Platform-Specific Techniques

Mastering Each Platform

🔄 Quick Recall: In the previous lesson, we learned systematic iteration workflows—changing one component at a time, using negative prompts, and image-to-image refinement. Now we’ll apply those techniques to each major platform’s specific capabilities.

Each AI image platform has unique strengths, parameters, and quirks. Writing the same prompt for DALL-E, Midjourney, and Stable Diffusion produces very different results—not because one is better, but because each interprets prompts differently.

By the end of this lesson, you’ll optimize your prompts for each platform’s specific strengths and parameters.

DALL-E (OpenAI)

Strengths

• Text rendering. Best in class for readable text within images
• Literal interpretation. Follows complex, specific instructions accurately
• Product mockups. Clean, professional product images
• Editing. DALL-E’s inpainting lets you modify specific areas of an image
• Integration. Built into ChatGPT—conversational image creation

Prompting Style

DALL-E responds well to conversational, descriptive prompts. It’s less sensitive to keyword stacking and more responsive to natural language.

DALL-E optimized prompt: “Create a product photo of a sleek wireless earbud case on a white marble surface. The case is matte black with a subtle logo. Soft studio lighting from the upper left, shallow depth of field, clean background with gentle shadows. The text ‘PULSE’ should be visible on the case.”

Best Practices

• Write in complete sentences rather than comma-separated keywords
• Be explicit about text you want in the image
• Use DALL-E for mockups, diagrams, and images needing text
• Leverage ChatGPT’s conversational interface to iterate: “Make it warmer” or “Remove the background plants”

Limitations

• Less artistic/aesthetic than Midjourney
• Limited parameter control
• No seed control
• Content restrictions can block valid creative requests

Midjourney

Strengths

• Aesthetic quality. Produces the most visually stunning results by default
• Artistic interpretation. Adds creative enhancements beyond what you describe
• Style consistency. Excellent at maintaining a cohesive aesthetic
• Speed. Fast generation with high quality

Key Parameters

Prompting Style

Midjourney responds best to concise, evocative descriptions. It interprets keywords and concepts rather than following instructions literally.

Midjourney optimized prompt:

elderly fisherman mending nets, golden hour, weathered hands, cinematic portrait, warm backlight, shallow depth of field --ar 3:2 --s 250 --v 6.1

✅ Quick Check: If your Midjourney result is too “artistic” and you want it to follow your prompt more literally, which parameter would you adjust?

Best Practices

• Keep prompts concise—Midjourney often produces better results with fewer words
• Use --stylize low (0-50) for literal results, high (250+) for artistic interpretation
• Use --chaos to explore unexpected variations
• Start without parameters, then add them to fine-tune
• Use the remix feature to evolve successful generations

Limitations

• Less literal prompt following than DALL-E
• Discord-based interface has a learning curve
• Struggle with specific text rendering
• Can be unpredictable with complex multi-subject scenes

Stable Diffusion

Strengths

• Complete control. Choose models, samplers, steps, CFG, seeds—everything
• Open source. Free, local, customizable, no content restrictions
• ControlNet. Use reference images to control pose, composition, depth
• Custom models. Fine-tune on specific styles, subjects, or brands
• Batch generation. Process hundreds of images automatically

Key Parameters

Prompting Style

Stable Diffusion responds to keyword-heavy, comma-separated prompts. Order matters—early words have more influence.

Stable Diffusion optimized prompt:

Prompt: elderly fisherman mending nets, golden hour, weathered hands, cinematic portrait photography, warm backlight, shallow depth of field, 8K, highly detailed, award-winning photography

Negative: blurry, low quality, deformed, cartoon, text, watermark, oversaturated

ControlNet: Precision Composition

ControlNet is Stable Diffusion’s killer feature for composition control:

• Canny/Edge: Use edge maps to define shapes and outlines
• Depth: Use depth maps to control spatial arrangement
• Pose: Use skeleton pose maps to control human positions
• Segmentation: Define areas of the image by category

This means you can sketch a rough layout, define poses precisely, or use a reference photo’s composition while generating entirely new content.

Best Practices

• Start with a well-known checkpoint (SDXL or a popular community model)
• Use the negative prompt field actively
• CFG Scale 7-9 balances prompt adherence with image quality
• Experiment with samplers—DPM++ 2M Karras is a reliable default
• Use ControlNet for any prompt where spatial precision matters

Limitations

• Requires technical setup
• Quality varies enormously with model and parameter choices
• No default UI—relies on community interfaces (Automatic1111, ComfyUI)
• Base models may not match Midjourney’s default aesthetic quality

Platform Comparison

Choosing the Right Platform

Try It Yourself

Take a single prompt and run it on two different platforms (use free tiers where available). Compare the outputs and note:

• Which produced a more aesthetic result?
• Which followed your prompt more literally?
• Which would you use for this specific use case going forward?

Key Takeaways

• DALL-E excels at literal interpretation, text rendering, and product mockups
• Midjourney produces the best aesthetic quality with concise, evocative prompts
• Stable Diffusion offers maximum control, customization, and local processing
• Each platform has a different prompting style—optimize accordingly
• No single platform is best for everything—match the tool to the task
• ControlNet in Stable Diffusion enables precision composition that other platforms can’t match

Up Next

In Lesson 7: Commercial Use and Licensing, you’ll learn the practical realities of using AI-generated images for business—licensing, attribution, legal considerations, and best practices.