21 个把 Jev 放进 agent 工作流的具体用法
作者列出 21 个用 Jev 替代大模型做小决策的场景，包括模型路由、工具选择、重试逻辑、消费防火墙和人工审核队列，并给出搭建思路。
I’m giving away 21 things I’d hand to Jev instead of Astra, Fable, or another giant model. 21 actual use cases + how I’d build each one. What's inside: - Why agents waste frontier-model calls on tiny decisions that should cost basically nothing - Where Jev actually fits inside an agent loop - The 3 question types: Choice, Score and Noul - How to use Jev for model routing, tool selection and retry logic - How to build a spend firewall before an agent is allowed to buy anything - How to gate risky / irreversible actions before they happen - How to dynamically give agents permissions for ONE task instead of permanent access - How to kill weak agent branches before you spend expensive reasoning on them - How to replace a lot of LLM-as-judge calls with cheap structured checks - How to rerank retrieval before your frontier model reads anything - How to build human review queues where people only see the uncertain cases - How I’d use it for support, refunds, lead qualification, incident response and marketplace dispatch - The exact setup I’d use to test Jev before ever trusting it in production - Where I would NOT use Jev Jev costs $42 per BILLION input tokens. Which is why some of these use cases get pretty ridiculous at scale. The full 21-use-case system paper + article is below 👇
这条是引用着另一条写的：x.com/layton_gott/status/2101450120466174351