Task Decomposition

This tutorial explores the concept of task decomposition in prompt engineering, focusing on techniques for breaking down complex tasks and chaining subtasks in prompts. These techniques are essential for effectively leveraging large language models to solve multi-step problems and perform complex reasoning tasks.

As AI language models become more advanced, they are increasingly capable of handling complex tasks. However, these models often perform better when given clear, step-by-step instructions. Task decomposition is a powerful technique that allows us to break down complex problems into smaller, more manageable subtasks. This approach not only improves the model's performance but also enhances the interpretability and reliability of the results.