Developer Ditches AI Classifier for Simple Rules in Tattoo Lettering Tool

A developer rebuilding a name tattoo tool initially considered using an AI language model to classify user text inputs such as initials, name pairs, and dates. After mapping out the actual classification cases needed, they found the problem was too narrow and well-defined to justify an AI model call. Instead, they wrote a small deterministic function using straightforward conditional rules to identify input structure and reorder lettering style recommendations accordingly. The rule-based approach eliminated inference costs, network latency, and unpredictable outputs, while making edge cases easy to reproduce and debug. The product still uses AI for generating custom lettering compositions, but structured input classification proved simple enough to handle with plain code logic.