AI Image Generation Tips and Tricks for Beginners: Complete Guide 2025

You've installed the software, loaded your first model, and typed a prompt. The result looks nothing like what you imagined. Hands have seven fingers, faces look distorted, and the style is completely wrong. Everyone online seems to create amazing images while you're stuck with AI-generated disasters.

Quick Answer: AI image generation has a learning curve, but a few key techniques dramatically improve results. Start with detailed prompts that specify subject, style, lighting, and composition. Use negative prompts to exclude common problems. Match your model to your desired output style. And most importantly, generate multiple variations because the best images come from iteration, not single attempts.

Why Do Your First AI Images Look Bad?

Understanding why images fail helps you fix them.

The Model Isn't Psychic

AI models generate images based on statistical patterns from training data. They don't understand your vision. When you type "beautiful landscape," the model draws from millions of landscape images without knowing you wanted a snowy mountain at sunset.

The Fix: Be specific. Instead of "beautiful landscape," try "snowy mountain peak at golden hour sunset, dramatic clouds, alpine lake reflection, photorealistic, cinematic lighting."

Default Settings Aren't Optimal

Most interfaces ship with generic default settings. These produce acceptable results for broad use cases but aren't optimized for any specific output type.

The Fix: Learn what each setting does and adjust for your goals.

You're Fighting the Model's Strengths

Different models excel at different things. Using an anime-focused model for photorealistic portraits produces predictably poor results.

The Fix: Research model specializations and choose appropriately.

How Do You Write Better Prompts?

Prompting is the highest-leverage skill for improving results.

The Anatomy of an Effective Prompt

Strong prompts typically include several elements.

Subject: What is the main focus?

• "A young woman" (vague)
• "A 25-year-old woman with auburn hair, green eyes, light freckles" (specific)

Style: What aesthetic are you targeting?

• "In the style of Renaissance painting"
• "Photorealistic, shot on Canon EOS R5"
• "Studio Ghibli anime style"

Lighting: How is the scene lit?

• "Soft natural light from a window"
• "Dramatic rim lighting"
• "Golden hour sunlight"

Composition: How is the frame organized?

• "Portrait shot, shallow depth of field"
• "Wide establishing shot"
• "Close-up detail"

Quality Modifiers: Technical quality indicators

• "Highly detailed, 8k resolution"
• "Professional photography"
• "Masterpiece, best quality"

Prompt Structure That Works

A reliable structure for beginners:

[Subject description], [action or pose], [environment], [style], [lighting], [technical quality]

Example: "Young woman with long dark hair reading a book, sitting in a cozy library, warm afternoon light through tall windows, photorealistic portrait photography, soft focus background, highly detailed"

What to Include in Prompts

Common Prompt Mistakes

Too Vague: "A pretty girl" gives the model too much interpretation freedom.

Too Cluttered: Cramming every possible descriptor creates confused outputs.

Conflicting Instructions: "Bright sunny day, dark moody atmosphere" contradicts itself.

Ignoring Model Conventions: Some models respond to specific trigger words or formats.

How Do You Use Negative Prompts Effectively?

Negative prompts tell the model what to avoid.

Essential Negative Prompt Elements

Start with these common exclusions:

lowres, bad anatomy, bad hands, extra fingers, fewer fingers, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry, deformed, disfigured, mutation, mutated, extra limbs, missing limbs

Customizing for Your Needs

Add specific exclusions based on what you're creating.

For Portraits:

cross-eyed, ugly, tiling, poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, mutation, mutilated, extra fingers, deformed, blurry, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck

For Landscapes:

people, figures, text, watermark, signature, border, frame, out of focus, blurry, oversaturated, ugly, deformed, duplicate

Don't Over-Negative

Too many negative terms can constrain the model excessively, producing bland outputs. Start minimal and add only what's needed.

Which Settings Matter Most?

Understanding key settings dramatically improves results.

CFG Scale (Classifier-Free Guidance)

CFG scale controls how closely the image follows your prompt.

For Beginners: Start at 7 and adjust based on results.

Sampling Steps

More steps generally means more refined output, with diminishing returns.

For Beginners: Use 30 steps as default.

Sampler Selection

Different samplers produce different results.

Recommended for Beginners:

• DPM++ 2M Karras - Good balance of quality and speed
• Euler a - Fast, good for exploration
• DPM++ SDE Karras - Higher quality, slower

Avoid getting lost in sampler comparisons early on. Pick one and learn it before exploring alternatives.

Resolution and Aspect Ratio

Generate at your model's native resolution for best results.

Generating far above native resolution causes quality issues. Instead, generate at native size and upscale afterward.

How Do You Choose the Right Model?

Model selection determines 80% of your output style.

Model Categories

Realistic Models:

• Optimized for photorealistic outputs
• Good for portraits, products, landscapes
• Examples: Realistic Vision, Juggernaut

Anime/Illustration Models:

• Stylized for 2D art aesthetics
• Good for characters, scenes in anime style
• Examples: Anything V5, Counterfeit

General Purpose Models:

• Balanced for multiple styles
• Good starting points for beginners
• Examples: Dreamshaper, Deliberate

Specialized Models:

• Trained for specific niches
• Architecture, fashion, food, etc.
• Choose based on your focus

Model Matching Guide

Where to Find Models

• Civitai - Largest community repository
• Hugging Face - Official model hosting
• Model-specific communities and forums

If model management feels overwhelming, Apatero.com provides curated model access without the complexity of downloading and configuring locally.

How Do You Iterate Toward Better Results?

Single attempts rarely produce ideal outputs.

The Batch Generation Workflow

1. Generate 4-8 images with same prompt
2. Identify which aspects work
3. Refine prompt based on observations
4. Generate another batch
5. Select best result

This workflow leverages the random variation in generation to find optimal outputs.

Progressive Refinement

Start broad, then narrow down.

Round 1: Test basic concept

• Simple prompt, default settings
• Verify concept works at all

Round 2: Refine subject

• Add subject details
• Adjust pose, expression, features

Round 3: Perfect environment

• Detail the setting
• Add lighting specifics

Round 4: Polish

• Fine-tune with negative prompts
• Adjust settings for quality

Using Seeds Effectively

Seeds control randomness. Same seed + same prompt = same image.

Useful for:

• Recreating images you liked
• Making small adjustments while preserving composition
• Batch variations with controlled differences

Don't:

• Keep using the same seed forever
• Assume good seeds work across different prompts

What Common Mistakes Should You Avoid?

Learning from common errors accelerates improvement.

Mistake 1: Ignoring Aspect Ratio

Generating square images when you need widescreen (or vice versa) wastes generations. Plan your aspect ratio before generating.

Mistake 2: Prompt Stuffing

Adding every quality word you've seen doesn't help: "masterpiece, best quality, ultra detailed, 8k, highly detailed, beautiful, stunning, amazing, professional..."

Most of these are redundant. Pick a few that matter.

Mistake 3: Fighting the Model

If your anime model keeps producing anime-style outputs when you want photorealism, the answer isn't more prompting. It's using a different model.

Mistake 4: Never Changing Settings

Default settings are defaults, not optimal. Experiment with CFG, steps, and samplers for your specific needs.

Mistake 5: Giving Up Too Early

AI generation is probabilistic. The perfect image might be in batch 5, not batch 1. Persistence pays off.

What Quick Wins Improve Results Immediately?

Some techniques provide instant improvements.

Quick Win 1: Add Lighting Details

"Natural lighting" beats no lighting specification. "Soft golden hour sunlight from the left" beats "natural lighting."

Quick Win 2: Specify Camera/Medium

"Shot on Hasselblad H6D, 85mm lens" for portraits "Oil painting on canvas" for art "Digital illustration, concept art" for stylized work

Quick Win 3: Use Quality Tags Selectively

For photorealism: "professional photography, detailed skin texture" For anime: "anime screencap, clean lineart"

Quick Win 4: Reference Specific Artists or Styles

"In the style of [artist name]" can dramatically shift aesthetics. Research artists whose work matches your vision.

Quick Win 5: Use Parentheses for Emphasis

Most interfaces support (parentheses) for emphasis:

• (important detail) - slight emphasis
• ((very important)) - stronger emphasis
• (detail:1.3) - numerical weight

Frequently Asked Questions

How long does it take to get good at AI image generation?

Basic competence comes within a few hours of focused practice. Intermediate skill develops over weeks. Mastery is ongoing as tools and techniques evolve.

Should I start with local tools or cloud services?

Cloud services like Apatero.com let you focus on learning prompting without hardware concerns. Local tools provide more control but require technical setup. Start with whatever removes friction.

Which model should I use first?

Start with a general-purpose model like Dreamshaper or the default model in your chosen tool. Specialize later once you understand basics.

How important are negative prompts?

Very important for avoiding common artifacts. Less important for overall style and composition. Develop a base negative prompt and customize as needed.

Why do hands always look wrong?

Hands are statistically challenging for diffusion models. Use negative prompts targeting hand issues, and consider inpainting to fix hand problems in otherwise good images.

Can I make AI art without any artistic background?

Absolutely. AI generation is more about clear communication of desired outcomes than traditional artistic skills. Visual literacy helps but isn't required.

How do I develop my own style?

Experiment widely first, then narrow down to aesthetics you like. Save prompts and settings that work. Build a personal prompt library over time.

Conclusion

AI image generation rewards experimentation and iteration. The techniques in this guide provide a foundation, but developing your intuition requires practice. Start generating, pay attention to what works and what doesn't, and continuously refine your approach.

Key Implementation Points:

• Write detailed prompts with subject, style, lighting, and composition
• Use negative prompts to prevent common problems
• Match your model to your desired output style
• Generate batches and iterate toward better results
• Experiment with settings rather than accepting defaults

The path from confused beginner to confident creator is shorter than it appears. Every professional AI artist started with bad hands and confused compositions. The difference is they kept generating, kept learning, and kept improving. Your journey starts now.