By skyforbes Yesterday we broke down the difference between drift and freeze.
Today is the “why” — why it happens, and why separating roles matters so much.
Here’s the clearest explanation I know.
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A beginner-friendly example
A) When you write everything in one block
“Explain like a teacher, make it a little fun, keep it short,
think step-by-step, be formal, be friendly, and sound like an expert.”
→ GPT merges all of that into one personality
→ The reply style becomes fixed
→ Everything after that looks the same
→ Freeze
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B) When you separate the roles
Identity: “You are a calm explainer.”
Task: “Explain this topic in 5 steps.”
Tone: “Add a slightly friendly note at the end only.”
→ Identity stays stable
→ Logic stays in steps
→ Tone appears only where it should
→ Replies stay consistent
That’s structure.
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Why role-separation actually works
It prevents instruction fusion — the model’s tendency to collapse multiple rules into one.
The danger moment is when GPT internally decides:
“Oh, these rules all mean the same thing. I’ll merge them.”
Once it merges them, it’s like pouring milk into coffee:
you can’t un-mix it.
Structure acts as a shield that stops blending before it starts.
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Tomorrow: simple Before/After examples showing
how big the stability gap becomes when roles stay isolated.