How to Improve Results with ChatGPT: Use This Prompt

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Producing vague prompts like “draft a business plan” or “act as my personal assistant” often leads to unsatisfactory AI responses from tools such as ChatGPT, Gemini, or Claude. Lack of specificity causes the AI to generate outputs influenced by its training data and biases, which may not align with your intentions.

To achieve better results, it’s crucial to craft highly detailed prompts that specify all vital variables and decision points influencing the outcome. For instance, when asking an AI to be your assistant, clarify the scope of responsibilities, decision-making processes, tone of communication, and the degree of assertiveness expected.

If outlining every variable feels overwhelming, an effective shortcut is to use a prompt that instructs the AI to analyze your task and break it down into its constituent elements. This process, guided by prompt engineering principles called “decomposition,” helps reveal how the AI considers the task and highlights the key factors to refine further.

After obtaining the AI’s breakdown, you can adjust and optimize these variables, then re-submit the prompt to produce a more tailored and precise result. This iterative process ensures that the final prompt is clear, structured, and aligned with your specific needs.

Here is an example prompt designed to dissect your initial request into core dimensions before creating a refined prompt:

“I want to design an effective prompt for this task:

[TASK]

Identify the 5–7 most impactful prompt dimensions—core variables, constraints, context, output criteria, or stylistic preferences—that will most influence the quality of the AI’s response.

For each dimension, briefly explain:

Why it’s important

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Which tradeoff or decision it controls
How it should shape the final prompt

Using these insights, craft a clear, detailed, and well-structured prompt that incorporates context, role definition, specific instructions, constraints, expected output format, quality standards, and ambiguity handling.”

For example, in the task of defining the AI’s interaction style and communication tone, the key variable might be:

Interaction Style & Communication Tone

Why it matters: It shapes whether the AI sounds like a strategist, assistant, or coach.
Tradeoff: Balancing brevity with thoroughness, formal with casual, directive with collaborative.
Prompt influence: Specify desired tone, output format, and adaptability to different tasks.

Once the AI breaks down these variables, it generates a reconstructed prompt that reflects your adjustments. You then review, modify if needed, and re-run to refine the output further, tailoring it precisely to your objectives.

This approach transforms vague requests into structured, actionable prompts, leading to higher-quality AI responses that align closely with your expectations.