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docs: Enhance AI agent description in intro tutorial (#4228)
Co-authored-by: Rowena Jones <36301604+RoRoJ@users.noreply.github.com>
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@@ -32,17 +32,17 @@ Many people find it easier to take in new information in video format. This tuto
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If you're already familiar with AI, feel free to skip this section. This is a basic introduction to AI concepts and how they can be used in n8n workflows.
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An [AI agent](/glossary.md#ai-agent) builds on [Large Language Models (LLMs)](/glossary.md#large-language-model-llm), which generate text based
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on input by predicting the next word. While LLMs only process input to produce
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output, AI agents add goal-oriented functionality. They can use [tools](/glossary.md#ai-tool), process
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their outputs, and make decisions to complete tasks and solve problems.
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An [AI agent](/glossary.md#ai-agent) builds on [Large Language Models (LLMs)](/glossary.md#large-language-model-llm). LLMs generate text based
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on input by predicting the next word. They can be used to select the best tool to achieve a task, or even simulate complex decision-making, but they can't act on decisions or use tools themselves.
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AI agents add goal-oriented functionality. They can use [tools](/glossary.md#ai-tool), act on
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their outputs, complete tasks and solve problems.
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In n8n, the AI agent is represented as a node with some extra connections.
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| Feature | LLM | AI Agent |
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|---------------------|----------------------------|------------------------------------|
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| Core Capability | Text generation | Goal-oriented task completion |
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| Decision-Making | None | Yes |
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| Decision-Making | Simulates choices in text | Selects and executes actions |
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| Uses Tools/APIs | No | Yes |
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| Workflow Complexity | Single-step | Multi-step |
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| Scope | Generates language | Performs complex, real-world tasks |
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