RAG vs Fine-Tuning: Which AI Approach Is Actually Right for Your Project? Every developer building on top of an LLM hits the same wall eventually. The base model is impressive, but it doesn’t know your data, doesn’t match your tone, and occasionally confidently hallucinates facts your users will immediately recognize as wrong. The two dominant solutions are retrieval-augmented generation (RAG) and fine-tuning, and picking the wrong one can cost you weeks of engineering time and thousands of dollars. This guide cuts through the hype to tell you exactly which approach fits your use case. ...