The other night I attended the first "pitch practice" for this year's set of TechStars Boulder companies. Watching the evolution is always fascinating. So far, my first impressions are holding strong. Those who I suspected would struggle, are struggling. Those who I expected would be knocking it out of the park are doing so.
Comparing and contrasting the 2009 crew to the 2008 crew, I find that this year's companies are, on the whole, more mature than last year's. More companies this year have their products further down the path of where I think they will ultimately end up, than last year. It's been nice to work with teams that are more crystallized in their thinking and implementations. Of course, there's always the crew that bounces back and forth for awhile until they hone things to the point they can walk down a straight line.
For those doing user facing products, the focus on the concepts that will "hook" a user is much better than last year. Too many priorities tend to doom a team, and recognition of this is coming fast. That said, there's a big difference between knowing which features to drop and actually dropping them; it can be hard to let go.
For those doing more infrastructure intense products, the technical skills brought to bare, and understanding of the issues at hand, is much more advanced than last year. The infrastructure plays have a special place in my heart so it's been fun to work with folks doing more backend stuff.
Of course, there's a star burning hotter than the others. This team has taken a problem that billions of dollars have been thrown at, to little avail, and turned it upside down. As a result, they have a phenomenal product that is going to do things for an industry that has been begging for it for decades. Brilliant, and totally cool. I can't say who it is, but it will be apparent when the season's over.
Some technical patterns/themes that pervade almost every team this year:
- Polling. Mashing APIs together is the norm now, and the access paradigm overly leveraged is polling. Conveniently my company Gnip (http://gnip.com) is trying to make this easier.
- Queuing. Polling's ugly sibling. More teams are challenged with queuing needs in their application which bumps complexity up a notch. The simplest advice is best here. Queuing Theory 101: if the average inbound rate of items is greater than the system's ability to digest them; you're screwed, rethink the model.
- Data Storage. "How am I going to store all that data in an access efficient manner?" The inbred offspring of Polling and Queuing, data storage challenges are real for a few of the companies. For the others, the age old simple relational DB model will foot the bill.
One thing that will never cease to amaze me is the energy, passion, and commitment that radiates from the teams. Amazing.
Boulder is lucky to have this program, and I'm lucky to be a part of it.
