Two people use the same AI, on the same day, to generate the same idea for an image. One gets back something that looks like it came out of a magazine. The other gets a dull blur, with deformed hands and odd colors. The difference is almost never the tool — it's the prompt.
A prompt is the text you write to describe the image you want. It sounds simple, and it's exactly because it sounds simple that most people write bad prompts: they type a short sentence, hit generate, look at the mediocre result, and conclude that "AI isn't that good after all." In practice, the model delivered exactly what was asked for — the request was what was vague.
This guide shows the structure that separates an amateur prompt from a professional one. You'll see the six-layer anatomy that makes up any good prompt, the technical vocabulary that actually changes the result, how word order affects what the AI prioritizes, how to adapt the same prompt across different tools, and which mistakes destroy images before generation even starts. All with ready-to-copy-and-adapt examples.
Why most prompts generate generic images
Image generation models learned from hundreds of millions of images paired with descriptions. When you write "a dog," the model has no clue which of the millions of dog photos it saw should serve as the reference. It does what any statistical system would: it delivers the average. And the average of everything is exactly what we call generic.
A vague prompt isn't interpreted as creative freedom. It's interpreted as an absence of information, and that absence gets filled with the most frequent clichés from the training set: centered framing, neutral light, blurred background, predictable composition. That's why short prompts tend to produce images that look like cheap stock photography.
The opposite path also has a trap. Prompts with eighty stacked words, full of contradictory adjectives, make the model dilute its attention across too many concepts and fail to properly execute any of them. The sweet spot is in the middle: specific description, organized in layers, with no repetition and no contradiction.
💡 Practical rule: if your prompt could describe a thousand different images, it's too vague. If you can't explain why each word is there, it's too long.
The anatomy of a prompt that works: the 6 layers
Practically every high-quality prompt — in any tool — can be broken down into six layers. You don't need to use all of them in every image, but the more layers you consciously fill in, the less room is left for the AI to choose for you.
1. Subject — what appears in the image
This is the core of the prompt and the part most people write poorly, because they write too little of it. "A woman" is a subject. "A middle-aged woman, gray hair pulled into a bun, white lab coat" is also a subject, and the difference in the result is enormous. Describe approximate age, clothing, distinctive features, expression and posture. If there's more than one element, define the relationship between them: who's in front, who's in the background, who's interacting with what.
2. Action and composition — what's happening and how it's framed
Here you state what the subject is doing and from what angle we see the scene. Terms like close-up, medium shot, three-quarter shot, aerial view, low angle, extreme close-up, symmetrical framing or rule of thirds completely change how the image reads. Without this layer, the AI almost always delivers a frontal, centered medium shot.
3. Environment — where the scene takes place
Setting, era, weather and context. "In a kitchen" is weak. "In a stainless-steel industrial kitchen, pots hanging in the background, steam rising" creates depth and gives the model material to fill the background coherently. The environment also carries implicit light and palette information, which helps the rest of the prompt.
4. Lighting — the most underrated layer
If you learn only one thing from this guide, learn this: lighting is what makes an image look professional. Soft natural light, side-window light, golden hour, blue hour, hard midday light, backlight, neon light, studio lighting with a softbox, Rembrandt light, volumetric light cutting through dust. Each of these terms activates an entire visual repertoire inside the model. Prompts with no light description get flat, personality-free lighting.
5. Style — the visual language
Realistic photography, vector illustration, watercolor, oil painting, concept art, pixel art, 3D render, editorial style, Scandinavian minimalism, cyberpunk, anime. This layer defines the image's "language." A classic mistake is mixing incompatible styles in the same prompt — asking for watercolor and photorealistic 3D render at the same time produces an ugly hybrid, because the model tries to satisfy both.
6. Technique — camera, material and finish details
This is the layer that pushes the result to a professional level in realistic images: 85mm lens, f/1.8, shallow depth of field, high resolution, 35mm film texture, subtle grain, calibrated colors. For illustrations, the equivalent layer describes line, stroke thickness, paper texture and palette.
From weak prompt to strong prompt: five transformations
The theory becomes clear when you see the before and after. In each pair below, the second prompt uses exactly the layers described above.
Professional portrait
Product photo
Illustration
Architecture and interiors
Cinematic scene
Word order changes what the AI prioritizes
In practically every image model, terms written at the start of the prompt carry more weight than those at the end. This means order isn't decorative: it's a form of control.
The most reliable sequence is to start with the subject, move to action and composition, then environment, lighting, style, and finally the technical details. If the most important element in your image is the setting — a landscape, for example — flip it and start there. The principle is simple: whatever comes first is what the AI tries to get right first.
Another practical effect of order is dilution. The longer the prompt, the less relative weight each individual word carries. A well-chosen 25-word prompt often performs better than a 90-word one, because in the 90-word version the AI spreads attention across concepts competing with each other.
💡 Diagnostic test: if an important element didn't show up in the image, move it to the start of the prompt before trying anything else. Most of the time, that fixes it.
Technical vocabulary that actually changes the result
There's a huge difference between generic adjectives and technical terms. Words like "pretty," "amazing," "high quality," or "masterpiece" barely affect the image, because they don't correspond to any concrete visual pattern in the training data. Terms used by photographers, illustrators and art directors, on the other hand, work as precise shortcuts.
| Goal | Instead of writing | Write |
|---|---|---|
| Blurred background | nice background | shallow depth of field, f/1.4, soft bokeh |
| Soft, flattering light | good lighting | diffuse natural window light, golden hour |
| Film look | movie style | cinematic aesthetic, 35mm grain, desaturated colors (50 prompts) |
| Clean product image | professional photo | studio lighting, side softbox, infinite white background |
| Sense of height | from above | aerial view, zenithal shot, drone at 40 meters |
| Imposing character | looking strong | low angle, hero shot, silhouette against the sky |
| Illustration with visible line | cute drawing | visible pencil sketch line, paper texture, watercolor |
| Sharp, detailed image | high quality | high resolution, sharp focus on the eyes, texture micro-detail |
The pattern is always the same: replace judgment with description. The AI doesn't know what you consider pretty, but it knows very well what an 85mm lens with a wide aperture looks like.
Negative prompts: saying what you don't want
Many problems in AI images aren't solved by adding information — they're solved by removing it. The negative prompt is a separate field (or a parameter, depending on the tool) where you list what should be avoided.
The items most worth putting in a standard negative prompt are: deformed hands, extra fingers, duplicated limbs, distorted faces, illegible text, watermark, signature, frame border, low resolution, unwanted blur, excessive noise, and incorrect anatomy. For product images, it's worth adding exaggerated reflections, hard shadows, and a cluttered background.
One important detail: the negative prompt isn't a place for vague adjectives. Writing "ugly" or "bad" in the negative field does nothing. Write the concrete flaw you want to eliminate. If the hands came out wrong, the negative is "deformed hands, extra fingers" — not "bad hands."
Not every tool has a dedicated negative field. In conversational models, like ChatGPT, the alternative is to write the restriction inside the request itself, affirmatively whenever possible: instead of "no text," ask for "clean composition, with no typographic elements at all." Models understand affirmative instructions better than negations.
Parameters: aspect ratio, seed, and prompt strength
Besides text, almost every tool offers numeric controls that influence the result as much as the words do. Knowing the main ones saves a lot of rework.
| Parameter | What it does | When to adjust it |
|---|---|---|
| Aspect ratio | Defines the format: 1:1, 4:5, 16:9, 9:16, 3:2 | Always. Set it before generating, don't crop afterward |
| Seed | Number that locks the random starting point | When you want variations of an image that already came out well |
| Prompt strength (CFG / guidance) | How literally the AI follows the text | Increase it if it ignores details; lower it if the image looks stiff and artificial |
| Steps | Number of refinements during generation | Medium values are usually enough; very high rarely justifies the extra time |
| Reference strength | Weight of an image uploaded as a base | When using a reference image for style or composition |
Aspect ratio deserves special attention because it has a direct impact on SEO and social media. Generating in 1:1 and cropping afterward to 9:16 wastes pixels and cuts the composition in the wrong places. It's better to generate directly in the final format. When the aspect ratio is wrong but cropping would mean losing something important, the path is to expand the image with AI. When cropping is unavoidable, use a tool that preserves quality — you can crop the image online with no unnecessary recompression.
How to adapt the same prompt across different tools
A prompt written for one tool rarely performs the same in another. It's not that one is better: they were trained differently and expect different instruction styles.
| Tool type | How it prefers to receive the prompt | Recommended adjustment |
|---|---|---|
| Conversational models | Natural, complete sentences, as if explaining to a designer | Write in prose, you can ask for corrections mid-conversation (ChatGPT guide) |
| Dense-description models | Comma-separated list of terms, most important first | Cut articles and connecting words, keep only the terms that carry image content |
| Models with good text control | Direct instruction with the text in quotes | Specify the typography and the text's position in the image |
| Open and local models | Dense terms + a separate negative prompt | Make heavy use of the negative field, that's where the biggest gain is |
In practice, keep a "master" version of the prompt in prose and a condensed version in comma-separated terms. Switching between the two covers almost every tool available today. If you're still deciding which one to use, it's worth comparing options in our guide to the best AI tools to create images.
Prompts by image type: what to prioritize in each case
Portraits and photos of people
Prioritize lighting and lens. Combining soft side light with shallow depth of field handles most of the work. Describe the facial expression instead of an abstract emotion: "subtle smile, direct gaze at the camera" works better than "happy." Avoid asking for many people in the same scene — the error rate in faces grows fast with the count. We have 50 portrait prompts with the lighting schemes ready to go.
Products and e-commerce
Prioritize background, material and reflection. Describe the surface the product is resting on, the type of background, and the direction of the light. An infinite white background with a side softbox is the marketplace standard — we have 50 ready-made product photo prompts. After generating, you'll almost always need to isolate the object — the fastest way is to automatically remove the background and save as a transparent PNG.
Logos and visual identity
Prioritize simplicity and shape. Logos call for short prompts, the opposite of everything else: describe the symbol, the number of colors, the style (geometric, organic, monoline), and ask for a neutral background. Too many adjectives produce cluttered symbols that are impossible to shrink down. Complex illustrations don't work as a mark because they disappear at small sizes. We have 50 AI prompts to create a logo organized by business industry.
Architecture and interiors
Prioritize materials and time of day — we have 50 architecture and interior prompts built this way. Naming real materials — exposed concrete, light oak, linen, brushed brass — gives far more realism than style adjectives. The time of day defines the light and, with it, the entire mood: late afternoon produces warm, inviting images, midday produces harsh, cold ones.
Characters and illustration
Prioritize consistency. Describe fixed traits that should repeat across images: hair color and shape, eye color, characteristic clothing, a scar, a distinctive accessory. Reuse the exact same description in every prompt in the series and lock the seed when the tool allows it — that's how you keep the same character across different scenes. The guide on AI character consistency details the four methods.
Wallpapers and background images
Prioritize aspect ratio and negative space. Generate directly in 9:16 for phones or 16:9 for desktop and ask for a clean area where icons and the clock will sit — we have 50 wallpaper prompts already built this way. Afterward, adjusting the exact dimensions for your device is just a matter of resizing the image to the right resolution.
The eight mistakes that ruin prompts the most
- Stacking empty adjectives. "Amazing, beautiful, masterpiece, 8K, ultra detailed" takes up prompt space without bringing any concrete visual information.
- Mixing incompatible styles. Watercolor with photorealistic 3D render, or pixel art with photography — the model tries to satisfy both and delivers neither.
- Describing emotions instead of appearance. The AI doesn't know how to draw "nostalgia"; it knows how to draw warm light, film grain, and faded colors.
- Ignoring the lighting. This is the most common and costly mistake. Without described light, the image comes out flat.
- Asking for text inside the image without specifying it. If the text matters, write it in quotes and say where it sits and in what typography.
- Prompts that are too long. Above about 60 words, each new term weakens the previous ones.
- Not using a negative prompt. Half of the recurring flaws disappear with a well-built negative list.
- Generating at the wrong aspect ratio. Cropping afterward destroys the composition and wastes resolution.
The three-round method for refining a prompt
A good prompt rarely comes out perfect on the first try. The mistake beginners make is rewriting everything from scratch on every attempt, which prevents them from discovering what worked. The method below isolates one variable at a time.
Round 1 — structure. Write the prompt with the six layers, generate four images, and evaluate just one thing: is the composition right? Do the subject, framing and setting match what you imagined? If not, adjust only the subject and composition, without touching style or light.
Round 2 — mood. With the composition settled, adjust lighting, palette and style. Change one element per generation. Swapping "diffuse natural light" for "late-afternoon backlight" and seeing the isolated effect teaches you more than ten random attempts.
Round 3 — finish. Now come the technical details, the negative prompt, and, if the tool allows it, locking the seed to generate variations of the image that came out well. This is also where you fix small flaws through editing, instead of generating everything again.
💡 Save the prompts that worked. A simple file with your best prompts, organized by image type, saves more time than any single trick. If you want a starting point, we have 100 ready-to-copy AI prompts, split into 12 categories. Good prompts are reusable with small subject swaps.
What to do with the image after generating
Generating is half the work. The image that comes out of an AI is almost never ready for publication: it tends to come out too heavy for the web, in the wrong format, and without the final touches.
Three steps solve most cases. First, convert to the format suited to the destination — WebP for websites, PNG when there's transparency, JPG for general sharing. Our image converter does this right in the browser. Second, reduce the file size: high-resolution AI images easily go over 5 MB, which tanks the loading time of any page; the image compressor cuts a good chunk of that with no visible difference. Third, if the generation came out slightly soft at the edges, it's worth improving the image's sharpness before publishing.
For brand visual content, there's still an extra step almost no one takes: extract the color palette from the generated image and reuse it across the rest of your material. This keeps visual consistency across images created in different sessions.
Prompt checklist before generating
- Is the subject described with at least three concrete attributes?
- Is there an indication of framing or angle?
- Was the environment described, and not just named?
- Is there an explicit lighting description?
- Is the visual style declared, without mixing incompatible languages?
- Are the technical details at the end, not the beginning?
- Is the prompt under 60 words?
- Is there a negative prompt with concrete flaws?
- Was the aspect ratio set before generating?
- Can you justify the presence of every word?
If all the answers are yes, the odds that the first generation already comes out usable are high. And when it doesn't, you'll know exactly which layer to adjust — which is exactly what separates someone who uses AI by luck from someone who uses it by method.
Put the theory into practice now
Describe your brand in a few words and see how a well-structured prompt becomes a professional logo in seconds, right in your browser.
Create logo with AI