According to OpenAIDevs on X, subagents are now supported in Codex, enabling developers to spin up specialized agents to keep the main context window clean, tackle parts of a task in parallel, and steer individual agents as work unfolds (source: OpenAIDevs). As reported by Greg Brockman on X, the feature is positioned to help teams complete large amounts of work quickly via parallelization and scoped contexts (source: Greg Brockman). According to the OpenAIDevs announcement video, business impact includes faster iteration cycles, reduced context-switching overhead, and clearer orchestration of complex, multi-step pipelines—key for use cases like multi-repo code refactors, data pipeline validation, and evaluation harnesses for model experiments (source: OpenAIDevs). For engineering leaders, the opportunity is to design agent architectures that allocate subagents to discrete responsibilities—planning, retrieval, code generation, testing—and consolidate results into a primary agent, improving throughput while preserving auditability and cost control (source: OpenAIDevs and Greg Brockman).