Course Outline
Day 1: Workflows and AI Integration
Introduction
- Determining when to use automation, AI steps, or autonomous agents
- Understanding n8n in context: cloud vs. self-hosted deployment and its impact on data control
Core n8n Concepts
- Understanding workflows, nodes, triggers, and execution cycles
- Transferring data between nodes using drag-and-drop functionality, eliminating the need for syntax entry
- Interpreting execution logs to identify and resolve issues
App and Data Integration
- Utilizing webhooks and form-based triggers
- Working with nodes for spreadsheets, email, and calendars
- Managing credentials and authentication for external services
- Step-by-step guidance on using the HTTP Request node
Implementing AI Steps
- Integrating AI models into existing workflows
- Crafting prompts for consistent and reliable outputs
- Managing structured outputs and automatically correcting malformed responses
- Classifying and extracting data from emails, forms, and documents
Decision Logic and Actions
- Implementing branching logic using If and Switch nodes
- Incorporating human approval steps before executing actions
- Recording results in spreadsheets and distributing notifications
Practical Lab: First End-to-End Workflow
- Building a complete flow from incoming request to a classified, recorded, and routed outcome
Day 2: Agents and Operational Management
Understanding Agents
- Components of an agent: model, memory, and tools
- Choosing between fixed workflows and autonomous agents
- Granting agents access to internal documents and spreadsheets
Agents in Action
- Distinguishing between read-only and write-capable tools
- Defining system prompt rules: required fields, preventing hallucinated data, and avoiding duplicates
- Stress-testing agents to ensure robustness
Communication Channels
- Setting up a chat interface for internal use
- Connecting agents to specific messaging platforms
Ensuring Reliability
- Implementing error workflows, retry mechanisms, and alert systems
- Utilizing logs and execution history for tracking
- Managing costs associated with model usage and executions
Data Privacy and Security
- Understanding what data is shared when external models are invoked
- Exploring self-hosting and local models through live demonstrations
- Reviewing a compliance checklist with IT and legal teams
AI-Assisted Workflow Development
- Using AI assistants to draft initial workflow structures
- Reviewing drafts: analyzing node functions, data sources, and empty-state handling
Final Project and Future Steps
- Participants will complete and present a workflow featuring an AI step and an agent tailored to their specific process
- Developing a maintenance plan and identifying future automation opportunities
Deliverables: A functional workflow with an integrated AI step, a data-connected agent, error handling, and a comprehensive review checklist.
Requirements
- No prior programming experience is necessary
- Familiarity with web applications and spreadsheet software
- A clear identification of at least one repetitive process in their current workflow
Target Audience
- Professionals in business operations, customer service, and related roles
- Team leaders and process owners
- Non-technical staff aiming to build automations and AI agents leveraging 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
