Former DeepSeeker and collaborators release new method for training reliable AI agents: RAGEN

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More 2025 was, by many expert accounts, supposed to be the year of AI agents — task-specific AI implementations powered by leading large language and multimodal models (LLMs) like the kinds offered by OpenAI, Anthropic, Google, and DeepSeek. But so far, most AI agents remain stuck as experimental pilots in a kind of corporate purgatory, according to a recent poll conducted by VentureBeat on the social network X. Help may be on the way: a collaborative team from Northwestern University, Microsoft, Stanford, and the University of Washington — including a former DeepSeek researcher named Zihan Wang, currently completing a computer science PhD at Northwestern — has introduced RAGEN, a new system for training and evaluating AI agents that they hope makes them more reliable and less brittle for real-world, enterprise-grade usage. Unlike static tasks like math solving ... Read full article.