The Hare with Amber Eyes by Edmund de Waal
A well-written history of a family of wealthy Jewish financiers who crossed paths with Proust and Rilke and then lost everything when Germany annexed Austria. At times, I couldn’t tell if the book was fiction or nonfiction. I never fell into this book.

Love and Shame and Love by Peter Orner
This book felt lazy, as if Orner-the-short-story-writer wanted a novel and so chained short stories together, rather than write a proper novel. I do have friends who loved the book.

Open City by Teju Cole
This novel doesn’t have much of a plot, doesn’t differentiate speech from narrative, and has a marginally-present main character — and yet I loved it as much as the deafening reviews suggested I would. “Ordinary solipsism” and all the rest.

Triumph of the City by Edward Glaeser
One of my favorite nonfiction books of late. It’s fast and overwhelms – in a good way – with evidence for city life. I came away more conscious of housing stock levels and land-use regulations. Definitely recommended, particularly the chapter on Detroit.

1. The paper’s introduction seems to suggest, without being direct, that the existence of reversible transactions (and the resulting need for dispute mediation) explain micropayments’ poor adoption. My impression had been that micropayments’ lack of success had more to do with marginal costs other than fraud being prohibitively high for both spenders and financial institutions. So even if we eliminated all fraud risk, I don’t believe micropayments would make sense.

1a. Transaction batching is often cited as the way we’ve gotten to what looks like micropayments. (Payments on Apple’s iTunes store and Flattr both look like micropayments, but neither are.) If anything this seems to support the it’s-transaction-risks-other-than-fraud hypothesis; batching transaction would seem to make chasing down any instance of fraud more difficult but reduce total costs because it’s (mc*1 transaction) rather than (mc*n transactions). Though transaction batching makes dispute resolution more difficult, we’re still willing to do it.

2. Bitcoin’s gold-mining analogy will likely become my at-hand anecdote for technology that borrows from but does not replicate “the real world.” Much has been written about the reasons social software should mimic the real world; I was once one of the advocates. Yet a few recent conversations have convinced me the best technology doesn’t mimic the real world but rather extends the real world.

3. The privacy models laid out in section 10 referenced banking, but they’re general. Here’s the models from the paper in which “Traditional Privacy Model” is a traditional bank and “New Privacy Model” is Bitcoin:

Here’s Facebook and Twitter repurposed in Bitcoin’s language. Interestingly, Facebook’s model is precisely that of a bank: it sees all transactions, knows the attached identities, and mediates between parties. Twitter is a bit different; it doesn’t shield anyone or anything from the public.

What social software divorces all content from any sort of identity (pseudonymous, anonymous, or identified)? I’m looking for something that has no concept of public identities, even those defined temporarily like 4Chan’s.

This is all very high level, so more practically: I would love to see a version of Twitter that includes replies, RTs, and favs but drops usernames and profile photos — if anyone works on this, please let me know.

It’s also very technical, but the interesting part here is in the feelings: I’m very curious about the experience of reading tweets on an identity-less Twitter stream. What would the product feel like? Would different tweets spread in an identity-less network, and if so, what does that mean for Twitter? How large must the difference be between identified Twitter and identity-less Twitter before you’d reconsider your beliefs about the social web? How large before you’d change your beliefs about Facebook?

1. I agree with the three general reasons Tyler lays out: “You are productive fairly quickly, you make good contacts with other smart people, and you can demonstrate that you are smart, for future employment prospects.”

1a. The productivity point may be controversial, but it shouldn’t be. If nothing else — and there is much else — it’s rendered true by salary in the medium- to long-run. Most corporations don’t (and arguably can’t) pay a $60-120k starting salary for 22 year olds. Maybe it’s because they have trouble identifying which 22 year-olds will be sufficiently productive to justify that salary, but maybe it’s because 22 year-olds just can’t be that productive in larger firms.

1b. These jobs pay well in part because the higher-ups in each field actually work with the recent graduates and get utility out of working with smart people. It’s often worth an extra $x,000 from the partners’ pool to get the recent grad whose market rate is $75,000 rather than the $(75-x),000 recent grad.

2. These fields are considered impressive and prestigious. Talented students who guide themselves toward increasingly prestigious problems were and probably still are likely to spend time in consulting, finance, or law. These fields are the output of “the Ivy League hill-climbing algorithm,” as one friend put it. (I do believe software engineering is gaining ground here.)

3. Consulting and finance firms have figured out how to allow smart young people to live in New York/Boston/San Francisco but work in Dayton/Piscataway/Bentonville where they are most needed. This is non-trivial.

4. Adjusting for quality of life, I don’t think consulting, finance, law (or even operations at Google) pay differently. There’s time at work and workplace culture and people’s utility functions — and then if that fails, there’s expense accounts. Consulting firms often have the best ones and pay less than banks and law firms at similar experience levels. But take-home pay matters less if you charge expenses 4.5/7 days of the week to your employer.

5. Coming out of school, declaring you “don’t know what you want to do,” and devoting time to “figuring it out” is hard for many high-achieving students. Those that pull it off still face awkward questions from friends and family members. Consulting and finance (and to a lesser extent law) seem like “places where one can go and be productive and figure out what one should really do.” In these fields, career swaps are the norm.

6. That these jobs are not the most exciting things one could be doing is often the worst that can be said. They are very rarely “bad options.”

Another way to phrase this question is “why can’t [some specific field] attract more smart young people?”

In Other Rooms, Other Wonders by Daniel Mueenuddin
Recommended by someone whose book-taste I trust, especially when it comes to stories like these. (How many “here’s a story of the hardships of daily life in South Asia” have been published in the past decade in the US?) It’s actually quite good though — Mueenuddin can write well, and his characters act and speak like people, not caricatures. Start with his New Yorker short story if you’re skeptical.

Poor Economics by Abhijit Banerjee and Esther Duflo
Skimming or reading this book gives an overview of the last decade-ish of development economics literature, in which Banerjee, Duflo, and their Poverty Action Lab have had a hand. The book explains, in clear English, the “paradoxes” of life in poorer countries without assuming irrationality or pity.

Tide Players by Jianying Zha
Stories of major figures in China’s business, intellectual, and cultural sectors. I didn’t find I empathized with or liked any of the people profiled — which admittedly isn’t the point — but did find the stories narrow, interesting windows into modern-day China.

Dancing in the Glory of Monsters by Jason Stearns
One of the best books I’ve read on the conflict in the Great Lakes. Stearns avoids moralism, even temporarily. The first three-quarters of the book, mostly historical, were better than the last quarter, which was mostly forward looking.

1. The internet offers products competitive to Hollywood: there’s loads of non-Hollywood content on the web that people enjoy. More entertaining stuff finds its way to the internet every day, and as content distributors (e.g. Amazon, Netflix, YouTube) start producing content, seeking to improve their economics, they’ll be more “premium, Hollywood-like” content.

2. Labor supply is changing too; some of the people who would have gone to work in Hollywood earlier are instead choosing to work on the internet.

3. Until streaming becomes a substantial revenue source for studios, they’ll continue fighting everything that seems like to interfere with box-office receipts or DVD sales – including the internet. Parallels to Hollywood’s initial opposition to VCR sales abound. Yet Hollywood can’t rival the distribution offered by the internet, especially with its current cost structure, and piracy is most common in places where content isn’t legally available. Studios cannot build their own networks of theaters and DVD sellers that rival the internet’s reach and would do well to embrace internet distribution.

4. Wider distribution means more popularity, more of a role in the “cultural consciousness,” and more merchandise sales. Moving forward, it’ll not just be the Twilights that have merchandising machines; more films and shows are turning toward merchandise as a revenue stream (e.g. Mad Men’s collaboration with Banana Republic.) A film industry that embraces distribution as a pathway to revenue is a film industry that’s likely to embrace the internet.

5. Box office revenues have been falling, but they still matter because they seem to be the best-available indication of a movie’s future cash streams. (For how much longer will the bragging rights of box-office receipts matter? When can we start using Facebook newsfeed data to predict box office takes?) Yet without revenues to securitize and sell off upfront or better control of production and marketing costs, studios will make bets that appear to be safe. In practical terms, this means more sequels and cookie-cutter plots.

6. Competition from the internet should improve the movie-going product. Theaters will have to offer a more differentiated experience than simply a big screen, surround sound, and comfortable chairs (you can have all that and more in your home.) I expect we’ll see “super-premium” theaters in big urban areas and theaters selling alcohol in many more areas.

7. Despite the downward price pressure from Moore’s Law and componetized software, movie-making technology is becoming more expensive. Call me techno-optimistic, but this seems unsustainable.

8. One interpretation of Kickstarter’s rise in the indie movie world is that it provides a proxy for market demand. A Kickstarter project’s success can be used to assess movie-product/market fit. It is also true that Kickstarter — and “the internet” more broadly — increases the chance an indie movie will be discovered; as grocery stores move to upper floors, movie marketing will matter less.

9. As other forms of media have moved online, they’ve gotten more participatory. Participatory projects succeed when: 1) the bigger project can be parceled into smaller, lower-cost pieces; and 2) there’s a large pool of potential workers available. Figuring out how to break apart movie production while controlling or lowering video-production costs will open up new forms of “movie media.”

10. The economics of Hollywood movie production seem sufficiently unattractive to support current production costs, but today’s studios aren’t being wholly irrational either. (Put differently: it would still be difficult to produce J. Edgar, even if you started from a Silicon Valley garage; put differently still: movie production isn’t yet garage ready.) Yet Hollywood, the high-cost and high-quality producer, has begun hitting diminishing returns, and there’s an opening for “a new type of movie” that starts out looking inferior but, over time, is able to win through relentless increases in efficiency.

1. Sandberg joined the company in March 2008; in December 2008, Facebook was being financed at a $15bn valuation.

2. Let’s take $15bn as Facebook’s valuation when Sandberg’s comp package was issued. (The number might be too high; maybe there was a premium placed on preferred shares, and the company certainly grew in 2008, but it’s in the ballpark.) From March 2008-January 2011, Facebook increased it value 6.67 times. ( = $100bn/$15bn.)

3. The Times calculated Sandberg’s comp package at $1.6bn if Facebook were valued at $100bn. What’s worth $1.6bn at a $100bn valuation was worth $240mm at a $15bn valuation. (Assuming no stock grants, options resets, etc.)

Punchline: Facebook’s board granted Sandberg a $240mm comp package because they thought she could build a business that would generate billions in profit and would increase the company’s value by way, way more than she was getting paid. She did it, and that’s why she’s the number-two at one of the most valuable companies in the world.

In many ways – all practical ways? – our class isn’t a design class. There’s some stellar design classes at SVA, but there seemed to be less awareness of entrepreneurship, or entrepreneurial-ish things, among students.

And so our fairly-explicit goal is to maximize the number of students who will start companies. We’re using stories from founders, which we call love letters, to humanize “the mythic entrepreneur,” and we’ve tried to use the projects to give experience and quick wins. The final project is literal ramen (or cereal) profitability.

Gary and I are very bullish on designers’ ability to create transformative products and services.

While our views have been informed by working at USV, we’re not assuming the “end goal” is or should be a venture-backed company. We are assuming the internet will be relevant to whatever one does.

We’ve also designed for openness: the syllabus and assignments are available online. We’ll be tumblr’ing about the classes and posting audio recordings of many guest speakers. The students will be sharing their work online as well. Please do follow along if you’re interested.

1. What do you think of X
I’ve gotten a few “what do you think of X” emails, where “X” is a new web or mobile service that wants to disrupt work in one way or another. I’m trying to think through these questions in a more systematic way, but in the meanwhile, I’ve found Cherry pretty compelling.

Cherry is an iPhone app that lets you order up an immediate car wash. Tell the service where your car is parked, and Cherry will send a professional washer to clean your car. The service has mostly been derided as a sign of an oncoming apocalypse/bubble/disaster, and maybe it is one. I don’t know, but I don’t find that a very interesting question either.

I do find Cherry compelling for two reasons:

A. “Liberating” workers
Like Opez, Cherry enables car washers to become freelancers. They don’t need to work for a car-washing shop and so can retain more of the profits generated by their work.

Historically, one service provided by a car-washing shop has been finding, staying in touch with, and retaining customers. The internet’s made it relatively easier for anyone – from a solo car washer to a car-wash shop manager – to find and retain customers: Angie’s List, Yelp, Groupon, foursquare .. the list of tools goes on and on. (And will continue to go on and on.) A motivated individual can use these tools by himself or herself or can rely on a lighter-weight solution (like Cherry) for the heavy lifting.

We’ll see more of services supporting newly liberated workers.

B. Shifting car washing from capital-intensive to labor-intensive
Over the past few decades, we’ve largely replaced people with machines in the car-washing process. (We’ve also done this in many other processes in our economy, but that’s mostly irrelevant to this argument.) This is capital-labor substitution: for years, the machines were relatively cheaper than the humans, and so we got relatively more machines (capital) and relatively fewer people (labor.)

Cherry’s reversing this trend: it’s suggesting it may be more efficient to have people and squeegees in the streets than big hoses inside of stone garages.

Why are we seeing a mix shift away from capital? Perhaps because labor is relatively cheaper than it has been. In the US at least, thousands of the people who have been laid off recently have not found productive, full-time work elsewhere. There’s an argument that these workers actually had zero marginal product in their previous occupation, and so the appropriate wage rate is zero; there’s also an argument that wages are sticky – that these workers will not accept wages commensurate with their (non-zero) marginal product – and this reluctance is keeping them under- or unemployed .. Or perhaps Cherry is an aberration, and we’ll soon be back on our capital-growth path.

2. Local real estate
The reputation-based world I started to lay out, taken to its extreme, would mean that real estate is less important today than it has been in the past.

Think about it this way: brick-and-mortar stores are generally located on the first floor of buildings to maximize their access to passers- and drivers-by. It’s been a method of discovery. How did you find your grocery store, your dry cleaner, your shoe repair shop? By “stumbling across” these places in the course of going about your day? That’s offline discovery, and that’s (mostly) how the world works today.

In a wholly reputation-based world, discovery will be wholly online where reputation can be tracked. You’ll use these reputation tools/metrics/systems to “discover” the place, and then you’ll go out and find it. It seems a stretch to imagine grocery stores and fast food restaurants on buildings’ upper floors, rather than ground floors, but I’m pretty convinced that’s what a world of online discovery, rather than local discovery, looks like.

Turns out the entire “explain the world” thing is pretty hard – but this post is my attempt to explain a few things at least.

What comes next
Now is a great time to be an internet entrepreneur. While much of the global economy sputters, tech companies post growth numbers other industries haven’t seen in years. Their success hasn’t gone unnoticed, and the pace of tech-company creation has quickened.

There’s more than me-tooism going on. It is, for example, easier to start a tech company than ever before – it’s easier to access startup capital, procure basic infrastructure and tools at lower prices, find and cultivate mentors, and join an accelerator program.

Accelerator programs that focus on early-stage technology companies have grabbed headlines recently. The programs are designed to be crash courses in starting a technology company and bringing a product to market. They often last three intense months, ending with a structured pitch to a roomful of investors. The most famous program is Y Combinator, based in Silicon Valley, but there are other programs around the world, including Techstars, 500 Startups, DreamIt, Excelerate, and Seedcamp.

Over the past few months, I’ve seen over 160 companies come through eight different accelerator programs. It’s a skewed group, but it captures the zeitgeist of a certain segment of the tech industry – and, I think, looking at these companies is one of the best ways to get a sense for which opportunities compel internet entrepreneurs today. Here’s a look at some of what these entrepreneurs are thinking about – and where we all might be headed:

Software is developing its own component industry
Last year, John Maeda predicted technology would become a cottage industry by 2020 “with bespoke applications made by many, rather than today’s industrialized, Microsoft-esque mass production and distribution model.” I doubt we’ve seen the last billion-dollar software company; tech companies will continue to ride the economics of software, and larger companies will use strong network effects and scale to drive consolidation. However, we’ll likely see fewer companies that need to build – and fewer companies that will build – every piece of their technology themselves.

Component sourcing has already begun to revolutionize the software industry. Take a look at Amazon’s or Rackspace’s cloud hosting services, which have lowered the price and complexity of hosting software, or the success of “outsourced” tools like Google Analytics, Twilio’s voice and text messaging infrastructure, or Urban Airship’s iOS notifications.

Entrepreneurs in this summer’s accelerator programs sliced off pieces of what it takes to build and run a web or mobile application and offered those slices as services. “I built this piece of technology three times at three different companies. I built it a fourth time, and that’s the service my company offers,” a Y Combinator CEO pitched.

Developers are the target customer for 30% of the companies I saw. Consider Parse, which provides a backend to a mobile app, and MongoHQ, which hosts instances of the open-source MongoDB. While LaunchRock offers user acquisition tools, TightDB provides a database customized for big data. ReportGrid provides website analytics, while CoderBuddy helps developers create and host websites on Google’s App Engine, and Creative Brain Studios allows game developers to deploy one game on several devices and operating systems.

Using components to build larger systems doesn’t require building monotonous systems. Consider the iPhone, made of component parts sourced from Chinese megafactories but designed in California. There’s something beautiful and unique about the iPhone that no other handset manufacturer has been able to match – even the ones that source parts from the same megafactories.

Similar to physical-product designers, when software developers start with components, they can concentrate on the core problem they’re solving and will create better products in less time. It’s exciting.

Work is shifting toward a peer-to-peer model
The first two decades of the modern internet broke industries built on distribution monopolies (e.g. music, news) and facilitated coordination between the consumer and the provider without the need for a middleman (e.g. hotels, car rentals.) The same will happen for a large fraction of our work, especially in cases where the work is standardized or employers “distribute” their workers to pools of customers.

One reason to create firms is the coordination and signaling problems of situations with imperfect information and transaction costs. As technology increases information flows and decreases transaction costs, individuals can leave their old employers and strike out on their own. Their livelihoods will still depend on providing valuable services in exchange for fees, but they’ll do so as freelancers – and on their own, they’ll capture more of the value generated by their work.

Just as blogs allowed talented writers to build audiences without being affiliated with large media organizations, and as Twitter and Tumblr allowed news- and tastemakers to succeed outside of established news or media properties, new web services will allow individuals to engage with customers without needing to work for a firm.

These free agents, disaggregated and newly empowered, can promote and sustain themselves with new tools: Opez caters to service professionals, like bartenders and hairdressers, and allows them to build followings independent of their employers, while Vayable and SideTour provide marketing and transaction-processing for neighborhood tour guides. Hiptic helps graphic designers promote their work, while Zerply helps creative professionals do the same, and InterviewStreet lets programmers show off their skills.

As technology creates new free agents, it’s also changing the notion of “work” to be less time- and location-specific. This is especially true of work that can be done easily at a distance. Workers who can’t differentiate themselves using their reputation will be commoditized. This summer, web services were launched that allow you to order up a proofreader (Kibin), blogger (Contently), tutor (LearnBop), language partner (Verbling), car ride (Ridejoy), science researcher (Science Exchange), cooking instructor (Culture Kitchen), mystery shopper (SpotCheck), or transcriptionist (Mobile Works) from your browser. The Mechanical Turkification of work has begun.

Between identified, liberated individuals and the nameless, faceless drones of Mechanical Turk lies identity: does it matter who performs the task at hand? If the worker’s background, skills, or experience matter, there’s likely to be higher variance in demand for a particular person’s services, and free agents will be sought after and chosen by reputation on services built for those purposes. Less-skilled people are likely better suited for tasks for which identity doesn’t matter, and other marketplaces that don’t include a concept of reputation will provide access to a global pool of workers.

What’s really next
Looking at activity across accelerator programs, it’s not clear which “one thing” will be next. This season’s 160 “accelerated” companies, nevermind other tech companies created outside of incubators, each seek to solve different problems and should be understood individually. (Making tricky, admittedly, sweeping essays like this one.)

Yet broader shifts like the componentization of some software development and a shift from employed workers to independent agents have begun to emerge; other shifts will become more apparent with time. These, plus the overall pace of tech-company creation, give me faith we haven’t seen anything yet.

Massive thanks to thanks to Dave, Albert, Andy, Brad, Fred, Gary, John, and Patrick for reading drafts along the way.

A few thoughts, still scattered:

1. This chart makes it seem recessions have little to do with technology adoption in the US. Even though the technologies tracked on the chart seems incomplete – what about the 1970s? – adoption seems to keep on goin’ regardless of macro-level economic trends. Could this be because tech adoptions is “even more macro” than a macroeconomic condition?

2. Are we really to believe there was no “new” technology diffusion between 1950 and 1990? I thought this was the US’s Golden Age of Growth. (Should we include penicillin, nuclear power, or desktop computers on this chart?)

3. The fast rise of TV is even more striking when compared with the seemingly-slower rises of desktop internet and mobile internet.

4. We’re only at 80% (desktop) internet penetration after ~20 years. By contrast, radio twenty years in was probably around 82% and TV at 95%. It’s striking because it’s slow, and it’s striking because I’m myopic – I look around and see Facebook and Twitter icons and just assume everyone in the US has internet. In fact, one out of five people don’t have internet access.

5. There’s all sorts of feel-good reasons to protect public libraries in the US, but I increasingly believe their free internet access (shared desktops and wifi) might be the most important. I’d put money on shared desktops being the most heavily-used resource in any urban library; I’d put even more money on the most-accessed site being YouTube.

6. It’s been less than a decade, granted, but mobile internet penetration is a paltry ~58% – and this is when manufacturers seem to be giving away devices. The service layer still seems to matter.

7. Let’s say there are 312 million Americans today. That means there’s approximately 187 million mobile internet users and 250 million desktop internet users. Meeker’s presentation has all sorts of stats from countries beside the US – the crux, basically, is that while there’s many people online today, “we ain’t seen nothin’ yet.”

8. Half the people who don’t have access to desktop internet don’t have access to mobile internet – okay, that’s credible perhaps – but there’s an equivalent number of people who don’t have access to mobile internet but do have access to the desktop internet. How many of these people do we think are under 18? Over 65? Or more concerning: how many are between the ages of 5 and 60 (very many), and how many will need to use the internet in the workforce (very very many, I’d assume)?

9. Why do we care so much about technology adoption? Well, it’s interesting for it’s own sake, and yes, large markets imply potential profits for entrepreneurs and investors. On a broader public-policy level, there’s some evidence of persistent effects: Diego Comin, Bill Easterly, and Erick Gong tried to show that technology adoption in 1500 explains some of the wealth of nations today. It’s an admittedly tall task, but there’s much that’s intuitive (but not inevitable) about the conclusion.

10. Despite the gloomy picture I painted above, Meeker’s chart actually makes me optimistic. We’re actually quite early in the internet technology adoption cycle, and there’s likely a whole lot more to come.