Backgrounds that can work (the skill matters more than the title): modern enablement at an AI-native company, qualitative/academic research, ethnography, instructional or curriculum design, knowledge management, product ops, technical writing, research ops, implementation, chief of staff roles, library and information science, AI ops / human-in-the-loop work, or startup operations where the systems were messy and someone had to make them legible. Were not bolting AI onto insurance - were rebuilding the entire business as software, on a simple bet: turning expert human judgment into compute is one of the largest transitions left to make, and a trillion-dollar industry still run 90% by hand is the place to prove it.