I’ve been working on a problem I keep seeing across LLM-based systems:
models can retrieve the “right” information, but still represent it in the wrong context.
I define this gap as:
GEO (Generative Engine Optimization) ≠ DED (Discovery with Exact Definition).
When this happens, companies face what I call Dark Revenue Loss, lost trust and misdirected decisions that never appear in funnels or analytics.
To address this, I’m designing an infrastructure layer called GEO Core,
a brand governance system for AI that aligns what a model “believes” with what a company truly is across RAG, chatbots, search, and agents.
I’d love guidance on which OpenAI team or program (research, partnerships, evals, or community) would be the right place to explore this direction further.