Researchers in NLP increasingly frame and discuss research results in ways that serve to deemphasize the field's successes, at least in part in an effort to combat the field's widespread hype. Though well-meaning, this often yields misleading or even false claims about the limits of our best technology. This is a problem, and it may be more serious than it looks: It harms our credibility in ways that can make it harder to mitigate present-day harms, from NLP deployments, like those involving discriminatory systems for content moderation or resume screening. It also limits our ability to prepare for the potentially enormous impacts of more distant future advances. This talk urges researchers to be careful about these claims and suggests some research directions and communication strategies that will make it easier to avoid or rebut them.