There is a story going around that Generative Engine Optimization (GEO) is dead. Google has been pushing back hard on the idea that you need hacky, machine-only tricks to show up in its AI Overviews, and a lot of people read that as "GEO is over, stop bothering." That read is wrong. Google is telling the truth, but only about Google. The rest of the AI landscape plays by different rules.
What Google Wants You to Stop Doing
Google's recent statements openly discourage trying to reverse-engineer AI summaries with gimmicks. The tactics people obsess over are exactly the kind of over-optimization their systems are built to ignore or bypass.
Take llms.txt files. They are useful for permission control, telling bots what they can and cannot scrape, but creating one does not earn you a ranking boost. Or micro-chunking, where you break a page into tiny fragments to feed retrieval systems. The AI infrastructure already handles that on its end, and if a human finds your page unreadable, you have just hurt your traditional SEO. Same story with AI-only schema. There is no magic structured data tag that whispers "Hey Gemini, put me in the AI Overview." Google's stance is blunt: format for human readers, get your technical fundamentals right, and their indexers will handle the rest.
Why GEO Still Matters
Here is the part most people miss. Google only speaks for Google.
Even if Google leans heavily on its traditional ranking systems to feed AI Overviews, the rest of the ecosystem does not work the same way. Google Search and its AI Overviews are deeply tied to standard web indexing, authority, and classic SEO infrastructure. That is where content depth and strong brand authority win.
But Perplexity, ChatGPT search, and Claude are a different animal. They use independent web crawlers, different retrieval architectures, and they weigh citation context heavily. These engines are extremely sensitive to brand mentions, entity relationships, and third-party validation across the web. If you optimize only for what Google says in its webmaster guidelines, you completely miss how these other massive answer engines discover and synthesize information.
The Shift From Hacking to Content Hygiene
The real change is that the definition of GEO is evolving. It is moving away from technical tricks and toward deep content hygiene and brand presence. Instead of reformatting text for machines, an effective strategy now focuses on a few things that actually compound over time.
First, information density and verifiability. Make claims an LLM can easily confirm by cross-referencing, which means citing data, original research, and real expert sources. Second, entity mapping. Make sure your business, your founders, and your products are clearly defined across the web so these models can map your brand's relationships accurately. Third, inbound context. Pay attention to how your brand is actually described in third-party articles, forums, and reviews, because that sentiment is the data feeding these models.
None of that is a hack. It is the opposite. It is the slow, honest work of being a clear, credible, well-documented business that both people and machines can understand.
Google is telling the truth about its own platform: you don't need to break your website to fit their AI. But as the post notes, managing how your brand is positioned across the entire generative AI landscape is an entirely different game, and that's why GEO isn't going anywhere.