Prompt Engineering

Prompt Engineering for AI ImagesWrite prompts that generate exactly what you see in your head — not what the model feels like giving you."Beautiful woman, masterpiece, 8k, best quality" doesn't work anymore. Modern DiT models (Krea 2, FLUX, Ernie Image) understand full sentences, not tag soup — and if you're still prompting like it's 2023, you're leaving quality on the table and fighting the model instead of directing it.This guide gives you the exact vocabulary, structure, and model-specific knowledge to write prompts that produce what you intended — the first time, not the fifth regeneration.What's InsideCh 1 — Why Prompts Matter More Than Models The same model, two prompts, two completely different results. Why the old tag-based approach is dead and what replaced it.Ch 2 — Anatomy of a Perfect Prompt The six-element structure every effective prompt follows, why word order changes the output, and the truth about token limits, CFG scale, and negative prompts on modern models.Ch 3 — Describing People The exact vocabulary for face, expression, hair, body type, skin, and age that gets you a specific person instead of a random attractive face.Ch 4 — Clothing and Materials Garment precision (the tights-vs-stockings problem and beyond), fabric keywords that change everything, fit descriptors, layering, and color precision.Ch 5 — Settings and Backgrounds How to build believable environments with 2-3 specific details instead of generic AI-blur backdrops — indoor, outdoor, and everything that avoids the "floating furniture" tell.Ch 6 — Lighting The most underrated element in prompt engineering. Natural light, artificial light, direction, quality, color temperature — and why one lighting keyword changes an image more than anything else you could add.Ch 7 — Camera and Composition Shot types, angles, lens feel, and depth of field — described in words, not camera settings the model doesn't understand.Ch 8 — Model-Specific Prompting What Krea 2, FLUX, Ernie Image, and SD1.5/SDXL each respond to best — because the same prompt gives different results on different models, and now you'll know why.Ch 9 — Video Prompts The fundamental shift from describing "what it looks like" to "what happens" — subject motion, camera movement, environmental detail, and matching prompts to camera control LoRAs.Ch 10 — Reference Image to Prompt Using local vision models to draft prompts from reference images in seconds, then editing them into exactly what you need.Who This Is ForAnyone generating AI images who's tired of regenerating the same prompt five times hoping for a better result. Beginners writing their first prompt, and experienced users who want to close the gap between what's in their head and what shows up on screen.Format111-page PDF. Instant download.by Nexus

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