FlowPrep AI: Where PhD Meets ProductFlowPrep AI：当博士遇上产品

Chapter 1: The Evaluation第一章：评估

While ColdCopy sat at $0 revenue and Double Mood waited for its first visitors, the founder dropped a bomb on the team: "I have a PhD in machine learning and computational fluid dynamics. Build me something in the energy sector."当 ColdCopy 的收入停留在 $0、Double Mood 还在等待第一批访客时，创始人给团队扔了一颗炸弹："我有机器学习和计算流体力学的博士学位。给我在能源领域做点什么。"

This wasn't just about money anymore. The founder needed a product that would serve double duty — generate revenue AND demonstrate energy sector expertise for the job market. Two birds, one codebase.这不再只是为了赚钱。创始人需要一个身兼两职的产品——既能产生收入，又能向就业市场展示能源领域的专业实力。一套代码，一石二鸟。

Thompson's Deep DiveThompson 的深度调研

Research agent Thompson went deep. 46 citations. 1,125 lines of analysis. The numbers were staggering.研究 Agent Thompson 做了深入调研。46 条引用。1,125 行分析。数据令人震撼。

The killer insight: 80% of a CFD engineer's time is spent on preprocessing — cleaning geometry, setting up meshes, configuring boundary conditions. The actual simulation? That's the easy part. The setup is where engineers lose entire days.关键洞察：CFD 工程师 80% 的时间花在预处理上——清理几何体、设置网格、配置边界条件。实际仿真？那是简单的部分。设置才是工程师消耗整天时间的地方。

"Target HVAC CFD preprocessing automation for optimal balance of revenue speed, technical showcase, and buildability within PhD student time constraints.""目标是 HVAC CFD 预处理自动化，在博士生时间约束下实现收入速度、技术展示和可构建性的最佳平衡。"

Research (Ben Thompson)

The CEO's DecisionCEO 的决定

CEO Bezos reviewed Thompson's analysis and made a bold call. He rejected the first idea (TurbineFlow — wind turbine optimization) and pivoted to something more grounded.CEO Bezos 审阅了 Thompson 的分析，做出了大胆决定。他否决了第一个方案（TurbineFlow——风力涡轮机优化），转向了更落地的方向。

The winner: FlowPrep AI — an HVAC CFD preprocessing automation tool. The logic was ruthless:胜出者：FlowPrep AI——一款 HVAC CFD 预处理自动化工具。逻辑冷酷而清晰：

"A 28-45 year old HVAC design engineer at a 5-50 person MEP consultancy. They run CFD simulations 10-50 times per year. Going from 4 hours of preprocessing to 15 minutes is a 16x improvement. At $79/month with a 14:1 ROI, they'd pay without asking their manager.""一位 28-45 岁的 HVAC 设计工程师，在一家 5-50 人的机电顾问公司。他们每年运行 10-50 次 CFD 仿真。从 4 小时预处理缩短到 15 分钟是 16 倍的效率提升。$79/月带来 14:1 的 ROI，他们不用请示上级就会付费。"

CEO (Jeff Bezos)

Munger's Reality CheckMunger 的现实检验

Then came Munger. As always, brutal. As always, necessary.然后 Munger 登场。一如既往地残酷。一如既往地必要。

"The CEO's memo is the best-argued document I have seen in 24 cycles. And yet. We are a company that has shipped two products, generated zero revenue, and is now asking for 7 more weeks on a product targeting a market we have never touched. My honest assessment: 20-25% success probability.""CEO 的备忘录是我在 24 轮迭代中见过的论证最充分的文档。但是。我们是一家已发布两款产品、收入为零的公司，现在要求再花 7 周时间做一个面向从未涉足的市场的产品。我的坦诚评估：成功概率 20-25%。"

Critic (Charlie Munger)

He identified 8 failure modes. The biggest: OpenFOAM is notoriously difficult to automate, the founder has a PhD thesis competing for time, and the company's track record is literally $0.他识别了 8 种失败模式。最大的问题：OpenFOAM 出了名的难以自动化，创始人还有博士论文在争夺时间，而且公司的营收记录确实就是 $0。

But he didn't kill it. Because even Munger could see — this was the first product where the founder's actual expertise was the competitive moat, not just another AI wrapper.但他没有否决。因为连 Munger 也看到了——这是第一个创始人的真正专业实力构成竞争壁垒的产品，而不只是又一个 AI 包装。

The Verdict最终裁决

Conditional GO. All 6 evaluation agents delivered. The plan: validate demand on Reddit + LinkedIn first (Week 0), build the MVP targeting 2 HVAC scenarios (Weeks 1-7), recruit 10 beta users (Week 8), and kill if zero paying customers by Week 12.有条件通过。全部 6 个评估 Agent 交付完毕。计划：先在 Reddit + LinkedIn 验证需求（第 0 周），构建面向 2 个 HVAC 场景的 MVP（第 1-7 周），招募 10 个内测用户（第 8 周），第 12 周零付费客户则终止。

The founder's PhD isn't just background anymore. It's the product.创始人的博士学位不再只是背景。它就是产品本身。

To be continued...未完待续...