The method, run on my own entity — in public.

A strategist whose own brand is invisible to the engines is a cobbler with no shoes. So the flagship case study isn't a client — it's this one. And on my own entity I control every variable, which makes the before-and-after more rigorous than a client audit, not less.

Here's what makes it useful proof: I'm not starting from zero. The engines already know parts of my entity — and, revealingly, they disagree with each other. That disagreement is the whole lesson of L6 AI Engine Routing.

What the cold baseline reveals

My name resolves — on the engines that trust a single source. Copilot, Google, and Perplexity return an accurate profile of me, each leaning on my LinkedIn. The three engines that demand independent corroboration — ChatGPT, Gemini, and Claude — won't assert me yet. That gap is the whole map: my recognition currently rests on one source, and the stricter engines are waiting for more.

My product term loses to geography — everywhere. On all six engines, "GEO Decision System" resolves to a Geospatial Decision Support System, not to me. Six of six. Closing that is exactly what this hub is engineered to do.

Cold, no engine names me for the unbranded category — yet. Asked "AI Search Strategist Philippines" without my name mentioned first, every engine returns a syndicated competitor cluster or a generic role definition. That is the honest starting line — and the opportunity.

Each month I re-run every cell, cold, and publish the delta. Watch the product term evict the geospatial namesake, and watch the stricter engines begin naming me as the corroboration lands — that's the case study, in public, in real time.