Course Outline
Day 1: Workflows and AI Integration
Introduction
- Distinguishing when to automate, use AI steps, or deploy full agents
- n8n in context: understanding the implications of cloud vs. self-hosted environments for company data
n8n Fundamentals
- Key concepts: workflows, nodes, triggers, and executions
- Transferring data between nodes via field mapping without writing syntax
- Diagnosing issues by reading execution logs
Integrating Applications and Data
- Setting up webhooks and form triggers
- Utilizing spreadsheet, email, and calendar nodes
- Managing credentials and authentication for external services
- A step-by-step guide to the HTTP Request node
Implementing AI Steps
- Incorporating AI models into your workflow
- Crafting prompts to ensure reliable outputs
- Handling structured output and automatically correcting malformed responses
- Classifying and extracting insights from emails, forms, and documents
Logic and Actions
- Implementing logic with If and Switch branches
- Designing approval steps that require human intervention before actions are taken
- Recording results in spreadsheets and triggering notifications
Hands-on Lab: Building Your First End-to-End Workflow
- Transforming an incoming request into a classified, recorded, and routed outcome
Day 2: Agents and Operational Excellence
Understanding Agents
- Core components of an agent: model, memory, and tools
- Choosing between fixed workflows and dynamic agents
- Granting agents access to internal documents and spreadsheets
Action-Oriented Agents
- Differentiating between read-only and write-access tools
- Defining system prompt rules: enforcing required fields, preventing data fabrication, and avoiding duplicates
- Testing agent robustness by attempting to break its logic
Communication Channels
- Setting up chat interfaces for internal use
- Connecting agents to specific messaging platforms
Ensuring Reliability
- Configuring error workflows, retries, and alerts
- Analyzing logs and execution history
- Optimizing model usage and execution costs
Data Privacy and Security
- Understanding what data is transmitted when external models are invoked
- Exploring self-hosting and local models through instructor demonstrations
- Reviewing a privacy checklist with IT or legal teams
Leveraging AI in Workflow Design
- Using AI assistants to draft initial workflow structures
- Reviewing AI-generated logic: verifying node functions, data sources, and empty-state handling
Final Project and Future Steps
- Participants finalize and present a personalized workflow featuring AI steps and an agent applied to their own process
- Developing a maintenance plan and identifying future automation opportunities
Deliverable: A fully functional workflow that includes AI integration, an agent connected to internal data, comprehensive error handling, and a completed review checklist.
Requirements
- No prior programming experience is necessary
- Proficiency in using web applications and spreadsheets
- A clear understanding of one repetitive task within your current workflow
Target Audience
- Professionals in business, operations, and customer-facing roles
- Team leaders and process owners
- Non-technical staff aiming to develop automations and AI agents leveraging internal company data
Testimonials (3)
The trainer is patient and very helpful. He knows the topic well.
CLIFFORD TABARES - Universal Leaf Philippines, Inc.
Course - Agentic AI for Business Automation: Use Cases & Integration
Good mixvof knowledge and practice
Ion Mironescu - Facultatea S.A.I.A.P.M.
Course - Agentic AI for Enterprise Applications
The mix of theory and practice and of high level and low level perspectives
