A hypothetical reconstruction of Jev, TypeSafe's closed "System One" decision model, in the spirit of nanoGPT: the smallest working version of what black-box probing suggests. It reads a state and answers typed questions (yes/no, pick one, ordered score) with probabilities instead of generated text.
Frozen TinyJev-0.6B + probability readout lifts BANKING77 intent macro-F1 from 75.7% to 90.1% without changing model weights. Plus semantic-question discovery experiments (BANKING77, CLINC150).
Build a 0.6B parallel decision model that turns states into probability distributions—no output-token decoding needed.
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