Most AI tools have limitations on the amount of text they can process at once.
Large inputs can hurt accuracy, cause memory issues, or lead to the AI getting “lost” in the complexity.
Proceeding in smaller chunks allows you to course-correct issues along the way for a better end result.
Precision: Smaller prompts give you more control over the AI’s output. You can provide tailored instructions for each step, directing the final result with greater accuracy.
Understanding how to break down complex tasks is essential for interacting effectively with AI tools. Even outside of prompt engineering, we do this naturally in many settings. Writing documentation often starts with a simple outline, expanding into greater detail over time. Similarly, a complex codebase is built through incremental steps, adding components over time. Learning to identify those smaller steps within a complex problem is fundamental to working with AI tools.
In this tutorial, you’ll learn to create a complex tree diagram (in ASCII text) from a JSON block. Breaking this task down into smaller steps will make it easier for the AI to process and will ultimately yield a more accurate and visually appealing diagram."
