{"id":1873,"date":"2026-07-06T11:32:16","date_gmt":"2026-07-06T03:32:16","guid":{"rendered":"https:\/\/www.lerwee.com\/?p=1873"},"modified":"2026-07-06T11:32:18","modified_gmt":"2026-07-06T03:32:18","slug":"launch-of-the-first-full-toolchain-operations-agent-2-0","status":"publish","type":"post","link":"https:\/\/www.lerwee.com\/en\/2026\/07\/06\/launch-of-the-first-full-toolchain-operations-agent-2-0\/","title":{"rendered":"Launch of the First Full-Toolchain Operations Agent 2.0"},"content":{"rendered":"

Back in March this year, we rolled out the first iteration of our full-toolchain Operations Agent 1.0. At that time, we carried out extensive trials and explorations centered on the Five-Tier Operations Agent Architecture: Perception, Planning, Memory, Reasoning, and Execution. We also encountered numerous pitfalls along the way. For instance, we once held overly high expectations for large language models, assuming that sufficiently powerful models could resolve most issues. Previously, we underestimated the complexities of interconnection, constraint management and control across operations toolchains. This led us to a clear realization: enterprise-grade operations agents are far more than simple dialogue tools. They must operate within a controlled, trustworthy, auditable and sustainably iterative management framework, which we define as the Operations Agent Harness Paradigm. This paradigm empowers agents to take action while confining them within defined boundaries; it enables them to grasp on-site conditions without spiraling out of control.<\/p>\n\n\n\n

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From early spring to midsummer, we have continuously refined and perfected the Lewei Operations Agent Harness Paradigm. Meanwhile, after hundreds of days of polishing, we have delivered three core deliverables: QwenPaw for private deployment scenarios, ArkClaw integration for cloud environments, and Agentic Ops built upon Lewei CoT Chain-of-Thought.<\/p>\n\n\n\n

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Part 1 Two Architectures Address Enterprises\u2019 Two Core Demands: Security & Control, Lightweight Cost Reduction<\/h2>\n\n\n\n

Many enterprises face a persistent dilemma when selecting AI operations solutions: Groups handling confidential data and subject to strict data compliance regulations cannot expose internal metrics, assets or work orders to the cloud; small and medium-sized businesses running cloud workloads cannot afford the high hardware and maintenance costs of private deployments. Instead of adopting a one-size-fits-all approach, we have developed two fully-fledged architectures deeply integrated with the Lewei Operations Agent to cater to both core requirements.<\/p>\n\n\n\n

01 Private Deployment Solution \u2013 QwenPaw: Local Closed-Loop Eliminates LLM Operations Hallucinations<\/h3>\n\n\n\n