WRITING
Decision models, in depth.
Articles on System One decision models — how they differ from LLMs, the Laya and Jev architectures, calibration, and publishing to the registry.
Laya, explained — an open decision model that runs on your own machine
Laya is an open-weights System One model built on a ModernBERT encoder. Here is how it scores options in one pass, what its checkpoints are for, and how to fine-tune it on a laptop.
Read the articleThe open reproductions — Nimble, Decider, Von, JevK5, OpenThai and the tiny ones
Within a week of Jev, individuals and small teams had rebuilt its shape from open bases. Some publish better calibration than the original. A guide to the ones worth knowing.
Kev, explained — a pointer head on a frozen Qwen
Kev is an open family of System One models from Jared Palmer that keeps a Qwen base frozen and learns only an adapter and a pointer head. Small to download, honest about calibration, and it speaks Jev's API.
GLiNER2.5-Decide, explained — labels you supply at runtime
Fastino's open-weight decision model does something the others do not. It classifies against label sets you hand it per request, extracts the spans that justify the answer, and enforces rules across decisions, all in one pass of a 340M encoder.
CLM, explained — decisions as a contrastive lookup
Contrastive Language Models do not classify. They embed the state and every candidate action and pick by similarity, which is why a decision can cost 28 milliseconds and why the heads are 75 MB.