Qwen3.8-27B reinforcement training fixes ThinkingBox agent failures

Researchers report that using executable database checks to evaluate AI agents can also effectively train them through reinforcement learning. By applying reinforcement learning to the Qwen3.8-27B model using binary rewards derived from final database states, the team significantly increased the model's reliability and reduced the cost of dependable task execution on a benchmark of simulated enterprise workflows. Open article →