### Q1: What is the primary focus of Prompt Engineering in the context of AI systems?  
### Q2: How does the choice of wording in a prompt affect the output generated by an AI model?  
### Q3: What are the implications of fine-tuning in enhancing NLP models for specific customer queries?  
### Q4: How can you implement prompt engineering principles to improve user engagement in product descriptions?  
### Q5: What potential challenges could arise from ineffective prompt design in customer support applications, and how can they be mitigated?  
### Q6: How might a clear understanding of NLP improve communication between product leaders and technical teams?  
### Q7: What are some specific examples of effective prompts that have led to improved AI interactions?  
### Q8: In what ways can iterative improvement in prompt engineering contribute to better AI responsiveness over time?  
### Q9: How can product leaders ensure that their teams are aligned on the key terminology used in Prompt Engineering?