Fundamentals of AI Agents
From conception to prompting to orchestration of intelligent agents
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.
This module serves as a joint introduction and establishes a common level of knowledge. We create an initial understanding and show where the journey can take us.
- The WOW demo: We start right away with practical application. A live demonstration of an autonomously operating agent shows the target vision of the course ("That's possible" moment).
- Agent vs. workflow vs. LLM: Initial fundamental distinction. When are we talking about a chatbot, when about automation, and when about a real agent?
- Market overview & classification: An initial guide to the jungle of tools (Agent.ai, Microsoft Agents, Lovable, Claude Code, Antigravity). We sort through the hype.
- Outlook: Presentation of the learning journey and objectives for the coming weeks.
Here you will lay the theoretical foundation and set up your technical environment so that you are ready to work in the subsequent webinars.
- Deep dive understanding: Why agents need external tools (tool use) and long-term memory (memory, e.g., Pinecone) to solve complex tasks
Glossary & Tech Stack: Detailed explanation of key terms and tools (LangChain, Make, Context, vector databases).
Low-code vs. code: A decision-making aid for getting started. Analysis of when low-code (Make) is sufficient and when engineering (LangChain> Python/TS) is necessary.
Setup: Instructions for setting up the necessary accounts so that everything is ready to go for the next webinar.
Knowledge check & homework for webinar 2:Think of an agent use case for the second webinar.
The focus is on the concept ("the agent's brain") and the economic perspective.
Strategy & Use Cases:
- Decision matrix: Differentiation in practice — is my case an assistant, a workflow, or an agent?
- Business Model Canvas for agents: Development of goals, required tools, contextual data, and ROI calculation. Validation of your own business case.
Context Engineering (Hands-on):
- Context > Prompt: Why engineering context is more important than "prompt magic."
- Live building: Together with the trainer, you as a learning group will build the "brain" of an agent (system prompts + context data) live.
- Structuring: Write system prompts and define what knowledge the agent needs.
Deepening of concepts and preparation for the big agent construction day in Webinar 3.
- The "Good Context Checklist": Criteria catalog for robust context. You check your designed use case for data completeness.
- Enterprise readiness: A critical examination of the stability of solutions. Distinguishing between hype demos and stable enterprise solutions.
- Fine-tuning the process: You prepare your company's internal process so that it can be technically implemented in the next webinar (create a flow chart, review API documentation).
The big implementation day. We build real agents and make them ready for operation.
Deep Dive Building:
- Hands-on group work: Building an agent depending on skill level (e.g., research agent, RAG document agent, or Workflow Plus agent).
- Integration: Connecting LLM (brain) and tools (hands). The trainer provides direct support in the breakout rooms if problems arise.
Production Readiness & Governance:
- Reality check: Dealing with loops, hallucinations, and unclear tools.
- Safety first: Implementation of kill switches, human-in-the-loop governance, and logging.
- Responsibility: Data protection, employee vs. agent responsibility, and ethical issues.
- Roadmap: Outlook on upcoming technologies (e.g., Manus, Antigravity) and strategies for integration into the team ("Build with Agents vs. Act with Agents").
Contents and course schedule
1. Understanding and demystifying agents
- Distinction: Assistant vs. deterministic workflow vs. autonomous agent.
- Why Agents Need Tools: Tool Use, RAG, and Memory (Long-Term Memory).
- Definition of the terms: prompt, context, memory, and orchestration.
2. Tool landscape and technology stack
- Low-code vs. engineering: Where is the best place to start?
- Overview and classification of relevant tools (LangChain/Langgraph, Pinecone, Make, Lovable).
- Enterprise Readiness: What’s just a gimmick, and what’s actually useful? Which use cases really work?
3. Mindset: Context engineering before prompt magic
- Why context is more important than the perfect prompt.
- The "Good Context Checklist" for reliable results.
- Preparing internal processes for automation using AI agents.
4. Identify strategy, business value, and use cases
- Decision matrix: When is an agent worthwhile, and when is a workflow sufficient?
- Business Model Canvas for Agents: Calculating Goals, ROI, and Value Creation.
- Structuring use cases based on tools and contextual data.
5. Hands-on: Building the agent's "brain"
- Write system prompts and optimize contextual data.
- Showcase: Live development using low-code approaches (Make, Lovable).
- Overview: Integrating LLM, tools, and documents (RAG).
6. Production Readiness and Governance
- Dealing with hallucinations, loops, and errors.
- Implement safety nets and "kill switches."
- EU AI Act, data protection, and ethical responsibility: What can the agent do autonomously?
7. Outlook and integration within the company
- Where is the market heading (autonomous coding agents and A2UI, etc.)?
- Build with Agents vs. Act with Agents: Embedding in the Organization.
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 that you can easily share on professional networks (such as LinkedIn).
Your benefit
- Youunderstand thefundamentaldifference between workflows and real AI agents and make the right choice for your scenario.
- You will learn how tobuildgood prompts androbust contextso that agents can work reliably.
- You canconfidently classify the currenttool landscape(LangChain, Pinecone, n8n, Make, etc.).
- Youwill developaproduction-ready agent (concept), including a business case and ROI calculation.
- Youwill experience firsthand how agents are built—from research to document chat (RAG).
- Youknow how to implement safety nets to avoid hallucinations and endless loops.
- You will receive ago-live checklist for governance, data protection, and security.
- You are ableto independently develop simple agents and integrate them into business processes.
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
- No prior installation is required. You work exclusively with free freemium web versions.
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
Training is guaranteed to take placeThe next booking ensures this course will take placeAbout us - The Haufe Akademie
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