Thermal energy storage has been a difficult place for climatetech in years past. The low cost of fossil fuels (the source for vast majority of high temperature industrial heat to date) and the failure of large scale solar thermal power plants to compete with the rapidly scaling solar photovoltaic industry made thermal storage feel like, at best, a market reserved for niche applications with unique fossil fuel price dynamics. This is despite some incredibly cool (dad-joke intended 🔥🥵🤓) technological ingenuity in the space.
But, in a classic case of how cheap universal inputs change market dynamics, the plummeting cost and soaring availability of renewable electricity and the growing desire for industrial companies to get “clean” sources of industrial heat has resulted in almost a renaissance for the space as this Canary Media article (with a very nice table of thermal energy startups) points out.
With cheap renewables (especially if the price varies), companies can buy electricity at low (sometimes near-zero if in the middle of a sunny and windy day) prices, convert that to high-temperature heat with an electric furnace, and store it for use later.
While the devil’s in the details, in particular the round trip energy efficiency (how much energy you can get out versus what you put in), the delivered heat temperature range and rate (how hot and how much power), and, of course, the cost of the system, technologies like this could represent a key technology to green sectors of the economy that would otherwise be extremely difficult to lower carbon output for.
Rocks and hotness have existed for billions of years, but it’s only now that the two can be used to help the world decarbonize — and it’s all because the insanely low cost of solar and wind power has made thermal storage economically possible.
I’ve been reading a lot of year-end/decade-end reflections (as one does this time of year) — and while a part of me wanted to #humblebrag about how I got a 🏠/💍/👶🏻 this decade 😇 — I thought it would be more interesting & profound to instead call out 10 worldviews & beliefs I had going into the 2010s that I no longer hold.
Sales is an unimportant skill relative to hard work / being smart As a stereotypical “good Asian kid” 🤓, I was taught to focus on nailing the task. I still think that focus is important early in one’s life & career, but this decade has made me realize that everyone, whether they know it or not, has to sell — you sell to employers to hire you, academics/nonprofits sell to attract donors and grant funding, even institutional investors have to sell to their investors/limited partners. Its a skill at least as important (if not more so).
Marriage is about finding your soul-mate and living happily ever after Having been married for slightly over half the decade, I’ve now come to believe that marriage is less about finding the perfect soul-mate (the “Hollywood version”) as it is about finding a life partner who you can actively choose to celebrate (despite and including their flaws, mistakes, and baggage). Its not that passionate love is unimportant, but its hard to rely on that alone to make a lifelong partnership work. I now believe that really boring-sounding things like how you make #adulting decisions and compatibility of communication style matter a lot more than things usually celebrated in fiction like the wedding planning, first dates, how nice your vacations together are, whether you can finish each other’s sentences, etc.
Industrial policy doesn’t work I tend to be a big skeptic of big government policy — both because of unintended consequences and the risks of politicians picking winners. But, a decade of studying (and working with companies who operate in) East Asian economies and watching how subsidies and economies of scale have made Asia the heart of much of advanced manufacturing have forced me to reconsider. Its not that the negatives don’t happen (there are many examples of China screwing things up with heavy-handed policy) but its hard to seriously think about how the world works without recognizing the role that industrial policy played. For more on how land management and industrial policies impacted economic development in different Asian countries, check out Joe Studwell’s book How Asia Works
Obesity & weight loss are simple — its just calories in & calories out From a pure physics perspective, weight gain is a “simple” thermodynamic equation of “calories in minus calories out”. But in working with companies focused on dealing with prediabetes/obesity, I’ve come to appreciate that this “logic” not only ignores the economic and social factors that make obesity a public health problem, it also overlooks that different kinds of foods drive different physiological responses. As an example that just begins to scratch the surface, one very well-controlled study (sadly, a rarity in the field) published in July showed that, even after controlling for exercise and calories, carbs, fat, fiber, and other nutrients present in a meal, diets consisting of processed foods resulted in greater weight-gain than a diet consisting of unprocessed foods
Revering luminaries & leaders is a good thing Its very natural to be so compelled by an idea / movement that you find yourself idolizing the people spearheading it. The media feeds into this with popular memoirs & biographies and numerous articles about how you can think/be/act more like [Steve Jobs/Jeff Bezos/Warren Buffett/Barack Obama/etc]. But, over the past decade, I’ve come to feel that this sort of reverence leads to a pernicious laziness of thought. I can admire Steve Jobs for his brilliance in product design but do I want to copy his approach to management or his use of alternative medicine to treat his cancer or condoning how he treated his illegitimate daughter. I think its far better to appreciate an idea and the work of the key people behind it than to equate the piece of work with the person and get sucked in to that cult of personality.
Startups are great place for everyone Call it being sucked into the Silicon valley ethos but for a long time I believed that startups were a great place for everyone to build a career: high speed path to learning & responsibility, ability to network with other folks, favorable venture funding, one of the only paths to getting stock in rapidly growing companies, low job seeking risk (since there’s an expectation that startups often fail or pivot). Several years spent working in VC and startups later, and, while I still agree with my list above, I’ve come to believe that startups are really not a great place for most people. The risk-reward is generally not great for all but the earliest of employees and the most successful of companies, and the “startups are great for learning” Kool-aid is oftentimes used to justify poor management and work practices. I still think its a great place for some (i.e. people who can tolerate more risk [b/c of personal wealth or a spouse with a stable high-paying job], who are knowingly optimizing for learning & responsibility, or who are true believers in a startup’s mission), but I frankly think most people don’t fit the bill.
Microaggressions are just people being overly sensitive I’ve been blessed at having only rarely faced overt racism (telling me to go back to China 🙄 / or that I don’t belong in this country). It’s a product of both where I’ve spent most of my life (in urban areas on the coasts) and my career/socioeconomic status (it’s not great to be overtly racist to a VC you’re trying to raise money from). But, having spent some dedicated time outside of those coastal areas this past decade and speaking with minorities who’ve lived there, I’ve become exposed to and more aware of “microaggressions”, forms of non-overt prejudice that are generally perpetrated without ill intent: questions like ‘so where are you really from?’ or comments like ‘you speak English really well!’. I once believed people complaining about these were simply being overly sensitive, but I’ve since become an active convert to the idea that, while these are certainly nowhere near as awful as overt hate crimes / racism, they are their own form of systematic prejudice which can, over time, grate and eat away at your sense of self-worth.
The Western model (liberal democracy, free markets, global institutions) will reign unchallenged as a model for prosperity I once believed that the Western model of (relatively) liberal democracy, (relatively) free markets, and US/Europe-led global institutions was the only model of prosperity that would reign falling the collapse of the Soviet Union. While I probably wouldn’t have gone as far as Fukuyama did in proclaiming “the end of history”, I believed that the world was going to see authoritarian regimes increasingly globalize and embrace Western institutions. What I did not expect was the simultaneous rise of different models of success by countries like China and Saudi Arabia (who, frighteningly, now serve as models for still other countries to embrace), as well as a lasting backlash within the Western countries themselves (i.e. the rise of Trump, Brexit, “anti-globalism”, etc). This has fractured traditional political divides (hence the soul-searching that both major parties are undergoing in the US and the UK) and the election of illiberal populists in places like Mexico, Brazil, and Europe.
Strategy trumps execution As a cerebral guy who spent the first years of his career in the last part of the 2000s as a strategy consultant, it shouldn’t be a surprise that much of my focus was on formulating smart business strategy. But having spent much of this decade focused on startups as well as having seen large companies like Apple, Amazon, and Netflix brilliantly out-execute companies with better ‘strategic positioning’ (Nokia, Blackberry, Walmart, big media), I’ve come around to a different understanding of how the two balance each other.
We need to invent radically new solutions to solve the climate crisis Its going to be hard to do this one justice in this limited space — especially since I net out here very differently from Bill Gates — but going into this decade, I never would have expected that the cost of new solar or wind energy facilities could be cheaper than the cost of operating an existing coal plant. I never thought that lithium batteries or LEDs would get as cheap or as good as they are today (with signs that this progress will continue) or that the hottest IPO of the year would be an alternative food technology company (Beyond Meat) which will play a key role in helping us mitigate food/animal-related emissions. Despite the challenges of being a cleantech investor for much of the decade, its been a surprising bright spot to see how much pure smart capital and market forces have pushed many of the technologies we need. I still think we will need new policies and a huge amount of political willpower — I’d also like to see more progress made on long-duration energy storage, carbon capture, and industrial — but whereas I once believed that we’d need radically new energy technologies to thwart the worst of climate change, I am now much more of an optimist here than I was when the decade started.
Here’s to more worldview shifts in the coming decade!
Having been lucky enough to invest in both tech (cloud, mobile, software) and “deeptech” (materials, cleantech, energy, life science) startups (and having also ran product at a mobile app startup), it has been striking to see how fundamentally different the paradigms that drive success in each are.
Whether knowingly or not, most successful tech startups over the last decade have followed a basic playbook:
Take advantage of rising smartphone penetration and improvements in cloud technology to build digital products that solve challenges in big markets pertaining to access (e.g., to suppliers, to customers, to friends, to content, to information, etc.)
Build a solid team of engineers, designers, growth, sales, marketing, and product people to execute on lean software development and growth methodologies
Hire the right executives to carry out the right mix of tried-and-true as well as “out of the box” channel and business developmentstrategies to scale bigger and faster
This playbook appears deceptively simple but is very difficult to execute well. It works because for markets where “software is eating the world”:
There is relatively little technology risk: With the exception of some of the most challenging AI, infrastructure, and security challenges, most tech startups are primarily dealing with engineering and product execution challenges — what is the right thing to build and how do I build it on time, under budget? — rather than fundamental technology discovery and feasibility challenges
Skills & knowledge are broadly transferable: Modern software development and growth methodologies work across a wide range of tech products and markets. This means that effective engineers, salespeople, marketers, product people, designers, etc. at one company will generally be effective at another. As a result, its a lot easier for investors/executives to both gauge the caliber of a team (by looking at their experience) and augment a team when problems arise (by recruiting the right people with the right backgrounds).
Distribution is cheap and fast: Cloud/mobile technology means that a new product/update is a server upgrade/browser refresh/app store download away. This has three important effects:
The first is that startups can launch with incomplete or buggy solutions because they can readily provide hotfixes and upgrades.
The second is that startups can quickly release new product features and designs to respond to new information and changing market conditions.
The third is that adoption is relatively straightforward. While there may be some integration and qualification challenges, in general, the product is accessible via a quick download/browser refresh, and the core challenge is in getting enough people to use a product in the right way.
In contrast, if you look at deeptech companies, a very different set of rules apply:
Technology risk/uncertainty is inherent: One of the defining hallmarks of a deeptech company is dealing with uncertainty from constraints imposed by reality (i.e. the laws of physics, the underlying biology, the limits of current technology, etc.). As a result, deeptech startups regularly face feasibility challenges — what is even possible to build? — and uncertainty around the R&D cycles to get to a good outcome — how long will it take / how much will it cost to figure this all out?
Skills & knowledge are not easily transferable: Because the technical and business talent needed in deeptech is usually specific to the field, talent and skills are not necessarily transferable from sector to sector or even company to company. The result is that it is much harder for investors/executives to evaluate team caliber (whether on technical merits or judging past experience) or to simply put the right people into place if there are problems that come up.
Product iteration is slow and costly: The tech startup ethos of “move fast and break things” is just harder to do with deeptech.
At the most basic level, it just costs a lot more and takes a lot more time to iterate on a physical product than a software one. It’s not just that physical products require physical materials and processing, but the availability of low cost technology platforms like Amazon Web Services and open source software dramatically lower the amount of time / cash needed to make something testable in tech than in deeptech.
Furthermore, because deeptech innovations tend to have real-world physical impacts (to health, to safety, to a supply chain/manufacturing line, etc.), deeptech companies generally face far more regulatory and commercial scrutiny. These groups are generally less forgiving of incomplete/buggy offerings and their assessments can lengthen development cycles. Deeptech companies generally can’t take the “ask for forgiveness later” approaches that some tech companies (i.e. Uber and AirBnb) have been able to get away with (exhibit 1: Theranos).
As a result, while there is no single playbook that works across all deeptech categories, the most successful deeptech startups tend to embody a few basic principles:
Go after markets where there is a very clear, unmet need: The best deeptech entrepreneurs tend to take very few chances with market risk and only pursue challenges where a very well-defined unmet need (i.e., there are no treatments for Alzheimer’s, this industry needs a battery that can last at least 1000 cycles, etc) blocks a significant market opportunity. This reduces the risk that a (likely long and costly) development effort achieves technical/scientific success without also achieving business success. This is in contrast with tech where creating or iterating on poorly defined markets (i.e., Uber and Airbnb) is oftentimes at the heart of what makes a company successful.
Focus on “one miracle” problems: Its tempting to fantasize about what could happen if you could completely re-write every aspect of an industry or problem but the best deeptech startups focus on innovating where they won’t need the rest of the world to change dramatically in order to have an impact (e.g., compatible with existing channels, business models, standard interfaces, manufacturing equipment, etc). Its challenging enough to advance the state of the art of technology — why make it even harder?
Pursue technologies that can significantly over-deliver on what the market needs: Because of the risks involved with developing advanced technologies, the best deeptech entrepreneurs work in technologies where even a partial success can clear the bar for what is needed to go to market. At the minimum, this reduces the risk of failure. But, hopefully, it gives the company the chance to fundamentally transform the market it plays in by being 10x better than the alternatives. This is in contrast to many tech markets where market success often comes less from technical performance and more from identifying the right growth channels and product features to serve market needs (i.e., Facebook, Twitter, and Snapchat vs. MySpace, Orkut, and Friendster; Amazon vs. brick & mortar bookstores and electronics stores)
All of this isn’t to say that there aren’t similarities between successful startups in both categories — strong vision, thoughtful leadership, and success-oriented cultures are just some examples of common traits in both. Nor is it to denigrate one versus the other. But, practically speaking, investing or operating successfully in both requires very different guiding principles and speaks to the heart of why its relatively rare to see individuals and organizations who can cross over to do both.
Special thanks to Sophia Wang, Ryan Gilliam, and Kevin Lin Lee for reading an earlier draft and making this better!
