Episode 23 of the Boss and Bosses podcast with John Binks digs into a seismic shift in data teams driven by modern AI: moving from static warehouses to AI-ready, temporal, real-time data streams that are dynamic, high-frequency, time-sensitive, and continuously updated.

Key takeaways include why temporal data matters for prediction, the urgent need to detect concept drift, design sequence-aware pipelines and event-driven architectures, and adopt reliability-first engineering with data contracts and continuous observability—while retaining SQL as the common language.

Leaders should prioritize temporal data capability, retrain and hire for systems thinking, reinforce SQL fluency, and invest in production-grade, observable pipelines to turn data into a continuously powered competitive advantage.