AI Artist - Prompt Engineering
Craft effective prompts for AI text and image generation models.
Core Principles
- Clarity - Be specific, avoid ambiguity
- Context - Set scene, role, constraints upfront
- Structure - Use consistent formatting (markdown, XML tags, delimiters)
- Iteration - Refine based on outputs, A/B test variations
Quick Patterns
LLM Prompts (Claude/GPT/Gemini)
[Role] You are a {expert type} specializing in {domain}.
[Context] {Background information and constraints}
[Task] {Specific action to perform}
[Format] {Output structure - JSON, markdown, list, etc.}
[Examples] {1-3 few-shot examples if needed}Image Generation (Midjourney/DALL-E/Stable Diffusion)
[Subject] {main subject with details}
[Style] {artistic style, medium, artist reference}
[Composition] {framing, angle, lighting}
[Quality] {resolution modifiers, rendering quality}
[Negative] {what to avoid - only if supported}Example: Portrait of a cyberpunk hacker, neon lighting, cinematic composition, detailed face, 8k, artstation quality --ar 16:9 --style raw
References
Load for detailed guidance:
| Topic | File | Description |
|---|---|---|
| LLM | references/llm-prompting.md | System prompts, few-shot, CoT, output formatting |
| Image | references/image-prompting.md | Style keywords, model syntax, negative prompts |
| Nano Banana | references/nano-banana.md | Gemini image prompting, narrative style, multi-image input |
| Advanced | references/advanced-techniques.md | Meta-prompting, chaining, A/B testing |
| Domain Index | references/domain-patterns.md | Universal pattern, links to domain files |
| Marketing | references/domain-marketing.md | Headlines, product copy, emails, ads |
| Code | references/domain-code.md | Functions, review, refactoring, debugging |
| Writing | references/domain-writing.md | Stories, characters, dialogue, editing |
| Data | references/domain-data.md | Extraction, analysis, comparison |
Model-Specific Tips
| Model | Key Syntax |
|---|---|
| Midjourney | --ar, --style, --chaos, --weird, --v 6.1 |
| DALL-E 3 | Natural language, no parameters, HD quality option |
| Stable Diffusion | Weighted tokens (word:1.2), LoRA, negative prompt |
| Flux | Natural prompts, style mixing, --guidance |
| Imagen/Veo | Descriptive text, aspect ratio, style references |
Anti-Patterns
- Vague instructions ("make it better")
- Conflicting constraints
- Missing context for domain tasks
- Over-prompting with redundant details
- Ignoring model-specific strengths/limits