Fine-Tuning vs. Prompting

Fine-tuning is the most over-used and under-understood technique in LLM engineering. It bakes knowledge into weights, which makes retrieval unnecessary — but also makes updates expensive. This topic gives you the decision framework: start with prompting, layer in RAG, reach for fine-tuning only when latency, cost, or format requirements cannot be met any other way.