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If you’re a Netflix subscriber, in all likelihood you’re a big fan of “House of Cards.” Netflix designed it that way.

With the release of “House of Cards” Netflix began the Moneyball-era of content production. The majority of Netflix subscribers watch Kevin Spacey, political thrillers and David Fincher’s movies. Guess what? “House of Cards” has all three.

In baseball, on-base percentage is the best predictive metric for team success. In content production, the best predictor is user viewership behavior.

When interviewing product managers at Google, we ranked candidates on four metrics: technical ability, communication skills, intellect and Googliness. A Googley person embodies the values of the company - a willingness to help others, an upbeat attitude, a passion for the company, and the most important, humility.

In the past week, I asked two heads of engineering to identify the most important characteristic in new hires. Both responded, “humility”. For one startup ascertaining humility is so important, it is the first filter in the interview process.

Kenny Van Zant is a marketing wizard. Before his current role at Asana, Kenny managed products and marketing for Solarwinds, a publicly traded company that sells networking equipment to the mid-market. Solarwinds pioneered the low-friction, high-velocity sales model in their segment to great success.

SolarWinds offered free products to their customers to gain usage data that informs their sales and marketing efforts. As one might expect, inside sales reps would call upon the most likely customers to up-sell them to paid. And of course, SolarWinds employed the enterprise sales team to win the business of the largest customers. Plain vanilla freemium, right?

David Brooks has a great op-ed this morning on the Philosophy of Data. He argues that data offers one major advantage and one major drawback. Data enables humans to discover patterns otherwise unobservable by our senses/intuition or patterns that violate human intuition. But the religion of data engenders a fallacy: that everything can and should be measured; and with this data, the best answer will emerge.

Belief in the power of data has become a sort of religious debate which has manifested itself in product design (data driven vs intuitive design), in politics, in baseball, in climate change debates and many others. At some level, it’s an extension of the religion/ science debate: what I feel/believe vs what my instruments indicate. Which is better?

With a litany of articles in recent months highlighting the number of companies with valuations greater than $1B, I’ve started to wonder about the valuation trends for the highest profile venture backed companies.

Venture capitalists are increasing market prices in Series A and Series B rounds aggressively in effort to reap disproportionate returns. And the variances in the prices of different startups in these early rounds is enormous, indicating a relatively inelastic market. Investors are chasing fast-growth startups irrespective of the price.

Even the greatest minds fear missing out. Nobel laureate Richard Feynman who assisted in the development of the atomic bomb, contributed substantial advances to quantum mechanics and particle physics, discovered the cause of the Challenger Shuttle disaster and popularized science as a witty and successful author, faced this fear when confronted with a menu.

How many different dishes should he order from a menu before settling upon a favorite? Feynman used probability theory to solve the problem. Below is the formula he developed with Ralph Leighton

The most important principle of start up fund raising is:

Raise enough money to achieve a set of milestones that will attract a subsequent round of investment from new investors.

Last week, a founder of a seed stage company came to pitch. When I told him the opportunity wasn’t a fit for us, he asked me what milestones he would need to achieve to raise a Series A - as he was raising a seed round! He was calibrating how much he needed to raise for in his seed to make sure he could raise a Series A.

Brokers serve two key roles within ecosystems. First, they introduce buyers and sellers. Second, they lend their expertise to help buyers and sellers make the right decisions in the market.

The internet neutralizes the first value proposition of brokers by leveling the information asymmetry between buyers and sellers at a far greater scale with much better data than any broker ever could. And for products and services with relatively small price points, commodity goods or where the cost of failure is low, market places often nullify the value (and cost) of an advisor.

Once each month I met Peter at Café Habana in Nolita for huevos rancheros drenched in tomato sauce and a glass of fresh orange juice. Mopping up yolks with tortillas, Peter and I chatted about his business: the techniques of scalable customer acquisition, the priorities of the product and engineering team, the structure of sales quotas and the ebbing and flowing dynamics of the market place he and his team were building.

Each time I open Salesforce in my browser, I think of Stephen Hawking. It’s because of an aphorism an entrepreneur shared with me a few weeks ago. He said:

The cost to fix a data error at the time of entry is $1. The cost to fix it an hour after it’s been entered is $10. And the cost to fix it several months later is $100+.

Take for example a venture capitalist’s CRM tool. If I mistype an email address or the details of the last fund raise, it might cost me a minute or two to fix it at that very moment. A minute of time is worth about $1.