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Duration 14 hours
Course Outline
Day 1: Workflows and the AI Step
Introduction
- Distinguishing when to automate, when to use an AI step, and when to deploy an agent
- n8n in context: comparing cloud and self-hosted options and their implications for company data
n8n Essentials
- Understanding workflows, nodes, triggers, and executions
- Transferring data between nodes by dragging fields, eliminating the need for syntax typing
- Interpreting execution logs to identify and resolve issues
Connecting Apps and Data
- Utilizing webhooks and form triggers
- Working with spreadsheet, email, and calendar nodes
- Managing credentials and authentication for external services
- Step-by-step guidance on the HTTP Request node
The AI Step
- Integrating a model into a workflow
- Crafting prompts for consistent and reliable output
- Achieving structured output and automatically correcting malformed responses
- Classifying and extracting insights from emails, forms, and documents
Decisions and Actions
- Implementing branching logic with If and Switch nodes
- Setting up approval steps to require human intervention before actions
- Recording results in spreadsheets and dispatching notifications
Hands-on Lab: First End-to-End Workflow
- Processing an incoming request through classification, recording, and routing
Day 2: Agents and Operations
Agents
- Defining an agent: the role of model, memory, and tools
- Choosing between fixed workflows and agents
- Granting agents access to company documents and spreadsheets
Agents That Act
- Differentiating between read-only and write-capable tools
- Establishing system prompt rules: enforcing required fields, preventing data fabrication, and avoiding duplicate records
- Stress-testing agents to identify vulnerabilities
Channels
- Using chat interfaces for internal communication
- Connecting agents to a single messaging channel
Reliability
- Implementing error workflows, retries, and notifications
- Utilizing logs and execution history
- Managing model and execution costs
Data and Privacy
- Assessing data exposure when external models are invoked
- Demonstrating self-hosting and local models
- Providing a checklist for review with IT or legal teams
Building Workflows with AI
- Leveraging AI assistants to draft workflows
- Reviewing drafts: understanding node functions, data sources, and handling empty states
Final Project and Next Steps
- Participants complete and present a workflow featuring an AI step and an agent applied to their own process
- Developing a maintenance plan and identifying future automation candidates
Deliverable: A functional workflow with an AI step, an agent linked to company data, error handling, and a review checklist.
Requirements
- No programming background required
- Familiarity with web applications and spreadsheets
- A clear understanding of one repetitive process in their own workflow
Audience
- Professionals in business, operations, and customer-facing roles
- Team leads and process owners
- Non-technical staff aiming to build automations and AI agents on 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
