a meteorologist got replaced by an AI weather model after 8 years on the job. 6 months later his bot printed $88,018 on Polymarket. $13,800 every month. curve never dipped. his boss still pays the AI subscription xd the trade itself isn't complicated. ECMWF and NOAA push raw forecast data every few hours. Polymarket temperature markets price on consensus narrative, not on the latest model run. the gap is 10x bigger than the book pricing implies. his best: - $5.50 -> $764.19 (+13,797%), NYC 44-45°F - $11.88 -> $1,496.00 (+12,497%), NYC 78-79°F - $18.32 -> $1,794.44 (+9,695%, NYC 63-64°F bot watches both APIs 24/7 and enters the second the spread opens. profile: this is Karpathy's CLAUDE.md thesis on a different table. > silent wrong assumption: "the market price already contains the forecast." it doesn't. > over-complication: stacking 7 indicators when one API gap is the whole edge. > orthogonal damage: hedging into correlated markets that resolve on the same event. he stripped all three. single markets, Kelly-sized, exit on resolution. that's the entire system. the leverage layer on top: same 4-5 entries combined into one parlay. four 95% legs multiply into a payout that doesn't fit a single position. it's not edge, it's compounding on edge that already works. the API gap is the alpha. the parlay is the multiplier. he used it: operator runs the API and knows why he's in every position. tourist runs the bot link without the API and finds out at resolution. the 12 rules I added on top of Karpathy's 4 are in the article. weather doesn't lie. the book does.