AI—It's Not Just What You Say; It's How You Say It

Why your phrasing matters more than you think when talking to large language models

Language is more than data to an AI; it's a signal. When you interact with a large language model (LLM), you're not just asking a question. You're setting the scene, defining the tone, and unconsciously shaping the kind of answer you get. Here's why the way you phrase your prompt matters so much.

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How Your Phrasing Teaches AI How to Respond

Tone Mirroring

AI responds in the tone you set

AI tends to mirror your tone—if your prompt is formal, it will likely respond with polished, academic language. If you're casual, friendly, or enthusiastic, it will pick up on that and match it.

Examples:

• Prompt: "Hey ChatGPT! I hope you're feeling as good as I am . . . "
  --> Response: Informal, upbeat, conversational ("Congrats on your promotion!")
• Prompt: "Please retrieve articles detailing Aristotle's views on consciousness."
  --> Response: Formal, academic tone with citations and summary structure.

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Lexical Framing

Your Word Choice Defines the AI's "Mental Model"

The words you choose signal what kind of domain you want to operate in– psychology, philosophy, tech, spirituality, etc. AI prioritizes language from that semantic field.

Examples:

• Prompt: "How does tarot work?"
  --> generalist, psychological response
• Prompt:"Is tarot random or intention-driven?"
  --> statistical and metaphysical nuance
• Prompt: "Retrieve peer-reviewed articles on tarot randomness."
  --> academic, evidence-heavy

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Complexity and Abstraction

Complex prompts get complex answers

If your sentence structure is abstract or layered, AI assumes you're comfortable with high-complexity analysis. If you ask direct questions with concrete terms, it will keep things more literal and grounded.

Examples:

• Prompt: "Can consciousness exist without embodiment?"
  --> Likely to return a philosophy-heavy answer involving dualism, embodied cognition, etc.
• Prompt: "Can AI think without a body?"
  --> Same core question, but likely framed in simpler language with practical metaphors.

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Emotional and Social Cues

Warm intros lead to warm replies

Phrases like "I hope you're well," "Hey ChatGPT," or "This might sound weird but..." signal emotional tone, vulnerability, or rapport. AI will respond more empathetically or reassuringly.

Examples:

• "I'm scared AI is getting too powerful."
  --> AI might respond with reassurance, nuance, and acknowledgment of the fear.
• "Can you explain AI alignment?"
  --> Just the facts.

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Embedded Expectations

You signal what kind of answer you want

The structure of your question implies what kind of answer you expect.

Examples:

• Prompt: "Please retrieve 3 peer-reviewed articles"
  --> You've implicitly said: "I want scholarly precision, not opinions."
• Prompt: "So what's the deal with Aristotle's idea of the soul"
  --> AI interprets that as: "Give me a fast, clear summary —don't get lost in footnotes."

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Final Takeaway

Language isn’t just how you ask—it’s how you frame the relationship between you and the AI. You’re teaching your AI how to speak to you, every time you write a new prompt.

So the next time AI gives you a weird or flat answer, ask yourself: Did I give it enough context, tone, or intention to work with? Speak to it like you'd train a helpful intern: clearly, intentionally, and in the style you want echoed back.

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Want help crafting better prompts or building your own AI interface? Contact me or check out my Prompt Wrapper App.