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MSTR’s Michael Saylor Challenges Chamath Palihapitiya’s AI Thesis – Why Quantum Computing Could Break Everything, Not Just Bitcoin

The discussion followed Palihapitiya sharing a note titled “The Collapse of Terminal Value,” which questioned how AI could reshape the way markets value companies.

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Sep 12, 2026 at 7:11 PM UTC · Updated vor 14 Stunden · 2 Min. Lesezeit

MSTR’s Michael Saylor Challenges Chamath Palihapitiya’s AI Thesis – Why Quantum Computing Could Break Everything, Not Just Bitcoin
Image via Stocktwits

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$1.5B Strategy Bitcoin purchase

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bitcoin

Market Impact

BTC-0.71%$76,764

Last Updated

vor 14 Stunden

Übersetzung…

The discussion followed Palihapitiya sharing a note titled “The Collapse of Terminal Value,” which questioned how AI could reshape the way markets value companies.

  • Saylor argued that if AI weakens long-term competitive advantages, investors may shift capital toward assets such as Bitcoin.
  • Palihapitiya countered that a store of value like Bitcoin must be completely resistant to hacking from potential quantum computing risks.
  • Saylor responded that any breakthrough capable of breaking cryptography would affect the entire digital ecosystem, including banks, AI infrastructure, and the internet.

Michael Saylor, executive chairman of Strategy (MSTR), pushed back against venture capitalist Chamath Palihapitiya on Monday over whether emerging technologies such as artificial intelligence (AI) and quantum computing could undermine the long-term investment case for Bitcoin (BTC).

“Your AI thesis assumes the digital world is quantum-resistant,” Saylor wrote. “If quantum breaks cryptography, it breaks AI, cloud infrastructure, banks, and the internet—not just Bitcoin. The entire stack upgrades together,” Saylor wrote in a post on X.

Source: @saylor/X

Chamath Raises AI Impact Concerns

The debate followed a note shared by Palihapitiya titled “The Collapse of Terminal Value,” which explored how the rapid development of artificial intelligence could change the way markets value companies. The post questioned whether AI might erode competitive advantages and business moats so quickly that investors could struggle to estimate what companies might earn a decade into the future.

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