Beginner

Images & Visuals

AI image generation has crossed the threshold for professional use — but only for specific types of images. Knowing which tool to use for which job, how to write prompts that produce consistent results, and how to avoid the failure modes that waste time is what separates effective use from frustrating experiments. This page covers the practical workflow for generating work-ready images.

What AI Image Generation Does Well

Strong use cases

Hero images and cover art for presentations, reports, and blog posts
Concept visualisations — abstract ideas, metaphors, moods
Stock photo replacements — people in contexts, environments, scenarios
Illustration-style diagrams with a consistent visual language
Brand-consistent backgrounds, textures, and decorative elements
Rapid visual prototyping — showing stakeholders what something could look like

Where AI still struggles

Accurate text in images — letters distort or hallucinate (use Ideogram for this)
Precise technical diagrams with exact shapes, labels, and measurements
Consistent faces across multiple images (without fine-tuning)
Hands and fingers — still unreliable in many models
Specific real people, logos, or branded assets (copyright and hallucination risk)
Charts and graphs — use a data visualisation tool instead

Tool Comparison

Tool	Best for	Strength	Access
DALL-E 3	Prompt accuracy; following complex instructions	Best instruction-following; integrates with ChatGPT	ChatGPT Plus / API
Midjourney	Creative, aesthetic, editorial, mood images	Highest aesthetic quality; consistent style	Midjourney.com (subscription)
Ideogram	Images with text overlays, posters, signs	Best text accuracy in generated images	Ideogram.ai (free tier available)
Adobe Firefly	Commercial-safe images; Adobe workflow integration	Trained on licensed content; IP-safe for enterprise	Adobe Creative Cloud
Stable Diffusion (local)	Fine-tuned styles; no content limits; high volume	Fully customisable; no API costs at scale	Self-hosted (AUTOMATIC1111, ComfyUI)

Prompt Patterns That Work

1. The Structured Prompt Formula

[Subject] — [Context/Setting] — [Style] — [Lighting/Mood] — [Technical spec]

Example:

A professional woman presenting at a whiteboard with a tech startup team watching — modern office setting, natural light — clean editorial photography style — confident, collaborative mood — 16:9 aspect ratio, photorealistic

Each element is optional but adding more specificity reduces random variation.

2. Style Reference Prompts

Instead of describing quality abstractly, name a visual category:

"flat vector illustration style, minimal colour palette, white background"

"isometric 3D illustration, soft shadows, pastel colours"

"editorial photography, shallow depth of field, warm tones"

"technical diagram style, clean lines, sans-serif labels, light grey background"

Named visual styles give the model a consistent reference. Vague quality words like "beautiful" or "high quality" add little.

3. Negative Prompting (Stable Diffusion / Midjourney)

Negative prompt: blurry, distorted hands, text, watermark, low quality, extra limbs, bad anatomy

Negative prompts explicitly exclude elements. DALL-E 3 handles exclusions in the main prompt ("no text in the image"); Midjourney uses --no flag; SD UIs have a dedicated negative prompt field.

Professional Image Workflow

Define the use case first: Where will this image appear? What size? What feeling should it evoke? Who is the audience?
Choose the right tool: Text-in-image → Ideogram; aesthetic/creative → Midjourney; following specific instructions → DALL-E 3; commercial-safe → Firefly
Write a structured prompt: Subject + context + style + mood. Be specific about what you do and don't want.
Generate 4 variations: Most tools generate multiple options per prompt. Evaluate all before regenerating.
Iterate with refinements: Keep what works, specify what to change. "Same composition but warmer lighting and no background people"
Post-process if needed: Crop, resize, or adjust in standard image editing tools. AI output is a starting point, not always final.
Check usage rights: Understand what the tool's terms allow for commercial use. Adobe Firefly is the safest for enterprise.

Getting Consistent Results

The biggest practical challenge with AI images in professional work is consistency across a project — different images that share a visual language. These techniques help:

Consistency techniques

Save a working prompt template — reuse it with only the subject changed across a series
Use a fixed style descriptor: add the same style string to every prompt in the project
In Midjourney, use --style codes or save seed numbers from successful images
In DALL-E via ChatGPT, ask "Generate another image in the same style as the previous one, but showing [X]"
For character consistency, use fine-tuned models (Midjourney reference images feature)

Common failures and fixes

Wrong style: add explicit style name; remove vague adjectives
Distorted text: switch to Ideogram; or add text in post-processing
Wrong proportions: specify aspect ratio explicitly (16:9, 1:1, 9:16)
Too busy: add "minimal," "simple composition," "clean background"
Generic stock photo feel: specify the lighting, camera angle, and exact subject action

Checklist: Do You Understand This?

Which tool is best for images that contain readable text, and why do other tools fail at this?
Write a structured image prompt using the Subject + Context + Style + Mood + Technical spec formula.
Why is "high quality, beautiful image" a weak prompt? What should you write instead?
What is a negative prompt and when would you use one?
What technique helps you maintain a consistent visual style across multiple images in a project?
Which image generation tool is considered most IP-safe for commercial enterprise use, and why?