Master System One models, the Playground, the API, and Python/JS SDKs to ship fast, typed AI decisions
Most AI courses teach you how to talk to a chatbot. This one teaches you how to build AI into your software — the part that never shows up in a chat window at all. TypeSafe AI's Jev is the first "System One model": no chat interface, no generated paragraphs to parse — you describe the shape of the answer you want, and Jev returns a typed, calibrated decision your code can act on immediately. This course takes you from the core concept through the Playground, real Python and JavaScript SDK code, a full support-ticket router build, production patterns like confidence-gated routing and cascades, and a section-length honest look at Jev's documented weaknesses.
Want a working understanding of AI decision layers — no code required for the first third of the course
Want to add a fast, cheap, typed AI judgment to an app or API you're already building
Building routing, scoring, or moderation pipelines that need a typed decision, not generated prose
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By the end of the program, you'll be able to:
Self-paced video course on TypeSafe AI's Jev: the Choice/Score/Noul primitives, the Playground and API, Python and JavaScript SDKs, a support-ticket router build, confidence-gated routing and cascades, and an honest look at where Jev fails.
Deep dives (free): TypeSafe AI launches Jev: a "System One Model" that never hallucinates · How does Jev work? RLCD and the System One mechanism · How to integrate Jev into your agent pipeline · Top 10 Jev / TypeSafe AI use cases · Where Jev actually fails: the specific complaints behind the hype.
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