Graph engineering scales Claude Code beyond loop limits

Graph engineering shifts AI coding workflows from traditional single-agent "loop engineering" to directed graphs where tasks are distributed across specialized agent nodes connected by explicit dependencies. By structuring complex coding requests into fan-out parallel subtasks and fan-in verification nodes, developers can dramatically improve output efficiency while reducing token payload costs. This technique allows developer tools such as Claude Code and OpenAI Codex to tackle large-scale repository refactoring and concurrent task execution without context window degradation.