Kasey Uhlenhuth

Agent work is moving beyond a single developer prompting a single model on a laptop. Omnigent provides the capabilities needed for team-scale agent work: portable context across harnesses, reusable agents and tools, session history, policy and quality protocols, async approvals, and mobile and web UI. This deep dive shows how those pieces fit together to make agent work persistent, collaborative, and production-ready. We'll show this in both forms: Omnigent OSS, the open meta-harness you can run anywhere, and Omnigent on Databricks, where the same agents, skills, and policies run on top of the governed Databricks Platform.

Ready to go beyond the basics of Mosaic AI? This session will walk you through how to architect and scale production-grade AI systems on the Databricks Data Intelligence Platform. We’ll cover practical techniques for building end-to-end AI pipelines — from processing structured and unstructured data to applying Mosaic AI tools and functions for model development, deployment and monitoring. You’ll learn how to integrate experiment tracking with MLflow, apply performance tuning and use built-in frameworks to manage the full AI lifecycle. By the end, you’ll be equipped to design, deploy and maintain AI systems that deliver measurable outcomes at enterprise scale.