LLM SEO
Last updated September 2026
LLM SEO is the set of practices that make a website's content more likely to be retrieved, parsed, and referenced by large language models, whether inside a chat interface like ChatGPT or a search feature like AI Overviews. It overlaps heavily with GEO and AEO, with more emphasis on the technical layer that determines whether a model can reach the content at all.
01
How language models actually find your content
Some models answer from pretrained knowledge baked in at a training cutoff. Some use a live web search tool call. Some run retrieval-augmented generation against an index built separately from the open web. Content needs to be crawlable, indexed by whichever search layer feeds a given system, and structured clearly enough to be lifted without ambiguity, regardless of which path applies.
02
The technical checklist
- 01
Crawlability
no robots.txt or meta directives blocking the content models rely on
- 02
Clean HTML semantics
real heading tags, not styled divs pretending to be headings
- 03
Schema markup that labels entities and answers explicitly
- 04
Canonical URLs so a model cites the intended page rather than a duplicate
- 05
Fast, stable page delivery, since a model retrieving live content will skip a page that times out
03
Where LLM SEO diverges from AEO
AEO and GEO focus heavily on how content is written: answer-first structure, quotable definitions, corroborated claims. LLM SEO's distinct contribution is the infrastructure layer underneath that writing, whether a model can even reach and parse the page in the first place. Neither works without the other.
Conduit's technical SEO audits already check crawl access, schema, and crawl budget, so extending that work to confirm whether AI crawlers like GPTBot or ClaudeBot are blocked fits inside existing engagements rather than requiring a separate service line.
The practical difference from traditional SEO work is testing: an agency has to periodically query the models directly with a client's target questions to see whether the optimization is actually landing, since there is no rank tracker for AI citations yet.
