Thought leaders profess that GEO requires a scaled content strategy of 100–300 pieces of Ultra Long Tail content at a cadence of 1 blog/day.

At that cadence and volume, you can't use classic SEO playbook. So they resort to AI + Human workflows.

Said workflows produce content at a somewhat faster cadence than before. More pages, more FAQs.., without asking whether if said content is “net new” for the LLMs, what the LLMs are hungry for, and what actually shifts the needle of what an LLM says about a brand.

This talk introduces Information Gain (IG) as the metric that's missing. IG is a way of scoring whether a piece of content is genuinely novel relative to what the models already know versus just retraining them on what they’ve already crawled.

Drawing on real RAG pipeline architecture (chunk retrieval, source traceability to avoid hallucination, IG-Corpus vs IG-Model scoring), Paris will show why Information Gain is what practitioners should actually consider prior to targeting another piece of content.