Jev AI Crash Course: System 1 Decision Models for AI Agents

About this course

This course contains the use of artificial intelligence :)Traditional LLMs excel at generating creative prose and open-ended text, but relying on them for simple decisions in production can be slow, expensive, and prone to hallucinations. When your system simply needs to route a ticket, evaluate sentiment, or gate a risky tool call, you don't need a generative LLM—you need a Decision Model.

This course is your complete guide to Jev AI and System 1 AI Decision Models, exploring the leading hosted and open-weights engines reshaping modern AI architectures: TypeSafe AI's Jev, OpenAI Decision APIs, and open-weights models like KEV-1.

You will learn how to replace bloated token completions with fast, typed evaluations built for production AI decision-making.

What you will master in this course:

System 1 vs. System 2 Architectures: Discover the hybrid pattern where fast decision models filter, route, and safeguard workflows before handing complex tasks to generative LLMs.

TypeSafe AI & Jev: Master Jev's core primitives—noul (calibrated probabilities), score (continuous rubrics), and choice (enum classification).

Open-Weights KEV-1: Learn how to run, evaluate, and deploy open-weights decision models without vendor lock-in.

OpenAI Decision APIs: Understand how OpenAI approaches decision tasks and compare trade-offs in latency, cost, and accuracy.

Autonomous AI Agent Safety & Tool Gating: Build middleware to intercept and block dangerous actions such as file deletions and system edits before autonomous agents execute them.

Smart Support Triage & Model Routing: Evaluate ticket urgency, sentiment, and team routing simultaneously in a parallelized API request.

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