Phoenix U Majumder

Traditional “data-to-compute” models create latency and fragmented governance that hinder Agentic AI. To solve this, Workday and Databricks advocate “bringing agents to data” via the Databricks Lakehouse. By operating on data in situ, autonomous agents maintain real-time consistency without the risks of replication. This architecture enables reliable multi-agent coordination at scale while ensuring unified data integrity and reduced operational costs across the enterprise. The technical core uses Apache Iceberg for ACID transactions and snapshot isolation, providing a stable foundation for agent reasoning. Databricks Unity Catalog adds a unified governance layer, enforcing fine-grained security, lineage, and auditability. This production-grade approach significantly cuts query latency and storage expenses, allowing organizations to scale from single-agent pilots to hundreds of coordinated agents across multiple departments like Customer Experience, RevOps and Analytics.

The traditional blueprint for building applications is more than 20 years old and optimized for a fragmented, ETL-heavy architectures of the early cloud era. The rise of agentic AI has broken this model, forcing us to reimagine how we — or perhaps agents — will build applications for the next 20 years. Today's AI native applications are increasingly written by agents, require easy access to real-time context and AI generated insights from other agents that legacy cloud platforms cannot provide without an expensive "Architectural Tax." Join Akhil Gupta and engineering leaders from the leading tech companies as they discuss the shift from legacy stacks to an interoperable foundation. We’ll explore the "Lakebase" paradigm, where Lakebase, Databricks Apps and Agent Bricks provide the modern way to build AI-native applications. This session will move beyond the "vibe check," offering a candid look at how to eliminate silos and ship governed, production-grade AI applications at scale. Key topics include: - Identifying and eliminating the "Architectural Tax" imposed by legacy cloud silos. - Understanding why AI-native applications require an interoperable app foundation: Lakebase. - How…