Course Outline
Day 1: Workflows and AI Integration
Introduction
- Determining when to automate, when to use AI steps, and when to deploy full agents
- n8n context: comparing cloud vs. self-hosted deployments and their impact on data control
Foundations of n8n
- Understanding workflows, nodes, triggers, and execution flows
- Transferring data between nodes using a drag-and-drop interface without writing code
- Analyzing execution logs to identify and resolve issues
Integrating Applications and Data
- Setting up webhooks and form-based triggers
- Working with spreadsheet, email, and calendar nodes
- Managing credentials and authentication for external services
- A step-by-step guide to using the HTTP Request node
Incorporating AI Steps
- Adding AI models to existing workflows
- Crafting prompts that ensure reliable output
- Handling structured outputs and automatically correcting malformed responses
- Classifying and extracting key information from emails, forms, and documents
Decision Logic and Actions
- Implementing branching logic with If and Switch nodes
- Creating approval steps that require human confirmation before executing actions
- Logging results to spreadsheets and dispatching notifications
Hands-on Lab: Building a Complete Workflow
- Building an end-to-end workflow from incoming request to classified, recorded, and routed outcome
Day 2: Agents and Operational Management
Understanding Agents
- Defining agent components: model, memory, and tools
- Evaluating when to use fixed workflows versus autonomous agents
- Granting agents access to internal documents and spreadsheets
Operational Agents
- Distinguishing between read-only and write-capable tools
- Establishing system prompt rules: enforcing required fields, preventing data hallucination, and avoiding duplicate records
- Testing agent robustness by attempting to break them
Communication Channels
- Setting up internal chat interfaces
- Connecting agents to single messaging platforms
Ensuring Reliability
- Implementing error workflows, retry mechanisms, and alert notifications
- Maintaining logs and reviewing execution history
- Managing costs associated with model usage and executions
Data Security and Privacy
- Tracking data egress when external models are invoked
- Demonstrating self-hosting options and local model deployment
- Using a review checklist for IT and legal teams
Leveraging AI in Workflow Design
- Using AI assistants to draft initial workflow structures
- Reviewing drafts: analyzing node functions, data sources, and handling empty data scenarios
Final Project and Future Steps
- Participants complete and present a workflow featuring an AI step and an agent applied to their own business process
- Developing a maintenance plan and identifying future automation candidates
Deliverable: A functional workflow featuring AI integration, an agent connected to internal data, error handling, and a review checklist.
Requirements
- No prior programming experience is necessary
- Proficiency with web-based applications and spreadsheets
- A clear understanding of at least one repetitive task in your current workflow
Target Audience
- Professionals in business operations and customer-facing roles
- Team leads and owners of business processes
- Non-technical staff aiming to build automations and AI agents using 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
