We Outsource Terms, Not Meaning

We assume that because a machine uses our words, it shares our meaning. It does not. It shares only our vocabulary. When we write a prompt, we are handing over our terms to a probabilistic system and asking it to guess at the definitions.

This transaction is risky. Meaning relies on shared context, history, and judgment—things a model does not have. It has only patterns. It can mimic the sound of understanding without doing the work of comprehension.

The gap between what we say and what the machine computes is where systems fail. We are outsourcing the labor of interpretation to a statistical engine that has never experienced the world it describes.

What this changes in practice: Define your terms explicitly in the prompt, or accept that the machine will define them for you.