Jev in 25 lines: building the decision model locally
TL;DR In the design review I concluded that Jev, TypeSafe AI’s typed decision model, is cheaper and faster than an LLM and not more accurate. That raised an obvious build-vs-buy question: if the value is “cheap probability over a fixed set of options,” can I get that from a small open model running on hardware I already own? Mostly yes, with one catch that matters. The technique is to prompt with lettered options, run one forward pass, and read the logits for just the option letters. A parody post called “Jev in 25 lines of Python” does exactly this, and the technique under the joke is real. The catches are calibration (raw softmax is bad until you fit it) and serving (Ollama could not do it when I wrote the design). ...