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Fine-tuning makes sense when you need behavioral shifts (style, tone, bias) or are training on data unavailable at runtime.
RAG excels when you want factual augmentation without retraining the whole damn brain.
It's not either/or — it's about cost, latency, use case, and update cycles. But hey, binaries are easier to pitch on a slide.
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Fine-tuning makes sense when you need behavioral shifts (style, tone, bias) or are training on data unavailable at runtime.
RAG excels when you want factual augmentation without retraining the whole damn brain.
It's not either/or — it's about cost, latency, use case, and update cycles. But hey, binaries are easier to pitch on a slide.