Source: https://arxiv.org/abs/2510.09244
Overview of the paradigm shift from traditionalĀ Large Language Models (LLMs)Ā toĀ Agentic LLMs, defining the latter as autonomous, goal-oriented systems designed to overcome the limitations of passive, stateless LLMs.
It details theĀ agentic architecture, which is based on four integrated componentsāPerception, Reasoning, Memory, and Executionāthat allow the AI to interact with and act upon the external world.
The text contrasts the reactive nature of traditional LLMs with the proactive, problem-solving capabilities of agents, exploring practical applications across sectors like healthcare, finance, and robotics.
Finally, the report addresses the significantĀ technical and ethical challenges, such as state desynchronization and accountability, and outlines future trends, including the move toward multi-agent systems and smaller, specialized models.