Introduction

I was in class during college when my classmate suddenly took out his phone. He entered something into ChatGPT, and then I saw the response begin to print out.
Custom instructions:

• Do not paraphrase quotations.
• Provide a single, coherent paraphrased version of the text:
• Line by line.
• Paraphrased text: Words appearing on the screen as if they were truly thinking in real time.

That moment felt different. I was completely captivated. I needed to find out exactly how it accomplishes that. How does it simply know what to say?

I followed the trail down the rabbit hole. What I discovered completely changed the way I use AI.

Here’s What AI Actually Does

Let me be honest with you: AI isn’t thinking. It’s not about understanding things in the way your mind does. It’s accomplishing something far simpler yet far more advanced at the same time; it’s identifying patterns.

Consider it this way. When someone begins with “Once upon a…” your brain naturally completes it with “a time.” You’ve heard that expression countless times. You have grasped the pattern. Your brain anticipates what will happen next since it usually does happen next.

That’s precisely what AI does. It has learned billions of patterns from an extensive collection of words.

When I use ChatGPT, it looks at every word I type and uses all the data it learned during training to predict the most likely next word. That is what it does again. Again. till you’ve finished writing a paragraph.
The humorous part? It is not actually “thinking” about what it is writing. It’s just finalising patterns. predicting statistically likely words.

Why It’s Really Important

Your approach to dealing with AI will drastically change if you understand that idea.

I used to think AI would just comprehend what I was saying, to understand what I meant. But now I see that it doesn’t understand anything at all. It involves spotting trends. I’ll create patterns that aren’t really beneficial to me if I’m too ambiguous or confusing.

The largest change is this one. The idea that “AI would just figure this out” gave way to the idea that “I need to be very, very explicit with what I tell AI.”

And the outcomes? Totally different. Day and night are not the same.

The Aspect of Prompts That No One Can Accurately Explain

Everyone talks about “prompt engineering” as if it were a mystical ability. It’s not. It’s just being explicit.

After much trial and error, I discovered that unclear prompts lead to poor outcomes. Detailed prompts yield results that are truly useful.

When I ask AI to “write about marketing,” for example, it provides me with a generic and worthless response. In reality, I can’t use it.

However, when I give it a thorough context—”write a 300-word intro to email marketing for small business owners who have never done it before, explain why it matters for their revenue, and give one specific example”—all of a sudden, I have something that works.

The disparity is absurd.

My Master Prompt Method (This Really Does Work)

I’ve discovered a way to save a ton of time. I let AI write the ideal prompt for me before attempting to do it myself.

This is how it operates. Assume I wish to create a picture. I can’t put all the specifics into words, but I have a general understanding.

I’m certain that I want a 3D animated girl seated at a desk with low lighting and a midnight atmosphere. I can’t, however, explain every single component.

“I want to produce a scene where a girl in a 3D animated manner is seated around the desk with dim lighting, the camera towards her, the bed in the scene, and the table,” is how I provide AI with the fundamental information. I’d like a proper, all-night scene.”

“Analyse the fundamental information I supplied you and write me a full-fledged prompt,” I then instruct it. Every important detail should be included, including the lighting, backdrop, character, clothing, hair, cosmetics, desk colour, background items, and colour of the drapes.

And AI develops my preliminary concept into this thorough prompt with all the particular components. I then really create the image using that specific request.

AI had to consider every single detail, which is why the photographs are so much superior.

Related: AI Image Generators Explained: Midjourney vs DALL-E

The blunders I’ve Actually Made

When it comes to AI, I’ve made a few stupid blunders. The kind that gave me lessons.

One of the most significant: I requested a list of keywords with search volume information from AI when conducting keyword research. It provided me with a list that indicated some terms had about 100,000 monthly searches.

I nearly made use of the information. I caught myself and double-checked it using SEMrush and Google Keyword Planner.

zero volume of searches. Zero, not 100,000.

I received the response from AI with complete assurance. It sounded correct. However, it was entirely incorrect.

At that moment, I came to the crucial realisation that AI doesn’t give a damn if something is true. It just uses patterns it has learned to determine what statistically sounds correct.

It’s not attempting to deceive me. It only involves finishing designs. Occasionally, the pattern it completes is entirely imaginary.

The Issue with Image Generation (And How to Solve It)

I encountered another problem when I began using AI to create images. It would simply copy the reference image I gave it to fit the style. Exactly.

I was not inspired by it. not using the style. precisely reproducing the image.

I got annoyed until I realised what was happening. I wasn’t sure how to use the signal (the reference image) that I was giving the AI.

Now I’m being clear. “Use this reference image as style inspiration, but do not copy this image,” I instruct it. Avoid imitating the style closely. Make something unique based on the style you see here.

Being honest about it actually works. These days, when I give AI reference photographs, it uses them as inspiration rather than merely copying them.

The Problem That Truly Affects Me

When beginners trust AI without doing any cross-verification, it greatly irritates me.

AI, however, aims to satisfy you. It won’t let you know you’re mistaken. It won’t say, “Actually, I don’t know this, and I’m making it up.” It simply provides you with a confident response.

When you’re working on something important, this is risky. a project requiring precise data. You can’t simply believe what AI says.

Every time, I double-check. Always. Data, computations, facts, everything.

Additionally, instruct AI to be honest and brutal. Say something like, “Be honest about this” or “Tell me what you’re not sure about.” It modifies the outcomes. When you explicitly encourage AI to be more cautious, it does so.

Related: How to Use ChatGPT for Content Writing: Complete Guide

How to Really Get Better Results

The secret isn’t hard to figure out. In a few areas, it’s consistent:

First, be clear. Not unclear. Specific. Tell AI everything you want, why you want it, and what format you need it in.

Second, try the master prompt method. If you don’t know how to ask for something specific, ask AI to make a detailed prompt for you based on basic information. Then use that.

Third, check everything twice. Especially facts. Especially numbers. Don’t believe AI just because it sounds sure of itself.

Fourth, make changes to everything. AI gives you a place to start. It’s not done yet. You need to make it your own, check the facts, and make sure it really fits what you need.

People Ask Me About This

Does AI really understand what I’m saying?
No. It’s seeing patterns. It doesn’t know what you mean. It knows how words are related to each other in terms of statistics.

When I ask the same question twice, why does AI sometimes give me very different answers?
It uses probability to guess what the next word is most likely to be. Different ways of saying things change the probability pathways. So even if you meant the same thing, the answer could be different.

Can I just believe AI data for research?
No. Check it again. AI makes things up and sounds sure of itself when it does. This is especially true of numbers, statistics, and facts.

Is there a prompt that works for all tasks?
No, different jobs need different amounts of detail and types of instructions. But the rule is always the same: be clear and specific about what you want.

Should I tell AI to be honest?
Yes. Does what it says it will do. When you say “Be honest about what you’re sure and unsure about,” it changes how it responds.

What This Really Means for You

You stop thinking of AI as magic and start thinking of it as a tool once you realise that it’s just a very advanced way of finding patterns.

That’s the real change.

You use it for what it’s good at: coming up with new ideas, writing drafts, and getting over writer’s block. You don’t use it for things it’s not good at, like making decisions or finding out facts without checking them.

You become clear and specific when you talk to it because you know it can only work with what you give it.

You check everything again because you know it can sound sure of itself when it’s not.

And you really think about it. You have the knowledge. You decide what to do. AI does the hard work.

That’s how you really win with these tools.

The people who are getting great results? They don’t think AI will be magic. They’re using it as a helper to do certain jobs while they do the important work.

That’s all. That’s it for now.

EXTERNAL REFERENCE: OpenAI’s Research Paper on Language Models
https://openai.com/research/language-models-unsupervised-multitask-learners