Prompt Engineering Best Practices for 2026

Getting great results from AI models isn't magic — it's engineering. Here's what works.

The Anatomy of a Good Prompt

Structure

[Subject] + [Style] + [Details] + [Modifiers]

Example:

"A majestic lion (subject), digital art style (style), golden mane flowing in wind, dramatic lighting (details), 8k, highly detailed (modifiers)"

Image Generation Tips

Be Specific About Style

Use Quality Modifiers

These consistently improve output:

Negative Prompts

Tell the model what to avoid:

Model-Specific Techniques

FLUX Models

FLUX responds well to:

SDXL

SDXL prefers:

Video Models

For video, add motion cues:

Common Mistakes

1. Too vague: "a cool picture" → no direction

2. Too long: 500-word prompts get ignored

3. Contradictions: "minimalist, highly detailed"

4. Wrong model: Using photo prompts for art models

Prompt Templates

Product Photography

[Product] on [surface], [background], professional product photography,
studio lighting, high-end commercial shot, 8k

Character Portrait

Portrait of [description], [style], [lighting], [mood],
detailed features, sharp focus, professional photography

Landscape

[Scene] at [time of day], [weather], [style],
cinematic composition, dramatic lighting, 8k resolution

Testing Your Prompts

1. Generate 3-5 variations

2. Note what works and what doesn't

3. Iterate on the best result

4. Save successful prompts as templates

The best prompt engineers treat it like code — version controlled, tested, and refined over time.