🏴‍☠️ Stop Blaming the AI for Bad Images

Six months ago, I was sure the AI just “wasn’t that good.”
Then I realized something uncomfortable: my prompts were lazy.
If you ask for a “cool cyberpunk city,” you’re not directing a scene, you’re tossing a vague wish into a slot machine.
A talented Reddit creator made that point so clearly it snapped my brain into place.
Their big idea is simple: stop describing a thing and start describing a shot.
Once you do, the image quality jumps, even if you change nothing about the model.

Free email without sacrificing your privacy

Gmail tracks you. Proton doesn’t. Get private email that puts your data — and your privacy — first.

Ditch the Gmail data grab

Stop Blaming the Model
Stop blaming the AI model for your average images; the real problem is likely a lack of structure in your request.

I used to type short prompts and pray. “Cool cyberpunk city.” “Epic knight.” “Cozy café.” Sometimes it worked, often it didn’t, and I always blamed the tool. But this creator reframed the problem in a way I couldn’t unsee: most prompts fail because we describe an object, not a cinematic moment. AI can’t read your mind, so it fills in the gaps with generic defaults, and those defaults are exactly what make images look cheap.

The fix is not “better adjectives.” It’s structure. A template that forces you to decide what you actually want before you generate anything.

It Is Not About Magic Words
The creator’s point is refreshing: consistency comes from controlling variables, not finding a secret phrase. When you specify lighting, camera angle, lens vibe, mood, and materials, you remove guesswork. And the less the model guesses, the less it drifts into that plastic, random, samey look.

Think like a cinematographer for 30 seconds. What’s the camera doing. What time of day is it. What’s the light source. Is the scene crisp or hazy. Are we close and intimate, or wide and epic. You’re not “prompting,” you’re making decisions.

The 10-Part Framework
The original poster breaks prompts into 10 sections: Subject, Action, Environment, Mood, Style, Lighting, Camera, Detail, Quality, and Negative Constraints. You don’t need to be a pro to use it. You copy the list, then fill the blanks like a checklist.

If you only remember one thing, remember this: Camera, Lighting, and Negatives do most of the heavy lifting. Camera tells the model how to frame reality. Lighting tells it how to sculpt depth. Negatives tell it what to avoid when it tries to “help.”

That’s the difference between “nice illustration” and “frame from a movie.”

Different by design.

There’s a moment when you open the news and it already feels like work. That’s not how staying informed should feel.

Morning Brew keeps millions of readers hooked by turning the most important business, tech, and finance stories into smart, quick reads that actually hold your attention. No endless walls of text. No jargon. Just snappy, informative writing that leaves you wanting more.

Each edition is designed to fit into your mornings without slowing you down. That’s why people don’t just open it — they finish it. And finally enjoy reading the news.

Try Morning Brew for free!

*Ad

Other awesome AI guides you may enjoy

• Your 3-month plan sorted

• Crush Burnout with This Pro’s AI Workflow

• Stop Blaming the AI for Bad Images: Use This Structure Instead

• Claudebot: The Open-Source AI That Beats Siri

• Turn ChatGPT into a Business Engine

The “Lock and Loop” Method
Here’s the editing advice that saves the most time: don’t rewrite everything when one thing is off. First you lock the story, meaning the subject and action. Then you lock the shot, meaning camera and lighting. After that, you loop changes one section at a time.

If a face looks weird, you adjust negatives. If the background changed when you didn’t want it to, you touched too many knobs at once. This method prevents that annoying problem where you fix an eye and accidentally lose the entire vibe of the scene.

Specific Fixes for Flat Images
The contributor also gives practical “try this first” fixes. Flat image? Add rim light or volumetric haze so edges separate and the scene gains depth. Generic style? Add three concrete, photographer-level details, like wear on leather, dust motes, or fingerprints on glass. Those details don’t just decorate the image, they guide texture, realism, and focus.

This approach takes the guesswork out of image generation.

You have to see the full post to copy the blank template and the huge list of negative constraints the author provided.