Glossary
Fine-tuning
Adjusting a model's weights on curated examples.
What it is
Fine-tuning further trains a base model on your labeled examples to shape style, format, or task behavior. It's best for consistency, not for injecting fresh facts — that's RAG's job.
Why it matters in production
Knowing when NOT to fine-tune is a senior-engineer signal. Fine-tune for format, tone, and narrow task consistency; use RAG for knowledge, prompts for behavior. Teams burn months fine-tuning what a good prompt already solved.
In practice
Fine-tuning a model to always emit your exact JSON schema for support-ticket classification — after a prompt with examples got you 80% there.
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Related terms
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