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Automating Feature Flag Cleanup at Scale with Multi-Agent LLM Systems: An Industrial Experience at DoorDash

Atharv Chandratre, Jai Datar · 2026 · arXiv

DOI: 10.48550/arXiv.2610.31351 · open-access PDF

German

Feature Flags sind Runtime-Konfigurationsmechanismen, die für allmähliche Feature-Rollouts, Experimente und Kill-Switches verwendet werden. Sobald ein Feature vollständig eingeführt ist, werden die Flagge und ihr Gated-Code zu technischen Schulden und können operative Risiken einführen, indem sie versehentlich Dormant-Code-Pfade ermöglichen. Bei DoorDash umfassen über 56.000 Feature-Flaggen 623 Repositories, wobei 1.659 derzeit bis Mai 2026 nicht mehr verfügbar sind, wobei interne Schätzungen von einer bis zwei Stunden pro manueller Reinigung liegen. Bestehende regelbasierte Reinigungswerkzeuge haben sich in den Codebasen von DoorDash als unzureichend erwiesen.

Machine translation (Meta M2M100); the English original follows.

Abstract

Feature flags are runtime configuration mechanisms used for gradual feature rollouts, experimentation, and kill switches. Once a feature is fully rolled out, the flag and its gated code become technical debt and can introduce operational risk through inadvertently enabling dormant code paths. At DoorDash, over 56,000 feature flags span 623 repositories, with 1,659 currently stale as of May 2026, with internal estimates of one to two hours per manual cleanup. Existing rule-based cleanup tools proved insufficient in DoorDash's codebases. Our contribution is an end-to-end automated LLM-based feat

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