From Generic to Genius: A Masterclass in Editing AI Prompts
Most people stop at the "First Draft" of a prompt. That's why 90% of AI-generated content sounds the same: bland, robotic, and boring.
Great prompt engineers don't just write; they iterate.
In this masterclass, we are going to play a game. We will take a single, terrible prompt and "Level It Up" through 5 stages of optimization. By the end, you'll see exactly how a few strategic edits can turn a "meh" answer into a viral masterpiece.
The Fix: We need to define the "Who" and the "What".
Result: Better. Now the advice is targeted (e.g., "nap when the baby naps"), but the tone is still likely boring.
The Fix: We need to kill the robot voice.
Result: Now we have personality! The AI might say things like, "Look, I know your coffee is cold, but listen..."
The Fix: Walls of text kill engagement. We need structure.
Result: Highly skimmable content. Readers stay longer because it looks easy to read.
The Fix: Boring advice is forgotten. We need a hook.
The Final Result:
Constraint: Do not use cliches.
Task: Argue that 'lazy' parenting is efficient. Give 3 actionable tips.
Format: Short sentences. Bold key points. Include a summary box."
Why this wins: It has Role, Context, Tone, Constraint, Format, and a Contrarian Angle. It is bulletproof.
Frequently Asked Questions
Can I use this process for coding prompts? +
Absolutely. Start with "Write code." Then add Language (Python), then Context (Data Science), then Constraints (No libraries), then Format (Commented code).
Does this work on Claude and Gemini? +
Yes. This logic is universal to all Large Language Models (LLMs). Clarity and specificity win on every platform.
Go Iterate
Next time you get a bad result, don't close the tab. Play the game. Level up your prompt one step at a time until you hit "Genius."