Two open-source GitHub projects have independently developed frameworks to improve AI coding agents' workflow efficiency and reliability by splitting tasks among multiple agents in a structured "plan, implement, review, fix" loop. This approach addresses the issue of single-agent drift and ensures better code quality through automated checks and enforced discipline, offering developers robust solutions for managing complex AI-driven development processes.
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