Every generation of data infrastructure was built for the needs of its time — and broke when GenAI changed the world. Warehouses offered structure but enforced proprietary formats and enginesw. Hadoop promised openness but delivered limitations. Cloud platforms offered scalability, then quietly locked organizations in at the storage layer.

Today's AI workloads — training runs, feature stores, RAG, agents — demand capabilities no prior generation anticipated. The pace of innovation requires infrastructure flexibility.

AI needs open standards. Apache Iceberg decouples storage, data, metadata, and compute behind an open spec. The data lakehouse serves analytics, ML, and real-time AI from one governed dataset. dbt makes the transformation layer portable, encoding business logic in version-controlled models instead of a vendor's metadata store.

Together, they create infrastructure that adapts as fast as AI does — without rebuilding the foundation every time the landscape shifts.