Turing Winner Stonebraker: Why LLMs Won't Replace Relational Databases & AI Agent Pitfalls
In an 80-minute interview, Turing Award winner Mike Stonebraker argues that relational databases will absorb AI workloads, explains why Text-to-SQL fails on real enterprise data due to schema corruption and access controls, details DBOS's persistent workflow approach for AI agents, and discusses saga patterns for compensating transactions, graph database limitations, and the future of open-source AI.
