Lesson 1238 of 1596
AI tools: RAG vs fine-tuning — picking the right adaptation
RAG is for changing facts. Fine-tuning is for changing behavior. Most teams reach for the wrong one first.
Creators · Tools Literacy · ~24 min read
The premise
Retrieval-augmented generation and fine-tuning solve different problems. RAG injects fresh facts at query time. Fine-tuning shapes how the model responds. Picking the wrong tool burns weeks.
What AI does well here
- Use retrieved context when it's well-formatted in the prompt
- Acquire stylistic and structural patterns from fine-tuning data
- Combine both when the use case genuinely needs both
What AI cannot do
- Get fresh facts from fine-tuning alone
- Get consistent voice from RAG alone
- Replace good evals with either technique
Key terms in this lesson
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