[2510.27176] Glia: A Human-Inspired AI for Automated Systems Design and Optimization

Computer Science > Artificial Intelligence arXiv:2510.27176 (cs) [Submitted on 31 Oct 2025 (v1), last revised 3 Apr 2026 (this version, v5)] Title:Glia: A Human-Inspired AI for Automated Systems Design and Optimization Authors:Pouya Hamadanian, Pantea Karimi, Arash Nasr-Esfahany, Kimia Noorbakhsh, Joseph Chandler, Ali ParandehGheibi, Mohammad Alizadeh, Hari Balakrishnan View a PDF of the paper titled Glia: A Human-Inspired AI for Automated Systems Design and Optimization, by Pouya Hamadanian and 7 other authors View PDF Abstract:Can AI autonomously design mechanisms for computer systems on par with the creativity and reasoning of human experts? We present Glia, an AI architecture for networked systems design that uses large language models (LLMs) in a human-inspired multi-agent workflow. Each agent specializes in reasoning, experimentation, and analysis, collaborating through an evaluation framework that grounds abstract reasoning in empirical feedback. Unlike prior ML-for-systems methods that optimize black-box policies, Glia generates interpretable designs and exposes its reasoning. When applied to a distributed GPU cluster for LLM inference, it produces new algorithms for request routing, scheduling, and auto-scaling that perform at human-expert levels in significantly less time, while yielding novel insights into workload behavior. Our results suggest that combining reasoning LLMs with structured experimentation, an AI can produce creative and understandable designs fo...