A decision framework for choosing between prompt engineering, RAG, and fine-tuning when building LLM applications. The choice depends on two key factors: the amount of external knowledge required and the level of model adaptation needed. RAG works best for custom knowledge bases without behavior changes, fine-tuning modifies
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FireGEO: An open-source Semrush for AI Prompting vs. RAG vs. Finetuning?P.S. For those wanting to develop “Industry ML” expertise:Sort: