The Core Problem
Most websites are built for human visual browsing — pricing implied by layout, availability implied by a grayed-out button, form intent implied by placement near other fields. An AI agent executing a task on a user's behalf can't reliably infer any of that without explicit, structured signals.
What 'Agent-Ready' Actually Requires
Explicit, structured, current information for pricing, availability, policies and product relationships that doesn't depend on visual inference. New standards are emerging specifically for this: Google introduced WebMCP in early 2026 so a site can expose structured 'tools' an agent can invoke directly, rather than reverse-engineering the interface by trial and error.
This Isn't a New Problem, It's GEO's Sibling
Everything that makes a page legible to an AI agent trying to complete a task overlaps heavily with what makes it legible to an AI answer engine trying to cite it (see What Is GEO): clean schema.org markup, an llms.txt-style plain-text summary, and content stating facts explicitly rather than implying them through design.
The Winning Combination, Not Either/Or
Sites positioned to do well here keep genuinely human-centered visual design and layer structured data, explicit agent capabilities and dependable APIs underneath it — not a choice between building for humans or for agents, since both are reading the same underlying markup.