Somewhere in the last year, "chunking" became a piece of standard advice for anyone trying to get cited by ChatGPT, Gemini, or Google AI Overviews. Shrink your paragraphs to one or two sentences. Format every subhead like a question. Break a real article into a script an AI can swallow whole. In January 2026, Google's own search team stood up and said: don't.
What Google actually said
On Google's Search Off the Record podcast, published January 8, 2026, Search Liaison Danny Sullivan addressed the trend directly. Sullivan confirmed that Google's ranking systems give no benefit to content broken into bite-sized chunks for large language models, and said it's not a practice Google wants site owners doing, after consulting Google's own search engineers before saying so publicly. John Mueller, who co-hosts the podcast, backed him up. Their broader point cut even deeper: rebranding standard SEO practice as "AEO" or "GEO," or hiring someone specifically for "AI optimization," doesn't change the underlying fundamentals. Same work, new acronym.
Write for the person reading it. The citation follows.
What "chunking" actually means
The practice Sullivan described has a recognizable shape. Real content gets rewritten into short, isolated paragraphs, sometimes a single sentence each, stacked under subheadings phrased like something you'd type into a chatbot: "What is X?" "How do I do Y?" The page stops reading like an article and starts reading like a FAQ script. In the more aggressive versions, sites build an entirely separate version of the page for bots, one that doesn't match what a human visitor actually sees.
Structure and fragmentation are not the same thing
Most of the coverage of Sullivan's comments blurred a distinction that actually matters. Clear structure, headings that make sense on their own, a direct answer stated early, normal paragraph length, is just good writing. It predates AI search by decades. Chunking is something else: severing that structure from the writing itself, shrinking real content into disconnected fragments, or serving a bot-only version of a page. That second habit already has a name in SEO, and it's not a flattering one.
One-line paragraphs, chatbot-style subheadings, sometimes a separate bot-facing version of the page
No proven ranking benefit; risks reading as manipulative, or as cloaking
Self-contained sections, direct answers up front, normal paragraph length, one page for every reader
Supported by Google's own guidance; serves human readers and AI retrieval at once
Long blocks of text with no heading logic and no early answer
Harder for both readers and AI systems to find a clear, citable point
That middle row is the entire game. It's also, not coincidentally, what a well-built AEO strategy already looks like once you strip the marketing language off it.
Cloaking, dressed up as a new idea
Serving one version of a page to human visitors and a stripped-down version to crawlers has a decades-old name: cloaking. Search engines have penalized it since long before anyone had heard of AI Overviews. Calling it "AI optimization" instead of cloaking doesn't change what it is, and Google's search team clearly isn't buying the rebrand either.
Does this apply outside of Google Search?
Worth naming the limit of Sullivan's comments: he and Mueller were speaking specifically about Google's own ranking and AI Overview systems. ChatGPT and Perplexity work differently under the hood. Both rely on retrieval-augmented generation, which does involve breaking indexed content into passages behind the scenes. That's a detail of how those systems index the web, not an invitation to hand-fragment a page for them. A well-structured, self-contained section still retrieves and cites cleanly under that kind of system. A page reduced to disconnected one-liners doesn't read as more authoritative to a retrieval system any more than it does to a person, and none of the major AI platforms have published guidance suggesting otherwise.
What actually works
The practices that hold up across Google AI Overviews, ChatGPT, Gemini, and Perplexity are the same practices that have always defined good, citable writing. State the direct answer in the first sentence or two, rather than building up to it. Write every section so it makes sense on its own, without leaning on "as mentioned above." Back every specific claim with a real, dated source, see the metrics that actually measure AI visibility for what "real" looks like in practice. Use the format the question calls for: a short definition for "what is" queries, a numbered list for "how to" queries, a table for comparisons. None of that requires shrinking a page into fragments. It requires writing it well the first time, a point covered in more depth in what answer engine optimization actually is.