All training courses
AI Engineering

AI Agents

Developing AI agents and tool-enabled LLM systems.

Connecting LLMs with tools, data, and controlled workflows to create actionable software systems.

Training format

2–3 days, depending on the depth and focus areas.

Content and duration are tailored to the team and the desired focus areas.

Area

AI Engineering

Duration

2–3 days, depending on the depth and focus areas.

Approach

Practical

Language

German or English

01

About the training

The training explains how agentic AI systems are technically designed and when their use is appropriate. It covers tool usage, state management, multi-step processes, error handling, control mechanisms, and the distinction between deterministic workflows and autonomous agents.
02

Learning objectives

Understand and assess agentic architectures Securely connect tools to LLMs Model multi-step AI workflows Manage state and context in a controlled manner Evaluate the limitations and risks of autonomous systems
03

Content and focus areas

Agents and agentic workflows Tool and function calling Tool design State and memory Planning and multi-step workflows Deterministic workflows versus agents Human in the loop Error handling and recovery Guardrails and security Evaluation and observability Architecture of production-ready agent systems
04

Practical work in the training

Toolfähige AI-Komponenten und mehrstufige Abläufe werden praktisch entwickelt. Besonderes Augenmerk liegt darauf, welche Teile deterministisch bleiben sollten und wo agentisches Verhalten tatsächlich einen Vorteil bietet.
05

Tailored training plan

The training is tailored to your team.

The content described provides the technical framework. The topics we explore in depth, the examples we use and the time we devote to each area depend on the participants' existing knowledge, goals and technical challenges.

Discuss your training needs