Most B2B websites are written for two audiences: a human visitor and a search engine crawler. There's now a third reader, and it behaves nothing like the other two. When an AI agent or answer engine visits your site to answer a buyer's question, it doesn't scroll, it doesn't parse your hero section for tone, and it has no patience for a mission statement before the facts. It's looking for a small set of plain, checkable claims it can quote with confidence. If your site doesn't offer them in a form it can extract, it moves on to a competitor's site that does.
That's the problem llms.txt and an AI-readable company page solve. We touched on this briefly in our AEO playbook; this post is the concrete build guide: what llms.txt actually is, what belongs on the page it points to, and the specific mistakes that keep otherwise-good B2B sites from ever getting cited.
What is llms.txt?
llms.txt is a plain-text (usually Markdown) file served at the root of your domain, at /llms.txt, that gives AI crawlers and agents a condensed map of your site: who you are, what your product does, and links to the pages that matter most, in the order they matter. It's modeled on robots.txt and sitemap.xml, but where those files exist for search crawlers and indexing bots, llms.txt exists specifically for large language models retrieving context about your company. Not every AI system reads it today, but the ones that do use it as a shortcut past your navigation and marketing copy straight to the substance.
Why this matters more than another blog post
Ready to turn this into pipeline?
Prospect AI runs research, copy, and multi-channel outreach as one system, so consistent pipeline stops depending on heroics.
A blog post can get cited for one question. An AI-readable company page gets cited every time a model needs to describe who you are, what you charge, or how you differ from a competitor, because it becomes the canonical source the model reaches for. Without one, a model answering "what does [your company] do" is left guessing from whatever fragments of your marketing site it managed to parse, and it will often get pricing, positioning, or category wrong in ways you have no way to correct after the fact. An AI-readable page is the closest thing B2B growth teams have to editing the summary an AI gives about them.
What actually belongs on the page
The page llms.txt points to (we keep ours at /llm-info) should read like a spec sheet, not a landing page. Include: a one-sentence description of what the product does and who it's for, the category you compete in, your pricing model (even a range, if exact numbers change), the three or four things that concretely differentiate you from the two or three companies you're most often compared against, founding year and team size if relevant to credibility, and direct links to pricing, docs, and case studies. Every claim should be specific enough that a model could quote it verbatim without sounding like marketing copy.
The mistake almost every company makes
Teams that build one of these pages usually reuse their About page copy, and that's where it fails. "We're passionate about helping businesses grow" has nothing for a model to extract. "We're an AI SDR platform that automates outbound for B2B teams under 200 employees, priced per meeting booked rather than per seat" is a sentence a model can lift directly into an answer. Write the page the way you'd write an internal fact sheet for a new sales hire, not the way you'd write a hero headline.
A structure that works
Lead with a single, dense paragraph answering "what is this company and what does it do," followed by a short bulleted fact list (category, pricing model, ICP, founded, notable customers if you can name them), then a brief comparison section naming the alternatives buyers actually consider and stating plainly where you're different, not just better. Close with links, not calls to action. The page isn't there to persuade; it's there to be quoted.
How to check whether it's working
Ask ChatGPT, Perplexity, and Google's AI Overview to describe your company and compare it to your top two competitors, on a recurring cadence, and read the citations. If your llm-info page shows up as a source and the facts it returns match what you wrote, it's working. If a model is still describing you from a three-year-old press mention or getting your pricing model wrong, that's a specific, fixable gap, not a reason to give up on the channel.
None of this replaces a real GTM motion. It's infrastructure that makes every other channel, outbound included, land on a prospect who already has an accurate picture of who you are before your rep says a word. That's a shorter path to a demo call than starting the conversation from a wrong assumption a model handed them.