Course Outline
Day 1: Workflow Fundamentals and AI Integration
Introduction
- Distinguishing when to automate, when to employ an AI step, and when to deploy an agent
- n8n in context: comparing cloud-based vs. self-hosted environments and their implications for data security
Core n8n Concepts
- Understanding workflows, nodes, triggers, and execution cycles
- Transferring data between nodes via drag-and-drop field mapping, eliminating the need for syntax entry
- Analyzing execution logs to diagnose and resolve issues
Application and Data Connectivity
- Utilizing Webhooks and form-based triggers
- Integrating spreadsheet, email, and calendar nodes
- Managing credentials and authentication for third-party services
- Step-by-step usage of the HTTP Request node
Integrating the AI Component
- Embedding a model within the workflow
- Crafting prompts to ensure reliable outputs
- Generating structured data and automatically correcting malformed responses
- Classifying and extracting insights from emails, forms, and documents
Decision Logic and Actions
- Implementing branching logic using If and Switch nodes
- Defining approval steps to require human verification before actions are executed
- Recording outcomes in spreadsheets and dispatching notifications
Practical Lab: Building the First End-to-End Workflow
- Transforming an incoming request into a classified, logged, and routed outcome
Day 2: Advanced Agents and Operational Resilience
Agent Architecture
- Defining an agent: the interplay of model, memory, and tools
- Evaluating fixed workflows versus agents to determine the best fit
- Granting agents secure access to internal documents and spreadsheets
Action-Oriented Agents
- Differentiating between read-only tools and write-enabled tools
- Establishing system prompt rules: enforcing mandatory fields, preventing data fabrication, and avoiding duplicate records
- Conducting stress testing to identify agent vulnerabilities
Communication Channels
- Configuring a chat interface for internal team use
- Connecting the agent to a specific messaging platform
Ensuring Reliability
- Setting up error handling workflows, retry mechanisms, and alert notifications
- Monitoring logs and execution history
- Managing model usage and execution costs
Data Security and Privacy
- Auditing data transmission when external models are invoked
- Demonstrating self-hosting capabilities and local model deployment
- Utilizing a compliance checklist for review with IT and legal teams
AI-Assisted Workflow Design
- Leveraging AI assistants to draft initial workflow structures
- Critically reviewing drafts: verifying node functions, data sources, and null-handling strategies
Capstone Project and Future Roadmap
- Participants finalize and present a workflow featuring an AI step and an agent applied to their own business process
- Formulating a maintenance plan and identifying future automation opportunities
Final Deliverable: A functional workflow incorporating an AI step, an agent connected to enterprise data, comprehensive error handling, and a compliance review checklist.
Requirements
- No prior programming experience is necessary
- Proficiency in using web-based applications and spreadsheets
- Identification of one repetitive workflow in current job duties
Target Audience
- Professionals in business operations, management, and customer-facing roles
- Team leaders and process owners
- Non-technical staff aiming to develop automations and AI agents using internal 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
