Master class: Advanced Prompting & Assistant Creation for UX Professionals

Writing prompts is easy – but developing an AI assistant that truly supports professional UX work is a different league. Many teams get stuck with simple ChatGPT queries and miss the real potential: systematic, reliable AI assistants that master complex UX tasks.  

The problem? Between a simple prompt and a production-ready assistant lies a world. Most don't know how to develop their AI tools from 'nice toy' to 'indispensable team member'. 

The result: lots of experimentation, few sustainable solutions.  

Let's do this systematically. In this seminar, you'll build a complete UX assistant – step by step, from simple prompt to robust, tested solution that masters your real work challenges.  

The seminar is aimed at UX professionals who want to go beyond simple prompts and develop systematic AI assistants: 

• UX designers who want to intelligently automate recurring tasks 
• UX researchers who want to use AI for systematic analysis and evaluation
• Design Operations teams who want to develop scalable AI tools for their teams
• Product managers who want to optimize UX processes through AI assistants
• UX leads and managers who want to establish AI-supported quality assurance
• All UX professionals who want to systematically learn the craft of assistant development

The workshop follows a systematic, practice-oriented approach where participants:  

• Build a complete UX assistant (UX Briefing Checker) step-by-step through all 4 maturity stages  
• Learn the systematic craft of assistant development - methodically structured, not through trial & error  
• Develop an assistant that works reliably even in difficult situations, not just in perfect test cases  
• Understand the 4-stage maturity model and apply it systematically to their own use cases  
• Learn how to stress-test AI assistants and make them fit for productive use  
• Understand how to integrate assistants into real workflows and automate processes  

Participants receive:  

• A functioning UX assistant and the know-how to develop more  
• Structured approach to assistant development using the maturity model  
• Immediately applicable knowledge for their own use cases  
• Testing and quality assurance techniques for AI assistants  
• Understanding of automation as the next step  
• Peer feedback and expert tips for their own assistant ideas 

Welcome & The World of AI Assistants 

• What distinguishes a prompt from a professional assistant? 
• Live demo of the finished 'UX Briefing Checker' as target vision 
• Understanding the 4-stage maturity model   

Stage 1: The Foundation - From Generalist to Knowledge-based Apprentice 

• Experience the weaknesses of generalist AI responses 
• Build structured knowledge base from real examples 
• The 'aha effect': When answers suddenly become specific and consistent 
• Practical implementation on UX Briefing Checker 
• Knowledge Base Design and Maintenance

Stage 2: Structure & Transparency - To Transparent Evaluator 

• Develop answer templates for clear, professional structure 
• Template extension for evidence-based evaluations 
• Make 'thought process' comprehensible for stakeholders 
• Consistent formats for different use cases 
• Integrate argumentation and reasoning logic

Stage 3: Quality & Robustness - To Reliable Colleague 

• Systematic testing with targeted vulnerability search 
• Develop 'stress tests' for difficult edge cases 
• Use in-prompt examples for behavior refinement 
• Identify edge cases and solve elegantly 
• Balance robustness vs. flexibility 
• Quality assurance and error handling

Stage 4: Transfer & Outlook - Automation and Integration 

• When is the step to automation worthwhile? 
• Integrate AI assistants into existing workflows 
• Understand tool connections and API integrations 
• Plan process automation with AI assistants 
• ROI evaluation for automation projects 
• Change management in AI integration

Use-Case Clinic - Your Next Assistant 

• Small group work on individual use cases 
• Apply maturity model to own challenges
• Plan first steps for next assistant 
• Roadmap for own assistant development 
• Peer feedback and expert tips

On completion of this course, participants will be able to:   

• Apply the 4-stage maturity model for systematic assistant development  
• Create knowledge-based assistants by structurally integrating domain knowledge  
• Design professional output formats and templates for consistent results  
• Develop systematic testing strategies to find and fix weaknesses  
• Apply advanced in-prompt engineering techniques for reliable responses  
• Evaluate when automation makes sense and plan integration into workflows  
• Build robust, production-ready AI assistants that handle edge cases elegantly  
• Transfer learned principles to their own use cases and challenges  
• Make the assistant's reasoning process transparent for stakeholders  
• Balance robustness and flexibility in assistant design 

Workshop with hands-on assistant development