AI SEO Answers
What is LLM SEO?
Quick answer
LLM SEO is optimizing a brand's visibility in the outputs of large language models — the systems behind ChatGPT, Claude, Gemini, and Perplexity. It's substantially the same discipline as generative engine optimization: making a brand readable, consistent, and corroborated enough that LLM-powered tools mention it when relevant. The term emphasizes the models; GEO emphasizes the search surfaces; the work is one body.
Where LLMs get their picture of you
Two channels: training data (the web as it existed when the model was trained — slow to change, impossible to edit retroactively) and live retrieval (web search the assistant performs at answer time — responsive to what your presence says today). You can't do anything about the first except be well-documented going forward; the second is where current work pays off, and it rewards exactly what GEO rewards.
What the work involves
The same three fronts as all AI visibility work: direct answers to real questions on a crawlable site, a consistent identity across every readable surface, and third-party corroboration. LLM SEO adds one emphasis worth naming — machine access: retrieval-time crawlers (GPTBot, PerplexityBot, ClaudeBot and peers) must be allowed in robots.txt, and content must exist in served HTML rather than only after JavaScript runs, or the assistant's reader gets a blank page where your answer should be.
Frequently asked
- What is llms.txt?
- A proposed convention — a plain-text file suggesting to AI systems which of a site's pages best represent it, analogous in spirit to robots.txt. Adoption by the AI platforms is unsettled, so treat it as a low-cost addition, not a strategy: it can't hurt, and shouldn't be relied on.
- Is LLM SEO worth pursuing separately from SEO?
- Not separately — as an extension. The foundations are shared; the additions (assistant crawler access, answer-first structure, corroboration audits) bolt onto an existing SEO practice cleanly.