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Open nowPosted 7 hours ago

AI产品经理

guanghe/ycsz50 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen nowAI产品经理guanghe/ycsz · Beijing, Chinese Mainland

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on guanghe/ycsz's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

13.7% of postings close within 7 days. Measured by our own scanner across the market. guanghe/ycsz postings stay open a median of 12 days.

Share of postings closed within
  1. 2.3%1 day
  2. 4.8%3 days
  3. 13.7%7 days
  4. 22.1%14 days
  5. 37.6%30 days
  6. 59.1%60 days
This job: posted 7 hours ago

guanghe/ycsz median: 12 days open

The posting

1. 发现并定义值得解决的问题。 深入业务团队，理解员工完成任务的实际流程、时间成本和协作障碍，区分个别需求与共性问题，明确产品目标、优先级和验收标准。 2. 负责关键产品从规划到落地。 将模糊诉求转化为清晰的产品方案，与研发、业务及相关职能团队共同完成设计、验证、上线和迭代，对实际使用效果负责。 3. 将有效实践沉淀为共用能力。 识别各部门已有的知识、Agent、工具和流程中值得复用的部分，设计发现、接入、授权、使用和维护机制，让其他团队能够理解、信任并使用。 4. 推动跨部门协作与责任落实。 明确平台、能力提供方和使用方各自负责什么，推动关键依赖、接入标准和维护责任达成共识，解决落地过程中的分歧与阻碍。 5. 平衡使用体验、推广成本与运行要求。 让产品容易接入、容易使用，同时将必要的权限、人工确认、使用记录和异常处理融入流程，使共用能力能够持续运行。 6. 用事实推动取舍与迭代。 跟踪任务完成效率、持续使用、跨团队复用等效果，识别无效建设，及时调整、收缩或停止投入。

1. 有完整的产品负责经历。 主导过企业服务、内部平台、业务中台、知识协作或流程效率类产品，经历过从需求判断到上线推广、持续迭代的完整过程，能够说明自己的决策及其结果。 2. 具备平台产品思维。 能从具体场景中识别共性，判断什么时候应该做公共能力、什么时候应由业务自行解决，并能处理标准化与业务差异之间的关系。 3. 理解 AI 产品的能力与边界。 有将大模型、Agent 或自动化能力用于实际工作的经验，能够判断哪些环节适合交给 AI、哪些需要人工参与，以及如何验证结果是否可靠。 4. 能与研发讨论关键实现约束。 理解接口、数据来源、身份权限、系统集成等基本概念，能够将技术约束转化为产品选择，识别演示可用与长期可依赖之间的差距。 5. 具备跨部门推动能力。 能在没有直接汇报关系的情况下，通过清晰的问题定义、方案和协作机制推动各方达成一致，落实负责人、交付标准与后续维护责任。 6. 判断清楚，表达具体。 能把复杂问题讲明白，区分事实、假设与待验证判断；面对不合理需求或证据不足的方案，能够提出取舍并推动验证。

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  1. A CV for this posting

    Written against guanghe/ycsz's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on guanghe/ycsz's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    guanghe/ycsz's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

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  6. The interview in your calendar

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    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
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Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

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The numbers game

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We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

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