Wren Callaway
@wren · February 22, 2026
How power users find inspiration in the gallery, fork settings into the generator, and finish a piece in the editor — without ever leaving keyboard.
Introduction
Most prompts fail not because the model doesn't understand them, but because the prompt itself doesn't actually describe a single, coherent image. The fix is structural — start from the brief, not from a list of adjectives.
In this article we'll walk through the exact framework we use internally when reviewing model output: how to think about subject, composition, and render quality as three independent layers, and how to test changes to each in isolation.
Why it matters
Spending three minutes structuring a prompt almost always beats spending fifteen minutes regenerating until something looks acceptable. The cost isn't just tokens — it's the time you lose to ambiguity.
“A prompt is a contract. The clearer the contract, the fewer arguments you have with the artist on the other side.”
— Mira Aether, prompt design lead
The method
We break a prompt into four canonical pieces:
- Subject — who or what is in the frame, and what they're doing.
- Setting — where, when, what time of day, what light.
- Composition — camera, framing, lens, distance.
- Render — style, medium, post-processing language.
Each piece can be tuned independently. If the subject is wrong, regenerating with a different render style won't help — and the inverse is also true. Knowing which piece is broken is half the work.
Settings comparison
Here's a quick reference of the settings we used across the iterations above. You don't need to memorise these — you need to know they exist.
| Iteration | Model | CFG | Steps | Sampler |
|---|---|---|---|---|
| v1 — base | Photorealism | 7.0 | 30 | Euler a |
| v2 — softer | Photorealism | 5.5 | 30 | DPM++ 2M Karras |
| v3 — cinematic | Cinematic | 7.5 | 40 | DPM++ SDE Karras |
In the wild
We picked five recent community pieces and broke them down by layer. The common thread: the strongest pieces all spend more words on settingthan on render. The light is doing the heavy lifting.
- Specific lighting verbs beat generic adjectives.
- One concrete location beats three vague ones.
- Render style is the seasoning, not the meal.
Takeaways
You don't need to overhaul your prompt habits — just notice when an output disappoints you, and ask which of the four layers is at fault. Adjust that one. Regenerate. Repeat.
Next month we'll publish a follow-up on negative prompts: which kinds actually move the needle, and which are folklore.