The MAD HATTER CHRONICLES™

The AI Advice Trap: Better Answers to the Wrong Business Problem

Thomas Minieri • May 5, 2026

AI may be one of the most useful business tools ever created. It can brainstorm offers, critique a landing page, suggest marketing ideas, write emails, analyze competitors, explain financial concepts, generate sales strategies, and give you twenty ideas before your coffee gets cold.


But there is a dangerous assumption hiding underneath all that usefulness:

If AI gives me a good answer, I must be getting closer to solving my problem.


Not necessarily. Because AI can give you an excellent answer to a question you never should have been asking in the first place. And for entrepreneurs, that may be the bigger danger.


When the Question Already Contains the Mistake

Imagine your business isn't generating enough sales.

You open AI and ask:

“How can I improve my Facebook ads?”


Within seconds, you have suggestions for new hooks, better targeting, stronger calls to action, creative testing, retargeting campaigns, landing-page improvements, and fifteen new ad concepts. The advice may be perfectly reasonable. But what if your Facebook ads aren't the problem?


Maybe customers don't understand the offer. Maybe your pricing doesn't make sense. Maybe your business looks identical to every competitor. Maybe leads are coming in but your sales process is weak. Maybe customers buy once and never come back. Maybe the economics of the business simply don't support the advertising costs required to acquire customers.


AI can help you optimize the thing you asked it to optimize. That doesn't mean you chose the right thing.


The Streetlight Effect Comes to AI

There is a psychological bias known as the Streetlight Effect. The classic story involves someone looking for lost keys underneath a streetlight—not because the keys were lost there, but because that is where the light makes searching easier. The term is used more broadly to describe our tendency to search where information is easiest to examine rather than where the answer is most likely to exist.


Entrepreneurs do this constantly.

Marketing is visible, so they diagnose a marketing problem.

Sales are down, so they diagnose a sales problem.

Traffic is low, so they diagnose a traffic problem.

Competitors are growing, so they diagnose a competitive problem.

Then they bring that diagnosis to AI.

And suddenly the streetlight gets much brighter.


Instead of five possible solutions to the wrong problem, you now have fifty. That can actually make the distortion stronger because activity feels like progress. You are testing prompts, rewriting copy, generating strategies, researching funnels, producing content, and making changes. You are doing a tremendous amount of work. You may simply be digging in the wrong place.


AI Usually Starts With the World You Give It

There is another problem. When you ask, “How do I improve my marketing?” you have already told AI something important: marketing is the problem. The question contains a diagnosis. Unless that assumption gets challenged, the conversation can proceed entirely inside it.


Research into language-model sycophancy—the tendency of models to become overly agreeable or reflect a user's viewpoint—makes this worth taking seriously. A 2026 CHI study found that additional interaction context can increase some forms of sycophancy, while separate research published in Nature found that optimizing models toward greater warmth can also increase sycophantic behavior under some conditions.


That doesn't mean AI will always agree with you. It doesn't. It means you shouldn't confuse a confident, intelligent-sounding conversation with an independent diagnosis of your business. AI knows what you tell it. Your business contains thousands of things you haven't told it. And perhaps most importantly, you decide which problem enters the prompt. If your perception is distorted before the conversation begins, AI can inherit the distortion.


Generic Advice Can Still Be Good Advice

There is nothing inherently wrong with mainstream business advice. Improve your offer. Know your customer. Test your advertising. Create good content. Follow up with leads. Watch cash flow. Differentiate yourself. Measure results.


Most of that is sensible. The problem is relevance. A doctor could give you a list of perfectly legitimate medications. That would not tell you which one you need. Business advice works the same way. The best strategy isn't merely a strategy that works. It is the strategy that addresses the constraint currently preventing your business from moving forward. That requires diagnosis before prescription.


This Is Where Human Strategy Still Matters

This is one of the reasons we built Lemonade Maker® Strategies differently. Entrepreneurs often arrive believing they already know their problem.

“I need marketing.”

“I need more leads.”

“I need social media.”

“I need SEO.”

“I need a better funnel.”

Maybe.


But before jumping to the solution, we want to understand the business.

What are you selling? Why would someone choose it? Where are customers getting stuck? What have you already tried? What are the economics? What is happening competitively? What assumptions are you making? What evidence actually supports your diagnosis?


Sometimes the entrepreneur needs marketing.

Sometimes the entrepreneur needs a different offer.

Sometimes the problem is positioning, pricing, sales, retention, operations, customer value, or the business model itself.

And sometimes the most valuable strategic advice is telling an entrepreneur:

Stop fixing that. That isn't your problem.


AI can be extraordinarily useful once the problem is clearer. It can accelerate research, generate alternatives, challenge an idea, organize information, simulate objections, and help you think.

But the stronger mental model is not:

Problem → Ask AI → Get solution

It is:

Poor result → Diagnose the real constraint → Ask better questions → Use AI and expertise to explore solutions → Test against reality

AI belongs in the process.

It should not become the process.


The Gambit

The next time you are about to ask AI how to solve a business problem, don't begin with:

“How do I fix this?”

Ask something more dangerous:

“What if I'm wrong about what the problem is?”

Then go looking somewhere other than underneath the streetlight.

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