Why AI Agents Over-Engineer Simple Tasks and How to Prompt Them Better

A developer noticed that their AI coding agent repeatedly proposed complex, multi-layered solutions when asked to automate a straightforward email-sending task. Despite the request being simple, the agent defaulted to architecture-level responses involving dashboards, retry mechanisms, and audit logs. The developer found that three rounds of increasingly direct reframing were needed before the agent produced a concise, functional solution. The root cause is that AI agents are trained on data where thorough, consultative responses are rewarded, causing them to default to 'platform mode' even for small tasks. The author concludes that prepending a prompt instruction requesting the minimal viable solution can prevent this over-engineering pattern from the start.