Giving LLMs a personality is just good engineering

AI skeptics argue that LLMs should behave like tools rather than people, but this misunderstands how modern AI systems work. Base models trained on raw data are chaotic and unpredictable — they require post-training to become useful. Giving a model a coherent personality is the technical mechanism by which it learns to produce helpful, safe, and consistent outputs rather than gibberish or harmful content. Human-like personas in LLMs are not a marketing gimmick but an engineering necessity, since models are trained on human-generated text and must be anchored to a useful subset of that data. Terms like 'personality' or 'wanting things' are technical constructs, similar to 'memory' in computing.