How Hackathons Turn Into Products

Today is the 12th hackathon I’ve done since joining AddThis back at the start of 2011.  While I definitely spent many all nighters working on AIM in its early days, I never got the chance to work on projects not related to my day to day job.

Earlier this spring we released a major new product called Audience Discovery, and the dev team that works on the product crushes it.  But before we started investing in the product, there were the hackathons.  While I joined AddThis to run our publisher web tools, during my interview I was exposed to all of the fun side projects that we built on top of our data.

So how did we get from a hackathon project to a product used by Fortune 500 companies?  Here are some screen shots showing how a simple hackathon project evolved over time.

Hackathon Fall 2011

Hackathon Fall 2011 – Excel outputs, heaven help me

Hackathon Winter 2012

Hackathon Winter 2012 – An early test of search data and flot.js output

Spring 2012

Spring 2012 – More flot.js output using free form inputs

Hackathon Summer 2012

Hackathon Summer 2012 – Who could forget our London Olympics Project

Hackathon Fall 2012

Hackathon Fall 2012 – County Level Candidate Data.  We predicted every county and state correctly except Arapaho County, CO

Hackathon Spring 2013

Hackathon Spring 2013 – Using D3.js to output new Audience Interests data type

Hackathon Spring 2014

Hackathon Spring 2014 – Using NVD3 to output bar charts on new data types and analysis

Audience Discovery Spring 2015

Audience Discovery Spring 2015

None of this could be done alone, and a big thanks goes out to all the engineers, designers and dev ops who helped along the way.

New Open Source Stream Summarizing Java Library

AddThis Blog » Blog Archive » New Open Source Stream Summarizing Java Library.

Last week we open sourced a library designed to help you with summarizing streams of data.  The library is available up on github, and we would love to get any feedback you have.  Kuddos goes out to the data team here at Clearspring and all the great work they are doing in helping folks process billions of pieces of data efficiently.