AI Automation Using n8n for Non-Technical Beginners

In today’s workplace, automation and AI agents are no longer limited to technical teams. With the rise of no-code platforms like n8n Cloud, everyday professionals can now design automated workflows that save time, reduce errors, and improve consistency—without writing a single line of code.

This 2-day practical course builds on the foundation from Generative AI for Daily Work Optimization and takes participants one step further: from prompting an AI model to orchestrating entire workflows that run on their own.

Through hands-on projects and guided exercises, learners will explore how AI agents act as the “thinking” part of an automation—connecting data, tools, and decisions into one seamless process. By the end of the program, participants will not only understand how automation works but will also be able to create, test, and deploy their own simple AI-powered workflows for everyday business tasks.

Upon completing the course, participants should be able to:

• Understand how AI agents fit into workflow automation and map how data, actions, and AI interact in a process.
• Navigate the n8n Cloud platform, connect basic applications, and use community templates to build simple automations.
• Use AI tools such as ChatGPT or Claude to troubleshoot, improve, and debug workflows through natural language.
• Design, test, and refine a complete workflow that automates a real work task using AI-driven components.
• Explain how the main parts of an AI agent—planning, memory, perception, and tools—work together to make smarter decisions.
• Build multi-step workflows that include fallback and escalation paths for smoother, more reliable automation.
• Create a simple RAG-based AI agent that retrieves accurate information from uploaded documents for real-world queries.
• Combine all learned techniques to design and present a working AI agent that automates a real business process responsibly and effectively.

• Executives and team leaders looking to improve efficiency and coordination across teams.
• Operations and administrative professionals who manage reports, schedules, or information flow across departments.
• Customer service or sales staff who want to automate responses, summaries, or follow-ups using AI-driven tools.
• Analysts and content creators who regularly process, summarise, or distribute information.

Participants are expected to have completed the “Generative AI for Daily Work Optimisation” programme or are comfortable with basic AI concepts such as prompting and basic Google Workspace tools. Each participant must come with the following accounts ready:

• Google account (Gmail, Google Sheets, Google Drive)
• ChatGPT account (free or Plus)
• Claude account (free or Pro)
• Telegram account

Note: An additional USD 2 per pax will be charged separately to cover OpenAI tokens and Google Cloud API usage.

Module 1: From Prompts to Workflows — Understanding AI Agents in Action

• Revisit the fundamentals of Generative AI and connect prompting concepts to real-world task automation.
• Explain the relationship between workflow automation and AI agents, highlighting how agents act as intelligent components within a larger process.
• Introduce the key elements of an AI Agent – Planning, Memory, Perception, and Tools – and explain their practical roles in workflow execution.
• Compare examples of traditional automation (rule-based tasks) versus AI-driven automation (context-aware responses).
• Discuss how combining structured workflows with AI reasoning improves accuracy, efficiency, and adaptability.
• Create a visual workflow chart illustrating how data, actions, and AI agents interact to complete a typical business process.

Module 2: Getting Started with n8n Cloud — Your No-Code Automation Canvas

• Walk through the n8n Cloud interface, including nodes, triggers, branching logic, the executions panel, and workflow templates.
• Demonstrate how to connect commonly used applications (e.g., Gmail, Google Sheets, Telegram) to form the building blocks of an automation.
• Explain the difference between triggers, actions, and data transformation nodes, and how they interact within a workflow.
• Explore the n8n community library and learn how to import pre-built workflow templates as starting points for customization.
• Introduce workflow versioning, execution logs, and basic troubleshooting using n8n’s built-in tools.
• Outline best practices for managing credentials, API keys, and usage limits when connecting AI or external services.

Module 3: Vibe Coding Techniques — Let AI Help You Debug and Build

• Introduce the concept of “Vibe Coding” as a technique for using LLMs to assist in workflow design, troubleshooting, and customization.
• Demonstrate how to consult AI tools such as ChatGPT or Claude to generate step-by-step setup instructions or resolve workflow errors.
• Learn to export workflows as JSON files and share them with LLMs for structural review, logic optimization, or debugging support.
• Show how to describe workflow logic in natural language and convert it into n8n-compatible expressions or function nodes using LLM guidance.
• Explain how to identify, isolate, and fix node-level errors through AI-assisted reasoning instead of manual debugging.
• Apply Vibe Coding to enhance an existing automation

Module 4: Mini Capstone #1 – Designing Your First Smart Workflow

• Consolidate the concepts learned in previous modules by designing a complete end-to-end workflow in n8n Cloud.
• Use community templates as a foundation and modify node configurations to suit the selected scenario.
• Incorporate AI nodes to enhance message generation, summarization, or tone adaptation based on user preferences.
• Apply Vibe Coding techniques to refine prompt quality, message formatting, and logic accuracy.
• Run, test, and optimize the workflow execution, verifying that each node performs as intended and data flows correctly across steps.
• Present the final version of the workflow for peer review and discussion of improvement opportunities.

Module 5: Inside the AI Agent — How Memory, Reasoning & Tools Work Together

• Learn how an AI Agent “thinks” and acts within a workflow by understanding its four main parts – Planning, Memory, Perception, and Tools.
• See how memory helps an AI Agent remember past messages or data, allowing it to give more consistent and relevant answers.
• Understand how reasoning allows the agent to decide what action to take next instead of just replying to one question at a time.
• Discover how perception helps the agent read and interpret information from text, files, or forms before responding.
• Explore how tools connect the agent to useful apps and systems such as search engines, Google Sheets, or chat platforms.
• Observe how these elements come together inside n8n Cloud, where each node represents one part of the agent’s thinking or action.

Module 6: Building Multi-Step Automations with Fallback & Escalation

• Learn how to combine multiple steps in a single workflow so that different actions happen automatically in sequence.
• Understand how to plan automation flows that can handle unexpected situations—such as missing data, failed responses, or unclear inputs.
• Explore how to create fallback paths, where the workflow can send a backup message, perform a simple retry, or use a different data source when something goes wrong.
• Set up escalation routes that notify a team member or send a request to a human when the AI Agent cannot give a confident answer.
• Learn how to use decision nodes like IF, Switch, or Error Trigger to make workflows more flexible and reliable.
• Practise adding checks and balances so your automation continues running smoothly without human supervision.

Module 7: Adding Knowledge — Building a Simple RAG Agent for Internal FAQs

• Learn how to give your AI Agent access to useful reference materials, such as company FAQs or policy documents.
• Understand the idea behind Retrieval-Augmented Generation (RAG) — how it helps the agent find and quote real information instead of guessing.
• Explore how to prepare and upload documents from cloud storage (e.g., Google Drive) for the agent to use as a knowledge source.
• Build a simple FAQ Agent that can answer questions based on stored documents and provide accurate, cited responses.
• Practise connecting your RAG setup to a chat platform such as Telegram to allow easy team interaction.
• Test how your Agent retrieves answers, handles missing information, and gracefully responds when data is unavailable.

Module 8: Final Capstone – Your Personal AI Agent in Action

• Combine workflow automation, Vibe Coding, and RAG techniques to create an agent that can retrieve, respond, and escalate when needed.
• Review best practices for maintaining reliable automations
• Discuss common pitfalls such as over-reliance on AI output, missing fallback logic, or poor credential management, and learn how to avoid them.
• Reflect on the role of AI automation as a tool to extend human capability, not replace it
• Practical tips for continuous improvement