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Ethan Brooks
Ethan Brooks

Posted on Originally published at prompthouse.studio

Treat image prompts like functions: what 1,446 shared prompts say about templates

#ai #promptengineering #tutorial #productivity

Most people write an AI image prompt the way they'd write a search query: once, for one result, then throw it away.

The prompts that get shared and reused look different. We went through 1,446 popular image prompts in an openly licensed dataset, and a lot of them are written more like code than like sentences.

Two patterns that stood out

About 22% are templates. 323 of the 1,446 prompts contain at least one placeholder in square brackets, such as [OBJECT], [COLOR], [COUNTRY] or [BRAND NAME]. The author wrote the structure once and left slots for the parts that change.

About 21% are written as JSON. 299 prompts are structured objects with keys for things like the scene, lighting and camera, rather than a paragraph.

They're also long. The median prompt is about 1,000 characters. These aren't one-liners.

Why a template beats a one-off prompt

The top-ranked prompt in the dataset, shared by TechieSA, starts like this:

Create a technical infographic of [OBJECT] with a 45-degree isometric 3D perspective…

Everything after that line, the angle, the annotation style, the colour-coded arrows, stays fixed. Only [OBJECT] changes. Swap in a phone, a camera or a coffee machine and you get a consistent series, not a pile of unrelated images.

That's the same reason we write functions instead of copying code: one definition, many calls, and a fix in one place applies everywhere.

Turning your own prompt into a template

  1. Write it once for a real case and keep iterating until you like the result.
  2. Circle what would change between uses: the subject, a colour, a place, a brand. Those become placeholders.
  3. Name the slots clearly. [PRODUCT] is better than [X], because future you won't remember what X was.
  4. Freeze everything else. The style, the lighting and the camera words are what make the series consistent, so resist editing them per image.
  5. Fill the slots in code if you're generating many images: 
template = open("infographic_prompt.txt").read()
for item in ["mechanical keyboard", "film camera", "espresso machine"]:
    prompt = template.replace("[OBJECT]", item)
    generate(prompt)  # your image API call here
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When JSON helps, and when it doesn't

JSON prompts make each part of the image an explicit field, which is handy when a script fills them in or when you want to change one property and keep the rest. Models still read them as text, though, so there's nothing magic about the braces. If a plain paragraph with clear placeholders does the job, it's easier to read and edit.

Where the numbers come from

The counts are from the nanobanana-trending-prompts dataset, published by MeiGen.ai under CC BY 4.0. The prompts belong to the creators who shared them.

Prompt House is a free gallery built on that dataset, with each prompt shown beside the image it produced and credited to its creator. If you want to see templates like these in action, browse the trending AI image prompts and look for the square brackets.

Written by the Prompt House team. Prompt House is a free AI prompt gallery made by APPDOOK. The counts above were made by searching the dataset's prompt text in October 2026.

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