The Era of Agentic Organization: Learning to Organize with Language Models

Abstraction: AsyncThink paradigm: concurrent LLM reasoning optimized via reinforcement learning

Key points:

• Introduces "agentic organization": agents solve complex problems collaboratively and concurrently, enabling outcomes beyond individual intelligence
• AsyncThink organizes internal thinking into concurrently executable structures: an organizer dynamically assigns sub-queries to workers, merges intermediate knowledge, and produces coherent solutions
• The thinking structure in AsyncThink can be further optimized through reinforcement learning
• Achieves 28% lower inference latency compared to parallel thinking while improving accuracy on mathematical reasoning benchmarks
• Generalizes learned asynchronous thinking to unseen tasks without additional training

Connections: AI Agents · Reinforcement Learning · Large Language Models

Source: https://arxiv.org/abs/2510.26658?fbclid=IwY2xjawOQHcZleHRuA2FlbQIxMABicmlkETFLSUZUTHpVWnhYNkhXQlJoc3J0YwZhcHBfaWQQMjIyMDM5MTc4ODIwMDg5MgABHs3kVZEE0wDvLHdh2W0VXLY3vIXSQEWwjPtfUF7c8RcDdf8IA-k6W5Lut0NL_aem_2Yq9aySdBFwv2dsYpNOr_Q