Learning Path · Module 05 · AI Enthusiast

Agentic AI | Basics

As early as 2025, the year of "AI agents" was proclaimed as the next evolutionary stage of GenAI. Agents possess a memory, can perform tasks autonomously, formulate plans, write code, and collaborate with one another. This training demonstrates the opportunities and risks of using AI agents to increase efficiency and automate complex problem-solving, and prepares participants for the skillset required to successfully keep AI agents and their token hunger in check.

Who is this training for?

Interested parties who wish to acquire further competencies in this topic.

Why this training

AI models, especially the language models underlying AI agents, are not deterministic. Consequently, the quality of the work produced by AI agents varies greatly and can only be ensured if the underlying functionality is understood. Otherwise, there is a risk of efficiency loss instead of gain, and token costs will skyrocket.

Contents

  • Introduction to Large vs. Small Language Models
  • Introduction to a simple agentic harness architecture
  • Introduction to the quality requirements for prompt engineering
  • Introduction to the Model Context Protocol (MCP)
  • Practical examples of AI agents (e.g., for quality assurance along guidelines)

Methodology

  • Online presentation with examples
  • Q&A between individual chapters

Ready for your next step?

Bring this format straight into your team - tailored to your tools, your roles and your context for human-centered AI.

Everything starts with a good conversation.

So let's explore the possibilities for your digital product development together. We look forward to your inquiry.

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