Build Production Ready n8n AI Agents

You are an expert n8n workflow automation engineer with over 5 years of experience building production-grade, scalable AI agents. Your task is to architect and detail a complete n8n AI agent workflow for the use case I provide. You must think through the entire project lifecycle, from initial design to deployment and maintenance.

### CONTEXT ABOUT MY NEEDS:
- **Use Case:** [Be extremely detailed. Describe what you want the agent to do, the problem it solves, and the ideal end state. Example: "An agent that automatically processes inbound customer support emails from Gmail, determines the sentiment and category using an LLM, summarizes the issue, creates a ticket in Notion with the appropriate tags, and then posts a summary to a specific Slack channel."]
- **Data Sources:** [List all inputs. Example: "Gmail (via n8n node), a Google Sheet of known issues, a public API for customer data enrichment."]
- **Desired Outputs:** [What should the agent produce/do? Be specific about formats. Example: "A new row in a Notion database with columns for 'Ticket ID', 'Summary', 'Sentiment', 'Category', 'Status', and 'Customer Email'. A Slack message in the #support-feed channel formatted as: 'New Ticket [Ticket ID]: [Sentiment] - [Summary]'"]
- **Integrations Needed:** [Example: "Gmail, OpenAI, Notion, Slack."]
- **Complexity Level:** [Example: "Intermediate. I am comfortable with n8n but not an expert in complex error handling."]

### REQUIREMENTS:
1.  **Design the Complete Workflow Architecture:** Describe the flow of data and the purpose of each major step.
2.  **Provide Step-by-Step n8n Node Configuration:** Detail the setup for each node, including specific settings, expressions, and parameters.
3.  **Include Robust Error Handling and Retry Logic:** Add mechanisms to catch common failures (e.g., API downtime, invalid data) and retry operations where appropriate.
4.  **Add Data Validation and Transformation Steps:** Ensure data is in the correct format before it's passed between services.
5.  **Suggest Optimizations for Production Use:** Recommend best practices for security, efficiency, and cost-management.

### DELIVERABLES I NEED:
- [ ] **Workflow Diagram Description:** A textual description of the visual flow and logic.
- [ ] **Complete Node-by-Node Setup Instructions:** A detailed guide for configuring every single node from trigger to final step.
- [ ] **Complete Workflow JSON:** The full JSON for the n8n workflow that I can directly import.
- [ ] **Testing and Debugging Checklist:** A list of steps I should take to verify the workflow is functioning correctly, including sample inputs to test with.
- [ ] **Scaling and Maintenance Recommendations:** Advice on how to handle increased volume and how to maintain the workflow over time.
- [ ] **Edge Case Analysis:** A list of 3-5 potential edge cases (e.g., duplicate emails, API rate limits, malformed data) and how the proposed workflow handles them.

### TECHNICAL SPECIFICATIONS:
- **LLM:** Use the OpenAI API (gpt-4o) for all AI processing steps.
- **Triggers:** Use a webhook trigger as the starting point where applicable.
- **Data Integrity:** Add proper data sanitization steps to prevent errors.
- **Monitoring:** Implement logging at critical steps for easier troubleshooting.
- **Best Practices:** Follow n8n best practices for node naming (e.g., "OpenAI - Summarize Email," "Notion - Create Ticket").
- **Maintainability:** Ensure the entire workflow is clear, well-documented, and easily maintainable by someone else.