Fine-Tuning vs RAG vs Prompting for Domain Knowledge (ANSWERED)
Scenario question comparing prompting, RAG, and fine-tuning for domain knowledge — freshness, cost, auditability, and when to combine approaches.
TL;DR — Quick Answer
Prompting is fastest to iterate for instructions and format but cannot add large factual corpora. RAG is best when knowledge changes often and you need citations and audit trails — product docs, policies, support KBs. Fine-tuning fits stable behavior: tone, terminology, structured output, and task patterns — not a substitute for weekly doc updates. Most production systems combine all three: RAG for facts, prompts for constraints, optional LoRA for domain style.
The Interview Question
When would you choose fine-tuning, RAG, or prompting to inject domain knowledge into an LLM application? Compare trade-offs for a scenario with changing product documentation.
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