"You should create an llms.txt for AI crawlers." "Chunk your content into smaller pieces so AI can parse it." "Rewrite for LLMs, not humans."

If you've spent any time in the GEO (Generative Engine Optimization) space in the last 18 months, you've heard versions of this advice everywhere. Now Google has officially weighed in — and most of it is a myth.

The Search Central team published Optimizing your website for generative AI features on Google Search in 2026, and the guide explicitly debunks five common GEO hacks. This post pulls out the verbatim verdicts, what to do instead, and the one new axis worth watching (hint: agentic experiences).

TL;DR

• Google officially says you don't need: llms.txt files, content chunking, AI-specific rewrites, inauthentic mentions, or excessive schema.org markup
• What actually works: continuing SEO best practices, creating non-commodity content with unique perspectives, and maintaining technical clarity (indexable + crawlable + good page experience)
• The new axis worth watching: agentic experiences (browser agents, Universal Commerce Protocol) and the MCP ecosystem connecting to it

1. Five GEO myths Google officially shot down

Myth 1: llms.txt and AI-specific files

"LLMS.txt files and other special markup: You don't need to create new machine readable files, AI text files, markup, or Markdown to appear in generative AI search."

The llms.txt convention has been making the rounds as the "robots.txt for LLMs." Google's verdict: you don't need it for Google's generative AI features (AI Overviews, AI Mode). If you want to publish one for Anthropic, OpenAI, or Perplexity's crawlers, that's a separate decision — but it does nothing on the Google side.

Myth 2: Chunking content

"Chunking content: There's no requirement to break your content into tiny pieces for AI to better understand it. Google systems are able to understand the nuance of multiple topics on a page."

The argument "LLMs can't handle long context, so split your content into single-topic pages" is also a myth in the Google context. Their systems can parse multi-topic pages and surface relevant sections to users. Write the length that serves your readers.

Myth 3: Rewriting just for AI

"Rewriting content just for AI systems: You don't need to write in a specific way just for generative AI search. AI systems can understand synonyms and general meanings."

You don't need an "AI-friendly" style separate from human-friendly writing. Synonyms and intent matching are handled by the model. Long-tail keyword stuffing is also unnecessary.

Myth 4: Inauthentic mentions

"Seeking inauthentic mentions: ...seeking inauthentic mentions across the web isn't as helpful as it might seem. Our core ranking systems focus on high-quality content while other systems block spam."

The "we need brand mentions everywhere so AI picks us up" → "let's seed mentions on blogs and forums" pipeline backfires. Google's spam systems block it, and the core ranking systems weight high-quality content over mention count. Authentic engagement (e.g., genuine Reddit discussions) is a different axis and still has value.

Myth 5: Overfocusing on structured data

"Overfocusing on structured data: Structured data isn't required for generative AI search, and there's no special schema.org markup you need to add."

Schema.org markup for rich results in regular SEO is still useful. But layering it on specifically for GEO purposes? Not required.

2. What Google actually recommends — the GEO mainline

The mainline is surprisingly boring: continuing SEO best practices is GEO optimization. AI Overviews and AI Mode sit on top of Google's existing ranking systems, so ranking high in regular Search and being cited by AI features map closely.

The mechanics underneath are:

• RAG (Retrieval-augmented generation): AI features retrieve relevant pages from the Search index, then generate grounded responses with clickable citations
• Query fan-out: A single user query expands into multiple related queries that pull additional results (e.g., "how to fix a lawn full of weeds" → "best herbicides", "remove weeds without chemicals", "prevent weeds")

The three practical axes Google calls out:

• Create non-commodity content: not "7 Tips for First-Time Homebuyers" (commodity, recyclable) but "Why We Waived the Inspection & Saved Money: A Look Inside the Sewer Line" (first-hand, expert angle, non-commodity)
• Maintain technical clarity: indexable + crawlable + snippet-eligible + good page experience (Core Web Vitals, mobile, distinguishable main content)
• Avoid scaled content abuse: don't generate a separate page for every long-tail variation. Google's scaled content abuse spam policy explicitly targets this. Structural completeness (filling in pricing, FAQ, brand, persona pages once) is different from variation factories

3. The new axis: agentic experiences

The most forward-looking part of Google's guide is the section on agentic experiences — AI agents that navigate websites autonomously to book reservations, compare products, or place orders.

Google explicitly mentions:

• Browser agents that interpret DOM structure, accessibility tree, and visual screenshots to navigate sites
• Universal Commerce Protocol (UCP) and similar emerging protocols that let Search agents execute commerce actions
• Implicit connection to the MCP (Model Context Protocol) ecosystem, which gives AI models structured access to external data sources

If you're building anything in the AI tooling space (I'm building RevenueScope, which exposes an MCP server for AI assistants to query store-level analytics), this is the axis to pay attention to. The official web.dev/articles/ai-agent-site-ux reference covers agent-friendly site best practices for browser agents specifically.

For most teams in 2026, this is still "directional" rather than "execute now" — but knowing what's coming 6-12 months out lets you avoid investing in axes that are about to be deprecated.

Wrap-up

If you've been spending engineering or content cycles on llms.txt, chunking, or AI-specific rewrites, Google just officially told you to stop. The boring answer wins: keep doing SEO well, write non-commodity content, and start paying attention to agentic experiences as the next axis.

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Originally posted on RevenueScope (with the full reference list).