Fine-tuning · model specialisation
Fine-tuning means partially retraining an existing model on your own examples, to adapt it to a domain, a tone or a specific task.
Why it matters
Fine-tuning is not always needed: for many cases, a good prompt plus RAG is enough and costs less. It is justified when the need is recurring, precise and high-volume. Knowing when not to use it is part of the job.