How to tell you’ve been working with your business partner too long:

———- Forwarded message ———-
From: Joshua Newman
Date: Fri, Jun 1, 2012 at 10:25 AM
Subject: Re: Cash flow through 31 May 2012
To: Hari Singh

Just updated the report. I assume we want to simply track “the number”, “the other number” and the actual members report number, yes?

j

———- Forwarded message ———-
From: Hari Singh
Date: Fri, Jun 1, 2012 at 10:28 AM
Subject: Re: Cash flow through 31 May 2012
To: Joshua Newman

Frighteningly, I think I actually understand what you’re asking here.

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Inside, Out

There’s been a lot written recently about ‘startup hubs’ – places like Silicon Valley and New York City, where the critical mass of investors and entrepreneurs create a positive feedback loop: the startups attract dollars, the dollars attract more startups, which in turn attract even more dollars, back and forth and back until a whole ecosystem of entrepreneurs and investors and employees and supporters crop up in one place, in a way that makes all of the players more likely to succeed.

Obviously, there’s a lot about that startup hub model that’s excellent, which is why most of the discussions have centered around how to create startup hubs in other places, or how to bolster them in places where they already exist.

But there are downsides to hubs, too. Chief among them the insular, almost provincial mindset that people tend to develop when they deal all day and night only with other people just like themselves.

Consider Hollywood, another sort of hub, which makes a disproportionate number of movies about making movies. If you’re in LA, every single person you talk with is somehow involved in the film industry, so movies about making movies start to seem like they’d have nearly universal appeal. *(Mea culpa: Back at Cyan, I actually exec produced a [totally indulgent, inward-focused, movie-making movie](http://en.wikipedia.org/wiki/I_Love_Your_Work). It sucked.)* Turns out, most people in the real world have only a passing interest in the business of the movie business, as the lackluster box office performances of film-focused films like *What Just Happened* and *The TV Set* demonstrated, despite their star-studded casts.

Similarly, in the tech world, a distressingly high percentage of the startups cropping up these days seem to solve problems and address pain points that only exist within that tech startup world. Consider the much-buzzed-about [Klout](http://www.klout.com), which simply ranks users’ power and influence by analyzing their social media habits. Outside the tech world, the vast majority of internet users could give two shits about how much of a ‘power player’ they are on Twitter. And even those who do might question the accuracy of a power and influence ranking system that puts a slew of bloggers ahead of President Obama. Still, inside the bubble, that seems reasonable enough to have driven a $30m funding round for Klout last fall – at a $200m valuation, and led by venerable VC Kleiner Perkins, nonetheless.

On balance, the advantages of startup hubs still clearly win out. But there’s real value in regularly traveling, socializing, and thinking outside of the confines of that hub. Facebook may now be a prime driver of the Silicon Valley startup ecosystem, but it started in a lonely freshman dorm room, three thousands miles away.

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Esq.

Over the course of my career thus far, I’ve spent enough on corporate legal bills to put an entire law firm’s children through college.

As I continue to dump dollars into legal costs – papering new deals, putting old ones to bed – I’ve started to think there should be some sort of law school equivalent of life experience credits.

Because if time working on contracts counted as sufficient prerequisite, I’m pretty sure I could by now totally ace the bar exam equivalent of the GED.

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Geek Ambassadors

More than a few people have observed that entrepreneurship is extremely simple: all it takes to build a successful company is to make something people want, then sell it to them.

Of course, there’s a difference between simple and easy. After all, 90% of new businesses fail. So entrepreneurs lay awake at night, thinking about how to grow their companies. But they tend to worry about the wrong things: how to make something, and how to sell it. In my experience, those parts aren’t actually the problem. Sure, getting the making and selling right requires ungodly amounts of hard work. As Paul Graham has described it, a startup is a bargain in which you squeeze a lifetime’s worth of work into three to five insanely hard years, in exchange for receiving a lifetime’s worth of salary at the end of that time. It’s tough. Very tough. But that work, the making and selling, is rarely where companies actually go off the rails. Indeed, it turns out both parts tend to yield eventually to smart, focused, head-down busting ass.

The thing that really kills companies is the part that founders worry about less: making something that people want. I’ve screwed that up in a bunch of ways in the past myself, and I’ve seen literally thousands of current and prospective companies do it, too.

Figuring out what people want is hard. And it’s hard for a lot of reasons. In the tech world, for example, it’s hard because builders tend to forget they’re different from regular users; hackers argue about the relative merits of Emacs vs VI, while according to recent research 90% of ‘regular people’ don’t use keyboard shortcuts. And it’s hard because, as Steve Jobs famously observed, those people don’t even know what they want until you show it to them.

So figuring out what people want is tough. During the first Internet bubble, VCs ‘solved’ that problem in a standardized way: by hiring MBA CEOs. Find someone with an HBS diploma and some biz dev / sales experience, put him (or her, but probably him) in charge, and task him with figuring out what users want, then with explaining it to the engineering team. While that sounds excellent, unfortunately, it doesn’t actually work, as the subsequent implosion of the internet sector demonstrated. In short, it turns out it’s nearly impossible to figure out what you should build, if you have no idea what you can or can’t build.

In today’s Internet Bubble 2.0, VCs read the lesson of the MBA CEO debacle as: put the tech guys in charge. Now, everyone wants teams of ‘technical founders’. But, in my estimation, that’s a bit of an oversimplification, as not all tech founders are the same. As Geoffrey Moore observed in his excellent (albeit slightly dated) Crossing the Chasm, bleeding edge types actually break into two, very distinct sub-groups: technologists, who are excited about technology for technology’s sake, and visionaries, who are excited about what technology can do for people, about how it might change real, day-to-day lives.

Both types these days pass themselves off as technical founders – that’s what gets funded. But when it comes to actually writing code, the visionaries tend to be more or less crap. Consider Foursquare founder Dennis Crowley – ‘technical’ visionary to Naveen Selvadurai’s legitimately technical technologist; while the two wrote the first version of the app together, their first hire, Harry, was initially tasked with rewriting all of Dennis’ code. At the same time, it’s the visionary who shoulders that crucial question of what people want. Hacking skill aside, it’s good news that Dennis squeezed his quasi-technical way to the helm, as Foursquare would never have grown to what it is today without his lead.

Even if we also call them ‘technical founders’, visionaries aren’t exactly tech peeople, nor exactly business people, but some weird hybrid, some kind of geek ambassador, living in the world between. As a result, the ideal technologist/visionary startup pairing is easy to miss – or, at least, to mischaracterize. Some would see the pair as a tech guy and a business guy, while others would see two tech guys. Neither is quite right. Because what, exactly, was Steve Jobs? Tech guy? Biz guy? Neither and both. He was the prototypical visionary to Woz’s prototypical technologist.

Recently, in an effort to re-secure the US’s place on the world innovation and economic stage, there’s been a strong push to increase the number of engineers coming out of America’s colleges and universities. But if we believe startups are a real driver of innovation and growth, I worry that education push will miss half of the founder equation. Our education system tends to divide students binarily into ‘art people’ and ‘science people’, giving short shrift to those in-between geek ambassadors.

Computer Science departments, for example, are notorious for disdaining ‘dilettantes’. If you’re not hacking compilers in assembly language, you might as well head back to the theater department, because most CS profs have little patience for or interest in anyone who isn’t at least willing to pretend they’re chasing a CS PhD down the line. Still, from what I’ve observed, at least a small number of budding visionaries manage to find ways to build the education they need, often hiding out in the slew of new ‘cognitive science’ majors that have popped up in the last decade – a spot that allows them to balance CS classes with psychology, philosophy, neuroscience and linguistics.

To grow the next generation of startups, we need to grow the next generation of both geek ambassadors and top-notch hackers, then to find smart ways to pair off the two. A technologist and a visionary. It’s the best way to build a startup that makes something amazing – something that people really want.

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Lean

I’ve been reading my old friend Eric Ries’ excellent new book, The Lean Startup. If you do – or want to do – anything entrepreneurial, in any industry, you’d be well-served reading it, too.

The hard truth is, most new companies fail. We write that failure off to bad luck, to bad timing, to bad leadership. But, really, we have no idea. Every new business faces a barrage of unexpected challenges, wades through strings of ambiguous victories and nebulous defeats. In the end, some companies thrive, while others disappear. That’s how entrepreneurship is, we say; it’s more art than science.

But, usually, when we say something is ‘more art than science’, it later turns out to be a science we just don’t yet fully understand.

Consider the world of medicine, where doctors diagnose patients. A uniquely human task. Governed by instinct and gut feeling. Another art!

Really? Or is it a science that depends on reserves of implicit knowledge that great diagnosticians possess but that they simply can’t explicitly articulate? I’d argue the latter. Which is why, over time, after decades of careful analysis and modeling and increases in computing power and information storage, we’ve begun to explicitly match that implicit knowledge, and computer-aided diagnosis systems have started to empirically best what physicians can do themselves.

So, too, in the startup world, where it turns out that a rigorous reliance on data, a unified customer-development process, and an adherence to agile development methods may take some of the ‘magic’ and ‘genius’ out of startup ideation and execution, but hugely up the odds of actual, lasting success.

Which is all to say: buy the book.

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In 1999, I think right after the iMac came out in a range of colors, I happened to sit in on an internal meeting at Apple, one in a large theater filled with employees. Steve Jobs came out and the whole theater burst into applause, and the clapping went on for minutes, with people standing and cheering. The success of the iMac was just becoming evident – the first act of Steve’s big return, leading from there to what Apple is now.

Steve let the applause go on for a little bit, then, with much effort, settled down the crowd. When things got quiet, the first thing he said was: “That’s an awful lot of applause considering that you guys are the ones who do all the work.”

– Marc Hedlund

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Have Relations With

I often hear from people that theirs is a ‘relationship business’, and that it therefore isn’t really susceptible to the influence of technology.

In my experience, there are two different types of businesses that are driven mainly by relationship: commodity businesses – where any choice is as good as any other – and businesses with terrible data – where people have no idea if any choice is better than any other.

In commodity businesses, perhaps that makes sense.  If you’re buying crates of #10 envelopes – all roughly the same in terms of quality or price – you might as well buy from the guy with whom you’d like to have expense account drinks.

But in data-less businesses, the situation is far less sensible.  A restaurateur stocks a given liquor due to relationship only because he can’t quantify whether his customers would more likely purchase a different drink, in a way that would yield better profits, customer satisfaction, or other ROI.

And, indeed, in the majority of professional or creative businesses – from medicine and law, to music, film, publishing, and fashion – where so many decisions are ‘relationship-driven’, I strongly, strongly suspect things fall into that second, less sensible, data-less relationship category.  Decision-guiding data has already started showing up increasingly in those worlds; as the data trickle turns to flood over the next five years, those industries will start looking very different than they do today.

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Coopetition

After ten years spent in the film world, dipping a foot back into the tech space has been a bit of a culture shock.

Tech people seem happy to help out even strangers at other companies, just for the good karma. Whereas in the movie world, even close friends secretly root for one another to fail, if just for the frisson of Schadenfreude.

I suspect that difference stems straight from the trajectory of the two industries: the tech space’s total market cap is growing rapidly, while the movie industry’s total grosses have held largely static.

In that context, it makes sense for film folks to resent the success of other players: in a zero sum game, others’ wins necessitate your losses. Whereas in a growth industry like tech, someone else’s achievements don’t inherently undercut your own.

In fact, as many tech companies and products benefit from [network effects](http://en.wikipedia.org/wiki/Network_effect), others succeeding is likely even a net positive, a rising tide lifting all boats (or, at least, all valuations).

Which is to say that, for whatever reason, the large number of tech people I’ve been dealing with of late have all been remarkably nice. After a decade of dog eat Hollywood dog, it’s a welcome change.

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Filmmaker == Hacker

Having split my professional life between the tech and movie worlds, I’ve always been struck by how similar filmmakers and hackers are. For example, both groups:

  • Think about the world as a collection of fascinating material to be mined / problems to be solved;
  • Disdain things that are boring and have already been done;
  • Distrust tradition/authority as a sufficient rationale in and of itself;
  • Respect competence and support meritocratic structure;
  • Work collaboratively and share ideas and solutions (even with ‘competitors’);
  • Are willing to put in huge amounts of work, even when unpaid, just for the love of the game.
  • And, most importantly, want to share the things they pour their hearts and souls into making with as many people as they possibly can.

In the tech world, that’s easy for hackers to do: they start startups, build stuff on their own terms, and then share their stuff with users by building direct customer relationships.

In the movie world, however, filmmakers haven’t had such a direct route; instead, they’ve traditionally had to rely on studios and distributors to build those relationships for them.

Now, sites like YouTube allow filmmakers to share directly. But those sites also don’t generate real filmmaker revenue. And while filmmakers (like hackers) don’t actually care all that much about getting rich, they do at least want to make enough money making their stuff that they can live comfortably, and show their investors strong enough returns to play again as soon as they come up with their next big idea.

With more and more films being made each year, it seems almost inevitable to me that new solutions will emerge somewhere between the studio and YouTube models – solutions that help filmmakers build broad audiences, profitably, and in ways they directly control.

I’ve been giving that a lot of thought of late. Because it seems like that’s a big problem waiting for a solution – and an equally big business waiting to be built.

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10k

There’s an excellent story in a recent edition of Tampa’s St. Petersburg Times, about Dan McLaughlin, a guy who’s decided to take up golf.

Or, rather, a guy who’s decided to really take up golf. Despite having never played before, he’s set his sights on a slot in the PGA tour. His plan is simple: practice golf for 10,000 hours over the next six years. (That’s six hours a day, six days a week, for those without a calculator.)

It’s a great, albeit clearly insane, experiment, that puts to test an academic theory popularized most recently by Malcolm Gladwell’s Outliers: that becoming truly excellent at something requires less talent and natural skill, and more a willingness to put in about 10,000 hours of hard, focused work.

If that theory is right, by the end of six years, Dan should be one hell of a scratch golfer. If not, then perhaps some of the research on expertise is bound back to the drawing board, and Dan is clearly headed back to a real job.

Either way, I’m curious to see how this pans out, so I’ll be following along at his blog, www.thedanplan.com. But I’ll also be giving some real thought to where the 10,000 hours idea might apply to my own life.

Because, at some basic level, much as I’m impressed with Dan’s commitment and focus, I’m also pretty sure I wouldn’t want to spend six years of my life devoted to nothing other than being a better golfer.

What I’m less clear on is, what would I devote six years to? And, similarly, where have I already been chalking up serious practice hours?

There’s trumpet playing, for example, which I’ve been doing regularly since the age of nine, and where I’ve, by napkin calculation, amassed about half of the expert count, weighing in somewhere near 5,000 hours total.

But there, too, I’m not (and don’t want to be) a full-time professional trumpet player. I do consider myself a full-time entrepreneur, however. Though, on that front, I’m not sure my daily work really qualifies as hard, focused practicing of entrepreneurship. In the world of practice research, that would be ‘deliberate practice’, which roughly boils down to:

1. Focusing on technique as opposed to outcome.
2. Setting specific goals.
3. Getting good, prompt feedback, and using it.

So I’ve been thinking about how I might make my work more deliberately practiceful. About what other areas of interest might warrant 10,000 hours of focus. And, finally, about how, as I’m certainly unwilling to put in 10,000 hours of practice on it, I’ll likely always be terrible at golf.

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