Agent-readiness, AEO and GEO: how they relate

#ai #agents #seo #webdev

Three terms describe overlapping work, and the difference matters when you decide what to fix. Answer engine optimization (AEO) is about the pages, so an AI engine can quote them as the answer to a question. Generative engine optimization (GEO) is about the signal around the pages, so an engine trusts the source enough to cite it. Agent-readiness is wider than both, because it also covers whether an agent can act on the site, not only read and cite it.

At a glance

Discipline	What it optimizes	Who consumes it	A typical fix
SEO	Ranking on a results page	A person choosing a link	Keywords, backlinks, page speed
AEO	A page an engine can quote	An AI answer engine	Schema, quotable passages, clear facts
GEO	The trust signal around the page	An engine deciding what to cite	Citations, directories, a resolved entity
Agent-readiness	What an agent can read and act on	An AI agent that acts	llms.txt, MCP, APIs, commerce endpoints

Answer engine optimization

AEO engineers the page itself. Structure, schema, source density, and passages an engine can lift cleanly. The practical test is whether the first sentence under a heading stands alone as a quotable answer, and whether the facts on the page are stated as data rather than buried in prose. Most of what makes a page AEO-ready also makes it agent-readable, because both depend on a machine reading the content without guessing.

Generative engine optimization

GEO engineers the trust signal. Directories, citations across independent sources, a consistent description of who you are, and a knowledge-graph entity an engine can resolve. An engine cites a source when several places agree on the same thing. AEO gives the engine something to quote. GEO gives it a reason to trust the quote. One without the other underperforms.

Where agent-readiness goes further

AEO and GEO stop at being read and cited. Agent-readiness adds the surfaces an agent needs to do something. An MCP server it can call, an API catalog it can enumerate, authentication it can pass, and commerce endpoints it can transact against. A site can be perfectly quotable and still give an agent nothing to act on. The reverse is also common, an API an agent could use that no engine can find.

How to sequence the work

Measure first, because the three overlap and you do not want to pay for the same fix twice. A scan shows which AEO and agent surfaces are present and which are missing. The page-level gaps are usually AEO and agent-readiness work, fixable on the site itself. The trust gaps are GEO work, earned offsite over time. The point of measuring is to spend effort where an engine or an agent actually changes its behavior, not where a checklist says you should.

For a measured audit across agent-readiness, AEO and the agent surfaces an engine cannot see, contact info@turva.dev.

Originally published at https://turva.dev/guides/agent-readiness-aeo-geo