An award-winning science journalist and author, Kevin Hartnett reveals how abstract ideas shape the technologies, economies and societies we live in. His work shows how breakthroughs in mathematics and computer science increasingly influence the modern world.
Formerly Senior Writer at Quanta Magazine, Hartnett spent years chronicling breakthroughs in mathematics, theoretical computer science and AI. His reporting has also appeared in The Atlantic, WIRED, Scientific American, Nautilus and The Boston Globe, where he wrote the weekly Brainiac column. His work has also been selected for multiple editions of Princeton University Press’ The Best Writing on Mathematics.
Kevin Hartnett’s expertise lies in uncovering the deeper significance behind scientific advances. Rather than reporting on technology alone, he explores the people, ideas and intellectual revolutions that drive it. His work demonstrates that mathematics is no longer confined to academia. Instead, it underpins modern computing, cybersecurity, scientific research and the next generation of artificial intelligence.
Harnett’s latest book, The Proof in the Code, traces the remarkable rise of Lean, a mathematical proof assistant. What began as an obscure software project is now becoming a foundation for trustworthy AI. The book follows the researchers who transformed Lean into a new kind of “truth machine”. It verifies mathematical proofs, validates software and increasingly works alongside large language models. In doing so, Hartnett uncovers one of AI’s most consequential yet overlooked developments: the growing partnership between human reasoning and machine intelligence.
As AI systems become more capable, Kevin Hartnett argues that the future depends not only on generating answers, but proving they are correct. His work explores how formal reasoning could overcome one of AI’s greatest weaknesses. It could reduce hallucinations, improve software reliability and enable more dependable scientific discovery. These advances have profound implications for business, technology, finance and public policy. Confidence in AI-generated outcomes is becoming just as important as the outcomes themselves.
