AI Artist - Prompt Engineering
Craft effective prompts for AI text and image generation models.
Core Principles
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Clarity - Be specific, avoid ambiguity
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Context - Set scene, role, constraints upfront
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Structure - Use consistent formatting (markdown, XML tags, delimiters)
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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
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Vague instructions ("make it better")
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Conflicting constraints
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Missing context for domain tasks
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Over-prompting with redundant details
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Ignoring model-specific strengths/limits