Jerry Liu published a post placing Jev next to model routing and post-training as ways to optimize intelligence for a specific task. In his framing, routing orchestrates frontier and open-weight models at the harness layer, post-training tunes an existing model toward task evals, and Jev introduces a new architecture for generalized classification.
For engineers, the framing separates three levers: harness, weights, and architecture, each trading accuracy, cost, and latency differently. The post is an opinion and does not provide measurements comparing the three approaches on any task.