John Brewster

Machine learning flavor prediction is one of the most active areas of food and beverage research right now, and brewing is at the center of it.

Online brewing timers exist in a spectrum from simple countdown clocks to fully integrated brew day managers that pull timing data directly from your loaded recipe.

Connecting brewing gear to smartphones has changed what’s manageable on brew day without a dedicated brewing partner.

Smart fermentation tanks have moved from expensive commercial curiosities to practical tools at mid-size craft brewery scale faster than most in the industry expected.

Brewing is resource-intensive — a typical 5-gallon homebrew batch uses 8–12 gallons of water, generates heat waste from the boil, produces spent grain, and creates packaging waste from bottles or kegs.

QR codes on beer labels went from a novelty to a mainstream feature in craft brewing faster than the industry expected.

Homebrewing communities online taught me more in the first year of brewing than any book I read. When a batch went wrong, someone on HomebrewTalk had encountered the same problem and documented the diagnosis and fix.

Dilution and ABV calculators are some of the most practically useful tools in brewing, and they’re underused because most homebrewers don’t realize how often they need them.

Consistency is the hardest thing to achieve in homebrewing, and it’s almost entirely a data problem. When I look back at my first three years of brewing, the variability between batches of the same recipe came from the same sources …

The brewing AI startup space has grown considerably since 2022, with companies tackling everything from recipe generation to fermentation optimization to supply chain analytics.