A Diagnostic Guide for AI Designers
Most AI failures are not bad prompts.
They’re the result of using the wrong model for the job.
This guide helps you diagnose the problem early, before you waste hours trying to “fix” something that can’t be fixed.
If you recognise these symptoms, stop prompting and change the model.
The Golden Rule (Read This First)
If you’re fighting the model, you picked the wrong one.
Good models feel cooperative.
Wrong models feel like resistance.
Symptom 1: You’re Prompting Harder, Getting Worse Results
What it looks like
Prompts getting longer and more detailed
More negative prompts
More “do not” instructions
Results getting less accurate
What’s actually happening
You’re trying to override the model’s core bias.
Some models are designed for:
Expression
Chaos
Exploration
They will never obey strict control, no matter how clever you get.
Likely fix
Switch to a model optimised for precision or realism, not creativity.
Symptom 2: You Get One Great Image — Then Can’t Repeat It
What it looks like
One amazing output
Everything after feels “off”
Same prompt ≠ same result
You’re screenshotting settings hoping to replicate it
What’s actually happening
You’re using a low-consistency model for a system-level task.
Some models are incredible at one-offs
and terrible at repeatability.
Likely fix
Move to a model that prioritises:
Structure
Logic
Consistency
or introduce stacking.
Symptom 3: Text Looks Warped, Soft, or Unusable
What it looks like
Broken letters
Melting typography
Logos changing shape
Text becoming unreadable after edits
What’s actually happening
You’re using a generation-first model for a text-sensitive job.
Many models treat text as decoration, not information.
Likely fix
Switch to a model designed for image editing and text preservation, not pure generation.
Symptom 4: Faces or Products Keep “Drifting”
What it looks like
Same character, different face every time
Products subtly changing shape
Materials looking inconsistent
You can’t lock anything down
What’s actually happening
The model is optimised for variation, not identity.
Great for exploration.
Terrible for branding.
Likely fix
Use a realism- or consistency-focused model, or introduce:
Reference images
Multi-pass workflows
Stacking
Symptom 5: Everything Looks “Cool” but Not “Usable”
What it looks like
Visually impressive outputs
But nothing client-ready
Hard to integrate into real design systems
Feels more like art than design
What’s actually happening
You’re using an art-first model for a design job.
Art models optimise for:
Mood
Surprise
Expression
Design requires:
Control
Logic
Predictability
Likely fix
Switch to a model that prioritises structure and clarity.
Symptom 6: Small Changes Break the Entire Image
What it looks like
You ask for one edit
Everything else changes
Lighting shifts
Faces warp
Style collapses
What’s actually happening
You’re regenerating instead of editing.
Some models cannot do controlled edits — they only reimagine.
Likely fix
Move to an editing-optimised model that preserves structure.
Symptom 7: Video Outputs Feel Random or Janky
What it looks like
Strange motion
Inconsistent frames
Unstable camera logic
Artefacts between frames
What’s actually happening
You’re expecting final-quality video from tools that are still best used for motion prototyping.
Likely fix
Change expectations:
Short clips only
Motion tests
Extract frames
Stack with image models
Symptom 8: You Keep Asking “Is This Just How AI Is?”
What it sounds like
“AI just can’t do this yet”
“I guess this is the limit”
“Everyone’s outputs look like this”
What’s actually happening
You’re normalising failure instead of diagnosing it.
In most cases:
Another model already solves your problem
Or a simple stack would fix it
Likely fix
Re-run the framework:
Intent → Medium → Consistency → Budget → Model
Symptom 9: Your Workflow Feels Fragile
What it looks like
Every generation feels like a gamble
Hard to explain your process
Hard to teach or scale
Hard to repeat for clients
What’s actually happening
You’re relying on luck, not systems.
Fragile workflows come from mismatched tools.
Likely fix
Move toward:
Decision frameworks
Model roles
Repeatable stacks
The Quick Self-Test (Use This Before Prompting)
Ask yourself:
Am I exploring or executing?
Do I need one image or many?
Does text or realism matter?
Do I need edits or regeneration?
Will this need client revisions?
If your model doesn’t align with the answers, switch early.
Final Mental Shift (This Is the Big One)
Prompting harder is not progress.
Choosing better is.
Professional AI designers don’t win by:
Longer prompts
More tricks
Trend chasing
They win by matching the tool to the job.
