Replacing an agentic classification loop with Jev: 7x faster

A researcher replaced an agentic LLM classification pipeline with TypeSafe's System One model (Jev) for product categorization tasks, achieving 7x speedup (3.68s vs 5.50s per item). Jev uses typed Choice questions returning probability distributions instead of generating text, enabling speculative fan-out to descend two tree levels per call, while eliminating the judge loop entirely.