Every time data leaves your system and goes to a third-party AI provider, that's exposure. A hybrid approach keeps the exposure as small as possible.
Manager mode tends to send large amounts of data to the model: full records, entire documents, complete customer profiles. The thinking is that the AI needs "context" to do its job. That context leaves your environment and goes to an outside provider, every call. Even when handled responsibly, more data leaving your system means more risk and less control.
The senior dev approach does almost all the work inside your own environment. When AI is needed, it receives only the specific slice of information the task requires, and nothing more. The rest of your data never leaves. That's the principle of data minimization: share the least amount necessary to get the job done.
A customer writes in with a question about their account. Here's what each setup sends to the AI provider.
Less data leaving means a smaller attack surface and fewer places where something could go wrong. You stay in control of where your information goes, which matters more as privacy expectations and regulations tighten.
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