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Peter Senge has been called the most influential business strategists of the century and in my view Senge is the successor of Peter Drucker, the management visionary. Senge published a book in 1990 called The Fifth Discipline which I think every manager, founder and CEO should read.

Great companies transcend their great products. Not defined by one product, these companies adapt, innovate and reinvent. They learn continuously to succeed as their environment changes. Senge’s book teases apart the five essential components to building a learning organization.

The Verge profiled Google Now, Google’s newest search technology which uses “predictive” queries to show users the information they want to see, before users ask.

In a single app, the company has combined its latest technologies: voice search that understands speech like a human brain, knowledge of real-world entities, a (somewhat creepy) understanding of who and where you are, and most of all its expertise at ranking information. Google has taken all of that and turned it into an interesting and sometimes useful feature, but if you look closely you can see that it’s more than just a feature, it’s a beta test for the future.

Over the last six months, I’ve been delving deeply into R, linear regressions and machine learning. Part of the rationale has been to remember some of the concepts I learned in grad school studying signal processing.

But a more important driver has been the need to better understand how to qualify, evaluate and hire data scientists because data science is a massive competitive advantage. And many of the companies I work with are hiring data scientists.

Last week, a close friend, who is a product manager/designer, told me he’s starting a company. He asked me where I thought the biggest opportunity lay given his skills and his passions. He’s incredibly capable and driven, but he hasn’t yet found the right place to apply his energy. My friend is in search of a problem to solve. He’s in the right place. After all:

“The essence of a startup lies in the process of discovering a problem shared by many people and trying to solve it.”.

When I walk into a bank today, I might deposit my cash in exchange for some interest rate. The interest rate is my cut of the profits the bank made on my deposit through their trading and lending activities. The more assets under management, the more money a bank can make on its own account.

Like banks, web companies are in the business of maximizing gigabytes of user data under management.

I met the Electric Imp team in April. I had bumped into one of their engineers at a party and he pinged me a few weeks later to say he was working for a startup and the company was raising. The company came in to the office on a Monday at noon.

Hugo, the founder, Electric Imp demoed their product to me. Ten minutes in, I stopped the pitch meeting, pulled 3 partners from their Monday partner meeting, and issued a term sheet that afternoon. The demo was just that compelling.

Examining a user’s motivations at the entry point of every major feature in a product and matching the product to this motivation is key to building a great product users love.

BJ Fogg’s Behavior Model Theory is a succinct summary of this idea in a formula:

Motivation + Trigger + Ability = Behavior

This model says that a user will perform a behavior when given the means, the motive, and the opportunity. The user brings motivation, but it’s the responsibility of the product to trigger a behavior and offer an intuitive experience to complete it.

It’s tempting to burrow within a garage or basement or apartment to develop a product for several months and emerge from the darkness with a new shiny product. But the launch will likely fall flat.

Products must be launched into ecosystems, in particular, into receptive ecosystems. In my view, there are three types of ecosystems that startups should cultivate. These ecosystems provide distribution leverage - that’s what makes them so powerful and so essential at the start of a company.

Every social service aims to achieve massive growth and deep engagement. But if forced to choose just one of these attributes, I would pick engagement every time. An active user base implies product/user fit for a social service.

Aside from the core functionality of social services, which is a solved problem (profiles, messaging, feed), the essence of a social startup is culture - the values of the community, the mores, the manners of interaction. The right culture attracts users, encourages participation and drives growth.

Freemium businesses' marketing techniques are immensely powerful. They drive large amounts of users to try a product and convert some small fraction of those to paid, upending the enterprise sales model.

In some sense, freemium businesses are real world Monte Carlo simulations. Because of the large volume of users using the product, freemium businesses can generates gigabytes of interaction data and conversion-to-paid data, which makes these kinds of startups particularly well suited to data science, A/B testing and regression analysis.