Course Outline
Day 1: Foundational Workflows and AI Integration
Introduction
- Distinguishing when to use automation, AI steps, or full agents.
- Understanding n8n’s context: comparing cloud versus self-hosted deployments and their implications for data security.
Core n8n Concepts
- Key components: workflows, nodes, triggers, and execution cycles.
- Data manipulation between nodes via drag-and-drop fields, eliminating the need for syntax typing.
- Analyzing execution logs to identify and resolve issues.
Application and Data Connectivity
- Implementing Webhooks and form-based triggers.
- Utilizing nodes for spreadsheets, email, and calendar integration.
- Managing credentials and authentication for external services.
- A detailed walkthrough of the HTTP Request node.
Implementing AI Steps
- Integrating models directly into the workflow architecture.
- Crafting prompts that yield reliable and consistent outputs.
- Ensuring structured output and automatically correcting malformed responses.
- Classifying and extracting key information from emails, forms, and documents.
Decision Logic and Actions
- Implementing branching logic using If and Switch nodes.
- Designing approval steps that require human verification before actions are executed.
- Recording results in spreadsheets and dispatching notifications.
Hands-on Lab: First End-to-End Workflow
- Building a complete pipeline from incoming requests to classified, recorded, and routed outcomes.
Day 2: Advanced Agents and Operational Management
Agent Fundamentals
- Defining an agent: the interplay of model, memory, and tools.
- Decision-making framework: fixed workflows versus dynamic agents.
- Granting agents access to internal company documents and spreadsheets.
Agent Capabilities
- Differentiating between read-only and write-enabled tools.
- Establishing system prompt rules: enforcing required fields, preventing data fabrication, and avoiding duplicate records.
- Stress-testing agents by attempting to induce errors.
Communication Channels
- Setting up chat interfaces for internal user interaction.
- Integrating the agent with a specific messaging platform.
Ensuring Reliability
- Configuring error handling workflows, retry mechanisms, and alert notifications.
- Leveraging logs and execution history for auditing.
- Optimizing and controlling costs associated with model usage and execution.
Data Security and Privacy
- Assessing data exposure when external models are invoked.
- Demonstration of self-hosting and local model deployment by the instructor.
- Reviewing a compliance checklist with IT or legal teams.
AI-Assisted Workflow Construction
- Using an AI assistant to draft initial workflow structures.
- Critical review process: validating node functions, data sources, and empty state handling.
Final Project and Future Roadmap
- Participants will complete and present a personalized workflow featuring an AI step and an agent applied to their own business process.
- Formulating a maintenance plan and identifying future automation candidates.
Deliverable: A functional workflow incorporating an AI step, an agent linked to company data, comprehensive error handling, and a review checklist.
Requirements
- No prior programming background is necessary.
- Proficiency in using web applications and spreadsheet software.
- A clear understanding of at least one repetitive task within their current workflow.
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 utilizing 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
