Prompt engineering is the art of designing input prompts that guide AI models like ChatGPT or Gemini to generate accurate, relevant, and consistent outputs. Think of it as talking to a genius who listens very literally—so you have to be crystal clear and smart in how you ask questions or give tasks.
This technique helps unlock superpowers like:
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Writing better content
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Summarizing documents
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Translating languages or code
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Classifying data
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Debugging software
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And more!
What’s Inside Google’s Prompt Engineering Guide?
The guide is a goldmine packed with practical advice. Here’s a quick breakdown:
1. Types of Prompting Techniques
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Zero-shot: Just give the task, no examples.
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One-shot & Few-shot: Provide 1 or a few examples to guide the model.
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System Prompting: Set instructions like “Reply in JSON format only.”
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Role Prompting: Tell the model to act like a teacher, coder, guide, etc.
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Contextual Prompting: Provide background info to help the AI understand better.
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Chain-of-Thought: Ask the model to think step-by-step.
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Self-consistency & Tree of Thoughts: Explore multiple reasoning paths for better answers.
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ReAct: Combine reasoning + actions, like searching online or calling APIs.
2. Output Control Settings
Learn how to control randomness and length using:
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Temperature
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Top-K / Top-P (nucleus sampling)
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Max token limits
3. Prompting for Code
From generating new scripts to explaining, translating, or debugging code, this guide shows how AI can become your coding assistant—even if you’re not a programmer.
4. Best Practices
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Be specific.
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Provide examples.
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Prefer positive instructions over negative constraints.
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Keep it simple and structured.
Who Is This For?
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Beginners trying to learn prompt engineering from scratch.
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Content creators using ChatGPT for ideas, scripts, or posts.
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Developers using LLMs in apps or automations.
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Freelancers & marketers who want better AI results without coding.
Ready to Dive In? Get the PDF Guide Now!
This is the same guide shared in the viral Instagram post.
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