If you want to learn:
- How do I create a two-way Telegram bot integration using n8n?
- What's the best way to send AI agent responses back to Telegram users?
- How do I use expressions and dynamic data in n8n workflows?
- How can I add memory to my Telegram chatbot so it remembers conversations?
- What's the difference between testing and publishing an n8n workflow to production?
- How do I configure webhook triggers and automate Telegram message responses?
Then this lecture is for you!
This lecture teaches you how to build a complete two-way Telegram integration with n8n workflow automation. You'll learn to configure a Telegram bot that receives messages via webhook triggers, processes them through an AI agent, and sends intelligent responses back to users. The tutorial covers essential n8n concepts including working with expressions using JSON data, dynamically mapping ChatID fields to ensure responses reach the correct users, and implementing Simple Memory with session keys so your chatbot remembers conversation context. You'll discover how to use the drag-and-drop interface to connect data between nodes, access data from the Telegram trigger node, and pass AI agent output back through the Telegram node. The lecture demonstrates integrating AI tools like current date functions, testing workflows with the Execute Workflow button, and finally publishing your automation to production so it runs continuously without manual intervention. By the end, you'll have deployed a live Telegram bot that can interact with users, call external tools, maintain conversation memory using ChatID or username as session identifiers, and operate as a fully automated workflow in your n8n instance.