Most discussions about AI SEO are still focused on content.
How do I get cited by ChatGPT?
How do I optimize for Perplexity?
What format does an LLM prefer?
I think that may only be the first layer.
The deeper shift is structural.
Today’s websites are largely organized around pages.
But an AI agent is trying to understand:
- entities
- attributes
- relationships
- categories
- expertise
- causality
- meaning
In other words: The human sees a website.
The machine is trying to reconstruct a model of the world behind the website.
That leads somewhere interesting.
- Taxonomies.
- Ontologies.
- Knowledge graphs.
- Semantic relationships.
- Agent-readable interfaces.
We’re experimenting with exactly this in an AI SEO project we’ve been building over the last few months.
Today, from 4:30–5:30 PM, we’re holding the second free Loop Meetup and opening up what we’ve learned.
We’ll go into:
Taxonomy → Ontology → Agentic Web → UX
Not as abstract concepts, but as pieces of the architecture we’re actually building.
Last meetup was about our experiments and AI agents.
This one is about the model underneath the system.
Next month we’ll show the implementation.
[Join us today →]
If you’re thinking seriously about where search goes when machines become active participants in the web, this conversation is for you.
The future of SEO may look more like an Ontology was originally published in Becoming Human: Artificial Intelligence Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.
