Living Lightning is a collaborative project as part of the Visual Studies sequence at Columbia University. By using Python in conjunction with the Rhino modeling platform, we set out to develop a responsive script that would display visual feedback to Twitter users. By tweeting a search term at the account @LvngLtng, users would promptly see a visualization of their location in the Twittersphere as it related to the prior 100 tweets containing that term. The script contained three parts. The first scanned all of Twitter for mentions of our account and checked for use of the applied search term. The second would plot a series of points based on data related to each tweet and then generate a series of lines from each point following the logic of a bolt of lighting. It would find the shortest route from point to point back to object zero. Finally, it would generate a screenshot of the result and reply to the original user letting them know their search was complete. Living Lighting is no longer active but you can see the results at http://twitter.com/lvngltng