Developer Builds Rule-Based Auto-Categorization for Expense App Before Adding AI

A developer building a personal expense tracking app has implemented a rules-based auto-categorization system as a deliberate first step before integrating an AI language model. The approach uses keyword matching rules and a nullable database column to assign spending categories, with existing uncategorized records left as null rather than forced into a default value. A key design decision was extracting the categorization logic behind a shared interface, allowing a future LLM to slot in without rewriting existing code. The developer encountered and resolved three bugs related to how empty or null values were handled during the build. A follow-up phase is planned to add an LLM-backed categorizer that will operate behind the same interface, with the rules engine serving as a fallback.