AI Agents vs. Agentic AI
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The curator’s take
This review paper distinguishes AI Agents from Agentic AI, presenting a structured taxonomy and comparing their architectures, capabilities, and challenges. AI Agents are defined as modular, task-specific systems powered by LLMs and tools, while Agentic AI represents a shift toward multi-agent collaboration, dynamic task decomposition, and orchestrated autonomy, with applications and challenges mapped out for both paradigms, along with proposed solutions like RAG, orchestration layers, and causal modeling.
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