AI RESEARCH
A Pattern Language for Resilient Visual Agents
arXiv CS.AI
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ArXi:2604.28001v1 Announce Type: new Integrating multimodal foundation models into enterprise ecosystems presents a fundamental software architecture challenge. Architects must balance competing quality attributes: the high latency and non-determinism of vision language action (VLA) models versus the strict determinism and real-time performance required by enterprise control loops. In this study, we propose an architectural pattern language for visual agents that separates fast, deterministic reflexes from slow, probabilistic supervision.