6 AI Prompt Tricks That Actually Work

This is an excellent and practical compilation. It cuts through the hype and focuses on what genuinely changes the output quality. I've seen the same results in my own use. The core principle you've highlighted is absolutely correct: specificity and structured thinking frameworks force the AI to access better, more nuanced parts of its training data.

Building on your list, here are a few complementary tactics that pair well with your six.

The Example Injection: After giving a prompt, add "For example, a good output would look like this:" and then paste a short snippet of the format, tone, or structure you want. This is more powerful than just describing it.

The Reverse Engineer: When you get a perfect output from the AI, your next prompt should be "Reverse engineer the process you just used. What were the key steps and decision points?" This turns a one-time success into a reusable template.

The Devil's Advocate: After the AI gives a recommendation, prompt "Now, argue against this recommendation. What are its three biggest weaknesses or risks?" This creates a balanced perspective and mitigates the AI's sometimes over-confident tone.

Your debugging trick is the most important point. The AI doesn't have common sense; it has pattern matching. Vague prompts get vague, cliche-ridden patterns. Specific prompts with context and constraints get detailed, useful patterns.

The pro insight about learning from the "show your work" step is huge. It transforms the tool from an answer machine into a thinking partner. You're not just getting a solution, you're getting an education in the solution's logic.

Your final reality check is crucial. Stacking is powerful, but over-stacking with five different framework commands can confuse the model's primary instruction. As you said, pick two or three that directly serve the goal. Clarity of intent is the ultimate prompt engineering trick. Great summary.