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In the years that followed, the goal went from taking huge risks to create new industries and grand new ideas, to chasing easier money by entertaining consumers and pumping out simple apps and advertisements. “The best minds of my generation are thinking about how to make people click ads,” Jeff Hammerbacher, an early Facebook engineer, told me. “That sucks.” Silicon Valley began to look an awful lot like Hollywood.

it's going great. Two months in, and I've created three apps." "Apps?" "For people who buy my book as an e-book --which will be everybody. The first is called Don't Look. It's for the overly sensitive. It blurs and turns the type red when a dog dies or a baby is born with a birth defect. Stuff like that. My second is It's Not Okay When You Say It, and it delivers an electrical zap if the reader laughs at a racial slur. My third is Jesus Thesaurus, which replaces explicit sexual language with church words. So, when one of my characters 'saints' a guy's 'disciple', He'll beg her to 'cavalry' his 'Baptists' and 'shout amen'.

Fortunately, there’s an app for that! It’s called Sonic Sleep Coach, created by Daniel Gartenberg, PhD, who has been awarded more than $1 million in NIH grants to study sleep.

The way we live now is an experiment in which we are the human subjects—treated as objects by the technology we have created. Our apps use us as much as we use our apps.

Shifting to an outcome mindset is harder than it looks. We spend most of our time talking about outputs. So, it’s not surprising that we tend to confuse the two. Even when teams intend to choose an outcome, they often fall into the trap of selecting an output. I see teams set their outcome as “Launch an Android app” instead of “Increase mobile engagement” or “Get to feature parity on the new tech stack” instead of “Transition customer to the new tech stack.

And to start with I would focus on five of these killer apps that have immediate application to governing today: (1) the ability to adapt when confronted by strangers with superior economic and military might without being hobbled by humiliation; (2) the ability to embrace diversity; (3) the ability to assume ownership over the future and one’s own problems; (4) the ability to get the balance right between the federal and the local—that is, to understand that a healthy society, like a healthy tropical forest, is a network of healthy ecosystems on top of ecosystems, each thriving on its own but nourished by the whole; and, maybe most important, (5) the ability to approach politics and problem-solving in the age of accelerations with a mind-set that is entrepreneurial, hybrid, and heterodox and nondogmatic—mixing and coevolving any ideas or ideologies that will create resilience and propulsion, no matter whose “side” they come from. Of

Most of the successful innovators and entrepreneurs in this book had one thing in common: they were product people. They cared about, and deeply understood, the engineering and design. They were not primarily marketers or salesmen or financial types; when such folks took over companies, it was often to the detriment of sustained innovation. “When the sales guys run the company, the product guys don’t matter so much, and a lot of them just turn off,” Jobs said. Larry Page felt the same: “The best leaders are those with the deepest understanding of the engineering and product design.”34 Another lesson of the digital age is as old as Aristotle: “Man is a social animal.” What else could explain CB and ham radios or their successors, such as WhatsApp and Twitter? Almost every digital tool, whether designed for it or not, was commandeered by humans for a social purpose: to create communities, facilitate communication, collaborate on projects, and enable social networking. Even the personal computer, which was originally embraced as a tool for individual creativity, inevitably led to the rise of modems, online services, and eventually Facebook, Flickr, and Foursquare. Machines, by contrast, are not social animals. They don’t join Facebook of their own volition nor seek companionship for its own sake. When Alan Turing asserted that machines would someday behave like humans, his critics countered that they would never be able to show affection or crave intimacy. To indulge Turing, perhaps we could program a machine to feign affection and pretend to seek intimacy, just as humans sometimes do. But Turing, more than almost anyone, would probably know the difference. According to the second part of Aristotle’s quote, the nonsocial nature of computers suggests that they are “either a beast or a god.” Actually, they are neither. Despite all of the proclamations of artificial intelligence engineers and Internet sociologists, digital tools have no personalities, intentions, or desires. They are what we make of them.

The all-consuming selves we take for granted today are “merely empty receptacles of desire.” Infinitely plastic and decentered, the modern citizen of the republic of consumption lives on slippery terrain, journeying to nowhere in particular. So too, nothing could be more corrosive of the kinds of social sympathy and connectedness that constitute the emotional substructure of collective resistance and rebellion. Instead, consumer culture cultivates a politics of style and identity focused on the rights and inner psychic freedom of the individual, one not comfortable with an older ethos of social rather than individual liberation. On the contrary, it tends to infantilize, encouraging insatiable cravings for more and more novel forms of a faux self-expression. The individuality it promises is a kind of perpetual tease, nowadays generating, for example, an ever-expanding galaxy of internet apps leaving in their wake a residue of chronic anticipation. Hibernating inside this “material girl” quest for more stuff and self-improvement is a sacramental quest for transcendence, reveries of what might be, a “transubstantiation of goods, using products and gear to create a magical realm in which all is harmony, happiness, and contentment… in which their best and most admirable self will emerge at last.” The privatization of utopia! Still, what else is there?

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Since tech became a consumer phenomenon, thousands of nontech people have come up with great ideas that use technology. But if their startups outsource their engineering, they almost always fail. Why? It turns out that it’s easy to build an app or a website that meets the specification of some initial idea, but far more difficult to build something that will scale, evolve, handle edge cases gracefully, etc. A great engineer will only invest the time and effort to do all those things, to build a product that will grow with the company, if she has ownership in the company—literally as well as figuratively. Bob Noyce understood that, created the culture to support it, and changed the world.

As should be obvious by now, surveillance is the business model of the Internet. You create “free” accounts on Web sites such as Snapchat, Facebook, Google, LinkedIn, Foursquare, and PatientsLikeMe and download free apps like Angry Birds, Candy Crush Saga, Words with Friends, and Fruit Ninja, and in return you, wittingly or not, agree to allow these companies to track all your moves, aggregate them, correlate them, and sell them to as many people as possible at the highest price, unencumbered by regulation, decency, or ethical limitation. Yet so few stop and ask who else has access to all these data detritus and how it might be used against us. Dataveillance is the “new black,” and its uses, capabilities, and powers are about to mushroom in ways few consumers, governments, or technologists might have imagined.

Using Anchors is a great approach to designing prompts because anyone can do it. There’s no need for fancy watches or whizzy apps to prompt new habits. You can do it yourself more effectively, and you will discover how transformative a simple design hack can be. The power of after is not magic, it’s closer to chemistry. Combine the right behaviors with the right chronology, and, poof, a new habit is created.

With 21 million people following her on Facebook and 18 million on Twitter, pop singer Ariana Grande can’t personally chat with each of her loves, as she affectionately calls her fans. So she and others are spreading their messages through new-style social networks, via mobile apps that are more associated with private, intimate conversation, hoping that marketing in a cozier digital setting adds a breath of warmth and a dash of personality. It’s the Internet’s equivalent of mailing postcards rather than plastering a billboard. Grande could have shared on Twitter that her most embarrassing moment on stage was losing a shoe. The 21-year-old instead revealed the fact during a half-hour live text chat on Line, an app built for close friends to exchange instant messages. It’s expensive to advertise on Facebook and Twitter, and the volume of information being posted creates uncertainty over what people actually notice. Chat apps including Line, Kik, Snapchat, WeChat and Viber place marketing messages front and center. Most-used apps The apps threaten to siphon advertising dollars from the social media leaders, which are already starting to see chat apps overtake them as the most-used apps on smartphones, according to Forrester Research. Chat apps “demand attention,” said Rebecca Lieb, an analyst at consulting firm Altimeter Group.

Jobs spent part of every day for six months helping to refine the display. “It was the most complex fun I’ve ever had,” he recalled. “It was like being the one evolving the variations on ‘Sgt. Pepper.’ ” A lot of features that seem simple now were the result of creative brainstorms. For example, the team worried about how to prevent the device from playing music or making a call accidentally when it was jangling in your pocket. Jobs was congenitally averse to having on-off switches, which he deemed “inelegant.” The solution was “Swipe to Open,” the simple and fun on-screen slider that activated the device when it had gone dormant. Another breakthrough was the sensor that figured out when you put the phone to your ear, so that your lobes didn’t accidentally activate some function. And of course the icons came in his favorite shape, the primitive he made Bill Atkinson design into the software of the first Macintosh: rounded rectangles. In session after session, with Jobs immersed in every detail, the team members figured out ways to simplify what other phones made complicated. They added a big bar to guide you in putting calls on hold or making conference calls, found easy ways to navigate through email, and created icons you could scroll through horizontally to get to different apps—all of which were easier because they could be used visually on the screen rather than by using a keyboard built into the hardware.

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Regardless of the propaganda espoused by large corporations, governments, religions, and other institutions, we can all follow this simple path in creating the seemingly elusive “world that works for everyone” right here and right now. Only we individuals can think and take action. No corporation will ever generate a single thought—much less invent the next great app, computer program, or ground transportation vehicle. No religion will ever come up with a single inspirational aphorism. And no government will ever shut down a single military facility. These things are all initiated and accomplished by individuals.

And the hot new things that were just starting out—Facebook and Twitter—certainly did not look like their predecessors—Hewlett-Packard, Intel, Sun Microsystems—that made physical products and employed tens of thousands of people in the process. In the years that followed, the goal went from taking huge risks to create new industries and grand new ideas, to chasing easier money by entertaining consumers and pumping out simple apps and advertisements. “The best minds of my generation are thinking about how to make people click ads,” Jeff Hammerbacher, an early Facebook engineer, told me. “That sucks.” Silicon Valley began to look an awful lot like Hollywood. Meanwhile, the consumers it served had turned inward, obsessed with their virtual lives.

In the longer term, by bringing together enough data and enough computing power, the data giants could hack the deepest secrets of life, and then use this knowledge not just to make choices for us or manipulate us but also to reengineer organic life and create inorganic life-forms. Selling advertisements may be necessary to sustain the giants in the short term, but tech companies often evaluate apps, products, and other companies according to the data they harvest rather than according to the money they generate. A popular app may lack a business model and may even lose money in the short term, but as long as it sucks data, it could be worth billions.4 Even if you don’t know how to cash in on the data today, it is worth having it because it might hold the key to controlling and shaping life in the future. I don’t know for certain that the data giants explicitly think about this in such terms, but their actions indicate that they value the accumulation of data in terms beyond those of mere dollars and cents. Ordinary humans will find it very difficult to resist this process. At present, people are happy to give away their most valuable asset—their personal data—in exchange for free email services and funny cat videos. It’s a bit like African and Native American tribes who unwittingly sold entire countries to European imperialists in exchange for colorful beads and cheap trinkets. If, later on, ordinary people decide to try to block the flow of data, they might find it increasingly difficult, especially as they might come to rely on the network for all their decisions, and even for their healthcare and physical survival.

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Take the New York–based Lemonade, arguably the best funded of today’s crowdsurance startups. Via an app, Lemonade brings together small groups of policyholders who pay premiums into a central “claim pool.” Artificial intelligence does the rest. The entire experience is mobile, simple, and fast. Ninety seconds to get insured, three minutes to get a claim paid, and zero paperwork. Adding more technology to this arrangement, companies like the Swiss firm Etherisc sell “bespoke insurance products” on the Ethereum blockchain. Because smart contracts remove the need for employees, paperwork, and all the rest, all sorts of new insurance products are being created. Etherisc’s first offering is something not covered by traditional insurers: flight delays and cancellations. Individuals sign up via credit card, and if their plane is more than forty-five minutes late, they’re paid instantly, automatically, and without the need for any paperwork.

However this future evolves, we will have to answer a pressing question: How will writers (or anyone else who creates content that can be digitized, from movies to music to apps to journalism) make a living in an era in which digital content can be freely replicated? That is now my greatest worry as I contemplate the so-called writing life that I hope to continue—and that I hope my daughter and all future generations will continue. For three hundred years, ever since the Statute of Anne was established in Britain, there has been a system under which people who created things, such as books or articles or music or pictures, had a right to benefit from copies that were made of them. Because of this “copyright” system, we have encouraged and rewarded three centuries of creativity in various fields of endeavor, and this has produced a flourishing economy based on the creation by talented individuals of intellectual property. Among other things, this allowed all sorts of people, ranging from Walker Percy on down to me, to make a living at the so-called writing life. May the next generation enjoy that delightful opportunity as well.

We pay a high price for this ingenious neural machinery, though, because the default mode network is responsible for mind-wandering. “Experience sampling”—which involves asking people about their mood and thoughts at random moments throughout the day—suggests that our minds wander from what we’re actually doing an amazing 30 percent to 50 percent of the time that we’re awake, and that this is often associated with feelings of unhappiness.6–8 According to Harvard psychologists Matthew Killingsworth and Daniel Gilbert, who created an iPhone app, Rate Your Happiness, to gather some of this data, fluctuations in happiness depend more on what we’re thinking than what we’re doing. Crucially, the results suggest that mind-wandering is the cause rather than the consequence of negative emotions. As the opening verse of the Dhammapada expresses it, “Our life is shaped by our mind; we become what we think. Suffering follows an evil thought as the wheels of a cart follow the oxen that draw it.”9 Less poetically, the psychologists concluded that “the ability to think about what is not happening is a cognitive achievement that comes at an emotional cost.” So, while

Mosseri’s answer to the important question was perfect by Facebook standards: “Technology isn’t good or bad—it just is,” he wrote. “Social media is a great amplifier. We need to do all we can responsibly to magnify the good and address the bad.” But nothing “just is,” especially Instagram. Instagram isn’t designed to be a neutral technology, like electricity or computer code. It’s an intentionally crafted experience, with an impact on its users that is not inevitable, but is the product of a series of choices by its makers about how to shape behavior. Instagram trained its users on likes and follows, but that wasn’t enough to create the emotional attachment users have to the product today. They also thought about their users as individuals, through the careful curation of an editorial strategy, and partnerships with top accounts. Instagram’s team is expert at amplifying “the good.” When it comes to addressing “the bad,” though, employees are concerned the app is thinking in terms of numbers, not people. Facebook’s top argument against a breakup is that its “family of apps” evolution will be better for users’ safety. “If you want to prevent interference in elections, if you want to reduce[…]

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Social networks including Facebook, Twitter and Pinterest took a step closer to offering ecommerce on their own platforms this week, as the battle to win over retailers hots up. Facebook announced on Thursday it is trialling a “buy” button to allow people to purchase a product without ever leaving the social network’s app. The initial test, with a handful of small and medium-sized businesses in the US, could lead to more ecommerce companies buying adverts on the network. It could also allow Facebook to compile payment information and encourage people to make more transactions via the platform as it would save them typing in card numbers on smartphones. But the social network said no credit or debit card details will be shared with other advertisers. Twitter acquired CardSpring, a payments infrastructure company, this week for an undisclosed price as part of plans to feature more ecommerce around live events or, as it puts it, “in-the-moment commerce experiences”. CardSpring connects payment details with loyalty cards and coupons for transactions online and in stores. The home of the 140-character message hired Nathan Hubbard, former chief executive of Ticketmaster, last year to work on creating an ecommerce product. It has since worked with Amazon, to allow people to add things to their online basket by tweeting, and with Starbucks to encourage people to tweet to buy a coffee for a friend.

Here’s some startup pedagogy for you: When confronted with any startup idea, ask yourself one simple question: How many miracles have to happen for this to succeed? If the answer is zero, you’re not looking at a startup, you’re just dealing with a regular business like a laundry or a trucking business. All you need is capital and minimal execution, and assuming a two-way market, you’ll make some profit. To be a startup, miracles need to happen. But a precise number of miracles. Most successful startups depend on one miracle only. For Airbnb, it was getting people to let strangers into their spare bedrooms and weekend cottages. This was a user-behavior miracle. For Google, it was creating an exponentially better search service than anything that had existed to date. This was a technical miracle. For Uber or Instacart, it was getting people to book and pay for real-world services via websites or phones. This was a consumer-workflow miracle. For Slack, it was getting people to work like they formerly chatted with their girlfriends. This is a business-workflow miracle. For the makers of most consumer apps (e.g., Instagram), the miracle was quite simple: getting users to use your app, and then to realize the financial value of your particular twist on a human brain interacting with keyboard or touchscreen. That was Facebook’s miracle, getting every college student in America to use its platform during its early years. While there was much technical know-how required in scaling it—and had they fucked that up it would have killed them—that’s not why it succeeded. The uniqueness and complete fickleness of such a miracle are what make investing in consumer-facing apps such a lottery. It really is a user-growth roulette wheel with razor-thin odds. The classic sign of a shitty startup idea is that it requires at least two (or more!) miracles to succeed. This was what was wrong with ours. We had a Bible’s worth of miracles to perform:

Patrick Vlaskovits, who was part of the initial conversation that the term “growth hacker” came out of, put it well: “The more innovative your product is, the more likely you will have to find new and novel ways to get at your customers.”12 For example: 1. You can create the aura of exclusivity with an invite-only feature (as Mailbox did). 2. You can create hundreds of fake profiles to make your service look more popular and active than it actually is—nothing draws a crowd like a crowd (as reddit did in its early days). 3. You can target a single service or platform and cater to it exclusively—essentially piggybacking off or even stealing someone else’s growth (as PayPal did with eBay). 4. You can launch for just a small group of people, own that market, and then move from host to host until your product spreads like a virus (which is what Facebook did by starting in colleges—first at Harvard—before taking on the rest of the population). 5. You can host cool events and drive your first users through the system manually (as Myspace, Yelp, and Udemy all did). 6. You can absolutely dominate the App Store because your product provides totally new features that everyone is dying for (which is what Instagram did—twenty-five thousand downloads on its first day—and later Snapchat). 7. You can bring on influential advisors and investors for their valuable audience and fame rather than their money (as About.me and Trippy did—a move that many start-ups have emulated). 8. You can set up a special sub-domain on your e-commerce site where a percentage of every purchase users make goes to a charity of their choice (which is what Amazon did with Smile.Amazon.com this year to great success, proving that even a successful company can find little growth hacks). 9. You can try to name a Planned Parenthood clinic after your client or pay D-list celebrities to say offensive things about themselves to get all sorts of publicity that promotes your book (OK, those stunts were mine).

Isaac Asimov’s short story “The Fun They Had” describes a school of the future that uses advanced technology to revolutionize the educational experience, enhancing individualized learning and providing students with personalized instruction and robot teachers. Such science fiction has gone on to inspire very real innovation. In a 1984 Newsweek interview, Apple’s co-founder Steve Jobs predicted computers were going to be a bicycle for our minds, extending our capabilities, knowledge, and creativity, much the way a ten-speed amplifies our physical abilities. For decades, we have been fascinated by the idea that we can use computers to help educate people. What connects these science fiction narratives is that they all imagined computers might eventually emulate what we view as intelligence. Real-life researchers have been working for more than sixty years to make this AI vision a reality. In 1962, the checkers master Robert Nealey played the game against an IBM 7094 computer, and the computer beat him. A few years prior, in 1957, the psychologist Frank Rosenblatt created Perceptron, the first artificial neural network, a computer simulation of a collection of neurons and synapses trained to perform certain tasks. In the decades following such innovations in early AI, we had the computation power to tackle systems only as complex as the brain of an earthworm or insect. We also had limited techniques and data to train these networks. The technology has come a long way in the ensuing decades, driving some of the most common products and apps today, from the recommendation engines on movie streaming services to voice-controlled personal assistants such as Siri and Alexa. AI has gotten so good at mimicking human behavior that oftentimes we cannot distinguish between human and machine responses. Meanwhile, not only has the computation power developed enough to tackle systems approaching the complexity of the human brain, but there have been significant breakthroughs in structuring and training these neural networks.

Key Points: ● Transparency - Blockchain offers significant improvements in transparency compared to existing record keeping and ledgers for many industries. ● Removal of Intermediaries – Blockchain-based systems allow for the removal of intermediaries involved in the record keeping and transfer of assets. ● Decentralization – Blockchain-based systems can run on a decentralized network of computers, reducing the risk of hacking, server downtime and loss of data. ● Trust – Blockchain-based systems increase trust between parties involved in a transaction through improved transparency and decentralized networks along with removal of third-party intermediaries in countries where trust in the intermediaries doesn’t exist. ● Security – Data entered on the blockchain is immutable, preventing against fraud through manipulating transactions and the history of data. Transactions entered on the blockchain provide a clear trail to the very start of the blockchain allowing any transaction to be easily investigated and audited. ● Wide range of uses - Almost anything of value can be recorded on the blockchain and there are many companies and industries already developing blockchain-based systems. These examples are covered later in the book. ● Easily accessible technology – Along with the wide range of uses, blockchain technology makes it easy to create applications without significant investment in infrastructure with recent innovations like the Ethereum platform. Decentralized apps, smart contracts and the Ethereum platform are covered later in the book. ● Reduced costs – Blockchain-based ledgers allow for removal of intermediaries and layers of confirmation involved in transactions. Transactions that may take multiple individual ledgers, could be settled on one shared ledger, reducing the costs of validating, confirming and auditing each transaction across multiple organizations. ● Increased transaction speed – The removal of intermediaries and settlement on distributed ledgers, allows for dramatically increased transaction speeds compared to a wide range of existing systems.

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me to be honest about his failings as well as his strengths. She is one of the smartest and most grounded people I have ever met. “There are parts of his life and personality that are extremely messy, and that’s the truth,” she told me early on. “You shouldn’t whitewash it. He’s good at spin, but he also has a remarkable story, and I’d like to see that it’s all told truthfully.” I leave it to the reader to assess whether I have succeeded in this mission. I’m sure there are players in this drama who will remember some of the events differently or think that I sometimes got trapped in Jobs’s distortion field. As happened when I wrote a book about Henry Kissinger, which in some ways was good preparation for this project, I found that people had such strong positive and negative emotions about Jobs that the Rashomon effect was often evident. But I’ve done the best I can to balance conflicting accounts fairly and be transparent about the sources I used. This is a book about the roller-coaster life and searingly intense personality of a creative entrepreneur whose passion for perfection and ferocious drive revolutionized six industries: personal computers, animated movies, music, phones, tablet computing, and digital publishing. You might even add a seventh, retail stores, which Jobs did not quite revolutionize but did reimagine. In addition, he opened the way for a new market for digital content based on apps rather than just websites. Along the way he produced not only transforming products but also, on his second try, a lasting company, endowed with his DNA, that is filled with creative designers and daredevil engineers who could carry forward his vision. In August 2011, right before he stepped down as CEO, the enterprise he started in his parents’ garage became the world’s most valuable company. This is also, I hope, a book about innovation. At a time when the United States is seeking ways to sustain its innovative edge, and when societies around the world are trying to build creative digital-age economies, Jobs stands as the ultimate icon of inventiveness, imagination, and sustained innovation. He knew that the best way to create value in the twenty-first century was to connect creativity with technology, so he built a company where leaps of the imagination were combined with remarkable feats of engineering. He and his colleagues at Apple were able to think differently: They developed not merely modest product advances based on focus groups, but whole new devices and services that consumers did not yet know they needed. He was not a model boss or human being, tidily packaged for emulation. Driven by demons, he could drive those around him to fury and despair. But his personality and passions and products were all interrelated, just as Apple’s hardware and software tended to be, as if part of an integrated system. His tale is thus both instructive and cautionary, filled with lessons about innovation, character, leadership, and values.

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The trainers at Uberversity, where new employees underwent a three-day initiation, began schooling everyone on this scenario: a rival company is launching a carpooling service in four weeks. It’s impossible for Uber to beat them to market with a reliable carpool service of its own. What should the company do? The correct answer at Uberversity—and what Uber actually did when it learned about Lyft Line—was “Rig up a makeshift solution that we pretend is totally ready to go so we can beat the competitor to market.” (Andreessen Horowitz, the venture capital firm where I work, invested in Lyft and I am on its board, so I was keenly aware of the dynamic between the companies—and I am decidedly biased.) Those, including the company’s legal team, who proposed taking the time to come up with a workable product, one far better than Uber Pool 1.0, were told “That’s not the Uber way.” The underlying message was clear: if the choice is integrity or winning, at Uber we do whatever we have to do to win. This competitiveness issue also came up when Uber began to challenge Didi Chuxing, the Chinese market leader in ride-sharing. To counter Uber, Didi employed very aggressive techniques including hacking Uber’s app to send it fake riders. The Chinese law on the tactic wasn’t entirely clear. The Chinese branch of Uber countered by hacking Didi right back. Uber then brought those techniques home to the United States by hacking Lyft with a program known as Hell, which inserted fake riders into Lyft’s system while simultaneously funneling Uber the information it needed to recruit Lyft drivers. Did Kalanick instruct his subordinates to employ these measures, which were at best anticompetitive and at worst arguably illegal? It’s difficult to say, but the point is that he didn’t have to—he had already programmed the culture that engendered those measures.

Image Assistant command line interface (CLI) operations. For more information, see Create Your AppStream 2.0 Image Programmatically by Using the Image Assistant CLI Operations.

Mind-mapping involves drawing a visual outline of your book on a large sheet of paper. You start in the middle with the core topic and then spider out to all of the sub-sections. For instance, with this book, I’d put Buy Buttons in the middle with lines connecting to Sharing Economy Platforms, Marketplaces to Sell Your Skills, and Marketplaces to Sell Physical Products. From there, I’d add the next layer. For instance, I’d add Ridesharing Platforms and Home Sharing Platforms and connect those to Sharing Economy Platforms. Off Ridesharing Platforms, I’d connect Uber and Lyft. In this way, you can create a visual map of your entire book before you even write your first words.

In the years that followed, the goal went from taking huge risks to create new industries and grand new ideas, to chasing easier money by entertaining consumers and pumping out simple apps and advertisements. “The best minds of my generation are thinking about how to make people click ads,” Jeff Hammerbacher, an early Facebook engineer, told me. “That sucks.” Silicon Valley began to look an awful lot like Hollywood. Meanwhile, the consumers it served had turned inward, obsessed with their virtual lives.

Because Bitcoin allows developers to build on top of the blockchain protocol, it enables countless new uses of the underlying technology. Just as Apple’s iOS platform created a world where “there’s an app for that,” we may soon be in a world where “there’s a Bitcoin app for that.

By settling, you are not giving up who you are but rather shifting your perspective with what is important to you currently. Ultimately, this could provide an opportunity to create deeper and more meaningful connections with someone special.

Using the Bible App at church not only has the benefit of driving growth, it also builds commitment. Every time users highlight a verse, add a comment, create a bookmark, or share from the app, they invest in it.

Ethereum’s network with its underlying blockchain went live on July 30, 2015. While much development energy had gone into creating the Ethereum software, this was the first time that miners could get involved because there was finally a blockchain for them to support. Prior to this launch, Ethereum was quite literally suspended in the ether. Now, Ethereum’s decentralization platform was open for business, serving as the hardware and software base for decentralized applications (dApps). These dApps can be thought of as complex smart contracts, and could be created by developers independent of the core Ethereum team, providing leverage to the reach of the technology.

To explain how a dApp works, we’ll use an example from the company Etherisc, which created a dApp for flight insurance to a well-known Ethereum conference. This flight insurance was purchased by 31 of the attendees.23 Figure 5.1 shows a simplified diagram. Using Ethereum, developers can mimic insurance pools with strings of conditional transactions. Open sourcing this process and running it on top of Ethereum’s world computer allows everyday investors to put their capital in an insurance pool to earn returns from the purchasers of insurance premiums that are looking for coverage from certain events. Everyone trusts the system because it runs in the open and is automated by code.

A still more sobering social media example of a different kind, one so important that it could well have influenced the presidential election of 2016, was the cooperation between Cambridge Analytica and Facebook. Cambridge Analytica, a political data firm, was largely the creation of Steve Bannon and his billionaire sponsor, Robert Mercer. One former co-executive referred to Cambridge Analytica as “Bannon’s arsenal of weaponry to wage a culture war on America using military strategies.” Cambridge Analytica combined a particularly vicious version of traditional “dirty tricks” with cutting-edge social media savvy. The dirty tricks, according to its former CEO, Alexander Nix, included bribery, sting operations, the use of prostitutes, and “honey traps” (usually involving sexual behavior, sometimes even initiated for the purposes of obtaining compromising photographs) to discredit politicians on whom it conducted opposition research. The social media savvy included advanced methods developed by the Psychometrics Centre of Cambridge University. Aleksandr Kogan, a young Russian American psychologist working there, created an app that enabled him to gain access to elaborate private information on more than fifty million Facebook users, information specifically identifying personality traits that influenced behavior. Kogan had strong links to Facebook, which failed to block his harvesting of that massive data; he then passed the data along to Cambridge Analytica. Kogan also taught at the Saint Petersburg State University in Russia; and given the links between Cambridge Analytica and Russian groups, the material was undoubtedly made available to Russian intelligence. So extensive was Cambridge Analytica’s collection of data that Nix could boast, “Today in the United States we have somewhere close to 4 or 5 thousand data points on every individual…. So we model the personality of every adult across the United States, some 230 million people.” Whatever his exaggeration, he was describing a new means of milieu control that was invisible and potentially manipulable in the extreme. Beyond Cambridge Analytica or Kogan, Russian penetration of American social media has come to be recognized as a vast enterprise involving extensive falsification and across-the-board anti-Clinton messages, with special attention given to African American men in order to discourage them from voting. The Russians apparently reached millions of people and surely had a considerable influence on the outcome of the election. More generally, one can say that social media platforms can now create a totality of their own, and can make themselves available to would-be owners of reality by means of massive deception, distortion, and promulgation of falsehoods. The technology itself promotes mystification and becomes central to creating and sustaining cultism. Trump is the first president to have available to him these developments in social media. His stance toward the wild conspiracism I have mentioned is to stop short of total allegiance to them, but at the same time to facilitate them and call them forth in his tweets and harbor their followers at his rallies. All of this suggests not only that Trump and the new social media are made for each other, but also that the problem will long outlive Trump’s brief, but all too long, moment on the historical stage.

of chess “forbidden”. Tiktok, the Chinese-owned short-video-sharing app popular with teens, instructed moderators to suppress posts created by users deemed too ugly, poor, or disabled for the platform.

By employing emotional design in our app, we’re consciously shaping positive memories of our brand that not only encourage users to stick around, but also turn them into evangelists for a product they love.

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Given the hostility and intensity of these supply operations, it is not too surprising that Disconnect software was banned from Google Play’s vast catalog of mobile apps, leading to Disconnect’s lawsuit against Google in 2015. The startup’s complaint explains that “advertising companies including Google use these invisible connections to ‘track’ the user as he/she browses the web or opens other mobile applications, in order to collect personal information about the user, create a ‘profile’ of the user, and make money targeting advertising to the user.

We see the same dynamic in climate discussions – the outsourcing to the individual to solve systemic problems, the familiar clichés that this will all be solved by individuals recycling, buying reusable coffee cups and possibly downloading an app. Personal ethical choice is undeniably important, for both the drugs trade and the environment. But as thinkers and campaigners, we cannot let these discussions be weaponized to derail the push for systemic change. Those who created these problems will try and make them yours to solve – don’t let them.

In 2012, Google Maps had become the premier provider of mapping services and location data for mobile phone users. It was a popular feature on Apple’s iPhone. However, with more consumer activity moving to mobile devices and becoming increasingly integrated with location data, Apple realized that Google Maps was becoming a significant threat to the long-term profitability of its mobile platform. There was a real possibility that Google could make its mapping technology into a separate platform, offering valuable customer connections and geographic data to merchants, and siphoning this potential revenue source away from Apple. Apple’s decision to create its own mapping app to compete with Google Maps made sound strategic sense—despite the fact that the initial service was so poorly designed that it caused Apple significant public embarrassment. The new app misclassified nurseries as airports and cities as hospitals, suggested driving routes that passed over open water (your car had better float!), and even stranded unwary travelers in an Australian desert a full seventy kilometers from the town they expected to find there. iPhone users erupted in howls of protest, the media had a field day lampooning Apple’s misstep, and CEO Tim Cook had to issue a public apology.19 Apple accepted the bad publicity, likely reasoning that it could quickly improve its mapping service to an acceptable quality level—and this is essentially what has happened. The iPhone platform is no longer dependent on Google for mapping technology, and Apple has control over the mapping application as a source of significant value.

A TikTok clone app script is a pre-built software solution that allows you to create a short-form video sharing app that is similar to TikTok in terms of features and functionality. TikTok clone scripts are typically much less expensive than developing a custom app from scratch, and they can be deployed quickly, allowing you to launch your video sharing app in a short amount of time. TikTok clone scripts are highly customizable, allowing you to tailor the platform to your specific needs. For example, you can change the branding of the app, add or remove features, and integrate your own monetization strategies. Here are some of the key features that you should look for in a TikTok clone app script: • Video recording and editing: The script should allow users to record and edit short-form videos. Editing features should include trimming, cropping, adding music and effects, and more. • Social features: The script should include social features such as following other users, liking and commenting on videos, and creating and participating in challenges. • Content moderation: The script should have robust content moderation systems in place to prevent the spread of harmful or offensive content. • Monetization options: The script should support a variety of monetization options, such as in-app advertising, subscription fees, and virtual goods. Once you have chosen a TikTok clone app script, you will need to work with a development team to customize the script and deploy your app. The development team will also help you to set up your monetization strategies and launch your app on the App Store and Google Play.

Every photograph has the capacity to be a creative canvas, and with the correct tools, commonplace events may become engrossing visual tales. Here's PicVik, an AI photo editor, collage creator, and background remover tool that blurs the lines between creativity and innovation. PicVik is more than simply an app; it's a doorway to a world where your artistic ambitions and the power of artificial intelligence collide. With PicVik, you can easily remove backgrounds from photos, create complex collages, and enhance the details in your images. PicVik is meant to be your go-to tool for digital art.

The way we live now is an experiment in which we are the human subjects -- treated as objects by the technology we have created. Our apps use us as much as we use our apps. We are treated as objects when we are swept up as data to be bought and sold on an international market. Or when our attention is manipulated by our devices, not just to keep us glued to them but to determine what we read, what images we see, and what programs get to see us. We reduce ourselves to objects when we are addressed by machine-generated text or voices, because to be understood, we can only respond in ways that such objects can understand. When we are treated as objects, we are encouraged to object4ify one another and, of course, ourselves.

Presenting to Investors TEAM FIRST • Who are you? • Why are you personally passionate (or uniquely qualified) about creating this business? MARKET/OPPORTUNITY • Who are you serving? • What is their unmet need? • Why is there an opportunity? • How big is that opportunity? IDEA • Why is your idea unique in the market? • Why is it changing how this customer need or problem is already being addressed? RISKS • What are the risks? (And be honest, there are always risks.) • How will you address them (if at all)? THE ASK • How much capital do you need to fund a pilot? The Beta? • In Year 1, what do you believe the costs and revenue will be? What about in Year 5?

In the Information Age and the age of the Internet, millions of people under the age of 30 are getting rich using their imaginations to create apps that change the world—from Facebook to Uber to Snapchat and others. Those with imaginations thrive while those without it are still looking for a job… a job that may soon be replaced by robots and technology.

Vision mission: What was the original market or technology insight that led you to create this company? Customers: Who do you envision buying this product or service? Who will use it? Problem statement: What’s the problem you think you can solve for your potential customers? Use cases: What are the specific ways people will use this product or service to solve their problem? Product/solution: Give a detailed explanation of the technology behind the solution—what does it do now, and what else is it capable of doing? Ecosystem: In many cases there are other companies involved in solving the problem or adding additional value. These companies form an ecosystem around the problem and solution. What are all the companies and where in the ecosystem are the control points where one company has leverage? Competition: Who else is trying to solve this problem—or, if no one else sees the problem yet, who might jump in to compete with you to solve the problem once you identify it? Business model: How will your product or service change business for your customers? Will it increase their return on investment or reduce costs in a significant way? Or does it allow them to do something that couldn’t have been done with prior technology, creating huge value? Sales and go-to-market: Enterprise companies should articulate how the product or solution will make its way to the market. Through a sales force? Through distribution partners? Both? For a consumer company, how will users find out about your solution? From app stores? Search? Viral adoption? Growth hacking techniques? Advertising? PR? Organization: How is the company organized? Who are the major influencers on the company? How are decisions made? What kind of culture will work? Funding strategy: What’s the next funding event? A private financing? An IPO? How much runway does the company have before it needs more money and what kind of funding is in place to execute against the category strategy?

How to Build a Mobile App with React Native With the continuous evolution of web applications, real-time apps, and hybrid apps, the companies want faster development and easy maintenance for their app. Due to high-end technologies, the React Native app development has earned its significance in bringing all of these together within the limited budget of the companies. Overview of React Native As the React Native is based on the React framework, it is good for React Native app development to follow the same. In addition to that, React Native has separate APIs for both the platforms, it allows development for both Android and iOS in the single app, and most importantly, it is free and open-source. Facebook’s React Native Developing apps that run on the different operating systems with one tool, especially mobile devices, would be a great advantage to the developers. Therefore, the React Native development by Facebook is one of the best ways to build apps that are scalable and flexible. The Android App Development with React Native With the number of active Android users, it has created more value to the companies in developing the apps for android mobile devices. Working with React Native In React Native, the developers have a lot of responsibilities. They do not need to write the code manually, as React Native automatically generates the code for the mobile app development. This is the reason why the developers need to focus more on the UX of the app. There are several UX aspects that are required for a development, such as the native code, the visual aesthetics, the technical and back-end aspects. All these aspects would be added together to design the user interface. This is why the React Native app development becomes quite important. The creation of the native code, design, and other technical aspects make React Native a valuable tool for developers and non-developers. Benefits of React Native React Native helps in building a complete native mobile app without any coding skills. The beautiful library creates responsive and interactive web apps from all the simple mobile web components and thus increases the creation of high-quality applications. React Native is a part of web development in its new form with its development of new concepts in application. It uses the native functionality of an operating system so that all of the advanced concepts of web development can be applied to mobile apps. This makes React Native a preferred platform for apps which are made specifically for Android and iOS. With React Native, the companies can develop a beautiful and efficient app in less time without having to spend too much time. Conclusion As stated in the above results of mobile app development, the UI remains the most important part of a mobile app. All developers are in love with different UI frameworks and libraries. As for this topic, given below are some of the great reasons to select React Native as a UI framework: It’s the only full-stack UI framework from Facebook. More than 20 frameworks have appeared, and React Native is the only one that was born out of Facebook. Features like rendering into the DOM, XHR, Native Embedding, data persistence, offline support and more. Although React Native is more than capable of tackling many challenges, it still falls short of some modern technologies like HOCs and Server-side Rendering (SSR).

Build Emotional Connection With Your Fans | Brand Loyalty The way influencers communicate with fans is continuously evolving. we discuss few ways so that you can keep on top of trends to grow the fanbase, keep fans engaged and engender loyalty in Velvetrope. 1. Offer something interactive to get fans engaged : quizzes, polls, and competitions are great ways to engage fans. There are many ways to build fan engagement such as asking followers for feedback, creating quizzes, polls, and competitions. Velvetrope is the best for this. 2. Create unique video content that appeals to your fans: The next generation of fans is growing up surrounded by digital and social content. Therefore, Influencer needs to work harder to ensure their content is unique, engaging, and stands out amongst the rest. Video content might take the shape of exercise tutorials, “top 10” countdowns, “best moment” sizzles, workout tip videos, player interviews, product and service videos, live streams, fan testimonials, competition announcements, and more. Velvetrope is a CRM application that lets you perform all of the above, as well as publish fresh information and make announcements. You can connect with your Fans easily. Velvetrope makes it easy for you to share your most recent blogs, videos, podcasts, and other special content with your followers. Begin sharing your unique content with your VIPs as soon as possible. Share exclusive content with your fans. Post, Stream, and Share: Everybody Makes Money via Velvetrope. You can create a referral program for your VIPs to share with their friends and VIPs. For your referral program, you can use our AI recommendations or create your own rewards. #engagementwithaudience #fanengagementapp

US military systems, where hardware has always been king and software largely an afterthought. For most military systems, the schedule for hardware updates determines the schedule for software updates. After all, most of the companies building these systems are hardware companies, not software companies. This has created multiyear software development cycles that are doomed to failure. Think of how well your mobile device would work if its software and apps were updated only every several years. That’s how it is for military systems.

The iPhone untethered the internet from the desktop. The energy of the blogosphere was redirected toward faster, mobile mediums. Twitter, Tumblr, and Instagram facilitated the transition to mobile. These sites had learned from Facebook’s streamlined profiles and easy feeds. But they diverged from Facebook’s friend-focused model, favoring an open network that allowed users to “follow” anyone they found interesting. This mirrored the subscriber-based model of YouTube as well as the open architecture of the blogosphere. Instead of trying to re-create real-world friend networks online, this new generation of social apps sought to build an audience of friends and strangers alike. At the same time, they took the lessons of the blog era—chiefly, that anyone could build a following online—and expanded upon them.

Embrace Efficiency, Elevate Flavor: Smart Kitchen Tools for Culinary Adventurers The kitchen, once a realm of necessity, has morphed into a playground of possibility. Gone are the days of clunky appliances and tedious prep work. Enter the age of the smart kitchen tool, a revolution that whispers efficiency and shouts culinary liberation. For the modern gastronome, these tech-infused gadgets are not mere conveniences, but allies in crafting delectable adventures, freeing us to savor the journey as much as the destination. Imagine mornings when your smart coffee maker greets you with the perfect brew, prepped by the whispers of your phone while you dream. Your fridge, stocked like a digital oracle, suggests recipes based on its ever-evolving inventory, and even automatically orders groceries you've run low on. The multi-cooker, your multitasking superhero, whips up a gourmet chili while you conquer emails, and by dinnertime, your smart oven roasts a succulent chicken to golden perfection, its progress monitored remotely as you sip a glass of wine. But efficiency is merely the prologue. Smart kitchen tools unlock a pandora's box of culinary precision. Smart scales, meticulous to the milligram, banish recipe guesswork and ensure perfect balance in every dish. Food processors and blenders, armed with pre-programmed settings and self-cleaning prowess, transform tedious chopping into a mere blip on the culinary radar. And for the aspiring chef, a sous vide machine becomes a magic wand, coaxing impossible tenderness from the toughest cuts of meat. Yet, technology alone is not the recipe for culinary bliss. For those who yearn to paint with flavors, smart kitchen tools are the brushes on their canvas. A connected recipe platform becomes your digital sous chef, guiding you through each step with expert instructions and voice-activated ease. Spice racks, infused with artificial intelligence, suggest unexpected pairings, urging you to venture beyond the familiar. And for the ultimate expression of your inner master chef, a custom knife, forged from heirloom steel and lovingly honed, becomes an extension of your hand, slicing through ingredients with laser focus and lyrical grace. But amidst the symphony of gadgets and apps, let us not forget the heart of the kitchen: the human touch. Smart tools are not meant to replace our intuition but to augment it. They free us from the drudgery, allowing us to focus on the artistry, the love, the joy of creation. Imagine kneading dough, the rhythm of your hands mirroring the gentle whirring of a smart bread machine, then shaping a loaf that holds the warmth of both technology and your own spirit. Or picture yourself plating a dish, using smart portion scales for precision but garnishing with edible flowers chosen simply because they spark joy. This, my friends, is the symphony of the smart kitchen: a harmonious blend of tech and humanity, where efficiency becomes the brushstroke that illuminates the vibrant canvas of culinary passion. Of course, every adventure, even one fueled by smart tools, has its caveats. Interoperability between gadgets can be a tangled web, and data privacy concerns linger like unwanted guests. But these challenges are mere bumps on the culinary road, hurdles to be overcome by informed choices and responsible data management. After all, we wouldn't embark on a mountain trek without checking the weather, would we? So, embrace the smart kitchen, dear foodies! Let technology be your sous chef, your precision tool, your culinary muse. But never forget the magic of your own hands, the wisdom of your palate, and the joy of a meal shared with loved ones. For in the end, it's not about the gadgets, but the memories we create around them, the stories whispered over simmering pots, and the laughter echoing through a kitchen filled with the aroma of possibility.

Apple is losing its grip on the IOS and iPhone ecosystems. One example is the bad experience of IOS killing the background apps, which shows that Apple is not planning and controlling the IOS ecosystem well. Another example is the sudden increase in RAM for different iPhone models, which creates a lot of fragmentation and confusion for developers and users. It also makes the iPhone less efficient and reliable. I remember the days when the iPhone had 1G RAM, and it could keep the app content even after restarting. But those days are gone and it's not over yet.

DEEPENING PRACTICES Here are practices you can do this week to integrate the information in this chapter into your life: Selective Attention Exercise 1: In what areas of your life do you focus on the negative rather than the positive? Write down three positive affirmations about that area of your life. Make 10 copies. Place one in your wallet. Tape others to your refrigerator, bathroom mirror, computer monitor, video screen, car dashboard, and other places you can’t avoid noticing them. Practice repeating the positive affirmations the second you catch yourself focusing on the negative. Journaling Exercise: Write down a list of personality flaws that you’d like to change. Create a reminder in your online calendar for 1 year from now, reminding you to check today’s date in your journal. Next year, you might be surprised to see how much some have shifted after a year of meditation. Emotional Contagion Practice: Put the power of emotional contagion to work for you. Make a list of the happiest people you know, and make a plan to get together with at least four of them in the coming month. Selective Attention Exercise 2: Whenever you hear a bad news story that upsets you, do a web search for contradictory evidence (e.g., “Good news about . . .”). This will put the bad news in context. Field Effects Exercise: Look at the Insight Timer app each day you meditate and notice how many other people are meditating worldwide. It’s usually hundreds of thousands. This reminds you that you are not alone.

Choosing an output as an outcome. Shifting to an outcome mindset is harder than it looks. We spend most of our time talking about outputs. So, it’s not surprising that we tend to confuse the two. Even when teams intend to choose an outcome, they often fall into the trap of selecting an output. I see teams set their outcome as “Launch an Android app” instead of “Increase mobile engagement” or “Get to feature parity on the new tech stack” instead of “Transition customer to the new tech stack.” A good place to start is to make sure your outcome represents a number even if you aren’t sure yet how to measure it. But even then, outputs can creep in. I worked with a team that helped students choose university courses who set their outcome as “Increase the number of course reviews on our platform.” When I asked them what the impact of more reviews was, they answered, “More students would see courses with reviews.” That’s not necessarily true. The team could have increased the number of reviews on their platform, but if they all clustered around a small number of courses, or if they were all on courses that students didn’t view, they wouldn’t have an impact. A better outcome is “Increase the number of course views that include reviews.” To shift your outcome from less of an output to more of an outcome, question the impact it will have.

Does It “Really” Need to Be an Email? By this point, you’ve probably figured out that I love email. Well, in spite of my love for email marketing, not every communication needs to be an email. In fact, there are times when emails really aren’t the best solution. So, if not email, what else? Other solutions include: In-App messages like popups, sidebars, site notifications, chat messages, browser or push notifications, desktop notifications, text messages, and even product tours and onboarding flows. Email is great when the user isn’t currently using your product. It’s great to drive them back in, but when they are right there using your product, you can’t expect them to be checking their emails at the same time. Before setting up a new email campaign, ask yourself if email is the best way to achieve your objective and drive the user behavior you seek. Maybe a popup or site notification would be more effective. Users can’t typically unsubscribe from popups, sidebars, site notifications, chat messages, or onboarding flows. They are usually better embedded into your app and more contextual. Because of this, they tend to reach users more directly than email can. That means that they can often be more effective to influence user behaviors. Push notifications, desktop notifications, and text messages still have some novelty to them. They can also reach users in different contexts from email. Although sometimes it’s better to use a different communication type, sometimes combining email with other options is the best way to go. For this reason, it’s important to consider the mix. For example, an email followed on-site by an In-App message, or an onboarding flow followed by an email summing up the process may be more effective than a single email. It will allow you to follow up on user actions, and make it really clear what needs to get done. By breaking down the steps one at a time, there’s more chances for users to learn. At LANDR, we often followed feature launch emails on-site with In-App messages. This helped to keep communications simple and goal-focused (one goal per message). The email was about getting people in the product, while the In-App message was about getting them to engage with the product. This approach allows you to evaluate and optimize each step of the process independently. Automation platforms like Intercom, ActiveCampaign and HubSpot generally allow you to combine messaging types. If your platform doesn’t currently have site messaging or onboarding functionalities, you may have to use multiple tools in conjunction in order to maximize results. This will make it trickier to track pacing, sequencing, and goals but it isn’t impossible. You also need to consider tracking effort when adding new communication types to your mix. As your program becomes more complex, it can be easy to lose track of the overall user experience: Are your users getting spammed? Are you creating a disjointed customer experience? Test things from your users’ perspective. Keep an eye out for social media messages and support requests as you do. In the next chapter we will look at setting up automations to minimize issues and maximize outcomes.

Your now just became the past, and your past just created your new future, so where is this imaginary pit stop called now that you think your meditation app is going to take you to?

The twelve-factor developer resists the urge to use different backing services between development and production, even when adapters theoretically abstract away any differences in backing services. Differences between backing services mean that tiny incompatibilities crop up, causing code that worked and passed tests in development or staging to fail in production. These types of errors create friction that disincentivizes continuous deployment. The cost of this friction and the subsequent dampening of continuous deployment is extremely high when considered in aggregate over the lifetime of an application.

Uber had to get creative to unlock the hard side of their network, the drivers. Initially, Uber’s focus was on black car and limo services, which were licensed and relatively uncontroversial. However, a seismic shift occurred when rival app Sidecar innovated in recruiting unlicensed, normal people as drivers on their platform. This was the “peer-to-peer” model that created millions of new rideshare drivers, and was quickly copied and popularized by Lyft and then Uber. Jahan Khanna, cofounder/chief technology officer of Sidecar, spoke of its origin: It was obvious that letting anyone sign up to be a driver would be a big deal. With more drivers, rides would get cheaper and the wait times would get shorter. This came up in many brainstorms at Sidecar, but the question was always, what was the regulatory framework that allows this to operate? What were the prior examples that weren’t immediately shut down? After doing a ton of research, we came onto a model that had been active for years in San Francisco run by someone named Lynn Breedlove called Homobiles that answered our question.22 It’s a surprising fact, but the earliest version of the rideshare idea came not from an investor-backed startup, but rather from a nonprofit called Homobiles, run by a prominent member of the LGBTQ community in the Bay Area named Lynn Breedlove. The service was aimed at protecting and serving the LGBTQ community while providing them transportation—to conferences, bars and entertainment, and also to get health care—while emphasizing safety and community. Homobiles had built its own niche, and had figured out the basics: Breedlove had recruited, over time, 100 volunteer drivers, who would respond to text messages. Money would be exchanged, but in the form of donations, so that drivers could be compensated for their time. The company had operated for several years, starting in 2010—several years before Uber X—and provided the template for what would become a $100 billion+ gross revenue industry. Sidecar learned from Homobiles, implementing their offering nearly verbatim, albeit in digital form: donations based, where the rider and driver would sit together in the front, like a friend giving you a ride. With that, the rideshare market was kicked off.

Tinder would work with Justin’s younger brother to throw a birthday party for one of his popular, hyperconnected friends on campus, and use it to promote Tinder. The Tinder team would do all the work to make it an incredible party. The day of the party, students from USC were getting bused to a luxurious house in LA, where everything had been set up to pull you inside. Sean described how it worked: There was one catch with the party: First, you had to download the Tinder app to get in. We put a bouncer in the house to check that you had done it. The party was great—it was a success, and more importantly, the next day, everyone at the party woke up and remembered they had a new app on their phone. There were attractive people they hadn’t gotten to talk to, and this was their second chance. The college party launch tactic worked. For the Tinder team, this one party created the highest ever one-day spike of downloads, however modest it might seem in retrospect. It’s not just the number that matters here, but that it was “500 of the right people”—Sean would explain to me later. It was a group of the most social, most hyperconnected people on the USC campus, all on Tinder at the same time. Tinder started to work. Matches began to happen, as the students who met each other from the previous night started to swipe through and then chat. Amazingly, 95 percent of this initial cohort started to use this app every day for three hours a day.

Tinder would work with Justin’s younger brother to throw a birthday party for one of his popular, hyperconnected friends on campus, and use it to promote Tinder. The Tinder team would do all the work to make it an incredible party. The day of the party, students from USC were getting bused to a luxurious house in LA, where everything had been set up to pull you inside. Sean described how it worked: There was one catch with the party: First, you had to download the Tinder app to get in. We put a bouncer in the house to check that you had done it. The party was great—it was a success, and more importantly, the next day, everyone at the party woke up and remembered they had a new app on their phone. There were attractive people they hadn’t gotten to talk to, and this was their second chance. The college party launch tactic worked. For the Tinder team, this one party created the highest ever one-day spike of downloads, however modest it might seem in retrospect. It’s not just the number that matters here, but that it was “500 of the right people”—Sean would explain to me later. It was a group of the most social, most hyperconnected people on the USC campus, all on Tinder at the same time. Tinder started to work. Matches began to happen, as the students who met each other from the previous night started to swipe through and then chat. Amazingly, 95 percent of this initial cohort started to use this app every day for three hours a day. The Tinder team built one atomic network, but soon figured out how to build the next one—just throw another party. And then another, by going to other schools, and throwing even more parties. Each network was successively easier to start. Tinder quickly reached 4,000 downloads, then 15,000 within a month, and then 500,000 just a month after that—first by replicating the campus launch, but then letting the organic viral growth take over.

The Instagram versus Hipstamatic story is perhaps the canonical example of a strategy made famous by Chris Dixon’s 2015 essay “Come for the tool, stay for the network.” Chris writes: A popular strategy for bootstrapping networks is what I like to call “come for the tool, stay for the network.” The idea is to initially attract users with a single-player tool and then, over time, get them to participate in a network. The tool helps get to initial critical mass. The network creates the long term value for users, and defensibility for the company.40 There are many other examples across many sectors beyond photo apps: The Google Suite provides stand-alone tools for people to create documents, spreadsheets, and presentations, but also network features around collaborative editing, and comments. Games like Minecraft or even classics like Street Fighter can be played in single-player mode where you play against the computer, or multiplayer mode where you play with friends. Yelp started out effectively as a directory tool for people to look up local businesses, showing addresses and phone numbers, but the network eventually built out the database of photos and reviews. LinkedIn started as a tool to put your resume online, but encouraged you to build up your professional network over time. “Come for the tool, stay for the network” circumvents the Cold Start Problem and makes it easier to launch into an entire network—with PR, paid marketing, influencers, sales, or any number of tried-and-true channels. It minimizes the size requirement of an atomic network and in turn makes it easy to take on an entire network. Whether it’s photo-sharing apps or restaurant directories, in the framework of the Cold Start Theory, this strategy can be visualized. In effect, a tool can be used to “prop up” the value of the network effects curve when the network is small.

To make these loops actionable for product teams, you can break them down into more granular steps, and A/B test them. For example, Uber’s viral loop for drivers involved a referral program that was exposed during the onboarding process. There were a dozen or so screens on the app that a driver moved through during the sign-up process—entering their phone number creating a password, uploading their driver’s license, etc. Each of these steps could be optimized so that more users would pass through. Then, drivers would be presented with an explanation on how to refer their friends, and what type of bonus they’d get for doing so. This could be improved as well—should the message offer $100 to sign up, or $300? If you invite five people should you get a bonus? Should an invite mention the name of the inviter, or just focus on Uber, as an app? On the sign-up page, should you ask for a driver’s email or their phone number, or both? A product team can brainstorm hundreds of these ideas and systematically try them, measuring for conversion rates and the number of invites sent. Optimizing each of these steps with A/B tests might only boost each step’s conversion by 5 percent here or 10 percent there, but it’s a compounding effect. Hundreds of A/B tests later, the millions of dollars you might be spending on acquiring customers is made substantially more efficient.

Measuring the Acquisition Network Effect To increase the Acquisition Effect, you have to be able to directly measure it. The good news is that viral growth can be rolled up into one number. Here’s how you calculate it: Let’s say you’ve built a new productivity tool for sharing notes, and after it launches, 1,000 users download the new app. A percentage of these users invite their colleagues and friends, and over the next month, 500 users download and sign up—what happens next? Well, those 500 users then invite their friends, and get 250 to sign up, who create another 125 sign-ups, and so on. Pay attention to the ratios between each set of users—1000 to 500 to 250. This ratio is often called the viral factor, and in this case can be calculated at 0.5, because each cohort of users generates 0.5 of the next cohort. In this example, things are looking good—starting with 1,000 users with a viral factor of 0.5 leads to a total of 2,000 users by the end of the amplification—meaning an amplification rate of 2x. A higher ratio is better, since it means each cohort is more efficiently bringing on the next batch of users.

It’s not just workplace collaboration tools that have higher conversion rates, it’s also networked products like marketplaces and app stores—though for different reasons. When more sellers are part of a marketplace, there’s more selection, availability, and comprehensive reviews/ratings—meaning people are more likely to find what they want, and each session is more likely to convert into a purchase. Social platforms often monetize users by providing social status, but status has value when there’s more people in a network. For example, on Tinder, users can send a “Super Like,” which lets a potential match know that you really like them. A feature like this is most useful once there’s a rich network of potential suitors and matches, giving users more of a reason to try to stand out. Same with virtual goods in multiplayer games like Fortnite, which has generated hundreds of millions in revenue on “emotes”—the virtual dances that differentiate a player. This only holds value if many of your friends play and appreciate the premium emotes you’ve purchased. As a result, a more developed network creates an incentive for people to invest in their standing within the game—this is the Economic Effect at work.

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The key to investing is not assessing how much an industry is going to affect society, or how much it will grow, but rather determining the competitive advantage of any given company and, above all, the durability of that advantage. The products or services that have wide, sustainable moats around them are the ones that deliver rewards to investors.84 Because Buffett generally invests in low-tech companies like See’s Candies or Coca-Cola, the moat he refers to is often a strong brand or a unique business model. For software products with network effects, a strong moat means something different: how much effort, time, and capital does it take to replicate a product’s features and its network? In the modern era, cloning software features is usually not the hard part—replicating the complete functionality of a Slack or Airbnb might take time, but it is tractable. It’s the difficulty of cloning their network that makes these types of products highly defensible. I’ll use an example to think through the competitive moat. Let’s start from first principles, with an example of Airbnb trying to launch in a new city with no competitors in sight. As the early Airbnb team described, the Cold Start Problem lies in the difficulty of launching a new city to a Tipping Point of over 300 listings with 100 reviews. This requires real effort, because the minimum network size is quite large—contrasted to many other network types like communication apps, which might only require two or three people to get started. But once Airbnb has reached Escape Velocity in a market, the Cold Start Problem creates the defense against new entrants.

Your Competition Has Network Effects, Too To figure out a response, it’s important to acknowledge a common myth about defensibility and moats: that somehow, network effects will magically help you fend off competition. This is a myth repeated again and again in startup pitch presentations to investors and entrepreneurs. It’s a lie that entrepreneurs tell to themselves. It isn’t true—simply having network effects is not enough, because if your product has them, it’s likely that your competitors have them, too. Whether you are a marketplace, social network, workplace collaboration tool, or app store, you are in a “networked category.” It’s intrinsic in these categories that every player is a multi-sided network that connects people, and is governed under the dynamics of Cold Start Theory. Effective competitive strategy is about who scales and leverages their network effects in the best way possible. No wonder we often see smaller players upend larger ones, in an apparent violation of Metcalfe’s Law. If every product in a category can rely on their network, then it’s not about who’s initially the largest. Instead, the question is, who is doing the best job amplifying and scaling their Acquisition, Engagement, and Economic effects. It’s what we see repeatedly over time: MySpace was the biggest social network in the mid-2000s and lost to Facebook, then a smaller, newer entrant with a focus on college networks with stronger product execution. HipChat was ahead in workplace communication, but was upended by Slack. Grubhub created a successful, profitable multibillion-dollar food-ordering company, but has rapidly lost ground to Uber Eats and DoorDash.

A well-organized revolt by the major members of its hard side can kill a product entirely. Twitter once bought an app called Vine for a reported $30 million. It let users create and view six-second looping video clips—it was ahead of its time, and not dissimilar from the insights behind TikTok. Like many social apps, the most popular content creators became very successful, and they were important to attract an audience. Unfortunately, a few years in, more than a dozen of the top content creators organized a revolt: Led by creators Marcus Johns and Piques, the group pitched an idea: If Vine paid each star $1.2 million and changed certain features of the app, each creator would post 12 Vines per month. Otherwise, all 18 would leave the platform. “We were driving billions of views—billions—before we left,” DeStorm Power explained of the monetary request.69 Vine turned down the plan, and a few years later, the service was shuttered. The hard side is worth the effort to cultivate. The most successful and prolific members of this side of the network also provide the highest level of service, are willing to make the investments to scale their impact, and ultimately become the defensible backbone of the network—assuming they can be retained. In Uber’s case, the power drivers represented the top 15 percent of drivers but constituted over 40 percent of our trips. They were also among the safest and most highly rated drivers—after all, it was their primary source of income.

Over the years, Facebook has executed an effective playbook that does exactly this, at scale. Take Instagram as an example—in the early days, the core product tapped into Facebook’s network by making it easy to share photos from one product to the other. This creates a viral loop that drives new users, but engagement, too, when likes and comments appear on both services. Being able to sign up to Instagram using your Facebook account also increases conversion rate, which creates a frictionless experience while simultaneously setting up integrations later in the experience. A direct approach to tying together the networks relies on using the very established social graph of Facebook to create more engagement. Bangaly Kaba, formerly head of growth at Instagram, describes how Instagram built off the network of its larger parent: Tapping into Facebook’s social graph became very powerful when we realized that following your real friends and having an audience of real friends was the most important factor for long-term retention. Facebook has a very rich social graph with not only address books but also years of friend interaction data. Using that info supercharged our ability to recommend the most relevant, real-life friends within the Instagram app in a way we couldn’t before, which boosted retention in a big way. The previous theory had been that getting users to follow celebrities and influencers was the most impactful action, but this was much better—the influencers rarely followed back and engaged with a new user’s content. Your friends would do that, bringing you back to the app, and we wouldn’t have been able to create this feature without Facebook’s network. Rather than using Facebook only as a source of new users, Instagram was able to use its larger parent to build stronger, denser networks. This is the foundation for stronger network effects. Instagram is a great example of bundling done well, and why a networked product that launches another networked product is at a huge advantage. The goal is to compete not just on features or product, but to always be the “big guy” in a competitive situation—to bring your bigger network as a competitive weapon, which in turn unlocks benefits for acquisition, engagement, and monetization. Going back to Microsoft, part of their competitive magic came when they could bring their entire ecosystem—developers, customers, PC makers, and others—to compete at multiple levels, not just on building more features. And the most important part of this ecosystem was the developers.

In this respect, creating is much like visiting the gym. You may desire to be fit and muscular, but the only way to make that happen is to keep showing up, day after day, and building on the previous days’ progress. You may never develop the “perfect” physique—just like you may never paint the perfect painting or build the perfect smartphone app—but your personal best will continue to get better as you put in the hours.

Going forward, Google will instead focus on a no-code platform called AppSheet, which allows those with no coding skills to create their apps.

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Your devices are very powerful in their ability to help you create, but they can also become sources of distraction and wasted time. During your creative time, turn off notifications and close apps and windows that are not essential to your creative work. Advertisers and other companies want you to pay attention to their creative ideas — instead, cultivate the ability to resist them and redirect your attention to monotasking your creative ideas.