information architecture

To put it another way: optimizing with GEO reverse engineering tactics is like entering a house through a small attic window. GEO ignores that the research frameworks literally embedded in the outputs of the model are the keys to the front door.

Perpetuated primarily by startups hungry for users and the entrepreneurial agencies and thought leaders who serve them, bad data begets worse expectations. Rapid rocketship visibility graphs imply that business results will follow—almost never the case long-term.

You can't predict the future, especially in publishing. You never know exactly which pieces of content will be hits and which will be a waste of time and money. But you can, as the finance folks have taught us, forecast your impact.

How do we expect audiences to find and read our content if we can't be bothered to research and build better structures?

Everything we've ever written about navigation, information architecture, and structuring content.

Should I, as a website publisher, be angry that an AI summary engine includes my content in its index? Or should I not be so precious about my intellectual property? Here's how I'm making that data-driven decision.