We have covered llms.txt and FAQ structure as separate topics before, and treated as separate jobs they usually get treated as separate priorities too, which means one gets written and the other sits on a list indefinitely. They should not be separate jobs. Both draw on exactly the same source material: the real questions your customers actually ask before they buy. Written together, in one sitting, they reinforce each other instead of quietly drifting apart over time.
Why these two documents keep drifting apart
An FAQ page is written for a visitor scanning a website. An llms.txt file is written for a model reading a plain text summary at the root of a domain. Because they serve different formats, they often get written at different times, by different people, months apart. The result in most of the test runs we complete is two documents that answer overlapping questions slightly differently, with slightly different facts, which is exactly the kind of inconsistency that makes an AI model less confident in either one.
Step one: collect the real questions first
Before writing either document, pull ten to fifteen questions your business actually gets asked, from booking emails, phone enquiries, or whatever your front desk or reception fields most often. Real phrasing matters more than polished phrasing here. "Do you take walk ins" and "is there parking" are exactly how customers ask, and exactly how they type the same question into ChatGPT or Gemini.
Step two: write the FAQ page from that list
Turn each question into a plain, direct answer, one to three sentences, no marketing language. Structure it the way we cover in our FAQ page guide: real question as the heading, factual answer underneath, with FAQPage schema markup so the structure is machine readable as well as human readable. This becomes the detailed, public facing version of the source material.
Step three: condense the same facts into llms.txt
The llms.txt file does not need the full FAQ. It needs a short, dense summary built from the same facts. Take the same ten to fifteen answers and compress each one to a single line under an optional FAQ section in the file, following the structure we set out in our llms.txt guide: business name, one line summary, a short About section, key pages with links, then the condensed FAQ lines. Because both documents were written from the same source list, the facts match exactly. A green fee figure, an opening time, a service area boundary, whatever it is, appears identically in both places.
A worked example
Source question: "What's included in a golf break package?" FAQ page answer: a full paragraph covering rounds included, accommodation, breakfast, and any add ons, with schema markup around it. llms.txt line: "Golf break packages include two rounds, one night's accommodation and breakfast; day packages available without accommodation." Same underlying fact, two formats, zero contradiction between them.
Why the consistency matters more than either document alone
AI models are more confident repeating a fact they can confirm in more than one place on a domain. A green fee figure stated identically on the FAQ page, in the llms.txt file, and ideally in schema markup as well, is a stronger signal than the same fact appearing once. This is the same underlying principle behind citation consistency across directories, applied inside your own site instead of across external listings.
Where to start
Block out ninety minutes. Spend the first thirty pulling real questions from wherever they already live. Spend the next hour writing both documents from that same list, FAQ page first since it forces you to write the fuller answer, then compress each one down for llms.txt. Publish both at once, so neither sits half finished while the other goes live alone.