Stop Anthropomorphizing LLMs, Treat Them as Tools

This article argues that marketers and tech professionals fundamentally misunderstand large language models (LLMs) by treating them as conscious entities. It explains that LLMs are statistical pattern engines that predict the next token based on probability, not logical reasoning. This leads to common failures like miscounting letters or clinging to incorrect answers. The author advises abandoning implicit logic by breaking tasks into single steps, providing tight constraints to reduce hallucinations, and not arguing with erroneous outputs. By reframing LLMs as tools rather than coworkers, marketing workflows can be made more effective and efficient.