Managing the Agent Lifecycle at Scale
As enterprises shift from AI experimentation to production deployment, managing AI agent lifecycles at scale has become a key challenge. Unlike traditional software, AI agents are nondeterministic, context-driven, and continuously evolving. This shift requires reimagining the software development lifecycle as an Agent Development Lifecycle (ADLC).
This talk explores how organizations can design, build, deploy, and operate AI agents reliably at scale. We will walk through the end-to-end lifecycle, from design and development to deployment and operations, highlighting the core capabilities required to take agents to production. These include evaluation-driven development (EDD) as a foundational engineering practice, deep observability and feedback loops for continuous improvement, guardrails and runtime controls to ensure safe and predictable behavior, and platform thinking, treating agent management as a unified control plane for the enterprise.
Speakers
Malith Jayasinghe is VP of AI at WSO2, where he leads initiatives to build scalable, secure, and production-ready AI systems for the enterprise. With over 15 years of experience in building, scaling, and optimizing complex systems, he focuses on making AI production-ready and improving developer productivity. His work spans AI strategy, agent platforms, observability, evaluation, governance, security, and enterprise integration. An architect, product leader, and frequent speaker at events such as DeveloperWeek, the Global Big Data Conference, and DEV DAY, Malith shares insights on enterprise AI, software architecture, and emerging technology trends. He holds a PhD in Computer Science from RMIT University, Australia, and has published in respected academic venues including IEEE Transactions on Parallel and Distributed Systems (TPDS) and the Journal of Parallel and Distributed Computing (JPDC).