TL;DR
It is argued that many current approaches to governing agentic systems can be understood as the next generation of stabilizing structures developed to manage increasing coordination complexity.
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.
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.
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.
Autonomous programming agents are commonly evaluated by whether they solve software tasks, providing limited insight into the execution processes that lead to success or failure. We present a process-centric approach to evaluating agent behavior through trajectories. We introduce Graphectory, which captures the structu...
Pera describes a persistent agent organized around perception and control components that continually perceive service-relevant signals from episodic task executions, internal context, and changes in the surrounding environment, and use these signals to construct lifecycle tasks.
This paper argues that architectural choices influence not only the functionality and performance of MAS but can also promote value-oriented system behavior, laying the foundation for a unified set of architectural patterns and guidelines towards the design of trustworthy MAS.
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