Master n8n AI Agent: The 5 Nodes Explained (Input, Chat Model, Memory, Tool, Output)

Build smarter AI workflows in n8n by mastering the five core nodes inside the AI Agent: Input, Chat Model, Memory, Tool, and Output. This short breaks down what each node does, how they connect, and when to use them to ship reliable, agentic automations. What you’ll learn: Input: Structure user prompts and pass context. Chat Model: Choose and configure the right LLM. Memory: Add conversation or vector memory for context. Tool: Trigger actions—HTTP requests, code, search, DB queries, and more. Output: Format clean, predictable responses for the next step. Perfect for builders automating customer support, data ops, and internal assistants with n8n, OpenAI, or Claude. Keywords: n8n AI Agent node, n8n Input node, Chat Model node, Memory node, Tool node, Output node, AI workflow automation, agentic workflows, autonomous agents, LLM automation, OpenAI, Claude, GPT, prompt engineering, no-code automation, open-source automation, HTTP Request node, function calling, retrieval, vector memory, conversation memory, AI tools in n8n. #n8n #AIAgent #AI #WorkflowAutomation #Automation #NoCode #OpenSource #LLM #OpenAI #Claude #GPT #AIWorkflow #PromptEngineering #Builders