High-throughput yeast engineering in biofoundries: towards autonomous and scalable synthetic biology

High-throughput yeast engineering is being transformed by biofoundries that integrate automation, artificial intelligence (AI), and standardized workflows. This review examines how these facilities accelerate strain development through the Design-Build-Test-Learn (DBTL) cycle, with advances in genome editing, phenotypic screening, and predictive modelling. It highlights Australia's involvement through the Australian Genome Foundry, Idea-BIO, and the CSIRO Biofoundiry and explores global efforts to overcome reproducibility and standardization challenges. Despite progress, key barriers remain, including protocol variability and integration of AI tools. We also highlight the opportunity for a shift toward autonomous, self-optimizing 'self-driving labs' that transition from DBTL to Design-Build-Deploy cycles. The future of yeast engineering depends not only on technological innovation, but also on the harmonization of international standards, data governance, and ethical safeguards. If fully realized, the convergence of robotics, AI, and synthetic biology will redefine yeast engineering, leading to step changes in strain performance for a variety of important products, thus enabling economic and sustainable biomanufacturing at scale.