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TypeSafe’s Jev is a new “System One” AI model designed for fast, structured decision-making instead of text generation. In this episode, we explain how Jev works, why it uses Choice, Score, and Noul outputs, how calibrated confidence changes AI system design, and why TypeSafe says Jev can run 40–200x faster and 40–400x cheaper than frontier LLMs like GPT-6 Astra. We also break down Jev’s pricing, benchmarks, real-world use cases, limitations, and the emerging cascade architecture where fast decision models handle routine classification and routing while frontier LLMs handle complex, open-ended tasks.
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