Artisans vs. Armies

There are moments in the history of software, when a product created by a tiny team has invented or transformed entire markets.  I was struck by evidence for a similar model in evolutionary biology: the theory of punctuated equilibrium, where there are long periods of relatively little change followed by short and dramatic periods of upheaval.

This kind of rapid change, brought on by an insightful act of creation, has happened repeatedly.  Afterwards, the market leaders usually settle into a period of stability and incremental refinement, backed by large teams.  For example:

UNIX: Ken Thompson and Dennis Ritchie were working at Bell Labs, and became disenchanted with a large-scale project to design a novel operating system, called Multics.  In reaction to its complexity, they created a much simpler alternative and impishly called it “Unics” (later renamed to Unix).  Thompson described Multics as “overdesigned and overbuilt and over everything” (a common complain about systems built by armies!).  Unix went on to become one of the two dominant server operating systems; it is now enhanced and maintained by an army of its own – thousands of developers around the world.

Visicalc: while a student at Harvard Business School, Dan Bricklin got tired of doing spreadsheets on paper.  He thought that he could use a personal computer to help, so he wrote Visicalc for the Apple II and transformed the role of the personal computer in business.  The spreadsheet has long since moved to the other model – Microsoft Excel has dominated the market for many years.

Electronic Arts: The company was originally created by Trip Hawkins in 1982 with a vision: find the brilliant programmers who could create amazing games for small computers, and celebrate those artists and their creations just as we do with great musicians.  One of my friends from junior high school wrote an early EA game (called Axis Assassin).  It was a very impressive homage to his favorite arcade game, Tempest, and he was the sole programmer who built it.  I still have the packaging with his picture and bio in it (at the ripe age of 18).  But that notion of the individual artist was abandoned by EA many years ago.  Now they make games like Madden NFL, which is built by 30 developers and has more than 10 million lines of source code.  The big PC and console games involve massive multi-year investments.  The artisans have moved to mobile, a disruptive domain where very popular games with millions of users are still being created by tiny teams of people.

American culture, I think, has always been caught between a celebration of the small (the lone inventor in a workshop building a better mousetrap, the small farmer setting forth in a Conestoga wagon on the Oregon trail, the “small is beautiful” philosophy of the 70s) and a celebration of the large (the great skyscrapers – “cathedrals of the machine age”, the massive industrial output that powered our economy and made us victorious in the world wars, the space program that landed astronauts on the moon).  Like the technology industry, our culture is tugged back and forth between these two extremes.

The Model

Across all of these examples, I find that there is a somewhat consistent pattern.  Typically, a new opportunity opens up due to some key technology transformation (like the advent of the PC or the Internet), which is not yet dominated by large established organizations.  Some ground-breaking programmers dream up a new kind of product and create it, often as an act of passion rather than of calculation. The new idea gathers popularity, and over time it either grows a large company around it or (occasionally) is taken over by some existing player that wakes up quickly enough and buys or builds their way into a dominant position.

Once a kind of software has become well-established, it usually stops being the realm of the artisan and becomes dominated by large, well-financed teams.  Division of labor was one of the foundational ideas of the machine age, allowing our society to generate massively more output than it ever could have from the labors of loosely organized artisans in their guilds.  The artisans in most industries were washed to the sea by mega-giants.

But division of labor has a great flaw in times of turbulence – it is extremely hard to rapidly re-architect large products or large teams.  At scale, nobody knows the full story of how either one functions.  In software, the products may be millions of lines of code.  The working relationships among hundreds of specialized experts on an engineering team is a tremendously complex system of its own – redesigning it can be even harder than redesigning the software.  Clayton Christenson and others have eloquently written about how hard it is for established players to reinvent themselves.

It’s Not Just Software

This alternation between artisan and army is not restricted to software.  I was fascinated to learn what happened in the 1800’s in manufacturing, elegantly described in the book The Tycoons (which I highly recommend).

During the Industrial Revolution, British industry was transformed by machine-based manufacturing.  Individual artisans were unable to compete and were largely supplanted.  That part I knew.  What I didn’t know, is that there were some key inventions in manufacturing that had the side-effect of making the roles within a factory require far less individual skill and judgment.  The British were slow to adopt them, and most British plant workers were artisans – in the 1890s, three-quarters of them were highly trained crafts-people with a lifetime of expertise.  By contrast, American plants had virtually none – somebody could be trained for almost any role in the plant relatively quickly.

For this and other reasons, American industry production sky-rocketed past the British.  In 1860, US output was one-third of Britain’s.  Fifty years later, it was 2.3 times larger (!).  Manufacturing has remained dominated by mass scale ever since, though there are interesting early signs of another major shift.  The rise of 3D printing technology makes it cost effective to do very small runs – we may see a new renaissance for the artisan manufacturer.

Another example is movie-making.  United Artists was founded in 1919 by four directors and actors, including Charlie Chaplin and Mary Pickford (two of the most popular actors of the day).  The vision, embodied in its name, was to create a place where the artists dominated, not what today we might call the “suits”.  The company struggled because the industry was moving to longer movies with high production values that required large teams and big investments (sound familiar?).

The company, and the broader industry, seesawed back and forth.  In the 1960s, United Artists created the Bond blockbuster franchise.  In the 1970s, they were involved in the shift towards small “auteur” movies that represented the singular vision of a one person (like Midnight Cowboy).  Then back to blockbusters in the 1980s.  Lately, “indie” pictures are all the rage.  The dynamics of the movie industry have interesting similarities to software, shifting back and forth across the spectrum between creation by artisan or by army.

We’re In a Time of Radical Change

As I’ve written elsewhere, because of the cloud and devices, technology is in a time of radical transformation – a lot of equilibriums are being punctured right now.  It’s a hard time to be an established leader – a threat can develop out of nowhere from a couple of passionate developers with a new idea, and it can grow to massive size in the relative blink of an eye.

But it’s a magical time for the artisans – they can challenge the dominions of the giants, tweaking the noses of the biggest companies in the industry.  And if they are right and they have a winning idea, they can have a tremendous impact.  You don’t need an army to change the shape of an industry – you can build a program and, with no capital investment at all, make it available to a billion people in an hour.  If you crack the code and build something that has real demand, there are ready accelerants poised to support you.  Investment capital is abundantly available to companies that have gotten traction, and people with every kind of specialized skill are ready to jump on the train once it has begun gathering speed.  I call it “scale fast or fail fast”.

I believe that during the next several years, many domains of human endeavor will be radically reshaped by small teams of scrappy challengers.  They will seize this period of transformation to forge and pursue new visions that will change the dynamics of whole industries.  It will be fascinating to see what they come up with.

Do You Learn More at a Startup?

I’ve had The Debate many times with people at very different stages of their career – whether to go to a startup, or to work at an established company.  One of the classic arguments for the startup is that you learn more than you would inside the belly of the beast at a large company.

Why it’s True

One of the distinctive things about life at a startup is that everything happens at a hyper-accelerated rate.  Which means that for a given amount of time, you will generally experience much more of the lifecycle of a product, a business, and a company.

I experienced this really vividly when I did my second startup, a  I left Microsoft for the opposite coast to co-found the company.  In two years, we grew it from a few people to over 100, built a massively scalable server infrastructure from scratch and shipped it in six months, became the 50th most active site on the Web, went on a road show and took the company public, lived the exhilaration of flying high, got caught up in the crash and watched our stock go into the tank, had it come back to a more reasonable level, and merged the company with another.  Then my previous partner convinced me to come back to Microsoft to do an internal startup .. and I ran into people who were still working on exactly the same product cycle they had been doing when I left (!).  I felt like a traveller who has gone out into the world, had exotic adventures, and feels utterly changed by them, only to come back and encounter the polite incomprehension of the folks who stayed at home muddling along just as usual.

Another thing is that you typically get involved in a much broader range of activity.  At a big company, division of labor exists (must exist!) at an extreme.  There are hundreds of finance people at Microsoft who are extremely expert at what they do, so your involvement in that discipline even at senior levels of business ownership is very limited.  You consume their work, but that’s very, very different from actually doing it.  Similarly for legal, HR, recruiting, sales, lab management, datacenter design, office facilities, networking infrastructure, ad infinitum.

At a startup, there aren’t any specialists in most areas, so you have to jump in and do them yourself.  You get exposed to many aspects of the business that you wouldn’t otherwise know anything about.  If you like a holistic understanding of what’s happening, you love that.  If you want to focus deep in an area, it can drive you nuts.

But .. It’s Not That Simple

That’s the “pro” argument, but there’s another side of the coin that I think is often glossed over by the advocates.

Because things are moving fast and there aren’t a lot of “experts” around, you usually won’t get trained with any kind of deliberation.  Big companies are very uneven about how thoughtfully they develop their people, so it’s by no means assured that you will get a better experience, but hopefully you will.  I think one of the best way to learn, especially early in your career, is to “apprentice” with a more experienced and expert person.  Ideally, they are a great coach who will push you with challenging work, will evaluate it deeply and give detailed feedback, and they will be there to help when (and only when!) appropriate.  I think you are more likely to get that experience at an established company ..  but lousy managers abound everywhere, so you’ll have to be lucky or smart to find a good one.

It’s rare to get the opportunity to learn big and complex things systematically.  There are areas of expertise that are deep, hard, and take time to absorb.  Things like operating system and database kernels, distributed system design, compiler optimization, and machine learning, are systematic bodies of knowledge that call for the accumulation of knowledge and wisdom over many years to become a true expert.  In startups, you are scrambling like hell and need to get something up that works, so it’s hard to create something that is carefully and thoughtfully designed for the long term.  There are wonderful counter-examples of well-architected systems built by startups, and many pieces of crap built by big teams at established companies, so this is not some universal law.  But, in my experience, you are more likely to get a chance to master those kinds of areas at a big company that has the resources to invest in thoughtful architecture and quantities of deeply trained people available to work on it.

Running a business at scale is different than running a small one.  You won’t learn how to operate at scale at most startups.  Managing teams of hundreds of developers, keeping hundreds or thousands of sales people productive, coordinating hundreds of subsidiaries around the world – these are very difficult things to do well, and you won’t learn about them at a small company.

How it Nets Out

So will you learn more at a startup?  It depends on what you want to learn.  If you want to experience the whole business from customer experience to support to revenue, choose a startup every time.  If you want to move fast and see a lot of things quickly, ditto.

But, if you want to go really deep and immerse yourself in something complex, or you want to train yourself in your craft (whatever it is – systems programming, project management, finance), or you want to learn how to operate at high scale, you might find that you will do better at a larger and more established company.

What’s my approach?  Do both.  I have had by far the most fun at the three startups I’ve done, but I’ve learned powerful lessons at large companies that serve me well in everything I take on, with teams large and small.  And if you are at a startup, and it’s successful, then it’s nice to know that you have experience operating at larger scale – you won’t have to learn every lesson on the fly, when it’s life or death for the company that you do it right.

Rise of Data Science

Radically accelerated by the advent of cloud computing and devices, a role has begun to develop that will flourish in the coming years, and I am convinced that it will have a major impact on our lives.

New technologies often usher in new disciplines; they typically begin as a chaotic area of focus, with all sorts of people falling into them from different backgrounds.  Over time, they take on structure, books are written, educational and training programs develop, and they turn into a mature discipline.  That’s what happened when the Web was created – building a web site requires a mix of skills that draw from what had been quite separate worlds of activity: art and visual design, image processing, and programming (among others).

The same arc happened a few decades earlier when programming was invented – it drew from fields like mathematics, engineering, and linguistics.  It attracted people from those fields and many others (including more than a few high school students who were supposed to be doing something else!).

This new field hasn’t been officially named yet, but one of the terms that people are using for it is “data science”.  I’ve been diving into it pretty deeply for our startup, and some remarkably interesting work has been happening over the past several years.

What Does a Data Scientist Do, Anyway?

As you would expect from an emerging discipline, people don’t agree yet on exactly what it is all about.  But the fundamental idea is that enormous bodies of data are being gathered through software, and somebody has to make sense of them.  The analysis can influence decisions that people make (“hey, this version of our web service gets 15% more people to sign up for an account than the other one”) and decisions that software makes (while browsing items on Amazon, the web site will tell you that people who bought this product also were interested in …).

A data scientist is somebody who figures out what data to gather, how to analyze it, and what to do with the results of that analysis.  The discipline combines ideas from areas like statistics, machine learning, mathematics, databases, and psychology.

What’s it good for?  Well, here are just a few ways it is being used today:

  • The magical ability of Google search to find what you need from a couple of words and no other hints.  Compare that experience to what you typically get from software – you usually have to tell applications in painfully explicit detail exactly what you want, in very tightly scripted sequences of commands, and it can be extremely frustrating if the programmers haven’t anticipated what you want.  With Google, you type just about anything into the search box, and with incredibly high probability, it will give you a useful set of answers.
  • The ability to recommend things that are likely to interest you.  Amazon is very, very good at helping you find a book you want on any subject under the sun, through a combination of search and recommendations.  Netflix has gotten to the point where 75% of the shows that people watch on their streaming service come from a recommendation
  • Web sites present users with multiple versions of their product simultaneously, watch how users react, and pick the best one.  Large web companies are running dozens or hundreds of these A/B tests simultaneously and are updating their product daily based on the result.  I used to ship large packaged software products to enterprises, and we would conduct a manual poll of our users years after we shipped to try to figure out whether they used the product and what they did with it – the results were very spotty, very late, and highly inaccurate.  It’s like trying to drive by covering the windows of your car with black paint and having somebody write you an occasional letter about where you are and the condition of the road.

Those are just a few examples – almost every Web-based company depends on data science as its lifeblood to make its product come alive for users and to run its business internally.

The Future

What’s being done today with data science, while impressive, just scratches the surface.  The current economic models have only begun to evolve.  And many parts of our lives remain deeply inefficient and filled with friction:

  • Transit is very wasteful – guessing about traffic patterns, individual drivers maneuvering 3000 pound chunks of metal with dubious competence.
  • Integration of medical carediagnosis, and monitoring our bodies, remains technologically primitive.
  • Energy use is highly inefficient, partly because we have little idea how to optimize or the implications of our decisions.
  • Education hasn’t improved much in the last few hundred years, when President Garfield said that the ideal college was a famous teacher (Mark Hopkins) at one end of a log and a student at the other.  It’s arguably the most important competency of a successful nation in the modern age, and our system (in the United States at least) is hardly flourishing.

Along with much of the economy, these areas are ripe to be transformed, and I am convinced that data scientists will be at the heart of that transformation (for good and for ill!).  If you’d like to learn more:

It’s a discipline that I think anyone involved in technology should understand at some basic level.  Pretty much whatever you do these days, there are probably large quantities of data being generated around it that can be mined for insight.  You want to leverage this power, to make your own decisions and to create a great experience for people using your software.  It’s going to continue to transform the world over the coming years .. and maybe you can become a real-life Hari Seldon.

We’re Living in Florence, in 1450 A.D.

If you work in technology, you have the amazing luck to be in the midst of one of the great transformations of human society.  There have been numerous times in history when technology has transformed the way we live, our understanding of the world, and the life we are able to experience.  I’ve had one of them on my mind a lot lately – the Renaissance.  I think there are very interesting parallels to be drawn.  It feels like we’re at the height of the first round .. which would put us in Florence, around 1450.

What Caused The Renaissance?

Many forces came together to enable that astonishing transformation of knowledge, art, architecture, and commerce, whose profound impact shaped the world and still fascinates us.

There were some key technology breakthroughs.  Gutenberg is famous for inventing the printing press in 1440, which greatly expanded our ability to distribute ideas.  But just as important, and less frequently remarked upon, was the spread of paper.  We take it for granted today, but it was a magical boost to our ability to capture and disseminate ideas.  Paper is far less costly to produce and can be manufactured in much greater quantity than alternatives like vellum, made from animal skins.  Invented in China in 100 AD, paper remained a closely held secret for several hundred years, but had become widely used by the time of the Renaissance.

The ability to travel and to trade was revolutionized by ocean-going ships (like the Portuguese caravel), which were capable of navigating the globe.  At the same time, the mariner’s astrolabe made it possible to measure latitude anywhere in the world.  With weapons like the arquebus, small groups were able to wreak havoc among less technologically advanced populations.

New technology called for new technique, as well.  The development of merchant capitalism, along with sophisticated means of tracking commercial activities like double-entry bookkeeping, allowed a modern system of banking to emerge.  It was banking that made Florence so wealthy, and that wealth enabled major investments in science and the arts.

In addition to a major infusion of money, the arts were transformed by new techniques as well.  Paintings became far more realistic using linear perspective.  Architecture took advantage of construction techniques both novel and rediscovered.  Grand new structures were created that finally matched and exceeded marvels (like the dome of the Pantheon in Rome) that had been built 1400 years earlier.

This confluence of breakthroughs in technology and technique allowed Europe to leap forward and become the dominant world power in a remarkably short period of time.  Businesses grew to previously unheard of scale and their activities reached across the globe.  Ideas moved much more quickly, too, because they were carried along by the people who were associated with this explosion of trading activity.  Control of knowledge moved from guilds to a mobile class of experts.  Liquidity, supported by precious metals imported from the New World, began to move the basis of wealth from land to capital.  Our world view also began to shift radically – from deism, centered on God, to humanism.  Our conception of the universe was rocked by the discovery that we were one of many planets orbiting around the sun.

The Modern Renaissance

Fast forward to today, and consider what is happening.  In technology, we are seeing two massive changes: devices and the cloud.  The cloud has transformed the cost and reach of computing.  By most estimates, Google runs well over a million servers in their data centers and handles something like three billion searches per day.  This is technology operating at a global scale that was absolutely inconceivable a few years ago.  At the same time, the programmable cloud has made it extremely cheap to build and deploy software.  For a few hundred dollars a month, a programmer with a laptop can take a program they have written and within minutes make it available to more than two billion people.

Smartphones and similar devices are also astonishing in their capability and their reach.  There are now around 1 billion smartphone users in the world with the Internet in their pocket and accessible at all times.  That number is growing rapidly – estimates are that there will be a billion net new smartphone users in the next few years.  The Apple App Store just crossed 25 billion downloads.  The pace of growth and the scale of what has already happened are just staggering.

As always, new technology encourages innovation in techniqueOpen source software has been around for decades, of course, but it has gotten a major boost from its intimate relationship to cloud computing.  A wide body of high quality components are available for free to anyone who wishes to build cloud applications, representing a dramatic reduction in the time and effort required to go from idea to product.  We’re benefiting from that tremendously in our startup.

Another key change is the move from on-premise software to software as a service.  It means that the latest version of every application is available to every customer, without their needing to deploy or manage it.  Services pair nicely with, and encourage, the shift from physical to virtual – instead of manipulating objects, increasingly we’re manipulating data.  We are doing research and developing new products using simulated environments.  We’re transporting knowledge and entertainment as packets over networks, not by sending boxes of plastic and paper around the world.  Increasingly, the basis of value is rooted in virtual goods and services.  I believe that is as profound an economic change as the shift from land-based wealth to capitalism.

Signposts of the Revolution

We have seen some dramatic evidence of the impact that these changes will have, but I think we’re just at the beginning.

  • Facebook has over 900 million active users, and is on track to hit a billion later this year.  It has grown to that size in .. eight years.  To put that in perspective, China’s population today is 1.3 billion; it took around 250 years to grow the last billion (and it took human beings about 12,000 years to hit their first billion).
  • Speaking of Facebook, they recently purchased Instagram.  This company, which serves 30 million users has .. 13 employees.  Two developers run the back-end service for their users.  A few years ago, it would have taken a big company with major resources to support that many users, and now it can be done with a handful of people and no capital expense at all.
  • Consider that icon of the industrial revolution – the car.  A modern premium automobile has something like 100 million lines of code to run the nearly 100 processors distributed throughout it.  It was simulated extensively on supercomputers, is supported by myriad online services, and the supply chain that delivered it to you only works because of massive amounts of software tracking every minute aspect of its progress in real time.

I could go on, but the point is that virtually every industry is in the process of being transformed by the combination of the cloud and the device.  The way we make discoveries and create new inventions.  The way we communicate.  How and what we buy.  How companies interact with each other and with their customers.  And this is all happening incredibly quickly – the cost and effort for new ideas to be tried, refined, and deployed globally has dropped to the floor.  We’ve seen some dramatic changes already, but that was just a warm-up – we’re in for quite a ride.

The Path Ahead is Uncertain

In 1450, Florence was unquestionably at the forefront of the Renaissance, and the city was dominated by the Medici family.  By 1500, the focus of the action had moved elsewhere in Italy and across Europe, and Florence never regained its dominance.  What happened?  Well, for one thing, Charles VIII of France invaded Italy in 1494 and kicked off the Italian Wars, a series of conflicts that involved various city states and several empires.  That first invasion forced the Medici to flee the city, though they returned and ruled it again later.  In the meantime, other parts of Italy and Europe took over and led the Renaissance forward.  I suspect that the fortunes of the early players in our current Renaissance will also dramatically rise and fall.

And worse than losing leadership, there is a darker side to change.  We like to celebrate the Renaissance and the great leap forward in human capability that it represented.  But it wasn’t positive for everyone; it was particularly brutal for indigenous cultures around the world who were now within reach of the Europeans.  Many of them were despoiled and enslaved.  The current changes will not be as violent, hopefully, but we have seen these forces help governments fall and companies be humbled, and there are industries filled with people whose economic future will be dramatically affected.

We can never know ahead of time how things are going to shake out for particular groups during times of great change.  But when transformative forces come along that are this strong, they cannot be denied – they will transform our lives, culturally and economically.

Leonardo Da Vinci.  Michelangelo.  Brunelleschi.  We are still inspired by what they accomplished.  They were amazing people … but they also had amazing luck.  They lived in a magical time and place in the history of mankind.  So do you.  How are you going to be part of this modern Renaissance?

On Being Acquired – Lessons Learned

Once upon a time, I was one of the three full-time employees at Colusa Software, which Microsoft acquired in 1996.  We all came to Microsoft as part of the buyout, and went on to learn some interesting lessons about having your very small company acquired by a very large one.

Who We Were

Colusa was building some nifty virtual machine technology – you could target it from any conventional language, could run in a protected sandbox, and could get close to natively compiled performance on a variety of hardware platforms.   Our dream was that we would contribute towards a VM for Windows that would ultimately run much of the software in the world.  Other companies wanted to acquire us, but we came to Microsoft because we thought it offered the best chance for our technology to be ubiquitous – we said to each other that it would be a place to build software that “my mom will use.”  That was a very powerful motivation.

What Happened

After we were acquired, we ended up in the Visual Studio organization.  It seemed to make sense because we needed to work closely with the compiler team to target the VM, but actually it was a mistake.  All of the major decisions about runtimes were being made elsewhere, and we had limited contact with the key people.  Many of them were already committed to other solutions.

The result was that we kept getting redirected from afar.  “Your VM would be perfect if the wire size was smaller than Java.”  Ok, we went and built a cool compression strategy that yielded extremely compact code.  “Your VM is out of the question because it isn’t compatible with Java bytecodes.”  Oh.  “Your VM is Microsoft’s future.”  Great!  “Your VM would be cool, but isn’t practical without a substantial modification to Windows that would require too many resources.”  But …  And so on.

Amidst these conflicting messages, we tried to soldier ahead.  We rebuilt our original system to work with Windows, and demonstrated that it worked  by recompiling Microsoft Word and running it on the VM with performance indistinguishable from natively compiled code.  Eventually the team helped design the bytecode strategy of one of the VMs in the operating system.  Although it wasn’t what we had originally hoped to accomplish, the ideas did influence the design of a part of Windows.

So, what did I learn from all this?

Lesson #1: Have a champion

By far the most important lesson is that you desperately want to have a senior person who is the champion for your group.  We didn’t have one, and we suffered badly for it.  The need is particularly acute if you walk into a politically charged area.  There were deep divisions in the company that we didn’t understand – it was confusing for long-time employees and utterly baffling to us.  We thought we had something that the company would eagerly seize upon.  Over the course of six months, we were told that we had one of the most important projects in the company, that our technology would be scrapped, and that we should redesign it in ways that we felt would be a disaster.  Not fun.

I don’t think anyone could have prevented the situation from being difficult and confusing, because the company was facing very tough and important decisions.  But at least we would have felt that somebody was in the key meetings advocating for us and then telling us what was happening.  I think the team was hurt, for example, by a feeling among some key partner teams that we were overselling.  We thought we had carefully explained that, for a commercially viable solution, we would have to rely on other parts of the company to deliver key missing pieces.  But that message didn’t get through.  This kind of disconnect happens all the time and is natural; people who hear about a technology without the details make assumptions about what it does and doesn’t deliver.  Teams have to actively (and continually) educate their partners.  We just weren’t talking to them.  In fact, we didn’t even know their names.

To a company being acquired, I can’t stress enough that you want a politically savvy champion who has the ear of the key architects, people in management, etc. and will go to bat for you when it is appropriate.  You want that person to be identified with the acquisition and their credibility on the line as to whether it succeeds or fails.  They should drive you hard and want to exploit your ideas for the maximum benefit of the company – after all, that’s what you want, too!

Lesson #2: End up in the right part of the organization

Many large organizations have teams that are quite autonomous from each other.  If you land in the right place, which we didn’t, the people around you will understand how to integrate your technology into the product portfolio of the company and be in a position to make that happen.  The key thing, though, is that your hosting organization is the one that drives the decisions that most directly affect you.

Lesson #3: Nobody trusts you

Getting acquired feels like a seal of approval.  It says that you were doing something cool enough that the big company felt it was better to buy it than to build it themselves.  That doesn’t prepare you for the likelihood that nobody in your new company will trust you at all.  They won’t believe that your code is any good or that your team is up to the standards of the rest of the organization.

As far as I’ve seen, there are only two solutions:

  • Seed your team with some experienced and trusted employees from the big company.  This is a great idea anyway, because in addition to providing credibility, they can also be enormously helpful in getting things done in your new environment.
  • Ship and win in the marketplace.  That’s the ultimate coin of the realm in any software company.

Final Thoughts

There were ups and downs throughout the experience, but I learned an enormous amount from being acquired by and working within a large company.  I’m doing my third startup now, and hopefully applying lessons learned from all the experiences I’ve been fortunate enough to have along the way.

Everything You Need to Know About Startups, You Can Learn From Mythbusters

I’m in the midst of another startup, with three friends, and we’re having a great time.  I realized last night how perfectly you can prepare for one of these adventures by studying one of my favorite TV shows, Mythbusters.  If you don’t know it, then you should probably stop reading and go watch an episode.

I reject your reality and substitute my own” – Adam

The core of every startup I’ve done is an overmastering conviction that you are doing something deeply important and new – that you have stumbled on an insight that nobody else understands as deeply and powerfully as you do.  You gather around you a small band of people with a similar conviction to pursue your crazy dream together.  Your day is not full of reviews and alignment meetings and sync-ups and constrained by “the way we do things here”.  You do them any damn way you please, and nobody around you is a naysayer.  Naysayers are not welcome and do not flourish in startups.  Only obsessive true believers, please.

They don’t just tell the myths, they put them to the test” – Narrator

The danger, of course, is that you might all be wrong.   Startups are highly prone to groupthink.  The brilliant vision you are chasing with all your heart and soul might not be something anyone wants.  To quote another sage, John Maynard Keynes has a great line about this: “It is astonishing what foolish things one can temporarily believe if one thinks too long alone.”

So, you have to mix in a ruthless focus on testing your ideas with customers.  This is the heart of the Lean Startup methodology, which I love and which we are using at Highspot.  You build something as quickly as possible that lets you evaluate your beliefs, and then you adapt based on what you find.  Just like the Mythbusters crew is constantly trying ideas, having their approach fail, and trying again and again, a startup is a succession of attempts to find a model that yields a product people want to use and a way to make money from it.

As Kari says, “I guess we don’t have a Plan B because we kinda expected Plan A to go off without a hitch.”  Adam’s response will resonate with most (successful) entrepreneurs:  “You should never, ever, ever expect Plan A to go off without a hitch. Usually, Jamie and I, it’s Plan D.”  Or in a startup, Plan Z.

And with any luck, you will end up with a conviction that is “Confirmed” and not “Busted”.

Failure is always an option” – Adam

One of the realities of startup life is that they mostly fail.  Going in, you have to have a crazy passionate belief that you can succeed, but you also know that the odds are not in your favor and you can’t allow yourself to be crushed if it doesn’t work out.  As Kari says, “If we’re wrong about this, we’re going to have a really bad day.”  But you have to embrace that possibility and forge ahead anyway.  I’ve met many people in comfortable big company jobs that talk about doing a startup .. but can’t bring themselves to leave their “gilded cage”.

“We have no idea what we’re doing.” – Grant

Another thing I love about startups and Mythbusters is the perpetual willingness to dive in and just figure something out you have no idea how to do.  You don’t apprentice with the person who has 20 years experience, you don’t go to school and get a degree .. you just dive in and make out the best you can.  And you mess up a lot.  Hence the Facebook mantra that they have tried to maintain to this day – “move fast and break things”.  Most large companies have long since lost that spirit by the time they get big and successful.  In a startup, if it needs to be done, you just do it.  By hook or by crook, the best you can, as quickly as possible, and with energy and passion.

If I had any dignity, that would have been humiliating” – Adam

If you are concerned about remaining in control and maintaining your dignity, go somewhere else where your needs will be respected.  Like honey badgers , “startups don’t care”.  You do what needs to be done.  But there’s a really great thing about it, too: “It’s funny what gets us excited, isn’t it?” – Jamie.  You will end up getting passionate about really oddball things that you don’t think twice about when other people are doing them for you – setting up your email hosting, picking desks for the office, stocking the frig with supplies.  It’s like parents getting excited and emotional about the minutiae of raising and taking care of the kids.

You SO wish you were me right now.” – Adam

When it all works, it’s just one of the best feelings in the world.  You dream up some concept, you band together with a group of kindred spirits, and you make magic out of thin air.  As Tory says, “Do ya think I’m excited? You better believe I’m excited. We just built a rubber moose and now we’re gonna crash cars into it. It doesn’t get better than this!