AI Agent Automation with Think-Plan-Act Architecture Using Llama-4 Reasoning

Overview

This workflow leverages the Think-Plan-Act architecture to build advanced AI agents using Llama-4 reasoning within n8n. It orchestrates multiple OpenRouter Chat Model nodes and structured output parsers to enable complex, multi-step decision-making and task execution.

Key Features

• Integrates Llama-4 via OpenRouter for sophisticated language reasoning
• Utilizes structured and autofixing output parsers for reliable data handling
• Employs webhooks for real-time external triggers
• Modular design with 33 nodes for scalable agent logic

Benefits

• Automates complex reasoning tasks, reducing manual intervention
• Ensures consistent, structured outputs for downstream processes
• Saves time by streamlining multi-step AI-driven workflows
• Enhances reliability with error-handling and output validation

Use Cases

• Automated customer support agents
• Intelligent data processing and analysis
• AI-driven decision support systems
• Workflow automation for content management or analytics

Integrations & Processes

Key integrations include OpenRouter for Llama-4 access and webhook triggers for seamless connectivity. The workflow parses and validates AI outputs, ensuring robust automation and business value.