This article argues that building an AI agent involves more than just crafting a detailed prompt. An agent is defined as a runtime process combining a model, a loop, tools, and state, which operates within an external environment. The core challenge for agents is bridging the gap between the model's limited judgment based on current input and the dynamic nature of real-world tasks requiring multi-step progress. True agent functionality emerges when this process is managed by a control system, distinct from the model itself, enabling task advancement through tools, state management, and error recovery. AI
IMPACT Clarifies the fundamental architecture of AI agents, emphasizing their operational runtime and tool integration over prompt engineering alone.
RANK_REASON The article provides an opinionated definition and explanation of AI agents, distinguishing them from simple prompts, without announcing a new product or research finding.
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