Tagged articles

semantic judgment

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Sep 30, 2026 · Artificial Intelligence

Jev: Separating Semantic Judgment from Generation in LLM Applications

TypeSafe's Jev introduces a decision model that returns typed probability outputs (Noul, Choice, Score) instead of natural language, moving semantic judgment from runtime generation to a designable, testable 'decision surface' developed with LLM assistance but executed by a specialized model, enabling calibrated thresholds, parallel evaluation, and deterministic code control flow.

Agent EngineeringDecision SurfaceJev

0 likes · 26 min read

Jev: Separating Semantic Judgment from Generation in LLM Applications

Architect

Sep 22, 2026 · Artificial Intelligence

Jev: Extracting Semantic Micro-Judgments from Agent Loops into Observable Decision Layers

TypeSafe's Jev isolates semantic micro-judgments — routing, risk scoring, boolean checks — from generative LLM calls using Choice, Score, and Noul primitives that return typed probabilities, enabling policy code to branch directly on observable, auditable signals instead of parsing free-text model outputs.

Agent ArchitectureChoice Score NoulJev

0 likes · 25 min read

Jev: Extracting Semantic Micro-Judgments from Agent Loops into Observable Decision Layers

Data STUDIO

Sep 21, 2026 · Artificial Intelligence

Jev: The $0.042/M Token 'System 1' Model for Fast Semantic Judgments

TypeSafe's Jev model returns calibrated probability distributions over predefined options instead of generating text, enabling 100ms semantic decisions like classification and routing at $0.042 per million input tokens, with production adoption in customer service, browser automation, CI/CD, and game agents within days of release.

AI decision-makingAgent ArchitectureJev

0 likes · 21 min read

Jev: The $0.042/M Token 'System 1' Model for Fast Semantic Judgments