How this site is built for AI
This site is a working example of Generative Engine Optimisation. Every page is engineered to be clear for both people and machines — structured data, a consistent entity, canonical URLs, an llms.txt and citable FAQs. This page lays out exactly what was done and how you can verify each claim yourself.
Why practise what we preach
It would be odd to advise businesses on AI visibility from a site that ignored its own advice. So this one is built to the same standard the AwarenessAI work recommends — not as a guarantee of any result, but as a demonstration of what good practice looks like when it is applied end to end.
The aim is simple: make it easy for a person — or a machine — to understand who Tom Mason is, what he does, and why the information here can be relied on. Everything below is something you can inspect.
The techniques, in plain terms
Each technique below is applied across the whole site, not just this page.
A single, consistent entity
Every page describes "Tom Mason" the same way and links the same profiles with sameAs — LinkedIn, AwarenessAI, Connect Lancaster and the book. This helps a machine reconcile one identity across the web rather than guessing. See entity clarity.
Structured data on every page
Each page carries JSON-LD using the Schema.org vocabulary — Person, Organization, Article, Book, FAQPage and BreadcrumbList — so key facts are stated explicitly, not left to be inferred.
Citable, self-contained answers
Important pages end with plain-English FAQs that answer one question each, in full. These are the kind of clear, quotable passages an AI answer can lift and attribute — and they mirror the on-page FAQPage markup.
An llms.txt for AI crawlers
A plain-text /llms.txt file summarises who Tom Mason is and maps the key pages — an emerging convention that gives language models a concise, reliable starting point.
Clean crawl foundations
A canonical URL on every page, an XML sitemap.xml, and a robots.txt that explicitly welcomes AI crawlers including GPTBot, PerplexityBot and ClaudeBot.
Visible trust signals
Named authorship with a bio on every article, dated content (datePublished and dateModified), references to primary sources, and clear, hedged language that doesn't overclaim. See AI trust signals.
Dense, sensible internal links
Pages link to each other in context — guides to the glossary, tools to the guides — so the relationships between concepts are explicit and easy to follow.
Verify it yourself
Claims about AI optimisation are easy to make and hard to check. These aren't — here's how to confirm them in a couple of minutes:
Open any page's source and search for application/ld+json to see its structured data.
Visit tommason.co/llms.txt and tommason.co/sitemap.xml directly.
Paste any URL into Google's Rich Results Test or the Schema Markup Validator.
Ask an AI assistant "Who is Tom Mason?" and see how clearly it can answer.
What this does & doesn't do
None of this guarantees rankings, citations or recommendations within AI systems — the internal workings of those systems are not public, and no honest practitioner would promise a specific outcome. What it does is improve information quality, structure and clarity: removing ambiguity, stating facts plainly, and making the site easy to read and trust. That is good practice regardless of any single platform.
Frequently asked questions
Does building a site this way guarantee AI visibility?
No. These techniques improve information quality, structure and clarity, which is good practice regardless of any specific system. They do not guarantee rankings, citations or recommendations within AI systems.
What is the single most important GEO technique?
For a person or organisation, entity clarity is usually the most important: a consistent name, a clear description, and sameAs links connecting your profiles so an AI system can reconcile one identity across the web.
Can AwarenessAI do this for my business?
Yes. AwarenessAI assesses how AI currently represents a business and provides a practical plan to improve it. You can also start with the free AI Tools.
Key takeaways
- The site applies the same GEO practices AwarenessAI recommends to clients.
- Structured data, a consistent entity, clean crawl foundations and an llms.txt are all in place.
- Every claim on this page is independently verifiable.
- Good structure helps, but it is never a guarantee — and this site says so plainly.
Cite this page
Found this useful? A link is the highest compliment. Copy a ready-made reference below.
https://tommason.co/geo-lab/how-this-site-is-built-for-ai
Mason, T. (2026). How This Site Is Built for AI. Tom Mason, GEO Lab. https://tommason.co/geo-lab/how-this-site-is-built-for-ai
<a href="https://tommason.co/geo-lab/how-this-site-is-built-for-ai">How This Site Is Built for AI — Tom Mason</a>
Related GEO Lab resources
What your organisation looks like to a machine.
What makes information more credible to AI systems.
Last reviewed: June 2026 · A case study in the GEO Lab knowledge library.
