Sketchfab and the democratization of 3D content

We’re about to see a lot more 3D content in our digital lives.  Various trends, some years in the making, are now intersecting to make this a near-term reality.

On the production side, 3D has of course existed for many years – this has been, in particular, the world of Computer Aided Design (CAD), which originated in part from MIT’s Sketchpad project in the early sixties.  In one form or another, 3D has been used as a professional format across many industries, such as architecture, engineering, construction, and entertainment. Creation of 3D content (even for consumer-facing products like gaming) has remained largely the province of a comparatively small group of specialized professionals.

This is no longer the case. We are witnessing today a significant evolution towards 3D content being democratized and accessible to a much wider audience, both on the production and consumption side.

For 3D production, a generational shift is happening within the creative community.  The new generation of designers grew up playing 3D games, and for many students graduating from design school today, 3D is a top choice.  In addition to its intrinsic value, 3D is also a great way of building realistic effects into 2D work. As a result, the number of young creatives with 3D skills is rapidly increasing.

Another trend on the production side is the democratization of 3D scanning as a widely available feature for professionals and the general public alike. Soon, 3D scanners will be widely distributed in the next generation of mobile phones, laptops, and tablets, enabling just about anyone to capture the world in 3D just as simply as they might today snap a photo.  Google has been working on Project Tango, now available to developers.  Intel has developed its Realsense technology, which is now shipping in various products (see list here), with many more to come.  Apple, characteristically secretive, is clearly up to something in the space with its acquisitions of of PrimeSense and LinX.

On the consumption side, 3D content is also being rapidly democratized. One major evolution has been the success of WebGL – the JavaScript API that allows 3D models to be rendered in any web browser without a plug-in.   WebGL opens the door to a fun and intuitive interaction with 3D models by just about anyone.   Users can manipulate, explore, rotate, and zoom in and out of models, providing a rich, deeply engaging way of experiencing any product on the web and on mobile. This multimedia is no longer static: 3D has allowed this content to be elevated as a destination unto itself.

Beyond the web and mobile, ways of consuming 3D content are broadening.   A lot of content can be 3D printed, and in fact some of the largest repositories of 3D content to date, such as Thingiverse, have been associated with 3D printing.  Another very exciting development for the future of 3D content is the emergence of augmented reality (AR) and virtual reality (VR). These technologies are essentially all about 3D content, immersing the user into the 3D environment itself. The applications of these technologies are vast, both in professional fields (job training, remote meetings, customer support) and consumer (gaming, movies, chats).

Today I’m thrilled to announce that we are leading a $7M Series A in Sketchfab, the fastest growing community of content for 3D, AR and VR on the web.

Sketchfab is following a tried-and-true “come for the tool, stay for the community” strategy.  At its core, Sketchfab is a publishing tool – basically the best 3D viewer on the web. It’s capable of ingesting 28 file formats and renders 3D content beautifully. Users can navigate content fluidly and are able to view content as it’s meant to be displayed with complex effects, including physically based rendering (PBR).

Leveraging this tool, Sketchfab has become the web’s fastest growing community and content repository around 3D files on the web. As often in early communities, the content skews heavily towards certain verticals like gaming (very much like VR), but Sketchfab is also  used by a variety of brands and cultural institutions, as well as a variety of professionals, hobbyists, amateurs, and curious passerbys.

Quietly over the last couple of years, the company has managed to superbly position itself at the intersection of production and consumption trends of the 3D ecosystem, partnering with just about every key company, large or small.  On the production side,  it is now integrated in (or with) the vast majority of 3D content creation tools (including native integration in Adobe Photoshop, for example). On the consumption side, Sketchfab is natively integrated in Facebook (only one of the 10 players to be natively integrated, across all categories, and the only 3D option), and has been used in a variety of platforms (Kickstarter, Reddit, etc) and publications.

Sketchfab has also caught the AR and VR wave early.  In April, the company announced that it was one of the 12 launch partners for Microsoft HoloLens, by far the youngest company to be included in the group.

Each time there’s been a new format on the web (whether video, sound, slides), there’s been a platform and community for it (YouTube, Soundcloud, Slideshare).  Sketchfab is well on its way to being “the place to be for 3D, AR and VR content on the web”.  We’re excited for the ride!

Hardware Startups: The VC Perspective

Among all the excitement for the Internet of Things and the resurgence of hardware as an investable category, venture capitalists, many of whom new to the space, have been re-discovering the opportunities and challenges of working alongside entrepreneurs to build hardware companies.  Below are the slides that David Rogg and I prepared for the recent Connected Conference, a great global event held in Paris.  They’re a good snapshot of how someone like me thinks about the hardware space, mid-2015.

 

 

The “Straight to A” Round

The venture financing path has evolved incredibly fast over the last 18 months. In this very busy financing market, what used to be a reasonably well understood progression from a seed round to a Series A to a Series B, etc. has now morphed into a more complex nomenclature of pre-seeds ($500k or less), crowdfunding rounds (especially for hardware), seeds ($1M-$2M, 6-9 months after the pre-seed), seed primes (an extra $1M or so, 12-18 months after the seed), Series A (now routinely $10-$12M in size, occasionally up to $15M), Series A-1, Series B, C, D, E, F etc. (as companies remain private longer).

The latest entrant in this rapidly evolving nomenclature seems to be what I’d call the “Straight to A” round, where the founders skip the seed stage altogether and raise directly a $5M-$10M Series A, often before building anything, sometimes even before incorporating a company. I had seen it here and there in the past, but it now seems to have become an accelerating trend.

The “Straight to A”, at least for now, seems to be an option available only to a very small number of startups, that have some of the following characteristics in common:

  • Exceptional founders, such as serial entrepreneurs with big prior outcomes (multi-hundred million dollar and above exits) and/or unique and deep technological expertise (world class level at a specific technical problem)
  • Often, but not always, entrepreneurs with long-standing relationships with the VC firms that invest in the “Straight to A” round
  • Founders starting a venture exactly in their area of expertise/prior success
  • Existing (meaning, comparatively less experimental) markets, with a reasonable chance that great entrepreneurs executing perfectly will be able to get significant traction quickly

The “Straight to A” is neither a good or bad thing in itself. Certainly, it reflects the specific context of the financing market we’re in; at the same time, there’s a real logic to it, for the right type of entrepreneur and venture.

But I worry that the addition of yet another type of financing scenario creates more confusion for most founders – my sense is that the dislocation of the traditional path to VC financing is increasingly bewildering, rather than liberating, to entrepreneurs.   “How much should I raise” and “when should I raise?” are questions that seem to be harder to answer than ever.

In this context, I would invite founders to be prudent, and focused on their actual needs. For all big raises that are announced in the press, many other deals never get done, behind the scenes. When talking to VCs, one bit of practical advice would be to communicate lower, rather than higher, round size targets in the earlier stages of the fundraising process, regardless of whether you’re raising a seed, Series A or any other type of round. While there’s something tempting about asking for a lot of money and conveying an impression of wanting to “go for it” and overall confidence, this backfires more often than one would think. It’s much easier to shoot for a lower amount and then increase it based on investor demand. The opposite – coming out of the gate with a big round size number and ending up having to reduce it – raises all sorts of red flags and could tank a round.   Overall, there’s some real value in shutting out the noise of the tech echo chamber, and focusing on what makes sense for you.

The Astounding Resurrection of AI [Slides]

A few days ago, I was invited to speak at a Yale Entrepreneurship Breakfast about about one of my favorite areas of interest, Artificial Intelligence.  Here are the slides from the talk — a primer on how AI rose from of the ashes to become a fascinating category for startup founders and venture capitalists.  Very much a companion to my earliest post about our investment in x.ai.   Many thanks to my colleague Jim Hao, who worked with me on this presentation.

x.ai and the emergence of the AI-powered application

AI is experiencing an astounding resurrection.  After so many broken promises, the term “artificial intelligence” had become almost a dirty word in technology circles.  The field is now rising from the ashes.  Researchers who had been toiling away in semi-obscurity over the last few decades have suddenly become superstars and have been aggressively recruited by the largest Internet companies:  Yann LeCun (see his recent talk at our Data Driven NYC event here) by Facebook; Geoff Hinton by Google; Andrew Ng by Baidu.  Google spent over $400 million to acquire DeepMind, a 2 year old secretive UK AI startup. The press and social media are awash with thoughts on AI.  Elon Musk cautions us against its perils.
 
What’s different this time? As Irving Wladawsky-Berger pointed out in a Wall Street Journal article, “a different AI paradigm emerged. Instead of trying to program computers to act intelligently–an approach that hadn’t worked because we don’t really know what intelligence is– AI now embraced a statistical, brute force approach based on analyzing vast amounts of information with powerful computers and sophisticated algorithms.”  In other words, the resurgence of AI is partly a child of Big Data, as better algorithms (in particular, what’s known as “deep learning”, pioneered by LeCun and others) have been enabled by larger than ever datasets and the ability to process those datasets at scale at reasonable cost.
 
The opportunity has not been lost on entrepreneurs, and a crop of startups has emerged at the intersection of Big Data, AI and machine learning (for an overview, see Shivon Zilis’ excellent landscape here).  Those startups seem to roughly follow two types of approach.
 
One approach is to think of AI as a largely horizontal platform, a core “global brain” than can then be selectively used for various specific uses across verticals.  This seems to be the approach taken by some prominent startups in the space, such as Vicarious and Viv Labs.
 
Another approach is to think that we’re about to witness the emergence of a number of deeply focused AI-powered applications that will achieve commercial success by solving in a definitive manner very specific issues.  This approach is perfectly summarized by Kevin Kelly in a recent Wired article:  “Most of the commercial work completed by AI will be done by special-purpose, narrowly focused software brains that can, for example, translate any language into any other language, but do little else. Drive a car, but not converse. Or recall every pixel of every video on YouTube but not anticipate your work routines. In the next 10 years, 99 percent of the artificial intelligence that you will interact with, directly or indirectly, will be nerdily autistic, supersmart specialists.”
 
Today, I’m excited to announce that FirstMark is leading a $9.2M Series A round in x.ai, a fascinating New York-based startup that resolutely falls in the camp of AI-powered vertical, focused applications.
 
x.ai doesn’t try to be all things to all people.  It is  an AI-powered personal assistant that schedules meetings for you.  Nothing more, and nothing less.  If, just like me when I was an employee at Oracle and Bloomberg, you need to schedule (and reschedule) dozens of meetings and calls every week without having the luxury of a personal assistant, then x.ai is for you.  After giving it a few tries, you quickly find yourself using x.ai on a daily basis, on par with any of your core productivity tools.
 
x.ai is the closest thing I have seen in a very long time to a “magical” product experience.  It quite literally functions like a human personal assistant, working invisibly behind the scenes and hiding tremendous complexity behind an incredibly simple experience.  There’s no app to download, password to remember, or new process to learn. All you do is connect your calendar, and start CC’ing amy@x.ai or andrew@x.ai (both are named so that their initials are “AI”) like you would if you had a PA (in particular, using normal language, as you would with a human).  The software then goes to work and emails back and forth with whomever you’re trying to meet with until a time and place has been agreed upon. As anybody who has tried the product will tell you: it just works, 100% of the time.  GigaOm called it recently “the best scheduling assistant ever“.  For a glimpse into how x.ai works behind the scenes, particularly in terms of AI/NLP/machine learning, see their talk at Data Driven NYC here.
 
x.ai is a very viral product, as it spreads through daily email conversations.  It also has the potential to build significant network effects.  As it schedules more meetings every day, it keeps accumulating relevant data and getting smarter about its specific mission. In addition, as more people use the product, everyone’s experience improves – when two people using x.ai try to schedule a meeting (and regardless of whether one is on Google Calendar and the other on Exchange for example), then meetings get immediately scheduled without any of the usual back and forth.
 
The team behind x.ai is a group of fearless seasoned entrepreneurs, led by Dennis Mortensen.  Several of them have worked together in previous successful data ventures and all are deeply focused on building a groundbreaking product that will change the lives of millions of professionals around the world.
 
As part of the investment, I am joining the x.ai board of directors, and I couldn’t be more excited to partner with this team, as well as their seed investors.
x.ai is currently in closed beta, but you an add your email to the waiting list on their home page. They give full access to new users every week.
 

 

Lending Club IPO: Nice Guys Don’t Finish Last, and Other Lessons

The superb Lending Club success story is what the startup world is all about: a software-based reinvention of massive and inefficient industry; a product that puts consumers first and delivers undeniable benefits ; and an entrepreneurial mega-hit that brings incredible riches and returns to its founder and investors.

In some ways, Lending Club is a classic Silicon Valley story; in some other ways, it is pretty atypical. As a friend of Renaud Laplanche’s for over 20 years, I have had a chance to witness from up close some parts of his journey with Lending Club. It is full of interesting lessons for entrepreneurs and the tech industry in general.:

1.  Nice guys don’t finish last. According to some, the tech ecosystem has been grappling with a proliferation of jerks with oversized egos at the helm of very successful startups (see Pando’s “asshole rollcall” here). Whether one shares that point of view or not, Renaud is exactly the opposite of that. Kind, loyal, generous and understated, he’s the living proof that world-class entrepreneurial talent, drive and persistence don’t necessarily come associated with arrogance and low EQ.

2.  CEO focus does matter. Renaud has been focusing maniacally on his venture for the last eight years. Up until recently, he had spoken at comparatively few conferences. He doesn’t have a portfolio of cool angel investments on the side. Heck, he doesn’t even have a Twitter account.

3. Great founders can come from all sorts of backgrounds. Renaud defies a lot of current startup CEO stereotypes. He is not a technical founder. He started his career as a (gasp) corporate lawyer.   He’s a sole founder. He is French, with an unmistakable accent.

4. Unicorns are not always “hot deals” at first.   It took a while for Lending Club to get going and it was largely under the radar for a long time. Most VC firms missed entirely this unicorn in the making. Lending Club had to do a down round in 2009 to survive, albeit in the specific context of the financial crisis (see financing history here).

5.  What matters is to be the last entrant. Like Google or Facebook, Lending Club was not the first entrant in its market. A part of the initial deck for the company’s seed round (when it was still code named “SocBank”) was devoted to explaining why prospective investors should not worry about Prosper, an early leader in the space (with 80,000 members at the time, and $18M cleared on the platform) and Zopa, a UK company with US expansion plans. It seems trivial now, but looked scary at the time.

6.  Embracing regulators is also a strategy. Truly disruptive startups often operate at the edge of rules and regulations. Many choose to push forward with the hope that regulators will adapt to the new world created by the startup, rather than the other way around. When the SEC came down on the nascent peer to peer lending industry in 2008, Lending Club chose to comply and voluntarily shut down operations while registering. Market leader Prosper didn’t. Lending Club emerged from the process fully compliant while Prosper had to finally suspend operations. Back in the market as the only game in town, Lending Club took the lead from Prosper and never relinquished it.

7. An immigrant is, once again, responsible for enormous value creation in the United States. As a backdrop to the debate on immigration reform, something to ponder: Renaud and I were co-founders in a previous venture, both under H1-B visas. We both filed for a green card in 2001. Four years later, our process had gone nowhere. Our venture was acquired by Oracle and our visa situation was such that we couldn’t work legally for another company in the US or start a new venture. Renaud actually decided to leave the U.S. and moved back to France. Had his green card situation not finally unlocked itself a few months later (or, had his green card taken another two years to be granted, like mine did), he may have never come back to the U.S., and Lending Club may have (almost certainly) never existed.

Congratulations to Renaud and the Lending Club team for an incredible success!

The Internet of Things: Reaching Escape Velocity

An edited version of this post appeared on TechCrunch here.  A downloadable version of the chart is available on SlideShare here.

It’s been about 18 months since my original attempt at charting the Internet of Things (IoT) space. To say the least, it’s been a period of extraordinary activity in the ecosystem.

While the Internet of Things will inevitably ride the ups and downs of inflated hype and unmet expectations, at this stage there’s no putting the genie back in the bottle. The Internet of Things is propelled by an exceptional convergence of trends (mobile phone ubiquity, open hardware, Big Data, the resurrection of AI, cloud computing, 3D printing, crowdfunding). In addition, there’s an element of self-fulfilling prophecy at play with enterprises, consumers, retailers and the press all equally excited about the possibilities. As a result, the IoT space is now reaching escape velocity. Whether we’re ready for it or not, we’re rapidly evolving towards a world where just about everything will be connected. This has profound implications for society and how we collectively interact with the world around us. Key concerns around privacy and security will need to be addressed.

For entrepreneurs, the opportunity is massive. Where Web 1.0 connected computers to the Internet and Web 2.0 connected people, Web 3.0 is shaping up to be connecting just about everything else – things, plants, livestock, babies… Each new wave has spun out giant companies (Google and Amazon for Web 1.0, Facebook and Twitter for Web 2.0). Will Web 3.0 create a comparable group of behemoths?

The space has been evolving so rapidly over the last year and a half that our IoT landscape became quickly outdated. Here is a revised and updated version. A few notes: as always, and despite our best efforts, a number of great companies will be missing; omissions are completely unintentional. Also, as much as possible, we have tried to put one brand per category, although many companies probably belong to several categories. Finally, categorization of a rapidly evolving space is an imperfect exercise – we have done our best to be directionally correct, but we’re certainly open to feedback on how to make this chart better and more accurate.

Some comments on the chart:

Explosion of startup activity: With hardware incubators graduating legions of new entrepreneurs, crowdfunding in full swing and an increasing number of VCs excited about the space, new companies and products are popping up left and right. The previous version of this chart featured 199 companies – it now has 612 logos!

Big companies are very active: I’ve written this before about the connected home segment, but this is a distinctive characteristic across the board: large companies have been active in this space or closely related spaces for a long time and are showing no interest in letting themselves get disrupted by small startups. This is true for industrial companies (GE, Siemens, Bosch, Philips, etc.) as well as big tech (Cisco, Intel, Apple, Samsung, etc.). The increasing impact on the space by Google, a fairly recent entrant in the hardware category, will be a development to keep an eye on in the coming months.

M&A activity is accelerating. Since the first version of the chart 18 months ago, a number of promising startups have been acquired: Nest and Oculus, of course, but also others such as Basis, Dropcam, SmartThings, Revolv, etc. Partly as a result of this, it’s pretty striking that there are comparatively few mid- to late-stage startups in the IoT space.

A global phenomenon: Innovation in the IoT space has been happening all around the world. Europe has been very active (Withings, Sigfox, Netatmo, Berg, and many others), as have other parts of the world (Australia with LIFX, etc.).

Some areas are getting overheated: The wearables market is probably getting close to its saturation point, at least for casual/consumer products (trackers, watches, etc.). The connected home segment has seen large companies make aggressive moves through acquisitions, investments or product launches (Google with Nest, Dropcam and Revolv, Apple with Homekit, Samsung with SmartThings, GE with Quirky/Wink), and the opportunity to become the home’s central “hub” is quickly becoming a deep-pocketed player’s game.

Plenty of other areas are just getting started: Innovation is accelerating at an incredible pace in a variety of segments such as digital health (patient monitoring), “invisibles” (connected pills, connected contact lenses), augmented reality, enterprise and industrial internet (asset tracking, energy management, machinery monitoring), smart cities, robotics, connected cars, aerials (drones, nanosatellites), user interfaces, software platforms and analytics, developer tools and ecosystems, security applications, and connectivity infrastructure. Just as certain verticals have neared critical mass, new and innovative applications have been spun up and built out.

In many ways, this is just the beginning. A lot can go wrong, but we are all in for an exciting ride.

This updated chart has been a team effort at FirstMark. Many thanks to David Rogg who handled the research and heavy lifting on the chart, as well as Caitlin Graham (logos), Dan Kozikowski (interactive version) and Sutian Dong (original version).

A Few Non-Obvious Things I Learned as a New VC

I joined FirstMark as a partner a little over 18 months ago now, and it’s been a thrilling ride.  It’s also felt like a steep learning curve: lots of nuances, and lots of institutional memory to absorb.  Below is a glimpse into what I’ve seen happening “behind the scenes” on the VC’s side to the table – stuff that was not obvious to me in my former roles as entrepreneur, angel investor or corporate incubator/strategic.

1.  A real commitment.  Like for many new VCs operating at the Series A level,  the biggest shock to the system was the realization that one gets to make very, very few investments – basically two or three a year.  You quickly find yourself having to choose between a number of opportunities you really like. Making a new investment is a big deal, and a decision that one has to live with for years to come. You also get to work with an entrepreneur very closely, and live up to their level of trust and expectations.  In a way, it feels like a marriage, except one where divorce is not really an option.  There’s an occasionally brutal asymmetry between the fundraising process (which can be quick and intense, especially if it is competitive) and what happens afterwards, which is a lot of hard work over a long period of time.  Both the entrepreneur and the VC would be well advised to get to know who they’re about to work with for the next few years of their lives.  You don’t need to be friends with your VC (although friendships develop over years of working together), but you do need a core of mutual respect and commitment to hard work and excellence, as well as a shared vision of the future.

 

2.  Conviction, not data. Early stage VCs (seed and Series A) operate in a daunting scarcity of data points. You get a few numbers, a few meetings with the founders, and also you see a bunch of companies, so you get a sense of how an opportunity compares to others. Other than that, and for all the thinking about data driven VC investing, the reality is that investment decisions are mostly about storytelling and forming personal conviction – painting a vision of the world where a company becomes hugely important. One consequence for entrepreneurs to bear in mind: VCs are really hungry for any data point that can help them.  It’s certainly true about the “big things” (revenue, traction, etc., especially as they compare to other opportunities the VC is seeing), but it’s also true for the “small things”, which can become become disproportionately important  (particularly if they add up), as the VC is trying to piece together a story: whether that’s signs of possible greatness (e.g., your former boss really insisted on putting $50k in your new venture) or trouble (being rude to the receptionist, consistently taking forever to reply to emails, etc).

 

3.  Not a single way to reach conviction:  VCs come in all sorts of flavors – some successful investors are deeply analytical (build roadmaps and investment thesis, get into details) while others are more “social” (relying on networks of trusted experts they’ve built over years to help them identify signal from noise).  What’s been interesting to me is that you find very successful investors on both sides of the spectrum, and also find those different types happily co-existing within the same firm.   Naturally, everyone is also heavily influenced by their professional history (what worked for them in the past as an operator or investor), as well as all sorts of personal criteria that often have nothing to do with the intrinsic merits of an opportunity – for example, the bar for a new investment will be naturally higher if an investor is already on 12 boards and always on the brink of being overwhelmed by the amount of work they face.   For the entrepreneur, it’s always a good idea to understand who they’re pitching to, as in any sales process, as an investor’s personal circumstances and background matter immensely.

 

4. VC firms are not a monolith. Once an individual investor has reached personal conviction, they need to sell it internally to get the deal done.  Because of the scarcity of data points and the range of personal styles, most investment decisions can be argued either way, and they often are. VCs are opinionated people, and there’s a fair amount of disagreement behind the scenes happening at firms during the discussions leading to an investment decision, which is a healthy thing, as you need checks and balances.  Many firms have reported that the most successful investments in the long run are the ones that were initially the most polarizing internally.  Depending on the firm, internal politics may come into play as well (glad to report that FirstMark is remarkably immune to this).  But, bottom line, decisions can come out either way quite easily, so for entrepreneurs, there’s certainly a numbers game involved.  Unless no one wants to take a first or second meeting (in which case there’s probably a deeper problem), it’s quite possible to get turned down by many firms before finding the one that will say yes (which can absolutely be a bigger name firm that the ones that said no).

 

5.  “Deal dynamics” matter a lot.  One really interesting aspect of seeing “how the sausage is made” on the VC side is to realize that the intrinsic merits of the opportunity is only a part of the equation. There’s also this thing called “deal dynamics” that VCs talk about all the time —  basically a catch all for all sorts of criteria related to timing, valuation, competition and to some extent, stage, geography and seasonality as well.  Because they see so many opportunities, VCs need to have strong filters in place about what makes sense for them – how they think about portfolio construction, ownership percentages, etc., matters a lot.  Here as well, this means that there is a number of reasons why an opportunity may not be a fit for a specific firm which have little to do with the fundamental merits of that opportunity.  Sounds like horrible VC bullshit, but it’s very true: a VC’s decision to “pass” is quite often not personal.

 

6. The VC world is really small.  While there are thousands of startups around at any point in time, there are only a few hundred active VC firms, which typically only have a handful of General Partners.  People come in and out of the industry all the time, VC firms rise and fall, but for the most part, the core remains the same and many people are around for years (or decades).   And it’s a pretty tight knit world:   there’s all sort of ways for VCs to meet (panels, industry conferences), socialize (informal small group dinners) and work together (sitting on boards together, switching firms, occasionally personally investing in each other’s funds, etc.). As a result, the industry is characterized by a deep connective tissue, full of history, institutional memory, cliques and alliances.   There’s this interesting “coopetition” dynamic where people sometimes compete, sometimes collaborate, but overall everyone tends to know each other well.  As a result, information often travels easily and quickly, although not necessarily reliably.  Facts can be checked, and reputations matter immensely.  For entrepreneurs and VCs alike, there are some real  benefits in handling difficult situations elegantly, fairly and transparently, as it’s all a long term game in a small echo chamber.

 

7.  VCs do things I hadn’t realized they did.   It’s perhaps obvious in retrospect, but one surprise to me was that VCs spend an awful lot of time raising money – you’d figure that as an early stage VC, you’d be the one investing the money but the reality is that, once you’ve made the initial investment, you find yourself involved in all sorts of fundraising processes for follow on rounds for your companies, so you end up hat in hand alongside your entrepreneur.   Another unanticipated aspect of the job is that VCs can really help with exits – particularly not-so-great ones.  It’s something that doesn’t make great press stories and that people don’t like to brag about, but behind the scenes, I have seen good VCs spend a lot of time engineering exits for companies that need to “find a home”.  That often makes the whole difference between a complete disaster and a “soft landing” or an acqui-hire that occasionally nets the founders some real money.   Of course, the VC is self-interested (optimizing for results and reputation) but in my opinion, just that is a real reason to take VC money.

NYC: A Natural Home for European Entrepreneurs

Last night I was invited to speak at the inaugural NYC European Tech Meetup.  There are tons of obvious reasons why the NYC and European tech ecosystems should work closely with one another, so a meetup on the topic was long overdue.  Congrats to Alban Denoyel and Anthony Marnell for starting it, and thanks for inviting me to speak, was a lot of fun.  Below are the slides I used – the presentation was meant to be a “State of the Union” of European tech in NYC, a high level overview fit for an inaugural meetup and get the conversation started.

 

Many thanks to David Rogg, our newest associate at FirstMark, for helping me with this.  I’m sure we missed some companies and people – if so, let us know in the comments, and we’ll update the presentation.

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