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Can AI actually beat prediction markets — or does the house always win? In Episode 26 of Built This Week, Sam Nadler and Jordan Metzner kick off 2026 by breaking down a real AI trading bot Jordan built for prediction markets like Kalshi, using live market data, whale detection, coordination signals, and confidence scoring. Jordan walks through the full system — backend, frontend, live alerts, and execution logic — and shares the honest results: a 66 percent win rate that still lost money once fees and market dynamics were factored in. The takeaway is not hype. It is reality. The episode also dives into: Why prediction markets feel like gambling but are regulated differently How insider-like signals emerge from coordination and volume behavior Why bots end up trading against bots Where real alpha might exist (and where it does not) We also cover: Google NotebookLM as a serious education and onboarding tool Turning documents into infographics, slide decks, and audio learning Nvidia entering autonomous driving and competing with Tesla Nvidia’s new Rubin architecture and why it matters Tesla vs Waymo economics and the future of Full Self Driving Why Anthropic and Claude Code are becoming developer defaults This is not theory. This is what happens when you actually deploy AI systems into real markets. Timestamps (0:00) Why prediction markets are exploding (1:07) Episode 26 kickoff (2:00) Why build a trading bot at all (4:30) Kalshi vs Polymarket APIs (6:00) Live market signals and whale detection (9:30) Win rate vs profitability (12:00) Why fees destroy returns (14:30) Bots trading against bots (17:00) Where real alpha might exist (18:00) NotebookLM for learning and onboarding (21:00) Nvidia enters autonomous driving (24:00) Tesla vs Waymo economics (27:00) Nvidia Rubin chips explained (28:30) Anthropic and Claude Code momentum (29:30) Final thoughts Links Built This Week New episodes every Friday Jordan Metzner https://x.com/mrjmetz Sam Nadler https://x.com/Gravino05