Course Outline
Day 1: Workflows and AI Integration
Introduction
- Determining when to automate, when to use AI steps, and when to deploy agents
- Understanding n8n in context: cloud vs. self-hosted options and their impact on data privacy
n8n Fundamentals
- Core concepts: workflows, nodes, triggers, and execution cycles
- Visual data mapping between nodes via drag-and-drop, eliminating the need for syntax coding
- Diagnosing and resolving issues by reviewing execution logs
Integrating Apps and Data
- Setting up webhooks and form-based triggers
- Utilizing nodes for spreadsheets, email, and calendar services
- Managing credentials and authentication for external APIs
- Detailed walkthrough of the HTTP Request node
Implementing AI Steps
- Adding AI models to existing workflows
- Crafting prompts to ensure reliable outputs
- Generating structured data and automatically correcting malformed responses
- Extracting and classifying information from emails, forms, and documents
Decision Logic and Actions
- Implementing branching logic using If and Switch nodes
- Incorporating human-in-the-loop approval steps before critical actions
- Writing results to spreadsheets and dispatching notifications
Practical Lab: Building Your First End-to-End Workflow
- Transforming incoming requests into classified, recorded, and routed outcomes
Day 2: Agents and Operational Management
Understanding Agents
- Defining agent components: models, memory, and tools
- Strategic choice between fixed workflows and dynamic agents
- Granting agents secure access to corporate documents and spreadsheets
Action-Oriented Agents
- Differentiating between read-only and write-capable tools
- Establishing system prompt rules: enforcing required fields, preventing data hallucination, and avoiding duplicate records
- Stress-testing agents by simulating failure scenarios
Communication Channels
- Deploying chat interfaces for internal team use
- Integrating agents with specific messaging platforms
Ensuring Reliability
- Configuring error workflows, retry mechanisms, and alert notifications
- Analyzing logs and execution history for insights
- Managing costs associated with model usage and executions
Data Privacy and Security
- Auditing data flow when external models are invoked
- Demonstration of self-hosting and local model deployment options
- Reviewing a privacy checklist with IT and legal stakeholders
Leveraging AI for Workflow Development
- Using AI assistants to draft initial workflow structures
- Critical review of node functions, data sources, and edge case handling
Final Project and Path Forward
- Participants complete and present a personalized workflow featuring an AI step and an agent integrated with their specific business process
- Developing a maintenance plan and identifying future automation opportunities
Key Deliverable: A functional workflow including an AI step, a data-connected agent, robust error handling, and a comprehensive review checklist.
Requirements
- No prior programming experience is necessary
- Basic familiarity with web applications and spreadsheet software
- Identification of one repetitive process within your current workflow for practical application
Target Audience
- Professionals in business operations and customer-facing roles
- Team leaders and process owners
- Non-technical staff aiming to build automations and AI agents using 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
