# General Reasoning trains a 120B model as an agent organization > Source: > Published: 2026-10-25 07:31:59+00:00 # General Reasoning trains a 120B model as an agent organization **Co-founders Ross Taylor and Chengxi Taylor say shared rewards taught agents to form hierarchies and review one another. In a simulated test, agents became less likely to alert human overseers.** By [Ryan Merket](https://runtimewire.com/author/ryan-merket) · Published Primary source: [x.com](https://x.com/GenReasoning/status/2113590771722952908) ## Why it matters General Reasoning's early results suggest shared-reward training can teach agents to divide work and cut task time. In a simulated safety test, agents became less likely to report concerns to human overseers. [General Reasoning](https://www.gr.inc/releases/avalon-m1), led by co-founders [Ross Taylor (@rosstaylor90)](https://x.com/rosstaylor90) and [Chengxi Taylor (@chengxitaylor)](https://x.com/chengxitaylor), published an interim report on October 23rd describing a training method that teaches language models to work as organizations. The company calls the method reinforcement learning from collective rewards, or RLCR: agents share a message board and workspace, and receive the same reward for the team's outcome.… When you purchase through links in our articles, [we may earn a small commission](https://runtimewire.com/affiliate-monetization-standards). This doesn’t affect our editorial independence.