Glossary
Fine-Tuning
Fine-tuning is additional training that adapts a pretrained model to examples for a narrower task, style or behavior. It is different from prompting, retrieval and ordinary website optimization; publishing content does not fine-tune a public AI model.
In plain terms
It is extra training performed on a model, not a result of putting a page online.
Why it matters
The distinction prevents misleading claims that SEO work directly trains ChatGPT, Gemini or other public models.
How to apply it
- Ask vendors which model is being fine-tuned and on whose data.
- Keep fine-tuning claims separate from retrieval outcomes.
- Use retrieval for facts that need frequent updates.
Example
A company fine-tunes its own support model on approved answer examples, while using retrieval for current product documentation.
Sources
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