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AI agent loops explained: state, action, and stopping conditions

By PulseAugur Editorial · [1 sources] ·

An agent loop is a fundamental concept in AI agents, describing the cyclical process of decision-making and action execution. This cycle involves an AI model determining an action, the program executing that action, and the results feeding back into the model's context for the next decision. This iterative process continues until a predefined stopping condition is met, differentiating agents from simple chatbots which respond to each input independently. AI

IMPACT Clarifies the core mechanism of AI agents, distinguishing them from chatbots and highlighting the importance of the execution cycle.

RANK_REASON The item explains a core concept in AI agents without announcing a new product or research breakthrough.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI agent loops explained: state, action, and stopping conditions

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The item explains a core concept in AI agents without announcing a new product or research breakthrough.
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High
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Ramón Chancay 👨🏻‍💻 ·

    What an agent loop is (and isn't): state, action, stop

    <p>An agent loop is the cycle in which a language model decides an action, that action runs, and the result feeds back in as context for the next decision, until a stopping condition is met. That repetition—decide, act, observe, repeat—is what separates an agent from a chat. A ch…

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