two-pizza team

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Working Backwards: Insights, Stories, and Secrets From Inside Amazon by Colin Bryar, Bill Carr

Amazon Web Services, barriers to entry, Big Tech, Black Lives Matter, business logic, business process, cloud computing, coronavirus, COVID-19, data science, delayed gratification, en.wikipedia.org, fulfillment center, iterative process, Jeff Bezos, late fees, loose coupling, microservices, Minecraft, performance metric, search inside the book, shareholder value, Silicon Valley, six sigma, Steve Jobs, subscription business, Toyota Production System, two-pizza team, web application, why are manhole covers round?

We learned as we went, adapting and refining the idea of two-pizza teams until, in the end, we had something far more capable. What was originally known as a two-pizza team leader (2PTL) evolved into what is now known as a single-threaded leader (STL). The STL extends the basic model of separable teams to deliver their key benefits at any scale the project demands. Today, despite their initial success, few people at Amazon still talk about two-pizza teams. We say that the STL is bigger and better, but better than what? Certainly it’s an improvement on the two-pizza team it evolved from, but is it better than other alternatives too?

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Rick solicited ideas from people throughout the company and synthesized them, then came back with a clearly defined model that people would talk about for years to come: the two-pizza team, so named because the teams would be no larger than the number of people that could be adequately fed by two large pizzas. With hundreds of these two-pizza teams eventually in place, Rick believed that we would innovate at a dazzling pace. The experiment would begin in the product development organization and, if it worked, would spread throughout the rest of the company. He laid out the defining characteristics, workflow, and management as follows. A two-pizza team will: Be small. No more than ten people. Be autonomous.

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The Order Pipeline and Payments teams, for example, had to be involved in almost every new initiative, even though it wasn’t in their original charters. Some Challenges Still Remained Two-pizza teams were a much-talked-about topic at Amazon, but as originally defined, they didn’t spread throughout the company as completely as some other new ideas had. While they showed great potential to improve the way Amazon worked, they also exhibited some shortcomings that limited their success and broader applicability. Two-Pizza Teams Worked Best in Product Development We weren’t sure how far to take the two-pizza team concept, and at the beginning it was planned solely as a reorganization of product development.

Making Work Visible: Exposing Time Theft to Optimize Workflow by Dominica Degrandis, Tonianne Demaria

cloud computing, cognitive bias, cognitive load, DevOps, Elon Musk, en.wikipedia.org, informal economy, Jeff Bezos, Kanban, loose coupling, microservices, Parkinson's law, Sheryl Sandberg, sunk-cost fallacy, systems thinking, TED Talk, transaction costs, two-pizza team

People aren’t available when you need them. A change in one part of the code/outline/plan unexpectedly changes something else. When the local pizza company delivers more than two pizzas to the same meeting room, pay attention. A two-pizza team is a team that can be fed with just two pizzas—about five to seven people depending on the size of the appetite. If three two-pizza teams need to have a joint meeting to discuss their dependencies on each other, then you have high coordination costs. Fifteen to twenty-one people bantering their point of view can consume a lot of time. When was the last time fifteen people agreed on anything?

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When one team breaks another team’s functionality by creating incompatible changes, the impacts can be destructive, as mentioned in the opening of this section about my friend’s $23 billion company. When we attempt to increase the performance of individual teams by breaking them down into smaller groups, hidden dangers await if there are unknown dependencies. Cross team communication is hard. When a bunch of two-pizza teams with lots of dependencies between them spend a lot of time coordinating to avoid stepping on each other’s code (due to the merging of the different teams’ code branches), the benefit of the small team diminishes. Smaller teams can increase integration costs. We like small teams because they can move fast.

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—Troy Magennis 2.3 EXPOSE DEPENDENCIES San Francisco, 2012 A large organization launches their third Agile transformation. A new team of consultants arrives to assess the situation. The new Agile teams are organized into subteams of five to nine people. Pizza is frequently delivered to these teams. (Remember the pizza problem from Section 1.2?) They had heard about the success Google had with two-pizza teams, and so this large organization decided it would work for them too. Many stories impacted other teams. They called these stories “away” stories because you had to go away to another team to solve the problem. Away stories impacted approximately 92% of the teams. Lots of people seemed to be away, well, a lot.

Team Topologies: Organizing Business and Technology Teams for Fast Flow by Matthew Skelton, Manuel Pais

anti-pattern, business logic, business process, call centre, cognitive load, continuous integration, Conway's law, database schema, DevOps, different worldview, Dunbar number, holacracy, information security, Infrastructure as a Service, Internet of things, Jeff Bezos, Kanban, Kickstarter, knowledge worker, Kubernetes, Lean Startup, loose coupling, meta-analysis, microservices, Norbert Wiener, operational security, platform as a service, pull request, remote working, systems thinking, two-pizza team, web application

LeadingAgile (blog), February 5, 2014. https://www.leadingagile.com/2014/02/structure-agile-enterprise/. Coutu, Diane. “Why Teams Don’t Work.” Harvard Business Review, May 1, 2009. https://hbr.org/2009/05/why-teams-dont-work. Crawford, Jason. “Amazon’s ‘Two-Pizza Teams’: The Ultimate Divisional Organization.” JasonCrawford.org (blog), July 30, 2013. http://blog.jasoncrawford.org/two-pizza-teams. Cunningham, Ward. “Understand the High Cost of Technical Debt by Ward Cunningham— DZone Agile.” Dzone.com, August 24, 2013. https://dzone.com/articles/understand-high-cost-technical. Cusumano, Michael A. Microsoft Secrets: How the World’s Most Powerful Software Company Creates Technology, Shapes Markets and Manages People, 1st Touchstone edition.

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Interestingly, there is an exception for testing, as software development engineers in testing (SDETs) work across the whole organization, looking to promote good testing practices and tools across teams (but each team has the day-to-day testing role embedded). They also ensure a smooth cross-service, cross-device, cross-geography user experience. The SDET role provides the kind of valuable input provided by people in a productivity or tooling team, facilitating and encouraging good practices across teams. The Amazon two-pizza-team model is an example of stream-aligned teams: the teams are substantially independent, have ownership over their services, and have responsibility for the runtime success of the software they write. The fact that Amazon has been using this model for over seventeen years shows how effective it can be to align teams to independent streams of change.

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Cohn, “Nine Questions to Assess Scrum Team Structure.” 16. Kniberg, “Real-Life Agile Scaling.” Chapter 3 1. Driskell and Salas, “Collective Behavior and Team Performance,” 277–288. 2. McChrystal et al., Team of Teams, 94. 3. Rozovsky, “Re:Work—The Five Keys to a Successful Google Team.” 4. Crawford, At opening quotes. “Amazon’s ‘Two-Pizza Teams.’” 5. Dunbar, “Neocortex Size as a Constraint on Group Size in Primates,” 469–493. 6. Snowden, “The Rule of 5, 15 & 150;” Dunbar, How Many Friends Does One Person Need?; Bennett, “The Dunbar Number, From the Guru of Social Networks;” Burgess, Thinking in Promises, 87. 7. Snowden, “The Rule of 5, 15 & 150;” Karlgaard and Malone, Team Genius, 201–205. 8.

The Everything Store: Jeff Bezos and the Age of Amazon by Brad Stone

airport security, Amazon Mechanical Turk, Amazon Web Services, AOL-Time Warner, Apollo 11, bank run, Bear Stearns, Bernie Madoff, big-box store, Black Swan, book scanning, Brewster Kahle, buy and hold, call centre, centre right, Chuck Templeton: OpenTable:, Clayton Christensen, cloud computing, collapse of Lehman Brothers, crowdsourcing, cuban missile crisis, Danny Hillis, deal flow, Douglas Hofstadter, drop ship, Elon Musk, facts on the ground, fulfillment center, game design, housing crisis, invention of movable type, inventory management, James Dyson, Jeff Bezos, John Markoff, junk bonds, Kevin Kelly, Kiva Systems, Kodak vs Instagram, Larry Ellison, late fees, loose coupling, low skilled workers, Maui Hawaii, Menlo Park, Neal Stephenson, Network effects, new economy, off-the-grid, optical character recognition, PalmPilot, pets.com, Ponzi scheme, proprietary trading, quantitative hedge fund, reality distortion field, recommendation engine, Renaissance Technologies, RFID, Rodney Brooks, search inside the book, shareholder value, Silicon Valley, Silicon Valley startup, six sigma, skunkworks, Skype, SoftBank, statistical arbitrage, Steve Ballmer, Steve Jobs, Steven Levy, Stewart Brand, the long tail, Thomas L Friedman, Tony Hsieh, two-pizza team, Virgin Galactic, Whole Earth Catalog, why are manhole covers round?, zero-sum game

Freed from the constraints of intracompany communication, Bezos hoped, these loosely coupled teams could move faster and get features to customers quicker. There were some head-scratching aspects to Bezos’s two-pizza-team concept. Each group was required to propose its own “fitness function”—a linear equation that it could use to measure its own impact without ambiguity. For example, a two-pizza team in charge of sending advertising e-mails to customers might choose for its fitness function the rate at which these messages were opened multiplied by the average order size those e-mails generated. A group writing software code for the fulfillment centers might home in on decreasing the cost of shipping each type of product and reducing the time that elapsed between a customer’s making a purchase and the item leaving the FC in a truck.

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(In this respect, Microsoft’s Bill Gates, who also took such annual think weeks, served as a positive example.) Returning to the company after a few weeks, Bezos presented his next big idea to the S Team in the basement of his Medina, Washington, home. The entire company, he said, would restructure itself around what he called “two-pizza teams.” Employees would be organized into autonomous groups of fewer than ten people—small enough that, when working late, the team members could be fed with two pizza pies. These teams would be independently set loose on Amazon’s biggest problems. They would likely compete with one another for resources and sometimes duplicate their efforts, replicating the Darwinian realities of surviving in nature.

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It would be his way of guiding a team’s evolution. Bezos was applying a kind of chaos theory to management, acknowledging the complexity of his organization by breaking it down to its most basic parts in the hopes that surprising results might emerge. That, at least, was the high-minded goal; the end result was somewhat disappointing. The two-pizza-team concept took root first in engineering, where it was backed by Rick Dalzell, and over the course of several years, it was somewhat inconsistently applied through the rest of the company. There was just no reason to organize some departments, such as legal and finance, in this way. The idea of fitness functions in particular appeared to clash with some fundamental aspects of human nature—it’s uncomfortable to have to set the framework for your own evaluation when you might be judged harshly by the end result.

Amazon Unbound: Jeff Bezos and the Invention of a Global Empire by Brad Stone

activist fund / activist shareholder / activist investor, air freight, Airbnb, Amazon Picking Challenge, Amazon Robotics, Amazon Web Services, autonomous vehicles, Bernie Sanders, big data - Walmart - Pop Tarts, Big Tech, Black Lives Matter, business climate, call centre, carbon footprint, Clayton Christensen, cloud computing, Colonization of Mars, commoditize, company town, computer vision, contact tracing, coronavirus, corporate governance, COVID-19, crowdsourcing, data science, deep learning, disinformation, disintermediation, Donald Trump, Downton Abbey, Elon Musk, fake news, fulfillment center, future of work, gentrification, George Floyd, gigafactory, global pandemic, Greta Thunberg, income inequality, independent contractor, invisible hand, Jeff Bezos, John Markoff, Kiva Systems, Larry Ellison, lockdown, Mahatma Gandhi, Mark Zuckerberg, Masayoshi Son, mass immigration, minimum viable product, move fast and break things, Neal Stephenson, NSO Group, Paris climate accords, Peter Thiel, Ponzi scheme, Potemkin village, private spaceflight, quantitative hedge fund, remote working, rent stabilization, RFID, Robert Bork, Ronald Reagan, search inside the book, Sheryl Sandberg, Silicon Valley, Silicon Valley startup, Snapchat, social distancing, SoftBank, SpaceX Starlink, speech recognition, Steve Ballmer, Steve Jobs, Steven Levy, tech billionaire, tech bro, techlash, TED Talk, Tim Cook: Apple, Tony Hsieh, too big to fail, Tragedy of the Commons, two-pizza team, Uber for X, union organizing, warehouse robotics, WeWork

The act of business building at Amazon was an editorial process, with papers subject to numerous revisions, debate over the meaning of individual words, and meticulous consideration by company leaders, most of all from Bezos himself. Meanwhile, working groups inside Amazon were broken into small versatile units, called two-pizza teams (because they were small enough to be fed with two pizzas), and were ordered to move quickly, often in competition with one another. This unusual and decentralized corporate culture hammered into employees that there was no trade-off between speed and accuracy. They were supposed to move fast and never break things.

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George also instituted a dramatic change in the Alexa group’s structure. It had been a functional organization, with centralized engineering, product management, and marketing teams. But that wasn’t growing smoothly or fast enough for Bezos’s liking. George instead reorganized Alexa around the Amazonian ideal of fast-moving “two pizza” teams, each devoted to a specific Alexa domain, like music, weather, lighting, thermostats, video devices, and so on. Each team was run by a so-called “single-threaded leader” who had ultimate control and absolute accountability over their success or failure. (The phrase comes from computer science terminology; a single-threaded program executes one command at a time.)

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To yoke them all together, George oversaw the creation of a “north star” document, to crystalize the strategy of a global, voice-enabled computing platform. Meanwhile Bezos approved all these changes and stayed intimately involved, attending product reviews and reading the Friday night compilation of updates from all the various two-pizza teams, and responding with detailed questions or problems that the groups would then have to fix over the weekend. Alexa execs, like leaders elsewhere in Amazon, became frequent recipients of the CEO’s escalation emails, in which he forwarded a customer complaint accompanied by a single question mark and then expected a response within twenty-four hours.

Ask Your Developer: How to Harness the Power of Software Developers and Win in the 21st Century by Jeff Lawson

Airbnb, AltaVista, Amazon Web Services, barriers to entry, big data - Walmart - Pop Tarts, Big Tech, big-box store, bitcoin, business process, call centre, Chuck Templeton: OpenTable:, cloud computing, coronavirus, COVID-19, create, read, update, delete, cryptocurrency, data science, David Heinemeier Hansson, deep learning, DevOps, Elon Musk, financial independence, global pandemic, global supply chain, Hacker News, Internet of things, Jeff Bezos, Kanban, Lean Startup, loose coupling, Lyft, Marc Andreessen, Marc Benioff, Mark Zuckerberg, microservices, minimum viable product, Mitch Kapor, move fast and break things, Paul Graham, peer-to-peer, ride hailing / ride sharing, risk tolerance, Ruby on Rails, Salesforce, side project, Silicon Valley, Silicon Valley startup, Skype, social distancing, software as a service, software is eating the world, sorting algorithm, Startup school, Steve Ballmer, Steve Jobs, Telecommunications Act of 1996, Toyota Production System, transaction costs, transfer pricing, two-pizza team, Uber and Lyft, uber lyft, ubercab, web application, Y Combinator

It all starts with small teams. In 2000 Amazon had a giant monolithic mess of engineers and code powering the fast-growing retail business. Engineers were stepping all over each other, and the coordination energy to get anything done was massive. Things were slowing down, so Bezos wrote the “two-pizza team” memo proposing that they divide the company into small teams in order to move faster. (The idea was that you could feed the whole team with two pizzas.) But they had a problem. How can you organize a company into a bunch of small, independent teams when their work is all intrinsically tied together in the code they write?

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We used to joke that there was a reason S3 was called the simple storage service, while FPS was the flexible payments service. Our product was ultimately too complicated and struggled to launch. But nonetheless, it was an amazing experience. Despite the fact that Amazon seemed to me like a huge company, it felt like a startup. The whole company was divided into small, two-pizza teams, each operating like a tiny startup. There was urgency. There was energy. What we were doing mattered. We were inventing the future—that’s the feeling you want your technical talent to feel. One of the things that struck me at Amazon was how much influence and decision-making ability developers had.

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All of these meetings are recorded, so people can watch later, and the documents become artifacts that can also be referenced later. The “read only” policy represents a big part of the open, learning environment, a way for everyone in the company to learn from others but still have a functioning meeting. The goal is to address one of the shortcomings of the “two-pizza team” approach, which is that when you have a large number of small teams (our product side alone has 150 teams) they all start to run in a thousand different directions and it can be difficult for any single team to know what all the others are doing. But some initiatives require multiple small teams to contribute code.

The Nature of Software Development: Keep It Simple, Make It Valuable, Build It Piece by Piece by Ron Jeffries

Amazon Web Services, anti-pattern, bitcoin, business cycle, business intelligence, business logic, business process, c2.com, call centre, cloud computing, continuous integration, Conway's law, creative destruction, dark matter, data science, database schema, deep learning, DevOps, disinformation, duck typing, en.wikipedia.org, fail fast, fault tolerance, Firefox, Hacker News, industrial robot, information security, Infrastructure as a Service, Internet of things, Jeff Bezos, Kanban, Kubernetes, load shedding, loose coupling, machine readable, Mars Rover, microservices, Minecraft, minimum viable product, MITM: man-in-the-middle, Morris worm, move fast and break things, OSI model, peer-to-peer lending, platform as a service, power law, ransomware, revision control, Ruby on Rails, Schrödinger's Cat, Silicon Valley, six sigma, software is eating the world, source of truth, SQL injection, systems thinking, text mining, time value of money, transaction costs, Turing machine, two-pizza team, web application, zero day

Bring sunscreen and grow mangoes. Team-Scale Autonomy You’re probably familiar with the concept of the two-pizza team. This is Amazon founder and CEO Jeff Bezos’s rule that every team should be sized no bigger than you can feed with two large pizzas. It’s an important but misunderstood concept. It’s not just about having fewer people on a team. That does have its own benefit for communication. A self-sufficient two-pizza team also means each team member has to cover more than one discipline. You can’t have a two-pizza team if you need a dedicated DBA, a front-end developer, an infrastructure guru, a back-end developer, a machine-learning expert, a product manager, a GUI designer, and so on.

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You can’t have a two-pizza team if you need a dedicated DBA, a front-end developer, an infrastructure guru, a back-end developer, a machine-learning expert, a product manager, a GUI designer, and so on. The two-pizza team is about reducing external dependencies. Every dependency is like one of the Lilliputian’s ropes tying Gulliver to the beach. Each dependency thread may be simple to deal with on its own, but a thousand of them will keep you from breaking free. No Coordinated Deployments The price of autonomy is eternal vigilance...or something like that. If you ever find that you need to update both the provider and caller of an service interface at the same time, it’s a warning sign that those services are strongly coupled.

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How high you are on the priority list determines when the DBA will get to your task. The same goes for downstream review and approval processes. Architecture review boards, release management reviews, change control committees, and the People’s Committee for Proper Naming Conventions...each review process adds more and more time. This is why the concept of the two-pizza team is misunderstood. It’s not just about having a handful of coders on a project. It’s really about having a small group that can be self-sufficient and push things all the way through to production. Getting down to this team size requires a lot of tooling and infrastructure support. Specialized hardware like firewalls, load balancers, and SANs must have APIs wrapped around them so each team can manage its own configuration without wreaking havoc on everyone else.

How to Build a Billion Dollar App: Discover the Secrets of the Most Successful Entrepreneurs of Our Time by George Berkowski

Airbnb, Amazon Web Services, Andy Rubin, barriers to entry, Black Swan, business intelligence, call centre, crowdsourcing, deal flow, Dennis Tito, disruptive innovation, Dunbar number, en.wikipedia.org, game design, Google Glasses, Google Hangouts, Google X / Alphabet X, growth hacking, iterative process, Jeff Bezos, Jony Ive, Kickstarter, knowledge worker, Lean Startup, loose coupling, Marc Andreessen, Mark Zuckerberg, Mary Meeker, minimum viable product, MITM: man-in-the-middle, move fast and break things, Network effects, Oculus Rift, Paul Graham, QR code, Ruby on Rails, Salesforce, self-driving car, Sheryl Sandberg, Silicon Valley, Silicon Valley startup, Skype, Snapchat, social graph, SoftBank, software as a service, software is eating the world, Steve Jobs, Steven Levy, subscription business, TechCrunch disrupt, Travis Kalanick, two-pizza team, ubercab, Y Combinator

So, irrespective of your size, I suggest having a number of simple processes in place to be in a position where your company can weather any kind of hiccups – and continue to scale quickly. Two-Pizza Teams and Internal APIs Amazon’s business model is predicated on the thinnest of margins, and as a result the company has been able to innovate in amazing ways that don’t require massive capital investment. The principles therefore apply to startups looking to stay lean. Amazon is undoubtedly one of the most entrepreneurial companies in history. Two reasons Amazon is able to keep its momentum even with 97,000 employees are pizza teams and APIs.1 TWO-PIZZA TEAMS. Jeff Bezos structured Amazon as a decentralised company where small groups can innovate independently and are free from the inherent problems of groupthink.

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Jeff Bezos structured Amazon as a decentralised company where small groups can innovate independently and are free from the inherent problems of groupthink. He introduced the principle of the two-pizza team. If two pizzas can’t feed a team, then the team is too large. That limits a task force to five to seven people, depending on their appetites. INTERNAL APIS. We talked about application programming interfaces (APIs) in Chapter 2. Think of them as clearly documented instructions about how two pieces of software should talk to one another and exchange data. At Amazon, Bezos mandated that every internal product or feature should have an API. This means that it can be more easily shared (and used) by internal product and development teams.

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Index Note: page numbers in bold refer to illustrations, page numbers in italics refer to information contained in tables. 99designs.com 111 500 Startups accelerator 136, 160 Accel Partners 3, 158, 261, 304, 321, 336, 383 accelerators 136, 159–60, 160 accountants 164, 316 accounting software 164 acquisition (of users) costs 148–9, 184, 236–7, 275–9, 282 and Facebook 271, 272, 273–4 for five hundred-million-dollar apps 327, 341–3 for hundred-million-dollar apps 252, 259, 266, 267–74, 275–84, 295–307 and incentive-based networks 270–1 international 295–307 for million dollar apps 136–7, 139, 140–51, 148–9, 153 and mobile social media channels 271–3, 272 and mobile user-acquisition channels 269–70 strategy 222–31 for ten-million-dollar apps 211–12, 213, 222–31, 236–7, 248–9 and traditional channels 268–9 and ‘viral’ growth 225, 278, 279–84 zero-user-acquisition cost 278 acquisitions 414–25 buying sustained growth 417–18 by non-tech corporations 418–20 initial public offerings 420–2 Waze 415–16 activation (user) 136, 137, 139, 153–4, 211–12, 213 Acton, Brian 54, 394 addiction, smartphone 30–1 Adler, Micah 269 administrators 409 AdMob 414–15 advertising 43 business model 67, 89–90 costs 140 and Facebook 271, 272, 273–4 mobile 148–9, 268–70, 272–3, 272 mobile social media 272–3, 272 mobile user-acquisition channels 269–70 outdoor 264 shunning of 42, 54–6 video ads 273 aesthetics 131 after product–market fit (APMF) 180 agencies 195–7, 264, 343 ‘agile coaches’ see scrum masters agile software development 192–3, 299, 315, 357, 377 Ahonen, Tomi 45 ‘aiming high’ 40–1 Airbnb 160, 301 alarm features 48 Albion 111 alerts 293 Alexa.com 146 Alibaba 227 ‘ALT tags’ 147 Amazon 7, 29, 131, 164, 227, 276, 366, 374–5, 401, 406 Amazon Web Services 374 American Express 347 Amobee 149 analytics 134–5, 149, 199, 205, 210, 212, 217–21, 294 and cohort analysis 287–8 Flurry 135, 149, 220 function 217–18 Google Analytics 135, 219–20, 345 limitations 284 Localytics 135, 221 and marketing 263 mistakes involving 218–19 Mixpanel.com tool 135, 217–18, 220–1, 287, 290–1, 345 Andreessen, Marc 180, 418–19 Andreessen Horowitz 72, 80, 180, 321, 383, 385, 418–19 Android (mobile operating system) 6, 23–4, 38, 415 advertising 274 audience size 119 beta testing 202 building apps for 116–22 and international apps 296 in Japan 306 scaling development and engineering 357–8 time spent on 26 and WhatsApp 55 Angel Capital Association 162 angel investors 154, 155–6, 323 AngelList 99, 131, 155, 159, 233 Angry Birds (game) 6, 42, 47, 57–8, 87, 89, 97 and application programming interface 36 delivering delight 207 design 131 funding 321 game in game 348–9 international growth 297–9 platform 117, 118 product extension 356 virality 282 annual offsites 379 annual revenue per user (ARPU) 215, 219, 232, 236 anonymity 43, 56–7 anti-poaching clauses 247 antidilution rights 245 API see application programming interface app descriptions 143 app development billion-dollar app 8, 389–425 CEO advice 406–13 getting acquired 414–25 people 395–405 process 390–1 five-hundred-million-dollar app 325–87 funding 328, 383–7 hiring staff 334–6, 337–40 killer product expansion 350–63 process 326–8 scaling 326, 330–6, 331–2 scaling marketing 341–9 scaling people 364–72, 377–9 scaling process 373–82 scaling product development 357–63 hundred-million-dollar app 251–324 international growth 295–307 process 252–4 product-market fit 255–6 retention of users 286–94 revenue engines 257–66, 275–85 user acquisition 267–74 million-dollar app 81–171 app Version 0.1 123–35 coding 133–4 design 129–33 feedback 127, 134–5 funding 152–60, 161–71, 176, 235–49 identity of the business 106–14 lean companies 115–22 metrics 136–9, 139 process 82–4 startup process 85–105 testing 126–8 user acquisition 140–51 ten-million-dollar app 173–249 growth engine 222–31, 235–49 metrics 211–21 new and improved Version 1.0 198–210 process 174–6 product–market fit 180–97 revenue engine 232–4 venture capital 235–49 app stores 22, 27–8, 33–4 see also Apple App Store; Google Play app-store optimisation (ASO) 142, 225 AppAnnie 205 Apple 19, 20, 31–2, 393 application programming interface 35–6 designers 129 Facetime app 46 iWatch 38–9 profit per employee 402–3 revenue per employee 401 visual voicemail 50 Worldwide Developers Conference (WWDC) 313 see also iPad; iPhone Apple App Store 22, 27, 32–3, 75, 88, 89, 117, 226 finding apps in 140, 141, 142–5 international apps 297–9 making submissions to 152–3 and profit per employee 403 ratings plus comments 204–5 Apple Enterprise Distribution 201–2 application programming interface (API) 35–6, 185, 360, 374 ARPU see annual revenue per user articles of incorporation 169 ASO see app-store optimisation Atari 20 Atomico 3, 261, 321, 383 attribution 227–31 for referrals 230–1 average transaction value (ATV) 214–15, 219, 232, 236, 387 Avis 95 backlinking to yourself 146 ‘bad leavers’ 247 Balsamiq.com 128 Banana Republic 352 bank accounts 164 banking 156–7 Bardin, Noam 43 Barr, Tom 338 Barra, Hugo 120, 306 Baseline Ventures 72 Baudu 226 beauty 131 BeeJiveIM 33 before product–market fit (BPMF) 180 ‘below the fold’ 143 Beluga Linguistics 297 Benchmark 75 benefits 398–400 beta testing 201–4 Betfair 358 Bezos, Jeff 366, 374 Bible apps 45 billion 9–10 Billion-Dollar Club 5 billionaires 9 Bing 226 ‘black-swan’ events 54 BlackBerry 23 Blank, Steve 257 Blogger 41 blood sugar monitoring devices 38 board seats 242, 243–4 board-member election consent 169 Bolt Peters 363 Booking.com 320 Bootstrap 145 Botha, Roelof 76, 77, 80 Box 7, 90, 276, 396–7, 411 brains 10 brainstorming 108 branding 111–13, 143, 263–4 Braun 129 Bregman, Jay xiii, 14–16, 95, 124, 209, 303 bridge loans 323 Brin, Sergey 366 Bring Your Own Infrastructure (BYOI) 17–18 Brougher, Francoise 340 Brown, Donald 44 Brown, Reggie 104–5 Bubble Witch 421 Buffet, Warren 4 build-measure-learn cycle 116 Burbn.com 72–4, 80 business advisors/coaches 103 business analysts 343 business culture 395–8 business goal setting 310–11 business models 67, 83, 87, 88–91, 175, 253, 259, 327, 351–2, 391, 400, 423–4 business success, engines of 183–4, 423–4 Business Wire 150 CAC see Customer Acquisition Cost Cagan, Marty 314 calendars 49 calorie measurement sensors 38 Cambridge Computer Scientists 160 camera feature 48 Camera+ app 48 Candy Crush Saga 6, 47, 87, 89, 131, 278–81, 318, 349, 421–2 card-readers 41–2 cash flow 164 CEOs see Chief Executive Officers CFOs see Chief Financial Officers channels incentive-based networks 270–1 mobile social-media 271–3, 272 mobile user-acquisition 269–70 source attribution 227–31 testing 224–7 traditional 268–9 viral 280–2 charging phones 49–50 Chartboost 149 chauffer hire see Uber app check-ins, location-based 72, 74 Chief Executive Officers (CEOs) 309, 380 advice from 406–13 and the long haul 68 and product centricity 185–6 role 337 Chief Financial Officers (CFOs) 316 Chief Operations Officers (COOs) 309, 326, 337–40, 380 Chief Technology Officers (CTOs) 186–7, 195 Chillingo 298 China 24–5, 146, 226, 306–7 Cisco 402 Clash of Clans (game) 6, 28, 36, 47, 87, 89, 97, 118, 227, 348–9, 398 Clements, Dave 120 Climate Corporation 412, 419 clock features 47 cloud-based software 67, 90 Clover 419 coding 133–4 cofounders 85, 91–105, 188, 191 chemistry 92–3 complementary skills 93 finding 96–9 level of control 94 passion 93–4 red flags 102–3 successful matches 104–5 testing out 100–2 cohort analysis 237, 287–8 Color.com (social photo-sharing) app 113, 255 colour schemes 111 Commodore 20 communication open 412–13 team 194 with users 208–9 Companiesmadesimple.com 163–4 computers 20–1, 29 conferences 97–8, 202, 312–13 confidentiality provisions 244 connectedness 30 ConnectU 105 consumer audience apps 233–4 content, fresh 147 contracts 165–6 convertible loans 163 Cook, Daren 112 cookies 228–9 Coors 348 COOs see Chief Operations Officers Cost Per Acquisition (CPA) 148–9 Cost Per Download (CPD) 148 Costolo, Dick 77–8, 79–80 costs, and user acquisition 148–9, 184, 236–7, 275–9, 282 Crash Bandicoot 33 crawlers 146–7 Cray-1 supercomputer 20 CRM see customer-relationship management CrunchBase 238 CTOs see Chief Technology Officers Customer Acquisition Cost (CAC) 148–9, 184, 236–7, 275–9 customer lifecycle 212–14 customer segments 346–7 customer-centric approach 344 customer-relationship management (CRM) 290–4, 343 customer-support 208–9 Cutright, Alyssa 369 daily active users (DAUs) 142 D’Angelo, Adam 75–6 data 284–5, 345–7 data engineers 284 dating, online 14, 87–8, 101–2, 263 decision making 379–82, 407–8 defining apps 31–4 delegation 407 delight, delivery 205–7 design 82, 129–33, 206–7 responsive 144 designers 132, 189–91, 363, 376 developer meetups 97 developers see engineers/developers development see app development; software development development agencies 196 ‘development sprint’ 192 Devine, Rory 358–9 Digital Sky Technologies 385 directors of finance 316–17 Distimo 205 DLD 97 Doerr, John 164, 310 Doll, Evan 42–3, 105 domain names 109–10 international 146 protection 145–6 Domainnamesoup.com 109 Dorsey, Jack 41, 58, 72, 75–7, 79–80, 104, 112, 215–16, 305, 312, 412–13 ‘double-trigger’ vesting 247 DoubleClick 414 Dow Jones VentureSource 64 down rounds 322–3 downloads, driving 150–1 drag along rights 245 Dribbble.com 132 Dropbox 7, 90, 131, 276 CEO 407, 410–11 funding 160 scaling 336 staff 399 Dunbar, Robin 364–5 Dunbar number 365 e-commerce/marketplace 28–9, 67, 89, 213–14 Chinese 306 Flipboard and 351–2 and revenue engines 232, 233–4, 276 social media generated 271–2 and user retention 288, 289 eBay 7, 28–9, 131, 180, 276 economic models 275 economies of scale 331–2, 331–2 eCourier 15, 95 education 68–9 edX 69 Ek, Daniel 357 Ellis, Sean 182 emails 291–3 emotion effects of smartphones on 29–30, 30 inspiring 223–4 employees see staff employment contracts 246–7 engagement 236, 278, 283 engineering VPs 337, 358–9 engineers/developers 190–1, 194–5, 361–2, 362, 370, 375–7, 405 enterprise 90, 233–4 Entrepreneur First programme 160 entrepreneurs 3–5, 7–8, 65, 262, 393–4, 409, 424 Ericsson 21 Etsy 107, 109, 110, 358 Euclid Analytics 149 Evernote 7, 90, 131, 399 ExactTarget 291 excitement 30 executive assistants 367 Exitround 419 experience 67–8, 264, 397 Fab.com 352 Facebook 7, 10, 26, 32, 48, 76, 226, 394, 422 and acquisition of users 271, 272, 273–4 acquisitions 416–18, 417 agile culture 375 alerts 293 and application programming interface 36 board 180 and business identity 114 and Candy Crush 280–1 Chief Executive Officer 406 cofounders 100–1 and Color 255–6 design 131, 206, 363 Developer Garage 97 driving downloads on 151 and e-commerce decisions 271, 272 and FreeMyApps.com 271 funding 419 and getting your app found 147 and the ‘hacker way’ 375 initial public offering 420–1 and Instagram 29, 51, 76–80, 90, 117 name 110 ‘No-Meeting Wednesday’ 376 product development 187 profit per employee 403 revenue per employee 401 scaling 336 and Snapchat 57 staff 339, 362, 363, 398, 401, 403 and virality 281 WhatsApp purchase 42, 54–6, 416–17, 417 zero-user-acquisition cost 278 and Zynga 279, 281 Facetime app 46 fanatical users 294 feedback 86, 127, 134–5, 182, 192–3, 198–201, 256, 396 loops 204, 211 qualitative 199 quantitative 199 see also analytics Feld, Brad 170, 241 Fenwick and West 168 Fiksu 264, 269–70 finance, VP of 317–18 finding apps 140–8, 148–9 FireEye 90 First Data 419 first impressions 107–10 Fitbit 38 fitness bracelets 38 flat rounds 322–3 Flipboard 6, 29, 42–3, 49, 51, 89–90 and application programming interface 36 Catalogs 351–2 cofounders 105 design 131, 207 funding 164 growth 351–2 platform choice 119 product innovation 351–2 user notifications 292 virality 281 zero-user-acquisition cost 278 Flurry 135, 149, 220 Fontana, Ash 233 Forbes magazine 40 Ford Motors 419 Founder Institute, The 168 founder vesting 166–7, 244 Foursquare 419 France Telecom 13 franchising 354 FreeMyApps.com 270–1 Friedberg, David 412 Froyo (Android mobile software) 7 Fujii, Kiyotaka 304 full service agencies 195–6 functionality 25–6, 45–50, 131 funding 72, 75–6, 84, 87–8, 152–60, 161–71, 179 accelerators 159–60 angel investors 154, 155–6, 323 for billion-dollar apps 391 convertible loans 163 core documents 169–70 for five-hundred-million-dollar apps 328, 383–7 founder vesting 166–7 for hundred-million-dollar apps 254, 258, 316–17, 318–24 incubators 159–60 legal aspects 163–4 and revenue engines 233–4 Series A 234, 238–40, 238, 240, 241, 242–6, 255, 319–21, 385 Series B 238, 241, 253, 260, 284, 319–21, 322, 384 Series C 384 signing a deal 167–8 for ten-million-dollar apps 152–60, 161–71, 176, 235–49 venture capital 72, 75, 156–8, 165–6, 235–49, 261–2, 383–5, 385, 418–19 game in game 348–9 gaming 42, 47, 318, 355 business model 67, 89 and revenue engines 232, 278–9 and user retention 288, 289 see also specific games Gandhi, Sameer 336 Gartner 271 Gates, Bill 4 general managers (GMs) 300–3 Gladwell, Malcolm 424 Glassdoor 361–2 Global Positioning System (GPS) 23 Gmail 72 GMs see general managers goal setting 40–1, 310–11 Goldberg, Dave 397 Goldman Sachs 385 ‘good leavers’ 247 Google 7, 19, 23, 27, 72, 88, 164, 226 acquisitions 43, 414–16, 418 application programming interface 35–6 beta testing 202 Chief Executive Officer 406–8 developer meetups 97 finding your app on 144, 147 Hangouts app 46 meetings 381–2 mission 404, 408–9 and the OKR framework 310 profit per employee 403, 405 revenue per employee 401, 405 scaling 332 and Snapchat 57 and source attribution 228–9 staff 339, 340, 361–2, 366, 401, 403, 404–5, 412 Thank God It’s Friday (TGIF) meetings 311–12 transparency 413 value 78 Waze app purchase 43 and WhatsApp 56 zero-user-acquisition cost 278 see also Android (mobile operating system) Google Ad Mob 149 Google AdSense 149 Google Analytics 135, 219–20, 345 Google Glass 38–9, 405 Google I/O conference 313 Google Maps 33, 35, 414, 416 Google Now 37 Google Play 88, 89, 117, 120, 226 and beta testing 202 finding apps in 141–5 profit per employee 403 ratings plus comments 204–5 Google Reader 72 Google Ventures 384 Google X 405 Google+ and business identity 114 and virality 281 Google.org 339 GPS see Global Positioning System Graham, Paul 184–5, 211 Graphical User Interface (GUI) 20 Greylock 321, 383 Gross, Bill 406–7, 409–10 Groupon 7, 51–2, 227, 344–5, 419 Grove, Andy 310 growth 267, 308–17 buying sustained 417–18 engines 184, 210, 222–31, 259, 265 and five-hundred-million-dollar apps 329–36 and Friday update meetings 311–12 and goal setting 310–11 and hiring staff 308–9, 411–12 and product and development teams 313–14 and staff conferences 312–13 targets 234, 260 see also acquisition (of users); international growth; scaling Growth Hackers 182 GUI see Graphical User Interface hackathons 99 Haig, Patrick 143 Hailo app xiii–xiv, 5, 36, 89, 386 big data 284–5 branding 112–13 cofounders 94–6 customer segments 346–7 customer-support 208–9 design 131, 132, 133, 206–7 development 123–7, 153–4 Friday update meetings 311 funding 162, 242 goal setting 310 growth 296–7, 299, 302–4, 308–11, 313, 315–17, 329–30, 334–6 hiring staff 308–9, 334–6, 338, 366–7 idea for 14–18 international growth 296, 297, 299, 302–4 market research 182 marketing 263, 264, 268, 270, 273, 341, 347–8 meetings 381 metrics 137–9, 216 name 107 organisational culture 396 platform choice 117, 120, 121 premises xiii–xiv, 177–8, 329–30, 371–2, 386 product development 189, 191, 196 retention 293–4 revenue engine 276 scaling development and engineering 357 scaling people 365–7 scaling process 377 team 258 testing 177–8, 201–4 and user emotionality 224 virality 280, 282 Hangouts app 46 Harris Interactive 31 HasOffers 149 Hay Day 47, 97 head of data 342 Heads Up Display (HUD) 38 heart rate measurement devices 37–8 Hed, Niklas 42 hiring staff 308–9, 334–6, 337–40, 365–70 history of apps 31–2 HMS President xiii–xiv, 177–9, 329, 371, 386 HockeyApp 202 HootSuite 151 Houston, Drew 407, 410–11 HP 180, 402 HTC smartphone 121 HUD see Heads Up Display human universals 44–5 Humedica 419 hyperlinks 147 hypertext markup language (HTML) 147 I/O conference 2013 202 IAd mobile advertising platform 149 IBM 20, 402 icons 143 ideas see ‘thinking big’ identity of the business 86 branding 111–13 identity crises 106–14 names 106–11 websites 113–14 image descriptions 147 in Mobi 149 in-app purchases 28 incentive-based networks 270–1 incorporation 163–4, 179 incubators 159–60 Index Ventures 3, 261 initial public offerings (IPOs) 64, 67–9, 78, 80, 246, 420–2 innovation 404–5 Instagram 6, 29, 48, 51, 67, 71–80, 88–90, 114, 117, 226, 278, 340, 417–18 cofounders 73–4 design 131 funding 75–6, 77–8 X-Pro II 75 zero-user-acquisition cost 278 instant messaging 46 Instantdomainsearch.com 109 integrators 410 Intel 310 intellectual property 165–6, 244, 247 international growth 295–307 Angry Birds 297–9 Hailo 296, 297, 299, 302–4 language tools 297 Square 295, 299, 304–6 strings files 296 Uber 299–302 International Space Station 13 Internet bubble 13 investment see funding iOS software (Apple operating system) 7, 23–4, 46, 75, 104 advertising 274 audience size 119 building apps for 116–22 and international apps 296 scaling development and engineering 357–8 time spent on 26 iPad 42–3, 118–20, 351 iPhone 6, 19, 22–3, 32, 38–9, 183, 351 advertising on 274 camera 48 designing apps for 117–18, 120 finding apps with 145 games 42, 47, 58 and Instagram 74–6 in Japan 306 and Square 104, 306 and Uber 301 user spend 117 and WhatsApp app 54–5 iPod 22 IPOs see initial public offerings Isaacson, Walter 32 iTunes app 22, 47, 88, 143 iTunes U app 69 Ive, Jony 129 iZettle 304 Jackson, Eric 40 Jain, Ankit 142 Japan 227, 304–6 Jawbone Up 38 Jelly Bean (Android mobile software) 7 Jobs, Steve 4, 22, 32, 323, 393, 425 journalists 150–1 Jun, Lei 306 Kalanick, Travis 299–300, 384, 422 Kayak 336 Keret, Samuel 43 Keyhole Inc. 414 keywords 143, 146 Kidd, Greg 104 King.com 349, 421–2 see also Candy Crush Saga KISSmetrics 291 KitKat (Android mobile software) 7 Klein Perkins Caulfield Byers (KPCB) 158, 261, 321, 383 Kontagent 135 Koolen, Kees 320, 339 Korea 30 Koum, Jan 42, 54, 55–6, 154, 321, 394, 416 Kreiger, Mike 73–6 language tools 297 Launchrock.com 113–14, 145, 202 Lawee, David 415 lawyers 103, 169, 170, 242 leadership 410–11 see also Chief Executive Officers; managers lean companies 69, 115–22, 154, 257, 320–1 Lee, Bob 340 legalities 163–70, 242–7, 301 letting go 406–7 Levie, Aaron 396–7, 411 Levinson, Art 32 LeWeb 97 Libin, Phil 399 licensing 356 life experience 67–8, 264 lifetime value (LTV) 184, 215, 219, 220–1, 232, 275–7, 279, 291, 342 Line app 46, 226 Lingo24 297 LinkedIn 97, 226, 406, 408–9 links 147 liquidation preference 242, 243, 245 non-participating 245 Livio 419 loans, convertible 163 Localytics 135, 221 locations 69 logos 111–14 LTV see lifetime value luck 412 Luckey, Palmer 39 LVMH 304 Lyons, Carl 263 Maiden 95 makers 375–7 see also designers; engineers/developers managers 189–90, 300–3, 375–7, 405 MapMyFitness 419 market research 115, 127, 182 marketing data 345–7 and Facebook 271, 272, 273–4 and incentive-based networks 270–1 marketing engineering team 344–5 and mobile social media channels 271–3, 272 and mobile user-acquisition channels 269–70 partner marketing 347–8 scaling 341–9 teams 262–6, 337, 342 and traditional channels 268–9 VPs 262–6, 337, 342 marketplace see e-commerce/marketplace MasterCard 347–8 Matrix Partners 283 McClure, Dave 136, 160, 211, 234 McCue, Mike 42–3, 105, 351 McKelvey, Jim 41, 104 ‘me-too’ products 181 Medium 41 Meebo 73 meetings 379–82, 412–13 annual offsite 379 daily check-ins 381 disruptive nature 376–7 Friday update 311–12 meaningful 381–2 monthly strategic 380 quarterly 380 weekly tactical 380 Meetup.com 98–9 Mendelsen, Jason 170 messaging platforms 226 time spent on 46 and user retention 288, 289 metrics 136–9, 139, 211–21 activation 136, 137, 139, 153–4, 211–12, 213 annual revenue per user (ARPU) 215, 219, 232, 236 average transaction value (ATV) 214–15, 219, 232, 236, 387 consensual 215–16 lifetime value (LTV) 184, 215, 219, 220–1, 232, 275–7, 279, 291, 342 and product-market fit 209–10 referral 137, 138, 139, 153, 154, 211–12, 213, 230–1 revenue 137, 138, 139, 154, 211–12, 213, 214–15, 219, 291 transparency regarding 312 see also acquisition (of users); retention (of users) mice 20 Microsoft application programming interface 35–6 revenue per employee 401 Windows 20, 22, 24 Millennial Media 149 minimum viable product (MVP) 123, 153 MirCorp 13–14 mission 261, 404, 408–9 Mitchell, Jason 51 Mitsui Sumitomo Bank 305 Mixpanel.com tool 135, 217–18, 220–1, 287, 290–1, 345 MMS see Multimedia Messaging Service Mobile Almanac 45 Mobile App Tracking 230, 231 mobile technology, rise of 19–39 MoMo app 306 Monsanto 419 moonshots 404–5 Moore, Jonathan 200 MoPub 149 Moqups.com 128 Mosaic 180 Motorola 21 Moz.com 143 Mullins, Jacob 419 Multimedia Messaging Service (MMS) 47 Murphy, Bobby 43, 104–5, 152–3 music player apps 47 MVP see Metrics into Action; minimum viable product names 106–11, 142 NameStation.com 108 Nanigans 273–4 National Venture Capital Association 64 native apps 33–4 NDA see Non Disclosure Agreement negotiation 265 Net Promoter Score (NPS) 206, 209 net-adding users 206 Netflix 400 Netscape 164, 180 New Enterprise Associates 385 New York Times news app 32–3, 256 news and alerts feature 48–9 Nextstop 72 Nguyen, Bill 255–6 NHN 227 Nike Fuelband 38 Nintendo Game Boy 47 Nokia 21, 35–6 Non Disclosure Agreement (NDA) 165 noncompetition/non-solicitation provision 244, 247 notifications 291–4 NPS see Net Promoter Score Oculus VR 39 OKR (‘objectives and key results’) framework 310–11, 380 OmniGraffle 128 open-source software 23, 34–5, 185 OpenCourseWare 68–9 operating systems 20–4 see also Android; iOS software operations VPs 337 org charts 258, 309 organisational culture 395–8 O’Tierney, Tristan 104 outsourcing 194–7 ownership and founder vesting 166–7 and funding 155, 156, 161–3, 318 oxygen saturation measurement devices 37–8 Paananen, Ilkka 118–19, 397–8 Page, Larry 4, 23, 382, 404, 407–8 Palantir 90 Palihapitiya, Chamath 187 Pandora 7, 47, 67, 131, 410 pay-before-you-download model 28 pay-per-download (PPD) 225 Payleven 304 payment systems 7, 33–4, 227, 304, 305 see also Square app PayPal 7, 227, 304, 305 Pepsi 196 Perka 419 perks 398–400 perseverance 67, 394, 410 personal computers (PCs) 29 perspiration measurement devices 38 Pet Rescue Saga 349, 421 Petrov, Alex 369 phablets 7 Pham, Peter 255 PhoneSaber 33 Photoshop 128 PIN technology 305 Pincus, Mark 311 Pinterest app 48, 226 and business identity 114 and e-commerce decisions 271, 272 and getting your app found 147 name 107 and virality 281 Pishevar, Shervin 300 pivoting 73–4 population, global 9–10 portfolio companies 261–2 PowerPoint 128 PPD see pay-per-download preferential return 243 premises 370–2 preparation 412 press kits 148, 150 press releases 150 Preuss, Dom 98 privacy issues 43, 56–7 private vehicle hire see Uber pro-rata rights 242, 243 producers 409 product chunks 360 product development scaling 357–63 scope 199 team building for 188–91 and team location 193–4 and vision 186–8, 191 see also app development; testing product expansion 350–63 product extension 354 product managers 189–90, 405 product-centricity 185–6, 314, 360 product-market fit 9, 180–97, 235–6, 248, 256–7 measurement 209–10, 212, 286–8 profit 267, 320, 342 profit margin 258–9, 318, 321 profit per employee 402–4, 403, 405 profitability 260, 277, 400 Project Loon 405 proms 12 proto.io tool 133 prototype apps 86, 174 app Version 0.1 123–35, 174 new and improved Version 1.0 198–210 rapid-design prototyping 132–3 PRWeb 150 PSP 47 psychological effects of smartphones 29–30, 30 pttrns.com 131 public-relations agencies 343 publicity 150–1, 225, 313 putting metrics into action 138–9 Puzzles and Dragons 47, 131 QlikView 221, 284–5 QQ 307 quality assurance (QA) 190–1, 196 Quora 76 QZone 307 Rabois, Keith 368, 369 Rakuten 227 Rams, Dieter 129 rapid-design prototyping 132–3 ratings plus comments 204–5 Red Bull 223 redemption codes 230 referrals (user) 137, 138, 139, 153, 154, 211–12, 213 attribution for referrals 230–1 referral codes 230 religious apps 45 remuneration 361–2, 362, 363 Renault 13 restated certification 169 retention (of users) 136–9, 153, 154 for five hundred-million-dollar apps 327, 341–3 for hundred-million-dollar apps 286–94, 288–9 measurement 286–8 for ten-million-dollar apps 206, 211–12, 213, 278 revenue 137–8, 139, 154, 211–12, 213, 214–15, 219, 236, 239–40, 267, 291, 331–2, 341–2, 354 revenue engines 184, 210, 232–4, 257–66, 265, 275–85 revenue per employee 400–2, 402, 405 revenue streams 27–9 Ries, Eric, The Lean Startup 115–16 Rockefeller, John D. 9 Rocket Internet 304 Rolando 33 Rosenberg, Jonathan 413 Rovio 58, 97, 118, 297–9, 318, 320–1, 336, 354, 409 see also Angry Birds Rowghani, Ali 77 Rubin, Andy 23 Runa 419 SaaS see software as a service Sacca, Chris 75–6 sacrifice 86–7 Safari Web browser 32 salaries 361–2, 362, 363 sales VPs 337 Salesforce 291 Samsung 23 Galaxy Gear smartwatch 38 smartphones 121 Sandberg, Sheryl 4, 100–1, 339, 397 SAP 304 scaling 259, 308, 312, 323–4, 326, 330–6, 331–2, 384–5 decision making 379–81 international growth 295–307 marketing 341–9 and organisational culture 396–8 people 338–9, 364–72 premature 334–5 process 373–82 product development and engineering 357–63 and product innovation 350–6 reasons for 333–4 skill set for 335–6 Schmidt, Eric 120 scope 199 screenshots 131, 144, 206 scrum masters (‘agile coaches’) 315, 359, 360 search functions 49 organic 141–2, 141, 145 search-engine optimisation (SEO) 142, 145–8, 225 Sedo.com 109 Seed Fund 136 Seedcamp 160 Sega Game Gear 47 segmentation 220, 287, 290, 346–7 self-empowered squads/units 360 SEO see search-engine optimisation Sequoia Capital 76, 77–80, 158, 255, 321, 383, 385 Series A funding 234, 238–40, 238, 240, 241, 242–6, 255, 261, 262, 319–21, 385 Series B funding 238, 241, 253, 260, 319–21, 322, 384 Series C funding 384 Series Seed documents 168 Sesar, Steven 263 sex, smartphone use during 31 Shabtai, Ehud 43 shares 156, 166–8, 244 ‘sharing big’ 51–2, 52 Shinar, Amir 43 Shopzilla 263 Short Message Service (SMS) 21, 46–7 Silicon Valley 71–4, 77, 79, 99, 162, 168, 180, 184, 255, 340, 361, 411, 422 Sina 227 sitemaps 146–7 skills sets complementary 93 diverse 409–10 for scaling 335–6 Skok, David 283 Skype app 7, 46, 111, 200–1, 226, 357, 419 Sleep Cycle app 48 Smartling 297 smartwatches 7, 38–9 SMS see Short Message Service Snapchat app 6, 43, 46, 56–7, 88, 89, 223, 226, 416, 418 cofounders 104–5 design 131 funding 152–3, 307, 320 name 107 platform 117 staff 340 valuations 333 virality 280, 283 zero-user-acquisition cost 278 social magazines 42–3 see also Flipboard social media 48 driving downloads through 151 and getting your app found 147 mobile channels 271–3, 272 and user retention 288, 289 Sofa 363 SoftBank 227 software development agile 192–3, 299, 315, 357, 377 outsourcing 194–5 see also app development software as a service (SaaS) 67, 90, 208, 214, 233, 276–7 Somerset House 329–30, 371 Sony 21, 47 SoundCloud 358 source attribution 227–31 space tourism 13–14 speech-to-text technology 50 speed 20 Spiegel, Evan 43, 56–7, 104–5, 152–3 Spinvox 50 Splunk 90 Spotify app 47, 357–8 SQL 284 Square app 6, 41–2, 58–9, 87, 89, 333, 350 branding 112 Chief Executive Officer 412–13 cofounders 104 design 131, 363 funding 320–1 international growth 295, 299, 304–6 marketing 348 metrics 215–16 name 107, 110 product–market fit 183 revenue engine 276 scaling people 367–8 scaling product innovation 352–3 staff 340, 367–8 transparency 312 virality 282 Square Cash 353 Square Market 353 Square Register 350, 352–3 Square Wallet 348, 350, 353 Squareup.com 144 staff at billion-dollar app scale 395–405, 423 attracting the best 91 benefits 398–400 conferences 312–13 conflict 334, 378 employee agreements 244 employee legals 246–7 employee option pool 244 employee-feedback systems 378 firing 370, 378 hiring 308–9, 334–6, 411–12 induction programmes 370 investment in 360 mistakes 369–70, 411–12 and premises 370–2 profit per employee 402–4, 403 revenue per employee 400–2, 402 reviews 370 scaling people 364–72, 377–9 scrum masters 315, 359, 360 training programmes 370 see also cofounders; specific job roles; teams Staples 419 Starbucks 338, 348 startup weekends 98 startups, technology difficulties of building 63–80 failure 63–5, 73–4 identity 106–14 lean 115–22, 154 process 82–4, 85–105 secrets of success 66–9 step sensors 38 stock markets 420–1 straplines 111 strings files 296 Stripe 160 style 111 subscriptions 90 success, engines of 183–4, 423–4 SumUp 304 Supercell 28, 47, 97, 118–19, 318, 336, 397–8, 401, 403 see also Clash of Clans; Hay Day SurveyMonkey 397 surveys 206, 209 synapses 10 Systrom, Kevin 71–80 tablets 7 Tableau Software 90 Taleb, Nicholas Nassim 54 Tamir, Diana 51 Tap Tap Revolution (game) 42 Target 419 taxation 164 taxi hailing apps see Hailo app TaxiLight 16 team builders 264 team building 188–91 teams 82, 174, 252, 390 complementary people 409–10 for five-hundred-million-dollar apps 326, 342–5, 357–63, 374, 386 growth 313–14, 326, 342–4 for hundred-million-dollar apps 258–61 located in one place 193–4 marketing 262–6, 342–4 marketing engineering 344–5 product development and engineering 357–63 ‘two-pizza’ 374 TechCrunch Disrupt 97, 99 technology conferences 97–8, 202, 312–13 Techstars 159, 160, 168 Tencent 307 Tencent QQ 226 term sheets 168, 169, 170, 243–4 testing 126–8, 177–8, 187–8, 192–3, 199–201 beta 201–4 channels 224–7 text messaging 21 unlimited packages 42 see also Short Message Service ‘thinking big’ 40–59, 82, 85 big problem solutions 41–3 disruptive ideas 53–9 human universals 44–5 sharing big 51–2, 52 smartphones uses 45–50 Thoughtworks 196 time, spent checking smartphones 25–6, 26, 45–50 Tito, Dennis 13 tone of voice 111 top-down approaches 311 traction 233, 252 traffic information apps 43 traffic trackers 146 translation 296–7 transparency 311–12, 412–13 Trilogy 13 Tumblr 110, 226, 399, 418 Twitter 41, 48, 54, 72, 226, 394 acquisitions 418 and application programming interface 36 and Bootstrap 145 and business identity 114 delivering delight 206 and e-commerce decisions 272 and FreeMyApps.com 271 funding 419, 421 and getting your app found 147 initial public offering 421 and Instagram 51, 76–7, 79–80 name 110 and virality 281 ‘two-pizza’ teams 374 Uber 6, 36, 87, 89, 333, 350 and attribution for referrals 231 design 131 funding 320, 384, 422 international growth 295, 299–302 name 107, 110 revenue engine 276 revenue per employee 401 scaling product innovation 355–6 staff 339, 399 user notifications 292 virality 280 Under Armour 419 Union Square Ventures (USV) 3, 158, 242, 261, 262, 288, 321, 323, 377, 383 unique propositions 198 UnitedHealth Group 419 URLs 110 ‘user experience’ (UX) experts 190 user journeys 127–8, 213–14 user notifications 291–4 user stories 193 users 83, 175, 252, 327, 390 activation 136, 137, 139, 153–4, 211–12, 213 annual revenue per user (ARPU) 215, 219, 232, 236 communication with 208–9 definition 137 emotional response of 223–4 fanatical 294 finding apps 140–8 lifetime value (LTV) 184, 215, 219, 220–1, 232, 275–7, 279, 291 metrics 136–9 net-adding of 206 ratings plus comments 204–5 referrals 137, 138, 139, 153, 154, 211–12, 213, 230–1 target 83, 115, 127 wants 180–97 see also acquisition (of users); retention (of users) Usertesting.com 200–1 USV see Union Square Ventures valuations 83, 161–3, 175, 237–8, 238, 253, 318, 319, 322, 327, 333, 391 venture capital 72, 75, 156–8, 165–6, 235–49, 261–2, 383–5, 385, 418–19 Viber app 6, 46, 1341 video calls 46, 47 viral coefficient 282–4 ‘viral’ growth 225, 278, 279–84 Communication virality 281 and cycle time 283–4 incentivised virality 280–1 inherent virality 280 measurement 282–4 social-network virality 281 word-of-mouth virality 281–2 virtual reality 39 vision 261, 393–4, 408–9, 414, 415 voice calls 46–7 voice-over-Internet protocol (VOIP) 46 voicemail 50 Wall Street Journal 43, 55 warranties 246 Waze app 6, 43, 97 acquisition 415–16 design 131 name 107 zero-user-acquisition cost 278 web browsing 49 Web Summit 97 websites 113–14, 144–8 WebTranslateIt (WTI) 297 WeChat app 46, 226, 306 Weibo 48 Weiner, Jeff 408–9 Wellington Partners 4 Weskamp, Marcos 207 Westergren, Tim 410 WhatsApp 6, 42, 46, 54–6, 87, 90, 226, 394 acquisition 42, 54–6, 416, 416–17, 417 cofounders 96 design 131, 144 funding 154, 320–1 platform 117–18 valuations 333 virality 280 White, Emily 340 Williams, Evan 41, 65 Williams, Rich 344 Wilson, Fred 110, 242, 288, 323, 377 Windows (Microsoft) 20–1, 22, 24, 24 Winklevoss twins 105 wireframes 127–8 Woolley, Caspar 15–16, 95, 124, 338 WooMe.com 14, 87–8, 101–2, 263 Workday 90 world population 9–10 Worldwide Developers Conference (WWDC) 313 wowing people 8–9 WTI see WebTranslateIt Xiaomi 306 Y Combinator 159–60, 184–5, 211, 407, 410–11 Yahoo!

One Click: Jeff Bezos and the Rise of Amazon.com by Richard L. Brandt

Amazon Web Services, automated trading system, big-box store, call centre, cloud computing, deal flow, drop ship, Dynabook, Elon Musk, Free Software Foundation, inventory management, Jeff Bezos, Kevin Kelly, Kickstarter, Larry Ellison, Marc Andreessen, new economy, Pershing Square Capital Management, science of happiness, search inside the book, Silicon Valley, Silicon Valley startup, skunkworks, software patent, Steve Jobs, Stewart Brand, Tony Hsieh, two-pizza team, Whole Earth Catalog, Y2K

One former executive recalled that, at an offsite retreat where other managers said the company employees should start communicating more, Bezos stood up and declared, “No, communication is terrible!” He wanted a decentralized, even disorganized company where people could come up with independent ideas rather than subscribe to groupthink. He ruled the company with the “two-pizza team” concept, that dictated any team should be small enough to feed with two pizzas. Empathy is not something that comes to him naturally. When he was ten years old, on a trip with his grandparents, he decided to try and get his grandmother to quit smoking. For that he relied more on his geekiness than on sensitivity to a sore subject.

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See Internet companies DREAM Institute Drugstore.com DVDs, Amazon sale of Dynabook Early adopters E-bay, versus Amazon Auctions E-books agency model and Amazon. see Kindle devices, competitive early readers free future view for Google market, growth of pricing of Edison, Thomas E Ink Corporation Elastic Compute Cloud (EC2) Electronics Ellison, Larry Employees Bezos interaction with compensation and cult of Amazon expansion (1998) firing (2000) hiring practices individualistic “Just Do It” award two-pizza teams Wal-Mart executives, hiring of work environment Endurance (Lansing) E-Niche Equinet Erwise Everybook Express Lane Farsight Financial status cost-cutting decline (2000) first investors growth versus profits strategy investment advisors IPO, Amazon leverage, Bezos approach to losses and debt (1999) pro forma net profit (2002) raising capital, problems of recovery of Amazon revenues in 2010, share price, growth rate stock downgraded valuations of Amazon, initial Web site building, profitability of Fitel, Bezos at Food and grocery items Fortune Frederick, Robert Free Software Foundation Frisbee Frox, Inc.

The Startup Way: Making Entrepreneurship a Fundamental Discipline of Every Enterprise by Eric Ries

activist fund / activist shareholder / activist investor, Affordable Care Act / Obamacare, Airbnb, AOL-Time Warner, autonomous vehicles, barriers to entry, basic income, Ben Horowitz, billion-dollar mistake, Black-Scholes formula, Blitzscaling, call centre, centralized clearinghouse, Clayton Christensen, cognitive dissonance, connected car, corporate governance, DevOps, Elon Musk, en.wikipedia.org, fault tolerance, financial engineering, Frederick Winslow Taylor, global supply chain, Great Leap Forward, hockey-stick growth, index card, Jeff Bezos, Kickstarter, Lean Startup, loss aversion, machine readable, Marc Andreessen, Mark Zuckerberg, means of production, minimum viable product, moral hazard, move fast and break things, obamacare, PalmPilot, peer-to-peer, place-making, rent-seeking, Richard Florida, Sam Altman, Sand Hill Road, scientific management, secular stagnation, shareholder value, Sheryl Sandberg, Silicon Valley, Silicon Valley startup, six sigma, skunkworks, Steve Jobs, TechCrunch disrupt, the scientific method, time value of money, Toyota Production System, two-pizza team, Uber for X, universal basic income, web of trust, Y Combinator

And most employees are dividing their creativity and focus across many different kinds of projects at the same time. A MODERN COMPANY has a new tool in its arsenal: the internal startup, filled with a small number of passionate believers dedicated to one project at a time. Like Amazon’s famous “two-pizza team”—no larger than you can feed with two pizzas—these small teams are able to experiment rapidly and scale their impact. Their ethos: “Think big. Start small. Scale fast.” AN OLD-FASHIONED COMPANY is composed of managers and their subordinates. A MODERN COMPANY is composed of leaders and the entrepreneurs they empower.

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Not only that, such a system delivers not only waste reduction and better morale but the possibility of an extra bonus return. Sometimes by fixing a small problem you stumble on an amazing opportunity. How would a company steeped in the Startup Way resolve the question of the many useless microwave buttons? By now, I hope the answer is clear: put a small “two-pizza team” on the problem and treat them as an internal startup. Have the startup build some minimum viable products and attempt to sell them to customers. One of my manufacturing clients actually did this, taking each MVP to a different local retailer and measuring the differences in both customer interest and conversion rates to real orders.

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Scale fast,” unemployment insurance Taylor, Frederick Winslow, 8.1 Team of Teams (McChrystal) teams attracting members corporate, typical, 3.1, 3.2 cross-functional, 1.1, 6.1, 6.2, p03.1, 10.1, 10.2, 10.3 executive sponsors, 6.1, 7.1, 7.2 focus on, 3.1, nts.1n3 incentivizing island of freedom or sandbox milestones for, 2.1, 5.1 modern company morale, 6.1, 7.1 small versus big, 3.1, p02.1 startup teams, 3.1, 6.1, p03.1 two-pizza team, 1.1, 5.1 Techstars, 2.1, 7.1, 7.2 Telefónica Tomoyama, Shigeki, 1.1, 6.1 Toyota, itr.1, 1.1, 6.1, 11.1 InfoTechnology Center (ITC) Internet-connected car TPS, 1.1, 1.2, 8.1 transformation (organizational), itr.1, itr.2, itr.3, p01.1, 6.1, p03.1, 10.1 beginning of common patterns energy (motivation) for outcomes of Phase One, p02.1, p02.2, 6.1 Phase Two, p02.1, p02.2, 7.1 Phase Three, p02.1, p02.2, 8.1 Phases and Scales, p02.1, 9.1 three questions for unified theory of Twilio, itr.1, 3.1, 4.1, 6.1 Twitter uncertainty, 1.1, 2.1, 7.1, 10.1 unicorn startup, 1.1, 11.1 unified theory of entrepreneurship universal basic income (UBI), 11.1, nts.1n20 USAID, U.S.

WTF?: What's the Future and Why It's Up to Us by Tim O'Reilly

"Friedman doctrine" OR "shareholder theory", 4chan, Affordable Care Act / Obamacare, Airbnb, AlphaGo, Alvin Roth, Amazon Mechanical Turk, Amazon Robotics, Amazon Web Services, AOL-Time Warner, artificial general intelligence, augmented reality, autonomous vehicles, barriers to entry, basic income, behavioural economics, benefit corporation, Bernie Madoff, Bernie Sanders, Bill Joy: nanobots, bitcoin, Blitzscaling, blockchain, book value, Bretton Woods, Brewster Kahle, British Empire, business process, call centre, Capital in the Twenty-First Century by Thomas Piketty, Captain Sullenberger Hudson, carbon tax, Carl Icahn, Chuck Templeton: OpenTable:, Clayton Christensen, clean water, cloud computing, cognitive dissonance, collateralized debt obligation, commoditize, computer vision, congestion pricing, corporate governance, corporate raider, creative destruction, CRISPR, crowdsourcing, Danny Hillis, data acquisition, data science, deep learning, DeepMind, Demis Hassabis, Dennis Ritchie, deskilling, DevOps, Didi Chuxing, digital capitalism, disinformation, do well by doing good, Donald Davies, Donald Trump, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, fake news, Filter Bubble, Firefox, Flash crash, Free Software Foundation, fulfillment center, full employment, future of work, George Akerlof, gig economy, glass ceiling, Glass-Steagall Act, Goodhart's law, Google Glasses, Gordon Gekko, gravity well, greed is good, Greyball, Guido van Rossum, High speed trading, hiring and firing, Home mortgage interest deduction, Hyperloop, income inequality, independent contractor, index fund, informal economy, information asymmetry, Internet Archive, Internet of things, invention of movable type, invisible hand, iterative process, Jaron Lanier, Jeff Bezos, jitney, job automation, job satisfaction, John Bogle, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John Zimmer (Lyft cofounder), Kaizen: continuous improvement, Ken Thompson, Kevin Kelly, Khan Academy, Kickstarter, Kim Stanley Robinson, knowledge worker, Kodak vs Instagram, Lao Tzu, Larry Ellison, Larry Wall, Lean Startup, Leonard Kleinrock, Lyft, machine readable, machine translation, Marc Andreessen, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, McMansion, microbiome, microservices, minimum viable product, mortgage tax deduction, move fast and break things, Network effects, new economy, Nicholas Carr, Nick Bostrom, obamacare, Oculus Rift, OpenAI, OSI model, Overton Window, packet switching, PageRank, pattern recognition, Paul Buchheit, peer-to-peer, peer-to-peer model, Ponzi scheme, post-truth, race to the bottom, Ralph Nader, randomized controlled trial, RFC: Request For Comment, Richard Feynman, Richard Stallman, ride hailing / ride sharing, Robert Gordon, Robert Metcalfe, Ronald Coase, Rutger Bregman, Salesforce, Sam Altman, school choice, Second Machine Age, secular stagnation, self-driving car, SETI@home, shareholder value, Silicon Valley, Silicon Valley startup, skunkworks, Skype, smart contracts, Snapchat, Social Responsibility of Business Is to Increase Its Profits, social web, software as a service, software patent, spectrum auction, speech recognition, Stephen Hawking, Steve Ballmer, Steve Jobs, Steven Levy, Stewart Brand, stock buybacks, strong AI, synthetic biology, TaskRabbit, telepresence, the built environment, the Cathedral and the Bazaar, The future is already here, The Future of Employment, the map is not the territory, The Nature of the Firm, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Thomas Davenport, Tony Fadell, Tragedy of the Commons, transaction costs, transcontinental railway, transportation-network company, Travis Kalanick, trickle-down economics, two-pizza team, Uber and Lyft, Uber for X, uber lyft, ubercab, universal basic income, US Airways Flight 1549, VA Linux, warehouse automation, warehouse robotics, Watson beat the top human players on Jeopardy!, We are the 99%, web application, Whole Earth Catalog, winner-take-all economy, women in the workforce, Y Combinator, yellow journalism, zero-sum game, Zipcar

That being said, it does get across the commitment that is required to make this kind of digital transformation. 113 “externally or internally”: Werner Vogels, “Working Backwards,” All Things Distributed, November 1, 2006, http://www.allthingsdistributed.com/2006/11/working_backwards.html. 114 “we are not always so helpful”: Mark Burgess, Thinking in Promises (Sebastopol, CA: O’Reilly, 2015), 6. 114 “communication is terrible!”: Janet Choi, “The Science Behind Why Jeff Bezos’s Two-Pizza Team Rule Works,” I Done This Blog, September 24, 2014, http://blog.idonethis.com/two-pizza-team/. 115 “both to technology and to the workplace”: Burgess, Thinking in Promises, 1. 116 animated explainer videos: Henrik Kniberg, “Spotify Engineering Culture (Part 1),” Spotify, March 27, 2014, https://labs.spotify.com/2014/03/27/spotify-engineering-culture-part-1/, and “Spotify Engineering Culture (Part 2),” September 20, 2014, https://labs. spotify.com/2014/09/20/spotify-engi neering-culture-part-2/. 116 low-alignment/low-autonomy organization: A still from Spotify’s animated video illustrates this nicely: https://spotifylabs com.files.wordpress.com/2014/03/spotify-engineering-culture-part1.jpeg. 116 “Follow the orders I would have given you”: This is not a verbatim quote, but my recollection from the interview with General Stanley McChrystal and Chris Fussell by Charles Duhigg on March 1, 2016, http://nytconferences.com/NWS _Agenda_2016.pdf.

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In some sense you can see these services as small startups within the walls of a bigger company. Each of these services require a strong focus on who their customers are, regardless whether they are externally or internally.” Work is done by small teams. (Amazon famously describes these as “two-pizza teams,” that is, teams small enough to be fed by two pizzas.) These teams work independently, starting with a high-level description of what they are trying to accomplish. Any project at Amazon is designed via a “working backwards” process. That is, the company, famous for its focus on the customer, starts with a press release that describes what the finished product does and why.

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Because this creates a tight feedback loop between the group and its customers, you can leave the implementation up to the creativity and the skill of the team building each function. Kim explained to me that “writing the press release first is a mechanism to make customer obsession concrete.” As are two-pizza teams producing services with hardened APIs. “Amazon does a better job of creating these kinds of mechanisms for its corporate values than any other company I’ve seen,” Kim added. “And it starts from first principles (values) more than other companies as well.” Music streaming service Spotify is another company exploring the intersection of online service design and organizational design.

Shipping Greatness by Chris Vander Mey

business logic, corporate raider, don't be evil, en.wikipedia.org, fudge factor, Google Chrome, Google Hangouts, Gordon Gekko, Jeff Bezos, Kickstarter, Lean Startup, minimum viable product, performance metric, recommendation engine, Skype, slashdot, sorting algorithm, source of truth, SQL injection, Steve Jobs, Superbowl ad, two-pizza team, web application

I learned (mostly) different lessons there, but repeated the class in hubris. Abashed, I went to Dartmouth, and studied at the Thayer School of Engineering and the Tuck School of Business, earning a master’s of engineering management degree. I left Dartmouth and joined Amazon, where I was a technical product program manager and an engineering manager (a.k.a. two-pizza team leader). On projects like customer reviews, identity, and fraud-fighting infrastructure, I saw how Jeff Bezos and his lieutenants worked and learned to mimic how some of the best in the business did the job. I eventually went to Google, and as a senior product manager I spent over five years focusing on scalability, business strategy, and the interpersonal dynamics inherent in software teams.

API Marketplace Engineering: Design, Build, and Run a Platform for External Developers by Rennay Dorasamy

Airbnb, Amazon Web Services, barriers to entry, business logic, business process, butterfly effect, continuous integration, DevOps, digital divide, disintermediation, fault tolerance, if you build it, they will come, information security, Infrastructure as a Service, Internet of things, Jeff Bezos, Kanban, Kubernetes, Lyft, market fragmentation, microservices, minimum viable product, MITM: man-in-the-middle, mobile money, optical character recognition, platform as a service, pull request, ride hailing / ride sharing, speech recognition, the payments system, transaction costs, two-pizza team, Uber and Lyft, uber lyft, underbanked, web application

Squads Over the lifetime of our Marketplace, there have been larger initiatives which did not fit into this rapid delivery mold. Initial attempts to bundle these initiatives resulted in a team size of close to 30. As a result, sprint ceremonies such as planning, standup, and retrospectives took a significant amount of time and were an inefficient use of the team’s valuable time. Taking inspiration from Amazon’s “two-pizza team” rule, which states that teams should be no larger than can be fed by two pizzas, we split the team into squads. The definition of a squad is a self-organized, cross-functional team that has skills to deliver a product end-to-end, with limited input from others. The squad should be composed of people that can design, develop, test, and deploy the product.

Monolith to Microservices: Evolutionary Patterns to Transform Your Monolith by Sam Newman

Airbnb, business logic, business process, continuous integration, Conway's law, database schema, DevOps, fail fast, fault tolerance, ghettoisation, inventory management, Jeff Bezos, Kubernetes, loose coupling, microservices, MVC pattern, price anchoring, pull request, single page application, single source of truth, software as a service, source of truth, sunk-cost fallacy, systems thinking, telepresence, two-pizza team, work culture

Now chairman of the company, John Timpson was famous for scrapping internal rules and replacing them with just two: Look the part and put the money in the till. You can do anything else to best serve customers. Autonomy works at the smaller scale too, and most modern organizations I work with are looking to create more autonomous teams within their organizations, often trying to copy models from other organizations like Amazon’s two-pizza team model, or the Spotify model.1 If done right, team autonomy can empower people, help them step up and grow, and get the job done faster. When teams own microservices, and have full control over those services, they increase the amount of autonomy they can have within a larger organization. How else could you do this?

The Connected Company by Dave Gray, Thomas Vander Wal

A Pattern Language, Alan Greenspan, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, Atul Gawande, Berlin Wall, business cycle, business process, call centre, Clayton Christensen, commoditize, complexity theory, creative destruction, David Heinemeier Hansson, digital rights, disruptive innovation, en.wikipedia.org, factory automation, folksonomy, Googley, index card, industrial cluster, interchangeable parts, inventory management, Jeff Bezos, John Markoff, Kevin Kelly, loose coupling, low cost airline, market design, minimum viable product, more computing power than Apollo, power law, profit maximization, Richard Florida, Ruby on Rails, Salesforce, scientific management, self-driving car, shareholder value, side project, Silicon Valley, skunkworks, software as a service, South of Market, San Francisco, Steve Jobs, Steven Levy, Stewart Brand, subscription business, systems thinking, tacit knowledge, The Wealth of Nations by Adam Smith, Tony Hsieh, Toyota Production System, two-pizza team, Vanguard fund, web application, WikiLeaks, work culture , Zipcar

Says Amazon CTO Werner Vogels: The Statistically-Improbable Phrases service…turns out to be a mechanism that brings very remarkable collections together…Remember that most of our developers are in the loop with customers, so they have a rather good understanding about what our customers like, what they do not like, and what is still missing. Teams are limited in size to about 8–10 people. At Amazon, they call them two-pizza teams: if you can’t feed a team with two pizzas, it’s too large. What keeps the teams close to customers? Three things: Each team has a fitness function—a number they are focusing on—and organizes its work in any way it pleases to improve that number. Such data is critical for organizing autonomous pods.

Bezonomics: How Amazon Is Changing Our Lives and What the World's Best Companies Are Learning From It by Brian Dumaine

activist fund / activist shareholder / activist investor, AI winter, Airbnb, Amazon Robotics, Amazon Web Services, Atul Gawande, autonomous vehicles, basic income, Bernie Sanders, Big Tech, Black Swan, call centre, Cambridge Analytica, carbon tax, Carl Icahn, Chris Urmson, cloud computing, corporate raider, creative destruction, Danny Hillis, data science, deep learning, Donald Trump, Elon Musk, Erik Brynjolfsson, Fairchild Semiconductor, fake news, fulfillment center, future of work, gig economy, Glass-Steagall Act, Google Glasses, Google X / Alphabet X, income inequality, independent contractor, industrial robot, Internet of things, Jeff Bezos, job automation, Joseph Schumpeter, Kevin Kelly, Kevin Roose, Lyft, Marc Andreessen, Mark Zuckerberg, military-industrial complex, money market fund, natural language processing, no-fly zone, Ocado, pets.com, plutocrats, race to the bottom, ride hailing / ride sharing, Salesforce, Sand Hill Road, self-driving car, shareholder value, Sheryl Sandberg, Silicon Valley, Silicon Valley startup, Snapchat, speech recognition, Steve Jobs, Stewart Brand, supply-chain management, TED Talk, Tim Cook: Apple, too big to fail, Travis Kalanick, two-pizza team, Uber and Lyft, uber lyft, universal basic income, warehouse automation, warehouse robotics, wealth creators, web application, Whole Earth Catalog, work culture

That idea is antithetical to what professors teach at the Harvard Business School. Communication and coordination are supposed to nurture teamwork and get employees to buy into a company’s strategy. Bezos concluded the opposite: that bringing everyone up-to-date on a project lengthens its gestation. In 2002, he instituted his now legendary two-pizza teams for software development. Project teams would include no more than ten people, a group small enough that they could be fed by two pizzas. This kept bureaucracy down and time-wasting corporate communications to a minimum. “Our overall approach to teams has evolved slightly,” says Amazon’s Greg Hart, “but the basic organizing principle is pushing responsibility and autonomy down to the smallest possible atomic unit, which to as great a degree as possible has complete control over the success or failure of what they’re working on.”

Building Microservices by Sam Newman

airport security, Amazon Web Services, anti-pattern, business logic, business process, call centre, continuous integration, Conway's law, create, read, update, delete, defense in depth, don't repeat yourself, Edward Snowden, fail fast, fallacies of distributed computing, fault tolerance, index card, information retrieval, Infrastructure as a Service, inventory management, job automation, Kubernetes, load shedding, loose coupling, microservices, MITM: man-in-the-middle, platform as a service, premature optimization, pull request, recommendation engine, Salesforce, SimCity, social graph, software as a service, source of truth, sunk-cost fallacy, systems thinking, the built environment, the long tail, two-pizza team, web application, WebSocket

Early on, Amazon started to understand the benefits of teams owning the whole lifecycle of the systems they managed. It wanted teams to own and operate the systems they looked after, managing the entire lifecycle. But Amazon also knew that small teams can work faster than large teams. This led famously to its two-pizza teams, where no team should be so big that it could not be fed with two pizzas. This driver for small teams owning the whole lifecycle of their services is a major reason why Amazon developed Amazon Web Services. It needed to create the tooling to allow its teams to be self-sufficient. Netflix learned from this example, and ensured that from the beginning it structured itself around small, independent teams, so that the services they created would also be independent from each other.