AI Defaults to Wrong System Design — Either Too Simple or Too Complex

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A software developer highlights two recurring failures when using AI for system design: when asked to write code, AI defaults to a single monolithic service that blocks on slow tasks like email delivery; when asked to design a system upfront, it over-engineers with microservices suited for large teams, not small ones. As an example, a simple rent-splitting app for two developers received a 10-component, five-service architecture from AI, when the actual need was just four components in a single deployment. The root cause, the author argues, is that AI matches the genre of the prompt rather than the real constraints of the project. Both failure modes stem from AI gravitating toward either the simplest code pattern or the most-discussed architectural pattern it has been trained on. The author concludes that a monolith is often the correct and mature choice for small teams, not a beginner shortcut to outgrow.

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