- Functional requirements that focus on what the agent will do and where humans-in-the-middle will provide oversight.
- A set of nonfunctional requirements focusing on areas of performance, compliance, security, observability, and other operational requirements, just as they would for APIs and automations.
- Another set of nonfunctional requirements focusing on data, including data quality, governance, bias, and AI model maintenance.
Nonfunctional requirements for AI agents can be like those for applications, where user stories are granular and target delivering small, atomic functions. These NFRs can guide developers in answering how to develop the functionality described in user stories and to help quantify what should pass a code review.
However, you may need another set of NFRs expressed at a feature or release level. These NFRs help qualify an AI agent’s release readiness, specify data and AI governance requirements, and define other devops non-negotiables.
“For teams working with agentic AI, it’s essential to differentiate which nonfunctional requirements are best enforced by machines, like security, compliance, and scalability, and which still demand human judgment, such as UX, aesthetics, and performance that feels fast,” says Jonathan Zaleski, director of technical architecture at HappyFunCorp. “The future of AI product development lies in hybrid workflows, where AI handles objective, measurable criteria at scale, and humans focus on the emergent, intuitive aspects that shape truly meaningful experiences.”
