We’ve shared our top 16 podcasts of the year. We’ve shared 16-ish listicles and videos. And so now, here are our 16 top posts (plus a few extra related podcasts) from 2016…
A very fitting 20-16 anniversary as well: this is also the year “software eating the world” turned 5 years old!
The computing industry progresses in two mostly independent cycles: financial and product cycles. While financial markets fluctuate unpredictably and get a lot of attention, it’s the product cycle that really drives the computing industry forward. In tech, product cycles are mutually reinforcing interactions between platforms and applications. Since new cycles that completely reshape the computing landscape begin about every decade, what current trends give us a glimpse into the future of computing?
“But at the same time, once you’ve achieved that scale, further changes in market share are not very meaningful…Where your users are, which users you want, and which users spend what is more important. That is, the war is over. Yes, we’ll go from 2.5bn smartphones to 5bn, but the dynamics of the two ecosystems will not change much with that growth… Rather, the changes, and the things to think about, come from other directions — VR and AR on one hand, AI and machine learning on the other.”
The future of immersive virtual reality is often depicted as a dystopian view of millions of people spending hours alone, with huge gadgets stuck to their face, enraptured by fantastical worlds. But it’s going to be millions of people spending time together — with friends, family, colleagues, and new acquaintances — experiencing moments together no matter the physical distance between them. The key to understanding why such “social VR” will be important is to think about virtual (and augmented) reality as a computing platform, rather than as a PC peripheral for gaming…
“It strikes me sometimes, as a reader of very old science fiction, that scifi did indeed mostly miss computing, but it talked a lot about ‘automatic’. If you look at that list, none of the items really look like ‘AI’ (though some might well use it in future), but a lot of them are ‘automatic’. And that’s what any ‘AI’ short of HAL 9000 really is — the automatic pilot, the automatic spell checker, the automatic hardware configuration, the automatic image search or voice recogniser, the automatic restaurant-booker or cab-caller… They’re all clerical work your computer doesn’t make you do anymore, because it gained the intelligence, artificially, to do them for you.”
Depression is now the leading cause of disability in the U.S. One in four Americans suffered from a diagnosable mental disorder in the last year, most of which were moderate to severe. We spend billions of dollars every year on mental health treatment, more than on any other medical condition — and yet we still have problems getting people the help they need. The overwhelming and giant lag in the system boils down to two things: coordinating care in our current health care framework, and getting the right treatment conveniently. So the great mental health challenge we’re facing right now isn’t just one of developing new therapies; it’s one of scalability and convenience. Which is where software comes in…
As digital wallets become the origination point for consumer spending, they become the platform for downstream financial services — creating an opportunity for startups and a problem for established players. The problem, of course, is that a payment type can become a wallet, and a wallet can become a payment type. As a stack, we have hardware (your mobile phone) at the top, and bank accounts holding the actual treasure at the very bottom. But it’s better to think of this “stack” as really a system of pointers. And the goal for businesses (new and old) is to find and occupy a defensible position in the stack that allows them to intercept payments…
+ bonus related a16z Podcast: Fintech Revolution or Evolution (with Charlie Warzel)
How far along are we towards the vision of a “cashless, cardless, walletless, frictionless future” for fintech? We’re not quite there yet; the reality may be that fintech innovation is much more incremental, evolutionary, and still only disintermediating the physical world than truly doing new things given what’s natively possible with web, cloud, and mobile…
“The key thing here is that the nice attention-grabbing demos of computer vision that recognize a dog or a tree, or a pedestrian, are just the first, obvious use cases for a fundamental new capability — to read images. And not just to read them the way humans can, but to read a billion and see the patterns. Among many other things, that has implications for a lot of retail, including parts not really affected by Amazon, and indeed for the $500bn spent every year on advertising. Really, though, we don’t know what all the implications might be…”
When evaluating an internet company’s strategic position (the defensibility of its profit moat), we need to consider not just how the company generates revenue but the broader loop of internet economics — beyond where its products currently sit in that loop. Think of the “internet economic loop” as a model-train track where new technologies can come along and create entirely new tracks that render the previous tracks obsolete. Where are the next flash points?
Startup CEOs have a bigger opportunity than ever before to build a long-lasting, fundamentally important technology company. But doing so requires growing — personally and professionally — to a higher level than experienced before. Doing so means committing to building a company that can go “all the way” on its own. Doing so requires scaling values, and not just in a siloed, one-time offsite kind of way. Here are some things I learned on my own journey doing this…
Company organization structure defines both how and what a company builds. It is also one of the few decisions that a CEO can clearly make. Because org structures appear to be easily distilled down to simple graphs, it’s frequently the case that when a company is doing well a given org structure serves as a model for others to follow; and when things are not going well there’s a chorus to change to some obvious alternative. Unfortunately, reality is far more complex…
Startup outcomes are, by definition, unpredictable. Working at a startup means getting in early for something that has yet to be proven, which means it could have great risks, and potentially, great rewards. But owning part of a company isn’t a static, fixed thing — it’s fluid, and there are a number of factors that could change the overall ownership equation over time. Every startup is unique, every situation has unknown variables, and new data will always change the economic outcomes. So here’s how the economics behind ownership works, from understanding cap tables and dilution to liquidation periods and ISOs vs NQOs…
One of the most vexing product challenges is evolving the UX (user experience, and/or user UI) over long periods of time, particularly when advancing a successful product with a supportive and passionate community. But once your product is woven into the fabric of people’s lives (aka customers) then change becomes extraordinarily difficult, even downright impossible. Yet change, even of a core user experience, is an essential part of the evolution of a product. For all of the debates, a product that fails to dramatically change is one that will be bypassed…
Why is it so damn hard to meet a sales forecast? There are so many ways things can go wrong during the sales process: prospects were super excited at first and indicated they were eager to buy your product, but then things got cold as it traveled through the enterprise; you thought you FOR SURE had the deal you were relying on, then later hear “I’m sorry, but…”; and so on. All it takes is for just one. little. thing. to. go. wrong. Sales professionals — as well as CROs, CFOs, and CEOs — can respond to this scenario in one of two ways: Control, or be controlled. But “control” means putting in place a strong sales, forecasting, and deal qualification process. This is not some nice-to-have operational exercise; it’s a must-have for successfully scaling your company…
Targeting customers at key inflection points — whether it’s a milestone, a point in time, or even a micro-moment — isn’t just a marketing campaign; it’s an optimal market entry (and even scaling) strategy for startups. But since the battle between startups and incumbents always comes down to “whether the startup gets distribution before the incumbent gets innovation”, the challenge for them will be to quickly expand beyond the initial inflection point to offer other products — scaling in both trust and reach — before the incumbent leverages their distribution advantage to catch up by offering better products of their own…
Many of the highest-profile tech policy issues of the day are predominantly or exclusively state, local, or international issues — not federal. And of the tech policy issues that do have a strong federal component, many are non-partisan or defy traditional partisan lines. So what about federal tech policy issues that are partisan or controversial, where the election outcome does make a big difference?
+ bonus a16z Podcast: Knowledge Builds Technology and Technology Builds Knowledge (with Joel Mokyr)
The period between 1500-1700 was an unprecedented age of technology and economic progress where we took “quantum leaps” forward in tech. But why did the Industrial Revolution take place in Europe and spread beyond? It has to do with a competitive, open market of ideas, and the conditions that created it — virtual networks, open access science, weak ties, and so on — are the very conditions we may need to sustain growth (no matter how you measure it) and prosperity today…
Doing business with — or in — China requires understanding nuances that go beyond the stats and typical headlines. Ultimately, however, learning from China also involves rethinking our mindsets around it … beginning with how to be open to learning from China in the first place, to preparing for future competition from there as Chinese companies aim to realize their global ambitions.
+ bonus related a16z Podcast: ‘In the Eye of a Tornado’ — Views on Innovation from China (with Clay Shirky)
Countries and companies (like Alibaba, WeChat, and Xiaomi) indicate a broader trend of innovation coming from China and countries that were once positioned as copycats or followers. But Chinese companies are also becoming innovation leaders in unexpected, non-obvious ways — through scale, distribution, logistics, infrastructure, O2O, a different kind of ecommerce, mobile marketing, even design. These are of a very different kind than iconic examples like, say, SpaceX or Apple, which, arguably, could damage the U.S. if single-mindedly regarded as “our official most innovative company”…