There's a narrative floating around right now that feels a bit too clean to be true. GEO is being presented as if it's the next big unlock, almost like someone finally cracked the system and figured out how AI visibility really works. And yes, there are some valid observations behind it. But the way they're being packaged and sold? That's where things start to fall apart.
From the outside, it's easy to believe we're entering a completely new paradigm. Mentions suddenly matter more than backlinks. Only the first part of a page counts. Traditional SEO is losing relevance. It all sounds compelling, especially when backed by clean charts and confident statements.
But if you're actually building with these systems, the view from the trenches is different.
Working hands-on with LLMs quickly shows they're not just picking up the obvious bits of content. They go much deeper. They parse full HTML structures, recognize layout patterns, and try to approximate how a real user would move through a page. It's not just about extracting text; it's about interpreting relevance in context.
And that has significant implications.
Look, in several real business cases, we've seen a site rank first for a niche product and simultaneously appear prominently in AI Overviews. When you dig into where that information is coming from, it's clear it's not some completely new source. It traces back, again and again, to Google Search.
That's the inconvenient truth many of these GEO narratives ignore.
A lot of what is now framed as "AI-driven discovery" is still heavily dependent on the same underlying systems that have been shaping visibility for years. It's just being accessed and repackaged differently. In many cases, what looks like a new signal is simply a new way of consuming the same old signals.
Take the claim that mentions are now more important than backlinks. There may be scenarios where that appears true, particularly for very specific brand queries, but turning it into a general rule is risky. The same goes for statements about how only the first portion of a page matters. These are observations under specific conditions, not universal mechanics.
The problem isn't the data itself. The problem is the jump from observation to conclusion.
Early signals are being treated as stable truths. Correlations are framed as if they explain the system. And from there, it's a short step to building entire strategies on top of assumptions that haven't really been tested across different contexts.
Meanwhile, the systems themselves are still evolving. Fast.
If anything, what we're seeing is not simplification but increasing complexity. Very similar to what happened with Google Search over the years. More signals, more layers, more interaction between different factors. Less room for clean formulas.
That's why positioning GEO as a kind of silver bullet is misleading. It suggests a level of certainty that simply isn't there yet. It also creates the impression that established fundamentals no longer matter, which is probably the most dangerous takeaway.
Because right now, those fundamentals still play a huge role. Content structure, relevance, authority, and how information is presented on a page are still deeply connected to what LLMs surface. The interface may have changed, but the underlying logic hasn't been replaced.
So yes, things are shifting. But they're not detached from what came before. They're built on top of it.
And that's exactly why it's worth staying cautious. Not dismissing new signals, but also not overinterpreting them. Especially when the story sounds just a bit too perfect.
