Productive AI agent workflows with n8n

Course

Booking no:

42635

Productive AI agent workflows with n8n

Agents are not just better workflows—they are architectures with decision-making, responsibility, and control. This course teaches how AI agents can be implemented with n8n in a practical and production-oriented manner. You will learn how to systematically expand classic workflows to include agent-based architectures – from simple single agents with tool use to decision-based orchestration logic to controlled agent systems with human control points. The goal is to automate real business processes with AI agents in a traceable, controlled, and responsible manner.

4 weeks

approx. 20 hours

Online

German

Professional and Master Class

Date preview

Start date

Last module

Availability

Location

3.8.2026

24.8.2026

Places free

Maximum planning security

Implementation already secured

Hook on!

Next booking secures the
implementation

Live-Online

4.11.2026

30.11.2026

Places free

Maximum planning security

Implementation already secured

Hook on!

Next booking secures the
implementation

Live-Online

Book course individually

Module overview

The following module overview shows dates for the course start on

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Module

Understanding agent architectures

Tool vs. AI assistant vs. workflow vs. agent
Single-agent architecture as an entry point
Overview of decision agents and decision-based orchestration (supervisor logic)
Overview of n8n and AI Agent Node

Webinar

3 hours

Monday, 03.08.2026
09:00 am - 12:00 pm

61459747

Module

Understanding agent architectures

Tool vs. AI assistant vs. workflow vs. agent
Single-agent architecture as an entry point
Overview of decision agents and decision-based orchestration (supervisor logic)
Overview of n8n and AI Agent Node

Webinar

3 hours

Wednesday, 04.11.2026
09:00 am - 12:00 pm

61459715

Module

Self-study phase 1

Implement single-agent systems

n8n basic logic and data flow
Setting up a simple single-agent system
First agentic decisions without tool use
Exercise: Setting up your own single-agent workflow

Agents with tool use and memory

Agents with external tools
Memory and state logic
Decision agents for path control
Exercise: Extending the agent with tool use and context

Self-study phase

approx. 6 hours

61459747

Module

Self-study phase 1

Implement single-agent systems

n8n basic logic and data flow
Setting up a simple single-agent system
First agentic decisions without tool use
Exercise: Setting up your own single-agent workflow

Agents with tool use and memory

Agents with external tools
Memory and state logic
Decision agents for path control
Exercise: Extending the agent with tool use and context

Self-study phase

approx. 6 hours

61459715

Module

Structured agent systems in companies

Simple agents vs. agent orchestration
Delegation of tasks to specialized sub-processes
Human-in-the-loop as a governance element
Live demo of a Smart Inbox agent

Webinar

3 hours

Wednesday, 12.08.2026
09:00 am - 12:00 pm

61459747

Module

Structured agent systems in companies

Simple agents vs. agent orchestration
Delegation of tasks to specialized sub-processes
Human-in-the-loop as a governance element
Live demo of a Smart Inbox agent

Webinar

3 hours

Monday, November 16, 2026
, 9:00 a.m. – 12:00 p.m.

61459715

Module

Self-study phase 2

Develop your own agent architecture

Selection of a use case
Definition of agent goals, roles, and control points
Implementation of an orchestrated agent workflow

Quality, testing, and control

Error handling and fallback strategies
Test cases for agentic systems
Human-in-the-loop and approval processes

Self-study phase

approx. 6 hours

61459747

Module

Self-study phase 2

Develop your own agent architecture

Selection of a use case
Definition of agent goals, roles, and control points
Implementation of an orchestrated agent workflow

Quality, testing, and control

Error handling and fallback strategies
Test cases for agentic systems
Human-in-the-loop and approval processes

Self-study phase

approx. 6 hours

61459715

Module

Presentation, reflection, and transfer

Presentation of proprietary agent architectures
Analysis of the selected architectures
Best practices and outlook for programmatic agent systems

Webinar

3 hours

Monday, August 24, 2026
, 9:00 a.m. – 12:00 p.m.

61459747

Module

Presentation, reflection, and transfer

Presentation of proprietary agent architectures
Analysis of the selected architectures
Best practices and outlook for programmatic agent systems

Webinar

3 hours

Monday, November 30, 2026
9:00 a.m. - 12:00 p.m.

61459715

Course overview

Contents and course schedule

1. Overview of agent architectures: From simple to structured

Difference between tool, AI assistant, workflow, and agent
Why large language models enable agentic systems
Overview of central agent architectures in a corporate context: single agent, decision agent, decision-based orchestration (supervisor logic), human-in-the-loop

2. Introduction to n8n and simple single-agent systems

Basic logic of n8n: triggers, nodes, and data flow
Building a single-agent system with the AI agent node
Initial agent decisions based on voice input

3. Empowering agents: Tool use and context

Integration of external tools and data sources into agents
Agents with memory and state logic
Agentic decision logic for controlling subsequent processes

4. Decision agents and agentic orchestration

Decision agents as a bridge between agent and workflow
Supervisor logic for delegating tasks to specialized subprocesses
Conceptual introduction to role-based agent systems

5. Human-in-the-loop and governance

Human checkpoints as an integral part of agentic systems
Limits of autonomous agents in a corporate context
Traceability, responsibility, and quality assurance

6. Develop your own agent architectures

Systematic selection of an application case
Definition of agent objectives, roles, and control points
Implementation of a custom agent workflow in n8n

7. Transfer to practice and outlook

Presentation and analysis of proprietary agent solutions
Classification of the selected agent architecture
Differentiation from programmatic agent systems

This is how you learn in this course

This course offers you a digital blended concept that has been developed for part-time learning. Thanks to a flexible mix of online seminars and self-study phases, you are sure to reach your goal. This is how you learn in this course:

Learning environment: In your online learning environment, you will find useful information, downloads and extra services for this training course after you have registered.

Self-study phases: Learn independently, at your own pace and whenever you want. Our courses offer you didactically high-quality learning material.

Live webinars: In regular online seminars, you will meet your trainers in person. You will receive answers to your questions, specific assistance and instructions on how to deepen your knowledge and apply the skills you have acquired in practical exercises.

Learning community: A digital learning community is available to you throughout the course. Exchange ideas with other participants and the trainers and ask questions.

Future Jobs Club: Get exclusive access to a business network, news, and future work hacks.

Certificate of completion and Open Badge: As a graduate of the course, you will receive a certificate of completion and an Open Badge, which you can easily share on professional networks (including LinkedIn).