
Get AI to Attack Its Own Naming Suggestions Before You Pick a Favourite
Andrew Miles Davis argues that when using AI to generate names for products, services, or campaigns, most people make the same mistake by asking for more options rather than building a better way to judge the options they already have. He outlines a four-part naming brief covering the product, the audience, the desired outcome, and the point of difference, arguing this alone produces better results than a vague request generating fifty forgettable names. Drawing on a real workshop example where a name loved by the room turned out to mean something offensive in another language, unnoticed by everyone except one person who spoke it, he demonstrates why the next step should be asking AI to attack its own suggestions, surfacing unintended meanings, generic overlap, and confusion risk before any name gets chosen. He connects this to his Story Lens method's exposure stage, arguing that a weak name often reveals an unclear understanding of positioning rather than a naming problem itself, and closes with the central lesson: never ask AI what is best without first establishing best according to what, since criteria must exist before judgement can happen. Subscribe to In AI Nutshell for daily ten-minute AI insight and to the YouTube channel for the full video breakdown with live examples.


















