Love at First Search is a podcast about expert authority, discoverability, and the future of search. Hosted by Meg Casebolt, it explores how experts become easier to recognize, understand, recommend, and find across search engines, AI tools, websites, podcasts, and other public platforms. Episodes dig into authority architecture, expertise legibility, positioning, narrative differentiation, semantic territory, omnichannel distribution, and the changing mechanics of search—without reducing the work to keywords, content volume, or platform hacks. This is the audio layer of a larger body of work from Love at First Search: the same core ideas may also appear in video, written articles, LinkedIn posts, frameworks, and case studies, each adapted to the format rather than simply duplicated. If your expertise is strong but your public signals are scattered, vague, outdated, or hard for humans and machines to connect, this show is about making that expertise clearer, sharper, and easier to trust.