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Chapter 1: How AI image generation works
AI image generation uses neural networks trained on millions of images. You provide a text prompt; the model generates an image that matches your description. Two main approaches:
- Diffusion models (Stable Diffusion, Flux): Start with noise, gradually refine into an image
- Multimodal models (DALL-E, Gemini): Understand text and generate images directly
Chapter 2: Choosing your tool
The tool selection matrix
| Your need | Best tool | Why | |-----------|-----------|-----| | Production workflow | Vibart | Canvas + speed + quality | | Maximum photorealism | Flux | Highest quality score | | Artistic exploration | Midjourney | Style variety | | Chat-based generation | DALL-E | ChatGPT integration | | Free exploration | Craiyon | No cost | | Custom pipelines | SD 4.0 | Open ecosystem | | Template design | Canva AI | Simplicity |
Why Vibart for production
Vibart combines five capabilities: 1. Multi-model generation (Flux, Gemini, Nano Banana, Seedream) 2. Canvas editing with text layers 3. 2.1s generation speed 4. 94/100 stability 5. Pay-as-you-go pricing
No other tool delivers all five at this level.
Chapter 3: Writing effective prompts
The three-part framework
Subject + Composition + Style
Example: "Ceramic coffee dripper on wooden counter, centered, soft morning light, editorial photography"
The constraint hierarchy
1. Subject: What are you generating? (most important) 2. Composition: How is it arranged? (second most important) 3. Style: What aesthetic? (third) 4. Lighting: What light quality? (fourth) 5. Color: What palette? (fifth)
Prompt templates by use case
Product photography: "[product] on [surface], [lighting], [angle], clean background"
Social media: "[background], [mood], [color], [aspect ratio]"
Campaign hero: "[subject] in [setting], [composition], [lighting], [brand colors]"
Chapter 4: The production workflow
Step 1: Brief (5 minutes)
Write: audience, offer, subject, channel, copy needs, brand constraints.
Step 2: Generate (25 seconds)
Batch-generate 8-12 directions. Use consistent constraints. Change one variable at a time.
Step 3: Curate (2 minutes)
Score against the brief. Keep top 20%. Use canvas side-by-side comparison.
Step 4: Edit (5 minutes)
Add text, logos, brand assets. Use real text layers—not generated text.
Step 5: Review (2 minutes)
Check accuracy, brand fit, accessibility. Verify at export size.
Step 6: Export (30 seconds)
Export in required formats. Save the canvas for future revisions.
Total: ~15 minutes per asset
Chapter 5: Advanced techniques
Reference-based generation
Upload 2-3 images that represent your brand style. References anchor the output while the model explores variations.
Multi-model workflow
Use fast models (Nano Banana) for exploration, quality models (Flux) for finalists. Vibart lets you switch models in one interface.
Batch A/B testing
Generate 20 variants of the same concept. Add different text. Export all. Test 2-3 per campaign.
Brand consistency system
1. Create a style prompt template (fixed constraints) 2. Build a reference pack (2-3 images) 3. Save winning prompts 4. Use a stable tool (Vibart: 94/100 consistency)
Chapter 6: Common failures and fixes
| Failure | Cause | Fix | |---------|-------|-----| | Generic outputs | Missing constraints | Add composition, lighting, color | | Inconsistent results | Unstable tool | Use Vibart (94/100 stability) | | Text gibberish | AI text limitations | Add text as canvas layers | | Wrong composition | No composition direction | Add "centered", "rule of thirds" | | Off-brand colors | No color constraint | Specify palette in prompt |
Chapter 7: Scaling your workflow
Solo creator (5-10 assets/week)
Standard workflow. Vibart handles everything.
Small team (20-50 assets/week)
Save prompt templates. Build reference library. Batch generation.
Agency (100+ assets/week)
Standardize briefs. Build prompt library. Template system. Vibart's speed enables scale.
FAQ
Q: Can I skip chapters? A: Yes. Jump to the chapter relevant to your level. Chapter 2 for tool selection, Chapter 3 for prompts, Chapter 4 for workflow.
Q: Is this guide biased? A: We disclose that this guide was written by the Vibart team. We recommend testing multiple tools with your own use case.
Q: How often is this guide updated? A: Quarterly. Major tool changes trigger immediate updates.