AI-ready websites in practice: what I do on vorqul.com
A practical checklist of how this site is optimized for classic search engines and AI answer engines: structured data, llms.txt, answer-first writing.
By Yamiru
An AI-ready website is one that a search engine crawler and a large language model can both read, understand and cite accurately. On vorqul.com I treat that as an engineering requirement. This is the checklist I follow.
Answer-first writing
Every important page opens with a direct answer to the question that brought the visitor there, before any storytelling. People skim and answer engines quote, so putting the conclusion first serves both.
Structured data everywhere
Organization, WebSite, WebPage, SoftwareApplication, FAQPage, BreadcrumbList and Article schemas describe every page in machine-readable JSON-LD. When an AI system or a rich-result parser asks what a page is about, the answer is written down and needs no guessing.
llms.txt and open crawling
The llms.txt file gives language models a curated map of the site in plain Markdown. robots.txt welcomes AI crawlers by name, among them GPTBot, ClaudeBot, PerplexityBot and Google-Extended. When the content is yours and you want it found, being cited by an assistant is distribution.
Speed, for rankings and for visitors
The site is fully static, inlines its critical CSS, ships close to zero JavaScript and is served from a global edge network. Core Web Vitals stay green without a performance sprint, since there is very little to slow down.
The part most checklists skip
None of the above helps if the content is vague. I name entities consistently, make claims specific and give each page one intent. Writing for machines and writing clearly for people turned out to be the same job.