How to prompt? I gave it a short textbook PDF and asked it to create a story and it keeps generating nonsense

Crafting Effective Prompts for AI: Overcoming Challenges with Textbook-Based Inputs

In the rapidly evolving landscape of artificial intelligence, utilizing AI language models to generate creative content can be both exciting and challenging. Many users experiment with feeding these models specialized texts—such as textbooks—and instructing them to produce narratives or summaries based solely on the provided material. However, this process is not always straightforward, and understanding the nuances of prompting can significantly impact the quality of the output.

The Challenge of Creating Coherent Stories from Textbook Content

Imagine you have a PDF of a textbook and aim to generate a story that incorporates specific vocabulary from the material. A common approach might involve extracting the first few chapters and instructing an AI to craft a narrative that includes all these words at least once, and solely those words. The goal is to produce a story that is both accurate to the source and engaging.

Despite clear instructions, many users encounter recurring obstacles. The AI may generate sentences that, while containing the required vocabulary, lack coherence or make little logical sense. Sometimes, the model adds extraneous words or phrases not present in the original material, further complicating the task. This disconnect can lead to frustration, especially when the instructions are precise, yet the outputs remain nonsensical.

Why Do These Challenges Occur?

Several factors contribute to these difficulties:

• Complexity of the Input Material: Textbooks often contain specialized terminology and complex sentence structures, which can be hard for the AI to interpret and incorporate meaningfully.
• Ambiguity in Prompting: Even clear instructions may be interpreted differently by the model, leading to unexpected output.
• Limitations of AI Understanding: While GPT models excel at language generation, they lack true comprehension, making it challenging to produce perfectly context-aware narratives solely based on specified vocabulary.
• Model’s Creativity vs. Constraints: Balancing creative storytelling with strict vocabulary constraints can be tricky, as the model’s innate tendency is to generate fluid, natural sentences rather than strictly adhere to word lists.

Strategies for Improving AI-Generated Content from Textbook Inputs

To enhance the effectiveness of prompting AI models for such tasks, consider the following best practices:

1. Simplify and Clarify Instructions: Be explicit about the purpose and structure of the output. For example, specify whether the story should be coherent, educational, or strictly vocabulary-focused.
2. Break Down Tasks: Instead of asking for a story that includes all words at once, generate smaller