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Duration 14 hours
Course Outline
Day 1: Workflows and the AI Step
Introduction
- Distinguishing when to automate, when to apply an AI step, and when to deploy an agent
- n8n in context: Comparing cloud and self-hosted deployment and their impact on company data
n8n Fundamentals
- Understanding workflows, nodes, triggers, and executions
- Transferring data between nodes by dragging fields, eliminating the need for manual syntax entry
- Analyzing executions to identify and resolve issues
App and Data Integration
- Configuring Webhooks and form triggers
- Utilizing nodes for spreadsheets, email, and calendars
- Managing credentials and authentication for external services
- A step-by-step guide to the HTTP Request node
The AI Step
- Incorporating a model into a workflow
- Crafting prompts for consistent and reliable output
- Achieving structured output and automatically correcting malformed responses
- Classifying and extracting data from emails, forms, and documents
Decisions and Actions
- Implementing branching logic with If and Switch nodes
- Establishing approval steps: Requesting human verification before executing 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: Components of model, memory, and tools
- Choosing between a fixed workflow and an agent
- Providing agent access to internal documents and spreadsheets
Agents in Action
- Differentiating between read-only and write-enabled tools
- Establishing system prompt rules: Mandatory fields, prohibition of hallucinated data, and prevention of duplicate records
- Stress-testing agents by attempting to disrupt their function
Communication Channels
- Setting up a chat interface for internal use
- Connecting the agent to a messaging channel
Reliability
- Implementing error workflows, retry mechanisms, and notifications
- Reviewing logs and execution history
- Managing costs associated with models and executions
Data and Privacy
- Assessing data exposure when external models are invoked
- Demonstration of self-hosting and local model execution by the instructor
- Creating a checklist for review with IT or legal teams
Building Workflows with AI
- Using an AI assistant to draft initial workflow structures
- Reviewing the draft: Analyzing node functions, data sources, and handling of empty states
Final Project and Next Steps
- Participants complete and present 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 including an AI step, an agent integrated with company data, error handling, and a review checklist.
Requirements
- No programming background is necessary
- Familiarity with web applications and spreadsheet tools
- Identification of a repetitive task within your current workflow
Target Audience
- Professionals in business, operations, and customer service roles
- Team leads and owners of business processes
- Non-technical staff aiming to build automations and AI agents using internal 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
