Jev — TypeSafe's System One model; sits with other frontier models, not complex-systems theory.
jev · 9 articles
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Jev made decision models a category. This survey groups a dozen-plus hosted and open models by how they work, checks vendor claims against Decision Index, JevBench and Red Hat's tests, explains why public scores, latency and "calibration" don't compare, and ends with a comparison table and an agent-loop checklist.
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Reading arXiv:2609.29429 RLCDAlignBench: TypeSafe Jev (RLCD) on 10 alignment failures × 44 benchmarks hits median AUROC 0.886 with a generic question, ~63× cheaper than LLM judges; checklist for wiring Just-Ask-Jev into an agent harness monitor.
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A deep read of Accenture arXiv:2609.28919—enterprise coding-agent bills are often blamed on “expensive models,” but the paper moves the blame to harness defaults; cache-safe routing with Jev recovers about 14–21% of model spend in a 10k-seat emulation, with a sovereignty ladder from observe to own.
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A deep read of arXiv:2609.29769—typed classifier Jev vs three flash LLM judges on nine panels and 5,003 pairs: accuracy seldom separates, cost/latency gaps hit 29–325× and 30–220×, and correlated errors cap a cheap-first cascade at about +1.5pp.
Read →A deep read of arXiv:2609.30243 JevOut—answer-preserving short context can redirect Jev and peer decision models from a correct choice to a pre-fixed wrong target—with checked numbers (Jev TFR 61.4%, high-confidence flips, BFCL tool-routing fragility) and a hardening checklist before treating probabilities as a control plane.
Read →A deep read of arXiv:2609.23986 Jev-Mem—separating memory organize/retrieve/stop into a System-One control plane—contrasted with this site’s Jev decision line and Growing Harness “sink control into code,” with checked LoCoMo numbers and a reusable design checklist.
Read →A deep read of arXiv:2609.30186 Jev-Mobile—moving Jev from judge/memory into an Android GUI executor—with checked AndroidWorld numbers (79% success; −32.7% time and −73.4% API cost on successful trajectories vs step-wise VLM) and a reusable VLM×typed-executor checklist.
Read →arXiv:2609.27678 compares Jev and nine hosted/local models on ContractNLI: cost, latency, baseline accuracy, and All-12 persistent correctness rank differently. Close means can hide flips—select on persistent correctness, not accuracy alone.
Read →A viral YouTube clip ties Jev to Claude Code, but Jev cannot be the CLI chat model. This post covers the official skill, boundary hooks, MCP, and per-turn routing, contrasts NobodyWho’s 25-line minimal build, and discusses OpenAI fast-follow pressure.
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