Episode

The 100 Year Thinkers: Chris Mayer on SpaceX, AI Reckoning, and Why Early Is Overrated

Podcast
Excess Returns
Published
Jun 27, 2026
Duration seconds
3506
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https://podcasters.spotify.com/pod/show/excess-returns/episodes/The-100-Year-Thinkers-Chris-Mayer-on-SpaceX--AI-Reckoning--and-Why-Early-Is-Overrated-e3lbuak
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https://traffic.megaphone.fm/APO8077244439.mp3
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Summary

On this episode of the 100 Year Thinkers, Chris Mayer and Matt Zeigler discuss long-term investing, 100-baggers, AI stocks, SpaceX valuation, founder-led companies, and why the best investments often come with brutal drawdowns. We also cover his new book The Investor's Odyssey, the danger of letting labels like AI do too much work, how to think about TAM and capital allocation, and why patience may be the biggest edge for investors trying to own great businesses for decades. ⁠Subscribe to the 100 Year Thinkers on Spotify⁠⁠ ⁠⁠Subscribe to the 100 Year Thinkers on Apple⁠ The Investor's Odyssey: Resisting the Sirens and Playing the Long Game ⁠ https://amzn.to/44BMXeJ⁠ Main topics covered Why SpaceX, AI and trillion-dollar IPOs are testing investor discipline How Chris Mayer thinks about valuation after watching Google become a huge winner Why great businesses can still be terrible investments at the wrong price The danger of letting labels like AI, quality and TAM replace real analysis Why many AI features may not create real customer value What the dot-com bubble can teach investors about AI adoption and shakeouts Why investors do not need to be early if a company is truly exceptional How to separate AI anecdotes from real financial impact Why capital allocation and return on invested capital matter more as companies scale How to evaluate founder control, governance, incentives and trust Why the best long-term stocks can still fall 50 percent or more along the way What rational exuberance might look like for long-term investors Timestamps 00:00 Intro: Chris Mayer on AI, SpaceX and long-term investing 04:00 SpaceX valuation vs Google and the risk of paying too much 08:01 Why labels like AI and quality can do too much work 12:05 The AI pause, the dot-com analogy and where…