Sequoia Productive Capital – Stratechery

I puzzled about exactly where we were in the Age of Information and Telecommunications: were we still in the turning point, as Carlota Perez, the author of Technological Revolutions and Financial Capital believes; into the Synergy phase of Deployment, where society re-organizes itself around the new paradigm; or into the Maturity phase where the current technological era starts to fizzle out, even as the next era starts to take root?

While my tentative conclusion at the end of that piece was that we were entering the Maturity phase, over the last couple of weeks I have increasingly come to believe that we are earlier in the cycle than I suggested: we have exited the turning point, and are firmly in the Synergy phase.

Evidence of Synergy

Perez identified six elements of her model that are transformed in a technological revolution:

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Here are some brief comments about a few of these, before I spend more time on financial capital and production capital.

Technological Revolution

The culmination of the current technological paradigm is mobile + cloud; I already made the case in 2020’s The End of the Beginning that tech history was best understood as consisting not of multiple eras — mainframes, PCs, mobile, etc. — but rather as a multi-decade transformation from a computer-as-destination to computing-as-background:

This last point gets at why the cloud and mobile, which are often thought of as two distinct paradigm shifts, are very much connected: the cloud meant applications and data could be accessed from anywhere; mobile made the I/O layer available anywhere. The combination of the two make computing continuous.
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What is notable is that the current environment appears to be the logical endpoint of all of these changes: from batch-processing to continuous computing, from a terminal in a different room to a phone in your pocket, from a tape drive to data centers all over the globe. In this view the personal computer/on-premises server era was simply a stepping stone between two ends of a clearly defined range.

It’s arguable that concepts like metaverses represent one final step down this path, and the final unification of the cloud and interaction; I don’t think that means we aren’t in the deployment period technologically speaking though: continuous computing is here (even if it might become even more immersive).

Techno-Economic Paradigm

In line with the nature of continuous computing, the techno-economic paradigm is Everything as a Service, a concept I wrote about in 2016:

Services sound a lot like software: both are intangible, both scale infinitely, and both are infinitely customizable. It follows that a services business model — payment in exchange for service rendered, without the transfer of ownership — is a much more natural fit for software than the transaction model characteristic of manufacturing. It better matches value generated and value received — customers only pay if they use it, and producers are rewarded for making their product indispensable — and more efficiently allocates fixed costs: occasional users may be charged nothing at all, while regular users who find your software differentiated pay more than the marginal cost of providing it.

The services business model is obviously dominant in terms of software: all new software companies are SaaS companies, and old-line companies like Microsoft and Adobe have long since transformed their licensing-based business models to the SaaS business model. All of these businesses make huge investments in fixed costs (building the software), and reach profitability by leveraging the zero marginal cost nature of software and the Internet to scale as large as possible as quickly as possible.

Meanwhile, all of these new companies operating with a SaaS model themselves depend on public clouds like AWS, which has the exact same model, just at even larger scale: gargantuan investments in fixed costs, made profitable by leveraging the zero marginal cost nature of software and the Internet to scale as large as possible as quickly as possible.

This isn’t just an enterprise story, though: huge consumer platforms like Facebook or Netflix are themselves services, operated on the same business model of massive investments in fixed costs, scaled via the zero marginal cost nature of the Internet. Of course the monetization may differ: Netflix charges a subscription, which aligns payment (continuous) with the delivery of value (continuous). Facebook monetizes via ads:

  • Some of these ads are for subscription-based services
  • Some of these ads are for other digital businesses like games based on the same economic principles
  • Some of these ads are for e-commerce

E-commerce might seem like an exception to the services narrative, but while you do get to keep the goods that are delivered, everything about how e-commerce functions is as a service. Shopify has made huge investments in fixed costs to provide a selling platform for goods that are stored in rented space in 3PL warehouses and delivered by companies like Fedex for a fee, which is another way of saying payment for services.

Here again Amazon is the ultimate example of this model: the company has made massive investments in everything from its online store to its distribution centers to even its own planes and delivery vehicles, and an ever-increasing share of its e-commerce revenue comes from merchants effectively renting access to the entire stack; merchants are still selling goods, and consumers are still receiving them, but everything in the middle is a software-driven service with a software-derived business model.

Local services are being impacted as well: Uber, Doordash, Instacart, etc. are only possible in a world of massive compute capacity and ubiquitous smartphones; this enables customers to order cars or food from anywhere, and drivers or delivery workers to know where to go and what to bring. This goes hand-in-hand with the COVID-driven rise in remote work: yes, only a portion of society has the luxury to work from anywhere (probably because they work in a digital services industry), but what is notable is the transformation of manual labor, from Amazon warehouses to Doordash delivery drivers, that has arisen to serve their needs.

Socio-Institutional Framework

This was the primary focus of my previous Article. Perez has long been puzzled by the seeming lack of response by governments to the new technological paradigm; I think that response is coming into sharp focus, but it is easily missed because it is rather dystopian:

What is worth noting, though, is that you can make the case that China has entered the Synergy phase in which government has aligned with technology to profoundly impact China’s citizens. That this entails mass surveillance, censorship, and propaganda doesn’t undo Perez’s thesis; it perhaps punctures her optimism.

There are signs a weaker, yet in some ways similar, form of synergy has happened in the U.S. as well; soon after the Dotcom Bubble came the Patriot Act, and while the political motivations were the 9/11 terrorist attacks, the implementation was very much about leveraging technology for government ends. The extent of this synergy only became clear in 2013 when the Snowden revelations exposed a vast web of surveillance conducted by tech and telecommunications companies in partnership with the NSA.

Then, over the last several years, there has been a concerted effort to push tech companies to increasingly limit misinformation on their networks, and post corrective information instead; it doesn’t take much squinting to re-label both efforts as censorship and propaganda. This is not, I would note, to pass judgment as to whether those efforts are right or wrong (although I am skeptical); merely to note that there may be more evidence of synergy between the government and tech than it seems. It’s all a bit dystopian, to be sure, but revolutions by their nature are unpredictable; it wasn’t a certainty that liberal democracy would triumph in the fourth revolution, much less the current one.

There is also an argument to be made that the dramatic shift in monetary policy over the last 13 years — prompted by the Great Recession, but interestingly enough perfectly aligned with the smartphone era — is itself evidence of synergy: tech is inherently deflationary, which could be balancing out the inflationary potential of printing new money. This, needless to say, is a very complex topic, which is why I didn’t include it in my previous article; consider this paragraph as a point of speculation.

Financial Capital and Production Capital

One of the most important principles in Perez’s model is the difference between Financial Capital and Production Capital and the roles they play in the Installation period versus the Deployment period (just look at the name of the book!). Perez explains:

Financial capital is mobile by nature while production capital is basically tied to concrete products, both by installed equipment with specific operational capabilities and by linkages in networks of suppliers, customers or distributors in particular geographic locations. Financial capital can successfully invest in a firm or a project without much knowledge of what it does or how it does it. Its main question is potential profitability (sometimes even just the perception others may have about it). For production capital, knowledge about product, process and markets is the very foundation of potential success. The knowledge can be scientific and technical expertise or managerial experience, it can be innovative talent or entrepreneurial drive, but it will always be about specific areas and only partly mobile…

All these distinctions lead to a fundamental difference in level of commitment. Financial capital is footloose by nature; production capital has roots in an area of competence and even in a geographic region. Financial capital will flee danger; production capital has to face every storm by holding fast, ducking down or innovating its way forward or sideways. Yet, though the notion of progress and innovation is associated with production capital – and rightly so – ironically when it comes to radical change, incumbent production capital can become conservative and then it is the role of financial capital (whether from family, banks or ‘angels’) to enable the rise of the new entrepreneurs.

Financial capital is critical in the Installation period of a technological revolution. Because it is mobile and seeking a return it flows to new technologies that are just emerging; in the case of the current era that meant chips, then software, then services. Financial capital is also highly speculative, and provokes a frenzy that leads to a bubble, which is exactly what happened in the Dot Com era.

Production capital, on the other hand, is harvested from profitable businesses that re-invest their earnings to improve their products and expand their markets during the Deployment period. This has clearly been happening with the largest tech companies: one of the best investments one could have made over the last decade would have been stock in Apple, Microsoft, Google, Amazon, and Facebook, not because they needed investor capital, but because they were so generating such exceptional returns from reinvesting their own profits.

Indeed, the fact that the big 5 tech companies were so clearly powered by production capital is one of the reasons why I have always been skeptical that we are still stuck in the Turning Point; at the same time, it is not as if the venture capital industry had disappeared.

Financial Capital = Venture Capital

Venture capital is another name for Financial capital; Perez writes:

As far as truly new ventures are concerned, innovators may have brilliant ideas for which they are willing to take huge risks, devoting their whole lives to bringing their projects to reality, but if finance is not forthcoming they can do nothing.

This is how I described venture capital in 2015’s Venture Capital and the Internet’s Impact:

In the case of startups, during the 45 years after Arthur Rock founded the first venture capital partnership in 1961, the vast majority of new firms needed significant funding from day one. Hardware startups of course needed specialized equipment, the funds to make prototypes, and then to set up actual manufacturing lines, but software startups, particularly those with any sort of online component, also needed to make significant hardware investments into servers, software that ran on said servers, and a staff to manage them. This was where the venture capitalists’ unique skill-set came into play: they identified the startups worthy of funding through little more than a PowerPoint and a person, and brought to bear the level of upfront capital necessary to make that startup a reality.

The point of that article, however, was to explain how AWS — a service — was transforming venture capital; now new products could be built in someone’s bedroom, leading to the rise of angels writing much smaller checks to much smaller teams achieving much larger impact much more quickly than ever before. This made a venture capitalist’s job easier in the short term — now they were writing checks based on existing products and growth metrics, instead of PowerPoints — but in the long run it meant that venture capital was becoming commoditized.

The story doesn’t end there: the trouble for venture capitalists is that they are getting squeezed from the top of the funding hierarchy as well: a new class of growth investors, many of them made up of traditional limited partners like Fidelity and T. Rowe Price, are approaching unicorn companies on a portfolio basis…Sure, this is relatively dumb money, but that’s where those angel and incubator relationships come in: if startups increasingly feel they have the relationships and advice they need, then growth funding is basically a commodity, so why not take dumb cheap money sooner rather than later?

Interestingly, just as in every other commodity market, the greatest defense for venture capitalists turns out to be brand: firms like Benchmark, Sequoia, or Andreessen Horowitz can buy into firms at superior prices because it matters to the startup to have them on their cap table. Moreover, Andreessen Horowitz in particular has been very open about their goal to offer startups far more than money, including dedicated recruiting teams, marketing teams, and probably most usefully an active business development team. Expect the venture capitalist return power curve to grow even steeper.

Brand, though, can only resist commoditization for so long; a16z in particular has dramatically accelerated its growth, and now the most famous brand name of all is going even further.

Sequoia’s Transformation

Sequoia Partner Roelof Botha wrote yesterday on Medium:

Innovations in venture capital haven’t kept pace with the companies we serve. Our industry is still beholden to a rigid 10-year fund cycle pioneered in the 1970s. As chips shrank and software flew to the cloud, venture capital kept operating on the business equivalent of floppy disks. Once upon a time the 10-year fund cycle made sense. But the assumptions it’s based on no longer hold true, curtailing meaningful relationships prematurely and misaligning companies and their investment partners. The best founders want to make a lasting impact in the world. Their ambition isn’t confined to a 10-year period. Neither is ours…

Today, we are excited to announce our boldest innovation yet to help founders build enduring companies for the 21st century. In our U.S./Europe business, we are breaking with the traditional organization based on fund cycles and restructuring Sequoia Capital around a singular, permanent structure: The Sequoia Fund.

Moving forward, our LPs will invest into The Sequoia Fund, an open-ended liquid portfolio made up of public positions in a selection of our enduring companies. The Sequoia Fund will in turn allocate capital to a series of closed-end sub funds for venture investments at every stage from inception to IPO. Proceeds from these venture investments will flow back into The Sequoia Fund in a continuous feedback loop. Investments will no longer have “expiration dates.” Our sole focus will be to grow value for our companies and limited partners over the long run.

This announcement, in Perez terms, is as clear as could be: Sequoia is transforming itself from financial capital to production capital. Instead of LP’s investing in funds that make speculative investments in risky endeavors, Sequoia wants to keep long-term positions in companies that have proven business models and are embarking on the decade (or longer) process of improving their products and expanding their markets to the entire world.

This also, I suspect, represents the formation of a sort of “Silicon Valley Inc.”; while the big 5 can entirely self-fund, the nature of the SaaS business model is such that companies with proven product-market fit are better off losing more money up-front rather than less:

  • Customers, once acquired, are like annuities that make money years into the future, but the cost to acquire them has to be paid up front.
  • The core software product represents a huge fixed cost investment that is leveraged by scaling to as many customers as possible.

The combination of these two factors means that SaaS companies take longer to self-fund, even if their models are proven; what Sequoia can do with their model is invest in an entire portfolio of these companies and hold onto them indefinitely, effectively recycling money from mature companies into nascent ones, much as Apple or Microsoft invests profits from their current products into the development of new ones. On an individual company level it looks like venture/financial capital; as a collective it is much more akin to production capital, especially once you realize that many of these companies, thanks to angels and AWS, are already fairly de-risked.

Moreover, while Sequoia’s announcement feels so momentous because of their long history in the Valley, institutions like Tiger Capital are already playing the exact same game; the era of production capital is firmly upon us, which means we are clearly in the Deployment period of Perez’s model.

Growth and Crypto

In Perez’s model the Growth element in the Deployment period means “converging growth of most industries using [the new] paradigm”; that seems inconsistent with a reality where tech continues to provide a huge amount of growth relative to the rest of the economy.

I think, though, that is a problem of definition: we still have a habit of calling everything that runs on a SaaS model a tech company, even if the actual industry or service being rendered isn’t about tech at all. Is Warby Parker a tech company? Is Carvana? Is DoorDash? The list goes on-and-on: new companies are created using technology, but of course they are! Calling everything a tech company is like calling a shopping mall a car company; sure, it was enabled by and undergirded by the automobile, but what in that era wasn’t? To return to The End of the Beginning:

Indeed, this is exactly what we see in consumer startups in particular: few companies are pure “tech” companies seeking to disrupt the dominant cloud and mobile players; rather, they take their presence as an assumption, and seek to transform society in ways that were previously impossible when computing was a destination, not a given. That is exactly what happened with the automobile: its existence stopped being interesting in its own right, while the implications of its existence changed everything.

That leaves the question of crypto; given its oppositional nature to the current paradigm — decentralization, encryption, and ownership — it is clearly something completely new; moreover, the capital chasing returns in crypto is clearly financial capital, not production capital.

It’s certainly possible for a new paradigm to emerge alongside an existing paradigm; Perez notes on multiple instances her model is stylized, and details multiple periods of overlap. What is notable, though, is that crypto draws talent from the same pool that drives the IT revolution, and it’s unclear what the impact of this drain will be on the current paradigm. The optimistic take is that the shift to remote work will dramatically increase the available talent pool to tech-companies-that-are-actually-just-companies, and it’s one I share: the opportunity now is in new markets, not new tech, and open source software, along with public clouds, provides a strong foundation for any new company.

That suggests that crypto will continue to exist in a bit of a parallel universe, which makes sense; it already has its own currencies, after all. That is another way of saying I think that crypto is still very early in its lifecycle; 2017 wasn’t the big crash, nor will the next one be — remember that tech had its own internal boom-and-bust cycles in the three decades between the introduction of the Intel processor and the Dotcom bubble. Nor is this a bearish take: those three decades were exceptionally profitable for everyone involved — including Sequoia, which was founded in 1972. Perhaps its successor, the one that shifts to providing productive capital for crypto companies decades from now, has already been born.