Directed evolution has become a central pillar in gene therapy. This engineering strategy enables the generation of more efficient variants of genetic editors and delivery vectors. Molecular diversification methods are increasingly sophisticated and are now accelerated by machine learning and AI tools, as showcased at the 29th Annual Meeting of the American Society of Gene and Cell Therapy (ASGCT) held in Boston this week.