Aug 2026· The AI Magazine· Vol 47· 0 citations· 25 references
TL;DR
It is argued that design for safe and effective teamwork must consider how human and software roles together manage, change, and coordinate their collective configuration over time to respond to changing work demands.
Abstract
This paper discusses the perspective that managing the configuration of a network of human and software agents is a form of distributed work that should be explicitly considered when designing human‐agent systems. We describe a configuration of human and software agents as the organization of their roles and relationships that shape and constrain their joint activity while responding to a dynamic flow of events. The paper argues that design for safe and effective teamwork must consider how human and software roles together manage, change, and coordinate their collective configuration over time to respond to changing work demands. We illustrate this form of distributed work at multiple layers of abstraction of a human‐agent system, describing how maintaining goal alignment, tracking and managing interdependencies, synchronizing multi‐threaded activities, and managing the structural topology all involve deliberate and continuous effort. In the second half of the paper, we connect these ideas to modeling approaches for supporting conceptual design of human‐agent systems. The paper discusses how functional modeling of work can help designers first envision the coordinative structures necessary for adaptation before specifying the technical details of how individual tasks are executed (a whole‐to‐parts and coordination‐first approach). We illustrate a specific modeling framework, currently under development, that aims to facilitate the envisioning of the work of configuration management and help designers identify competencies and coordinative structures to support it. We provide an initial discussion of a three‐phase “bootstrapping” approach for using this framework in human‐agent system design. This paper contributes a new direction for explicitly modeling and designing for reconfiguration in human‐agent systems. Future work is needed to further develop the tooling and techniques, evaluate and validate their ability to inform human‐agent system design, and ultimately create more resilient human‐agent systems.
Agents are increasingly considered first-class participants in the software development lifecycle. However, architectural choices that govern the collaboration of agents are fixed inside the frameworks that implement multi-agent systems, leading to difficulty of measuring the individual contribution of these architectu...
Konsta Kalliokoski, François Christophe, Henri Kärkkäinen et al.· Proceedings of the ACM/IEEE...· 0 citations
This paper contrasts Coordination‐First architectures that explicitly address the competencies and constraints of coordinated joint activity across multiple roles and layers with the current Coordination‐Last paradigm that focuses primarily on deploy‐fast‐and‐fix‐later strategies.
David L. Alderson, David D. Woods· The AI Magazine· 0 citations
Agentic system design is increasingly shifting from hand-crafted prompts and workflows toward automated search over agentic programs and interaction structures, with multi-agent systems receiving growing attention. Yet a central question remains unresolved: when does an automatically generated multi-agent structure exh...
Shao-Jun Xia, Yun-Er Zhang, Hui-Xin Zhang et al.· 0 citations
This work contributes a typology of eight incongruence modes as a vocabulary for the structural breakdowns that human-agent collectives produce, specifying a generative model of human-agent collectives and using Monte Carlo simulation to parameterize it.
J. Oppenlaender, Aku Visuri, S. Hosio· Proceedings of the 2026 ACM...· 0 citations
A unified, taxonomy-driven, and deployment-oriented survey of agentic AI systems, synthesizing recent advances through a modular reference architecture and a four-dimensional taxonomy that characterizes agents along the axes of autonomy, tool use, collaboration, and safety–governance is presented.
Sparsh Bajoria, Shreyanshu Ranjan, Adhitya M et al.· Cognitive Computation· 1 citation
This work introduces a unified formalism for proactive robot assistance, organize it into three levels, and provides a framework to address the highest level of unprompted proactive assistance, and presents a method, GAP, that instantiates the framework, learning from passive observation to anticipate user goals and ac...
Maithili Patel, Sonia Chernova· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.