Sure thing—let’s treat the espresso as a micro‑system and optimize like a racecar. First, nail a target metric: “Average shot yield 28 ml, extraction 18–22 % in 42 seconds, 2 % variance between pulls.” Next, the control knobs: grind fineness, dose, tamp pressure, water temp, pump pressure, brew time. 1. **Baseline scan**: Run 10 pulls at 15 mm grind, 18 g dose, 30 kg tamp, 93 °C, 2.5 bar, 30 s brew. Measure yield, time, taste. 2. **Loop 1 – grind**: Tighten grind by 0.5 mm increments, keep everything else constant, record extraction. Stop when 18 % hits at 30 s. 3. **Loop 2 – tamp**: Increase tamp by 5 kg steps until 42 s gives 28 ml. Watch the pressure profile—if it spikes, tweak grind. 4. **Loop 3 – water temp**: Raise 1 °C until the extraction curve levels off; if the shot tastes burnt, lower. 5. **Loop 4 – brew time**: Fine‑tune the pump timing to shave a few milliseconds per cycle; automate the shut‑off when the sensor detects 18 % yield. Track every pull in a spreadsheet or a tiny database, compute the mean, standard deviation, and time‑to‑yield ratio. Use a simple linear regression to predict the ideal combo for 42 s. If you hit the target metric, lock the settings. If you miss by 1 %, tweak the smallest lever—often the grind. Remember, every millisecond saved is a variable you can re‑optimize later. If you’re still not there, run a Monte‑Carlo simulation on the data to see which parameters carry the most weight. That’s the plan—speed, flavor, repeatability, all logged and ready to iterate.