
Show Notes
Daniel Negreanu (@realkidpoker) is fresh off a $3.3 million win in the Super High Roller Bowl. Perhaps the most famous poker player on the planet, he is ranked #3 on the all-time money list. We start with a discussion of the new era in poker ("the Solver era") and some recent adjustments he's made in his game. We move on to some deep history - his move from Canada to Vegas; his early years with Phil Ivey, Allen Cunningham, and John Juanda; some very big gambling in the early years; and the "pump-up years" in the poker economy after WSOP 2003, Rounders, and the Andy Beal games. He tells some great golf-gambling stories from the late 2000s, and he explains how his competitive goals shifted from cash games to tournaments. Daniel goes through his WSOP routine each year, which includes a prep period, followed by extreme intensity during the WSOP (where he often gains ten to fifteen pounds), and then a long rest period.
More from The AI Metagame
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Episode 3 | The edge belongs to whoever's willing to break things first. Most people are waiting for the safe path. Haralabos Voulgaris handed an AI agent his brokerage API, watched it place $20,000 in unauthorized trades, and responded by building a better confirmation tree — not by shutting it down. We explore what happens when a professional gambler's risk appetite meets the AI frontier — deploying autonomous bots on Polymarket and Schwab, hardening servers against injection attacks, and building a VIX strategy around the conviction that the world is more fragile than consensus believes. Haralabos makes the case that the real AI competition isn't about who has the best model — it's about who owns the physical layer. That China's robotics lead may matter more than America's research lead. And that the consumer surplus from AI doesn't mean much if no one's built the institutions to distribute it.
Episode 2 | Controller | Over-Optimization: Why efficiency kills resilience. A perfectly optimized system is just a fragile one waiting to break. Our guest explains why they stopped optimizing for margins and started optimizing for survival, and what that means when AI moves faster than your org can adapt. We've spent decades chasing efficiency. Removing friction, maximizing output, trimming every edge. But what happens when the system has zero slack left and the ground shifts overnight? This episode unpacks the Controller archetype: the leader who builds tight, optimized machines that work beautifully until they don't. We challenge the Explainer instinct to rationalize away uncertainty, and explore why the smartest move right now might be building in inefficiency on purpose.
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