Scaling long-running autonomous coding

This post details the evolution of autonomous coding agents from single-agent limitations to a planner-worker architecture. It describes the challenges encountered with coordination mechanisms like locking and optimistic concurrency, and the solutions implemented, such as separating roles into Planners and Workers. The post also highlights the importance of model choice (GPT-5.2 for planning, Opus 4.5 for shortcuts) and prompt engineering for effective agent coordination and long-running tasks. Experiments demonstrate the ability of hundreds of concurrent agents to work on large codebases for weeks, including building a web browser and migrating a framework.