TypeSafe AI's Jev decision model claims 200x faster, 400x cheaper classification in agent loops
LangChain · x · 2026-10-09
LangChain published a guide to Jev, TypeSafe AI's new "System One" decision model: it generates no text, instead returning typed answers and probabilities for a given state, trained via RLCD for calibrated decisions. TypeSafe claims up to 200x faster inference and 400x lower cost than LLMs on classification, letting agent loops skip full LLM calls per decision. Sam Crowder also discussed decision models on First Pass, noting OpenAI's Decisions API and Databricks' aidecide.
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