Oct 26, 2017


Oct 24, 2017

Thoughts on Reset

I just had a chance to read Ellen Pao's Reset: My Fight for Inclusion and Lasting Change. If you're unfamiliar, Ellen Pao is primarily famous for two things: suing venture capital firm KPCB and stepping down as CEO amid controversy at Reddit.

Reset is an auto-biographical narrative that focuses the bulk of its attention on Ellen's experiences in and around the VC and tech industry. She provides context on her family and personal life where it's helpful, but otherwise spends her time on what matters most to her: the inequity in the tech industry, her personal experiences, and her fight to address it.

I really enjoyed Reset. I watched in real-time as most of the major events from the book unfolded and was very interested in them even at the time. Ellen's first-hand account of the events and what was going on outside of the public eye is fascinating simply for the lens it gives into events that are important to my professional life. It's also fascinating because I'm familiar with many of the characters (most often villains) that figure in the narrative. I've seen them talk, been in conference calls with them, and followed their activities online. Reset provides a view of them that I can't imagine getting anywhere else.

One of the things that Ellen touches on in the book is the negative PR machine that KPCB spun up as a part of its "defense" in the trial. With the new perspective I have from the book, I have to admit: that PR effort was absurdly effective. As a long-time Reddit user and a member of the VC community, it was all too easy for me to believe elements of the slander directed against Ellen Pao. I'd like to think that I reserved judgement around motivations and other elements of the events that I had no ability to verify, but I certainly didn't apply much of a critical lens to the general depiction of Ellen as an unsympathetic character.

Over the past couple of years my viewpoint has matured substantially. I've come to care a lot more about the issues of equity in the tech world I learned about as an investor. It has become much, much easier to believe that sexism, racism, ageism, and a host of other forms of discrimination are rampant in virtually all of the top institutions in the tech world (though the problem is by no means limited to our industry). Reset offered a rare view into the worst of these elements. I'm tremendously grateful to Ellen Pao for having the courage to stand up for herself, for her convictions, and for the rights of all underrepresented groups.

Reset's probably the best book I've read this year. I would highly recommend it to anyone.
Sep 18, 2017

Representing investor preferences as a vector

At 4Degrees we're focused on forming stronger and more authentic relationships between professionals. My co-founder and I both come from venture capital, so we've decided to focus our early efforts toward that mission in the VC and entrepreneur space.

One of the questions we've struggled with early on is how to intelligently match investors to startups. That type of matching has a lot of potential value- both to flag interesting relationships that already exist as well as to tee up introductions that could be mutually beneficial.

The first problem we ran into is that there's no good public structured dataset with this information. This isn't a deal breaker for us: we know a few sources of this information that aren't public and/or aren't structured and have the capabilities to wrangle that to our needs.

Probably more importantly, the traditional way of thinking of investor interests makes the obvious solutions in this space frustrating.

To illustrate, I'll start with the "good" case. Adam is a partner at Pritzker Group Venture Capital focused on healthcare technology investment. Silvervue is a startup providing solutions to hospitals. Adam is interested in Silvervue. All is good.

Now the "bad". Chris is another partner at PGVC focused on B2B investment. Outbound Engine is a marketing automation platform focused on the SMB market (small and medium sized businesses). Using the simple logic above (which predominates even the sophisticated approaches today), Chris should be interested in Outbound Engine. But he's not. While Chris does make some investments into SMB-targeted businesses, his true focus is on enterprise-targeted businesses. Even if a dataset does differentiate between SMB and enterprise investment (most don't), Chris does technically invest in SMB businesses. He just needs to see a more robust set of validating factors to lean in.

That brings us to the issue with current approaches: they assume investment interest is binary. As Chris' example shows, they're not.

In talking with Ben Blaiszik last week, we came across an interesting alternative. What if we treated investment interest as a continuous range, varying by sector? Perhaps instead of just being interested in SMB-targeted startups, Chris has a 0.3 interest value (in comparison to his 0.8 interest in enterprise-targeted companies).

Transforming the data in this way allows for much more intelligent and accurate matching of investor interests to startup focuses.

But why stop there? On the flip side, a startup's sector(s) could also be vectorized for more accurate representation.

The implications beyond this single matching problem are very interesting as well. This type of data structure allows us to make more powerful connections between investors and between entrepreneurs. And the structure could perhaps be extended to a multitude of other attributes: personal interests, industry expertise, skillsets. The list goes on and on.

At first blush, this type of structure presents a data collection challenge. Humans aren't really conditioned to apply gradations to their categories like this. But that doesn't trip us up for too long- the far more interesting application is categorization at scale. And when you think about the usage of probabilistic classifiers for automated categorization, this data structure is actually particularly well-suited. Rather than setting a binary threshold and converting a probability estimate to a 0 or 1, why not just score that probability directly as an element in the vector space?
Sep 18, 2017

Thoughts on Inda

I've been negligent in writing up my thoughts after finishing books. Part of it is due to not having read that many books... I got hung up about halfway through The Hero with a Thousand Faces and then began Techstars back in July. A couple of weeks back I finally gave up on Campbell and used the excused of travel and a need to unwind to start a new fantasy series. Thanks to the travel and a hunger for fantasy I hadn't fully appreciated, I tore through the four books in just a couple of weeks.

The Inda series was a nice dip back into fantasy literature. Not the best I've ever read, but definitely a top 25 series. The first book got off to a slow start and for most of it I didn't think I was going to continue past the first book. But the ending of that book was solid and Smith's writing progressively improved throughout the rest of the series. A bit strange given I understand she was an experienced author, but I was thrilled to see the progress.

Inda was neat in a number of ways. It started off in an academy setting and then evolved into maritime. I wasn't expecting the transition at all but it set a good scene (or collection thereof) for the rest of the series. It had a unique perspective to offer on mental disability, sexuality, the evolution of language/culture, and a number of other really interesting themes. It was probably one of the most enriching fantasy series I've read.

One of the great things about diving head first back into fantasy was a reminder of its restorative properties. Getting lost in a book feels so much less purposeless than watching TV or playing games often does. I constantly struggle with a feeling of listlessness from my time destressing; reading is a great alternative that avoids some of that.
Sep 18, 2017

How to Form Meaningful Relationships with Investors

I forgot to link to this post from a month back on how to form meaningful relationships with investors. The post is targeted toward entrepreneurs. The main idea is to seek out relationships with investors before you start raising a round. Not exactly novel advice, but it seemed particularly important to me as I mentally transitioned from VC back to founder.