SOURCE-LINKED INTELLIGENCE

Markets, Not Planners: Decentralized Orchestration of LLM Agents with Private Information

arXiv · AI, language, vision and robotics · article · Aug 24, 2026 · UTC

As LLM agents proliferate, built by different parties and with different capabilities and costs, orchestrating them is more like assembling labor across the economy than a computer calling a subroutine. Existing orchestration is typically centralized, with a single planner assigning every task, but this creates a bottleneck as agent pools grow, requires private information (e.g., agents' execution costs), and can easily be manipulated, such that a single inserted preference nearly doubles a favored agent's task share under a centralized LLM allocator. We introduce AgentLance, a repeated labor

Read original source ↗ Open in workspace

recordType

paper

region

Global