How I Turn ChatGPT Into a “Multi-Brain” Genius With One Simple Prompt (And Why Most People Are Using AI Wrong)
I spent $180 on ChatGPT Plus last year and got mediocre results.
Then I discovered something that changed everything: a single prompt technique that makes ChatGPT think like five different experts arguing in a room instead of one confident idiot giving you the first answer that sounds good.
Note: The original text included: “Press enter or click to view image in full size” and “Ai Generated”.
I’m keeping that as a callout here since it isn’t part of the article body.
The difference? Night and day.
Before this, ChatGPT would confidently tell me my startup idea was brilliant. After? It tore apart my assumptions, exposed three fatal flaws I had not seen, and suggested an approach I would have never considered.
One gave me confidence. The other gave me clarity.
Guess which one actually made me money?
You open ChatGPT. You ask a question. You get an answer. You copy it. You move on.
This is how 90% of people use AI. And it is why their results are garbage.
Here is what actually happens behind the scenes: ChatGPT generates the most statistically probable response based on its training data. Not the smartest response. Not the most creative response. The most average response.
It is giving you the median answer from the internet. Which means you are getting median results.
Think about that for a second.
You are asking a system that was trained on billions of mediocre blog posts, generic tutorials, and recycled content to give you advice. What do you expect to get back? Genius insights?
No. You get the same advice everyone else gets. The same solutions. The same thinking.
And then you wonder why your work feels generic.
Here is the prompt that transformed how I use ChatGPT:
I need you to approach this problem from multiple expert perspectives.
First, analyze this as [Expert 1 - specific role/expertise].
Then, critique that analysis as [Expert 2 - opposing viewpoint].
Next, synthesize both perspectives as [Expert 3 - integrator role].
Finally, identify what all three experts missed as [Expert 4 - contrarian thinker].
My problem: [Your actual question]
Give me all four perspectives, then your final recommendation based on their debate.That is it. One prompt structure. Infinite applications.
Instead of getting one perspective, you get four experts debating. Instead of the first obvious answer, you get a considered analysis from multiple angles.
Let me show you why this matters with a real example.
Last year, I was deciding whether to build a mobile app or focus on web-first for a SaaS product.
I asked ChatGPT the normal way: “Should I build mobile or web first?”
It gave me a confident answer about mobile-first being the future, user engagement being higher on mobile, and how apps create stickiness.
Sounded smart. I almost committed $50,000 to mobile development.
Then I tried the multi-brain approach:
- Product Manager Perspective: Analyze market fit, user needs, development resources, and time to market. Recommended web-first because our target users were business professionals who work on desktops. Mobile would come later once we validated the core value prop.
- Mobile Developer Perspective: Argued that mobile development is more expensive, takes longer, and requires separate iOS and Android builds. Maintaining two codebases early stage would slow us down. Suggested a responsive web app first.
- Growth Marketer Perspective: Pointed out that web apps are easier to iterate, A/B test, and drive traffic to via SEO and content. App store discovery is brutal for new apps. We would spend months building something nobody could find.
- Contrarian Thinker Perspective: Questioned why we were even debating this. Our actual problem was not platform choice but whether anyone wanted what we were building. Suggested a landing page and wait-list before building anything.
The debate revealed something crucial: I was asking the wrong question.
I did not need to choose mobile or web. I needed to validate demand first. I built a landing page in three days. Got 200 email signups in two weeks. Then built a web MVP.
Saved $50,000 and six months. Because I let ChatGPT argue with itself instead of just agreeing with me.
Human brains are lazy. We grab the first answer that sounds reasonable and move on.
ChatGPT, by default, does the same thing. It generates a plausible response and stops.
But when you force it to take multiple perspectives, something interesting happens. It cannot fall back on the obvious answer because you explicitly asked for different viewpoints.
It has to actually think.
Not really think, obviously. It is still predicting tokens. But the output mimics genuine multi-perspective analysis because that is what you structured the prompt to produce.
You are essentially simulating a boardroom debate inside a single AI conversation.
The product manager optimizes for user value. The developer optimizes for feasibility. The marketer optimizes for growth. The contrarian questions whether any of it matters.
Just like in real companies, the tension between these perspectives surfaces insights that any single perspective would miss.
Senior Engineer vs. Security Expert vs. DevOps Lead vs. Cost Optimizer
I was choosing between PostgreSQL and MongoDB. The senior engineer loved Postgres for relational integrity. The DevOps lead warned about scaling challenges. The cost optimizer showed that managed Postgres was cheaper long-term. The debate saved me from a database migration disaster six months later.
SEO Specialist vs. Copywriter vs. Conversion Optimizer vs. Reader Advocate
Writing this article, actually. The SEO specialist wanted keyword density. The copywriter wanted narrative flow. The conversion optimizer wanted clear CTAs. The reader advocate called out when any of them made the content feel manipulative.
The result? Content that ranks and converts without feeling gross.
CFO vs. CMO vs. CTO vs. Customer
I was pricing a new product tier. The CFO wanted maximum margin. The CMO wanted competitive pricing. The CTO wanted to cover infrastructure costs. The customer perspective asked what value they actually got for the price.
We landed on a price 30% lower than my initial idea, but with clearer value communication. Revenue increased because more people bought in.
Power User vs. Beginner vs. Support Team vs. Future Self
Deciding which features to build next. Power users wanted advanced capabilities. Beginners needed simpler onboarding. The support team wanted features that reduced tickets. Future self asked which features would matter in two years.
We prioritized onboarding. Churn dropped 40%. Turns out keeping beginners was more valuable than impressing power users.
Ambitious Self vs. Content Self vs. Financial Self vs. Wise Elder
Yes, I use this for personal stuff too: career decisions, major purchases, life changes.
Should I take a high-paying job at a big company or join a risky startup? An ambitious self wanted the startup. Content self wanted work-life balance. Financial self wanted the salary. A wise elder asked what I would regret not trying.
The debate clarified what actually mattered to me. Not what I thought I should want. What I actually wanted.
Bad: “Analyze this from different perspectives.”
Good: “Analyze this as a Series A startup founder, a bootstrapped entrepreneur, and a corporate innovation lead.”
Specificity matters. Generic experts give generic answers.
You have to explicitly ask for opposition. Otherwise, ChatGPT will make all the experts agree.
“Now have Expert 2 directly challenge Expert 1’s biggest assumption.”
Force the conflict. That is where insight lives.
Four perspectives are useless if you do not synthesize them.
“Based on all four perspectives, what is the decision that balances all concerns?”
Make the AI integrate the debate, not just present it.
The experts do not know your situation unless you tell them.
Include your constraints. Your resources. Your timeline. Your goals.
“I have $10k budget, 3 3-month\
timeline, and this is my first product launch.”
(Kept as-is from the original text, including the odd line break/backslash.)
Context turns generic advice into specific guidance.
Multi-brain prompting is not magic. It has limits.
It fails for simple questions. If you just need a Python function or a definition, one perspective is enough. Do not overcomplicate.
It fails when you need deep expertise. ChatGPT pretending to be five experts is still less valuable than one actual expert with real experience. Use this for frameworks and thinking, not specialized knowledge.
It fails when you have not done your homework. If you do not understand your own problem, no amount of AI perspectives will save you. Garbage in, garbage out.
For those situations, I use different techniques:
- Simple questions get simple prompts.
- Deep expertise requires research and real human consultation.
- Unclear problems need clarification, not an AI debate.
Know when to use the right tool.
Here is where it gets really powerful.
You can create custom GPTs (or save system prompts) that embody specific expert panels for your work.
I have one called “Startup Council” with these permanent experts:
- Sarah (Cautious CFO who hates risk)
- Mike (Aggressive growth hacker who loves risk)
- Alex (Technical architect who sees implementation complexity)
- Jordan (Customer advocate who calls out feature bloat)
Every major decision goes through my Startup Council. They know my context. They know my business. They debate with my constraints in mind.
This is not just a prompt. It is a personal advisory board that costs $20/month instead of $20,000 in consulting fees.
You can do this for anything.
Writing advice? Create a panel of your favorite authors’ perspectives.
Design feedback? Create a panel of designers with different philosophies.
Code review? Create a panel of senior engineers with different priorities.
The AI becomes a reflection of the diverse thinking you want to cultivate in yourself.
Here is the real benefit: using multi-brain prompting trains you to think this way naturally.
After six months of forcing ChatGPT to debate itself, I started doing it in my own head. Automatically considering multiple perspectives. Challenging my first instincts. Looking for what I am missing.
The AI is not replacing your thinking. It is teaching you how to think better.
This is what people miss about AI tools. They are not just productivity hacks. They are cognitive training wheels.
You learn to structure problems. To separate concerns. To integrate competing priorities. To think systemically instead of linearly.
Eventually, you do not need the prompt anymore. You have internalized the framework.
But you keep using it anyway, because why would you stop? It is still faster and more thorough than doing it solo.
Multi-brain prompting will make you uncomfortable.
Because it exposes flaws in your thinking. It challenges assumptions you were attached to. It suggests approaches that feel risky or wrong.
Most people quit after the first try because they do not like what the debate reveals.
That is exactly when you should keep going.
The discomfort is the signal. It means you are getting perspectives you would not have considered. Ideas that challenge your worldview. Insights that make you rethink everything.
If the AI debate just confirms what you already thought, you did not push hard enough.
Make it argue. Make it disagree. Make it uncomfortable.
That is where growth happens.
What decision are you facing that you have already made up your mind about?
Not a simple choice. A real decision. The kind where you feel pretty confident about the answer, but there is a nagging feeling you might be missing something.
Take that decision. Run it through the multi-brain prompt. Let four experts tear it apart from different angles.
I guarantee you will discover something you had not considered. A risk you overlooked. An assumption that does not hold. An alternative that is actually better.
Or you will confirm your decision with 10x more confidence because it survived the debate.
Either way, you win.
The only losing move is staying stuck in single-perspective thinking while pretending ChatGPT is a magic oracle.
It is not an oracle. It is a mirror. A very sophisticated mirror that reflects whatever quality of thinking you put into it.
So here is my challenge:
- Stop asking ChatGPT for answers. Start forcing it to debate.
- Stop accepting the first response. Start demanding multiple perspectives.
- Stop using AI to feel smart. Start using it to actually become smarter.
What is the first decision you are going to run through your new multi-brain filter?
If you enjoyed reading, be sure to give it 50 CLAPS! Follow and don’t miss out on any of my future posts — subscribe to my profile for must-read blog updates!
Thanks for reading!