What is fine-tuning and when should you do it?

Fine-tuning is the process of further training a pretrained model on a smaller, task-specific dataset to improve its performance on a particular task or domain. You should fine-tune when prompt engineering and RAG cannot achieve the desired output style, when you need consistent structured output, when you want to teach domain-specific reasoning, or when you want a smaller model to match a larger one's behavior.