Inside the Agent Loop: Building Reliable Enterprise AI Agents
AI agents can interpret goals, use tools, observe results, and adapt their approach over multiple steps. But while the model provides the underlying intelligence, the agent loop determines how that intelligence is applied. It controls how context is assembled, tools are selected, results are fed back, state is maintained, and execution continues or stops.
In this hands-on lab, participants will explore agent loop engineering and the practical design decisions behind reliable enterprise AI agents:
- How the agent loop and harness connect instructions, context, tools, memory, and observations
- Why context and tool design often matter more than choosing a more powerful model
- How memory and state support complex, multi-step execution
- How planning, stopping conditions, retries, and self-correction affect agent behavior
- How traces and evaluations uncover failures and guide improvements
- When to use a deterministic workflow, a single-agent loop, or a multi-agent system
By the end of the lab, participants will understand how agent loop engineering separates a promising demo from a reliable enterprise AI agent. They will leave with practical patterns for designing, evaluating, and improving agents without introducing unnecessary complexity.
Speakers
Ramith Jayasinghe is a Senior Enterprise Architect at WSO2, blending over 16 years of expertise in integration, API management, and application development with strategic solution engineering leadership. He guides organizations in delivering complex technical initiatives - from architecting robust, agent-ready platforms to accelerating AI adoption with WSO2 technology.
Nadheesh Jihan is a Senior Technical Lead and AI leader at WSO2, with nearly a decade of experience in machine learning, deep learning, generative AI, and agentic systems. His expertise covers building practical AI agents and securing, governing, and managing them for enterprise use. He played a core leadership role in shaping WSO2's Agent Manager platform and now helps shape AI strategy and lead key initiatives as part of the Corporate AI team. His work focuses on applying AI to enterprise platforms while leveraging those platforms to enable scalable, production-grade AI systems.