Developer learns AI coding agents excel locally but miss big-picture context in overbuilt prototype

A software builder developing 'Porch Light', an AI agent that monitors public meeting agendas, found that a simple stack-validation exercise ballooned from a planned two-hour task into a full build day. The developer uses AI tools Kiro and Claude to write and review code respectively, while personally directing and validating the work. A key observation emerged when Kiro wrote a byte-identity test for a folder explicitly tagged as throwaway, and Claude approved it — both agents performed their assigned tasks correctly but neither flagged the broader pointlessness of the work. The developer concluded that AI coding agents reason locally and rigorously without tracking higher-level context like deadlines or throwaway markers, making human oversight of scope and intent essential. The incident prompted a reflection on the value of structured 'spikes' — short, pass-or-fail experiments — as a deliberate mechanism to surface wrong assumptions early before they compound across a project.