What llms.txt means
llms.txt is a proposed web standard — introduced by Jeremy Howard of Answer.AI in 2024 — for giving AI systems a curated, machine-friendly map of a website. It's a plain markdown file served at the site root (/llms.txt) that summarizes what the site is and links to its most important pages, so that a language model can grasp the essentials without crawling and parsing hundreds of HTML pages full of navigation, scripts, and boilerplate.
The comparison that locates it: robots.txt tells crawlers what they may access, an XML sitemap tells them what exists, and llms.txt tells AI systems what matters — in prose they can read directly. A companion convention, llms-full.txt, inlines the full text of key pages; some sites also publish markdown versions of individual pages for the same reason.
What an llms.txt file looks like
The format is deliberately minimal — a title, a short summary, then annotated link lists:
# Acme Analytics
> Acme Analytics is a product analytics platform
> for B2B SaaS teams.
## Docs
- [Quickstart](https://acme.com/docs/quickstart.md):
Install and send your first event
- [Pricing](https://acme.com/pricing.md): Plans and limits
## Optional
- [Changelog](https://acme.com/changelog.md)
For a brand, the strategic content is the summary and the selection: it's a chance to state, in your own words, what your company is, who it serves, and which pages carry the authoritative facts — exactly the framing you want an AI crawler to encounter first.
Does llms.txt actually work?
Honest answer: adoption is real on the publishing side — many developer-tool and SaaS companies ship one — but the major engines have not formally committed to honoring the file, and there's little public evidence that ChatGPT, Gemini, Perplexity, or Claude systematically fetch it when answering. That makes llms.txt a hedge, not a lever: cheap to add, zero downside, potential upside if engine support arrives — and immediately useful for AI coding assistants and agents that do read it when pointed at your site. What it is not is a substitute for the things engines demonstrably use: crawlable pages, structured data, and content worth citing. A deeper cost-benefit take: what is llms.txt and do I need it.
llms.txt in a GEO program
Treat it as one hour of work inside a larger content strategy for AI search: write the summary carefully (it's your self-description for machines), keep the link list short and canonical, update it when facts change, and don't expect it to move metrics on its own. Whether any of this is changing how engines present your brand is an empirical question — one that scheduled prompt tracking answers, before and after.