This workshop focuses on the practical application of generative AI. Participants will learn how the quality of the results is influenced by context, the task at hand, data and the desired output format, and how unstructured information can be processed systematically.

Contents:

• Context Engineering Instead of “Magic Prompts”

• Structured Tasks: Role, Context, Task, Format, and Constraints

• Structuring Unstructured Information

• Key-Value Extraction and Structured Output Formats

• Hallucinations and Other Common Sources of Error

• Quality Assurance Through Source-Bound AI Systems

• Human Oversight and Verification

Learning Objectives:

Participants will be able to…

• Formulate tasks and contexts for AI systems in a structured and goal-oriented manner,

• Convert unstructured information into comprehensible structures using generative AI,

• Identify typical sources of error, such as hallucinations, and assess their impact on FDM processes,

• Systematically review and improve AI-generated results using appropriate sources.

Registration form (deadline: 10.11.2026)