University of Chicago: Agentic Systems – A Guide to Transforming Industries with Vertical AI Agents
The content explains agentic systems—industry-specific AI agents powered by large language models—that offer real-time adaptability, domain expertise, and complete workflow automation through components like memory, reasoning engines, and cognitive modules.
University of Chicago: Agentic Systems – A Guide to Transforming Industries with Vertical AI Agents
Summary of Read" class="text-blue-600 hover:text-blue-800" target="_blank" rel="noopener noreferrer">https://arxiv.org/pdf/2501.00881'>Read Full Report
This paper introduces agentic systems, a new generation of AI solutions using Large Language Models (LLMs) to create adaptable, industry-specific software agents. These agents offer advantages over traditional systems by providing domain expertise, real-time adaptability, and end-to-end workflow automation.
The paper details the core components of these agents, including memory, a reasoning engine, cognitive skills modules, and tools, and explores different categories of agentic systems: task-specific, multi-agent, and human-augmented.
Finally, it discusses current industry and academic efforts in building these systems and outlines future research directions.
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