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

Jev AI Crash Course: System 1 Decision Models for AI Agents
Published 10/2026
Created by Eden Marco
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 10 Lectures ( 32m ) | Size: 314.9 MB

Build ultra-low-latency AI agents with Jev & TypeSafe AI. Master decision models, tool-gating, rubrics, and triage.

What you'll learn
⚡ Learn when to use fast System One decision models vs. heavy System Two generative LLMs.
⚡ Learn TypeSafe AI's core primitives: Noul (probability), Score (rubrics), and Choice (classification).
⚡ Build ultra-low-latency (sub-100ms), cost-effective decision pipelines for real-time AI systems.
⚡ Implement agent safety guardrails and tool-gating to intercept and block risky actions in real time.
⚡ Extract deterministic, typed JSON evaluations without LLM text bloat or hallucinations.

Requirements
❗ Basic understanding of programming (Python, JavaScript, or any language interacting with REST APIs and JSON).
❗ Basic familiarity with AI concepts (prompts, LLMs, or AI agents) is helpful, but no advanced machine learning or math background is required.
❗ A computer with internet access to use the TypeSafe AI console and APIs.

Description
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 aDecision Model.

This course is your complete guide toJev 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 likeKEV-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.

Whether you are building autonomous agents, enterprise workflow automation, or real-time event processing pipelines, this course will give you practical tools to build faster, cheaper, and safer AI applications withJev and modern Decision Models.

Who this course is for
⭐ AI Engineers & Backend Developers building autonomous agents, workflow automations, or high-volume data pipelines.
⭐ Software Developers who need ultra-low-latency (sub-100ms) classifications, support ticket triage, or bug severity scoring.
⭐ Engineers building Agent Guardrails looking to reliably gate dangerous tool calls (e.g., in coding agents like Claude Code or Cursor).
⭐ Teams looking to cut AI costs by replacing expensive generative models with lightweight, sub-cent decision models for non-generative tasks.