21 concrete ways to put Jev inside agent workflows
The author lists 21 cases where Jev replaces large models for small decisions, including model routing, tool selection, retry logic, a spend firewall and human review queues, with a build approach for each.
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 👇
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