Know when to fine-tune, when few-shot prompting is enough, and when RAG outperforms both — without wasting six figures of GPU budget.
Five passes over the same idea, each from a different angle. Do them in order, or jump to whichever you need.
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.
