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Key Takeaways Getting recommended by AI platforms comes down to the same trust signals that have always mattered. But teams are making preventable mistakes by treating generative engine optimization like an exotic new discipline.
These mistakes include flooding the internet with AI-generated content, chasing citations instead of earning mentions, going quiet after launch and treating GEO as something separate from SEO.
Additionally, most teams are tracking their GEO performance with dashboard numbers that don’t connect to anything real.
Founders across all industries and geographies are currently looking into how to get their brands recommended by ChatGPT and Claude. And that’s no surprise: These platforms are rapidly becoming the first place people go to evaluate products and services. If you’re invisible there, you’re losing deals you’ll never even know about.
But in the rush to do so-called generative engine optimization (GEO), I’m watching smart teams make the same preventable mistakes. They’re chasing shortcuts, measuring the wrong signals and treating generative engine optimization like some exotic new discipline when it’s really a credibility game built on familiar foundations. Here are the five I see most often.
1. Flooding the internet with AI-generated content and hoping nobody notices
The math seems irresistible. AI writing tools can produce a finished article in minutes, so why not publish 300 pages targeting every long-tail keyword in your space?
Simple: Because Google is watching — and penalizing. Their guidance on generative AI content explicitly warns that producing large volumes of pages without adding genuine user value may violate their spam policies. This isn’t a footnote. It’s an enforcement priority.
I’ve seen brands spin up hundreds of near-identical articles in weeks, only to watch their organic visibility collapse when the next core update lands. Traffic spikes briefly as pages get indexed, then drops off a cliff once Google’s systems flag the content as scaled and low-value. The brands that got hit hardest treated AI as a publishing engine rather than a drafting assistant.
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