The Agent Development Life Cycle: A Framework for Designing Agents That Work

This IDC Market Note discusses how the agent development life cycle (ADLC) provides a structured framework for moving AI agents from experimentation to production, emphasizing explicit design decisions across seven dimensions: work definition, role, data and context, memory, tools and actions, handoffs and failure paths, and evaluation. ADLC applies to both custom and commercial agents, ensuring agents deliver accurate, governed, and traceable outcomes. Teams that rigorously define these dimensions will deploy agents that are useful, safe, and measurable, while those that skip these steps risk unreliable systems. ADLC is essential for operationalizing agentic AI in enterprise environments