Startups and Job Redesign: Evidence from the Third Age of Artificial Intelligence”, examines the contexts in which VC-funded startups accelerate the AI-driven redesign of jobs. With the falling cost of prediction, a growing number of occupations are redesigned to include AI prediction tasks within their task bundle. Such job redesign is the main margin of adjustment within the labour market in response to the emergence of Artificial Intelligence, and within startups, over 20% of jobs are redesigned. By decomposing with NLP over 250 million online job postings into 1.2 billion task descriptions, I document that startups’ experimentation with job redesign has large local spill-over effects on incumbent firms. The effect is asymmetric, and incumbents have a much weaker effect on the prevalence of job redesign at startups. I find that the startup’s efforts to redesign jobs are associated with improved fundraising success. For incumbent firms, the redesign of jobs results in increased return on assets and sales growth. These findings establish an important role which VC-funded startups play in the dissemination of complementary work practices to AI adoption. We also highlight a new margin of experimentation for entrepreneurs, which increases fundraising success.