How AI Agents Change the ML for Trading Workflow

Stefan Jansen is the founder of Applied AI and author of Machine Learning for Trading, now in its third edition. He teaches how to move from an idea to a reliable production system: define requirements, design data and evaluation, test failure modes, and establish the operating process. His work spans quantitative research and live trading infrastructure, contract intelligence for insurers, healthcare forecasting, and AI agents. He currently builds multi-agent systems and coding-agent workflows, with particular attention to verification, governance, and deciding where agents fit. More than 100,000 people have taken his courses. Stefan holds a Harvard master’s in economics and public policy, a Georgia Tech MS in computer science, and the CFA charter.