Generative engine optimization vs SEO: what is actually different

Generative engine optimization (GEO) and classic SEO overlap far more than the marketing around GEO suggests. Most of what lets ChatGPT search, Perplexity, Claude or Google AI Overviews use a page is the same technical groundwork SEO has always needed: the page loads, crawlers are allowed in, the text is in the HTML, and the structure is clear. What is genuinely new is narrower: a set of named AI crawlers with separate purposes, opt-outs that split search from training, crawlers that do not run JavaScript, and edge rules that can block them.

This post sorts the acronyms, the overlap, the new parts and the hype, with the evidence for each.

What GEO, AEO and LLMO actually mean

The three labels describe roughly the same goal from different angles. None is defined by a standards body, and none appears in the crawler documentation of OpenAI, Anthropic or Perplexity.

GEO is the only one with a clear origin. The paper GEO: Generative Engine Optimization by Aggarwal and colleagues (first posted November 2023, accepted to KDD 2024) introduced a benchmark called GEO-bench and tested content rewrites, such as adding citations, quotations and statistics, against generative engines. It reported visibility gains of up to 40% on that benchmark and noted that results varied by domain. The authors also ran a smaller test on Perplexity.ai, supplying the source texts as uploaded files rather than letting it search the web. That is a useful research result. It is not a description of how ChatGPT, Perplexity or Google choose sources from the live web today, and those operators have not said they work that way.

Google addresses the labels directly. Its AI optimization guide says that, from Google Search's point of view, optimizing for generative AI search is optimizing for the search experience, which is SEO, and points anyone weighing "AEO" or "GEO" services to its guidance on evaluating third-party SEO advice.

In practice, people use the labels interchangeably. If you want a single term for the technical side, AI search readiness is the one we use: can AI tools reach and read your pages at all.

What overlaps with technical SEO (most of it)

Before any AI system can quote a page, something has to fetch it and extract its text. That pipeline has the same failure points it always had.

• Status codes and redirects. A page that returns 403, 404, a 5xx or a long redirect chain is unusable to every crawler, AI or not.
• Crawl access. robots.txt rules, noindex and X-Robots-Tag headers apply to AI search crawlers that honor them, just as they do to Googlebot.
• Indexability. Google states that to be a supporting link in AI Overviews or AI Mode, a page must be indexed and eligible to show in Google Search with a snippet, and that there are no additional technical requirements.
• Snippet controls. Google's nosnippet, data-nosnippet and max-snippet also limit what AI Overviews and AI Mode can use as direct input. These are old SEO controls with a new effect.
• Structure. One clear title, a matching H1, a sensible heading order, descriptive link text and a self-consistent canonical make extraction easier for any parser.
• Structured data that matches the page. JSON-LD that parses and agrees with visible facts helps machines identify entities. It is not a separate AI format.
• Discovery. A valid sitemap and working internal links help every crawler find pages.

Microsoft describes the same dependency: Microsoft Copilot grounds answers in current web information via the Bing search service. A page Bing has not crawled and indexed is unlikely to reach Copilot that way.

If your technical SEO is in good shape, most of your GEO groundwork is already done.

What is genuinely new for AI search

Four things matter for AI search that classic SEO rarely had to deal with.

Named AI crawlers with different jobs

In classic SEO you mostly cared about Googlebot and Bingbot. AI operators now run several agents each, and they do different things. The split that matters is training, search and user-triggered:

Sources: OpenAI, Anthropic, Perplexity, Google, Apple, all read on 2026-11-08. OpenAI also documents a fourth agent, OAI-AdsBot, which checks ad landing pages submitted to ChatGPT.

User-triggered fetchers behave differently from crawlers. Perplexity says Perplexity-User generally ignores robots.txt because a person asked for the page, and OpenAI says robots.txt rules "may not apply" to ChatGPT-User. Anthropic says its bots, Claude-User included, honor robots.txt. A rule that works for one operator's fetcher may not work for another's.

Training and search opt-outs are separate

This is the most useful new control. OpenAI says the OAI-SearchBot and GPTBot settings are independent: you can allow search and disallow training, and stay eligible for ChatGPT search results. Google-Extended controls whether Google may use your content to train Gemini models and for grounding in Gemini Apps and Vertex AI, and Google says it does not affect inclusion or ranking in Google Search. Applebot-Extended does the same for Apple's foundation models: pages that disallow it can still appear in Apple's search results.

A robots.txt that allows AI search and opts out of training looks like this:

User-agent: OAI-SearchBot
User-agent: Claude-SearchBot
User-agent: PerplexityBot
Allow: /
Disallow: /admin/

User-agent: GPTBot
User-agent: ClaudeBot
User-agent: CCBot
User-agent: Google-Extended
User-agent: Applebot-Extended
Disallow: /

User-agent: *
Disallow: /admin/

Two cautions. A crawler that finds a group naming it ignores the * group, which is why Disallow: /admin/ is repeated in the search group: the longer /admin/ rule wins over Allow: / for those paths. And blocking Google-Extended does not keep content out of AI Overviews: that is controlled by Googlebot rules and the snippet controls above. The full pattern is in how to allow AI search but block AI training.

Many AI crawlers read only the raw HTML

Googlebot renders JavaScript with an evergreen Chromium, after a render queue. Many AI crawlers do not. Vercel and MERJ's December 2024 analysis found that none of the major AI crawlers it measured, including OpenAI's crawlers, ClaudeBot and PerplexityBot, executed JavaScript at the time. OpenAI's and Anthropic's crawlers downloaded some script files but did not run them. The same analysis said Applebot renders JavaScript, so the gap is not universal, and crawler behavior can change after a snapshot like this one.

That means a client-side rendered page can do fine in Google and still look empty to a crawler that reads only the HTML the server sends. Classic SEO could tolerate this because Google renders. We cover the detail in do AI crawlers run JavaScript?

Edge rules decide more than robots.txt

OpenAI recommends allowing OAI-SearchBot in robots.txt and also allowing requests from its published IP ranges. A CDN bot rule or WAF challenge that blocks those requests keeps the crawler out even when robots.txt is correct. Bot protection rarely came up in SEO work; with AI crawlers, a bot rule written to stop scrapers can catch the crawlers you wanted to let in.

What is still unproven or hype

These claims circulate widely. None is backed by the operators' own documentation at the time of writing.

• "Add llms.txt to appear in AI answers." llms.txt is a proposal from llmstxt.org, not a standard. Google's AI optimization guide says Google Search does not use it, and OpenAI, Anthropic and Perplexity do not document that their crawlers read it on other sites. It is cheap to publish, but do not expect it to change visibility.
• "AI Overviews need special schema." Google says no special schema.org structured data, AI text files or markup are needed.
• "FAQ schema gets you into AI answers." FAQ rich results stopped appearing in Google Search on May 7, 2026, and Google's AI features page lists no schema requirement. FAQ markup no longer earns a search feature.
• "Rewrite your copy with statistics and quotes to be cited 40% more." That figure is the upper end of results on one benchmark in one paper, with a small follow-up test that fed source texts to Perplexity.ai directly. Clear, sourced writing is good practice anyway; the paper does not show the same gain for your pages in live search.
• "We can get you cited by ChatGPT." No one controls which sources an assistant picks. Fixing technical barriers makes a page eligible to be read; whether it is quoted depends on the question, the competition and the operator's systems. More of these are in eight AI search myths.

How to check where your site stands

You can test the new parts in a few minutes.

1. Read your robots.txt per crawler. Open https://yoursite.com/robots.txt and, for each token in the table above, find the group that names it. If none names it, the * group applies.
2. Fetch a page the way a non-rendering crawler does. Check the status and whether a sentence from your main content is in the raw HTML:

UA="Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko); compatible; GPTBot/1.4; +https://openai.com/gptbot"
curl -s -o /dev/null -w "%{http_code}\n" -A "$UA" https://yoursite.com/pricing
curl -s -A "$UA" https://yoursite.com/pricing | grep -c "a sentence from your main content"

A 200 and a count above 0 mean the text is in the HTML. A 0 usually means client-side rendering. A 403 or a challenge page means an edge rule. This test runs from your own IP, so it will not reproduce rules that depend on the crawler's IP ranges; check your CDN or WAF settings and logs for those.

3. Check snippet and index controls. Look for noindex or nosnippet in the response headers and in the robots meta tag:

curl -sI https://yoursite.com/pricing | grep -i x-robots-tag
curl -s https://yoursite.com/pricing | grep -io '<meta[^>]*name="robots"[^>]*>'

4. Look for real visits. Search your server or CDN logs for the tokens OAI-SearchBot, GPTBot, ClaudeBot, Claude-SearchBot and PerplexityBot, and verify the source IPs against each operator's published list before trusting them.

How to prioritize the work

Treat GEO as technical SEO plus a crawler policy, in this order:

1. Fix anything that breaks every crawler: status codes, redirect chains, accidental noindex, challenge pages.
2. Make sure main content is in the server-sent HTML (server rendering or static generation).
3. Decide your policy per purpose: search, training, user-triggered. Write it into robots.txt and match it at the CDN or WAF.
4. Clean up structure: titles, headings, canonicals, structured data that matches the page, sitemap.
5. Only then spend time on optional extras like llms.txt, and measure rather than assume.

Frequently asked questions

Is GEO replacing SEO?

No. Google says AI Overviews and AI Mode use pages that are indexed and eligible for snippets, and Microsoft says Copilot grounds answers through the Bing search service, so SEO foundations remain the entry ticket. GEO adds a crawler policy and a raw-HTML requirement on top.

Does blocking GPTBot remove my site from ChatGPT search?

No. GPTBot controls whether content may be used for OpenAI model training. ChatGPT search eligibility is controlled by OAI-SearchBot, and OpenAI says the two settings are independent.

Do I need llms.txt for AI search?

It is optional. Google Search does not use it, and no major AI search operator documents reading it on third-party sites at the time of writing. Publishing one does no harm, but it does not replace crawl access or readable HTML.

Can anyone guarantee AI citations?

No. Technical readiness removes barriers that stop AI tools from reaching and reading your pages. Which sources an assistant cites depends on factors no site owner or agency controls.

Next step

If you want to know which of these technical barriers apply to your site, start with the free single-page check, which needs no account. For a full-site audit of up to 500 pages, with evidence and prioritized fixes, see the audit.