Generative engine optimization in practice: what LLMs actually quote, the schema and llms.txt setup I use on kescoda.com, and how to measure citations.
Generative engine optimization (GEO) is the practice of structuring content so that AI systems, ChatGPT, Perplexity, Google AI Overviews, select it, quote it and cite it in their answers. SEO competes for the ranked link; GEO competes for the sentence the machine repeats. Same raw material, different unit of competition.
I do this work professionally for clients at diShine, and I run the same system on my own site, so this is a practitioner playbook, not theory. Everything measurable below is sourced; everything tactical is what I actually deploy: entity building, quotable answer blocks, FAQPage and DefinedTermSet JSON-LD, hub-and-spoke architecture, an llms.txt file, and a measurement loop in GA4.