Generative Engine Optimization (GEO): A technical blueprint for ranking in LLMs

OP here. I've been analyzing how search behavior is shifting from standard SEO (10 blue links) to AI-synthesized answers (Perplexity, SGE, ChatGPT).

It seems the ranking algorithm is moving from 'PageRank' (Backlinks = Votes) to what I'm calling 'Citation Authority' (Data Density + Structural Parseability).

I wrote this guide breaking down the technical differences:

Data Density: Why LLMs prioritize sources with unique statistics/integers over opinionated text. Knowledge Graph: How to structure 'Hub and Spoke' content so RAG pipelines recognize entity authority. Inverted Pyramid: Why 'burying the lede' destroys your chances of being cited in a generative response. Curious to hear how others are adjusting their content architecture for RAG-based search?

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