Fine-Tuning

Fine-tuning updates a pretrained model’s weights on a smaller, targeted dataset. It is the right tool for teaching form — tone, format, a classification scheme — and the wrong tool for teaching facts, which RAG handles better and cheaper. Most teams try fine-tuning too early; prompt work and retrieval solve more problems than expected.

In practice: 500 examples of your support tone, so replies stop sounding like a press release.