Founder’s Lessons: Dr. Hong Tang, Former Chief Architect of Alibaba Cloud (Part 2)
Hong discusses key learnings from his journey, including differences between Chinese and U.S. tech companies and the best advice he’s received
About
Welcome to the eleventh installment of Tsingyuan Ventures’ Lessons from Founders series. Every week, we publish an in-depth founder interview. This week, we’re highlighting our venture partner Dr. Hong Tang. Our conversation covers his personal journey, the lessons that shaped him, and his vision for the future. These insights and lessons are applicable to any entrepreneur — current or future. Read past interviews here.
This is Part 2 of a two-part series. Read Part 1 here.
Meet Dr. Hong Tang
Interview edited for clarity and length.
“Before you answer a question, make sure you know it is the right question.”
Part 2: Hong’s Learnings
On handling stress and pressure
In my early years, I actually didn’t feel much stress. We were a bunch of kids who were very young, most of us single, coming to Silicon Valley to work and play, and we all had very similar backgrounds and a lot of commonalities. Naturally we had a very good bond and really enjoyed working together as a bunch. It was quite similar to the startup vibe.
But later on, I did become more aware of stress and pressures and how to deal with them. I don’t have a clear formula, but you need to first be aware that you are stressed. In the moment, you have to tell yourself to slow down. You need to take a break, talk with someone, or find another way to slow down.
In the moment, you have to tell yourself to slow down.
Another big part is energy management, which I think is more important than time management. You need to prioritize and understand your state and what things you should drop instead of taking all of them on. That’s important for surviving when you’re juggling a lot in the later part of your career.
On failures and biggest learnings
I actually found this is the hardest question for me to answer. I know where this question comes from. Generally people would think: there are a lot of lucky factors contributing to success, but you can pinpoint situations that lead to failures. So your biggest learnings probably come from your biggest mistakes. But from my own experience, while I’ve learned a lot from my mistakes, my biggest learnings have not been from failures.
In my opinion, there are two kinds of learning:
- Going from the unknown to the known. This is easier, because whenever you learn something new, that information is added to your model and understanding of the world.
- Going from the known to the “new known.” This is really hard learning. You think the world works a certain way, but something happens and you need to change your internal model to reflect this new understanding. This is a disruptive change.
You need to change your internal model to reflect this new understanding. This is a disruptive change.
For the hard learnings, I tend to think that you only learn little by little. There’s a reinforcement process. You need to sort of wiggle your belief loose, a little better every time things don’t come out as you expected, until you eventually believe you should change your belief. There isn’t a clear correlation between learning and a singular event, and you often forget the true source for learning. Unless it’s something really catastrophic, like you blew up a rocket or space shuttle, you won’t have a clear correlation. Maybe some failures are just crystallizations of your learning, like the last nail in the coffin. It’s more of an iterative and continuous feedback loop.
You need to sort of wiggle your belief loose and then continue until you eventually believe you should change your belief.
For a big project, the factors that contribute to failure happen over a long period of time. In the end, it doesn’t go the way you want it to, but there could be a lot of factors behind it. You can think about tuning one thing and maybe the outcome would be different. You can have many different guesses. But you can’t be sure that’s the reason; you don’t have a control group. Only at a later time can you see if you have success with a different approach on a similar situation. The learning comes much later.
The factors that contribute to failure happen over a long period of time.
Learning from your own mistakes is actually harder than learning from other people’s mistakes. You tend to glorify yourself and think you’re more capable than you actually are. And then when you actually realize your mistake, you want to look forward and try something different rather than look backwards. So although you learn things from your own failures, it’s harder to be objective.
Learning from your own mistakes is actually harder than learning from other people’s mistakes.
Sometimes it is not a good thing to accept changes to your “prior known” too willingly. Don’t try to overcorrect your mistakes or to change 10 different things at once. Maybe there is some part you are doing right, and you don’t want to completely change course. Self-introspection is very important. It’s a tremendous help if you can get feedback from others who know you well and can be your sounding board or mirror to speak to you bluntly and clarify your mistakes.
One thing I learned that’s really useful is to always take and keep notes. Your memory can fail and change, and when something happens later, you won’t know what you original thought process is. Your mental state has already changed, and you don’t even realize it. So you need to write down everything, and later you can come back and create a more objective feedback loop.
One thing I learned that’s really useful is to always take and keep notes.
On contrasts between Chinese and U.S. tech companies
My knowledge is limited to Alibaba in China and my own observations of many other companies are from an external point of view. But I do have some thoughts that are open for debate.
- My biggest impression is that Chinese tech companies tend to iterate much, much faster. They’re more willing to try something out and push it to the product. They let the user and marketer decide whether it will stick. (But most of the top Chinese tech companies are consumer-facing companies, not business or B2B companies. Businesses probably wouldn’t tolerate these kinds of experiments.) These quick iteration cycles are also reflected in their internal process, which is very bottom-up. When people want to try something, there’s not a lot of deliberation or asking for permission. You just go do it and prototype, and the upper level will say: yes, let’s try that. The timely execution is a big difference.
There’s not a lot of deliberation or asking for permission.
2. The government is very supportive to innovation and plays a heavy hand in driving it (which can be positive or negative). They give out subsidies and provide strategic directions in their five-year strategic plans. Chinese companies, particularly internet companies, are heavily regulated and they tend to have a much closer relationship with the government. They apply for government funds and support government projects. The government is very, very enthusiastic about pushing the envelope and building technology innovations, often in competition with the U.S.
The government is very, very enthusiastic about pushing the envelope and building technology innovations.
They are willing to leave open some regulatory gray areas, while in the U.S. we have a more rigorous regulatory system. They are more tolerant of letting companies try new things. Then, if they can see the benefits for the public, they start to draft regulations and steer them in the right direction. That is why I believe that China can innovate much faster in areas like fintech, medical AI, and autonomous driving. Even for blockchain, although China has been adamant about prohibiting cryptocurrency, its central bank recently launched its digital currency based on blockchain. They’re looking at the aspects that are truly useful. In the U.S., the pace of innovation in healthcare and autonomous driving is much slower because regulations tend to err on the safe side.
The pace of innovation in healthcare and autonomous driving is much slower because regulations tend to err on the safe side.
3. Third, in the U.S., companies tend to have very focused areas and collaborate a lot. But in China, companies tend to distrust each other. That leads to a “multiverse.” The biggest two universes in China’s internet ecosystem are Alibaba and Tencent. A lot of startups end up having to take sides. There are two main parallel universes and they offer many products in direct competition. Bytedance is probably a lone exception; it maintained its independence and neutral status very well.
On building the most effective company culture
There’s no single “best model” for a company culture. It can differ for companies with different sizes, in different industries. It can even be different for the same company at different stages. For example, the culture for companies that rely on execution would be very different from that for companies that rely on true tech innovation.
But I have do some learnings from a kind of companies that require “collective innovation.” Many of the biggest companies in today’s tech world are not just based on brilliant product ideas or technology inventions. It’s really the accumulation of many people’s work together and the sum of many small parts. Success is driven by many small parts. If you break them apart, you don’t see a significant difference. But the brilliance is in the sum of those small parts. By putting them together you suddenly see a huge competitive advantage.
The brilliance is in the sum of those small parts. By putting them together you suddenly see a huge competitive advantage.
A lot of companies fit that profile. Amazon, for example: you pick all of the things apart and nothing seems super different or advanced. But you put them together and they are just efficient and work together. A lot of the things Alibaba does also fit this profile. It’s called the flywheel effect.
To create this kind of innovation culture, I think the critical thing is that you want to motivate everyone to contribute. In each of their own parts, they need to feel that they have the power to make changes and do something better or unconventionally. You want to make them feel that they are the owner of their whole piece. So you need to start with openness and transparency; everything you do and say needs to be honest and straight. You won’t be afraid if a certain decision being leaked out will be perceived as unfair or biased or self serving. You want to maintain transparency.
The critical thing is that you want to motivate everyone to contribute.
The second thing is: you want to have a very big mission. So, instead of saying, we want to build a product and here are the attributes and aspects, you want to say: here is the end purpose and mission of it. In Alibaba, they have one sentence like: make it easy to do business anywhere in the world. You want to have something really simple and grand, so that people can easily remember and feel proud. If I do something good, I know I did my part in fulfilling the mission. That tends to raise their level of performance.
You want to say: here is the end purpose and mission.
The third thing is, you want to encourage collaboration. That’s easier said than done. You need to set up the internal processes to make sure that collaboration is rewarded. It’s easy to say: okay, we want to have collaboration in our culture. But the rules are set up in a way where there is some kind of zero-sum game. If I win, you lose. That would naturally lead people to not want to collaborate with each other. You need the culture to be respectful and empathetic to others.
The best advice he’s received
I learned a lot from others and mentors throughout my journey. Here are four pieces of advice:
1. Before you answer a question, make sure you know it is the right question that should be asked. A question may be asked with some hidden assumptions that could be irrelevant or even false. It may also have a hidden purpose, but the way how the question is framed may not help discover the right answer to that purpose. The other way to think about it is: if you find a question very hard to answer, you should first ask whether it’s the right question.
Before you answer a question, make sure you know it is the right question.
Similarly, before you ask a question, make sure it’s the right question to ask. What’s behind this advice is first-principle thinking. When people ask you a question, you have to figure out: why did they ask that question and what are they trying to achieve? That’s very useful in terms of resolving conflicts. This applies to more than just questions. It can be proposals that are different from your own. You should ask, why are you proposing this? Make sure you figure out the original intention. Finding common ground is very important for collaboration.
2. When you have more than three priorities, you have no priorities. You tend to feel everything’s important and don’t want to drop anything. But you’re not really driving the prioritization process, you’re being driven by the process. You don’t know what your priority actually is.
When you have more than three priorities, you have no priorities.
3. Be precise and pointy with your words. What this advice asks for is the rigor of your thinking process. I’m working on it myself. Two examples for how this advice can be very important. First, when you make a statement, you should be ready to put your stake on the line and be proven wrong about it.
When you make a statement, you should be ready to put your stake on the line and be proven wrong about it.
When we needed to report to upper management about a software project, we could set the goal as: it will be production-ready by November 1st. The reason we use “production ready” is because we want to shield ourselves from uncertainties during the deployment stage. But “production-ready” has vagueness, because technically you could still push something that’s not actually production-ready by the deadline, and continue fixing bugs during the deployment cycle. So you will never miss the promised deadline and you can always meet it (to avoid embarrassment). That’s not the right thing to do. You should push yourself to something that can be objectively evaluated with no ambiguity. You should say: we will finish all the deployment by December 1st. That’s something you can’t dodge.
Another example: when you state your position, try to be absolute and don’t leave any room for interpretation. Let’s say that we think cloud is a strategy for Alibaba and we want to move internal business units to the cloud. We should just say: “everything should be on Cloud.” You don’t want to say: “most of the companies should be on the cloud, unless it meets conditions x, y, z.” Because then people will squeeze into that “unless” part or beg to add another condition. You know that the company will never be 100% on the Cloud. Having exceptions is the norm, so there is no point to explicitly spell them out. But if you do spell out exceptions, it’s much weaker of a statement. You want to make people know that this is the way to go. It makes your point carry much more weight.
Having exceptions is the norm.
4. There’s a Chinese saying: 三人行必有我师. There is always some virtue you can learn from anyone in a crowd. It is kind of obvious and I only felt its importance in my later career. Many of us who make it to the executive levels were often top students in schools. It was easy for us to be critical and find flaws in other people or a business idea. You shouldn’t dismiss an idea or say that something is not going to work because of this flaw. There are a lot of things you can learn from anybody, particularly your peers. Everyone has limitations and shortcomings, but they also definitely have virtues. They’ve earned their right to be in a certain place.
Don’t dismiss someone’s success or achievements as random luck. It’s not random luck, there’s something there, and you should figure it out. That’s one thing I learned, and I try to not easily dismiss someone’s ideas. On the flip side, don’t be fooled by the halo effect. Don’t look at successful people and think that everything they do or say is correct.
It’s not random luck, there’s something there, and you should figure it out.
Technology spaces he’s excited about
Naturally, I’m a big believer in the Cloud, because I’ve been working on that front for such a long time. I would say that even though the Cloud has become so big now, we are still in the first inning. We are at a very basic stage of utilizing Cloud. Because of COVID-19, a big part of the world that was previously offline now has to become online. That means a digital transformation process for many companies.
This also opens the question, how can we replicate social experiences from offline to online? That’s another area I’m very excited about. Thirdly, I’m keen on sectors that are currently very human labor intensive. Those are the ones that are very prime for disruption at this stage. For example, agriculture, energy, healthcare, logistics, and manufacturing. Obviously, there are many obstacles in terms of AI or robotics, but I’m excited about the prospects. I think the key technological areas for disrupting these industries will be in new sensor technologies, new materials, battery technologies, and robotics. Those are the areas I’m interested in, similar to the rest of the software team at Tsingyuan.
I’m keen on sectors that are currently very human labor intensive. Those are the ones that are very prime for disruption at this stage.
His hobbies
Reading, running, and taking photographs are my biggest ones. Other than that I probably spend the majority of my spare time playing with kids.
His book recommendations
As you get older you become more curious about philosophy. I want to recommend four books that can be grouped together into one topic — Big History. So from the Big Bang to the origin of the human race to evolution and then to the future of the human race and the universe.
- Origin Story: A Big History of Everything by David Christian. It covers from the Big Bang to the end of the human race (in the author’s speculation). Read this first as the framework.
- A Briefer History of Time by Stephen Hawking. I like this version rather than A Brief History of Time, because I think it explains concepts more clearly. This one touches on the universe part of Big History.
- Sapiens: A Brief History of Humankind by Yuval Noah Harari. I am sure everybody knows this one, and it covers the human history part.
- Life 3.0 by Max Tegmark. He’s an MIT professor. The book deals with the future of human beings. You see from an evolutionary perspective how the human race will evolve together with AI.
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