Building Scalable Agentic Systems for Science: Concepts, Architectures, and Hands-On with Academy

Agentic systems, in which autonomous agents collaborate to solve complex problems, are emerging as a transformative methodology in AI. However, adapting agentic architectures to scientific cyberinfrastructure—spanning HPC systems, experimental facilities, and federated data repositories—introduces new technical challenges. In this half-day tutorial, we introduce participants to the design, deployment, and management of scalable agentic systems for scientific discovery. We will present Academy, a Python-based middleware platform built to support agentic workflows across heterogeneous research environments. Participants will learn core agentic system concepts, including asynchronous execution models, stateful agent orchestration, and dynamic resource management. A guided hands-on session will help attendees build and launch their own agentic workflows. We will present case studies in materials discovery, biology, and chemistry. This tutorial is designed for researchers, developers, and cyberinfrastructure professionals interested in advancing AI-driven science with next-generation autonomous systems.