The Rollout Infrastructure Tax in Coding-Agent Reinforcement Learning

Researchers have identified that reinforcement learning for coding agents often overlooks the significant time and resource costs associated with executing software rollouts. By treating infrastructure as a background detail rather than a measurable variable, current development processes frequently ignore performance bottlenecks that limit agent training efficiency. Integrating infrastructure metrics into the learning loop could allow models to optimize for faster, cheaper code execution during the training phase.