Google has published a new documentation page titled “Optimizing your website for generative AI features on Google Search,” and within it, the company delivers its most explicit verdict yet on two of the most debated acronyms in the search industry: AEO and GEO. The short answer is that from Google’s perspective, neither represents a new discipline. Both are simply SEO.
The new guide, which builds on earlier AI features documentation released in 2025, goes beyond explaining how AI Overviews and AI Mode function. It directly addresses the tactics that a growing ecosystem of consultants and third-party tools have been promoting as essential for visibility in generative search results. By naming these tactics explicitly and advising site owners to ignore them, Google has drawn a clear line in the sand. For anyone optimizing specifically for Google Search, the message is unambiguous: foundational SEO practices remain the foundation, and the emerging playbook of specialized AI optimization is largely unnecessary.
Google Officially Redefines AEO and GEO as SEO
The new documentation opens by grounding Google’s generative AI features in the same systems that have always powered Search. The company states that these AI features are “rooted in our core Search ranking and quality systems” and rely on retrieval-augmented generation (RAG) and query fan-out to pull content from the standard Search index. The implication is clear: if your content is not already optimized for Google’s core ranking systems, no amount of AI-specific tinkering will help.
On the terminology front, Google is unusually direct. The guide defines “AEO” as answer engine optimization and “GEO” as generative engine optimization. It then states unequivocally: “From Google Search’s perspective, optimizing for generative AI search is optimizing for the search experience, and thus still SEO.” This is not a casual remark. It is a formal, published position that echoes what Google employees Gary Illyes and Cherry Prommawin told attendees at Search Central Live. At the time, they argued that GEO and AEO do not require separate frameworks. The difference now is that the position is codified in official documentation, giving publishers a concrete source to cite when evaluating claims from the growing AEO and GEO service industry.
The Mythbusting Section: Tactics Google Says You Can Skip
The most striking section of the new guide is labeled “Mythbusting generative AI search.” It lists several optimization tactics that have gained traction in recent months and explicitly tells site owners they can ignore them for Google Search. This moves beyond the more general guidance of the earlier 2025 documentation and directly challenges specific practices that have become common in GEO-focused advice.
On llms.txt files and other specialized markup, Google states that there is no need to create machine-readable files, AI text files, or Markdown versions of content to appear in generative AI search. While the company notes that its crawlers may discover and index many file types beyond HTML, it emphasizes that those files do not receive special treatment in generative AI features. The implication is that creating an llms.txt file as a signal for AI systems is a wasted effort if the underlying HTML content is already well-structured and crawlable.
On content chunking, the guide is similarly definitive. It says there is no requirement to break content into small pieces for AI systems. Google’s systems, the documentation explains, “are able to understand the nuance of multiple topics on a page and show the relevant piece to users.” This aligns with comments Danny Sullivan made in early 2026, when he said he had spoken with Google engineers who actively recommended against chunking. The practice, which involves splitting long-form content into discrete, self-contained segments to theoretically help AI models retrieve specific answers, appears to be unnecessary for Google’s implementation.
On rewriting content specifically for AI systems, Google advises against it. The guide states that AI systems can understand synonyms and general meanings, so site owners do not need to capture every long-tail keyword variation or adopt a specific writing style for generative AI search. This is a direct rebuke to the idea that content needs to be reformulated into a question-and-answer format or stripped of natural language variation to perform well in AI Overviews.
On seeking inauthentic mentions, the guide acknowledges that AI features can surface what is said about products and services across blogs, videos, and forums. However, it warns that pursuing inauthentic mentions “isn’t as helpful as it might seem.” Core ranking systems continue to focus on quality, while separate spam-blocking systems work to filter out artificial signals. The message is that buying or engineering mentions specifically for AI visibility is unlikely to provide a meaningful return.
On structured data, the guide takes a nuanced position. It says structured data is not required for generative AI search and that there is no special schema.org markup to add for AI features. However, it recommends continuing to use structured data as part of an overall SEO strategy for rich results eligibility. This is consistent with Google’s long-standing position that structured data helps with specific search features but is not a ranking factor. The difference now is that some GEO resources had promoted structured data as a priority specifically for AI search visibility, a claim the new guide directly contradicts.
What Google Wants You to Focus On Instead
After clearing away the tactics it considers unnecessary, the guide turns to what actually matters. The advice is largely familiar to anyone who has been following SEO best practices, but Google contextualizes it specifically for the generative AI environment.
The concept of “non-commodity content” receives particular emphasis. Google contrasts a generic article titled “7 Tips for First-Time Homebuyers” with a more unique piece titled “Why We Waived the Inspection & Saved Money: A Look Inside the Sewer Line.” The distinction is about whether content offers insight that goes beyond common knowledge. Generative AI systems, which draw from the entire Search index, are more likely to surface content that provides a distinct perspective or original data. This is not a new SEO principle, but the guide reframes it in terms of how AI features select which sources to cite.
On the technical side, the requirements are straightforward. Pages must be indexed and eligible for snippets to appear in generative AI features. Google recommends following standard crawling best practices, using semantic HTML where possible, adhering to JavaScript SEO best practices, ensuring a good page experience, and minimizing duplicate content. None of this is specific to AI features, but it serves as a reminder that the technical fundamentals remain the gatekeepers to any form of Google Search visibility, generative or otherwise.
Local and ecommerce optimization receives its own dedicated section. For product visibility in AI responses, Google recommends using Merchant Center feeds. For local businesses, it points to Google Business Profiles. The guide also mentions Business Agent, a conversational experience that allows customers to interact directly with brands within Google Search. This suggests that ecommerce and local businesses may have specific advantages in generative AI features if they maintain structured, verified data through Google’s own platforms.
Agentic Experiences Enter Google’s Official Guidance
A notable addition to the documentation is a section on agentic experiences. Google describes AI agents as “autonomous systems that can perform tasks on behalf of people, such as booking a reservation or comparing product specifications.” This moves beyond the current generative AI features into a future where AI systems actively interact with websites on behalf of users.
The guide notes that browser agents may access websites by analyzing screenshots, inspecting the DOM, and interpreting the accessibility tree. It links to web.dev’s guide to agent-friendly website best practices and references the Universal Commerce Protocol (UCP) as an emerging standard that “will allow Search agents to do more.” Google announced UCP earlier this year, with Vidhya Srinivasan’s annual letter stating that it was co-developed with Shopify and endorsed by more than 20 companies.
The inclusion of agentic experiences in official documentation signals that Google is thinking beyond the current generation of AI Overviews. However, the guide frames this guidance as optional, recommending it for businesses where agent access is relevant and where there is extra time to explore. That positioning suggests that agent optimization is forward-looking rather than urgent, but its presence in the documentation gives publishers a reason to start paying attention.
Why the New Documentation Matters for the Industry
This guide represents a consolidation of positions that Google had previously scattered across conference talks, podcast appearances, and blog posts. Having an official reference to cite changes the dynamics of the conversation. When a vendor pitches a specialized AEO or GEO service that involves chunking, llms.txt files, or structured data specifically for AI visibility, publishers now have a direct source from Google that says these tactics are unnecessary.
The mythbusting section carries significant weight precisely because it names the tactics explicitly. Google is not offering general advice about focusing on quality. It is telling you to skip specific practices that a growing industry has been promoting as essential. This does not settle the debate for non-Google AI platforms such as ChatGPT or Perplexity, which may weigh signals differently and may indeed benefit from some of these tactics. But for Google Search, the official position is now on record, and it is unequivocal.
The agentic experiences section, while early and framed as optional, puts browser agents and the Universal Commerce Protocol into official documentation for the first time. This gives forward-thinking publishers a framework to consider as the technology evolves. The mention of UCP, in particular, suggests that Google sees structured, machine-readable transaction protocols as important for future AI-driven commerce interactions.
Looking at the Broader Context
The guide closes with a reminder that publishers do not need to accomplish everything in the document to succeed. Google notes that “plenty of content thrives in Google Search (including generative AI experiences) without any overt SEO at all.” The agentic experiences guidance is explicitly labeled as something to explore “if this is something that’s relevant to your business and you have extra time.”
This measured tone is consistent with Google’s broader approach to generative AI in Search. The company has been gradually rolling out AI Overviews and AI Mode while emphasizing that existing SEO fundamentals remain the primary path to visibility. The new documentation does not introduce any radical changes to how publishers should approach their work. Instead, it filters out a set of emerging practices that Google considers noise and reinforces the principles that have defined search optimization for years.
For publishers who have been wondering whether they need to invest in specialized AI optimization services, the answer from Google is clear: focus on creating unique, well-structured content that serves users, maintain solid technical fundamentals, and ignore the growing list of AI-specific shortcuts. The discipline that matters is the same one that has always mattered. It is still SEO.
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