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Metric Views: fuel agents with semantics

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About This Event

In the era of AI-driven automation, the push to be "data-driven" often fails because of a very human problem: we aren't speaking the same language. This semantic drift happens when different teams — and now, their AI agents — interpret the same information in conflicting ways. Without a unified semantic layer, a single KPI, like "Average Revenue Per User" (ARPU), can be interpreted in conflicting ways; a business user might calculate it based on active monthly subscriptions, while an AI agent might interpret it across all registered accounts.