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“Every generation laughs at the old fashions, but follows religiously the new.”― Henry David Thoreau, Walden
In my last post, we talked about why AI automation is the new industrial revolution. At its core, such revolution represents a major landscape shift that will give birth to a new breed of tech companies — what I called the AI-first species.
Just like any emergence of new species in mother nature, AI-first companies, although share some common traits with traditional software/ SaaS counterparts, carry very different characteristics. More interestingly, the new species behave, in many ways, more aggressively than the incumbents.
In this post, we will examine a few intriguing aspects of this AI-first specie: from the gross margin, product form, business moat, to ultimately the billion-dollar question — how do we adequately measure the size (value) of these AI-first companies.
1) Unlike typical software companies, the “AI-first” companies might have a non-software-like low margin (at first). And it might be a good thing.
Investors love the 80% margin business. So do traditional software companies. Over the last decades, we have seen powerful high-margin software companies — such as Salesforce, Oracle, and SAP — created and dominated the respected fields for a long time. One of the advantages of having a high-margin product is that it allows you to stack up on your well-oiled go-to-market machine continuously. In other words, it enables the incumbents to be extremely good at doing what they have been doing. And it’s a comfortable situation.
For the new species of “AI-first” companies, they wear the cover of “low margin,” at least initially, to enter different business territories. And this is not by choice. It’s the embedded nature of AI companies at its initial phase for the following two reasons:
a) In the field of AI, it’s easy to get to 80% accuracy; it takes investment and resources to get to 95%, but it’s near impossible to get to 100% because of the diminishing returns of solving the last 5% edge cases. Because of such dynamics, AI companies still employed humans on two fronts — data labeling/training and edge-case solving. And these humans are often data scientists who are not cheap. The cost of such eats away margins.
b) Contrary to popular belief, AI computing actually costs more than the traditional one, especially as more training data accumulates *and* as your algorithm is getting more complicated. Ironically, AI companies’ cloud computing costs are likely to be much higher as the business becomes more successful. And this is not even counting the often-ignored fact that AI companies, unlike traditional software ones, will need to retrain or “refresh” their data-algorithm periodically to refresh the latest reality (e.g., mapping data, latest business wording, etc.)
It’s worth noting that both constraints above are not unsolvable, especially as we make more progress on the improvement of AI-computing infrastructure. It will just take some time. Therefore, these AI-first companies will usually carry a non-attractive low margin, at least initially.
Believe it or not, this might be a good thing, which leads me to my second point.
2) “AI-first” species’ low margin is its deceptive camouflage. Underneath, it is often a highly attractive ROI solution or service. It should get incumbents worried.
As Clayton Christensen — author of the classic book “Innovators’ Dilemma” — would point out, disruptive new entrants usually come in the form of “non-attractive low margin” business that’s “easy to ignore.” Such dynamics happened when Minicomputer (DEC, Wang, etc.) disrupted Mainframe Computer (mostly IBM), and then quickly Personal Computer (Microsoft, Apple, etc.) made Minicomputer absolute. In both cases, the emergence of Minicomputer and PC came with audiences that were rather niche but were proliferating nonetheless.
The nature of a “niche” market made the “customer-driven” incumbents turn the heads sideways because their main customer base didn’t demand either Minicomputer or PC at the time. More importantly, the “low margin” characteristics of the new entrants essentially stripped incumbents’ incentives to be “lean” and to be innovative again**.
Now with such framework in mind. Let’s look at what’s happening now.
AI-first companies are attacking new territories and replacing older software the same way illustrated in the PC era. Yet AI-first companies are making the moves more aggressively in a pattern we have rarely seen before. So it’s incredibly tricky and dangerous for incumbent tech companies on two folds:
1) Unlike traditional software companies that usually offer one specific value (i.e., Salesforce for CRM, Box for storage, etc.), a robust AI-first company might propose itself as a full-service company with better ROI for customers. For example, we have seen AI companies “disguise” as a virtual lead-gen / sales force service agency that could potentially replace companies’ in-house business development or sales staff. Under the hood of these “service” companies, most of the operations are automated through AI. Therefore, it results in lower monthly costs to the customers, even though the initial COGS might be higher than that of AI-first companies.
On top of that, it would be easier to match sales/lead gen performance against the cost: it’s not hard for an executive to choose $100K on sales staff vs. $20K “service” fee to this AI solution. Other territories that are being trembled are: customer service/call centers, executive assistants/ scheduling, and legal document review/ compliance, just to name a few.
The customers who are responding well and quickly are often the ones who value cost-efficiency the most. They are usually startups and SMBs. They are AI-first companies’ first “nitch market” that is often underserved (and overcharged) by incumbents. They are the beachheads.
By establishing an ultra-strong ROI case on a particular business function (i.e., sales, call center, EA, etc.), AI-first companies are quickly building up the beachheads before attacking incumbents’ primary market — fortune 500 customers.
2) On the incumbents’ side, the existing high margin software business offers little incentive to explore AI-service-like products with a lower margin. More importantly, much incumbents’ existing customer base — the stable large-cap companies — might be willing to try out some AI-first products, but they do not demand them.
First, the mainstream market, by definition, is conservative and usually likes to wait until fully adopt a new product. Second, thanks to software incumbents’ decade-long effort in building high-switching costs to their products, the customers are even less likely to be proactively looking for new solutions.
Therefore, the “conservative” customer base, plus the high margin “lifestyle,” will immobilize incumbents to react and defend the inevitable take-over from the new breed of AI-first companies. Such is life.
However, this is not to say that AI-first companies don’t have shortcomings. Other than the “low margin” factor as mentioned above, AI companies will have to figure out a few things, including the sustainability of the moat. This lead to my third point.
3) Unlike typical social network or marketplace companies, the moat for “AI-first” companies might not be deep. Therefore, the initial data advantage and an ongoing low-cost data acquisition would be the key.
Because AI algorithms are widely open-sourced, the keys to building a defensible business are proprietary data and the method of keeping acquiring quality data cheaply***.
Because of such dynamic, it’s not hard to foresee the successful breed of AI-first companies will be heavily vertical-integrated and even service-oriented (at first.) Therefore, there won’t be such a thing as horizontal AI (with the exceptions that maybe Alphabet or Microsoft can morph into horizontal AI players). Instead, we will be seeing AI companies build their data pools, users, and brands in specific verticals such as healthcare, payment, media, automotive, and manufacturing.
We are still in the early days. I don’t think we have figure out the best practices of obtaining sustainable data moat yet.
On the one hand, it could be a capital intensive endeavor as we have seen Google/ Waymo invest billions in its self-driving AI as it keeps updating the mapping and driving data on its own. On the other hand, we have seen some startups being creative by striking partnerships with hospitals, payment processors, and OEMs to get the initial data advantage started. However, is either approach sustainable and scalable? We don’t know. We haven’t figured out the formulas as much as we have on many of the SaaS calculations.
One might imagine a very different pricing model that is offered by AI companies. We have discussed AI-first companies might charge customers on a service basis (initially). But the pricing model might eventually mutate into data-discounted pricing where the customers might enjoy much of the discount in exchange for the training data they contribute. So that would be very different than the typical SaaS companies’ per-seat model.
Parting thoughts: the next mega-giants?
How do we, the investors, properly evaluate these pricing models and the underlying business created by this new breed of “AI-first” companies?
I don’t have the definitive answer, but I would expect it to be different from a typical Cloud/ SaaS multiple. My guess: In the coming ten years, we will be witnessing a new breed of tech companies that are much more automated, intelligent, and ever more embedded in business functions. And this unleashes value.
The market valuation for these AI-first companies will likely be much higher than the “1-billion-dollar unicorns” over the next decade — perhaps we will see a few trillion-dollar companies across the US and China. What would be the AI-first equivalents of Amazon, Apple, and Alibaba?
If history is of any guidance, we should be well prepared by studying the trend and then embrace it. Fully.
** Another example would be Netflix vs. traditional media companies. Started as a DVD rental business (i.e., you actually have to mail out physical DVDs and then expect consumers to mail them back via US Postal Office), Netflix’s original business model was heavy with DVD warehouse and intense sorting and mailing labor operation, thus, relatively low margin business. Because of the initial “low margin” characteristic, many media senior executives were blindsided. The gravity of short-term quarterly profit pulled them away from the long-term threat of Netflix. Many in the media industry failed to imagine how Netflix could morph into a digital-first streaming product that left giants such as Disney, Warner to play catch-up.
*** This is assuming everything else being equal. It’s worthwhile to point that compared to traditional software companies, AI-first companies might have to be better at sales and marketing as the customer market will experience a learning curve on its own. Within the AI companies — which are often staffed with engineers and data scientists — the ones who have the best GTM approach /team will dominate, since the end market doesn’t care about the technology but rather the ROI-proven solutions.
“Money” and “Wealth” are two simple concepts that people often use interchangeably. Growing up, I have always thought these two are the same. That turns out to be a mistake. They are two different things — i.e., money is a medium of wealth, but wealth is not all money.
Let’s talk about money first. It usually comes with a currency sign and can be in the form of paper or digital credit. A simple enough concept we typically don’t overthink about. At its essence, money is a fictional concept that we humans together have faith in, just like religions, corporation entities, and even Bitcoin. If we look at human history, it was a big breakthrough when humans collectively decide to take this concept of “money” for trades instead of real goods. Money allows convenience and enables faster trades when you don’t have to drag a sheep for shoes. Money is a medium of wealth, but it’s also an enabler for speedier wealth creation. So when we say “how to make money,” we mean “how to make wealth.”
Now let’s talk about wealth.
On a macro level, wealth represents a society’s overall living standard, wellbeings, and goods it possesses. And these tangible and intangible kinds of stuff are created by humans working collectively in a flexible fashion.
For example, living in the modern world, we don’t need to ask for or get to the know the person who makes our clothes, preps our food or build our shelter. We have this massive system called “Division of Labor” — with each member making things that other people want. More importantly, we can do it flexibly within either a small commune group or a thousand-person entity called a multinational corporation. It’s a powerful thing. In the animal world, for example, bees can have a perfect “division of labor” system, but the structure is very rigid, and there are certainly no corporations among the bees.
Humans are the only species who can create wealth on a massive, systematic level and yet in a flexible, adaptable fashion. And that’s how we create wealth for humanity as a whole.
Now let’s zoom in to a micro-level. An often-used phrase “turn lemon into lemonade” does capture the essence of creating wealth. In this case, one lemon at a time. For example, on a hot summer day, a little girl — also a future entrepreneur — bought a lemon for $0.5, squeezed it, and put into a cup. Now it’s sold for $1.5. Then that extra $1 is wealth that didn’t exist before she squeezes the lemon.
It’s important to note that the dollar sign (money) is a measurement of wealth but not wealth itself. Now let’s say if the little girl doesn’t sell the lemonade but instead drinks it herself. Does that wealth disappear? No. The wealth was still created because it had improved one’s living condition by quenching the maker’s thirst on a hot summer day. Other examples would be that if you decide to renovate your house by yourself — the end product would definitely increase the value of your home (assuming you don’t have a terrible decor taste.) But even if you don’t sell it, the renovation improves your well beings and life condition. And that’s wealth.
So making wealth is about making stuff people want, for oneself or others. Once we establish that, we can then dig into the topic of how to create wealth fast.
You would generally need two qualities: 1) make things not just for yourself, but for many others**; 2) make things once, but they can be used by others many times. In business terms, the first one is called “total addressable market,” and the second is “scalability or leverage.” There is a reason that investors love technology business because it usually resembles both qualities. If we look at the most valued companies and the wealthiest people today, most of them are undoubtedly in or related to the technology business (Financiers can get wealthy too because they usually master the quality of “leverage.”) It’s not coincident.
I believe it’s important to have such a mental framework for money v.s wealth, as wealth is the one we are seeking to create, and money is often a measurement of that. So “how to make money” turns out to be a false question. What we really want to have is to create wealth. To do that, we will need to make things other people want — hopefully, many people will want it; ideally, we want to make it once but sell it many times. Simple yet tricky, for that it’s the essence of technology entrepreneurship and venture capital.
Either you are a founder or a VC; what we stand behind is the startup entity that’s going to change the world. Often time it's hard to tell if the evolving market is big enough, especially if you only get to stare at the current one. Think Airbnb vs. hotels in the early days; think Google vs. Yahoo plus thousands of other search engines; Think Salesforce vs. on-premise CRM solutions. There was no way to know if the majority of people in the future would need the stuff you are building/ funding now. Hence the inevitable uncertainty of wealth creation. Unless you can envision. Or imagine.
Albert Einstein’s famous quote goes:
“Imagination is more important than knowledge. For knowledge is limited, whereas imagination embraces the entire world, stimulating progress, giving birth to evolution.”
The longer that I am in the technology and investment business, the stronger I hold on to such belief: the ability to imagine is the key for the ultimate wealth creation and is what separates a great Founder / VC vs a good one.
And in venture, being great is where it all matters.
**we can go more in-depth on the first quality — i.e., make things. I do believe what to make matters. There is a substantial difference in making things that will drastically increase society’s productivity versus diminish it, although both ways can make the makers very wealthy in the short term. But that would be the topic for another post.
For a long time, I’ve had this old poster that illustrates the mechanics of the first steam engine in my office. One might wonder what does a steam engine has to do with the “groundbreaking” technology companies a VC gets to interact with. The answer is “drastic productivity improvement.” The poster helps remind myself that with each tech breakthrough, it unleashes a tremendous amount of productivity — thus, value and wealth — within the society. Like how the industrial revolution freed up labor and accelerated production, the age of AI Automation is going to generate significant value for humanity in multiple ways.
Why AI Automation matters now
The term AI is not new — it originated in the 1960s among computer scientists. However, the real breakthroughs came within the last decade when we have developed new algorithms/ techniques set of Machine Learning (a subset of AI), Deep Learning (a subset of ML), Reinforced Learning and Transfer Learning, etc. Because of those, coupled with an abundant amount of data for training, cloud computing, and sophisticated advancements of hardware AI chips, we are seeing highly valuable tech products being created every day based on such breakthroughs.
AI automation can materialize itself into multiple forms of products:
1) New product/category. Examples include self-driving cars, voice-enabled IoT, etc. Without AI being the backbone, we wouldn’t be able to enjoy these products;
2) Help with existing products’ scalability. Chatbot, virtual executive assistants, and face/image recognition would be in this category. It’s the territory where we used to have products in place but were either a) rule-based or b) man-powered and not scalable;
3) Inject efficiency and efficacy into software products. This is the category I’m most excited about as it will have profound implications for both B2B software / SaaS and enterprise customers across multiple industries and verticals. Think high-accuracy fraud detection, robotics/ smart manufacturing, predictive maintenance, and auto business insight, etc.
What has happened?
Over the past five years, investors have rushed into the AI space without thinking too deeply about the hype cycle. Namely, we have funded many self-driving cars/trucks/tractors and the related sensor components, but few can claim victory just yet. Instead, the abundance of capital inevitably diminishes the upside return and typically excludes startups’ purpose in solving a real market need.
That being said, one of the benefits of re-examing the AI investment landscape is that most of the hype dust is settled and we now have a clearer view of this new macro trend. The trend is going to boost humanity’s productivity to the next level.
Characteristics of the new “AI-first” species
What the new AI automation presents is a unique landscape shift that will make many incumbents struggle to adopt. On the other hand, it will also give rises to many “new species**” companies that are AI-first.
Last few times when major landscape shifts took place, we have had “new species” rose in response to the new world. Think Industrialization (Ford Motors), Computer (IBM, Intel, Apple, Microsoft), Internet / Cloud / Mobile (Salesforce, Amazon, Google, Facebook). Iconic companies were created when they can ride major tech tides.
This time is no different. Except the unleashed productivity will likely be in the trillions of trillions of dollars, and the impact will last centries. That’s why we need to study and take a closer look at the early characteristics of these “AI-first” companies — the new type of specie that they are.
In the next post, we will examine the interesting characteristics of these AI-first species…
**As strange as it might sound, when I was a kid, I was fascinated by Darwin’s book “On the Origin of Species.” The work not only lays out how animals adapt to a new environment, but it also paints a competitive dynamics between the old and emerging species that leads to such adoption/evolution. Even as an adult, I still love books and documentaries about nature.
It has absolutely delighted me when I find out how similar it is between nature and our business world — i.e. bio-ecosystem vs market dynamics, landscape shift vs new tech breakthroughs, startups & incumbents vs new & old species. How the business world evolves is really not that much different than our mother nature.
This started with something silly. I ran into some click-bait youtube videos with dramatic thumbnail photos (of course!). They showed the drastic differences of “before v.s after 30-day burpee challenge.” It was at the beginning of the lockdown, so I thought to myself, “why the hell not? I’ve got time..”
So it began.
I downloaded a free app to count my daily progress. The app allows me to start at a lower count (30 burpees a day) and then gradually increase to 175 burpees a day. Truth to be told, I only made it halfway: I wrapped up 100 burpees on the 15th day, counting close to 1000 burpees finished over two weeks. The reason being that I found it increasingly difficult to combine 100 burpees a day with my regular resistant training since my major muscles were fatigued all the time. It was a big bummer since I really felt great, even having made it only halfway. It improves my strength and conditioning, and I hope I would be able to pick it up once again in the future soon.
One thing a YouTuber who was doing the challenge said had echoed in my head, which I’m paraphrasing here: “as you are doing these mindless, repetitive burpees every day, your mind is conditioned into this ‘fall and get up, fall and get up’ mode, just like life…”
Well, who knew burpees could be so zen!
This is my second attempt in cold showering. I tried it the first time when I was catching up with my friend Aki last year. And through him, I learned about the Wim Hof Method (TLDR: his own breathing technique + cold shower). It was actually somewhat extreme to me. But I gave a try regardless. And the very second day, I caught a cold. So I stopped.
For whatever reason, I bumped into those “cold shower changed my life” videos again during the lockdown (The AI must be targeting me). So I gave it another try: only this time, I didn’t start with cold water immediately. Instead, I took my regular warm shower and then switched to cold water for the last 1–2 min when I needed to rinse off.
Interestingly, time always seems to slow down when you watch your hand is on its way to turn on the cold water, like a slow-motion playback. During those moments, a few thousand things are going through in your head — things like “wait a minute, didn’t you just do that yesterday when you were screaming like a little girl” and “why am I doing this, it’s still not too late!”
But I must say, cold shower worked for me this time. It’s a great way to start your day (some people take it both morning and night time, but hey, I’m not that crazy… yet).
I think it does take your body a few days or even a few weeks to become fully adjust to the cold shower norm. But this is where you realize that the human body is a very powerful, adaptable machine. Despite how uncomfortable it is in the beginning, your body and mind will learn to adapt. Physiologically, cold shower trains our minds to be okay with consistently stepping out of the comfortable zone; and it helps our bodies act on impulses, in a good way.
I think I will keep doing the cold shower thing :)
Reading before bed
I feel lucky that I have been more conscious of setting aside time for reading over the past two months. Before the lockdown, life seemed to pass us by so fast with travel, social occasions, etc. and if I were lucky, I might get some weekends to catch up on the books I’ve been meaning to read.
Since I am not able to travel as frequently now, the anti-social quarantine time does provide a safe bubble for a more stable routine. Although it’s still to be seen, I have been somewhat consistent in setting aside 1 or 2 hours for reading before bed.
For me, I like to mix a few books at the same time. Currently, I’m reading Exhalation by Ted Chiang (fiction), Unlocking the Mysteries of Birth & Death: A Buddhist View Life by Ikeda (non-fiction) and The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail by Clayton Christenson (Business — a classic, can’t believe I’m only reading it now).
Yep. I tried it again too. Not my thing. It only resulted in many late-night binge eating and self-loathing :(
I enjoy cooking. It provides me with a time and space where I can just focus on one thing. As strange as it might sound, cooking is kind of relaxing for me. In the past, I have been a long-time subscriber to meal prep services like Plated and Blue Apron. Each time I finished a well put together plate, I feel a sense of accomplishment. (I’m an easily satisfied person ;)
I used to not understand why anybody (mostly the weight training guys) just let the boring meal-prep boxes suck the joy out of their lives. However, as life gets busier, I turned into one of those meal-prepping joyless guys.
I usually do it once a week and prepare six meals at once. I leave out Friday / weekend for the “fun meals”— that is, I can order take-out and eat whatever I want on the “cheat day.”
Embarrassingly, those “cheat days” often become “cheat weekends,” but luckily haven’t turned into “cheat week” yet. We will just have to see.
I was lucky enough to get my hands on a PC in the 90s, among the first waves of families owning a computer in China. My first programming language was BASIC. It sounds so ancient (and basic!). And it was. The TIME magazine wrote a long piece on this language, and it was fun to read, especially by staring at the old “minimalist” interface again.
During the shelter-in-place, I felt it might be a good opportunity to brush up on the coding skills again. Only this time, not with BASIC. I’m picking up Python, and reading up all I can on AI / ML. We will see how it goes.
Breathing matters. I didn’t realize how important it is paying attention to our breath. By being conscious of our breath, we are actually sending an active signal to our brain and body to help us live in the moment.
For most of the days, I keep meditation twice a day. And because I know that maintaining consistency is more important to me than the duration, I only keep each session at roughly 5 -10 min. So that I know even at the most tiring night, I would be able to practice it before bed.
Journalling via audio
This new habit has been incredibly helpful to me. I used to keep a habit of doing a five-minute journal for several years until I find myself often too tired to type/ write at the end of the day. However, thanks to the new AI, I now can easily do audio journaling while having my words transcribe simultaneously (amazing how accurate the AI service could be).
Coupled with daily meditation, the journal helped me uncover a lot of weakness in me and help me reflect on a lot of deep unresolved emotions that were not previously discovered. As funny as it might sound, my journal notebook has been an incredible therapist for me and has helped me recognize some major personal growth hurdles. I think I will keep doing that.
So here are the few things I picked up during this lock-down time. As the world is turning more upside down, it’s ever important to keep our inner peace and use this window to do more self-reflection. I thought it might be interesting to document the strange period this way.
This is the article I had long intended to write. My last (2018) post on US-China became quickly dated because of the trade war in 2019 and then the pandemic outbreak in 2020. The situation is changing so fast that the whole world is merely trying to catch up. There is never a good time to write on this topic, so here it is.
Just when we were grappling with the global economic impacts of the US-China trade war for the better part of 2019, no one had expected it was merely a rehearsal. We had not dared to predict that anything bigger would come.
Came it did. A once-in-a-century pandemic that has, tragically taken over 120,000 lives, impacted millions in losing their jobs, is truly a Black Swan occurrence that will leave its mark on future generations.
At a time like this, it’s important to be a student of history, so that we can get a better, if not a more holistic perspective on things. One may say that our past consists of Black Swan events. To list a few from recent to more distant ones within the last century -
You might be able to see where I’m going with this.
Black Swan events are not always bad — they represent infrequent, unpredictable, major changes. Sometimes changes are for the better like the invention of the internet, but often are disruptive and can be detrimental to society as a whole. Yet we have shown the resilience of the human race, each and every time. And we have always learned and adopted something new from the experience.
The COVID19 pandemic is a once-in-a-century event. One might say it’s a combination of 1918 flu (disease) + great depression / financial crisis (employment loss) + worldwide (war-like) defense. It’s nothing we have ever seen.
So what does it mean for the world going forward?
New World Order: the great decoupling accelerated by the COVID19
Our generation has enjoyed the tailwind of globalization over the past few decades. And now the pendulum seems to swing the other way. As I’m writing this, countries, including the US, China, Japan, and major European countries, have all adopted strict policies of flight travels. Noticeably, as each nation is scrambling to handle its own coronavirus crisis, we have unfortunately seen little global collaboration. Instead, we have witnessed mistrust, misinformation, scapegoating, and interfering.
It’s disheartening for sure, but not surprising. Thanks to the tone set by the trade war, the US and China have started its painful decoupling procedure, followed by the world’s search for new leadership in the global stage. For someone like myself, a Chinese immigrant to the US, it feels like you are caught in the middle of divorcing parents. It has been messy, uncomfortable, and emotional.
China and the US have very different political and societal structures. I can empathize on both sides, as a person who has spent a roughly equal amount of life in both countries. Amidst Covid19, the US and China demonstrated to the world the pros and cons of their systems — China, with the big government, showed impressive strength in containing and stopping the virus by rallying the entire nation’s resources behind one task.
The US, with the democratic system and its current white house leadership, has shown the opposite — the lack of attention from the beginning and then the chaos during. However, the US system shines its advantages during the “peacetime” when it makes sure the decision power is not overly concentrated and (ideally) quality decisions come from thoughtful deliberations.
It might be easy to fall into the heated debate on which system is better. But this post is not about that. I expect that both systems, just like Yin and Yang, can and will co-exist equally in the long foreseeable future.
The keyword at issue here is “equally.”
Future is past rolled into presence
According to the chart below, over the past 1400 years, China had been the #1 for roughly 850 years in terms of global power (starting from 600 AD to 1250, then 1400 to 1600). And it’s no surprise to anyone who studies China’s history that China is coming up and “reclaiming” its global position. On the other hand, the US has been the world’s # 1 power for less than 100 years and is very anxious in retaining its global leadership. Since Trump’s election, the America-centric view has been boosted. The Covid19 development has only accelerated such trend and hardened the viewpoint of the populists. But it is a slippery slope. Closing the border may have short-term comfort, but the long-term damages are yet to come.
China knows it fully because it had suffered from it. To the western world, China appears to be this “mysterious dragon” that just woke up and ready to take over. However, few realized that China was going through a painful nineteenth and twentieth centuries when trading prospered the rest of the world. For much of the seventeenth and eighteenth centuries, China was steadily declining, being fully ignorant of the emergence of the Netherlands and UK empires.
Until the 19th century, China continued to see itself as the center of the world, with neighboring countries bowing to its Emperor. As time progressed, China became more closed up with uprising nationalism and smug complacency for centries, even as the western world was going through a major tech breakthrough, namely the Industrial Revolution in 1760. We all know what happened afterward. China was left behind for the following 200 years, was invaded many times, and has ever since attempted to catch up.
History seems to be repeating itself on its early pattern, only this time in the US, not in China. While the US is focusing on its political fights and its close-up “America First” policies, the rest of the world, certainly China, is beaming with 5G, Clean Tech, and AI automation. This early trend ought to worry everyone.
It is my hope that, with its democratic structure, the US will not follow the suit of old China. Hopefully, the 2020 election will help slow the swing of US nationalism and place the US in a non-hostile position with the world.
In any case, we are likely to see a world moving forward with two “parallel universes.”
We are certainly at a historic moment, and it would be fascinating to see how the “parallel universes” dance with each other (hopefully more peacefully) over the next decade.
Like everyone else, I’ve been spending a fair amount of time trying to understand the length and impacts of this pandemic. (I will try to write COVID19’s impact on the new world order in a separate post)
The “hammer and dance”
First, let’s talk about duration. I will be the first to admit that a lot of us were in the phase of denial, thinking that “oh, it’s an outbreak in China” and “oh, it will last only a few months, and things will be back to normal soon.” But in reality, we will likely be living in this “hammer and dance” dynamics for the next couple of years.
At a high level, what the researchers present here is that our social activity will emerge and retreat based on the cyclicality of the virus. Since we can not completely contain or remove COVID19, the situation will continue until the vaccine comes out and is distributed to billions of people worldwide for the next two years.
It’s a very dim vision, I know. But if it’s the truth, we should keep a rational mind and prepare ahead. Specifically, as founders and investors, we should be thinking about the future, what our society needs in which what will change, and what will not.
I will start with something simple — things that won’t change, perhaps never will — the basic human needs. People still need to eat, shelter, work, socialize, feel worthy, love, and be loved.
However, a lot will change, mainly how we deliver/resolve those needs, if not entirely reimagined in the post-COVID world. Whether you agree with it or not, the pandemic is forcing humanity to overhaul our status quo and to reexamine our priorities.
In a way that’s not trying to predict the future, I’m convinced that we are likely to see a few megatrends playing out in the few decades owing to COVID19. I will list the following three as examples.
1. The “stay-at-home economy” would further penetrate our society, taking more values away from the conventional offline economy.
The “stay-at-home economy” category is not new — it consists mostly of the internet companies we see today. Netflix, Zoom, Amazon, Doordash, Facebook in the US, along with Meituan, ByteDance, Alibaba, Tencent in China, were all founded before the pandemics and are all taking the tailwinds.
But that’s not all. Some of the “tougher” categories would be cracked: Grocery, higher education, healthcare, mobile payment, cloud-kitchen, fitness, etc. In a post-pandemic world, how people buy, learn, care, pay, eat, and work out will be changed in an accelerated fashion.
A months-long window of habit-forming is a powerful thing. Just when the global B2C opportunities were nearing to the tail end in 2018 /2019, I expect we might see a new breed of “stay-at-home” companies that will be created in the next few years and completely reimagine the way that we live.
The “losers” owing to the pandemics are the traditional economy consisting of restaurants, shopping malls, gyms, office spaces, and so on. Their values are being squeezed out and will have to find a new place to go. What this means is that the “offline economy” will either have to embrace the digitalization more aggressively or compete harder with new offerings. I don’t think restaurants, theaters, airlines would go away, despite popular beliefs. Instead, they would be “upgraded,” perhaps much more “personalized,” catering for a new type of experience. That takes me to my second prediction.
2. Social norms will never be the same. In-person time will be “luxurious.”
Many years following the potentially two-year-long pandemic, we will continue to keep our distance with each other. Handshaking is likely not going to happen in most social settings. We will start to see in-person meetings much like a “luxurious” experience, reserving it only to those we love, care for, and consider important.
By “luxurious,” I don’t mean the service will be expensive; it may very well be affordable and minimalist — it just means that psychologically, people are going to set aside a special place for the in-person time. And they would want it to be unique, well planned, and about who they are.
I don’t know what format and at what price this new type of service will be offered. And I don’t know how technology would be leveraged to achieve a reasonable scale such that more people will be able to enjoy it. But I know there will be needs for it. And people will pay for it.
3. Digitalization and AI automation will be accelerated
During (and after) this pandemic, most enterprises worldwide are (and will continue to be) pressured on two ends.
First, the frontend. Following consumers’ demand for digital experience, companies will be replacing a more considerable portion of their “fat infrastructure” (e.g., physical space, human-interacting staff) with leaner tech stacks (e.g., cloud, bots). For instance, certain restaurants might not need to rent a full venue to serve their customers. Instead, they would open shops on delivery apps. Physicians might only see patients in person on a very selected basis, with most people comfortable with telehealth service going forward.
We have seen this consumer digitization trend taking place in China over the past ten years in areas like food delivery, remote health, and mobile payment. However, it would be fascinating to see the US is finally getting on the transformation. Tremendous values will be generated as companies in various verticals are switching to a new “interface.”
Second — probably a more important point — we would expect businesses worldwide to be challenged on the backend- the company operation side: e.g., logistics, manufacturing, warehousing, sales, marketing, recruiting, planning, etc. What it means is that as the economy takes on further downward pressure over the next few years, companies will have to work out a more efficient, automated way to operate on the backend, *while* many of them are forced to adopt a more digital frontend.
This represents a significant challenge and opportunity for enterprise software companies. For one, it will push B2B companies to demonstrate their ROI even more. The nice-to-have “vitamin” B2B solutions would be washed out, quickly. And two, just like a sick patient in need of good medicine, corporate customers are more eager to experience and try new solutions, particularly solutions that can solve their transformation dilemma. But the catch here is that you will have to show results quickly.
On the backend, a mere “digitalization” or “change of the interface” is not enough. For example, with manufacturing, it has never been about making digitalized records but rather how to use that digitalized information to make intelligent decisions, or better yet to automate certain tasks so that efficiency can be created. We are seeing startups like PlusOne Robotics, Kubit.ai that are taking an AI-first approach to demonstrate such ROI through automation, and will expect to see more.
In all honesty, the solutions will continue to come and evolve, but in the enterprise space, market readiness is the key. In a post-pandemic world, most enterprise customers worldwide will not only be ready but will demand a new form of software or solutions that will help with the automation of business tasks. It goes beyond “digitalizing” or “moving to the cloud,” it will push us into a new era of enterprise tech that is enabled by AI and automation.
Like every generation ahead of us who have gone through famine, wars, and the Great Depression, we are experiencing our own crisis. In Chinese, crisis (危机）is written as “danger and opportunity” in a single word. It cannot describe what we are going through any better. It is a tragic occurrence worldwide, but it’s also a forceful catalyst for our society to evolve, improve, and adopt a new, more reflective norm. When we look at humanity’s history, we have always come out the other end, stronger and more unified than ever before.
And this time is no different.
首先，让我们谈谈持续时间。 我将是第一个承认我们很多人处于否认状态的人，认为“哦，这是中国的爆发”和“哦，它只会持续几个月，而一切很快就会恢复正常” 。” 但实际上，未来几年我们可能会生活在这种“锤子和舞蹈”的动态中。
我知道这是一个非常黑暗模糊的愿景。 但是如果这是事实，我们应该保持理性的头脑并做好准备。 具体来说，作为创始人和投资者，我们应该考虑未来，我们的社会需要什么，什么将会改变，什么不会改变。
2020 has caught everyone by surprise. First, the coronavirus emerged and China was taking swift action in shutting down cities but the world was paying little attention. Then the virus spread and the global economy ground to a halt. Now we are all scrambling to adjust ourselves to the new reality that is mixed with fear and anxiety.
It might be easy to surrender ourselves to the overwhelming news and the uncertainties to the future. But if history is of any guide to us, we know that major crises are usually filled with mega opportunities, and that things will return to normal one day.
But for now, enter social distancing.
You have nowhere to go but to stay at home, with yourself. And our minds are not used to that. We were used to grabbing morning coffee with our friends, chatting with the coworkers during the day, and cuddling with the loved ones at night. And now, suddenly, we stare at the mirror and the mirror stares back. We are by ourselves.
Even though I still fill my schedule with back-to-back conference calls but it's just not the same. Somewhere inside me keeps asking me the question: so what truly matters to you.
The COVID19 outbreak provided us the opportunity to take a pause and re-evaluate our priorities. I had the chance to think about several issues in life since I had been working from home for the last week. To remind my future self on what is important and what is not, I want to compose them here:
Health and families come number one.
Without health and families, the future does not matter. Early this year, I already lost my grandma and I certainly want to see myself and my families stay healthy.
Helping others matters.
It takes courage to go beyond our egocentric selves and to care for others. In the past, it was easy to brush it away by simply saying that I was too busy but during this crisis, witnessing countless medical professionals and volunteers stepping up had a significant impact on me. We all need other people's help one day. It's all for one and one for all.
Humanity as one.
In a crisis, it's easy for us to turn against each other out of fear and hatred, but let's resist that. The world does not need one or two politicians to lead us. But instead, all of us can start from within to calm the fear and start to embrace the uncertainties.
As a human race, we have to reckon the damages we have done to the environment, other animals and the earth. As we all become adults, we have long put aside our childhood ambitions to become astronauts or to save the earth. But maybe it's time we all pick it up.
Do your job, but with a bigger goal.
Each of us has a role to play in this society. The once-in-a-century crisis offered us the opportunity to examine our contribution to the world and, once again re-appreciate the things we take for granted. Many restaurants we visit are now closed. The over-talkative barber who we once felt overwhelming is now much missed. The noisy bars across the street are not filled with dreadful emptiness.
As a generation who grew up without the Great Depression or severe property, we think the world is always up-to-the-right, with many services available to us, just one click away. The so-far weeks-long social distancing teaches us the lesson of valuing other people's work and rethinking of our own.
I hope when the whole thing is over, we come out of the other end much stronger. Much more energized in building the common future. I certainly am. I know that after the pandemic passes, the world will be the same, but yet not the same.
It is often said that crises are embedded with opportunities. I'm a true believer in that. As a VC, in a way as a societal resource allocator, I will be even more excited to find the next opportunities with resilient founders.
Our world economy mirrors nature. New species and vibrant ecosystems only emerge after a devastating storm. We are in the midst of that. I'm worried as anybody else, but I'm ever optimistic about the future.
My grandmother and I were really close together. She raised me mostly and had made me who I am.
She was diagnosed with late-stage liver cancer in late December 2019, and we had been told there is not much time left. Mom called me and was weeping on the phone, telling me the news. I asked to video chat with grandma. She was lying on the bed, looking tired, but as usual, her voice was loud. She managed to smile while we were talking somehow. Looking back now, she must have made an enormous effort not to let me worry. At that time, I was in Europe, planning to return for the CES and other business meetings in the States. After the call, I felt like there might a bit more time left. Not much, but probably enough to wrap up my US business commitments before returning to China. At least that’s what I had thought.
My mom called again one day later and said grandma wanted to see me. I knew it was different now. Over the years, Grandma was always considerate about my job, my sleep, and even my diet. She must have been suffering from the condition. So I booked a last-minute flight, leaving the very next day for China.
From the Netherlands to my home town in Fujian, as it turned out, it’s about 22 hours away by flight. During those long hours, I was immersing myself in the past. I couldn’t recall much of my early childhood, but I can always remember the bits about grandma and me. She loved kissing me on the forehead, even as I grew taller and as she appeared smaller.
Some memories were so vivid they were just there in front of me when I closed my eyes, like a movie playback.
To make me eat my food when I was about five years old, grandma would make up stories about the shapes of food such as pickles: I was made to believe that some were shaped like Monkey King, and some were like evil monsters — so that a five-year-old boy would find it interesting to eat more. And believe me, I had “destroyed” a lot of those kings and evil monsters. And I was a chubby kid.
Grandma liked to save food, particularly for me. When I was a kid, she always kept me tons of cookies and treats. And I’d shamelessly indulge myself each time I visited her. Over the years, grandma still managed to save snacks for me, even though I am a grown-up man and no longer even enjoy snacks. She would some times hand me molded snacks with a happy face, as she couldn’t see the expiration date well. Each time, I’d just laugh and tell her that’s not healthy. She then brings the snacks closer to her eyes and mumbles, “how weird, why it went bad quickly.” Visibly disappointed, she had to throw away food.
Grandma was fond of music. She was a very outgoing person. She also enjoyed teaching people to dance. There were a lot of memories where I was her reluctant, awkward dance partner. Every time I messed up, she would laugh and say to me, “Silly, this is so simple…. see, just follow me like this…” Memories like this concluded many summer evenings when I was a child.
Grandma was born in 1937, before the CCP took over China. Being fierce and brave, She had gone through WWII, the Japanese invasion, the Great Chinese Famine, and then the Cultural Revolution. In my memories of her, grandma had always been a very optimistic person too. She always said, “No difficulty is too big to overcome. Things are going to pass, and life will go on.” I heard she said things like that over the years.
My grandma was one of the very first women who attended college before the Cultural Revolution. She was smart and bold. Grandma told me saddening stories about the Cultural Revolution and how she and my grandpa were persecuted just because they were intellectuals. She told me there were times when the “Red Guards” would just appear in our house and ask to take grandpa out for a “humiliation walk.” Many people committed suicide due to the emotional and physical suffering. But my grandparents survived. Grandma usually ended the stories with some conclusion like: “Things are going to pass, and life will go on,” as it was just a little chapter of her life.
After the Cultural Revolution, grandma became a math teacher in high school and community college. She loved teaching me math too! But as a young kid, I had always disliked these “after-school math sessions”. I wanted to play soccer, basketball, or just fool around with my little friends. So I tried to find ways.
Grandma didn’t have good eyesight. She had to wear glasses when trying to look for things. Most of the time, she just had a good sense of where things were. But it’s hard to track a kid who was determined to sneak out and play. My mom always fondly recalled the stories where I’d sneak out of the house and then only to surprise grandma later when she was yelling my name at the balcony. I wouldn’t say that happened many times, but indeed for the one time I can remember, Grandma was surprised and then rushed me to the dining table half-blaming, half-laughing. It was just like yesterday.
Then I went abroad. Grandma and I would talk over the phone or even video chat from time to time, but we hadn’t been spending much time together. Sometimes I would manage to visit my home town and grandma once a year but often it was usually once every few years. Each time when she saw me, she was so excited, hugging me tight, just like a little kid. The saying seems true — as you’ve grown up to be an adult, your parents and grandparents become like kids.
Each time when I’m home, grandma would give me a small piece of paper where she wrote down her “new friends” numbers and ask me to input them to the phone. Without me asking, she usually fondly told me where she made these friends, who they were, and all the gossips that related to it. There were times when I was impatient and didn’t heed the stories. But she didn’t mind — she was just happy to talk to me. Now looking back, grandma must have waited a long time to tell me all the tales of her new friends. Much like when I was in kindergarten, eagerly waiting to share my day.
As I am writing this, all of the fond memories are floating before my eyes. I am incredibly grateful for having such a caring grandma over the last 30 plus years. She had made me who I am.
Thank you; for the unconditional love that you had given me. Thank you; for demonstrating what optimism looks like in the most challenging life situation. Thank you; for teaching me how to be a courageous person, just like you.
My grandma passed away on January 5th, 2020, after fighting late-stage liver cancer.
I love you, grandma. Rest in peace.
As I'm writing this, I just finished a long email with a startup founder. This startup has a stellar team, and they quickly realized what didn't work. The company is going through a pivot. The CEO and I have been on the phone, on the email over the past few months, during which we have discussed, tested, and debated no less than five ideas.
I will be the first one to admit that, at times, as a VC/ advisor, it's tempting to jump in and offer one's own idea.
But that's not the right way to do it.
For one, VCs are generally good at observing the macro trends and betting on it - but terrible at originating great ideas. If we look at the iconic consumer tech companies over the past decades - Netflix, Uber, Airbnb, Twitter, Snap, TikTok, etc - none of those startup ideas come from VCs. Almost 100% of the time, these ideas were products of founders' own life experience and insights, which could be very different from a typical Sand Hill VC. That's why when the majority of great consumer companies get started, they had the most challenging time to convince others to invest. On the contrary, consumer startups who had an effortless time to raise money early on - thanks to VC hype - often turn out to be living short of the expectation and running of gas in the long term.
Secondly, VCs do play an important role and add value to a company's early life. Investors usually have the privilege to observe the macro market and study the ever-evolving dynamics by comparing multiple companies and tech. But VCs have to be very thoughtful about how an investor's insights can be translated into a company's actions. Over the past 10+ years as an investor, I've shared boards with both excellent and mediocre VCs. I learned that a good VC tends to ask great questions to provoke new thinkings from founders, whereas a bad one tends to force-feed his / her thoughts into the company.
During a startup pivot, the dynamics could be confusing and sometimes frustrating. And that's when a great founder / VC partnership is needed.