Tagged: start-ups
De-emphasize Age, Refocus on Play
In response to the TechCrunch article, “Silicon Valley’s dark Secret: It’s All About Age“…
I once started a company called HotSwap as the CTO with some of the brightest minds from Berkeley, MIT, and Stanford (including some ACM world finalists). We had a lot going for us — press, partnerships, an amazing platform, Steve Wozniak as our advisor. However, we were young and lacked the business acumen to run a profitable start-up, let alone a proper business model. For many reasons, we had to ultimately close down the company and I had to resign. As young entrepreneurs, we wanted to work on something “cool” as opposed to something that was like a “business.” More recently, I worked with some older Yahoo veterans (Senior VPs and such) who were very experienced in the field. Truth be told, they were just as clueless as we were with our first start-up, and they didn’t quite understand what really mattered (though with more funding, we all had more time to learn it). Until we discover the secret to success, everyone is like a poisoned ant running around in circles with no apparent direction.
From these two experiences, I learned that entrepreneurs are much better equipped after their first venture and specific experiences are a much better predictor than age.
Psychology suggests that there are two components of general intelligence, fluid and crystallized intelligence. Fluid intelligence is the ability to “think logically and solve problems in novel situations independent of acquired knowledge”. Crystalized intelligence is the ability to “use skills, knowledge and experience” to solve problems, usually those dependent on acquired knowledge. Fluid intelligence generally peaks at the age 25 and then steadily declines while crystalized intelligence increases gradually until age 65.
So then, we must ask ourselves, is building a start-up primarily about fluid, crystalized intelligence, or both? According to the Founder Institute’s entrepreneur test, “openness and fluid intelligence are the key factors” predicting success. Yet, Founder’s also found that the older the entrepreneur is, the better he generally performed when fluid intelligence was taken into account — age was not the best predictor.
Play: How it Shapes the Brain, Opens the imagination, and Invigorates the Soul by Stuart Brown and Christopher Vaughan talks about how play is vital to brain development. They found that employees who have engaged in play throughout their lives outside of work and bring that emotion to the office are able to do well at work-related tasks that at first might seem to have no connection to play. In one case study, even though JPL hired top graduates from top engineering schools like MIT, Stanford, and even Cal Tech itself, the new hires were often missing something. JPL found that “newly minted engineers didn’t do well with taking a complex project from theory to practice”. They had found that the older, problem-solving employees had taken apart clocks to see how they worked, made soapbox derby races, built hi-fi steroes, fixed appliances… during their youth. The young engineering school graduates who had also tinkered around with gadgets were adept at the types of problem solving management sought. Those who hadn’t, generally were not. From that point on, JPL asked questions about applicants’ youthful projects and play during job inteviews.
Contrastingly, these older employees had a higher fluid intelligence than their younger peers, even though fluid intelligence generally diminishes with age. Silicon Valley should soon realize that the unqualified young engineers from top engineering schools are not performing well due to the lack of play, the cultivation of fluid intelligence — not age. Perhaps people are learning to take this information into account, which is probably why YCombinator seems to have an admission process based on the “youthful projects” of applicants. This also means that there is a large chance that fluid intelligence can be altered to improve performance, or that people who have side projects have high fluid intelligence, making it easy to filter out such individuals.
With this knowledge in mind, I am bootstrapping a start-up with very “intelligent” people, a solid business model, and people who have experienced prior start-ups — and my head hurts much less these days.
Thoughts on Domain Acquisition and Branding using AI
Creating a good brand is one of the hardest tasks of an entrepreneur. Aaron Patzer, CEO of Mint, stated that you should “expect to pay $3 to 15k for a 6-8 letter, single word, English domain name.” In fact, he paid $180,000 in equity for “mint.com”, which took over three months of negotiation. A domain name should be spelled unambiguously to prevent losing word-of-mouth referrals. Sean Cheyene of Herbal Ecstasy believes that brand is everything. Without the brand name, it would have been nearly impossible to create a $350 million dollar company from selling a plastic baggy with herbal pills — with no reputation and money.
Today, there are 88,312,535 million top-level “.com” domain names registered, which makes it difficult to purchase a domain like “efax.com”. (To put this in perspective, Webster’s Unabridged Dictionary has 475,000 words.) Thus, any combination of existing words we come up with for a “.com” domain name will probably be taken. We can browse existing domain names for sale at sites like BrandBucket, where they have “brandable business names and unique domain names”. However, a domain name like “Zables.com” goes for $5,000 and I am still not happy with that name. Perhaps then, a good indicator is to look at expiring domains, which I can try to bid for — for only $69.
I recently stumbled upon Namejet, which receives over 16,000 soon-to-expire domain names per day. I can bid on these domains, although it’s difficult to navigate through the list and find a good name, thanks to it being filled with domains like sxwzjhxx.com. Also, we have biased and limited searching capabilities. For example, if I am looking for a real-estate domain, I would try all possible combinations of keywords related to real-estate (as would every other person building a real-estate website) — then find that the names that I’m interested in are overpriced and difficult to win.
Since a company’s success can greatly increase from a good domain name (think Mint vs. Geezeo), I decided to use my machine learning knowledge and build a predictor to determine the probability that a given domain name resembles an English word: P(w=domain_name). After downloading then sorting 340,000 domains with a “score”, I found reasonable domain names with ease: flipcast, drawmash, idealix, shopvolt, swerp, raideye, geekleaf, wirednut, moccah…just to name a few. (I computed the probability score using n-gram letters. If the first 3+ letters of the domain matched the dictionary (e.g. shop in shopvolt), then the probability for that section of the domain is set to 1.0 to handle transitions such as “pv”, which are not found in the English dictionary.)
While it’s still difficult to find a domain name for a specific product, I just found meaningful domain names for a streaming video website (Flipcast), a creative company (Drawmash), a gaming company (Raideye), a shopping CSE (Shopvolt), and some new blogs (Geekleaf, Wirednut). Win.











