Three Scenarios Where AI-Assisted Task Splitting Breaks Down for Developers

Backend engineer Anton has outlined three specific conditions under which his structured, specification-driven development method fails. The approach collapses when the scope of work is genuinely unknown upfront, as no meaningful task specification can be written before a decision is made. It also struggles with unfamiliar codebases, where a lead engineer must manually read the code tree before writing any task — a slow, non-parallelisable step that multiplies in cost if skipped. The third failure point is tasks lacking a clear definition of done, such as 'improve the error handling,' since no automated acceptance command can confirm completion. Anton notes that vague tasks can be partially rescued by converting subjective goals into measurable checks, but the method's core assumption — that all key facts are known before writing begins — must hold for it to work.