Course Outline
Day 1: Workflows and the AI Component
Introduction
- Determining when to automate, when to incorporate an AI step, and when to deploy a full agent
- Understanding n8n’s context: comparing cloud and self-hosted deployments and their implications for corporate data
n8n Fundamentals
- Overview of workflows, nodes, triggers, and executions
- Transferring data between nodes via field dragging, eliminating the need for manual syntax entry
- Analyzing execution logs to identify and resolve issues
Integrating Apps and Data
- Utilizing webhooks and form triggers
- Incorporating nodes for spreadsheets, email, and calendars
- Managing credentials and authentication for external services
- A step-by-step guide to the HTTP Request node
Implementing the AI Step
- Integrating AI models into workflows
- Crafting prompts to ensure reliable output
- Achieving structured outputs 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
- Incorporating approval steps to pause actions pending human confirmation
- Recording results in spreadsheets and dispatching notifications
Hands-on Lab: First End-to-End Workflow
- Transforming an incoming request into a classified, recorded, and routed outcome
Day 2: Agents and Operations
Understanding Agents
- Defining an agent: the role of the model, memory, and tools
- Choosing between a fixed workflow and a dynamic agent
- Granting agents access to corporate documents and spreadsheets
Agent Capabilities
- Differentiating between read-only and write-enabled tools
- Establishing system prompt rules: enforcing required fields, prohibiting fabricated data, and preventing duplicate records
- Stress-testing agents to ensure robustness
Communication Channels
- Setting up a chat interface for internal use
- Connecting the agent to a single messaging platform
Ensuring Reliability
- Configuring error workflows, retry mechanisms, and notifications
- Maintaining logs and tracking execution history
- Managing model usage and execution costs
Data Security and Privacy
- Identifying what data is exposed when external models are invoked
- Demonstrating self-hosting and local model usage by the instructor
- Providing a checklist for review with IT or legal teams
Leveraging AI in Workflow Construction
- Using AI assistants to draft initial workflow structures
- Reviewing the output: analyzing node functions, data sources, and handling empty states
Final Project and Future Steps
- Participants finalize and present a workflow that includes an AI step and an agent applied to their own specific process
- Developing a maintenance plan and identifying future automation candidates
Deliverable: A functional workflow featuring an AI step, an agent integrated with company data, comprehensive error handling, and a verification checklist.
Requirements
- No prior programming knowledge is necessary
- Proficiency in using web applications and spreadsheets
- A clear understanding of one repetitive task in the participant’s own workflow
Target Audience
- Professionals in business, operations, and customer-facing roles
- Team leaders and process owners
- Non-technical staff interested in creating automations and AI agents leveraging 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
