Equipment & Tools

Most homebrewers buy the cheapest refractometer they can find and use it for years without knowing how much measurement error they’re accepting.

Most fermentation errors are visible in the data before they’re apparent in the beer — if you know what to look for.

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.

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 …

Virtual reality training for brewers sits at the intersection of two things I find genuinely interesting: immersive technology and the challenge of teaching process skills that are traditionally learned only through hands-on experience.