Day by day the amount of data that exists is ever growing along with the need to understand it. StackExchange is a frequently used site by many software developers for finding solutions to common bugs and problems. Answers on the site are generally verbose and result in loss of time during comprehension of the solution. Summaries are an efficient method for condensing large articles whilst preserving details from the source text. In this project the effects of using summarized answers on StackExchange was evaluated. A text summarizer with a tensorflow backend was used to generate summaries of answers on StackExchange. A survey on Mechanical Turk was used to evaluate the usability of the generated summaries. Through analysis of participant responses the generated summaries are effective in reducing verbosity and retaining the details of the original answer.