把 Jev 当 agent 决策节点：八步接入指南

Simplifying AI @simplifyinAI原推发布于 2026.09.19

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jev might be the next real unlock for agent systems, split intelligence from execution. step 1 → meet jev: the llm writes and reasons, agents act, jev decides which move happens next step 2 → every agent fork breaks into 3 typed outputs: a choice from options you define, a score against a scale, or a yes/no with a probability attached step 3 → build now on openai or anthropic, swap in jev later without rebuilding your agent graph, typesafe's adapter is designed for exactly that step 4 → jev can't hallucinate an option outside what you gave it, it only ever returns one of your defined choices step 5 → typesafe reports up to 193x faster and 444x cheaper than a frontier llm on their own routing benchmarks, treat that as workflow-specific, not universal step 6 → real use cases: routing (which tool, model, or agent), scoring (risk, urgency, confidence), verification (accept, reject, escalate to a human) step 7 → plugs into an existing langchain or vercel ai gateway setup as one decision node, not a replacement for your main model step 8 → keep it out of math, writing, and anything irreversible, code computes, llms create, jev decides between defined options the idea: instead of burning a full llm call on a multiple-choice decision, you get a typed answer with a confidence score in milliseconds.