This walkthrough demonstrates how to integrate Jev decision models into an agent harness to handle routing, risk gating, and tool selection without relying on full LLM calls.
Original by Sam WitteveenAgent workflowsIntermediate20 min 24 secPublished
Jev can act as a fast decision layer for risk gating before executing potentially destructive tool calls.
Progressive disclosure allows agents to categorize and load only necessary skills to help reduce token costs.
Decision models can efficiently score and re-rank retrieved passages before sending them to a larger LLM.
Worth knowing
These notes use fetched automatic captions, not an audiovisual watch or independent performance test. The walkthrough's routing and tool-selection examples were not executed here. Jev is presented as a hosted API; check privacy obligations before sending local state to the service.