Kristian Fagerlie reviews the first five days of an automated GPT-6 trading botAn AI trading bot uses AI-assisted analysis or decision logic to generate and execute trades under defined rules and controls. that uses a Google DeepMind weather modelA weather forecasting model estimates future atmospheric conditions from observations, physical relationships or learned patterns in historical data. to estimate New York City temperature outcomes on Kalshi. The system runs continuously on a virtual private server and chooses a position only when market pricesA prediction market lets participants trade contracts whose value depends on the outcome of a future event. meet its configured thresholdA decision threshold is a cutoff that converts a score or estimate into a choice to act, reject, classify or abstain. for a conservative expected edge.
The self-reported results include a loss on the first day, gains on later contracts and one position described as effectively settled but not yet formally resolved. Kristian Fagerlie estimates the account was approximately $34 positive when unrealized positions were included, but the transcript does not establish the capital at risk, a percentage return or a fully settled profit after all fees.
For the live example, the bot freezes its weather forecast shortly before the market opens and compares both sides of each temperature range. It requires at least a five-cent modeled edge. When no offer met that threshold, the automation completed successfully without placing a trade, showing that its risk rule can override the pressure to participate.
Kristian Fagerlie explicitly cautions that five daysSample size is the number of observations used in an analysis, which affects how precisely the evidence can distinguish a real pattern from random variation. cannot demonstrate a durable advantage and that the early result may be luck. The experiment shows that the automation is operating and following its configured rules, but it does not yet prove that the forecast model has a genuine predictive edge or that the strategy will remain profitable after more trades, fees and drawdowns.
Watch on YouTube
