At Databricks Data + AI Summit this week, Satya Nadella talked about something he called the system of context. Human capital and token capital compounding together. You can’t outsource the learning, he said. Passive knowledge doesn’t build anything. That line stayed with me because it gets at something the infrastructure announcements earlier in the week don’t fully address. The stack finally caught up. One platform, unified governance, agents built in from the start represe

Collecting customer data, governing how it moves, enriching it, and making it available in real time for experimentation and personalization has always meant assembling the pieces yourself. A collection engine. A governance layer. A real-time API. A historical store. A consumption platform. Each from different vendors, integrated by hand. I’ve worked inside that complexity. I know what it takes to make it work and what breaks when the seams give. At Databricks Data + AI Summi

AI initiatives often fail for the same reason: the data foundation isn’t ready. Teams move ahead with model development before addressing data quality, governance, or ownership, making it difficult to scale or even deliver reliably. In a recent conversation with leaders at a fintech building ML-based fraud detection, the use cases were clear and the signals were mapped. But during integration, most of those signals turned out to come from legacy pipelines. The data wasn’t com