AEO Foundations Series, Entry 1
This isn’t a definitive guide. It’s an exploration in progress.
We’re still in the earliest stage of Answer Engine Optimization (AEO). There are no long-term case studies yet. What you’ll read here is a working theory of AEO vs SEO, a framework in progress that is being tested through experiments and observations.
From AEO vs SEO: Why We Need a New Frame
The other day, I uploaded a picture of my face to ChatGPT and asked it to recommend glasses.
The answers were messy. Some products linked to 404s. Others didn’t exist. But one brand kept surfacing.
When I clicked through, everything aligned: style, price, construction. Even adjustable nose pads, the small feature I cared most about.
So I asked:
“Why do you keep recommending glasses from this brand?”
The explanation wasn’t backlinks, press mentions, or snippets. It came down to structured product data — attributes like shape, material, fit, and price, consistently tagged across the catalog. When I compared the marketing copy on the site to the attributes stored in the back end, I could see how the two layers worked together: one written for humans, the other built for machines.
That was the “click” moment. This brand wasn’t just built to be found. It was built to be understood. And that’s where schema — which I’ll dive into more in a future post — quietly becomes the bridge between the two.
Where Current Thinking Stops Short
As I’ve explored AEO, I keep seeing the same traps:
Some guides reduce it to PR mentions and citations. That explains visibility, not reasoning.
Others limit it to snippets and FAQs. Useful for retrieval, but not enough for AI reasoning.
Even thoughtful SEO pros argue AEO is “just SEO.”
If that were true, strong-ranking brands would dominate AI answers already. They don’t.
And then there’s the hype around llms.txt. At best, it’s a polite suggestion, not a reasoning layer.
The common thread: these approaches stop at retrieval. They don’t address how facts survive the reasoning layer where AI assembles answers.
What Is the Difference Between AEO and SEO?
Search and answer optimization overlap, but they don’t aim for the same outcome. SEO is built around pages and rankings; AEO is built around fields and facts. Where they meet is in the shared groundwork: schema, indexability, and governance. The diagram below shows how the two models intersect and where they diverge, making clear why AEO goes beyond visibility to focus on answer survival.
The Four R’s (Early Framework)
AI doesn’t just retrieve information. It moves through a sequence of stages that determine whether your facts survive into an answer. First, it needs to recognize and classify your content.
Then it has to reason with the underlying attributes to make comparisons. In Google’s own description of AI Mode, this reasoning involves breaking a query into subtopics and issuing multiple searches simultaneously, so the system can dive deeper into the web and reassemble an answer from structured facts.
Here’s how those stages break down:
- Retrieval – Schema markup helps AI find and classify content.
- Reasoning – Structured attributes make facts usable and comparable.
- Representation – Representation is the glue. Without it, AI can’t map human intent to your structured facts.
- Response – Stable schema and governance ensure your facts are safe to reuse.
To bridge human queries with structured facts, it relies on clear representation. Finally, only stable schema and governance make those facts safe to reuse in generated responses.
To bridge human queries with structured facts, it relies on clear representation. Finally, only stable schema and governance make those facts safe to reuse in generated responses.
Example Thought Experiment
An SEO-optimized site might say:
“Sleeps four. Price from €129 per night.”
That’s crawlable, but opaque for reasoning.
An AEO-ready site stores fields like:
capacity = 4
price_min = 129
currency = EUR
From there, schema is auto-generated. Copy and schema stay in sync (schema parity).
Now when AI gets the query, “best small RV for a family of four under €150 per night,” your brand survives retrieval, reasoning, and response.
Why Should Businesses Care About AEO?
Most websites today are built for visibility. Few are built for understanding.
That gap is widening. Sites that invest in structured attributes, parity, and representation will earn persistent inclusion in AI answers.
The compounding effect is powerful:
- lower acquisition costs,
- higher trust,
- and competitive displacement.
SEO improves your odds of being found. AEO improves your odds of being chosen. And in the AI era, being chosen is what compounds.
What Comes Next
This is the first entry in the AEO Foundations Series.
Next, we’ll break down the Four R’s in detail, starting with Retrieval and Reasoning, the foundation that makes or breaks every AEO effort.
We’ll show test methods like prompt sets, schema parity checks, and catalog audits, so you can run your own experiments.
Closing Challenge
There aren’t many case studies yet. That’s the point. We’re still navigating.
Aeonautics exists to map this space as it emerges. The field is shifting under our feet, and the only way forward is exploration.
The brands that treat AEO as uncharted waters, and start testing now, will be the ones setting the landmarks everyone else sails toward later.