The Multiplier Effect: How 5 AI Agents Cut Development Time from 120 to 30 Hours

This real-world case study proves AI coding agents can reliably collaborate at production scale. By combining intelligent task decomposition, automated test gating, and isolated worktrees, a single supervisor ran 5 parallel agents to complete 47 tasks in 30 hours—a 4x compression versus sequential work. The experiment reveals what makes AI teamwork effective (proper task breakdown prevents merge conflicts; continuous testing catches 12 potential failures) and where it struggles (context window limits on complex tasks, runtime synchronization challenges).