The RAG-vs-fine-tuning debate is mostly a false binary, but the wrong default still wastes real time and money. Here's how to choose deliberately.
Reach for retrieval when the problem is knowledge; reach for fine-tuning when the problem is behavior.
Choose retrieval when
Your knowledge changes often or is too large to bake into weights.
- Facts update weekly or faster
- You need citations and traceability
- Coverage matters more than tone
Choose fine-tuning when
You need a consistent format, style, or narrow skill the base model won't reliably follow.
The Bottom Line
Most production systems end up using both โ retrieval for freshness, a light fine-tune for format and tone.