According to Ethan Mollick, AI labs risk brand confusion and public backlash when using overly technical strings like GPT 5.5 xhigh Codex nano or pop culture code names such as Agent Smith or Mythos, highlighting a naming problem with real market impact. As reported by his tweet on X, vague or ominous names can undermine user trust, complicate procurement, and hinder enterprise adoption where clear SKU-level differentiation and governance mapping are required. According to industry practice referenced by Mollick’s critique, consistent, human-readable, and lifecycle-aware naming improves model catalog navigation, compliance documentation, and benchmarking clarity for buyers. For AI vendors, the business opportunity is to standardize nomenclature into a layered scheme model family version capability tier domain variant that supports pricing pages, eval dashboards, and API headers, reducing legal risk and support costs. As noted in Mollick’s observation, avoiding loaded mythic or villain archetypes also lowers reputational risk in regulated sectors and media monitoring.