Companies often use A/B testing to optimize their websites, but they rarely use it for anything else. This is a wasted opportunity. It turns out that if you capture enough data, any repeated, measurable activity can be framed as an A/B test. For example, how does breakfast affect your morning work productivity? If you spend a month or two tracking your productivity along with the breakfast meals that you eat, you'll quickly learn if skipping breakfast turns you into a zombie or if having eggs instead of pancakes will help you get a promotion.
Once you internalize the idea that anything you repeat can be an A/B test, you starting seeing optimization opportunities everywhere.
In late 2012, I made the transition from software engineering to seed stage investing. I started Susa Ventures with several friends, and I was going to be the person in charge of all technical diligence. Since practicing software engineers are relatively rare in the VC industry, I (naively) assumed that my background would give Susa a big competitive advantage when making investing decisions. For the most part, I was wrong.
What should seed stage technical diligence actually measure?
My early attempts at doing technical deep dives turned out to be fruitless for a number of reasons:
Early versions of a product are often prototypes that are intentionally meant to be rewritten or heavily refactored in the near future.
Because getting a product in the hands of users is a top priority, even great engineers will intentionally take shortcuts and accumulate technical debt in order to launch sooner.
I was lucky enough to be one of LinkedIn's earliest employees in 2003. I joined the company when it was just over a dozen people and was the 2nd non-founding engineer hire.
Team photo from 2005, when we reached 2,000,000 users
Yesterday, I woke up to the news that Microsoft is acquiring LinkedIn for $26b in cash. It was a surreal story to read because when I left Microsoft to join LinkedIn in 2003, I never imagined that one day that tiny startup would be acquired for almost 7% of Microsoft's market cap.
The acquisition announcement got me reminiscing about LinkedIn's early days, so I thought I'd share some of my favorite memories from my two years at the company (2003-2005).
Once your startup has some traction, fundraising becomes more straightforward. Investors still care about your vision and your team, but much of their focus shifts toward analyzing and interpreting your numbers: how fast is revenue growing? How many users are logging in monthly? How about daily? What fraction of users are retained for at least 3 months? 12 months? Strong numbers reduce the perceived riskiness of your company even if other parts of your pitch are weak. After all, if your company is making $2m/year and growing 20% monthly, then you must be on to something, right?
Raising before you have significant traction is a different story. Instead of data, all you have are hypotheses, anecdotes, assumptions, and beliefs. The best way to win over investors at this stage is to pursue a large market and to have strong answers to three questions: 1) why this? 2) why now? and Continue reading “Why This? Why Now? Why You?”
Startup founders are sometimes surprised when they spend a year or two executing against their roadmap, make a lot of progress, and still have to struggle to raise more capital. Why wouldn't investors be interested in a company if it's much further along than it was last year? Why are the few investors who are interested only willing to invest at a lower valuation?
Unfortunately, all progress is not created equal. Sometimes moving forward gets founders closer to the goal of building a huge, profitable company, but sometimes it shows that they're on the wrong path, or that their goal is unattainable.
A bundle of risks
In order to understand if a startup is making meaningful progress, it's useful to analyze it as a bundle of risks that must eventually be addressed. Here are a dozen sample startup risks:
Can the founders work well together? (What if the team starts
Most founders try to raise their seed rounds in one shot, but some do their fundraising over long stretches of time and across a series of (rising) valuations. For most founders in the latter group, piecemeal fundraising is out of necessity: if they can't raise $1.5m but can raise $400k, then $400k is almost certainly better than nothing. Some founders, however, do fundraising in small increments in an effort to fight dilution, on the assumption that more capital will be available later. Unfortunately, incremental fundraising does little to combat dilution while posing significant existential risk. If you have the opportunity to raise your target seed amount in one shot at reasonable terms, then you should take it.
To make the following arguments more concrete, let's look at a typical scenario:
When founders are raising their seed rounds, they try to meet with as many investors as possible — a sound strategy for raising money. However, after those seed rounds close, most founders are unsure about how to allocate time to new investor relationships. Should they start reaching out to Series A investors even though a Series A is over a year away? Should they accept meeting requests from VCs they've never talked to before? If they do meet with new investors, what should such meetings be about? This post will address some of the most common questions about meeting with investors when you're not fundraising.
Should you meet with investors when you're not fundraising?
Yes. Each meeting is a valuable learning opportunity. Things you might discover include:
What kind of insights does the investor have about your business?
For most disciplines, it only takes one hundred hours of active learning to become much more competent than an absolute beginner.
The downside of achieving basic competence is that it often leads to overconfidence. This is called the Dunning-Kruger effect. In a study published in 1999, David Dunning and Justin Kruger found that unskilled individuals greatly overestimated their abilities, while highly skilled individuals underestimated their abilities. Here's an illustrative figure from the study:
The figure above shows that regardless of actual skill level, most people consistently perceived themselves as slightly above average. This is a gross underestimate for an expert, and a gross overestimate for a newbie.
A recently popularized meme is the 10,000-Hour Rule, which describes the amount of time required to achieve mastery of a field. This rule has several implications:
Since the required time commitment is so high — three hours per day for a decade! — a person can only master a few things in their lifetime.
Because time moves at the same speed for everyone, you can't accelerate the acquisition of mastery. If you've mastered something (e.g. sales or programming or product management) and your competition has not, that's a huge competitive advantage.
The commitment for mastery is so high that a lot of people become intimidated and give up early — or never even begin. For every violin virtuoso, there are many more people that quit after a few lessons, or who never picked up a violin in the first place.
A useful software engineering practice is to work on the hardest part of a program first. If you can't complete that piece then you'll never be able to get the full system to work. For example, if a program has 10 components, and component #10 is the most challenging one, then coding up #1 through #9 first means that an engineer might waste a lot of time before figuring out that the entire project is impossible. It's more sensible to start with #10 to understand if the project is viable in the first place. Tackling the easy stuff first is basically procrastination.
The Lean Startup approach is very similar to this engineering practice: instead of building a full-featured product upfront, you talk with prospective customers and build an MVP quickly to see if an idea merits more significant investment. While it's easier and more fun to start writing code, that's Continue reading “Tackle the Hard Stuff First”
There are many articles these days about young startups raising tons of money. There is also an increasing number of articles about well-funded startups suddenly struggling or shutting down. Every time a new story comes out, there's a chorus of comments about how a failing company was doomed from the start, or how the VCs investing at huge valuations are dumb, or how the founders of a company don't know what they're doing. Sometimes these comments are accurate, but much of the time they're ill-informed. These comments also reveal two common biases: the tendency to underestimate others (and overestimate oneself), and the tendency to draw conclusions from present data without considering what data might be missing. These are dangerous biases — especially when used by founders to hastily dismiss the quality of their competition.
The startup ecosystem is interesting because of its extremely capitalist nature. Everyone wants to
A few years ago, I became interested in the philosophy of stoicism. These days, calling someone stoic means that they appear cold and emotionless. The original meaning of stoicism was more about being calm and tranquil in the face of trials and tribulations. The goal wasn't to eliminate all emotions, but to eliminate negative feelings like jealousy or anger or sadness. Many of of stoicism's principles and practices can be applied to building and investing in startups.
One of the main observations of stoicism is that many sources of unhappiness originate from within ourselves. A friend forgets to invite us to a party, so we become upset. A driver cuts us off, so we become angry. A high school classmate wins the lottery, so we become jealous. These are natural responses, but also unproductive ones. Becoming upset doesn't fix our problems, it only exacerbates them. Stoicism's key insight is Continue reading “Startups and Stoicism”
One of my friends is about to start a company, and he asked me if location matters. He lives in Mountain View and doesn't want to move north to SF, but he's not sure if staying south impedes his startup's chances of success.
Not having a good answer to the question, I decided to look at some data. Fortunately, AngelList contains a fairly comprehensive list of startups around the world, as well as a Signal score for each startup. This score represents AngelList's estimate of a startup's quality based on the people involved (the founders, investors, advisors, et cetera). It's not a perfect metric for a startup's level of success, but it's not bad.
To answer my friend's question, I analyzed the composition of low vs. medium vs. high Signal startups for different metro areas and cities. What I found is that there are significant differences in startup qualities across
Most startups have a roadmap for the next year or two, and most investors ask about that roadmap during pitch meetings. The question usually sounds something like this: "If you raise the $1.5m that you're looking for, how much runway would that get you? What would you hope to do that in that time frame?" The answers can reveal unrealistic assumptions about operating costs or about growth trajectories. On rare occasions, they can also reveal a lack of understanding about how startups work.
About a third of the founders I talk to will mess this question up in some way, either by underestimating operating costs or overestimating growth rates. Below are five tips for better roadmap planning. These tips are specifically targeted at SaaS startups, but I think they're applicable to other tech startups, too.
TL;DR: 1) assume ~20% monthly growth; 2) don't promise hockey stick growth without justification;
TL;DR: If you're a founder and you want your company to succeed, you have to put what's best for the company ahead of what feels most comfortable for you.
One of the first engineering teams I was on had a lot of micromanagement. The tech lead did (unsolicited) reviews of everyone's code, and also gave implementation tips for new features down to the "you should write a function called XYZ" level. If you're not an engineer, that's akin to giving a writer a list of paragraphs to include in their short story.
Senior developers on the team were frustrated by this level of micromanagement, but I thought it was great. My main programming experience was in college, and having a smart tech lead tell me exactly how he would implement each feature was a wonderful learning opportunity.
"Don't tell me the moon is shining; show me the glint of light on broken glass."
– Anton Chekhov
A frequent staple of startup pitches is lauding your team's abilities. "Dude, you should see our lead engineer. She is a Ruby ninja." Or, "our Head of Sales is totally crushing it." **
The challenge with these claims is that anyone can make them. Here, watch this: "I am awesome at PR and business development." Sounds good, right? Except it's not true. Well, I've never tried PR or biz dev, so maybe I would be awesome at those things, but it's not very likely.
One of the maxims of writing is "show, don't tell." This is great advice for startups, too. Don't just tell investors that you're great at something when you can show them instead. Some examples:
TL;DR: If you want to work at a startup, email a VC or angel investor and ask them for company recommendations. Because of the well-aligned incentives between investors, founders, and job seekers, investors are a great resource for finding the perfect job.
This post is about incentive structures for various job-search assistants (friends, external recruiters, and investors). In any industry, whether recruiting or investing, there will be bad players who only care about maximizing personal gain, and good players who will do the right thing even if it runs counter to their financial incentives. That said, I do think investors have better aligned incentives for recruiting than other alternatives.
Finding Jobs through Friends
A friend can vouch for you, which makes your job application significantly stronger.
A friend has your best interests in mind, not just their employer's, which means they will help you avoid a poor fit.
You might resent the investors. If you feel like investors are taking advantage of you, you might not want to work with them after the investment closes, which means you'll miss out on free help, and they won't be able to strongly recommend you to Series A firms because they are not close to you.
Recently, there has been a lot of talk about a possible bubble in startup valuations. The question I want to explore is: "How are VC investment returns affected by bubbles?" That is, if it's a bubble, should VCs (and by extension, startups that need VC funding) close up shop for a few years and wait until market conditions change?
Assertion #1: VC returns are governed by power laws
Most VC funds have somewhere between 15 and 50 portfolio companies. It turns out that almost all of a fund's returns will come from its best 1-3 investments. Here's a chart of outcomes for a typical individual investment:
I meet with a lot of startup founders, and many of them don't have well-balanced teams. For example, a company might have two non-technical cofounders who are outsourcing all of their early engineering work, or two technical cofounders who want to build enterprise SaaS products but have no sales experience and no connections to their target market.
These imbalances might exist because the founders prioritized working with trusted friends over better qualified acquaintances, or because they paired up based on who was between jobs rather than who was the right partner, or one of many other reasons. Regardless of the underlying cause, team imbalances hurt companies in the long run. The right team can make a company while the wrong team will break it — often before the company even gets off the ground.