and OpenAI to go public quickly reflects internal recognition that the window may close, with both companies racing to raise massive amounts of public capital before market conditions change. Unlike the 2001 dot-com crash, the current situation lacks clear precedent because the technology is genuinely transformative and revenue growth is real rather than purely speculative, making it impossible to predict when or how the bubble might deflate, though the concentration of capital in a few mega-IPOs suggests the market dynamics have fundamentally changed from previous technology cycles.
Episode transcript
Voice 100:15

Everyone is wrong about AI, but if you know the history of technology, you can be wrong and still be right.

Voice 200:21

I know the history since I started in technology with the personal computer in 1980. So listen in while we explore what is true about AI.

Voice 100:31

Welcome to the Stuart Squared podcast. Today we're going to be talking about a few different things, but the anthropic IPO is coming up and last time we did a deep dive on the SpaceX, IPO and that was super interesting. I think, we were pretty right. I know I made a prediction and I was right about what happened afterwards. and so we're going to start to dive into the ipo, but also learn about the foundations of global, global commerce, stock markets, public markets, private markets, and like how they're all relating and how it's changed over history, which I'm always excited about doing every week because we come up with a lot of crazy stuff because you have this fountain of knowledge about how it's worked since the 1970s, 1980s, and it is changing pretty drastically, but a lot of things stay the same. So with that, what have you read about Anthropic?

Voice 201:23

So, you know, I consider it a good source of the Wall Street Journal story that has gone viral in the sense that what they said is what everybody now believes. and shoot, I have to log in and then I have to blah, blah, blah, come on. which I said, that Anthropic is expected to tell investors it sees over 30 trillion in potential revenue. That headline like, got everybody's attention primarily because it's actually higher than what Elon Musk forecast for SpaceX, which was like 27.5 trillion. So like anthropic saying, you know, this AI stuff's going to happen and it's going to harvest up to 30 trillion in potential revenue at some point in the future. And which is interesting because they're currently said to be on a path for 65 billion. I think that's the number. I could probably look it up in

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