1. Navigating Rapidly Evolving AI Tech StacksThe Case for PostgreSQL as the Foundation for AI Data InfrastructureUnderstanding the Need for Open Standards and Flexibility from Pluggable Vector Stores2. Accommodating Diverse Data Types and SourcesWhy RAG Requires a Diversity of Data SourcesWhy You Need Unified Data Access Across Disparate SourcesBalancing Transactional, Operational, External, and Unstructured Data3. The Complexity of Handcrafted Data PipelinesWhy Roll-Your-Own Slows InnovationWhy Automation Is Key in Data Preprocessing Pipelines4. The Painful Route from Prototype to ProductionDistributed Scaling and ResilienceRow-Level Geo-Partitioning for Data ResidencyMulti-Cloud, Multi-Region, and Hybrid Deployment StrategiesMulti-API Flexibility for Rapidly Changing Environments