Fine-tuning is a way to adapt an AI model using examples, so it can perform a particular kind of task more consistently. The examples show the model what input and output should look like.
Imagine giving a new helper several examples of how your team writes short support replies. With practice examples, the helper may learn the expected pattern.
Fine-tuning is different from simply adding instructions to a prompt. It takes planning and suitable examples, and it does not guarantee that a model will always give the right answer.