A coding agent that drops 800 lines into your repo in 90 seconds feels productive. Six months later, when someone is paged at 2am to debug a layer of unused abstractions and inconsistent error handling, that same agent looks expensive. James Shore made the point bluntly in a recent essay: the value of an AI coding tool is not how fast it writes code — it is whether the resulting codebase costs less to keep alive. We ran the same maintenance-heavy workflows through Copilot, Cursor, and Claude Code: refactors that touched 30+ files, bug fixes inside legacy modules, and incremental feature work on top of pre-existing patterns. The results are not what the lines-per-minute marketing suggests. Maintenance is where software actually costs you Industry estimates put maintenance at 60-80% of total software lifecycle cost, and that ratio has been remarkably stable across decades of research — from Lehman's laws in the 1970s through Glass's surveys in the 2000s. The reason is mechanical.…