Jev as a decision layer with Opus 5.5 cuts cost and runtime by about 80%
The author inserts Jev into an agent workflow to handle small bounded decisions like context filtering, task routing and failure recovery, leaving hard reasoning to Opus and cutting overall cost and execution time by roughly 80%.
Jev + Opus 5.5 is one of those combinations that makes me wonder why more people aren't building AI workflows this way. In my workflow, adding Jev as a decision layer cut cost and execution time by ~80%. It handles the small, bounded decisions that happen constantly inside an agentic system: which project notes are relevant enough to load into context, whether a task can go to a faster worker, which recovery path to take when a tool fails, and which focused checks should run before triggering the full test suite. Opus still handles the hard reasoning. Jev isn't replacing it. The harness prepares a constrained set of options, Jev makes the cheap decision, and the system validates what happens next. I think this is where a lot of AI workflows are still designed backwards. We keep sending every decision to the most capable model available, even when most of those decisions don't require frontier-level intelligence. The better architecture is to spend expensive intelligence only where the problem is actually expensive to think through. I break down how to build that decision layer in the article below.
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