For most of 2025, the standard AI-search audit I saw from peer agencies looked the same: run a list of prompts once each, screenshot the outputs, code the citations, write the report. Sometimes the prompt list was thoughtful. Sometimes the engines were comprehensive. The methodology, though, almost always assumed that one run per prompt was enough. It isn't. We learned this slowly, then quickly, then expensively. The pilot that broke our methodology Our first GEO audit, back in mid-2025, ran 30 prompts once each on four engines and shipped the report. The client made a budget decision based on it. A month later, doing a follow-up before any work had actually been implemented, we re-ran the same prompts and got materially different citation results on a notable share of them. The variance was bigger than the trend we'd been claiming. The report we'd shipped was, in retrospect, an artifact of a single-day snapshot of these engines' behavior. We hadn't lied; we'd just oversampled certainty.…