Do not train a filing cabinet
Distinguish when business facts belong in retrieval instead of fine-tuning data.
The move: do not use fine-tuning as document storage. Fine-tuning and retrieval solve different problems. Fine-tuning changes the model's tendencies: answer format, tone, classification behavior, adherence to repeated instructions, or performance on a narrow task. Retrieval changes the evidence available at answer time. That difference matters because business knowledge ages. A support policy can change this morning, a SKU can be discontinued, and a legal clause can be superseded. If that information is baked into training examples, the system cannot show a source, cannot update instantly, and cannot easily forget one fact while keeping the behavior. Use a decision matrix…
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