What is LLMO? LLM Optimization — Be reachable, parseable, ingestible.
LLM Optimization (LLMO) is the practice of making your content reachable, parseable, and trustworthy to the LLMs themselves — at both training time (large-scale crawls) and retrieval time (RAG pipelines, browsing tools, agent crawlers like GPTBot, ClaudeBot, and PerplexityBot). LLMO is the plumbing layer that AEO and GEO sit on top of.
How LLMO differs from AEO, GEO, SEO
LLMO is the plumbing layer. AEO works on the answer surface, GEO works on the generative surface, and LLMO makes sure the model and its crawlers can actually reach, parse, and trust your content in the first place. Without LLMO the other two can't fire.
How Mentionwell handles LLMO
- Site-wide llms.txt and llms-full.txt published at the canonical paths.
- Per-article .md mirrors at <path>.md so any LLM can ingest a clean Markdown version of the article.
- Stable canonical URLs, RSS, and JSON Feed for retrieval pipelines.
- Embeddings indexed per article for semantic search and similarity-based internal linking.
- Explicit AI crawler allowlist in robots.txt — every major bot named individually so the policy is unambiguous.
Frequently asked questions about LLMO
What is LLMO?
LLMO stands for LLM Optimization. It's the practice of making content reachable, parseable, and trustworthy to LLMs themselves — at both training time (large-scale crawls) and retrieval time (RAG, browsing tools, agent crawlers like GPTBot, ClaudeBot, PerplexityBot). LLMO is the plumbing layer that AEO and GEO sit on top of.
What's in a good LLMO setup?
A site-wide llms.txt and llms-full.txt, per-page .md mirrors, an explicit AI crawler allowlist in robots.txt, stable canonical URLs, RSS and JSON Feed, and embeddings for semantic retrieval. Mentionwell ships all of these by default.
What is llms.txt?
llms.txt is a proposed standard (llmstxt.org) for a site to expose a concise overview of itself, in Markdown, at /llms.txt. It tells AI assistants what the site is, what it covers, and which pages matter most — like robots.txt, but for LLM context rather than crawl policy. Mentionwell serves both /llms.txt and a deeper /llms-full.txt.
Should I block AI crawlers?
Only if you have a specific reason. Most sites benefit from being crawlable: that's how their content shows up in ChatGPT, Claude, Gemini, and Perplexity answers. Mentionwell's default robots.txt explicitly allows GPTBot, ClaudeBot, PerplexityBot, Google-Extended, and 15+ others.
How is LLMO different from GEO?
LLMO is the plumbing — making sure the model and its crawlers can reach and parse your content. GEO is the layer above — making the content the kind of source the model wants to cite. You need LLMO before GEO can fire.
See also
Sources
Per the Princeton GEO study (2024), pages with inline citations to authoritative sources see roughly +30% higher LLM citation probability. We surface ours so you can verify every claim on this page — and so generative engines can cross-reference us against the originals.
- The /llms.txt file proposal Original llms.txt specification — the canonical surface for LLMO.
- OpenAI: GPTBot crawler documentation Authoritative reference for the GPTBot user agent and robots.txt directives.
- Anthropic: ClaudeBot user agents ClaudeBot, anthropic-ai, and Claude-User crawler reference.
- Google-Extended documentation Per-crawler control for Google's generative AI uses.
Ship LLMO-optimized articles automatically
Mentionwell handles LLMO on every published article — alongside the other six optimization targets in this glossary — so you don't have to think about it per post. Drop a domain, approve the first headline, watch the pipeline run.