The advent of COVID-19 ended an era of stable US retail food prices that followed the world food price crisis of 2010-2012. Pandemic-related disruptions, avian influenza outbreaks, and the Russia-Ukraine war drove 2022 food-at-home inflation to its highest rate since 1974 (11.4%). In 2023, US Department of Agriculture (USDA) economists responded to these changes by updating food price forecasts with statistical learning protocols to select time-series models and prediction intervals to convey their uncertainty. We characterise the public good provided by these "adaptive" inflation forecasts and enhance them by continuously selecting exogenous variables, improving their precision and explanatory power. The all-items-less-food-and-energy ("core") index helps predict food prices until 2017; then, the money supply, wholesale-food prices, and food service wages help generate optimal forecasts. The strong relationships between food prices and other prices and the money supply indicate the sensitivity of food markets to macroeconomic forces and government policy choices.