Prompting and context management

The course shows you how to use AI models more effectively with modern methods instead of classic prompting - through context management, roles and examples.
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With Timo Springer

Video duration

30 Minutes

Study Time

1 Hours

Skill-Level

Starter

Role

All Roles

What you will learn in this course:

In this course, you will learn how the field of prompt engineering has evolved and why advanced techniques such as chain-of-thought are rarely necessary anymore. Instead, the focus is on what information you provide to the model and how you structure your context optimally. Modern language models already understand even unstructured queries very well, so the real added value now lies in clear context management. You learn:
  • The “prompt engineering” revolution in retrospect: Why complex prompt structures are becoming less important.
  • The basis for better results: Clarity, specificity and meaningful examples replace extensive fiddling with individual wording.
  • Role Setting & Output Control: Learn to use roles and output specifications effectively to get exactly the result you want.
  • Iterations & feedback loops: How to improve your result step by step and feed new information to the AI in a targeted manner.
  • Context management: Create central context documents and ensure that the model can access important information.

Chapter in this course: