🏴‍☠️ ChatGPT, Driving Your Ferrari, Not a Golf Cart

Most people are sitting behind the wheel of a Ferrari but driving it like a golf cart when it comes to AI. If you use ChatGPT but only type a question and hit enter, you’re leaving real capability unused. An AI professional shared a framework that closes the gap between casual prompting, the top 1% of prompters, and even the “top 0.0001%” level of consistency.

This isn’t about longer prompts; it’s about changing how you run the interaction. The system is built around four moves: Start Different, Think Different, Search Different, and Set Up Different.

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Mastering the Setup and Launch
Output quality is decided before the AI writes a word. Instead of “write X,” “Start Different” by programming behavior first. Begin by assigning a persona.

“Act as [role]” sets the lens for priorities and expertise. Add: “Propose plan; wait for go/no-go.” That forces an outline, then a hard stop for your approval, so the model doesn’t hallucinate or wander for five paragraphs.

You can also add a cognitive constraint: “Think deeply, spend 200 tokens.” It nudges the model to invest in structure before drafting, like outlining before writing.

Strategic Thinking and Revision
After role and plan, “Think Different.” Tell the model to enter “Thinking mode” before you ask for output. You’re signaling analysis, not autocomplete.

For creative work, add “Think deeply before creating.” It pushes the model to consider composition, lighting, and style instead of generating generic defaults.

Then run an audit: “Argue against this, revise.” LLMs are agreeable, so you must force critique. This exposes weak logic, bias, missing constraints, and shaky assumptions, then delivers a stronger second pass.

Optimizing Search and Research
“Search Different” means separating quick facts from deep dives. Use standard search for immediate, factual questions. Use deep research modes when you need a sourced, structured report.

The safety rail is: “Cite sources or say insufficient evidence.” If sources aren’t there, the model should admit it instead of inventing plausible details. This is especially important for professional or academic work.

The Technical Foundation
Prompting tricks don’t stick if your setup is wrong. “Set Up Different” starts with enabling reference-based memory and reference chat history, which most users ignore. Otherwise, you restart from zero every session.

With memory and history, the AI can retain your tone and recurring context. Update it deliberately with lines like “Remember I prefer concise bullet points” or “Remember my target audience is software engineers.” Over time, you need fewer words to get the same precision.

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The Learning Curve
This structure adds friction upfront. “Propose plan; wait for go/no-go” can feel slower when you want an instant answer. The payoff is fewer wrong turns and fewer rewrites, because you’re treating the chat box less like a search bar and more like a command line.

Captain’s Action Plan
Ready to apply the framework and move closer to the top 0.0001%?

• Audit your settings: confirm memory and history are enabled.

• Use the go/no-go protocol: for the next complex task, ask for a plan first.

• Force self-correction: after any answer, ask it to find flaws and revise.

Prompt of the Day

If you want to see the full cheat sheet and the original breakdown, check out the source!