Agents that build their own databases are forcing a data foundation rethink
AI agents are changing how enterprises create, move and govern information, and data observability is turning into a prerequisite rather than a nice-to-have. Models get most of the attention, but the data beneath them decides whether they hold up in production. That pressure is now reaching the cloud-native community, where KubeCon organizers added a dedicated […] The post Agents that build their…
The rise of AI agents is reshaping the way enterprises handle information creation, movement, and governance. While models have taken center stage, the data that supports them is proving to be just as critical. At KubeCon + CloudNativeCon NA, Sanjeev Mohan, principal at SanjMo and author of "Designing the AI-Driven Data Foundations," emphasized that AI success hinges on a robust foundation.
Mohan explained that unlike traditional data pipelines, which moved data from operational systems for batch processing, AI agents now require direct access to databases. This shift has led to a new generation of databases that can spin up, copy data, and test various decision-making paths before settling on an action. As agents perform tasks like evaluating loan applications by querying multiple sources, the need for robust governance and data observability becomes paramount.
Mohan's book, published in June 2026, delves into how AI agents are redefining traditional architectural principles, pushing for a new era of converged systems that handle both structured and unstructured data.
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