Software Engineering Daily

Tim O’Reilly’s book What’s the Future? is an overview of business, technology, and society. As the founder of O’Reilly Media, Tim has been steeped in technology trends for the last 40 years. From his vantage point running conferences and publishing technical content, Tim has been able to make informed predictions about what is coming next.

In today’s conversation, Tim gave his perspective on how artificial intelligence will impact our world in the coming decades. More importantly–Tim emphasizes the role of human agency. The future is not something that merely happens to us as we sit back and eat popcorn. Today, we make decisions, and those decisions that we make could help lead us to a technology utopia or towards the fall of our great technological empire.

On the subject of business, Tim gave a radically different perspective than most of the entrepreneurs that come on Software Engineering Daily. In our conversation, he raised the question of why entrepreneurs raise massive amounts of money, get on the treadmill of startup hype, and build a company around negative cash flows. For that model, the only possible outcomes are going public, being acquired, or flaming out completely. O’Reilly Media has been cash-flow positive since the beginning, and the company has steadily compounded, growing successively bigger businesses from publishing to conferences to online learning.

This episode gave me a lot to think about–just as the O’Reilly Conferences have throughout the years. O’Reilly Media has graciously partnered with SE Daily since we were very small, so I have great admiration for the company and Tim himself. It was a pleasure to get the chance to meet him in person.

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Computer systems consume memory, CPU, battery, data, and network bandwidth as inputs. These systems provide value for the end user by delivering information, virtual objects, and physical products as outputs. Another fundamental resource that is becoming easier to consume as input is money. There are also new outputs–financial constructs that are made possible by cloud computing, machine learning, and cryptocurrencies.

This is why so much opportunity exists in fintech. Money has always been a flexible tool for brokerage between humans. But as recently as the early 2000s, the interfaces between money and computers have been clunky and inflexible. Engineers that wanted to build financial systems around money had to work directly with banks and credit card processors.

More recently, there has been an explosion in new APIs and completely new financial primitives like cryptocurrencies. In the year 2000, a well-funded team had to struggle to put together a basic ecommerce company. Today, a blue ocean of opportunity has opened up for entrepreneurs building businesses around lending, insurance, underwriting, banking, and every other microcosm of the financial system.

Michael Walsh is a general partner and co-founder of Green Visor Capital. In today’s episode, he described his perspective on the modern fintech environment, and what the future holds.

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Investing is an infinite game.

In a game, a player can formulate a strategy based on the available resources, the apparent variance of the environment, and the metagame of the other actors involved. For an investor, the game board includes companies, currencies, and people.

A successful game player can model their actions mathematically. They can describe a thesis for an in-game decision with clear language. Game players who reason through “gut feeling” do not perform well (unless their “gut” is aligned with correct mathematical heuristics). The same is true for investors. An investor who is going to be successful in the long term will be able to explain their investment thesis crisply.

Each investment represents a bet with the net positive expected value. The expected value of an investment is the sum of all potential probability-weighted future outcomes of a business. Each of those potential expected outcomes is the anticipated outcome times the probability that the investment works out in an anticipated way.

Brian Singerman is a computer scientist and partner at Founder’s Fund. He is on the board of Affirm, AltSchool, Emerald Therapeutics, and a variety of other companies in disparate areas. He also plays lots of board games. Brian was a lot of fun to talk to because he was willing to field questions from an expansive range of topics–and he answered them so quickly and concisely that I started to get nervous that I was going to run out of things to ask him.

Many of the businesses Brian has invested in do not have a well-defined historical precedent. If a venture capital investor was trying to make bets in defined “sectors” that investor would probably overlook a business like Forward (a vertically integrated healthcare company) or Cloud9 (a collection of esports teams).

If an investment does not have a historical precedent, it’s harder to reason about it by analogy. You have to judge it by fundamental reasoning: the current market, the capability of the founders, and the economics of the business model.

In many professions, reasoning by analogy will work out perfectly fine. You can pattern match on the past, and use that to justify decisions for the future. But if your professional livelihood depends on reasoning by fundamental principles, you get trained to assess situations that do not have precedent.

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Self-driving, electric cars will someday outnumber traditional automobiles on the road. As transportation becomes autonomous, it is hard to imagine an industry that will not be affected by the downstream effects of this change.

These cars will likely be managed by fleet operators like Lyft and Uber. We will need fewer cars, and the amount of space dedicated to those cars will shrink dramatically. Parking lots, massive roads, and gas stations will be reclaimed or repurposed. City planning departments will have to devise entirely new strategies.

As the self-driving cars reach consumer availability, an intricate supply chain for these cars will develop. When smartphones became mass-produced, the costs of GPS devices, accelerometers, and other small components dropped steeply. A consequence of the smartphone supply chain was that other devices like consumer drones became affordable. The self-driving car supply chain will lead to the mass production of building blocks for other new devices.

With fewer automotive fatalities, the economics of the car insurance industry might collapse completely. At a minimum, the costs of car insurance will likely shift to the fleet operators, who can purchase that car insurance at prices factoring in their large risk pool.

Frank Chen is a deal and research partner with Andreessen Horowitz. In a series of presentations on the Autonomy Ecosystem, Frank explores the effects of our impending shift to self-driving electric cars. His analysis considers changes to energy infrastructure, the competitive landscape of software companies, and a range of other topics. Frank joins the show to discuss autonomous vehicles and the side effects of widespread autonomous deployments.

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The world of software moves faster than the laws that regulate it. When software companies do get regulated, that regulation is often enforced unevenly among different companies.

Software continually presents the legal system with new requirements. Consumer data privacy needs to be enforced on a granular level. Software developers need a system of protecting their intellectual property. When a company becomes dominant, our legal system needs to scrutinize that company for potential antitrust violations.

Micah Kesselman is a lawyer specializing in software IP prosecution. Prior to becoming a lawyer, he studied computer science. He joins the show to discuss a range of issues at the intersection of software and the law–including GDPR, software patents, and self-driving cars.

These are topics we will cover in more detail in the future, but it was great to have Micah bring the perspective of a lawyer to the show.

Massachusetts Autonomous Vehicles Working Group

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