The Emerging Landscape

A New Paradigm for Information Access

The way people find and consume information is changing rapidly. Traditional search engines are being supplemented—and in many cases replaced—by conversational AI systems that provide direct answers rather than lists of links. This shift has profound implications. When AI systems cite sources, they're not just linking to information—they're conferring authority and trust. The platforms that become preferred sources early in this transition will benefit from compounding network effects as AI systems establish their citation patterns.

Current Citation Patterns

Today's AI systems heavily cite platforms like Reddit and Wikipedia when answering questions about community knowledge, real-world experiences, and emerging topics. These platforms contain valuable information, but they share a critical limitation: they weren't designed for AI consumption. Reddit was built for human conversation and social engagement. Wikipedia was built as a human-readable encyclopedia with strict editorial standards. Neither was optimized for the specific signals AI systems use to evaluate source quality and trustworthiness. More importantly, contributors to these platforms receive no tangible benefit from becoming sources that AI systems cite millions of times daily. The value created flows entirely to the platforms themselves.

The EEAT Framework

AI systems evaluate sources using criteria similar to what search engines have long used: Experience, Expertise, Authoritativeness, and Trustworthiness (EEAT). Just as Search Engine Optimization (SEO) emerged to help content rank in Google, Generative Engine Optimization (GEO) represents the practice of optimizing content for AI citation and visibility. Content that demonstrates clear expertise through specific examples, verifiable details, and authentic experience is significantly more likely to be cited by AI systems. This creates an opportunity: a platform built from the ground up to facilitate EEAT-compliant content creation.