Large Language Models (LLMs) have transformed artificial intelligence from primarily generative systems into increasingly capable reasoning agents. Recent advances in theorem proving, autoformalization, symbolic reasoning, and tool-augmented language models demonstrate substantial progress toward machine-assisted formal reasoning. However, current reasoning systems still suffer from hidden logical inconsistencies, hallucinated symbolic transitions, unsupported theorem applications, and limited reliability guarantees. Existing approaches remain fragmented across formal verification, runtime assurance, neuro-symbolic reasoning and trustworthy Artificial Intelligence (AI) research communities. This paper introduces ReasonOps, a unified operational paradigm for trustworthy verified reasoning systems. Inspired by operational ecosystems such as DevOps and MLOps, ReasonOps treats reasoning as a continuously monitored, verifiable, reliability-aware operational process rather than an isolated inference task. The proposed paradigm integrates semantic interpretation, autoformalization, symbolic reasoning, theorem proving, runtime assurance, probabilistic reliability estimation, and adaptive correction into a unified reasoning lifecycle. The paper further presents the ReasonOps architecture, demonstrates its workflow using an autonomous braking system analysis example, and discusses its potential role in future safety-critical autonomous AI systems. We argue that operational reasoning paradigms such as ReasonOps may become foundational infrastructure for next-generation trustworthy AI ecosystems.

翻译：大语言模型已将人工智能从以生成为主的系统转变为能力日益增强的推理主体。近期在定理证明、自动形式化、符号推理和工具增强语言模型方面的进展，展示了机器辅助形式推理领域的重大突破。然而，当前的推理系统仍存在隐式逻辑矛盾、幻觉性符号转换、无依据定理应用以及可靠性保障不足等问题。现有方法在形式验证、运行时保障、神经符号推理和可信人工智能研究社区之间仍显割裂。本文提出ReasonOps——一个针对可信验证推理系统的统一运维范式。受DevOps和MLOps等运维生态系统的启发，ReasonOps将推理视为一个持续监控、可验证、注重可靠性的运维过程，而非孤立的推理任务。该范式将语义解释、自动形式化、符号推理、定理证明、运行时保障、概率可靠性估计和自适应校正整合为统一的推理生命周期。本文进一步呈现了ReasonOps架构，通过自主制动系统分析示例演示其工作流程，并探讨其在未来安全关键型自主AI系统中的潜在作用。我们认为，诸如ReasonOps之类的运维推理范式可能成为下一代可信AI生态系统的基础设施。