Jev as an agent decision layer: intercept, route, execute, verify
The author places Jev between the agent and the models as a decision layer that checks tool calls, assesses risk, routes to the right model and verifies output, with the execution layer swappable across Opus, GPT, Gemini and other LLMs.
I still don't understand why everyone is NOT putting Jev in their AI agent stack most agents don't need another LLM deciding what to do. they need a proper decision layer. I compiled the complete Jev workflow: intercept → route → execute → verify Jev checks the tool call, evaluates the risk, routes it to the right model, then verifies the output before it reaches the user. and you can run the execution layer with whatever model fits the task; Opus, Sonnet, Haiku, GPT, Gemini, or other supported LLMs. the whole point is having Jev sit between your agent and the models, making the workflow more controlled and reliable. i broke down the entire system in my JEV MASTERCLASS article below 👇
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