A Timeless Tech Reading List

In mature fields like physics and mathematics, you can’t earn an advanced degree without learning a core “canon” of the classic works. Because of this shared understanding, experts speak a kind of special language – they can mention a classic paper to make a point that would otherwise take hours to explain.

I’ve had similar experiences. I talk with my colleagues repeatedly about a set of core concepts, which are captured in a small library of technology books. Their ideas have a staying power, with messages that are timeless.

This article surveys my favourites, which together contain the core tech ideas of our time.

Some history first. The genre of technology literature for the masses is relatively new. Aldous Huxley challenged writers in his 1963 essay ‘Literature and Science’ to embrace an accelerating scientific and technological revolution. He wrote that “machinery” has not aroused the sort of “passionate interest” that typically lies at the heart of creative literature. Yet, Huxley was optimistic: “The conceptual and linguistic weapons with which this particular combat must be waged have not yet been invented… but sooner or later the necessary means will be discovered.”

Huxley was right – technology books are now widely read, with passion and interest.

A quick side note: I don’t include academic books in my list since they aren’t accessible to a general audience. I have also avoided any biographies of individuals (like Steve Jobs) or companies (like The Facebook Effect), to keep the focus on compelling ideas. Also, there is a thin line between a technology book and a business book, so some books on my list can be seen as members of either category.

To begin, Tracy Kidder’s 1981 book The Soul of a New Machine is a Pulitzer Prize-winning bestseller. It’s one of the earliest examples of technical books with a broad appeal, combining cutting-edge tech problems with human drama. This page-turner describes how a team of engineers fights impossible deadlines to build a new-generation computer, in this case, the Data General Eclipse MV/8000. The result is part-management textbook, part-thriller.

Futurist Ray Kurzweil’s 1999 book The Age of Spiritual Machines predicted that low-priced computers could match the power of the human mind, and that the difference between man and machine would begin to blur, with positive benefits for humanity. And, in many cases, Kurzweil was correct: several predictions he made for 2020 are materialising today, especially in the areas of artificial intelligence and machine learning.

In Invisible Engines, authors Andrei Hagiu, David S Evans, and Richard L Schmalensee explain that “software platforms are the invisible engines that have created, touched, or transformed nearly every major industry for the past quarter century”. AirBNB owns no real estate; Lyft owns no cars; Facebook, the world’s most popular media company, creates no media. Underlying them are platforms, which “provide enormous value to consumers”, and have created great fortunes. Platforms are driving changes that dwarf the technology revolution we have seen to date. And, though platforms are covered by many writers today, Invisible Engines is my pick.

One of the newer books on my list, Steve Blank and Bob Dorf’s 608-page The Startup Owner’s Manual: The Step-By-Step Guide for Building a Great Company (2012) is included because it’s based on material developed starting over 10 years earlier. Used today by thousands of entrepreneurs, the book is a step-by-step guide to Silicon Valley best practices, which were tested in many organisations. The guide was also validated by the National Science Foundation, and is taught at Stanford, Berkeley, Columbia, and many other universities worldwide.

The Wisdom of Crowds: Why the Many Are Smarter than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nations (2004), by James Surowiecki, explains a big idea that overturns conventional wisdom: mob rule is usually right. If you guess the weight of an ox at a county fair, odds are that you’ll be wrong. But the average of all guesses will often be quite close to the truth. This kind of aggregation of information by groups often leads to better predictions and decisions than those made by individuals, even experts. The Wisdom of Crowds describes several crowd initiatives, including prediction markets, Wikipedia, alternate reality games, and Betfair, the world’s first betting exchange.

Chris Anderson explains in The Long Tail: Why the Future of Business is Selling Less of More (2006) how the infinite “shelf space” of the internet and the efficiency of search engines together allow obscure products to sell in small quantities. While blockbuster items receive the bulk of marketing attention, a larger share of sales for any product category is in the “long tail” of a distribution graph. This translates into a massive profit opportunity for companies, even for products that sell in small quantities. The result for consumers is a new universe of choices, along with improved competition. So businesses based on providing buyers access to the long tail of sellers often prosper through deployment on platforms that centralise scale economies.

Fred Brooks’ 1975 project management classic The Mythical Man-Month: Essays on Software Engineering explains, counter-intuitively, how “adding manpower to a late software project makes it later” – a rule that has come to be known as “Brooks’s law”. Mythical Man-Month is based on the author’s experience at IBM, while managing the development of the OS/360 operating system. Brooks’ project there was falling behind, and things got worse when he added more resources. Brooks also once made the mistake of asserting that one project – writing an ALGOL compiler – would require six months, regardless of the number of workers involved (it required longer). These kinds of errors continue today. Indeed, Brooks once quipped that his book is called “the Bible of software engineering”, because “everybody quotes it, some people read it, and few people go by it”.

Geoffrey Moore, Michael Lewis, Nassim Nicholas Taleb, and Malcolm Gladwell are all prolific tech writers; so it is difficult to pick one book from their many classics. Each one is an outstanding intellect, with an uncanny ability to make connections in ways others cannot.

My favourite Gladwell book is Outliers. In it, he describes a pattern where the common link between many successful people is at least 10,000 hours of practice. For instance, Bill Gates, co-founder of Microsoft, and Bill Joy, co-founder of Sun Microsystems, both wrote software for over 10,000 hours before they undertook their most ambitious creations. This book belies the myth that genius alone, without practice, is enough.

I am fortunate to have met many tech gurus and thought leaders during my time working in Silicon Valley. In particular, I had the opportunity to work with organisational theorist Geoffrey Moore and his team last year. Moore’s 1998 book Crossing the Chasm is mentioned a lot in the halls at work.

The technology adoption cycle is supposed to have five segments: innovators, early adopters, early majority, late majority, and laggards. According to Moore, the marketer should focus on one group of customers at a time, using each group as a base for marketing to the next group. The most difficult step is making the transition between visionaries (early adopters) and pragmatists (early majority). This is the chasm he refers to.

His more recent Zone to Win (2008) is a practical manual to address the challenge that large enterprises face when they seek to add a new line of business to an already established portfolio.

Amazon lists hundreds of books on innovation, but Clayton Christensen’s The Innovator’s Dilemma (1997) stands out. It makes a counter-intuitive point – that listening to customers too often can cause executives to misread the market. Too many are afraid to disrupt their own products, and so they are disrupted instead. According to Christensen, you need “disruptive innovation” to stay ahead; otherwise, if you keep improving your products routinely, you may miss the boat when a new technology comes along.

Michael Lewis is an incredible storyteller – he can make complex topics look simple. It is hard to choose just one of his books for my list, but let me recommend two. The Big Short tracks the mavericks who bet against the market and made massive profits from the financial meltdown of 2008-09. Moneyball is about how an American baseball team used rigorous statistical analytical tools to get much better results, given its tight budgets. Both books are those rare birds: highly entertaining yet classic stories that teach important lessons about technology and how it interacts with society.

Machine learning and artificial intelligence are important technologies that are the subject of much interest today. There are many academic books on these topics, but hardly any that can be read by a layman looking to maximise the technologies’ value for their organisation. When I asked my friend and machine learning guru, Lorien Pratt (author of Learning to Learn), if there is any easy-to-read book on machine learning, her response was, “Nope, sorry. That’s the one I’m writing.”

I invite you to check out these important works. I hope you find, as do I, that they speak to each other, and to your own experience.

Together, these titles weave a cloth of ideas that are critical for navigating technology towards maximum value to humanity in the twenty-first century.