Hey Robert — "the same data can mean completely different things depending on timing, audience, regulation, geography, business objective, or operational circumstance" is the sentence that should be on a wall in every data team's office. That's the whole problem with AI in one line — the model has the data but not the context, and without context it's just confidently wrong.

I build AI agents for businesses and context governance is basically what separates an agent that works from one that embarrasses you. The agent knows your pricing — that's data. But does it know that the $200 rate is for new clients and the $150 rate is for returning ones? Does it know not to quote weekend rates on a Tuesday inquiry? That's context. And it lives in the owner's head until someone pulls it out and bakes it in.

The metadata piece connects too — most agents fail not because they don't have the right information but because nobody tagged what the information is FOR. Sharp framework. Sharing this with my team.

Thanks!

Colleen