### Q1: What is the core practice of AI engineering, and how does it combine different fields?  
### Q2: How does machine learning differ from traditional programming in terms of data usage?  
### Q3: What are the key components of the AI development lifecycle, and why is it considered iterative?  
### Q4: In what ways can AI and machine learning enhance user experience in business applications?  
### Q5: How might you leverage machine learning to improve product recommendations for your customers?  
### Q6: What challenges might businesses face when implementing AI technologies in their operations?  
### Q7: Why is effective communication important when discussing AI concepts with non-technical stakeholders?  
### Q8: How can you simplify complex AI terminology to make it more accessible to your team?  
### Q9: What strategies can be employed to foster open discussions about AI capabilities and limitations within your organization?