The Black Box Problem: Why AI-Generated Code Stops Being Maintainable

AI-generated code tends to become unmaintainable due to structural problems: monolithic outputs, implicit circular dependencies, missing contracts, and implementation-only documentation. The core issue is that AI tools generate code without real-time structural feedback, producing what the author calls 'black boxes.' The solution isn't better prompting but enforcing architectural constraints during generation itself — explicit component boundaries, validated dependency graphs, isolated testability, and typed interfaces. Practical advice covers how to prompt with architectural intent, audit existing generated code for implicit coupling, and evaluate AI tools by their post-generation reviewability and structural enforcement.