Small Language Model Fine-Tuning: The Production Workflow Developers Need Now

A tuned small model should be treated as one route inside a production system, not as a smaller clone of a frontier model. Frontier models are still the best default for unknown work. But repeated, narrow, high-volume tasks are becoming the place where fine-tuned small language models quietly win. The easiest AI architecture to ship is also the one that starts hurting first: send every request to the biggest model, add context when it fails, and hope caching saves the bill. That works for prototypes. It does not age well in production.