Course Outline
Day 1: Workflows and the AI Step
Introduction
- Determining when to automate, when to apply an AI step, and when to deploy an agent
- Contextualizing n8n: cloud versus self-hosted options and their implications for company data
Essentials of n8n
- Understanding workflows, nodes, triggers, and executions
- Transferring data between nodes via drag-and-drop fields, without requiring syntax knowledge
- Analyzing execution logs to identify and resolve issues
Integrating Apps and Data
- Utilizing webhooks and form triggers
- Working with spreadsheet, email, and calendar nodes
- Managing credentials and authentication for external services
- A step-by-step guide to the HTTP Request node
The AI Step
- Incorporating models into workflows
- Crafting prompts for consistent and reliable outputs
- Implementing structured outputs and automatic correction of malformed responses
- Classifying and extracting information from emails, forms, and documents
Decision Logic and Actions
- Creating branching logic using If and Switch nodes
- Implementing approval steps: requiring human validation before actions are executed
- Recording results in spreadsheets and dispatching notifications
Practical Lab: First End-to-End Workflow
- Processing an incoming request through classification, recording, and routing
Day 2: Agents and Operations
Agents
- Defining agent components: model, memory, and tools
- Selecting between fixed workflows and agents: decision-making criteria
- Granting agents access to corporate documents and spreadsheets
Agents in Action
- Differentiating between read-only and write-enabled tools
- Establishing system prompt rules: mandatory fields, prohibiting fabricated data, and preventing duplicate records
- Testing agents through adversarial scenarios
Communication Channels
- Deploying chat interfaces for internal use
- Connecting agents to a single messaging platform
Reliability and Stability
- Configuring error workflows, retries, and alert notifications
- Reviewing logs and execution history
- Optimizing model and execution costs
Data Privacy and Security
- Assessing data exposure when external models are invoked
- Demonstration of self-hosting and local models by the instructor
- Developing a checklist for review with IT or legal teams
Building Workflows with AI Assistance
- Using AI assistants to draft initial workflow concepts
- Validating drafts: verifying node functions, data sources, and handling empty data states
Final Project and Future Roadmap
- 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
Outcome: A functional workflow incorporating an AI step, an agent linked to company data, error handling mechanisms, and a comprehensive review checklist.
Requirements
- No prior programming experience is necessary
- Proficiency in using web applications and spreadsheets
- A clear understanding of one repetitive process within their own role
Target Audience
- Business, operations, and client-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
