A Decoupled Human-in-the-Loop System for Controlled Autonomy in Agentic Workflows
For developers of multi-agent systems, this work addresses the need for reusable and scalable human oversight mechanisms, but it is incremental as it applies known HITL concepts to a new architectural context.
The paper proposes a decoupled Human-in-the-Loop (HITL) system architecture that separates human oversight from application logic, enabling scalable and consistent governance in multi-agent workflows. It introduces a design framework for formalizing HITL integration across four dimensions.
AI agents are increasingly deployed to execute tasks and make decisions within agentic workflows, introducing new requirements for safe and controlled autonomy. Prior work has established the importance of human oversight for ensuring transparency, accountability, and trustworthiness in such systems. However, existing implementations of Human-in-the-Loop (HITL) mechanisms are typically embedded within application logic, limiting reuse, consistency, and scalability across multi-agent environments. This paper presents a decoupled HITL system architecture that treats human oversight as an independent system component within the agent operating environment. The proposed design separates human interaction management from application workflows through explicit interfaces and a structured execution model. In addition, a design framework is introduced to formalize HITL integration along four dimensions: intervention conditions, role resolution, interaction semantics, and communication channel. This framework enables selective and context-aware human involvement while maintaining system-level consistency. The approach supports alignment with emerging agent communication protocols, allowing HITL to be implemented as a protocol-level concern. By externalizing HITL and structuring its integration, the system provides a foundation for scalable governance and progressive autonomy in agentic workflows.