Like many of you, my feed is full of "AI business gurus" selling step-by-step blueprints. But if the formula is so good, why sell it?
I decided to check the actual data on these business models. The numbers are grim:
[80-90% of e-commerce sites fail.]
[The top 3% of YouTube channels get almost all the views.]
[90% of AI projects fail to reach production.]
But I was still interested in the idea of using AI as a co-founder to build something useful. I didn't want a generic idea; I wanted a viable product.
The Experiment:
I prompted six models: Kimi, DeepSeek, GLM, GPT, Claude, and Copilot. I asked for high-profit, low-risk business ideas. Then, I tested their logical consistency. I challenged their outputs and acted as if I knew better.
The Results were fascinating:
Claude, GPT, and Copilot: The moment I challenged them, they apologized and completely changed their answers to agree with me, even when my logic was flawed. This is classic RLHF (Reinforcement Learning from Human Feedback) sycophancy—they are trained to please the user.
Kimi and GLM: These two models held their ground. They argued back with actual data. If I made a strong counter-point, they adapted and developed the idea further. If I was wrong, they corrected me with facts.
The Takeaway:
If you are using AI to build a business, you cannot trust a model that just says "You are absolutely right!" to everything. You need reasoning models that will challenge your assumptions, find flaws in your logic, and defend their own.
I ended up using this insight to build a tool that solves a real problem for creators. I didn't just ask AI for a business; I used AI reasoning to validate a business.
Have you noticed how easily LLMs fold when you push back? Which model do you trust for actual logical reasoning?
