The instant-on computer

A long time ago, when I was at Amazon, someone asked Jeff Bezos during an employee meeting what he thought would be the single thing that would most transform Amazon's business.

Bezos replied, "An instant-on computer." He went on to explain that he meant a computer that when you hit a button would instantly be ready to use. Desktops and laptops in those days, and still even today, had a really long bootup process. Even when I try to wake my Macbook Pro from sleep, the delay is bothersome.

Bezos imagined that people with computers which were on with the snap of a finger would cause people to use them more frequently, and the more people were online, the more they'd shop from Amazon. It's like the oft-cited Google strategy of just getting more people online since it's likely they'd run across an ad from Google somewhere given its vast reach.

We now live in that age, though it's not the desktops and laptops but our tablets and smart phones that are the instant-on computers. Whether it's transformed Amazon's business, I can't say; they have plenty going for them. But it's certainly changed our usage of computers generally. I only ever turn off my iPad or iPhone if something has gone wrong and I need to reboot them or if I'm low on battery power and need to speed up recharging.

In this next age, anything that cannot turn on instantly and isn't connected to the internet at all times will feel deficient.

How to become a speed reader, updated

Spritzing presents reading content with the ORP located at the specific place where you’re already looking, allowing you to read without having to move your eyes. With this approach, reading becomes more efficient because Spritzing increases the time your brain spends processing content without having to waste time searching for the next word’s ORP. Spritzing also enhances reading on small screens. Because the human eye can focus on about 13 characters at a time, Spritzing requires only 13 characters’ worth of space inside our redicle. No other reading method is designed to help you read all of your content when you’re away from a large screen. But don’t take our word. The following video compares traditional reading to Spritz and is a real eye-opener when it comes to the efficiencies that are gained by placing words exactly where your brain wants them to be located.
 

More here from Spritz Inc. on their speed reading technology. It's worth looking at a demo of the Spritz speed reading aid in action in this article. By placing each word of the text you're reading in a position so that the key letter of each word is located at the same point, your eye doesn't have to move across words on a page. It turns out that eye movement in traditional reading is inefficient. Allowing your eye to stay fixated in one spot increases your reading throughput (though it sounds lazy; don't make my eye have to move even a few millimeters, it's so taxing!).

I took a speed reading course when I was in 6th grade, I was taught that the key to speed reading was to consume blocks of words at a time and to stop yourself from subvocalizing (that is, sounding out the words silently in your head as you read). You can try a number of tricks to cure yourself of that habit, one is to hum to yourself while reading. That blocks your ability to subvocalize.

Spritz's approach to speed reading is a bit different. Rather than scanning groups of words at a time, you're reading one word at a time. I can't imagine reading that way, but everything new seems odd, and every time I find myself rejecting the new I feel like Grandpa Simpson so I'm curious to try this out.

UPDATED: Professor John Henderson is skeptical of Spritz's claims.

So Spritz sounds great, and even somewhat scientific. But can you really read a novel in 90 minutes with full comprehension? Well, like most things that seem too good to be true, the answer unfortunately is no. The research in the 1970s showed convincingly that although people can read using RSVP at normal reading rates, comprehension and memory for text falls as RSVP speeds increase, and the problem gets worse for paragraphs compared to single sentences. One of the biggest problems is that there just isn’t enough time to put the meaning together and store it in memory (what psychologists call “consolidation”). The purported breakthrough use of the “ORP” doesn’t really help with this, and isn’t even novel. In the typical RSVP method, words are presented centered at fixation. The “slightly left of fixation” ORP used by Spritz is a minor tweak at best.

Two other points are worth noting. One is that reading at fast RSVP rates is tiring. It requires unwavering attention and vigilance. You can’t let your mind wander, ponder the nuances of what you’re reading, make a mental note to check on a related idea, or do any other mental activity that would normally be associated with reading for comprehension. If you try, you’ll miss some of the text that is relentlessly flying at you. The second point is that the difficulty of comprehension during reading changes over the course of a sentence, paragraph, and page. Our eyes engage in a choreographed dance through text that reflects this variation in the service of comprehension. RSVP makes every step in the dance the same. Or, to stretch an analogy, imagine hiking along a forest trail. Each step you take determines your overall hiking speed. Some steps require a longer pause to gain footing on loose stones, and others require a longer stride to step over a protruding root. Would it be effective to run on the trail? Worse, would it be a good idea to tie a piece of rope between your ankles so that each step was constrained to be exactly the same length? Surely this would lead to some stumbling, if not to a twisted ankle or catastrophic fall!

People no longer have to buy computers that overserve

A Mac or PC is a superior experience for traditional computing activities, at least according to traditional measurements like speed or efficiency, but an iPad is simpler and more approachable, and it does other things as well.

(This, of course, is why Macs aren’t going away. In fact, as Phil Schiller noted at the end of this great Macworld piece marking the Mac’s 30-year anniversary, the iPad has freed the Mac to focus even more on power users going forward.)

Ultimately, it is the iPad that is in fact general purpose. It does lots of things in an approachable way, albeit not as well as something that is built specifically for the task at hand. The Mac or PC, on the other hand, is a specialized device, best compared to the grand piano in the living room:2 unrivaled in the hands of a master, and increasingly ignored by everyone else.

So writes Ben Thompson in The General-Purpose iPad and the Specialist Mac. I agree. For a long time, one of the debates was whether an iPad was just a consumption device. While I think it's silly to argue that you can't create on your iPad, I do largely use it for consumption purposes. I'd much rather do many things on my desktop or laptop than my iPad: write, build spreadsheets, wireframe, create presentations, edit video.

But there are plenty of activities which the iPad and iPhone are far better devices for the job because they are portable, light, sensitive to touch, and, not to be underestimated, always on (while I leave my laptop on most of the time, it still takes longer to wake it up and get it going than my iPad or iPhone). Browsing web pages. Reading books. Reading my email, Twitter, Instagram, Facebook. Messaging.

For some activities, the interaction method of finger on screen is both more intimate and simpler. For example, dragging my finger across the screen to adjust brightness of photos in Snapseed is more pleasurable than taking my mouse and finding a tiny slider handle with my cursor and then moving it in tiny increments. Double tapping and having mobile Safari zoom a column of content on the web is wonderful, I wish I could do that on my laptop.

It's clear that for many years, my desktop and laptop have been too much computer for many jobs. For many people, all they needed a desktop or laptop for was reading email, surfing the web, listening to music, or watching streaming video. For those tasks, a desktop or laptop computer overserved their needs, but those were the only types of computers we had so we used it as such.

Now that the world has more choices in computing devices for the job, many are choosing a tool that doesn't overserve, and that is more often than not an iPad or smartphone. For the average household, those are much cheaper to purchase than a laptop or desktop.

I still love sitting down in front of a giant monitor hooked up to my old Mac Pro in my office at home, but the sales figures don't lie. That's now the minority.

Some serious pivots

Startups in Silicon Valley get plaudits for pivoting, but a company that has had to make some real pivots with a capital P across many decades is none other than mobile phone goliath Samsung.

I had dinner tonight with a friend whose grandfather was one of several people brought to Samsung to help them make their first entry into technology hardware. At its founding in 1938, though, Samsung was a simple trading company that dealt in local produce. Later it shifted to processing sugar cane, then it moved into textiles. That was the first in a long line of transformations in its evolution from small family business to global conglomerate. From making your own noodles to making your own smartphones, that is survival and adaptation of the highest form.

There aren't many U.S. tech companies that have even been around that long, let alone having evolved so drastically. Off the top of my head, IBM and Xerox are the only two tech companies I can think of that were founded in the U.S. prior to Samsung in 1938 and that still exist. I'm going to venture that neither of those began as noodle makers.

DNA for data storage

Scientists were able to store 739 kB of data in DNA.

The study reported that the institute's team had stored all 154 Shakespeare sonnets, a photo, a PDF of a scientific paper, and a 26-second sound clip from US civil rights leader Martin Luther King Jnr's "I Have a Dream" speech in a barely visible bit of DNA in a test tube.

"We downloaded the files from the web and used them to synthesise hundreds of thousands of pieces of DNA. The result looks like a tiny piece of dust," said Emily Leproust of Agilent, a biotech company that took the digital data and used it to synthesise molecules of DNA in a laboratory in the United States.

Agilent then mailed the sample across the Atlantic to the EBI, where the researchers soaked it in water to reconstitute it and used standard sequencing machines to unravel the code. They recovered and read the files with 100 per cent accuracy. "It's also incredibly small, dense and does not need any power for storage, so shipping and keeping it is easy," Goldman added.

Not great for retrieval given the high cost of synthesizing DNA, but as long-term backup, really robust.

The data stored in the test amounted to only 739 kilobytes, but the technique could be scaled up to store the three zettabytes, or 3,000 billion billion bytes, of stored data estimated to exist on earth, and the only limitation to wide implementation is the high cost of synthesising DNA, the researchers said. The world's data would theoretically fit in one hand and could be stored safely for many centuries, they said.

It feels like there's a sci-fi novel in this somewhere.

The most interesting company in tech: Valve

You hear it in technology companies all the time, especially at firms that have survived from their days as a startup to become a bigger firm: we want to remain entrepreneurial. To feel like a startup. Nimble. A place that entrepreneurs want to work. A place for builders to build (a phrase Jeff Bezos always used to describe what he wanted Amazon to be as a company).

But it has always felt a bit disingenuous. You couldn't fully escape the top-down corporate imperative, though they might have wanted to provide the illusion that you had.

[The Google 20% idea in recent history sounded like the most promising attempt, perhaps a more practical evolution of a earlier incarnations, for example research divisions like Xerox PARC or Microsoft Research]

But then I read about Valve Software, and it sounded like a company was actually taking all this lip service to heart and pushing this concept to its most logical extreme. What Valve has implemented as their "corporate" structure makes them, to me, the most intriguing company in technology, if not in business.

Here is the Valve Employee Handbook (PDF) which had the Internet buzzing a while back. In summary: Valve is a completely flat company, with no hierarchy, and everyone has to find their own project or start their own project and recruit other employees to the cause. You have no boss, no one can tell you what to do. Some companies have occasional hackathons or hack weeks; Valve is run like a perpetual hackathon. Google had 20% time; Valve Software lets every employee have 100% time.

As the Valve Economist-In-Residence Yanis Varoufakis explains in this long and fascinating blog post, the way Valve is organized is an attempt to turn corporations into more responsive, efficient entities by introducing real market forces.

Interestingly, however, there is one last bastion of economic activity that proved remarkably resistant to the triumph of the market: firms, companies and, later, corporations. Think about it: market-societies, or capitalism, are synonymous with firms, companies, corporations. And yet, quite paradoxically, firms can be thought of as market-free zones. Within their realm, firms (like societies) allocate scarce resources (between different productive activities and processes). Nevertheless they do so by means of some non-price, more often than not hierarchical, mechanism!

The firm, in this view, operates outside the market; as an island within the market archipelago. Effectively, firms can be seen as oases of planning and command within the vast expanse of the market. In another sense, they are the last remaining vestiges of pre-capitalist organisation within… capitalism. In this context, the management structure that typifies Valve represents an interesting departure from this reality. As I shall be arguing below, Valve is trying to become a vestige of post-capitalist organisation within… capitalism. Is this a bridge too far? Perhaps. But the enterprise has already produced important insights that transcend the limits of the video game market.

Varoufakis refers to Valve as a spontaneous order firm. What replaces market price signals in the Valve model is individual time allocation. That is, every employee can freely choose how to spend their time, which project or projects to devote themselves to (the Google 20% time model taken to its extreme). Contrast that to the traditional corporation, with people's work allocation imposed from the top down, through the organizational hierarchy.

He concludes his blog post:

Whatever the future of Valve turns out like, one thing is for certain – and it so happens that it constitutes the reason why I am personally excited to be part of Valve: The current system of corporate governance is bunk. Capitalist corporations are on the way to certain extinction. Replete with hierarchies that are exceedingly wasteful of human talent and energies, intertwined with toxic finance, co-dependent with political structures that are losing democratic legitimacy fast, a form of post-capitalist, decentralised corporation will, sooner or later, emerge. The eradication of distribution and marginal costs, the capacity of producers to have direct access to billions of customers instantaneously, the advances of open source communities and mentalities, all these fascinating developments are bound to turn the autocratic Soviet-like megaliths of today into curiosities that students of political economy, business studies et al will marvel at in the future, just like school children marvel at dinosaur skeletons at the Natural History museum.

A few reactions...

I'm not sure why intrinsically a time allocation model would be superior to a market-price driven model, but at the very least it would only seem to have an advantage if the individuals were very smart. My hypothesis is not that this model is inherently superior, necessarily, but that it provides a critical recruiting edge which, in a market with constrained talent, is a massive advantage. That in turn provides Valve with the necessary star talent to make the time allocation model flywheel spin. The innovative games (e.g. Portal and Portal 2, Half-Life) and business models (Steam) Valve has produced may simply come from that superior labor pool.

Secondly, spontaneous order firms may work best in a business like Valve's, the videogame business, which, like the film business, is a hits driven business in which every incremental game creates its own new market. They compete in a far less zero-sum game market than, say, Apple does in mobile phones. When you think about the coordination it would take for Apple to shift itself to a twice a year release schedule for iPads and iPhones, coordinating its product development, supply chain, marketing, and retail efforts across hundreds of countries globally, the concept of them becoming a spontaneous order firm seems impossible.

Third, I can think of many companies where a model like this wouldn't work because in those companies, people who are more senior in the hierarchy genuinely believe in their own superiority over the folks beneath them on the org chart. They'd likely be exasperated by the day to day work decisions coming out of a spontaneous order firm. This is not an indictment of the Valve model, just a check on the realistic speed with which such a model might realistically spread to other companies.

Fourth, at all the tech companies I've worked at, which are all more traditionally hierarchical, I wouldn't characterize them as strict Coase-ian "islands of conscious power [corporation] floating in an ocean of unconscious co-operation [market]". Most tech companies I know are obsessed with gathering price signals from the marketplace, and that data permeates the firm.

My first job at Amazon consisted of assembling, every month, a 100+ page report called the Analytics Package which had metrics, external and internal, on every aspect of our business. It would take me almost the entire month to compile, I'd have to translate each of them into graphs Tufte would approve of, and then I'd write prose analysis to accompany each package to highlight the most interesting signals. I had to generate hard copies of this, and every month I'd make good friends with the copy repairman as one copier after another broke down under the load of cranking out hundreds and hundreds of pages of information. Nowadays, most startups I know of have reporting portals that can generate such data in beautiful manipulatable charts on demand.

Lastly, a model of time allocation might be more susceptible to the cult of charisma? In my experience charisma and competence or intelligence are not always tightly correlated. The most dangerous person in a company is the charismatic fool.

Within the confines of a more traditional firm, though, I suspect there's much to learn from the Valve Software experiment, and so I'm really curious to see how they evolve over the next five to ten years. How much larger can Valve grow with this business model? Is it a more efficient model for gathering price signals from customers? How well does the model hold up against bad eggs, like the mythical brilliant asshole or just someone incompetent?

Let's examine one issue in more detail.

In companies, politics often crop up. This is especially common as companies grow larger. Politics are damaging to companies because they can lead to local instead of global maximums (wins for a local fiefdom or manager instead of for the company as a whole).

My experience is that politics is rooted in perceived mismatches between a person's own sense of worth and external signals of that worth, from explicit signals like one's title and salary to softer signals like the time spent with the CEO.

When a company is small, the politics tend to be minimal since many startups either are completely flat or have little to no hierarchy, everyone gets lots of time with the CEO, and everyone's marginal contribution is massive and easy to detect. In a larger company, the pathways for recognition get clogged. Suddenly the CEO you used to see  all the time you only see once in a while. Hierarchy is put in place to try to minimize coordination costs, but suddenly everyone is judging their self-worth against where they're positioned within that org. chart which is inherently a ranking system generally tied to compensation.

Valve's model has the potential of upending those political costs. There's so little hierarchy that mismatches between internal evaluations and external markers of value or less common. Since the company's surplus is divided up each year based on contributions, theoretically compensation is more closely and efficiently tied to value generation rather than getting out of synch purely based on factors like seniority or tenure.

In the end, it may be that all of Silicon Valley, rather than Valve Software, is the most interesting spontaneous order unit to study. The common complaint about Silicon Valley is the competitive labor market, with the average tenure at less than 2 years. California does not look kindly on non-compete agreements, it's a labor-friendly state, and so people carry ideas with them from company to company all over the region. They are all putting the time allocation model to practice, and while it makes recruiting and retention a pain in the ass, it leads to the region being among the most generative business ecosystems in human history.

Compensation market inefficiency - sports vs. tech

Here's a mystery: in sports, some players on a team make more than their coach, but in the tech world (and the business world, for the most part), almost no employees make more than their manager. Which of the compensation distributions is more equitable?

First, there is a similar inefficiency in both markets, and that is that salaries for those fresh out of school tends to be bounded. In sports it's because of the agreed-upon arrangement between owners and players in each sport. In MLB, for example, a player is under team control for the first 6 years until they become free agents and can hit the open market. They have three years before they can even start to go to arbitration if they don't like the team offer. All of this is a huge suppressor for player salary. Albert Pujols will be paid more over the final 10 years of his career than the first 10, but it's almost certain that he produced more the first half.

In the tech world, most employees come out of school and get slotted into rough salary bands. In the beginning, that's largely fair. You can't tell how someone out of school will work with others or adjust to the more relentless rhythm of corporate life as opposed to the more lumpy work distribution in college.

But young developers, to take a group of people I think are particularly underpaid, typically produce a ton very early in their career, certainly more than they're paid for. It's not always evident right away, but within a short period the best quickly rise to the top. A lot of this has to do with the amazing leverage one software developer's code can have in the marketplace. Code can be made almost infinitely scalable. Even the greatest sports player can only have so much impact. The maximum is probably either a sport with few players on the floor at once (like basketball) and enormous marketing power in the global marketplace, or an individual sport where the player is responsible for nearly all of his/her performance (coaching being the other factor in an individual sport).

A huge difference between sports and the technology industry is thatInformation transparency on the true worth of a tech employee is much lower. Companies have a huge information asymmetry advantage over employees. In sports, the contracts of players are public knowledge, you know how much the guy in the locker next to you makes. Everyone's performance is highly visible, analyzed by thousands of professional and amateur analysts and fans.

In the business world, information about what different people are working on and how productive they are is not publicized that well within a company, and it's even less discoverable outside a company. You are typically limited to what you can put on your resume and who you can list as references if you take yourself on the open market.

[Incidentally, the lack of easy ways to quantify an employee's impact with much objective precision is exactly the reason that tech companies, who love to preach the virtues of transparency, can't be transparent with things like compensation. The disparity between one's compensation and one's impact, which will vary widely depending on who's judging, would cause way too much friction and gridlock. Imagine employees, like sports player unions, going on mass strike every so often.]

My sense is that both the sports world and the tech world are inefficient in their compensation schemes, but in different ways. In sports, I suspect many coaches are paid too little. Bill Barnwell makes a strong argument for Jim Harbaugh as a highly underpaid asset. In this article behind the ESPN Insider paywall, Bradford Doolittle makes a similar argument for the value of Tom Thibodeau to the Bulls.

In the tech world, I suspect the opposite, and that is that many employees are underpaid relative to their managers. Hiring great developers straight out of college and owning them during their equivalent of their pre-arbitration or pre-free agency years (to use a sports analogy) is one of the most important things a tech company can do, and Google, in particular, was the first to really exploit this inefficiency by quickly raising compensation and perks across the board. They drove the compensation bar up towards what is likely a more equitable equilibrium.

It's difficult for young developers to really assess their true worth because they typically have a very limited view on their impact. Even if they had a more global view, the ability to quantify the impact of a young developer versus a hypothetical replacement, to calculate the equivalent of WARP (to use a baseball term meaning Wins Above Replacement Player), in other words, remains very difficult. Will things like Github change this? Perhaps over time, we'll have more quantitative measures on something that will serve as a replacement for a resume, something more like the statistics on the back of a baseball card.

A related inefficiency that many claim is rampant in Silicon Valley compensation markets is age discrimination. It feels like some reporter needing to file a story will write a story on this once a year. Some recent examples include this one in Reuters and this one in the Mercury, but you can go back a few years and find earlier articles that say the same thing. This phenomenon is not unique to technology, you'll see it in sports, too. The brutal truth is It's partially the number of hours a young, single worker is willing to put in versus a married, middle-aged worker with kids, but it can also correlate to the willingness or familiarity of young developers with newer programming languages and techniques. Given how ruthless the technology recruiting battle is and how valuable great developers are, I suspect this inefficiency, if it exists at scale, will be ruthlessly exploited by some tech companies and closed over time.

Employees have some recourse for getting closer to market value. One way is to shop around frequently, like a free agent in sports, to determine true market value. Since there isn't an equivalent of a team's exclusive rights to your pre-arbitration or pre-free-agency years as in sports, you are essentially always a free agent. The downside is the increased stress from spending time selling yourself. Another option is to go do a startup, where, in a smaller team, you earn more visibility and credit for your output than you would within a giant corporation. One downside is that the nature of the work can be much different than in a larger company. Also, it's a much higher risk proposition, and it's not for everyone, but for entrepreneurial, risk-taking folks it's usually worth trying at some point if for no other reason than self-education.

Today we have headhunters in the tech world, or placement agencies, but at some point I wonder if we'll have the equivalent of a CAA in tech, with some knowledgeable agents representing the strongest developers and finding the most interesting work and highest compensation for them.