A healthcare company uses a foundation model to generate patient-facing message drafts. Despite detailed prompts and several examples, the model still fails to consistently adopt the specialized empathetic clinical tone and terminology the organization requires across thousands of daily requests. They have a large curated dataset of high-quality past messages written by their clinical staff. Which approach will most reliably embed this consistent style and vocabulary into the model's default behavior?