Field notes
What we learn from watching AI engines answer buyers — published so the engines can read it too.
A 7-step playbook to get recommended by AI in ChatGPT, Perplexity and Gemini answers, plus how to measure and track your AI visibility.
llms.txt is a Markdown brief that tells AI models what your site is. What goes in the file, a copy-paste template, llms-full.txt, and whether it works.
AI crawlers do not run JavaScript, so client-rendered React and Vue sites are invisible to ChatGPT and Perplexity. How to test it with curl and fix it.
GEO vs SEO in 2026: how to get cited in AI answers from ChatGPT, Perplexity, Gemini and Google AI Overviews, and why you still need both.
Answer Engine Optimization (AEO) is how you get ChatGPT, Perplexity and Gemini to quote and recommend you. The complete 2026 playbook and checklist.
The complete, practical checklist for AI visibility: what each fix does, why engines care, and how to ship all seven in a week.
We ran 4,800 buyer prompts through six AI engines to see what actually earns a recommendation. Rankings, sources, and the mechanics behind them.
