SEO, GEO, Santa Claus, And The Tooth Fairy. Which is Real?

Good Lord. Here we go again.

Let me be clear, as a veteran who’s been around since before “mobile-first” meant anything other than “oops, my desktop site looks tiny on my flip phone,” Generative Search Optimization is not a new specialization. It is a subset—a feature—of Search Engine Optimization. It’s like saying a spoon is a whole new category of cutlery, completely separate from the fork and knife. No, buddy. It’s just what you use for soup.

We’ve Been Writing for AI Since… Well, Before It Was Cool

The biggest eye-roll I get from this whole “GSO is new!” narrative is the implication that suddenly, we’re all scrambling to figure out how to write for a machine.

Newsflash: We’ve been doing that for years!

Remember when your content had to be perfectly structured, answer the explicit question, and be authoritative enough to land that coveted Featured Snippet? That little box at the top of the search results? That was the original generative AI answer box, people! We were structuring our content with clear headings, crisp answers in the first paragraph, and bulleted lists so that a machine (Google’s algorithm) could instantly lift it and spit out a direct response.

We were literally writing for an AI to quote us long before ChatGPT was a twinkle in an LLM’s eye. We were the original AI content writers, just without the fancy-pants term!

The Algorithm Updates Tell the Real Story

If you want the proof that GSO is just the latest evolution of SEO, look no further than Google’s own history of machine learning updates. This isn’t a new paradigm; it’s the natural progression of the algorithm getting smarter.

We’re not talking about simple keyword matching anymore. Remember when Google introduced RankBrain back in 2015? That was a machine-learning system designed to better understand the intent behind search queries. It was the moment Google began truly shifting from a library catalog to a clever assistant. Then came BERT and other Natural Language Processing (NLP) advancements, helping the algorithm understand the nuance, context, and conversational flow of a user’s query.

• Before RankBrain: You had to search for “how to fix flat tire bike.”
• After RankBrain/BERT: You could search for “my bicycle tire is deflated, what do I do?”

This was Google using machine learning to process human language better. The current “Generative Search Experience” (or AI Overviews, or whatever they call it this week) is simply the output of those same core machine-learning principles. The new generative summaries are simply a fancier, more chatty way of presenting the information the algorithm has been processing for years.

The core task of the SEO professional remains identical:

1. Understand the user’s intent.
2. Create the most authoritative, trustworthy, and helpful content that explicitly satisfies that intent.
3. Structure that content so a machine can easily read and verify it.

Whether the machine shows a list of links, a Featured Snippet, or a fully synthesized AI overview—it all boils down to whether your content is the best-structured, most helpful resource available.

So, let’s stop acting like we need to split off a whole new department, hire a “Chief Generative Optimizer,” and invest in a new suite of snake-oil software. Generative search optimization is just what we call good, modern, E-E-A-T-focused SEO.

Now if you’ll excuse me, I have to go create a perfectly structured, authoritative FAQ section so the next AI-generated answer quotes me. Because that’s just SEO, buddy. And it’s what I’ve been doing all along.