arXiv:2606.00288v1 Announce Type: new Abstract: Large language models are undergoing a transition from model technology to system technology. As developers use Codex, Claude Code, AutoGPT, and related agents to write code, manage projects, and execute multi-step tasks, recurring engineering problems such as cache reuse, context management, agent scheduling, and permission control increasingly resemble classical computer systems problems. This paper develops that analogy as a visionary survey. We map concepts from computer architecture to the emerging model-native stack and review work on LLM-a

Source: arXiv cs.AI — read the full report at the original publisher.

This is a curated wire item. The Continuum Brief does not republish full third-party articles; this entry links to the original source.