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Duration 14 hours
Course Outline
Day 1: Workflows and the AI step
Introduction
- Determining when to automate, when to apply an AI step, and when to utilize an agent
- n8n in context: comparing cloud versus self-hosted deployments and their implications for corporate data
n8n essentials
- Understanding workflows, nodes, triggers, and executions
- Transferring data between nodes by dragging fields, eliminating the need for syntax typing
- Analyzing execution logs to identify and resolve issues
Connecting apps and data
- Using Webhooks and form triggers
- Integrating spreadsheet, email, and calendar nodes
- Managing credentials and authentication for external services
- Step-by-step usage of the HTTP Request node
The AI step
- Integrating a model into a workflow
- Writing prompts to ensure reliable output
- Achieving structured output and automatically correcting malformed responses
- Classifying and extracting information from emails, forms, and documents
Decisions and actions
- Implementing branching logic with If and Switch nodes
- Adding approval steps: requiring human verification before actions are executed
- Recording results in a spreadsheet 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 combination of model, memory, and tools
- Choosing between a fixed workflow and an agent
- Granting an agent access to internal company documents and spreadsheets
Agents that act
- Differentiating between tools that read data and tools that write data
- Establishing system prompt rules: mandatory fields, prohibition of invented data, and prevention of duplicate records
- Testing agent robustness by attempting to break it
Channels
- Setting up a chat interface for internal use
- Connecting the agent to a specific messaging channel
Reliability
- Implementing error workflows, retries, and notifications
- Reviewing logs and execution history
- Monitoring and controlling model and execution costs
Data and privacy
- Identifying what data leaves the company when a model is invoked
- Demonstration of self-hosting and local models by the instructor
- Providing a checklist for review with IT or legal teams
Building workflows with AI
- Requesting an AI assistant to draft a workflow
- Reviewing the draft: understanding each node's function, data sources, and handling of empty values
Final project and next steps
- Each participant will complete and present a workflow featuring an AI step and an agent applied to their own process
- Creating a maintenance plan and identifying future candidates for automation
Deliverable: a functional workflow with an AI step, an agent connected to company data, error handling, and a review checklist.
Requirements
- No programming experience is required
- Proficiency in using web applications and spreadsheets
- A clear understanding of one repetitive process within their own role
Target Audience
- Business, operations, and customer-facing professionals
- Team leads and process owners
- Non-developers interested in building 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
