Believability of automated characters in virtual worlds has posed a challenge for many years. In this paper, the author discusses a novel approach of using human-inspired mirroring behavior in MirrorBot, an Unreal Tournament 2004 game bot which crossed the humanness barrier and won the 2K BotPrize 2012 competition with the score of 52.2%, a record in the five year history of this contest. A comparison with past contest entries is presented and the relevance of the mirroring behavior as a humanness improvement factor is argued. The modules that compose MirrorBot's architecture are presented along with a discussion of the advantages of this approach and proposed solutions for its drawbacks. The contribution continues with a discussion of the bot's results in humanness and judging accuracy.