你好!我是 Guo Qiang,一名专注高确定性系统与一手实现的 Product Engineer。曾负责 GitLab (CN) SaaS 与研发基建,并在 哔哩哔哩、携程 等平台深耕高并发架构与核心业务增长。
我的关注点始终在于复杂系统抽象、状态编排与真实商业约束的闭环统一。
在 AI 时代,我践行 AI Pair Programming 与“干中学”:告别浮于表面的 Prompt 抽卡,专注于端侧 DAG 调度引擎、本地 Agent 工具链与确定性系统的构建。让业务场景定义关键架构,让 AI 启发底层规约与死锁排查,并通过极限压测完成工程闭环。
Hi there! I'm Guo Qiang, a Product Engineer focused on deterministic systems and hands-on craftsmanship. Previously led GitLab (CN) SaaS & platform engineering, and scaled high-concurrency systems and core growth funnels at Bilibili and Ctrip.
My craft centers on the convergence of complex system abstractions, state orchestration, and grounded commercial reality.
In this AI era, I practice AI Pair Programming and "Learning by Doing"—moving far beyond superficial chat wrappers toward client-side DAG engines, local agent primitives, and deterministic architectures. Workflows define critical architecture, AI reveals edge contracts & deadlock hazards, and rigorous stress testing closes the loop.
十年以上技术与平台产品经验,覆盖企业级 SaaS、大流量平台与 AI 工作流。 10+ years of technical & platform product management across enterprise SaaS, high-traffic systems, and AI workflows.
作为一名 Product Engineer,我不相信空谈愿景或纯靠 Prompt 抽卡能做出真正可靠的生产级系统。
大模型天然具备概率与不确定性,但企业的业务逻辑和自动化流水线必须是确定性的。我的工程目标,就是用 DAG 状态机、Kahn 拓扑排序和受限解码 等确定性铁轨,把不可控的概率收敛在安全边界之内。
在技术实现上,我坚持“平台底蕴 + 商业增长”的双轨实践:既要把控底层系统的稳定与防死锁,又要站在真实用户视角把上手门槛做低。
As a Product Engineer, I don't believe vague vision statements or prompt tinkering alone produce reliable production systems.
LLMs are inherently probabilistic, but real business automation requires determinism. My engineering focus is laying white-box rails—DAG state machines, Kahn topological scheduling, and constrained decoding—to keep non-deterministic models bounded within safe contracts.
In practice, I balance platform engineering rigor with product growth: maintaining rock-solid deadlock prevention beneath the hood while obsessing over zero-friction user onboarding.