Dalton + Michael

Shockingly Good Predictions

Most people focus on predictions that were too optimistic. But some of the most interesting moments in tech are when reality completely blows past expectations. In this episode of Dalton + Michael, the two discuss times when an expectation was off in this way. Topics discussed include the investing outside of Silicon Valley, Sam Altman’s nuclear energy vision, Sam’s hiring advice, and the extent to which customers of a product care more about growth potential than cost savings. Dalton + Michael is brought to you by @Standard_Cap Dalton Caldwell on X: https://x.com/daltonc Michael Seibel on X: https://x.com/mwseibel

DCDalton CaldwellhostMSMichael Seibelhost

Feb 16, 2026·20m·Watch on YouTube ↗

📖 CHAPTERS

1. 1

   Big tech isn’t guaranteed to last: incumbents must keep winning

   Dalton and Michael open with a reminder that even the most dominant tech companies can fade quickly if they stop executing. What looks “infallible” in the moment can be irrelevant a decade later, which changes how founders should think about competing with giants.

2. 2

   A venture blind spot: underestimating how much US market structure drives returns

   Michael reflects on dismissing an LP’s claim that most venture returns come from the US, then realizing how structurally advantaged the US market is. They contrast the belief that building global unicorns is equally easy everywhere with the practical reality of market depth, capital, and outcomes.

3. 3

   YC’s international successes: the upside of being ‘unsophisticated’ and naive

   They note that YC’s willingness to fund outside the expected playbook helped them back major Indian winners. Their lack of conventional finance-market constraints sometimes acted as an advantage, letting them see founders and momentum rather than rules about where returns ‘should’ come from.

4. 4

   Sam Altman’s early nuclear/power thesis: energy as the foundation of progress

   Dalton recounts Sam leaving YC leadership focus (circa 2013) to pursue nuclear power because “electricity and power is everything.” What sounded random then now aligns with today’s narrative: energy abundance is a limiting factor for major technological leaps, including AI.

5. 5

   “Smart people win” becomes visible in the Bay Area (and beyond)

   They discuss a social/market inversion: many high-achieving tech and business leaders weren’t “cool” early, but later environments reward intelligence and ambition heavily. The Bay Area amplifies this dynamic, though they argue it holds across law, medicine, finance, and even sports.

6. 6

   Updating the investor mental model: talent, ambition, and seeing what others can’t

   Dalton notes he once overweighted factors like fundraising or surface-level signals, but came to see that aggressive, high-clarity thinkers often outperform. Michael frames this as an advantage that can sometimes outweigh starting conditions like background or wealth—especially in innovation hubs.

7. 7

   Hidden decay in strong-looking companies: ‘watermelon’ incumbents and internal rot

   Michael describes how Yahoo! and HP once looked formidable yet deteriorated from within, and how hard it is to spot today’s equivalents in real time. The lesson: some incumbents are weaker than they appear, creating opportunity for startups who can detect organizational decay.

8. 8

   Why Microsoft became impressive: big companies can still string wins together

   They contrast the usual expectation that big companies make wrong decisions with Microsoft’s resurgence via cloud, developer tools, and acquisitions. The broader point is that incumbents can recover and even accelerate if they make a few high-leverage correct bets at scale.

9. 9

   Hype cycles are like weather: predictable phenomenon, wrong emotional response

   Dalton reflects on dot-com-era hype (e.g., Iomega) and how repeated cycles teach pattern recognition. They argue hype cycles are inevitable; the useful posture is neutrality and strategic awareness—spotting what’s rising, what’s falling, and the side effects of both.

10. 10

    Mission and ambition as a recruiting engine: making ‘impossible’ feasible

    Michael shares a Sam Altman lesson: beyond mechanics (market/product/pricing), great companies rally talent around an exciting mission. If the goal is compelling enough, it attracts the smartest people—who can then make seemingly impossible outcomes real (Apollo and OpenAI as examples).

11. 11

    B2B reality check: revenue growth beats cost-cutting in buyer behavior and markets

    They dissect a common startup pitch: ‘we save you five engineers, so pay us $100k,’ and why it often fails. Michael explains that public markets and executive incentives reward revenue growth and credible attempts at 10x expansion more than vague or indirect savings—making “cost saving” a harder sell unless it’s massive and measurable.

12. 12

    AWS as a nuanced case: paying more to reduce complexity and upfront burden

    They use AWS to illustrate that buyers may accept higher unit costs in exchange for reduced operational complexity and lower upfront investment. The key is framing value in terms executives feel directly—simpler operations, faster execution, and better cash-flow dynamics—not theoretical headcount reductions.