The Voting Trick That Eliminates 67% of AI Errors

The Concept: The AI as Your Unbiased Board of Advisors

Jessica Palmer was sitting in her car outside her daughter’s soccer practice, hands shaking as she stared at her phone.

She’d just gotten off another soul-crushing call with her biggest client; the healthcare startup that represents 40% of her boutique agency’s revenue.

They wanted “just a quick revision” on the brand strategy.

The fourteenth revision.

This week.

The math was eating her alive: $12,000 monthly retainer, but she’d logged 67 hours last week alone on their account. That’s $44 per hour. Her junior contractor makes more than that!

“I should fire them,” she mumbled to herself.

But then thought “I can’t fire them. The mortgage. The kids’ tuition. My team’s salaries.”

This is exactly the kind of decision that keeps agency owners awake at 3 AM. The kind where being wrong could mean everything. Losing your business or losing your sanity.

So Jessica did something different.

Instead of agonizing alone or asking her wine club friends (who’d all say “dump them, girl!”), she assembled an unbiased board of advisors. Five independent strategists who couldn’t influence each other, couldn’t groupthink, couldn’t be swayed by one persuasive voice.

Her board of advisors? The same AI, consulted five separate times, with no memory between sessions.

It’s called the Self-Consistency Method, and it’s based on a powerful principle: if multiple independent analyses all reach the same conclusion, you can trust that conclusion. It’s how academic researchers validate findings, how doctors seek second opinions, and how smart CEOs make bet-the-company decisions.

Instead of trusting AI’s first answer (which could be random, biased, or oversimplified), you gather multiple independent opinions by running the same prompt in completely separate sessions. The consensus that emerges? That’s your truth.

Let me show you how it works.

How It Works: The Self-Consistency Method

The Self-Consistency Method in AI prompting is a technique you can use to improve Large Language Model (LLM) accuracy.

Step 1: Write Your Prompt

Write one clear, specific prompt that includes context and asks for both recommendation and reasoning. This is your “board meeting agenda.”

Step 2: Conduct Private Advisory Sessions.

Open a brand new chat session and ensure memory is turned off (this is crucial).

Paste your question and get the complete response.

Open a second brand new chat session and ensure memory is turned off (no memory of previous discussion).

Paste your question and get the complete response.

Repeat this process several more times times for truly independent perspectives.

Step 3: Find the Consensus.

Now it’s time to observe the output from each session.

What do most advisors recommend?

What reasoning appears repeatedly?

Step 4: Trust the Pattern.

The recommendation that emerges from multiple independent analyses is statistically far more likely to be correct.

Note: You can boost the performance by conducting private advisory sessions using different AI platforms. So you could run one session in ChatGPT, one in Google’s Gemini, and a third in Anthorpic’s Claude.

Comparison: “The Panic Decision” vs. “The Board Consensus”

Let’s watch Jessica work through her client crisis.

The Panic Decision (Single Query)

In this example, Jessica only asks once, desperately looking for guidance.

I am Jessica Palmer, the owner of a boutique agency, and I’m sitting outside my daughter’s soccer practice contemplating whether to fire my biggest client—a healthcare startup that represents 40% of my revenue but has demanded fourteen revisions this week alone on their brand strategy. Despite paying a $12,000 monthly retainer, the client’s excessive demands have reduced my effective hourly rate to $44, less than what I pay my junior contractor, leaving me torn between protecting my financial stability and preserving my sanity in a decision that could make or break my business.

Should I fire the client who pays me $12K/month but is driving me crazy with demands? Answer using one paragraph.

Now, before you look at the AI response, I want to tell you something that’s really important.

NEVER ask the AI to answer YES or NO in these situations. The reason is because it’ll stifle the AI’s creativity in responding.

The better approach is to just ask for an answer in one paragraph, or leave the question without an output limit because sometimes unrestricted verboseness by the AI gives a better answer.

Here’s the response by the AI using Anthropic’s Claude Sonnet 4:

Fire the client—your sanity and business sustainability are worth more than short-term revenue security. At $44 per hour, you’re not just undervaluing your expertise, you’re creating an unsustainable business model that will burn you out and prevent you from serving better clients who respect your time and processes. The mental and emotional toll of dealing with excessive demands will inevitably affect your other work and personal life, while the precedent you’re setting by accepting this treatment will attract similar problematic clients. Use this as an opportunity to restructure your business: implement clear revision limits in future contracts, raise your rates to reflect your true value, and focus on attracting 2-3 clients who pay fairly rather than one who monopolizes your time and energy. The short-term financial hit will be offset by improved work quality, better client relationships, and the ability to scale your business properly—plus you’ll likely discover that replacing 40% of your revenue with respectful clients is easier than you think once you’re not drowning in endless revisions.

So the single response was fire them!

Now let’s implement the Self-Consistency Method.

The Board Consensus (Self-Consistency Method)

I’m going to use different AI models for each of the responses. You don’t have to, but it will lead to increased quality.

Anthorpic’s Claude Sonnet 4:

I am Jessica Palmer, the owner of a boutique agency, and I’m sitting outside my daughter’s soccer practice contemplating whether to fire my biggest client—a healthcare startup that represents 40% of my revenue but has demanded fourteen revisions this week alone on their brand strategy. Despite paying a $12,000 monthly retainer, the client’s excessive demands have reduced my effective hourly rate to $44, less than what I pay my junior contractor, leaving me torn between protecting my financial stability and preserving my sanity in a decision that could make or break my business.

Should I fire the client who pays me $12K/month but is driving me crazy with demands? Answer using one paragraph.

You should fire this client because they’re systematically destroying your business model and personal well-being while setting a dangerous precedent that devalues your expertise. At $44 per hour, you’re essentially subsidizing their indecisiveness and poor planning with your premium-level skills, which not only undermines your profitability but also prevents you from serving clients who respect your time and value your strategic input. The psychological toll of endless revisions and unreasonable demands will inevitably affect the quality of work you deliver to other clients, potentially damaging your reputation and long-term business prospects. While losing 40% of your revenue feels terrifying, this client is actually costing you money when you factor in opportunity costs, stress-related impacts on your other work, and the precedent they’re setting for how clients can treat your agency. Use this moment to restructure your contracts with clear revision limits, raise your rates to reflect your true value, and focus on attracting clients who view you as a strategic partner rather than an on-demand creative service—your future self and your family will thank you for choosing sustainable growth over short-term financial security.

The AI suggests that Jessica should fire them, restructure future contracts with clear revision limits, raise her rates, and change which clients she goes after (e.g., a strategic partner vs. an on-demand creative service).

OpenAI GPT-5

I am Jessica Palmer, the owner of a boutique agency, and I’m sitting outside my daughter’s soccer practice contemplating whether to fire my biggest client—a healthcare startup that represents 40% of my revenue but has demanded fourteen revisions this week alone on their brand strategy. Despite paying a $12,000 monthly retainer, the client’s excessive demands have reduced my effective hourly rate to $44, less than what I pay my junior contractor, leaving me torn between protecting my financial stability and preserving my sanity in a decision that could make or break my business.

Should I fire the client who pays me $12K/month but is driving me crazy with demands? Answer using one paragraph.

If the client’s demands have pushed your effective rate below your costs and are draining your bandwidth and morale, you should move to reset the relationship immediately—and be prepared to part ways if they won’t accept boundaries. Present a clear scope with capped revisions (e.g., two rounds), defined turnaround times, and out-of-scope hourly rates; tie extra iterations to change orders, and introduce a premium “rapid-response” add-on if they want unlimited access. Communicate that this protects quality and timelines and that continuing at the current pace is unsustainable. Give them a short window to agree; in parallel, line up replacement revenue (warm leads, upsells to other clients, short-term projects) and reduce overhead risk. If they won’t honor the new terms, let them go—because keeping them undermines profitability, team health, and your ability to serve better-fit clients, which is ultimately a bigger risk than losing 40% of revenue on bad economics.

OpenAI’s response is interesting. Instead of quickly suggesting to fire the client, it offered other ways to handle the situation. Some of its ideas matched what Claude suggested, like putting a limit on revisions. But it also came up with cool solutions maybe Jessica hadn’t thought of, such as setting specific turnaround times and offering a premium “rapid-response” option for clients who want unlimited access.

Google Gemini 2.5 Pro:

I am Jessica Palmer, the owner of a boutique agency, and I’m sitting outside my daughter’s soccer practice contemplating whether to fire my biggest client—a healthcare startup that represents 40% of my revenue but has demanded fourteen revisions this week alone on their brand strategy. Despite paying a $12,000 monthly retainer, the client’s excessive demands have reduced my effective hourly rate to $44, less than what I pay my junior contractor, leaving me torn between protecting my financial stability and preserving my sanity in a decision that could make or break my business.

Should I fire the client who pays me $12K/month but is driving me crazy with demands? Answer using one paragraph.

Based on your situation, you should fire the client, but only after attempting one final strategic pivot. The core issue isn’t the $12,000 retainer; it’s the unprofitable effective hourly rate of $44 and the immense strain on your well-being. Before ending the relationship, present the client with a revised contract that explicitly defines the scope, limits the number of revisions to a reasonable number (e.g., two or three rounds), and clearly states that any additional work will be billed at a premium hourly rate. This action does one of two things: it either transforms the unprofitable relationship into a sustainable and respectful one, or it provides a clear, business-based justification for parting ways if they refuse. While the immediate 40% revenue loss is intimidating, shedding a client who drains resources and morale is a necessary step to free up your capacity to find and serve multiple, more profitable clients who value your expertise, ensuring the long-term health and sanity of your business.

Gemini doesn’t jump straight to firing the client either. It suggests trying one last strategic pivot, and if that doesn’t work, then you fire them.

Responses Compared

Jessica has now asked three times (and even using different AI models) what she should do with her client.

According to the output, two of the three AI models suggest the same thing: don’t fire the client right away. Instead, try to redefine the scope and boundaries the relationship first. If that doesn’t work, then it’s time to let them go.

What you or Jessica do with these different opinions is up to you, but at least you’ve got several perspectives to help you feel more confident about your decision.

When to Deploy Your Board of Advisors

In my opinion, you should reserve using this method for decisions where being wrong is expensive:

Firing/Hiring Decisions: When the wrong choice could destroy culture or revenue.

Pricing Strategy Changes: When you need confidence to have difficult conversations.

Major Platform Investments: When you’re committing significant time or money to new tools/platforms.

Service Model Pivots: When changing how you deliver value to clients.

Brand Positioning Decisions: When the message will define you for years.

Growth Strategy Choices: When you can only pursue one path and need to choose wisely.

Your Next Board Meeting

Tonight, after your kids are asleep and your laptop’s open, think about that decision that’s been keeping you up at night. The client situation. The pricing change. The strategic pivot.

Don’t ask your wine club (they love you too much to give it to you straight). Don’t trust just one AI response (it might be having an off day).

Build your board. Ask your question five times in five separate sessions. Look for where they agree.

The truth isn’t in any single answer. It’s in the pattern that shows up when multiple independent views point to the same thing.

That’s not artificial intelligence. That’s collective intelligence.

And if you’re a boutique agency owner juggling everything alone, it might just be the board of advisors you’ve always needed but could never afford.

Until now.