Lyft is a leader in the hyper-competitive world of ridesharing, providing millions of rides a day across the entire United States. Mapping is a key component to every part of Lyft operations from providing accurate ETAs, multiple passenger pickup and drop off scenarios and a seamless user and driver experience in both rural areas and urban canyons. The small but growing OSM team at Lyft has been tackling some tough and not so glorious mapping within OSM including hyper-attributing the road network, adding toll locations, lane counts, bike lanes and pedestrian crossings. With the recently announced Autonomous Vehicle team, Lyft is looking new ways to bridge the gap between community contributed content in OSM and the high precision and high accuracy mapping needs required by the next generation of autonomous vehicles. In this talk, we will present on some of these challenges at Lyft, what our team is using from OSM, what Lyft may be able to contribute back and how corporate values of taking a harmonious and collaborative approach with local governments and the community it serves can apply equally to OSM.