Lakehouse transactional analytical processing is useful only when teams define freshness, isolation, and workload boundaries clearly.
Enterprise AI advantage increasingly comes from governed context, semantic models, and operational data contracts, not only from model choice.
Python-first Iceberg work is useful when it stays honest about what Python should and should not do.
The real-time lakehouse is not one engine. It is a contract between streams, table commits, query paths, and freshness expectations.
