https://gibbok.github.io/myvar/tags/ai-reasoning/Recent content in Ai-Reasoning on MyVar.devHugoen-USSat, 19 Sep 2026 15:19:14 +0000https://gibbok.github.io/myvar/decision-engine/jev-system-one-decision-engine-overview/Sat, 19 Sep 2026 15:19:14 +0000https://gibbok.github.io/myvar/decision-engine/jev-system-one-decision-engine-overview/<h2 id="overview">Overview</h2> <p>Jev is TypeSafe AI’s System One decision engine, designed to return typed, probabilistic outputs from structured input state and bounded questions. It offloads fast categorical reasoning to specialized models while leaving policy execution, state changes, and safety thresholds entirely inside application code.</p> <h2 id="key-insights">Key Insights</h2> <ul> <li><strong>Bounded Decision Space</strong>: Evaluates text, JSON, or array state against predefined answer schemas rather than generating open-ended prose.</li> <li><strong>Native Typed Outputs</strong>: Supports <strong>Choice</strong>, <strong>Score</strong>, and <strong>Boolean</strong> data types accompanied by explicit probability distributions across allowed answers.</li> <li><strong>Independent Semantics</strong>: Evaluates multiple concurrent questions against shared evidence without introducing cross-question bias or prompt contamination common in standard LLM adapters.</li> <li><strong>Structural vs. Semantic Safety</strong>: Guarantees output schema conformance, but requires developer validation against historical data to ensure real-world routing accuracy.</li> <li><strong>Decoupled Execution</strong>: Generates decision traces and routing predictions while keeping action authority strictly within application code.</li> </ul> <h2 id="technical-details">Technical Details</h2> <h3 id="system-one-paradigm">System One Paradigm</h3> <p>Named after Daniel Kahneman’s framework for fast, intuitive reasoning, Jev provides an interface optimized for immediate decision-making. Unlike generative language models that produce freeform text or code, Jev accepts a defined state payload and evaluates explicit, bounded questions to return structured choices.</p>