The agentic era is forcing a reset in enterprise architecture. Agents taking action go far beyond just analyzing data living in lakehouses. Agents acting on behalf of humans, continuously, at machine scale bring new architectural requirements to the enterprise. The so-called “modern data stack” as most organizations know it, has become a sort of “new legacy.” No longer can organizations rely on stitched-together systems, fragmented governance, batch pipelines, and historical security boundaries. As we move from human-scale dashboards to agent-scale execution, fragmentation becomes an operational and compliance risk. This is where we believe Google has an underappreciated advantage. Our research indicates the winning architectures in the agentic era will be the ones that operate as a coherent, end-to-end system — where the model, the cognitive engine, and the infrastructure are tightly integrated and share a single trusted boundary, consistent security controls, and an efficient cost structure that can generate tokens in volume but doesn’t collapse under thousands of agent interactions per minute. This is the premise behind our Google thesis. We believe Google is in a strong position to build on decades of infrastructure and data excellence and push toward an AI powered cloud that goes beyond a reactive system of intelligence to one that takes action at scale. Essentially we see Google as one of the companies best positioned to execute on our vision of delivering a real-time digital representation of an enterprise. One that blends the power of generative AI with trusted and consistent determinism to deliver real time actions that leverage both structured and unstructured and can execute transactions as scale.