Trustworthy AI in the Agentic Lakehouse: Reconciling Concurrency and Isolation Contracts

This article addresses the concurrency and isolation problems that arise when multiple AI agents interact with a data lakehouse, focusing on Apache Iceberg's optimistic concurrency control (OCC) for managing multi-agent writes. It details how Iceberg's partition-aware conflict detection allows non-conflicting writes to succeed while handling conflicts through snapshot validation. The article also covers fine-grained access control to restrict agent data access, guardrail policies for autonomous SQL access, and isolation contracts defining what each agent can see. Practical strategies for partitioning and scaling are discussed to minimize conflicts in agentic analytics and pipeline workloads.