Six hundred essays landed in the contest on “big questions about AI.” The winner, Jassi Pannu of Johns Hopkins, laid out a plan to eliminate airborne disease transmission. She argues this move would add more than $1 trillion to global GDP by ending flu and other respiratory infections, while slashing the risk of engineered pandemics. Her core idea: build far-UVC lighting and other passive, pathogen-agnostic infrastructure in schools and transport hubs. She estimates $40–60 billion over ten years could cut seasonal flu mortality by 60 percent and make pandemic-scale spread far less likely. In second place, Ege Erdil of Mechanize and formerly Epoch AI tackled how smaller economies can stay relevant in the AI boom. He recommends proven growth policies—strong property rights, low capital taxes, open regulations—rather than grandstanding geopolitical stunts. Erdil points out that these measures already boost productivity; with AI raising the stakes, they’ll count for even more. Third place goes to Michael Li, a Harvard Kennedy School policy student. He compares AI labs to Hong Kong’s Mass Transit Railway model. MTR invests huge capital in trains and tunnels but recoups costs by developing the land around stations. Li suggests AI firms could follow a similar path—finding or creating complementary assets that deliver steady returns even if core products need massive up-front spending. After the winner profiles, the article prints the full essays. Pannu’s piece dives deep into biology-focused resilience. She warns that AI-driven pathogen design will outpace traditional defenses, so we need layers of passive tech now. Erdil’s essay outlines policy playbooks for catching up, while Li’s draws analogies and asks readers to imagine what “adjacent properties” look like for AI. Each winner blends practical steps with larger strategic visions.