Example Concept: Multi-turn conversation handling can be enhanced by using context-aware NLP models that track user intents and entities across multiple interactions. Implementing dialogue state management allows the chatbot to remember past interactions and make decisions based on the conversation history. Additionally, designing conversation flows with clear transitions and fallback mechanisms ensures that the chatbot can handle unexpected user inputs gracefully.