Some Lessons for Startups (pdf with notes)


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My talk at the Stanford Technology Ventures Program on March 6, 2013. I talk about some technical and business lessons from Square, Uber, AirBnB, and the Google Autonomous Vehicle that are applicable to today's startups.

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Some Lessons for Startups (pdf with notes)

  1. Some Lessons for Startups Tim O’Reilly O’Reilly Media @timoreilly Stanford Technology Ventures Program March 6, 2013Friday, March 8, 13
  2. “The skill of writing is to create a context in which other people can think.” -Edwin SchlossbergFriday, March 8, 13 I like to begin my talks with a quote, because, as Oscar Wilde once said, “Quotation is a serviceable substitute for wit.” Edwin Schlossberg once said... Today, I’m going to look at a couple of startups or tech projects that I find really interesting, and try to explain why I find them interesting, both from a technical and a business perspective, and as a way of helping you to develop your own “interestingness” filters.
  3. Friday, March 8, 13I want to start out by talking about Square. There’s so much to learn from this business.How many of you have ever bought something from a store with Square’s iPad cash register? How many of you had the SquareWallet app running on your phone when you did that?
  4. Friday, March 8, 13It automatically checks you in when you walk into a participating merchant. Your name and face appear on the register, andsince your payment details are already on file, all the retail clerk has to do is confirm your identity, as shown in this screen shot.
  5. Lesson #1: Do LessFriday, March 8, 13This is so key. The phone already knows you’re there. Why make you “check in” manually? This makes sense for apps likeFoursquare, but it’s so important to think through what the sensors in the phone let you take out of the UI. This is going to beone of the big voyages of discovery over the next few years, as we design interfaces for devices that have “senses” of their own.
  6. Lesson #2: Get creative with hardware, not just softwareFriday, March 8, 13Square started with this creative hardware hack, a little free dongle that uses the phone’s microphone jack to turn it into a creditcard reader.
  7. Lesson #3: Build “software above the level of a single device”Friday, March 8, 13But with the addition of the cash Register app, Square saw the possibilities of building a system that actually connected buyerand seller in a more profound way. The software system includes both an app on your phone, and an app on the merchant’sipad, and a cloud database and services in between.
  8. Lesson #4: Harness network effects in dataFriday, March 8, 13When I first talked to Jack about Square, he talked about it as a data business - using social network data to make better creditscoring decisions. Long term, once square has millions of participating merchants and consumers, they have built a powerfuldata system that literally gets better the more people use it. But even apart from this banking angle, think how Squaretransforms the way a small merchant operates, bringing “knowing your customer” to a new level. Square has my face, my creditcard info, and, potentially for a repeat buyer, my preferences, like what kind of coffee I normally order.
  9. ` Lesson #5: Rethink workflows and experiencesFriday, March 8, 13And that leads to a profound rethinking of the retail experience.
  10. Friday, March 8, 13Another example of someone rethinking the workflows in retail is the Apple Store. Where most stores (at least in America) haveused technology to eliminate salespeople, Apple has used it to augment them. Each store is flooded with smartphone-wieldingsalespeople who are able to help customers with everything from technical questions to purchase and checkout. Walgreens isexperimenting with a similar approach in the pharmacy, and US CTO Todd Park foresees a future in which health workers will bepart of a feedback loop including sensors to track patient data coupled with systems that alert them when a patient needs to bechecked up on. The augmented home health worker will allow relatively unskilled workers to be empowered with the muchdeeper knowledge held in the cloud.
  11. Friday, March 8, 13This may be the real opportunity for new information retrieval UIs like Google’s Project Glass - in specialized settings whereaccess to a computer can be seen as a powerful kind of human augmentation. I expect it to be used in professional settingsbefore it becomes popular as a consumer device. (In social settings, it will require even more profound resets of behavior thanthe “always-on” mobile phone.)
  12. Lesson #6: Rethink the possibilities in man-machine symbiosisFriday, March 8, 13In this context, I can’t help but mention the Google Autonomous Vehicle project.
  13. The Google Autonomous VehicleFriday, March 8, 13The Google autonomous vehicle is thought-provoking on a number of levels.
  14. 2005: Seven Miles in Seven HoursFriday, March 8, 13But that’s not the most important lesson from the Google autonomous vehicle.You see, back in 2005, the winning vehicle in the DARPA Grand Challenge went seven miles in seven hours.
  15. “We don’t have better algorithms. We just have more data.” - Peter Norvig, Chief Scientist, GoogleFriday, March 8, 13Yet only five years later, Google announced that they had a car that had driven hundreds of thousands of miles in ordinarytraffic. Was this a triumph of AI? It was surely that. But there’s another important factor that is easy to overlook. Google’s chiefscientist, Peter Norvig, says that the algorithms aren’t any better. Google just has more data. What kind of data?
  16. AI plus the recorded memory of augmented humansFriday, March 8, 13It turns out that the autonomous vehicle is made possible by Google Streetview. Google had human drivers drive all those streetsin cars that were taking pictures, and making very precise measurements of distances to everything. The autonomous vehicle isactually remembering the route that was driven by human drivers at some previous time. That “memory”, as recorded by thecar’s electronic sensors, is stored in the cloud, and helps guide the car. As Peter pointed out to me, “picking a traffic light out ofthe field of view of a video camera is a hard AI problem. Figuring out if it’s red or green when you already know it’s there istrivial.” So this is a unique and unexpected application of the notion of human-machine symbiosis, which was originally calledout as an important thread in computing by JCR Licklider in a paper all the way back in 1960.
  17. Friday, March 8, 13Many of the notions that I highlighted about Square also show up in an app like Uber. A driver and a passenger both augmentedwith a smartphone changes our expectations about transit, and has the ability to change the way we organize public transit.Uber also shows us the principles of Software Above the Level of a Single Device, the use of sensors (both you and the driver havephones that know where you are), a data back end as part of the system, and “doing less.” Because your credit card is already onfile, they’ve taken payment out of the workflow. And replaced it with reputation - they ask you to rate the driver, and the driverto rate the passenger.
  18. To what extent can reputation systems replace or augment regulation?Friday, March 8, 13That leads me to an interesting question. Uber asks every passenger to rate each driver. Drivers who don’t do well areeliminated from the service. This actually leads to better results than a system that licenses drivers up front.
  19. Lesson #7: Close the loopFriday, March 8, 13But there’s one other great lesson from Uber.
  20. “What I learned from Google is to only invest in things that close the loop.” - Chris SaccaFriday, March 8, 13Investor Chris Sacca, who used to run special projects for Google, and who is an early investor in Uber, once remarked “What Ilearned...”This is what Google did with advertising, figuring out how to predict what ads people would click on. And in the case of Uber,it’s fundamental to the value proposition. With a taxi, you wait and hope to find one. With Uber, you know where the car is,when it’s going to arrive, and can even watch its progress towards you. Uber closes the loop and takes the uncertainty out of theexperience.
  21. Lesson #8: Create More Value Than You CaptureFriday, March 8, 13But I want to return to Square. There’s one other great lesson there. Create value for more than yourself.Jack’s original inspiration for Square was that he wanted to make it possible for anyone to take a credit card. He wanted toenable a fairer, more evenly distributed economy.Don’t just think about how much value you can create for yourself, your company, and your investors. Think about how muchvalue you can create for your customers.
  22. “There’s a wonderful section in Les Miserables about the good that Jean Valjean does as a businessman (operating under the pseudonym of Father Madeleine). Through his industry and vision, he makes an entire region prosperous, so that “there was no pocket so obscure that it had not a little money in it; no dwelling so lowly that there was not some little joy within it.” And the key point: “Father Madeleine made his fortune; but a singular thing in a simple man of business, it did not seem as though that were his chief care. He appeared to be thinking much of others, and little of himself.”Friday, March 8, 13 I’m reminded of this wonderful quote from Les Miserables.
  23. I call it “the big lie” of modern businessFriday, March 8, 13 This is in sharp contrast to the dominant ideology of modern capitalism over the past few decades, which says that the only responsibility of a company is to make money for its shareholders. Leaving aside the fact of excessive executive compensation as prima facie evidence that no big company really believes that principle, this notion misses the point that an economy is an ecosystem.
  24. Friday, March 8, 13This desire to build value for a community of stakeholders also shapes companies like Etsy, AirBnb, and Kickstarter.
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  27. Lesson #9: Work on stuff that mattersFriday, March 8, 13Perhaps the more general lesson here is to work on stuff that matters.
  28. Open Source Web 2.0 The Maker Movement Open Data Open GovernmentFriday, March 8, 13But there’s another lesson here. Let me point to some of the things that matter that I’ve worked on. In each of these cases, Idid some good for my business, but I was mainly concerned with telling the story of an industry movement, and trying to createawareness and value that benefited many people besides myself and my own company.
  29. Lesson #10: Idealism is the best marketingFriday, March 8, 13People are hungry for meaning. When you really care about creating value for more than yourself, and work hard at it, peopleunderstand it. So don’t be afraid to talk about your values, and why what you do matters. Tell it to yourself, and then tell it toyour customers.
  30. Why I love hackersFriday, March 8, 13One of my best experiences with doing this was when I gave a talk at my Emerging Technologies Conference in 2008 entitled,“Why I love hackers.”They work on what is hard.I recited a poem by Rilke, the Man Watching, which talks about Jacob wrestling with an angel. He knew he couldn’t win, but cameaway strengthened from the fight. The poem ends with something like this:“What we fight with is so small, and when we win, it makes us small.What we want is to be defeated decisively by successively greater beings.”
  31. Friday, March 8, 13A great example of this is a company called Makani Power, which is building drone aircraft for high altitude wind farms. One ofthe early employees left a Wall Street hedge fund not because he thought he’d make more money, but because, as he said, “themath is harder and more interesting.”
  32. Friday, March 8, 13There are lots of ways to work on stuff that matters. Code for America, a non-profit I’ve been working with, brings talent fromthe tech industry to work with local governments to build simple, beautiful and easy-to-use interfaces to government servicesand challenging government to reinvent the way it engages with citizens.
  33. Friday, March 8, 13This coming year, we’re going to be working with New York City and Louisville KY on a project that Anne Milgram from theArnold Foundation, calls Moneyballing Criminal Justice. It turns out that pre-trial incarceration is one of the biggest costs forcities. Using predictive analytics to figure out who to release on bail can save huge sums for cities, but more importantly, it cansave jobs and families. Keep someone in jail unnecessarily and they may lose their job, forcing them into the very life of crimewe’re trying to avoid. This is an incredibly meaningful application of today’s “big data” technology to an important real-worldproblem.
  34. Friday, March 8, 13The White House Presidential Innovation Fellows offers similar opportunities to bring technology expertise into the FederalGovernment. I encourage any of you to apply to either of these programs.
  35. Friday, March 8, 13Health care is another area where today’s skills can be put to use working on stuff that really matters. Here’s a report I co-authored recently that covers some of my ideas on the subject.I don’t have time to go into all the details today, but the report is a free download.
  36. Friday, March 8, 13And there are also amazing entrepreneurial opportunities building companies that also solve interesting social problems. JenPahlka, who founded Code for America, wrote a blog post recently that summarized one of these opportunities, which we’vebeen brainstorming recently. How do you reinvent the corner store so that it delivers what people really need, at affordableprices, in a walkable city?
  37. Friday, March 8, 13These are the kinds of opportunities that we’re looking for at O’Reilly AlphaTech Ventures, our early stage venture firm. If youwant to apply the principles I’ve outlined here to build a great business that also just happens to make the world a better place,we’d love to hear from you.