A product manager stares at a support ticket. The company’s new AI-powered “summarizer” is spitting out nonsense—polite, grammatically correct nonsense, but nonsense all the same. The bug isn’t in their code. It’s somewhere in the ghost logic of the third-party model they call with a single line of code. Who gets the ticket? The engineer who wrote the wrapper? The finance department, since the fix might mean switching to a more expensive model? Or the new “Prompt Czar” who curates the magic incantations sent over the wire?
Welcome to the next phase of AI adoption. The hard part isn't the code. It's the org chart.
For the past year, the industry has been intoxicated by the simplicity. An engineer gets an API key, writes a few lines of Python, and conjures a miracle for the demo. It feels like cheating. But that simple API call is a Trojan horse. Once it moves from a developer’s laptop to a production system, it ceases to be a tool and becomes a dependency. It becomes a contract, a budget line item, and a political football. We thought we were integrating a feature. We were actually creating a new department, one we don't even control.
This is how the new bureaucracy is born. It doesn’t look like gray cubicles and TPS reports. It looks like a Slack channel dedicated to monitoring the output quality of a model whose version number just changed without warning. It’s the
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