Building AI & Data products requires strategizing across data collection & scaling techniques, accounting for uncertainty in AI outcomes, and building feedback loops for the AI flywheel effect. In addition to ML techniques strategies, MLOps and Data architectures are also critical. This talk will go through frameworks, challenges and best practises on these topics.