Step-by-Step Instructions

Complex tasks often cause ChatGPT to trip over its own logic. The solution is to break the task down into a sequence of instructions.

1. Why Sequencing Matters

When you ask for a final result immediately, the model might skip logic steps. By forcing it to go step-by-step, you are effectively increasing its "thinking time."

2. The "Chain of Command"

Instead of one big paragraph, use numbered lists for your instructions.

Example Prompt:

1. First, summarize the main points of the attached text.
2. Second, identify any logical fallacies in the author's argument.
3. Third, draft a rebuttal to each point.
4. Finally, format the output as a memo to the Board of Directors.

graph TD
    Task[Complex Task] --> S1[Step 1: Summarize]
    S1 --> S2[Step 2: Analyze]
    S2 --> S3[Step 3: Rebut]
    S3 --> S4[Step 4: Format]
    S4 --> Final[High-Quality Outcome]

3. "Think Step-by-Step"

The most famous "magic phrase" in prompt engineering is simply adding: "Let's think step by step." This triggers something in the model's training that encourages it to slow down and verify its logic before giving a final answer.

4. Conditional Steps

You can even give the AI a decision tree.

"If the text is positive, suggest a reward. If the text is negative, suggest a correction plan."

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Hands-on: The Multi-Step Challenge

Try to get ChatGPT to solve a logic puzzle by asking for the answer directly. If it fails, try again but specify: "First, list the known facts. Second, list the constraints. Third, evaluate the first possible solution. Finally, give the answer."

Key Takeaways

• Sequence = Stability.
• Numbered steps prevent the AI from missing parts of your request.
• Use Checklists within your prompts.