Google just published an official guide on optimizing for generative AI features in Search. Read that sentence again. The same company that spent a decade telling us “just write good content” felt the need to publish 2,000 words on how to show up in AI Overviews.
And then, somewhere in the middle, they helpfully clarify that GEO (“generative engine optimization”) and AEO (“answer engine optimization”) aren’t really things. It’s all just SEO, they say. Same horse, new lipstick. Move along.
Sure, Google. That’s why you needed a whole new page for it.
I’ve been in martech long enough to recognize this dance. We saw it with content marketing around 2012, with growth hacking a few years later, with whatever “conversational AI” was supposed to be in 2017. The pattern is always the same: deny the new category exists, quietly absorb its practices into the existing framework, then look vaguely surprised when everyone keeps using the new name anyway.
So let me walk you through what Google actually says about GEO. The substance is useful, even if the framing is a wink.
How AI Search actually works under the hood
Two mechanisms are doing the work.
RAG (retrieval-augmented generation): Google retrieves relevant pages from its index, then generates an answer grounded in that content. The same ranking systems decide which pages get pulled in.
Query fan-out: the model spins off related sub-queries to gather a fuller picture. Ask “how do I fix a lawn full of weeds,” and the AI is quietly also searching for “best herbicides,” “remove weeds without chemicals,” and so on.
The takeaway is unambiguous. If you’re not indexed and rankable, you’re not in the AI answer. Visibility in AI features sits on top of visibility in regular Search. There is no back door.
What Google says actually matters for content
The content advice will sound familiar to anyone who’s been doing SEO for more than five minutes.
Original perspectives beat regurgitated common knowledge. Google’s example here is sharp. “7 Tips for First-Time Homebuyers” is the bad version. “Why We Waived the Inspection and Saved Money: A Look Inside the Sewer Line” is the good one. The difference is real experience and a specific story, not another generic listicle scraped from the same five sources.
First-hand expertise. Original takes. Content a generative model couldn’t easily produce on its own. This is where Google is essentially admitting: yes, we know the web is being flooded with AI slop, and we’re trying to surface the stuff that isn’t.
Reader-friendly structure. Headings, paragraphs, sections. Written for humans, not for parsers.
High-quality images and video, because AI features pull these in too.
And one warning worth highlighting: don’t write a separate page for every fan-out query variation. Google explicitly says this violates their scaled content abuse policy. Tempting? Sure. Smart? No.
The technical baseline
Nothing exotic. Be crawlable. Be indexable. Be eligible to show a snippet. Follow JS SEO best practices if your site uses JavaScript frameworks. Have a decent page experience. Reduce duplicates. Verify in Search Console.
One slight nuance: semantic HTML isn’t strictly required for Google’s parsers, but they recommend it anyway because of agents. More on that below.
The mythbusting section is genuinely the best part
This is where Google names specific “GEO hacks” you can stop paying for:
- llms.txt files: not needed, not treated specially
- “Chunking” content into AI-friendly micro-pieces: not needed
- Rewriting content in some special LLM-friendly voice: not needed, the model handles synonyms fine
- Buying inauthentic “brand mentions” across forums and blogs: not needed, and flagged as spam
- Piling on structured data specifically for AI: not needed (still useful for rich results, but not an AI hack)
But we know between what Google suggests and what we do to improve our visibility, there is and was always a gap ;-).
The agentic frontier is the actually new part
The most forward-looking section is a short bit on AI agents. Browser agents that book reservations, compare specs, fill out forms. These agents interact with sites by reading visual renderings, the DOM, and the accessibility tree.
This is where semantic HTML, good accessibility, clean DOM structure, and emerging protocols like UCP (Universal Commerce Protocol) start to matter in a new way. Not for AI ranking. For AI agents actually using your site.
If you’re building anything transactional online, this is the section I’d read twice.
Where OtterlyAI comes in
Here’s what Google’s guide doesn’t say, because it can’t: even with perfect optimization, you have no idea what’s actually being said about your brand inside AI answers. Google can tell you how to optimize for AI Overviews. They can’t show you what ChatGPT, Perplexity, Gemini, and their own AI Mode are saying about you right now. Which prompts you appear in. Which sources get cited about you. What the sentiment is.
That visibility gap is exactly what we built OtterlyAI for. We track brand mentions, citations, and sentiment across the major AI search engines. Less guessing, more data.
(Yes, that was the founder pitch. I’ll keep it short.)
What I’d actually take away from this guide
The fundamentals haven’t changed. Google is doubling down on E-E-A-T signals: real experience, demonstrable expertise, and specifics that prove you’ve done the thing.
Most of the “GEO playbooks” being sold right now are only scratching the surface.
Track your brand visibility in AI search yourself. Google’s guide tells you what to do, but nothing about what’s actually working for you.
Start paying attention to agent-readiness. That’s the part of the article that ages forward, not backward.
And enjoy the small irony that Google had to write this guide at all. They can call it SEO if they want. The rest of us know what it is.
