There's no AEO checklist that reliably works. Anyone selling you one is guessing.
What we do have is enough data—from watching AI citations across Perplexity, ChatGPT, and Google's AI Overviews—to notice patterns. Certain content formats get cited more. Not always. Not perfectly. But consistently enough to be worth paying attention to.
Here's what I've seen work, and why I think it does.
The core problem AEO is solving
When someone asks an AI "what's the best way to do X," the model doesn't rank ten blue links. It synthesizes an answer and picks sources to cite. The selection criteria aren't fully transparent, but the outputs reveal a lot.
AI engines favor content that is:
- Easy to extract. A clear answer to a clear question.
- Trustworthy enough to attribute. Written by someone with visible credentials or experience.
- Structured for scanning. Headers, short paragraphs, lists that can be lifted directly.
This is why format matters as much as substance. A technically accurate answer buried in three dense paragraphs loses to a less accurate but scannable one.
Formats that earn citations
1. Definitions with context
"X is Y" sentences are extremely citeable. Not just the definition—but the definition followed by why it matters or how it differs from something adjacent.
Example structure:
Answer Engine Optimization (AEO) is the practice of structuring content so AI systems cite it in synthesized responses. Unlike traditional SEO, which optimizes for ranking position, AEO optimizes for inclusion in an answer directly.
That second sentence is what makes it useful to a model. It answers the obvious follow-up.
2. FAQ sections
FAQ blocks are probably the highest-ROI AEO format right now. AI models love them because each question-answer pair is self-contained and extractable. They don't need to infer context.
A few things that matter:
- Write questions the way people actually ask them (conversational, not keyword-stuffed).
- Keep answers to 2–4 sentences
- Don't make the answer dependent on reading the article above it
The FAQ at the bottom of this post follows these rules.
3. Comparison tables
When someone asks "X vs Y," they want a clear comparison. A table that explicitly names both options and lists dimensions side-by-side is very easy for a model to cite or reproduce. Prose comparisons are not.
Dimensions to compare should be things that actually differentiate, not just features both products share.
4. Numbered how-to lists
Procedural content—"how to do X in N steps"—gets cited a lot because the format implies completeness. Step 1, step 2, step 3. Done. The model can pull that structure directly.
The key is that each step should be independently meaningful. A step that says "do the important thing here" is useless both to readers and to AI.
5. First-person experience with specifics
This one surprises people. AI engines increasingly cite opinionated first-person content when it contains specific, verifiable details—numbers, timelines, named tools, outcomes.
"We ran this campaign from January to March. Traffic to the comparison page went from 200 to 4,400 monthly visits. The conversion rate held steady at 3.2%."
That's citeable because it's specific. Vague success stories aren't.
What doesn't move the needle
- Long-form introductions that delay the actual answer
- SEO filler (restating the keyword six times in the first paragraph)
- Conclusions that summarize what you just said
- Images without descriptive alt text and surrounding context
- Dense paragraphs with no structural breaks
The honest caveat
We're still early. The citation logic in these models shifts with every update. What works in Perplexity today might not work in Google AI Overviews tomorrow, and vice versa.
The more durable bet is: write clearly, write specifically, and make it easy for a reader—human or machine—to extract a direct answer. That's always been good writing. AEO just gives it a new surface to pay off on.
If you're working on AEO strategy or want to share what you're seeing, I'm on X and LinkedIn.