Fundamentally Changing the 'Quality of Thought' in AI: The Battle Between Linear OS and Non-Linear OS Thinking
The prompt introduced this time
# The Battle Between Linear OS and Non-Linear OS Thinking
When you ask an AI for something, have you ever had an experience like this? 'It answers properly, but it feels somehow lacking,' 'This isn't what I wanted,' or 'It just gives safe, generic answers that I've read somewhere before.' If you've ever felt that way, this prompt should really hit home.
Instructions (prompts) for AI are not just 'commands.' Depending on what words you use and what structure you provide, the 'breadth of thought' that the AI unfolds internally changes completely. This prompt was created to confront that difference head-on; it is, in a sense, an 'AI thought experiment device.'
The key points of this prompt!
At the heart of this prompt is a confrontation between two ways of thinking: 'Linear OS' and 'Non-Linear OS.' It might sound a bit difficult, but in short, it means this.
'Linear OS' is how an AI moves when it tries to provide the correct answer in the shortest distance. It is a straight-line thinking pattern that prioritizes efficiency, thinking, 'I will answer this question like this.' Think of it as a veteran office worker who quickly provides answers according to the manual. It is fast and accurate, but it is difficult to generate discoveries from unexpected angles.
On the other hand, 'Non-Linear OS' is a way of moving that involves churning through meanings before providing an answer. It generates answers through a process of taking things apart and reassembling them while asking itself, 'What is the true meaning of this question?' or 'What happens if I look at it from a different perspective?' It might be closer to how a poet or philosopher faces a question.
The most ingenious part of this prompt is that it does not make the AI 'execute one or the other,' but rather 'makes it execute both and coldly compare and judge them.' By placing the AI in the persona (role) of a 'judge,' it elicits 'meta-thinking,' which rarely happens normally, as it oversees and evaluates its own output. This is a very advanced technique in the world of prompt engineering (instruction design for AI).
What is even more striking is the mechanism called 'failure condition design.' If the task is too simple or the Non-Linear OS answer is just a paraphrase of the Linear OS answer, the AI is designed to spontaneously raise the difficulty level or restart its thinking. This is an advanced technique for embedding 'self-inspection rules' into the AI, which makes it easier to guarantee the quality of the output. The constraint of 'forbidding a draw through a compromise' is the same, ensuring the AI cannot escape into an ambiguous landing.
How to actually use it: Explanation of user variables
This prompt has three 'blank spaces' that the user fills in themselves.
First, in the 'Specific task to pit against each other,' you write the theme or question you want the AI to think about. For example, you input things you are genuinely worried about in your daily life, such as 'How can I make morning chores easier?', 'How to get children to develop a reading habit?', or 'Tips for getting along well with neighbors.'
Next, in the 'Linear OS prompt,' you write a simple, linear instruction that you have tried for that task. A normal question format, such as 'Tell me 5 tips to make morning chores more efficient,' falls under this category.
Finally, in the 'Non-Linear Circular OS prompt,' you write an instruction designed to think more deeply about the same task. This is where you write in a way that questions the premise itself, such as 'I want you to give me an answer after questioning what I truly value as someone who wants to make chores more efficient.'
Try using it in these situations!
The first is a situation where 'you have an answer, but for some reason, you aren't convinced.' You have to make a decision at work, but the more you look into it, the more confused you get. At times like that, if you pit your own thinking against both 'Linear' and 'Non-Linear' approaches, you can see where you are getting stuck. In the process of the AI comparing and judging both, the core of the question that you hadn't been able to verbalize yourself may emerge.
The second is a situation where 'you are thinking about a plan or proposal, but you can only come up with cliché ideas.' You can use it for brainstorming new service ideas or setting themes for school research projects. By placing 'normal questions' and 're-questioning type questions' side-by-side, the AI may open up perspectives you hadn't thought of.
The third is a situation where 'you want to persuade someone, but logic alone doesn't hit the mark.' When consulting with parents, proposing to friends, or expressing opinions at work. It is a common problem that just lining up correct things doesn't get the message across. By using this prompt to have your arguments verified from both 'Linear' and 'Non-Linear' perspectives, you may get hints on how to phrase things so they reach the other person's emotions.
One-point advice
With this prompt, the quality of the 'task' you input directly translates to the quality of the output. The design of this prompt comes to life the more you bring in 'difficult problems that even you don't know how to think about,' rather than 'questions that are easy to answer.' Instead of 'What is 1+1?', try inputting a question like 'What are the conditions for a person to feel happy?'
Also, if you find it difficult to write a 'Non-Linear OS Prompt' yourself, it is perfectly fine to start by preparing only a 'Linear OS Prompt' and having the AI automatically generate the other side (the Non-Linear OS). This prompt itself is designed with such flexible usage in mind.
Summary
For those who have been thinking, 'I want the AI to think more deeply' or 'I want truly useful insights, not just safe answers,' this prompt will serve as a breakthrough. As a first step toward using AI not as a 'machine that provides answers' but as a 'partner that enhances the quality of your thinking,' please try bringing your most difficult problem to it.