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I am most grateful for my work experiences that were apprenticeships. Whether it was Philip who taught me how to write a proper Java function (10 lines or less), or Kim and Scott who are great managers, or the partners at Redpoint who invested a huge amount of time to educate me, those collections of experiences have taught me far more than I could’ve expected.

Worklife is nuanced. Reading a blog article here or in HBR article there, a business book or an academic paper only goes so far because these summaries of knowledge lack one key ingredient. Judgment.

The New Zealand All Blacks are the most successful athletic team perhaps of all time. A rugby outfit whose name originates from the solid black uniforms, they have won 79% of their international matches spanning 68 years. James Kerr followed the All Blacks, interviewed them and distilled his learnings into a book, Legacy. Kerr organizes the book into 15 life lessons, three of which stood out to me.

Humility is the first. After each match, the All Blacks, among the greatest rugby players in the world, sweep up after themselves. They clean up their locker room after all the celebration of a victory or the disappointment of defeat.

What could be more natural than a marketer selling a product to other marketers? Or an engineer pushing a new devops tool to other developers? Or a customer success person pitching CS tools? After all, they both speak the same language, come from the same domain, will develop trust quickly. Consequently, they will sell faster and more efficiently. This might seem like a very logical argument for differentiating on sales processes, but it’s a fallacy.

We’ve entered an era when computers can understand speech, computers can synthesize speech, computers can develop music, author encryption algorithms, create novel art, respond to customer support questions, and even generate new summaries and reports from data. Increasingly, humans will struggle to distinguish between computer-generated and human generated. Consequently, here’s an opportunity for startups to lead, not just technologically, but more broadly.

DT is a creative digital agency business based in Australia that developed a prototype that distinguishes between human speech and synthetic speech. Shaped like a hearing aid, the Anti AI AI chills the listener behind the ear using a Peltier device when the onboard TensorFlow model detects computer-generated speech. It’s one of undoubtedly many technologies which will use one machine learning model to detect another machine learning model.

When I was taught Michael Porter’s value chain analysis, I learned to analyze at the industry level. A beer supplier sells to wholesaler sells to distributor sales to retailers sells to customer. But as I went back last night and reread Porter’s Competitive Strategy, I was surprised to learn that Porter’s intended value chain analysis to be used also at the business unit and at the company level.

The more interesting of the two for startups is the company level. A value chain analysis of the company level aims to determine the primary focus/competitive advantage of each company within a space. In order to be successful, startups have to be good at many things. But most of the time, they are exceptional at one thing.

In January 2010, Andrew Parker wrote a post called the Spawn of Craigslist. Andrew identified companies that had built businesses by unbundling Craigslist. The vacation rentals link gave rise to AirBnB and HomeAway. Etsy dominated the arts and crafts for sale. This same unbundling is occurring to Excel.

Microsoft Office has more than 1 billion users globally. Assuming a 33% penetration of Excel, that’s a user population 300M users. Like Craigslist in the consumer world, Excel became the tool for nearly everyone to get stuff done at work.

In Bias Against Creativity, a team of researchers at Cornell discuss the bias against creativity they revealed in their study. Originally published in 2010, the article resurfaced yesterday on Hacker News. It raises the question of how to evaluate creative ideas and how to engender internal incentives to support creativity.

From the Cornell paper:

People often reject creative ideas even when espousing creativity as a desired goal. To explain this paradox, we propose that people can hold a bias against creativity that is not necessarily overt, and which is activated when people experience a motivation to reduce uncertainty.

As the number of SaaS applications has exploded, the SaaS ecosystem is responding to data fragmentation with middleware. This isn’t the middleware of the early 2000s, which was focused on helping developers build software. This is middleware that is focused on helping end-users unify data from the vast numbers of data repositories now existent.

Ten years ago, sales teams captured basic data on customers and prospects. Names, addresses, budget, time frame. All of it collected over the phone.

How much revenue do you want to book for your SaaS startup next quarter? And in 12 months? It is one thing to put a number down on the financial plan. It’s another thing altogether to have the sales team staffed to close that amount of business.

The bookings capacity of the business is the amount of business a sales team should book in a certain period. Bookings capacity is calculated as:

In January, I wrote The Hardest Round to Raise which argued Series B rounds would be the most challenging early stage round in 2017. Irrespective of the annual vicissitudes of the fundraising market, Series Bs are always the most challenging rounds to raise because they are in-between rounds. The Series B is the pimpled and gangly adolescent phase of startup evolution.

If the aim of every round of venture funding is to prove a hypothesis - which I believe is true in Series Seed, A and B - then the Series B is the last milestone before proving cash is the business’ limiting factor.