As a product VP at Google Cloud, Michael Gerstenhaber works mostly on Vertex, the company’s unified platform for deploying enterprise AI. It gives him a high-level view of how companies are actually using AI models, and what still needs to be done to unleash the potential of agentic AI.
When I spoke with Michael, I was particularly struck by one idea I hadn’t heard before. As he put it, AI models are pushing against three frontiers at once: raw intelligence, response time, and a third quality that has less to do with raw capability than with cost — whether a model can be deployed cheaply enough to run at massive, unpredictable scale. It’s a new way of thinking about model capabilities, and a particularly valuable one for anyone trying to push frontier models in a new direction.
This interview has been edited for length and clarity.
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