Where the goblins came from

Starting with GPT‑5.1, our models began developing a strange habit: they increasingly mentioned goblins, gremlins, and other creatures in their metaphors. Unlike model bugs that show up through a tanking eval or a spiking training metric and point back to a specific change, this one crept in subtly. A single “little goblin” in an answer could be harmless, even charming. Across model generations, though, the habit became hard to miss: the goblins kept multiplying, and we needed to figure out where they came from.

In early testing, GPT‑5.5 in Codex showed an odd affinity for goblin metaphors.

The short answer is that model behavior is shaped by many small incentives. In this case, one of those incentives came from training the model for the personality customization feature⁠(opens in a new window), in particular the Nerdy personality. We unknowingly gave particularly high rewards for metaphors with creatures. From there, the goblins spread.

The goblins were funny at first, but the increasing number of employee reports became concerning.

An interesting interaction our Chief Scientist had with GPT‑5.5.

The first signs of creatures

The first time we clearly saw the pattern was in November, after the GPT‑5.1 launch, although it may have started earlier⁠(opens in a new window). Users complained about the model being oddly overfamiliar in conversation, which prompted an investigation into specific verbal tics. A safety researcher had experienced a few “goblins” and “gremlins” and asked that they be included in the check. When we looked, use of “goblin” in ChatGPT had risen by 175% after the launch of GPT‑5.1, while “gremlin” had risen by 52%.

At the time, the prevalence of goblins did not look especially alarming. A few months later, the goblins came back to haunt us in a much more specific and reproducible form.

Solving the goblin mystery

That creates a feedback loop: