Course Outline
Day 1: Workflows and the AI Component
Introduction
- Determining when to automate, when to use an AI step, and when to deploy an agent
- n8n in context: comparing cloud versus self-hosted setups and their implications for company data
n8n Essentials
- Understanding workflows, nodes, triggers, and executions
- Transferring data between nodes by dragging fields, without entering syntax
- Analyzing executions to identify and resolve issues
Connecting Applications and Data
- Implementing Webhooks and form triggers
- Utilizing spreadsheet, email, and calendar nodes
- Managing credentials and authentication for external services
- Navigating the HTTP Request node step by step
The AI Component
- Integrating a model into a workflow
- Crafting prompts to ensure reliable output
- 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
- Creating approval steps that require human confirmation before actions are taken
- Recording results in spreadsheets and dispatching notifications
Hands-on Lab: First End-to-End Workflow
- Processing from incoming request to a classified, recorded, and routed outcome
Day 2: Agents and Operations
Agents
- Defining an agent: understanding the model, memory, and tools
- Choosing between a fixed workflow and an agent
- Granting agents access to company documents and spreadsheets
Action-Oriented Agents
- Distinction between tools that read data and those that write data
- System prompt rules: enforcing required fields, prohibiting fabricated data, and preventing duplicate records
- Testing agents by attempting to disrupt their functionality
Channels
- Deploying a chat interface for internal use
- Connecting the agent to a single messaging channel
Reliability
- Setting up error workflows, retries, and notifications
- Reviewing logs and execution history
- Managing model and execution costs
Data and Privacy
- Identifying data that leaves the company when a model is invoked
- Exploring self-hosting and local models: instructor demonstration
- Developing a checklist for review with IT or legal teams
Building Workflows with AI Assistance
- Prompting 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 Future Steps
- Each participant completes and presents a workflow featuring an AI step and an agent applied to their specific process
- Developing a maintenance plan and identifying future automation candidates
Deliverable: A functional workflow incorporating an AI step, an agent linked 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 your own work
Target Audience
- Business, operations, and customer-facing professionals
- Team leads and process owners
- Non-developers interested in building automations and AI agents using 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
