The hidden cost isn’t your words — it’s the inference layer

Most “AI optimization” advice starts with rewriting: shorter copy, cleaner phrasing, more keywords, more structure. But rewriting doesn’t remove the inference layer. It only changes the wording the model must still infer.

The agent still has to determine what this page is, why it exists, how it fits the site, and whether it can be trusted. The interpretive workload stays the same.

"Expensive" sites aren’t penalized — they’re avoided

AI systems don’t punish inefficiency. They route around it. Pages that require excessive inference aren’t “wrong.” They’re costly.

Costly sources get used less—quietly, consistently, and eventually, permanently. That’s economic survival for the AI Agent.

MSP-1 changes the economics

MSP-1 collapses inference upstream. Instead of forcing AI agents to guess, a site can declare—clearly and minimally— what the page is, what role it serves, and how it should be treated.

Less ambiguity. Fewer tokens. Lower energy cost per understanding. Not better wording—better signals.

Example: A medical article with MSP-1 declarations tells agents "peer-reviewed, board-certified author, last updated [date]" before they process a single sentence. Zero inference required.

This isn’t SEO — it’s cognitive efficiency

The AI-mediated web won’t reward whoever shouts best. It will reward whoever is easiest to understand responsibly.

MSP-1 isn’t about gaming the system. It’s about costing less to think about.