JDR’s Newsletter – #8

Hello there,

This is a (roughly) weekly newsletter experiment containing links to things I’ve written and made, plus links to other interesting articles, reports and essays I’ve come across.

In case you haven’t already subscribed, you can do so through Tinyletter. You can find an archive of this and previous issues of my newsletter at news.jdr.fyi.

Thoughts, opinions and typos are my own.


My blog posts and articles

A Beginner’s Guide To VC (Mattermark)

This week, I compiled a list of some of the best resources I’ve used to learn about the venture capital industry over the past couple of years. It contains over 60 links to books, academic articles, explanations of common terminology and a list of influential VC blogs and podcasts. If there is anything that I may have left out, please let me know and I’ll be sure to add it if it’s a good fit.

3 Places To Start Learning About Marketplace Businesses (jasondrowley.com)

After the Mattermark piece, I received a lot of requests to provide resources on specific industry verticals. In what’s probably going to be an occasional series on my blog, I start with marketplace businesses. Here, I identify my essential list of readings from Version One Ventures, Benchmark’s Bill Gurley and product maestro Rishi Dean, all of which provide their own analytical frameworks for understanding and evaluating marketplace businesses.

Notes on Twilio, Line, and the Open (?) Window (jasondrowley.com)

On Thursday, Twilio, the cloud communications company, made its public debut on the NYSE. And boy what a debut it was. Priced at $15, opening at $23.99 and closing nearly 90% above its IPO price, investors from Sand Hill Road to Wall Street may feel tempted to proclaim the tech IPO window is open. 🎉 But as I point out in this post, one data point does not a trend make, and the next company on the IPO docket, Line, may curb some of that enthusiasm.

Brexit: History, Market Failure, Threat (jasondrowley.com)

Thursday’s vote for the United Kingdom to exit the European Union was certainly interesting. It’s tragic for some, and a point of elation for others… exactly what you’d expect from a highly contentious referendum. To me, though, the most interesting aspects of Brexit is the failure of prediction markets to anticipate the outcome and the impact the move may have on the scientific and tech communities in the UK and EU going forward. In this brief post, I share some of the best analysis of the prediction markets and science stories that I could find.

Other Tech News

Boston Dynamics Debuts SpotMini

Robotics company Boston Dynamics unveiled their new model, SpotMini in a Youtube video on Thursday. This smaller, nimbler successor to Big Dog and other models moves even more smoothly and has an attachable “neck” that can be held stable in space as the body moves around it. The unit in the video has a (presumably detachable) neck with a “mouth” that can grasp and manipulate delicate objects, but this mouth module could presumably be replaced by a camera or other sensor array. We’re definitely creeping into Uncanny Valley territory here.

After watching the SpotMini video, you might want to read this essay about the Uncanny Valley from n+1.

Elon Musk’s Company Bids For Elon Musk’s Company

In a move that would make even the best due diligence team die a little, Elon Musk’s Tesla announced a bid to acquire green energy installation company Solar City, of which Elon Musk is largest shareholder. Remember that Tesla is trying to expand its network of car battery charging stations and expand its “Power Wall” battery business, so the missions of the two companies are well aligned. This would move Tesla further down the road toward becoming the generalized energy infrastructure company it aims to be, if and only if SolarCity shareholders, Tesla shareholders, and in all likelihood some court feels as though there’s no conflict of interest here.


Other news and links

Best Of

Like most Chicagoans, I like giardiniera, the spicy mixture of pickled veggies and hot peppers usually served with Italian beef sandwiches. I made a batch using this recipe and it is diabolically good.

Patrick van Hoof published a guide to AI for designers. And, while on the subject of AI, it might be fun to check out The Scientific American’s reporting on Facebook’s AI and machine learning efforts. The piece goes into significantly more detail than reporting in the big tech press.

Tech Trends & Industry Commentary

In an essay on Medium, software engineer Laura Montoya helps to unpack the tension between diversity and “cultural fit” in the tech business.

Leigh Honeywell’s post about the problem of “rock stars” in the tech business is amazing. If you’re reading this, you’ve probably seen an a job listing or heard someone describe someone as a “rock star [developer/designer/sales person]”. According to Honeywell, a senior staff security engineer at Slack, this sort of characterization breeds the culture of narcissism and arrogance that tech is known for and even celebrates. I agree, and you should read her post.

It turns out that Uber drivers don’t make a lot of money, according to reporting on leaked internal data by Buzzfeed’s Caroline Donovan, but that shouldn’t have surprised anyone. Average wages: less than $13.25 per hour.

Brexit: History, Market Failure & Science Threat

The late-breaking news on Thursday night that the United Kingdom voted to exit the European Union left global markets rattled and many scratching their heads. As John Goodman points out in his history of referenda for Atlas Obscura the UK overwhelmingly voted to stay in the European Community (the EU’s predecessor) in 1975. Obviously, much has changed since.

To me, the two most interesting aspects of the “Brexit” vote are the failure of prediction markets and the impact the move may have on science and technology in Europe. I don’t have much analysis of my own to share here, so in lieu of that I’ll share some links to some of the more interesting articles I’ve read as I’ve tried to wrap my head around the vote.

Failure of Prediction Markets

  • If you don’t know what a prediction market is or if you want to learn more, you might want to check out this list of resources from ConsensusPoint, a Nashville-based research group that specializes in prediction markets.
  • The Economist explains that prediction markets are subject to a number of cognitive biases that create a gap between expectation and reality. Their take: this gap can be exploited by the likes of pro-Brexit folks and such black swan political candidates as Donald Trump.
  • David M. Rothschild, an economist with Microsoft Research and proprietor of PredictWise, published an article analyzing the statistical upset of the Brexit vote. According to him, prediction markets failed due to market forces… most traders discounted the possibility of Brexit and held positions that would lose their entire value if (and when) the measure passed. In other words, it’s the same story as other market failures: over-confidence in one outcome and lots of unhedged risk led to a bad outcome.

Threats To European Science and Tech Research & Investment

  • Published before the vote, the MIT Technology Review explored the impact of a (then hypothetical) Brexit vote on British science research. Highlights from the article include: 83% of British scientists opposed Brexit; Britain is an outsized benefactor of EU funds for scientific research, receiving more money than it contributes to the fund (meaning Brexit has negative ROI for UK science); UK scientists may lose out on collaboration opportunities, much like Swiss scientists did when Switzerland tightened its borders in 2004.
  • Although the European Investment Fund has not announced any plans to change its relationship with the UK post-Brexit vote, there’s now a risk that the EIF will hold off on investing in new venture capital funds located in the UK, according to an article in FT Alphaville.

Remember, the Brexit vote is just the first step in what might be a long and messy divorce from the EU. In this particular case, researchers, technologists, entrepreneurs and investors might be caught in the crossfire. But a broader takeaway is the fallibility of prediction markets and polling data, which we should all keep in mind leading into the US election cycle.