Written and reviewed by Manish Kulkarni · About the author
Most of us write to an AI the way we text a friend: short, and assuming the other side already knows the situation. The model can't see your screen, doesn't know your deadline and has no idea who will read the result unless you say so. Skilled prompting is mostly the habit of closing that gap on purpose.
If you have not read What a Prompt Actually Is, start there. This lesson builds on it with techniques you can use straight away.
The second version is not longer for the sake of it. Every added phrase removes a guess: the length, the reader, the platform, and what to leave out.
"Explain this so a beginner can follow it" and "explain this so an expert can skim it" produce very different answers from the same facts. Naming the reader is often the single biggest improvement you can make.
Length, tone, required points and things to leave out all narrow the answer. "No jargon" and "no more than five bullets" are small instructions with a big effect.
If you want a particular style, paste one or two examples of what you mean. This is called few-shot prompting, and it usually beats describing the style in words. For instance, you could paste two of your own product descriptions and ask for a third in the same voice.
For anything complicated, add: "Ask me clarifying questions before you start." In my own test, I typed a very vague request for help planning a trip, and ChatGPT replied with six questions: when, how many days, how many people, where from, what budget and what kind of trip. Once I answered them in one short line, it produced a full itinerary. Many people never use this, and it is one of the quickest ways to find out what you forgot to say.
When you paste an article, an email or a spreadsheet, mark where it begins and ends and put your instruction clearly outside it. For example: "Summarize the email below in two sentences. Email starts: ... Email ends." That stops the model from confusing the text you want worked on with the instructions you are giving.
This is a template, not a test result. Replace the brackets with your own details:
In October 2026 I tried the difference between a vague and a detailed prompt in Claude, using something I actually needed: the About text for this website.
Vague prompt: "Write an About text for my website." Claude did not write anything. It asked which of my websites I meant and what tone I wanted, because I run more than one.
Detailed prompt: "Write a 60-word About text for learnaiplainly.net, a site that explains AI in plain language to beginners. Tone: friendly and honest. Do not say I am an AI researcher." This time I got a finished text of about 61 words in a friendly tone, which followed my instruction not to call myself a researcher.
What I noticed: the detail I added (which site, who it is for, the tone, and one thing to avoid) was exactly what the tool had asked for in the first round. I still checked the result before using it. It was written in my voice, so anything it says about me or my reasons has to be something I would really say.
Not necessarily — the goal is relevant detail, not length. A tightly-written 3-sentence prompt with the right context beats a rambling paragraph with none.
Templates can help as starting scaffolding, but understanding the four elements above lets you adapt to any situation instead of memorizing rigid formulas.
The fundamentals stay the same across models, though some tools are tuned for shorter, direct prompts while others handle longer, more detailed context better — check the specific tool's guidance if unsure.