Agents Are All You Need vs. Agents Are Not Enough: A Dueling Perspective on AI’s Future

Author(s): Emil Walleser, DVM, PhD

Originally published on Towards AI.

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The rapid evolution of artificial intelligence (AI) has sparked a compelling debate: Are autonomous agents sufficient to tackle complex tasks, or do they require integration within broader ecosystems to achieve optimal performance? As industry leaders and researchers share insights, the divide between these perspectives has grown more pronounced.

An AI agent is an autonomous program designed to perform tasks on behalf of a user. These agents range from simple systems, such as thermostats that adjust temperature based on sensor input, to advanced applications like virtual assistants scheduling appointments or autonomous vehicles navigating traffic. AI agents distinguish themselves by learning, adapting, and making decisions independently, often using machine learning, natural language processing techniques, and access to outside tools. Their ability to offload repetitive and increasingly complext tasks has made them the hot topic and 2025 being declared “The Year of the AI Agent”.

While the concept of AI agents isn’t new — dating back to symbolic systems in the 1950s and expert systems in the 1980s — recent advancements in large language models (LLMs) have revitalized their potential. LLMs excel at mapping complex dynamics, such as interpreting human… Read the full blog for free on Medium.

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Published via Towards AI