12.2.1 Image Generation Roadmap: Prompt, Control, Review

Image generation is a workflow, not a single prompt. A useful result needs intent, prompt records, parameters, optional controls, candidate comparison, and review.

See the Pipeline First

The first habit is to log what you asked for, which mode you used, which seed or parameters shaped the result, and what must be reviewed before export.

Build a Prompt Record

import json

brief = {
    "topic": "RAG basics",
    "audience": "beginners",
    "style": "clean editorial cover",
}
prompt = f"{brief['style']} for {brief['topic']}, friendly visual metaphor for {brief['audience']}, clear layout"
record = {
    "mode": "text-to-image",
    "prompt": prompt,
    "negative_prompt": "blurry, watermark, unreadable text",
    "seed": 42,
    "review": ["legibility", "copyright", "brand safety"],
}

print(json.dumps(record, indent=2))

Expected output:

{
  "mode": "text-to-image",
  "prompt": "clean editorial cover for RAG basics, friendly visual metaphor for beginners, clear layout",
  "negative_prompt": "blurry, watermark, unreadable text",
  "seed": 42,
  "review": [
    "legibility",
    "copyright",
    "brand safety"
  ]
}

If you cannot reproduce the prompt record, you cannot reliably improve the image.

Learn in This Order

Step	Read	Practice Output
1	Diffusion intuition	Explain noise, denoising, seed, and sampling
2	Stable Diffusion parts	Map text encoder, U-Net, VAE, and latent space
3	Applications and control	Compare text-to-image, image-to-image, inpainting, ControlNet, LoRA

Evidence to Keep

Keep this page’s proof of learning as a small evidence card:

Prompt Record

prompt, negative requirements, reference, seed/model, and version number

Candidate Outputs

generated or simulated results with selection reason

Technical Note

diffusion step, latent, cross-attention, LoRA, or application mode

Failure Check

prompt drift, style mismatch, artifact, copyright, portrait, or review failure

Expected Output

selected image/version record plus rejected-candidate notes

Pass Check

You pass this chapter when you can write a prompt record, explain which generation mode you chose, save 3 candidate notes, and mark at least one review risk before export.

Check reasoning and explanation

1. A passing answer names the modalities involved, the input-output contract, and how text, image, audio, or video evidence is aligned.
2. The evidence should include a real media artifact or trace, plus a note on quality, safety, and failure cases.
3. A good self-check explains whether the task needs generation, understanding, retrieval, tool orchestration, or human review rather than treating every multimodal problem as the same kind of demo.