Jev 作为 agent 内循环决策层的用法拆解
作者解释 Jev 不是 LLM 而是决策模型：给上下文和问题，毫秒返回结构化选项、概率与置信度，可用于路由模型、选工具、打分验证、加护栏和人工升级。
Could Jev be the iPhone moment for agents? Not because it is a smarter LLM. It isn’t even an LLM. @typesafeai's Jev is a decision model: give it context and a set of questions, and it returns structured choices, probabilities and confidence scores in milliseconds. That makes it ideal for the inner loop of an agent: • Route requests to the right model • Select the next tool or action • Score and verify results • Apply guardrails • Escalate uncertain decisions to humans Today, agents burn time and tokens asking generative models to make thousands of small decisions. Jev could turn those calls into a fast, inexpensive and predictable decision layer. Large models reason and create. Jev decides. Could that be the missing primitive that makes agentic applications faster, cheaper and reliable enough to operate at massive scale?