Course Outline
Day 1: Workflow Design and AI Integration
Introduction
- Distinguishing between simple automation, AI-assisted steps, and autonomous agents
- Understanding n8n deployment options: cloud vs. self-hosted, and the implications for data governance
n8n Fundamentals
- Core concepts: workflows, nodes, triggers, and execution lifecycles
- Visual data manipulation: dragging and dropping fields between nodes without syntax entry
- Diagnostic skills: analyzing execution logs to identify and resolve issues
Application and Data Connectivity
- Setting up webhooks and form-based triggers
- Integrating with spreadsheets, email systems, and calendars
- Managing credentials and authentication for external services
- A detailed walkthrough of the HTTP Request node
Implementing AI Steps
- Integrating AI models into workflow logic
- Prompt engineering techniques for consistent and reliable outputs
- Enforcing structured data formats and automatically correcting malformed responses
- Techniques for classifying and extracting insights from emails, forms, and documents
Logic and Action Control
- Implementing conditional logic using If and Switch nodes
- Designing approval gates to ensure human oversight before critical actions
- Recording outcomes in spreadsheets and dispatching automated notifications
Practical Lab: First End-to-End Workflow
- Building a complete flow from initial request intake to classified, recorded, and routed outcomes
Day 2: Autonomous Agents and Operational Excellence
Understanding Agents
- Defining agent components: underlying model, memory state, and available tools
- Strategic decision-making: when to use fixed workflows versus dynamic agents
- Granting agents secure access to internal documents and data repositories
Action-Oriented Agents
- Differentiating between read-only tools and tools that modify data
- Establishing system prompt rules: enforcing mandatory fields, preventing data hallucination, and avoiding duplicates
- Adversarial testing strategies to stress-test agent reliability
Communication Channels
- Setting up chat interfaces for internal user interaction
- Linking agents to specific messaging platforms
Operational Reliability
- Configuring error handling workflows, retry mechanisms, and alert notifications
- Leveraging logs and execution history for audit and troubleshooting
- Strategies for managing and optimizing model usage costs
Data Governance and Privacy
- Tracking data flow when external models are invoked
- Exploring self-hosted and local model options via live demonstration
- Creating a compliance checklist for review with IT and legal departments
AI-Assisted Workflow Construction
- Utilizing AI assistants to generate initial workflow drafts
- Critical review process: validating node functions, data sources, and null-value handling
Capstone Project and Future Pathways
- Participants complete and present a personalized workflow featuring AI steps and an agent applied to a real-world process
- Developing a maintenance plan and identifying future automation opportunities
Deliverable: A functional workflow incorporating AI capabilities, an agent integrated with company data, comprehensive error handling, and a governance checklist.
Requirements
- No prior programming knowledge is necessary
- Familiarity with web-based applications and spreadsheet software
- Identification of at least one repetitive process within your current workflow
Target Audience
- Professionals in business operations, general management, and client-facing roles
- Team leaders and owners of specific business processes
- Non-technical staff aiming to create automations and AI agents utilizing 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
