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InfoQ · September 18, 2026 · On the brief until October 2, 2026

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

Computer ScienceOperationsInformation Systems
THE AI ANGLE
Automating stale feature flag refactoring and testing

DoorDash deployed a multi-agent LLM workflow to automate the cleanup of stale feature flags across complex enterprise codebases, addressing technical debt where traditional AST-based tools fall short due to semantic dependency injection patterns. The system couples human-in-the-loop approval with autonomous agents operating in isolated Git worktrees to modify code, run tests, and perform static analysis. This implementation provides an operational blueprint for using LLM agents to slash routine software maintenance from hours to minutes while preserving code reliability.

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THE TEACHING ANGLE
Students can examine the trade-offs between deterministic, rule-based abstract syntax tree refactoring and probabilistic, LLM-driven agents when untangling complex technical debt across distributed software architectures.

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