Visualizing Deep Agents in Long-Horizon Tasks: Towards Explainable and Trustworthy Agentic AI
A general-purpose observability framework that decomposes agent execution into four distinct visualization dimensions: Temporal, Cognitive, Hierarchical, and Spatial is proposed that reduces the Time-to-Insight (TTI) for complex behavioral analysis by 56% and significantly lowers cognitive load (NASA-TLX) compared to state-of-the-art linear traces.