Researchers have introduced Hybrid Reasoning Agents, a new framework where large language models perform internal reasoning within a continuous latent space and only generate explicit text when taking actions. By keeping intermediate thought processes hidden in latent representations, this approach aims to significantly improve computational efficiency and reduce token consumption while maintaining complex problem-solving capabilities.