The 7-step technical SEO checklist for AI search.
What schema to ship, what canonicals to fix, which AI crawlers to allow, and the one robots.txt mistake that gets you silently dropped from training corpora.
Technical SEO for AI search isn't a different discipline from technical SEO for Google search — but the priorities shift. Some things that used to be "nice to have" became mandatory; some things that were table stakes are now nearly irrelevant. Here's the 7-step checklist we run for every new SEONova customer in their first week.
1. Ship Article + Organization JSON-LD on every URL
LLMs prefer to cite content that's structurally legible. Schema.org isn't a ranking factor in AI search the way it is in traditional SEO, but it materially improves citation rates because the model can extract clean metadata (author, publishDate, topic) without parsing your HTML.
2. Allow AI crawlers in robots.txt (selectively)
GPTBot, ClaudeBot, PerplexityBot, Google-Extended — each one separately. Blocking them via wildcard is the single most common reason brands disappear from AI recommendations. If you want to opt out of training corpora but be included in retrieval-augmented search, the right config is more nuanced than "User-agent: * Disallow: /".
# Allow retrieval-augmented search but opt out of training:
User-agent: GPTBot
Disallow: /
User-agent: ChatGPT-User
Allow: /
User-agent: Google-Extended
Disallow: /
User-agent: Googlebot
Allow: /
User-agent: PerplexityBot
Allow: /Watch out for GPTBot vs ChatGPT-User
GPTBot is the training crawler. ChatGPT-User is the retrieval crawler that fires when a user asks ChatGPT a question. Blocking both removes you from BOTH training AND live answers. Most brands want to block one and allow the other.
3. Fix your canonicals (yes, still)
LLMs are surprisingly sensitive to canonical confusion. If you serve the same content at /blog/post and /post and /p/post, you'll see your citations fragmented across all three URLs in source lists, which dilutes your aggregate authority.
4. Get your dates right
Models heavily prefer recent content. If your articles don't have a clearly-marked publish date (in schema, in meta tags, and visually), they get downranked in retrieval-augmented citation pools. "Last updated" stamps help too.
5–7: Sitemap, internal linking, performance
Maintain a clean XML sitemap (we wrote a separate piece on this); cross-link your core content into topical clusters so the model can infer your topical authority; keep Core Web Vitals green because slow pages are deprioritized in retrieval the same way they are in Google's main index.
Written by
Daniel Vance
Co-founder & Head of Engineering
Crawls, parses, ranks, retries. Cares more about p99 than p50, and more about correctness than either.
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