Agile Methods and AI: AI Use Cases, Prompt Evaluation, and Team Reflection

Course overview

The training "Agile Methods and AI: AI Use Cases, Prompt Evaluation, and Team Reflection" combines theoretical foundations with application-oriented exercises on the topics of "AI use cases", "prompt evaluation", and "team reflection". Documented results show how Artificial Intelligence and Agile Methods interact in their respective fields. The learning sequence connects role clarification, transparent task management, team coordination, and reflective adjustment of the approach. The application of Artificial Intelligence is reinforced through structured tasks and documented decisions. The guiding theme is the task "Agile Methods and AI"; it is addressed from a technical, methodological, and quality-related perspective. The technical classification of Artificial Intelligence is complemented by specific tasks related to Agile Methods. Participants work on comprehensible practical cases from AI-supported work and application situations, compare solution paths, and document assumptions, decisions, and results. The goal is a structured understanding of the fields of tasks described in the title and their application in different work situations. Program In Artificial Intelligence, the focus is on a proper and comprehensible approach. The educational content is divided into seven interrelated learning sections: - Context of use and basic terms: The focus "Agile Methods and AI" is classified in terms of task framework, typical areas of application, and the necessary steps involved. The orientation is specified through task management, role coordination, visible progress, and the gradual adjustment of the approach. Commonalities, differences, and sensible transitions between Artificial Intelligence and Agile Methods are worked out. - AI use cases: Use possibilities are described based on clear tasks; inputs, outputs, limits, and control steps are examined together. - Prompt evaluation: Participants choose appropriate evaluation methods, compare results, and justify the chosen representation. The focus is on the competence field of Artificial Intelligence and the application focus of Agile Methods. - Team reflection: Collaboration is structured based on clear responsibilities, suitable conversation formats, and comprehensible agreements. The transfer part deepens Artificial Intelligence and translates the insights into Agile Methods into a coherent task. - Roles, collaboration, and decisions: Responsibilities, coordination paths, and decision criteria are clarified and applied in a common working rhythm. - Result quality, limits, and responsibility: Outputs are checked for plausibility, traceability, and possible errors; limits of use are documented. For Artificial Intelligence, selection criteria, work steps, and result characteristics are recorded. - Practical case and transfer: Participants work on a coherent case, justify their approach, and transfer the insights gained to a changed task. In the result control, both Artificial Intelligence and Agile…

Upcoming dates

• 2026-08-16T22:00:00.000Z · 2026-10-11T22:00:00.000Z · München · Combined Learning
• 2026-08-16T22:00:00.000Z · 2026-12-06T23:00:00.000Z · München · Combined Learning
• 2026-09-13T22:00:00.000Z · 2026-11-08T23:00:00.000Z · München · Combined Learning
• 2026-09-13T22:00:00.000Z · 2027-01-03T23:00:00.000Z · München · Combined Learning