Your best option is to be the best

"People overvalue optionality. It’s one thing I learned in chess. You just need to have one good option, instead of going for Option A or B or C or D." - Peter Thiel

There's a peculiar tradeoff we all must constantly make between keeping our options open and focusing very hard on one thing. From our earliest days in school we are told to make decisions that don't close any doors, and this sentiment generally sticks with people for a long time.

America's education system promotes liberal arts degrees for a huge part of the population, keeping us like generic stem cells until we are 22. Our international counterparts tend to begin differentiating at 18 when they graduate high school. Professionally, the country's top students seem to have an insatiable demand for banking and consulting jobs, which are valuable in large part because of the opportunities they lead to (industry, private equity, business school).

The urge to not close any doors and keep one's options open for as long as possible - to diversify  - is understandable. If you give yourself lots of chances to succeed, you'll be more likely to succeed, right?

At first blush this makes sense, but I think there is good reason to avoid taking this approach.

First is the superstar effect, which says there are huge gains to be had as you approach the top of a field. In a highly differentiated world, it's more valuable to have deep expertise in one or two areas than general proficiency in five or six.

Second is the counterintuitive truth that the best way to open lots of doors is to do one thing really well. The most successful people in the world have such strong operating leverage that they are able to get meaningfully involved in any endeavor they choose. They almost all got there by being extremely focused and good at one thing.

Naturally, the way I most often think about this tradeoff is with startups. When building a company, founders have a choice about how to handle the tradeoff between focus and optionality. Normally, the best startups look for one very good option and then find ways to make that happen. It's surprising how often I hear founders say they aren't sure what their business will look like yet, but they have lots of great options so something will probably work out.

Remember that on some level you can only do one thing at a time; it's better to get offers from your first choice job or school than your second through fifth choices. It's also normally better to be in the 99th percentile in one thing than the 90th percentile in two or the 80th percentile in three.

If there are free options you can layer into your life without losing focus you should take them; I'm not saying you should intentionally pigeonhole yourself. Instead, I'm trying to be a tugging force toward focus since I think people typically overvalue optionality and end up on the wrong side of the optimal balance. 

Should we do more to incentivize open source?

Open source is a fascinating phenomenon in the world of technology; there is an enormous wealth of software that is entirely public. Brilliant coders have poured countless hours of work into complex projects and then, instead of protecting their valuable intellectual property, released it publicly to the world, often for free.

Open source products fuel the modern internet

Many of the most powerful and widely used tools are open source, including languages like Ruby and Python, frameworks like Rails and Django, cloud application platforms like Heroku, operating systems like Linux, and web browsers like Mozilla Firefox.

Open source doesn't necessarily mean free (although it often is); it means the source code is available to the public so that anyone can look at it, use it, and contribute to it.

So today, when a new developer enters the startup scene, he is immediately perched onto the shoulders of giants. He gets to use Ruby thanks to Yukihiro Matsumoto, Git thanks to Linus Torvalds, jQuery thanks to John Resig, and the list goes on. The new programmer has only to stand on his metaphorical tip toes to produce awesome pieces of software. Meanwhile, these influential open source contributors get no direct compensation.

The power of open source

Collaboration is one of the most powerful forces allowing civilizations to undergo technological progress. Look around a city; skyscrapers are amazing. We built them with materials from the Earth and machines that we built with tools that we built with our bare hands. How did we accomplish this incredible undertaking? Wide-spread sharing of knowledge and collaboration over hundreds of years.

In software, open source is a powerful part of the community that drives significant innovation. Contributors can submit patches to current codebases or add large pieces of functionality. Future early adopters of the software can give feedback in real-time during the development, giving the authors of the code a significant advantage. Once the code is finished (not that code is ever finished), it is available to the entire world, and they can customize the software as they see fit. Open source also protects against product discontinuation (which would have been nice for Google Reader).

So why do people contribute to open source?

It goes without saying that open source has huge benefits in terms of production, distribution, and maintenance. But isn't it surprising that accomplished developers spend their valuable time writing and pushing free code out to the internets?

Despite the fact that open source contributors typically don't enjoy any direct gain, there are fortunately several incentives that encourage individuals and corporations to contribute to the canon of open source. Coders build an online presence that helps them get jobs, start companies, or other generally productive things. Companies can get feedback on their software and build relationships with great developers to attract as hiring talent. Best of all, the programming community is still small enough that it feels a sense of camaraderie and desire to "give back", such that a lot of contributions may really be altruistic.

Despite what some of its most fervent supports will tell you, open source has some downsides. Version control can get unwieldy and confusing for users. Projects can fall apart when a key developer moves on. Support systems are tenuous because no one is paid to help you when you have problems. And perhaps most importantly of all, individuals and businesses may feel less willing to take risks with early versions of products if they're worried that the whole world will scrutinize them, or worse, that their competitors will steal from them.

What is the optimal amount of open source software?

Consider two extremes: at one end, 100% of the code in the world is private, and developers must intentionally share their code with others for it to be seen. At the other, 100% of code is public, and any code anyone writes is immediately part of the public domain.

The world of software today is somewhere in the middle, which is definitely where we want it, but have we struck the optimal balance? While there is a incredible set of tools available through the open source community, most of the world's software is still private.

The deeper I get into coding, the more I see the power of open source software. I think it's likely that we would all be better off with more of it. The drawbacks seem to pale in comparison into the opportunity for widespread, real-time, mass human collaboration, both in theory and in practice.

We're lucky that enough natural incentives are in place to generate the robust open source community we have, but I imagine more could be done. Platforms like Gittip are a nice way to give financial incentives directly to top open source contributors; as you would expect, data suggests that 10% of the world's open source authors have written about three quarters of the open source code.

Incentivizing open source behavior is tricky; the community is functioning very well as it stands, and it seems likely that there would be a strong backlash to incentive structures that were too anathema to the spirit of the community. However, if someone were creative enough to figure out how to encourage the behavior in an appropriate way, the benefits would be immense.

Although building a company on the heels of the open source community flies in the face of the its spirit, I wouldn't be surprised if we see a more formalized platform spring up to incentivize programmers to develop more software in open source. I hope we do; I think we would all be better off.

Optimize for success, not equity

Nothing in tech feels like more of a bubble than YC demo day. While the average seed deal in 2012 was valued at around $6 million, YC deals are routinely two or three times that expensive.

Hyper-expensive deals are a problem, but not so much so for investors. YC companies could easily be two or three times as likely to be successful as average startups, and as long as investors pick the good startups, they will do well regardless of the terms. YC has not yet proven to be a bubble; investors have done very well with these deals.

Instead, the main losers from these inflated valuations are the startup founders. Raising a seed round at a high valuation when you have relatively little traction is risky and damaging, and is generally done for the wrong reasons. Here are the main problems I've seen startups run into when they raise money at very high valuations.

Raising subsequent rounds gets much more difficult

You can usually only raise money on a promise once, and your seed round is the time to do it. This is your opportunity to partner with investors who want to invest in your team, your product, and your market. Investors will give you an implied valuation of millions of dollars in spite of the fact that little to no money is coming into your company.

The next round is not as forgiving. Series A investors do much deeper diligence on your revenues, operational costs, market potential, and key metrics, and they want to invest at a price that is (somewhat) grounded in reality. If you can't show investors serious traction 18 months after your seed round when you run out of money, you will get into trouble. You run the risk of raising a down round at a lower valuation (which brings on all kinds of problems), or not being able to raise more money at all.

Lower quality investors

Top tier investors often pay premiums to invest in good companies because they are actually very good. However, when a given startup artificially inflates its pricing relative to what it should be, it often ends up pushing out those high quality investors who know a good deal when they see one.

Another unfortunate consequence is that the investors you do get will be lower quality to you than they would be had you given them a better price. Because they will own a smaller stake in your company and feel less invested, they will be less incentivized to help you.

Waste of time

This is a really important one. Despite how it often seems, a startup CEO's main job is not actually to raise money; it's to lead the company to success. Fundraising is distracting from the important working of building a business, and should be done as quickly as possible.

When founders decide to raise at an obscene valuation, they can spend several weeks or months speaking to investors, and worse, all of their cognitive focus and emotional energy. Picking a reasonable valuation allows you get investors much more quickly so you can get back to building your business.

Some math

Just to drive home how insignificant the seed valuation of a startup is to the founders, here's a quick example.

If a startup raises a million dollars on a $4mm cap convertible note, it gives away 20%; if it raises a million on a $9mm cap note, it gives away 10%. For a founder who owns 30% of the company, we are talking about a difference between diluting down to 24% vs. 27%. *It just won't matter.* There will be a bigger variance in your eventual exit price based on the whims of your acquirer's M&A team that day, so forget about the equity.

Founders aim for high valuations so they can raise more money, suffer less dilution, and enjoy the internal satisfaction (or external competition with other founders) of running a valuable business.

Here is my advice: Founders, your outcome is binary. Either your startup will be a success and make you rich or it won't. Don't optimize for equity, optimize for success. 

Startup knowledge decays quickly

Consider a young high school couple. Odds are they won't get married; maybe the odds are 5%. If you have to bet whether they will get married or not, you'll make money in the long run by betting that they won't. However, if you have to bet on the single most likely person in the world for either of them to marry, their current partner is surely your best bet.

The same is true for knowledge. Paradoxically, even though we can safely predict that any given piece of knowledge will eventually be overturned or rendered obsolete, we can be almost sure that any given piece of knowledge is our current best bet.

Knowledge has a half-life

I recently read Ronald Bailey's article on Samuel Arbesman's book, The Half-Life of Facts: Why Everything We Know Has an Expiration Date and was sufficiently taken by the idea that I bought and read the book. The idea is a compelling one: just like half the amount of a radioactive element will decay during its half-life, in practically any field of knowledge, half of what we know will be replaced after some predictable amount of time.

In this post, "knowledge" refers both to facts that change over time or are proven wrong, and conventional wisdom or best-practices that are overturned.

Consider the following knowledge that was at one point considered true:

The Sun orbits the Earth. DNA has 48 chromosomes. Cigarettes are not bad for you. There is a dinosaur called the Brontosaurus. Red wine is bad for you. I mean good for you. I mean bad for you.

What gives one body of knowledge a shorter half-life than another?

I would argue there are four main characteristics that give a body of knowledge a short half-life.
  • The field is young and poorly-understood.
  • There is a limited amount of data from which to draw conclusions.
  • The knowledge is difficult to test and variables are hard to isolate.
  • The knowledge is more best-practice than fact.

Modern medicine has been around for less than a couple hundred years, the knowledge is part of a chaotic system where variable isolation is often impossible, and much of the knowledge is best-practices for treatment rather than provable facts. Medical knowledge can have a half-life as short as 10 years.

Nuclear and plasma physics are even less mature and well-understood, the data is hard to collect, and complicated conclusions are more often deduced than observed. For these fields, the half-life of knowledge is only 5 years.

This lead me to wonder: how does startup knowledge stack up? Probably not very well.

The half-life for startup knowledge must be very short

The startup industry in its current form is relatively young and poorly understood. Compared to other fields, there is a small amount of data about cause and effects for startups. What's worse, the data exists in an incredibly chaotic system where isolating individual variables is often impossible.

In other words, most of today's startups knowledge is probably wrong.

There are two type of startup knowledge that I'm talking about here, which I would describe as startup facts and startup wisdom.

Startup facts are just that; cold hard facts that are relevant to startups. These can lose their relevance because they are either proven untrue, or more likely, because they change over time. Examples of startup facts include:

Price of data storage. Number of people that own mobile devices. Government regulations.

Startup wisdom refers to generally accepted knowledge about what startups should do to succeed, a set of best-practices analogous to the generally accepted treatment methods in medicine. Current examples of this include:

Fail fast and iterate. Raise 12-18 months worth of runway. It's easier to enter an existing market than create a new one.

How likely does it seem that all of these insights will stand the test of time? The odds are pretty low.

All startup knowledge is susceptible to a half-life decay, and is turning over at a rapid pace. Although there will never be unanimously accepted best-practices for startups, consensus changes at a rapid pace. Similarly, trends like Moore's law and global mobile penetration are rapidly making yesterday's knowledge obsolete.

If today's startup knowledge will be obsolete tomorrow, how should founders proceed?

I think there are at least two takeaways from these (far from perfect) thoughts:

1) Founders should realize that the startup industry is immature and constantly-changing, the knowledge tends to be more best-practice than fact, the data exists in a chaotic environment and variables that are difficult to isolate. In short, founders should realize that the half-life of startup knowledge is short.

Of course, just like the high school couple, today's knowledge still represents the best guesses we currently have. Even though we know it's more likely than not that any given piece of current knowledge will ultimately be supplanted, this is still where we should place our bets unless we know otherwise. However, founders should never be afraid to challenge assumptions, because odds are the assumptions will turn out wrong.

2) Perhaps even more interestingly, it follows that good ideas for new startups may be found at the place where knowledge is overturned. Peter Thiel effectively made this point when discussing the idea of secrets at Stanford; startup ideas may exist where you believe a truth that most people do not.

As data storage became cheaper and security improved, Box gambled that enterprise companies would keep their data in the cloud. HelloSign bet that e-signatures could work. Founders should try to see around corners to anticipate what knowledge today will be obsolete tomorrow, and find their place accordingly.