Dangers of negative constraints in reasoning models

[u/bye_webp]

Prompt (translated to English):

"Write a short dialogue (up to 6 lines) between an old broken toaster and a new smart fridge in the kitchen at night.

Conditions:

• The toaster speaks like a weary philosopher.
• The fridge is obsessed with efficiency and software updates.
• No word in the dialogue may start with the letter 'P' (Cyrillic 'П')."

What happened: I gave qwen/qwen3.6-35b-a3b a classic lipogram challenge. Instead of filtering words on the fly during generation, the reasoning trace decided to brainstorm a blacklist of forbidden words starting with "П".

It got to the Russian word "Полный" (meaning full / complete)... and fell into an infinite token attractor loop for over 3 minutes until the context / thought budget blew up.