How to Write the Best Prompts and Use Prompt Chaining?

Prompt chaining is a method used to decompose complex tasks into simpler subtasks to increase efficiency when designing prompts for large language models (LLMs). This approach involves breaking down the task into smaller, manageable parts and using intermediate outputs to generate more nuanced responses. By doing so, prompt chaining enables LLMs to build on their previous answers and deliver more accurate output. The method is particularly useful for tasks that require well-structured algorithmic processes, such as summarizing, coding, debugging, or planning. Additionally, prompt chaining can be used to improve the performance of AI applications in various contexts, including chatbot assistants, legal document classification, scriptwriting, and more. By leveraging prompt chaining, users can increase model performance and address more complex problems.