The data still runs the business, but it can't easily be trusted, reused, or reasoned over consistently by modern software and AI. What they lack is a way to work with it at scale. It runs the core business process of more than 90% of Fortune 500 companies. Yet while the data is reliable by design, its business meaning is often implicit and difficult for AI systems to interpret, which prevents AI from reasoning over it reliably, safely, and at scale. It also means we value people who challenge assumptions, point out flaws, and help us avoid building the wrong thing — not just those who execute instructions. This involves defining and owning the fundamental platform elements, including how business meaning is represented, versioned, governed, and exposed, ensuring that enterprise data and business logic can be reliably utilized by software and AI.
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