This talk explores the geo-location of WiFi access point data - as a novel proxy for estimating human population distribution. I examine how open-source data—previously leveraged in research such as Erik Rye's work with Apple's WiFi location API—can be harnessed for localised analysis. Rye’s approach, which utilizes Apple’s API to return locations of BSSIDs and their neighboring networks, inspired a deeper question: Could one "crawl" outward from a single point to systematically map all BSSIDs in a region?

Finding no existing tool to automate this process, I embarked on developing my own solution. Leveraging Google’s Firebase Studio and the concept of “vibe coding,” I iteratively built a tool capable of mapping BSSIDs across geographic areas. This talk details my journey from conception to a functional tool, including technical challenges, methodology, and insights gained along the way - without writing a single line of code, in a language and hosted environment I have very little clue about, while both loving and hating my AI coding partner. Attendees will learn about the intersection of open wireless data, coding experimentation, and creative problem solving, as well as the broader implications for privacy, urban analytics, and open-source intelligence.