[dekhn]

I had never used SAT before (was familiar with the concept) and recently wanted to avoid thinking, so I asked gemini (after a few test prompts):

"""Create a MiniZinc script to find the optimal E12-series resistor values for the base ($R_B$) and collector ($R_C$) of a PN2222A transistor switch.

Specifications:

Collector Voltage Supply ($V_{CC}$): 12V DC

Base (Input) Voltage ($V_{IN}$): 3.3V DC

Target Collector Current ($I_C$): Maximize, but do not exceed, 1W (1 watt).

The script must correctly model the circuit to ensure the transistor is in saturation and must execute without Gecode solver errors like 'Float::linear: Number out of limits"""

After a few more try-paste exception loops, that generated a lovely and readable MiniZinc script with variables I can adjust for other circuits. It was exciting to see that basically every constraint problem I learned in school ("at what angle should you swim across the river..." is just a matter of encoding the problem and running a solver (I still think people should learn the basics of constraint problems, but after a certain point the problems are just tricky enough that it makes more sense to teach people how solvers work, and how to encode problems for them...")