Course Outline
Day 1: Workflows and AI Integration
Introduction
- Determining when to automate, when to apply an AI step, and when to deploy an agent
- Contextualizing n8n: cloud versus self-hosted deployments and their implications for corporate data
Core n8n Concepts
- Understanding workflows, nodes, triggers, and execution cycles
- Transferring data between nodes by dragging fields, eliminating the need for manual syntax entry
- Analyzing execution logs to identify and resolve issues
Connecting Applications and Data
- Utilizing webhooks and form triggers
- Integrating spreadsheet, email, and calendar nodes
- Managing credentials and authentication for external services
- Step-by-step guide to using the HTTP Request node
The AI Step
- Integrating a model into a workflow
- Crafting prompts to ensure reliable outputs
- Achieving structured output and automatically correcting malformed responses
- Classifying and extracting information from emails, forms, and documents
Decision Making and Actions
- Implementing branching logic using If and Switch nodes
- Adding approval steps: requiring human validation before executing actions
- Recording results in spreadsheets and dispatching notifications
Hands-on Lab: Initial End-to-End Workflow
- Building a complete flow from an incoming request to a classified, recorded, and routed outcome
Day 2: Agents and Operations
Agents
- Defining an agent: the role of the model, memory, and tools
- Choosing between a fixed workflow and an agent
- Granting agents access to corporate documents and spreadsheets
Actionable Agents
- Distinguishing between tools for reading and writing data
- Establishing system prompt rules: enforcing required fields, preventing data hallucination, and avoiding duplicate records
- Testing agent robustness through adversarial testing
Communication Channels
- Deploying chat interfaces for internal use
- Connecting the agent to a single messaging platform
Reliability and Stability
- Configuring error workflows, retry mechanisms, and notifications
- Leveraging logs and execution history for oversight
- Managing model usage and execution costs
Data Privacy and Security
- Auditing data exposure when external models are invoked
- Instructor demonstration of self-hosting and local model deployment
- Reviewing a compliance checklist with IT or legal teams
Building Workflows with AI Assistance
- Using AI assistants to draft initial workflow structures
- Reviewing AI-generated outputs: verifying node functionality, data sources, and handling of empty values
Final Project and Future Steps
- Participants complete and present a workflow featuring an AI step and an agent applied to their own business process
- Developing a maintenance plan and identifying future automation opportunities
Deliverable: A functional workflow incorporating an AI step, an agent connected to corporate data, error handling, and a review checklist.
Requirements
- No prior programming experience is necessary
- Proficiency with web applications and spreadsheet software
- A clear understanding of one repetitive process within the participant's current role
Target Audience
- Professionals in business operations, management, and customer-facing roles
- Team leads and process owners
- Non-technical users aiming to develop automations and AI agents leveraging corporate 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
