Prompt Engineering in Practice: From Prompt to Result

• AI tool users (ChatGPT, Claude, Gemini) who want to go deeper
• Specialists outside IT (office, marketing, finance, HR)
• Anyone who wants to systematise their work with AI and improve output quality

• How to create structured prompts using proven frameworks
• How to use advanced techniques
• How to test, measure and optimise AI output quality
• How to recognise differences between models and choose the right tool
• How to build and manage your own prompt template library

• Own ChatGPT Plus licence
• Basic computer and office tool proficiency

AI fundamentals and prompt engineering

• How LLM models work and how they process input
• Principles of generative AI and their impact on output
• The most common mistakes when writing prompts
• Moving from trial and error to a systematic approach

Frameworks and creating quality prompts

• Structured prompts
• Role, context, task, format (practical application)
• Rewriting everyday assignments into professional prompts
• Creating reusable templates

Advanced techniques for working with AI

• Chain-of-thought prompting
• Few-shot learning and working with examples
• Role prompting and controlling output style
• Combining techniques for higher quality and consistency

Testing, optimisation and working with a prompt library

• Methods for testing and iterating prompts
• Measuring output quality
• Organising and managing prompt templates
• Building your own library (5–8 templates)

Hands-on practice

• Rewriting real work assignments into quality prompts
• Writing emails, analyses and document summaries
• Iteratively improving prompts based on outputs
• Building your own prompt template library
• Simulating common workplace scenarios

Wrap-up

• Summary of key principles and techniques
• Discussion of participants' specific use cases
• Q&A
• Tool and resource recommendations for further development