InfoQ - AI Coding

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

Leela Kumili — Fri, 18 Sep 2026 13:50:00 GMT

DoorDash built a multi-agent LLM system to automate stale feature flag cleanup across more than 60,000 flags and 623 repositories. The workflow combines live experimentation data through MCP, engineer approval, isolated Git worktrees, parallel agents, and automated validation. In an evaluation of 50 flags, 45 produced usable pull requests at an average of 13.8 minutes and $4.79 per cleanup.

By Leela Kumili

Article: When Spec-Driven Development Pays off

Nitin Garg — Thu, 10 Sep 2026 09:00:00 GMT

AI coding assistants have become a core part of software development. AI-generated code has shown productivity gains, but it's also contributing to security weaknesses and familiar bug patterns. In this article, author Nitin Garg highlights the bottleneck has moved from code generation to code verification, and how to detect & mitigate it when the AI-generated behavior diverges from the intent.

By Nitin Garg