8. Brief interactions with LLMs are often

misleading

While many deployed LLMs are largely able to follow in-
structions, this instruction-following behavior isn’t inherent
to the model, but rather is grafted onto it using highly im-
perfect tools (Section 4). In part because of this, models
can be sensitive to the contents of their instructions in id-
iosyncratic ways. Often, a model will fail to complete a task
when asked, but will then perform the task correctly once
the request is reworded or reframed slightly, leading to the
emerging craft of prompt engineering (Brown et al., 2020;
Reynolds & McDonell, 2021; Radford et al., 2021; Dohan
et al., 2022; White et al., 2023; Si et al., 2023).
These contingent failures are evidence that our techniques
for controlling language models to follow instructions are
not reliably effective. However, simply observing that an

5However, explicit demonstrations of racist
Eight Things to Know about Large Language Models