DoorDash Uses Multi Agent LLMs to Clean up 60,000 Feature Flags

DoorDash has implemented a multi-agent system powered by large language models to automate the identification and removal of over 60,000 stale feature flags across its codebase. The workflow integrates live experimental data and parallel agents to manage repository cleanup, requiring human engineer approval before finalizing changes. This automation addresses technical debt by streamlining the maintenance of complex, large-scale software systems.