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汽車製造商福特公司的創始人亨利.福特講述了以下故事:

「當世界上還沒有汽車的時候,如果你問人們:『你想要什麼樣的交通工具?』他們會說:『一匹更快的馬』。」

傾聽客戶的聲音,努力滿足客戶的需求,是企業管理的常態。然而,光影法則在這裡也起了作用。

正如亨利.福特所說,如果只聽從顧客的聲音,最終只會找到並養出一匹跑得快的馬。用生產線方式製造大規模廉價汽車的創新思路將不會誕生。受制於客戶的需求,將無法應對環境的變化。

AI and ML companies face a similar dynamic. While terms like machine learning are not new, specific solutions areas like “decision intelligence” don’t fall within a clear category. In fact, even grouping “AI/ML” companies is awkward, as there is so much crossover with business intelligence (BI), data, predictive analytics and automation. Companies in even newer categories can map to terms like continuous integration or container management.

ai

If you’re paying attention, you’ll be asking at this point not just how to avoid the fatal pinch, but how to avoid being default dead. That one is easy: don’t hire too fast. Hiring too fast is by far the biggest killer of startups that raise money. 

Plus founders who’ve just raised money are often encouraged to overhire by the VCs who funded them. Kill-or-cure strategies are optimal for VCs because they’re protected by the portfolio effect. VCs want to blow you up, in one sense of the phrase or the other. But as a founder your incentives are different. You want above all to survive. 

Airbnb waited 4 months after raising money at the end of Y Combinator before they hired their first employee. In the meantime the founders were terribly overworked. But they were overworked evolving Airbnb into the astonishingly successful organism it is now. 

首先,講清楚你所在的市場,並且這個市場體量足夠大、成長性足夠好。這個市場可以是全球汽車保有量、手機用戶數量這樣清晰的市場,但不可以是物聯網、智慧城市、SaaS平台這樣模糊的概念。

其次,自己有實力拿下這個大市場。如果你只是畫了一個大大的餅,但是沒有資格拿下這塊市場也是不行的。科技企業的優秀要體現在對這個問題的回答上:為什麼這個市場我能拿下來,別人做不到?

甚至在已經明確市場規模的基礎上,科技企業還能不斷探索未來想像空間,進一步打開成長的天花板。比如電動汽車可以靠軟體提升盈利,亞馬遜除了電商還可以佈局雲計算等等。

It turns out we’ve been getting it wrong all along.

We’ve all been told that AI by itself, 5G by itself, and edge computing by itself were all supposed to trigger monumental changes in computing. As a result, we’ve built up expectations around what each of these technologies was supposed to enable on their own, but frankly, the real-world results have been disappointing.

People are starting to figure out that you need all three of them working together simultaneously to feel their full impact. It’s the combination of the speed and low latency of 5G, plus the extended reach of edge computing, and the intelligence of AI that can power the kinds of impactful applications and futuristic scenarios that we were all originally promised with 5G.

An MVP is a process that you repeat over and over again: Identify your riskiest assumption, find the smallest possible experiment to test that assumption, and use the results of the experiment to course correct.

In a trial-and-error world, the one who can find errors the fastest wins. Some people call this philosophy “fail fast.” At TripAdvisor, we called it “Speed Wins.” Eric Ries called it Lean. Kent Beck and other programmers called it Agile. Whatever you call it, the point is to find out which of your assumptions are wrong by getting feedback on your product from real users as quickly as possible.

Whether you’re building a product, writing code, or coming up with a marketing plan, you should always be asking yourself two questions:
- What is my riskiest assumption?
- What is the smallest experiment I can do to test this assumption?