In my first programming job out of college our bosses told us to entirely rebuild our product. The person in charge of the networking layer decided the best way to do this was to write our own low-level networking toolkit, using some new, relatively untested networking techniques. We also wrote our own versions of core Java libraries (because, it was said, the existing ones weren’t sufficiently thread safe). This decision ended up leading to repeated delays and bugs, and a codebase that most of the other employees didn’t understand. It also made it much harder to train new hires and find replacements for departed employees.

A related issue is what is usually called the “bleeding edge” tendency: the desire to use the shiny & new over the older & battle-tested. Lately, I’ve personally been programming with MongoDB and love it. But I’m also an investor in a startup that made Mongo their main production database, and when their Mongo expert left unexpectedly it took them far longer to find a replacement than it would have to find a MySQL expert.

Great programmers are intensely curious and inventive. They love to improve code and try new things. There will always be bedrock and bleeding edge tendencies within strong engineering teams. The key is to have a great VP Engineering/CTO who can balance those tendencies with the reality that talent, money, and time are scarce, especially in startups.

1. Jobs & the economy. Businesses all over the world need more programmers. Every company I know is hiring engineers (e.g. see this list of NY tech startups). Top programmers can make $100K+ right out of college. Yet there were only about 14,000 computer science (CS) majors last year. Meanwhile about 40,000 people got law degrees even though demand for lawyers has been shrinking. America is suffering from what economists call structural unemployment:  jobs are available but our labor force isn’t trained for those jobs.

2. Programming is a great foundation for a tech/startup career. CS is a great foundation to do other things in tech industry like starting a tech company (although I’d argue that design is an increasingly valuable foundation for web startups). I suspect one of the reasons for the low number of CS majors is people don’t realize all the non-programming opportunities that are opened up by a background in programming.

3. Programming is an important part of being “culturally literate.” Algorithmic thinking is as fundamental a type of thinking as mathematical thinking. For example, Daniel Dennett convincingly argues that the best way to understand Darwin’s theory of evolution is by thinking of it as an algorithm. (I haven’t read it yet but I’m told the premise of Stephen Wolfram’s A New Kind of Science is that algorithmic methods should be applied much more broadly across the sciences). Teaching algorithmic thinking – which is what CS does – should be a core part of a liberal arts education.

4. Programming is a great activity.  Most people who program describe themselves as entering a mental flow state where they are intensely immersed and time seems to fly by. It feels similar to reading a great book. You also feel great afterwards – it is the mental equivalent of going to the gym.

5. Should non-technical people at tech startups learn to code? This is where I disagree with some of the conventional wisdom. Certainly it is worthwhile learning programming, at least for reasons 3 & 4 above. You should realize, however, that to become a good programmer takes thousands of hours of practice. I’d also argue that if you are a non-technical person working at a web company the the first thing you should learn is internet architecture (DNS, http, html, web servers, database, TCP/UDP, IP, etc). Learning some programming is good too, to help relate to technical colleagues. But if your goal is to build a large-scale web service, your time as a non-technical person is better spent recruiting people who have been coding for years.

* Disclosure: I’m an investor via Founder Collective in two companies related to teaching programming:  Codecademy and Hacker School.

It comes down to what each company has promised its users. Facebook promised its users their stuff would be private, which is why users rightfully get pissed when that line blurs. Twitter has promised users, well, that it will stay up, and that is why users rightfully get pissed when the whale is back.

Google has promised its users and the entire tech community, again and again, that it would put their interests first, and that is why Google users, rightfully get pissed when their results are deprecated to try to promote a lesser Google product instead.

It’s all about expectations.

Most websites spend massive amounts of time and money to get any of their pages index and ranked by Google’s search engine. Indeed, there is a entire billion dollar industry (SEO) devoted to helping companies get their content indexed and ranked.

Twitter and Facebook have decided to disallow Google from indexing 99.9% of their content. Twitter won’t let Google index tweets and Facebook won’t let Google index status updates and most other user and brand generated content. In Facebook’s case this makes sense for content that users have designated as non-public. In Twitter’s case, the vast majority of the blocked content is designated by users as public. Furthermore, Twitter’s own search function rarely works for tweets older than a week (from Twitter’s search documentation, they return “6-9 days of Tweets”).

There is a debate going today in the tech world: Facebook and Twitter are upset that Google won’t highly rank the 0.1% of their content they make indexable. Facebook and Twitter even created something they call the “Don’t be evil” toolbar that reranks Google search results the way they’d like them to be ranked. The clear implication is that Google is violating their famous credo and acting “evil”.

The vast majority of websites would dream of having the problem of being able to block Google from 99.9% of their content and have the remaining 0.1% rank at the top of results. What would be best for users – and least “evil” – would be to let all public content get indexed and have Google rank that content “fairly” without favoring their own content. Facebook and Twitter are right about Google’s rankings, but Google is right about Facebook and Twitter blocking public content from being indexed.

Update: after posting this I got a bunch of emails, tweets and comments telling me that Twitter does in fact allow Google to index all their tweets, and that any missing tweets are the fault of Google, not Twitter. A few people suggested that without firehose access Google can’t be expected to index all tweets. At any rate, I think the “Why aren’t all tweets indexed?” issue is more nuanced than I argued above.

Most recent successful tech companies seem to have chosen the former: growing revenues at the expense of margins. Again and again, we see S-1 filings with revenues growing rapidly but profit margins that are low to negative. The same is true for the rumored financials of private companies. I think I understand why they made this choice, but wonder if it was a mistake.

To understand why these companies made this choice, you need to look at their formative stages. Many of them raised money from VC’s at multi-hundred-million to multi-billion dollar valuations, often before the companies were profitable or had even settled on a business model. In most cases, the companies and investors were acting reasonably[2]. But the end results might have been to unwittingly commit themselves to revenue over margin growth.

Why? Money has its own inertia and somehow always seems to get spent. Some of this spending is reasonable and even necessary (infrastructure, defensive expansion to international markets). But then there are harder choices. For example, do you invest heavily in sales and marketing to grow your revenue faster? Do you stay open and try to become a platform and therefore force yourself to experiment with new business models? Or do you become closed to “own the user” and therefore benefit from existing business models like advertising? Fast revenue growth seems to be the best way to justify your valuation. But the next thing you know you have a high cost structure that requires you to raise even more money and grow revenue even faster.

The root cause here is a deeply held belief throughout the business world that exceptional revenue growth is more likely than exceptional margins. For example, if you talk to professional public market investors and analysts you’ll often hear statements like “that’s a low margin industry” – implying that every industry has “natural” profit margins which companies can only defy for short periods of time. This belief is also reflected in public market valuations for recent tech IPOs: companies like Groupon that put revenue over margins command very healthy valuations.

The problem is that this deeply held belief in “revenue exceptionalism” over “margin exceptionalism” is a hangover from the industrial era. Unlike industrial era companies, information businesses tend to be deflationary, shrinking the overall revenue of an industry. They also tend to have network effects (and complementary network effects), making them more defensible and therefore higher margin than non tech businesses. Given this, why do companies continue seeking revenue at the expense of margins? Fred made this same point in his original post, but people didn’t seem to listen.

[1] Companies (like all cash generating assets) are ultimately valued at a multiple of present and projected future profits. The historical average P/E ratio of the DJIA is about 15, meaning that (on average) if a company is generating $100M in profit, it is valued at $1.5B (Fred prefers to use a 10 multiple, perhaps to be conservative?). One way to understand this is to imagine that companies dividend out all their profits every year. If you bought something for $1.5B and it dividended out $100M every year, that would be a 6.6% annual return.

[2] Why are these high-priced financings reasonable? From the company’s perspective: your traffic is growing so fast you need to invest millions of dollars in infrastructure. Meanwhile copycats are popping up in other countries. You don’t know if the financial markets will suddenly dry up. Someone offers you, say, $50M for minimal dilution. Seems like a reasonable hedge. From the investor’s perspective: the history of venture capital shows that almost all the returns are generated from big hits like Amazon, eBay, Facebook and Google. (As Paul Graham once put it: “The difference between a bad VC fund and a great VC fund is one big hit”).

Some of the most interesting startups today are founded on the same premise of maximizing capacity utilization. Being information technology startups, their method for doing so is generally by matching demand for capacity with supply of un-utilized capacity. AirBnB lets people rent out unused space, increasing the utilization of their homes. Uber lets drivers rent out their unused time, increasing the utilization of their cars and labor. Services like TaskRabbit are trying let people fully utilize their “labor capacity”. Over time, services that increase capacity utilization tend to drive prices down (even if, at first, they sometimes have higher prices).

Whenever Southwest would begin servicing a new city, it drove prices down so dramatically that economists began referring to it as the “Southwest Effect“. One particularly remarkable aspect of the Southwest Effect: when Southwest began servicing a city, it would stimulate new business activity – and thus air travel – to such an extent that even Southwest’s less efficient competitors ended up benefiting.

Instagram built a product devoted to a job that users were previously performing improvisationally using multiple products. This is a common pattern for popular software and services. Before Twitter, people shared interesting links through email or “link round-up” blog posts. Tumblr’s short-form blogging/re-blogging was inspired by an “unintended” use of long-form blogging platforms like WordPress. Before Foursquare, power socializers sent out mass text messages with their locations (in fact, Foursquare’s predecessor Dodgeball did exactly that).

New startup ideas are all around you, in the improvised behaviors of people you know. It takes a keen product eye, however, to notice these improvisational behaviors and recognize which ones are worthy of being developed into standalone products.

- The most important thing to understand is what motivates programmers. This is where having been a programmer yourself can be very helpful. In my experience programmers care about 1) working on interesting technical problems, 2) working with other talented people, 3) working in a friendly, creative environment, 4) working on software that ends up getting used by lots of people. Like everyone, compensation matters, but for programmers it is often a “threshold variable”. They want enough to not have to spend time worrying about money, but once an offer passes their minimum compensation threshold they’ll decide based on other factors.

- Software development is a creative activity and needs to be treated as such. Sometimes a programmer can have an idea on, say, the subway that can save weeks of work or add some great new functionality. Business people who don’t understand this make the mistake of emphasizing mechanistic metrics like the number of hours in the office and the number of bugs fixed per week. This is demoralizing and counterproductive. Of course if you are running a company you need to have deadlines, but you can do so while also being very flexible about how people reach them.

It is sometimes helpful to think of recruiting as 3 phases: finding candidates, screening candidates, and convincing candidates to join you.

- Finding means making contact with good candidates. There are no shortcuts here. You need to show up to schools, hackathons, meetups – wherever great programmers hang out. If your existing employees love their jobs they will refer friends. Try to generate inbound contacts by creating buzz around your company. If you have trouble doing that (it’s hard), try simple things like blogging about topics that are interesting to programmers.

- Screening. Great programmers love to program and will have created lots of software that wasn’t for their jobs or school homework. Have candidates meet and (bidirectionally) interview everyone they’ll potentially be working with. If the candidate has enough free time try to do a trial project. There are also more procedural things that can be useful like code tests (although they need to be done in a respectful way and they are more about getting to know how each side thinks than actually testing whether the candidate knows how to program (hopefully you know that by this stage)).

- Convincing them to join you. This is the hardest part. Great programmers have tons of options, including cofounding their own company. The top thing you need to do is convince them what you hopefully already believe (and have been pitching investors, press etc): that your company is doing something important and impactful. The next thing you need to do is convince them that your company is one that values and takes care of employees. The best way to do this is to have a track record of treating people well and offer those past employees as references.

A few things not to do: you will never beat, say, Google on perks or job security so don’t even bother to pitch those. You’ll never beat Wall Street banks or rich big companies on cash salary so don’t pitch that either. You’ll never beat cofounding a company on the equity grant, but you can make a good case that, with the right equity grant, the risk/reward trade off of less equity with you is worth it.

Finally, I’ve long believed that early-stage, funded startups systematically under-grant equity to employees. Programmers shouldn’t have to choose between owning a fraction of a percent of an early-stage funded company and owning 50% of an unfunded company they’ve cofounded. Naval Ravikant recently wrote a great post about this:

Post-traction companies can use the old numbers – you can’t. Your first two engineers? They’re just late founders. Treat them as such. Expect as much.

Making those first engineers “late cofounders” will dramatically increase your chances of recruiting great people. This is a necessary (but not sufficient) condition for getting the recruiting flywheel spinning where great people beget more great people.

* As someone who personally programmed for 20 years including about 10 years professionally, I preferred to call myself a “programmer.” Some people prefer other words like “hacker” “developer”, “engineer” etc. I think the difference is just uninteresting nomenclature but others seem to disagree.

An internet of people

Making industries “garage ready” for startups

Business development: the goldilocks principle

Some lessons learned

Do you want to sell sugar water or do you want to change the world?

What the NYC startup world needs (and doesn’t need)

Founder/market fit

Best practices for raising a VC round

There are two kinds of people in the world

Apple and the TV industry

Google’s social strategy

MIT is a national treasure

Dropbox and why you should invest in people

SEO is no longer a viable marketing strategy for startups

Selling pickaxes during a gold rush

Predicting the future of the Internet is easy: anything it hasn’t yet dramatically transformed, it will.

For older posts, see the contents page. I haven’t updated this page in a long time but plan to do so soon.

Alcoa, the biggest aluminum company in the country, encountered two problems peculiar to Iceland when, in 2004, it set about erecting its giant smelting plant. The first was the so-called hidden people—or, to put it more plainly, elves—in whom some large number of Icelanders, steeped long and thoroughly in their rich folkloric culture, sincerely believe. Before Alcoa could build its smelter it had to defer to a government expert to scour the enclosed plant site and certify that no elves were on or under it. It was a delicate corporate situation, an Alcoa spokesman told me, because they had to pay hard cash to declare the site elf-free, but, as he put it, “we couldn’t as a company be in a position of acknowledging the existence of hidden people.” The other, more serious problem was the Icelandic male: he took more safety risks than aluminum workers in other nations did. “In manufacturing,” says the Alcoa spokesman, “you want people who follow the rules and fall in line. You don’t want them to be heroes. You don’t want them to try to fix something it’s not their job to fix, because they might blow up the place.” The Icelandic male had a propensity to try to fix something it wasn’t his job to fix.

Back away from the Icelandic economy and you can’t help but notice something really strange about it: the people have cultivated themselves to the point where they are unsuited for the work available to them. All these exquisitely schooled, sophisticated people, each and every one of whom feels special, are presented with two mainly horrible ways to earn a living: trawler fishing and aluminum smelting. There are, of course, a few jobs in Iceland that any refined, educated person might like to do. Certifying the nonexistence of elves, for instance. (“This will take at least six months—it can be very tricky.”) But not nearly so many as the place needs, given its talent for turning cod into PhDs. At the dawn of the twenty-first century, Icelanders were still waiting for some task more suited to their filigreed minds to turn up inside their economy so they might do it.

Enter investment banking.

It’s a short book – just 5 chapters covering Iceland, Ireland, Germany, Greece, and California. What’s particular fascinating is how each place had a wildly different reaction to the credit glut.

- Great for Boston. Fairly or not, Boston is often typecast as an infrastructure, B2B, hardware, and biotech town. Between Tripadvisor and Kayak, Boston now has at least two very important consumer internet companies.

- Big win for the “golden age of SEO”.  By which I’m referring to roughly 2001-2008 when “demand” for content (people typing in search queries) far outpaced supply (good content). Companies like Yelp and TripAdvisor (along with Wikipedia, IMDB, etc) grew huge during this period, almost entirely through SEO. They did this by getting highly defensible flywheels spinning where more content meant more SEO which meant more users which meant more content. It is now far more difficult to grow a startup primarily through SEO. Almost all monetizable search categories have vast excesses of SEOd content. Moreover, Google is creating their own content (e.g. Google Places) which, at least at times, they have favored in their search results.

- The user experience should improve. MG Siegler and others have criticized TripAdvisor for an excess of ads. I don’t disagree with MG, but I also think this is largely the result of the broken online ad attribution system that punishes intent generators and rewards intent harvestors. Travel reviews are for users at the beginning of the travel research process (which on average takes weeks), but all CPA and CPC ad programs pay only for the last click which usually means when users are purchasing tickets or making reservations. Hence review sites are forced to saturate their website real estate with purchasing widgets and display ads. Hopefully as online ad attribution improves this will no longer be necessary.

- It’s weird how little coverage this IPO got and how the financial press missed the interesting stories. TripAdvisor ended the day at ~$3.5B in market cap, making it the second most valuable East Coast consumer internet company (after Priceline). Every story I saw focused on the share price drop over the day. The fact that the price dropped from its opening price simply means the bankers mispriced the stock and therefore insiders didn’t get the sweetheart deal they thought they were getting.

Update: I interviewed the CEO/founder of TripAdvisor on TechCrunch yesterday. Topics include the company’s origins, relationship with Google, SOPA, and advice to fledgling entrepreneurs.

A fast-food restaurant chain wanted to improve its milkshake sales. The company started by segmenting its market both by product (milkshakes) and by demographics (a marketer’s profile of a typical milkshake drinker). Next, the marketing department asked people who fit the demographic to list the characteristics of an ideal milkshake (thick, thin, chunky, smooth, fruity, chocolaty, etc.). The would-be customers answered as honestly as they could, and the company responded to the feedback. But alas, milkshake sales did not improve.

The company then enlisted the help of one of Christensen’s fellow researchers, who approached the situation by trying to deduce the “job” that customers were “hiring” a milkshake to do. First, he spent a full day in one of the chain’s restaurants, carefully documenting who was buying milkshakes, when they bought them, and whether they drank them on the premises. He discovered that 40 percent of the milkshakes were purchased first thing in the morning, by commuters who ordered them to go.

The next morning, he returned to the restaurant and interviewed customers who left with milkshake in hand, asking them what job they had hired the milkshake to do. “Most of them, it turned out, bought [the milkshake] to do a similar job,” he writes. “They faced a long, boring commute and needed something to keep that extra hand busy and to make the commute more interesting. They weren’t yet hungry, but knew that they’d be hungry by 10 a.m.; they wanted to consume something now that would stave off hunger until noon. And they faced constraints: They were in a hurry, they were wearing work clothes, and they had (at most) one free hand.”

The milkshake was hired in lieu of a bagel or doughnut because it was relatively tidy and appetite-quenching, and because trying to suck a thick liquid through a thin straw gave customers something to do with their boring commute. Understanding the job to be done, the company could then respond by creating a morning milkshake that was even thicker (to last through a long commute) and more interesting (with chunks of fruit) than its predecessor. The chain could also respond to a separate job that customers needed milkshakes to do: serve as a special treat for young children—without making the parents wait a half hour as the children tried to work the milkshake through a straw. In that case, a different, thinner milkshake was in order.

There are at least three obvious ways to apply this concept: 1) when searching for startup ideas, think about jobs people want done that they can’t currently get done, 2) when thinking about how to fix or improve your product, understand why existing users are hiring your product (or should be hiring your product) and try to improve those experiences, 3) when analyzing markets, segment companies by the jobs they are hired for. Sometimes products that might appear similar (e.g. two photo sharing apps) are actually hired for very different purposes, and are therefore misclassified as competitors.

There’s actually 2 levels of trust here. The first is knowing and trusting the person you’re buying from. And if you don’t know who they are, then you must move on to the second level of trust, which is do you know and trust the platform the person is using.

The ability to have “second order trust” is one of many reasons the internet has made so many institutions obsolete. Take the SEC’s role in policing private companies that market themselves to potential investors. This was sensible consumer protection back when the government was arguably the only organization that had the means and incentives to identify fraudulent investment schemes. But today we have many examples of websites that’ve built mechanisms for reliably tracking the reputations of individuals and organizations. This means the SEC could – in theory – make the unit of regulation platforms instead of investors and startups (something the crowdfunding bill being considered by Congress seems to do at least in part), which in turn could unleash a new wave of innovation among crowdfunding platforms and crowdfunded startups.

When a trend like this emerges, it’s always interesting to ask “why now?” For example, for almost a decade, entrepreneurs tried to create video sharing services like YouTube, but only succeeded when certain key dependencies – broadband, digital video cameras, a version of Flash that “just worked” – became widespread.

I asked Roelof Botha the “why now” question regarding web-based marketplaces. He said something I thought was really interesting: marketplaces depend on trust, and trust requires knowing the reputation of a prospective counterparty. Today, for the first time, you can get background information on almost any prospective counterparty by searching Google, Facebook etc. Or put more simply: we finally have an internet of people.

I’ve been blogging more lately which explains why Dec 2011 is tracking to be up near 2M page views (although frankly that number seems high to me- I wonder if somehow they are counting each page view multiple times – maybe due to the way WordPress works?)

As if we needed another reminder of how wrong Compete data is here is their chart:

Not even directionally correct.  Yeah they show UVs and not pageviews but I don’t see any reason those would have gotten decoupled.

(I had cdixon.org tagged with Quantcast for a while but removed it a few weeks ago –  their chart when cdixon.org was tagged makes more sense (as you’d expect)).

I blog just for fun / hobby, so don’t really care about these stats. But it’s interesting to see the (in)correctness of these popular analytics services.

You can count on there being a whole host of impinging forces that will affect the dynamic of decision-making on any issue at a big company.

The consensus building process, trade-offs, quids pro quo, politics, rivalries, arguments, mentorships, revenge for past wrongs, turf-building, engineering groups, product managers, product marketers, sales, corporate marketing, finance, HR, legal, channels, business development, the strategy team, the international divisions, investors, Wall Street analysts, industry analysts, good press, bad press, press articles being written that you don’t know about, customers, prospects, lost sales, prospects on the fence, partners, this quarter’s sales numbers, this quarter’s margins, the bond rating, the planning meeting that happened last week, the planning meeting that got cancelled this week, bonus programs, people joining the company, people leaving the company, people getting fired by the company, people getting promoted, people getting sidelined, people getting demoted, who’s sleeping with whom, which dinner party the CEO went to last night, the guy who prepares the Powerpoint presentation for the staff meeting accidentally putting your startup’s name in too small a font to be read from the back of the conference room…

Man, I wish Marc still blogged.  (ht saul lieberman)

These CEOs are worrying too much. VCs know what they are doing and almost always invest with a financial instrument – preferred shares – that protects them even when the valuation is very high. Preferred shares behave like a stock on the upside and a bond on the downside.  The only way investors actually lose money is if the company is sold for less than the amount of money raised (which is generally significantly lower than the valuation).

Here is what the payout function looks like for common stock (for example, what you get when you buy stocks in public markets):

And here is what the payout function looks like for preferred shares:

So, to take a concrete example, Dropbox reportedly raised their last financing at a $4B valuation*. If you think of this as a public market valuation of common stock, you might think this means the VCs are betting $4B is the “fair value” of the company, and will lose money if Dropbox’s exit price ends up being less than $4B.  But in reality, assuming the standard preferred structure, the last round investors’ payout is as follows :

Scenario 1: Dropbox exits for greater than $4B ==> investors get a positive return (specifically, exit price divided by $4B)

Scenario 2: Dropbox exits for between $257M (total money raised) and $4B ==> investors get their money back (possibly more if there is a preferred dividend)

Scenario 3: Dropbox exits for less than $257M ==> investors lose money

If reports are true that Dropbox is profitable and generating >$100M in revenue, then scenario 3 – the money losing scenario – is extremely unlikely.

Will investors be thrilled with scenario 2?  No, but they are pros who understand the risks they are taking.

Going back to the entrepreneur’s perspective, in what sense is a high valuation “setting the bar high”?  In the preferred share payout model, there are two “bars”:  money raised and valuation.  I don’t see any reason why entrepreneurs shouldn’t be as aggressive as possible on valuation, especially if they are confident they won’t end up in scenario 3.

An important point to keep in mind is that, in order to maintain flexibility, entrepreneurs shouldn’t give new investors the ability to block an exit or new financings. Investors can get this block in one of two ways – explicit blocking rights (under the “control provisions” section of a VC term sheet) or by controlling the board of directors. These are negotiable terms and startups with momentum should be very careful about giving them away.

* Note that I have no connection to Dropbox so am just assuming standard deal structure and basing numbers on public reports. I am making various simplifying assumptions such as not distinguishing between pre-money and post-money valuation.

I think the most common form of tech acquisition is a variant of the [business acquisition], in which the acquirer wants to inject forward motion into the organization. It’s far more difficult for a public company to rally around a launch into what might seem like a small sector… it just doesn’t seem worthy of the biggest brains and bravest folks, so it gets shunted aside.

On the other hand, once a smart tech company acquires a smaller company with momentum, it gives the company permission to drive, perfect, polish and grow that business. I’d argue that this what actually happened with YouTube.

The logic underlying organizational momentum acquisitions can be found in Clay Christensen’s disruptive technology theory. Smart CEOs of large companies realize how hard it is to shift internal momentum away from developing sustaining technologies. As a way to avoid this trap, Christensen recommends that large companies set up internal startups that are as organizationally separate as possible. But, as Seth points out, acquiring startups with momentum is another way to get the same result.

- Talent. When the acquirer just wants the team (generally just engineers and sometimes designers). As a rule of thumb, these acquisitions are priced at approximately $1M/engineer.

- Tech: When the acquirer wants the technology along with the team. Generally the prices for these acquisitions are significantly higher than talent acquisitions. Sometimes they are even in the hundreds of millions of dollars for fairly small teams (e.g. Siri). The calculation the acquirer uses to price tech acquisitions is usually “buy vs build”. An important component in this calculation is not just the actual cost to build the technology but the opportunity cost of the time it would take them to do so.

- Business: When the company is either bought on a financial basis (the acquisition is “accretive”) or bought based on non-financial but highly defensible assets (Google buying YouTube which had minimal revenue at the time but a huge network of producers and consumers of video).

As large companies mature they move from doing just talent acquisitions to doing talent and tech acquisitions to eventually doing all three types of acquisitions. Usually it takes a startup beating the large company in an important area for the large company to realize the necessity of business acquisitions. For example, Google seemed to dramatically change its attitude when YouTube crushed Google Video. Eventually every large company has a moment like this.

If I understand correctly, “garage-ready” essentially means separating design from manufacturing, i.e. “creativity-intensive” processes from capital-intensive ones. This may be an inevitable result of industry maturation and specialization, but there is a downside to it, at least for the so called “developed” nations. The result of differential costs for commodity labor, the fungibility and liquidity of capital, and the ease of transmitting both human and machine-readable information across arbitrary distances, means that capital-intensive processes – i.e. making things – migrate to locations with lower total cost of operations (which, Germany excepted, tend to be locations with lower labor costs). Another way of saying this is that nothing is fabless; the foundry is merely outsourced and moved to a cheaper location. This reality is great for the creative class and for the lower cost locations, but it’s less happy for the residents of the higher class locations that are not so lucky to be part of the creative class.

I’m not ready to draw the conclusion that this is the cause of the economic inequality in the US and malaise across Europe and Japan, but there definitely appears to be some correlation. Again, I don’t know if these results of the “garagification” of an industry can be reversed or mitigated in the name of societal stability, but if anyone can find a way to do it it would be the creative class. Unfortunately, because techies and entrepreneurs are solidly part of the creative class and perhaps even *the* primary beneficiaries of the separation of design and manufacturing, we generally avoid acknowledging or discussing the negative aspects of this trend.

Note that I said “reversed or mitigated.” Trying to reverse or stop these trends is probably a quixotic goal, but perhaps mitigation is in fact possible. For example, is it possible to create a country in which the entire labor force is “creative”? I myself have trouble seeing how such a possibility could be made real, but I’d like to see more intellectuals and entrepreneurs spend some brainpower on the question.

It is true that new technologies often lead, in the short term, to lower wages and fewer jobs. Craigslist, for example, has about 30 employees yet, by replacing the classified ad industry, eliminated many thousands of jobs (local newspaper reporters, classified ad salespeople, etc). The same could be said for almost every popular website.

On the flip side, new technologies have driven down prices (Walmart and Amazon), led to massive increases in information productivity (Google and Wikipedia), and created new income sources (eBay and Craigslist). Greater productivity and lower prices at least partly compensate for part-time jobs and lower wages.

Jordan is right that these are questions we – the technology community – should spend more time discussing.

I remember first observing this when I worked at Bessemer. For example, there was a startup that supplied services to video websites. For years, the company soldiered along, barely growing. Then, suddenly, YouTube blew up and this company took off along with it.

As a founder, these exogenous shocks are out of your control, but you can 1) understand what exogenous shocks you depend on, 2) try to guess when those shocks will hit, 3) manage your runway so you survive long enough for them to hit.

More adventurous entrepreneurs might argue 18 months is too conservative. It’s true that following the 18 month rule can be extra dilutive. At SiteAdvisor, we raised our Series A about three months before we were acquired. So we gave up equity for cash that we never spent. But in retrospect, given what we knew at the time, I think it was the right decision.

The question of when to raise money is one of the few times that entrepreneurs and early-stage investors have somewhat divergent economic interests. If you control a large investment fund, you always have the option to extend a company’s runway. The entrepreneur doesn’t have this option. I’ve even heard some entrepreneurs whisper about Machiavellian VCs who deliberately try to get you to the end of your runway so they can negotiate harder. I think this is a bit of a conspiracy theory. Almost all VCs I know care primarily about the success of their companies and not about extracting every last point of equity.

Before the 1980s, if you wanted to invent a new semiconductor, you had to both design and manufacture it. This meant you had to build a large manufacturing plant, something only large companies like Intel, Motorola, and IBM could afford. Hence, semiconductor design was generally too expensive for venture-backed startups.

In the 1979, two computer scientists published a seminal book that argued for the separation semiconductor design and manufacturing. Followed by years of investment by DARPA and others, an industry emerged where chip designers used software (“EDA software”) to design and test semiconductors, and then sent standardized specifications to “foundries” that did the manufacturing (most of which were located in Taiwan – the largest in the world to this day is Taiwan Semiconductor Manufacturing Company).

This dramatically lowered the cost of starting semiconductor design shops, and in turn led to a massive wave of startup innovation. These startups designed chips for cell phones (Qualcomm), Wifi (Atheros), computer graphics (Nvidia), and much more.  Most were funded by venture capitalists and located in Silicon Valley.

Tech sectors tend to get really creative when they become “garage ready”:  a Steve Jobs and Steve Wozniak, or a Larry Page and Sergey Brin, can, with very little capital, change the world. It happened with semis in the 80s and happened in the 90s and 2000s for internet companies.

Eventually every vertically integrated, capital-intensive sector becomes garage ready. Someday, for example, we will have “fabless” gadget design and biotech research, enabling a small shop in Brooklyn or SoMa to create an iPhone killer or next-generation cancer drug.

In my opinion, enterprise technology is WAY behind consumer technology for one reason: because it can be.

In a [B2B] transaction, one good salesperson (the “seller”) only has to sell one person (the “buyer”) on the value of the technology. Once the product is sold, the buyer forces their 50,000 employees to use that technology whether they like it or not. A good salesperson with a good deck can do this fairly reliably.

And a good account manager can typically retain the client for a while; employees usually get used to the product and rarely complain enough for the buyer to cancel the contract and force the seller to improve the product. As a result, an enterprise product can suck and still flourish.

With a B2C product, this is much, much more difficult. The seller has to sell 50,000 individual “users”, one by one, on the value of the product without the luxury of a face to face meeting or 18 holes on the golf course. The B2C model forces the seller’s product to “sell itself”. As a result, a consumer product can’t suck if it wants to flourish. It has be good. Much better than the enterprise product needs to be.

Fortunately, as I discussed yesterday, trends like cloud-based delivery (aka SaaS) are starting to align the interests of enterprise users and buyers.

SAP bought SuccessFactors today, in a big win for “cloud” based enterprise software. The cloud might sound like a buzzword but is in fact a vastly superior architecture, not because it makes installation and updates easier (although that’s good too), but because it starts to remove IT from the purchasing process, meaning the user and the buyer are, increasingly, the same person.

* A corollary to this is that IT-related enterprise software, i.e. infrastructure, is generally pretty good.

We’re located on 21st between 6th and 5th aves and have had a very difficult time getting reliable internet access for our office. We’re frankly not particularly price sensitive on this given how critical fast low-latency access is for our programmers. When our internet access is down our programmers cannot be productive and our site can’t be monitored — we’re helpless and twiddling our thumbs. Every hour of no internet access is about $1,000 of wasted salary across all of our employees.

We’ve tried wireless WiMax from TowerStream, ethernet-over-copper from Megapath, T1s from Verizon, DSL from Verizon and cable modem access from Time Warner Business Services. Verizon Fios is not available. Verizon and Megapath could literally never get working lines installed for our building despite months of effort. The WiMax service suffered high latency and weather outages every time it rained hard. The Time Warner cable modem service has gone weeks with hour or two outages per day.

By my last count, there are 5 internet startups on our block alone. The situation is so bad someone set up a Twitter account so we could all go to our iPhones and lament whenever the internet is down.

It’s embarrassing how bad internet access in Manhattan is.  As a side note, I think it undermines the arguments by people who claim there is actual broadband choice (e.g. regarding the net neutrality debate).

I haven’t slept well for years. Even now with my last startup sold, I stay up at night thinking about how to change the website, make payroll, raise more money, etc.

In 1995, I was a graduate student studying philosophy at Columbia.  I was also doing computer programming on the side.  The programming was going well and I was getting some good job offers. I happened to get to have dinner with the philosopher Daniel Dennett, and I asked him what he thought I should do with my career.  He said: “If there is absolutely no way you can imagine being happy except studying philosophy, study philosophy. Otherwise do something else.”

I’d say the same thing about starting companies.

Somewhat counterintuitively, the biggest problem we encountered when pitching Hunch technology to potential partners wasn’t that it wasn’t interesting or useful to them, but that it was so interesting and useful that they considered it “strategic” or “core” and thus felt they needed to own and not rent it. The situation reminded me of the “Goldilocks principle” sometimes referred to in scientific contexts:

The Goldilocks principle states that something must fall within certain margins, as opposed to reaching extremes. It is used, for example, in the Rare Earth hypothesis to state that a planet must neither be too far away from, nor too close to the sun to support life.

Basically, if your technology is “too hot” – or, in business-speak, “strategic” or “core” – then there are three likely outcomes:

1. The potential partner turns you down because they decide to build a similar product themselves. This happened to us a number of times. I think part of the reason was that there was a lot of market buzz around “big data” and machine learning which lead to the perception – rightly or wrongly – that those capabilities needed to be owned and not rented.

2. The potential partner says yes because your assets are so defensible they can’t replicate them. I’m sure Zynga considers the social graph strategic but at least for now they have no choice but to partner with Facebook to access it. It is very rare for startups to have this kind of leverage, but ones that do are extremely valuable.

3. The potential partner wants to own what you do, but thinks you have a sufficiently superior team and technology that acquiring you instead of replicating you makes more sense. This is only possible if the partner is large enough to acquire you and has a philosophy consistent with acquiring versus building everything in-house. (A common tech business term is “NIH” which stands for “Not Invented Here”. It refers to a set of companies that consider anything developed outside of their offices technologically inferior).

At the other extreme, if your technology is “too cold” – perceived as not useful by potential partners – you’re going to have a lot of frustrating meetings.  In this case, it is probably wise to reconsider whether there is actually demand for your product.

To build a long-term sustainable business, the best place to be is “just right” – useful to lots of partners but not so strategic that they are unwilling to rent it. This is where I wanted Hunch to be but we never got there.  Most companies I know use externally developed products (commercial or open source) for databases, web servers, web analytics, email delivery, payment processors, etc. These are often highly competitive markets but the companies that win in these markets tend to become large and independently sustainable. These “just right” companies – to extend the astronomy analogy – are the planets that support life.

Today, I wanted to talk about some of the most important lessons I’ve learned over the years from my experiences as an investor and entrepreneur.

1. If you aren’t getting rejected on a daily basis, your goals aren’t ambitious enough

My most humbling and educational career experience was when I was starting out in the tech world.  I applied to literally hundreds of jobs:  low-level VC roles, startup jobs, and various positions at big tech companies.  I had an unusual background: I was a philosophy undergrad and a self-taught programmer. I got rejected from every single job I applied to.

The reason this experience was so useful was that it helped me to develop a thick skin.  I came to realize that employers weren’t really rejecting me as a person or on my potential – they were rejecting a resume.  As the process became depersonalized, I became bolder in my tactics. Eventually, I landed a job that led to my first startup getting funded.

One of the great things about looking for a job is that your payoff is almost entirely a max function – the best of all outcomes – not an average. This is also generally true for lots of activities startups do: raising money, creating partnerships, hiring, marketing and so on.

So, every day – to this day – I make it a point of trying something new and ambitious and getting rejected.

2. Don’t climb the wrong hill

I spend a lot of time trying to recruit people to startups, and I’m surprised how often I see smart, ambitious people who get stuck in fields they don’t like because they sense they are making incremental, day-to-day progress.

I think a good analogy for escaping this trap can be found in computer science, in what are known as hill climbing algorithms. Imagine a landscape with hills of varying heights.  You are dropped randomly somewhere on the landscape. How do you find the highest point?

The lure of the current hill is strong.  There is a natural human tendency to make the next step an upward one.  People fall for a common trap highlighted by behavioral economists:  they tend to systematically overvalue near term over long term rewards.

This effect seems to be even stronger in more ambitious people. Their ambition seems to make it hard for them to forgo the nearby upward step.

The lesson from computer science is: meander some in your walk (especially early on), randomly drop yourself into new parts of the terrain, and when you find the highest hill, don’t waste any more time on the current hill no matter how much better the next step up might appear.

3. The next big thing will start out looking like a toy

A majority of the top internet companies a decade ago are barely in existence today.  How did this happen?  These companies weren’t complacent – they were run by smart executives who were constantly aware that they could lose their lead.

The reason big new things sneak by incumbents is that the next big thing always starts out being dismissed as a toy.  This is one of the main insights of Clay Christensen’s “disruptive technology” theory, which has been widely studied but I think is still rarely applied because it is so counter-intuitive to conventional management practices.

Disruptive technologies are dismissed as toys because when they are first launched they “undershoot” their users’ needs. The first telephone could only carry voices a mile or two. The leading incumbent of the time, Western Union, chose not to acquire telephone technology because they didn’t see how it could be useful to businesses and railroads – their best customers. What they failed to anticipate was how rapidly telephone technology and infrastructure would improve. The same was true of how mainframe companies viewed the PC, and how modern telecom companies viewed Skype.

The list of top internet companies in 10 years will look very different than that same list does today. And the new ones on the list will be companies that snuck by the incumbents because people dismissed them as toys.

4. Predicting the future of the Internet is easy: anything it hasn’t yet dramatically transformed, it will.

The Internet has gone through fits and starts – a bubble, a crash, and now a revival.  Pundits are speculating that another crash is coming. Regardless of what happens in the near term, what we do know is that every year we will continue to see more and more industries succumb to the transformational power of the Internet.

Already transformed: music, news, advertising, telecom. Being transformed: finance, commerce, TV & movies, real estate, politics & government. Soon to be transformed: healthcare, education, and energy, among others.

Thus far the US has led Internet innovation. There are things the US can do to keep this lead, including: exporting the entrepreneurial ethos of Silicon Valley to the rest of the country, and allowing talented people to go where their skills are most needed – for example by changing US immigration policies.

Most importantly, we have too many people pursuing careers in banking, law and consulting. I personally encounter this bias all the time when I go to college campuses to recruit for startups. We need to convince the upcoming generation to innovate and take risks in sectors that have a direct impact on the quality of peoples’ lives.

So my advice is:
1) get rejected more
2) climb the right hill
3) create an amazing toy
4) grow that toy into something big that transforms an important industry

REVISIONS TO UNITED STATES PATENT LAW
As you may be aware, the Senate passed the America Invents Act (AIA) on September 8, 2011. This act will create sweeping changes in US patent law once signed by President Obama, who has stated his intention to sign this bill.

The AIA will create significant changes to the law, and we wanted to take a moment to inform you of some of its most important provisions.

First to File System:

The United States will move to a first-to-file system instead of a first-to-invent system. This will put the US in closer alignment with rest of the world in determining priority of invention based on the earliest date a patent application was filed with a patent office. There is a limited one-year grace period related to public disclosures made by the inventor.

Further, the long-standing procedure to prove a prior invention, i.e., interference proceedings, will be replaced with “derivation proceedings” to determine whether an inventor of a first-filed patent application derived the claimed subject matter without authorization from an inventor named in a laterfiled application.

Post Grant Review:

There will be a nine-month window for challenging a patent on any ground. Review may be granted upon a showing that it is more likely than not that at least one of the challenged claims is unpatentable. After the window of post-grant review has passed, patents may be challenged on the basis of patents or printed publications only. Under a new transitional post-grant review process that applies to certain business-method patents, only parties who have been sued for infringement or otherwise charged with infringement (the recipient of a cease-and-desist letter, for example), may petition for review.

Patent Related Provisions:

Patents will not be granted to any strategy for reducing, avoiding, or deferring tax liability, or to claims covering human organisms. There will also be a 15% surcharge added to all patent-related fees and patent-maintenance fees, beginning 10 days after the date of the new law’s enactment.

Prioritized Examination:

The USPTO will be authorized to proceed with a program for a fee-based prioritized examination, which may be a useful tool for clients who are interested in an expedited examination for particular patent applications. This will cover applications for original utility or plant patents, and will take effect ten days after the date of the enactment of this Act. Initially, only 10,000 applications will be accepted in any fiscal year. Accordingly, space in this program may be limited, and it may be best to apply for this program earlier in the fiscal year.

My (non-expert) analysis:  seems to me this doesn’t fix any of the very serious problems in our current patent system.  First-to-file seems to reward companies with the resources to file many patents.  The post grant review seems to imply you should to monitor every patent issued and challenge them within 9 months. I don’t see how any organization without massive resources could do this.

What belongs in common to the most people is accorded the least care: they take thought for their own things above all, and less about things common, or only so much as falls to each individually. – Aristotle *

A major policy goal of capitalist countries in the 20th century was to encourage home ownership. It is widely believed that owners take better care of their homes than renters as they have much more at stake financially. There is also evidence that home owners are happier, healthier, and participate more in civic and political life.

The desire to create an “ownership society” led to some smart policy decisions like the mortgage tax deduction and some bad decisions like hazardously low interest rates that contributed to the housing bubble. Home ownership is a noble goal even if home ownership fueled by excessive debt can be disastrous.

Entrepreneurs figured out a long time ago that the benefits of having equity in your company are similar to the benefits of having equity in your house. Silicon Valley expanded this concept by making it standard to grant equity to non-founder employees. It’s no coincidence that Silicon Valley continues to innovate and create jobs while the rest of the economy is stagnant.

Some people think we are in a startup bubble, and that once the bubble bursts people will run back to the supposed safety of non-startup jobs. I’d prefer to think we are at the beginning of a movement to create a true ownership society, where people own stakes not just in their space but also in their time.

“Do you want to sell sugar water for the rest of your life or come with me and change the world?” – Steve Jobs

I sometimes wish that instead of working on internet and software projects, I worked on cleantech or biotech projects. That way, when I came home at night, I’d know that I had literally spent my day trying to cure cancer or prevent global warming.  But information technology is what I know, and it’s probably too late for me to learn a new field from scratch.

That doesn’t mean information technology can’t improve people’s lives. Google’s search engine helps people find information, which, for example, makes cancer and cleantech researchers more productive. Skype allows companies to collaborate remotely, and connects people with friends and family around the world. In the area of information technology, we create infrastructure and hope that people use it for more good than bad.

That said, the best entrepreneurs seem to follow a path of increasing gravitas. Scott Heiferman started out selling online ads and is now creating new communities. Jack Dorsey created Twitter and is now democratizing payments so sole proprietors can compete on a level playing field with large companies. Elon Musk started with online payments and is now developing electric cars and space programs.

Founders of large companies sometimes also follow the path of increasing gravitas. Google is developing new energy technologies, self-driving cars and other world-changing technologies. Bill Gates devotes almost all of his time and money to charity.

The tech press is preoccupied with investments, trends, exits, and other “inside baseball” topics. But these are all means to an end. Investments provide fuel for entrepreneurs to convert ideas into products. Trends shape the terrain that entrepreneurs navigate. Exits provide financial incentives for investors and entrepreneurs.

Tim O’Reilly says that entrepreneurs should try to create more value than they capture. You can make money selling people obfuscated financial products, entertaining them with mind-numbing TV shows, or selling them sugar water decorated in elegant designs.

Alternatively, you can make something that matters and — if you are lucky and smart — change the world.

1) Some extremely successful startups. We need PayPals – companies that spin out boatloads of talented entrepreneurs and “smart money” angel investors. Big successes also reinforce the “culture of equity” that is so strong in California – the idea that owning options in a startup is the best path to financial and career success.

2) More web product design talent. This is the scarcest talent of all (more so than engineering). NYC has perhaps the best design community in the world, but most of the designers are trained in non-web design fields (e.g. print design).  Most of the good design schools don’t emphasize web product design (some exceptions – e.g. my friend Zach Klein taught an excellent class at the School of Visual Arts last semester on web product design). NYU’s ITP stands out as a program that focuses on the intersection of design and technology (e.g. the Foursquare team went to school there). CMU’s HCI program and MIT’s Media Lab are also great. Other schools need similar programs.

3) More engineers. However, this doesn’t mean we need more engineering schools (although that wouldn’t hurt). Like Silicon Valley, NYC is populated mostly by people who moved here from other places. For the right opportunity, it isn’t hard to convince, say, recent MIT grads to move to NYC.  The problem is that NYC startups are basically unknown to students at MIT, CMU, Penn, and even (shockingly) to engineering students at NYU and Columbia (big props to HackNY for trying to fix this). East Coast CS students also view startups as a much riskier path than they actually are. I say this having been at dozens of events with East Coast students over the last year or so talking about startups. I’m constantly amazed that most of the students simply don’t realize startups are a viable option. What we have is primarily a marketing, not a supply, problem.

4) High-speed internet throughout all the “startup areas” of Manhattan (Flatiron, Meat Packing, Soho etc) and Brooklyn (Williamsburg, Dumbo, etc). It’s amazing that we have such a fundamental infrastructure problem in a city as advanced as NYC, but I can’t tell you how many startups I know that struggle to get working high-speed internet access that has solid uptime.

5) More marquee tech companies opening large tech offices here. Google has something like 1500 engineers here. This adds a lot of vibrancy to the tech culture and attracts more engineering and design talent to the city.

Some things we don’t need:

1. Government or university organized events that introduce entrepreneurs to other entrepreneurs. There seems to be one such event each week. Entrepreneurs are by nature very good at meeting one another and it’s a small enough community that pretty much everyone already knows each other anyways.

2. Expensive projects like big engineering universities. Again, the more engineers and CS programs in the US the better (even better yet we need more CS majors – which probably means more CS education in high school and earlier), but I can think of far more productive ways to spend $100M to help the NYC startup and tech world.

3. Lower rents. No doubt the rents are too damn high and lower rents would be great. I’ve been living here since college when my room for one year was a hallway in a friend’s apartment. I sympathize with people who say this. But the idea that NYC is unaffordable on a typical startup salary is a complete myth. You can rent a decent place in a cool part of town on a typical startup salary. As to commercial space, for venture-backed startups the difference between rent in NYC and rent in other cities is generally the difference between spending, say, 3% versus 4% of your total financing on rent.

4. More early-stage investment capital. There are plenty of smart angels, seed funds, and VCs who are either based here or are based elsewhere but actively invest here.

Most of all what we need is for our tech and startup scene to reach critical mass (and to sustain that critical mass even if a tech downturn comes). Facebook wasn’t started in Californa and lots of future big successes will be started in all sorts of random places.  NYC needs enough tech critical mass that the next Mark Zuckerberg seriously considers relocating to NYC.

At Founder Collective, we think of ourselves as investing primarily in people, and only secondarily in ideas or products. I have to admit that until I heard about these situations happening, I hadn’t even conceived of the possibility of “pivots into new corporate structures”. In retrospect, I suppose it was inevitable given the founder-friendly market and the rapidly evolving venture environment.

As a legal matter, assuming the founders worked on the idea on the original company’s time and/or money, the seed investors probably have a strong claim. Founders and employees normally sign “invention assignment” agreements that would make the new ideas and products property of the original company (again, these aren’t situations I’m personally involved in so I am just speculating on the specifics).  The reality is that most professional seed investors aren’t going to sue founders and will likely instead try to work out some compromise.

This is not to suggest, by the way, that founders are indentured servants to investors. It is perfectly fine, if an idea isn’t working out, to wind down the company, return the remaining capital, and go off and work on new ideas. If one of those new ideas shows promise, the founders are then (legally and morally) free to form a new corporate entity and raise new financing from whomever they choose. From news reports, it sounds like this is what the Odeo team did before they pivoted to Twitter. It’s the conventional and, in my view, correct way to handle these situations.

Here’s what really worries me. If it becomes a norm for founders to jettison seed investors when their company’s focus changes, seed investors who invest “primarily in people” will stop doing so. I think that would be a real shame: we’d lose an important source of capital and a lot of innovative startups wouldn’t get funded.

This is bad news for everyone. Most significantly, founders often give up significant control to people they won’t get along with or even might end up hating. Having bad investors might not matter if the company executes flawlessly and the financing market stays frothy. But most companies have difficult episodes, and the financing market will eventually return to normal. Sadly, founders with bad investors will likely face punishing down rounds, key employees being indiscriminately fired, and elaborate financial shenanigans engineered to dilute founders and seed investors.

“It’s only when the tide goes out that you know who’s been swimming naked.” Warren Buffet likes to say this about investors, but it applies to founders as well. Taking on a new major investor should be treated with the same gravitas as taking on a new cofounder. You can’t do it in less time than it takes to really get to know someone, which is usually weeks or months. Quick financings might seem attractive but are actually fraught with risks.

The commons leads to overuse and destruction; the anticommons leads to underuse and waste. In the cultural sphere, ever tighter restrictions on copyright and fair use limit artists’ abilities to sample and build on older works of art. In biotechnology, the explosion of patenting over the past twenty-five years—particularly efforts to patent things like gene fragments—may be retarding drug development, by making it hard to create a new drug without licensing myriad previous patents. Even divided land ownership can have unforeseen consequences. Wind power, for instance, could reliably supply up to twenty per cent of America’s energy needs—but only if new transmission lines were built, allowing the efficient movement of power from the places where it’s generated to the places where it’s consumed. Don’t count on that happening anytime soon. Most of the land that the grid would pass through is owned by individuals, and nobody wants power lines running through his back yard.

From The Permission Problem, James Surowiecki, The New Yorker Magazine.  A very worthwhile read.

If nature has made any one thing less susceptible than all others of exclusive property, it is the action of the thinking power called an idea, which an individual may exclusively possess as long as he keeps it to himself; but the moment it is divulged, it forces itself into the possession of every one, and the receiver cannot dispossess himself of it. Its peculiar character, too, is that no one possesses the less, because every other possesses the whole of it. He who receives an idea from me, receives instruction himself without lessening mine; as he who lights his taper at mine, receives light without darkening me.

That ideas should freely spread from one to another over the globe, for the moral and mutual instruction of man, and improvement of his condition, seems to have been peculiarly and benevolently designed by nature, when she made them, like fire, expansible over all space, without lessening their density in any point, and like the air in which we breathe, move, and have our physical being, incapable of confinement or exclusive appropriation. Inventions then cannot, in nature, be a subject of property.

Society may give an exclusive right to the profits arising from them, as an encouragement to men to pursue ideas which may produce utility, but this may or may not be done, according to the will and convenience of the society, without claim or complaint from anybody. Accordingly, it is a fact, as far as I am informed, that England was, until we copied her, the only country on earth which ever, by a general law, gave a legal right to the exclusive use of an idea. In some other countries it is sometimes done, in a great case, and by a special and personal act, but, generally speaking, other nations have thought that these monopolies produce more embarrassment than advantage to society; and it may be observed that the nations which refuse monopolies of invention, are as fruitful as England in new and useful devices.

- Letter from Thomas Jefferson to Isaac McPherson

During that time, I was spending most of my personal time trying to develop new startup ideas. I ended up co-founding an online marketing company during school and then after school co-founding other companies (SiteAdvisor, Hunch, Founder Collective). Meanwhile, Facebook – the best internet business of the decade – was being hatched. Its first version looked a lot like classcards, and perhaps it wasn’t a coincidence that it was founded just down the street at the same university. The “toy” I was staring at every day was actually a much better business than all the “serious” ideas I spent so much time working on.

But it takes time to reach product/market fit. Founders have to choose a market long before they have any idea whether they will reach product/market fit. In my opinion, the best predictor of whether a startup will achieve product/market fit is whether there is what David Lee calls “founder/market fit”. Founder/market fit means the founders have a deep understanding of the market they are entering, and are people who “personify their product, business and ultimately their company.”

A few points about founder/market fit:

Founder/market fit can be developed through experience: No one is born with knowledge of the education market, online advertising, or clean energy technologies. You can learn about these markets by building test projects, working at relevant companies, or simply doing extensive research. I have a friend who decided to work in the magazine industry. He discovered some massive inefficiencies and built a very successful technology company that addressed them. My Founder Collective partners Eric Paley and Micah Rosenbloom spent many months/years becoming experts in the dental industry in order to create a breakthrough dental technology company.

Founder/market fit is frequently overestimated: One way to have a deep understanding of your market is to develop product ideas that solve problems you personally have. This is why Paul Graham says that “the best way to come up with startup ideas is to ask yourself the question: what do you wish someone would make for you?”  This is generally an excellent heuristic, but can also lead you astray. It is easy to think that because you like food you can create a better restaurant. It is an entirely different matter to rent and build a space, market your restaurant, manage inventory, inspire your staff, and do all the other difficult things it takes to create a successful restaurant. Similarly, just because you can imagine a website you’d like to use, doesn’t mean you have founder/market fit with the consumer internet market.

Founders need to be brutally honest with themselves. Good entrepreneurs are willing to make long lists of things at which they are have no ability. I have never built a sales team. I don’t manage people well. I have no particular knowledge of what college students today want to do on the internet. I could go on and on about my deficiencies. But hopefully being aware of these things helps me focus on areas where I can make a real contribution and also allows me to recruit people that complement those deficiencies.

Most importantly, founders should realize that a startup is an endeavor that generally lasts many years. You should fit your market not only because you understand it, but because you love it — and will continue to love it as your product and market change over time.

Allocation investing has a number of perverse effects on financial markets. For example, in the 80s and 90s venture capital was deemed to be a successful, independent asset class. As a result, many funds decided to allocate some portion of their capital to VC. These pools of capital were so large that they caused the VC industry to grow orders of magnitude larger – many say larger than it should be. In turn, this led to many bad venture investments that drove down returns in the industry (these problems were further exacerbated by the fee structure of VC that encouraged funds to get large and rapidly “put money to work”).

Another perverse effect caused by allocation investing happens in public stock markets when investors decide to allocate a portion of their funds to specific sectors. I recently heard some money managers saying they wanted to allocate portions of their funds to “social media”. Combining this “allocated” demand with a constrained supply (due to the small float of many of these IPOs) can lead to prices that are disconnected from fundamental values. In this scenario, supply will try to match demand, which means mediocre social media companies will go public and non-social media companies will reposition themselves as social media companies or acquire social media companies. They will be chasing the “social premium.”

We saw this happen in the 90s with the rush of companies to reposition themselves as internet companies. In that case, many non-professional investors ended up owning shares in crappy companies when the music stopped. The primary difference now is that the flagship companies like LinkedIn and Facebook have excellent fundamentals. Hopefully this time the market will be discerning and value investing will win out over allocation investing.

Here is an example of Lodsys’ accusations, in this case against bestbuy.com:

The reference to ’908 is referring to patent 5,999,908, which was filed in 1997.  It is an invention that appears to allow users to give feedback to websites:

Here is one example diagram from the patent about how the invention could be embodied:

Here is the specific claim (claim 37) that bestbuy.com and other retailers are allegedly infringing:

As far as I can tell, the first clause says that it the claim is referring to a computer product, which in the case of bestbuy.com seems to be their website, where the user and server can send information back and forth.  The second clause seems to say that this system includes computer code. The third clause seems to say this system includes a database.  The fourth clause seems to say there is a information transmitted between the user, web server and database.

I sketched some notes for the class which I’m posting below. I’ve written ad nauseum on this blog (see contents page) about venture financing so hadn’t planned to blog more on the topic.  But since I wrote up these notes already, here they are.

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1. Best thing is to either never need to raise money or to raise money after you have a product, users, or customers.  Also helps a lot if you’ve started a successful business before or came from a senior position at a successful company.

2. Assuming that’s not the case, it is very difficult to raise money, even when people (e.g. press) are saying it’s easy and “everyone is getting funded.”

3. Fundraising is an extremely momentum-based process.  Hardest part is getting “anchor” investors.  These are people or institutions who commit significant capital (>$100K) and are respected in the tech community or in the specific industry you are going after (e.g. successful fashion people investing in a fashion-related startup).

4. Investors like to wait (“flip another card over”) while you want to hurry. Lots of investors like to wait until other investors they respect commit. Hence a sort of Catch-22. As Paul Graham says:

By far the biggest influence on investors’ opinions of a startup is the opinion of other investors. There are very, very few who simply decide for themselves. Any startup founder can tell you the most common question they hear from investors is not about the founders or the product, but “who else is investing?”

5. Network like crazy:

• Make sure you have good Google results (this is your first impression in tech). Have a good bio page (on your blog, linkedin and about.me) and blog/tweet to get Google juice.
• Get involved in your local tech community.  Join meetups. Help organize events.  Become a hub in the local tech social graph.
• Meet every entrepreneur and investor you can.  Entrepreneurs tend to be more accessible & sympathetic and can often make warm intros to investors.
• Avoid anyone who asks you to pay for intros (even indirectly like committing to a law firm in exchange for intros).
• Don’t be afraid to (politely) overreach and get rejected.

6. Get smart on the industry:

• Read TechCrunch, Business Insider, GigaOm, Techmeme, HackerNews, Fred Wilson’s blog, Mark Suster’s blog, etc (and go back and read the archives).  Follow investor/startup people on Twitter (Sulia has some good lists to get you started here and here).
• Research every investor and entrepreneur extensively before you meet them. Entrepreneurs love it when you’ve used their product and give them constructive feedback.  It’s like bringing a new parent a kid’s toy. Investors like it when you are smart about their portfolio and interests.

6. How much to raise?  Enough to hit an accretive milestone plus some buffer. (more)

7. What terms should you look for?  Here are ideal terms.  You need to understand all these terms and also the difference between convertible notes and equity.  More generally, it’s a good idea to spend a few days getting smart about startup-related law – this is a good book to start with.

8. Types of capital:  strategic angels (industry experts), non-strategic angels (not industry experts, not tech investors), tech angels, seed funds, VCs.

• VCs can be less valuation sensitive and have deep pockets but are sometimes buying options so come with some risks (more).
• Industry experts can be really nice complements to tech investors (especially in b2b companies).  (more)
• Non-strategic angels (rich people with no relevant expertise) might not help as much but might be more patient and ok with “lifestyle businesses.”
• Tech angels and seed funds tend to be most valuation sensitive but can sometimes make up for it by helping in later financing rounds.

9. Pitching:

• Have a short slide deck, not a business plan. (more)
• Pitch yourself first, idea second. (more)
• Pitch the upside, not the mean (more)
• Size markets using narratives, not numbers (more)

10.  Cofounders: they are good if for no other reason than moral support. Find ones that complement you. Decide on responsibilities, equity split etc early and document it.  (Legal documents don’t hurt friendships – they preserve them).

11. Incubators like YC and Techstars can be great.  99% of the people I know who participated in them say it was worth it.

12. To investors, the sexiest word in the English language is “oversubscribed.”  Sometimes it makes tactical sense to start out raising a smaller round than you actually want end up with.

[Google] was too good. If Excite were to host a search engine that instantly gave people information they sought, [Excite's CEO] explained, the users would leave the site instantly. Since his ad revenue came from people staying on the site—“stickiness” was the most desired metric in websites at the time—using Google’s technology would be counterproductive. “He told us he wanted Excite’s search engine to be 80 percent as good as the other search engines,” … and we were like, “Wow, these guys don’t know what they’re talking about.” - Steven Levy, In The Plex (p. 30)

Famed investor/entrepreneur Reid Hoffman says world-changing startups need to be premised on “accurate contrarian theories.”  In Google’s case, it was true but non-contrarian to think users would prefer a better search engine. What was true and contrarian was to think it made business sense to get users off their site as quickly as possible. The business model to support this contrarian theory wouldn’t emerge until years later, and by then Google would already have become the world’s most popular search engine.

In theory, the primary societal purpose of derivates is for businesses to hedge against “exogenous” risks.  For example. Southwest Airlines is famously prudent about buying futures on oil to mitigate the effect of fluctuating oil prices on their core business.

In practice, most derivatives are bought and sold by speculators. One of the first speculators was a philosopher names Thales, who Aristotle described in his book Politics (Book 1, Part XI):

There is the anecdote of Thales the Milesian and his financial device, which involves a principle of universal application, but is attributed to him on account of his reputation for wisdom. He was reproached for his poverty, which was supposed to show that philosophy was of no use. According to the story, he knew by his skill in the stars while it was yet winter that there would be a great harvest of olives in the coming year; so, having a little money, he gave deposits for the use of all the olive-presses in Chios and Miletus, which he hired at a low price because no one bid against him. When the harvest-time came, and many were wanted all at once and of a sudden, he let them out at any rate which he pleased, and made a quantity of money. Thus he showed the world that philosophers can easily be rich if they like, but that their ambition is of another sort.

Valuing options was a mystery until 1973 when the Black-Scholes model was invented. The main practical outcome of this model was the idea that the value of an option was determined mostly by the volatility of the underlying security.

One way to understand the important of volatility is to think of options as the opposite of insurance policies. Suppose you are selling insurance on houses in one region that is prone to catastropic events and another that isn’t. Rational insurers would price insurance policies higher in the catastrophe-prone areas.

Startups are inherently very volatile – their price can increase or decrease dramatically in short periods of time. Having an option on a startup is the economic opposite of selling insurance in a catastrophe-prone area.

The US tax system has some rules related to startup options.  The first rule is that there is a special class of options called ISO options that can be granted to employees. ISO options are tax exempt until the options are exercised, which allows employees to receive them and not be liable for taxes until they actually realize cash gains. This rule only applies if the options are assigned a strike price equal to or greater than the “fair market value” of the company’s common shares. The fair market value is normally assessed by an outside valuation firm (a so-called 409A valuation) and usually ends up being significantly lower than the last round VC valuation (a rule of thumb for early-stage companies is the strike price will be approximately 20% of the last VC valuation).

When you are granted options in a startup there are a couple of important things to keep in mind:

1) You should know your percentage ownership of the company’s “fully diluted” outstanding shares (number of shares of the company including the option pool).

2) You should understand that if you leave the company, you normally have 90 days to “exercise” the options (purchase the shares you have the right to buy) before you forfeit your options. Normally the company has no obligation to inform you of this possible forfeiture, and in fact the standard practice is to hope the employee forgets and loses the options.

3) You should know the “preferences” on the company.  The preferences normally equals the amount of money raised. If the company sells for near or less than that number the common shareholders, and hence the employees (who own options on common shares), will receive little or no money.

The strike price of the options is somewhat important but, if you study options theory, not nearly as important as the volatility of the underlying stock. Financially, what matters most is having a reasonable percentage of options in a company with lots of volatility (and hopefully a stock price that has an upward slope).

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1. Valuation: Come up with what minimum valuation you’d be happy with but never share that number with any investor.  If the number is too low, you’ve set a low ceiling. If your number is too high, you scare people off. Just like on eBay, you only get to your desired price by starting lower and getting a competitive process going. When people ask about price, simply tell them your last round post-money valuation and talk about the progress you’ve made since then.

2. Never tell VCs the names of other VCs that are interested.  Reasons: 1) if you are overplaying your hand that could send a negative signal.  Most VCs know each other and talk all the time. 2) it is possible they’ll get together and offer a two-handed deal in which case you have less competition.

3. I think the optimal number of VCs to talk to seriously is about 5.  That is usually enough to get a sense of market but not so much that you get overwhelmed.  You should pick these VCs carefully – this is where trusted, experienced advisors are critical.

4. If there is a VC you really like, have a “buy it now price” and if they hit that valuation (and other terms are clean) do the deal.  Otherwise, say you’d like to “run a process” and include them in it.

5. Try to set timelines that are definite enough that investors feel some pressure to move but not so definite that you look dumb if you don’t have a term sheet by then.  (Investors have an incentive to wait – “to flip another card over” as they say – whereas entrepreneurs want to get the financing over with asap). Depending on where you are in the process, say things like “we’d like to wrap this up in the next few weeks.”

6. Once you start pitching, the clock starts ticking on your deal looking “tired.”  I’d say from your first VC meeting you have about a month before this risk kicks in.  You could have a great company but if investors get a sense that other investors have passed, they assume something is wrong with your company and/or they can wait around and invest later at their leisure.

7. The earlier stage your company is the more you should weight quality of investors vs valuation.  For a Series A, you are truly partnering with the VCs.  You should consider taking a lower valuation from a top tier firm over a non top tier firm (but probably any discount over 20% is too much). If you are doing a post-profitable “momentum round” I’d just optimize for valuation and deal terms.

8. Term sheets:  talk about terms in detail over the phone.  Only accept a term sheet once you have decided that if it matches what was described you are prepared to sign it.  After sending a term sheet VCs get worried you’ll shop it and usually want it signed in 24 hours.

9. Get to know the VCs.  Talk to their other portfolio companies, read their blogs, call references, etc.  You will be in business with this person for (hopefully) a long time.

10. Timing.  While it’s ideal to raise money once you hit the milestones you set out initially, you also need to be opportunistic.  Right now, for example, seems to be a really good time to raise a VC round.  You could make a ton of progress over the next 6 months but the market could tank and end up in a worse place than you would be today.

I don’t care if you succeed or fail, if you are Bill Gates or an unknown entrepreneur who gave everything to make it work but didn’t manage to pull through. The important distinction is whether you risked everything, put your life on the line, made commitments to investors, employees, customers and friends, and tried – against all the forces in the world that try to keep new ideas down – to make something new.

[Google CEO Eric] Schmidt said that while the Google Instant predictive search technology helps shave an average of 2 seconds off users’ queries, the next step is “autonomous search.” This means Google will conduct searches for users without them having to manually conduct searches. As an example, Schmidt said he could be walking down the streets of San Francisco and receive information about the places around him on his mobile phone without having to click any buttons. “Think of it as a serendipity engine,” Schmidt said. “Think of it as a new way of thinking about traditional text search where you don’t even have to type.”  - eWeek

When users type phrases into Google, they are searching, but also expressing intent. To create the “serendipity engine” that Eric Schmidt envisions would require a system that infers users’ intentions.

Here are some of the input signals a mobile device could use to infer intent.

Context

Location: It is helpful to break location down into layers, from the most concrete to the most abstract:

1) lat / long – raw GPS coordinates

2) venue – mapping of lat / long coordinates to a venue.

3) venue relationship to user – is the user at home, at a friend’s house, at work, in her home city etc.

4) user movement – locations the user has visited recently.

5) inferred user activity – if the user is at work during a weekday, she is more likely in the midst of work. If she is walking around a shopping district on a Sunday away from her home city, she is more likely to want to buy something. If she is outside, close to home, and going to multiple locations, she is more likely to be running erands.

Weather: during inclement weather user is less likely to want to move far and more likely to prefer indoor activities.

Time of day & date: around mealtimes the user is more likely to be considering what to eat. On weekends the user is more likely to be doing non-work activities. Outside at night, the user is more likely to be looking for bar/club/movie etc.  Time of days also lets you know what venues are open & closed.

News events near the user: they are at the pro sporting event, an accident happened nearby, etc.

Things around the user: knowing not just venues, but activities (soccer game), inventories (Madden 2011 is in stock at BestBuy across the street), events (concert you might like is nearby), etc.

These are just a few of the contextual signals that could be included as input signals.

Taste

The more you know about users’ tastes, the better you can infer their intent. It is silly to suggest a great Sushi restaurant to someone who dislikes Sushi. At Hunch we model taste with a giant matrix. One axis is every known user (the system is agnostic about which ID system – it could be Facebook, Twitter, a mobile device, etc), the other axis is things, defined very broadly: product, person, place, activity, tag etc.  In the cells of the matrix are either the known or predicted affinity between the person and thing.  (Hunch’s matrix currently has about 500M people, 700M items, and 50B known affinity points).

Past expressed intent

- App actions:  e.g. user just opened Yelp, so is probably looking for a place to go.

- Past search actions: user’s recent (desktop & mobile) web searches could be indications of later intent.

- Past “saved for later” actions:  user explicitly saved something for later e.g. using Foursquare’s “to do” functionality.

Behavior of other people

- Friends:  The fact that a user’s friends are all gathered nearby might make her want to join them.

- Tastemates: That someone with similar tastes just performed some actions suggests the user is more likely to want to perform the same actions.

- Crowds: The user might prefer to go toward or avoid crowds, depending on mood and taste.

How should an algorithm weight all these signals? It is difficult to imagine this being done effectively anyway except empirically through a feedback loop. So the system suggests some intent, the user gives feedback, and then the system learns by adjusting signal weightings and gets smarter.  With a machine learning system like this it is usually impossible to get to 100% accuracy, so the system would need a “fault tolerant” UI.  For example, pushing suggestions through modal dialogs could get very annoying without 100% accuracy, whereas making suggestions when the user opens an application or through subtle push alerts could be non-annoying and useful.

If you are a company that just raising seed funding, financing risk should be top of mind.  Here are some tips for mitigating it:

- Start by thinking about the next round of financing and work backwards.  What milestones do you have to hit to get VC funded at an upround?  If you are a consumer internet company, the milestone probably involves getting a certain number of users.  If you are building hardcore tech, it probably means building a working prototype.  Basically you want to take the main risks that exist at the seed stage and eliminate as many as you can. A good way to discover what milestones you need to hit is to talk to as many VCs as possible. Experienced seed investors can also advise you on this.

- Raise enough seed money. How much money will it take to hit those milestones?  A good rule of thumb is 18 months – 3 months to get going, 12 months to execute, 3 more months to raise VC.  But it really depends on the specifics of the milestones, your operational plan, etc. which is why you need to figure those out first.

- Preserve cash.  Pay only subsistance wages but be generous with equity for great people (this also provides a screen for hiring people with the right startup mindset).  Keep legal fees low (try to keep incorporation and financing costs to $10K or lower – this is one reason I prefer convertible notes).  Act like a scrappy startup.

A rule of thumb is a successful Series A is one that is led by quality VCs with a pre-money at least 2x the post-money of the seed round.

So this weekend I thought I’d try an experiment. I took about 100 of my blog posts (the ones that I thought were most “evergreen”), bundled them as a PDF and submitted them to the Kindle Store. The Kindle submission process was surprisingly easy. You give your book a name and upload the PDF and then choose pricing.  They force you to charge a minimum of $0.99.  Also, strangely, if you charge less than $2.99, Amazon takes 70% of the revenue, but if you charge between $2.99-$10 they only keep 30%.

I decided to price my book at $2.99 and donate all of the proceeds (~$2 book) to HackNY, a non-profit that “keeps the kids off the Street” (encourages college students to join/start tech startups instead of working on Wall Street). All of the content in the book is available for free on cdixon.org. The only reason to buy the book is to get this blog in a different format and to support a good charity. It is available in the Kindle Store here.

I don’t expect many people to buy the book but maybe some first-time entrepreneurs will stumble on it and from there discover more tech blogs. Think of it as “Kindle SEO” for tech blogs.

Finally, I am having trouble getting the links to work on the Kindle version. I’m not sure if this is an Amazon policy or if I am just doing something wrong (the links work fine in the PDF I uploaded to Amazon). So here is an alternative version on Scribd that has working links.