GenAI interview guides / RAG vs Fine-Tuning Interview Guide
RAG vs Fine-Tuning Interview Guide
Choose among prompting, RAG, fine-tuning, and combinations based on where the missing capability actually lives.
Diagnose first
Use retrieval for fresh/private knowledge gaps; consider fine-tuning when the model repeatedly misses a behavior or task pattern.
RAG strengths
Fast knowledge updates, citations, access-controlled corpora, and inspectable evidence—at the cost of retrieval and indexing failure modes.
Fine-tuning strengths
Can improve behavior, format, style, domain decisions, or prompt efficiency; it is not a database for changing facts.
Combined systems
Many strong systems tune behavior and retrieve dynamic knowledge. Evaluate the complete pipeline end to end.