1.5M ratings
277k ratings





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.


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. 




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?