I’m trying to learn how to generate AI images, but I keep getting confusing results and I’m not sure which tools or prompts I should be using. I need help understanding the best way to create better AI art images for personal projects without wasting more time on trial and error.
Start with one tool, not five. Midjourney, DALL-E, and Stable Diffusion all work. Midjourney is easiest for pretty images. Stable Diffusion gives you more control. DALL-E is simple for beginners.
Your prompt needs structure:
subject, style, lighting, camera/view, background, details
Example:
portrait of a woman, 1990s anime style, soft window light, close-up, city background, detailed eyes, clean lines
If results look messy, your prompt is too vague or too packed. Trim it down. Test 1 change at a time.
For people, add:
age, pose, expression, clothes, lens, lighting
For better consistency, use image references, seed settings, and negative prompts if the tool supports them. Example negative prompt:
blurry, extra fingers, bad hands, distorted face
Do 20 prompt tests. Save the best 3. Compare what changed. Thats how you learn fast.
Honestly, I’d add one thing to what @voyageurdubois said: sometimes the problem is not the prompt, it’s the model. People act like every generator can do every style well, and that’s just not true.
If you want better AI art for personal projects, pick based on goal:
- photoreal people: Midjourney or Flux
- anime/illustration: anime-focused Stable Diffusion models
- product/mockup stuff: DALL-E is often easier
- exact edits to an image: Stable Diffusion inpainting wins imo
Big mistake beginners make: writing prompts like they’re giving a life story. AI image tools respond better to visual direction than lore. Describe what should be visible, not the backstory.
Bad:
“a warrior who has seen many battles and carries emotional scars”
Better:
“female warrior, scar on cheek, worn armor, tired expression, muddy battlefield, cinematic light”
Also, use aspect ratio on purpose. A portrait idea in a wide canvas can come out wierd. And if hands/faces keep breaking, zoom out a bit or make the composition less crowded. Sounds dumb, helps alot.
My actual learning method:
- Find one image you like
- Reverse engineer it
- Copy its structure
- Swap only subject/style
- Repeat till your brain gets it
Prompting matters, sure, but composition matters more than ppl admit.
One thing I’d push back on a bit from @voyageurdubois is the idea that confusing results are mostly a prompt problem. A lot of the time it’s a control problem.
If you want better AI images, stop changing 8 things at once.
Change only one variable per test:
- subject
- style
- camera angle
- lighting
- prompt strength
- seed
- negative prompt
That’s how you figure out what’s actually breaking the image.
A simple prompt framework that helps:
- Subject: “young woman”
- Medium/style: “editorial fashion photo”
- Framing: “waist-up portrait”
- Lighting: “soft window light”
- Detail cues: “natural skin texture, realistic eyes”
- Background: “minimal studio backdrop”
Then add negatives only for recurring problems, not everything under the sun. Huge negative lists can make images look flat.
Also, beginners ignore reference images way too much. Text-only prompting is fine, but image prompting usually gets you closer faster if your tool supports it.
Pros for ':
- can improve readability if it organizes prompt building cleanly
- useful if it compares models by use case
- good for beginners if it shows examples
Cons for ':
- if it stays too generic, it won’t fix bad outputs
- beginners may copy prompts without learning why they work
- can make tools seem interchangeable when they aren’t
Best tip: build a small “prompt library” of your own good results. Reuse winners. That beats starting from zero every time.