Summary
In this episode, host Chrystina sits down with Priyabrata Nandi, Vice President of Software Engineering at Fidelity Investments, to explore how enterprises can build AI systems that truly adapt to changing markets and why data reliability must be the foundation.
Key Topics Covered:
- Why AI breaks without trusted and continuously validated data
- How to build AI systems that adapt to changing markets
- The role of data reliability in preventing AI failures
- What teams misunderstand about testing training datasets
- Real-world examples of data drift and model degradation
- Why enterprises need testing monitoring & observability – not tools in silos
- Priyo’s perspective on operationalizing AI in large organizations
This episode brings honest, experience-based insights on the intersection of AI, data quality, and real-world engineering.
