Prompting for behavior, RAG for knowledge, fine-tuning for form — most 'we should fine-tune' instincts are RAG jobs, and the cheapest adequate
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System prompts plus few-shot examples solve more than teams expect, at zero infrastructure. Exhaust this before anything fancier; it's also your baseline for measuring the fancier things.
Knowledge changes; retrieval stays current without retraining. If the failure mode is 'the model doesn't know our stuff,' that's RAG, full stop.
Style, format, and high-volume classification — where consistent shape matters and examples abound. Fine-tuning does not reliably add knowledge; using it for that is the classic misfire.
Ask what's missing: behavior → prompt; facts → RAG; form → fine-tune. Combine when justified by measurements, not ambition.
Skipping the discipline this article describes until an incident, audit, or stalled project forces it — every practice above is cheaper adopted early than retrofitted under pressure.
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