AI image generation 101: Midjourney vs DALL·E vs Flux
A practical first guide to AI image generation in 2026 — the three main tools, what each is best at, the universal 6-part prompt template, and the line between \"good enough for work\" and \"clearly AI-generated.\"
AI image generation is one of the categories that crossed from "interesting demo" to "actually useful tool" sometime in 2024 and has only got better since. In 2026 you can produce slide art, blog illustrations, social posts, marketing visuals, product mockups, and respectable illustrations of just about anything, in under a minute.
This article is the practical first guide. We will cover the three tools you actually need to know about, what each is best at, the prompt template that works across all of them, and the line you have to know between "good enough for work" and "obviously AI-generated."
The three main tools
There are dozens of image-generation tools in 2026. Three cover 95% of real use:
Midjourney. The artistic default. Strongest aesthetics; consistently produces images that look like they belong in a portfolio. Best at moody, atmospheric, illustrative, and stylised work. Lives in its own web app at midjourney.com (and a Discord bot, historically). Subscription starts around $10/month.
ChatGPT image generation (GPT-image / DALL·E successor). The fastest path. Generated directly inside ChatGPT, so you can iterate conversationally — "make it warmer, add a coffee cup, switch the background." Strongest at illustration, slide art, infographics, and anything that needs to be embedded into a workflow. Free tier exists with limits; ChatGPT Plus unlocks generous use.
Flux (and the open-source ecosystem around it). The control-heavy option. Strong on photorealism, fine-grained control over composition, and consistency across images. Used heavily by professionals via tools like fal.ai, Krea, Leonardo, and Runway. Pay-per-image or subscription depending on the platform.
There are honorable mentions — Gemini's image generation (integrated nicely with Google Workspace), Adobe Firefly (built into Adobe's apps with commercial-use guarantees), Ideogram (best for accurate text in images), Stable Diffusion (open-source, runs locally). For a beginner, master one of the main three first.
When to use which
A short decision tree:
Illustration, art, atmosphere, distinctive style → Midjourney.
Fast in-chat, infographics, slide art, conversational iteration → ChatGPT image generation.
Photorealism, product mockups, fine control over composition, character consistency → Flux.
Text in the image (signage, posters with words, UI mockups) → Ideogram or GPT — Midjourney still struggles with legible text more than its rivals.
Need a commercial license guarantee → Adobe Firefly or your enterprise tier's licensed model.
For most everyday work — slides, social posts, blog illustrations — ChatGPT image generation is the right starting point. It is fast, lives where your other AI use already lives, and iterates conversationally. Add Midjourney when you need something more polished or stylised; add Flux when you need control.
The universal 6-part prompt template
Across all three tools, the same prompt structure works. The six parts:
- Subject — what the image is of.
- Action / pose — what the subject is doing.
- Environment / setting — where this happens.
- Style — the visual language (photo, illustration, painting, anime, etc.).
- Lighting / mood — how it feels.
- Technical / framing — camera angle, lens, composition.
A worked example:
A young woman in a tailored grey wool coat (subject) walks across a cobblestone street with a paper coffee cup in one hand (action) in the old town of Tallinn at dawn, just after light rain (environment), in a high-end editorial photography style reminiscent of a Wallpaper magazine feature (style), with soft directional morning light from the side and slightly muted colors (lighting), shot at 35mm with shallow depth of field, three-quarter angle (technical).
That single prompt produces a noticeably better image than "woman walking in Tallinn." Each part of the template adds specificity that the model can use.
A few notes on each:
- Subject. Be specific. "Woman" is weak; "young woman in a tailored grey wool coat" is strong.
- Action. What is the subject doing? Even still scenes have implied action — "looking out the window" beats "standing."
- Environment. Place, time of day, weather, season, era.
- Style. This is the most powerful part. "Editorial photography," "watercolor illustration," "Pixar-style 3D render," "1970s film photograph," "matte oil painting" — each radically changes the output. Use known reference styles when you can.
- Lighting. "Soft golden hour," "harsh noon," "moody overcast," "candlelit warm interior." Lighting carries half the emotional weight.
- Technical. Camera angle, lens, framing. "Three-quarter portrait, 35mm, shallow depth of field" or "wide overhead shot, fish-eye lens, full focus."
You will not need all six parts every time. Three or four is often enough for a quick utility image. All six are worth it when the image really matters.
Common mistakes
A few patterns that consistently produce bad images:
Too many adjectives. "A beautiful, gorgeous, stunning, vibrant, dynamic, eye-catching image of..." The model averages out the adjectives. One precise descriptor beats five superlatives.
Mixed styles. "In the style of a watercolor painting and a high-fidelity 3D render and a black-and-white photograph." Pick one. Mixed styles produce muddy results.
Too much detail in the subject. "A dog with brown and white fur, blue eyes, a red collar with a silver tag that says 'Max,' wearing a tiny green raincoat..." The model will get parts wrong. Less detail, picked carefully, produces more reliable results.
Negative prompts in tools that don't support them. "No people, no text, no logos" — Midjourney has explicit negative prompt syntax; ChatGPT image generation does not. In ChatGPT, just describe the positive (what the image should contain) rather than negatives.
Generating once and accepting it. First images are rarely the best. Generate four, pick the best, ask for variants of that one. Most tools have a "make four variations" or "use this as reference" button.
The lines you should know
A few practical lines that matter in 2026.
Hands and text are the lingering weaknesses. AI image models have gotten dramatically better at hands and text, but they still get them wrong sometimes. If your image features prominent hands holding things or legible text, scrutinise the output. Ideogram is the most reliable for text. For hands, just regenerate until you get a clean one.
Famous people, copyrighted characters, and trademarked brands. Most consumer tools have guardrails — they refuse or produce a generic look-alike. Do not try to circumvent these for commercial use; you are courting legal trouble.
The "AI art smell." As of 2026, a generated image still has a recognisable look to people who see a lot of AI art. Smooth-textured faces, slightly-too-perfect lighting, suspiciously elegant compositions. For a slide deck, this is fine. For a wedding portrait commission, it is not.
Commercial licensing. What you generate is, in most major tools, yours to use commercially — but the rules vary by provider and tier. If you are using AI images in paid work, especially for clients who care, check the license. Adobe Firefly offers the strongest commercial-use guarantees and indemnification.
A few practical workflows
Slide deck illustrations. ChatGPT image generation. Prompt: "[subject] in a flat illustrated style with [your brand colors], suitable for a presentation slide, minimal background, plenty of negative space." Use iteratively for a whole deck and you get a consistent visual language for free.
Blog post hero images. Midjourney or Flux. Use the 6-part template carefully. Generate four, pick the best, refine. Aim for a single strong image rather than a busy collage.
Social posts. Either tool. For Instagram, square format with strong central composition. For LinkedIn, landscape with room for text overlay. Specify the aspect ratio explicitly.
Product mockups. Flux is strongest. "A [product] on a [surface], in [lighting], shot in [style], with [context elements]." Generate variations to show options.
Quick "what does this concept look like" sketches. ChatGPT image generation, conversational mode. "Generate a rough sketch of what a settings page for a meal-planning app might look like." Treat as a visual brainstorming partner, not a final design.
The 80% that is enough
For most of the work most people need image generation for — slide art, blog illustrations, social posts, mockups, brainstorming visuals — getting "good enough" takes about a minute and one revision. You do not need to be a prompt-engineering wizard.
The 20% that needs to be perfect — magazine-cover-quality, photoreal product shots, complex compositions — takes proper craft, multiple tools, and serious iteration. That is a different article.
But the 80% is the daily-use case, and it is much more accessible than it was even a year ago. The universal template, one good tool, and a willingness to iterate twice — that is enough for most working professionals to make image generation a habit.
Try it on your next presentation. Pick one slide that needs an image. Spend three minutes with the 6-part template and ChatGPT image generation. You will probably ship something better than what was there before, in less time than searching for a stock photo.