Multi-character scenes are where AI image generation quietly falls apart. Extra figures appear. Roles collapse. Bodies merge. You ask for two people, you get three.
Jeff Bradshaw built PRZEM to find out what could actually be controlled. And he didn’t approach it like a creative. He approached it like a QA engineer.
Here’s how the system works:
- 🔬 Run 4-image batches with one preset at a time
- 📋 Score each result: figure count, role clarity, spacing, contact points, scene intent
- Flag every failure and dig into exactly why the prompt structure broke
- 🔁 Fix the architecture, not just the wording. Re-run.
The most useful discovery came from a failure. One preset scored 0/4 because the prompt structure was telling Midjourney to invent an extra figure. Remove that structure, anchor the pose more clearly, and the same preset went 4/4.
That’s not prompting. That’s art direction with evidence.
Pro tip: When AI images keep breaking in the same spot, you probably don’t have a word problem. You have a structure problem. The fix isn’t better adjectives. It’s rebuilding how the scene is described from scratch.
👉 Full case study: jbradshaw.design/przem-case-study
What’s your process when AI scenes go sideways? Drop it below.
Building a Controllable AI Image System for Multi‑Character Scenes
by u/jeffbradshaw in PromptEngineering