For roughly two decades, the SEO discipline operated on a quiet assumption that turned out to be one of its most valuable features. Guidance from one search engine traveled. If Google said sitemaps mattered, Bing said sitemaps mattered. If Bing said structured data deserved real effort, Google said the same. Practitioners optimized for Google with reasonable confidence that the work would carry across the other engines, and most of the time it did. That portability was not luck. It was the product of a structurally large overlap layer that the major search engines had jointly built, brick by brick, over twenty years.
That world doesn’t exist in LLM-land. The major providers train on different corpora, run different crawlers under different policies, route different queries through different retrieval systems, and apply different alignment processes that shape the final response in ways the upstream signals can’t predict. Guidance from any one provider, including Google’s guidance about its own Gemini products, is one data point. Practitioners carrying the SEO habit forward, the habit of treating one engine’s guidance as roughly the whole map, will optimize confidently for one platform and miss the others.
Sidebar: As I was finalizing this piece, Google published fresh guidance on optimizing for their generative AI features. Their framing is explicit: from Google Search’s perspective, optimizing for AI search is still SEO. That framing is accurate for Google Search. It does not extend to ChatGPT, Claude, Perplexity, or any other LLM, and that is precisely the trap this article is about.
The Shared Standards That Made SEO Guidance Portable
The era of portable guidance was built on actual collaboration, not coincidence. The Sitemaps protocol became the joint property of Google, Yahoo, and Microsoft in November 2006, when the three engines formally agreed to support a common protocol at version 0.90, building on Google’s earlier Sitemaps 0.84 from June 2005. Five years later, on June 2, 2011, the same three engines launched Schema.org, with Yandex joining shortly after, to create a common vocabulary for structured data markup. That was the announcement that got made on stage at SMX Advanced. I was on the Bing team at the time, and what struck me then is what still matters now. The engines were competitors, but they had decided that a shared vocabulary served them all. Webmasters got one set of rules. The web got cleaner data. The engines got better signals. Everybody won. The pattern repeated with robots.txt, the 1994 convention that became RFC 9309 at the IETF in 2022, formalizing what every serious crawler already honored. And it repeated again, more recently, with IndexNow, the protocol Microsoft Bing and Yandex launched in October 2021. IndexNow is now supported by Bing, Yandex, Naver, Seznam, and Yep. Google has tested the protocol since 2021, but has not adopted it.
That overlap layer is exactly why Google’s guidance felt safe to follow, even if you cared about Bing traffic. The signals the engines used were not identical, but the inputs they accepted, the protocols they honored, and the standards they advertised were. Optimization had a shared substrate.
Where The LLM Stacks Actually Diverge
The LLM environment doesn’t have a shared substrate of comparable size. The differences are not cosmetic, and they are not temporary. They are baked into how the systems are built. Start with training data. OpenAI has signed disclosed licensing deals with News Corp worth up to $250 million over five years, Axel Springer at roughly $13 million per year, Reddit at an estimated $70 million per year, plus the Financial Times, Condé Nast, Hearst, Vox Media, The Atlantic, the Associated Press, Le Monde, and others. Google has its…