Course Outline
Day 1: Workflows and AI Integration
Introduction
- Distinguishing between automation, AI steps, and agent usage
- n8n context: comparing cloud versus self-hosted deployment and their implications for data control
n8n Fundamentals
- Understanding workflows, nodes, triggers, and execution cycles
- Transferring data between nodes via drag-and-drop, eliminating the need for syntax
- Analyzing execution logs to identify and resolve issues
App and Data Connectivity
- Utilizing webhooks and form triggers
- Integrating spreadsheet, email, and calendar nodes
- Managing credentials and authentication for third-party services
- Step-by-step guide to using the HTTP Request node
Integrating the AI Step
- Adding models to existing workflows
- Crafting prompts for consistent and reliable outputs
- Handling structured outputs and automatically correcting invalid responses
- Classifying and extracting data from emails, forms, and documents
Decision Making and Actions
- Implementing branching logic with If and Switch nodes
- Incorporating approval steps to ensure human verification before actions are executed
- Recording results to spreadsheets and dispatching notifications
Practical Lab: Building the First End-to-End Workflow
- Processing an incoming request to achieve a classified, recorded, and routed outcome
Day 2: Agents and Operational Management
Agents
- Defining agents: the role of models, memory, and tools
- Choosing between fixed workflows and dynamic agents
- Enabling agent access to corporate documents and spreadsheets
Active Agents
- Differentiating between read-only and write-enabled tools
- Establishing system prompt rules: enforcing required fields, prohibiting fabricated data, and preventing duplicates
- Stress-testing agents to ensure robustness
Communication Channels
- Setting up internal chat interfaces
- Connecting agents to specific messaging platforms
Ensuring Reliability
- Configuring error workflows, retry mechanisms, and alert notifications
- Reviewing logs and execution history
- Managing model usage and execution costs
Data Security and Privacy
- Assessing data exposure when invoking external models
- Demonstrations of self-hosting and local model usage by the instructor
- Providing a review checklist for IT and legal teams
AI-Assisted Workflow Construction
- Using AI assistants to draft initial workflow structures
- Conducting reviews: analyzing node functions, data sources, and empty-state handling
Capstone Project and Future Steps
- Participants finalize and present a workflow incorporating an AI step and an agent applied to their own business process
- Developing a maintenance plan and identifying further automation opportunities
Final Deliverable: A functional workflow featuring an AI step, a data-connected agent, comprehensive error handling, and a verification checklist.
Requirements
- No prior programming experience is necessary
- Familiarity with using web applications and spreadsheets
- A clear understanding of at least one repetitive process within your own workflow
Target Audience
- Professionals in business, operations, and client-facing roles
- Team leads and process owners
- Non-technical staff aiming to create 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
