wallstreetbets debates whether AI is the next dot-com bust
As seen on the 24/7 Wall St. homepage on November 3, 2026.
Greenspan called it "irrational exuberance" in Dec '96 and the Nasdaq still nearly 4x'd before topping, so being right about the bubble but early is just being wrong with extra steps. Amazon dumped ~90% in the crash and still became one of the best trades of the century, while META and ORCL print tens of billions in cash flow, they're not pets.com. Doom posts always sound smarter, but the money goes to whoever can sit through the ugly headlines, not to whoever predicts them.
The thread's argument is about financing costs: the claim that money-losing AI builders now face double-digit borrowing costs while profitable ones keep compounding. The top replies push back that being early on a bubble call is still being wrong.
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A widely upvoted r/wallstreetbets post from Puzzled-Question-156 argues that rising borrowing costs are repeating the dynamic that killed dot-com companies, which survived on cheap credit by issuing shares and bonds. Once the 10-year yield climbed to 6.7% in a single year, that lifeline snapped and mass bankruptcy followed roughly a year later.
The post applies that framework to AI, citing discounted share and bond sales at Meta and Oracle and CoreWeave's inability to secure new loans below a 15% yield. Private credit investors are already demanding double-digit returns from AI companies, choking off the cheap capital that loss-making builders depend on.
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The top reply, from Tegob13, pushes back on timing: Greenspan called "irrational exuberance" in December '96, yet the Nasdaq still nearly quadrupled before it peaked. Being correct about a bubble but early is functionally the same as being wrong, and Meta and Oracle print tens of billions in cash flow rather than resembling the pets.com variety.
A structurally sound bear case does not translate into a tradeable short if the market stays irrational long enough to wipe out the position, and several replies note the Nasdaq keeps running in the meantime. The post acknowledges the flip side: profitable AI businesses ultimately benefit as weaker competitors fail, even if their stocks fall near term alongside the wave of bankruptcies.