How do you adjudicate a proposal to fine-tune a model o...

The proposal to move sensitive customer data from inference-time prompts into model weights via fine-tuning is fundamentally flawed from a compliance and privacy perspective. While it is true that prompts can cross trust boundaries—entering request logs and being subject to vendor retention policies—fine-tuning does not solve the underlying privacy issue. In fact, it makes the data harder to manage. Once data is baked into model weights, there is no granular ‘delete’ operation to remove specific customer records, making it a worse solution for compliance than prompt-based approaches.