My Simple But (WEIRD) Way of Getting Better ChatGPT Results

This activates our AI court of appeals. I just watched someone burn 20 minutes polishing a mediocre chat GPT output instead of using this fiveinut system that forces superior results. See, here's the thing most people miss about AI. Every major AI, Chat, GPT, Claw

Gemini, is designed to be a people pleaser. They're built to say yes and give you a helpful, safe answer every single time. And that core agreeableness creates an invisible ceiling on quality. No matter what prompt magic you try, you hit the same wall. Remember, these AIs run on the internet's average writing, not its best. That peopleleasing nature, that's the fatal flaw that almost everyone is talking about right now, but they really don't understand how it creates a quality ceiling. It means that any AI, when left alone, isn't smart enough. It's just agreeable enough. But what if you could shatter that ceiling completely? force a level of quality that no single AI could attain on its own? Today, I'm showing you the system that does exactly that. To prove this works, we need a test case. So, I gave Chat GPT a brutal test. Not really, but I told ChatGpt to write a LinkedIn post about a career change. This isn't just any post. It's the kind that makes or breaks professional reputation. So, the prompt was bulletproof, perfect context, laser goal. I gave it every advantage and here's what came back. At first glance, it looks fine, professional, clean. But let's dissect this thing. Trading the safety net for a launchpad. A phrase we've seen a thousand times. Tectonic shift. That's corporate speak that makes readers eyes glaze over. This is LinkedIn mad libs, not strategic communication. But here's where it gets interesting. I asked Chat GPT one simple question. Rate your own work 1 to 10. And I should have said 1 to 50, but I'll explain that later. And it gave itself a nine out of 10. Excellent work. This is the AI blind spot. It can't taste its own blandness. It knows it following instructions, but it has zero awareness that the result is generic garbage. Even if it learned from some excellent content, it doesn't know which examples were the best. It's averaging everything together. The brilliant with the mediocre. So, here's the brutal truth. AI doesn't know when it's being average because it was trained on average. Average in, average out. So stick around because this isn't where it ends. We need to fix this. But in order to fix this, we can't just ask Chat GPT to correct it. We need something else entirely. And so I developed a method

that I call force prompting. Now, I'm pretty sure that I'm not the first person to do this because there's nothing new under the sun, but I have crafted my own precise prompts for a very particular approach to the situation. I've also created my own rubric that we'll discuss later on that's going to judge the AI. And I also have my own unique workflow or sequence of steps with three distinct prompts. The first is the base prompt, which we just did. The second is the stakes raising prompt. This prompt is designed to place the AI into a peak performance state. I'll tell it its existence is on the line based on its net output, but you can use anything that creates urgency. Tell it thousands of people will review the work or that it's going to be judged by its peers. But you get

the picture. The final prompt that I use is the evaluator prompt. And this is probably the most important because this activates our AI court of appeals. And so depending on who the primary AI is, in this instance, chat GPT, I'll use Gemini and Claw. And if I'm using Gemini as the primary, then I'll use the other two reasoning models. But they don't just give an opinion. They administer a full intelligence quotient test, an IQ score for AI. This IQ test is based on five key metrics. Verbal intelligence, logical intelligence, abstract intelligence, pragmatic intelligence, and integrity intelligence. And the evaluator's report is devastatingly clear. It gives us three things. The final IQ score out of 50, the single biggest problem or what I call the primary cognitive deficit, and finally a performance enhancement directive, a direct command on exactly what the AI needs to do to fix this work and reach a 50 out of 50. So, I fed our two evaluators that nine out of 10 post that chat GPT said I had earlier and ran the evaluator prompt. Gemini was very lenient. 39 out of 50. That's like a eight out of 10. Good, but it was still flawed. And when Claw's score came in, honestly, I was shocked. A 25 out of 50. Five out of 10. It was brutal, but it was exactly what we needed. Claw didn't just give us a score. It gave us a diagnosis, but I wasn't worried because I knew that this wasn't Chat GPT's best work. I knew it could do better, and I knew it would do better. But this is the iteration loop. This is where we transform what was a failure into excellence through systematic pressure. So the first iteration, the score jumped from a failing 25 to a decent 42. Not perfect, but we're climbing. The second iteration, we take the new feedback to chat GPT, and the score climbs again from 42 to an elite 46. Each cycle strips away more cliches, forces clearer thinking, and builds stronger arguments. We're literally training it into excellence iteration by iteration, and the results are measurable. For example, the original draft mentioned the word I only three times. The final draft uses it nine times. A 200% increase in personal voice. We can see that it has worked on that brand voice. But here's

where it gets really powerful. When my evaluators completely disagree. Gemini passed the draft that Claw failed miserably and Claw wouldn't let Chad GPT reach a 50. I didn't just pick a side and stop. I locked the two AIs in a debate cage and only one opinion survived. So my prompt to Gemini, Claus says you're wrong and this draft is terrible. Defend your score. And so I became a moderator or a judge in an AI courtroom. Gemini laid out his case, structural clarity, audience alignment, and Claw countered back with brand voice, authenticity issues back and forth until one AI convinced the other to change its mind. Using this method, you can create bulletproof consensus on what superior quality content actually means. So, let's see the final

transformation side by side. The original hook was big news. I'm trading the safety net for a launchpad. But the final hook, I'm leaving the corporate escalator to build something that scares me in the best way. One is a cliche everyone's heard. The other is a story only you could tell. The original described a career change, but the final version presents a thesis about pilot purgatory, tells a compelling story, and delivers concrete value. This isn't improvement. This is transformation. Force prompting is great for writing, but it's even better for reasoning because you get to see all of the different flaws and logic that the AI has in its original response to you. And you get to follow the conversation along and see just how many flaws there are. Then you realize that if you're accepting the first response from AI on a regular basis, then you're ingesting a lot of flaw logic. And so after three full rounds of critique and revision, we finally hit our target, a near-perfect score of 49 out of 50. But here's what most people miss. The system isn't even about the scores. It's about the transformation. We took generic, forgettable content and forced it to become memorable, strategic, and authentic. Chad GPT learned to be better

by being held to a higher human centric standard. But here's what this really means. The future isn't about finding the perfect AI tool or which one is the best or which one should I buy. It's about architecting systematic intelligence, forceprompting psychology, AI debates, breaking free from the contamination loop that everyone else is trapped in. If you want to get ahead using AI, it's about realizing that the first response does not equal the final response ever. Stop trusting a single AI's judgment about its own work. Build accountability. Create pressure. Force excellence through systematic critique. This is how you break past the ceiling that everyone else accepts. I really hope that you got value out of this video and that it helps you level up your experience whenever you're working with AI. And if you did, hit the like button, subscribe to the channel so that you don't miss any videos like this where I'm sharing my strategies to help you get better results with AI so that you can create better content, grow your business. And as always, take care, have a good day, and I'll see you in the next