This post announces the top three winners from a 600+ submission essay contest on major AI challenges. Jassi Pannu outlines a state-scale plan to end airborne pathogens, Ege Erdil advises growth-focused policies for countries outside the AI supply chain, and Michael Li compares AI labs’ economics to Hong Kong’s MTR model. Each full essay follows the brief winner descriptions.

• Far-UVC lighting infrastructure could cut seasonal flu mortality 60% and add $1T+ to global GDP for a $40-60B/10-year investment, while also blunting engineered pandemic risk.
• Erdil argues countries outside the AI supply chain should pursue standard growth policies (property rights, low capital taxes, light regulation) rather than geopolitical maneuvering to stay economically relevant.
• Li compares AI labs to Hong Kong's MTR, suggesting labs could offset massive compute costs by owning complementary "adjacent" assets rather than relying solely on core product revenue.

The article shows how Cursor achieved rapid growth by forking VS Code’s open-source code, preserving every user’s settings and extensions so there’s zero switching cost. It argues that instead of forcing users to jump to a new tool, you can “inherit” their staying value by building on the exact platform they already use. This approach lets you slip in a deeper advantage where the incumbent can’t follow without breaking their ecosystem.

• Cursor forked VS Code and kept all user settings/extensions intact, hitting $100M ARR in under two years with almost no marketing spend
• The growth strategy was "inherit, don't overcome": build on the exact platform users already have so switching costs drop to zero
• Forkable open-source codebases (VS Code, Chromium, Postgres) or open APIs/plugin hooks let you legally piggyback on an incumbent's ecosystem
• The real advantage gets layered one level deeper (e.g., AI-first engine) where the original developer can't follow without breaking their own product

Successful waitlist strategies have evolved from simple sign-up forms to essential marketing tools that enhance lead quality for startups. By analyzing case studies, the article emphasizes the importance of understanding user intent, segmenting potential customers, and rapidly converting waitlisted users into paying customers. Founders are encouraged to use waitlists not just for hype, but as a way to generate valuable insights and revenue.

• Waitlists now function as lead-qualification and segmentation tools rather than mere hype-generators
• Speed matters: converting waitlisted users into paying customers quickly is key to capturing momentum
• Collecting intent signals (not just emails) from waitlist sign-ups yields actionable insights for prioritizing which users to convert first
• Case study evidence shows waitlists can directly drive revenue, not just anticipation, when designed with conversion in mind