mlsanityData to 7 Oct 2026

Quine: Realizing LLM Agents as Native POSIX Processes

arXiv 2603.18030 ↗First posted 8 Mar 2026cs.OS cs.AI cs.PLcited by 1

On the map: LLM agents and tool use → Software engineering coding agents

Abstract (arXiv)

Current LLM agent frameworks often implement isolation, scheduling, and communication at the application layer, even though these mechanisms are already provided by mature operating systems. Instead of introducing another application-layer orchestrator, this paper presents Quine, a runtime architecture and reference implementation that realizes LLM agents as native POSIX processes. The mapping is explicit: identity is PID, interface is standard streams and exit status, state is memory, environment variables, and filesystem, and lifecycle is fork/exec/exit. A single executable implements this model by recursively spawning fresh instances of itself. By grounding the agent abstraction in the OS process model, Quine inherits isolation, composition, and resource control directly from the kernel, while naturally supporting recursive delegation, context renewal via exec, and shell-native composition. The design also exposes where the POSIX process model stops: processes provide a robust substrate for execution, but not a complete runtime model for cognition. In particular, the analysis points toward two immediate extensions beyond process semantics: task-relative worlds and revisable time. A reference implementation of Quine is publicly available on GitHub.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 4 of its 16 references that are in the map. First posted on arXiv 8 Mar 2026.

Builds on

4 of 16 references.

Closest ancestors · 2

Same direction, newest first

  1. 2024OpenHands: An Open Platform for AI Software Developers as Generalist Agents23 Jul
  2. 2024SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering6 May

Other references · 2

  1. 2025UFO2: The Desktop AgentOScited by 38
  2. 2026Architecting AgentOS: From Token-Level Context to Emergent System-Level Intelligencecited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

Similar, not cited

Close in wording, no citation either way

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  4. 2026A Policy-Driven Runtime Layer for Agentic LLM Serving
  5. 2026Pythia: Exploiting Workflow Predictability for Efficient Agent-Native LLM Serving
  6. 2026From Agent Loops to Structured Graphs:A Scheduler-Theoretic Framework for LLM Agent Execution
  7. 2026Orchestral AI: A Framework for Agent Orchestration
  8. 2026A Formal Hierarchical Architecture for Agentic Orchestration with Stack-Based Execution and Lazy Discovery