Jev for beginners: how to use it and what to build

About this episode

Jev is TypeSafe AI’s new decision model. It returns type-safe structured values (a choice, a score, a probability) instead of generated text, at 4 cents per million input tokens with no output charge. This week I ran it on five real projects: PR categorization, a meta-analysis of my own Claude and Codex sessions, Gmail triage, the ChatPRD product insights graph, and a live audience dashboard built from 4,500 YouTube comments. What you’ll learn: • What makes Jev fundamentally different from every other model I’ve used • How I analyzed 1,700 PRs for 9 cents and what I found out about where my engineering effort actually went • The personal meta-analysis you can run on your own Claude and Codex sessions right now • Why I stopped using Jev alone, and what I pair it with now • How I turned 4,500 YouTube comments into a searchable audience dashboard for almost nothing • The real-time app I built in an afternoon that shows something surprising about Jev’s speed • Why Jev’s pricing model is different from any LLM I’ve used, and what it makes practical to build • The ChatPRD product insights project: 1,100 signals, 200,000 classifications, and what it cost me — Brought to you by: Ope