A practical framework from Y Combinator's Jared Friedman for how to generate and evaluate startup ideas. Covers the 4 most common founder mistakes, 10 key evaluation questions, 3 counterintuitive signs of a good idea, and 7 proven recipes.

With generative AI becoming ubiquitous, programming educators face a critical challenge: designing assessments that measure genuine learning without being circumvented by AI tools. This article examines multiple methods with explicit tradeoffs.

Machine learning course projects at MIT are a rare chance to practice real research judgment under tight time and compute constraints—without the pressures of funding, publication, or product delivery. Drawing on experiences across MIT ML courses, this article explains how to choose project questions that maximize insight, learning, and scientific value rather than scale or raw performance.