For March’s book club we read Aaron Sorkin’s 1929: Inside the Greatest Crash in Wall Street History–and How It Shattered a Nation. There was something almost too on-the-nose reading 1929 while sitting in New York City, speaking at a conference focused on the future of data centers—how fast they must scale, how much capital they require, and how insatiable the demand for AI infrastructure has become.
It felt less like reading history and more like watching a pattern repeat itself in real time.
I didn’t love the book. It’s highly stylized, driven by Sorkin’s signature rapid-fire dialogue, and while in some books that works, given that this occurred nearly 100 years ago there was something not-quite legitimate about it. The voicing didn’t match the age; at times it feels more like a performance rather than a deep exploration of the history and forces behind the 1929 market crash. I kept wanting more grounding, more synthesis, more of the “this is what actually happened and why it matters” that strong narrative nonfiction delivers. Instead, it offers fragments—compelling, articulate, but ultimately inconclusive.
And yet, despite that frustration, I couldn’t stop thinking about it.
Because what 1929 does capture—perhaps unintentionally—is the power of narrative itself. Not just the story of the market, but the story about the market. The media voices, the confident assertions, the polished explanations that don’t just describe reality—they shape it.
In Sorkin’s world, everyone sounds certain. The language is crisp, persuasive, almost irresistible. And that’s the point, whether the book fully realizes it or not: when enough authoritative voices repeat a story, it becomes truth-adjacent. It becomes investable.
Sitting in conference rooms in New York, listening to conversations about AI infrastructure—about exponential demand, about the race to build, about the inevitability of growth—it was hard not to hear echoes of that same tone. Different domain, same cadence. The certainty. The momentum. The underlying assumption that this time, the scale is justified.
And maybe it is.
But we’ve seen this before.
The parallels aren’t about predicting a crash—they’re about recognizing a pattern:
- A transformative technology reshaping the economy
- Massive capital flowing into infrastructure to support it
- Media and market narratives reinforcing the inevitability of growth
- A feedback loop where belief drives investment, and investment reinforces belief
Today, that narrative is amplified not just by traditional media, but by social media and algorithmic ecosystems. The velocity is higher. The reach is broader. The line between analysis and amplification is blurrier. And increasingly, AI itself is both the subject of the hype cycle and a participant in spreading it.
What 1929 hints at—but never fully dissects—is how dangerous that convergence can be. Not because the underlying innovation isn’t real, but because the narrative around it can outpace reality. Confidence becomes consensus. Consensus becomes momentum. And momentum becomes hard to question.
Reading the book in isolation, I found it lacking. Reading it in context—in the middle of a modern infrastructure boom, surrounded by conversations that felt eerily familiar—it became something else entirely. Less a definitive account, and more a mirror.
A reminder that markets don’t just run on fundamentals. They run on stories.
And we are very, very good at telling ourselves the ones we want to believe.