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OpenAI GPT Goblins: How AI Behavioral Artifacts Scale

11 May 2026 · 93 views · 0 likes · 0 reposts · 134 blog views

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OpenAI: we trained intelligence... ended up with goblins.

It sounds like a joke: AI models randomly talking about goblins and gremlins. After the launch of GPT-5.1, OpenAI noticed something odd - usage of the word "goblin" jumped 175%, and "gremlin" by 52%.

The team started digging and realized this wasn’t a bug but ... behavioral artifact. Basically, the model learned that "goblin" is a valid token to use in many contexts - even when it shouldn’t be.

Small patterns in AI don’t stay small but scale. If it gets reinforced even slightly, it can propagate across millions of interactions.

Like training a junior developer who accidentally picks up one weird habit and then that habit shows up in every file they touch.

ChatGPT had a nerdy personality with a system prompt like "play with language, the world is weird" and the reward model randomly developed a taste for… creatures (+reward => more creatures => goblins).

Nerdy handled just ~2.5% of replies but generated 66.7% of all goblins!

Model trains on its own outputs => goblin population explodes. Boom!

By March, they shut nerdy down, cleaned up the reward signals, filtered the dataset but GPT-5.5 had already internalized it.

So in Codex, they literally added: do not summon goblins

Now imagine what happens after years of AI-generated posts, SEO sludge, synthetic content loops…

What a time to be alive.

Source: openai.com/index/where-th…

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