82% of companies make decisions based on stale data—but only 23% can access real-time ERP information. In this episode of AppDevANGLE, Paul Nashawaty sits down with Justin Borgman, CEO and Co-Founder of Starburst, to discuss how modern query engines are transforming AI application development. 🔑 Key Topics Covered: • Why real-time data access is critical for AI-powered applications • How Starburst's query engine connects distributed data sources without moving data • Data as a Product: Rethinking application design and ownership • Integrating AI features safely into CI/CD pipelines • Bridging legacy systems with modern data architectures • Open-source solutions: Trino and Apache Iceberg for cost-effective data management • Data governance, security, and compliance in AI applications • The rise of citizen developers and AI-driven app creation • Agent-to-agent communication and MCP servers About the Guest: Justin Borgman is the Co-Founder and CEO of Starburst, creators of the open-source Trino project. Starburst provides a data platform for running analytics and building applications that access data across lakes and enterprise sources. About the Host: Paul Nashawaty is the Practice Lead and Principal Analyst at ECI Research, specializing in application development, DevOps, and enterprise software. 🔗 Try Starburst Galaxy (Free Tier): 📧 Contact Paul: paul@ Timestamps: 0:00 - Introduction: The Real-Time Data Crisis 0:38 - Meet Justin Borgman & Starburst Overview 1:53 - AI Applications and the "Wrong Data" Problem 4:25 - Data as a Product: Should Developers Rethink Design? 6:35 - Testing AI Features in CI/CD Pipelines 9:00 - Citizen Developers and AI-Powered App Creation 12:05 - Trino, Iceberg, and Open-Source Data Management 14:24 - Advice for Teams: Experimentation and MCP Servers #DataEngineering #AIApplications #Starburst #Trino #ApacheIceberg #DataGovernance #RealtimeData #AppDevelopment #DevOps #DataMesh #CICD #EnterpriseAI #CloudData #DataProducts #TechPodcast