LLM SEO
LLM SEO is the technical work underneath AEO — the crawler access, entity signals, and structured data that determine whether ChatGPT, Claude, and Perplexity can actually read and trust a site at all. Most of what's sold in this category is theater. This is the part that measurably isn't.
By Nithish Govindasamy · Updated August 2026
The gap between what's sold and what works
Nearly every "LLM SEO checklist" leads with llms.txt as the essential first step. The real data doesn't support that: it's a niche convention with no official backing from OpenAI, Anthropic, or Google, and independent monitoring shows AI crawlers almost never fetch it directly — they crawl the HTML instead, the same as any other bot. Being straightforward about that, and where the real leverage actually is, is the whole point of doing this technically instead of by checklist.
What Nivonto actually does under "LLM SEO"
- Crawler access audit — auditing robots.txt for the search-time bots that matter (the ones answering a live query, distinct from training-only crawlers) and fixing blocks that make a site invisible to a given engine.
- Entity resolution — Organization and Person schema, sameAs links, and consistent facts across every public source, so engines have a confident, unambiguous entity to attribute claims to.
- Structured, extractable content — answer-first paragraphs, FAQ schema, and comparison tables, since these are what engines lift directly into a generated answer.
- Freshness cadence — a real update rhythm on key pages, since recently-updated content is measurably more likely to surface in AI answers than stale content, even when the underlying facts haven't changed.
How this differs from a generic "AI SEO checklist"
Most checklists are written once and copied across a hundred blog posts, which is exactly how a marginal tactic like llms.txt became conventional wisdom. Nivonto's approach is to verify what each engine actually does — re-checked as behavior changes — rather than follow the same list everyone else is following. See the free audit for where a specific site's crawler access and entity signals currently stand.
Frequently asked questions
- Does llms.txt actually help with LLM SEO?
- Its impact is far smaller than the marketing around it suggests. Of the most AI-cited domains, the large majority don't have an llms.txt file, and independent traffic studies show AI crawlers fetch it in a tiny fraction of visits — no major AI lab has publicly committed to reading it in production. Nivonto still publishes one (cheap, harmless, a few agent plugins do use it), but never sells it as the mechanism that gets a client cited.
- What actually matters more than llms.txt?
- Two things, in order: entity clarity (Organization schema with sameAs links to Wikipedia, Crunchbase, and LinkedIn, so an engine can resolve who you are with confidence) and crawler access (making sure search-time bots — the ones fetching live to answer a query right now, not just training bots — can actually reach your pages). Sites that deliberately unblock the right crawlers see measurable AI-referral traffic gains within months.
- Do ChatGPT, Perplexity, and Google AI Overviews read the same signals?
- No, and treating them the same is a common mistake. Perplexity runs a live search on every query and weights Reddit and content freshness heavily. ChatGPT leans on a retrieval layer triggered mainly by commercial-intent phrasing, and favors Wikipedia disproportionately. Google AI Overviews doesn't crawl independently at all — it only synthesizes from pages already ranking well in classic Google search, so traditional SEO is a prerequisite there, not an alternative.