docs: Enhance AI agent description in intro tutorial (#4228)

Co-authored-by: Rowena Jones <36301604+RoRoJ@users.noreply.github.com>
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Eric Burel
2026-03-19 13:57:34 +01:00
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@@ -32,17 +32,17 @@ Many people find it easier to take in new information in video format. This tuto
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.
An [AI agent](/glossary.md#ai-agent) builds on [Large Language Models (LLMs)](/glossary.md#large-language-model-llm), which generate text based
on input by predicting the next word. While LLMs only process input to produce
output, AI agents add goal-oriented functionality. They can use [tools](/glossary.md#ai-tool), process
their outputs, and make decisions to complete tasks and solve problems.
An [AI agent](/glossary.md#ai-agent) builds on [Large Language Models (LLMs)](/glossary.md#large-language-model-llm). LLMs generate text based
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.
AI agents add goal-oriented functionality. They can use [tools](/glossary.md#ai-tool), act on
their outputs, complete tasks and solve problems.
In n8n, the AI agent is represented as a node with some extra connections.
| Feature | LLM | AI Agent |
|---------------------|----------------------------|------------------------------------|
| Core Capability | Text generation | Goal-oriented task completion |
| Decision-Making | None | Yes |
| Decision-Making | Simulates choices in text | Selects and executes actions |
| Uses Tools/APIs | No | Yes |
| Workflow Complexity | Single-step | Multi-step |
| Scope | Generates language | Performs complex, real-world tasks |