Show Notes
Episode 4 | The 600,000-Claim Brain: How Lev Milman Uses AI to Map Reality How do you stay ahead of the curve when the "curve" is moving at the speed of light? In this episode, we sit down with Lev Milman, a former U20 US Chess Champion and macro trader, to explore his radical, AI-driven approach to information processing and belief updating.
Lev has constructed a massive digital knowledge base consisting of over 600,000 atomic claims about the world. He doesn't just "read the news"—he has built a sophisticated "information funnel" that uses Large Language Models (LLMs) to ingest, grade, and de-duplicate content from over 1,300 RSS feeds, hundreds of YouTube channels, Twitter, Discord, and academic journals.
We dive into:
The "Greater" and the "Deduper": How Lev uses AI to filter out 80% of incoming noise and focus only on information with high novelty and belief-update potential.
Hyper-Speed Learning: Lev’s workflow for "listening" to thousands of words of summarized research at 4.5x speed using custom text-to-speech setups, often while multitasking.
The Chess Champion’s Edge: How a childhood spent studying chess for 10 hours a day wired his brain for the deep, contingency-based reasoning required to navigate the AI frontier.
Actionable Intelligence: Moving from curiosity-driven learning to a practical framework where information is rated by how much it changes his decisions in fields like AI development and health.
Lev makes a compelling case that in the AI era, the ultimate competitive advantage isn't just knowing more—it's having a superior system for updating what you believe.
More from The AI Metagame
In this episode of The AI Metagame, host Brandon Adams sits down with famed forecaster Nate Silver (@NateSilver538) and digital media builder Raf Michalowski to talk about AI slop and where the content industry is headed. At its peak, Raf's pipeline was uploading around 60,000 videos a day to YouTube — roughly 3% of all daily uploads on the platform. He walks through the economics, how platforms end up incentivizing this kind of volume, and what happens when they eventually crack down. Nate works in the part of media where AI doesn't really help — forecasting, accountability, and predictions that can be graded. The conversation maps where human judgment still has a moat, and whether quality can survive when the marginal cost of content is zero.
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.
Episode 1: Builder | Controller | Premature Abstraction "I built for scale before I understood the problem" In a world where tools allow us to scale instantly, the temptation to build big is overwhelming. But what happens when you scale the wrong thing? The AI Metagame is a twelve-episode series that looks at four archetypes in AI — Builder, Explainer, Interpreter, Narrator — to map where AI creates leverage and where it creates traps. For every great advantage of AI, there are disadvantages lurking. Each episode explores both sides. In our premiere episode, we explore the Builder's most dangerous trap: Premature Abstraction. Modern AI leverage is a double-edged sword — it amplifies errors faster than ever before. True control now requires staying small enough to pivot until the problem itself is fully understood.
Alex Hutchinson (@sweatscience) is my favorite fitness journalist. This podcast was an absolute pleasure. We had the opportunity to explore his outstanding new book, The Explorer's Gene. We also discuss, in detail, his 2018 NY Times bestseller Endure: Mind, Body, and the Curiously Elastic Limits of Human Performance. I rate this book among my top ten favorite works of non-fiction.