Retrospective on a dying technology cycle, part 1: Mobile
Contents
I missed the introduction of the original iPad.
Instead of watching Steve Jobs unveil his bulky slab of aluminum and glass, I was picking my way through the streets of downtown Burlingame. I’d spent what was left of my available credit card balance on a ticket to SFO.
I was due for my first tech interview.
Before he created the chat juggernaut Discord, Jason Citron founded a mobile game startup. After middling success selling games themselves, Aurora Feint had pivoted to middleware: client- and server-side social technology to serve the growing ranks of independent, mobile game developers.
A few blocks’ walk from the Caltrain station, I’d found my destination: a plain office building hosting a bank and an insurance broker on the lower floors. Hidden away upstairs, thirty employees of Aurora Feint were toiling away, trying to capture turf in the unspooling mobile revolution.
The interview was a grueling, all-day affair running 10:30 to 4, including one of those friendly lunches where the engineers try to figure out if you’re full of shit.
It was 2010, and the inertia of the financial crisis was still on me. Weeks away from homelessness, I somehow closed the day strong enough to earn my first startup job.
As a result, I got to watch the last technology cycle from its earliest phases.
It transformed my life. I wasn’t the only one.
Animating forces
The last cycle was activated by convergent forces:
- The mobile revolution: An all new set of platforms for communication, play and productivity with no incumbents. A green field for development and empire-building
- The rise of cloud computing: In the past, computing resources were expensive and provisioning was high-friction. By 2010, cloud computing offered low-risk, highly-scalable capacity for teams of any size.
- The power of open source software: Open source transformed the economics of building a software business. A vast, maturing bazaar of software resources, free to use, gave founding teams a head-start on the most common tasks. This amplified their power and allowed small seed investments to produce outsized results.
- An economy on life support: In the wake of the 2008 financial crisis, economic malaise dominated. Central bankers responded with historically low interest rates. Growing money needed a new strategy, and the growth potential of software empires was irresistible.
Each of these, alone, promised incredible power. In combination, they were responsible for a period of growing wealth and narrow prosperity without precedent. As the cycle draws to a close, we find each of these factors petering out, losing sway, or maturing into the mundane.
As a consequence, the cycle is losing steam.
This wasn’t a bubble—though it did contain a bubble, in the form of cryptomania. The last cycle was a period of dramatic, computing-driven evolution, whose winners captured value and power.
New platforms and a digital land rush
The 2007 introduction of the iPhone is a pivotal moment in the history of consumer computing. An Apple phone had been rumored for years, and on the heels of the popular iPod, it was an exciting prospect.
Mobile phones of the day were joyless, low-powered devices that frustrated users even for the most common tasks. While Palm, Blackberry and Danger were nibbling around the envelope of what was possible, none of them had command of the overall market or culture of cellphones.
So when Jobs, barely suppressing a shit-eating grin, walked through the demo of Apple’s new iPhone—easy conference calling, interactive maps, software keyboard, convenient texting—the audience gasped audibly, cheering with unrestrained delight. The user experience of the cell phone was changed forever.
To accomplish this transformation, Apple had pushed miniaturization as far as possible for the day. Using a high-efficiency processor built on the ARM architecture was a typical move for mobile computing—even Apple’s failed Newton from 15 years earlier used this approach. The revolution came from porting the foundations of Apple’s existing operating system, Mac OS X, into a form that could run within the narrow headroom of an ultra-efficient, battery-powered portable computer.
On this foundation, Apple shipped a cutting-edge UI framework that supported multitouch gestures, realtime compositing of UI elements, lush animation, and a level of instant responsiveness that had never existed in a handheld context.
While the iPhone wasn’t an overnight success—it would take years to capture its current marketshare—it was an instant sensation, eventually demolishing the fortunes of Palm, Blackberry, and Microsoft’s mobile strategy.
And without Apple’s permission, people began writing code for it.
The promise of a vast green field
Hobbyist hackers broke the iPhone’s meager security within months of its launch, and went straight to work building unauthorized apps for it. Regardless of Apple’s original plans, the potential of the platform was unmistakable, and within a year of its 2007 introduction, both the iPhone OS SDK and App Store launched.
This was yet another sensation. Indie developers were crowing about shocking revenue, with the earliest apps taking home six figures in the first month. Apple had created a vast, fertile market with turn-key monetization for every developer.
The rush was on.
Google soon joined the fray with Android, offering their own SDK and marketplace.
So by 2010, mobile was a brand new platform strategy. It used new libraries, targeted new form factors, and had all new technical constraints.
There were no incumbents. Anyone could be a winner in mobile, so loads of people tried. Moreover, the use-cases mobile presented—always connected, with realtime geolocation and communication—were entirely novel.
The story of Uber is impossible without the substrate of mobile. March of 2009, 18 months into the launch of the iPhone OS SDK, Uber was hard at work building unprecedented, automated infrastructure for car dispatch. The iPhone 3G, the most recent model of the day, had integrated cell tower-assisted GPS, allowing any device to know its exact position in realtime, even in urban areas, and report that information back to a central server. Add this to an advanced mapping API included in every iPhone, and Uber had leverage to build a category of business that had never existed.
We know the rest of the story. Uber transformed urban transportation worldwide, adopting a take-no-prisoners approach and burning through vast sums of cash.
The gig economy and the automated supervisor
Of course, Uber wasn’t the only player leveraging this power to the hilt.
Lyft and other “rideshare” startups built their own spins on the model. But the power of automation delivered through pocket-sized, always-connected computers created a new category of labor and business, which the press dubbed “the gig economy.”
Using software automation, companies could animate the behavior of legions of dubiously-categorized independent contractors. Software told these workers what to do, where to go, and when they were needed. Software onboarded these workers, software paid them, and using ratings and algorithms, software could fire them.
In an unexpected but inevitable twist of Taylorism, modern automation replaced not the worker themselves but middle managers.
Gig work created new categories of service, and invaded existing ones as well. There were apps for delivery of all foods, apps for cleaning and home handiwork, even an app that handled packing and shipping of goods, sparing you a trip to the post office. Seeimingly every commercial relationship where Silicon Valley could interpose itself, through the lure of convenience, it tried.
Reporting not to other humans but faceless, algorithm-driven apps, gig workers were precarious. Their pay was volatile, their access to opportunity was opaque. The capricious whims of customers and their ratings—a central input to the middle-management algorithms—dictated their ongoing access to income. They had limited redress when things were bad for them because the apps that defined their daily work weren’t built to express curiosity about their experiences.
And they had no direct relationships to their customers.
Gig work companies responded to these complaints by touting the flexibility their platforms offered. The rigid scheduling of legacy labor was replaced by the freedom to work when you wanted to, even at a moment’s notice.
That was just one of many opportunities created by an always-online, always-with-you computer.
The attention economy
In 1990, the only way to reach someone waiting in line at a bank was to put a poster on the wall. Most banks weren’t selling wall space, so this was their exclusive domain to sell financial products like small business loans, mortgages and savings accounts.
20 years later, a customer waiting in line at a bank had a wealth of smartphone apps competing for their attention.
Social media platforms like Facebook and Twitter were in their mobile infancy, but by 2010 anyone with a smartphone could tune out their immediate surroundings and connect with their friends. It wasn’t just social platforms, either. Mobile games like Words With Friends, Angry Birds, and Candycrush competed vigorously to hold the attention of their enthralled users.
Mobile computing created an entirely new opportunity for connecting to humans during the in-between times. Historically, digital businesses could only access humans when they were at their desks in their homes and offices. With mobile, a 24/7 surface area for commerce, advertising, culture and community arrived overnight.
Mobile ossification
So we see that the new paradigm of mobile computing opened the door to previously impossible feats. It was a space where the primary obstacles were time and funding to create something people wanted.
Today, mobile is full of incumbents. Instead of a green field, it’s a developed ecosystem full of powerful players worth trillions in total. It is a paradigm that has reached maturity.
More than a decade after smartphones became a mass-market phenomenon, they’ve grown commonplace. Yearly iterations add marginal improvements to processing speed and incremental gains on camera systems.
When Facebook craves the metaverse, it’s because their totalizing strategy for growth—two billion users to date—is approaching a ceiling. They badly want a new frontier to grow in again, and they’d love to control the hardware as much as the software.
But VR doesn’t solve everyday problems the way smartphones did. No one craves a bulky headset attached to their face, blocking reality, with battery life measured at a couple hours. Augmented reality might have greater impact, but miniaturizing the technology needed to provide comfortable overlays with the same constant presence as the smartphone in your pocket is still years away. Could it be less than five? Maybe, but I wouldn’t bet on it. More than ten? Unlikely.
That range doesn’t present immediate opportunities for new growth on the scale they need. Indeed, Facebook is retreating from its most ambitious positions on the metaverse, as its strategy committed billions to the effort for limited return.
There will be new paradigms for mobile computing. But we’re not there yet. Even so, Apple—16 years gone from their revolutionary iPhone announcement—is poised to release their own take on VR/AR. And like Facebook, they’re stuck with technological reality as it is. Perhaps their software advantage will give them the cultural traction Facebook couldn’t find.
Next
In my next post, I’ll get into the twin engines of cloud computing and open source, which were crucial foundations to the mobile revolution.
Native code wasn’t enough. True power was orchestration of opportunity between devices, which needed server-side technology. Through the power of open source code running in the cloud, any team could put together a complete solution that had never been seen before.