From Concept to a Functional AI Agent
Agent Deep Dive
Did you know?
This course is part of the certified "AI Agent Specialist" Master Class. Whenyou enroll in the entire Master Class,you’ll save 22 percent compared to enrolling in the individual modules.
- Orientation: What defines an agent and how they differ from an assistant.
- Architecture decisions: Single-agent, multi-agent, and agentic RAG compared.
- Understanding patterns: When to use RAG, when to use tools, when to use webhooks — and when combinations make sense.
- Context design: prompt composition, memory strategies, and guardrails for stable agent behavior.
- Define the business problem: Develop a shared language, identify stakeholders, make success measurable.
- Group exercise: Define your own agent with goals, users, input/output, success criteria, and limitations.
Agent Design & Canvas
- Finalize scope: Refine and define your own agent design from Webinar 1.
- Tool selection: Identify and document relevant tools and APIs for implementation.
- Create agent canvas: 1-page concept document based on template — goal, architecture, interfaces, risks.
- Preparation Build phase: Clarify technical requirements, set up n8n access.
- Submission: Agent Canvas before Webinar 2
- n8n Basics for Agents: Create workflows, set up webhooks, build your first automations.
- Tool integration: Integrate external APIs, files, and repositories.
- Agentic Orchestration: Incorporate planning steps, sub-tasks, and control questions.
- Observing vs. acting: When does the agent intervene—and when does he wait?
- Troubleshooting: Logging, monitoring, and typical sources of errors in practice.
- Hands-on: Each group builds its agent using at least two external tools — initial demo at the end.
Agent Refinement & Testing
- Extend prototype: Add a second function or workflow.
- RAG integration: Connect and test knowledge base.
- Develop test prompts: Run through and document typical user cases.
- Error analysis: Identify edge cases, evaluate logging, derive improvements.
- Documentation: Record technical implementation and open issues for webinar 3.
- Submission: Working prototype before Webinar 3
- UX & degree of autonomy: How much automation makes sense? Control questions, risk checks, safety loops.
- Quality measurement: Establish a KPI system — make accuracy, task success, and time savings measurable.
- Benchmarks & Testing: Use test prompts systematically, evaluate results.
- Final Build Sprint: Final adjustments, review of success criteria.
- Pitch session: Each group presents their agent, including value and learnings.
Contents and course schedule
1. Make confident architecture decisions
- Recap Course 1 (42631): The difference between an assistant and an agent.
- A Deep Dive into Agent Architecture: When to Use RAG, When to Use Tools, When to Use Webhooks—and When to Use a Combination?
- Define agent objectives, establish success criteria, and build in control mechanisms.
- Systematically identifying the use cases that fit the architecture.
2. Designing advanced context engineering and prompts for agents
- Prompt composition, memory strategies, and context engineering in the context of architecture.
- Understanding the risk of errors and setting guardrails.
- From a single inquiry to consistent agent behavior.
3. Identify the right business problem & develop a use case
- Developing a Shared Language: Problem, Process, Pain Points, KPIs.
- Stakeholder analysis: Who benefits, who loses?
- Measuring success: costs, time, error rate, satisfaction.
4. Building agents practically with n8n
- N8n Basics for Agents: Webhooks, External APIs, Files.
- Implement the first tool integrations.
- From concept to working prototype.
5. Orchestrate complex agents
- Include planning steps, subtasks, and checklists.
- Observing vs. acting: When does the agent intervene?
- Troubleshooting, Logging, and Monitoring in Practice.
6. Measuring quality and making it scalable
- Setting up a KPI system: Accuracy, task success, time savings.
- Determining the degree of autonomy: How much automation makes sense?
- Check go-live readiness.
This is how you learn in this course
This course offers a digital blended learning approach designed for working professionals. Through a flexible combination of online seminars and self-study sessions, you’ll be sure to achieve your goals. Here’s what you’ll learn in this training program:
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 will be available to you throughoutthe course. trainers with other participants and the trainers , and ask any questions you may have.
Certificate of Completion and Open Badge:As a graduate of the class, you will receive a certificate of completion and an open badge, which you can easily share on professional networks (such as LinkedIn).
Your benefit
- You understand what distinguishes an AI agent from an assistant—and when true autonomy makes sense.
- You will learn how to make confident architectural decisions: RAG, tools, or webhooks—and when which combination is appropriate.
- You'll learn which business problems are suitable for agents —and which aren't.
- You are able to clearly define agent goals, success criteria, and control mechanisms.
- You understand how prompt composition, memory, and context engineering work together.
- You know how to set guardrails and avoid common pitfalls.
- You will build a working agent prototype in n8n —with at least two integrations with external tools.
- You will learn how to orchestrate complex agents: incorporating planning steps, sub-tasks, and control questions.
- You systematically measure quality: accuracy, task success, and time savings become tangible for you.
- You make informed decisions about the right degree of autonomy.
Technical Requirements & Prerequisites
This course is right for you if you want to build AI agents yourself. You'll build, test, fail, and solve problems. If you just want to see how finished agents work, this isn't the course for you.
What You'll Bring to the Table
- A basic understanding of technology and a sense of curiosity—you don’t need any programming skills, but you do need a willingness to learn how to use tools and code
- Practical experience with automation tools such as make or n8n—or the discipline to teach yourself the basics using the provided materials before the course begins
- Practical Understanding of Digital Business Processes and Data Flows
- Your own data (real or synthetic) that you can use to train and test your agents
- A desire for personal responsibility—not as a duty, but as a driving force
Technical requirements
- Computer or laptop with a current operating system (Windows, macOS, or Linux)
- A stable internet connection and a recent web browser (Chrome, Edge, or Firefox)
- Access to Web-Based Tools
In addition to the participation fee, there are additional tool costs.
- n8n Cloud account (free 14-day trial, then Starter plan approx. 20 € / month) — or self-hosted via Docker (free)
- Access to a large language model, such as Claude from Anthropic
- Anthropic API key (pay-as-you-go via credit card; approximately 20 € in usage)
Tools
Recommended for
With this training program, you’ll become the go-to person for intelligent AI agents and play an active role in shaping your company’s hybrid workforce (humans & AI). You want to understand how to build AI agents, integrate them securely into your company, and determine their ROI.
- Technically savvy process managers automation experts
- Technically Savvy Product Owners & Digital Project Managers
- innovation managers data professionals
- Technical specialists and managers seeking to take AI integration to the next level
- Customized training courses
- Direct application in practice
- Efficient use of time and resources
Mastering the future
Design, develop, and control production-ready AI agents – with the "AI Agent Specialist" master class
Start dates and details
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