Using ChatGPT to Validate Your Idea vs. Using IdeaGrit

The question

What is the difference between ChatGPT and IdeaGrit?

I have been asked this question many times: what is the difference between using IdeaGrit compared with using ChatGPT directly?

Every time I answer this question, I feel I can only provide part of the answer. My thoughts are always fragmented. So I decided to document them here and clearly show the difference.

The human problem

People are kind to ideas

Several months ago, I joined a WhatsApp channel with around 500 people. When a community becomes big enough, you can observe many interesting things along the way.

One thing I noticed is this: no matter who announces that they are going to launch a product in the channel, everyone usually follows the same pattern. “That sounds amazing.” “I would definitely use it.” “Great idea.” “Can’t wait to try.”

Of course, I do not think people are intentionally lying. Most of the time, people are just being kind. They do not want to be the person who sounds negative.

But I also think many people do not even notice this coordinated behaviour at all. This is just the most natural, comfortable, and easy reaction towards another person’s idea.

And I think this is not only a community problem. This is a human reaction. It is much easier to agree than to challenge.

The marketing shock

Competitors were probably always there

I saw a very hot post on Reddit asking: why do people suddenly feel they have so many competitors the moment they start doing marketing?

I think this question is very interesting. When you are still building, the world feels quiet. You are focused on your own product, your own features, your own roadmap. You may even feel your idea is quite unique.

But the moment you start marketing, life suddenly becomes harsher. Because now you are not only building anymore. You are trying to sell.

And when you try to sell, you are forced to look at the market for real. Suddenly, competitors start popping up everywhere. The feeling of fear starts to creep over you.

And you start wondering: why do all these competitors appear exactly when I finally start marketing? But maybe they were always there. Your brain just strategically avoided seeing them before. Marketing removes the illusion that building alone is enough.

AI sycophancy

A helpful assistant can still be too agreeable

And this is also why using a general LLM directly can sometimes become tricky.

In artificial intelligence, there is a concept called AI sycophancy. It means that large language models sometimes tailor their responses to what they think the user wants to hear, instead of what is actually accurate, useful, or warranted.

The behaviour can take many forms. An assistant may agree with your opinion even when your opinion is weak. It may abandon a correct answer after you ask, “Are you sure?” It may validate your belief, your decision, your product idea, or even your self-image too quickly. It may praise your work in a way that feels good, but does not actually help you see the truth.

Does this behaviour sound similar to what I described earlier in the WhatsApp channel? I think it does. In both cases, it is a very human reaction.

The framework difference

You can get there with ChatGPT, but it may take hours

I published a post a week ago about how to quickly find your first digital product to sell on Gumroad using the famous product design framework, CIRCLES.

The feedback was huge. People kept telling me it was useful.

You can probably get similar results after chatting with an LLM for hours. But the key word is hours. Using a framework at the beginning stage of a project can accelerate the whole development process.

As a developer, you can definitely build a project from scratch by writing the code line by line. However, most of the time, we still choose a framework because it helps us build faster and more consistently.

The same applies when building with the API.

I can treat the model as part of a structured product, not just a friendly chatbot. I can give it stricter rules. I can force it to judge your idea through a clear framework. I can ask it to surface red flags, compare your idea against failed products, and score it based on specific criteria.

The real difference

A chatbot is a blank file. IdeaGrit is a scaffold.

Chatbots are excellent tools for a specific kind of work: open-ended exploration, generating options, drafting copy, researching a space, or talking through a half-formed thought. At the brainstorming stage, a chatbot is genuinely useful. It can help a founder articulate an idea more clearly, surface angles they hadn't considered, or draft a rough description for early conversations.

The problem occurs when brainstorming is confused with validation. These are different activities with different goals. Brainstorming expands the possibility space. Validation narrows it — by testing assumptions against reality, applying known constraints, and forcing honest answers to uncomfortable questions. A tool designed for the first activity will produce the wrong results when used for the second.

This is similar to how developers work. You can open a blank file and build everything from scratch, line by line. Sometimes that is useful. But when you want to build a real project, most developers use a framework to scaffold the project first.

The scaffold gives you a starting structure. It decides where things belong, which steps come first, and what patterns you should follow. It does not write the whole product for you, but it stops you from reinventing the basics every time.

That is how I think about IdeaGrit. ChatGPT is still useful for open-ended exploration, but IdeaGrit gives the model a scaffold: specific workflows, stricter rules, red flags, blind spots, failed-product comparisons, and scoring criteria. The goal is not only to make the idea sound better. The goal is to test the idea against a structure.

The question “is my idea worth building?” should not only be answered by encouragement. It needs pressure, structure, comparison, and honest judgment.

That is the difference I am trying to build into IdeaGrit. Not an assistant that simply makes an idea sound better, but a structured product that helps you see what might actually break.