Real-world application and challenges of Forward Deployed Engineers (FDE) in AI project implementation, specifically in FMCG and Japanese markets.
Raw Developer Origin & Technical Request
GitHub Issue
Jul 30, 2026
你好,我长期关注 AI 是如何在真实产业场景中落地的,也会通过访谈和写作,记录一线从业者如何理解客户、产品与组织之间的关系。
之前我和两位从事相关工作的朋友做过比较深入的交流,并整理成了两篇文章:
- [从中台支持到业务前台:一个快消 FDE 的一线观察|别处上岸 EP06](mp.weixin.qq.com/s/skKd0ufgtw_nb9W...
- [在日本市场做 FDE:AI 落地不是追新,而是走进客户现场|别处上岸 EP07](mp.weixin.qq.com/s/Lh524GdufjDGV2w...
一篇来自快消企业内部,讨论一个原本偏中台和技术支持的角色,如何逐渐走到业务前台;另一篇来自日本市场,讨论 AI 产品进入不同市场时,FDE 如何面对信任、本地化、既有工作流程和模糊需求。
在这些交流里,我感受到几条可能与这本书相关的一线观察:
1. FDE 的第一步往往不是实现需求,而是和客户一起判断:真正需要解决的问题是什么。
2. 客户最初提出的需求不一定等于真实问题。很多 AI 项目开始时,客户自己也还没有形成清晰的需求说明。
3. Excel、旧系统和 shadow IT 不只是需要被替换的“落后工具”,它们也是企业真实工作方式的一部分。FDE 需要先理解这些现场,再判断 AI 应该进入哪里。
4. 在日本市场,客户不一定最关心模型是否最新,而更关心它能否解决具体问题、是否容易试用,以及供应商能否诚实说明产品边界。
5. FDE 与传统售前、项目经理或 SI 的差别,可能不只在于岗位职责,而在于它需要同时连接客户现场、产品判断和工程实现,并对最终业务结果保持关注。
这些内容可能和书中已有的一些章节有所呼应,也可能适合作为来自中国快消企业和日本市场的补充案例。
我暂时不确定它们更适合放在正文案例、章节旁注,还是延伸阅读中,所以先通过 Issue 分享出来。如果作者觉得其中有值得展开的部分,我也很愿意根据书稿结构开一个分支,把相关内容整理成更短、更适合书稿的案例。
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