I Dream of 3D: Makerbot, IP, and the advance of Technology

There is an oddly fascinating documentary on Netflix about 3D Printers, Print the Legend. The story follows two startups–MakerBot and Formlabs–and three established companies–Stratasys, PrintForm and 3D Systems.

I don’t think we’re heading toward a micro-industrial revolution, a 3D printer in every backyard, but they have many interesting possibilities:

3D printing seems perfect for reasonably small, individually customized items like prosthetics, dentures, hearing aids, and shoe inserts. I can easily imagine a vending machine at the shoe store that takes an impression of your feet and then prints custom inserts while you wait–like the photo booth that prints silly pictures of you and your friends.

But let’s discuss possibilities later–today we’re discussing MakerBot, IP, and learning curve. MakerBot was founded in 2009 by Adam Mayer, Zach Smith, and Bre Pettis. The original MakerBot Printers were quite cute, with a DIY, home-hobbiest feel. (They were, in fact, DIY-kits you assembled yourself.) Later MakerBots, by contrast, look like digital ovens and come pre-assembled–aimed at the “professional consumer” market.

In its early days, MakerBot was a creativity-driven startup cobbling everything together in a warehouse where, as they put it, new employees even had to build their own chair when they arrived.

In those days, MakerBot attracted the sorts of hacker nerds who wanted to work in a startup warehouse, and adhered to hacker ethics: the hardware was open-source.

Open-Source hardware meant you could copy their design and build your own, or you could modify your MakerBot and share your innovations with the broader MakerBot community. With an enthusiastic community working together, it wasn’t long before user-created innovations were incorporated back into the MakerBot’s products.

MakerBot also launched Thingiverse, essentially the MakerBot Open-Source community’s home and database on the web.

As MakerBot moved from startup dream to reality, the culture changed. By mid-2011, they had sold about 3,500 bots. In late 2011, The Foundry Group (venture capitalists) invested $10 million and joined the company’s board. In 2012, Bre Pettis pushed out co-founder Zach Smith, (who wanted to remain true to their founding principles.) A month later, the company moved from its startup garage to a New York apartment office headquarters in the sky.

Bre Pettis fired about 100 people (they only had 125 employees when they moved) and hired far more. These new employees weren’t hacker nerds; they were the kinds of people who wanted to wear suits and work in an office.

A few months later, in a massively controversial move, MakerBot went closed-source.

By June of 2013, they had sold 22,000 printers, and competitor Stratasys Incorporated decided to eliminate them by buying them for $604 million. Good deal for Bre Pettis; shitty for Zach Smith and all of the folks in the MakerBot community whose Open Source hardware ideas eventually made Pettis rich.

In 2016, MakerBot/Stratasys moved their manufacturing plant from New York to China.

Did MakerBot do wrong by transitioning from Open to Closed source? Did they cheat the people who helped them grow, or did they make a wise economic decision?

The growth curve for new startups is initially quite flat:

This is actually the growth curve for yeast, but it’s the same for companies. In their first few years, companies experience little–even negative–growth. Only once they reach a particular size and level of competence do corporations enter a period of rapid growth (until, at maturity, they have captured as much of the market as they reasonably can.)

Much of the difficulty for a new company–especially a company that is building a new product–is informational. Where do I buy parts? Where do I buy 10,000 parts? Where can I hire workers? How do I withhold income taxes from paycheques? Where did I put the receipts for those 10,000 widgets I ordered? What do you mean you threw out all of the steel because it wasn’t good enough?

Solving problems and then routinizing those solutions–as Auerswald would put it, developing code–is critical to early growth. More employees means more knowledge and ideas, but employees cost money, and new companies don’t have a lot of money.

Here’s where Open-Source comes in: by expanding the number of people effectively working on the problem (at least on the hardware end), the open-source community greatly increased MakerBot’s effective company size without increasing costs. Free expertise=faster growth. The community also fostered growth by increasing demand for the bots themselves, as each person who contributed quality printing ideas to the Thingiverse databases increased the realm of ideas other makers and potential makers had to be inspired by.

Once the hardware designs were basically perfected, Open-Source could no longer contribute to hardware innovation, and became a liability, as people could simply download blueprints and make their own bots without paying any money to MakerBot. At this point, as MakerBot entered its rapid growth phase, moved to bigger offices and hired a ton of new employees, it abandoned open-source.

There is a very similar phenomenon in the world of writing, but the ethics are regarded very differently. Many aspiring novelists are members of writer’s clubs, critique groups, or fandoms where they post, share, read, and give feedback on each other’s work. This creative foment and mixing of ideas spurs innovation–as when fan works take on a life of their own nearly independent of the original–and refinement, as when a novel is finally polished and sent out to publishers.

In some cases, very popular writers initially built up followings by publishing in fandoms based around established books or movies before transferring that audience to their own, original works. 50 Shades of Gray, for example, started as Twilight fan-fiction before morphing into its own book.

In other words, in their initial, creative phases, many novels are essentially “open;” this allows the writer to draw on the knowledge and expertise of dozens of other writers. When the novel is good enough to consider publication, it becomes “closed;” a published novel costs money. (It is considered good manners, though, to offer a free copy of the novel a a thank-you gift to anyone who gave significant help along the way.)

This is the same open and closed process as MakerBot pursued, but since it is considered normal and completely expected in writing communities for people to take suggestions, incorporate them into their stories, and then try to pitch the stories to agents, no one looks askance at it. I myself have edited many novels, one of which is now an Actually Published Book by a Real Author. I don’t resent that the book I once read for free and offered feedback for now costs money; I’m just happy on behalf of the author and glad I could help.

By contrast, people were surprised by MakerBot’s pivot, even though it made sound business sense. Surprising people tends to piss them off.

Traditional IP is structured so that copyright/patent protection starts at the time of innovation and eventually runs out; it doesn’t really include an open or semi-open period after which the work becomes closed. In writing this is handled by a convention that so long as the entire novel is not openly posted on the internet or elsewhere, the author can still sell the rights to it. I don’t know how things work over in patents, but given the number of patent infringement lawsuits filed every year, attempting to share designs that you would later like to make closed sounds like a potential nightmare.

Nevertheless, I think something like this Open-Closed process would be beneficial for many new companies, especially as they struggle to grow, learn, and optimize. If it were expected, as in writers’ communities, then the pivot to closed-source wouldn’t be seen as a betrayal, but as a sign of success–a company that had made it big.

Spurring innovation doesn’t just help companies and their owners. We all benefit from better products. Amputees benefit from better, cheaper prosthesis. Sick people benefit from better, cheaper medicines. Poor people benefit from better, cheaper houses.

Just imagine three of these, joined together, located anywhere you want to live…