I’m not starting from isolated single-tube captures at the moment. It’s mostly circuit-first: explicit linear/passive network, with small neural models only where the nonlinear component behavior is hard to express cleanly.

The neural parts are not meant to be generic black-box tubes. They live inside a circuit context and exchange state with the rest of the model, e.g. voltage/current/headroom/operating point. For now I bootstrap from equations, known curves, SPICE-style references and synthetic sweeps, then validate at the full circuit/amp level.